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Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?

April 1, 2019

Occupancy models are widely applied to estimate species distributions, but few methods exist for model checking. Thorough model assessments can uncover inadequacies and allow for deeper ecological insight by exploring structure in the observed data not accounted for by a model. We introduce occupancy model residual definitions that utilize the posterior distribution of the partially latent occupancy states. Residual‐based assessments are valuable because they can target specific assumptions and identify ways to improve a model, such as adding spatial correlation or meaningful covariates. Our approach defines separate residuals for occupancy and detection, and we use simulation to examine whether missing structure for modeling detection probabilities can be distinguished from that for occupancy probabilities. In many scenarios, our residual diagnostics were able to successfully separate inadequacies at the different model levels, but we describe other situations when this may not be the case. Applying Moran's I residual diagnostics to assess models for silver‐haired (Lasionycteris noctivagans) and little brown (Myotis lucifugus) bats only provided evidence of residual spatial correlation among detections. Targeting specific model assumptions using carefully chosen residual diagnostics is valuable for any analysis, and we remove previous barriers for occupancy analyses — lack of examples and practical advice.

Citation Information

Publication Year 2019
Title Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?
DOI 10.1002/ecy.2703
Authors Wilson Wright, Kathryn M. Irvine, Megan D. Higgs
Publication Type Article
Publication Subtype Journal Article
Series Title Ecology
Index ID 70202863
Record Source USGS Publications Warehouse
USGS Organization Northern Rocky Mountain Science Center