A review of integrated analysis in fisheries stock assessment

By Mark N. Maunder, André E. Punt. 2013

452 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/b98f2ee6f9d7ce2839dfa4ea2c9974d0c191c0ec

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In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Integrated population models facilitate ecological understanding and improved management decisions (2018, methodology): “Finally, a Bayesian implementation allowed for complete propagation of parameter uncertainty to derived parameters (Maunder and Punt 2013), including population growth rates (Koons et al. 2017) and adult sex ratio (Arnold et al. 2017:fig.”
Contemporary fisheries stock assessment: many issues still remain (2015, methodology): “It is this lack of consistent age-composition data that has led to the extensive use of integrated analysis (Maunder and Punt, 2013; Punt et al., 2013).”
A simple length-structured model based on life history ratios and incorporating size-dependent selectivity: application to spawning potential ratios for data-poor stocks (2016, background): “605 However, stock assessment models often do not incorporate age or size-specific mortality 606 directly, perhaps because of the paucity of data for estimating natural mortality rates 607 (Maunder and Punt 2013, Punt et al. 2013, Prince et al. 2015b).”
Accounting for correlated observations in an age-based state-space stock assessment model (2016, methodology): “Integrated assessment models (Maunder and Punt, 2013) allow optimal weights to be estimated through the optimization of a joint likelihood for all the observed data.”
Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species (2015, background): “…total mortality and exploitation rates and solving for components of mortality (e.g. Hewitt et al., 2007), (iv) mark-recapture and telemetry studies (e.g. Hoenig et al., 1998; Knip et al., 2012), and (v) estimating M internally in an integrated stock assessment model (see Maunder and Punt, 2013).”