Update on methods to improve inference in point-transect models

Speaker: Richard J. Camp (CREEM)

Abstract

Point-transect distance sampling is particularly useful for surveying birds, and over the last four decades it is the standard method employed in Hawaiian forest bird monitoring. Accurate and precise estimates are essential to understanding how populations change across space and through time, particularly for rare species and in response to conservation efforts and management actions. Point-transect sampling involves recording distances to individually detected birds at samplers located along transects. In my previous CREEM seminar I demonstrated how the sampler-level data can be used to calculate density estimates and evaluate trends in densities for the endangered Hawai?i ?Akepa (Loxops coccineus) using smoother methods. In this presentation I detail how the detection probability uncertainty is propagated using posterior simulation methods and describe why methods such as bootstrap and delta methods are not appropriate. An alternative to density surface modelling and smoother methods is to model the density time series using state-space models. State-space models can be expanded to incorporate demographic vital rates. I describe the population dynamics models I have been exploring and illustrate how they improve inference by reducing uncertainty in the point-transect density estimates.