Prediction–variance relation in a state-space fish stock assessment model

Breivik, Olav Nikolai; Nielsen, Anders; Berg, Casper Willestofte

doi:10.1093/icesjms/fsab205

Cited by 4 publications

(1 citation statement)

References 11 publications

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“…Extending models to include new processes can produce worse predictive performance even when model selection criteria (e.g., AIC, model residuals) indicate that including new processes improves model fit (Collie et al., 2016; Trijoulet et al., 2019). Model validation via hindcasts and retrospective analyses can directly examine the predictive skill of models to understand whether overfitting is a problem and if a model can provide the short‐term predictions necessary for tactical fisheries management (Breivik et al., 2023; Kell et al., 2021). Given that this modelling framework relies on model selection criteria, model validation will serve as an important, complimentary process.…”

Section: Discussionmentioning

confidence: 99%

Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

Robertson,

Cadigan,

Regular

et al. 2024

Fish and Fisheries

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Despite continued calls for the application of ecosystem‐based fisheries management, tactical fisheries management continues to be heavily reliant on single‐species stock assessments. These stock assessments rarely quantitatively integrate the effects of ecosystem processes on fish stock productivity. This lack of integration is ultimately driven by the complexity of interactions between populations, ecosystems and fisheries, which produces uncertainty when defining which processes to include and how to include them. Models developed using a structured hypothesis testing framework would allow formalizing uncertainties while underscoring the importance of incorporating different population and ecosystem processes to explain non‐stationary stock productivity. Here, we develop a conceptual framework for extending and comparing population dynamics models of increasing complexity. We illustrate the utility of the framework by investigating the population and ecosystem processes that most likely affected the differential recovery of two flatfish populations (American plaice and yellowtail flounder) on the Newfoundland Grand Banks over the past three decades. We found that yellowtail flounder population dynamics were primarily driven by recruitment variability, which was negatively affected by warmer climatological conditions, as indicated by an integrated regional climate index. Meanwhile, American plaice population dynamics were affected by a combination of temporal variability in recruitment and natural mortality, where natural mortality increased during colder than average conditions. By exploring hypotheses about the effects of population and ecosystem processes on population dynamics, this modelling framework will improve understanding about the drivers of shifts in population productivity while serving as a transparent and robust approach to support ecosystem‐based fisheries management.

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Section: Discussionmentioning

confidence: 99%

Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

Robertson,

Cadigan,

Regular

et al. 2024

Fish and Fisheries

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Incorporation of observation uncertainty in stock assessment using spatio-temporal modeling of catch-at-length and age-at-length survey data

Breivik,

Zimmermann,

Johannesen

et al. 2024

ICES Journal of Marine Science

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Spatio-temporal models are essential tools for estimating abundance indices and quantifying the associated uncertainty. Time series of index uncertainties can be used to objectively determine the influence each index has on the assessment. This can involve reducing the influence of indices in years with limited data. However, incorporating uncertainty in age-length conversion into assessment models has remained a challenge. In this research, we propose an index estimation approach that combines an abundance-at-length model with a model for age-at-length to generate age-specific abundance indices. By jointly modeling abundance-at-length and age-at-length, we address uncertainties in both components of the index-at-age. Using North East Arctic haddock (Melanogrammus aeglefinus) as a case study, we validate the uncertainty of the indices by integrating them into the state space assessment model SAM. The results indicate that the uncertainty estimates are realistic, and we further demonstrate that incorporating uncertainty in age conversion has effects on the assessment results. Our case study demonstrates that incorporating the uncertainty in age-at-length data improves the characterization of uncertainty in stock assessment, and hence better accounts for risk in precautionary management.

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A Tweedie Markov process and its application in fisheries stock assessment

Zheng

Lim

Cadigan

2023

Journal of the Royal Statistical Society Series C: Applied Statistics

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The Tweedie distribution is a useful tool to model zero-inflated non-negative continuous data. However, the Tweedie dispersion relationship (DR) is not general enough to cover some important forms such as quadratic dispersion, and an easy and fast-to-implement Tweedie AR(1) model (first-order autoregressive model) needs to be developed for spatio-temporal modelling. In this research we extend the Tweedie distribution to accommodate flexible DRs, and propose a Tweedie Markov process (TMP) with the AR(1) autocorrelation structure. This TMP is simple to implement and requires only the Tweedie probability density function. Simulation studies and real data analysis are conducted to validate our new approach.

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Prediction–variance relation in a state-space fish stock assessment model

Cited by 4 publications

References 11 publications

Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

Incorporation of observation uncertainty in stock assessment using spatio-temporal modeling of catch-at-length and age-at-length survey data

A Tweedie Markov process and its application in fisheries stock assessment

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