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

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.