Geoscience Reference
In-Depth Information
dation. If deer are not present, moose are not limited by wolves. Buried in this
consideration of probabilistic hypotheses are many philosophical issues and
value judgments, but the major thrust is to replace ecological hypotheses with
multiple-regression statistical models. Peters (1991) seemed to adopt this ap-
proach as one way of making applied ecological science predictive.
The more usual entry point for statistical hypotheses in ecology is through
standard statistical tests. Ecological papers are overflowing with these statisti-
cal hypotheses and their resulting
p
-values. We spend more of our time
instructing students on the mechanics of statistical hypothesis testing than we
do instructing them on how to think about ecological issues. I make four
points about statistical inference:
• Almost all statistical tests reported in the literature address low-level
hypotheses of minor importance to the ecological issues of our day, not the
major unsolved problems of ecological science. Therefore, we should not get
too concerned about the resulting
p
-values.
• Achieving statistical significance is not the same as achieving ecological sig-
nificance. You may have strong statistical significance but trivial ecological sig-
nificance. You cannot measure ecological significance by the size of your
p
-values. What matters in ecology is what statisticians call
effect size:
How large
are the differences? There is no formal guidance in what are ecologically sig-
nificant effect sizes. Much depends on the structure of your ecological system.
For population dynamics we can explore the impact of changes in survival and
reproduction through simple life table models. Similar sensitivity analyses are
not possible with questions of community dynamics.
• The null hypothesis of statistical fame, which suggests no differences
between treatments or areas, is not always a good ecological model worth test-
ing. We should apply statistics more cleverly when we expect differences
between treatments and not pretend total ecological ignorance. We can often
make a quantitative estimate of the differences to be expected. One-tailed tests
ought to be common in ecology. Testing for differences can often be used, and
specified contrasts should be the rule in ecological studies. We should use sta-
tistics as a fine scalpel, not as a machete, and we should not waste time testing
hypotheses that are already firmly established.
• No important ecological issue can be answered by a statistical test. The im-
portant ecological issues, such as equilibrium and nonequilibrium paradigms,
