Part 1: Fearsome Frogs
I know that
sometimes it seems like I’m being really glib, but I assure you I am not when I
say this: I had no idea frogs could climb mesh fences. It’s one of those things
that I guess should have been blatant, but when the gentleman from the video
talks about the frogs climbing his fences, the mental picture nearly sent me
rolling out of my chair giggling like … There’s really no appropriate way to finish that simile is there? Anyway, on to
solutions: There really isn’t one to be honest. I know it sounds sad and really
dismal, but once we screw something up like this, we can’t really fix it. The
most direct fix would be bounty slayings to wipe them out (like we’ve done with
larger predators on several occasions), but the lessons of that type of “fix,”
have been hard learned, and held little variation: they always hurt the
situation in small (or at times huge) ways. It turns out that if you cause an
overpopulation, then reverse it to zero population or low population, something
else winds up starving, dying, or combusting spontaneously. Okay, I’m kidding
about the combustion thing, but it really can be startling when you realize
that your actions have lead to some species of something that the animal you
just got rid of interacted with has suffered and/or disappeared entirely from
the region. To be completely honest, I think the best thing to do (even given
my opposition to such behavior) would be a closely
controlled bounty based culling to try
to avoid throwing something else out of whack the other direction. I
suppose option B would be convincing Arizonians that frog is tasty (which for
the record it is) and rely on the sudden surge of interest in eating them
(which couldn’t possibly result in
something even worse). Look, the real lesson here is this: we really shouldn’t
mess with this kind of thing simply because we fancy ourselves some kind of
magical curator of nature; the fact is we rarely guess what our actions will
result in correctly, and it seems like everything we alter (even when we’re trying
to help) simply winds up in a worse way than when we found it due to some unforeseen
variable or ripple effect started with intentions of pure gold.Part 2: Sampling Lab
Random Sampling
Data
|
Actual Data
|
||
Grid Segment
(number and letter) |
Number of Sunflowers
|
Total number of Sunflowers 228
(count by hand)
Average number of Sunflowers
(divide total by 100) Per grid 2.28 (about 2) |
|
B4
|
2
|
||
E7
|
2
|
||
I8
|
1
|
||
G3
|
4
|
||
J9
|
1
|
||
H5
|
2
|
||
B1
|
3
|
||
G9
|
2
|
||
C6
|
1
|
||
B2
|
2
|
||
Total Number of Sunflowers
|
20
|
||
Average (divide total by 10)
|
2
|
||
Total number of plants in meadow
(multiply average by 100) |
200
|
1.
Compare the total number you got for
sunflowers from the SAMPLING to the ACTUAL count. How close are they? The two averages are within .28 of one
another (certainly close enough to be considered accurate). The total count (correlating
with the average of course) is off by 28 flowers, again the sample count is definitely
close enough to the actual count to be considered accurate.
2.
Why was the paper-slip method used to select
the grid segments? The paper slip method was used in this
lab to make sure the samples were legitimately random, and demonstrate the
importance of randomizing your samples (rather they come out of a cup or are
collected in person).
3.
A lazy ecologist collects data from the same
field, but he stops just on the side of the road and just counts the ten
segments near the road. These ten segments are located at J, 1-10. When she
submits her report, how many sunflowers will she estimate are in the field? She
would report an average of .7 flowers per block (or 1 depending on her personal
preference). Her estimate for total flowers would be around 70, which is (of
course) quite off.
4.
Suggest a reason why her estimation differs
from your estimation. Her estimation varies so greatly from
mine because all her data was collected in one spot. You (of course) can’t do this, because you
have no idea if that one spot is in any way representative of the actual
population over a broad area. It may not be perfect, but wander sampling can yield
much more accurate results (and can alert the gatherer of said information of
polar variations and their causes).
5.
Population sampling is usually more effective
when the population has an even dispersion pattern. Clumped
dispersion patterns are the least effective. Explain why this
would be the case. Any population that is evenly
dispersed is easier to get a general count of. If you know that Wild Corn Vines
(yes I just made that up) grow pretty evenly across a large area, it shrinks
the area you must traverse to collect sample information; or at the very least
makes your results tend to be more accurate. Now on the other hand, if the Wild
Corn Vine (not giving it up) is known to clump together where it sprouts up
(being a giant root and all) getting an accurate count can be a huge pain,
because you may simply find a clump every other mile (where you happen to stop)
then assert that there are thousands of Wild Corn Vines in that area, not
realizing that your results have been tainted by their population being really
clumped up, and in fact, the Wild Corn Vine is nearly extinct.
6. Describe
how you would use sampling to determine the population of dandelions in your
yard. Unfortunately, I can answer this right
now: there are zero :( However, if we were counting anything anywhere, the best
ways are either mark out a map with a grid and make counts of each randomly
selected square (or for fun, you and the team I’d hope you’d have for this type
of work can each pick a square), or mark out the ground itself using chords or
tape to create your grid. Suffice to say, the grid is the key.
7. In an
area that measures five miles by five miles, a sample was taken to count the
number of desert willow trees. The number of trees counted in the grid is shown
below. The grids where the survey was taken were chosen randomly. Determine how
desert willow trees are in this forest using the random sampling technique.
Show your calculations. Well,
based on the information below, there were 25 areas 5 of which were counted for
a total of 35 Desert Willow Trees in the sample group. So, to find the average,
we take our 35 Desert Willow Trees and divide that number by the number of
samples taken, in this case: 5 (35 / 5 = 7) resulting in an average count of 7.
Since there are 25 areas total, we multiply the average count by the total
number of areas (7*25=175) resulting in an estimated region population of
Desert Willow Trees of 175.
7
| ||||
3
| ||||
5
| ||||
11
|
9
| |||
Reference
Biology Corner. Random Sampling. 2014 Apr 6. Web.