Site-selection bias can drive apparent population declines in long-term studies

Mississippi State University, Biloxi, Mississippi, United States
Center for Population Biology, University of California, Davis, Davis, United States
Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada
DOI
10.7287/peerj.preprints.27507v3
Subject Areas
Conservation Biology, Ecology, Natural Resource Management, Population Biology
Keywords
Population Decline, Conservation, Abundance, Population Dynamics, Site Selection
Copyright
© 2019 Fournier et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Fournier AMV, White ER, Heard SB. 2019. Site-selection bias can drive apparent population declines in long-term studies. PeerJ Preprints 7:e27507v3

Abstract

Detecting population declines is a critical task for conservation biology. The spatiotemporal variability of populations, along with logistical difficulties in population estimation, makes this task difficult. Here we call attention to a possible bias in estimates of population decline: when study sites are chosen based on abundance of the focal species, for statistical reasons apparent declines are likely even without an underlying population trend. This “site-selection bias” has been mentioned in the literature but is not well known. We show using simulated and real population data that when site-selection biases are introduced, they have substantial impact on inferences about population trends. We use a left-censoring method to show patterns consistent with the operation of the site-selection bias in real population studies. The site-selection bias is, thus, an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis.

Author Comment

This version fixed an issue with the Figures.

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