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CitationBrian J. Burke, Aimee H. Fullerton, Brian K. Wells, Jan Ohlberger, Improving salmon marine survival models with covariance map indices of sea surface temperature (CMISST) and sea surface height (CMISSH), Ecological Informatics, Volume 93, 2026, 103575, ISSN 1574-9541, https://doi.org/10.1016/j.ecoinf.2025.103575. (https://doi.org/10.1016/j.ecoinf.2025.103575)
TitleImproving salmon marine survival models with covariance map indices of sea surface temperature (CMISST) and sea surface height (CMISSH)
Publication Year2026
Volume93
KeywordsPacific salmon, environmental covariates, modelling, forecasting, stock-specific
AbstractPacific-basin scale atmospheric and oceanographic conditions cascade to regional environmental conditions. In turn, these regional conditions in the nearshore ocean have direct and indirect impacts on coastal ecology and influence everything from primary productivity to top predator abundance and distribution. Quantitatively representing these conditions with consolidated metrics allows the ocean environment to be represented in a small number of variables, or indicators, and can aid in fisheries management and policy decisions. As an example, Pacific salmon face numerous challenges during their migration from freshwater rivers to the ocean and back, and managers must make accurate assessments of their marine survival to inform effective conservation and management strategies. From satellite data and earth systems models, we now have rich data sets with complete spatial and temporal coverage to use for these applications. Here, we create a spatial map of covariance values between salmo
Official CitationBrian J. Burke, Aimee H. Fullerton, Brian K. Wells, Jan Ohlberger, Improving salmon marine survival models with covariance map indices of sea surface temperature (CMISST) and sea surface height (CMISSH), Ecological Informatics, Volume 93, 2026, 103575, ISSN 1574-9541, https://doi.org/10.1016/j.ecoinf.2025.103575.
Links (https://doi.org/10.1016/j.ecoinf.2025.103575)