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Biology 103 Lab 2002 Forum |
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Survey of Unknown Planet Name: Heather Pr Date: 2002-09-10 14:59:57 Link to this Comment: 2589 |
The planet PSB had 20 different types of weed. All were green in color, and few had flowers, so the main criterion for categorization was leaf shape and size. A few species include the jagged-edge clover weed, the fat fuzzy weed, and the Minnesota weed which we felt was reminiscent of the wheat fields of the state.
In the tree category, we only found two species. The star tree was characterized by large, star-like leaves. As opposed to the spikey tree which had longer, spikier leaves.
On the surface of PSB, we found a vast array grasses, lichen and moss. There was soft moss and hairy moss, which generally covered the base of trees. Only one form of lichen was found, but the dead banana lichen proved to be most interesting. However, further study was inhibited by lack of funding. The grasses proved to be most difficult in its classification because of the various types. There were three particular types of grass-voluptuous, tall and shaggy- which were closly related and could belong to the same genius.
Finally the bushes and shrubs included blooming, spikey berry, spoon, and crew. We differentiated between them based on leaf shape. For instance, the blooming shrub has small bright green leaves and the spoon bush has dark, spoon-shaped leaves. We also encountered a dead bush that with further analysis could be identified.
Though this first encounter proved successfull in finding life on another planet, further study is required to fully understand the complexity and the actual relationship between plants on both planet PSB and planet Earth.
Name: Date: 2002-09-10 15:00:46 Link to this Comment: 2590 |
exploration of new planet Name: Date: 2002-09-10 15:04:05 Link to this Comment: 2592 |
24 plants were discovered. They were placed into the following categories: bushes, trees, grasses, small plants and ground covers.
Bushes: 3 types. All bushes have the following traits: they stem from one root (branching off close to the ground), have green leaves, and are able to grow in the shade.
Bush #1: Fuzzy leaves growing in clusters of 9+ leaves. Big leaves at the bottom, newer growth towards the center of the cluster.
Bush #2: Waxy, short needles. Small red berries and immature dark green berries.
Bush #3: Small, oval shaped waxy leaves. Many per branch.
Also found: dead shrub, uncertain which variety.
Trees: 2 types. All trees have green leaves and have a trunk growing from a single root. Ground cover #1 (see below) growing near base and on trunk. Root system partially exposed. About 40 feet tall.
Tree #1: smooth bark with disruptions. Multiple leaves per stem growing out of branches. Spikey nuts (seeds) fall from tree.
Tree #2: Star shaped green leaves. Rough bark.
Grasses: 3 types. Both are green and long. Stay close to the ground.
grass #1: thin individual leaves.
grass #2: thicker reed-like leaves with sharp edges.
grass #3: dark green, thicker than grasses 1 or 2.
Small plants: 13 types. All have green leaves with distinct shapes. Grow no higher than 2 feet.
s.p. #1: green, flat spikey leaves.
s.p. #2: medium sized green leaves, on single stem.
s.p. #3: dark green, two leaves on a single stalk.
s.p. #4: tiny green leaves and small yellow flowers (5 petals). All clustered on a single fuzzy stalk.
s.p. #5: smooth green leaves.
s.p. #6: serated green leaves (5 per stalk).
s.p. #7: small green leaves on single stalk with flower cluster (yellow) at top.
s.p. #8: flat leaves with green seed stalk growing out of center.
s.p. #9: huge, broad leaves. Grows straight from the ground. Diameter of about 3 feet.
s.p. #10: green leaves with white splotches (disease?)
s.p. #11: bright green leafy clusters, short to ground, concentrated in one area.
s.p. #12: tiny dark green plant with small leaves. White spots. 3 leaves per stalk.
s.p. #13: enormous dark green leaves, red stems.
Ground Cover: 2 kinds.
g.c. #1: soft, easily removed, green/brown in color, individual growths in a large group. Grows in shade.
g.c. #2: green leaves on a long, vining red stem.
The plants evolved close to the ground because there is not enough sunlight in the area to let them grow higher. The trees are higher because they're older - they cause the shade that stunts the other plants' growth. Keep the competition down!
Where there's no shade, the plants are smaller because they are new growth - haven't reached their full height yet? Need funding to investigate this further.
Lab #1 Tuesday, 9.10.02 Name: Kyla Ellis Date: 2002-09-10 15:04:38 Link to this Comment: 2593 |
Background:
Due to all prior knowledge, we hold that life exists when any or all of the following occur in an organism:
* dependent on energy
* highly impobable / organized
* bounded
Introduction:
Drs Hoyt, Ellis and Amlin landed on a previously uncharted, undiscovered, and unnamed planet on the 10th of Spetember at 1.30pm Atlantic Earth time. We hereby claim the right to name said planet, (as defined in the Eplorer's Law) which we shall exercise at a later date and time.
Upon arrival, we encountered certain organisms which, in conjuction with our background knowledge, we deem to be, in fact, living. These organisms were dependent on a source of light and heat similar to our Sun. Organisms which were not touched by this source of light and heat lost energy and died. (They became brittle, changed color, fell to our feet and became, in fact, lifeless.) They therefore show evidence of a life-span. Each organism exhibited a complementary structure that extended underground. The larger organisms showed major evidence of waste products. We also found evidence of growth with different sizes of the same-looking organism. For these reasons, we consider that all these organisms are living.
Observations:
We classified the organisms into three classes according to size:
CLASS A) Shorter than two feet tall.
1) All one floppy, pliable piece of organism. Moves with any type of force (wind, etc.)
2) Identifiable stem, but still bendable. Also move with slightest force.
3) Very small. Inter-connected growth-system. Seemingly dependent on class C.
GENERAL OBSERVATIONS FOR CLASS A: The largest class -- covers the most area.
Most variable types of organisms. Basically all the same shade of green. Least permanant -- most easily displaced. Least amount of waste. Each organism has one long stalk. No branches. Stems/stalks are very thin. Color
CLASS B) 2 ft to 8 ft tall.
1) Broad, single leaves. Many veins in leaves. Branches are most spread-out. Tends to be shorter than others in class. Leaves appear in clusters.
2)Sword-type leaf. Small leaves in abundance. Numerous leaves. Spherical red berry-like growth attached to random branches.
3) Circular, shiny, broad leaves. Leaves appear in pairs on stem. Thicker leaves.
GENDERAL OBSERVATIONS FOR CLASS B: Leaves on branches were arranged in some kind of pattern.
More complex branch pattern than Class A.
All branches made up plant -- as opposed to one trunk with many branches.
Lots of evidence of waste.
Branches were brittle, less pliable than in Class A.
Definitive underside of leaf.
CLASS C) Over 8 ft.
Appeared to have distinctions in leaf and stem. But adequate study was not performed due to time and monetary constraits. The most promising of the three classes, we all agree that this Class is worthy of further investigation.
GENERAL OBSERVATIONS FOR CLASS C:
Flat, broad leaves with veins.
Thick, stocky trunk.
Not easily displaced, very attached in its environment.
CONCLUSION:
We conclude that the organisms were living. Yet the only way to unquestionably discover if this is "true" would be to further study the said planet with observations over time.
Astronauts Name: Yarimee, J Date: 2002-09-10 15:05:35 Link to this Comment: 2595 |
Description of life forms in the "remote planet"...
I.Short organisms (.5 inches- 1 ft.)
a. dry/weathered/brown/crispy/yellow/thin/fragile/weak
b. under tall organisms- less sunlight; less energy?
II. Medium organism (4 ft.to 7ft.)
a. "shrub-like" organisms; thicker leaf, but shorter than short organisms...start to develop closer to the ground;
b. Even though they're in the same conditions, one is completely dried out while the others are green and flourishing
c. located under tall organisms which implies they get less sunlight due to shaded areas
III. Tall Organisms (15ft. -25ft.)
a. greener than all other organisms because they have the most direct access to the sunlight?
b. different "leaf" shapes implies different types of trees live on this planet
Questions??
1. What energy sources do these organisms depend on to survive?
2. Why are some short organisms greener than the rest? Is it because of sunlight or location?
3. Does it rain? Snow? Do these organisms depend on anything other than sunlight?
4. Fact: The greener short organisms "soil" is moist, while the drier short organisms are dry. Does this contribute to the outcome?
survey of unknown planet nte Name: Date: 2002-09-10 15:07:54 Link to this Comment: 2596 |
Tools we used to differentiate plant species: We used organizational structure to determine different plant species desptite different stages in development. For example leaf patterns, veins, size, etc..in combination these categories allowed us to determine different species. The following plants are what our team discovered on the unkown planet:
Grasses: pre-requisites for classification: Slim leaves, parallel veins, smooth edges.
Grass 1: Bluish-green color, 7-8in tall, smooth, grows abundantly in shaded areas, in the far corner.
Grass 2: Yellow-green color, shoots of leaves come out of the stalk, 12-18 in tall, had a seed puff growing out the top, with long hairs and fuzzy seeds.
Grass 3: Green, short leaves growing out of the stalk, leaves were pointed, 6-7in tall, seed pod at the top.
Grass 4: Green, 3-6 in, no visible seeds, individual leaves growing straight out of the ground, didn't grow well without sunlight.
Weeds: pre-requisites for classification: Found intermittedly among other plans species, leaves seemed to grow from focal point beneath the ground.
Weed 1: Jagged leaves, flower growing in middle. 6in.
Weed 2: 1 ft tall, hairs on the leaves, leaves little and round, seeds in pods on top.
Weed 3: 7in tall, sparse rounded leaves.
Ferns: we only have one
Fern 1: light yellow green, clustered leaves, 8 in, low to the ground.
possible food sources: Plants that bore fruit, possibly edible.
Bush 1: 7ft, branches coming from one root, leaves on tips of every branch, bore small red berries.
Plant 1: Heart shaped leaves, small red berries with seeds on outside, low to the ground.
Clover 1: small to ground yellow flowers, 3 leaves on stem, shaded,
Bushes:
Bush 2: 6ft, waxy rounded leaves.
Bush 3: 6ft, light green clustered leaves.
Trees:
Tree 1: 3 stories tall, rounded leaves bark peeling
tree2: 2.5 stories tall, light green 5 pt leaves, produces a spikey ball shaped nut.
Fungus 1: jagged and porous mint green, grows on bark.
Fungus 2: orabge bumps, looks like melted wax.
Fungus 3: tubular, white yellow color, 3 cm. tall.
Fungus 4: white dispersed throughout the bark, when in crevases displays underside, which has a fan shape.
Fungus 5: white with yellowish top, fan shaped.
Fungus 6: spongy moss at the bass of Tree 1 small green leaves.
unkown1: greenish pink color, in young plants large plants had a solid green color,
Unknown2: tiered, 4 petaled flowers, bursts of 5-6 leaves.
Unknown 3: 1ft tall located near bush 2.
unknown 4: jagged leaves growing out of the grate.
Mom plants are large specimens of weeds:
Mom 1:2 feet across, low to ground, veined leaves,
Mom2: bubbly leaves, shiny looking, leaves heart shaped.
Mande Maclay, Tegan Georges, Diana Fernadez
planet exploration Name: virginia & Date: 2002-09-10 15:08:03 Link to this Comment: 2597 |
our trip to the subject planet was informative, but there remains much research to be done. our general summary of observations is
as follows:
we divided the obvious plant life into three basic categories, based on size, shape/form, and similarity to plnat forms on earth:
1) plants resembling earth trees (tall, rigid, with a hard bark-covered trunk like stem, and branches ending in leaves): 2+ different
species
we considered the two "trees" we found to be different species because, while they were similar in size and general tree-like
attributes, they had different leaf forms, different branch patterns and different trunk characteristics ("bark" texture and color, size,
ratio to rest of tree)
2) bushes/shrubs: 5+ since these plants seemed to be of a size in between that of the "trees" and the ground cover plants, we
decided to call them "bushes" due to their similarities with earth bushes. these plants were all roughly 3-6 feet tall, with branches
that ended in leaves an/or needles. these were of varying shapes and sizes and textures and colors, but they all shared the
characteristic of being smaller than those of the trees. Some bushes were found to bear fruit or seed-like "pods", as was one of hte
trees, whereas nothing of that form was found on ground cover plants upon our brief inspection. However, this could be much
better determined by more extensive research. We came up with three possible hypotheses explaining the size of hte shrubs: a) they
are a different category of plants from the trees and ground cover, b) they are trees whose growth is not yet complete, or c) they are
trees whose growth has been stunted by being shaded from light by the (seemingly) fully developed trees.
3) ground cover plants: 31+ these came in all shapes and sizes, from under two centimeters up to more than 30, and everthing in
between. their stems were more flexible and soft than those of hte trees and shrubs, and they seemed to lack the protective "bark"
layer for the most part. the exception to this were some small plans with similar leaves to one of hte trees, and our hypothesis is that
this could possibly be a "sapling" or some sort of very early "tree" growth. within the category of "ground cover" we discoverd
what we believe to be two sub-categories, one being "moss" and the other "fungi", based on their similarities to the earth organisms
by those names. the "fungi" seemed to only be growing on what we believe to be teh dead remains of a "tree," which lead us to
believe that they may be some sort of parasite, possibly the cause of the "tree"'s death. Another hypothesis is that the seemingly
dead tree died because it was completely shaded by light from both the tree branches above it and a large hunk of what appeared to
be shale rock. another interesting characteristic of the ground cover is taht we were able to determine that, at least amongst the
plants that we sampled, there is an obvious root structure underlying hte soil while the part above is green and of a different texture.
this lead us to believe that these plants possibly recieve some sort of chemical from the sunlight that affects their coloring, similar to
plants on earth. we were unable to verify this finding with the trees and shrubs, as the plants were too big for any excavation under
such a short research period, but with a more extended deadline and budget we would be able to further investigate this topic. what
we were able to verify was that the trees seem to have a broad underground root system as well, which we concluded after
observing roots partially protruding from the ground surrounding the tree which had similar "bark" patterns, leading us to believe
that they were part of the same plant. also, the bushes and trees did display the same generally green coloring as the ground cover.
specific examples:
-there was one seemingly dead bush, which had no leaves and whose branches were dry, brown and brittle both inside and out
upon inspection, whereas the other bushes had branches whose insides were somewhat moist and green.
-there was a big patch of ground cover which appeared different from the rest, and which seemed to be in cooler, moister soil
overall. at hte time of our inspection the area was completely covered by shadow, and with further research we would be able to
determine if this were a different climate which would affect the plant's progress. also, as the patch of this different vegetation was
rather large, wiht all the plants growing densely together, we could assume that they do in fact reproduce and were spreading.
however, few plants and VERY few ground cover plants bore any evidence of fruits, seeds, or any other reproductive method
resembling those of earth plants. however, we have no way to know if this is simply because htese plants reproduce on some sort of
larger cycle, which we would be able to determine wiht more extensive research and more time for the project.
-on the ground on nearly all of hte site, particularly near the "trees", we observed leaves which appeared to be from said trees and
which were both brown and yellow in coloring, and appeared to be either dead or dying. the brown ones were of a brittle, easily
broken texture, whereas the yellow retained some of the rubbery, plastic categories of the green tree leaves.
survey of unknown planet Name: Date: 2002-09-10 15:09:12 Link to this Comment: 2599 |
A. One foot and below
I. <3 inches
a. light green
1.1/16 " stalks
a) leaves
1) spade shape
i) jagged contour
ii) smooth contour
2) oval shape
i) jagged contour
ii) smooth contour
3) rectangle shape
b) no leaves
2.1/8" stalks
a) leaves
1)spade shape
i) jagged contour
iii) smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) no leaves
b. dark green
1.1/16 " stalks
a)alternating leaves
1)spade shape
i)jagged contour
ii)smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) leaves symmetrical from stalk
c) no leaves
2.1/8" stalks
a)leaves
1)spade shape
i) jagged contour
ii)smooth contour
2)oval shape
i)jagged contour
ii)smooth contour
3) rectangle shape
b) no leaves
c. green/brown
II. < 6 inches (See above key)
III. < 9 inches (See above key)
IV. < 12 inches (See above key)
B. Between one and 10 feet
1. less than 1 " oval leaves
2. cylindrical leaves
3. large circular leaves
C. Between Above 10 feet
* ground cover and community of plant species noted for observational purposes. The possible takeover of portion of planet hospitable by humans is a large concern. Further rescources would allow for further research
Sarah Frayne and Kathryn Bailey
plant findings Name: Date: 2002-09-11 14:49:07 Link to this Comment: 2613 |
On Planet PSB we discovered many plants. We separated them into the following categories:
tree, small plants, grasses, mosses, shrubs, large plants.
we defined these with our accepted definitons from earth. a small plant was something under a foot or so tall, and a large plant was something larger than that. grass was short but widespread; moss was close to the ground and didn't have easily definable leaves. shrubs were short and fat trees that grew out rather than up; they also didn't have trunks. trees had trunks! they grew up rather than out.
we found 28 different specimens.
some examples of each:
we found 17 different varieties of small plants.
one example is a chive-like plant, which smells and looks exactly like a chive. interesting. what would darwin say about this? it is thin and long, no leaves, and feels like it is hollow. it has a pungent aroma.
another example is a flowering leafy small plant. the leaves are thin and grow directly off the stem. they have a grainy texture. at the top there are buds for flowers. the flowers will be yellow.
we found two different varieties of trees
both were tall; one had wider leaves than the other. the one with wide leaves had forked leaves and spikey balls that were attached to the leaf clusters. the bark was more course than the other tree. the tree with the slender leaves (which were also in clusters) had bark that was smoother and flakey.
we found four different varieties of grass
one example has flat leaves that are very thin and long. it divides at the top into more than one leaf. the leaves have grooves. they are cupped with a definitive point at the bottom of the cup. (like a piece of paper folded).
we found three different varieties of shrub
one example had waxy rounded leaves (they look like fake nails) that grew in clusters. the shrub was about six feet tall and about as wide. the stems were hard to break off. it was similar to a beach umbrella. the leaves were dark in color.
another example had small dark green leaves that grew in circular clusters around the stem. the shrub had small red berries with a large seed. the shrub had the appearance of an evergreen.
we found one variety of a large plant. it looked like a rhubarb plant. we smelled the stem but found no smells similar to the rhubarb; this could be because of its young age, or because it is not a rhubarb. the leaf is fuzzy and has a spade shape. it is deep green. the stem is a reddish color. the veins are very defined. the leaf is about the size of a normal human's face and can be larger.
we found one variety of moss. it grew close to the ground, was fuzzy to the touch, and very very dark green. forest green, actually. in places it was yellow in appearance but we concluded it was the same type of moss due to its appearance apart from color.
we have concluded that the environment on Planet PSB is very similar to that on Earth. the plants seem to resemble almost exactly those found on earth. one could say one was on earth. funny, that.
Plants on New Planet Name: Chelsea R. Date: 2002-09-11 14:49:59 Link to this Comment: 2614 |
Plant Lab Report Name: Emily Sene Date: 2002-09-11 14:50:50 Link to this Comment: 2615 |
Plant life on PSB Name: Date: 2002-09-11 14:51:04 Link to this Comment: 2616 |
We found 32 species of plant life on the planet. They ranged in size from tiny to huge and spanned ground, mid, and high levels of growth. We distinguished the plant species by color, shape, size, texture, and location. All plants were green unless otherwise noted.
The following are the species we determined
#1 -- mid level bush with shiny, fuzzy, green, almond-shaped leaves, remnants of flowers.
#2 -- high level tree with 5-6 pointed, star-like, green leaves, on outstretched branches.
#3 -- ground level thin bladed grass
#4 -- ground level thick bladed grass
#5 -- ground level heart-shaped grean leaves
#6 -- ground level long, green, pointed leaves
#7 -- mid level tiny, shiny, smooth, green leafed bush
#8 -- mid level red berry producing thin, green, spikey needled bush
#9 -- ground level tall yellow-green medium width blade grass
#10-- ground level spikey moss
#11-- ground level soft fern-like spikey green leaves
#12-- ground level fuzzy spikey- edged prickley weed-like leaves.
#13-- high level flaking bark green, tear-dropped shaped, smooth leaves, branches growing straight up tree. Had spikey pods on ground.
#14-- mid level smooth, velvety green leaves, sappling/shrub.
#15 -- 3-leafed in shade, green ground covering.
#16 -- Discolored green/brown "eaten Looking" plant, sappling or shrub.
#17 -- ground level, small yellow flowers on clover-like tiny round leaves growing in groups of three.
#18 -- tall wide bladed grass with centers of long fuzzy "wheat" like flowers.
#19 --almond shaped weed like leaves ground level.
#20 -- fuzzy leafy geranium shaped leaves ground level.
#21 -- non-fuzzy spikey weed-like leaves layered and grow out of center.
#22 -- scalloped leaves with buds red and brown stem, green leaves.
#23 -- tall stemmed long weed like spikey flowered plant.
#24 -- tiny bunched up layered leaves with fuzzy new leaves at center.
#25 -- light green tiny scalloped layered leaves growing to med ground level with flowered plant and white speckles on leaves.
#26 -- Super shiny giant spikey edged green leaves with red stalks. Ground level.
#27 -- Huge green thick stalked ruffled edged leaves at ground level.
#28 -- Huge red-stalked scalloped and ruffled heart shaped green leaves, floppy, hang over to ground from stems.
#29 -- Parsley looking clustered bunched leaves.
#30 -- Symmetrical light green with a lighter greenish-white pattern on leaves, flat fern-looking ground level.
#31 -- Vine like leaves grow in circular pattern around stalk.
#32 -- Five leaves clustered with scalloped edges red around edges.
Bio 103 Lab #1 Name: Date: 2002-09-11 14:55:42 Link to this Comment: 2617 |
In order to count the number of plants, we observed and noted specific characteristics that differentiated and distinguished them. The following is our observations:
1. Really thin (gossamer) grass-like plant, yellowish.
2. Thin grass-like plant, green
3. Thicker grass-like plant, green
4. Broad leaf grass-like plant, green, very close to ground in clusters
5. Spiny grass-like plant, green
6. Tall, thin grass with alternate thicker blades at 90 degree angles
7. Small clovers with round leaves, green, very close to ground
8. Large clovers, green
9. Small plant with three spikey, green, tear-drop shaped leaves all at the top of the stem of the same plant
10. Small plant with four spikey, green, tear-drop shaped leaves with red spots, all at the stem of the same plant
11. Small plant with five spikey, green, tear drop shaped leaves all at the stem of the same plant
12. Cluster of broad, spikey leaves with deep cuts into the sides, close to the ground with basically no stem
13. Flowering very thin leaved and stalked with whorled leaves. Flowers were small, whitish and ball-like
14. Small, fern-like, double compounded plant
15.Moss, flat on the ground, with a dark base but small, green-tipped spongey tecture
16. Tree with star-shaped leaves
17. Tree with tear-drop shaped leaves
18. Six inch tall plant with a thick, red-striped stalk, alternate branches and two small leaves at the base of a really big leaf
19. Spade shaped small, single-leaved plant, lighter green in color
20. Five-point leaf with two small points at the base of three more pronounced points
21. Tear drop shaped, lopsided leavesm, three on a cluster on each stalk
22. Seven foot bush with thin needles at the end of branches, very small base but branches spawl
23. Six foot bush with small, round, waxy leaves and red berries
24. Similar to six foot bush in shape but leaves were longer and broader and no berries or wax coating. There were small bunches of leaves.
Name: Date: 2002-09-11 15:21:46 Link to this Comment: 2625 |
Questionables (molds and fungi that are either animal or plant)
- Moss (2)
soft spikes growing on the bark of trees
fern like, on ground between plants with star blooms
- Fungus (3)
blue fungus growing on trees, sprawling out from a central place
striped mushroom in shades of brown and white
yellow that sprouted like a mushroom on stump
Grasses (10)
Crab Grass
Club-shaped, leaved ivy
Prairie Grass
Wheat Grass
Long, thin grass, dark green, growing parallel to ground
Standard short grass, more yellow (lack of water?), 2-3 inches
Clovers (4)
Three-leaved
Four-leaved
14 round points
Speckeled leaves
Plants (15)
Strawberry-like plants, red berries
Mutant Collard Greens (2)
Green Stems, thin leaves
Purple Stems, wide leaves
Marigold-like, non-blooming plants
Dandilions (4)
Spiked leaves
Low, fuzzy
Rounded
Fern-like, centralized, low to ground
Small plants(7)
Vertical (5)
Spiked, enlongated leaves, with red base
Minature pussywillow, long stem, with white bloom
Lower leaves purple, upper leaves green (of medium size)
Violets
Mushroom-shaped leaves
Horizontal (2)
Red stem, small round green leaves, glossed
Thin, green Ivy with small staggered leaves
Trees and Bushes (5)
Maple tree
Silvery-green leaves, pointy
Pine bush with red berries
Larger leaves, thin, yellowy green
Small, hard, glossy dark-green leaves
categorization of plants Name: Diana & A Date: 2002-09-17 14:35:53 Link to this Comment: 2722 |
2. Brown stalk
A: < 10 ft
a. needles b.soft leaves bb1.rounded bb2. pointed
B:>10ft
a:single point b:multi point
3.No stalk
A:green
a. spongy leaf b.no leaves/hard
B:other(color, or "Grobstein" category)
a. flat aa1:bumpy aa2:smooth/close to surface
b. protruding bb1:disc shape bb2:tubular shape
Amanda Maclay Diana Fernandez
Planet Courtyard Key Name: Date: 2002-09-17 14:39:59 Link to this Comment: 2723 |
A. Tree Like
1A. Tall (8' and taller)
1A'. Jagged leaves (papery bark)
1A". Five lobe leaves (regular bark)
2A. Smaller (8' and smaller)
2A'. needles with berries
2A". leafy
2A"1. Alive
2A"1'. Lt green leaves (not waxy)
2A"1". dk green leaves (waxy)
2A"2. Dead
B. Un-tree Like
1B. Ground Cover
1B'. Leafy
1B'1. Stringy
1B'2. Vuluptuos
1B'3. Shag
1B'4. Crab Grass
1B'5. Tall
1B". "Mossy"
1B"1. Moss
1B"1'. Soft
1B"1". Hairy
1B"2. Lichen
2B. Individual Plants
2B'. Leafy
2B". Flowery
2B"1. Red-vein crawling
2B"2. Tall flowering
2B"3. Yellow flowering
2B"3. Oreo
2B"4. Squash
2b"5. Pumpkin
2B"6. Red Berry
2B'1. More than one stem
2B'2. Single-stemed
2B'1'. Clusters
2B'1'1. Lilly pad
2B'1'2. Jagged-edge clover
2B'1'3. Clover
2B'1". Not clustered
2B'1"1. Smooth leaves
2B'1"2. Jagged leaves
2B'1"3. Spunky fern
2B'1"4. Fat fuzzy
2B'1"5. Long fuzzy
Stephanie Lane, Katie Campbell, Kate Amilin
lab report II Name: Joanna, Ya Date: 2002-09-17 14:43:37 Link to this Comment: 2724 |
****************************PLANT LIFE*********************************
I. PLANTS
A. soft texture
1. moss (close to ground)
2. skinny leaf/Linear
3. thick leaf
B. thin/hard texture and leaves
1. leafy branches/ Even Pinnate
2. few leaves/ Biternate
3. single leaves/YEW(needle foliage leaf)
C. single thick/hard trunk and leaves
1. Orbicular
2. Palmately Lobed
II. FUNGI
A. Black
1. round/cap/ Pilius
2. Oyster
B. Tan
1. Fan-shaped Pilius
C. White
1. Fan- shaped Pilius
D. Lite Beige
1. Mushroom
Planet Courtyard - Voyage #2 Name: virginia l Date: 2002-09-17 14:45:27 Link to this Comment: 2725 |
back to planet PSB Name: Date: 2002-09-17 14:46:42 Link to this Comment: 2726 |
We noticed that the biggest difference between the plants is the support system, which then determines the size, shape, and foliage of the plants. We wanted to find the least complex way of organizing all of the differences. We didn't classify and specifically name all of the plant life here, we are just presenting the basic outline of how the organization.
Support System
I. Brittle
A. Trees
1. horizontal branches
2. vertical branches
B. Bushes
1. Needles
2. Contoured
a.Round tip
b. Pointy tip
II. Non-Brittle
A. Mosses
1. Soft spike
2. Fern like
B. Grasses
1. Bladed
a. Long and skinny
b. Long and flat
c. Short and skinny
2. Non-Bladed
a. Clover
-3 leaves
-4 leaves
-14 leaves
C. Small Plants
1. Leaves from root
2. Leaves from stalk
Planet Courtyard Key Name: Date: 2002-09-17 14:46:50 Link to this Comment: 2727 |
PLANTS
1.0) Single Stalk 2.0) Mult. Stalk 3.0) No Stalk
(single root) (single root) (sngl. or mult.)
1.1 - Branches
1.1.1 - smooth bark (oval leaves - tree#1)
1.1.2 - rough bark (star shaped leaves - tree#2)
1.2 - No Branches (weeds)
1.2.1 - Flowers
1.2.1 A - clover-like flowers (s.p.#12)
1.2.1 B - small plant with yellow flowers (s.p.#7)
1.2.2 - No Flowers
1.2.2 A - big spotted leaves (s.p. #10)
1.2.2 B - dk. green multiple solid leaves (s.p. #3)
1.2.2 C - dk. green single solid leaves (s.p. #2)
2.1 - Branches
2.1.1 - Needles (bush #2)
2.1.2 - Leaves
2.1.2 A - fuzzy leaves (bush #1)
2.1.2 B - waxy leaves (bush #3)
2.2 - No Branches
2.2.1 - weed with small yellow flowers (s.p. #4)
3.1 - Ground Covers
3.1.1 - Vine (g.c. #2)
3.1.2 - Moss (g.c. #1)
3.2 - Leaves straight from Root
3.2.1 - Skinny (grasses)
3.2.1 A - flat leafed grass (grass #2)
3.2.1 B - thin leafed grass (grass #1)
3.2.1 C - Fine grass (grass #4 - new!)
3.2.1 D - Chive (grass #3)
3.2.2 - Wide Leaves
3.2.2 A - Horizontal growth
3.2.2 A' - large leaves with seed stalk (s.p. #8)
3.2.2 A'' - huge plant (s.p. #13)
3.2.2 A''' - big plant leaves (s.p. #9)
3.2.2 A'''' - dandylion (s.p. #11)
3.2.2 B - Vertical Growth
3.2.2 B' - spikey plant (s.p. #1)
3.2.2 B'' - white spot plant (s.p. #5)
3.2.2 B''' - serated leaf plant (s.p. #14 - new!)
plant key Name: sarah fray Date: 2002-09-17 14:49:25 Link to this Comment: 2728 |
II No Trunks
---A no leaves
-----1 green
-----2 brown
---B leaves
-----1 linear leaves
-------
-----2 non linear leaves
-------a cordate
-------b jagged
-------c straight
-------d pinnatifid
Lab 2 Name: Kyla And M Date: 2002-09-17 14:49:29 Link to this Comment: 2729 |
1. Is it a plant? Yes? Go to 2.
2. Is it dificult to uproot? ...Yes: go to 3
............................No: go to 11
3. Is it majorly difficult to uproot? ...Yes: go to 4
......................................No: go to 7
4. Difficult to uproot......Has deep ridges on trunk?....Yes, go to 5
......Has smooth trunk with easy- peelable bark?...Yes, go to 6
5. Has 5-point leaf? CLASS C SUB 1
6. Has one-point leaf? CLASS C SUB 2
7. Do branches grow straight up?...Yes: go to 8
................................No: go to 10
8. Are leaves blade-like?.......Yes: go to 9
9. Does plant have red berries?.....Yes: CLASS B SUB 1
10. Has glossy leaves?....Yes: CLASS B SUB 2
.....................No: CLASS B SUB 3
11. Does it have blades? Yes: go to 12
.....................No: go to 17
12. Does it have a stalk? Yes: go to 13
..........................No: go to 16
13. Is stalk thick or thin? Thick: go to 14
.............................THin: go to 15
14: Does plant have a bud-like growth? Yes: CLASS A SUB 1
........................................No: CLASS A SUB 2
15. Does it have broad leaves? Yes: CLASS A SUB 3
..................thin leaves? Yes: CLASS A SUB 4
16. Does it have broad leaves? Yes: CLASS A SUB 5
..................Single blades? Yes: CLASS A SUB 6
17. Does it have a Stalk? Yes: go to 18
..........................No: go to 19
18. Does it have a flower? Yes: CLASS A SUB 7
............................No: CLASS A SUB 8
19. Does it have spiky leaves? Yes: CLASS A SUB 9
...............................No: go to 20
20. Are leaves elliptical in shape? Yes: CLASS A SUB 10
....................................No: CLASS A SUB 11
Classifications Name: Adrienne, Date: 2002-09-18 14:03:01 Link to this Comment: 2747 |
PLANTS
I. Woody
A. Trees
...1. branches
......-location
......-shape
......-size
......-texture
...2. leaves
......-shape
......-color
......-size
......-texture
......-location
...3. Fruit/Flower/Seed
......-color
......-texture
......-taste/smell
......-size
......-shape
...4. Root
......-location
......-shape
......-size
......-depth
...5. Trunk
......-texture
......-thickness
......-strength
......-color
......-height
B. Shrubs
II. Non-Woody
**see Woody Plants**
A. Plants
B. Grasses
Maggie, Emily, Laura B., Adrienne
planet psb revisited Name: Date: 2002-09-18 14:04:59 Link to this Comment: 2748 |
on planet PSB the diversity was broken down into woody and non-woody.
1. woody plants : as the definitions below state, trees and shrubs are both woody plants. they are differentiated by height and where the branches start. we have them in the same category due to their woody stems.
...A) tree: a woody plant at least 5 metres high, with a main axis the lower part of which is usually unbranched.
...B) shrub: a woody plant less than 5 metres high, either without a distinct main axis, or with branches persisting on the main axis almost to its base.
(definitions found at http://www.b-and-t-world-seeds.com/k-o.htm#karyoevolution)
2. non-woody plants : these plants did not have a well-defined support system. they did not have woody stems.
...A) stems : these plants did have stems, but they were not woody; they were soft and fleshy. the stems were green or reddish in color.
.......a) large plants : the large plants were over one foot tall.
.......b) small plants : the small plants were under one foot tall.
............1) flowering
............2) non-flowering
...B) no stems : these plants did not have stems that were readily discernable. these plants grew close to the ground and in clusters. the clusters also grew close together, so it was hard to distinguish them from one another.
.......a) mosses : the mosses looked like a plant carpeting the ground. it was a consistent dark green color with yellow discolorations. the leaves are not distinct from each other. mosses grow along the ground, spreading out rather than growing vertically.
.......b) grasses : the grasses, although they do not have stems, were one continuous plant. the leaves had vein and were vertical and thin.
............1) flowering
............2) non-flowering
Classifications Name: Mer, Chels Date: 2002-09-18 14:13:23 Link to this Comment: 2749 |
I. Plants
------A. No Bark
--------------1. Flowering plants
------------------a. Leaf distinctions (color, shape, size etc.)
------------------b. Stalks (color, thickness - realizing that age of the plant is an influence)
--------------2. Fronds - Non flowering plants (no visible buds and no evidence of sprouting)
------------------a. Generic Grasses (in referenece to earth's many and diverse grasses)
------------------b. Tall Grasses (over 7 inches tall)
------------------c. Stalked Plants (differentiated by leaf shape, color, patterns, etc)
--------------3. Mosses
------B. Bark
---------------1. Bushes
-------------------a. Texture of bark
-------------------b. Leaf shape, color, size, texture, etc.
-------------------c. Berries
---------------2. Trees
-------------------a. Growth Pattern
-------------------b. Leaves
-------------------c. Bark
II. Fungi
A Return to the Planet of Pretty Plants, Intern in Name: Carrie, La Date: 2002-09-18 14:14:05 Link to this Comment: 2750 |
Name: Anne, Bobb Date: 2002-09-18 14:18:31 Link to this Comment: 2751 |
B). Trees--Large
A single vertical growing plant that branches out as height increases. It grows independently. Has one main stem which is grounded by stable roots. Height is normally greater than width. Able to sustain secondary growth (leaves). Branches begin growing outward at mid trunk.
C). Bushes--Medium
A plant having a width greater than (or close in length to) height. Branches begin growing outward at base of trunk. Branches contain many smaller leaves.
Plant with minimal height (in comparison with other groups found on planet)
D). Moss:
A ground plant with relatively no height. Grows ouward, over a surface area. Spft texture.
Surface Growing Plants
A) flat (1)
B) bushy (2)
Within the small plants:
A) grasses-a plant that grows in an individual strand
B) weeds--a small plant that has a stem which is the base for other growth such as leaves, buds, or flowers.
Small Plants
A) grasses- 1) thin i) long, thin, green waxy clusters (1)
2) thick i) leaf like one stem branches out (2)
B) weeds- 1) seeds i) loose seeds (12)
ii) grouped soft seeds (13)
2) cloved i) ridged leaves (6)
ii) smooth leaves (7)
3) vine-like i) tall (5)
ii) stuck to ground (11)
4) wide leafed i) tall (9)
ii) close to ground (3)
iii) spiky leafed (15)
iv) lettuce like leaves (17)
v) spotted (14)
5) flowered i) one stem with multiple flowers (8)
ii) with oval leaves (19)
iii) one flower (10)
6) buds i) long and stubbly (4)
Medium Plants
A) Bushes- 1) non leafed (4)
2) leafed i) needle-like (2)
ii) oval shaped a) large (1)
b) small (3)
Big Plants
A) Trees- 1) rough bark (1)
2) smooth bark (2)
Classifying Plants Name: Date: 2002-09-18 14:24:51 Link to this Comment: 2752 |
IF:
A. Plant has continuous root system:
---a.If plant has clover-shaped leaves.
----------1.Small clovers with round leaves, green, very close to ground
----------2.Large clovers, green
---b.If plants have individual blades:
----------1.Thick blades
--------------------i. Thicker grass plant, green
--------------------ii. Broad leaf grass plant, green, very close to ground in clusters
--------------------iii. Spiny grass plant, green
---------------------iv..Cluster of broad, spikey leaves with deep cuts into the sides, close to the ground with basically no stem
----------2. Thin blades
--------------------i. Really thin (gossamer) grass plant, yellowish
--------------------ii. Thin grass plant, green
--------------------iii. Tall, thin grass with alternate thicker blades at 90 degree angles
B. If plants have individual roots:
--a. If plant has soft exterior
----1. Spikey leaves
----------i. Small plant with three spikey, green, tear-drop shaped leaves all at the top of the stem of the same plant
----------ii. Small plant with four spikey, green, tear-drop shaped leaves with red spots, all at the stem of the same plant
----------iii. Small plant with five spikey, green, tear drop shaped leaves all at the stem of the same plant
----2. Tear-drop shaped leaves
----------i.Compound leaves
----------------Small, fern-like, double compounded plant
----------ii. non-compound leaves
----------------* non-flowering
----------------------Tear drop shaped, lopsided leavesm, three on a cluster on each stalk
----------------------Six inch tall plant with a thick, red-striped stalk, alternate branches and two small leaves at the base of a really big leaf
---------------* Flowering
----------------------very thin leaved and stalked with whorled leaves. Flowers were small, whitish and ball-like
----3. Spade shaped leaves
---------i. spade shaped small, single-leaved plant, lighter green in color
--b. If plants have hard exterior (bark)
----1. branches originate at base of plant
--------i. needles
-------------Seven foot bush with thin needles at the end of branches, very small base but branches spawl
--------ii. leaves
----------waxy leaves
--------------Six foot bush with small, round, waxy leaves and red berries
----------non-waxy leaves
--------------similar to six foot bush in shape but leaves were longer and broader and no berries or wax coating. There were small bunches of leaves.
----2. branches originate above the base
--------i. star shaped leaves
--------------Tree with star-shaped leaves
--------ii. tear shaped leaves
--------------Tree with tear-drop shaped leaves
C. Un/Classified
----1. Moss, flat on the ground, with a dark base but small, green-tipped spongey tecture
----2. Appears to be a small tree, but did not know how to classify it until it matures to full size- Five-point leaf with two small points at the base of three more pronounced points
Classification Name: Date: 2002-09-18 14:34:19 Link to this Comment: 2753 |
This classification should be used only on Planet Courtyard. It is created from our discoveries.
cells Name: TEGAN, AMA Date: 2002-09-24 14:47:34 Link to this Comment: 2873 |
Observations:
Fungi:uniform cells, 10.4 Micrometers in diameter, slightly oblong shape.
Small leaf: Jigsaw membrane: 39Micrometers, Stomatal: 26 Micrometers.
Large Leaf:Jigsaw membrane, Stomatal: 23.4 Micrometers
Earthworm: Non uniform cells: 13-15.6 Micrometers.
Human cartilage: Non Uniform: 10.4-13.0 Micrometers
Conclusion: We did not find a sepcific corrolation between size of organism and size of cell. We did however find that there was more variance in cell size the more complex the multi cellular organism.
Diana Fernandez, Amanda Maclay, Tegan Georges
Ginny, Maggie, Kyla Name: Date: 2002-09-24 14:56:42 Link to this Comment: 2874 |
Hypothesis: We think that diferent types of organisms have different types of cells.
Data:
Fungi cells: Long and stringy like spagetti, but not arranged in a cohesive pattern
Berry Cells: slightly elliptical with solid nuclei, kinda like fried eggs
Leaf Cells: circular, with jagged edges
Grass Cells: Rectangular/elliptical
Hair Cells: Long, stringy, ("hair-like" hehe...) cells that fit together in a set pattern
Eyelash Cells: Had similar structure as the hair, but had a deep, dark core that was continuous except for at the two ends. The edges had ragedy edges and the core was smooth
Earthworm Cells: Different shaped-sized cells, indicating different pars of the worm's body.
Human cartilagde: Elliptical roundish shape with possible nucleus inside.
Conclusion:
Yes, different organisms have different cells. Not only that, but diffrent parts of the organism are made up of different cells. Identification of a species/plant/organisms can be traced down to the most basic form, i.e., the cell. Because each organism's cells are so destinctive, identification can be based on those cells alone. This is cause for futher study.
Cell Sizes Name: Date: 2002-09-24 14:58:30 Link to this Comment: 2875 |
In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)
We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.
The following is our recorded observations of their size.
PSB courtyard planet bush
Organism sixe: 2.6 m approximately
Cell size: 26 micrometers
Paramecium
Organism size: +/- .5 milimeters
Cell size: 156 micrometers by 36.4 micrometers
Human thyroid
Organism size: 2-2.5 m approximately
Cell size: 85.8 micrometers
Blade of Grass
Organism Size: 114 mm approximately
Cell Sizes: 18.2 - 57.2 micrometers
Earthworm
Organism Size: 74 mm approximately
Cell Sizes: 10.4 - 182.0 micrometers
Buttercup Stem
Organism Size: 115 cm approximately
Cell Sizes: 15.6-26 micrometers
Corn Stalk
Organism Size: 3 m
Cell Sizes: 208-1040 micrometers
We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.
Cell Sizes Name: Date: 2002-09-24 14:58:47 Link to this Comment: 2876 |
In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)
We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.
The following is our recorded observations of their size.
PSB courtyard planet bush
Organism sixe: 2.6 m approximately
Cell size: 26 micrometers
Paramecium
Organism size: +/- .5 milimeters
Cell size: 156 micrometers by 36.4 micrometers
Human thyroid
Organism size: 2-2.5 m approximately
Cell size: 85.8 micrometers
Blade of Grass
Organism Size: 114 mm approximately
Cell Sizes: 18.2 - 57.2 micrometers
Earthworm
Organism Size: 74 mm approximately
Cell Sizes: 10.4 - 182.0 micrometers
Buttercup Stem
Organism Size: 115 cm approximately
Cell Sizes: 15.6-26 micrometers
Corn Stalk
Organism Size: 3 m
Cell Sizes: 208-1040 micrometers
We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.
Cell Sizes Name: Katie, Kat Date: 2002-09-24 14:59:46 Link to this Comment: 2877 |
In beginning to compare the size of cells with the size of their organism and then with each other, we hypothesized that the size of a cell would correspond with the kingdom of its organism. Therefore we predicted animal cells would be the largest whereas plant cells would be smaller. (In this stdy, we did not compare all five kingdoms, but just Animals and Plants.)
We looked at seven cells from a variety of sources such as a Paramecium, human thyroid, PSB courtyard planet bush, buttercup, and earthworms.
The following is our recorded observations of their size.
PSB courtyard planet bush
Organism sixe: 2.6 m approximately
Cell size: 26 micrometers
Paramecium
Organism size: +/- .5 milimeters
Cell size: 156 micrometers by 36.4 micrometers
Human thyroid
Organism size: 2-2.5 m approximately
Cell size: 85.8 micrometers
Blade of Grass
Organism Size: 114 mm approximately
Cell Sizes: 18.2 - 57.2 micrometers
Earthworm
Organism Size: 74 mm approximately
Cell Sizes: 10.4 - 182.0 micrometers
Buttercup Stem
Organism Size: 115 cm approximately
Cell Sizes: 15.6-26 micrometers
Corn Stalk
Organism Size: 3 m
Cell Sizes: 208-1040 micrometers
We were wrong (#5421 this week). Organisms don't just have one cell size but many different cells. The sizes aren't consistant within the organisms themselves, nor the different kingdoms. If we could look into this further, we might discover and define certain types of cells and find their size and how they correlate and compare that way.
cell size Name: Date: 2002-09-24 15:04:58 Link to this Comment: 2878 |
We feel that maybe the size of the cell is perhaps determined by the function of the cell- otherwise our data should be more consistent to our first thoughts about cell size. Even within the samples we found, there were different size cells.
Heather, Christine, Margot
kathryn bailey, sarah frayne, laura sylvius Name: Date: 2002-09-24 15:06:10 Link to this Comment: 2879 |
corn............10 ft...........................0.80 um
tree leaf.......20 ft...........................1.30 um
earthworm.......0.25 ft.........................1.04 um
elodea..........0.50 ft.........................0.68 um
moss............0.10 ft.........................2.58 um
hypothesis: There is a direct correlation between the size of the organiism and the size of the organism's cells.
Conclusion: Our hypothesis was disproven because we did not find a sizable correlation between the size of the five organisms and the size of their cells.
Cells Name: Date: 2002-09-24 15:06:18 Link to this Comment: 2880 |
Our original hypothesis was that all cells would be of a comprable size, regardless of the size of the organism. However, our observations proved that our hypothesis was wrong. No only did cell size vary from plant to plant, but there were also cells of differing sizes within the same organism.
We observed five different samples: grass, a tree leaf, and clover from the courtyard, and an earthworm and moss from the prepared slides. For individual cell size, our measurements were as follows (in micrometers):
Moss (1 inch): from 10.4-78
Earthworm (8-10 inches): from 5.2-13
Clover (3 inches): from 5.2-26
Grass (6 inches): from 13-104
Tree leaf: (40ft tree): from 26-130
cells Name: joanna, ya Date: 2002-09-24 15:16:20 Link to this Comment: 2882 |
hypothesis: Cell size does not depend on organism size
observations:
moss- 52.0 mm
Elodea- 102 mm
cheeck- 78.0 mm
corn stalk- 67.6 mm
earthworm- 52 mm (LONGER cells)
13 mm ( small cells)
Conclusion: Size of the organism does not account for cell size, but all cells are not the same size. There are even different cell sizes within one organism.
Questions....
1. Does cell function determine cell size?
2. Was it human error that accounts for the differences we saw?
3. Is volume a better way to measure cells?
Joanna Robertson, Yarimee Gutierrez, Jennifer Rusk
Cell Lab Name: Diana, Mic Date: 2002-09-25 14:33:13 Link to this Comment: 2888 |
The original hypothesis was that organism size depends on cell size, that bigger organisms will have bigger cells.
Results are as follows:
Elodea cell - 50 um
Plant from PC cell - varied from 7.8 to 28.6 um
Zea stem cell - varied from 7.8 to 117 um
Amoeba cell - 262.6 um
Paramecium - 65 um
Our conclusion is that cell size does not determine organism size. However, this hypothesis stands when used for single celled organisms alone. Our observation of plant cells demonstrated the various cell size within one organism. Due to the congregration of similar sized cells within multicellular organisms, we concluded that they have varying sized cells for various functions.
Cell Size Name: Chelsea R. Date: 2002-09-25 14:48:42 Link to this Comment: 2889 |
Hypothesis: The size of an organism will not always correlate to the size of its cells.
Data/Observations: Corn Stem Cell - length: 70um Moss Cell - length: 78 um Elodea Cell - length: 50um Ameoba Cell - length: 36.4um Hair Cell - length: 100um
Note: Many of these samples showed cells of varying sizes within the organism. We recorded, for our purposes, the length of what appeared to be a relatively represetative cell (except, of course, in the ameoba, which is a one-celled organism).
Conclusion: Our hypothesis still appears to work. Within each organism, cell size varied, and between organisms cell size also varied, although without any apparent correlation to size of organism. For example, a moss plant is smaller than an elodea plant, but our observations showed moss cells larger than elodea cells.
Cells Fabulous Cells! Name: Date: 2002-09-25 14:50:18 Link to this Comment: 2890 |
Lab Hypothesis: Bigger organisms have bigger cells.
Collected Data through use of microscope:
Corn Stem cell size range: 7.8 -143 micrometers
Clover flower petal cell (from planet courtyard): 13 micrometers
Earthworm (one of many cells): 18.2 micrometers
Elodia cell width: 26 micrometers
Elodia cell length: 61.8 micrometers
Erin's Cheek cell: 50 micrometers
Ameba proteus : 200 micrometers
Conclusion: Bigger organisms do not actually have bigger cells. Cell size varies from organism to organism not depending on the size of the organism.
bio lab #3 Name: Annie and Date: 2002-09-25 14:53:31 Link to this Comment: 2891 |
human thyroid
length: 234 um
width: 78 um
area: 18252 um^2
mushroom
length: 156 um
width: 9.1 um
area: 1419.6 um^2
earthworm
length: 169 um
width: 31 um
area: 5239 um^2
clover leaf
length: 91 um
width: 31 um
area: 2821 um^2
moss
length: 174 um
width: 52 um
area: 9048 um^2
(obviously, the area calculated is only a rough estimate not account for the irregular shape of the cells)
areas (ranked by size, largest to smallest):
human thyroid (18252), moss (9048), worm (5239), clover (2821), mushroom (1419).
The cells we measured are only single examples of a cell in each organism. The size of cells within a single organism vary greatly.
