On scientists’ discomfort in fisheries advisory science: the example of simulation‐based fisheries management‐strategy evaluations

Scientists feel discomfort when they are asked to create certainty, where none exists, for use as an alibi in policy‐making. Recently, the scientific literature has drawn attention to some pitfalls of simulation‐based fisheries management‐strategy evaluation (MSE). For example, while estimates concerning central tendencies of distributions of simulation outcomes are usually fairly robust because they are conditioned on ample data, estimates concerning the tails of distributions (such as the probability of falling below a critical biomass) are usually conditional on few data and thus often rely on assumptions that have no strong knowledge base. The clients of scientific advice, such as the European Commission, are embracing the mechanization of the evaluation of proposed Harvest Control Rules against the precautionary principle and management objectives. Where the fisheries management institutions aim for simple answers from the scientists, giving ‘green/red light’ to a proposed management strategy, the scientists are forced into a split position between satisfying the demands of their advisory role and living up to the standards of scientific rigour. We argue against the mechanization of scientific advice that aims to incorporate all relevant processes into one big model algorithm that, after construction, can be run without circumspection. We rather encourage that fisheries advice should be a dynamic process of expert judgement, incorporating separate parallel concurrent, lines of scientific evidence, from quantitative and qualitative modelling exercises and factual knowledge of the biology and the fishery dynamics. This process can be formalized to a certain degree and can easily accommodate stakeholder viewpoints.     

Global fishery dynamics are poorly predicted by classical models

Fisheries dynamics can be thought of as the reciprocal relationship between an exploited population and the fishers and/or managers determining the exploitation patterns. Sustainable production of protein of these coupled human‐natural systems requires an understanding of their dynamics. Here, we characterized the fishery dynamics for 173 fisheries from around the globe by applying general additive models to estimated fishing mortality and spawning biomass from the RAM Legacy Database. GAMs specified to mimic production models and more flexible GAMs were applied. We show observed dynamics do not always match assumptions made in management using “classical” fisheries models, and the suitability of these assumptions varies significantly according to large marine ecosystem, habitat, variability in recruitment, maximum weight of a species and minimum observed stock biomass. These results identify circumstances in which simple models may be useful for management. However, adding flexibility to classical models often did not substantially improve performance, which suggests in many cases considering only biomass and removals will not be sufficient to model fishery dynamics. Knowledge of the suitability of common assumptions in management should be used in selecting modelling frameworks, setting management targets, testing management strategies and developing tools to manage data‐limited fisheries. Effectively balancing expectations of future protein production from capture fisheries and risk of undesirable outcomes (e.g., “fisheries collapse”) depends on understanding how well we can expect to predict future dynamics of a fishery using current management paradigms.     

Modelling angler behaviour as a part of the management system: synthesizing a multi‐disciplinary literature

It is often said that managing fisheries is managing people. This truism implies that fisheries science inherently involves disciplines that focus on fish and their population dynamics, humans and their behaviour, and policy and decision making. This is particularly true for recreational fisheries, where the human behavioural motivation and human response to management actions may be more difficult to predict than in commercial fisheries. We provide a synthesis of the multi‐disciplinary literature on modelling recreational angler behaviour to inform management of recreational fisheries. We begin by defining the recreational fisheries system in an interdisciplinary manner. We then assess the literature for empirical evidence of disciplinary crossover. Using bibliometric data, we provide evidence that there is little disciplinary crossover, particularly between fisheries biology, including applied ecology, and quantitative social science, including economics. We identify critical barriers to disciplinary crossover, such as database indexing issues and nomenclature. Next, we provide a review of critical contributions to the literature, and locate these contributions within our interdisciplinary conceptualization of the recreational fisheries system. This synthesis is intended to be a cross‐disciplinary bridge to facilitate access to the broader literature on modelling angler behaviour, with the ultimate goal of improving recreational fisheries management.     

Behavioural diversity in fishing—Towards a next generation of fishery models

Despite improved knowledge and stricter regulations, numerous fish stocks remain overharvested. Previous research has shown that fisheries management may fail when the models and assessments used to inform management are based on unrealistic assumptions regarding fishers' decision‐making and responses to policies. Improving the understanding of fisher behaviour requires addressing its diversity and complexity through the integration of social science knowledge into modelling. In our paper, we review and synthesize state‐of‐the‐art research on both social science's understanding of fisher behaviour and the representation of fisher decision‐making in scientific models. We then develop and experiment with an agent‐based social–ecological fisheries model that formalizes three different fishing styles. Thereby we reflect on the implications of our incorporation of behavioural diversity and contrast it with the predominant assumption in fishery models: fishing practices being driven by rational profit maximizing. We envision a next generation of fisheries models and management that account for social scientific knowledge on individual and collective human behaviours. Through our agent‐based model, we demonstrate how such an integration is possible and propose a scientific approach for reducing uncertainty based on human behavioural diversity in fisheries. This study serves to lay the foundations for a next generation of social–ecological fishery models that account for human behavioural diversity and social and ecological complexity that are relevant for a realistic assessment and management of fishery sustainability problems.     

