AbstractIdentifying techniques for conducting frequent, effective, and inexpensive monitoring of small mammals can be challenging. Traditional approaches such as livetrapping can be laborious, expensive, detrimental to animal health, and ineffective. Passive approaches such as tracking (e.g., from tracks on the ground or footprints collected at a tracking station) have been shown to lessen those burdens, but a problem with tracking, particularly for rodents, is the uncertainty in identifying species from footprints. To address the need for a more accurate method of identifying small mammal tracks, we measured footprints from live-captured rodents and developed a classification tree for distinguishing between subspecies and species using footprint widths treated as having known or unknown identification. We captured rodents within or near the coastal dunes of Florida and Alabama with a focus on areas occupied by threatened and endangered beach mice Peromyscus polionotus subspp., whose populations warrant regular monitoring but whose tracks are not easily distinguished from those of some sympatric species. We measured 6,996 front and hind footprints from 540 individuals across eight species. The overall accuracy of our classification tree was 82.6% and we achieved this using only the front footprint width. Footprint width cutoffs for species identification were < 5.5 mm for house mice Mus musculus, 5.5–6.7 mm for beach mice, and 6.7–8.3 mm for cotton mice Peromyscus gossypinus. We were most successful in confirming the identity of beach mice: we correctly classified approximately 94% of beach mice, while we misclassified fewer than 6% as house mice and fewer than 1% as cotton mice. When we input a beach mouse individual into the classification tree as of an unknown species, we correctly identified 78.1% of individuals as beach mice from their tracks, and most incorrect identifications were of house mouse tracks. Our study demonstrates that researchers can identify sympatric rodent species in coastal dune communities from tracks using quantitative classification based on footprint width. Accurate identification of beach mice or other imperiled species from tracks has important management implications. Not only can wildlife managers determine the presence of a species accurately, but they can monitor populations with considerably less effort than livetrapping requires. Although our study was specific to coastal dune communities, our methods could be adapted for the creation of a classification tree for identifying tracks from suites of species in other areas.
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