Species distribution models (SDMs) use information about where a species occurs to determine the relationship between species occurrence and environmental variables and thus create maps that predict the species’ distribution. We conclude that Ma圎nt offers advantages for predicting the distribution of rare species, which can help inform conservation actions. The overall similarities between the Ma圎nt and occupancy models increased our confidence of the ecological factors influencing the distribution of the chipmunk. Likelihood of occurrence was positively related to elevation, piñon woodland vegetation type, and topographic variables associated with escarpments.
The Ma圎nt and occupancy models selected similar environmental variables and the overall spatial pattern of occurrence was similar for each model. We compared the distribution maps and variables selected by Ma圎nt to the results of our occupancy model for this taxon. We adjusted model complexity using a novel method for tuning both the regularization multiplier and feature class parameters while also performing variable selection. We created Ma圎nt models using occurrence records from baited camera traps and opportunistic surveys. Our goal was to create a Ma圎nt 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. Ma圎nt is another SDM method that is particularly effective at testing large numbers of variables and handling small sample sizes. 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. 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. 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.
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