Abstract

AbstractThe recognition of adequate sampling designs is an interdisciplinary topic that has gained popularity over the last decades. In ecology, many research questions involve sampling across extensive and complex environmental gradients. This is the case for stable isotope analyses, which are widely used to characterize large‐scale movement patterns and dietary preferences of organisms across taxa. Because natural‐abundance stable isotope variation in the environment is incorporated into inert animal tissues, such as feathers or hair, it is possible to draw inferences about the type of food and water resources that individuals consumed and the locations where tissues were synthesized. However, modern stable isotope research can benefit from the implementation of robust statistical analyses and well‐designed sampling approaches to improve geographic assignment interpretation.We employed hydrogen stable isotope simulations to study inferences regarding the probability of origin of migratory individuals and reveal gaps in sampling efforts while highlighting uncertainties of assignment model extrapolations. We present an integrative approach that explores multiple sampling strategies across species with different geographic ranges to understand advantages and limitations of animal movement inferences based on stable isotope data.We show the characteristics of different sampling strategies through geographic and isotopic gradients and establish a set of diagnostic tools that uncover the attributes of these gradients and evaluate uncertainties of model results.Our analysis demonstrates that sampling regimes should be evaluated in relation to specific research questions and study constraints, and that adopting a single method across species ranges can lead to a costly but less effective sampling strategy.

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