According to our data, there is no parallel between the size of the cells and the size of the organism. Our hypothesis is therefore incorrect.
cell size Name: no Date: 2002-09-25 14:55:40 Link to this Comment: 2892 |
Our hypothesis was that cell size relates directly to plant or animal size. We found, however, that just because a plant or animal is large is doesn't necessarily mean the cells of that living organism are large as well. Our evidence for this new idea is as follows:
Corn stem cells, from a corn stem, which as we all know is quite a large plant, were found to have cells about 90 micrometers across.
The Water Plant cells were between 50 and 100 micrometers. The water plants found in the lab are as big as that particular plant grows.
Buttercup stem cells were found to be between 50 and 70 micrometers. As we all know, buttercups are plants the size of redwoods, and are found in only select parts of Maine and New Hampshire. NO! This is actually a lie. Buttercups are small flowering plants found throughout the world. SMALL is the point we need to make here.
Moss (Mature Archegonium) was found to have cells roughly 125 micrometers in size. Think about moss. Think about size. Moss is small.
We also looked at a sample of cells from Ja Ja's mouth. As we all know, she is a large animal, being human. The cells were found to be from 50 to 120 micrometers in diameter.
From these samples we have determined that although there are many different sized plants and animals in the world, they do not all have different sized cells. Just because a plant may be larger than another plant does not mean its cells are larger than those in other plants. It would make sense that this is true, because if a plant had very large cells I would think the plant would be brittle, as the cell wall would have to be very large and tough to support a large plant. It makes more sense to build a large building with smaller, stronger bricks than with larger bricks. As Woo Woo just said, it's more the TYPE of cells.
We hope we have not offended anyone with our findings. Can we go home now?
ps tobacco looks nasty under a microscope. so does bleached hair. ...excellent...
Determining Cell size of different specimens Name: Date: 2002-09-25 14:58:37 Link to this Comment: 2893 |
For this lab we looked at different cell specimens and determined the average cell size for each specimen.
Hypothesis: The larger the organism is in real life the larger its cells.
Methods: For this experiment we used a simple microscope to determine cell structure and cell size for 5 different specimens, 4 of which had been previously prepared and one specimen for which we prepared the slide.
The general method we followed was to adjust the slide under the microscope under various lenses (usually using the highest powered lens) and moving the stage till the cell was at its best focus. Then we went on to measure its size using the ruler inside the lens. We looked at three different cell sizes for each specimen and then took the average of all the three measurements that we determined.
Observations:
Specimen 1:
HB 7-12, Hyaline Cartilage
1) 13x2.6 =33.8micrometer
2) 15x2.6 =39micrometer
3) 12x2.6 =31.2 micrometer
Avg. size =34.67micrometer
Roundish/Elliptical in shape
Specimen 2:
Elodea (plant)
1) 40x2.6 =104micrometer
2) 42x2.6 =109.2 micrometer
3) 39x2.6 =101.4micrometer
Avg.size =104.87micrometer
Rectangular in shape with rounded edges, lots of chloroplasts inside.
Specimen 3:
Lumbricus X-Section
1) 4x2.6 =10.4micrometer
2) 5x2.6 =13micrometer
3) 3x2.6 =7.8micrometer
Avg.size =10.4micrometer
Elliptical purple cells and roundish green cells could be seen.
Specimen 4:
Zea Stem C.S.
1) 43x2.6 =111.8micrometer
2) 59x2.6 =153.4micrometer
3) 46x2.6 =119.6micrometer
Avg.size =128.27micrometer
Different cells could be seen but the one examined and measured is a transport cell from the vascular tissues.The cell is big and unevenly shaped.
Specimen 5:
Cheek cells
1)77micrometer
2)76micrometer
3)78micrometer
Avg.size = 77micrometer
roundish in appearance.
Conclusion: We are happy to say that our hypothesis is wrong (yay!). Larger organisms do not necessarily have larger cells than smaller organisms.
Cell size Name: heidi adle Date: 2002-09-25 15:03:20 Link to this Comment: 2894 |
Hypothesis: The size of an individual cell is directly related to the size of the complete organism.
Earthworm--> 5.2 micrometers (ums)
Moss--> 130 mircometers (ums) (we also saw smaller cells, but could not measure them)
Elodea--> 85.8 mircometers (ums)
Dried Tobacco--> 33.8 micrometers (ums)
Mare's skin--> 65 micrometers (ums)
An individual moss is about 5 cm long compared to an elodea branch which is about 10 cm long. The cells of these two organisms are 130 ums and 85.8, respectively. A human epidermis covers a person who is about 5'4", with a cell size of 65 ums, in comparision with tobacco (dried) that has a cell of 33.8 ums. Finally, the earthworm can grow up to 20 cm long, and its cells are only at the size of 5.2 ums.
In conclusion, the size of an individual cell is not directly related to the size of the complete organism. Also, different parts of the same organism can have different sized cells (as seen in the moss cells)
Microscope Name: The Cool G Date: 2002-09-25 15:08:34 Link to this Comment: 2895 |
Bead measurements Name: Mande and Date: 2002-10-01 15:13:59 Link to this Comment: 3064 |
Measurments:
2micrometer bead-143 micrometers in movement
4micrometer bead-80.4 micrometers in movement
6micrometer bead-5micrometers in movement
Variables: due to the fact that i have a lazy eye and Mande has horrendous vision, keeping track of the bead proved difficult and may have had have effected our outcome.
Onion cell
Hypothesis: Adding water will create movement within the cell wall therefore causeing the cell membrane to expand (turgid), the addition of salt however will cause the membrane to retract within the cell wall.
Observations:
3% salt solution-all cells are turgid with noticible nucleus.
Distilled H2O- Cells are clear under scope, with turgid cells, noticable nucleus.
25% salt solution- Cell membrane appears smaller than cell wall(plasmolized), not all of the cells retain this plasmolized state, some are still turgid.
Conclusion:
Water molecule movement seems to be inhibited in some way by the addition of salt, because the cell membrane retracted within the cell wall, when salt was applied therefore implying that the water created movement within the cell hence swollen and retracted states of the membrane.
Molecule Movements Name: Date: 2002-10-01 15:20:17 Link to this Comment: 3066 |
Movement in a thirty second period
2 microns: First Trial- 35 units (91 microns)
Second Trial- 22 units (57.2 microns)
4 microns: First Trial- 11 units (28.6 microns)
Second Trial- 14 units (36.4 microns)
8 microns: First Trial- no movement
Second Trial- 1 unit (2.6 microns)
This data supports the hypothesis that bigger molecules do not move as quickly as the smaller ones.
Onion Observations
3% solution- some plasmolyzed cells
Distilled Water- mostly turgid cells
25% solution- mostly plasmolyzed cells
Water fills up the cells because its molecules are lighter than salt's and move quicker. Distilled water has a lower viscosity than saltwater, so it can flow quicker into the cells.
plastic beads Name: Date: 2002-10-01 15:26:58 Link to this Comment: 3067 |
2um............4 segments
4um............2 segments
8um............1 segments
all measurements were taken at the 40x power
the data suggests that the hypothesis is correct. the larger the bead the less it moves
onion data
3% salt.......turgid
H2O...........turgid
25% salt.......plasmolyzed
the data suggests that the presence of salt changes the cells.
Both observations combine to suggest that the cells are turgent with water because the movement of the molecules pushes the membrane, but when the salt is added the membrane becomes denser/heavier and so the water is unable to move it outwards to the cell wall.
Sarah Frayne
Stephanie Lane
On the Consequenses of Having Blue Eyes Name: The blue-e Date: 2002-10-01 15:27:07 Link to this Comment: 3068 |
Trial #2: We looked at what we think was 4 Micron beaded water, but we couldn't see it moving. Then we thought that we saw the molecules, but they were stationary. Then Will and Prof. Grobstein informed us that we did not have enough water on our slide, and so we tried again.
Trial #3: This time we were sure to put 4 Micron beaded water on the slide, and after again much playing wih the microscope, we were able to find the water molecules, which were moving, but very slowly, especially when compared to the movement of the 2 Micron water. The 4 Micron water moved about 109 micrometers in three minutes.
Trial #4: With the 8 Micron beaded water, we looked through the 'scope and saw that the molecules were hauling ass (it's an industry term) on the slide. When we expressed our surprise about this, Will informed us that perhaps we should look in again, and when we did, the molecules had slowed down significantly - in fact, they were hardly moving at all. We concluded that we had begun our observation too early and had not given the molecules tme to settle down. In three minutes, the 8 Micron water moved 44 micrometers.
The Onion Phenomenon
#1: With the 3% salt solution, several of the cells were plasmolyzed, and some are even empty (AAHH!!!). This is because Will overestimated the isotonic solution, which is the level of salt solution that is in perfect harmony with the cells (bad Will.) This may also be because we chose as our subject the outermost layer of the onion, which Will says may be closer to death. Perhaps our obervations would have been different if we had chosen a layer of onion closer to the core.
#2: After adding the water, all of the cells appeared to be empty. However, we have learned that this clear and empty appearance is somewhat deceptive. All of the cells were turgid, and Will was wrong when he told us that the cells were really plasmolyzed. After reducing the light source and focusing in a little closer, we could see the green chloroplasm along the cell wall, and a nucleus in almost every cell.
#3: After adding the 25% salt solution, we found that a large percent of the cell membranes have been plasmolyzed. This would lead us to believe that the more salt which is present, the more plasmolyzed the cells become.
OConclusions: Because the cells were the most turgid when immersed in the pure water solution, the NaCl is therefore responsible for the collapse of the Cell Membranes. We hypothesize this occurs because the NaCl has an averse reaction to the water: when the onion sample is immersed in the pure water solution, the molecules move faster and therefore become turgid enough to fill the entire space of the cell wall. Because when NaCl is present, the cell membrane shrinks away from the cell wall, we think that the salt causes the molecules to move slower, thereby making it unable to become completely turgid.
Names Name: Laura Date: 2002-10-01 15:28:20 Link to this Comment: 3069 |
microbeads! Name: ginnie & m Date: 2002-10-01 15:30:06 Link to this Comment: 3070 |
Beads!! (and onions) Name: The Ks Date: 2002-10-01 15:30:29 Link to this Comment: 3071 |
Hypothesis: Our idea was that in water, big beads would move less than smaller beads following the principle that the water molecules are also moving.
We observed different sized beads in water and measured the largest radius covered by each over a period of four minutes.
8 micron beads: largest radius covered 18.2 micrometers
4 micron beads: largest radius covered 24.3 micrometers
2 micron beads: largest radius covered 33.8 micrometers
Our observations supported our hypothesis and so we will use these observations to aid explaination of the onion and water/salt solutions.
The onion cells with 3% salt solution showed primarily turgid cells with a few beginning to plasmolyze with the corners of their cell membranes pulling away from the cell wall.
The onion cells in water (distilled H20) were completely swollen, all cells are turgid.
The onion cells in the concentrated 25% salt solution are plasmolyzed. The cell membranes appear squished and shrunken within the cell walls.
So to explain this phenomena and what it has to do with the beads...
Both observations prove that water is in constant motion.
Our observations with the onion showed us the different ways that cells look with different concentrations of water and salt.
Our idea is that the concentration of salt in the water effects the degree to which water moves in and around the cell. Just like the size of the beads effected how much they moved.
So our next course of action would be to determine what the degree of water movement has to do with the appearance of the cell. Hopefully this would have something to do with density, but maybe not.
This exercise has challenged us in many ways and we realize that our final obersations are inconclusive, leading us to be wrong, yet again.
sarah tan, kathryn bailey Name: Date: 2002-10-01 15:30:55 Link to this Comment: 3072 |
data:
bead size............maximum radial distance
2 um.................156um
4um..................15.6um
8um..................7.8um
conclusion: the data supports the hypothesis, leading us to believe that the larger the bead, the shorter the distance it will move. however, since we only did one trial of each bead size, these data may not reflect an actual trend.
-------------------
Procedure:
Prepared onion slide with one-cell layer.
When we looked at the onion cells in a 3% salt solution, the cell membranes and cell walls were quite close to each other, and the cells were turgent. When we looked at the cells after changing to a 25% solution, the cell membranes had drastically pulled away from the cell walls, and the cell itself had shrunk.
Given our new observations that water molecules are always in motion, we hypothesize that the cells shrank in the 25% salt solution because the water molecules had a smaller radial distance than when the cells were in a pure water solution, in which case the radial distance increased. We would like to take this lab to be one of our times to be wrong every day.
Name: Date: 2002-10-01 15:33:45 Link to this Comment: 3073 |
In the slide of the onion with 3 percent saltwater, we observed some shriveling of the membranes. When the distilled water was added, there cell membrane swelled to where they were turgid. When the 25 percent solution was added, there was severe shriveling of the membaranes. From this we concluded that the amount of salt in the water determines the amount of contraction of the cell membrane.
From both activities, we can conclude that water particles are always moving. Water caused the onion cell membranes to move; when the water was replaced by the salt, there was a moving in of the membrane, not a swelling out.
Christine Traversi
Margot Rhyu
Name: Joanna Rob Date: 2002-10-01 15:41:47 Link to this Comment: 3075 |
Bead Size Distance Traveled
8 micrometer 10 micrometers
4 micrometers 104 micrometers
2 micrometers 13 micrometers
Onions
3% salt solution-> most cells are turgid, but some cells are plasmolyzed
0% salt solution-> more cells are turgid than plasmolyzed
25% salt solution-> most cells are asignificantly plasmolyzed.
Observations-
1. Water molecules are constantly in motion.
2. The quantiy of salt directly affects the distance traveled by water molecules.
3. Perhaps salt molecules are bigger.
Molecular Motion Name: Date: 2002-10-02 15:11:25 Link to this Comment: 3085 |
Hypothesis: The smaller the microsphere; the faster its motion.
Methods: We took a special slide which had depressions on either side to act as a reservoir for any liquid that we would place there. After putting a specific liquid in the reservoir we covered it up with a cover slip and put the slide on the stage of the microscope to determine our observations. In this case we are supposed to measure the speed of the liquid molecules which can be found by measuring the distance a certain molecule moves in a fixed period of time since speed is distance divided by time. We used 2 minutes as the time for observation.
Observations 1:
1) 2 micrometer bead moved 30 micrometers in 2 minutes.
2) 4 micrometer bead moved 21 micrometers in 2 minutes.
3) 8 micrometer bead moved 1 micrometer in 2 minutes.
Conclusion: Sadly, we were right. Thus the smaller the size of the microsphere the faster it seemed to move. We believe that our conclusion is correct because it follows that a smaller molecule when bombarded by other moving molecules will move faster because the energy generated by the impact will cause the molecule to move faster.
Observations 2:
An onion membrane was placed on the slide and 3% salt water was dropped on it. The onion cells turned turgid. Next, distilled water was put on the same membrane and it was observed that the cells turned more turgid. 25% salt water was next added to the membrane and plasmolysis of the onion cells were observed.
Relating observations 1 and 2 we can say that the molecules moved from inside the onion cell to the outside area because the outside area had a higher concentration. We observed that as the added solution became more concentrated the cells became more plasmolyzed. In the higher concentration of solvent the number of molecules increased in each group (as the molecules bombarded each other they clustered together in groups) and therefore the groups moved more slowly.
These experiments have successfully demonstrated both brownian motion and osmosis.
Water and Onions Name: Maggie and Date: 2002-10-02 15:14:14 Link to this Comment: 3086 |
Our findings support the thesis that says that water molecules are continuously moving, and the smaller the object was the more it moved.
Experiment 2:
3% salt solution made almost all of the cells turgid but a few of them were partially plasmolyzed.
0% salt solution made the cells even more turgid, and filled out the ones that were plasmolyzed earlier.
25% salt solution made the cells very plasmolyzed.
When there is salt in the environment outside of the cell, it takes water away from the inside of the cell, making the cell plasmolyzed. This relates to the hypothesis we supported in our last experiment (that water molecules are always moving whether we can see them or not) because the water was moving from the inside of the cell to outside of the cell, or vice versa.
Maggie Scott-Weathers and Emily Senerth
Beakman's World Name: Will and D Date: 2002-10-02 15:22:30 Link to this Comment: 3087 |
Onion Cell Observations:
In 3% solution the onion cells are pretty much turgid, and there is not much change from the cell appearance when the 3% solution is changed to distilled water, which has a 0% salt content. However, when the distilled water is replced by the 25% solution a majority of the cells become plasmolyzed.
Onion Cell Story:
When salt is introduced to the surrounding environment, the NaCl molecules are too big to pass through the cell wall. Therefore, to create equilibrium, water leaves the cell into it's surrounding environment. A cell is turgid when it has many water molecules in it because the water molecules move around and stretch the cell membrane to its capacity. This is the case in the distilled water solution. When salt is introduced to the cell's environment and water leaves the cell there are not as many water molecules to move around and thus the cell membrane "shrinks" and is not stretched to its capacity. The more concentrated the salt solution the more water exits the cell and thus the fewer water molecules inside the cell which makes the cell more plasmolyzed.
Lab 4 Name: Annie S., Date: 2002-10-02 15:28:27 Link to this Comment: 3088 |
Experiment #2 Plant cells under three different conditions:
Th onion with the 3% salt solution showed all turgid cells. After replacing the solution with distilled water, not notced no change in the cell walls and membrane. We then replaced this solution with a 25% salt solution. We noticed that this solution caused the cell membranes to shrink, or to pull away from the cell wall.
Conclusion: In a higher salt concentration solution, we observed that the cells are all plasmalyzed. This is because the salt ions absorb the water molecules, which causes the actual membrane to shrink. Water is necessary to sustain the shape and structure of the cell membrane (in a plant cell, the cell wall will not move).
learning through osmosis Name: Date: 2002-10-02 15:28:32 Link to this Comment: 3089 |
Microspheres
2m beads moved ~30 microns
4m beads moved ~13-15.6 microns
8m beads couldn't be seen moving
Onion Skin
distilled water saturated had mostly turgid cells
3% NaCl(q) saturated had some turgid cells and some plasmolyzed cells
25% NaCl(q) saturated had mostly plasmolyzed cells
The vacuoles of the cell filled with water when saturated with distilled water. This made the cell bigger and pushed its mebrane up against its cell wall (turgid). When we added 3% NaCl solution, water escaped the vacuoles and cell membrane as salt came into the cell, trying to equalized the salt level inside and outside the cell. This made the cells smaller and the membrane recede from the cell wall. When we added the 25% NaCl solution even more water was required outside the cell to equalize the salt levels in and out of the cell, making the individual cells more plasmolyzed.
Microbeads and onions are connected...
Water Movement & Onion Cells Name: Date: 2002-10-02 15:29:02 Link to this Comment: 3090 |
Chelsea R., Adrienne, & Laura B.
Part I: Motion of Microspheres in Water
Prediction: Smaller microspheres will move more than bigger microspheres in water.
Observations:
8um microsphere had no visible motion during a three-minute period.
4um microsphere moved 15.6um in 2 minutes.
2um microsphere moved 390um
Conclusion: Because our 2um microsphere measurement was so large compared to the other groups' observations, we think we were looking at the wrong things. However, according to our observations and the other groups' observations, it seems that our prediction (that smaller microspheres would move more than larger microspheres in water) still holds true at this time. This appears to show that water molecules do move. (Though of course nothing can be proven absolutely.)
Part II: Onion Cells in Salt and Water Solutions
Observations: Turgid or Plasmolyzed?
3% salt: the majority of the cells appear mostly turgid
0% salt: the majority of the cells appear turgid
25% salt: the majority of the cells appear plasmolyzed
Part III: Putting It All Together
Since water molecules move (as observed in Part I) and in order for a cell to be turgid it requires something to fill it, the water molecules probably move into the cell to fill it up, and since the water is moving so much it pushes the cell wall out, causing the cell to be turgid. When more NaCl is added to the water, there are fewer water molecules to fill the cell and make it turgid. So when the solution is 25% NaCl, the cells are plasmolyzed because there is less water to fill the cell and push against the cell wall.
call me sketchy. Name: Jody, Carr Date: 2002-10-02 15:37:35 Link to this Comment: 3093 |
the wonderful world of beads Name: Chelsea, M Date: 2002-10-02 15:38:55 Link to this Comment: 3094 |
Observations: The 2micrometer bead moved a total of 20.8 ums away from its point of origin. The 4 micrometer bead moved a total of only 1.4 ums away from its point of origin. The 8 micrometer bed moved only .75 ums in total.
In the second half of the lab, we watched the cells of an onion react with different levels of salt within water. When the cells were placed in the 3% salt solution, we noticed that the cells' membranes were mostly turgid, although is some of the coners of the cells, there was slight plasmolyzation. In the distilled water, the cells were completely turgid, and fianlly in the 25% solution, the cells became very plasmolyzed, with the membranes clumpy together, pulling all the internal organelles closer together within the cell wall. (The wall itslef does not move).
Therefore, given these observations and our previous observations, we have found the meaning of life and the orgin of clumpy diversity.
The membrane retracting from the wall is a consequence of its interaction with the salt, an interaction due to the fact that water continually moves and passes through the membrane.
Once upon a time there was not a whole lot of salt in the ocean, right? That is analogous to the distilled water, so the cell (ie the earth's diversity) was turgid (and the reason for that more species and variations can exsist in distilled H2O then in the salt solution). THEN, salt slowly began to be more prevalent in the ocean and along with this, there came a little tiny bit of plasmolyzity (ie, clumpiness, because some of the intermediary species, like perhpas Heterotrophs with cell walls, couldn't manage). Even more salt came, and so the end result, which is the plasma all being CLUMPED together in the middle of the cell, was that all of the intermediary species that didn't work became extinct, and what you have left is clumpiness.
Oxygen levels Name: Date: 2002-10-08 15:10:03 Link to this Comment: 3205 |
All measurements were taken at 15 second intervals.
First experiment: 0, .2, .4, .4, .6, 1, 1.2, 1.4, 1.6, 1.8, 2, 2, 2.2, 2.2, 2.4, 2.6, 2.6, 2.8, 2.8, 3, 3, 3.
After change in H2O2 level (Experiment #2): .4, .4, .5, .6, .7, .8, 1, 1.1, 1.3, 1.4, 1.5, 1.6, 1.7, 1.7, 1.8, 1.9, 2, 2, 2, 2.2, 2.2, 2.3, 2.4
We used less H2O2 in the second experiment which raised the rate of reaction, resulting in a lower production of oxygen within the same time period.
Reaction Rate (First experiment)= .4
Reaction rate (second experiment)= .7
experiment 5 Name: amanda mac Date: 2002-10-08 15:15:48 Link to this Comment: 3206 |
reaction rate = (1.2-.9)/3 = .1/1 minute
method: our portion of the experiment was to see if changing temperature would affect reaction time of the enzyme. We hypothesized that temperature woudl slow down the reaction time by making the oxygen release per minute lower than the test run that we first ran.
we found that the reaction time during trial one of the experiment was much higher (.8/1minute) than that of our reaction time for experiment number five.
mande adn debe
Catalase Lab Name: MaryBeth & Date: 2002-10-08 15:23:14 Link to this Comment: 3207 |
Name: kyla &laur Date: 2002-10-08 15:23:54 Link to this Comment: 3208 |
Experiment 1, Trial 1 (Volume of Oxygen in CCs, taken at 15 second intervals):
0,0,0,.2,.4,.5,.62,1,1.1,1.2,1.4,1.5,1.6,1.8,2,2.2,2.3,2.4,2.6,2.6,2.7,2.8,2.9,3,3.1,3.2,3.3,3.4,3.5,3.6,3.6,3.7,3.7,3.8,3.9,3.9,3.95,3.95,4,4.1,4.2,4.2,4.2,4.2
Reaction Rate:.533
Experiment 2, Trial 1:
.4,.4,.5,.6,.8,1,1.2,1.4,1.8,2,2.2,2.4,2.6,2.9,3,3.2,3.3,3.6,3.7,3.9,4,4.1,4.4,4.5,4.6,4.7,4.8,4.9,4.9,5,5.1,5.18,5.2,5.2,5.3,5.35,5.4,5.5,5.5,5.6,5.7,5.8,5.8,5.8,5.8
Reaction Rate:.83
Experiment 2, Trial 2:
0,.1,.2,.5,.7,1,1.2,1.4,1.6,1.8,2.2,2.2,2.4,2.6,2.7,2.9,3.2,3.2,3.4,3.7,3.9,4.1,4.2,4.3,4.4,4.6,4.6,4.8,4.8,4.9,5,5,5.1,5.2,5.2,5.2,5.3,5.4,5.4,5.4
Reaction Rate: .76
When we increased the amount of H2O2, the reaction became quicker and more noticeable to the naked eye.
We conclude that as the ratio between the two components decreases, the reaction becomes more rapid and stronger.
Chemical Reactions Name: the Ks Date: 2002-10-08 15:25:54 Link to this Comment: 3209 |
(All volume units are in cc.)
EXPERIMENT #1:Standard Catalase at Room Temp.
DATA: .1,.2,.3,.4,.6,1.0,1.2,1.5,1.5,1.8,2.0,2.3,2.4,2.5,2.7,2.8,
2.9,3.0,3.2,3.3,3.5,3.6,3.7,3.7,3.7
REACTION RATE: Volume at 2 minutes = 1.5cc
Volume at 4 minutes = 2.8cc
(2.8cc - 1.5cc)/2 = 0.65cc/min
EXPERIMENT #4:Change of pH of Buffer
(Due to time constraints we were only able to conduct one trial.)
DATA: 0.0,0.0,0.0,0.0,0.1,0.2,0.2,0.2,0.3,0.3,0.4,0.5,0.6,0.6,0.7,0.8,
0.8,0.9,1.0,1.1,1.2,1.2,1.3,1.4,1.4,1.5,1.6,1.7
REACTION RATE: Volume at 2 minutes = 0.2cc
Volume at 4 minutes = 0.8cc
(0.8cc - 0.2cc)/2 = 0.3cc/min
CONCLUSION: The pH effects the reaction rate. Lowering the pH
significantly slowed the rate of the reaction between the
enzyme and the hydrogen peroxide.
Obviously the enzyme reacts with the hydrogen peroxide to release the oxygen. The pH only effects the reaction time. It does not effect the amount of oxygen that is produced by the chemical reaction. As you can see from our second experiment in which we changed the pH of the buffer, the reaction would still produce the same amount of oxygen that the first experiment did but at a much slower pace.
Lab Name: Date: 2002-10-08 15:28:43 Link to this Comment: 3211 |
This is our data:
Experiment 1:
0, .2, .4, .6, .8, 1.0, 1.2, 1.4, 1.5, 1.6, 1.65, 1.8, 1.9, 2.0, 2.0, 2.05, 2.1, 2.15, 2.2, 2.2, 2.3, 2.35, 2.4, 2.4, 2.4, 2.4
Total time: 6 minutes 30 seconds
Rate: .2 ml/min
Experiment 2C:
Trial 1:
.2, .35, .6, .85, 1.2, 1.5, 1.8, 2.0, 2.3, 2.6, 2.8, 3.0, 3.2, 3.4, 3.6, 3.7, 3.8, 4.0, 4.1, 4.2, 4.25, 4.4, 4.5, 4.6, 4.6, 4.6, 4.65, 4.7, 4.8, 4.8, 4.8, 4.8
Total time: 8 minutes
Rate: .6 ml/min
Trail 2:
.1, .2, .4, .6, .8, 1.1, 1.4, 1.7, 2.0, 2.2, 2.4, 2.7, 3.0, 3.1, 3.3, 3.4, 3.6, 3.8, 4.0, 4.1, 4.3, 4.4, 4.5, 4.6, 4.65, 4.8, 4.8, 5.0, 5.0, 5.1, 5.2, 5.2, 5.4, 5.4, 5.4, 5.4
Total time: 9 minutes
Rate: .7 ml/min
Trial 3:
.1, .2, .4, .6, .8, 1.1, 1.4, 1.7, 2.0, 2.2, 2.4, 2.6, 2.7, 3.0, 3.1, 3.2, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4.0, 4.0, 4.2, 4.2, 4.3, 4.4, 4.4, 4.4, 4.5, 4.6, 4.6, 4.6, 4.7, 4.8, 4.8, 4.8, 4.8
Total time: 10 minutes
Rate: .52 ml/min
Christine Traversi
Heather Price
oxygen levels Name: Jen + Step Date: 2002-10-08 15:31:56 Link to this Comment: 3212 |
Trial B Results
.6
.8
.8
1.0
1.2
1.3
1.5
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.3
3.4
3.5
3.6
3.8
3.9
4.0
4.1
4.2
Trial B reaction rate: .075
(Trial A reaction rate: .015)
Methods: Every fifteen seconds recorded reaction measurement from the injection of the H2O2.
Observations: We found a variety of observations. In trial A, nothing really moved and when it did, it was slow. In Trial B, the results were similiar to the original.
Our enzyme did not change because our rate stayed the same as X went up.
Results Name: Kathryn Ba Date: 2002-10-08 15:33:20 Link to this Comment: 3213 |
0,0,0,0,0,.1,.2,.2,.4,.4,.4,1.1,1.3,1.5,1.5,1.8,2.0,2.2,2.2,2.3,2.4,2.6,2.8,2.8,2.8
Reaction Rate: 0.7 O2/minute
Trial 2
(Increased Temp)
0,.1,.4,.6,1.0,1.3,1.6,1.8,2.2,2.4,2.8,3.0,-,-,-,3.8,3.8,4.0,4.1,4.2,4.2,4.3,4.3,4.3
Reaction Rate: .8 O2/minute
Trial 3
(Increased Temp)
0,0,.2,.6,.8,1.0,1.4,1.6,1.8,2.2,2.4,2.8,3.2,3.2,3.2,3.2,3.5,3.8,4.0,4.0,4.1,4.1,4.2,4.2,4.3,4.3,4.3
Reaction Rate: .8 O2/minute
Our data shows that the reaction rate was slightly faster when the chemicals at higher temperatures. The amount of overall O2 volume was higher at the larger temp, however we only did one trial at room temperature, toconfirm this change we would need to do another trial at room temp. Our story is that the hightened temperature allowed for a faster reaction rate because the molecules were moving around faster. that's our story and we're sticking to it....for a while anyway.....
Name: Yarimee Gu Date: 2002-10-08 15:36:57 Link to this Comment: 3214 |
Rate of Oxygen produced:
Ex 1 (control):0.6 cc/min
Ex 2 (pH 2.0): 0.067 cc/min
Observations:
-Reaction rate significantly decreased.
-x(plateu value) significantly decreased.
Story- The pH level affects how the Catalase works.
Name: Michele an Date: 2002-10-09 14:15:27 Link to this Comment: 3226 |
Trial 1:
.2, .4, .8, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.3, 3.4, 3.4, 3.5, 3.6, 3.6, 3.7, 3.8, 3.8, 4.0, 4.0, 4.0
The rate of change is fairly constant for 4 minutes at an additional .2 cm for every 15 seconds. After 4 minutes it changes .2 cm for every 30 seconds until it stabilizes after 6 min 40 sec reaching 4.0 cm of oxygen in the tube.
Breakin' Down H2O2 Baby!!! Name: Date: 2002-10-09 14:47:25 Link to this Comment: 3227 |
Introduction:
This experiment demonstrates the effects of the enzyme Catalase on hydrogen peroxide.
Methods:
We were given a nicely set-up apparatus consisting of a ring stand and a Scholander respirometer. We had two vials one of which was a control vial and the other was the experimental vial. In the control vial we put in 0.5cc of H2O2 and 4.5cc of pH 7.4 buffer and in the experimental vial we first put in 1.5cc of Catalase and 3cc of the buffer. The two vials were attached to the respirometer and then 0.5cc of H2O2 was injected into the experimental vial and the small plug was pushed in and at the same time the oxygen syringe was slowly pulled up and different volumes of oxygen were measured for different time intervals. The methods are the same for both trial 1 and trial 2.
Observations:
Trial 1
Time/sec Volume O2
15 .2
30 1
45 1.6
60 2.2
75 2.7
90 3
105 3.1
120 3.2
135 3.2
150 3.4
165 3.4
180 3.6
195 3.8
210 3.8
225 3.9
240 3.9
255 3.9
270 3.9
. .
. .
. .
. .
Trial 2(performed twice)
Time/sec Volume O2
15 .2/.4
30 .9/.8
45 1.4/1.4
60 1.8/1.8
75 2.2/2.0
90 2.4/2.4
105 2.7/2.7
120 2.8/2.8
135 3.0/3.0
150 3.2/3.2
165 3.2/3.3
180 3.4/3.4
195 3.6/3.5
210 3.8/3.6
225 3.9/3.8
240 3.9/3.9
255 3.9/3.9
270 3.9/3.9
. .
. .
. .
. .
Conclusion/ThE StoRY:
Rate of Concentration= 1.6/2= 0.8cc of O2/min
Our experiment remained the same, thus observations remained similar and hence we conclude with our rate of concentration and alas, no remarks on enzyme behavior!!!
Lab 5 Name: Brie Farle Date: 2002-10-09 14:50:31 Link to this Comment: 3228 |
Our results from experiment two were:
DATA: .1, .5, 1, 1.5, 1.9, 2, 2.2, 2.4, 2.4, 2.6, 2.6, 2.6
Our data was collected over a period of three minutes. This experiment was the first trial of adding .40 H2O2 to the experimental mixture, which contained 1.50 ml of Catalase and 3.10 ml of 7.4 Buffer for a total volume of 5.00 ml.
Our results from the second trial of the same experiment were:
DATA: .1, .5, 1, 1.4, 1.8, 2.1, 2.2, 2.4, 2.6, 2.6, 2.8, 2.8
In the first experiment the rate we computed over two minutes was 1 O2/minute. In the second experiment the rate we computed over two minutes was .9 O2/min. When we add less H2O2, we ended up with less O2 per minute, but our rate was the same in both experiments. This means that the rate is independent of the amount of H2O2 that is added. Our conclusion is that the rate is determined by the enzyme that is added. Since the amount of enzyme was the same in both experiments, the rate should stay the same. Since it did, our conclusion has been proven.
Name: Maggie Sco Date: 2002-10-09 14:59:56 Link to this Comment: 3229 |
1.8, 2.1, 2.4, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.25, 3.3, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55, 3.6, 3.6, 3.6
Experiment 4B:
(Experiment 4 was using a buffer of 4.01 pH instead of the previously used pH level of 7.4)
Trial 1: .2 cc after 15 seconds
Trial 2: .2 cc after 15 seconds.
In both of our trials for experiment 4, the brody shot up quickly, equalling .2 cc, but then stopped moving completely.
This made us come to the conclusion that the higher the buffer's pH is, the longer the reaction will run, and the lower the buffer's pH is, the shorter the time of the reaction. This may mean that the lower the buffer's pH, the less effective the catalase (the enzyme) is at breaking apart the peroxide.
Our rate = .2/15= .01333 cc/sec. However, this rate could be deceiving because while we took the first measurement at fifteen seconds, the oxygen had stopped moving before that.
October 9th Lab Name: Annie S., Date: 2002-10-09 15:05:32 Link to this Comment: 3230 |
Name: Heidi & Mi Date: 2002-10-09 15:07:01 Link to this Comment: 3231 |
Trial A: (at room temperature)
.2, .4, .8, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.3, 3.4, 3.4, 3.5, 3.6, 3.6, 3.7, 3.8, 3.8, 4.0, 4.0, 4.0
The rate of change was fairly constant for 4 minutes at an additional .2 cm for every 15 seconds. After 4 minutes it changed .2 cm for every 30 seconds until it stabilized after 6 min 40 sec reaching 4.0 cm of oxygen in the tube.
Our rate between 1 and 3 minutes was 0.80 O2 per minute.
Trial B: (at heated temperature)
test #1
.3, .8, 1.3, 2.0, 2.4, 2.7, 3.0, 3.2, 3.4, 3.6, 3.7, 3.8, 4.0, 4.1, 4.2, 4.2, 4.3, 4.4, 4.4, 4.5, 4.6, 4.6, 4.6, 4.7, 4.8, 4.8, 4.8, 4.9.
Our rate between 1 and 3 minutes was 0.90 O2 per minute.
test#2
.2, .8, 1.4, 2.0, 2.5, 2.8, 3.2, 3.4, 3.6, 3.8, 4.0, 4.1, 4.2, 4.4, 4.4 4.6, 4.6, 4.7, 4.8, 4.8, 4.9, 5.0, 5.0, 5.0
Our rate between 1 and 3 minutes was 1.05 O2 per minute.
** Our average rate of O2 per minute for Trial B was 0.98***
Discussion:
With higher temperature the rate of the O2 per minute was greater than the rate of the room temperature by a difference in rate of 0.18 O2 per minute.
We love Hiooouuueeee Name: MC the ama Date: 2002-10-09 15:07:58 Link to this Comment: 3232 |
The control trial involved 1.5cc of the Catalase, 0.50cc of the Hydrogen Peroxide, and 3.00cc of the buffer. The readings were taken every 15 seconds.
Our control set of data was as follows:
.4, .8, 1.2, 1.6, 2, 2.2, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, ~3.2, 3.2, 3.2,
3.3, 3.3, 3.4, 3.4, 3.4
Our next trials involved 0.6cc of Hydrogen Peroxide, 2.9cc of the buffer, and the enzyme remained constant at 1.5cc. The rate from our first trial (for minutes 1-3) was 0.7cc/minute of oxygen; the rate from the data set below with the increased amount of Hydrogen Peroxide is 1cc/ minute. Our data for the second set was as follows:
.3, 1.0, 1.8, 2.4, 2.8, 3.2, 3.5, 3.7, 3.9, 4.1, 4.2, 4.4, 4.4, 4.5, 4.6,
4.7, 4.8, 4.8, 4.9, 5.0, 5.0, 5.1, 5.2, 5.2, 5.2
Based on our scientific observations, we have concluded that increasing the amount of HP added to the enzyme increases the rate at which oxygen converts to a gas. NOTE: Although the time is different on each of these trials, we feel that it is not really legitimate to say that the amount of HP affects time as well because our first trial was shorter than the control.
Hydrogen Peroxide and Catalase Lab Name: Chelsea an Date: 2002-10-09 15:09:28 Link to this Comment: 3233 |
Summary of Data from Trial 2 (with same substances, but chilled):
Volume of Oxygen: .2, .2, .6, .8, 1, 1.2, 1.6, 1.8, 2, 2, 2.2, 2.4, 2.4, 2.6, 2.6, 2.8, 2.8, 3.0, 3.0, 3.0, 3.2, 3.2, 3.2, 3.3, 3.3, 3.4, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.7, 3.7, 3.8, 3.8, 3.8, 3.8, 3.8,3.8, 3.8
Rate of Reaction: .3 mL of Oxygen/minute
Summary of Data from Trial 3 (with same substances, but chilled):
Volume of Oxygen:.2, .4,.8, 1. 1.4, 1.7, 2, 2.2, 2.4, 2.6, 2.8, 3.0, 3.0, 3.2, 3.4, 3.6, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.0, 4.0, 4.1, 4.1, 4.1, 4.1, 4.2, 4.2, 4.2, 4.2
Rate of Reaction: .3 mL of Oxygen/minute
Cooler temperatures mean slower molecules. Thus, when all the solutions were chilled, their slower molecular movement accounts for the drop in reaction rate. Rock on.
Name: Adrienne & Date: 2002-10-09 15:10:01 Link to this Comment: 3234 |
Adrienne & Laura B.
First Data Set:
Vol. O2 in 15 sec. increments:
.7, 1.9, 2.3, 2.6, 2.8, 2.9, 2.9, 2.9, 2.9, 2.9, 2.9
Second Data Set:
Vol. O2 in 15 sec. increments with pH 2.0:
Trial #1: .2, .2, .3, .4, .4, .5, .7, .9, .9, .9, .9, 1.0, 1.0, 1.0, 1.1, 1.1, 1.1, 1.1, 1.1
Trial #2: .7, .7, .8, .9, .9, .9, .9, .9, 1.0, 1.0, 1.0, 1.0, 1.1, 1.1, 1.1, 1.1, 1.1, 1.2, 1.2
Trial #1 Reaction Rate = .05 O2 per minute
Trial #2 Reaction Rate = .1 O2 per minute
The Story:
According to our observations, a change in the pH of the buffer slows the reaction down. The first experiment that we did as a class with a pH 7.4 buffer had an average reaction rate of about .7 O2 per minute, while our experiment with a pH 2.0 buffer had a reaction rate of about .075 O2 per minute.
Hydrogen Peroxide Name: Lawral and Date: 2002-10-09 15:12:11 Link to this Comment: 3235 |
Experiment #1:
All measurements were taken at 15 second intervals.
.8, 1, 1.2, 1.6, 2, 2.4, 2.5, 2.7, 2.8, 2.9, 3, 3, 3.1, 3.2, 3.2, 3.2
The solution reacted for 4 full minutes (240 seconds).
Experiment #4c:
3.00cc of pH 10.4 buffer was added to the original experiment.
All measurments were taken at 15 second intervals.
.6/.6, .8/.8, 1/1.2, 1.3/1.4, 1.6/1.7, 2/2, 2.2/2.3, 2.4/2.6, 2.7/2.8, 2.9/3, 3.1/3.2, 3.2/3.4, 3.4/3.5, 3.5/3.6, 3.6/3.8, 3.7/3.9, 3.8/4, 3.8/4.1, 3.9/4.2, 4/4.3, 4/4.4, 4.1/4.4, 4.2/4.4, 4.2, 4.2
The solution reacted for 375sec/345sec.
When a higher pH was added to the experiment, the solution reacted for a longer time. The rate of reaction was also higher. In the original solution, the rate of reaction was .4 O2/min. The average rate for the experiment with the added pH was .692 O2/min. The higher pH level is condusive to the reaction; it helps remove more oxygen for a longer amount of time.
Not just for hair Name: Date: 2002-10-09 15:16:13 Link to this Comment: 3236 |
Volume Gas reading every 15 seconds (ml)
Experiment 1: 0.2, 0.4, 0.8, 1.4, 1.6, 2.0, 2.2, 2.5, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.2, 3.3, 3.4, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.6
rate volume O2/min (0-2mins): 1.3
rate volume O2/min (1-3mins): 0.8
rate volume O2/min (1-4mins): 0.633
Experiment 3 increase in amount of calalase
3a: 0.6,1.4,2.0,2.4,2.8,3.1,3.2,3.4,3.5,3.6,3.7,3.8,3.8,3.8,3.9,4.0,4.0,4.1,4.2,4.2,4.2,4.2
rate volume O2/min (0-2mins): 1.7
3b:
0.4, 0.8, 1.4, 2.0, 2.4, 2.7, 2.8, 3.0, 3.0, 3.1, 3.2, 3.2, 3.4, 3.4, 3.5, 3.6, 3.6, 3.6, 3.6
rate volume O2/min (0-2mins): 1.5
rate volume O2/min (1-3mins): 0.7
3c:
0.8, 1.6, 2.2, 2.6, 3.0, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.1, 4.1, 4.1, 4.2, 4.2, 4.2
rate volume O2/min (0-2mins): 1.7
An increase in the amount of calalase yielded an increase in the rate of production of O2 gas. It did not yield more O2 gas.
enzyme numbers Name: Diana and Date: 2002-10-09 15:25:03 Link to this Comment: 3237 |
Trial 2 (less enzyme):
.2, .3, .4, .6, .8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.5, 2.6, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.5, 3.6, 3.7, 3.7, 3.8, 3.9, 3.9, 4.0, 4.0, 4.0
total time: 8 minutes 15 seconds
Rate from minute 2 to minute 5: .6 O2/minute
Trial 3 (less enzyme):
.1, .2, .3, .4, .6, .75, .9, 1.1, 1.3, 1.5, 1.8, 1.9, 2.1, 2.2, 2.4, 2.6, 2.8, 2.9, 3.0, 3.1, 3.2, 3.4, 3.5, 3.6, 3.7, 3.8, 3.8, 3.9, 4.0, 4.1, 4.2, 4.2, 4.3, 4.3, 4.3
total time: 8 minutes 45 seconds
Rate from minute 2 to minute 5: .66 O2/minute
Trial 4 (less enzyme):
.0, .1, .2, .4, .5, .6, .8, 1.0, 1.1, 1.3, 1.4, 1.6, 1.8, 1.9, 2.0, 2.2, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.05, 3.1, 3.3, 3.4, 3.45, 3.6, 3.6, 3., 3.8, 3.9, 4.0, 4.0, 4.0
total time: 9 minutes
Rate from minute 2 to minute 6: .56 O2/minute
Name: Maggie Date: 2002-10-22 14:50:39 Link to this Comment: 3315 |
Experiment 1
Initials Base Line Rate Exercise Rate
KC 54 78
SL 72 110
KA 70 128
MH 74 118
KE 68 122
Experiment 2
Hypothesis:
We hypothesized that if a person would hold their breath, their resting heart rate would be lower than when breathing normally.
Data:
We used MH as our lab rat, particularly because she had a really strong beat. We recorded her resting heart rate while breathing normally 3 times before we recorded the heart rate while she held her breath. We then did another trial where MH breathed normally just to make sure her heart rate hadn't dropped while breathing normally.
trial 1 (breathing normally)
94
86
84
trial 2 (holding breath)
64
68
64
trial 3 (breating normally)
92
93
90
Conclusions:
Because MH's heart rate dropped while she held her breath, the obvious conclusion is that breathing makes the heart beat faster. Therefore, the process of respiration requires oxygen and a faster heart beat.
HR lab Name: Amanda, Di Date: 2002-10-22 14:58:03 Link to this Comment: 3316 |
Heart Rates Name: Date: 2002-10-22 14:58:57 Link to this Comment: 3317 |
We ran a couple of trials to test the effects of different influences on heart rates. First, we experimented with the effect of laughter on heart rate. We found that the heart rate didn't vary overall, but it spiked when the subject laughed. This may be due to the motion caused by laughing. Next, we experimented with the effect of raising an arm over the head on heart rate. The heart rate quickened slightly, along with an increase in pressure. However, the heart rate was not significantly affected by either of these changes.
Sarah Tan is a rock Name: Date: 2002-10-22 14:59:01 Link to this Comment: 3318 |
After exercise
Sarah 136 beats per min.
Heather 152 beats per min.
Margot 146 beats per min.
Sarah after being "scared"- There was no effect on her heart rate after Grobstein screamed. Her heart rate stayed the same.
Heather held her breath for thirty seconds. Her heart rate increased to 96 beats per min. but the pressure decreased.
Margot thought sad thoughts for thirty seconds. We showed her a sad picture, thus making her heart rate slow down to 80 beats per min.
Our story about heart rates is that they increase or decrease depending upon both physical and emotional stimuli.
Heart Rate Name: Kathryn, S Date: 2002-10-22 15:00:46 Link to this Comment: 3319 |
Any sort of heightened stimulation requires a higher heart (more oxygen) because internal functions are in a more active state- for example, there is more going on in your brain, you blush, you sweat, stomach gets tight, you laugh....etc. By the same logic, a relaxed state , or a conserted effort to lower the heart rate, should have been sucessful in slowing the functions. However, the conditions of the experiment were less than ideal, random, noise, movements and other exterior stimulants and distractions most likely played a role in theresults nd the abiity to concertrae on specific emotional or mental states.
Heart rate Name: Yarimee Date: 2002-10-22 15:20:20 Link to this Comment: 3320 |
Base Rate:
Virginia-> 94
Yarimee -> 82
Jen -> 70
Joanna -> 80
After 2 min of rigorous exercise
V-> 102
Y-> 150
Je->96
Jo->96
Hypothesis:
-Increases with exercise because of the need for more oxygen.
-Increases due to need to rid body of carbon dioxide.
Holding Breath
Virginia -> 144
Jen -> 64
Emotions
Joanna-> when told to imagine a happy scenario heart beat increased
Virginia-> when told to imagine a frightening senario heart rate increased a very small amount.
Food for thought:
-Maybe caffein and nicotine affect heart rate?
-relaive body health affects heart rate? (prior Knowledge)
Heart rate measurements Name: Date: 2002-10-23 14:44:46 Link to this Comment: 3325 |
Hypothesis: A person's heart rate varies from its base rate due to activity (eg. exercise), emotion (eg. fear) etc.
Observations: A converter and a computer program called SuperScopeII was used to measure the heart rates at different stages for 30 seconds of three human subjects and then the different measurements were recorded.
AVG. RESTING HEART RATES:
Roma: 92 beats/min
Melissa: 83 beats/min
Adrienne: 91 beats/min
HEART RATES AFTER VIGOROUS EXERCISE:
Roma: 154 beats/min
Melissa: 156 beats/min
Adrienne: 252 beats/min
HEART RATES AFTER A PARTICULAR EMOTIONAL EXPERIENCE:
Roma (after Melissa pinched her hand HARD!!): 111 beats/min
Melissa (after thinking happy thoughts of going home): 96 beats/min
Adrienne (after trying very hard to think sad thoughts): 111 beats/min
Adrienne (after practising yoga breathing): 87 beats/min
Melissa (after holding her breath): 105 beats/min
Roma (after letting her head hang upside down): 87 beats/min
Conclusion: A person's heart rate does indeed vary from its resting stage with changes in physical activity or emotional state of mind. As physical activity is increased more oxygen is required, hence the heart rate increases to allow for that. As for emotional state, depending on a particular emotion a person's heart rate may increase or decrease from normal. Yoga breathing and letting one's head hang upside down causing the blood to rush to it decreases heart rate while holding one's breath increases it. For further research one can look into changes in heart rate after consumption on different levels of nicotine, caffeine, alcohol etc. That should provide an interesting perspective on the effects of different chemicals in the blood system on a person's heart rate.
Heart Rate Lab Name: Bobbi, Ros Date: 2002-10-23 15:10:29 Link to this Comment: 3327 |
Heart Rate Name: Date: 2002-10-23 15:11:18 Link to this Comment: 3328 |
The Scientists: Emily S., Maggie S.-W., Chelsea R., and Laura B.
Observations:
Resting Heart Rate | After 2 mins. Vigorous Exercise | While Holding Breath (Trial 1) | While Holding Breath (Trial 2) | |
Laura | 82 | 156 | 88 | 90 |
Emily | 78 | 126 | 96 | 84 |
Chelsea | 98 | 106 | 104 | 90 |
Maggie | 86 | 140 | 74 | 72 |
Hypothesis: We all agreed that we thought our heart rates would increase after exercising. When coming up with a hypothesis for what would happen to our heart rate when we held our breath, however, some of us thought that heart rate would increase and some of us thought that heart rate would decrease.
