Improving inference for aerial surveys of bears: The importance of assumptions and the cost of unnecessary complexity.

ABSTRACT: Obtaining useful estimates of wildlife abundance or density requires thoughtful attention to potential sources of bias and precision, and it is widely understood that addressing incomplete detection is critical to appropriate inference. When the underlying assumptions of sampling approaches are violated, both increased bias and reduced precision of the population estimator may result. Bear (Ursus spp.) populations can be difficult to sample and are often monitored using mark-recapture distance sampling (MRDS) methods, although obtaining adequate sample sizes can be cost prohibitive. With the goal of improving inference, we examined the underlying methodological assumptions and estimator efficiency of three datasets collected under an MRDS protocol designed specifically for bears. We

SUBMITTER: Schmidt JH 

PROVIDER: S-EPMC5496527 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature