Wed, Aug 17, 2022: 8:00 AM-8:20 AM
520F
Background/Question/MethodsThe culture of ecology is shifting towards collaborative approaches that integrate various data sources, from in-situ to remotely sensed to community science data. Integration can be particularly useful for the conservation of poorly understood species because it can pool information from multiple sparse datasets. The common nighthawk is a nocturnal, long-distance migratory bird whose ecology is poorly understood, and yet available monitoring data suggest that this species has undergone steep population declines.Long-term monitoring datasets like the North American Breeding Bird Survey (BBS) can be used to evaluate causes of population declines; however, the dawn BBS is suspected to monitor common nighthawks poorly. We therefore assessed the value of integrating other datasets with the BBS for monitoring nighthawk populations. Next, we integrated various human observer and passive acoustic monitoring datasets to calculate the probability of common nighthawk detection under various conditions. Finally, we used those offsets to integrate multiple monitoring datasets and evaluate various full annual cycle hypotheses for causes of common nighthawk population declines. Covariates used to represent competing hypotheses were selected from times and places when common nighthawk migratory connectivity is elevated, as determined using GPS tags to track individual birds across their full annual cycle.
Results/ConclusionsData integration provided multiple benefits along our journey to understand common nighthawk population declines. First, we found that integrating the BBS with targeted nocturnal monitoring increased the probability of detecting a 30% population decline from 38% to 69%. Integrating the two monitoring programs also improved the predictive performance of species distribution modelling. Data integration for calculating probability of detection improved the temporal, spatial, and data type coverage of our offsets, which facilitated greater statistical power in evaluating causes of population declines. Preliminary analysis suggests the causes of differential common nighthawk population trends likely occur on the breeding grounds, in northern South America during spring migration, or while crossing the Gulf of Mexico. Our analytical journey emphasizes the value of data integration for overcoming statistical hurdles, particularly for conservation research of data sparse species.
Results/ConclusionsData integration provided multiple benefits along our journey to understand common nighthawk population declines. First, we found that integrating the BBS with targeted nocturnal monitoring increased the probability of detecting a 30% population decline from 38% to 69%. Integrating the two monitoring programs also improved the predictive performance of species distribution modelling. Data integration for calculating probability of detection improved the temporal, spatial, and data type coverage of our offsets, which facilitated greater statistical power in evaluating causes of population declines. Preliminary analysis suggests the causes of differential common nighthawk population trends likely occur on the breeding grounds, in northern South America during spring migration, or while crossing the Gulf of Mexico. Our analytical journey emphasizes the value of data integration for overcoming statistical hurdles, particularly for conservation research of data sparse species.