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Natural Mortality: Theory, Estimation, and Application in Fishery Stock Assessment Models
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CITE Title : Natural Mortality: Theory, Estimation, and Application in Fishery Stock Assessment Models Corporate Authors(s) : Hamel, Owen S.;Punt, Andre E.;Kapur, Maia S.;Maunder, Mark N.; Conference Author(s) : Northwest Fisheries Science Center (U.S.). Fishery Resource Analysis and Monitoring Division.;Alaska Fisheries Science Center (U.S.). Resource Ecology and Fisheries Management Division.;University of Washington. School of Aquatic & Fishery Sciences.;Inter-American Tropical Tuna Commission.;Center for the Advancement of Population Assessment Methodology.; Published Date : 2023 Series : NOAA processed report NMFS-NWFSC-PR ; 2023-02 DOI : https://doi.org/10.25923/xqv2-2g73 Hamel, Owen S. (2023). Natural Mortality: Theory, Estimation, and Application in Fishery Stock Assessment Models. https://doi.org/10.25923/xqv2-2g73 Hamel, Owen S. "Natural Mortality: Theory, Estimation, and Application in Fishery Stock Assessment Models" (2023), https://doi.org/10.25923/xqv2-2g73 Hamel, Owen S. "Natural Mortality: Theory, Estimation, and Application in Fishery Stock Assessment Models" , 2023, https://doi.org/10.25923/xqv2-2g73 Export RIS Citation Information.
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Corporate Authors:
Hamel, Owen S. ...
2023 | NOAA processed report NMFS-NWFSC-PR ; 2023-02
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The natural mortality rate, M, is one of the key parameters in stock assessments based on age- or size-structured population dynamics models. However,...
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Assessing likelihoods for fitting composition data within stock assessments, with emphasis on different degrees of process and observation error
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CITE Title : Assessing likelihoods for fitting composition data within stock assessments, with emphasis on different degrees of process and observation error Personal Author(s) : Fisch, Nicholas;Camp, Ed;Shertzer, Kyle;Ahrens, Robert; Published Date : 2021 Source : Fisheries Research, 243: 106069 DOI : https://doi.org/10.1016/j.fishres.2021.106069 Journal Title : Fisheries Research Fisch, Nicholas et al. (2021). Assessing likelihoods for fitting composition data within stock assessments, with emphasis on different degrees of process and observation error. 243https://doi.org/10.1016/j.fishres.2021.106069 Fisch, Nicholas et al. "Assessing likelihoods for fitting composition data within stock assessments, with emphasis on different degrees of process and observation error" 243 (2021), https://doi.org/10.1016/j.fishres.2021.106069 Fisch, Nicholas et al. "Assessing likelihoods for fitting composition data within stock assessments, with emphasis on different degrees of process and observation error" vol. 243, 2021, https://doi.org/10.1016/j.fishres.2021.106069 Export RIS Citation Information.
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Personal Author:
Fisch, Nicholas ;
Camp, Ed
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2021 | Fisheries Research, 243: 106069
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Fisheries stock assessments have traditionally modeled age and size composition data using the multinomial likelihood, however the multinomial cannot ...
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[PDF - 12.37 MB]