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A goodness-of-fit test for occupancy models with correlated within-season revisits

Overview of attention for article published in Ecology and Evolution, August 2016
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Title
A goodness-of-fit test for occupancy models with correlated within-season revisits
Published in
Ecology and Evolution, August 2016
DOI 10.1002/ece3.2292
Pubmed ID
Authors

Wright, Wilson J, Irvine, Kathryn M, Rodhouse, Thomas J

Abstract

Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodness-of-fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie-Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie-Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and specifically evaluates occupancy model lack of fit related to correlation among detections within a sample unit. Our diagnostic tool is available for practitioners that serially deploy survey equipment as a way to achieve cost savings.

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Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 53 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 24%
Student > Master 11 20%
Student > Ph. D. Student 7 13%
Other 6 11%
Unspecified 5 9%
Other 12 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 52%
Environmental Science 14 26%
Unspecified 8 15%
Biochemistry, Genetics and Molecular Biology 1 2%
Veterinary Science and Veterinary Medicine 1 2%
Other 2 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 August 2016.
All research outputs
#7,153,890
of 8,272,014 outputs
Outputs from Ecology and Evolution
#2,008
of 2,168 outputs
Outputs of similar age
#213,733
of 253,542 outputs
Outputs of similar age from Ecology and Evolution
#138
of 151 outputs
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