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Atlantic ghost crabs (Ocypode quadrata) are predators of beach-nesting shorebird nests and chicks on the United States’ Atlantic and Gulf coasts. Ghost crabs may also disturb birds, altering foraging, habitat use, or nest and brood attendance patterns. Shorebird conservation strategies often involve predator and disturbance management to improve reproductive success, but efforts rarely target ghost crabs. Despite the threat to shorebird reproductive success, ghost crabs are a poorly understood part of the beach ecosystem and additional knowledge about ghost crab habitat selection is needed to inform shorebird conservation. We monitored ghost crab activity, defined as burrow abundance, throughout the shorebird breeding season on Metompkin Island, Virginia, an important breeding site for piping plovers (Charadrius melodus) and American oystercatchers (Haematopus palliatus). We counted burrows at shorebird nests and random locations throughout the breeding season and investigated whether ghost crab activity was greater at nest sites relative to random locations without shorebird nests. While we observed burrows at all nest sites (n= 63 nests), we found that burrow counts were lower at piping plover nests with shell cover, relative to random locations with no shell cover. Ghost crabs may avoid piping plover nest sites due to anti-predator behaviors from incubating adults or differences in microhabitat characteristics selected by piping plovers. We also investigated the effects of habitat type, date, and air temperature on the abundance of ghost crab burrows. We found that while crab burrows were present across the barrier island landscape, there were more burrows in sandy, undisturbed habitats behind the dunes, relative to wave-disturbed beach. Additionally, ghost crab activity increased later in the shorebird breeding season. Understanding when and where ghost crabs are most likely to be active in the landscape can aid decision-making to benefit imperiled shorebird populations. 

Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data, and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for correcting, standardizing, and indexing world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In assessing geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled the detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a significant data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and is accessible via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows.