Quantifying the Value of Community Science Data for Conservation Decision-making

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Allison Binley , Jeffrey Hanson, Orin Robinson, Greg Golet, Joseph R Bennett


Monitoring biodiversity can be critical for informing effective conservation strategies, but can also deplete the resources available for management actions. Freely-available community science data may help alleviate this issue, but only if data quality is sufficient to inform the best decisions. Our objective was to quantify the predicted outcomes of prioritizing conservation action based on regional community science compared to using targeted professional monitoring data. Using data from the BirdReturns program in the Central Valley of California as a case study, we prioritized management units for conservation action based on the predicted probability of detecting seven shorebird species. Crowd-sourced data performed better than professional data even before accounting for the cost of professional monitoring, and substantially better when monitoring costs were explicitly considered. Thus, conservation action based on freely-available community science data could theoretically result in better biodiversity outcomes than paying for targeted professional monitoring.




Life Sciences


citizen science, conservation, agriculture, shorebirds, BirdReturns, Central Valley, habitat enhancement, site selection, eBird


Published: 2024-05-02 09:17

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Conflict of interest statement:

Data and Code Availability Statement:
Data for this project are available at DOI 10.17605/OSF.IO/E536U. Note that the shapefiles for private properties have been removed from this version to protect the privacy of the landowners involved in this project.