Putting it all together: According to the observations made by the class, our hypothesis that heart rate would increase after exercise appears to be true. However, we could not really conclude anything based on our observations of heart rate while holding one's breath. We measured our heart rate while holding our breath for 30 seconds, and some of our heart rates increased and the others decreased, so we cannot really conclude anything. Those of us who thought that heart rate would decrease while holding our breath, thought that because we thought that heart rate was dependent on oxygen intake and when you stop taking in oxygen (i.e.: hold your breath) your heart rate should decrease. Those of us who thought that heart rate would increase thought that because we thought that the heart would pump faster because the heart would try to get all the remaining oxygen in the lungs distributed to the body in an attempt to start the breathing process again.
Heart Rate Lab Name: Date: 2002-10-23 15:19:23 Link to this Comment: 3329 |
Our base heart rates are as followes:
MS- 98 (just came from badminton)
HAM- 72
WSSC- 72
DGL- 84 (fasting for last two days)
CLP- 78 (drank coke)
Exercise:
MS- 146
HAM- 102
WSSC- 128
DGL- 178
CLP- 152
Hypothesis: Caffine will increase heart rate, as it is a stimulant.
Caffine:
MS- control 101
HAM- 76 (weaker beats)
WSSC- 82 (stronger beats)
DGL- 96
CLP- 92 (stronger beats)
Massage:
MS- 88
Thinking happy thoughts:
CLP: 88 (after coffee)
Laughing:
CLP: 128 (after coffee)
In conclusion, we feel that caffine increases heart rates, massage decreases, and so does thinking happy thoughts. Laughing we feel was affected by the movement of the hands as well.
THE END. yummy cooooooffeeeeeeeeeeeee:)
Hot damn. Pump it up, yo. Name: see below, Date: 2002-10-23 15:20:39 Link to this Comment: 3330 |
Name | Resting | Vigorous Exercise | Cigarette | Coffee | Cigarette + Coffee | Cigarette + Stairs |
Lauren | 86 | 150 | 92 | -- | -- | -- | Jodie | 72 | 160 | -- | 84 | -- | -- | Carrie | 84 | 130 | -- | -- | 86 | -- | Lawral | 90 | 126 | -- | -- | -- | 108 |
Caffeine, Massage, Nicotine Name: Date: 2002-10-23 15:23:46 Link to this Comment: 3331 |
Resting Rates
Erin: 80bpm
Michelle: 80bpm
Diana: 82bpm
Brie: 82bpm
Post-Exercise (2 min. vigorous stair-running)
Erin: 128bpm
Michelle: 146bpm
Diana: 132bpm
Brie: 124bpm
Relaxation Techniques
Sleeping
Michelle: 66bpm
Diana: 88bpm (recently exercised, medication)
Massage
Erin:
pre-massage: 102bpm (recently exercised)
Brie:
pre-massage: 94bpm (recently exercised)
Erin:
post-massage: 92bpm
Brie:
post-massage: no change (new noise in room)
Exciting Techniques
Cigarette
Michelle:
pre-cigarette: 80bpm
post-cigarette: 78bpm
Coffee
Erin:
pre-coffee: 86bpm
post-coffee: 88bpm (immediately after consumption)
CONCLUSIONS!
Context in environment has strongly affected our results. (noise in room, etc.) For the most part, relaxation techniques of sleep and massage lowered bpm, exercise raised bpm, and coffee and nicotine had trivial results.
reaction lab Name: Diana and Date: 2002-10-29 15:07:09 Link to this Comment: 3414 |
Right side Left side
Diana : Feet- .291 .141
Shin - .125 .114
hands - .055 .016
chest - .231 .041
head - .022 .062
Mande : feet - .244 .231
shin - .248 .247
hands - .281 .278
chest - .197 .091
head - .092 .073
Our hypothesis held true for mande ,the closer we moved to the brain, the faster the reaction time. For Diana, either she doesn't have a brain or ah aha, or our hypothesis does not hold true. Notably, the reaction times for Diana's head and hands were similar indicating that perhaps the amount of nerve endings have an effect on the time of a reaction from a tactile stimulus.
Tactile test Name: Brenda and Date: 2002-10-29 15:11:14 Link to this Comment: 3415 |
We ran the tactile test multiple times, focusing on the differences a change in the location of the touch would make in reaction time. All tests run on bare skin.
Muscle reaction time: .076
First Location (10 trials): HAND- Average reaction time: .0318
Second Location (5 trials): LOWER ARM- Average reaction time: .0616
Third Location (5 trials): FOREHEAD- Average reaction time: .0078
Fourth Location (5 trials): LOWER LEG- Average reaction time: .0128
We concluded that the reaction time was not much affected by the changing of locations, with the exception of the forehead.
reaction time Name: Date: 2002-10-29 15:14:49 Link to this Comment: 3416 |
Visual
CT - 0.212
HP - 0.250
LS - 0.239
Tactile
CT - 0.226
HP - 0.207
LS - 0.273
Muscle Contraction Time
CT - 0.078
HP - 0.074
LS - 0.086
Based on our results, we believe that our anticipation and the expectation of the sound/visual/tap may have accounted for some of our faster reaction times. We hypothesize that if the subject was preoccupied and could not hear the click of the mouse, then the reaction time would be slower and more accurate to what it would be without any anticipation.
We took our test subject (Heather) and put headphones on her while she tried to memorize a poem in Russian. The stimuli (taps and beeps) were given at random to help create a more realistic reaction. Our results are as follows:
Audio: 0.331, as opposed to the previous experiment's result of 0.179
Tactile: 0.286, as opposed to the previous experiment's result of 0.207
We believe that our results would be more accurate given a more realistic setting. The more the subject is consumed with their present activities the slower their reaction time becomes.
Christine Traversi
Heather Price
Laura Silvius
Response Times Name: The Ks Date: 2002-10-29 15:22:20 Link to this Comment: 3418 |
Experiment One-
Reaction Time to Beeps, Pokes, and Flashing things...
(All numbers in milliseconds)
Kate
Aud median-
186
Vis median-
183
Tac median-
126
Median Muscle contraction time-
49
Katie
Aud median-
202.5
Vis median-
213
Tac median-
158.5
Median Muscle contraction time-
63
Kyla
Aud median-
202.5
Vis median-
238.5
Tac median-
260.5
Median Muscle contraction time-
70
Experiment 2
Location of Poke!!! Our next inquiry is what difference in response time does it make if you are poked on different places of your body?
Our points of inquiry will be
finger tips
back of the hand
palm of the hand
face (forehead)
Experiment 3
Then we will test out random placements on the body and see what kind of variation in response time occurs.
Each place was tested with ten trials, all on Kate.
#2
Collected Data:
Finger Tips
302, 123, 108, 7.81x10^-3, 178, 55, 78, 109, 155, 244
Median-116
Back of Hand
119, 119, 97, 184, 59, 130, 161, 270, 192, 122
Median-126
Palm of Hand
127, 139, 122, 127, 172, 142, 114, 152, 130, 170
Median-134.5
Face (Forehead)
25, 178, 166, 142, 144, 164, 284, 134, 127, 112
Median-143
#3
Collected Data:
Random Placements
back of hand-195
right bicep- 180
right quadracep- 194
right elbow- 227
right calf- 203
right side of head- 164
right forearm- 205
forehead- 120
left calf- 212
left bicep- 166
Conclusions:
#2- The fastest reaction time was for the finger tips. The slowest reaction time was for the face (forehead). We assume from this experiment that reaction time varies for different physical locations, and that areas with faster reaction times have more nerve endings.
#3- The subject did not know where she would be poked and therefore could not anticipate the sensation. This affected her reaction time -- in general the reaction times are longer than the medians for experiment #2 (the anticipated areas). We realize that we did not perform an adequate amount of tests (due to time constraints) but we believe that the data gives us reason to conclude temporarily as such.
Name: katheryn b Date: 2002-10-29 15:22:28 Link to this Comment: 3419 |
........auditory...........visual..........tactile........muscle contracion
kb......0.91...............0.110...........0.292..........0.059
sf......0.225..............0.300...........0.1835.........0.0405
These are the medians of ten trials. The data shows that there is visaul difference. The visual seems to be slightlyslower than the auditory, however the tactile is not consistantly faster or slower than either of the other two tests. This is not suprising becuase there are only two subjects.... the trends were much more easily seen after looking at the class's data.
different places on the body
.......head..........finger tips........shins
kb.....0.334.........0.300..............0.315
sf.....0.1735........0.159..............0.1615
the response times for the finger tips were faster for each of us. this may be because we use this our fingers for touch more regularly and are therefor conditioned to respomd quickly to touch there, or we may have more sensory equipment for touch on our finger tips either on the the fingertips or in the wiring of the sensors to the brain. again it may be helpful to see trends in a larger tested group. our original hypothesis that distance from the brain would have a direct relationship to the response times of the sensory stimulas.
Reaction Time in Body Name: Yarimee, J Date: 2002-10-29 15:35:44 Link to this Comment: 3420 |
Body reaction time to different "triggers"
SARAH:
Auditory-.159
Visual-.137
Tactile-.175
Muscle contraction-.044
Yarimee:
Auditory-.260
Visual-.206
Tactile- .109
Muscle contraction- .049
Jen:
Auditory-.100
Visual- .131
tactile- .166
Muscle contraction- .044
from these results, it is obvious that there is something else that plays into reaction time because muscle contraction only accounts for a very small number in this.
We attempted to account for some of the other reasons for the reaction time. Jen experimented with being poked in different areas of the body, with her eyes closed so that she could not expect where we would poke her next. She was testing whether not knowing where she would be poked would affect reaction time because in the original tests, all pokes were limited to the forearm. Yarimee tested reactions time with her glasses off, and Sarah tested with her glasses off and sat about 7 feet away. Both the visual tests were to determine whether reaction time would be affected by how clearly we could see the pop-up box. We hypothesized that reactions times for all the tests we chose would increase.
Mean results:
Jen- .316
Yarimee- .216
Sarah- .200
Conclusion: As it turned out, our hypotheses were right, and reaction times increased with the varying tests. The difference between Yarimee and Sarah's original and new reaction times especially proved that not being able to clearly see the visual stimulus affected reaction time because Sarah's reaction time greatly increased when she could barely see the screen, and Yarimee's reaction time slightly increased, and she was much closer to the screen.
visual stimuli and such Name: Date: 2002-10-30 15:00:15 Link to this Comment: 3426 |
Introduction: An experiment was carried out to see if the right and left hands respond differently to visual stimuli. Our hypothesis is that the right-hand responses will be faster than the left-hand ones.
Methods: We used an analogue digital input-output system and a computer program called SuperScope to measure the reaction times of the left and right hands to visual stimuli.
Observations:
Avg. right-hand response to visual stimuli :
RH-.1940ms
MB-.2356ms
AW-.3410ms
CR-.1870ms
Avg. left-hand response to visual stimuli :
RH-.2099ms
MB-.2777ms
AW-.3228ms
CR-.2712ms
Conclusions: Since we are all right -handed, we are more comfortable using our right- hands than our left -hands. Therefore we can't determine whether variation between the right-hand responses and the left -hand responses resulted from being conditioned for right-hand usage or by some other factor such as inheritance. This experiment could have been modified to test visual stimuli responses for the right and left eyes too.
Tests Name: Brie, Erin Date: 2002-10-30 15:18:23 Link to this Comment: 3428 |
Name: CLP Date: 2002-10-30 15:20:13 Link to this Comment: 3429 |
The first experiments (aud, vis, tactile, muscule contraction)
were done with everyone and are as follows:
Heidi- .0986 .168 .1626 .0674
Chelsea- .111 .204 .1728 .0396
Mer- .1312 .1562 .544 .0396
Diana .148 .1852 .191 .0804
Michelle- .1686 .3046 .215 .0784
Heidi and Chelsea did three separate experiments. First, they performed a conrol, second they recorded their response times while having a conversation, and lastly, Mer joined them for a stimulating intellectual conversation.
CONTROL
Chelsea- .1982
Heidi- .0962
Conversation (Heidi and Chelsea)
Chelsea- .2557
Heidi- .2396
Conversation #2 (Heidi, Mer, Chelsea)
Chelsea- .2232
Heidi- .1651
Any active distraction increases reaction time, and when two distract a third, concentration is still affected, but slightly less than talking to only one other person. We believe this is because it takes less concentration to follow a conversation involving three people than two (you actually have to listen when you are the only one expected to respond to the other person's comments).
Name: Date: 2002-10-30 15:21:53 Link to this Comment: 3431 |
Maggie S-W, Emily Senerth, Laura Bang
Our initial results were:
Auditory | Visual | Tactile | Muscle Contraction | |
Maggie | 0.1372 | 0.1831 | 0.1512 | 0.035 |
Emily | 0.1669 | 0.2264 | 0.1437 | 0.059 |
Laura | 0.2279 | 0.2744 | 0.3692 | 0.069 |
For the second experiment we each did different things to play around with the visual test. Emily and Maggie did the test with their right hand, and alternated which eye they covered. Laura did the test without her glasses on. Emily has contact lenses, and Maggie should have glasses but doesn't. And Laura's glasses aren't very strong, so she can still see fairly well without them, it's just a bit fuzzy.
Both of Maggie's second trials were faster, but only by about 0.005 seconds. Since this is such an insignificant difference, covering one eye probably didn't really effect the outcome. Both of Emily's second trials were faster than her original times as well -- her right eye/right hand was 0.02 seconds faster, and her left eye/right hand was 0.007 seconds faster. Laura's results from her second trial averaged about 0.03 seconds slower.
Laura's slower results without her glasses is what we expected, since it seems reasonable that the sharper your vision is the faster you would be able to react. However, her results are the only ones that really support this hypothesis. Maggie's vision is slightly worse when she closes one eye, so we expected her results to be slower, but her reaction time was about the same. Emily should have 20/20 vision in each eye since she has contacts, so seeing out of one eye shouldn't have effected her reaction time. We believe the decrease in her reaction time is due more to familiarity with the test than improved vision.
Name: Rosie, Ana Date: 2002-10-30 15:26:04 Link to this Comment: 3432 |
Rosie: Audio - .2211
Visual - .2293
Tactile - .1919
Muscle contraction - .07
Annie: Audio - .142
Visual - .2416
Tactile - .1637
Muscle contraction - .044
For the second experiment we first tested Audio when one person was having a conversation with the person who was being tested.
The average reaction time for this was .2186.
We then tested the reaction time for Touch when the person's eyes were closed and they were hit randomly anywhere on their body. The average reaction time for this was .1638.
Finally we tested the reaction time Visually. The person watched the screen with only one eye open. The reaction time for only the right eye was .3008 and the reaction time for the left eye was .2374. The person was using their right hand to click.
From this experiment we concluded that for Audio it was much faster when the person was not being distracted. Annie originally had .1416 as her reaction time, but when she was being distracted her reaction time was .2186. It almost doubled. For Visual reaction time, we concluded that when the eye on the same side as the hand that clicks the button is open, the reaction time is slower. For the right hand and right eye, the reaction time was .3008. For the right hand left eye, the reaction time was .2186.
Name: carrie gri Date: 2002-10-30 15:29:09 Link to this Comment: 3433 |
Hypothesis: When standing, your tactile reaction time will be slower than when you're sitting. And, furthermore, different parts of the body (i.e. arm v. leg) would yield different reactions times.
Conclusions: However, we discovered that neither criteria made any difference. Our results remained the same, despite the location of the hit and the difference between sitting and standing.
Sitting:
Jodie: arm-.161
leg- .172
Carrie: arm-.187
leg-.227
Lauren: arm-.146
leg- .213
Lawral: arm- .326
leg- .213
Standing:
Jodie: arm-.189
leg- .172
Carrie: arm- .187
leg- .247
Lauren: arm-.130
leg- .194
Lawral: arm-.198
leg- .223
Name: carrie gri Date: 2002-10-30 15:29:09 Link to this Comment: 3434 |
Hypothesis: When standing, your tactile reaction time will be slower than when you're sitting. And, furthermore, different parts of the body (i.e. arm v. leg) would yield different reactions times.
Conclusions: However, we discovered that neither criteria made any difference. Our results remained the same, despite the location of the hit and the difference between sitting and standing.
Sitting:
Jodie: arm-.161
leg- .172
Carrie: arm-.187
leg-.227
Lauren: arm-.146
leg- .213
Lawral: arm- .326
leg- .213
Standing:
Jodie: arm-.189
leg- .172
Carrie: arm- .187
leg- .247
Lauren: arm-.130
leg- .194
Lawral: arm-.198
leg- .223
Read/Think/Negate/Act Name: Laura Silv Date: 2002-11-05 14:58:49 Link to this Comment: 3537 |
I think that the two factors which could have affected this experiment the most are the internal/external factors and the practice effects which we discussed during lab time. Everything, from emotion to sleep (whether or not you get enough, which is another issue altogether) to room temperature could affect how quickly our minds are able to tell our fingers to push those buttons. For example, a sleepy person would have a longer reaction time than one with, say, 13 cups of coffee flowing through her veins (that's me!). If the temperature had been warmer in the room (it's freezing in here - can we do something about that?), we might have felt more awake and had better reaction times.
The practice effect was something that I noticed helped out my reaction times a lot. Between cases 2 and 3, my reaction time went up from 0.313 seconds to 0.404 seconds because of the vast differences between the excersizes. However, between cases 3 and 4, my reaction time went down to 0.347 seconds, and I got the feeling that it was because I was now accustomed the the manner of the excersize. I simply had to change my word association (that is, whenever I see the word "Don't", I know to push the button, and when I see the word "Do", I know NOT to push the button). This, by the way, also ties in to the "Strategy Affect" that we discussed in class also.
These were my own personal average times:
Case 1: 0.221 seconds, +/- 0.019 sec.
Case 2: 0.313 seconds, +/- 0.082 sec., average difference 0.092 sec.
Case 3: 0.404 seconds, +/- 0.059 sec., average difference 0.091 sec.
Case 4: 0.347 seconds, +/- 0.066 sec., average difference -0.057 sec.
I'd like to see if men or women have better reaction times. I think that would be pretty interesting to see.
Trial 3 test Name: Date: 2002-11-05 15:09:25 Link to this Comment: 3538 |
For our experiment we decided to see if a person's reaction time on the Act/Read/Think trial would be affected by repitition. Our hypothesis was that if you did the same trial over and over, your reaction time would be quicker and you would get a lower score. While the score initially was reduced considerably, in subsequent times the scores increased. Although they increased, they stayed lower than the initial score.
Our final reasoning why the scores first lowered and then increased is that the subject did initially become more familiar with the experiment ( lowering their score), then subsequently got bored with the experiment, causing sloppier, slower behavior. This caused the scores to rise again.
Brenda's data for the Act/Read/Think experiment:
trial #1: 526ms
trial #2: 416ms
trial #3: 419ms
trial #4: 445ms
trial #5: 445ms
Trial 3 test Name: Date: 2002-11-05 15:09:34 Link to this Comment: 3539 |
For our experiment we decided to see if a person's reaction time on the Act/Read/Think trial would be affected by repitition. Our hypothesis was that if you did the same trial over and over, your reaction time would be quicker and you would get a lower score. While the score initially was reduced considerably, in subsequent times the scores increased. Although they increased, they stayed lower than the initial score.
Our final reasoning why the scores first lowered and then increased is that the subject did initially become more familiar with the experiment ( lowering their score), then subsequently got bored with the experiment, causing sloppier, slower behavior. This caused the scores to rise again.
Brenda's data for the Act/Read/Think experiment:
trial #1: 526ms
trial #2: 416ms
trial #3: 419ms
trial #4: 445ms
trial #5: 445ms
hey Name: debe and m Date: 2002-11-05 15:14:05 Link to this Comment: 3540 |
observations:
mande before fart noise- 244, 746, -484, -58
during fart noise - 274, 334, 540, 123
After experimenting with the external noise, diana and i found that at first, my reaction times when acting during the noise was affected slightly but after time there was not much of a differance. We conclude that over time I became acclimated to the noise.
Name: Date: 2002-11-05 15:17:58 Link to this Comment: 3542 |
Case one (act): 576 +/- 72
Case two (think): 778 +/- 158
Case three (read): 934 +/- 95
Case four (negate): 876 +/- 235
Act time: 576
Think time: 202
Read time: 156
Negate time: -58
For trial two, the two subjects switched places, so that ST watched the screen and CT clicked the mouse. Results for that trial are:
Case one (act): 550 +/- 130
Case two (think): 833 +/- 149
Case three (read): 928 +/- 130
Case four (negate): 1023 +/- 344
Act time: 550
Think time: 283
Read time: 95
Negate time: 95
Conclusions:
The communication time from the person watching the screen to the person clicking the mouse definitely increased the total resulting time. The average additional time seemed fairly consistent between the two trials, thus validating our hypothesis.
Christine Traversi
Sarah Tan
Reaction Lab Name: MaryBeth C Date: 2002-11-05 15:24:52 Link to this Comment: 3543 |
Later on, in my room, I plan to experiment with one of the other factors that I think affected my reation times, the distractions of the classroom. I will experiment with total silence, and lots of noise to see how these factors effect my performance.
I would also lik to experiment with how the body reacts to auditory stimulation, as opposed to the visual stimulation of this particular test, but I have not figured out how to accomplish this task as yet.
peripheral vision Name: jen Date: 2002-11-05 15:25:40 Link to this Comment: 3544 |
Hypothesis: By looking straight ahead, while taking part in this activity,your perepheral vision will not be as accurate as you normal vision.
Observations: When not looking directly at the computer, reaction time was longer becauseyou could not see exactly what was wrtten on the screen. After two ro three times, once you get the idea of what each prompt is telling you, you become more familiar and reaction time increases similiar to what it was originally, but not completely. our numbers increased by 100 millseconds(at least)
Conclusion: Our hypothesis was right.By notlooking straight at the scrren, our perepheral vision would delayreaction time.
Practice Makes Perfect? Name: Stephanie Date: 2002-11-05 15:25:48 Link to this Comment: 3545 |
CASE 2:
trial 1: 317 +or- 105
trial 2: 279 +or- 37
trial 3: 519 +or- 544
CASE 3:
trial 1: 472 +or- 72
trial 2: 397 +or- 61
trial 3: 462 +or- 106
CASE 4:
trial 1: 451 +or- 114
trial 2: 384 +or- 78
trial 3: 436 +or- 105
Our hypothesis was proven false. In many cases, reaction time increased after practice. This leads us to conclude that many internal factors affect reaction time, including but not limited to: Attention span, level of frustration with the trial, desire to push the button, degree of overall physical exhaustion (esp. in the eyes).
Stephanie's reaction times for Case 1 got lower with practice, but her reaction times for Cases 2- 4 got higher with practice. This seems to indicate that an action can increase with practice but thinking can't.
Name: Margaret H Date: 2002-11-05 15:27:14 Link to this Comment: 3546 |
We wanted to see if women could really multi-task. If outside influences and activity would affect the response time for the Act, Think, Read, Negate experiment. We took the first test with a silent room. In fact, Laura turned around to Maggie while Kyla was taking her test and remarked on how quiet the room was. For the next trial, we decided to tell each other stories while the other person was taking the experiment. Results are as follows:
Trial 1:
Maggie:
Act 277
Think 231
Read 146
Negate 302
Kyla:
Act 279
Think 138
Read 217
Negate 180
Trial 2 (with distraction)
Maggie:
Act 335
Think 141*
Read 280
Negate 192*
*lower times than Trial 1, all other times were higher
Kyla:
Act 330
Think 120*
Read 151*
Negate 194
Conclusions:
Our hypothesis was that the distractions would have an increased effect on response times. However, that was not the case for all of the times. Both act times were significantly higher, however Maggie had lower times for Thinking and Negating while Kyla had lower times for Thinking and Reading. We do not have enough evidence to conclude that distractions make a difference in reaction times for Acting, Thinking, Reading, and Negating.
Name: kathryn ba Date: 2002-11-05 15:29:33 Link to this Comment: 3547 |
Data:
HERBIE HANCOCK..............KB................Sf
Act Time...................239................239
Time to Think..............115................78
WHITESNAKE
Act Time..................242.................257
Time to Think.............51...................58
SPOTLIGHT ON GUITAR
Act Time..................251................257
Time to Think.............32..................48
Results:
The data shows that time to think was greatest for both subjects when listening to Herbie Hancock, and smallest when listening to Spotlight on Guitar. The Act Times were consistent across all trials.
Discussion:
This experiment indicates that music can affect one's ability to think quickly. It also is significant that the think times are consistent across two people. This experiment does not answer the question of why different music has particular effects on one's ability to think, suggesting that further study is needed.
Reaction Times Name: Date: 2002-11-06 14:54:35 Link to this Comment: 3562 |
Hypothesis: Distractions will slow down reaction time.
Methods: We used the reaction time applet in serendip to measure reaction times for case 1:"act" and case 3:"read, think, act" experiments. During these experiments the person reacting was also engaged in a conversation with her partner who attempted to distract her by asking questions.
Observations:
Chelsea:
Case 1 without distraction: 295 +/- 63
Case 1 with distraction: 734 +/- 369
Case 3 without distraction: 735 +/- 102
Case 3 with distraction: 1157 +/- 249
Roma:
Case 1 without distraction: 274 +/- 30
Case 1 with distraction: 422 +/- 69
Case 3 without distraction: 544 +/- 164
Case 3 with distraction: 661 +/- 200
Conclusions:
There is substantial difference between the data gathered for experiments with and without distraction strongly suggesting that our hypothesis is correct. There also may have been a larger disparity in the data had the initial experiment been carried out in a silent room. Additionally worth noting is that the incidence of error (ie: clicking when told not to which removes the last recorded piece of data) was much higher with distraction. Further experiments might involve other types of multi-tasking.
Name: Laura B. a Date: 2002-11-06 15:01:14 Link to this Comment: 3563 |
Adrienne: Act time: 331; Think, act time: 468; Read, think, act: 941; Read, think-negate, act: 1996
For our second experiment, we decided to try talking while performing case 1 and case 4. Our hypothesis was that our reaction times would be slower because of the distraction of carrying on a conversation. Our results were as follows:
Laura: Act time: 374; Read, think-negate, act: 622
Adrienne: Act time: 385; Read, think-negate, act: 1409
Our results were slower except for Adrienne's negating time, which was probably due to the practice factor. Therefore, with that one exception, our hypothesis proved to be true.
thinking time Name: Date: 2002-11-06 15:14:10 Link to this Comment: 3564 |
We decided to see if our thinking time was inhibited by over-thinking. When some of us were doing the tests we realized that we had to think the command, "Click!" before we actually did. This was above and beyond thinking aboiut whether we had to click or not. To conduct our experiment, we distracted our minds slightly by either singing to ourselves or reciting poetry. In doing this we hoped to make our overall thinking time faster. Our results are as follows:
Margot:
Control: 251+/-14 258+/-14 519+/-29 614+/-65
Experiment: 322+/-18 406+/-70 955+/-857 582+/-54
Michele:
Control: 212+/-28 286+/-46 454+/-15 1421+/-1358
Experiment: 380+/-42 301+/-20 453+/-38 537+/-72
Diana:
Control: 239+/-21 374+/-83 536+/-30 801+/-141
Experiment: 289+/-53 379+/-131 499+/-41 659+/-127
Our results show that for cases 1 and 2 our times are slower, which is understandable. In our last lab we found out that reflex times slow when one is distracted and case one is a reflex test. We also found that we made significantly more mistakes on case 2, although Michele made the same amount of mistakes. For cases 3 and 4 however our times were better, especially in case 4. Our overall deviation was higher for most all cases in the experiment.
We believe that a slight distraction from the test will help most people do better, although this is not true for all people.
Name: Rosie, Bob Date: 2002-11-06 15:22:27 Link to this Comment: 3567 |
Case 1: all three of us increased in reaction time.
Case 2: Rosie increased, Annie and Bobbi decreased.
Case 3: Annie increased, Bobbi and Rosie decreased.
Case 4: all three of us decreased in reaction time.
Our data shows no correlation between reaction time and increased experience or practice. Our hypothesis is therefore incorrect. The results seem random. The practice effect cannot help in this situation because the test is still random and the prompts are unexpected (concentration is still necessary). While we may have gained familiarity with the practice (meaning that our times should have decreased), we were also growing distracted and tired of taking the test--these two factors may have counteracted one another.
Reaction Time Name: Catherine Date: 2002-11-06 15:23:13 Link to this Comment: 3568 |
Name: Mer Date: 2002-11-06 15:28:55 Link to this Comment: 3569 |
The first time that we all used the Thinking Program, we came up with the following results:
CHEL:
233 +- 30 (1)
308 +- 89 (2)
582 +-66 (3)
585 +-66 (4)
233 +- 30 (acting)
75 +- 94 (thinking
274 +- 41 (reading)
6 +-128 (Negating)
MER
269 +-81 (1)
304 +- 69 (2)
369 +- 115 (3)
631 +- 439 (4)
269 +- 81 (acting)
35 +- 107 (thinking)
63 +- 135 (reading)
262 +-464 (negating)
HEI:
224 +-20 (1)
245 +-19 (2)
475 +- 141 (3)
467 +- 144 (4)
224 +- 20 (acting)
21 +- 28 (thinking)
330 +- 143 (reading)
-8 +- 202 (negating)
For our second experiment, we decided to test the impact of practice with the system, and using another set of data for comparison, what the impact of distraction was upon Chelsea.
Our hypothesis is thus, Chelsea will get better with practice and her times will improve. Also, Chelsea will become distracted with the noises, and as a result, her scores will drop.
Results:
Quiet Practice:
Trial 1
Average: 459.9 SD: 84.5 Errors: 3
Trial 2
Average: 412.4 SD: 126.5 Errors: 2
Trial 3
Average: 462.1 SD: 291.5 Errors: 1 (two times high because of double clicks)
Total Average: 444.8 SD: 167.5 Errors: 2
So far, Chelsea improved greatly from her first trial (with the class), and since the last trial was inaccurate, we cannot decisively say that she continued to get better (but she did improve from trial 2 to 3)
Experiment 2
Distracted
Average: 352.1 SD: 122.5 Errors: 2 (both when clapped)
Trial 2
Average: 513.1 SD: 258 Errors: 2
Trial 3
Average: 361.6 SD: 120 Errors: 1 (clapping)
Total Average: 408.93 SD: 166.83 Errors: 2ish
Conclusions: Overall Chelsea concentrated better with distractions, although practice might play a role (we need to do more experiments to decide though). It is important to note that while times seemed to improve, consistency did not, meaning that Chelsea was faster, but also just as inaccurate. We think that noises that are sharp (clapping) have a great impact on concentration than softer or less aggressive noises.
if you can't walk the walk, don't fall out of your Name: Lauren Fri Date: 2002-11-06 15:30:25 Link to this Comment: 3570 |
Case 1 | Case 1 + | Case 2 | Case 2 + | |
Lauren | 215 | 252 | 304 | 330 |
Carrie | 254 | 337 | 375 | 386 |
finally. ha ha. Name: jodie and Date: 2002-11-06 15:39:27 Link to this Comment: 3572 |
Lawral:
case 2 accuracy - 390 +- 105 100% accuracy
case 2 speed - 355 +- 70 84% accuracy
case 3 accuracy - 581 +- 188 100% accuracy
case 3 speed - 434 +- 81 83% accuracy
case 4 accuracy - 536 +- 87 93% accuracy
case 4 speed - 492 +- 83 86% accuracy
Jodie:
case 2 accuracy - 312 +- 63 100% accuracy
case 2 speed - 274 +- 37 90% accuracy
case 3 accuracy - 366 +- 53 100% accuracy
case 3 speed - 415 +- 160 71% accuracy
case 4 accuracy - 414 +- 128 91% accuracy
case 4 speed - 360 +- 277 72% accuracy
for the most part, our hypothesis was correct. our accuracy was affected by concentrating on speed. the actual speed, however, was affected by
concentrating on it in a negative way because we were flustered by the amount of mistakes we were making. we would also like to note that we are sorry for posting this in the regular forum. oops.
"The Flaming Lips" Name: Will, Dian Date: 2002-11-06 15:40:16 Link to this Comment: 3573 |
Act time: 237 +/- 22, 215 +/- 20
Think time: 76 +/- 60, 76 +/- 44
Read time: 122 +/- 99, 121 +/- 62
Negate time: 68 +/- 166, 7 +/- 74
Diana:
Act time: 258 +/- 37, 221 +/- 15
Think+A time: 298 +/- 26, 302 +/- 52
Read+T+A time: 464 +/- 65, 493 +/- 70
R+Think Negate+A time: 620 +/- 109, 905 +/- 293
Act time: 258 +/- 37, 221 +/- 15
Think time: 40 +/- 46, 83 +/- 55
Read time: 166 +/- 71, 189 +/- 88
Negate time: 156 +/- 127, 412 +/- 302
Brie:
Act time: 210 +/- 17, 229 +/- 19
Think+A time: 264 +/- 30, 234 +/- 11
Read+T+A time: 450 +/- 25, 391 +/- 27
R+Think Negate+A time: 408 +/- 40, 312 +/- 46
Act time: 210 +/- 17, 229 +/- 19
Think time: 54 +/- 35, 5 +/- 22
Read time: 186 +/- 40, 157 +/- 30
Negate time: -42 +/- 48, -79 +/- 54
Second times in each were while listening to music.
FLY LAB Name: Brenda and Date: 2002-11-12 15:24:41 Link to this Comment: 3695 |
For our experiment, we crossed a long-antennaed (Ar) female with an Eyeless (Ey) male.
Cross #1: Their Children
264 Wild-type (+) female, 256 (+) male
257 (Ar) female, 249 (Ar) male
The eyeless trait did not appear in the children.
Now, we'll cross the children with each other.
Cross #2a: (+) female crossed with (+) male
Results: 369 (+) female, 382 (+) male
134 (Ey) female, 140 (Ey) male
In this cross, the (Ar) trait did not show up
Cross #2b: (Ar) female crossed with (Ar) male
Results: 132 (+) female, 147 (+) male
265 (Ar) female, 248 (Ar) male
42 (Ey) female, 35 (Ey) male
103 (Ar/Ey) female, 87 (Ar/Ey) male
All traits appeared in the children, with a 3:3:1:1 ratio
Cross #2c: (Ar) female crossed with (+) male
Results: 171 (+) female, 200 (+) male
187 (Ar) female, 207 (Ar) male
63 (Ey) female, 65 (Ey) male
59 (Ar/Ey) female, 51 (Ar/Ey) male
Once again, all traits showed with a 3:3:1:1 ratio
Cross #2d: (+) female crossed with an (Ar) male
Results: 187 (+) female, 174 (+) male
175 (Ar) female, 192 (Ar) male
53 (Ey) female, 77 (Ey) male
62 (Ar/Ey) female, 80 (Ar/Ey) male
Again, all traits appear with a 3:3:1:1 ratio
Fly Lab Name: Kate Amlin Date: 2002-11-12 15:30:20 Link to this Comment: 3696 |
First we established that the
purple eye gene is an example of true breeding, and recessive...
then that the lobed eye gene is also and example of true breeding,
but it is dominant.
We hypothesized that breeding a purple, lobed female with a wild type male would produce a
9 lobed m/f : 3 wild type m/f : 3 purple, lobed m/f : 1 purple m/f.
We tested the hypothesis by breeding a purple, lobed female with a wild type male.
They produced=> lobed females + lobed males (1:1) ratio
the lobed males and females produced=> 1 wild m/f : 2 lobed m/f : 1 purple, lobed m/f
Our hypothesis was disproven since tour results were in a
1 wild: 2 lobed: 1 purple, lobed : 0 purple ratio
INSTEAD OF A 3 wild: 9: lobed: 3 purple, lobed: 1 purple ratio
So because our hypothesis was disproven, we concluded that there must be some linkage between the genes. Instead of each gene being carried by a different chromosome (which would result in our hypothesized Punett Square with 16 combinations), the genes are linked and share the same chromosome. The lobed and the purple eyes were carried on one chromosome and the wild gene was carried on a chromosome. This would then give us 4 possible results when doing the Squares and explain the 2:1:1 0 ratio that resulted in our experiment.
Kate Amlin, Katie Campbell, Stephanie Lane
virtual fruit flies Name: Kathryn Ba Date: 2002-11-12 15:35:40 Link to this Comment: 3697 |
(e)PR & (e) PR = PR
* PR is true breeding; Phenotype PR, Genotype PR PR
2) Next we tested (e)PR and (a) AR
PR AR & PR AR = (1) PR + : (2) PR AR
* PR again was homozygous, the AR seemed to be heterozygous
3) We examined (a) AR further
AR & AR = (2) AR: (1) +
* As with (2) the part of the model of genes where the AR AR should have existed was absent. The only way to obtain the ratio is if the phenotype AR is genotypically AR +
4) In order to test this further, we bred (e)PR (a) AR and an (e)+ (a) +
PR AR & + + = (1) (e) + (a) AR : (e) + (a) +
* This shows that the (e) + is dominant over the (e) PR and that the AR AR combination does not exist and is always heterozygous
Fly lab Name: Mande Macl Date: 2002-11-12 15:36:59 Link to this Comment: 3698 |
genes Name: joanna yar Date: 2002-11-12 15:37:56 Link to this Comment: 3699 |
CV and + Name: Margot and Date: 2002-11-12 15:45:11 Link to this Comment: 3700 |
We decided to test the wing vein trait of crossveinlessness.
When both male and female were crossveinless (CV), the kids were both CV and there was an equal number of males and females. When we mated the kids, the grandkids were also both CV, and there was also an equal number of males and females.
When the female is CV and the male is wild (+), the female kids were all + and the males were all CV, with equal amounts of male and female. When the kids were mated together, there were equal amounts of male and female. Within the females, there were equal amounts of + and CV, and in the male there were also equal amounts of + and CV.
Now...
When the female is + and the male is CV, the kids were ALL +, with equal amounts of male and female. In the grandkids, there were equal amounts of male and female, but there were ONLY female +. Within the males, there were equal amounts of + and CV.
And then...
When we mated the grandkids of a female + and a male CV, we got equal amounts of male and female and within each gender, equal amounts of + and CV.
So how do we account for the reappearance of the female CV when it seemed to have disappeared in both the female kids and grandkids generations? Our theory is that CV is a recessive gene that exists on the sex chromosome. This follows the same type of genetic pattern as recessive genes in humans, where recessive genes on the X chromosome do not show up in the female unless it is on both of her X chromosome. However, because males only have one X chromosome, when they have a recessive gene on the X, it will show up no matter what. Therefore, it is more unlikely for a recessive gene to affect the phenotype of the female than in the male.
CV and + Name: Margot and Date: 2002-11-12 15:46:43 Link to this Comment: 3701 |
We decided to test the wing vein trait of crossveinlessness.
When both male and female were crossveinless (CV), the kids were both CV and there was an equal number of males and females. When we mated the kids, the grandkids were also both CV, and there was also an equal number of males and females.
When the female is CV and the male is wild (+), the female kids were all + and the males were all CV, with equal amounts of male and female. When the kids were mated together, there were equal amounts of male and female. Within the females, there were equal amounts of + and CV, and in the male there were also equal amounts of + and CV.
Now...
When the female is + and the male is CV, the kids were ALL +, with equal amounts of male and female. In the grandkids, there were equal amounts of male and female, but there were ONLY female +. Within the males, there were equal amounts of + and CV.
And then...
When we mated the grandkids of a female + and a male CV, we got equal amounts of male and female and within each gender, equal amounts of + and CV.
So how do we account for the reappearance of the female CV when it seemed to have disappeared in both the female kids and grandkids generations? Our theory is that CV is a recessive gene that exists on the sex chromosome. This follows the same type of genetic pattern as recessive genes in humans, where recessive genes on the X chromosome do not show up in the female unless it is on both of her X chromosome. However, because males only have one X chromosome, when they have a recessive gene on the X, it will show up no matter what. Therefore, it is more unlikely for a recessive gene to affect the phenotype of the female than in the male.
Flies in my eyes Name: Mags and K Date: 2002-11-12 15:49:59 Link to this Comment: 3702 |
We crossed a Purple-eyed Female with a Wild-eyed male.
The offspring had a 3:1 ratio for wild-eye color to purple. And after hand graphing the crossing of a PR PR female and a + + male, it was confirmed that the PR gene is recessive.
We then crossed a Curley-winged Female to a normal (wild type) male. For that, we had a two to one ratio. When hand-graphing the results of mating a CY CY female and a + + male, we realized we should have had all offspring be the same if that was to work. Therefore, (because we know that the wild type is + + from a previous experiment) the curly eyed gene cannot be CY CY. Upon graphing the results of a CY+ female mating with a ++ male, the correct ratio of two to one appeared. In order for the 2:1 to hold, we must assume that the CY gene is dominant over + gene. Also, the CYCY gene does not exist.
Finally, we paired a purple eyed, curly winged female with a wild-type male. The first generation offspring have two wild type offspring(both eyes and wings) and two wild type eyes with curly wings. When hand graphing the mating of a CY+, PRPR female with the ++,++ male, we realize there is a 50% chance of finding an offspring with curly wings (CY+) and no chance of the PR gene appearing. This holds, since the CY gene is dominant over the wild type and the wild type is dominant over the Purple eye gene.
Fly Lab Results Name: Emily and Date: 2002-11-13 15:04:56 Link to this Comment: 3718 |
Cross 1:
Purple-Eyed Female x Purple-Eyed Male
result - 492f and 499m ALL PURPLE
1b:
offspring of cross 1
result - 505f and 513m ALL PURPLE
CONCLUSION - purple-eyed trait is true breeding
Cross 2:
Eyeless Female x Eyeless Male
result - 511f and 475m ALL EYELESS
2b:
offspring of cross 2
result - 498f and 506m ALL EYELESS
CONCLUSION - eyeless trait is true breeding
Cross 3:
Purple, Eyeless Female x Purple, Eyeless Male
result - 528f and 506m ALL EYELESS
3b:
offspring of cross 3
result - 498f and 493m ALL EYELESS
CONCLUSION - because both parents were homozygous for eyeless, there was no chance for the eye color trait to be displayed phenotypically since they could not have eyes
Cross 4:
Purple, Eyeless Female x Wild Eyed Male
result - 518f and 471m ALL HAD WILD EYES
4b:
offspring of cross 4
result - 297f and 280m WILD EYES
101f and 84m WILD-SHAPED, PURPLE EYES
129f and 133m EYELESS
CONCLUSION - for eye shape, parents in the second generation were heterozygous for wild eye and eyeless. as a result, some of the offspring in the 3rd generation showed the wild-eye trait and others were eyeless.
for eye color, parents in the second generation were heterozygous for wild eye and purple. as a result, some offspring showed the purple eye trait and others were wild.
the ratio for this double-trait cross was 3:1:1 instead of the regular 9:3:3:1 ratio. when more eye-color traits would have been displayed, some offspring turned out eyeless. this is because the 3rd gen. the genotypes that would have shown purple eyeless and wild-colored eyeless could not be distinguished as two different phenotypes. we could not see the eye color trait if they did not have eyes.
Mellow Yellow Name: Date: 2002-11-13 15:26:15 Link to this Comment: 3720 |
We were curious about the inheritance of the yellow gene and whether it was passed on specifically by the male or the female and if it was possibly passed on to a specific sex.
Our first experiment was conducted with a yellow male and a "true" wild female. The offspring were all phenotype wild.
Once we continued the experiment and bred both phenotype wild sexes they yielded all phenotype wild flies again.
Our first hypothesis was that the male fly could not pass on yellow to either sex offspring.
For our second experiment we mated a yellow female with a "true" wild male fly. The offspring were about half phenotype wild female and half yellow male. We had no idea then how female yellow flies could possibly exist. Next we bred the offspring (wild phenotype females with yellow males) and this produced both wild phenotype males and females, and yellow phenotype males and females.
After this occured we started pulling our hair out, we knew something was wrong with our original hypothesis but we couldn't figure out how yellow males and females had been produced or if one sex had passed it on to its offspring.
After strenuous thinking aided by our lab companion Will, we came to the conclusion that the yellow allele is a recessive trait on the X chromosome. Thus, if a male has a yellow allele on his X chromosome he will be phenotype yellow. In order for a female fly to be phenotype yellow, she needs both of her X chromosomes to have yellow alleles. We wondered if this trait was similar to that of color blindness in humans, since colorblindness is more common in males.
virtual fly lab Name: drosophila Date: 2002-11-13 15:29:02 Link to this Comment: 3721 |
Hypothesis: Both male and female fruit flies have two genes for each characteristic and the characteristics which are exhibited in inheritence will reflect this fact, with the wild type of each trait being dominant.
Methods and Results: We mated male and female brown-eyed fruit flies and found them to be "true breeding" (ie: their off-spring were all brown-eyed). Then, we mated a brown-eyed female with a wild-type male, producing offspring which all exhibited the wild-type phenotype. These offspring, when mated, produced offspring some of which are wild-type, some brown-eyed in an approximately 3:1 ratio.
We then examined wing angle, first mating a male and female both with the dichaete wing angle. This trait did not appear to be "true-breeding" as some of the offspring produced had a wildtype wing angle and some had a dichaete in an approximately 1:2 ratio.
Experimenting with a combination of these traits (eye color and wing angle) produced other interesting results. We mated a brown-eyed female with a dichaete wing angle with a wild type male, resulting in offspring which all had wild-type eyes and some of which had a wild-type wing angle and some a dichaete wing angle. Mating two of these offspring (a female wild-type and a male with wild-type eyes and dichaete wing angle) produced offspring in a 3:3:1:1 ratio (+, dichaete, brown-eyed, brown-eyed dichaete).
Conclusion:
The results of breeding brown-eyed fruit flies supports our hypothesis, as the presence of two genes for every trait would lead to the 3:1 ratio which was present in our results. Experimenting with wing angle, however, suggested that our hypothesis (wild type is always dominant) was incorrect, as it suggests that dichaete is a dominant trait and, in fact, lethal in a double dose. Also, the experiment combining brown eyes and dichaete wing angle further supported these findings because the ratio produced was what was expected in accordance with the punnett square examining that combination.
Weird Genes Name: Will Carro Date: 2002-11-13 15:33:06 Link to this Comment: 3722 |
Curly Wings:
First generation
Curly Fem. X Curly Male
353 Curly Fem.
168 Wild Fem
349 Curly Male
156 Wild Male
2:1 (ignoring sex)
Second generation
Wild Fem x Father (Curly Male)
257 Wild Fem
241 Curly Fem
235 Wild Male
255 Curly Male
1:1 (ignoring sex)
Hypothesis: Curly wings are a heterozygous genotype. Wild type wings are homozygous dominant. A homozygous recessive genotype is fatal.
First generation
MOTHER C c |
||
F C A T H c E R |
CC (wild) |
Cc (curly) |
Cc (curly) |
cc (fatal) |
Second generation
MOTHER C C |
||
F C A T H c E R |
CC (wild) |
CC (wild) |
Cc (curly) |
Cc (curly) |
White eyes:
First generation
White Fem. X Wild Male
495 Wild Fem.
502 White Male
Ratio 1:1
Second generation
Wild Fem. X White Male
266 White Fem.
259 White Male
252 Wild Fem.
247 Wild Male
Ratio: 1:1:1:1
Third generation
First generation Wild Female X Wild Male
487 Wild Fem.
267WildMale
250 White Male
Ratio: 2:1:1
Hypothesis: White eyes are a X-chromosome linked characteristic. A female that carries only one chromosome associated with the white eye gene has wild eyes. A female must have both chromosomes associated with the white eye gene to have white eyes. Because males only have one X chromosome, if they carry the white eyed gene they have white eyes.
First Generation
MOTHER X Xw |
||
F X A T H Y E R |
XwX (wild) |
XwX (wild) |
XwY (white) |
XwY (white) |
Second Generation
MOTHER Xw X |
||
F Xw A T H Y E R |
XwXw (white) |
XwX (wild) |
XwY (white) |
XY (wild) |
Test Cross
MOTHER Xw X |
||
F X A T H Y E R |
XwX (wild) |
XX (wild) |
XwY (white) |
XY (wild) |
gene lab Name: Annie S., Date: 2002-11-13 15:36:26 Link to this Comment: 3723 |
Our next experiment examines double trait flies in comparison to the wild type mate. We first bred a purple-eyed, cossveinless female with a wildtype male. Our results: 2 images; 528 wild type females and 493 CV males. Purple eyes is a recessive trait and CV is carried on the x chromosome of the female. We cross that generation and we got a 3:1:3:1 ratio of wild type to purple eyes to cross veined to purple eyed cross veined.
The female will always contribute the following traits: ++, +CV, p+, p CV. The male will contribute one of two sets of genes depending on whether the offspring is male or female. Is the offspring is female, he will either contribute +CV, or pCV. If the offspring is male, he will give either +Y, or pY. The Y trait here is essentially "empty" since it cannot carry the CV trait.
Name: Chelsea Date: 2002-11-13 15:39:12 Link to this Comment: 3724 |
Scalloped winged: True Breeding
Wild Winged: True Breeding
Hypothesis:
Either wild winged or scalloped winged will be dominant. (regardless of sex).
One female Scalloped winged and One male Wild winged: all female offspring are wild winged and all males are scalloped. In the second generation males and females both had equal proportions of wild and scalloped winged.
One male Scalloped and One female wild winged: all offpring are wild winged in the first generation and in the second generation all females are wild winged and all males are equally split between scalloped and wild winged.
Conclusion:
Dominance is sex related in this case of scalloped versus wild winged fruit flies. This is due to the fact that some genes are located exclusively on the X chromosome and there is no counterdominant gene on the Y chromosome. Because females have 2 X chromosomes and males one X and one Y, then whatever gene is on the X (scalloped) will be dominant in males because there is no counter gene on the Y chromosome. Also, the female flies with wild prove that scalloped is recessive, since they have both scalloped and wild genes. Finally, a female with two scalloped is not lethal, merely guarentees that her son will be scalloped.
damn bugs Name: Date: 2002-11-13 15:58:00 Link to this Comment: 3725 |
we tested aristapedia antennae and dichaete wing alignment. we have been testing both of these characteristics together and separately in males and/or females for the last two hours. we have figured out that both traits are lethal homozygos, meaning that they cannot truebreed because there can never be a homozygos aristopedia or a homozygos dichaete. any fruit flie that is aristapedia or dichaete is heterozygos. the problem is that these traits are only lethal homozygos in females. because they are only lethal in females, the genes for the aristapedia and dichaete are in the x chromosome. because the genes are both on the x chromosome, they cannot be separated, except in the case of cross-over when the chromosome splits.
our results were as follows:
m(ArD) & f(++):
1:1
of Ar:D
f(ArD) & m(++):
1:15-20:15-20:1
of ++:Ar:D:ArD
oops Name: Erin Myers Date: 2002-11-14 16:20:44 Link to this Comment: 3738 |
fly lab Name: Heather an Date: 2002-11-18 21:23:00 Link to this Comment: 3783 |
Then we crossed a wild type male with a purple-star-eyed female. From the first cross we got only wild type and wildtype with star eyes. we then bred the two wild/star-eyed flies together. What we recieved were wild/wild, wild/star, and purple/star in a ratio from 1.5:2.5:1. We were then confused because when we did the cross ourselves, the results were very different. We soon learned that we had a lethal combination in out genetic set. if the fly recieves two star-eyed dominant genes, then that fly cannot exist. Also, purple/wild type flies did not exhist. That's because both the gene for purple and that for star are on the same chomosome. These genes are linked, so there is something that makes this mix impossible, though Will never really explained what...
