Monitoring population extinction risk with community science data

1. The robust estimation of local extinction risk is central to inform management andconservation efforts. Still, estimating this key demographic parameter requiresstandardized monitoring data that are lacking for most species and systems. Theanalysis of community science data is emerging as a promising alternative. Theseexpansive datasets leverage observations from multiple volunteers that providehigher temporal and spatial resolution. Nevertheless, the proper analysis of com-munity science data is challenging because it requires accounting for additionalcomplexities in the intrinsic ecological and observational processes.2. To address this issue, we describe and test a quantitative approach that fits con-tinuous state-space models iteratively to eBird data with the ultimate goal of es-timating local persistence probability through time.3. We evaluated model accuracy by comparing estimates and trends from eBirdwith those from the endangered Everglades' snail kite long-term, standardizedmonitoring project. We also performed two separate sensitivity analyses (tempo-ral and sampling thinning) to assess how robust the persistence estimates are to areduction in the number of eBird observations available.4. Our results showed that the temporal trend trajectory of local population persis-tence estimated from eBird closely matched that from standardized monitoring.Moreover, the trend remained similar even when reducing the amount of eBirddata available to 5% of the original dataset—a reduction from 258 to 13 weeks orfrom 7714 to 385 lists of observations across 5 years of monitoring.5. Synthesis and applications. Our modelling framework provides a robust, com-putationally efficient and easy-to-apply tool for monitoring local persistence probability that can support global conservation efforts. This will complementthe monitoring of species population viability in places where standardized moni-toring is still lacking, but community science observations are common.