Combining genetic and isotope frameworks improves reconstruction of fish provenance across riverscapes

Abstract Understanding the spatial ecology of migratory species is uniquely challenging using conventional approaches. In fisheries such as for Pacific salmon, genetic stock identification (GSI) and isotope‐based methods have emerged as strategies for reconstructing spatial ecology but are limited by the spatial resolution of genetic differentiation and isotopic heterogeneity. We show that integrating these complementary datasets improve the spatial resolution of provenance assignments. To do so, we reconstructed basin‐wide estimates of natal origin locations for Chinook salmon in the Yukon River using samples ( n = 247) from an experimental fishery designed to assess in‐season run timing. A combined framework improved precision of likely provenance assignments (stream km > 0.7 posterior probability) by 92% over genetic assignments and 52% over strontium isotope methods. In doing so, we illustrate watershed scale estimates of natal origin distributions with a greater resolution available from GSI or isotope data alone.