Journal Article

Occupancy estimation and the closure assumption

Betts, Matthew G, Dorazio, Robert M, Rota, Christopher T, Fletcher Jr, Robert J

2009

Overview

1. Recent advances in occupancy estimation that adjust for imperfect detection have provided substantial improvements over traditional approaches and are receiving considerable use in applied ecology. To estimate and adjust for detectability, occupancy modelling requires multiple surveys at a site and requires the assumption of 'closure' between surveys, i.e. no changes in occupancy between surveys. Violations of this assumption could bias parameter estimates; however, little work has assessed model sensitivity to violations of this assumption or how commonly such violations occur in nature. 2. We apply a modelling procedure that can test for closure to two avian point-count data sets in Montana and New Hampshire, USA, that exemplify time-scales at which closure is often assumed. These data sets illustrate different sampling designs that allow testing for closure but are currently rarely employed in field investigations. Using a simulation study, we then evaluate the sensitivity of parameter estimates to changes in site occupancy and evaluate a power analysis developed for sampling designs that is aimed at limiting the likelihood of closure. 3. Application of our approach to point-count data indicates that habitats may frequently be open to changes in site occupancy at time-scales typical of many occupancy investigations, with 71% and 100% of species investigated in Montana and New Hampshire respectively, showing violation of closure across time periods of 3 weeks and 8 days respectively. 4. Simulations suggest that models assuming closure are sensitive to changes in occupancy. Power analyses further suggest that the modelling procedure we apply can effectively test for closure. 5. Synthesis and applications. Our demonstration that sites may be open to changes in site occupancy over time-scales typical of many occupancy investigations, combined with the sensitivity of models to violations of the closure assumption, highlights the importance of properly addressing the closure assumption in both sampling designs and analysis. Furthermore, inappropriately applying closed models could have negative consequences when monitoring rare or declining species for conservation and management decisions, because violations of closure typically lead to overestimates of the probability of occurrence.

• Publisher: Oxford, UK : Blackwell Publishing Ltd,Blackwell Publishing,Blackwell Publishing Ltd
• Subject: Animal populations / Applied ecology / Birds / breeding birds / colonization / Conservation biology / Datasets / detection probability / dynamic models / Ecological modeling / Environmental monitoring / estimation / Estimation bias / Extinct species / extinction / Field tests / Habitats / metapopulation / Metapopulation ecology / Modeling / Montana / New Hampshire / Parametric models / point counts / Population Estimation / population size / Probability / probability analysis / Rare species / removal models / robust design / Sampling / simulation models / Species / surveys / wild birds / wildlife habitats