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Simulating the migration dynamics of juvenile salmonids through rivers and estuaries using a hydrodynamically driven enhanced particle tracking model



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  • Journal Title:
    Ecological Modelling
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Juvenile salmonids migrate hundreds of kilometers from their natal streams to mature in the ocean. Throughout this migration, they respond to environmental cues such as local water velocities and other stimuli to direct and modulate their movements, often through heavily modified riverine and estuarine habitats. Management strategies in an uncertain future of climate change and altered land use regimes depend heavily on being able to reliably predict their ocean entry timings, route use, and survival rates through rivers and estuaries. We developed a spatially-explicit agent-based model of fish movement in response to hydrodynamic flows that uses movement dynamics gleaned from multi-dimensional tracking datasets of acoustically tagged juveniles moving through an urbanized, branched tidal estuary. We demonstrate how such models can be calibrated, and we apply it to the Sacramento-San Joaquin Delta in Central California. The quality of the out-of-sample validation of the model to predict juvenile salmon survival and route selection indicates that the model is versatile and flexible enough to be used in novel hydroclimatological conditions.
  • Source:
    Ecological Modelling, 482, 110393
  • DOI:
  • ISSN:
    0304-3800
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  • Rights Information:
    CC BY-NC-ND
  • Rights Statement:
    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
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    Library
  • Main Document Checksum:
    urn:sha-512:b257709a9766eca29fbd8940b334f2e324a7802bc310123621ea7625e2644ca33caeadeb19217a165f41d4de613d1a6c4cee4d8ca35a3418939525b7a10481df
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