Estimation of time-varying selectivity in stock assessments using state-space models

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Contemporary fisheries stock assessment: many issues still remain (2015, background): “The indirect methods are potentially biased with low precision as they are generated based on relationships with other unreliable estimates of natural mortality (Pascual and Iribarne, 1993; Maunder and Wong, 2011).”
TMB: Automatic Differentiation and Laplace Approximation (2015, background): “sam State-space fish stock assessment model (Nielsen and Berg 2014) 650 16 banded(33) no”
Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets (2017, methodology): “Maunder et al. (2014) suggest that it is prudent to model dome-shaped and time-varying selectivity for all fisheries using nonparametric methods (e.g. Thorson and Taylor 2014; Nielsen and Berg 2014), particularly if a survey with constant asymptotic selectivity is available.”
Accounting for correlated observations in an age-based state-space stock assessment model (2016, methodology): “The stock assessment model used here is an extension of the statespace assessment model (SAM) by Nielsen and Berg (2014), which is used as basis for management advice for several stocks monitored by the International Council for the Exploration of the Sea. State-space models present a general framew”