
all

i have a question about evaluating maxent models in dismo with presence-absence data ...

i'm modeling species where most have 30-300 presences in ~1500 plots (eg. 1200 - 1470 absences).
i read maxent performs best with large #s of background points (eg. ~10,000 pseudo absences), but
for evaluation, background data give a good measure of model fit, not predictive skill. as an alternative:

1) can i use all my absences as test data (as opposed to 20% partition), since these were not used to train models?

2) for species with less than 1000 absences, is this approach likely to be sufficient for evaluation?


thanks for any help in advance!

cheers,
j






-- 

jason mackenzie, phd

senior conservation fellow
the nature conservancy
201 mission street, 4th floor
san francisco, ca 94105
jmackenzie@tnc.org

jasonbmackenzie        [skype]


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