PhD Defense: Rowenna Gryba

PhD Defense by

Rowenna Gryba

Time: 1:00 PM, Friday, February 23, 2024
Location: Room 200 of the Graduate Student Centre (6371 Crescent Road)

New approaches to understand species-habitat relationship using Indigenous Knowledge and scientific data

Indigenous Knowledge (IK) holds information on the relationships between animals and their environment, among many other things. Although the depth of ecological information embodied within IK is often recognized, it is rarely included in species-habitat models as a sole data source or combined with scientific data. In partnership with IK holders, I have developed methods to include IK in statistical approaches to model species-habitat relationships. First, I documented IK focused on species-habitat relationships of ringed seals (natchiq in Iñupiaq; Pusa hispida), bearded seals (ugruk; Erignathus barbatus), and spotted seals (qasigiaq; Phoca largha), in the waters near three Arctic communities: Utqiaġivk, Tikiġaq, and Kotzebue, Alaska. Results showed that all three species use currents during foraging activity, which is not a behaviour captured by previous satellite telemetry studies, but have differing associations with sea ice and thus potentially different responses to climate change. Regional differences in seal behaviour and habitat between the IK from each community were also apparent, highlighting changes along species migration routes. I then developed methods for species-habitat models that rely on IK as the sole data source. The method provides an approach to interpret different types of IK as probability of species presence associated with different habitat types, including dynamic habitat covariates, and combines them in a single model. I applied the method to ringed seals, providing an approach where IK is presented in a way that can be easily considered and included in current species and ecosystem management frameworks. Next, I developed a method to include IK as informed priors and habitat covariates in Bayesian habitat selection functions applied to animal movement data. I show that the inclusion of IK in habitat selection functions can identify important areas for the species that would not have been predicted using scientific data alone, due to the lack of data at appropriate scales. Overall, my work has provided new methods to include IK in species-habitat modelling, highlighting the depth of ecological information within IK. These methods provide approaches to better our understanding of species-habitat relationships that can fully consider IK in species management and conservation.

Dr. Marie Auger-Méthé (co-supervisor)
Dr. Greg Henry (co-supervisor)
Dr. Tara Martin
Dr. Francis Wiese