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The utility of spatial model-based estimators of unobserved bycatch

CITE Title : The utility of spatial model-based estimators of unobserved bycatch Personal Author(s) : Stock, Brian C;Ward, Eric J;Thorson, James T;Jannot, Jason E;Semmens, Brice X; Published Date : 2018 Source : ICES Journal of Marine Science, 76(1), 255-267 DOI : https://doi.org/10.1093/icesjms/fsy153 Journal Title : ICES Journal of Marine Science Stock, Brian C et al. (2018). The utility of spatial model-based estimators of unobserved bycatch. 76(1). https://doi.org/10.1093/icesjms/fsy153 Stock, Brian C et al. "The utility of spatial model-based estimators of unobserved bycatch" 76, no. 1 (2018), https://doi.org/10.1093/icesjms/fsy153 Stock, Brian C et al. "The utility of spatial model-based estimators of unobserved bycatch" vol. 76, no. 1, 2018, https://doi.org/10.1093/icesjms/fsy153 Export RIS Citation Information.

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Stock, Brian C

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Ward, Eric J

2018 | ICES Journal of Marine Science, 76(1), 255-267

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Quantifying effects of fishing on non-targeted (bycatch) species is an important management and conservation issue. Bycatch estimates are typically ca...
Ocean model-based covariates improve a marine fish stock assessment when observations are limited

CITE Title : Ocean model-based covariates improve a marine fish stock assessment when observations are limited Personal Author(s) : du Pontavice, Hubert;Miller, Timothy J;Stock, Brian C;Chen, Zhuomin;Saba, Vincent S; Published Date : 2022 Source : ICES Journal of Marine Science, 79(4): 1259–1273 DOI : https://doi.org/10.1093/icesjms/fsac050 Journal Title : ICES Journal of Marine Science du Pontavice, Hubert et al. (2022). Ocean model-based covariates improve a marine fish stock assessment when observations are limited. 79(4). https://doi.org/10.1093/icesjms/fsac050 du Pontavice, Hubert et al. "Ocean model-based covariates improve a marine fish stock assessment when observations are limited" 79, no. 4 (2022), https://doi.org/10.1093/icesjms/fsac050 du Pontavice, Hubert et al. "Ocean model-based covariates improve a marine fish stock assessment when observations are limited" vol. 79, no. 4, 2022, https://doi.org/10.1093/icesjms/fsac050 Export RIS Citation Information.

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du Pontavice, Hubert

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Miller, Timothy J

2022 | ICES Journal of Marine Science, 79(4): 1259–1273

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The productivity of many fish populations is influenced by the environment, but developing environment-linked stock assessments remain challenging and...
The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs

CITE Title : The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs Personal Author(s) : Thorson, James T;Miller, Timothy J;Stock, Brian C; Published Date : 2022 Source : ICES Journal of Marine Science (2022) DOI : https://doi.org/10.1093/icesjms/fsac159 Journal Title : ICES Journal of Marine Science Thorson, James T et al. (2022). The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs. https://doi.org/10.1093/icesjms/fsac159 Thorson, James T and Miller, Timothy J and Stock, Brian C "The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs" (2022), https://doi.org/10.1093/icesjms/fsac159 Thorson, James T et al. "The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs" , 2022, https://doi.org/10.1093/icesjms/fsac159 Export RIS Citation Information.

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Thorson, James T

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Miller, Timothy J

2022 | ICES Journal of Marine Science (2022)

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Weighting data appropriately in stock assessment models is necessary to diagnose model mis-specification, estimate uncertainty, and when combining dat...