Dear friends,
It has been recently suggested by Legendre and co-authors that we
include quadratic and product terms of our environmental variables in
constrained ordinations. For instance, to include not only latitude but
also latitude^2 and latitude*longitude, the same with physical and
biotic variables aimed at being correlated with ordination axis in some
way.
I am following McCune and Grace's book (2002) suggestion of
correlating environmental variables with NMDS axes. However common
correlations of multiple variables x each nmds axis are not the best
options because at each correlation they do not control for the other
variables in the dataset. Those authors also state that multiple
regression use partial correlation coefficients and thus would be a
better methos for correlating several environmental variables with
ordination axes.
However, multiple regression suffers from multicolinearity, which is
greatly enhanced when we use product or quadratic terms of the
environmental variables.
What do you think about that?
Best whishes,
Alexandre
Dr. Alexandre F. Souza
Programa de Pós-Graduação em Biologia: Diversidade e Manejo da Vida
Silvestre
Universidade do Vale do Rio dos Sinos (UNISINOS)
Av. UNISINOS 950 - C.P. 275, São Leopoldo 93022-000, RS - Brasil
Telefone: (051)3590-8477 ramal 1263
Skype: alexfadigas
[email protected]
http://www.unisinos.br/laboratorios/lecopop
