Predicting the distribution of a rare chipmunk (Neotamias quadrivittatus oscuraensis): comparing MaxEnt and occupancy models

Abstract

Abstract Species distribution models (SDMs) use presence records to determine the relationship between species occurrence and various environmental variables to create predictive maps describing the species’ distribution. The Oscura Mountains Colorado chipmunk (Neotamias quadrivittatus oscuraensis) occurs in central New Mexico and is of conservation concern due to its relict distribution and threats to habitat. We previously created an occupancy model for this taxon, but were concerned that the model may not have adequately captured the ecological factors influencing the chipmunk’s distribution because of the data hungry nature of occupancy modeling. MaxEnt is another SDM method that is particularly effective at testing large numbers of variables and handling small sample sizes. Our goal was to create a MaxEnt model for the Oscura Mountains Colorado chipmunk and to compare it with our previous occupancy model for this taxon, either to strengthen our original assessment of the relevant ecological factors or identify additional factors that were not captured by our occupancy model. We created MaxEnt models using occurrence records from baited camera traps and opportunistic surveys. We adjusted model complexity using a novel method for tuning both the regularization multiplier and feature class parameters while also performing variable selection. We compared the distribution maps and variables selected by MaxEnt to the results of our occupancy model for this taxon. The MaxEnt and occupancy models selected similar environmental variables and the overall spatial pattern of occurrence was similar for each model. Likelihood of occurrence was positively related to elevation, piñon woodland vegetation type, and topographic variables associated with escarpments. The overall similarities between the MaxEnt and occupancy models increased our confidence of the ecological factors influencing the distribution of the chipmunk. We conclude that MaxEnt offers advantages for predicting the distribution of rare species, which can help inform conservation actions.