Animal Ecology (Zoology 441) at UT
Martin
Practice Question Set #1 ? factors in ecology, scientific
method, Connell study, types of error, statistics, sampling
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Ecology can be defines as "the scientific study of factors determining
the distribution and abundance of organisms." (a) At what levels can distribution
be measured? (b) At what levels can abundance be measured?
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What are the two categories of factor that determine the distribution and
abundance of organisms? Give examples of each. Explain why
the distinction between the two is not always clear cut.
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List the major types of biotic interaction discussed in lecture, state
what causes each, and state whether each interacting species are positively
or negatively impacted by the interaction.
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Explain why it is never possible to prove a hypothesis.
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Ecological studies can be descriptive or experimental; experimental studies
can be lab-based or field-based. What are the general pros and cons
of each of these forms of study?
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Distinguish between systematic error and random error. Which results
in bias? Which is most likely to be decreased by increasing sample
size? What are the major kinds of problem with interpretation caused
by each type of error? What are possible causes of each kind of error
in ecological studies?
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In a scientific paper, you read that "the mean number of turtle nests per
m2 in sandy soil is significantly higher than in clay soil (t=
8.2, df=34, p<0.01)." What does "significantly higher" mean in this
statement? What does p mean?
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Distinguish between the terms signficance and power. Why do ecologists
care about significance? Why do ecologists care about power?
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What can ecologists do to increase statistical power in their studies?
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To study nest site choice in pileated woodpeckers (a species that excavates
nest holes in trees), you sample large quadrats to describe the relationship
between the number of woodpecker holes per quadrat and two vegetation variables:
tree dbh (diameter at breast height, a standard measure of tree width),
which you measure, and amount of understory cover, which cannot be
quantitatively measured but can be divided into two categories, high cover
and low cover. If you sample quadrats at random, what kind of error will
you avoid? Suppose that you can only sample 10 quadrats. How
will this affect your conclusions if you find a significant association
between number of holes and one of your variables? How will this affect
your conclusions if you do NOT find a significant association between number
of holes and one of your variables?
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An ecologist is interested in determining whether the abundance of beavers
is related to the predominant tree type in woodlands. The number
of beaver lodges per hectare is compared between a pine forest, an oak-hickory
forest, and a beech-maple forest. Suppose there turn out to be significantly
more lodges per hectare in the pine forest than in the oak-hickory or beech-maple
forest. The researcher wants to conclude that beavers are more abundant
in pine forests. Is this conclusion valid? Why/why not?
If not, state an alternative hypothesis that could explain beaver abundance.
What would you do to better test between your hypothesis and the original
hypothesis?
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You are studying vole (small rodent) density in a cow pasture by sampling
the number of vole holes per m2 in a number of 1 m2
quadrats. Since you notice that the cow pasture has two apparently
different kinds of vegetation, one dominated by cheatgrass and one dominated
by bluegrass, you are careful to choose some of your quadrats in
cheatgrass areas and some in bluegrass areas. Why is this NOT the
best way to sample vole density in this field? What would be a better
approach?
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In a study of territoriality in sparrows, researchers found that average
territory size was larger during a cold year than it was during a warm
year. They concluded that temperature affects sparrow resources so
they require larger territories during cold years. What is wrong
with this conclusion? What information is needed to make this conclusion
stronger?
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Suppose you are studying home range size in different habitats for two
species of deer, mule deer and white-tailed deer. You are using
radio tracking to obtain accurate estimates of home range size. You
are able to study 8 mule deer in riparian habitats and 6 in upland habitats;
you study 9 white-tailed deer in upland habitats and 7 in riparian habitats.
Suppose you find that home range size is significantly larger for mule
deer in upland habitats than mule deer in riparian habitats. You
find that there is no statistical difference in home range size between
the two habitats for white-tailed deer. In which conclusion do you
have more confidence: (i) that home range size for mule deer is larger
in upland than riparian habitats in the area you studied them, or (ii)
that there is no difference in home range size of white-tailed deer between
upland and riparian habitats in the area where you studied them?
Explain why you have more confidence in one conclusion than in the other.