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dc.contributor.authorMeehan, Timothy D.
dc.contributor.authorMichel, Nicole L.
dc.contributor.authorRue, Haavard
dc.date.accessioned2019-08-18T13:48:37Z
dc.date.available2019-08-18T13:48:37Z
dc.date.issued2019-04-09
dc.identifier.citationMeehan, T. D., Michel, N. L., & Rue, H. (2019). Spatial modeling of Audubon Christmas Bird Counts reveals fine-scale patterns and drivers of relative abundance trends. Ecosphere, 10(4), e02707. doi:10.1002/ecs2.2707
dc.identifier.doi10.1002/ecs2.2707
dc.identifier.urihttp://hdl.handle.net/10754/656484
dc.description.abstractBird counts by community volunteers provide valuable information about the conservation needs of many bird species. The statistical modeling techniques commonly used to analyze these counts provide robust, long-term population trend estimates from heterogeneous community science data at regional, national, and continental scales. Here, we present a new modeling approach that increases the spatial resolution of trend estimates and reduces the computational burden of trend estimation, each by an order of magnitude. We demonstrate the approach with data for the American Robin (Turdus migratorius) from Audubon Christmas Bird Counts conducted between 1966 and 2017. We show that aggregate regional trend estimates from the proposed method aligned well with those from the current standard method, and that spatial variation in trends was associated with winter temperatures and human population densities as predicted by ecological energetics. This technique can provide reasonable large-scale trend estimates for users interested in general patterns, while also providing higher-resolution estimates for examining correlates of abundance trends at finer spatial scales, which is a prerequisite for tailoring management plans to local conditions.
dc.description.sponsorshipWe thank the thousands of volunteers who participate in the Audubon Christmas Bird Count, as well as the two anonymous reviewers who helped improve this manuscript.
dc.publisherWiley
dc.relation.urlhttps://onlinelibrary.wiley.com/doi/abs/10.1002/ecs2.2707
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/
dc.subjectAudubon Christmas Bird Count
dc.subjectBayesian hierarchical model
dc.subjectconditional autoregressive model
dc.subjectNorthAmerican Breeding Bird Survey
dc.subjectpopulation trends
dc.subjectrange shifts
dc.subjectspatially varying coefficients model
dc.titleSpatial modeling of Audubon Christmas Bird Counts reveals fine-scale patterns and drivers of relative abundance trends
dc.typeArticle
dc.contributor.departmentStatistics Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalEcosphere
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionNational Audubon Society, Boulder, CO, United States
dc.contributor.institutionNational Audubon Society, Portland, OR, United States
kaust.personRue, Haavard
dc.relation.issupplementedbygithub:tmeeha/inlaSVCBC
refterms.dateFOA2019-08-18T13:49:25Z
display.relations<b>Is Supplemented By:</b><br/> <ul><li><i>[Software]</i> <br/> Title: tmeeha/inlaSVCBC: Repo for developing spatially varying coefficient models for analysis of CBC using R-INLA. Publication Date: 2018-05-31. github: <a href="https://github.com/tmeeha/inlaSVCBC" >tmeeha/inlaSVCBC</a> Handle: <a href="http://hdl.handle.net/10754/666976" >10754/666976</a></a></li></ul>
dc.date.published-online2019-04-09
dc.date.published-print2019-04


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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.