A multi-isotope (δ(13)C, δ(15)N, δ(34)S, δ(2)H) approach to establishing migratory connectivity in lesser snow geese: Tracking an overabundant species

Expanding populations of North American midcontinent lesser snow geese (Anser caerulescens caerulescens) have potential to alter ecosystems throughout the Arctic and subarctic where they breed. Efforts to understand origins of harvested lesser snow geese to better inform management decisions have traditionally required mark-recapture approaches, while aerial photographic surveys have typically been used to identify breeding distributions. As a potential alternative, isotopic patterns that are metabolically fixed within newly grown flight feathers following summer molting could provide inferences regarding geographic breeding origin of individuals, without the need for prior capture. Our objective was to assess potential to use four stable isotopes (δ(13)C, δ(15)N, δ(34)S, δ(2)H) from feather material to determine breeding origins. We obtained newly grown flight feathers from individuals during summer banding at three Arctic and two subarctic breeding colonies in 2014 (n = 56) and 2016 (n = 45). We used linear discriminant analyses to predict breeding origins from models using combinations of stable isotopes as predictors and evaluated model accuracy when predicting colony, subregion, or subpopulation levels. We found a strong inverse relationship between δ(2)H values and increasing latitude (R(2) = 0.83), resulting in differences (F(4, 51) = 90.41, P < 0.0001) among sampled colonies. No differences in δ(13)C or δ(15)N were detected among colonies, although δ(34)S in Akimiski Island, Baffin Island, and Karrak Lake were more enriched (F(4, 51) = 11.25, P < 0.0001). Using δ(2)H values as a predictor, discriminant analyses improved accuracy in classification level as precision decreased [model accuracy = 67% (colony), 88% (subregion), 94% (subpopulation)]. Application of the isotopic methods we describe could be used to provide an alternative monitoring method of population metrics, such as overall breeding population distribution, region-specific productivity and migratory connectivity that are informative to management decision makers and provide insight into cross-seasonal effects that may influence migratory behavior.