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Adaptive Management of Flows in a Regulated River: Flow-ecology Relationships Revealed by a 26-year, Five-treatment Flow Experiment

Adaptive management (AM) is often proposed as a means to resolve uncertainty in the management of socio-ecological systems but successful implementation of AM is rare. We report results from a 26 year, five-treatment, AM experiment designed to inform decision makers about the response of juvenile sa...

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Detalles Bibliográficos
Autores principales: Bradford, Michael J., Korman, Josh, Sneep, Jeff
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9892159/
https://www.ncbi.nlm.nih.gov/pubmed/36449050
http://dx.doi.org/10.1007/s00267-022-01750-4
Descripción
Sumario:Adaptive management (AM) is often proposed as a means to resolve uncertainty in the management of socio-ecological systems but successful implementation of AM is rare. We report results from a 26 year, five-treatment, AM experiment designed to inform decision makers about the response of juvenile salmonids (Oncorhynchus spp.) to flow releases from a dam on the regulated Bridge River, British Columbia, Canada. Treatments consisted of a baseline (no dam release) and four different dam release regimes that followed a semi-natural hydrograph but varied in the magnitude of spring-summer freshet flows. We found total salmonid biomass was highest at the lowest flow release, and decreased with increasing flow, consistent with a priori predictions made by an expert solicitation process. Species-specific responses were observed that in some cases could be attributed to interactions between the flow regime and life history. The relationship between juvenile biomass and flow resulting from the experiment can inform decisions on water management for this river. The documentation of successful AM experiments is sorely needed to allow for reflection on the circumstances when AM is likely to deliver desirable outcomes, and to improve other decision processes that require fewer resources and less time to implement.