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"Without data, you're just
another guy with an opinion." - Anon
But data on their own aren't enough. You need a good
scheme to gather the data and proper analysis if your
conclusions are to be more credible than another guy's opinion.
This group of web pages grew out of our in-house staff
training sessions. They now reflect the material presented
during our 2-week stats "Boot Camps" run in co-operation
with the
Biodiversity Conservation Society of Sarawak (BCSS).
The
icon indicates
material which we only include in the basic Boot
Camp if there is sufficient interest - and time! Topics without hyperlinks are still
being worked on.
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Rationale
Why is a specialist course (or web site) on
wildlife study design and data analysis needed?
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Teaching approach
We try to get away from sit-and-listen lectures
and include lots of practical activities, games and
exercises.
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R software
We recommend R and use it in most of our courses.
Details of other software packages we use are
here.
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 Inferences based on samples
We can rarely measure the whole population or area, so we
take a sample and use this to make inferences about the whole. Our
inferences will not exactly equal the values for the population, due
to random errors or noise introduced by sampling.
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 Testing hypotheses
We get different results when we draw 2 samples from the
same population, so samples from
different populations may differ just by chance, not because
of the effect we are interested in. We must always ask, "Could it
just be due to chance?"
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Models and model selection
This is a key topic and underlies most approaches to
detection probability
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Study design and sample selection
Without good study design, your data may turn out to be of
little use. The design stage of a research project is usually
skimped as people rush out to start collecting data.
- What's the question? - different questions need different
designs.
- Review of basic sampling schemes.
- Using simulations to compare sampling designs.
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Bayesian approaches
These methods quantify the uncertainty about estimates and
produce information which can be fed into decision-making processes
for management.
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 Estimating occupancy
Simple 'presence/absence' data can give useful results, if
corrected for detection probability
You may also like to look at the
exercises on occupancy at U of Vermont.
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Estimating animal densities from transects
'Distance sampling' using line or point transects give
estimates of density, and hence numbers of animals in the area of
interest.
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Using dung or nests to estimate
animal densities
The density of animal signs, such as dung piles or nests, can
be used, provided rates of production and decay can be estimated.
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Estimating animal populations with mark-recapture methods
Mark-recapture methods provide estimates of the number of
animals in the area sampled. If that is known, the density can be
calculated.
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Species richness and diversity
Biodiversity must be protected - even promoted - but is
fiendishly difficult to quantify.
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Miscellaneous
Various topics which don't fit well under other headings
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Content on this site,
except for photographs, is licensed under a
Creative
Commons Attribution 3.0 License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original
author is acknowledged.
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