Name: kathryn ba Date: 2002-11-19 14:24:17 Link to this Comment: 3789 |
Body Cells and their Functions Name: Diana Fern Date: 2002-11-19 14:30:21 Link to this Comment: 3790 |
Observations:
Esophogus - thick epithereal layer, inside ring is composed of purple cells, cilia is present
Trachea -
thin epithereal layer, large lumen amount in the cell, also a layer of small purple cells.
Lung - resembles trachea in that it has a lot of lumen, a layer of purple cells, evident oblong cells in the epithereal layer that stretch from one side of the layer to the other.
In conclusion we found that our hypothesis was right. Since teh trachea and lung both function to get air to teh blood stream, they had very similar structures.
Cells Name: kate katie Date: 2002-11-19 14:32:23 Link to this Comment: 3791 |
We decided to explore cells of the liver, kidney, and lung. We wanted to observe the similarities and differences in the cells and the higher assemblies of cells and how they relate to the function of the organ.
Our hypothesis was that the cells and their organization would be similar in each of the organs because we believed that their functions were closely related in responsibility of delivering materials to the blood.
We looked at the three differnt slides and discovered that at first glance, each of the organs looked pretty similar. Our observations on a more detailed cell level, however, showed us that the liver and kidney cells were of similar size and make-up. The nucleus took up approximately half of the cell size. Whereas the appearance of the lung cells reminded us of the liver and kidney cells they were noticably smaller than the other cells.
Although the cells seemed to be physically similar, the spatial organization of the liver, kidney, and lungs were quite different. The liver cells were organized in rings/clumps. The kidney cells were arranged in long strings with more lumen than in the liver cells. The lung cells were placed in long, twisty strings and the lung had the most lumen of the three slides.
From these observations we conclude that the lumen plays a key role in the function of the lung. The empty space provides room for the oxygen that enters the lung each time an individual inhales. However, the lumen found in the kidney and liver would not serve the same purpose. Therefore, the lumen is not a similarity that can connect the functions of these three organs. Perphaps similarities of the individual cells are what link the purposes of the liver, kidney, and lung.
Intestines Name: Midgie Date: 2002-11-19 14:34:50 Link to this Comment: 3792 |
Small Intestine:
Cross section appeared to be tubular in shape - with a band of muscle fibers or tissues around the outside of the tube, and finger-like extensions reaching into the empty space (lumen). The fingers were very long and had high concentration of cells in them.
Large Intestine:
Cross section appeared to be only half of what we assume would be another tube. The fingers were shorter in length and close together. The fingers had more cells in them than in the band on the outside.
Comparasion:
Band is thicker in the large intestine, with the finger extensions shorter in length and set closer together than the small intestine. The small intestine fingers were longer than the large intestine, but had a larger concentration of cells in the fingers. Because food is processed in the small intestine before it travels to the large intestine, we think that the high concentration of cells in the large fingers of the small intestine serve to absorb the nutrients from the food. The large intestine also absorbs whatever nutrients haven't been absorbed in the small intestine, but basically serves to turn the food into waste, since all the nutrients are gone. Therefore, the large intestine doesn't need the long fingers and high concentration of cells to absorb the nutrients the way the small intestine does.
Heart cell:
Unlike the tubular appearance of the intenstines, the heart slide lacks the large pockets of lumen. What lumen we could see was very long and stringy, and blended in with the muscle fibers of the heart. There seemed to be a more even distribution of cells throughout the cell, rather than in concentrated areas.
Ovaries, TESTES, and spinal cord, oh my!! Name: Heather, M Date: 2002-11-19 14:41:27 Link to this Comment: 3793 |
So, the testes. Singular, testis. There were many chambers which the cells organized themselves into, which, depending on the section we looked at, looked like rings or tubey things. Naturally, those were all made up of cells. It was interesting that because new sperm is created every 70 days (information courtesy of Wil), unlike the ovaries, where eggs come prepackaged for life, we could see cells dividing in the testes. In some cells in the chamber linings, we could even see the individual chromosomes, which looked like sausages. Within the chambers, there were big masses of "furry things," which, it turned out, was sperm. Sperm tails, to be exact. Really, this is what does it for Grobstein. He said so.
Okay, so maybe the spinal cord lacks the excitement of the ovaries and the testis, but it is still pretty important. The cells are really tightly packed together- this is why a small impact on the spinal cord greatly affects the rest of the body. Also, since the spinal cord is vertical, a cross section only shows basically tiny circles. The basic function of the spinal cord is to transport information and the organization of the cells reflects this.
The cells in the spinal cord are really different from those in the reproductive organs. This is because so many different stages of the reproductive process have to be accomadated by those cells for the organs to perform their function. However, all of the cells in the spinal cord have the same basic function, they specialize in transmitting information.
Sarah Tan- testis
Heather Price- ovaries
Margot Rhyu- spinal cord
Cell shape and function Name: Jen Rusk, Date: 2002-11-19 14:58:45 Link to this Comment: 3795 |
The kidneys are where blood is filtered for different things, such as salt and water. So the cells are probably set up in this way (tubular fashion) to allow liquid to pass by so it can be filtered.
The Liver had a similar structure, in that there were tubular openings. From prior knowledge we know that impurities, such as alcohol, are filtered and broken down in the liver. This could account for the similarities in shape and organization, the similar functions.
We also looked at a crossection of the aorta as comparison. there was a big difference in the way the cells looked and were organized. In the aorta, the clumpy and more scattered, with blood vessels (some of different sizes) spread throughout.
lab Name: Date: 2002-11-20 14:07:40 Link to this Comment: 3805 |
We studied three organs: Small intestine, large intestine, and skeletal muscle. The questions we were asked are:
1. # of cell types/tissues?
2. arragement of tissue within tactic organ?
3. Can an organ be formed from the cells of another?
Small intestine
3 types of cells:
outer layer- very elongated, thin, smooth muscle to help move food
middle layer- space between cells, lumen, spongy looking
inner layer- concentration of nuclei and spaced out
Large intestine
3 types of cells: similar to structure of small intestine cells
Overall make up of them took up a larger area, they're larger, hence large intestine.
Skeletal muscle
one type of cell but it did look like there might have been connective tissue. It appeared smooth and thin.
Discussion:
Small and large intestines appeared to have the same types of cells. The only major difference was that the large intestine's cells took up greater space. It appears that the cells of the small and large intestines could make up one another. The skeletal muscle cells appeared to be the same type of cell as the outer layer of the large and small intestine. This is probably because the outer layer is smooth muscle that aids in parastolisis.
cells Name: Adrienne a Date: 2002-11-20 14:11:33 Link to this Comment: 3806 |
We looked at the small intestine vs. the large intestine, and then looked at the lung.
Small intestine: We found about 6 or 7 different cell/tissue types. The cells were more densely packed toward the outside of the cross section, and toward the middle they got less dense, and then in the very middle, there was a bunch of blank space (lumen).
Large intestine: We found about 6 different cell/tissue types. The cell arrangement was pretty much the same as the small intestine, but the less dense cells toward the middle were more stringy.
Lung: We found about 8 different cell/tissue types. The cell arrangement is VERY different from that in the intestines. There is no blank space (lumen) in the middle, rather there are smaller blank spaces spread throughout the sample we looked at. The cells look very different from the intestines' cells as well.
Comparison: The intestines seemed pretty similar, but since they are separate in our bodies they probably can't replace each other. The lung cells looked totally different and therefore could not replace intestine cells.
organs and cells Name: Date: 2002-11-20 14:14:50 Link to this Comment: 3808 |
We examined different organs taken from various organisms for the classification of different cell types. The experiment was carried out with the help of a simple microscope. Our hypothesis is that all of the organs examined would have same types of cells since all these different organs work together to carry out the many bodily functions.
At first, we looked at a section of pig liver cells. Clumps of cells which looked like they were the same kind of cell could be seen along with lumens. Perhaps one reason for the existence of many lumen is the function of the liver which is to channel out impurities from the bloodstream.
Next, kidney cells were observed. Elongated, elliptical and tubular cells were seen along with lumen which had larger surface areas than the lumen in the liver cells. The function of the kidneys is to filter the salt and water from the bloodstream and an arrangement of longish-shaped cells could account for this function.
Cells from the cardiac muscle in the heart were then examined. The arrangement in this organ is very different from the cell arrangement in the other two organs previously observed. The lumen is arranged in a stringy longitudinal way. The cells are longitudinal as well and are tightly packed. This is probably to enhance the function of the heart, since such narrow passageways would regulate blood flow and balance the pressure of blood flow as well.
We found out that the cells in the different organs were not the same after all and the reason would be that they have different functions and even if the functions are carried out harmoniously, they are still different functions being carried out by different organs.
Today's Lab Name: Bobbie, An Date: 2002-11-20 14:23:00 Link to this Comment: 3810 |
Almost Thanksgiving Name: Brie and D Date: 2002-11-20 14:23:11 Link to this Comment: 3811 |
1. # of Cell Types/Tissues
Trachea=4-5
Esophagus=3-4
Lung=3-4
2. Arrangement of tissues w/in entire organ
Trachea=4 layers; cartillage type cells to help keep structure rigid and open for air, more lumen than esophagus.
Esophagus=muscular layers, darker layers around lumen, outside shredded layer.
Lung=mostly spongey layer that looks perforated, a lot of air. Oval longer shapes in the spongey layer, thick dark layer around lumen, tiny dark spotty layer around lumen.
3. Can one organ be formed from the cells of another?
No! If the esophagus was made from Trachea cells, it would not be able to perform peristalsis which would result in choking and suffocation. The trachea must be rigid to prevent choking and allow air to flow continuously. The lung tissue must be expandable to allow the influx of air.
3a. Are they made of different types of tissues? Yes! Rigid vs. Muscle vs. Airy !
Cell Lab Name: Chelsea, M Date: 2002-11-20 14:37:38 Link to this Comment: 3812 |
Ovaries
a. outer lining cells which resemble the cells in the testes
b. inner lining cells present directly around the egg cell which are the same kind as the outer liner cells but located in a different place
c. egg cell with a membrane
function: outer and inner liner cells protect and contain egg cells. the outer cells form a cushion around the egg to protect it from destruction.
compare:
the lining cells of the testes and ovaries seem to be simiar and perform a similar function- protecting the reproductive cells
Lung
a. many of the same type of smaller cell with large, round lumen gaps in between groups of cells
b. pink, spongy-looking groups of blood cells present in clumps throughout the other cells.
c. there are blood vessels throughout the lung cells
function: the cells form gaps in between for the purpose of flexibility and being able to hold oxygen. lungs need to expand and contract to take in air.
the blood vessels and blood cells are present because blood flows through the lungs to become oxygenated.
Can one organ be formed from the cells of another?
From looking at the cells, we noticed a lot of similarities, but we think cells are specialized to organize themselves in a certain pattern depending on what organ they make up. As a result, cells from one organ can't rearrange themselves to form another.
testes! ovaries! heart! Name: jodie and Date: 2002-11-20 14:43:01 Link to this Comment: 3813 |
Testes: There are three different kinds of cells we observed in the testes. The first kind, oblong in appearance, seem to be spread between the main cell groups. These cell groups are themselves made up of two kinds of cells. One of these forms a boundary for the cell group; the other is contained within the group. It's like one of those balloons with confetti inside. (See Figure 1.1.) You know. The balloon and the confetti make up the "cell group," but the balloon is made up of one kind of "cell" and the confetti is made up of another kind of "cell." The second cells, which are the balloon cells, are sort of rectangular, with the nucleiaeouii toward the outside. The confetti cells are actually sperm cells, some of which appear different since they regenerate every 70 days. they are basically little spikes of color with bluriness around them. ha ha! and so, we conclude that the testes have three different types of cells.
Fig 1.1 : A confetti filled balloon. The confetti would be one kind of cell, and the balloon would be another.
Ovaries: The ovaries are very special to us. We have them, after all. (One of us also has testes, but we're not going to tell you who. Guess.) The structure of the cells within the ovaries is similar to that of the testes. We have determined that there are indeed three different types of cells contained within these wondrous little organs. The first type (which resembles the first type described in the testes) is also oblong in nature, with a stringy-seeming consistency and visible nucleeeeeaauoui. There is another balloon-like structure with cells that form the "balloon" and cells that form a sort of "toy" inside. (See Fig 1.2.) (IT'S A BOY! but it's actually a girl. ovaries. get it?) The cells in the middle have four layers. The outside layer looks like a bunch of nucleaeauai, possible cells that will eventually become fully-formed egg cells. The next layer is like the shell, containing the "egg white" and the "yolk" inside of it. (The nucleus is the "yolk," the "egg white" is the "stuff" surrounding it.)
Fig 1.2: A balloon with toys inside. Imagine it with only one toy. The toy would be one kind of cell, and the balloon would be another.
Heart: The outer layer of the culture is made of of small, dark cells. Inside this boundary, there is mostly one kind of cell, which has a rather indefinate form and are all irregularly shaped. They all seem to be "flowing" in one direction. There is a "chamber" in the heart full of blood cells, a third type of cell. These "chambers" are bound by the same type of cell that bounds the whole culture (the small, dark ones). Thus, we conclude that the heart has three clear different types of cells, probably more.
Fig 1.3: A heart. (Not anatomically correct.)
examining cells (your mom) Name: Mer, Chel, Date: 2002-11-20 14:49:27 Link to this Comment: 3814 |
Pig liver: At least magnification there appear to be two different types of cells. There appear to be purple veins intersecting the pink portion of the cells. The smaller of the two (orange colored cell) seems to be surrounded by the bigger (pink colored cells) appearing as pistol surrounded by petals.
After increasing the magnification by one level, there appear to be three differnet types of cells: The original pink cells, the orange cells in the middle and other smaller pink colored cells separating the orange and pink cells from each other. They fit in perfectly into the mold. It is possible that this is just a lumen filled up with somthing other than cells. At this magnification the size differences become clearer and the small orange cells in the middle are visibly smaller compared to the others than we first assumed.
After increasing the magnification by another level, there appear to clearly be no more than two differnet types of cells: The pink cells surrounding the orange centers. The pink mass inbetween the two, that we thought might be another type of cell, has turned out to be white instead and a clear lumen.
Kidney, non-med: At least magnification there appear to be three differnet types of cells. There are big pink masses that look like cells, orange cells pulled in oval circles and smaller pink cells that have lumen in their centers.
At greater magnification there seem to still be three different types of cells but the arrangement becomes clearer. It seems that the cells are within each other starting with the small pink ones that at this magnification look like thumb prints with a white hole in the middle, the next circle are the orange cells and these are in turn surrounded by the huge pink mass we discribed earlier.
At even greater intensity the orange mass we assumed to be another type of cell resembles blood vessles instead. We believe now that there are only two different types of cells in the kidney. There is a light pink mass that is clearly a cell type (with white lumen all throughout the mass) and a deeper pink colored cell type that is stringy.
Spinal cord: At least magnification there appear to be three different cell types. There is a cell type in the middle that is surrounded by a great space of nothing. Further out, there is a cell type that is shaped like a butterfly. This cell is surrounded by a mass of less intense pink almost orange color. This massive cell type is of oval shape.
At greater magnification there appear to be three different types of cells. There is the small pink cell in the middle surrounded by lumen, the dark pink cell type and the pink cell typ on the outside. The second cell type from the inside is very dense compared to the outside cell type is spaced out with little "buds" connected by longer cells of the same type.
We believe that it is possible to form one organ from the cells of another organ. There were some cells in the liver that look like they could be closely related to the cells of the kindey and vise versa. But, in comparing the liver or kidney cells to the spinal cord cells, it is more than apparent that the spinal cord cells are completely different. Whereas the liver and kidney cells were boxish of different shapes and sizes, the spinal cord cells were bunched, almost as if being "baby's breath." We think that the budding is conducive to transfering information, but we would need more testing to be positive.
Cells, cells, everywhere Name: Will and E Date: 2002-11-20 14:50:10 Link to this Comment: 3815 |
Testes:
The sample provided us with a cross section of the many tubes that make up the testes. There seemed to be two types of tubes, with some cells within a tube and empty tubes.
There were five types of cells we identified in the testes:
1) The "divider cells" as we called them, formed a divider between the two type of tubes. These cells were streaky and surrounded the main tubes.
2) The first type of tubes (the ones which contained another type of cells), irregularly shaped, generally bigger than the other tube cells.
3) Sperm cells, the cells within one of the types of tubes. We were able to indentify the flagellum of the sperm.
4) The border of the sperm-filled tubes were of a different type, many of which had chromosomes in the process of replicating.
5) The final type of cell was another type of tube that was not filled with anything. Rather, these cells were in the midst of mitosis AND meiosis, whoa. These were developing sperm cells, and therefore look like a different type of cell.
Spinal cord:
"The spinal cord looked stupid" - Erin Myers
"I wish we had tails" - Will Carroll
The cell was ovular with an x-shape of a different cell type and a lumen space in the center, with a border of similar cells to the x-shape.
Two kinds of cells:
1) The cells not in the x-shape are spongey and irregularly shaped.
2) The cells in the x-shape and along the border are "super small" and more densely packed in a longitudinal pattern.
There are also vein-like things running through the less densely packed cells that oringinate in the center of the cell.
examining cells (your mom) Name: Mer, Chel, Date: 2002-11-20 15:08:46 Link to this Comment: 3816 |
Pig liver: At least magnification there appear to be two different types of cells. There appear to be purple veins intersecting the pink portion of the cells. The smaller of the two (orange colored cell) seems to be surrounded by the bigger (pink colored cells) appearing as pistol surrounded by petals.
After increasing the magnification by one level, there appear to be three differnet types of cells: The original pink cells, the orange cells in the middle and other smaller pink colored cells separating the orange and pink cells from each other. They fit in perfectly into the mold. It is possible that this is just a lumen filled up with somthing other than cells. At this magnification the size differences become clearer and the small orange cells in the middle are visibly smaller compared to the others than we first assumed.
After increasing the magnification by another level, there appear to clearly be no more than two differnet types of cells: The pink cells surrounding the orange centers. The pink mass inbetween the two, that we thought might be another type of cell, has turned out to be white instead and a clear lumen.
Kidney, non-med: At least magnification there appear to be three differnet types of cells. There are big pink masses that look like cells, orange cells pulled in oval circles and smaller pink cells that have lumen in their centers.
At greater magnification there seem to still be three different types of cells but the arrangement becomes clearer. It seems that the cells are within each other starting with the small pink ones that at this magnification look like thumb prints with a white hole in the middle, the next circle are the orange cells and these are in turn surrounded by the huge pink mass we discribed earlier.
At even greater intensity the orange mass we assumed to be another type of cell resembles blood vessles instead. We believe now that there are only two different types of cells in the kidney. There is a light pink mass that is clearly a cell type (with white lumen all throughout the mass) and a deeper pink colored cell type that is stringy.
Spinal cord: At least magnification there appear to be three different cell types. There is a cell type in the middle that is surrounded by a great space of nothing. Further out, there is a cell type that is shaped like a butterfly. This cell is surrounded by a mass of less intense pink almost orange color. This massive cell type is of oval shape.
At greater magnification there appear to be three different types of cells. There is the small pink cell in the middle surrounded by lumen, the dark pink cell type and the pink cell typ on the outside. The second cell type from the inside is very dense compared to the outside cell type is spaced out with little "buds" connected by longer cells of the same type.
We believe that it is possible to form one organ from the cells of another organ. There were some cells in the liver that look like they could be closely related to the cells of the kindey and vise versa. But, in comparing the liver or kidney cells to the spinal cord cells, it is more than apparent that the spinal cord cells are completely different. Whereas the liver and kidney cells were boxish of different shapes and sizes, the spinal cord cells were bunched, almost as if being "baby's breath." We think that the budding is conducive to transfering information, but we would need more testing to be positive.
Name: kathryn ba Date: 2002-12-03 14:23:18 Link to this Comment: 3938 |
http://www.radford.edu/~swoodwar/CLASSES/GEOG235/biomes/intro.html
http://earthobservatory.nasa.gov/Laboratory/Biome/
http://curriculum.calstatela.edu/courses/builders/lessons/less/biomes/introbiomes.html
Biomes vary with location because of a multitude of environmental differences, such as temperature and precipitation. These factors are directly related to longitude and latitudes, as well as topography.
Different communities are describes most generally in seven different biomes.
1. coniferous forest: temperature = -40-20 C / precipitation= 300-900 mm/year
2. temperatue decidous forest: temp= -30 - 30 C / precip = 750-1500 mm/year
3. Desert: temp= -3.9 -38 c / precip= 250 mm/year
4. grassland: -20 -30C / precip 500-900 mm/year
5. rain forest: 20 -25 C / precip= 2,000-10,000 mm/year
6. shrubland: 20- 10 C / precip= 200-1,000 mm/year
7. tundra: -40-18C / precip= 150-250 mm/ year
Biomes are subject to change due to deforestation, global warming, and climate change. A typical progression is from forest to grassland to desert.
Aquatic Biomes Name: Date: 2002-12-03 14:37:04 Link to this Comment: 3939 |
We chose to compare the different aquatic biomes on Earth. There are two main categories: marine and freshwater.
Marine: Covers 75% of the Earth. Is comprised of oceans, coral reefs and estuaries. Within the ocean there are different zones (each zone supports a different series of flora and fauna).
The tidal zone has a lower diversity because the wave action disrupts the area from becoming a stable habitat. Shorebirds will come to feed on what is washed up. The shorebirds will vary on what part of the world you are in: in Alaska, you might find bird like puffins which are adapted to the cold water, while in Florida a heron or egret will be easier to find.
The pelagic zone (farther out into the ocean) is home to whales, dolphins and other large marine species (as well as lots of plankton!)
The benthic zone hosts primarily bacteria and fungi.
The deep sea, or abyssal zone, is very cold yet supports a great biodiversity near mid-oceanic ridges (thermal rifts which heat the nearby water, as well as provide nutrients).
Closer to the surface, coral reefs surround islands in the tropics. They are home to many different plants and animals. A single reef can support a diverse population.
The final marine category is estuaries, which is where rivers meet the ocean. The mixture of fresh and salt water creates an enviornment for unique species of trees, birds and other wildlife.
Freshwater: Must have less than 1% salt content, and is divided into ponds and lake, streams and rivers, and wetlands (this last category is controversial).
Ponds and lakes have a lower biodiversity because they are isolated environments. Within a single pond or lake there will be many species of fish, birds and amphibians. Species will vary from one lake/pond to another. Fish species vary because they cannot transplant themselves between isolated bodies of water (they [or their eggs] must be carried by birds). The birds will vary from lake to lake because of their mating habits and climatic differences. You're not gonna find a flamingo in Minnesota.
The next sub-division is streams and rivers. These offer more diversity, but it depends on the type of stream (meandering, braided, etc.) and how turbid the water is. If the water is full of sediment, it will block sunlight (therefore block plant growth), but will offer habitats for fish like catfish. The diversity of a stream/river will increase towards the center of the channel. Along the edge, other wildlife will venture into the water to drink or eat.
The third category is wetlands. Wetlands are home to acquatic plants known as hydrophytes. Wetlands are placed in neither the freshwater nor the marine category, since both saltwater and freshwater wetlands exist. This difference alone will vary the biodiversity between each wetland.
a few links:
http://www.ucmp.berkeley.edu/glossary/gloss5/biome/aquatic.html
http://www.worldbiomes.com/biomes_aquatic.htm
Communities Name: Amanda Mac Date: 2002-12-03 14:48:52 Link to this Comment: 3940 |
Hot and Dry:
"Canopy in most deserts is very rare. Plants are mainly ground-hugging shrubs and short woody trees. Leaves are "replete" (fully supported with nutrients) with water-conserving characteristics. They tend to be small, thick and covered with a thick cuticle (outer layer). In the cacti, the leaves are much-reduced (to spines) and photosynthetic activity is restricted to the stems. Some plants open their stomata (microscopic openings in the epidermis of leaves that allow for gas exchange) only at night when evaporation rates are lowest. These plants include: yuccas, ocotillo, turpentine bush, prickly pears, false mesquite, sotol, ephedras, agaves and brittlebush.
The animals include small nocturnal (active at night) carnivores. The dominant animals are burrowers and kangaroo rats. There are also insects, arachnids, reptiles and birds. The animals stay inactive in protected hideaways during the hot day and come out to forage at dusk, dawn or at night, when the desert is cooler."
Cold Desert:The winters receive quite a bit of snow. The mean annual precipitation ranges from 15-26 cm. Annual precipitation has reached a maximum of 46 cm and a minimum of 9 cm. The heaviest rainfall of the spring is usually in April or May. In some areas, rainfall can be heavy in autumn. The soil is heavy, silty, and salty. It contains alluvial fans where soil is relatively porous and drainage is good so that most of the salt has been leached out.
The plants are widely scattered. In areas of shad-scale, about 10 percent of the ground is covered, but in some areas of sagebush it approaches 85 percent. Plant heights vary between 15 cm and 122 cm. The main plants are deciduous, most having spiny leaves. Widely distributed animals are jack rabbits, kangaroo rats, kangaroo mice, pocket mice, grasshopper mice, and antelope ground squirrels. In areas like Utah, population density of these animals can range from 14-41 individuals per hectare. All except the jack rabbits are burrowers. The burrowing habit also applies to carnivores like the badger, kit fox, and coyote. Several lizards do some burrowing and moving of soil. Deer are found only in the winter.
Comparision:
We found that there were many similar animals in both hot and cold deserts which led us to conclude that the harsh conditions and ground brush found in both deserts may make the similarties; such as the kangaroo rats and burrowing predaters. Differances amongst the two desert creatures may be attributed to the homogenous climate of the hot and dry desert to the variations in hot and dry to the cold and moist. This is demonstrated by teh deer that exist in the cold desert during the winter times. We found that these deer most likely leap down the surrounding mountains - as cold deserts are nestled betwixt mountain ranges- when the climates of the mountain become too cold on the tipey tops. Thus, the location of the desert affects whether or not the desert is cold or hot, and also affects teh surounding locations such as teh mountains aroudn the cold desert.
The "bo...real" forest Name: KKS Date: 2002-12-03 14:52:19 Link to this Comment: 3941 |
Web Sources
http://www.ucmp.berkeley.edu/glossary/gloss5/ biome/forests.html#boreal
http://www.borealnet.org/overview/whatistheboreal.html
http://www.borealnet.org/overview/whataretheproblems.html
http://www.borealnet.org/overview/whycare.html
In the boreal forest temperatures are generally very low and little precipitation in the form of snow. The plant population is composed of "cold-tolerant evergreen conifers with needle-like leaves like pines, firs, and spruces. The lack of floor vegetation, apart from fungi, is because the canpoy of these trees allows low light penetration so it's difficult for floor or "understory" plants to grow.
The boreal spatial arangement is effected by humans logging the trees for paper and drilling for oil.
Before people tree arangement looks like:
aghe;wagn;asn
a;genaoighwaoi
nage;owingaeio
angeo;inae
After people:
B B B B
B B B B
B B B B
In this "emerald halo" there are five thousand species of fungi. This is possible because they are able to grow without so much sunlight. The presence of fungi relates to the fauna population that in addition to woodpeckers, hawks, moose, bear, weasel, lynx, fox, wolf, deer, hairs, munks, and bats, includes squirrels that eat the fungi and spread the spores.
Obviously there is reason behind the spatial array of the boreal forest.
BIOMES Name: marybeth y Date: 2002-12-03 14:57:43 Link to this Comment: 3943 |
in our search, we found that "biomes" are basically the different types of ecosystems found on the earth. the most inclusive list we found is as follows:
rainforest, tundra, taiga, desert, temperate, grasslands, rivers & streams, ponds & lakes, wetlands, shorelines, temperate oceans, and tropical oceans.
examples for each and explanations:
rainforest - there are actually 2 types of rainforest, temperate and tropical. we will focus on tropical as it is the more well known of the two. some characteristics is that they are warm and moist and very green with a large array of diverse plant and animal life. in fact, half of the earth's plant and animal species are found in the tropical rainforests of the world.
tundra - characterized by being fairly stark and barren, year-round. short cool summers, long cold winters. plants grow low to the ground. animals breed fast and are well adapted for the extremely cold conditions, and many animals even hibernate during hte winter months
taiga -this biome stretches across a large portion of the world. in fact, it is the largest biome in the world. winters are cold. summers are warm. lots of conifers grow here. snow, cold, and a scarcity of food make life very difficult, especially in the winter. some taiga animals migrate south, others go into hibernation, while others just cope. the taiga is characterized by having larger numbers of hte same plant and animal species - i.e. much less diveristy than a tropical rainforest
desert - There are 2 main types of desert, hot and cold. both get very small amounts of precipitation. Only difference is that cold deserts main form of precipitation is snow, and for warm deserts it's rain. deserts have more plants and animals than people think. in fact, deserts are second only to tropical rainforests in the variety of plant and animal species that live ther
temperate - temperate climates are those in which there are defined seasons with significant rainfall, just slightly less than that of a rainforest. These areas are also characterized by the presence of deciduous forests and significant coverage by wooded areas. Bryn Mawr, and much of the United States are located in temperate biomes.
grasslands - Grasslands are typified by low, ground-covering plant life, such as grasses and shrubs. Grasslands are generally located in plains, valleys, and other flat landscapes. The Midwestern United States praries are a kind of this grassland environment.
rivers & streams - Rivers and streams are one of the primary habitats for aquatic life on earth. Rivers and streams are the homes and breeding grounds for many species of fish, plantlife, amphibians, and others. These waterways are also vital to the suvival of many land species for drinking and bathing.
ponds & lakes - Ponds and lakes are also the homes of countless fish and animals, but are also hugely important for aquatic plantlife. The stillness of the pond and lake setting is ideal for kinds of algae and others to form on the surface of the water. Again, these bodies of water are important for the survival of surrounding land species, as well.
wetlands - Wetlands are marshy landscapes that can range from swamps to bogs. Wetlands are key in the sustenance and reproduction of many bird species, as well as some tall grasses and plants. Wetlands also play a key role in the maintenance of the ecosystem in that they often act as a kind of filtration system for the waters before they move on to rivers, streams, ponds, lakes, and oceans.
shorelines - Shorelines are another aquatic habitat for many shellfish, insects, and grasses, among others. The Shoreline is an environment that is always changing, and quickly. Therefore, all species who live in this habitat are mobile, or firmly attached to the earth or rocks, such as deeply rooted grasses, and barnacles.
temperate oceans - Temperate oceans share seasons like those familiar to us. These marine habitats are home to both the largest and smallest species known to man.
tropical oceans - Tropical oceans are most frequently characterized as the homes of coral reefs. These bodies are located in the south Pacific and Indian Ocean.
http://mbgnet.mobot.org/
Each of these ecosystems has a very distinct array of lifeforms because the climates have affected the evolution of these species. They've adapted to contend with the different challenges posed by each of these habitats.
Name: Maggie and Date: 2002-12-03 15:02:18 Link to this Comment: 3944 |
We were interested in comparing the different types of forest biomes. 3 different forests exist, Tropical, Temperate (Decidious), and Boreal (Tiaga). We concentrated on Temperate and Boreal forests with the hope of understanding more about biomes and biological communities.
According to http://www.ucmp.berkeley.edu/glossary/gloss5/biome/,
"the world's major communities, classified according to the predominant vegetation and characterized by adaptations of organisms to that particular environment"
In other words, different animals (and plants and insects) live in different environments. The type of climate and vegetation highly influence the type of organisms inhabiting a biome.
http://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.html suggests that different animals live in different areas because of the weather conditions. Animals must adapt to live in their environment - after living in one particular climate for so many years, their systems become accustomed to the fluctuations of one particular biome.
In fact, all of the changes that differentiate one type of biome from another are directly responsible for the varying organisms living within. For example, Boreal forests do not let a lot of sunlight reach the understory layers of the forest; therefore, only plants thta do not require large amounts of sunlight can live there. It is a codependent environement: the plants live in a particular biome because of the climate, and the animals live in a biome because of the plants. Therefore, the climate is responsible for all living organisms within a biome.
Below are the key differences between a Temperate forest and a Boreal or Tiaga forest.
Temperate:
*well defined seasons with distinct winter
*soil is very fertile
*canopy is moderately dense and allows some light to penetrate through to the forest floor
*flora: about 3-4 species for every square kilometer.
According to http://www.enchantedlearning.com/biomes/:
*Fall Colors: In the Fall, the number of hours of daylight decreases. This causes some plants and trees (called deciduous) to stop producing chlorophyll (a green pigment that converts sunlight into chemical energy) and eventually lose their leaves. During this time, these leaves turn brilliant colors, ranging from red to orange to yellow to brown.
*Soil: The soil in the deciduous forests is quite fertile, since it is often enriched with falling leaves, twigs, logs, and dead organisms.
Layers of the Temperate Deciduous Forest: There are five layers (also called zones or strata) in the temperate deciduous forest. These include the:
* Tree stratum, the tallest layer, 60 -100 feet high, with large oak, maple, beech, chestnut, hickory, elm, basswood, linden, walnut, or sweet gum trees.
* Small tree or sapling layer - short tree species and young trees.
* Shrub layer - shrubs like rhododendrons, azaleas, mountain laurels, and huckleberries.
* Herb layer - short plants.
* Ground layer - lichens, clubmosses, and true mosses.
Boreal or Tiaga
*short, moist, warm summers, and long, cold, dry winters.
*soil is thin and acidic, is rocky and has deep gorges often frozen over with water.
*canopy is thick and allows almost no light to reach understory
*flora is comprised of only cold-tolerant evergreens
*taiga, also called a boreal forest or northern coniferous forest, is a cold woodland or forest. This biome span the northern parts of North America, Europe, and Asia. Taigas are generally located south of tundras and north of temperate deciduous forests and temperate grasslands. The taiga is the largest land biome on Earth, covering about 50 million acres of land (20 million hectares); this is about 17% of the Earth's land area. Taiga is a Russian word for marshy pine forest.
*The taiga is characterized by a cold, harsh climate, a low rate of precipitation (snow and rain), and short growing season. There are two types of taigas: open woodlands with widely spaced trees, and dense forests whose floor is generally in shade.
*Taigas are relatively low in animal diversity because of the harsh winters. Some taiga animals are able to cope with the cold winter environment, but many migrate south to warmer climates during the winter and others go into hibernation.
Because of the temperate climate, fertile soil, moderate canopy, and sunlight, a plethora of animals and other organisms inhabit a Temperate forest. Whereas the Boreal forest has little sunlight and extremely cold temperatures, the organisms and animals living there are less in number.
Studying forests is very important for the advancement of mankind. Potential medicines and undiscovered plant speicies could exist. The trees seem to exist as a buggering agent for the ozone layer and the effect of global warming. And because all of the organisms within the forests have evolved together, the resulting biome is interdependent.
Name: Date: 2002-12-03 15:07:48 Link to this Comment: 3945 |
2.www.ucmp.berkeley.edu/glossary/gloss5/biome/
3.www.emc.maricopa.edu/faculty/farabee/BIOBK/Biobookcommecosys.html
4.www.pbs.org/wgbh/evolution/library/04/1/1_041_01.html
5.www.scu.k12.ca.us/pomeroy/1st/Animals.html
Groups of organisms live together because they are adapted to live with each other. An example of this is the food web, where organisms are interedependent and are adapted to eat what is available to them. It is also important that the food web is not disrupted by one organism not being too overly preyed upon. Groups of organisms occur in different locations because of the limitations of their geography and because of their specific adaptations. Certain organisms depend on others with which they live to create the environment in which they need to survive.
Christine Traversi
Margot Rhyu
Sarah Tan
dessert biomes Name: Joanna Rob Date: 2002-12-03 15:17:47 Link to this Comment: 3947 |
Desert Biomes
Desert Biomes are the final stage of a biome. Due to global warming and climate change. The Biome cycle starts with aquatic to forest, grassland, and finally deserts. Desert biomes differ according to location. There are four different types of deserts that vary in temperature and location.
Hot and Dry
temps on average range from 20-24c. They are located inthe lower latitudes of North America.
Semiarid
Temps on average range from 20-24c. They are located in the basins of America, for example in Utah. The Semiarid deserts are similiar to hot and dry deserts.
Coastal
Temps on average range from 13-20c They are located on the coast of chile.
Cold
Temps range from -2-4c. They are located in colder climates, such as Greenland. Cold deserts has precipatation due to snowfalls. As a result there are plant life and animal life as such as deers and rabbits. Opposed to the other 3 which contains lizards.
In general the mortality rate in desert Biomes are higher than Rain forest. In hot and dry deserts plants absorb and store water becuase there is a lack of rainfall.
http://www.ucmp.berkeley.edu/glossary/gloss5/biome/deserts.html
http://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.htmlhttp://www.cotf.edu/ete/modules/msese/earthsysflr/biomes.html
tropical rainforests Name: Date: 2002-12-04 14:16:40 Link to this Comment: 3955 |
We decided to investigate the climate and environment of rainforests.
Tropical rainforests are complex ecosystems, which are made up of four distinct environments. These "sub-ecosystems" are referred to as levels. In each level, animals and plants have adapted to the existing environmental conditions. The different levels are: the emergent level, the canopy, the understory, and forest floor.
Tropical rainforests are spread over the Americas, Africa , Asia and the Caribbean with the largest portion found in Puerto Rico and Trinidad.
Lush vegetation, rainfall througout the year and a high temperature make the rainforest one of the world's most diverse ecosystems.
Rainforests are a product of planetary processes and are - in turn - contributors to the water and carbon cycles on which all life depends. Rainforests control climate by influencing wind, rainfall, humidity and temperature. They recycle water, oxygen and carbon which reduces soil erosion, flooding and air pollution.
More than 65 million years old, rainforests are the oldest major vegetation types on Earth. Fossil records show that the forests of Southeast Asia have existed in more or less their present form for 70 to 100 million years.
Certain environmental conditions must be present in order for the delicate balance of rainforest to be held intact. There must be substantial rainfall (at least 80 inches) of rain each year, but many rainforests receive in excess of 200-300 inches annually.
Because rainforests are in tropical areas, they have a very hot, wet climate. Temperatures can be above 24 degrees centigrade all year round and rainfall levels can be up to 2,400mm a year.
The soil in the rainforest is 4 inches deep with a layer of clay beneath, hence trees have shallow roots.
A variety of living organisms at all different sub-ecosystems exist in the rainforests. Tropical rainforests contain more than half of the Earth's plant and animal species, yet cover only about 7% of the earth's land surface. A typical forest in the United States contains from 5 to 12 different kinds of trees, while a typical rainforest may have over 300 different kinds. If the rainforests are destroyed, most of these plant and animal species will be lost forever. The different species of plants and animals along with microscopic living organisms co-exist in their own way in the rainforests. In just four square miles of some Rainforests you might find over 750 species of trees, 1500 types of flowering plants, 125 different kinds of mammals, 400 different birds, 100 reptiles, 65 amphibians, and a staggering number of insects. One quarter of today's pharmaceuticals come from Tropical Rainforest plants.
The Amazon Rainforest is the richest biological incubator on the planet. It supports millions of plant, animal and insect species - a virtual library of chemical invention. In these archives, drugs like quinine, muscle relaxants, steroids and cancer drugs are found. More importantly, are the new drugs still awaiting discovery - drugs for AIDS, cancer, diabetes, arthritis and Alzheimer's. Thus it is very clear that the rainforests are a major part of life on earth and all living organisms are dependent on this biome in some way or another.
Loss of these incredibly diverse forests would be a serious loss for people everywhere. The loss of thousands of acres of tropical rainforests is already causing serious local problems, including increased soil erosion and water pollution. As more deforestation occurs, the problems will increase.
People don't have the right to destroy the world's rainforests and other habitats for their own purposes.
IDEA: Further investigation can be carried out on the differences between tropical and temperate rainforests.
WEB REFERENCES:
http://www.animalsoftherainforest.org/map.htm
http://www.orecity.k12.or.us/ogden/BBBeck/TropicalRainforest.html
http://www.stemnet.nf.ca/CITE/rainforest_what.htm
Name: Rosie, Ana Date: 2002-12-04 14:19:20 Link to this Comment: 3956 |
The climactic charactetic he arctic are cold, windy temperatures, and often snowy biomes. Dry air, wind, and snow are part of the climate. 90% of the land area is covered with hardy, cold-and-dry vegetation. Animals that live in the Arctic are adapted to extreme conditions. Those with coats, have coats that thicken and change color to white in order to be camoflouged with the snow. Many animals also hibernate.
desert life Name: Brie Miche Date: 2002-12-04 14:31:37 Link to this Comment: 3957 |
There are four different types of deserts. They vary in
temperature and location.
Hot and Dry
20-24c. Lower latitudes of North America.
Semiarid
20-24c. Basins of America (Utah). Similiar to hot and dry deserts.
Coastal
13-20c. Coast of chile.
Cold
-2-4c. Colder climates (Greenland). Cold deserts have precipitation due to snowfalls. Plant life and animal life exists.
Plants and Animals have adapted to these extreme desert climates. The lack of water creates a survival problem for all desert organisms, so they have evolved behavioral and physiological mechanisms to avoid excess heat, dissipate heat, retain water, and acquire water.
To avoid heat , many animals (especially mammals and reptiles) are active only at dusk and again at dawn. Likewise, many animals are completely nocturnal, restricting all their activities to the cooler temperatures of the night. Bats, many snakes, most rodents and some larger mammals like foxes and skunks, are nocturnal, sleeping in a cool den, cave or burrow by day.
To dissipate heat , many desert animals are paler than their relatives elsewhere in more moderate environments. Pale colors may be seen in feathers, fur, scales or skin. Pale colors not only ensure that the animal takes in less heat from the environment, but help to make it less conspicuous to predators in the bright, pallid surroundings.
Some animals retain water by burrowing into moist soil during the dry daylight hours (all desert toads). Some predatory and scavenging animals can obtain their entire moisture needs from the food they eat (e.g., Turkey Vulture) but still may drink when water is available.
Acquiring water in the desert is a challenge. Kangaroo Rats, for example, live in underground dens which they seal off to block out midday heat and to recycle the moisture from their own breathing. They also have specialized kidneys with extra microscopic tubules to extract most of the water from their urine and return it to the blood stream. Much of the moisture that would be exhaled in breathing is recaptured in the nasal cavities by specialized organs.
Thousands of animal species exist in the desert. Obviously, the extreme conditions have created a need to evolve and adapt their needs to the environment. Desert animals are characteristic to this environment because if these animals were relocated, they would have no need for these specializations. Their adaptations would be detrimental in a different environment. If a desert animal was relocated to a tropical environment, retaining water might result in drowning. Pale coloring that helps to dissipate heat in the desert would make the animal a target in a darker, greener biome.
Plant Life in Deserts
Most desert plants are succulents, meaning they store water to survive the dry, hot, desert climates. One of the most well known species of desert plants is the cactus. The Saguaro Cactus has grows in a dry hot desert climate. It's waxy skin helps it keep water in. When it rains, the Saguaro Cactus soaks up water and holds it in its ribs. The ribs on the plant expand to absorb a lot of water. The plant itself does not need a lot of water to survive. It depends on heavy winter precipatation. During dry periods, the Saguaro Cactus uses water it has stored. The Saguaro has a very special root system. It has two sets of radial roots, a thick set about one foot long, and a thinner set which is often as the same length as the height of the cactus itself. The Saguaro, like many other species of Cactus, has 3-4 inch spines to protect it from predators. In addition to protection from predators, these spines help cool the outer skin of the plant, as well as redirect the wind and insulate the outer skin of the cactus. The Saguaro typically flowers at night when it is cool. Animal and insect species that live in the same environment are: long-nosed bats, bees, wasps, ants, butterflies, and some small rodents, like pocket mice.
For More information:
Mojave Desert
Desert Plants
Desert Animal Survival
Desert Biomes
Organisms live in characteristic environments. Desert Life is related by certain adaptations to their environment. Therefore, if life from other climates and conditions were relocated to the desert, they would not survive.
Tundras Name: Date: 2002-12-04 14:40:19 Link to this Comment: 3959 |
In investigating websites on the ecosystem known as the tundra, we found observations which show organisms which are interdependent and existing in specific, cooperative communities. This system of organisms, like other systems which we have studied, exhibits a quality of being substantially influenced by the physical conditions in which it exists. The thick protective fur pocessed by the musk ox of the tundra is one instance of the relationship between organisms and the physical conditions under which they live and have evolved. It's fur is composed of two layers: an outer protective layer and an under layer which is nearly waterproof (The Tundra Biome). Examples of the interdependence of organisms includes the presence of lichen in the tundra, which then provides sustinence for caribou and musk ox (Tundra Plants).
The teperature in the tundra tends to range from -40 to 18 degrees celcius (Earth Observatory Tundra). The ground is permanently frozen -- permafrost (The Tundra Biome), and thus soil in a form useable by plants only exists in small clumps, like in cracks between rocks. The bacteria that can survive in such conditions in turn enables specific low-growing shrub-like plants to grow.
It can be infered that, as tundra organisms have developed under similar conditions (i.e.: those of extreme cold and little moisture) they have also developed to be dependent upon those things which are available under those conditions, leading them to evolve into interdependent communities.
biomes: tundra vs. grassland Name: Laura B. a Date: 2002-12-04 14:42:39 Link to this Comment: 3960 |
Biomes: Arctic Tundra vs. Grasslands
Brought to you by: Laura Bang and Adrienne Wardy
Arctic Tundra | Grasslands | |
Average Temperatures | -34 degrees Celsius in winter; 3-12 degrees Celsius in summer | as low as -40 degrees Celsius in winter; higher than 38 degrees Celsius in summer |
Yearly Precipitation | 15-25 cm | 50.8-88.9 cm |
Characteristics | ||
Location | The Arctic regions of the Northern Hemisphere | Veldts of South Africa; puszta of Hungary; pampas of Argentina and Uruguay; steppes of former Soviet Union; plains and prairies of central North America |
Plant Life | About 1700 kinds of plants: low shrubs, sedges, lichen, reindeer mosses, liverworts, grasses; about 400 varieties of flowers | Lots of different kinds of grass; very few tall shrubs and/or trees, although there are some trees in river valleys |
Animals | lemmings, wolves, caribou, arctic hares, foxes, polar bears, ravens, falcons, terns,... | gazelles, zebras, rhinos, wild horses, lions, wolves, prairie dogs, jack rabbits, coyotes, foxes, skunks, badgers, blackbirds, grouses, meadowlarks,... |
For more exciting information about these biomes, go to Biomes.
Not ALL deserts are created equal! Name: Heidi Mer Date: 2002-12-04 14:48:20 Link to this Comment: 3961 |
One of the best known deserts in the world: The Sahara Desert, Africa
Geographical features: Shallow basins, highest point is 11,204 feet, lowest .....point is 436 feet, 25% sand sheets and dunes, underground waterways.
Weather: short to medium length dry and humid conditions.
Two major climates:
.....dry tropical climate: mild and dry winters, hot and dry season, 1 annual temperature cycle, 5 in annual rainfall.
.....dry subtropical climate: annual high temp ranges, cold winters, hot summers, two rainy seasons, 3 in annual rainfall at most.
Vegetation: varied, sparse, include grasses, shrubs, and trees that are .....adapted to unreliable precipitation and excessive heat
Animal life: varied and numerous, gerbil, jerboa, Cape hare, the desert hedgehog, dorcas gazelle, dama deer, Nubian wild, anubis baboon, spotted hyena, common jackal, sand fox, Libyan striped weasel, and the slender mongoose. Variety of birds also exists.
The largest block of ice you'll ever see: Antarctica
Geographical features: 95% ice, 70% of the earth's fresh water is locked .....within this ice
Weather: coldest temp -129F, high winds
Climate: less than 2 in annual precipitations, this makes it a desert.
Vegetation: current tundra cannot have vegetation, fossilized plants have been found from 2 million years ago.
Animals: exist in water and on coastline, includes macaroni penguins as well as other species, albatross, elephant seals and leopard seals as well as other seals, killer whales and right whales as well as other whales, seabirds.
Conclusion: Both the Sahara and Antarctica are technically deserts because they each get very little annual precipitation. However, as noted above, the organisims that live within each desert are obviously different. In the Sahara desert, reptiles are the most obvious difference because being cold blooded, they need to remain in an area that remains warm. The other birds and mammals are found in and around oasises for the most part. The Sahara also consists of two subclimates because of the span of latitude in relation to the equator. Antarctica never has a significant difference in distance from the equator to change the climates.
Antarctica, being almost a complete sheet of ice, is obviously much colder and as a result all of the plants and animals that might live in that climate have a thick layer of fat or other natural protection from the cold. Therefore, the zebra that lives in the Sahara could not live in the arctic and the penguin would probably overheat and die in the Sahara.
Marine Ecology Name: Date: 2002-12-04 14:50:21 Link to this Comment: 3962 |
Name: Date: 2002-12-04 14:53:10 Link to this Comment: 3963 |
Animal Live
The Living Africa
Nature: Antarctica-Life In The Icebox
Forest Biomes Name: Maggie Sco Date: 2002-12-04 14:59:03 Link to this Comment: 3964 |
Characteristics
Tropical
-greatest diversity of species
-occur near the equator, within the area bounded by latitudes 23.5 degrees N and 23.5 degrees S.
-two seasons are present are rainy and dry
-daylight is 12 hours with little variation.
-temperature is on average 20-25° C and varies little
-precipitation is evenly distributed throughout the year, with annual rainfall exceeding 2000 mm.
-soil is nutrient-poor and acidic
-canopy in tropical forests is multilayered and continuous, allowing little light penetration.
-flora (plantlife) is highly diverse, one square kilometer may contain as many as 100 different tree species. Examples include trees (mostly evergreen, with large dark green leaves), plants such as orchids, bromeliads, vines, ferns, mosses, and palms.
