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Modeling Avian Full Annual Cycle Distribution and Population Trends with Citizen Science Data

View ORCID ProfileDaniel Fink, Tom Auer, Viviana Ruiz-Gutierrez, Wesley M. Hochachka, Alison Johnston, Frank A. La Sorte, Steve Kelling
doi: https://doi.org/10.1101/251868
Daniel Fink
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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  • For correspondence: daniel.fink@cornell.edu
Tom Auer
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Viviana Ruiz-Gutierrez
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Wesley M. Hochachka
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Alison Johnston
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Frank A. La Sorte
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Steve Kelling
Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA
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Abstract

Information on species’ distributions and abundances, environmental associations, and how these change over time are central to the study and conservation of wildlife populations. This information is challenging to obtain at relevant scales across range-wide extents for two main reasons. First, local and regional processes that affect populations vary throughout the year and across species’ ranges, requiring fine-scale, year-round information across broad — sometimes hemispheric — spatial extents. Second, while citizen science projects can collect data at these scales, using these data requires additional steps to address known sources of bias. Here we present an analytical framework to address these challenges and generate year-round, range-wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate relative occupancy and abundance with enough spatiotemporal resolution to support inference across a range of spatial scales throughout the annual cycle. This includes intra-annual estimates of the range (quantified as the area of occupancy), intraannual estimates of the associations between species and features of their local environment, and inter-annual season-specific trends in relative abundance. This is the first example of an analysis to capture intra‐ and inter-annual distributional dynamics across the entire range of a broadly distributed, highly mobile species.

Authors’ contributions.

DF, WMH, and STK conceived and designed this study. DF designed the statistical methodology. TA and DF designed the computational methodology, processed data, and distribution models. TA, VRG, WMH, AJ, and FAL designed the analysis of the model products. DF wrote the first draft of the manuscript, and all authors contributed substantially to revisions. All the authors have approved the final version of this manuscript and agree to be accountable for all aspects of the work.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 22, 2018.
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Modeling Avian Full Annual Cycle Distribution and Population Trends with Citizen Science Data
Daniel Fink, Tom Auer, Viviana Ruiz-Gutierrez, Wesley M. Hochachka, Alison Johnston, Frank A. La Sorte, Steve Kelling
bioRxiv 251868; doi: https://doi.org/10.1101/251868
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Modeling Avian Full Annual Cycle Distribution and Population Trends with Citizen Science Data
Daniel Fink, Tom Auer, Viviana Ruiz-Gutierrez, Wesley M. Hochachka, Alison Johnston, Frank A. La Sorte, Steve Kelling
bioRxiv 251868; doi: https://doi.org/10.1101/251868

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