[Fwd: Re: suggestion to jessica and others]

[Jessica Junker]

Dear Maxent users,

This question links up with my previous question on whether Maxent
captures interactions between environmental variables or whether these
interactions have to be included into the input variable before running
the model (e.g. creating an .asci layer that includes distance to
rivers, where in high human density areas, probability of ape occurrence
decreases with distance to rivers, whereas near rivers in low rainfall
areas with gallery forests and not humid rain forest, ape probability
increases - here, the problem is that I don't exactly know how the
distance to rivers function looks, i.e. linear or quadratic
relationship??).

In the Maxent output document, in the response curves section, I read
"Note that the curves can be hard to interpret if you have strongly
correlated variables, as the model may depend on the correlations in
ways that are not evident in the curves. In other words, curves show
the marginal effect of changing exactly one variable, whereas the model
may take advantage of sets of variables changing together".

Does this mean that the response curves show the modelled effect of the
different variables (in isolation) on the logistic prediction, or is
this just the effect that the program "sees" (I am sorry, I don't know
how else to say this, do you know what I mean?)? I mean in a GLM, for
example, I have to specify which variables interact with one another and
how (the type of relationship) they interact with the response variable
prior to running the model? Do I have to do the same when using Maxent?

I hope someone can help me clarify things. Thank you!
Regards
Jessi


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Jessica Junker
Max-Planck Institute for Evolutionary Anthropology
Department of Primatology
Deutscher Platz 6
04103 Leipzig
Germany

tel: +49 341 3550 254
fax: +49 341 3550 299
cell: +49 0160 90594996
email: jessica...@eva.mpg.de

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