| Summary: | Half the world’s river volume is affected by flow alterations and/or fragmentation, a figure that is likely to increase with the current global surge in hydropower development. At the same time, freshwater biodiversity is in rapid decline. In fluvial ecosystems, streamflow is a master variable, shaping riverine species’ habitat over space and time. Atlantic salmon (Salmo salar) and brown trout (S. trutta) are examples of species that need fluvial habitats for reproduction and juvenile rearing, and whose flow needs can come in conflict with hydropower production objectives. This necessitates tools for predicting the effect of fluvial habitat alteration on fish production. In this thesis, I applied the individual-based model inSTREAM to simulate salmon and trout in the Gullspång Rapids, a residual flow stretch of the Gullspång River, Sweden, over a ten-year period. InSTREAM uses sub-daily time steps to simulate individual fish interacting with their biotic and physical environment, and tracks the fitness consequences of their main actions: habitat and activity selection. For inSTREAM input, I had to describe key habitat features, create a 2D hydraulic model of the rapids, model river temperature, and gather data on salmon and trout eco-physiology and life history characteristics in the Gullspång River. I ran simulation experiments varying either flow input, the number of spawners, spawning gravel, shelter and boulder availability, or temperature. Flow alterations had limited benefit. Only the scenario where the current minimum flow was set three times higher yielded increased production, and only for trout. Trout dominated salmon in competition, and production was density dependent. The model predicted that the only way to increase production of both species at current spawner numbers was to add instream structures offering more energetically profitable feeding positions. Half the world’s river volume is affected by flow alterations and/or fragmentation –a figure that is likely to increase with the current ...
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