Design considerations for community-based stream monitoring to detect changes in Pacific salmon habitats

Abstract

Communities in the Great Bear Rainforest of British Columbia, Canada are highly dependent on Pacific salmon (Oncorhynchus spp.) and the watersheds that support them, yet current monitoring efforts are likely inadequate for detecting changes in stream habitats that may affect salmon populations. The Coastal First Nations Regional Monitoring System is attempting to address these information gaps through a new stream assessment program that collects baseline information and tracks changes in stream habitats. Using the program's monitoring protocol, we assessed the habitat characteristics of eight streams within the Koeye and Namu watersheds, then used a statistical power simulation to determine within-stream sampling requirements for detecting changes in substrate composition that may affect salmon habitat suitability. We also assessed resource constraints and perceived threats to stream habitats via questionnaires to coastal First Nations' stewardship staff. Results suggest that the current recommended sample size of 6 within-stream transects has low statistical power for detecting biologically significant changes in fine sediment. Given limited monitoring resources, we recommend higher transect sampling intensities within productive riffle-pool streams, but an emphasis on monitoring site level characteristics, such as large woody debris and pool volume, in less productive, high gradient cascade-pool streams. Questionnaire results highlight the need for flexibility and local adaptation in monitoring efforts because of differences in resource constraints among First Nations communities. If successfully implemented, the stream assessment program can integrate local knowledge with western science to inform ecosystem-based management of watersheds within the Great Bear Rainforest.

Keywords

• adaptive governance
• ecosystem-based management
• First Nations management
• Great Bear Rainforest
• Pacific salmon
• power analysis
• stream monitoring