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Species traits and observer behaviors that bias data assimilation and how to accommodate them.

Publication ,  Journal Article
Scher, CL; Clark, JS
Published in: Ecological applications : a publication of the Ecological Society of America
April 2023

Datasets that monitor biodiversity capture information differently depending on their design, which influences observer behavior and can lead to biases across observations and species. Combining different datasets can improve our ability to identify and understand threats to biodiversity, but this requires an understanding of the observation bias in each. Two datasets widely used to monitor bird populations exemplify these general concerns: eBird is a citizen science project with high spatiotemporal resolution but variation in distribution, effort, and observers, whereas the Breeding Bird Survey (BBS) is a structured survey of specific locations over time. Analyses using these two datasets can identify contradictory population trends. To understand these discrepancies and facilitate data fusion, we quantify species-level reporting differences across eBird and the BBS in three regions across the United States by jointly modeling bird abundances using data from both datasets. First, we fit a joint Species Distribution Model that accounts for environmental conditions and effort to identify reporting differences across the datasets. We then examine how these differences in reporting are related to species traits. Finally, we analyze species reported to one dataset but not the other and determine whether traits differ between reported and unreported species. We find that most species are reported more in the BBS than eBird. Specifically, we find that compared to eBird, BBS observers tend to report higher counts of common species and species that are usually detected by sound. We also find that species associated with water are reported less in the BBS. Species typically identified by sound are reported more at sunrise than later in the morning. Our results quantify reporting differences in eBird and the BBS to enhance our understanding of how each captures information and how they should be used. The reporting rates we identify can also be incorporated into observation models through detectability or effort to improve analyses across species and datasets. The method demonstrated here can be used to compare reporting rates across any two or more datasets to examine biases.

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Published In

Ecological applications : a publication of the Ecological Society of America

DOI

ISSN

1051-0761

Publication Date

April 2023

Volume

33

Issue

3

Start / End Page

e2815

Related Subject Headings

  • Ecology
  • Birds
  • Biodiversity
  • Bias
  • Animals
  • 41 Environmental sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences
 

Citation

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Scher, C. L., & Clark, J. S. (2023). Species traits and observer behaviors that bias data assimilation and how to accommodate them. Ecological Applications : A Publication of the Ecological Society of America, 33(3), e2815. https://doi.org/10.1002/eap.2815
Scher, C Lane, and James S. Clark. “Species traits and observer behaviors that bias data assimilation and how to accommodate them.Ecological Applications : A Publication of the Ecological Society of America 33, no. 3 (April 2023): e2815. https://doi.org/10.1002/eap.2815.
Scher CL, Clark JS. Species traits and observer behaviors that bias data assimilation and how to accommodate them. Ecological applications : a publication of the Ecological Society of America. 2023 Apr;33(3):e2815.
Scher, C. Lane, and James S. Clark. “Species traits and observer behaviors that bias data assimilation and how to accommodate them.Ecological Applications : A Publication of the Ecological Society of America, vol. 33, no. 3, Apr. 2023, p. e2815. Epmc, doi:10.1002/eap.2815.
Scher CL, Clark JS. Species traits and observer behaviors that bias data assimilation and how to accommodate them. Ecological applications : a publication of the Ecological Society of America. 2023 Apr;33(3):e2815.
Journal cover image

Published In

Ecological applications : a publication of the Ecological Society of America

DOI

ISSN

1051-0761

Publication Date

April 2023

Volume

33

Issue

3

Start / End Page

e2815

Related Subject Headings

  • Ecology
  • Birds
  • Biodiversity
  • Bias
  • Animals
  • 41 Environmental sciences
  • 31 Biological sciences
  • 30 Agricultural, veterinary and food sciences
  • 07 Agricultural and Veterinary Sciences
  • 06 Biological Sciences