Oceans of plenty? Challenges, advancements, and future directions for the provision of evidence-based fisheries management advice

Marine population modeling, which underpins the scientific advice to support fisheries interventions, is an active research field with recent advancements to address modern challenges (e.g., climate change) and enduring issues (e.g., data limitations). Based on discussions during the ‘Land of Plenty’ session at the 2021 World Fisheries Congress, we synthesize current challenges, recent advances, and interdisciplinary developments in biological fisheries models (i.e., data-limited, stock assessment, spatial, ecosystem, and climate), management strategy evaluation, and the scientific advice that bridges the science-policy interface. Our review demonstrates that proliferation of interdisciplinary research teams and enhanced data collection protocols have enabled increased integration of spatiotemporal, ecosystem, and socioeconomic dimensions in many fisheries models. However, not all management systems have the resources to implement model-based advice, while protocols for sharing confidential data are lacking and impeding research advances. We recommend that management and modeling frameworks continue to adopt participatory co-management approaches that emphasize wider inclusion of local knowledge and stakeholder input to fill knowledge gaps and promote information sharing. Moreover, fisheries management, by which we mean the end-to-end process of data collection, scientific analysis, and implementation of evidence-informed management actions, must integrate improved communication, engagement, and capacity building, while incorporating feedback loops at each stage. Increasing application of management strategy evaluation is viewed as a critical unifying component, which will bridge fisheries modeling disciplines, aid management decision-making, and better incorporate the array of stakeholders, thereby leading to a more proactive, pragmatic, transparent, and inclusive management framework–ensuring better informed decisions in an uncertain world

Lessons learned from practical approaches to reconcile mismatches between biological population structure and stock units of marine fish

Recent advances in the application of stock identification methods have revealed inconsistencies between the spatial structure of biological populations and the definition of stock units used in assessment and management. From a fisheries management perspective, stocks are typically assumed to be discrete units with homogeneous vital rates that can be exploited independently of each other. However, the unit stock assumption is often violated leading to spatial mismatches that can bias stock assessment and impede sustainable fisheries management. The primary ecological concern is the potential for overexploitation of unique spawning components, which can lead to loss of productivity and reduced biodiversity along with destabilization of local and regional stock dynamics. Furthermore, ignoring complex population structure and stock connectivity can lead to misperception of the magnitude of fish productivity, which can translate to suboptimal utilization of the resource. We describe approaches that are currently being applied to improve the assessment and management process for marine fish in situations where complex spatial structure has led to an observed mismatch between the scale of biological populations and spatially-defined stock units. The approaches include: (i) status quo management, (ii) "weakest link" management, (iii) spatial and temporal closures, (iv) stock composition analysis, and (v) alteration of stock boundaries. We highlight case studies in the North Atlantic that illustrate each approach and synthesize the lessons learned from these real-world applications. Alignment of biological and management units requires continual monitoring through the application of stock identification methods in conjunction with responsive management to preserve biocomplexity and the natural stability and resilience of fish species.</p

The Robustness of Brownie Tag Return Models to Complex Spatiotemporal Dynamics Evaluated through Simulation Analysis

The development of a reliable tagging program requires simulation testing the experimental design. However, the potential for model misspecification, particularly in the underlying spatiotemporal dynamics, is often ignored. A continuous time, spatially-explicit, age-structured, capture-recapture operating model was developed to better emulate real-world population dynamics typically overlooked in spatially-aggregated or discrete time tagging models. Various spatiotemporal model parametrizations, including case studies with Atlantic bluefin and yellowfin tunas, were explored to evaluate the bias associated with Brownie tag return estimation models. Simulations demonstrated that accounting for connectivity was essential for obtaining unbiased parameter estimates, and that migration rates could be reliably estimated without the correlation associated with other parameters (e.g., between tag reporting and mortality). Mortality parameter estimates were particularly sensitive to the temporal dynamics of the tagging and fishing seasons, but accounting for the seasonality in tag releases and fishery recaptures allowed for relatively unbiased estimation. Our results indicate that parameter bias and uncertainty can be severely underestimated when discrete time or spatially-aggregated operating models are used to determine optimal experimental design of tagging studies.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Introduction to ‘Space Oddity: Recent Advances Incorporating Spatial Processes in the Fishery Stock Assessment and Management Interface’

This is an introduction-style article for the special issue and thus does not contain an abstractThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Space Oddity: the Mission for Spatial Integration

Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability, and ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Closing the Feedback Loop: On Stakeholder Participation in Management Strategy Evaluation

Management strategy evaluation (MSE) is a simulation-based approach to examine the efficacy of management options in achieving fishery-, ecosystem-, and socioeconomic-related objectives while integrating over system uncertainties. As a form of structured decision analysis, MSE is amenable to stakeholder involvement, which can reduce implementation barriers associated with non-transparent decision-making procedures. Based on analysis of three MSE processes (Atlantic tunas, Atlantic herring, and eastern oysters), we provide suggestions for improving stakeholder engagement in MSE. By assembling a workgroup and modeling team with diverse backgrounds, including professional facilitators, communication liaisons, and social scientists, dialogue can be improved and an atmosphere of mutual learning fostered. Communication further benefits from clearly defining roles, responsibilities, and terms of engagement for all involved; explicitly and transparently identifying goals and objectives of the MSE before modeling has begun; and, when appropriate, revisiting goals and objectives throughout the MSE process. Although MSEs are not without limitations, the participatory modeling framework, wherein stakeholders are actively engaged at each stage of MSE development, provides a useful mechanism to support fisheries management.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author