Indigenous Knowledge as a sole data source in habitat selection functions.

Area of Science:

• Conservation Biology
• Wildlife Management
• Ethnoecology

Background:

• Western species-habitat models often exclude Indigenous Knowledge (IK), potentially impacting Indigenous communities and species conservation.
• Exclusion of IK in management can lead to limited access to culturally and subsistencely important species.
• There is a need to integrate IK into scientific frameworks for effective species management.

Purpose of the Study:

• To develop statistical methods for characterizing Indigenous Knowledge (IK) of species-habitat relationships.
• To create species-habitat models that solely utilize IK to identify important habitats and species use areas.
• To demonstrate the application of these methods for dynamic habitat types and species management.

Main Methods:

• Developed statistical techniques to characterize Indigenous Knowledge (IK) regarding species-habitat associations.
• Created species-habitat models based exclusively on documented IK, including dynamic habitat variables like ice concentration.
• Applied the methodology to ringed seals in Alaskan waters, incorporating Iñupiat hunters' knowledge.

Main Results:

• Successfully developed and applied methods to statistically model species-habitat relationships using Indigenous Knowledge (IK).
• Identified important habitats and areas of species use for ringed seals based solely on IK.
• Demonstrated that IK, especially with dynamic habitat considerations, enhances existing mapping and identification approaches.

Conclusions:

• Indigenous Knowledge (IK) provides a valuable and statistically characterizable dataset for species-habitat modeling.
• Integrating IK, including dynamic habitat types, offers a robust method for identifying critical species habitats.
• This approach facilitates meaningful inclusion of IK in species management and co-management initiatives.