An open spatial capture–recapture model for estimating density, movement, and population dynamics from line‐transect surveys. Issue 12 (3rd May 2021) - Gowan, Timothy A.; Crum, Nathan J.; Roberts, Jason J.
Abstract: The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line‐transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture–recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture–recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture–recapture model that can be applied to line‐transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line‐transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line‐transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics. Abstract : We developed an open spatial capture–recapture model that can be applied to line‐transect survey data. The model estimates demographic parameters while simultaneously providing inference on factors that influence spatial and temporal variation in density and space use. We illustrate its use with aerial survey data for North Atlantic right whales ( Eubalaena glacialis ) in the southeastern United States.