American Woodcock Singing-ground Survey
The Logistical Challenges Associated with Route Consistency through Time
The American Woodcock Singing-ground Survey (SGS) is a long-term roadside survey (1968–present) administered by the U.S. Fish and Wildlife Service (USFWS). The SGS was developed to provide indices to changes in American woodcock (Scolopax minor) abundance. The population index derived from the survey is the primary metric used for the United States (US) harvest strategy. Integral to any long-term wildlife-monitoring program (e.g., SGS) with replicated spatial point-count locations is accurate management of metadata related to those locations. Technological advances over the last 20 years have resulted in large-scale coordination and logistical planning changes for the SGS, including improved communication between stakeholders and the creation of a database that houses metadata for all point-count locations. These improvements revealed weaknesses in the historical record-keeping system used for official paper route-maps that may have led to point-count location inconsistencies over time. To summarize the scope of the problem, and make corrections, we compared submitted GPS coordinates for count locations on SGS routes against indicated route paths on official route maps. Across the entire SGS coverage area, we found that 9.9% of observer-submitted point-count coordinates did not match the route path highlighted on the official route maps. We also compared a subset of digitized Minnesota and Wisconsin submitted point-count coordinates and found that 20.9% did not match the route path highlighted on the official route map. We quantified and grouped Minnesota and Wisconsin route-map discrepancies to provide perspective on the types and magnitude of the discrepancies that occur throughout the SGS coverage area. Reasons for the mismatch were many. We share the many challenges of maintaining route consistency and provide recommendations on how to best alleviate route map discrepancies, thus improving the integrity of the SGS and its data.