-fauna (animal life) includes numerous birds, bats, small mammals, and insects
Tropical forests can be further subdivided based on seasonal distribution of rainfall:
evergreen rainforest has no dry season.
seasonal rainforest has a short dry period in a very wet tropical region
semievergreen forest has a longer dry season
moist/dry deciduous forest has a dry season that increases as rainfall decreases
Temperate
-occur in eastern North America, northeastern Asia, and western and central Europe
-have well-defined seasons with a distinct winter
-moderate climate and a growing season of 140-200 days during 4-6 frost-free months
-temperature varies from -30° C to 30° C.
-precipitation (75-150 cm) is distributed evenly throughout the year.
-soil is fertile, enriched with decaying litter.
-canopy is moderately dense and allows light to penetrate, resulting in well-developed and richly diversified understory vegetation and stratification of animals
-flora is characterized by 3-4 tree species per square kilometer. Trees are distinguished by broad leaves that are lost annually and include such species as oak, hickory, beech, hemlock, maple, basswood, cottonwood, elm, willow, and spring-flowering herbs
-fauna is represented by squirrels, rabbits, skunks, birds, deer, mountain lion, bobcat, timber wolf, fox, and black bear
Temperate forests can be further subdivided based on seasonal distribution of rainfall:
moist conifer and evergreen broad-leaved forests have wet winters and dry summers
dry conifer forests dominate higher elevation zones, have low precipitation
mediterranean forests have precipitation that is concentrated in winter, with less than 1000 mm per year
temperate coniferous have mild winters, high annual precipitation (greater than 2000 mm)
temperate broad-leaved rainforests have mild, frost-free winters, high precipitation (more than 1500 mm) evenly distributed throughout the year
Boreal
-represent the largest terrestial biome
-occur between 50 and 60 degrees north latitudes
-found in the broad belt of Eurasia and North America, two-thirds in Siberia with the rest in Scandinavia, Alaska, and Canada
-seasons are divided into short, moist, and moderately warm summers and long, cold, and dry winters
-growing season in boreal forests is 130 days
-temperatures are very low
-precipitation is primarily in the form of snow, 40-100 cm annually
-soil is thin, nutrient-poor, and acidic
-canopy permits low light penetration, and as a result, understory is limited
-flora consist mostly of cold-tolerant evergreen conifers with needle-like leaves, such as pine, fir, and spruce
-fauna include woodpeckers, hawks, moose, bear, weasel, lynx, fox, wolf, deer, hares, chipmunks, shrews, and bats
Conclusion
Groups of organisms live in the same areas and are associated with each other because they adapted to live in similar environments. Organisms, depending on their specific adaptations, depend on each other and their environment in different ways. The food chain in an example of how animals depend on each other, and plants, in order to live. By looking at the specific information about the three different types of forests, it is apparent that different types of animals and vegetation are found in different environments.
Sources
http://www.enchantedlearning.com/biomes/
http://www.ucmp.berkeley.edu/glossary/gloss5/biome/forests.html
A Tundra Site we made Name: the crew Date: 2002-12-04 15:00:27 Link to this Comment: 3965 |
Anonymity Name: Catherine Date: 2002-12-04 15:27:53 Link to this Comment: 3968 |
Evolution Lab Name: Paul Grobstein Date: 2002-12-09 21:23:18 Link to this Comment: 4019 |
The Game of Life, at http://serendipstudio.org/complexity/life.html
The Prisoner's Dilemna, at http://serendipstudio.org/playground/pd.html
(Pseudo)-Altruism, at http://www.brynmawr.edu/Acads/Biology/Bio101/prot/pseudoaltruism.html - thanks to Ted Wong - REQUIRES Internet Explorer instead of Netscape
Some additional models to play with (also require Internet Explorer):
ANTS Name: Diana Aman Date: 2002-12-10 14:19:53 Link to this Comment: 4024 |
Ants!!! Name: Date: 2002-12-10 14:31:23 Link to this Comment: 4025 |
First, we ran a control run from which to base our hypothesis about ant survival.
Cooperative ants (red): 50
Selfish ants (blue): 1
Probability of altruism: 1
Fidelity: 0
The two populations crossed at 50 time units. The red ant population crashed, while the blue went up to 967 members and reached an equilibrium.
From this we hypothesized that if we increased the initial number of red ants that it would take longer for the blue ant population to overtake them.
Red ants: 100 individuals
blue ants: 1
probabilty: 1
fidelity: 0
The results were the same as the initial experiment, but this time the maximum ant populations were 1019. (first the red, then the blue) Our hypothesis was proved incorrect!
We then messed around with the other controls, to see what the effect would be on the population (we wanted to try and keep the red ants alive).
All experiments were conducted with a 100 red: 1 blue ant ratio
First, reduced the probability of altruism from 1 to 0.
The red ants grew to a population of 988. The blue ants had a small population at first, but died out completely by 300 time units.
Next, we changed the probability to .5 from 1.
The red increased greatly to 1029, then began to decrease rapidly. The blue ants increased and crossed the red ant population at 100 time units. The red ants flat-lined at 130 time units. The blue stabilized at 1029 individuals.
Then, we changed the fidelity to 1 from 0, and put the probabilty back to 1 as well.
The red ants increased to 1018 and stay there. The blue rises slowly, but doesnt get very high. They decrease and eventaully die at 170 time units.
We then changed the fidelity to .5 and kept the probability at 1.
The red went up to 955 individuals. They start to decrease (blue rises) at 100 time units. The two cross at 160 time units. Red ants are gone by 254 time units. The blue ants stabilize at 955 individuals.
Next, we tried the fidelity at 1 and the probabilty at 0.
The red ants increased to 962. The blue ants stay low and die before 100 time units.
This time, we put the fidelity at 0 and the probabilty at .1 units
The red increased to 984; around 250 time units, they dropped. The blue began to rise. Reds decrease some more at 319. Blues rising fast at 400 time units. The blue and red ant populations cross at 502 time units. They stay together (coexisting for a short while) before the red drops and the blue continues to rise (slowly).
Last test, we put both the probability and fidelity at .5 units
The red ant population increased to 987 ants. It stays there until 160 time units, when the population starts to go down. The blue ants stay low until 160 when they start to rise. The populations cross at 210 time units. The red ants are all dead by 400 time units and the blue have levelled off around 990.
When the altruism probabilty was lowered, the red ants were more likely to survive, as well as when the fidelity was increased (this allows altruistic ants to gain energy from each other).
GO ANTS!
prisoners' dilemma Name: Margot "it Date: 2002-12-10 14:48:20 Link to this Comment: 4028 |
Sarah Tan
Yarimee Gutierrez
Margot Rhyu
Strategerie Name: Midgie Date: 2002-12-10 14:57:54 Link to this Comment: 4031 |
We suveyed the different types of strategy involved with the game. Below is an outline:
A. You can cheat the whole time.
You will win only by one coin
B. You can cooperate the whole time.
You will tie
C. You can alternate clicking cooperate and cheating
You will tie
D. You can alternate cheating and cooperating
You will tie
E. You can cooperate the whole time, then anticipate when the "Wizard" will end the game and then jump ahead and cheat just before the game ends. This is risky, and you still only win by five points.
F. You can choose to cheat first since you will automatically benefit by either one coin or five.
After the first time cheating, you can either chose to tie (by going back to cooperating) or only increase by one for the rest of the game (by cheating). If you cheat for the rest of the game and only increase by one, the computer dubs you as "Flirting With An Inconcievably Foul Fate" and therefore not be a very nice person. However, you never get ahead by being nice. (You never fall behind either).
Ultimatley, you can only win by 5 points and the computer will tell you that you can do better. But you really can't.
the life of a prisoner Name: kathryn ba Date: 2002-12-10 14:58:05 Link to this Comment: 4032 |
the improbability of altruistic action Name: KKS Date: 2002-12-10 15:05:35 Link to this Comment: 4033 |
For this lab we came up with the following hypothesis:
(As postulated with The Prisoner's Dilemma:) "The best strategy for a given player is often one that increases the payoff to one's partner as well."
First, we explored The Prisoner's Dilemma by playing the game with four different strategies:
Strategy #1: We competed each time.
The outcome: We had 14 coins, serendip had 9.
Strategy #2: We cooperated each time.
The outcome: We had 36 coins, serendip had 36.
Strategy #3: We cheated the first time and then cooperated for the remaining times.
The outcome: We had the same number of coins that serendip did.
Strategy #4: We cooperated until the last time when we cheated.
The outcome: We had 41 coins, serendip had 36.
This leads us to believe that pure cooperation is not MORE beneficial than our other strategies.
However, since pure cooperation, in this instance, is defined as your ability to increase your oponents ability and not just your own, we began to question the nature of altruistic action.
This led us to the exploration of the (Pseudo) - Altruism Game.
We started out with equal numbers of selfish and altruistic ants, an .5 altuistic probability, and .5 fidelity probability.
The altruistic ants were extinct around 128 time-intervals.
When we kept the alruistic and fidelity probabilities at .5, increased the altruistic population to 100, and decreased the selfish population to 10, the altruistic ants became a minority at 90 time-intervals and were extinct at around 319 time-intervals.
When we increased the fidelity level to 1, kept the probability level at .5, and set selfisth and altruistic ant levels at 50...
the altruistic ants maintained a population comparable to the selfish ants.
Therefore, we disproved our hypothesis. We conclude that it is impossible for life to exist, and therefore evolve, with purely altruistic actions.
The Prisoner's Dilemma showed us that alruistic actions can be beneficial.
However, our experiences with the (Pseudo) - Altruism experiment prove that pure altruism will inevitably lead to extinction. Since life cannot be substained without some selfish acts, it is doubtful that any action in life is void of selfishness.
Name: Rosie, Ana Date: 2002-12-11 14:26:18 Link to this Comment: 4048 |
Alternate cheating/cooperating you can earn a maximum of 5 pts. in two rounds if Serendipity does the opposite of your move.
Cooperate each time, earn maximum of 6 pts. per 2 rounds and then cheat the last round to earn 5 pts. in the end. If both start to cheat you reduce pts. to only one per round.
This only works because you are able to predict the computer's move. Also it is necessary to know when the last round is which is a chance because it is whenever the wizard is tired of playing.
to cheat or not to cheat Name: Heidi & co Date: 2002-12-11 14:40:46 Link to this Comment: 4049 |
Ok. In the prisioners dilemea we must look at the probability of profit. Serendip will mirror your actions, but always starts off cooperating. If you both cooperate, you will each gain 3 coins. If you both cheat, you will each gain one coin. If one of you cheats and the other does not, the cheater gets 5 coins. Simple, right? Here are the possibilites (excluding random cooperation/competition):
1. It seems as if cheating is the most profitable way, but if you cheat you will gain 5 coins. Serendip will then mirror your actions. You will then only gain 1 coin each time unless you decide to cooperate while serendip cheats and come off even in the end.
5 coins
6 coins
7 coins
2. Then maybe cooperation is best. If you do this, you will continue to get 3 coins each and stay tied throughout the entire game. Your overall coinge will be higher than the previous example, but the hightest?
3 coins
6 coins
9 coins
3. Wouldn't it be better to cooperate up until the last moment, when you cheat serendip? This way you would have gotten many more coins than if you had cheated throughout and an extra 2 coins at the end when you cheat.
3 coins
6 coins
11 coins
Which is the best strategy? Is there a best strategy? In the game it seems that you should cooperate until just before the end. The problem with this is that we do not know when the end of the game is. We are not told until some limiting number is reached that we have reached the end of the game. Thus, this theory is not as good as it seemed initially. In real life it seems as if it might be the most profitable overall. However, we can not say that this is the best.
merry christmas. Name: see below. Date: 2002-12-11 14:50:28 Link to this Comment: 4050 |
No matter how much life you start with, whether a small or large amount, the area will be populated evenly, then eventually kill itself out through overcrowding, and then will finally separate itself into separate, sustainable colonies of either three in a line or four in a square or diamond formation. For example, if every spot is populated, every spot dies out in only one time step. Also, if the player begins with isolated squares of four, no changes occur throughout the timesteps, because the colonies are already stable.
There needs to be a certain amount of red squares to supply the green squares with what they need to sustain life. When the green squares compete, only the fittest survive. The problem is that there are a limited number of resources (red squares) to go around no matter how many green squares there are. This gives the smaller, more isolated "colonies" a better shot at survival and sustainability.
The best conditions for life exist in the creation of small, isolated colonies in which there is minimal competition for the limited resources. In fact, this formation, which reconciles the competition versus cooperation issue, is the only viable option for continued sustainability.
ants are better than cows Name: Brie and W Date: 2002-12-11 14:56:02 Link to this Comment: 4051 |
If you begin with 50/50 selfish/altruistic
Altruism Probability (AP) = 1
Fidelity (F) =1
Results: Red took over after 400 units of time.
We repeated this test, and the blue held out for 500 units of time until they all died.
Next...
Population: 50/50
AP=1
F=.5
Results: Blue took over in 75 units of time
Population: 50/50
AP=.5
F=1
Results: Equal for a long time, then blue died off slowly but surely.
Population: 50 selfish/25 altruistic
AP=.5
F=1
Results: Both were steady, with blue higher than red until becoming even, finally red took over and blue died out.
Population: 50/50
AP=0
F=1
Results: Both red and blue rose quickly, but red died out slowly once carrying capacity was reached.
Our first test was successful (selfish died) because all of the reds were cooperating with eachother, while blues could not depend on eachother or anyone else. Whereas reds were able to support eachother and thrive!
In our second test, red ants would get fitness 3/4 of the time, and the blue ants were getting fitness 1/4 of the time, but the blue ants had an advantage because they never had to give up anything, whereas the red ants were supporting both blue and red ants.
Next, this was the same as the first experiment, but it took longer because altruism did not occur as frequently so the red ants were not cooperating as frequently, so they weren't benefitting as frequently.
In our fourth test, we started with fewer reds, so the process was much longer. Each state was prolonged because there were fewer ants to begin with.
Our final test was confusing, because the probabilty of altruism is zero, so noone is giving up anything or sharing, so there should be no advantage and no disadvantage. We expected red and blue to reach steady levels.
Our conclusion is that the only time red ants will win is if Fidelity is 1. The altruism probability just affects the amount of time it will take. Time is also affected by the population.
ANTS Name: Date: 2002-12-11 14:56:17 Link to this Comment: 4052 |
Trials and Tribulations of Altruistic Ants
Trial 1:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 1
Fidelity � 0
Outcome: All blue (Time: 126)
Trial 2:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 1
Fidelity � 0
Outcome: All blue (Time: 202)
Trial 3:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 0
Fidelity � 0
Outcome: Some blue, some red
Trial 4:
Initial-selfish � 1
Initial-altruist � 100
Altruism-probability � 1
Fidelity � 0
Outcome: All blue (Time: 100)
Trial 5:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 1
Fidelity � 1
Outcome: All red (Time:158)
Trial 6:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 1
Fidelity � .5
Outcome: All blue (Time: 200)
Trial 7:
Initial-selfish � 1
Initial-altruist � 50
Altruism-probability � 1
Fidelity � 0
SPATIAL STRUCTURE ON
Outcome: All blue (Time: 100)
All of this data suggests that pseudo-altruism (that is, "altruism" with 100% fidelity) may be the most conducive to domination by the pseudo-altruistic population.
Tit for Tat Name: Laura and Date: 2002-12-11 14:57:22 Link to this Comment: 4053 |
Laura Bang and Adrienne Wardy
We looked at the prisoners' dilemma game. Serendip uses a very simple (and predictable) strategy called "Tit for Tat". Tit for Tat means that Serendip's default first move is to cooperate, and for every move after that Serendip copies the previous move of its opponent. This strategy is very easy to beat because all you have to do is start out cooperating every time, and then at some point to cheat, and from that point to keep on cheating. This leads to a win of 5 points higher than Serendip. The difficult part is anticipating when the "wizard" will decide the game is over, because you have to make your cheating move before that happens, or you and Serendip will tie. The longer you keep cooperating the more coins you will get overall, but no matter what you can only win by 5.
The strategy of "Tit for Tat" is encouraging toward cooperation: its first move is to cooperate, then if you cheat it will cheat too, but once you cooperate again "Tit for Tat" forgives you and cooperates again. However, in order to win, you have to cheat.
This applies to evolution because if we cooperate within and between species, we get more as a whole; but for the most part we act in our own self-interest (trying to win, even though it is only a small win), which leads to survival of the fittest.
cheeeeeeat!!!! Name: Mer and Ch Date: 2002-12-11 14:58:45 Link to this Comment: 4054 |
We decided to play Pirate's Dilemma. First, we tried cooperating each round until the game was over. This resulted in a goodly amount of booty for both players. Then, we decided that cheating is cool, so we cheated until the game was over. Trusting serendip cooperated the first round, giving us 5 more coins-ha! Serendips, unfortunately learns quickly and cheated as well for the rest of the game. We then tried to cheat and then cooperate. Initially the computer cooperated and we cheated, then it cheated and we cooperated and from then on, we both cooperated. We've determined that the computer basis its decisions on what we did in the previous round. Finally, we determined the best way to beat serendip AND have a decent average is to cooperated for approx. 10 rounds, then stab the in the back- bloody landlubbers!!
We then focused on how many rounds we can play all cheating or all cooperating. We found a negligable difference of 1-2 rounds longer in games where we only cooperated. The average number of rounds when only cheating is 10.5, when only cooperating approx. 13 (one time we had 23, go us!).
Given these results, we determined that stabbing the computer in the back after the tenth round was most profitable. We also noted that if we were wrong and the game didn't end, we should continue cheating because, once betrayed, serendip doesn't trust us anymore.
In conclusion, although continually cooperating yields a better average and more coins on average, to beat serendip you must be a blue-blooded, bearded, bastard and cheat at the last minute- harharhar.
Darwin's Voyage Revisited Name: Paul Grobstein Date: 2003-09-09 09:53:29 Link to this Comment: 6386 |
Expeditionary groups have been formed to undertake an initial survey of "plant" life on Nearer and Farther. Their goal is to try and determine the number of different kinds of plant life on each planet without prior presumptions that categories of plant life on Nearer and Farther are necessarily similar to those on Earth.
You are a member of one such expeditionary group. Your group must return with a scheme for categorizing plant life on the planet assigned that is clearly described and yields a definite quantitative result for numbers of kinds of plants on that planet. You may also want to consider why the planet contains the particular number of different plants you describe. Your findings will be presented at a conference on "Diversity in BioSystems: New Findings From Additional Cases", focused on the question of whether "diversity" is or is not a fundamental characteristic of living systems.
Some related readings:
Lab Report for Elizabeth Bryan, Brianna Twofoot, E Name: Elizabeth Date: 2003-09-09 14:44:44 Link to this Comment: 6391 |
Grass:
-No stems
-Comes to a point
-Thin
-Grows close to ground
Trees:
-Produce leaves
-Have dark colored bark
-Have a trunk
-The largest group found
-Found five types
Shrubs:
-Half a knee to stomach height (5'8 ft. person)
-Had 3 to 49 leaves
-Had 2 to 12 parting branches
-No flowers or buds
-Scattered location
-Either oval or pointed extremeties
Leaves:
-Some have holes
-Different shapes and sizes
-Mostly close to trees
Planet Nearer Observations Name: Talia Libe Date: 2003-09-09 14:47:50 Link to this Comment: 6392 |
I. Ground Coverings (3) - direct ground coverage that varied in terms of color and texture
II. Low Proximity to Ground (9) - thick, diverse populations of low growing plants
a) Blade (1)
b) Leaf
i) Singular (1)
ii) Multiple
1) Smooth edged (5)
2) Jagged edged (2)
III. Medium Proximity to Groud (3) - branched entities greater than a foot from the ground
a) Spiked (1)
b) Elliptical (1)
c) Waxed (1)
IV. High Elevation (2) - vegetation greater than six feet from the ground
a) Smooth base/vertical branching (1)
b) Ridged base/horizontal branching (1)
Total Plant Types Found: 17
Again, while we recognize that this is not an all-inclusive list, this scheme provides a basis for the categorization of vegetation found in Nearer.
This system, the Planet Nearer, offered an example of the diversity which can be found in a given area in terms of energy sources and stage of growth. Both aspects are elements which attribute to the diversity and variation among the vegatation of the same type.
Message 6392 Talia Liben, Abby Fritz, Melissa Hope Name: see below/ Date: 2003-09-09 14:51:56 Link to this Comment: 6393 |
Name: Date: 2003-09-09 14:58:38 Link to this Comment: 6394 |
GROUP NEARER: Justine Patrick, Shafiqah Berry, Latoya Lavita, Vanessa Herrera
Criteria for plant description
Premise: All specimens observed are living plants.
Shape, texture, and shape distinguished our observations.
Specimen # 1: Has attachments that are green star-shaped. There are two cylindrical shaped objects, they appear to be the same shape and size, indicating that they may be of the same species, but texture variations indicate possible reproduction, that is duplication without exact replication.
Specimen # 2: Amorphous cube, smooth top, rough and jagged sides, pattern of uniform discoloration, appears to be another specimen in and of itself. There is a possibility of it being an older version of specimen # 1, perhaps a fossilization of the cylindrical shapes.
Specimen # 2a: Green rug-like texture gets less green as the shape declines.
Specimen # 3: Broad brown surface has two parts interwoven with specimen # 1 into a symbiotic relationship.
Specimen # 4: Presented in an upright position, it's green, crisp, and easiest to break of all the specimens so far.
Specimen # 5: Similar to specimen # 1, but shape is not cylindrical. The shorter attachments are closer together and there are more of them. The extensions have pricklier attachments.
Specimen # 6: Appear to be from the same family, characteristic of having similar organisms growing on them, which may indicate an eco-system within an eco-system within the greater hierarchy of different systems.
What we have gathered from our overall findings is that plot of"land" we observed is a symbiotic eco- system supporting various life forms while itsef being supported.
Farther Team 1 Name: Date: 2003-09-09 15:03:16 Link to this Comment: 6395 |
Lab expedition to "Farther"
Observations:
I. Small (1 ft. and under) –
a. Rooted vs. Unrooted
b. Clustered vs. Unclustered
c. Green vs. Brown vs. Yellow vs. Red
d. Long, pointy, broad, branched
1. Leaves
a. tear shaped
b. jagged tear shaped
c. heart shaped.
2. No Leaves
e. Long, pointy, skinny
1. Leaves
a. round
b. reverse heart
c. jagged tear shaped
d. tear shaped
e. fuzzy
2. No Leaves
II. Medium (1-5 ft.)
a. Pliant vs. Non-pliant
b. Lowlying vs. Tall
c. Cluster/unclustered
d. Rough vs. Smooth bark
e. Number of branches/types of branches
f. Leaf Shape
g. Appendages: berries/none
h. Thorns/no thorns
III. Big (over 5 ft)
a. 1 person to hug vs. 1+ persons to hug
b. numerous branches vs. minimal branches vs. one big black metal branch
c. tear shaped vs. rigid tear shaped leaves vs. glove shaped
Conclusions:
There are approximately 37 species of plant life in the area we studied. There was a wide range in the size of plants. The reason for this diversity is to allow the different plants to take advantage of limited resources in different ways. The vertical occupation of space, as well as horizontal, allows plants to compete for light, air and space. The sizes cannot be assumed to follow a plant's time line (juvenile, adult, old) as that would be basing our judgments on the case on Earth. Because the period during which we studied these samples is an insufficient timescale to study growth, this remains an unacceptable assumption and thus, we must receive the grant for further observation.
Planet Nearer Plant Life Analysis Name: Date: 2003-09-09 15:04:35 Link to this Comment: 6396 |
The "Low-to-the-Ground" categorization describes vegetation that was less than six inches tall and it generally covered a large area of ground space. We broke this category into two sub-categories "leafed" and "leafless" based on the presence or absence of leaves. The leafed sub-category includes further sub-groups based on leaf quantity and shape. The leafless category is further divided into subcategories based on texture and size.
The "Low Branched" category refers to plant life with stems and branches that expand horizontally starting at ground level. On the stems were either leaves or needles. The leafed sub-group of low branched plant life was divided into Shiny, and Mat refering to the texture of the leaves and Tiny, refering to the relative small size of one variaty of Low branched plant life.
The "Extended Trunk" category refers to plant life with a thick tall trunk, whose branches expand horizontally. The extended trunk types are further subcategorized by the types of leaves which grow on their branches. They are star shaped leaf and tear drop shaped leaf.
The "Fuzzy Stuff" category refers to a unique type of plant life that spread out over a diverse array of surfaces includingother plant life and inanimate objects in the environment. The sub-groups were categorized onthe basis of color and texture.
The "Nasty Stuff" category refers to t he plant life that grows from other oragisms and is also less than 6 inches tall. The Nasty Stuff types are further subcategorized by its physical appearance. These types are "puffy", "shell like", "orange". A unique characteristic of this plant life is that one could see the immature and mature state of this particular organism.
The expeditionary force discovered five major groups of plant life and twenty-two minor ones in total.
Name: Sarah, Mar Date: 2003-09-09 15:13:09 Link to this Comment: 6397 |
Groundcover:
-groundcovering thinned as light diminished
-common disturbance of ground seems to coincide with a lack of ground covering
1) Long, thin, fibrous, green leaves:
-partially subterranean
-shallow roots
-pigmentation lessens near the roots
-variation within stalks (either 1 stalk or multiple)
-variation of height, but average of Romina's hand length
2) Single stalk with 3 round/oval leaves:
-symmetrical discoloration and veins
-grow in clusters
-edges are ridged
Below Waist:
1) Groups of branches with thicker stems and more leaves:
-only grew in 3rd (smallest) area
-leaves are almond shaped
-leaves have shiny, waxy texture on one side
-backside of leaves is lighter, duller, and has prominent stem through middle
-branches were thicker, brown, and sturdy
Above Eye-Level:
1) 5-Point Leaf:
-found on 3 of 4 above eye-level organisms in open area
-base of plant was brown, thick, with textured, apparently protective covering
-sturdier build
-irregular breaks in covering on one of specimens, which seemed suggestive of an unidentifiable, external force
2) Oval Leaf:
-only specimen with branches lacking foliage
-covering of stem was rougher and more textured than 5-point variety
-many branches were without foliage and were discolored
Plant Life on Planet Nearer Name: Melissa Te Date: 2003-09-10 14:35:59 Link to this Comment: 6406 |
I. Ground Coverage
a. Plants that grow off of ground
1. Leaves
-grows in patches in dark areas
-grows more plentifully in sunny areas
2. Branches and Leaves
-Stem with one leaf
a. small heartshaped leaves
b. large elongated leaves
c. medium oval shaped leaves with stems growing out of middle of
patches
d. medium elongated and serrated leaves
-Stem with multiple leaves
a. stems with a few larger leaves
b. stems with many smaller leaves
c. stems with many smaller speckled leaves
d. stems with many leaves and fruit
b. Plants growing on the ground
1. Hairy looking
2. Blanket-like
a. fuzzy and darker colored
b. granular-looking and lighter colored
3. Leaf-like with red hairs
II. Plants taller than 4 feet
a. Shorter Plants - plants that branch closer to the ground
1.leaves
-smaller oval leaves with more leaves on each branch, darker color
-larger oval leaves with less leaves on each branch, lighter color
2. needles and fruit
b. Taller Plants - plants that branch farther away from the ground
1.star shaped leaves with spiney geometric pods
2.oval shaped leaves
Name: Date: 2003-09-10 14:41:39 Link to this Comment: 6407 |
Name: Date: 2003-09-10 14:41:40 Link to this Comment: 6408 |
lab report 1 Name: Mariya Sim Date: 2003-09-10 14:50:16 Link to this Comment: 6409 |
Category 2:
Bladelike structure, no stem or trunk, vertical, grounded (3 sub categories)
Category 3:;
Free-floating, elongated round and flat. (5 sub categories)
September 10th lab-Voyage to Planet Far Name: anonymous Date: 2003-09-10 14:56:30 Link to this Comment: 6410 |
We arrived at Planet Far and were overwhelmed by the diversity of life. In order to make sense of it all, we developed broad categories into which we grouped the subjects of our observations.
Realizing the magnitude of our task, we focused on distinguishing the different kinds of life close to the ground. The criteria for classifying our subjects as plant life include the implicated growth found in the various sizes and stages of life that particular subjects exhibited. They also were rooted in the ground signifying permanancy within their life cycle, thus exposing themselves to the elements.
We noted a variety of texture, shapes, sizes, and colors.
We divided the subjects into:
We found three different forms of strands: wide, narrow, and circular. Within these groups there were green and brown specimens, the green more moist and the brown more brittle.
We had eight different varieties of stems with colorful appendages.
We had a group of five different longer stemmed, rounded/oval large and flat shaped samples.
We had six samples with stemmed extensions off of their main shoot.
Bring it on! :)
Planet Farther Name: Julia Wise Date: 2003-09-10 14:57:01 Link to this Comment: 6411 |
We classifed plant life on Planet Farther based on four categories: number of leaf prongs, length to width ratio,
Upon discovering a new plant, we first counted the number of leaf prongs, categorizing these in groups of 1, 2-3, and 4 or more. After that, we looked at:
- # of leaves
- leaf shape (lobes and notches)
- leaf size ratios (length to width)
- leaf vein structure
- general plant shape and size (length to width/depth ratio)
- patterns of change in size and shape (tendency to get wider or narrower as height or length increases)
- # of branches, and branching tendency (# of branching nodes)
- Texture and changes in texture
Other criteria that we did not get to measure include:
-Root structure or what happens where plant connects to ground
- proximity to other plants like it
- # of plants per given distance (10 sq. yards)
- flexibility or rigidity, stability
- average size
- leaf thickness
- presence of seeds/flowers/fruit/spores/etc
For example, one plant we loooked at had one prong on each leaf, oval-shaped leaves with no notches or lobes, one central vein in each leaf with smaller veins branching from the central one, a total plant height of about 2.5 feet and width of about 3.5 feet, and about 30 main branches coming from the ground.
Our data:
Non-leaved plants: 1
1-prong: 11
2-3 prong: 3
4 or more: 5
Total plant species observed: 20
Life on Planet Nearer Name: group near Date: 2003-09-10 14:59:38 Link to this Comment: 6412 |
Discerning life on Planet Nearer was a difficult task indeed. We were able to uncover what we believe to be 22 different species of plant life, with several other objects which classified as inanimate.
Ground Growth [1-17 types]
Specimens 1-4: grew closest to the ground, like a blanket over the dirt.
1.looked and felt like felt and was a deep green color. next was an even 2.darker green with tiny ball shapes composing the covering.
3.light green and string-like.
4.light green and found in the far corner of the planet. felt like shag carpet.
Specimens 5-9: all specimens were less than two inches from the ground, and had visible stems, leaves, and were all green.
5.ovular leaf shape, and grew in clusters across the planet.
6.round leaf shape
7.spade shaped leaves
8.ridged shaped leaves, with five leaves per sprout, was also a darker hue of green than the other specimens.
9.ridged and covered with fuzz, three sections per leaf.
Specimens 10-11: blade like leaves protruding from the ground in clumps. Both types of clumps were green. In the far corner of the planet these clumps grew in a darker green and thicker, perhaps because of the favorable conditions in this portion of the planet.
10.this type of growth sprouted from the ground, and separated above ground.
11.this type of growth sprouted and separated below ground.
Specimens 12-17: ranged in height from 4-6.5 inches off the ground, most were a light green hue.
12.very thin with no visible leaves but perhaps seedlings sprouting from the weed.
13.growing close to the ground, with thin leaves.
14.taller than most weeds, with large leaves.
15.long, bottom, with leaves on top.
16.low growing, with many clustered leaves and visible seeds growing on the stalk.
17.long bottom, with spade shaped leaves on top. the leaves were shades of white, green, and purple.
Bushes [18-20 types]
Specimens 18-20:
18.thin, sharp leaves like pine needles. some berries spotted sprouting from the tips of some of these needles. they appeared to be underdeveloped. branch separated below ground.
19.shiny, ovular leaves. branches separated below ground, and were a ligher color.
20.light green matte finish leaves. there was a knotted, twisted trunk, with branches sprouting above ground.
Very Tall Bushes [2 types]
Specimens 21-22: About twenty foot tall, cylandrical base, branching out over the entire planet. Extensions of this species were noted to be growing both above and below ground surrounding the tree. Two types of this species were observed.
21.The base appeared dark brown and chunky, with leaves of a light to dark green hue. These leaves were five pointed. One section of the tree had brown leaves.
22.The base was smooth and a lighter brown. The leaves were tear drop shaped and of a medium green hue.
Name: Alison Jos Date: 2003-09-10 15:05:11 Link to this Comment: 6413 |
"Grass-like" plants:
-Long-stemmed grass
-Dry grass
-Thin/fine grass
-Regular
-Thick grass
"Trees"
-Maple (?) tree
"Other" tree
"Bush-like" plants:
-Big bush # 1 (smooth surfaced leaves)
-Big bush # 2 (x-mas, needle leaves), bush appeared 4 times
-Big bush # 3 (penny-sized, oval leaves), bush appeared 3 times
"Ground"-coverings, stemmed:
-Long-stalked w/stacked leaves
-Uni-leafed "weed" with rigid edges
-5-leafed with serated edges
-Uni-leaf, teardrop shape
-Mini-strawberry plant
-Three leaved clover
-Long, seeded, corn-like plant
-Tiny, muliple-leafed weed
-Plant with one, fan-shaped leaf
-Oak-like weed
-Tri-leafed plant with serated edges
"Ground"-coverings, non-stemmed:
-Moss
Our group was surprised to find the extent to which the plant life on "planet nearer" varied. With ground coverings, in particular, the number of different species of plant life found was extremely surprising.
Name: Date: 2003-09-10 15:21:45 Link to this Comment: 6415 |
the last group nearer Name: Date: 2003-09-10 15:46:14 Link to this Comment: 6416 |
Further exploration requests approved Name: Paul Grobstein Date: 2003-09-16 13:04:26 Link to this Comment: 6493 |
Follow-up investigations should be undertaken with the same general objectives as the initial exploration but with the following additional recommendations in mind:
Relevant information about plant life on earth:
Paula, Bessy, Katie, Melissa, Abby Name: Date: 2003-09-16 14:33:54 Link to this Comment: 6494 |
*We have addressed issues that came up in the first presentation of this system of categorization. The first element of the system that we tried to clarify was the size boundaries for each category. We have also considered possible alternative energy sources other than the seemingly dominant one. This is a seemingly simplified system of organization given that we have not been able to examine the internal features of each species.
Category 1: Immediate proximity to a surface, whether the ground or surface of another organism - a negligable distance from the ground - under 1/2 inch
A. spongey ground covering that spreads out moreso than growing up
B. plants that seem to derive energy from plants in Category 4
Category 2: Low proximity to the ground - from 1 inch to 1 foot.
A. single blade
B. leaf-like structure
1. singular leafed
2. multi-leafed
Category 3: Medium proximity to ground - from 1 foot 1 inch, to 6 feet
A. eliptical shaped needle-like leaf
B. spiked leaf
C. oval, smooth, waxy leaf
Category 4: High proximity - 10 feet and above
A. rigid base with horizontal branching
B. smooth, flakey base with vertical branching
Lab 2 Name: Date: 2003-09-16 14:34:36 Link to this Comment: 6495 |
Plants:
I. Green
A. Leaves
1. petal-like
a. single
~ star
~ heart
~ other
b. multiple
~ from-ground
~ from-branches
* diverge at ground level
+ shiny
+ matte
* diverge from trunk
+ star
+ tear-drop
2. Needle-like
B. No Leaves
1. fuzzy
a. dark green
b. light green
2. blade-like
II. Not Green
A. Shelf-like
1. orange
2. brown
B. Flaky
1. blue
2. white
C. Puffy
This expeditionary team followed-up on the research of the previous expeditionary force on planet Nearer. This group improved on the categorization methods by creating a hierarchy of differences among forms of plant life, whereas the previous group categorized plant life broadly according to similarity of features, without any linkage between categories.
The categories of the previous group did not relate the different types of plant life to one another. This group's categories, by contrast, are a coherent map of all plants on planet Nearer.
Report for Brianna Twofoot, Emily Breslin, Shafiqa Name: Brianna, E Date: 2003-09-16 14:35:40 Link to this Comment: 6496 |
1 Not Green (Brown)
2 Fleshy mold (1)
2' Hard mold
1'Green
3 Algae: Lichen
3' Not Algae
4 No true leaves/small
4' True leaves/big
5 ferns
5' not highly divided
6 no fruit/prolific wood
6'flowering plants
**6.5 Clearly defined trunk (2)
**6.5' random assembly of branches (7)
7 parallel veins in leaves
7' floral veins (1)
- Found system of organization to be extremely helpful.
- Last week, without any prior knowledge, each group began by focusing on size of flora and fauna. However, we learned that size was problematic because a younger version of the same species may be mistaken for an entirely separate species due to observation. We felt an additional step was necessary, in order that, by default, size was incorporated into the schema. We eliminated the possibility of error based on age by focusing on the structure of the flora and fauna as opposed to the size alone.
- This classification is more efficient because it groups flora and fauna together on broader terms.
Plant lab 2 Name: Date: 2003-09-16 14:56:26 Link to this Comment: 6497 |
Based on observations made by the eyenad other senses, on Planet Farther, plants can be classified by size:
Big (taller than 5 ft)
Medium (above ankle but below waistline)
Small (below ankle).
By color: Green or Not Green
By function (whether they produce flowers, leaves, fruits or not).
By the shape and texture: description of the leaf-like structure, if it is present, (direction where the veins go (vertical and parallel, or horizontal/diagonal), smooth or rough), or sensory perception of the organism itself.
By location (where they grow- on the ground, on another organism, in the light, in the shade)
By characteristics of the stem: for example: brown and hard, none, green and frail.
What we found:
A mushroom-like thing: small, fleshy, easy to break, feathery, no fruits, leaves or flowers, brown (not green) , grows in the shade, frail, brown stem.
Big plant one: no fruits, no flowers, 5 pointed leaf-life structure, with diagonal veins, green that grow in the sunlight, has a stem like structure connected to the ground that is brown, rough, and sturdy). It sheds, and when it does, some of the leaves in the ground become discolored.
-An independent organism grows from the stem of big plant 1. It is whitish green and rough, very, very small without flowers or fruits. We put it in an independent category, although it is connected to Big plant 1.
Big plant two: produces fruits - a cluster of samll green, hard berries, no flowers, long, pointy, green leaf with diagonal veins, grows in the sunlight, thick, brown, rough stem (different in texture than Big plant one).
Grassy-like plant: small, green, does not produce fruits or flowers, grows in sunlight and moderate shade, parallel fibers growing from north to south.
Medium-flowery-green plant: grows in molch-like shady territory, produces flowers, long, smooth, green leaf that is lighter on the back than on the front, which is waxy and shiny, veins grow diagonally, small sturdy branches that interlock.
Medium cabbage-like plant: grows in the territory as the previous one, highly textured, dark brown leaf, did not have a visible stem, fragile.
White flower-like plant: puffy, white, long, thin, green stem with smaller ones that open up to flower, no leaves, looks like earth's cottonballs, grows in the sunlight, no leave-like structures.
Name: Date: 2003-09-16 14:58:52 Link to this Comment: 6498 |
Critique of Baseline Report:
-Insufficient number of samples had been taken by the previous group. This resulted in incomplete and therefore highly inaccurate results.
-The sample size used by the previous group in their classification scheme wasn't diverse or large enough. ( For example, the sample they used did not include a sample of fungus, though it was present in the area.)
-The previous group's classification scheme underestimated the number of species due to small sample size, as was illustrated by the omission of fungus in the previous report
-The previous group's use of size as a method of classification proved problematic. A difference in size could simply indicate an organism at a different stage of development as opposed to different species, ex: fully mature maple tree and sapling
-The previous group's use of size as a method of classification resulted in an overestimation of the number of species.
Critique of Earth Plant Classification Scheme:
- The classification scheme did not account for free-standing, un-rooted specimens which on Earth would be assumed dead, but are not necessarily the case on Farther.
Problems in both schemes:
-not detailed enough, insufficient categories (didn't differentiate between vein patterns in leaves)
-location of organisms: it is unclear why organisms grow in certain locations... further investigation could reveal another set of categorizations based on similar observations
New Categorization Scheme:
- Made observations on additional and different samples, more diverse selection of specimens in order to obtain more accurate results.
- Size no longer used as the primary means of differentiating between organisms and therefore not as likely to mistake organisms at different stages of development as different species
Green vs. not green: Free-standing elements, divided by color, shape, texture.
Lichens: expand category to include color, texture, location
Leaves: location (ground/trees), clusters, rooted, shape (jagged/rounded edges), texture (fuzzy, smooth), veins (more categories: not all were strictly parallel or branching)
Planet Nearer Name: Date: 2003-09-17 14:31:43 Link to this Comment: 6511 |
We classified the plants by Leaves
I. No Leaves
-hairy (1)
-feathery (1)
-carpet-like (1)
-flat/thin (looked like cracked paint) (1)
II. Leaves
-Needles (1)
-Parallel Veins (2)
-Branched Veins
---one main wooden trunch (2)
---multiple trunks (2)
---no trunk
------stemmed
---------leaves in multiples of 3 (3)
---------leaves in multiples of 4 and 5 (1)
---------only one leaf (3)
---------more than five leaves (2)
------non-stemmed (1)
# of species = 21
revision of categories of lifeon planet far Name: jessica Date: 2003-09-17 14:38:05 Link to this Comment: 6512 |
Having looked at previous analyses of plant life on planet far, we found the systems of categorization to be insufficient. Specifically, we were troubled by the use of categories that occured along a gradient, and therefore had no distinct divisions amongst them. Our new system utilizes categories that are drawn from far less arbitrary distinctions.
The past categories were based on qualitative definitions of color, shape, texture, and size. We reformed each as follows:
- color: green or not green
- shape: monochot or dichot
the basis for the categorization is the structure. we noticed that plants which appeared to have parallel veins generally took on one group of leaf shapes (long and thin), whereas plants which had many branching veins had different groups of leaf shapes (not long and thin). plants that had many divided leaves, constituting one big leaf formed another category.
- texture: hard and woody or soft and fleshy
- size, or height: plants that cling to surfaces get a different categorization from ones that appear to rise out of the ground
Life revision Name: Explorers Date: 2003-09-17 14:39:18 Link to this Comment: 6513 |
In this new exploration of Planet Far we came to realize that the previous report needed major revision as it did not nearly approximate the intricacies and details of the plant life we were observing. The already mentioned report had 3 major classification, one of which was "free-floating." Including Rock type objects as well as wood chips adn dead leaves. We decided that this category did not fit into any of the descriptions given to us by Prof. Franklin, so left in untampered, leaving room for possible, further "discovery?" as it didn't fit with any of the categories in the given scheme.
For the remaining categories we did the following:
Tree like structures were reclassified into 2 groups:
1. green, woody, dichots (2 varieties)
a. fruit producing (3)
b. flat leaves (2)
Small plants like:
1. green dichot, flowering (13)
2. GREEN, dichot (12)
3. Green, monochot, flowering (1)
4. Grass like: Green, monochot (6)
With this we concluded that the categories from the previous exploration had to be reorganized into more detailed sub types, as we were blessed with more information.
Lab 2 Name: Nearer II Date: 2003-09-17 14:41:18 Link to this Comment: 6514 |
To further classify the lant and fungus life on planet Nearer, we used the basic classifications of plant life cited in Will Franklin's Plant and Fungi Key for the Biology Courtyard. We were able to categorize 29 species of Plant and Fungi life.
Basidiomycota: 3
Ascomycota: 2
Lichen: 1
Bryophyta: 4
Pterophyta: 0
Coniferophyta: 1
Anthophyta: 18
Monocots: 5
Dicots: 13
Disclaimers:
1) It was difficult to differentiate between one sample of tree bark and an organism of the class Ascomycota as covering one of the trees was a brown to black hard globular substance which could have been either.
2) There was also an unidentified large brownish-gray object with bryophyte growths which could have been stone or a type of Fungi; we could not tell.
3) Some items were of the same shape but different colors; i.e. we did not include instances of brown leaves where green leaves of the same shape were already present in our classification.
4) Our reasons for utilizing this system of classification for plants and fungi on planet Nearer were as follows:
-We found few exceptions to the rules of this classification
-It provides a useful vocabulary that we might have a starting point for discourse on the life of Planet Nearer.
-It eliminated the problem of size in classifying different species as experienced by previous teams of explorers.
-Just as this system is founded on earth to be a useful differentiation between the life cycles of different species, we believe that a similar premise holds true on the planet Nearer.
Review of Base Report on Planet Near Name: Date: 2003-09-17 14:42:30 Link to this Comment: 6515 |
All members of the group agreed that the Base Report prepared by Group Near 2, which was done according to specimen size, was an adequate preliminary observation of specimen characteristics. However, holes existed in the report, because the size categorizations were rather vague. Just because something is a particular size, for example, doesn't mean it can't be associated with things of other sizes.
By referencing the detailed work done in the base report, and utilizing Will's classifications this exploratory group deems it possible to begin getting these categorizations "less wrong". However, limitations will still exist due to the fact that it is not possible at this time for us to discern some of the classifications Will describes. Further funding would allow the purchase of more advance technology, which would in turn allow us to continue the process of getting it "less wrong". Lastly, the following list has been reclassified after reviewing the base report in conjunction with Will's classifications. It should be noted that Will's report prompted this exploratory group to include several species which had not been classified as "living" in the preliminary report.
Chlorophyllus:
Specimens 1-4
We believe at this time that three of the four initial ground growth species are lichen. These growths appeared light green and stringy, which fits with Will's categorization of the lichen family. The last specimen in this group appeard a very deep hue of green and "clingy" which would correlate with the Bryophyta classification.
Specimens 5-9
The team has concluded that speicmens 5 and 8 are dicots because of the appearance of five leaf structures on the specimens.
This group believes that speicmens 6,7, and 9 are monocots because they came in clusters of three and have a branching vein structure.
Speicmens 10-11
We conclude that Specimens 10 and 11 are monocots because of the visible parallel vein structure (and the fact that these are grasses, and Will's classification clearly lists "grasses" as monocots.
Speicmens 12-17
This category of specimens is still uncertain, but it is believed that all of these specimens can be categorized as dicots.
Specimens 18-20
These species are most likely anthopytha because they were flowering bushes, and this was the best classification within our means.
Specimens 21 and 22
21 and 22 are coniferophyta because of the appearance of prolific wood.
Non-Chlorophyllus
These were not noted in the base report, but it appears that there is the appearance of both ascomycota and basidilmycota, which would bring the specimen total up to 24 from the initial 22.
lab 3 Name: Paul Grobstein Date: 2003-09-23 12:38:18 Link to this Comment: 6585 |
Scientific research can also be done by using general questions and existing observations to shape an hypothesis that itself motivates new observations. Today's lab is aimed at giving you some experience with the latter kind of scientific research.
We know that multicellular organisms come in a variety of sizes but that they all have in common that they are assemblies of cells. A general question that follows from this is "is there any relation between the size of an organism and the size of the cells that make it up?".
Your task today (in groups of two) begins with thinking of some possible general answers to this question, and about which ones make good (ie interesting and testable) hypotheses. You should then pick such an hypothesis and (using tools we will make available, including a microscope) collect relevant observations.
Your report should include a brief description of your hypothesis and of what motivated it, an account of your observations, and a conclusion in which you discuss the significance of your observations for your hypothesis.
Natalya Krimgold and Nancy Evans Name: Date: 2003-09-23 14:50:25 Link to this Comment: 6587 |
does size really matter? Name: Maria Scot Date: 2003-09-23 15:00:02 Link to this Comment: 6588 |
Hypothesis:
If two organisms (regardless of their size) belong to the same species, then their cell sizes will be similar.
Motivation of Hypothesis:
Common sense told us that all cells are not the same size. For example, an ostrich egg is one complete cell while an amoeba is also one complete cell but of significantly smaller size. But within the same species if size differs, then the quantity of cells may differ but the size of the cells which actually make up the organism does not differ.
Observations:
(Human)
5'7" --> 10x = 7 um/OR
5'5" ---> 10x = 7 um/OR
(Maple leaf)
4" --> 10x = 2 um/OR
1.5" --> 10x = 2 um/OR
(Clover leaf)
1/2" --> 10x = 1.5 um/OR
1/4" --> 10x = 1.5 um/OR
(Mushroom)
3/4" --> 10x = 3 um/OR
1/2" --> 10x = 3 um/OR
Conclusions:
From the small sample of organisms we investigated we have concluded that our hypothesis is correct; as long as the specimens are within the same species their cell sizes are the same. However, within our sample of organisms cell sizes proved to differ between species relevant to the organisms' size (i.e. Humans over 5' tall, 7 um; clover leaves smaller than 1", 1.5 um).
Bio Lab Name: Brianna Tw Date: 2003-09-23 15:02:20 Link to this Comment: 6589 |
Problem: Does the size of cells depend, relatively, on the size of the overall organism?
Hypothesis: Cells occur in a size range which varies according to the size of the multicellular organism. For example, human cells will be bigger than moss cells.
Observations (in microns)
Algae: 40—60
Cheek cell: 30—50
Trachea cell: type 1: 1—2
Type 2: 3—7
Worm epidermis: ~ 350
Moss globule: 30—50
Moss strand: ~10
These observations indicate that cells do not occur in a size-relative relationship. For example, while the earthworm as a whole organism is smaller than a human, the human cheek cells are smaller than the earthworm epidermis cells. However, we must keep in mind that we only sampled a specific type of cell for each organism. There are many different types of cells. For example, of the two moss cell-types sampled, one type was 10 microns in length while one was 30—50 microns. We must modify our hypothesis to say that not only do cells not vary in size relative to their greater organism, but cells within a certain-sized organism come in many different shapes and sizes, each different, none relative to the overall size of the organism.
LaToiya, Katie Name: see subjec Date: 2003-09-23 15:05:09 Link to this Comment: 6590 |
Data:
Algae:
- cell #1: 26 um (@ 4x)
- cell#2: 72 um (@4x)
Human Cheek:
- cell #1: 5.2 um (@40x)
- cell #2: 5.85um (@40x)
Human Spinal Cord:
- cell #1: 1.82 um (@40x)
- cell#2: 2.6 um (@40x)
Earthworm:
-cell#1: 13 um (@40x)
- cell#2: 14.3 um (@40x)
Based on our observations it seems that our hypothesis may not be correct. From the size of the cells measured, it appears that smaller organisms have larger cells, which means that from the size of the cells you can estimate the size of the organism. Perhaps smaller organisms have fewer, larger cells than larger organisms, which have many small cells. In other words, "size does matter".
