A Bayesian approach to include Indigenous Knowledge in habitat selection functions

Gryba, R.; Von Duyke, A. L.; Huntington, H. P.; Adams, B.; Frantz, B.; Gatten, J.; Harcharek, Q.; Sarren, R.; Henry, G. H.; Auger-Methe, M.

doi:10.1101/2025.03.26.645387

bioRxiv · 10.1101/2025.03.26.645387

A Bayesian approach to include Indigenous Knowledge in habitat selection functions

Gryba, R.·Von Duyke, A. L.·Huntington, H. P.·Adams, B.·Frantz, B.·Gatten, J.·Harcharek, Q.·Sarren, R.·Henry, G. H.·Auger-Methe, M.

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Abstract

Indigenous Knowledge (IK) of species-habitat relationships provides in-depth understanding of species presence. While IK and Western scientific data are rarely combined in the same model, Bayesian statistics provides a method to include IK as prior knowledge (priors) and combine it with Western data. In partnership with Inupiat hunters, we developed a method to include IK in Bayesian habitat selection functions as priors and show how habitat variables mapped by IK holders can be included as covariates. We explain how to include IK and show the effects of IK in a case study for ringed seals (natchiq in Inupiaq; Pusa hispida). We show that influence of IK can vary depending on the covariate, and how IK provides information at scales not available in Western data. Our work points to the importance of both Western science and IK data sources in models that may be used for conservation and management decisions.

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Gryba, R., Von Duyke, A. L., Huntington, H. P., Adams, B., Frantz, B., Gatten, J., Harcharek, Q., Sarren, R., Henry, G. H., Auger-Methe, M.. 2025-04-01. A Bayesian approach to include Indigenous Knowledge in habitat selection functions. https://doi.org/10.1101/2025.03.26.645387

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