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Abstract
As multiple species of bats are currently experiencing dramatic declines in populations due to white‐nose syndrome (WNS) and other factors, conservation managers have an urgent need for data on the ecology and overall status of populations of once‐common bat species. Standard approaches to obtain data on bat populations often involve capture and handling, requiring extensive expertise and unavoidably resulting in stress to the bats. New methods to rapidly obtain critical data are needed that minimize both the stress on bats and the spread of WNS. Guano provides a noninvasive source of DNA that includes information from the bat, but also dietary items, parasites, and pathogens. DNA metabarcoding is a high‐throughput, DNA‐based identification technique to assess the biodiversity of environmental or fecal samples. We investigated the use of multifaceted DNA metabarcoding (MDM), a technique combining next‐generation DNA sequencing (NGS), DNA barcodes, and bioinformatic analysis, to simultaneously collect data on multiple parameters of interest (bat species composition, individual genotype, sex ratios, diet, parasites, and presence of WNS) from fecal samples using a single NGS run. We tested the accuracy of each MDM assay using samples in which these parameters were previously determined using conventional approaches. We found that assays for bat species identification, insect diet, parasite diversity, and genotype were both sensitive and accurate, the assay to detect WNS was highly sensitive but requires careful sample processing steps to ensure the reliability of results, while assays for nectivorous diet and sex showed lower sensitivity. MDM was able to quantify multiple data classes from fecal samples simultaneously, and results were consistent whether we included assays for a single data class or multiple data classes. Overall, MDM is a useful approach that employs noninvasive sampling and a customizable suite of assays to gain important and largely accurate information on bat ecology and population dynamics.
Highlights
With animal species increasingly facing threats to their persistence from changing climates, disease, habitat loss, and other pressures from human activities, scientists are observing accelerated rates of extinction (Barnosky et al, 2011; Ceballos et al, 2015; IPCC, 2007)
| 1127 diet items (Tables 1 and 2, Supporting Information Tables S1 and S2), from 42 fecal samples each of A. pallidus and L. yerbabuenae from the controlled feedings at the Fort Worth Zoo, (iii) fourteen microsatellite loci to genotype 71 C. rafinesquii fecal samples, (iv) eight microsatellite loci for 23 samples of C. rafinesquii, which were replicated to determine repeatability, and 5) four primers for sex identification that were amplified in 10 samples each of seven species: E. fuscus, L. borealis, M. austroriparius, M. grisescens, M. lucifugus, M. sodalis, and N. humeralis
The primers employed in the multifaceted DNA metabarcoding (MDM) run were as follows: two for insectivorous diet, four for nectivorous diet, one for Pseudogymnoascus destructans (Pd), one for endoparasites, five for bat species ID, four for sex ID, and eight microsatellite loci for C. rafinesquii (Table 2 and Supporting Information Table S2)
Summary
With animal species increasingly facing threats to their persistence from changing climates, disease, habitat loss, and other pressures from human activities, scientists are observing accelerated rates of extinction (Barnosky et al, 2011; Ceballos et al, 2015; IPCC, 2007). Collection of the data needed to inform conservation efforts requires teams with specialized field expertise, may involve capture and handling of the animals, and typically results in stress to the target species. Noninvasive sampling (NIS), which involves sampling individuals indirectly by collecting biological materials left in the environment, such as eggshells, feathers, saliva, hairs, urine, or feces, is increasingly being employed to conduct assessments of animal populations, eliminating the need to capture or handle an animal (Beja-P ereira, Oliveira, Alves, Schwartz, & Luikart, 2009) and vastly reducing the stress involved (Arandjelovic et al, 2010; Eggert, Eggert, & Woodruff, 2003; Rudnick, Katzner, Bragin, Rhodes, & Dewoody, 2005; Steyer, Simon, Kraus, Haase, & Nowak, 2013). One of the most common ways that NIS samples are used to conduct population assessments is through the analysis of DNA in the sample, which can provide information about the genotype of a target individual as well as data on population parameters such as genetic diversity, population size, and population structure (Adams, Kelly, & Waits, 2003; Bellemain, Swenson, Tallmon, Brunberg, & Taberlet, 2005; Fernando, Pfrender, Encalada, & Lande, 2000; Flagstad et al, 2004)
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