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Management decisions involving species at risk are typically made in the face of sub- stantial biological uncertainty. Incorporating uncertainty into decision-making allows managers to perform risk/benefit analysis. Stable hydrogen isotope ratios (δD) provide a tool for studying large- scale movements of migratory organisms and can contribute to the management of migratory spe- cies at risk. However, this analytical approach is based on predicted precipitation amount-weighted average deuterium (δDp) values, and individual years of interest can involve substantial departures from long-term averages. Local growing-season δDp at locations within the Great Plains of North America deviates from that described by GIS-based models of δDp derived from long-term estimates based on the Global Network of Isotopes in Precipitation (GNIP). We augmented the GNIP dataset with information from the US Network for Isotopes in Precipitation database for sites in the Great Plains, refining a previously published isoscape for inferring origins of migratory wildlife. Accounting for longitude and the coefficient of variation within precipitation in a single year at specific locations allowed us to determine year- and site-specific estimates of δDp and esti- mated rates of long-distance dispersal for 3 species of grassland songbirds based upon δD values of feathers (δDf). Using a likelihood-based approach to classify individuals as 'local' or 'immigrant,' we incorporated uncertainty in making these designations. This approach provides a convenient tool to effectively communicate research results to policy makers, who must make decisions at the level of risk which they are willing to assume when determining management strategies.

Assessing dispersal in threatened migratory birds using stable hydrogen isotope (δD) analysis of feathers