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Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future
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<em>Abstract.</em>—In this review, we argue that modeling salmonid populations needs to integrate multispecies dynamics to better address the keystone role of salmon in their ecosystems and management needs for co-occurring species. Despite several challenges of modeling salmon communities, including multiple threats, variable spatial and temporal scales, and different types of interspecific interactions, a number of modeling approaches are potentially available to examine interspecific interactions. We examine these choices in the context of the salmon communities, and discuss opportunities for improving multispecies models to successfully address the ecological and management questions facing salmon populations. To effectively integrate multiple species into salmonid population models, researchers should utilize relatively simple, transparent models that have the capability of examining parameter uncertainty and systematically adding complexity.
American Fisheries Society
Title: Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future
Description:
<em>Abstract.
</em>—In this review, we argue that modeling salmonid populations needs to integrate multispecies dynamics to better address the keystone role of salmon in their ecosystems and management needs for co-occurring species.
Despite several challenges of modeling salmon communities, including multiple threats, variable spatial and temporal scales, and different types of interspecific interactions, a number of modeling approaches are potentially available to examine interspecific interactions.
We examine these choices in the context of the salmon communities, and discuss opportunities for improving multispecies models to successfully address the ecological and management questions facing salmon populations.
To effectively integrate multiple species into salmonid population models, researchers should utilize relatively simple, transparent models that have the capability of examining parameter uncertainty and systematically adding complexity.
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