DNA contained in animal scat provides a wealth of information about the animal, and DNA metabarcoding of scat collections can provide key information about animal populations and communities. Next-generation DNA sequencing technologies and DNA metabarcoding provide an efficient means for obtaining information available in scat samples. We used multifaceted DNA metabarcoding (MDM) of noninvasively collected bat guano pellets from a Myotis lucifugus colony on Fort Drum Military Installation, New York, USA, and from two mixed-species bat roosts on Fort Huachuca Military Installation, Arizona, USA, to identify attributes such as bat species composition, sex ratios, diet, and the presence of pathogens and parasites. We successfully identified bat species for nearly 98% of samples from Fort Drum and 90% of samples from Fort Huachuca, and identified the sex for 84% and 67% of samples from these same locations, respectively. Species and sex identification matched expectations based on prior censuses of bat populations utilizing those roosts, though samples from some species were more or less common than anticipated within Fort Huachuca roosts. Nearly 62% of guano samples from Fort Drum contained DNA from Pseudogymnoascus destructans, where bats with wing damage from White-nose Syndrome were commonly observed. Putative dietary items were detected in a majority of samples from insectivorous bats on Fort Drum (81%) and Fort Huachuca (63%). A minority of guano samples identified as the nectarivorous Leptonycteris yerbabuenae (28%) provided DNA sequences from putative forage plant species. Finally, DNA sequences from both putative ecto- and endoparasite taxa were detected in 35% and 56% of samples from Fort Drum and Fort Huachuca, respectively. This study demonstrates that the combination of noninvasive sampling, DNA metabarcoding, and sample and locus multiplexing provide a wide array of data that are otherwise difficult to obtain.
Keywords: Chiroptera; DNA barcode; DNA sexing; noninvasive genetics; trophic analysis; wildlife disease surveillance.
© 2022 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.