Finding the perfect mismatch: Evaluating misspecification of population structure within spatially explicit integrated population models

Bosley, Katelyn M.; Schueller, Amy M.; Goethel, Daniel R.; Hanselman, Dana H.; Fenske, Kari H.; Berger, Aaron M.; Deroba, Jonathan J.; Langseth, Brian J.

doi:10.1111/faf.12616

Cited by 10 publications

(7 citation statements)

References 71 publications

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“…Therefore, if movement is not occurring and other process variability is correctly specified, such as on natural mortality and selectivity, numbers at age can reasonably be excluded from the random effects. If substantial movement or stock mixing is occurring, models can account for this though auxiliary information like tagging data and/or restructuring management units to reflect closed populations (Berger et al, 2021;Bosley et al, 2022;Goethel et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

The Effect of Process Variability and Data Quality on Performance of a State-Space Stock Assessment Model

Liljestrand,

Bence,

Deroba

2023

Preprint

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Section: Discussionmentioning

confidence: 99%

The Effect of Process Variability and Data Quality on Performance of a State-Space Stock Assessment Model

Liljestrand,

Bence,

Deroba

2023

Preprint

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“…marlin can help researchers generate data for further testing of the performance and design of spatially explicit integrated population models, in the manner of Bosley et al. (2022). In addition, the process‐based movement model used in marlin can directly use empirical estimates of movement dynamics derived in the manner of Thorson et al.…”

Section: Discussionmentioning

confidence: 99%

“…We envision marlin being applicable to research on dynamic ocean management, range shifts, management strategy evaluation, policy interactions and spatial stock assessment. marlin can help researchers generate data for further testing of the performance and design of spatially explicit integrated population models, in the manner of Bosley et al (2022).…”

Section: Con Clus Ionsmentioning

confidence: 99%

Simulating benefits, costs and trade‐offs of spatial management in marine social‐ecological systems

Ovando,

Bradley,

Burns

et al. 2023

Fish and Fisheries

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Designing effective spatial management strategies is challenging because marine ecosystems are highly dynamic and opaque, and extractive entities such as fishing fleets respond endogenously to ecosystem changes in ways that depend on ecological and policy context. We present a modelling framework, marlin, that can be used to efficiently simulate the bio‐economic dynamics of marine systems in support of both management and research. We demonstrate marlin's capabilities by focusing on two case studies on the conservation and food production impacts of marine protected areas (MPAs): a coastal coral reef and a pelagic tuna fishery. In the coastal coral reef example, we explore how heterogeneity in species distributions and fleet preferences can affect distributional outcomes of MPAs. In the pelagic case study, we show how our model can be used to assess the climate resilience of different MPA design strategies, as well as the climate sensitivity of different fishing fleets. This paper demonstrates how intermediate complexity simulation of coupled bio‐economic dynamics can help communities predict and potentially manage trade‐offs among conservation, fisheries yields and distributional outcomes of management policies affected by spatial bio‐economic dynamics.

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“…With improved scientific understanding of the spatiotemporal nature of ecosystem drivers and the redistribution of marine species due to climate change, there has been an increase in the development of spatial assessment models to better represent spatial processes (Berger et al., 2017; Punt, 2019a, 2019b). Although spatially explicit simulation tools have demonstrated that spatial assessments are typically more robust than single‐region or spatially implicit (i.e., areas‐as‐fleets, AAF) approaches when spatial dynamics are present, there remains ambiguity as to the conditions that necessitate implementing a spatial assessment (Bosley et al., 2022; Guan et al., 2019; McGilliard et al., 2015; Punt et al., 2017). Moreover, operational application of spatial assessments tends to be focused on highly mobile, wide‐ranging large pelagic species (i.e., tunas; Punt, 2019a).…”

Section: Introductionmentioning

confidence: 99%

‘Drivin' with your eyes closed’: Results from an international, blinded simulation experiment to evaluate spatial stock assessments

Goethel,

Berger,

Hoyle

et al. 2024

Fish and Fisheries

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Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real‐world stock assessment process, and a data‐conditioned, high‐resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna (Thunnus albacares). Six analyst groups developed both single‐region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single‐region models within a given assessment platform. Balancing parsimony and complexity trade‐offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time‐ and age‐variation in movement and appropriate tag mixing periods) was critical to model performance. We recommend expanded use of high‐resolution OMs and blinded studies, given their ability to portray realistic performance of assessment models. Moreover, increased support for international simulation experiments is warranted to facilitate dissemination of methodology across organizations.

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Finding the perfect mismatch: Evaluating misspecification of population structure within spatially explicit integrated population models

Cited by 10 publications

References 71 publications

The Effect of Process Variability and Data Quality on Performance of a State-Space Stock Assessment Model

The Effect of Process Variability and Data Quality on Performance of a State-Space Stock Assessment Model

Simulating benefits, costs and trade‐offs of spatial management in marine social‐ecological systems

‘Drivin' with your eyes closed’: Results from an international, blinded simulation experiment to evaluate spatial stock assessments

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