Abby, Melissa, Talia Name: Date: 2003-09-23 15:05:21 Link to this Comment: 6591 |
Su-Lyn & Sarah Name: Date: 2003-09-23 15:05:51 Link to this Comment: 6592 |
Manuela Ceballos and Laura Wolfe Name: Manuela Ce Date: 2003-09-23 15:06:23 Link to this Comment: 6593 |
Larynx cell = 18.2 micro meters
Spinal cord cell = 13 micro meters
Moss cell = 150 micro meters (50 micro meters in width)
Earth worm cell = 39 micro meters
Buttercup cell = 48.2 micro meters
Based on these observations, our original hypothesis was proven wrong. For instance, an earth worm is generally smaller than a human, however its cells were found to be larger. In addition, in each sample we found cells multiple sizes, colors and shapes - the measurements were taken from the clearest areas of vision. This leads us to a more important point - different organisms have different kinds of cells, (in humans, for example, the larynx cells differed significantly from the spinal cord cells). We can suggest, from our observations, that the link between size of an organism and the size of its cells is more arbitrary than we orginally hypothesized. Perhaps if we compared corresponding cells in organisms, such as a human spinal cord cell to a dog's spinal cord cell, we might get closer to finding a relationship concerning size. However, these correspondences are not often present, because plants have no spinal cords, for instance, so we would be required to find a different method of comparison.
Cell size Name: Charlotte Date: 2003-09-23 15:06:30 Link to this Comment: 6594 |
hypothesis: The greater the size of an organism, the greater the size of its cells.
Observations:
- Humans:
cheek cell: average size = 70 microns
vein cell: average size = 46.8 microns
spinal cord cell = 57.2 microns
- Elodea:
between 19 and 27 hash marks (X40)
average cell size = 241.8 microns
- Wild Algae
between 14 and 19 hash marks (X40)
average cell size = 174.2 microns
Conclusion:
There is no absolute relation between the size of an organism and the size of the cells that constitute it. As we observed earlier, the elodea's average cell size is larger than that of the human's. We also observed that cells within one organism are approximately the same size.
Lab3 Name: Paula & Ro Date: 2003-09-23 15:07:10 Link to this Comment: 6595 |
Hypothesis: The smaller the organism, the smaller the cell. We felt that the most obvious way of trying to make relationships between these different organisms is to begin by making size/cell comparisons.
Observations:
Romina's cheek cell:
4x--104 mm/or
10x--70 mm/or
40X--65 mm/or
Description: Small, oval
Paula's cheek cell:
4x--100 mm/or
10x--60 mm/or
40x--59.8 mm/or
Algea 1
4x--650 mm/or
10x--600 mm/or
40x--26 mm/or (26 was the measurable unit because it extended beyond the measurement capacity of the ruler)
Description: Long, rectangular, green
Algea 2
4x--104 mm/or
10x--150 mm/or
40x--130 mm/or
Description: Small, brownish
Buttercup Mature Root
4x--52 mm/or
10x--6 mm/or
40x--57.2 mm/or
Description: Small, circular
Flowering Plant
4x--104 mm/or
10x--100 mm/or
40x--130 mm/or
Description: Long, thin, rectangular
Conclusions:
Well, our observations have led us to believe that the size of the organism and the size of the cells are independent of each other. For example, we noticed that the buttercup mature root had almost the same size as that of a human cheek cell. We, therefore, cannot say with any certainty that this presumed relationship exists.
Name: justine & Date: 2003-09-23 15:07:56 Link to this Comment: 6596 |
does size really matter? Name: Maria Scot Date: 2003-09-24 13:28:53 Link to this Comment: 6606 |
Hypothesis:
If two organisms (regardless of their size) belong to the same species, then their cell sizes will be similar.
Motivation of Hypothesis:
Common sense told us that all cells are not the same size. For example, an ostrich egg is one complete cell while an amoeba is also one complete cell but of significantly smaller size. But within the same species if size differs, then the quantity of cells may differ but the size of the cells which actually make up the organism does not differ.
Observations:
(Human)
5'7" --> 10x = 7 um/OR
5'5" ---> 10x = 7 um/OR
(Maple leaf)
4" --> 10x = 2 um/OR
1.5" --> 10x = 2 um/OR
(Clover leaf)
1/2" --> 10x = 1.5 um/OR
1/4" --> 10x = 1.5 um/OR
(Mushroom)
3/4" --> 10x = 3 um/OR
1/2" --> 10x = 3 um/OR
Conclusions:
From the small sample of organisms we investigated we have concluded that our hypothesis is correct; as long as the specimens are within the same species their cell sizes are the same. However, within our sample of organisms cell sizes proved to differ between species relevant to the organisms' size (i.e. Humans over 5' tall, 7 um; clover leaves smaller than 1", 1.5 um).
lab 3 Name: megan will Date: 2003-09-24 14:37:50 Link to this Comment: 6607 |
Our data-
Buttercup- measured at 40x, 23or= 53.8 um
Corn- measured at 40x, 22or= 51.2 um
Moss- measured at 10x, 15or = 150 um (length)
Larynx- measured at 40x, 50or = 130 um (length)
Human Cheek- measured at 40x, 30or = 78 um
Our observations lead us to the conclusion that size of an organism is not the deciding factor in cell size. We noticed also that while some of the plant samples (buttercup and corn) were close in cellular size, the moss was much larger. So we can also derive that similar species do not necessarily have similar cell size. A question we have from our observations is, is the complexity of the cellular make up of an organism a factor in similarity in cell size?
cells cells cells Name: Date: 2003-09-24 14:47:17 Link to this Comment: 6608 |
Hypothesis: There is no correlation between the size of the organism and the size of the cell.
Observations:
Spinal Cord - 13 um
Buttercup - 39 um
Shark Brain - 36.4 um
Enor's Cheek - 80 um
Algae - 169 um
Our observations support our hypothesis in the sense that cell size had no relation to the size of the organism (seeing as how a human is larger than a tiny piece of algae). Our measurements were based on what appeared to be the average cell size - we measured the longest points.
Lab 3 Name: Date: 2003-09-24 14:48:07 Link to this Comment: 6609 |
Hypothesis:
Cell size has no direct relation to the size of the organism. The size of the organism is determined by the number of cells that it is composed of.
Observations:
Human Cells:
Vena Cava: Average 85um
Cheek cells: Average 70um
Plants:
Buttercup Root Cells: Average 46um
Algae cells: Average 50um
Conclusion:
Our observations show that our intitial hypothesis is correct. A human organism is composed of cells of different sizes. If
cell size determined the size of the organism, the sizes of the human cells would have been the same. Moreover, a buttercup is bigger than an algae plant, but its cells are smaller. Therefore, there is no direct relationship between the cell size and the size of the organism. Rather, we can hypothesize that each organism is composed of different cells and that the cell size varies with the particular kind and function of each cell (for instance, see the discrepancy in the size of different human cells).
Cell/Size correlation Name: Date: 2003-09-24 14:48:48 Link to this Comment: 6610 |
Hypothesis: Size of cell ought not have a direct correlation with the size of the orgmanism. Rather, the relation ought to lie in the amount of cells an organism has in accord with it's size.
Butter Cup: 12um at 40x
Moss: 7um at 40x
Cheek: 1um at 40x
Based on the latter observations we conclude that our hypothesis holds true for the experiment. As shown, the size of a cheek cell was many times smaller than that of a butter cup cell. As is clear, a human is many times larger than a butter cup plant which goes to show that size of cell and size of organism are not directly correlated.
Cells Name: Anna & Ali Date: 2003-09-24 14:53:49 Link to this Comment: 6611 |
Cheek Cells
-cell 1- 5 um
-cell 2- 4 um
Note: In the animal/ human cells it was more difficult to measure, because the walls were globulous and not really as thick, or as perceptible as plant cell walls. All data has been converted.
Tonsil
-cell 1- 2.6 um
-cell 2- 4.6 um
Shark Brains
-cell 1- 13 um
-cell 2- 39 um
Human Skeletal Muscle
-cell 1- 22 um
-cell 2- 40 um
Spinal Cord
-cell 1- width 15 um, length 40 um
-cell 2- width 25 um, length 30 um
-cell 3- width 20 um, length 20 um
Alison and I agreed that our hypothesis was workable, but it still remains difficult to come upon an answer. The spinal cord is fairly large, and its cells were the largest, however, the shark brain cell was also comparable, as was cell 2 from the Human Skeletal Muscle. We have no conclusion other than that we believe that the size of cells has nothing to do with the size of the thing they make up. Since cells divide to make new cells, we really cannot make any sort of correlation between the sizes.
Micro Name: Date: 2003-09-24 14:55:24 Link to this Comment: 6612 |
Hypothesis:
there is no correlation between cell size and organism size.
In order to prove we will look at cells from organisms of varying sizes. we will look at more than one cell from each organism in order to account for possible variation within the organism.
Observations:
1. Corn Cell: 70 um
2. Human Cheek Cell: 50 um
3. Elodia Cell: 100 um
We observed that there is no correlation between the size of an organism and the cell size of that organism.
Cell size vs. organism size Name: Julie and Date: 2003-09-24 14:58:48 Link to this Comment: 6613 |
Sub-hypotheses included: Cell shape will depend on presence/absence of a cell wall; cell size will depend on presence/absence of a cell wall; cell shape and size will depend on the function of the cell in the organism.
We based our hypotheses on previous observations collected in former biology classes.
We recorded the size measurements and shapes of cells from the bulbilis moss, earthworm cells and human nasal cells. Our data were:
Moss cells (In moss stem): long and thin, average 1,800 micrometers. Shape: rectangular.
Earthworm cells: average 100 micrometers. Shape: roughly oval or round.
Human nasal cells: average 650 micrometers. Shape: globby; roughly oval or round.
Our data and observations support our hypotheses, suggesting that larger organisms do not necessarily have larger cells (moss cells > human cells), and that cell size and shape does depend on absence or presence of a cell wall (the plant cells were decidedly larger, on average, and more rectangular or box-shaped than the animal cells).
We were not able to collect any data with regards to cell function; however , a new hypothesis would be that the cells in moss stems are long and thin because they are vascular cells, and that vascular cells are generally longer and thinner.
Lab #3 Name: Date: 2003-09-24 15:00:11 Link to this Comment: 6614 |
Hypothesis: We believe that cell size is irrelevant in relation to the size of an organisim.
Measurements:
Spinal Cord 14.0 um
Worm 36.4 um
Buttercup 44.2 um
Our findings suggest that the larger the organism, the smaller the cell size; however it is important to note the limited number of specimens that we measured (3). We are not confident in making any conclusion from our measurements. We feel we would need more specimens of different sizes to have a more inclusive summary of possible observations.
Lab 3 Name: Date: 2003-09-24 15:07:39 Link to this Comment: 6616 |
Hypothesis: Smaller organisms are made up of smaller cells and larger organisms are made of larger cells.
Observations:
Moss- 3 OR at 10x = 30 um for round cells
1 OR at 10x = 10 um for striped cells
Corn Prop root- 27 OR at 40x= 70.2 um
Human trachea- 7 OR at 40x= 18.2 um
Earthworm- 12 OR at 40 x = 31.2
Our collection of observations disproved our theory because the corn prop roots and the earthworm both had bigger cells than the trachea cells, although humans are larger organisms than earthworms. Also, corn prop roots had a significantly larger measurement of cells than humans even though they are around the same size.
So we concluded that the because the organism is large, that does not necessarily mean that the cells of that organisms are large and vica versa.
Lab #3 Romatu Kallon, J'London Hawkins, Patricia P Name: Ramatu Kal Date: 2003-09-24 15:10:01 Link to this Comment: 6617 |
We assert that the size of a cell is NOT dependent upon the size of the entire organism.
MOTIVATION:
Although we HUMANS are large organisms in relationship to that of a plant, we are compoosed of extremely small cells. Each cellular size depends not upon the size of the organism but is POSSIBLY correlated to the function that cell executes in relationship to the larger body.
OBSERVATIONS:
WORM CELL 1430.0 um/OR @ LENS 4X
FLOWER CELL 91.0 um/OR @ LENS 40X
J'LONDON'S CHEEK CELL 500.0 um/OR @ LENS 100X
We find that our collected data supports the original hypothesis, in that the cheek cell of a 5'9.5" human being weighing an undisclosed amount proved to be the SMALLEST cell. While the worm, which is often times squished by the feet of human beings proved to have the LARGEST cell.
Randomness: A first mover? Name: Paul Grobstein Date: 2003-09-30 11:54:02 Link to this Comment: 6710 |
The activity falls into three parts. The first we will do and discuss together. From it will emerge an hypothesis that groups will attempt to test with relevant observations. A summary of your observations and the conclusions you draw from them should be the first part of your lab report. Your group will then be asked to make an additional set of observations, and try and come up with an hypothesis to account for it that draws from the first two activities in the lab. The second part of your lab report should include a summary of your observations, the resulting hypothesis, and a suggestion of a set of new observations that could be used to test it.
Microsphere Observations for Liz Bryan and Romina Name: Liz Bryan Date: 2003-09-30 14:31:45 Link to this Comment: 6714 |
Observations:
8 Micron Microsphere (measured at 4):
-Quick jiggling movements, all in similar directions
-Beads are small and circular shaped
-Microns moved in 2-3 degree distances*
4 Micron Microsphere (measured at 10):
-Quick jiggling/jutting movements
-Outside force is causing them to move in similar directions
-Microns moved in 2 degree distances*
2 Micron Microsphere (measured at 10):
-Faster movement than any other group
-Microns moved in 1 degree distances*
*measured using micron ruler
Conclusion:
We couldn't really draw an absolute conclusion because the microspheres kept vibrating, and we couldn't differentiate between their movement and outside movement.
Lab Three Name: nancy kati Date: 2003-09-30 14:31:49 Link to this Comment: 6715 |
Hypothesis: Larger microbeads will move father distances (randomly) than smaller microbeads during a constant period of time.
Our period of time was 10 seconds for each size of microbead. After establishing what movement could be attributed to bulk movement, currents, table shaking, and other outside forces, we came up with the following observations:
2 Micron-sized beads:
moved 30 ums
4 Micron-sized beads
moved 2.6-4.8 ums
8 Micron-sized beads
moved 50 ums
we realize the discrepancies in our accounts of the observations, and these errors could be attributed to any number of sources. the flawed measurements were wrong, but we did resist the urge to change our data and observations to match our expectations. since we learned this valuable lesson, we believe our erroneous data collection should be discarded.
Melissa, Talia, Abby Name: Melissa, T Date: 2003-09-30 14:32:14 Link to this Comment: 6716 |
8um-- 3 tics, 4, 5
4um-- 5 tics,7,10
2um-- 9 tics, n/a, n/a
Observations and conclusions: Given that the results are inconclusive, from those which we were able to gather, we found that the smaller the sphere size, the greater the movement. There was a visible difference between the 8um ad 2um spheres, in that the latter would migrate further from their origin point, whereas the former would circulate around their origin area ,moreso.
Sarah Kim, Brianna Twofoot Name: Brianna Tw Date: 2003-09-30 14:32:21 Link to this Comment: 6717 |
We recorded movement in a given amount of time in units of micron, under a magnification of 40.
8 micron spheres: Moved 5 microns in 5 seconds
4 micron spheres: Moved 9 microns in 5 seconds
2 micron spheres: Moved 9 microns in 3 seconds
Conclusion: Observations support our hypothesis.
Why? Name: Date: 2003-09-30 14:34:22 Link to this Comment: 6718 |
We looked high and low, nearer and farther for these moving microspheres, and got nothing, what is this? why can't these storming malestroms be seen? What is science? who are we? Oh, where are you beadies...? The conclusion is we were duped, hoodwinked, bamboozled , but Ah we found some with help from Professor Grobstein. Part two better be an improvement or else what is the point of these futile efforts on the part of people who are born to die and get three hours of sleep while living anyway?!!!!!!!!!!
We discovered four moving "beadies" that moved pretty slowly, but were cool nonetheless. However, many of the surrounding beads were still, which sucked. We were unable to measure the size and speed due to lack of time, but from our very general observations, we saw a bead move 1 milimeter in about 1.5 seconds, this is for the largest bead, but we have yet to measure the others.
moving balls Name: emily and Date: 2003-09-30 14:46:19 Link to this Comment: 6719 |
Further observations to support or not support the implication:
The smaller microspheres will move faster and have more movement in comparison to larger microspheres; compared to each other, 2nm will move the most and the fastest, 4 nm will move a little less, and 8 un will move the least and the slowest.
Observations:
8 nm:
30 un --> 35 sec
30 un --> 31 sec
30 un --> 19 sec
avg = 28.33 sec
4 nm:
30 un --> 9 sec
30 un --> 9 sec
30 un --> 8 sec
avg = 8.66 sec
Conclusion:
As we had predicted, the movement of the 4 un microspheres was more eradic than the 8 un microspheres. This fact made it more difficult to collect the data. However, the information that we did collect supports the implication made previously with the class.
Microsphere Observations for Liz Bryan and Romina Name: Liz Bryan Date: 2003-09-30 14:53:59 Link to this Comment: 6720 |
Observations:
8 Micron Microsphere (measured at 4):
-Quick jiggling movements, all in similar directions
-Beads are small and circular shaped
-Microns moved in 2-3 degree distances*
4 Micron Microsphere (measured at 10):
-Quick jiggling/jutting movements
-Outside force is causing them to move in similar directions
-Microns moved in 2 degree distances*
2 Micron Microsphere (measured at 10):
-Faster movement than any other group
-Microns moved in 1 degree distances*
*measured using micron ruler
Conclusion:
We couldn't really draw an absolute conclusion because the microspheres kept vibrating, and we couldn't differentiate between their movement and outside movement.
Brianna Twofoot, Sarah Kim Name: Brianna Tw Date: 2003-09-30 15:20:46 Link to this Comment: 6721 |
We recorded movement in a given amount of time in units of micron, under a magnification of 40.
8 micron spheres: Moved 50 microns in 5 seconds
4 micron spheres: Moved 90 microns in 5 seconds
2 micron spheres: Moved 90 microns in 3 seconds
Conclusion: Observations support our hypothesis.
Observation:
1% Salt Water
- Long, thin cells
- Stationary
25% Salt Water
- Little bubble like things are forming within the cell walls. The cell membrane is shrinking.
- Keep getting smaller, i.e. cell membrane keeps shrinking.
- Not necessarily all pulling away in a circle or uniform shape.
Distilled Water
- Begins to return to normal shape, but does not return entirely.
Story: The cell is made up of water. The presence of salt begins to eliminate the presence of water, or pushes out/extracts water from the cell. The presence of distilled water refloods the cell, causing it to return to its normal shape.
Lab Three--Part Two Name: Natalya, N Date: 2003-09-30 15:22:54 Link to this Comment: 6722 |
WATER ONE(1% salt concentration) observations:
well-defined cells with cell walls; can see organelles inside cells. Nothing appears to be moving at this magnification (4x) or at a higher magnification (10x).
WATER TWO (25% salt concentration) observations:
cell walls got darker, smaller. and seem to be more condensed. They appear to have lost water content as a result of adding the salt water.
WATER THREE (distilled water- 0% salt concentration) observations:
upon addition of the distilled water, we observed the un-doing of the salt water addition: the cells appeared condensed like before, at first, but were more transparent than with the salt . Over a longer period of time, the cells were even more transparent, but now the "pockets" of space created by salt water filled back up. evantually things looked "back to normal".
OBSERVATIONS:
Salt water removed the water from the cell membrane, and left the wall intact. It took a longer period of time for the cell wall to retain its original appearance as distilled water is added.
HYPOTHESIS:
during the addition of the different waters, the cell wall remains intact, however the cell membrane contracts (as more salt is added) and water is drawn out and expands (as less salt is present).
CONCLUSION:
Salt affects the movement of water across the cell membrane.
Turgid Glory Name: emily & mi Date: 2003-09-30 15:30:12 Link to this Comment: 6723 |
Are water molecules in constant random motion? YES.
Conclusion:
Obviously, water is crucial in maintaining the structure of cell walls in plants. The movement of water molecules pushes the NaCl or the distilled water through the semi-permeable cell walls, resulting in the destruction and restoration of the cells.
New Hypothesis:
Water molecules are in constant motion.
Su-Lyn, Brittany Name: Date: 2003-09-30 15:31:22 Link to this Comment: 6724 |
Implications of hypothesis ("test"-able observations): When smaller objects are placed in water, they will "jiggle" around more than larger objects in water. This will happen because the moving molecules will push them around more.
Group: Su-Lyn, Brittany
Observations:
The 8 micrometer beads didn't appear to move at all at a magnification of 10x, but we used a coverslip, so that could have affected the outcome. The second time we tried, however, the 8 micrometer beads rocketed across the screen in circular patterns at very fast speeds; however, some of them were moving faster, others slower, and some didn't move at all. The 4 micrometer beads, however, moved quite a lot a magnification 10x.
8 m: 0, 30, 40, and 100 microns/second
2 m: 0, 200, 250, and 300, 2740 microns/second
Our conclusions support the idea that larger objects, on average, "jiggle" or move less in water than smaller objects, which in turn would support the greater hypothesis that liquids such as water are not static at the molecular level. However, discrepancies in our experiment---for example, the different particles moving at different speeds and the fact that some didn't move at all---indicate that more observations will be necessary to formulate a new less wrong hypothesis. However, we did notice that the particles seemed to be moving in the same direction, so we hypothesize that the movement of the particles is not totally random. New observations will be necessary to determine the order (if, in fact, any) of the particles' movement.
********************
Plant Cell Experiment
Regular plant cells
Plant cells w/distilled water
Plant cells w/salt water
Plant cells w/distilled water again
What happens when we put in the 25% salt: the yellow areas swell up.
What happens when we put in distilled water: the yellow areas shrink.
Melissa, Abby, Talia Name: Talia Libe Date: 2003-09-30 15:33:37 Link to this Comment: 6725 |
1% Solution of NaCl-- Distinguishable pattern of the cell walls and membrane with nuclei
25% Solution of NaCl-- The NaCl absorbed the moisture from the cells, thereby causing the cell membrane to contract
Distilled H20-- The solution restored moisture to the cell, therefore returning the cell wall and membrane to its original shape
Story:
The NaCl properties cause the membrane to contract as it absorbs the moisture. Once the distilled water replaces the salt water, the cells return to their original state.
Onion Cells and Salt Water Name: Liz and Ro Date: 2003-09-30 15:33:42 Link to this Comment: 6726 |
Hypothesis: Water molecules are constantly in motion.
Observations:
1% NaCl
-The observations started at lens 4. The different cells are visible. They are long and rectangular. We cn see the outline of the cell walls and when we magnified to 10, there was a clearer picture of the cell walls and we were able to observe the nuclei in some of the cells. We were not able to differentiate the cell wall from the cell membrane.
25%
-We were able to see both the cell wall and the cell membrane. The membrane appears to have shrunk with the salt water. We could now see the nucleus in all of the cells.
Distilled Water
The cell membranes appear to have gone back to their original position, pressed up against the cell wall. The nuclei was visible.
Conclusion:
We know that a cell membrane is permeable. Thus when the salt water enters the cell it shrivels up the cell membrane, pushing the water out and thus making it easier to observe. We can assume that the salt in the water dehydrates the cell membrane. Then when we put distilled water back onto the cell, the membrane becomes hydrated and it is harder to see.
Name: Shafiqah a Date: 2003-09-30 15:33:48 Link to this Comment: 6727 |
Name: Charlotte Date: 2003-09-30 15:36:03 Link to this Comment: 6728 |
Hypothesis: The smaller the object, the faster it moves.
Observations:
At 8 microspheres, the beads jiggled individually and moved in one direction simultaneously.
At 4 microspheres, the beads also jiggled individually and moved in more random directions at a faster speed than the 8 microsphere beads.10s.-->2
At 2 microspheres, the beads jiggled, moved in random directions at a higher speed. 10 s. -->4
Conclusion: The observations are consistent with the hypothesis.
Hypothesis:
Water makes things move.
Observations:
1%: we can observe long thin cells, cell walls, membranes and mnucleus are visible.
Salt Water(25%): salts eats up the cell and diminishes its size.
Distilled Water: the cell takes its initial form within the cell wall.
Our Story: When salt water is added, the size of the cells diminish. But when distilled water replaces the salt water, the sizes of the cells take their initial form. It seems that water allows the mobility of cells, whereas salt inhibits them from moving, therefore the cells contract.
We can come to the conclusion that water is essential for cell function.
Bessy Guevara, Paula Arboleda Name: Date: 2003-09-30 15:49:58 Link to this Comment: 6729 |
Part II
Original hypothesis: Water molecules are constantly in motion
Observations: When using the 1% salt water, the plant cell is considered to be at the natural state, where the cell walls are rectangular shaped and seem uniformly position in the area. When adding the 25% salt water, we observed that the cell membrane shrunk and the cell walls lost it's rectangular shape. The high concentation of salt shriveled the cell walls. When distilled water was added, the cells took their rectangular shape. However, they were wider and seemingly bigger with small circular pockets(cell membrane) within the cell wall. With these observations we can state that the concetration of salt greatly affects the plant cells by either making them bigger or smaller; salt molecules affect the rate of motion of the water molecules.
Melissa, Talia, Abby Name: Melissa, T Date: 2003-09-30 15:56:52 Link to this Comment: 6730 |
8um-- 3 tics, 4, 5
4um-- 5 tics,7,10
2um-- 9 tics, n/a, n/a
Observations and conclusions: Given that the results are inconclusive, from those which we were able to gather, we found that the smaller the sphere size, the greater the movement. There was a visible difference between the 8um ad 2um spheres, in that the latter would migrate further from their origin point, whereas the former would circulate around their origin area ,moreso.
Name: Laura Wolf Date: 2003-09-30 16:01:20 Link to this Comment: 6731 |
The 4 micron object, over a time period of one minute, traveled within a range of 50 micrometers, but traveled back and forth multiple times so that the total distance it moved was unclear.
Although it would be helpful to gather more data, the data we have so far is consistent with the original hypothesis.
Now we are testing a small sample of onion to see what effect water has on the cells.
When adding salt water: the cells (perhaps the cell membranes) changed from straight and even to shriveled and bubbly-looking. They look destroyed.
When adding Distilled water: there are water pockets inside the cell walls.
We have two possible explanations/ new hypotheses:
1) that the salt molecules might be moving faster than the regular water molecules, causing more damage/ change to the plant cells.
2) that water molecules might be smaller and move faster than the salt molecules, and so when there is salt in the solution, there is a longer time for change to occur.
With more time and funding, we could ake more observations and see which of these hypotheses we want to keep.
movers and shakers Name: Date: 2003-10-01 14:27:31 Link to this Comment: 6747 |
Obsevations:
In ten seconds, the spheres moved the following distances:
2 um spheres -- 10.4 um
4 um spheres -- 7.8 um
8 um spheres -- 3.9 um
We observed that as the size of the particles decreased, the speed of the movement increased.
Name: Date: 2003-10-01 14:27:32 Link to this Comment: 6748 |
Our hypothesis was that the smaller particles would move further distances.
However, in the short time that we had to make observations, our evidence did not support that.
2-micron particle traveled 15 tics in 30 seconds
4-micron particle traveled 30 tics in 30 seconds
8-micron particle traveled 100 tics in 30 seconds
We suspect that there is a large percentage of error due to movement of the slide, movement of the table, etc.
Name: Date: 2003-10-01 14:31:39 Link to this Comment: 6749 |
Ammendment to our posting:
We measured it under the 40X lense.
so the 2 micron particle moved 39 um
the 4 micron particle moved 78 um
and the 8 micron particle moved 260 um
Particle motion Name: Mariya Date: 2003-10-01 14:32:07 Link to this Comment: 6750 |
Hypothesis:
Smaller particles move faster in water than larger particles do.
Observations:
All observations were made in 30 seconds span.
8um -- moved 16.1um , 10.4um
4um -- moved 44.2um, 39um
2um -- moved 52um, 49.4um, 52um
Conclusion:
Our observations are consistent with our hypothesis. The smaller particles have a larger diameter of motion than the larger particles, therefore the smaller particles move faster than the larger particles. We anticipate some measurement error due to random movement of particles (the precise distance they travel is hard to measure).
invisible beads Name: Alison J., Date: 2003-10-01 14:32:55 Link to this Comment: 6751 |
we were only able to collect data for the smallest size of bead. the beads were obviously moving at what seemed to be a rather fast rate. however, we were unable to find any movement in the other sizes. but may be inclined to say that the large beads would have moved less than the smaller beads.
Microbeads Name: Date: 2003-10-01 14:33:56 Link to this Comment: 6752 |
Hypothesis: Smaller microbeads will move faster than larger microbeads in water.
We looked at three different sizes of microbeads, but only got measurements for two sizes. What we observed did not support our hypothesis but instead implied that smaller microbeads moved more slowly.
Size four microbeads moved 50 micrometers in 30 seconds, or 100 a minute.
Size two microbeads moved 25 micrometers in 30 seconds, or 50 a minute. Most of these actually vibrated in place, even though we examined them at multiple depths.
Lab 4 Name: Date: 2003-10-01 14:36:02 Link to this Comment: 6753 |
Before we began our observations, we predicted that the larger beads would move slower and be less affected by the collisions, because they had a larger body and that the smaller beads would move faster because they had less mass and more affected by the collisions.
Our results were as follows:
8 in 5 seconds approx. 52 emds
4 in 5 seconds approx. 30-40 emds
2 in 5 seconds approx. 8-12 emds
We believe that the quicker/ further travel of the smaller beads, and the less distance the beads traveled within 5 seconds as they got larger, supports our hypothesis.
Excercise #1 Name: J'London, Date: 2003-10-01 14:38:31 Link to this Comment: 6754 |
Hypothesis: We beleive that the smaller particles move at faster rate due to the fact that they possess less mass, in conjuntion with the idea that these particles contain less energy in proportion to the energy emitted by the water.
Observations:
8 microspheres- particles moved approximately 6um in 10 seconds
4 microspheres- particles moved approximately 15 um in 10 seconds
2 microspheres- partcles moved approximately 23 um in 10 seconds
These observations were obtained using the 40x lens.
We proved our hypothesis to be true as the larger microspheres moved at a slower rate than each of the smaller ones.
Movement of particles Name: Date: 2003-10-01 14:39:51 Link to this Comment: 6755 |
Hypothesis: Smaller particles move around more than bigger particles.
Observations:
8 microns: beads moved 5.2 ums in a time span of about 30 seconds. The beads were vibrating.
4 microns: beads moved 26 ums in a time span of 30 seconds. The beads were vibrating quickly, but drifting slowly.
Our observations supported our hypothesis that smaller particles moved more than larger beads.
Name: Date: 2003-10-01 15:11:32 Link to this Comment: 6756 |
We think that the cells will look more shriveled up in the 25% salt solution because the salt removes the water from the cell, but when the cells are in the distilled water, we feel it was return back to its regular shape and plumpness.
Observations:
1% salt - cell walls are stable, not deteriorating, thick
2% salt - the membrane is shrinking, the inside of the cell is shriveling up, the cell wall appears to be thinner
distilled water (0% salt) - returning to original shape, cell wall thicker, membrane plump
We felt that this happened because the salt could have broken down the particles of the cells and therefore resulted in a shriveling effect.
Part 2, onion/salt water Name: Date: 2003-10-01 15:22:23 Link to this Comment: 6757 |
Observations--
1% NaCl-- cell walls and membranes appear to be intact and stable, not moving
25% NaCl-- cells have shrunken, cell membranes have been destroyed, looks collasped. still able to see cell walls intact. little circles that appear to be smaller cells are smaller as well.
Distilled water-- cells have returned to normal size, initial conditions
Due to our observations, we would hypothesis that 25% salt solution causes water to move out of a cell membrane which makes the cell shrink. Pure water moves back into the cell membrane and returns the cell to its original size.
Onions Name: Stefanie F Date: 2003-10-01 15:22:24 Link to this Comment: 6758 |
After adding 1% NaCl, we noticed a very small change in the size of the cells.
After extracting the 1% and adding 25% we saw a very pronounced change in the appearance of the cells. The cells had contracted, and were obviously darker, almost filled with solution.
In the presence of distilled water, the cells were wide and clear.
We have hypothesized that, salt decreases the size of the cells.
salt Name: Date: 2003-10-01 15:29:11 Link to this Comment: 6759 |
Observation: The cell nuclii grow with salt.
Hypothesis as to why this occures: The water particles move the salt inside the cell nucleus, and this pushes the outside of the nuclues in all directions, stretching it.
Semi-Organic Hypothesis Name: J'London H Date: 2003-10-01 15:30:47 Link to this Comment: 6760 |
Well, through observing the onion cell and cooperating the knowledge we observed through phase one of our explanation we are able to assert that:
NaCl @ 1% we observed no movement of the cells, however we were able to note the rectangular shape of the cells, which is very different from the organism we observed prior to this experiment.
NaCl @ 25% we were able to detect slight movement in the cells, we noted the rectangular shape of the cells observed at 1% we now perceived to be ovular.
Distilled Water we did not notice much difference from NaCl 1%.
Onion Cells Name: Mariya Date: 2003-10-01 15:31:04 Link to this Comment: 6761 |
Observations:
Onion cells in 1% salt solution: clearly visible cell walls and cell membranes, transparent cells
Onion cells in 25% salt solution: the cell walls stay the same, while the membrane shrinks significantly, cells get more clouded
Onion cells in 0% salt solution: the membrane expands back to its regular size, cells look the same as the cells in the 1% solution (perhaps a bit more transparent). The cell walls stay the same throughout.
Hypothesis: The 25% salt solution draws water out of the cell through the cell membrane. Because there is less water left in the cell, the membrane shrinks. When we add pure distilled water, its constantly moving particles enter into the cell through the membrane, filling it again to the size observed in the first instance.
pt II of water motion lab Name: Date: 2003-10-01 15:32:15 Link to this Comment: 6762 |
Original hypothesis: water molecules are constantly in motion.
Observations:
onion skin + 1% NaCl solution: cells are in "normal" state. long, thin cells with very distinct cell walls. cell membrane not remarkably visible.
onion skin + 25% NaCl solution: cell walls remain completely intact; however, cell membranes are now distinctly shriveled or shrunken.
onion skin + DI H20: cells return to "normal" state - looked identical (if not even clearer) to original set of observations.
Conclusions:
It seems that salt affects the motion of water molecules by slowing them down: we can infer from our observations that the salt molecules caused water to move more slowly inside the cell membrane, which would have caused it to lose its shape and shrink or shrivel.
Lab 4 part 2 Name: Date: 2003-10-01 15:36:21 Link to this Comment: 6763 |
Hypothesis: The 25% salt would leave a residue on the cells of the onion membrane and that the water would move across the onion faster than salt.
N.Cl on Onion- You can see cells clearly. Can see small amount of motion. Nothing to compare the motion to yet.
25% Salt on Onion- Can see what we feel are salt particles moving rapidly and randomly across the onion membrane. The salt seems to spread itself out over the membrane, eventually causing a film over the membrane. The 1% N.Cl and the 25% salt, we assume, have appeared to mix over the membrane. while causing the walls of the individual cells to appear thicker.
0% distilled water- Seemed to rinse off some of the residue. Allow the walls of each individual cell to appear sharper and thinner. The cells also looked lighter under what remained the same magnification and light the entire observational period.
Flux and Its Regulation: Chemical Reactions and En Name: Paul Grobstein Date: 2003-10-07 09:53:37 Link to this Comment: 6819 |
We will begin with some basic observations implying the existence of enzymes and then explore a particular chemical reaction, the "falling apart" of hydrogen peroxide into water and oxygen gas, as it is affected by the enzyme hydrogen peroxidase:
Your report should include a description of your observations relevant to identifying important characteristics of enzymes and some hypotheses about what produces those characteristics.
Temperature Name: emily & mi Date: 2003-10-07 14:51:51 Link to this Comment: 6822 |
Iced H2O2:
5.0 sec
4.0 sec
5.0 sec
Room temperature H2O2:
4.0 sec
3.5 sec
3.3 sec
Warmed H2O2:
2.5 sec
2.5 sec
3.0 sec
Name: Su-Lyn, Br Date: 2003-10-07 14:54:15 Link to this Comment: 6823 |
(each number is a different trial)
La Toiya, Natalia Name: La Toiya L Date: 2003-10-07 14:58:29 Link to this Comment: 6825 |
Part III - Effects of pH on Enzyme Activity
{2.0 Buffer w/ 10ml of Hydrogen Peroxide w/ Catalase B}
It took the filter disc 2 seconds to rise to the top of the solution
Part I Name: emily & mi Date: 2003-10-07 15:10:39 Link to this Comment: 6826 |
1.5
1.7
1.9
2.3
3.0
3.5
4.0
4.5
5.5
6.4
6.5
6.6
6.7
7.0
7.1
7.2
7.3
7.5
7.5
7.6
7.8
8.0
8.0
8.0
8.0
In the same amount of time, 0.5 H2O2 < 1.0 H2O2 gas. Less hydrogen poroxide produces less gas (O2). The enzyme doesn't affect the final state it just affects how fast you get there.
Brianna Twofoot, Liz Bryan, Justine Patrick Name: Brianna Tw Date: 2003-10-07 15:14:31 Link to this Comment: 6827 |
.8
1.4
1.9
2.4
2.8
3.1
3.5
3.8
4.1
4.4
4.7
4.9
5.1
5.3
5.5
6.0
6.5
7.5
8.5
9.5
Experiment 2 Observations
Catalase B:
Run 1- 5
Run 2- 3
Run 3- 2
Catalase C:
Run 1- 6
Run 2- 4
Run 3- 5
Catalase D:
Run 1- 11
Run 2- 10
Run 3- 8
Yes, rate depends on concentration of the enzyme. The less concentrated the enzymes, the slower the rate of reaction.
- An enzyme speeds up something that is already occuring more slowly. Only affects speed, not destination.
An enzyme is a something that can speed or slow a reaction based on ph or temperature, and can increase the rate of a reaction based on concentration. Perhaps an enzyme is some sort of a living thing, because much like a plant or animal or person, if you heat it up too much, it will slow down, and if you freeze it it will slow down. This is different than what we observed about water molecules, where the extreme temperature in fact made the molecules move faster.
What is an enzyme? Name: emily & mi Date: 2003-10-07 15:21:56 Link to this Comment: 6828 |
katie ottati, nancy evans, abby fritz Name: see subjec Date: 2003-10-07 15:27:23 Link to this Comment: 6829 |
Catalase B (full):
1 - 3 seconds
2 - 5 seconds
3 - 5 seconds
Catalase C (1/5):
1 - 8 seconds
2 - 9 seconds
3 - 8 seconds
Catalase D (1/10):
1 - 12 seconds
2 - 12 seconds
3 - 11 seconds
A decrease in the enzyme concentration means a slower reaction rate.
What is an enzyme?: We do not know. It appears to have characteristics in common with living organisms (it has an optimal temp & pH), but it also has characteristics in common with water (H20 molecules break down the cracker, as do the enzymes in spit). The group was unable to decide whether we thought enzymes were living organisms or perhaps molecules that move faster than most and thus better facilitate the breaking down of things.
Name: Su-Lyn, Br Date: 2003-10-07 15:27:54 Link to this Comment: 6830 |
Bessy Guevara, Vanessa Herrera Name: Date: 2003-10-07 15:29:20 Link to this Comment: 6831 |
@ Chilled 4.0 4.0 4.0
@ Room Temp. 4.0 3.0 4.0
@ Warmed 3.0 2.0 3.0
These observations reveal that as the temperature rises, the reaction rate of the disc is faster therefore, taking less time to reaching the top of the solution. However, had the warmed temperature been higher, the reaction rate would have been slower and the time in reaching the top would have been greater.
In our observations, we concluded that the property of an enzyme is a catalyst that promotes the speed in which a chemical reaction takes place . In our second set of observations, we investigated the effect of temperature on the reaction rate of an enzyme.
There's an optimal temperature where the speed can reach its summit; at chilled and very warm temperatures it decreases the rate of reaction. Since, everything is falling apart, it most hold true that the enzyme will breakdown.
enzymes Name: Laura Wolf Date: 2003-10-07 15:29:30 Link to this Comment: 6832 |
Data:
pH level......... Number of seconds (trial 1, trial 2, trial 3)
pH 2.0 ............... 6 , 6, 5
pH 7.4 .............. 6, 4, 5
pH 10.1 ............ 8, 6, 8
This data is not convincing that a higher pH either speeds up or slows down the process, because the data is all relatively the same. There is no gap, or significant difference, among the groups of data. From the observations collected, the hypothesis is wrong.
However, combining my data with the other group's data seems to suggest a curve; that on the pH scale the reaction time goes from slower to faster to slower. My results could have been due to human error or other small problems.
********What is an enzyme, then, and how is it related to the speeds of these reactions?
Why did the enzymes work fastest in a pH of 7.4 which is close to distilled water (7.0)? My guess was that acidic solutions would contain more enzymes to help break things down faster (such as stomach acids that are used to break down food), and also basic solutions (such as bleach) are more hamful to humans than water because they break things down faster too. So maybe enzymes balance pH. Maybe the reason that solution was a steady 7.4 pH was because it had more enzymes in it than the 2.0 or the 10.1 solutions.
But the data from the "temperature" group supports our hypothesis from last week, which says reactions happen faster in warmer temperatures, and it helped speed up the enzyme's productivity.
So my new hypothesis is that enzymes speed up reactions and balance pH towards a neutral number.
enzyme Name: Elisabeth Date: 2003-10-07 15:30:43 Link to this Comment: 6833 |
Temperature Observations:
>Chilled hydrogen peroxide: 3.67s, 4.73s, 3.59s
>Room temperature: 3.20s, 3.51s, 3.24s
>Warm temperature: 2.50s, 1.87s, 1.80s
Conclusions: The higher the temperature of the hydrogen peroxide, the greater the speed of the reaction.
What is an enzyme? : Based on our observations, we know that an enzyme is a mobile molecule that serves as a catalyst. Its function is to speed up a reaction, without changing its final state.
La Toiya Natalya Name: Date: 2003-10-07 15:31:02 Link to this Comment: 6834 |
temperature Name: Jessica an Date: 2003-10-08 14:56:30 Link to this Comment: 6842 |
trial 1: 5 sec
trial 2: 5 sec
trial 3: 4 sec
chilled
trial 1: 7 sec
trial 2: 8 sec
trial 3: 8 sec
warmed
trial 1: 5 sec
trial 2: 6 sec
trial 3: 6 sec
Name: stefanie f Date: 2003-10-08 15:14:50 Link to this Comment: 6843 |
Enzyme B (highest concentration):
Trial 1: 4 seconds
Trial 2: 3 seconds
Trial 3: 4 seconds
Enzyme C (middle concentration):
Trial 1: 13 seconds
Trial 2: 14 seconds
Trial 3: 13 seconds
Enzyme D: (lowest concentration):
Trial 1: 13 seconds
Trial 2: 15 seconds
Trial 3: 15 seconds
An enzyme is a catalyst; it is a substance with a chemical composition that speeds a reaction. In other words, adding an enzyme produces an increased rate of change in a process that would have been slower otherwise.
Bio Enzyme Lab Name: Anna & Mel Date: 2003-10-08 15:15:51 Link to this Comment: 6844 |
Part IV: Temperature
Chilled:
8
7.5
8
Room Temp:
5
5
5
Hot:
12
13
30
What is an enzyme?
We think that an enzyme is something that speeds up a process; something that acts as a catalyst to speed up a reaction. We have observed that the enzyme works at a faster rate as the concentration increases, and that there is no linear relationship between the rate the enzyme works to temperature or pH. At this point, all we can say for sure is that it is some kind of substance that speeds up a reaction at different rates depending on the concentration of the enzyme.
Enzymes Name: Date: 2003-10-08 15:21:19 Link to this Comment: 6845 |
We measured the time it took for a filter disc soaked in Catalase B to rise to the surface with different ph buffer solutions. We repeated each trial 3 times for each ph solution.
2.0 ph buffer- 17 sec, 15 sec, 16 sec
7.4 ph buffer- 12 sec, 13 sec, 13 sec
10.1 ph buffer- 11 sec, 11 sec. 11 sec
Our results show that the rate of rising accelerated as the ph level increased. Unfortunately, this was not supposed to happen. However, we learned from the first part of the lab that an enzymes do not affect what happens, only how quickly it happens. Also, they work better at some ph levels and not others. So based on our observations, we can infer that an enzyme is alive, because it needs certain conditions to function effectively. Our results showed that enzymes just like other living organisms need a certain temperature and ph level to function best.
Part III Name: Date: 2003-10-08 15:23:24 Link to this Comment: 6846 |
Does pH level affect the rate and time of a chemical reaction?
pH 2.0: 20, 24, 18 seconds
pH 7.4: 32, 24, 22 seconds
pH 10.0: 31, 31, 30 seconds
It appears as though pH level does have some effect on the rate and time of the reaction's "falling apart." Certain pH levels seem to be more effective than others in speeding up the reaction. From the data of other groups, it appears that the temperature of the enzyme affects the reaction in a similar way.
From what we have seen in the past two hours, an enzyme is a liquid that has some bearing on the rate of a reaction. It is actvated more optimally by certain temperatures and pH levels. When the rate of the reaction is increased, bubbles appear more quickly and move more rapidly, which tells us that things are falling apart faster. Also, the higher the concentration of the enzyme added to the reaction, the faster the reaction will occur.
Our hypothesis for enzyme reactions is that the more concentrated the enzyme, the faster a reaction will occur, but for pH and temperature, there is no linear relationship between acid/temperature levels and reaction rate. Rather, there are certain optimal temperatures and pH levels which cause the enzyme to work at its highest possible rate.
conclusion Name: Diana and Date: 2003-10-08 15:23:41 Link to this Comment: 6847 |
This goes to show that enzymes are important as catalysts to reactions in nature, but we find that their temperature does not necessarily affect the speed of their reaction. If this is the case at all times, we can say that the effect of an enzyme will be the same in all temperature conditions.
(our data is posted above, but for your convenience, here it is again. )
room temp: (5, 5, 4)
chilled: (7, 8, 8)
warmed: (4, 6, 6)
lab #4 Name: J'London, Date: 2003-10-08 15:24:59 Link to this Comment: 6848 |
We conducted PART IV of the group experiment entitled EFFECTS OF TEMPERATURE ON ENZYME ACTIVITY.
Our observations yielded the following data:
ACTIVITY @ ROOM TEMPERATURE:
trial one... 2.25 sec
trial two... 3.5 sec
trial three... 3.5 sec
ACTIVITY @ CHILLED TEMPERATURE:
trial one... 7 sec
trial two... 5 sec
trial three... 5 sec
ACTIVITY @ WARMED TEMPERATURE:
Our results were deviant from the other experiments conducted. Our "nubbie" failed to rise in the hydrogen peroxide, giving us the time constraint of the infinite. We believe that the Hydrogen Peroxide, during the hot test segment, imposed some ill effect onto our nubbie.
THE STORY BEGINS:
It was a hot october afternoon when jlo, enor and rochelle were stirred from the dining hall and drawn mystically to the biology laboratory. We observed soft nubbies of varying thickness as they were expelled from the tweezers into solutions of different temperatures and compositions. The reaction perplexed us, however divine intervention in conjuction with the genius that is these budding scientists we have concluded:
1) Microscopic Organisms from Planet Farther infaltrated the soft glove like exterior of the nubbies causing them to scurry to the top of the solution of hydrogen peroxide. They are drawn to the nubbies because they are soooooo soft.
2) We believe that the reactants in causing these reactions are an improbable assembly of elements which when forced into the solution of hydrogen peroxide actively effect the maelstorm of motion.
Name: Date: 2003-10-08 15:26:06 Link to this Comment: 6849 |
Once apon a time we studied the Enzyme Concentration Effects on Rate. We got the following results:
Enzyme Concentration B:
1) 4 seconds
2) 4 seconds
3) 5 seconds
4) 4 seconds
Enzyme Concentration C:
1) 17 seconds
2) 16 seconds
3) 23 seconds
4) 16 seconds
Enzyme Concentration D:
1) 23 seconds
2) 20 seconds
3) 27 seconds
4) 19 seconds
Like a living organism, the enzyme appears to have peak performance levels at certain temperatures and pH levels. Also like a living organism, there is a limit to its possibilities (as is shown in our results). Based on this story, we think enzymes are ALIVE!!!
The end.
substrate level effects on rate + end product Name: Date: 2003-10-08 15:28:18 Link to this Comment: 6850 |
Effect of Enzyme Concentration on Rate Little Slip Name: Nomi alone Date: 2003-10-08 15:33:12 Link to this Comment: 6851 |
Hypothesis: Increasing the concentration of the enzyme peroxidase will increase the rate at which a paper slip (of a given size) will rise to the top of a beaker of H202 (of a given volume). Conversely, decreasing the concentration of peroxidase will decrease the rising rate. Concentration and rate should increase proportionally.
Concentration ~ Rising Rate.
My data were:
Concentration B - Most Concentrated
5 sec, 4 sec, 4 sec ---> avg. about 4 sec.
Concentration C - Intermediate Concentration
8 sec, 6 sec, 7 sec ---> avg. 7 sec.
Concentration D - Least Concentrated
24 sec, 17 sec, 19 sec ---> avg. 20 sec.
My data support my hypothsis. In the most concentrated enzyme, the paper rose in as little as 4 seconds -- quite quickly. On the other hand, the third and least concentrated enzyme caused the paper to take as much as 24 seconds to rise -- a very slow rate. Greater concentration induced greater rising speeds.
The function appears to be linear.
The paper slips allowed us to trace the rate at which oxygen bubbles rose, which, in turn, indicate the rate at which an enzyme reaction has occurred. [Is this true? What effects might the paper have on the accurracy of the experiment.]
What is an enzyme? Why does it increase the rate of chemical reactions (of "falling apart")?
I think an enzyme is a molecule or cluster of molecules that uses and stores energy (taken from the environment). The enzyme can then use or expend this stored energy toward a useful purpose: breaking molecules apart. In the case of 2H202 ----------> 2H20 + 02 , peroxidase speeds the natural process of dissociation (into water and oxygen) by GRABBING molecules of hydrogen peroxide and FORCING them apart, rather than leaving this breakdown to the natural but slow process of randomness.
