Integrating counts, telemetry, and non‐invasive DNA data to improve demographic monitoring of an endangered species

• Published in: Ecosphere
• Main Authors: Moeller, Anna K., Nowak, J. Joshua, Neufeld, Lalenia, Bradley, Mark, Manseau, Micheline, Wilson, Paul, McFarlane, Samantha, Lukacs, Paul M., Hebblewhite, Mark
• Other Authors: University of Montana
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2021
• Subjects: Rangifer tarandus
• Online Access: http://dx.doi.org/10.1002/ecs2.3443; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3443; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.3443; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3443

Abstract Population monitoring can take many different forms, and monitoring elusive and endangered species frequently involves a variety of sparse data from different sources. Small populations are often hard to sample precisely and without bias, so when estimates of vital rates like survival or recruitment point to conflicting population trends, it can be hard to determine which is more correct. Furthermore, data can be extremely hard to collect on small populations and it can be helpful to find a way to use all available hard‐won data. To address these issues, we developed an integrated population model (IPM) using all available data to estimate vital rates and abundance for a case study of an endangered woodland caribou ( Rangifer tarandus caribou ) population. This IPM allowed us to incorporate data from juvenile recruitment surveys, telemetry‐based survival, aerial population counts and mark–resight data, and non‐invasive capture–recapture DNA data to better understand population status and trend. We estimated survival, abundance, and recruitment of four age classes of male and female caribou: young, juveniles, subadults, and adults. The four‐age class structure of the IPM allowed us to estimate recruitment from reproductive‐aged female caribou alone, even though it can be difficult to distinguish age classes—and even sexes—in the field. As part of our IPM, we developed a novel mixture model to break apart data from different age classes when age is unobservable, as it typically is from non‐invasive DNA samples. This helped us decrease bias in juvenile and adult survival estimates from scat data, which was important to our understanding of the population dynamics. Overall, our integrated model provided more precise estimates of population trends than any one method (e.g., telemetry or non‐invasive DNA) alone. This IPM provides a useful, flexible tool for biologists to monitor populations and provides a valuable example of the benefits of integrated population modeling approaches for endangered species ...