An open-population hierarchical distance sampling model

By: , and 



Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

Publication type Article
Publication Subtype Journal Article
Title An open-population hierarchical distance sampling model
Series title Ecology
DOI 10.1890/14-1625.1
Volume 96
Issue 2
Year Published 2015
Language English
Publisher Ecological Society of America
Publisher location Brooklyn, NY
Contributing office(s) Patuxent Wildlife Research Center
Description 7 p.
First page 325
Last page 331
Online Only (Y/N) N
Additional Online Files (Y/N) N
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