How does an enzyme do this? An enzyme must be shaped in such a way that it can grab or latch onto, in this case, a molecule of H202. This means the peroxidase enzyme must be shaped so that it can fit or match hydrogen peroxide. Enzymes must also be capable of stretching themselves out a relatively large amount. Hence, peroxidase, having securely attached itself to the hydrogen peroxide, must STRETCH it out to the extent that the bonds of the molecules break down! The thus broken-off atoms then reform into oxygen and water, probably with the aid of different enzymes (enzymes with remarkable powers of CONTRACTION, rather than stretching, so they can stick different atoms together).
Alternatively, enzymes may be molecule clusters that possess a "saw-like" molecular compound capable of "sawing" apart other molecules' bonds every time it randomly bumps into them. Enzymes that assemble rather than disassemble molecules would have, in place of the "saw," a kind of molecular or atomic "glue" that sticks to select atoms and causes them to stick together more rapidly when they bump. However, this explanation seems unlikely because analysis of assembled molecules does not indicate the presence of special "glue" particles; so, enzymes, must do their work without using any other intermediary substance.
Whatever the means, I think enzymes speed up disocciation (and assembly) of atoms by making the atoms more likely to bump into each other and to break apart (or stick together).
Question: where do enzymes get the energy they use to put things together or break things apart? Maybe as a part of the process of respiration? Maybe that's why only living things have enzymes -- because only living things respire?
Oneself As A Biological Entity. I. The Pulse and I Name: Paul Grobstein Date: 2003-10-21 12:30:59 Link to this Comment: 6930 |
We will introduce you to some techniques for observing the pulse, and make a few observations on it together. It is then your task, in groups of three, to develop an interesting inquiry using those techniques to explore the regulation of the pulse ("who's in control?"), carry it out, and report your study (motivation, observations, interpretations) here in the lab forum area.
ABBY,NANCY,NATALYA,MELISSA Name: Date: 2003-10-21 14:36:49 Link to this Comment: 6932 |
DATA:
Over 12 seconds -
normal: 87.5 bpm
in 2, out 2: 70 bpm
in 4, out 4: 80 bpm
in 6, out 6: 85 bpm
Over 30 seconds -
normal: 86 bpm
in 2, out 2: 84 bpm
in 4, out 4: 78 bpm
in 6, out 6: 82 bpm
Analysis: Our first set of data was inconsistent with our hypothesis. There didn't appear to be a direct correlation between breathing and heart rate. Over a 30 second interval, the first three data points were consistent with our hypothesis, but the fourth was not, so we cannot draw any definite conclusions.
A possible reason for discrepancies is thats perhaps the body needs a specified amount of time for heart rate to change in accordance with breathing.
Pulse and smoking Name: Date: 2003-10-21 14:40:09 Link to this Comment: 6933 |
We took samples from two subjects: a smoker and a non smoker. Our samples consisted in 20 second intervals where we recorded heart rate before smoking one cigarrete, immediately after smoking a cigarrete and 10 minutes after smoking the cigarrete, to see how pulse was affected over time by smoking in both subjects.
Before:
Sarah (smoker) 81
La Toiya (non smoker) 78
Immediately after:
Sarah 96
La Toiya 90
After 10 minutes:
Sarah 87
LaToiya 78
Sarah's pulse increased by 15 after the cigarrete. After 10 minutes it went by 9 (7 beats away from what it was before smoking).
LaToiya's pulse increased by 12 after the cigarrete. It decreased by 12 after 10 minutes (back to the initial heart rate).
Our observations did not confirm our hypothesis in these two subjects, since our non smoker's pulse increased less than our smoker's pulse, and "recovered" faster.
tick tick tick Name: Group Supe Date: 2003-10-21 14:45:56 Link to this Comment: 6934 |
Hypothesis: Music Affects the Heart rate.
Methods:
Everyone in the group had their heart rate taken four times. The first time was a control with no music. The second time was with the subject listening to Cuban rap. The third time was a control. And the fourth time was with the subject listening to funky jazz.
Findings:
Control 1
Shafiqah: 99.01
Romina: 98.20
Paula: 81.74
Vanessa: 77.52
Cuban Rap
Shafiqah: 93.31
Romina: 88.63
Paula: 81.08
Vanessa: 69.93
Control 2
Shafiqah: 69.93
Romina: 85.11
Paula: 81.41
Vanessa: 62.70
Funky Jazz
Shafiqah: 93.17
Romina: 100.2
Paula: 80.86
Vanessa: 81.86
Conclusion
Our results were inconclusive. Different people had different results. For example, Shafiqah's highest was the 1st control and the lowest was in the second control. Romina's highest was funky jazz and the lowest was the second control. Paula's highest was the 1st control and the lowest was funky jazz. Vanessa's highest was funky jazz and the lowest was the 2nd control.
Some of the things that might have affected these results would be preferences in music, previous exposure to the songs. These two things appeared to result in lower heart rates for the people in the group. The second control resulted in lower heart rates which could be due to familiarity to the testing procedure as opposed to the first time when people might have been a little nervous or excited about the test.
Stay in School, Don't Do Drugs Name: Brianna Tw Date: 2003-10-21 14:52:32 Link to this Comment: 6935 |
Variables & Observations:
Coldplay (mellow): 93.19, 94.96, 89.71 --> 92.62
Techno Music: 91.63, 93.92, 97.27 --> 94.27
Sad Thoughts: 96.8, 95.57, 92.33 --> 94.9
Angry Thoughts: 98.06, 93.77, 94.66 --> 95.49
Smoking: 124.8, 113, 107.5 --> 115.1
Height: n/a
Hypothesis:
Heart rate is sensitive to external variables.
Discussions:
External variables affect the heart rate.
Using our data collected from testing mental variables (ie. Sad Thoughts and Angry Thoughts), perhaps it is partially possible for humans to mentally control their heart rates. However, the heart rate seemed to adjust closer to the resting heart rate as time progressed.
Smoking is bad.
Name: Date: 2003-10-21 14:54:18 Link to this Comment: 6936 |
Thanks.
Katie Ottati, Bessy Guevara, Laura Wolfe Name: Bessy Guev Date: 2003-10-21 14:54:46 Link to this Comment: 6937 |
Hypothesis for breathing: The less oxygen you take in, the higher the heart rate. e think the heart has to work faster when there is less oxygen coming in, and we've observed that when you hold your breath your heart seems to be pounding.
Data:
Control (sitting without moving or talking, breathing normally)
1) 69 beats/min
2) 75 beats/min
3) 93 beats/min
Holding breath
1) 64.5 beats/min
2) 92 beats/min
3) 132 beats/min
Deep Breathing
1) 69 beats/min
2) 87 beats/min
3) 87 beats/min
Conclusion: some data increased with the lack of air, which would support our hypothesis, but not all the data followed the same pattern. Therefore, we are unable to support the hypothesis with this data.
hypothesis for activity: We think more activity would increase the heart rate. We used only one subject.
Control = 93 beats/min
Resting= 75 beats/min
After jogging in place = 150 beats/min
Conclusion: Our data supports our hypothesis.
Lab Name: Justine, S Date: 2003-10-21 14:58:55 Link to this Comment: 6938 |
Method:
We retrieved various pieces of art retrieved from different websites. We had one "dark" piece, one "light" piece, and one "scary/shocking" piece for each. We showed the images to each group member and recorded her reaction.
Justine
Light: small decrease in amplitude, no change in frequency
Shock: large decrease in amplitude, " "
Dark: medium decrease in amplitude, but an overall wave pattern, " "
Su-Lyn
Light: Amplitude falls, no change in frequency
Dark: increase in amplitude, no change in frequency
Shocking: decrease in amplitude w/a slight wave pattern, no change in frequency
Brittany
Light: smaller decrease in amplitude, no change in frequency
Dark: huge decrease in amplitude, no change in frequency
Happy: increase in amplitude, increase in frequency
Methods: Each member of the group searched the web and found different websites that showed different pictures of art.
Conclusions
First off, the main thing we learned in this lab is that visual stimulus *does* affect heart rate. No matter what image we showed a given group member, she had *some* sort of reaction to it.
The observations support our hypothesis. However, we did not learn exactly how, as there were a number of factors we could not control. For example, the picture was *not* the only thing each group member saw, the art we used varied across different genres/styles/subjects, and we did not have a wide enough sample of different types of images to draw any conclusions about what type of image affects heartrate in what way. We also couldn't be 100% sure what changes were attributed to the visual stimuli themselves and what changes were attributed to the physical act of focusing on the images. Additionally, we had a huge number of technical difficulties, including slow internet, malfunctioning equipment, and difficulty in finding images. To determine with greater accuracy what types of visual stimuli affect heartrate in specific ways, we'd need more time, more subjects, and more images.
Jump Around Name: Stefanie Date: 2003-10-22 14:26:27 Link to this Comment: 6945 |
We hypothesize that physical activity will increase the heart rate of a person. In order to test this hypothesis we had each member of the group take their standing heart rate. Each member was then subject to a "rigorous" physical test (25 jumping jacks), a second reading was taken immediately following the physical activity.
Data:
Stefanie:
Resting: 72 beats/minute
After exercise: 112 beats/minute
Increase in beats/minute: 40
Julia:
Resting: 76 beats/minute
After exercise: 116 beats/minute
Increase in beats/minute: 40
Alison:
Resting: 92 beats/minute
After exercise: 144 beats/minute
Increase in beats/minute: 52
Mariya:
Resting: 90 beats/minute
After exercise: 120 beats/minute
Increase in beats/minute: 30
Our data supports the hypothesis that exercise will increase a person's heart rate.
Therefore, from our observations, we may further hypothesize that other variables such as physical fitness, or pre-existing health conditions may also affect the number of beats per minute. Stefanie is an athlete who exercises seven days a week, and had both the lowest resting number of beats per minute and the lowest following the physical test. Julia, who lives in Brecon and exercises at the gym about once a week, had the second lowest standing number of beats per minute and the second lowest following the physical test. Mariya, who suffers from asthma which impedes her ability to exercise regularly, had a significantly higher resting heart rate and also a higher rate following the physical test. Alison, who would rather die than exercise, had the highest resting rate and the largest increase in beats per minute following the physical test.
Other variables might include: anxiety regarding the act of performing jumping jacks in front of laughing peers (Alison), the pace at which each subject performed their jumping jacks (Mariya). We suspect that Mariya, who was not as enthusiastic about the testing (and was wearing heels) performed her jacks less rigrously than the other subjects. This might explain why she had the lowest increase in beats between her standing and post-activity heart rate.
Name: Date: 2003-10-22 14:33:40 Link to this Comment: 6946 |
We decided to investigate the effects of proximity to another classmate, as well as physical contact with another classmate, on a student's heart rate. Specifically, we measured Patty's seated heart rate while looking at the wall (baseline rate), while looking at Megan from a comfortable distance of about 4 feet, while looking at Megan from a culturally uncomfortable distance of about 1 foot, as well as while Megan patted her shoulder gently and, lastly, gave her a forceful shoulder massage.
Our hypothesis: As compared to the base rate, increasing proximity to another and increasingly forceful touch will correspond with an increase in the seated person's heart rate. That is, a person at a comfortable distance will cause a slight increase in HR from the base rate (of sitting alone), a person at an uncomfortable distance will increase HR even more, a gentle touch will yield an HR that is higher still, and a forceful touch will cause the highest HR of all.
Name: Date: 2003-10-22 14:33:53 Link to this Comment: 6947 |
We hypothesize that all of the following things will increase our heart rates:
Holding our breath, Exercise, Smoking
Normal Resting Heart Rate:
Maggie: 60 bpm
Anna: 94 bpm
Adina: 63 bpm
Melissa: 93 bpm
Heart rate while holding breath:
Maggie: 72
Anna: 105
Adina: 72
Melissa: 93
Heart rate while performing abdominal exercise (which does not include Movement):
Maggie: 138
Adina: 108
Anna: 159
Melissa: N/A
Heart rate immediately after smoking one cigarette:
Anna: 108
Melissa: 96
From these observations, it appears that heart rate is affected by outside viariables as we have deduced from the above tests. True to our hypothesis, exercise greatly affected heart rate. Holding breath increased heart rate slightly as did smoking. However, there was not as dramatic a difference in these last two cases.
Had we more time, and funding for beds, we would have liked to have ruled out excess stimuli that could have had an affect on the resting heartbeats of our subjects. If we were to test them overnight, it would be interesting to see how dreams affect one's heartbeat. And had we male subjects to observe, how their heartbeat differs from females'.
Heart Rate Name: Lindsay, A Date: 2003-10-22 14:37:08 Link to this Comment: 6948 |
We hypothesized that standing would increase our control heart rates (sitting down) and that jogging would increase it to an even greater extent.
1. Sitting Down:
Lindsay: 87 bpm
Alice: 99 bpm
Rochelle: 84 bpm
Christina: 84 bpm
2. Standing
Lindsay: 93 bpm
Alice: 102 bpm
Rochelle: 96 bpm
Christina: 102 bpm
3. After Jogging
Lindsay: 105 bpm
Alice: 180 bpm
Rochelle: 165 bpm
Christina: 105
Everyone's heart rate increased somewhat while standing, and after jogging around the hall for about thirty seconds it increased significantly for some of us and very little for others. This may be due to the fact that some of us get more exercise on a regular basis. Also some people may have taken longer to run although we all ran the same distance.
We also tested holding our breath while taking our heart rates.
Lindsay: 93 bpm
Alice: 87 bpm
Rochelle: 87 bpm
Christina: 72 bpm
We did not notice a significant difference in the frequencies of heart rates while holding our breaths. However, amplitude was lower than for the other tests and seemed to increase while taking the heart rates for Rochelle and Christina. We inferred from this that after holding our breath for a few seconds, our hearts start to work harder to circulate blood.
From this data we can conclude that some factors that affect heart rate are sitting/standing position, exercise, and respiration.
The Affected Heart Rate Name: enor lara Date: 2003-10-22 14:42:57 Link to this Comment: 6949 |
Hypothesis: External factors will affect the heart rate and amplitude.
Observations:
Normal Heart Rates
Lara: 88 beats per minute
Ramatu: 88 beats per minute
For the second part of our experiment we told the subject jokes (why was Helen Keller's ear red? Her iron rang. + What did the redneck boyfriend say to his redneck girlfriend when he wanted to break up? We can still be cousins) and read their affected heart rate after.
Lara: We may have miscalculated the heart rate since the bar should have probobly been lowered, however it read 72 beats per minute - The more noticable change was the amplitude. At the highest point - the amplitude increased by 10 millivolts.
Ramatu: again - this calculation may be wrong - 54 beats per minute
But the more noticable amplitude change 10 millivolts.
The third part of our experiment focused on what happens to your heart rate when you lie. Two questions were asked wherein the subject told the truth - then a third question was asked and a lie was told. The answered question for the third was an OBVIOUS lie.
Lara : When she told the truth the amplitude remained steady however, when she lied the amplitude fluctuated. Heart rate 88 beats per minute.
Ramatu: Same results as Lara
Our fourth experiment tested heart rate when pain was inflicted. The pain was in the form of flicks and pinches.
Lara: Amplitude increased by 20 mv when the first pinch occured. The second, more expected time, the amplitude increased by 5. The heart rate remained the same.
Ramatu: Before flick the amplitude was steady - after the flick the amplitude went crazy and remained this way until the end of the trial even though there were two more flicks coming.
continued! Name: Nomi et. a Date: 2003-10-22 14:45:20 Link to this Comment: 6950 |
We took measurements at 20 second intervals and multiplied the number of beats (number of graph peaks) by three to get beats/minute. These are the data we collected:
At Rest (Baseline): 69 beats/min
Comfortable distance: (about 4-5 feet) 69 beats/min
Uncomfortable distance: (about 1 foot) 69 beats/min
Light Touch: 78 beats/min
Forceful Touch: 81 beats/min
Our data are partially consistent with our hypothesis but partially inconsistent. The fact that Patty's heart rate remained the same regardless of whether Megan was absent, near her, or very very near her suggests that proximity of another person does NOT affect heart rate (we had hypothesized that it would cause an increase). However, the increase from 69 beats/min to 78 beats/min when Megan touched Patty, and the subsequent increase to 81 beats per minute when Megan gave her a forceful massage, suggests a clear trend: having someone touch you will increase your heart rate, and the harder a person touches you, the more your heart rate will increase. This piece of our data is consistent with our hypothesis. Our data suggest, in sum, that proximity has no effect on heart rate, but that heart rate increases proportionally with the forcefulness of touch.
Why? We think physical contact stimulates psychological responses associated with anxiety, which causes an increase in heart rate. With further investigation, we might test whether our findings are statistically significant (not due to chance) and, if so, why that might be so.
Name: Date: 2003-10-22 14:50:29 Link to this Comment: 6952 |
Hypotheses: Heart rate is increased by running, lying, and holding your breath.
Maria: heart rate when...
resting 114 beats/min
lying 114 beats/min
running 162 beats/min
holding breath 114 beats/min
Flicka's heart rate when....,
resting 90 beats/min
lying 114 beats/min
running 168 beats/min
holding breath 111 beats/min
Katy's heart rate when....
resting 84 beats/min
lying 84 beats/min
running 159 beats/min
holding breath 75 beats/min
Our observations showed that running had a big impact on one's heat rate, greatly increasing in each case. However, lying had almost no impact on heart rate, except for Flicka's case. Holding breath was more ambiguous because it increased in some cases and decreased in others.
Oneself As A Biological Entity. II. Reacting Name: Paul Grobstein Date: 2003-10-27 18:18:43 Link to this Comment: 7015 |
So, how about when something touches us and we move? What sorts of smaller things are going on? That's what we want to look into today.
A touch starts signals moving in sensory neurons which eventually cause signals to move in motor neurons which eventually cause muscle contractions and movement. How long does it take to move when one is touched? And how much of that time is the time it takes for signals to move from the endings of sensory neurons to the endings of motor neurons? How much of that time is the time it takes muscles to contract and cause movement? That's what we'll be looking at in the first part of the lab.
In the second part of the lab, you and your team should develop your own questions and observation protocols to explore some interesting aspect of what is going on in reacting. For example, would you expect the time taken to be different if the stimulus occurred at a more distant location on the body? On the same side as the response as opposed to the opposite side? If the response was with your dominant or your non-dominant hand? Would you expect the time to change if you were tired? preoccupied? had recently had coffee? Is it the time that signals take within the nervous system that changes or the time for muscles to contract and cause movement? Or both?
Don't try and answer ALL the questions. Pick one (or think up one) that you're interested in and have a guess about. And collect enough data so you have some confidence in your conclusions about that situation. And write up your question/hypothesis, observations, conclusions in the lab forum.
dominant hand vs latency Name: Nancy and Date: 2003-10-28 14:34:05 Link to this Comment: 7025 |
HYPOTHESIS: The dominant hand will have a faster reaction time than the subordinate hand.
Note: we are both right handed.
Nancy Right Hand:
trial one
- TTL latency-- .22
- Latency one-- .11
- Latency two-- .11
trial two
- TTL-- .14
- one-- .08
- two-- .06
Talia right hand:
trial one
- TTL-- .20
- one-- .04
- two-- .16
trial two
- TTL-- .35
- one-- .31
- two-- .04
Nancy Left hand
trial one
TTL-- .29
-one-- .19
- two-- .10
trial two
TTL-- .57
-one-- .52
- two-- .05
Talia Left hand
trial one
TTL: .24
one-- .21
two-- .03
trial two
TTL-- .26
-one-- .22
- two-- .04
OBSERVATIONS: We observed that there seemed to be faster respnse times in the dominant hand. This was the case in three out of four trials. The fourth trial could have been influenced by a numer of factors, including outside noise, thought patterns, etc.
Time between stimulus and reaction in dominant and Name: Charlotte Date: 2003-10-28 14:54:27 Link to this Comment: 7026 |
Hypothesis: With the assumption that the dominant hand is more used than the non-dominant hand, the time of reaction for the dominant hand would occur in less time than it would for the non-dominant hand.
Observations in the thumb of the dominant hand:
1. muscle activity 5.93
total time of reaction 5.97
initial time of stimulus 5.56
Latency 1 = 0.37
Latency 2 = 0.04
2. muscle activity 4.2
total time of reaction 4.29
initial time of stimulus 3.98
Latency 1 = 0.22
Latency 2 = 0.09
3. Muscle activity 4.5
total time of reaction 4.61
initial time of stimulus 4.35
Latency 1=0.15
Latency 2=0.11
Observations in the thumb of the non-dominant hand:
1. muscle activity 4.62
total time of reaction 4.69
initial time of stimulus 4.48
Latency 1= 0.14
Latency 2=0.07
2. muscle activity 4.23
total time of reaction 4.27
initial time of stimulus 4.01
Latency 1 = 0.26
Latency 2 = 0.04
3. muscle activity 4.84
total time of reaction 4.86
initial time of stimulus 4.67
Latency 1=0.17
Latency 2=0.02
Conclusion:
Our initial assumption that the dominant hand would react faster to the stimulus was proved wrong: the time between the stimulus and the movement of the muscle is approximately the same and sometimes faster in the non-dominant hand and the time of the muscle contraction shows a faster movement in the non-dominant hand. Therefore, there is no correlation between a dominant side of the body and its time of reaction and movement.
Manuela, Katie, Bessy, LaToiya Name: Date: 2003-10-28 14:55:08 Link to this Comment: 7027 |
Katie: Latency 1 (average) 0.2 Latency 2 (average) 0.05
Manuela: Latency 1 (average) 0.075 Latency 2 (average) 0.041
Bessy: Latency 1 (average) 0.2 Latency 2 (average) 0.05
La Toiya: Latency 1 (average) 0.22 Latency 2 (average) 0.06
Our hypothesis states that when a person can see the stimulus coming, both latency periods will be shorter.
Eyes open, watching stimulus:
Katie: Latency 1 (average) 0.07 Latency 2 (average) 0.03
Manuela: Latency 1 (average) 0.02 Latency 2 (average) 0.062
Bessy: Latency 1 (average) 0.03 Latency 2 (average) 0.06
La Toiya: Latency 1 (average) 0.04 Latency 2 (average) 0.07
Our hypothesis was only partially correct. The response time (Latency 1) is shorter, but muscle movement (Latency 2) still takes about the same amount of time.
Melissa Hope, Abby Fritz Name: Date: 2003-10-28 15:01:45 Link to this Comment: 7028 |
DATA:
Dominant --
Melissa: TL - .383, L1 - .370, L2 - .330
Abby: TL - .177, L1 - .148, L2 - .136
Non-dominant --
Melissa: TL - .266, L1 - .246, L2 - .041
Abby: TL - .291, L1 - .246, L2 - .047
Summary: After performing three trials on each variable (dominant/non-dominant), we averaged the times and came up with the data presented. Abby's data was consistent with the hypothesis, but Melissa's was not. The data therefore was could not support this hypothesis or the opposite of this hypothesis, because of the inconsistency of our data.
We found that L1 was consistently slower than L2, but the lag time varied significantly. Why?
These discrepancies may have been due to the fact that stimulus was applied to the same arm in both experiments.
Name: Sarah, Nat Date: 2003-10-28 15:09:15 Link to this Comment: 7029 |
Test Subject 1 (Natalya):
Latency 1(between stimulus and muscle contraction): .18, .24, .12
Latency 2 (between muscle contraction and response): .07, .07, .07
Test Subject 2 (Sarah):
Latency 1: .28, .18, .16
Latency 2: .12, .07, .09
Test Subject 3 (Brittany):
Latency 1: .04, .21, .29
Latency 2: .06, .07, .06
For the second part of the lab, we attempted to determine whether or not the location of the stimulus on the test subject's body affected their reaction time. We tested 3 stimulus locations: the original data from tapping on the leg, and then 2 new locations (3 trials each) on the head and the foot. Our hypothesis was the the closer the stimulus is to the brain, the faster the reaction time. Therefore, we hypothesized that the head tap would produce the fastest reaction time and the foot tap would produce the slowest. Here is our data in seconds:
Test Subject 1:
(Natalya - Head):
Latency 1: .27, .16, .11 Average: .18
Latency 2: .05, .51, .06 Average: .20
(Natalya - Ankle):
Latency 1: .24, .28, .15 Average: .22
Latency 2: .05, .05, .12 Average: .07
Test Subject 2:
(Sarah - Head):
Latency 1: .17, .19, .13 Average: .16
Latency 2: .05, .10, .09 Average: .08
(Sarah - Ankle):
Latency 1: .25, .14, .20 Average: .19
Latency 2: .07, .15, .07 Average: .09
Test Subject 3:
(Brittany - Head):
Latency 1: .22, .22, .19 Average: .21
Latency 2: .07, .05, .08 Average: .06
(Brittany - Ankle):
Latency 1: .26, .36, .27 Average: .29
Latency 2: .06, .03, .04 Average: .04
Overall, our results for the latency 1 period (from the stimulus to the muscle action) is faster when the stimulus location was closer to the head. But the latency 2 period (from the muscle action to the response) varied by test subject. So though our results appear to corroborate our hypothesis, the results are not conclusive. Our hypothesis for further research is that the latency 2 period is independent of stimulus location in relation to the head. We do believe that our data supports our claim for at least the latency 1 period.
Name: Date: 2003-10-28 15:12:32 Link to this Comment: 7030 |
Hypothesis: Our hypothesis for this experiment was to test the difference in reaction between the dominant hand and the other. Both subjects were hit on their knee in the area above the patella.
Results:
Vanessa:
- standing up during both trails
Right Hand: (dominant)
Latency Total: -.240 (Trial 1)
Latency Total: -1.05 (Trial 2)
Latency Total: -1.186 (Trial 3)
Left Hand:
Latency Total: -.081 (Trial 1)
Latency Total: -.107 (Trial 2)
Latency Total: -.167 (Trial 3)
Justine:
- sitting down in the chair
Right Hand: (dominant)
Latency Total:-.187 (Trial 1)
Latency Total:-.198 (Trial 2)
Latency Total: -.184 (Trial 3)
Left Hand:
Latency Total:-. 194 (Trial 1)
Latency Total: -.136 (Trial 2)
Latency Total: -.152 (Trial 3)
Conclusion:
See first conclusion (ie experiment done by the first group)
Right/Left hand dominance Name: Date: 2003-10-29 14:38:00 Link to this Comment: 7037 |
We tested the muscle reaction times on both our left and right hands. All of us are right-handed. We hypothesized that the muscle contraction times would be faster on our right hands.
Data (Average of 3 tests):
Margaret:
Right Hand: 0.05 milliseconds
Left Hand: 0.06 milliseconds
Mariya:
Right Hand: 0.03 milliseconds
Left Hand: 0.06 milliseconds
Lindsay:
Right Hand: 0.03 milliseconds
Left Hand: 0.03 milliseconds
The data seems to have supported our hypothesis. Lindsay's reactions could be explained by the fact that she was ambidextrous as a child but got used to using her right hand to write. The muscles in the right hand are more trained to reacting to stimuli. This is why it takes them less time to shorten and press the button. It was interesting that the times between the initial stimulus and beginning of muscle reaction did not vary significantly between hands. This could lead to a further hypothesis that since the arms are equidistant from the central nervous system, it takes the left and right equal amounts of time to process the reaction signal.
Name: Date: 2003-10-29 14:50:39 Link to this Comment: 7038 |
Hypothesis: We observed the reaction times of the dominant vs. the non-dominant hands. We hypothesized that the dominant hand would have a faster reaction time than the non-dominant hand.
Note: Each of the women observed was dominant in her right hand.
Key:
first figure = time from stimulus to muscle activity
second figure = time from muscle activity to response
Dominant:
Anna
1.) 90 ms
43 ms
2.) 4 ms
28ms
3.) 78 ms
39 ms
J'London
1.) 140 ms
64 ms
2.) 126 ms
63 ms
3.) 120 ms
31 ms
Enor
1.) 185 ms
29 ms
2.) 252 ms
21 ms
3.) 214 ms
36 ms
Non-Dominant:
Anna
1.) 153 ms
40 ms
2.) 143 ms
27 ms
3.) 141 ms
28 ms
J'London
1.) 77 ms
92 ms
2.) 154 ms
50 ms
3.) 121 ms
48 ms
Enor
1.) 97 ms
32 ms
2.) 150 ms
62 ms
3.) 236 ms
69 ms
Anna's data was consistent with our hypothesis in regards to the time from the stimulus to muscle activity; however, J'London's and Enor's data was inconsistent. In regards to the time from muscle activity to response, we did not see enough of a change in time from dominant to non-dominant hand for it to be significant.
We cannot say for sure if our hypothesis was correct or not based on our data. Perhaps there is no difference from dominant to non-dominant hand. We attribute our inconsistencies in observations to expectancy, which hand was tested first, desensitization of reactions, etc.
Name: Date: 2003-10-29 14:50:47 Link to this Comment: 7039 |
We studied the effect of distance of stimulus from the brain on reaction time. The body parts we tested were upper arm, ankle, and head, and we tested each body part of each person three times. We hypothesized that the further from the brain the stimulus, the longer the response time would be.
Average Results:
Alison:
Arm: 0.17 sec
Head: 0.21 sec
Ankle: 0.38 sec
Adina:
Arm: 0.51 sec
Head: 0.23 sec
Ankle: 0.35 sec
Julia:
Arm: 0.40 sec
Head: 0.37 sec
Ankle: 0.41 sec
These results do not support our hypothesis. There are other factors that influence reaction time but distance does not appear to be significant.
Name: Date: 2003-10-29 15:06:21 Link to this Comment: 7040 |
Hypothesis: Poking people in places farther away from the brain will take them longer to react to the stimulus.
Alice:
ankle: 0.24-0.04
knee: 0.17-0.04
chest: 0.19-0.04
foot: 0.34-0.02
calf: 0.18-0.04
back: 0.19-0.03
calf: 0.20-0.02
wrist: 0.18-0.04
forehead: 0.19-0.03
Flicka:
b. knee: -0.54-0.03
forearm: 0.34-0.01
neck: 0.23-0.03
thigh: 0.43-0.01
elbow: 0.12-0.01
b of shoulder: 0.22-0.01
calf: 0.49-0.01
l. hand: 0.26-0.03
forehead: 0.38-0.01
Conclusion: We decided that there is no correlation between the poking and the distance from the brain because in some cases, the reaction time was greater when stimulated farther away from the brain. Our data was inconsistent, which leads us to conclude that there are other factors that influence the reaction time.
The Effect of Right vs. Left Hand on Stimulus-Resp Name: Denise, Me Date: 2003-10-29 15:06:23 Link to this Comment: 7041 |
We tested the effect of using the right vs. left hand to push a button on total response time. Does the hand used make a difference in total reaction time?
Hypothesis: Total reaction time will be higher for the left hand in right-handed people than for the right hand. This will occur because right-handed people have better developed nerve pathways and muscles on the right side of the body than the left.
We took 5 measurements for each the right and the left hand in three subjects (a total of 30 pieces of data collected). We then averaged the 5 left- and right-hand data points for each person, resulting in one figure for each hand of each person. To keep variables other than the experimental (which hand) constant, subjects positioned their arm on the table and held the button in the same way each time. The administrator-of-touch hit the subject in the same place each trial with as constant a force as possible. The subjects closed their eyes so they would not overly anticipate the time of touch administration.
Our averages were as followed:
Total Average Time between stimulus and response
Subject A
right hand- .18
left hand - .20
Subject B
right hand- .19
left hand- .18
Subject C
right hand - .20
left hand - .16
These data do not support our hypothesis. Although the left hand response time was longer for one subject (A), it was actually shorter for the other two cases -- the reverse of our hypothesis. Moreover, the differences among all of the data points -- no more than .04 in total, and no more than .02 in all but one cases -- do not appear significantly / proportionally large enough to suggest any significant trend. Rather, the differences in response time seem attributable to chance / experimental error.
The fact that the left hand response time was slightly longer in one case and slightly shorter in two cases suggests that these differences, rather than representing a trend, are randomly distributed around some average. This means that the response times for right vs. left hands are probably NOT significantly different from each other, as a whole. Nor do they seem to be significantly different for any one subject we tested.
Our results also indicate, by induction, that the neural pathways and muscles involved with the left vs. right hands -- and perhaps the left and right sides of the body? -- do not significantly differ.
Muscle Reaction Time Name: Patty Date: 2003-10-29 15:20:29 Link to this Comment: 7042 |
We hypothesized that the closer the probe was located to the brain on the body, the shorter the distance would be for the message to travel from the probed area of the body-to the brain-and back to the subjects hand for a response.
We took 3 samples of responses from being probed in 4 diffrent parts of the body: 1) The thigh, 2) the toe, 3) the shoulder, and 4) the forehead. We wanted to use body parts that we 1) a moderately far place on the body as a type of control, 2) the farthest place on the body from the brain, 3) a place that is between the brain and the hand that will be responding, and 4) the place closest to the brain. We wanted to observe which place would elicit the quickest response.
L1 Neural Processing
L2 Motor Response
TL L1+ L2
Thigh Test
Trial 1 L1= .3147
L2= .0123
TL= .327
Trial 2
L1= -.066
L2= .3185
TL= .3845
Trial 3
L1= -.014
L2= .0405
L3= .0265
Toe Test
Trial 1
L1= .1841
L2=.2364
TL= .4205
Trial 2
L1= -.005
L2= .1076
TL= .1026
Trial 3
L1= .0801
L2= .2328
TL= .3129
Shoulder Test
Trial 1 L1= .1275
L2= .1678
TL= .2953
Trial 2
L1= .0524
L2= -.173
TL= -.1206
Trial 3
L1=.0826
L2=.0761
TL= .1587
Forhead Test
Trial 1
L1= .059
L2= .0761
TL= .6661
Trial 2
L1= .0847
L2= .1325
TL= .9795
Trial 3
L1= .125
L2=.0509
TL= .1759
We determined that the shortest time between L1 and L2 on average would indicate that the travel time of the neural message to response was fastest. .246 was the average TL for our control (the thigh.) .278 was the average TL for the toe test, which supported our hypothesis. .3337 was the average TL for the shoulder test, which was extremely suprizing to us, as it would have little space between the hand and the brain and this response time took longer than the toe. (we poked on the arm that we were responding with.) And finally, the average TL on the forehead test was .607 which was far greater than we had expected.
Oneself As A Biological Entity. III. Thinking Name: Paul Grobstein Date: 2003-11-03 21:10:45 Link to this Comment: 7097 |
So, what about "thinking"? Can that be "quantified in time and space"? Its an interesting question, first asked explicitly in the late 1800's with a very clever set of observations then requiring elaborate equipment. Today we can make the same observations more easily. See Time to Think?.
The observational set up allows one to measure various kinds of thinking, as well as to test hypotheses about how they are related to one another. Once you get the hang of it, you can/should develop your own hypotheses about what might or might not influence the various kinds of thinking time. And develop your own experiments. Do one as a group in class. And you're free to do additional ones any place you can find a computer.
Remember that we've reached a phase where we'd like to have our hypotheses and observations sufficiently in hand so that we can generate as conclusions something more than "more data is needed".
Name: Date: 2003-11-04 13:04:52 Link to this Comment: 7103 |
Hypothesis: Poking people in places farther away from the brain will take them longer to react to the stimulus.
Alice:
ankle: 0.24-0.04
knee: 0.17-0.04
chest: 0.19-0.04
foot: 0.34-0.02
calf: 0.18-0.04
back: 0.19-0.03
calf: 0.20-0.02
wrist: 0.18-0.04
forehead: 0.19-0.03
Flicka:
b. knee: -0.54-0.03
forearm: 0.34-0.01
neck: 0.23-0.03
thigh: 0.43-0.01
elbow: 0.12-0.01
b of shoulder: 0.22-0.01
calf: 0.49-0.01
l. hand: 0.26-0.03
forehead: 0.38-0.01
Conclusion: We decided that there is no correlation between the poking and the distance from the brain because in some cases, the reaction time was greater when stimulated farther away from the brain. Our data was inconsistent, which leads us to conclude that there are other factors that influence the reaction time.
Name: Group Supe Date: 2003-11-04 14:55:37 Link to this Comment: 7104 |
Hypothesis: Foreign language speakers will react slower to English instructions b/c it takes longer to process.
Observations:
These are only the averages out of 10 trials.
Romina (non native speaker)
Case 1: 250 sd:16
Case 2: 340 sd 82
Case 3: 495 sd 49
Case 4: 968 sd 323
Toiya (English speaker)
Case 1: 234 sd 16
Case 2: 320 sd 65
Case 3: 514 sd 78
Case 4: 555 sd 147
*sd= standard deviation
Overall, our results supported our hypothesis. It seemed that Romina had a significantly slower reaction time than Toiya, especially when the instructions became more complicated, i.e Case 4. In the case of Case 3, Romina pressed the button at the wrong time several times causing her scores to be randomly deleted. She therefore had to pay closer attention which may have contributed to her faster score.
Reaxn Name: emily & mi Date: 2003-11-04 14:56:25 Link to this Comment: 7105 |
Michelle
Case 1: 207 ms, 13 ms.
Case 2: 308 ms, 97 ms.
Case 3: 474 ms, 131 ms.
Case 4: 471 ms, 131 ms.
Average:
Case 1: 313.39 ms.
Case 2: 376.59 ms.
Case 3: 633.34 ms.
Case 4: 773.55 ms.
Conclusions:
By analyzing the steady increase in reaction time, it is apparent that thinking and reacting are two different processes. They are certainly related, but represent very different demands on the brain. When the exercise demanded a simple reaction, response time was much quicker. As the demands increased, so did the response time.
Brain Reaction Name: Brianna Date: 2003-11-04 14:57:32 Link to this Comment: 7106 |
Time to Act: 245 p/m 62
" Think: 85 p/m 93
" Read: 177 p/m 119
" Negate: 175 p/m 193
I thought that the more trials I did, the faster my time would become, because my brain would adjust/anticipate the next action of the program. However, it happened that the last two trials of each test were the worst times. Additionally, outside distractions increased my response time. So, there was no consistency in the trials of each test, when isolated, probably due to outside distraction. However, as I suspected, the more processes the test had, the longer it took my brain to react. In other words, each test took longer and longer to complete. However, my thinking time was less than half the time it took me for the other processes. I anticipated the act time to be the least, because it was the least complex of the processes, basically muscle reaction. However, it was longest. The think time was the least. This leads me to the conclusion that thinking and reacting are two different processes.
Time and Thinking Name: Sarah and Date: 2003-11-04 14:59:34 Link to this Comment: 7107 |
Test Subject 1 (Sarah):
A: 282, sd: 47
TA: 392, sd: 58
RTA: 490, sd: 71
RNTA: 585, sd: 164
Test Subject 2 (Natalya):
A: 241, sd: 21
TA: 276, sd: 47
RTA: 428, sd: 88
RNTA: 455, sd: 85
Next, we decided to investigate how chewing gum affected our thinking time. We used the same method as in the first set of trials, but each chewed a piece of Dentyne Ice while conducting the new trials. Sarah hypothesized that she would perform better while chewing gum, while Natalya had the opposite hypothesis for herself. These hypotheses were based on previous experience and personal preferences. Here are the data:
Sarah (test subject 1):
A: 249, sd: 80
TA: 384, sd: 85
RTA: 622, sd: 141
RNTA: 569, sd: 177
Natalya (test subject 2):
A: 284, sd: 28
TA: 403, sd: 130
RTA: 539, sd: 72
RNTA: 740, sd: 393
Sarah's hypothesis for herself was supported by the data because overall, her average times for every test were faster when chewing gum. The standard deviations for each of her tests while chewing gum were bigger though, than the original test, showing that while in general, the second trial was faster, it also had a bigger variety. Natalya's hypothesis for herself held true in all cases as well. However, her standard deviations were also larger, except in the RTA case. But the RNTA case shows an especially large standard deviation during her second trial while chewing gum.
Overall we can't conclusively state that chewing gum either helps or hinders thinking time, but we can state that our individual hypotheses based on personal preference were correct.
Melissa, nancy, Abby Name: nancy abby Date: 2003-11-04 15:04:40 Link to this Comment: 7108 |
Hypothesis 2: Performing the second group in a reversed order, our case 4 (Originially case 1) times would decrease due to prolonged focus on the previous three tests.
Method: We performed 10 trials twice for each of the four cases. The first group of data was simply following the case as laid out. For the second group of data, the sequence was performed in reverse order- from case 4 to case 1. The data is as follows:
MELISSA:
Group 1
subj_id trial_type avg sd num_trials
675 A 255 30 10
675 TA 325 99 10
675 RTA 559 140 10
675 RNTA 495 74 10
Group 2
subj_id trial_type avg sd num_trials
686 A 270 65 10
686 TA 302 57 10
686 RTA 492 148 10
686 RNTA 430 105 10
NANCY:
Group 1
subj_id trial_type avg sd num_trials
689 A 270 58 10
689 TA 371 96 10
689 RTA 501 56 10
689 RNTA 578 119 10
Group 2
subj_id trial_type avg sd num_trials
695 A 271 31 10
695 TA 362 57 10
695 RTA 532 90 10
695 RNTA 449 31 10
ABBY:
Group 1
subj_id trial_type avg sd num_trials
690 A 334 142 10
690 TA 303 65 10
690 RTA 578 126 10
690 RNTA 597 51 10
Group 2
subj_id trial_type avg sd num_trials
696 A 244 42 10
696 TA 370 63 10
696 RTA 522 99 10
696 RNTA 568 138 10
Summary: From our results, our results were not consist with our hypothesis- actually becoming the opposite of the expected in two of the three case subjects.
We observed that when performing task 4 (the most difficult) first a opposed to last, times decreased for all of us.
Laura Wolfe, Katie Ottati Name: Date: 2003-11-04 15:07:58 Link to this Comment: 7109 |
When acting/talking, subjects carried on a conversation while completing the "Act" excercise.
Subject 1 -
Act: 234 +/- 27
Acting & thinking: 304 +/- 28
Reading, thinking, acting: 553 +/- 124
Reading, thinking, negating, acting: 722 +/- 522
*Acting, talking: 320 +/- 19
Subject 2 -
Act; 233 +/- 25
Thinking, acting: 398 +/- 81
Reading, thinking, acting: 664+/- 107
Reading, thinking, negating, acting: 901 +/- 142
* Acting, talking: 464 +/- 145
Conclusion: Our data supports our hypothesis. Subject 2, for example, had a diference of 165 milliseconds between "act" and "thinking and acting", and a 66 millisecond difference between "thinking and acting" and "talking and acting". It appears that talking requires thought and thus slows the reation time.
Time to think Name: Date: 2003-11-04 15:11:12 Link to this Comment: 7110 |
Manuela A 191 10 5 Average reactions: 312.11
Manuela TA 292 58 5 Average 375.55
Manuela RTA 387 53 5 Average 630.87
Manuela RNTA 373 92 5 Average 769.23
Maria A 193 40 5
Maria TA 215 41 5
Maria RTA 408 70 5
Maria RNTA 345 59 5
Time to Act: 193 ± 40 milliseconds
Time to Think: 22 ± 58 milliseconds
Time to Read: 193 ± 82 milliseconds
Time to Negate: -63 ± 92 milliseconds
Our hypothesis predicted that Manuela as a non native English speaker would take significantly longer to follow instructions and react and follow instructions and do the opposite than Maria, native English speaker.
Observations: Both students have comparable times, though Maria was faster in the last trial (negating instructions). Both students were also significantly faster than the averages in all of the trials, and it is important to keep in mind that our times to act and think and act, are pretty similar, Maria being faster in the second.
Our hypothesis then can not be confirmed. Also keeping in mind the averages, for which we are assuming most test takers have English as a native language (?), both the native and the non native English speaking students were quicker. Determining level of fluency is also more difficult, which might undermine differences.
Su-Lyn, Brittany Name: Date: 2003-11-04 15:15:01 Link to this Comment: 7111 |
Act Time Think, Act Time: Read, Think, Act Time: Read, Think-Negate, Act Time: Time to Act: Time to Think: Time to Read: Time to Negate: |
Su-Lyn control 250 ± 73 milliseconds 339 ± 40 milliseconds 541 ± 151 milliseconds 504 ± 60 milliseconds 250 ± 73 milliseconds 89 ± 84 milliseconds 202 ± 157 milliseconds -37 ± 163 milliseconds |
Su-Lyn with music 325 ± 134 milliseconds 355 ± 52 milliseconds 558 ± 159 milliseconds 587 ± 164 milliseconds 325 ± 134 milliseconds 30 ± 144 milliseconds 203 ± 168 milliseconds 29 ± 229 milliseconds |
Act Time Think, Act Time: Read, Think, Act Time: Read, Think-Negate, Act Time: Time to Act: Time to Think: Time to Read: Time to Negate: |
Brittany control 244 ± 41 milliseconds 281 ± 54 milliseconds 575 ± 224 milliseconds 546 ± 119 milliseconds 244 ± 41 milliseconds 37 ± 68 milliseconds 294 ± 231 milliseconds -29 ± 254 milliseconds |
Brittany with music 348 ± 122 milliseconds 384 ± 47 milliseconds 483 ± 45 milliseconds 700 ± 166 milliseconds 348 ± 122 milliseconds 36 ± 47 milliseconds 99 ± 45 milliseconds 217 ± 166 milliseconds |
Vanessa Herrera, Shafiqah Berry Name: Date: 2003-11-04 15:15:36 Link to this Comment: 7112 |
Variable A:
A 318
A 291
A 242
A 253
A 287
A 306
A 512
SA 356
A 321
A 304
RNTA 834
RNTA 522
RNTA 888
RNTA 1076
RNTA 988
RNTA 1047
RNTA 943
RNTA 908
RNTA 511
RNTA 468
Shafiqah
Control B:
A 254
A 214
A 234
A 259
A 237
A 424
A 226
A 276
A 231
A 233
RNTA 908
RNTA 834
RNTA 704
RNTA 712
RNTA 896
RNTA 748
RNTA 450
RNTA 758
RNTA 608
RNTA 650
Variable B:
A 243
A 493
A 234
A 225
A 208
A 276
A 272
A 288
A 257
A 307
RNTA 638
RNTA 554
RNTA 822
RNTA 832
RNTA 796
RNTA 794
RNTA 674
RNTA 632
RNTA 578
RNTA 530
Our variable represents the change in action time and thinking speed after prayer. Our observatins concludes that our times are much slower in the variable than in the control. We believe this to be so, for when the mind has been cleared we have to think twice as much.
Name: Stefanie F Date: 2003-11-05 14:18:36 Link to this Comment: 7124 |
Summary of Data:
Stefanie's Average Times:
Trial 1: 196 milliseconds
Trial 2: 251 milliseconds
Trial 3: 479 milliseconds
Trial 4: 536 milliseconds
Alison's Average Times:
Trial 1: 231 milliseconds
Trial 2: 320 milliseconds
Trial 3: 499 milliseconds
Tiral 4: 721 milliseconds
From the data, we see that Alison's reaction times are consistently slower than Stefanie's. Our data is consistent with our hypothesis in that Stefanie, the athlete, is faster than Alison.
reaction time Name: Megan, Eno Date: 2003-11-05 14:21:50 Link to this Comment: 7125 |
Hypothesis- Reaction time will consistently go down as the subject become habituated to the experimental process. The response time will become increasingly lower because the subject is desensitized to the directions.
Megan's data (in milliseconds)
ACT- 196, 213, 198, 185, 265
THINK, ACT- 288, 470, 274, 236, 251
READ, THINK, ACT- 426, 356, 365, 336, 298
READ, THINK/NEGATE, ACT- 784, 409, 319, 352, 367
Enor's data (in milliseconds)
ACT- 232, 271, 260, 211, 217
THINK, ACT- 242, 612, 458, 454, 354
READ, THINK, ACT- 692, 848, 610, 520, 619
READ, THINK/NEGATE, ACT- 1104, 941, 744, 826, 419
Conclusions- Our results did not prove our hypothesis. We noticed that many of our trials had a slight improvement in reaction time as the trials went on, yet the improvement was not consistent in the majority of our trials. The reason for this may be that when the directions are first read, the subject anticipates the response more strongly. The experiment is more exciting because it is new and thus your mind is more focused on the experiment. As the time goes on, and more trials are done, the anticipation lessens.
Julia and Alice's marvelous data Name: Date: 2003-11-05 14:44:16 Link to this Comment: 7127 |
Julia
Undistracted: (701) 289, 780*, 639, 1009
Distracted: (704) 445, 531, 611, 1071
Alice
Undistracted: (708) 210, 321, 585*, 476
Distracted: (711) 260, 417, 530, 573
*There were two pieces of data that did not support the hypothesis. The first was when Julia got distracted when she wasn't supposed to, making her reaction time ridiculously long. The second was Alice's undistracted read/think/react time, which for reasons unknown to us was higher than we would have expected.
Except for these two glitches, though, the data did support the idea that distraction lengthens people's times.
distractions and time to think/react Name: Lara Kalli Date: 2003-11-05 14:51:12 Link to this Comment: 7128 |
Test time averages without an object:
A: 232 ms (sd 39)
TA: 375 ms (sd 100)
RTA: 511 ms (sd 87)
RNTA: 637 ms (sd 119)
Acting time: 232 ms
Thinking time: 143 ms
Reading time: 136 ms
Negating time: 126 ms
Test time averages with an object (in this case, my car key, which is of the totally awesome switchblade design):
A: 284 ms (sd 32)
TA: 406 ms (sd 93)
RTA: 577 ms (sd 116)
RNTA: 828 ms (sd 173)
Acting time: 284
Thinking time: 122 ms
Reading time: 171 ms
Negating time: 251 ms
Discussion:
First of all, it is important to note the following external factors which would most definitely have affected my results: a) I am extremely tired and b) the room in which I conducted this experiment was quite noisy. That having been said, these results seem to be in support of the part of my hypothesis that claimed that fidgeting with an object would lengthen my reaction time. In fact, according to the data it would be safe to say that fidgeting slows down all of my actions. In the second trial, my thinking time actually became shorter (by, it should be noted, the smallest increment of change out of all the results above); however, that could just as easily be attributed to my having familiarized myself with the structure and content of the experiment. Thus: will fidgeting help me think about my homework? We're not really sure, but it's possible. Will it help me finish my homework faster? Conclusively: no.
Of course, these results are only really applicable to myself.
