Delete Unmatched Columns button   Use this to remove samples that are not
present in both data sets.
Truncate Longest Dataset button   Use this to truncate both data sets to the
number of samples in the smaller data set.
OK button   Click to continue with analysis
Environmental variables from biological features
There is a paradox in gradient analysis: species respond to the environment, but they
also modify the environment. For example, vegetation itself can be considered an
environmental factor to which vegetation responds. There are a suite of variables
derived from species data which might be useful in CCA and other constrained
ordinations: maximum height of vegetation, total biomass, light penetrating through
the canopy, woody plant cover, etc.
These variables might be quite informative in an exploratory analysis, though the
ecologist must realize that it would be difficult to distinguish cause and effect.
Species derived variables should NOT be used in hypothesis testing, because the
same data would be represented in both the dependent and the independent
variables. This would lead to circular reasoning. A compromise would be to have these
vegetation derived variables considered "passive" or "supplementary"   i.e. they
would be included in diagrams, but would not otherwise influence the ordination.
An extreme case of species derived variables is to use dummy variables derived from
a classification of samples. The classification could either be a result of a subjective
procedure (e.g. the Braun Blanquet approach or something less formal) or a
Copyright 2004  PISCES Conservation Ltd

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