Design‐ and model‐based recommendations for detecting and quantifying an amphibian pathogen in environmental samples |
| |
Authors: | Brittany A. Mosher Kathryn P. Huyvaert Tara Chestnut Jacob L. Kerby Joseph D. Madison Larissa L. Bailey |
| |
Affiliation: | 1. Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA;2. US Geological Survey, Oregon Water Science Center, Portland, OR, USA;3. Department of Biology, University of South Dakota, Vermillion, SD, USA |
| |
Abstract: | Accurate pathogen detection is essential for developing management strategies to address emerging infectious diseases, an increasingly prominent threat to wildlife. Sampling for free‐living pathogens outside of their hosts has benefits for inference and study efficiency, but is still uncommon. We used a laboratory experiment to evaluate the influences of pathogen concentration, water type, and qPCR inhibitors on the detection and quantification of Batrachochytrium dendrobatidis (Bd) using water filtration. We compared results pre‐ and post‐inhibitor removal, and assessed inferential differences when single versus multiple samples were collected across space or time. We found that qPCR inhibition influenced both Bd detection and quantification in natural water samples, resulting in biased inferences about Bd occurrence and abundance. Biases in occurrence could be mitigated by collecting multiple samples in space or time, but biases in Bd quantification were persistent. Differences in Bd concentration resulted in variation in detection probability, indicating that occupancy modeling could be used to explore factors influencing heterogeneity in Bd abundance among samples, sites, or over time. Our work will influence the design of studies involving amphibian disease dynamics and studies utilizing environmental DNA (eDNA) to understand species distributions. |
| |
Keywords: |
Batrachochytrium dendrobatidis
Chytridiomycosis detection probability eDNA filtration host‐pathogen dynamics qPCR monitoring multiscale occupancy |
|
|