Distractions Name: Lindsay, A Date: 2003-11-05 14:56:46 Link to this Comment: 7129 |
Lindsay Not Distracted:
Acting: 252 ms
Thinking:73
Reading: 157
Negating: 82
Lindsay Distracted:
Acting: 319
Thinking: 64
Reading: 222
Negating: 48
Lindsay Difference:
Acting: 67 ms
Thinking: -9 ms
Reading: 65 ms
Negating: -34 ms
Adina Not Distracted
Acting: 268 ms
Thinking:45 ms
Reading: 224 ms
Negating: 246 ms
Adina Distracted
Acting: 308 ms
Thinking: 52 ms
Reading: 271 ms
Negating: 51 ms
Adina Difference:
Acting: 40 ms
Thinking: 7 ms
Reading: 47 ms
Negating: -195
Our acting and reading times were both lengthened by the distractiions. However, our negating times were both reduced and our thinking times were about the same. From our observations, it appears that the visual distraction hinders our physical responses like acting and reading, but not our mental processes like thinking and negating. To account for the significant in negating time, we believe that we became accustomed to the distractions and were able to focus and overcome them.
Are Foreigners Dumb? Name: Date: 2003-11-05 14:58:28 Link to this Comment: 7130 |
We postulated that it takes more time for a non-native speaker of English to read the commands in English and to negate the commands in English. Mariya also thought that it will be easier for her to think in Russian while she was negating the commands.
We performed three sets of trials (10 trials each). Maggie performed the trials as a native English speaker and Mariya as a Russian native speaker. Mariya performed two sets of reading and negation trials. During the first one she tried to just read the instructions and react to them without focusing on the language in which she was processing it. During the second one she read the instructions in English, translated them to herself and told herself to negate them in Russian.
Observations:
Maggie
A 260 milliseconds
TA 331 milliseconds
RTA 523 ms
RNTA 437 ms
With Average Negation Time of -86ms
Mariya
1st set of observations (simply thinking and negating)
A 232 ms
TA 324ms
RTA 538ms
RNTA 873ms
With Average Negation Time of 335ms
2nd set of observations (thinking and negating in Russian)
RTA 526ms
RNTA 1412ms
With Average Negation Time of 886ms
The first part of our hypothesis is supported by data collected. It took Mariya and Maggie about equal time to respond to non-verbal stimulae, however, it took Mariya significantly longer than Maggie both to read the instructions and to negate them. The second part of our hypothesis (that it will take less time for Mariya to negate the instructions if she thinks in Russian) is not refuted by data. Mariya's Average Negation Time when she was thinking about verbal instructions in Russian was significantly longer (886ms) than her Average Negation Time when she wasn't focusing on the language she was using (335ms). She believes that she was thinking in English during her first trials.
Name: Date: 2003-11-05 14:59:40 Link to this Comment: 7131 |
Hypothisis: Level of sleep will correlate with all categories(time to act, time to think, time to read, and time to negate).
*All time is in milliseconds
Test Subject A (Denise):
Tme to Act: 200 sd. 23
Time to Think: 57 sd. 65
Time to Read: 284 sd. 98
Time to negate: 38 sd. 323
Test Subject B (Ramatu):
Time to Act: 260 sd.74
Time to Think: 133 sd. 119
Time to Read: 306 sd. 217
Time ti Negate: 124 sd.371
Test Subject C (Rochelle):
Time to Act: 280 sd. 76
Time to Think: 413 sd. 105
Time to Read: 1080 sd. 228
Time to Negate: 942 sd. 228
We conclude our hypothesis to be inaccurate. As shown in our observation there are clearly other factors beside sleep level that can affect our response times, there were no data to establish any patterns,including one that would support our hypothesis.
Brain Name: Patricia P Date: 2003-11-05 15:02:28 Link to this Comment: 7132 |
We hypothesised that attempting to hold a generic conversation would raised the times in the trials of cases 2, 3, and 4, but would not have any significant effect on trial 1.
Jessica, the first subject, recored these marks:
Control (ID 713)
AVG SD
A 306 106
TA 391 107
RTA 641 66
RNTA 796 159
Distracted (1D 710)
AVG SD
A 330 82
TA 400 71
RTA 728 43
RTNA 950 164
We found that, on average, it took more time when the subject was distracted, but the standard deviation was less for the set of distracted trials.
Patty's marks:
Control (ID 717)
AVG SD
A 193 13
TA 311 38
RTA 481 61
RNTA 671 341
Distracted (ID 721)
AVG SD
A 285 69
TA 268 52
RTA 509 94
RTNA 992 498
For Patty, it took more time when distracted, but the standard deviation was also larger for the set of distracted trials.
We found that relatively, all of the trials were affected by conversational distraction, so our hypothesis was partly false. We may have been originally assuming that if thinking or motor skills were needed from the subject, as long as it did not involve the specific re-actionary tasks as provided by the first trial we were messuring, that it would nothave as great of an effect. However, cases 1-4 were all affected by conversational distration.
Thinking Time Name: Katy and F Date: 2003-11-05 15:02:51 Link to this Comment: 7133 |
Hypothesis: Distraction increases the time it takes to act, think, read and negate.
Results:
Flicka
Case 1
No Distraction Av 248 ms SD 15 ms
Distraction Av 231 ms SD 19 ms
Case 2
No Distraction Av 335 ms SD 105 ms
Distraction Av 331 ms SD 54 ms
Case 3
No Distraction Av 584 ms SD 136 ms
Distraction Av 582 ms SD 134 ms
Case 4
No Distraction Av 515 ms SD 84 ms
Distraction Av 739 ms SD 188 ms
With distraction time to act DEcreased 17 ms
time to think DEcreased 4 ms
time to read DEcreased 2 ms
time to negate INcreased 224 ms
Katy
Case 1
No Distraction Av 199 ms SD 15 ms
Distraction Av 216 ms SD 57
Case 2
No Distraction Av 330 ms SD 88 ms
Distraction Av 323 ms SD 44 ms
Case 3
No Distraction Av 474 ms SD 131 ms
Distraction Av 544 ms SD 151 ms
Case 5
No Distraction Av 547 ms SD 134 ms
Distraction Av 748 ms SD 322 ms
With distraction time to act INcreased 17 ms
time to think DEcreased 7 ms
time to read INcreased 70 ms
time to negate INcreased 201 ms
*****
Based on our results we think that distraction affects people differently. Flicka was able to block out the distractions and even think faster than without distractions. In Case 4 this was reversed. We believe that this is due to the difficulty of the case because we both had trouble with it even without the distractions. While Katy's acting time is faster, it took longer for her to respond with distractions in 3 out of 4 cases.
Wherin Lies the "Disability"? Name: Nomi, Chri Date: 2003-11-05 15:03:39 Link to this Comment: 7134 |
Hypothesis: As compared to a person with no such disability, a person with a diagnosed reading disability will take longer to perform a task involving reading, but will not take significantly longer or shorter to perform tasks involving only reacting and thinking.
Data Collected:
Person #1 has no diagnosed reading disability (Control).
Person #2 HAS a diagnosed reading disability (Experimental).
Controls: both subjects wear glasses (corrected vision).
Each avg. number was compiled from 10 pieces of data.
Person #1: Task -- Act
Average Time -- 264 milliseconds
Standard Deviation -- 62 milliseconds
Task -- Think, Act
Average Time -- 348 millisec.
Standard Deviation -- 83 millisec.
Task -- Read, Think, Act
Average Time -- 571 millisec.
Standard Deviation -- 114 millisec.
-----------------------------------------------------------------------
Person #2: Task -- Act
Avg. Time -- 259 millisec
Stand. Dev. -- 111 millisec.
Task -- Think, Act
Avg. Time -- 426 millisec.
Stand. Dev. -- 92 millisec.
NOTE: Errors - 2 x click-too-soon, 1 x click incorrectly
Task -- Read, Think, Act
Avg. Time -- 678 millisec.
Stand. Dev. -- 434 millisec.
NOTE: Errors - 1 x click-too-soon, 1 x click incorrectly
Our Findings:
Our findings support our hypothesis. While average reaction times (Act) are very similar for persons #1 and #2 -- 264 vs. 259, not significantly different -- average Read, Think and Act times are significantly different for the two, with Person #2 being significantly slower at 678 millisec. as opposed to 571 millisec, a difference of approximately 15% (which counts for something!). It seems that having a reading disability does, indeed, increase reading time!
But this is not for certain, because it might just be increasing thinking time. The two averages obtained for the Think, Act experiment were also significantly different: 434 for #2, vs. 348 for #1, about a 20% difference! According to this data, it would appear that having a reading disability increases THINKING time, but not reading time. This suggests that our hypothesis does not "work" in this case, and that a "Reading disability" might actually suggest a disability -- or slowing down -- in THINKING rate.
Wherin Lies the "Disability"? Name: Nomi, Chri Date: 2003-11-05 15:03:40 Link to this Comment: 7135 |
Hypothesis: As compared to a person with no such disability, a person with a diagnosed reading disability will take longer to perform a task involving reading, but will not take significantly longer or shorter to perform tasks involving only reacting and thinking.
Data Collected:
Person #1 has no diagnosed reading disability (Control).
Person #2 HAS a diagnosed reading disability (Experimental).
Controls: both subjects wear glasses (corrected vision).
Each avg. number was compiled from 10 pieces of data.
Person #1: Task -- Act
Average Time -- 264 milliseconds
Standard Deviation -- 62 milliseconds
Task -- Think, Act
Average Time -- 348 millisec.
Standard Deviation -- 83 millisec.
Task -- Read, Think, Act
Average Time -- 571 millisec.
Standard Deviation -- 114 millisec.
-----------------------------------------------------------------------
Person #2: Task -- Act
Avg. Time -- 259 millisec
Stand. Dev. -- 111 millisec.
Task -- Think, Act
Avg. Time -- 426 millisec.
Stand. Dev. -- 92 millisec.
NOTE: Errors - 2 x click-too-soon, 1 x click incorrectly
Task -- Read, Think, Act
Avg. Time -- 678 millisec.
Stand. Dev. -- 434 millisec.
NOTE: Errors - 1 x click-too-soon, 1 x click incorrectly
Our Findings:
Our findings support our hypothesis. While average reaction times (Act) are very similar for persons #1 and #2 -- 264 vs. 259, not significantly different -- average Read, Think and Act times are significantly different for the two, with Person #2 being significantly slower at 678 millisec. as opposed to 571 millisec, a difference of approximately 15% (which counts for something!). It seems that having a reading disability does, indeed, increase reading time!
But this is not for certain, because it might just be increasing thinking time. The two averages obtained for the Think, Act experiment were also significantly different: 434 for #2, vs. 348 for #1, about a 20% difference! According to this data, it would appear that having a reading disability increases THINKING time, but not reading time. This suggests that our hypothesis does not "work" in this case, and that a "Reading disability" might actually suggest a disability -- or slowing down -- in THINKING rate.
Correction! Name: Nomi, Chri Date: 2003-11-05 15:11:32 Link to this Comment: 7136 |
Mendel's Garden Name: Paul Grobstein Date: 2003-11-11 12:38:39 Link to this Comment: 7197 |
In this lab you will be invited to participate yourself in making the kinds of observations and inferences that Mendel made. We will do so together studying not pea plants but fruit flies, and using not live animals (for which the studies would take weeks or months) but a computer simulation which is quite realistic in most important characteristics. The simulation, called FlyLab, is available to registered individuals (students in this class) at http://biologylab.awlonline.com.
After we've worked through some of the basic observations together, you should work in pairs to make observations yourself on some fly traits other than those we have explored together. Your task is to "make sense" of your observations starting with the basic ideas we develop together and adding whatever additional ideas seem necessary. Try and find some traits that yield unexpected results in a monhybrid cross, as well as some that yield unexected results in a dihybrid cross.
Fly Lab Name: Nancy Evan Date: 2003-11-11 15:06:42 Link to this Comment: 7200 |
First Generation:
50% white eyes
50% red eyes
*two flies appeared on the screen
Second Generation: (used two flies from first generation)
50% white eyes
50% red eyes
*four flies appeared on the screen
Third Generation: (used top two flies from second generation, both had red eyes)
75% red eyes
25% white eyes
*the white eyes only appeared in the males in this generation.
For my second cross, I used a female with spread wings (D) and a black body and a wild type male.
First Generation:
50% closed wings
50% open wings
Second generation:
75% wild type bodies
25% black bodies
Third Generation:
75 % wild type bodies
25% black bodies
HYPOTHESIS: Some traits do not follow the general ratio of 9:9:3:1. Some traits may not be able to be expressed at the same time (such as open wings and black bodies). Also, some traits may be muted in a sex (as in the case with females and white eyes).
Because I wrote my hypothesis after I performed the experiment, my hypothesis seems to follow the data. However, I don't know why this is true. Why could first and second generation females have white eyes but not third?
Fly Lab Name: Sarah Kim Date: 2003-11-11 15:12:49 Link to this Comment: 7202 |
Katie Ottati, Michelle Choi Name: Katie, Mic Date: 2003-11-11 15:14:03 Link to this Comment: 7203 |
Dicheate:
- exhibits true breeding
- is not more dominant than "wild type" wing angle. Starting from the first generation of offspring, there was a 1:1 ratio of each wing angle.
- is not gendered. Both males and females exhibit the trait at the same frequency
Eyeless:
- exhibits true breeding
- is recessive in relation to the "wild type" eye shape. In the first generation of offspring there were no phenotypically eyeless flies, in the second there was a 2:1 ratio of eyes to eyeless. In subsequent generations, whether or not there were eyeless flies depended on whether or not we selected a phenotypically eyeless parent.
- is not gendered.
Dicheate wing angle and eyelessness do not seem to have any impact on one another. When we bread an dicheate mother with wild type eyes and an eyeless father with wild type wings (and vice versa), each trait appeared with the frequency that would be expected based on the earlier experiments.
Bessy Guevara, Vanessa Herrera, Shafiqah Berry Name: Date: 2003-11-11 15:18:27 Link to this Comment: 7204 |
First Generation: Female (white eyes) Male (wild)
Second Generation: Female (wild) Male (white eyes)
Given that the white eyes appeared in the first process of mating, white eyes are clearly not a recessive trait in the male of the second generation, but is in the female of the first generation. We concluded that the white eyed trait is sex-linked since it turns up to be neither a dominant or recessive trait.
Third Generation: 1 Female (wild) 1 Male (wild)
2 Female (white) 2 Male (white)
Throughout the three generations the ration of wild to white is 1:1. In the last observation, only one of the males turned up with white eye. Yet we had to take in account that the female that turned up white in the Second generation still carried the white eyed trait from the first generation. We assumed the same for the males.
Brianna Twofoot, Emily Breslin Name: Date: 2003-11-11 15:19:05 Link to this Comment: 7205 |
+ (wild type): 552
PR (like the mother): 204
M (like the father): 192
PR, M (combination of the mother and father traits): 64
These results yielded an approximate ratio of: 9:3:3:1
These were the expected results based on two parents with traits that we determined to be true breeding.
We discovered that the wing trait of Dicheate, where the wings are spread apart, was not true breeding. Any combination of breeding, over numerous generations, yielded a mysterious disappearance of the trait. This confused and baffled us. We determined that perhaps there is something inherent in the definition of "not true breeding" that allows traits to completely disappear or appear completely randomly.
Does a not true breeding trait mean that it is a mutation of a gene and cannot be inherited in the same statistical way that 'normal' genes are?
Fly Lab Name: Date: 2003-11-11 15:20:02 Link to this Comment: 7206 |
1002 flies -all lobe eyed w/ wildtype wings
we assumed that lobe eyes might be dominant, and that the female parent was homozygous(LL). To prove this, we checked to see if the lobe eyed trait was a true breed. and it was! :)
The male's apterous wings were also proven to be true breed.
Next we crossed the offspring of our lobe eyed female and apterous male. (lobe eyed wildtype) w/ the following results out of a total of 998 flies:
34 wildtype(ratio:1)
723 lobe eyed wildtype wings(ratio:21.265)
206 apterous wildtype eyes(ratio:6.059)
35 lobe eyed apterous(ratio:1.029)
For a second experiment we crossed a female with apterous wings and a male with lobe eyes.
For this experiment we got very similar results, which we could infer from that there are no sex linked traits.
Lobe eyes must have been dominant over wildtype eyes. And the apterous is a recessive gene. Both are homozygous.
We DO NOT have an explanation for why we hae such peculiar ratios.
Su-Lyn Name: su-lyn Date: 2003-11-11 15:20:29 Link to this Comment: 7207 |
RESULTS 1:
Parents + and CY --> F1 50+ and 65CY i.e. 1 : 1.3 ratio
This fairly equal distribution suggests that + is not dominant over the CY. In fact, a greater proportion of offspring are CY phenotypes, but dominance is not total.
RETEST:
I crossbred a new pair of flies, CY and CY. Based on the assumption that they were homozygous, I predicted that they would produce offspring that were all CY in phenotype.
RESULTS 2:
Parents CY and CY --> F1 32+ and 79CY i.e. 1 : 2.47 ratio
Subsequent crossbreeds of two CY offspring produced the following +:CY ratios
1 : 1.81
1 : 1.842
1 : 1.941
1 : 1.872
CONCLUSION:
This implies that CY is not a homozygous phenotype. It is possible that one of the two variants that make up CY is recessive to +, and the other variant is dominant over +. This would help explain the first set of results in the crossbreed between + and CY.
Fly Lab Name: Team Bitte Date: 2003-11-11 15:26:43 Link to this Comment: 7208 |
First Generation
Tan Female and Wild Male
Offspring
519Tan male
504 Wild Female
Second Generation
WIld Female and Tan male
262 Tan male
271 Tan Female
257 Wild Male
266 Wild Female
Third Generation
Wild Female and Wild Male
514 Wild Female
243 Wild Male
249 Tan Male
Fourth Generation
Wild Female and Wild Male
508 Wild Female
521 Wild Male
Observation
When there is a tan female the tan gene appears in the male in the first offspring. We then crossed a wild female and a tan male and you had a 50% chance of getting a tan offspring in both the male and females. We then crossed a wild female and a wild male and we got the tan gene appeared only in the males but most of the offspring were wild type. When we crossed another wild female and another wild male, the tan gene disappears and you only get wild offspring. In other words, the tan gene disappears in the fourth generation. It is interesting to note that in the 3rd generation there were no tan females.
fly lab Name: Charlotte Date: 2003-11-11 15:30:00 Link to this Comment: 7209 |
hypothesis:
It seems that the variations present in the parent or parents increase the chances for the traits to take on the dominant gene in the offsprings.
Observations:
Experiment 1:
Female (tan body) + Male (wild)
-> Female (228 wild) + Male (228 wild)
-> Female (255 tan) + Male (264 tan)
-> Female (473 tan) + Male (512 tan)
-> Female (477 tan) + Male (508 tan)
Tan body: dominant trait
Experiment 2:
Female (curly wings) + Male (purple eyes)
-> Female (257 W) + Male (218 W)
-> Female (271 C) + Male (240 C)
-> Female (175W) + Male (160 W)
-> Female (76 P) + Male (92 P)
-> Female (239 C) + Male (200 C)
-> Female (25 PC) + Male (32 PC)
-> Female (158 P) + Male (176 P)
-> Female (327 PC) + Male (328 PC)
Conclusion: Our hypothesis was proved right since in each experiment the offspring took on the variant traits. In the first experiment, the offspring showed to have tan bodies just like the female parent at the beginning of the chain. In the second experiment, the traits surface in further generations simultaneously in both sexes. Therefore, not only are the variant traits passed on to future generations, but also become more apparent as the chain progresses.
sex-linked traits discovered?! Name: stefanie a Date: 2003-11-12 14:53:44 Link to this Comment: 7227 |
For our next experiment, we mated a yellow-bodied female with a wildtype-bodied male. In the F1 generation half of the offspring were yellow and half wild-type, unlike the other experiments we performed, where all offspring were wild-type.
To ensure that it was not another type of variable we tested a yellow-bodied female with a yellow-bodied male, and offspring in three generations to follow were all yellow-bodied, this led us to conclude that yellow-bodiedness is in fact a pure-breeding trait.
Upon further review of our results, we realized that only the males were yellow-bodied, which would mean that the yellow body color gene is sex-linked.
fly incest Name: Julia and Date: 2003-11-12 14:57:29 Link to this Comment: 7228 |
F2:
p +
p pp(purple) p+ (red)
+ p+ (red) p+ (red)
This supports the idea that the combination of two genes from two parents leads to four possibilities in each generation. In the F1 generation, because every offspring got one purple gene from the mother and one wild type gene from the father, they all had the same combination of one p and one +. In the next generation, though, offspring could inherit a p or a + gene from either parent. So one possibility was pp, one was ++, and the other two were +p. The phenotype of the +p genotype in the F2 generation would reveal which of these genes overrides the other. We found that 3/4 of the F2 generation had the wildtype phenotype, so we concluded that + was the gene that overrode p.
Lindsay and Alice Name: Date: 2003-11-12 15:01:00 Link to this Comment: 7229 |
Purple, regular shaped + Purple, star shaped
Yielded half Purple, regular shaped and half purple, star shaped again.
Purple, regular shaped + purple, regular shaped
Yielded all purple, regular shaped
Purple, star shaped + purple, star shaped
Yielded 1/3 purple regular shaped and 2/3 purple star shaped.
When we isolated the eye shape gene and disregarded the eye color gene, the resuts of the cross
Star shaped + star shaped
still yielded this 2:1 ratio. So the fact that our results were the same when the two traits were isolated says that eye color and eye shape are not related in their inheritance. However, we do not know how to account for this 2:1 ratio when crossing eye shapes. We found this ratio odd because when we crossed flies with different eye colors, we came up with a 3:1 ratio in phenotype in the first generation, and either a 1:1 or 1:0 ratio in the second generation. We think that in order for this 2:1 ratio to occur there must be some other factor contributing to the flies' inheritance of eye shape.
fly-love Name: lara kalli Date: 2003-11-12 15:01:14 Link to this Comment: 7230 |
Given that these results were a bit different from the all same/3:1 ratios that we saw in the earlier examples, I decided to test whether or not curly-wingedness was a true-breeding characteristic:
2nd cross: CY male and female
F(1): 50% CY, 50% +
F(2): 50% CY, 50% +
F(3): 50% CY, 50% +
Hypothesis: In a monohybrid cross, a trait that is characteristic of one of the parents that does NOT appear in F(1) is a true-breeding characteristic; conversely, a trait characteristic of one of the parents that DOES appear in F(1) is not a true-breeding characteristic.
Fly Lab Name: Date: 2003-11-12 15:10:01 Link to this Comment: 7231 |
First I bred a tan female fly with a wildtype male fly.
F1- 1 female wildtype, 1 male tan
F2- 2 wildtypes, 2 tan (1 male and female of each)
bred male and female tan
F3- 2 tan (1 female tan, 1 male tan)
Next, I bred a female wildtype with a shaven male.
F1- 2 wildtypes
F2- 2 wild types, 2 shaven
bred 2 shaven
F3- 2 shaven
So, I can conclude from my results that tan coloring and shaven are true breeding traits since when I bred 2 tan flies or 2 shaven flies together the offspring continually showed these traits and no others.
Flies Name: Date: 2003-11-12 15:12:05 Link to this Comment: 7232 |
Hypothesis: There is equal chance for the offspring to have either father or mother traits.
Parents:
Mother: Wild type (+) Father: Curly Wings (cy)
Offspring:
females + 271, Male + 247
females (cy) 271, Males (cy) 243
Second generation incest:
Mother (cy) father (+)
offspring:
females: (+) 253 Males (+) 241
females:(cy) 238 Males (cy) 268
Conclusion:
Our hypothesis seems to have proven correct as we came to see that in only changing one trait in the original parents, offspring were equally likely to have curly wings or wild type bodies.
As for the second generation we saw that characteristics equally carried through to the third generation.
There were variations but they were probably insignificant.
FlyLab with Respect the the Characterisitcs of Sha Name: J'London a Date: 2003-11-12 15:12:46 Link to this Comment: 7233 |
We very much enjoyed taking on the brain and logic of Mendel. We mated every "weird" thing with the wild type and they only produced about five offspring. Why were there no babies?
Name: Date: 2003-11-12 15:12:53 Link to this Comment: 7234 |
We hypothesized that either dichaete-winged or wildtype would be a dominate gene, and whichever was not dominate would be recessive.
We bred a dichaete-winged fly with a wildtype fly. These flies produced an f1 generation of 50% dichaete-winged and 50% wildtype. This continued for all subsequent breedings involving one dichaete and one wildtype.
We did two types of breeding variation once this constant was found. For our first variation, we bred two dichaetes. We ended up with a ratio of 1 wildtype: 2 dichaete. This pattern remained constant when we continued to breed two dichaete from each subsequent generation.
For the second variation, we bred two wildtypes after the initial hybrid breeding. Our f2 generation consisted of all wildtyped. As two wildtypes were continuing to be bred, the dichaetes did not reappear.
Our results were not true to our hypothesis. Neither gene stood out as either recessive or dominate but we do not know why these results occurred.
Fly Eye Color Trends Name: Patricia P Date: 2003-11-12 15:15:55 Link to this Comment: 7235 |
Key: W = wild eyed; P = Purple eyed
Rule #1: Breed W with P whenever possible (whenever both w and p exist among offspring).
Rule #2: Breed W whenever possible.
Rule #3: Breed P whenever possible.
Test #1: Applying Rule #1
P 1:1
F1 2:0
F2 1:1
F3 2:0
F4 1:1
F5 1:1
and follows with breeding as 1:1
Test #2: Applying Rule #2
P 1:1
F1 2:0
F2 1:1
F3 1:1
F4 2:0
F5 2:0
and follows with breeding as 2:0
Test #3: Applying Rule #3
P 1:1
F1 2:0
F2 1:1
F3 0:2
F4 0:2
F5 0:2
and follows with breeding as 0:2
The interesting occurance was that consistancy with seeing just wild type in test two (which was what we were looking for) arrived by trial F4. But the consistancy of seeing just purple in test 3 (which was what we were after in that test) arrived earlier, in the F3 breeding. This lead us to infer that the red contains something thats holds on to a "hiddenpurple " longer. While the purple does not hang on to a red trait for any length of time.
Name: Maria S-W Date: 2003-11-12 15:16:18 Link to this Comment: 7236 |
fly-love: a revision Name: Date: 2003-11-12 15:47:16 Link to this Comment: 7237 |
Name: Date: 2003-11-12 15:47:51 Link to this Comment: 7238 |
Watching Cellular Life in Process Name: Paul Grobstein Date: 2003-11-18 12:34:18 Link to this Comment: 7308 |
This description, however, summarizes a more complex reality, involving many individual chemical reactions and different enzymes in particular spatial arrays. In this lab we will explore the implications of both the overall breakdown process involved in life and its complexity. To do this, we will look at CO2 production by yeast cells under a variety of conditions.
You will work in pairs to set up a series of experimental conditions. While these are evolving measurable CO2, you should write a set of predictions about which tubes should generate the most carbon dioxide and why. We will then look at the collected data and see to what extent it satisfies the various predictions.
Predictions Name: Sarah, Nat Date: 2003-11-18 14:14:19 Link to this Comment: 7312 |
We predict this because we think that glucose will break down faster than sucrose because sucrose is made up of glucose and fructose, therefore, 2 will produce more carbon dioxide than 1. Also, pyruvate breaks down into ethanol and carbon dioxide, therefore 4 will have more carbon dioxide than 1. Will said that fluoride was an inhibitor, so the more fluoride, the less carbon dioxide, so 6 will have more than 7. Without oxygen, the citric acid cycle cannot take place, therefore, the anaerobic yeast will produce the least carbon dioxide.
Predictions Name: Brittany, Date: 2003-11-18 14:26:58 Link to this Comment: 7313 |
4. Active Yeast with Pyruvate (closer to end product)
2. Active Yeast with Glucose
3. Active Yeast with Sucrose (more complex)
6. Active Yeast with 0.01 NaF (inhibitor)
7. Active Yeast with 0.1 NaF (more inhibitor)
5. Lysed Yeast (uh, Will...?)
8. Anaerobic Yeast (produces smaller amount than aerobic)
1. Active Yeast with Water (nothing to break down)
Su-Lyn & Brittany
Predictions Name: brianna tw Date: 2003-11-18 14:29:18 Link to this Comment: 7314 |
Test Tube #: 4, 7, 6, 2, 5, 3, 1.
We thought that an element is produced closer to the end of the process would yield more carbon dioxide when introduced to the yeast.
Abby and Melissa Name: Abby Fritz Date: 2003-11-18 14:35:14 Link to this Comment: 7315 |
Name: Date: 2003-11-18 14:49:05 Link to this Comment: 7316 |
(All in accordance to the Spacial Arrangements and Metabolism)
We made these predictions based on a scale from 1-10
Tube 1 ( 9)
Tube 2 (6)
Tube 3 (4)
Tube 4 (8)
Tube 5 (7)
Tube 6 (9)
Tube 7 (10)
Results Name: Sarah, Nat Date: 2003-11-18 15:03:19 Link to this Comment: 7317 |
Net gas volume:
Test Tube 1: 0 cc/hr
Test Tube 2: 3 cc/hr
Test Tube 3: 4 cc/hr
Test Tube 4: 0 cc/hr
Test Tube 6:2.75 cc/hr
Test Tube 7: 0.5 cc/hr
Test Tube 8: 1.25 cc/hr
In looking at the results, we noticed that there was no sugar in either 1 or 4, therefore, no change in carbon dioxide is to be expected. 7 had the most fluoride, which is an inhibitor, so that makes sense. Since the concentration of fluoride in 6 isn't very large, the lack of oxygen in 8 served as more of an inhibitor. Since sucrose is made of glucose and fructose, and fructose will break down into glucose, the sucrose may be providing more volume of glucose, leading to 3 producing more carbon dioxide than 2. So our predictions were mainly incorrect, but we were correct that 2 and 3 would produce the most carbon dioxide.
co2 production Name: denise,meg Date: 2003-11-19 14:24:07 Link to this Comment: 7327 |
We hypothesis the following order of gas reading, from most gas to least gas: (1=most, 7=least)
1. Active Yeast/Glucose/H2O (2)
2. Active Yeast/Sucrose/ H20 (3)
3. Lysed Yeast/Glucose/H2O (5)
4. Active Yeast/H2O (1)
5. Active Yeast/Pryruvate/H20 (4)
6. Active Yeast/Glucose/0.01 M NaF (6)
7. Active Yeast/Glucose/0.1 M NaF (7)
We made the following predictions based on our previous knowledge that flouride is an inhibitor of gas production. We also know that glucose promotes the production of gas. We also think that the active yeast will produce more gas b/c it is "active" versus the lysed yeast.
Name: Date: 2003-11-19 14:25:36 Link to this Comment: 7328 |
Our predictions:
1 is most carbon dioxide and 8 is least carbon dioxide:
1. tube 3
2. tube 2
3. tube 5
4. tube 7
5. tube 6
6. tube 8
7. tube 4
8. tube 1
We chose this order based on how long we thought the breakdown process would take place. If it took longer to break down, then we thought it would produce more carbon dioxide, but if it broke down quickly, then we thought it would produce less carbon dioxide.
yeast waste Name: Date: 2003-11-19 14:31:00 Link to this Comment: 7329 |
CO2 yield predictions for yeast metabolic activity (least to most)
- 1. Active yeast + water
- 8. Anaerobic yeast + glucose + water
- 7. Active yeast + glucose + 0.1 NaF
- 6. Active yeast + glucose + 0.01 NaF
- 5. Lysed yeast + glucose + water
- 3. Active yeast + sucrose + water
- 2. Active yeast + glucose + water
- 4. Active yeast + pyruvate + water
Name: Date: 2003-11-19 14:38:00 Link to this Comment: 7330 |
1. Lysed Yeast/Glucose/H2O
2. Active Yeast/Sucrose/H2O
3. Active Yeast/Glucose/H2O
4. Active Yeast/Pyruvate/H2O
5. Anaerobic Yeast/Glucose/H2O
6. Active Yeast/Glucose/0.01M NaF
7. Active Yeast/Glucose/0.1M NaF
8. Active Yeast/H2O
We think that Lysed Yeast will produce the most gas in 45 minutes because the cell membrane is already broken down. We thought the next three would happen in that order because of the sequence of sucrose, glucose, and pyruvate in the breaking down process. If the reaction starts later in the process, less enzymes will be active. Starting from the back, we thought that active yeast and H2O would be last because there would be no enzymes active in the reaction. We thought that the mixtures wih NaF would be next to last because they seem to act as a block in the order of the reaction. Anaerobic Yeast is fifth because the reaction is stopping at the pyrubic acid phase.
Predictions for CO2 Name: Date: 2003-11-19 14:40:22 Link to this Comment: 7331 |
Here are our predictions for the most CO2 to the least CO2.
Test Tube 1: 7
Test Tube 2: 2
Test Tube 3: 6
Test Tube 4: 1
Test Tube 5: 5
Test Tube 6: 4
Test Tube 7: 3
my hand smells Name: stefanie a Date: 2003-11-19 14:44:12 Link to this Comment: 7332 |
1: 1.75
2: 3.5
3: 2
4: 2
5: 2.5
6: 2
7: 2
8: .75
We predict that the tube which would have the greatest net change would be in tube number 4. The tubes that follow, from greatest net evaporation to least, would be:
3
2
1
5
8
6
7
Test Tube CO2 Name: Nomi and J Date: 2003-11-19 14:48:57 Link to this Comment: 7333 |
Hypothesis: Amounts of CO2 will occur, from most to least, in this order:
#1) Pyruvate. Pyruvate is one of the products of glucose; it occurs later in the cycle. Because glucose breaks down into other substances in addition to pyruvate, 5 ml glucose would yield less than 5 ml pyruvate. So, using 5 ml pyruvate, which is implicated in later CO2 production, should produce more CO2 than any of the tests that use 5 ml of any kind of sugar (and hence less pyruvate) instead.
#2) Active Yeast and Glucose. Active yeast should be stronger than, and produce more CO2 than, lysed yeast (which is really dead already and so weaker) and anaerobic yeast (which doesn't perform the citric acid cycle and so can't produce CO2). Glucose, as a pure, simple reactant that is used in full and doesn't need converting from a more complex sugar or carb, should allow a lot of CO2 to be produced.
#3) Active Yeast and Sucrose. Should produce almost as much CO2 as #2 above, but not quite, because sucrose (a double sugar) must be broken down to form glucose (a simple, single sugar). This process of breaking down takes time and energy, so at any given point in time, this reaction will be less far along in its CO2 production than the reaction above, which uses pure glucose.
#4) Lysed Yeast and Glucose. Lysed yeast, since it is dead, won't be as potent. However, some of the enzymes should still be working, and some CO2 should still be produced.
#5) Active Yeast, Glucose, .01M NaF. NaF should inhibit the action of the enzyme which converts the glucose into other forms, thereby limiting CO2 production.
#6) Active Yeast, Glucose, .1M NaF. A higher concentration of NaF will have the same effect on CO2 production as in #5 above, but to a greater extent, because there is more of it to inhibit the enzyme action.
#7) Active Yeast, Water, No Glucose. Without glucose as the substrate/reactant, a lot less CO2 should be produced. However, Julia has observed that plain yeast mixed with water does produce bubbles of CO2, so we decided not to place this one last on the CO2 hierarchy.
#8) Anaerobic Yeast, Glucose. Anaerobic yeast cannot, without using oxygen, go through the Krebs / Citric Acid cycle, so it cannot produce CO2. According to this estimate, the anaerobic yeast should do whatever it can do without oxygen without producing ANY CO2. Maybe it will produce something else....
Name: Date: 2003-11-19 15:01:37 Link to this Comment: 7335 |
From our observations we hypothesize that the lysed yeast will produce the most amount of gas, because it expands when it comes in contact with water.
Ranking of tubes that will produce the most gas (from greatest to least):
4
5
2
3
7
6
8
1
We really do not have an explanation to why we have picked this order.
Who's In Charge? Name: Paul Grobstein Date: 2003-12-02 12:21:31 Link to this Comment: 7425 |
The models we will use come from Northwestern University's Center for Connected Learning and Computer Based Modelling and run in a program called Netlogo. The program and models are available for downloading, so you can continue to explore them on your own computers if you're so inclined.
The models from this site that we will be exploring in class are:
Whichever model you choose to explore, think of it as a process of making observations in order to try and come up with a "story" of how the system behaves. Report your observations and story in the course forum area.
Name: Denise and Date: 2003-12-02 14:42:01 Link to this Comment: 7428 |
Our hypothesis was that if we put everything exactly in the middle on the bars---if the sheep and wolves, for example, had the same reproduction rate and nutrition intake--the ecosysem would be balanced.
We were wrong. Yay for us.
After scrupulous experimentation with differing levels of variables, we discovered a model in which the ecosystem sustained itself. In this system, while the wolves got more nutrition from their food, the sheep reproduced faster. We kept the grass rate at around 100 (if we took away the primary nutrition source of the sheep, they died off and the wolves followd them), and eventually the screen flashed, alternately, full-sheep and full-wolves. Then the mac crashed, because macs are evil.
In conclusion, we suggest a new hypothesis. Wheras wolves, as predators, will deplete the sheep population if they are allowed to reproduce equally, if they simply gain more from their food (as actually happens in real life, considering they're eating meat, which has a higher nutritional quotient anyway) and reproduce less than the sheep, the sheep will be able to maintain a stable population. To test this hypothesis, we could run the simulation several more times.
Abby and Melissa Name: melissa ab Date: 2003-12-02 15:03:51 Link to this Comment: 7429 |
Initially, we attempted to achieve homeostasis by setting all rates at the same level. In doing so, we found inverse relationships between the sheep/grass levels and the sheep/wolf levels.
In revision, we increased wolf gains from food. This resulted in the inherent death of sheep.
Our optimal level, yet not consistently sustained, was when when the sheep population levels were slightly higher than wolf, yet the wolf gain from consumption was considerable higher. While the model began with a direct relationship between the species, it ended in the inverse fluctuations of population levels.
In conclusion, death is inherent. While we are dealing with only two to three variables, it is possible that other external variables not introduced into the model aid in the consistency of survivorship curves.
epidemic Name: Charlotte, Date: 2003-12-02 15:09:31 Link to this Comment: 7430 |
The factors that can be changed with this program include probability of having a sexual relationship, condom use, length of relationship, and frequency of testing.
We kept these factors constant:
-300 people
-5 average coupling tendency
-20 week duration of relationship
-observed over 30 years
**we altered the condom use and frequency of testing.
Our hypothesis was that condom use would be the most important factor in preventing the spread of HIV.
Scenario 1:
Condom use: 3/10
Testing: 0 times a year
Percent infected: 99%
Scenario 2:
Condom: 3/10
Testing: 1 time a year
Percent infected: 9.33%
Scenario 3:
Condom: 3/10
Testing: 2 times a year
Percent: 4.33%
Scenario 4:
Condom: 7/10
Testing: 0 times a year
Percent: 97.67%
Scenario 5:
Condom: 7/10
Testing: 1 time a year
Percent: 8.67%
Scenario 6:
Condom: 7/10
Testing: 2 times a year
Percent: 3.33%
Final Observations: Condom use was important; but test frequency had a greater effect on percent infected. We were shocked at how drastic the difference was, particularly between scenario 4 and 6, because we set them up to simulate what we estimate is closest to real life in our generation.
Conclusion: get tested. twice a year.
don't follow the leader Name: Natalya an Date: 2003-12-02 15:09:36 Link to this Comment: 7431 |
Katie Ottati, Manuela, Laura Wolfe Name: Date: 2003-12-02 15:12:32 Link to this Comment: 7432 |
We wanted to make the sheep, wolves and grass all survive for a long period of time. We figured out since the sheep are lower on the food chain you need a lot more of them. You also need more grass than sheep fr the same reason. We found that it was easier to have the grass on, so that would be a variable as well, because when there was a never-ending supply of grass the populations never stayed stable. By letting everything depend on the other variables, everything stayed more stable.
Also, we played with how much energry wolves can derive from eating a sheep compared to how much energy sheep got from grass. We ended up succeeding in making a stable environment.
stuff Name: Date: 2003-12-02 15:26:40 Link to this Comment: 7433 |
We used the sheep and wolf model. We kept all of the variables the same, the results were always random. When we tried changing the number of sheep and wolves, while still keeping the other variables the same, the results were either one or both would die. Our observations were inconsistent with our hyothesis. We then reduced alll variables for the sheep and the esults showed (surprisingly) that the wolves died first and the sheep reproduced continously.
When examining with grass as a changing factor, we followed the same procedures as the first trial. The results we had were always random with one or both dying.
Sheep
165
5- food gain
9% reproduction
wolves
100
25-food gain
10% reproduction
Grass at 30 reproduction rate
It was at this point that we found equilibrium.
Name: Date: 2003-12-03 14:55:36 Link to this Comment: 7440 |
We played around with the termite model. We found that changing the density determined how well the termites clustered the wood chips. When we changed the population, the only thing that changed was how fast or slow the termites clustered the wood chips.
A bigger density resulted in huge irregular looking clumps, almost like bands. A smaller density caused termites to make a lot of really small piles before eventually building up into few large clusters.
Since they move randomly, the clusters are always of different shapes and patterns. There is no predictability.
wolf and sheep Name: anonymous Date: 2003-12-03 15:03:28 Link to this Comment: 7441 |
We tried to create a system which ensured that no species would become extinct by lack of food or by becoming food for predators.
We assumed that in creating a balance of wolf, sheep, and grass, it was important to begin with the same number of wolves and sheep, including the gain from food and reproduction rate.
Having attempted to begin with equal numbers, we found that an equilibrium of species could not be maintained. The wolves ate the sheep too quickly, so we decreased their number, assuming that the sheep population would be maintained due to a decreased number of predators. However, we soon came to see that the wolves would eventually become extinct, whereas the sheep would not become extinct and exist with the grass. Something else that we noticed was that the relative gain from food for sheep was quicker than that of the wolves, even with less number of wolves. If we had kept the gain from food equal, the sheep would have had a better advantage. We decided to lower the gain from food for sheep, so that the wolves had a better chance of remaining part of the ecosystem.
We then came to understand that in order to maintain equilibrium, we had to start out with a smaller number of wolves and sheep in general. We kept the proportion of wolves and sheep the same as the previous experiments, but lowered the number from 100 sheep to 44 and 80 wolves to 32.
This produced an equilibrium of species, that is, all were able to survive together.
sheep and wolves Name: Date: 2003-12-03 15:10:33 Link to this Comment: 7442 |
For this lab we studied the Wolf/Sheet Predation model. We went into experiment expecting to be able to find a harmonious balance between wolves and sheep. We first increased the sheep population to 250 and increased the wolf population to 120. This lead to the extinction of wolves. We changed reprodution rates of both animals, and yet the wolves stiff suffered from extinction. Differnces in the wolf population were also made, but failed to yeild positive results. After these many changes in variables we decided that balance could not be reached with this vast number of sheep.
We then added grass as another variable, again starting with 250 sheep and 120 wolves. However, the wolves still became extinct.
At this point, we decided to use the initial populations given by the computer program -- 49 wolves and 82 sheep. We kept the grass as a variable, decreasing the regrowth rate to 25. With these factors in place, we found a stable environment for an infinate number of time. The sheep were dominate at most points in time, however, neither species became extinct.
and the green grass grows all around Name: Stefanie a Date: 2003-12-03 15:11:10 Link to this Comment: 7443 |
At these setting the sheep and wolf populations expanded indefinitely. The rate of expansion of the sheep population was very high, and for the wolves very low. Yet, somehow a balance was achieved because both populations survived until our computer ran out of memory, and terminated netlogo. The sheep population at the time of termination was 28,774 and the wolf population a mere 188.
We had the grass option turned off in our first couple of trials. We hypothesize that the grass option, while complicating the experiment, will ultimately serve to limit the expansion of the sheep population.
After setting the grass option to on, and changing the rate of grass regrowth time to 50 (all other values were constant), we found a repeating, self-perpetuating pattern that continued indefinitely. The number of sheep was still greater than the number of wolves, however unlike our previous trials the number of sheep was closer to the number of wolves (about three times the number of wolves).
The pattern gained stability, with the values fluctuating around a point, with no net gain or loss. Our data supports our original hypothesis, that the use of the grass option will limit the expansion of the sheep population. This limitation is what allowed the values to become stable (because the sheep did not increase indefinitely as before).
Slime mold Name: Mariya and Date: 2003-12-03 15:12:47 Link to this Comment: 7444 |
There was not a regular pattern in the increase of the number of clusters, but the number of clusters did increase as the population increased. We think this is because the cells don't have to go as far to form clumps when there are lots of cells present. If there are too few cells, the green chemical evaporates before any other cells happen upon it, so they do not form clumps. (We think they might eventually, given a long time, but we did not observe any clumps below a population of 150.)
sheep and wolves and grass and DEATH Name: Date: 2003-12-03 15:14:27 Link to this Comment: 7445 |
In dealing with the wolf-sheep predation model, we quickly discovered that the key to creating a stable ecosystem was to, without changing any of the other settings, "turn on" the grass. So we decided to change several of the other settings. We found that this ecosystem has a tendency to stabilize at a point where there are approximately twice as many sheep as there are wolves, even if the starting numbers of both are equal or even if the starting number of wolves is greater. We also found that altering the "sheep/wolf reproduce" numbers (the probabilities of each group reproducing at each timestep) did not really destabilize the ecosystem by that much. We found, however, that altering the "sheep/wolf gain from food" numbers had very significant effects on the ecosystem - if we increased the sheep gain-from-food, both the sheep and wolves became extinct very quickly. We then decided to increase proportionally the wolves' gain from food, and found once again that both species quickly became extinct.
Why did this happen? We're not really sure. However, we can hazard a guess:
When, for example, the sheep gain from food was increased, the number of sheep that showed up on the field greatly increased. This would suggest that the probability of their reproducing at each timestep had increased, but we knew that we controlled that number, so we had to discard that idea. What we believe was happening can be explained as follows: Sheep can die in two ways, according to this model: starvation and being eaten by a wolf. Having a low gain from food entails a greater likelihood of dying from starvation (if the grass function is turned on, of course). So, when the gain from food was increased, the sheep were much less likely to starve, causing there to be more of them over the course of time....
as stated above, we're not really sure. at all.
Who's In Charge? Name: Katy and F Date: 2003-12-03 15:24:43 Link to this Comment: 7446 |
We attempted to achieve a stable environment in which both sheep and wolf populations coexisted for a long duration.
We observed the effect of altering one variable at a time while keeping the others constant. This confirmed for us that the relationship between all of the variables is highly important.
We noticed that different combinations of variables; inital number of sheep/wolves, gain from food, and reproductive rate, not only produced different results, but the time until extinction also changed.
We hypothesized that the number of sheep had to be greater than the number of wolves, that the wolves had to gain more from their food than the sheep, and that the rate of reproduction for wolves had to be slightly greater than that of sheep.
The closest we got to achieving a long duration of existence was:
# of sheep: 102 # of wolves: 60
gain from food: 11 gain from food: 25
reproduction: 6% reproduction: 7%
Wolf and Sheepies Name: Fabulous A Date: 2003-12-03 15:28:17 Link to this Comment: 7447 |
Example:
Init.sheep Init. Wolves SheepgainFood W.G.F S. repro W. repro
100 40 5% 15% 5% 5%
Thus, sheep Up, wolves Up--> sheep Down, wolves Down--> sheep Up
The one we did that worked:
I. Sheep I. Wolves S.gainFood W.gainFood S. repro W. repro
100 40 29 60 19 6
After 53 time units there were
sheep--- 339351
Wolves---649
grass----420
The sheep were continuing upward, while the wolves increased at a steady, but slower rate. In conclusion, although our model works, we believe that there is no real solution to this problem: the key is moderation and balance, and diversity. Things are dependent upon one another, in order to create something new, something must first be destroyed---if a model could give us a solution to this problem, then life would be very easy.
HIV spread Name: Patricia P Date: 2003-12-03 15:28:46 Link to this Comment: 7448 |
We thought it would be intersting to test the spread of HIV observing two main variables: Weeks of commitment between partners and condom use. There was a constant 300 person population and 2.67 % was infectd to start.
An extremely brief conclusion: (we will explain further)
with 50 weeks commitment, 0 condom use
65.67% infected by 10 years
with 10 weeks commitment, 0 condom use
100% infected in 10 years
with 50 weeks commitment, 10 condom use (full condom use)
32.88% infected in ten years
10 week commitment, 10 condom use
48.66%
We determined from this that we need to know several other factors. What changes once the people know they are infected? Based on the experiment, we can still see them coupling rapidly. This would not happen in real life. We also wanted to know if 10 condom use stood for 100% of the population using condoms, because that seemed unlikely and high for the scores we got.
Basically we can conclude that if no condoms are used, and commitment to one partner is extreamly short, than the entire population of 300 would contract HIV in 10 years. With comparitive observations of our data, we can say that condom use is a more important factor in stopping the spread (or slowing the spread) of HIV than lengthening the weeks commitment.
Name: Ramatu Kal Date: 2003-12-03 15:35:17 Link to this Comment: 7449 |
Hypothesis:
We hypothesize that when the density of the simulation is higher, there will be none or fewer piles, on the contrary to that when the density of the simulation is lower there will be more piles.
Observations:
1st Test
Number of Termites- 110 (number used in all test)
Density- 30%
@ 2 mins. 4 piles
@5 mins. 4 piles
@7 mins. 4 piles
2nd Test
Density- 70%
@2 mins..- 0 piles
@ 5 mins.- 0 piles
@ 7 mins- 0 piles
3rd Test
@2 mins. 2 piles
@5mins- 2 piles (one extremely large and 1 tiny)
@ 5mins- 2 piles
Conclusion:
We feel that to get a proper set we will need to do more trials.
wolf/sheep trials Name: megan will Date: 2003-12-03 23:09:41 Link to this Comment: 7457 |
I tried many different combinations to match the level of growth of all 3 species. The final one I came up with kept an environmental balance, each of the 3, grass, sheep, and wolves, would increase and decrease interchangeably. None of the species died out, and they continuously overlapped each other in population. I ran this trial for 350 ticks.
Starting combo:
Sheep settings:
Initial number: 75
Gain: 5.0
Reproduction: 6%
Wolf settings:
Initial number: 50
Gain : 25
Reproduction: 7%
Grass growth time: 25
My observations from the graph were that as each species population increased, so did the other, and as each decreased, the same occurred. Since the wolves did have a limited food source, the sheep also had to have a limited food source, or their population would skyrocket within seconds. The 25 extra sheep in the beginning were enough of a buffer to let the wolves catch up, then for the two to grow and decline together.
Chromosome and DNA Name: HT Binh Date: 2005-04-09 05:58:02 Link to this Comment: 14395 |