Quantifying the value of participatory science data for conservation decision-making

Abstract

Monitoring biodiversity can be critical for informing effective conservation strategies, but can also deplete the resources available for management actions if the time and money available for both activities are limited. Freely available participatory 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 participatory 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 properties for conservation action based on the predicted probability of detecting seven shorebird species, using a range of budgets as constraints. For prioritizations conducted using data from the professional surveys, the cost of monitoring was deducted from the total budget available for conservation action. 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. The difference in performance was particularly stark at lower budgets, where the professional monitoring data consumed a substantial proportion of the budget. Synthesis and applications. Prioritizing conservation action based on high-quality, freely available participatory science data could theoretically result in better biodiversity outcomes than paying for targeted professional monitoring, allowing managers to redistribute limited conservation resources from monitoring to action.