Data from: Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

Stable hydrogen isotope (δD) methods for tracking animal movement are
widely used yet often produce low resolution assignments. Incorporating
prior knowledge of abundance, distribution or movement patterns can
ameliorate this limitation, but data are lacking for most species. We
demonstrate how observations reported by citizen scientists can be used to
develop robust estimates of species distributions and to constrain δD
assignments. We developed a Bayesian framework to refine isotopic
estimates of migrant animal origins conditional on species distribution
models constructed from citizen scientist observations. To illustrate this
approach, we analysed the migratory connectivity of the Virginia rail
Rallus limicola, a secretive and declining migratory game bird in North
America. Citizen science observations enabled both estimation of sampling
bias and construction of bias-corrected species distribution models.
Conditioning δD assignments on these species distribution models yielded
comparably high-resolution assignments. Most Virginia rails wintering
across five Gulf Coast sites spent the previous summer near the Great
Lakes, although a considerable minority originated from the Chesapeake Bay
watershed or Prairie Pothole region of North Dakota. Conversely, the
majority of migrating Virginia rails from a site in the Great Lakes most
likely spent the previous winter on the Gulf Coast between Texas and
Louisiana. Synthesis and applications. In this analysis, Virginia rail
migratory connectivity does not fully correspond to the administrative
flyways used to manage migratory birds. This example demonstrates that
with the increasing availability of citizen science data to create species
distribution models, our framework can produce high-resolution estimates
of migratory connectivity for many animals, including cryptic species.
Empirical evidence of links between seasonal habitats will help enable
effective habitat management, hunting quotas and population monitoring and
also highlight critical knowledge gaps.