LAUSR

Small rodents are prevalent and functionally important across world’s biomes, making their monitoring salient for ecosystem management, conservation, forestry and agriculture. Yet, there is a dearth of cost-effective and non-invasive methods for large-scale, intensive sampling. As one such method, fecal pellet counts readily provide relative abundance indices. Given available analytical methods, feces could also allow for determination of multiple ecological and physiological variables, including community composition. We developed calibration models for rodent taxonomic determination using fecal near-infrared reflectance spectroscopy (fNIRS). Our results demonstrate fNIRS as an accurate and robust method for predicting genus and species identity of five co-existing subarctic microtine rodent species. We show that sample exposure to weathering did not reduce accuracy, indicating suitability of the method for samples collected from the field. Diet was not a major determinant of species prediction accuracy in our samples, as diet exhibited large variation and overlap between species. While regional calibration models predicted poorly samples from another region, calibration models including samples from two regions provided a good prediction accuracy for both regions. We propose fNIRS as a fast and cost-efficient high-throughoutput method for rodent taxonomic determination, and highlight its potential for cross-regional calibrations and use on field-collected samples. FNIRS can facilitate rodent population censuses at larger spatial extent than before deemed feasible, if combined with pellet-count based abundance indices. Given the versatility of fNIRS analytics, developing such monitoring schemes can support ecosystem- and interaction-based approaches to monitoring.