Citizen science data enhance spatio-temporal extent and resolution of animal population studies

摘要: Informed management and conservation decisions for animal populations often require data at sufficient geographic, temporal, demographic resolutions precise unbiased estimates of parameters including population size rates. Recently developed integrated models estimate such by unifying presence-absence data, we demonstrate how citizen science offers a cost-efficient mechanism to collect data. We describe the early results iSeeMammals, project that collects opportunistic on black bear in New York State enlisting volunteers through observations, hikes, trail cameras. In 10 months, iSeeMammals increased spatio-temporal extent collection approximately fourfold reduced cost 83% compared systematic sampling. combination with other datasets model frameworks, large, spatiotemporally extensive from projects like can help improve inferences about population-level structure dynamics.