It is past time to use ecosystem models tactically to support ecosystem-based fisheries management: Case studies using Ecopath with Ecosim in an operational management context

The implementation of ecosystem management requires ecosystem modelling within the context of a natural resource management process. Ecopath with Ecosim (EwE) is the most widely used modelling platform for investigating the dynamics of marine ecosystems, but has played a limited role in fisheries management and in multi-sector resource decision-making. We review 10 case studies that demonstrate the use of EwE to support operational resource management. EwE models are being used to inform tactical decision-making in fisheries and other ocean use sectors, as well as to identify key trade-offs, develop appropriate policy objectives, and reconcile conflicting legislative mandates in a variety of ecosystems. We suggest the following criteria to enhance the use of EwE and other ecosystem models in operational resource management: (1) a clear management objective that can be addressed through modelling; (2) an important trade-off and a receptive policy context amenable to trade-off evaluation; (3) an accessible and well-documented model that follows best practices; (4) early and iterative engagement among scientists, stakeholders, and managers; (5) integration within a collaborative management process; (6) a multi-model approach; and (7) a rigorous review process. Our review suggests that existing management frameworks are as much or more of a limitation to the operational use of EwE than technical issues related to data availability and model uncertainty. Ecosystem models are increasingly needed to facilitate more effective and transparent decision-making. We assert that the requisite conditions currently exist for enhanced strategic and tactical use of EwE to support fisheries and natural resource management.     

Climate change alters fish community size‐structure,requiring adaptive policy targets

Size‐based indicators are used worldwide in research that supports the management of commercially exploited wild fish populations, because of their responsiveness to fishing pressure. Observational and experimental data, however, have highlighted the deeply rooted links between fish size and environmental conditions that can drive additional, interannual changes in these indicators. Here, we have used biogeochemical and mechanistic niche modelling of commercially exploited demersal fish species to project time series to the end of the 21st century for one such indicator, the large fish indicator (LFI), under global CO₂ emissions scenarios. Our modelling results, validated against survey data, suggest that the LFI's previously proposed policy target may be unachievable under future climate change. In turn, our results help to identify what may be achievable policy targets for demersal fish communities experiencing climate change. While fisheries modelling has grown as a science, climate change modelling is seldom used specifically to address policy aims. Studies such as this one can, however, enable a more sustainable exploitation of marine food resources under changes unmanageable by fisheries control. Indeed, such studies can be used to aid resilient policy target setting by taking into account climate‐driven effects on fish community size‐structure.     

Integrating physiology and life history to improve fisheries management and conservation

Knowledge of life‐history traits is increasingly recognized as an important criterion for effective management and conservation. Understanding the link between physiology and life history is an important component of this knowledge and in our view is particularly relevant to understanding marine and freshwater fishes. Such linkages (i.e. the life‐history/physiology nexus) have been recently advocated for avian systems and here we explore this concept for fish. This paper highlights the gap in fisheries literature with regard to understanding the relationship between physiology and life history, and proposes ways in which this integration could improve fisheries management and conservation. We use three case studies on different fishes (i.e. the Pacific salmon, the grouper complex and tuna) to explore these issues. The physiological structure and function of fish plays a central role in determining stock response to exploitation and changes in the environment. Physiological measures can provide simple indicators necessary for cost‐effective monitoring in the evaluation of fisheries sustainability. The declining state of world fisheries and the need to develop and implement restoration strategies, such as hatchery production or protected areas, provides strong incentive to better understand the influence of physiology on population and reproductive dynamics and early life history. Physiology influences key population‐level processes, particularly those dealing with reproduction, which must be incorporated into the design and successful implementation of specific and broadscale initiatives (e.g. aquatic protected areas and bycatch reduction). Suggestions are made for how to encourage wider application of the physiology/life‐history link, in fisheries management and conservation, as well as more broadly in education and research.     

A novel spatiotemporal stock assessment framework to better address fine‐scale species distributions: Development and simulation testing

Characterizing population distribution and abundance over space and time is central to population ecology and conservation of natural populations. However, species distribution models and population dynamic models have rarely been integrated into a single modelling framework. Consequently, fine‐scale spatial heterogeneity is often ignored in resource assessments. We develop and test a novel spatiotemporal assessment framework to better address fine‐scale spatial heterogeneities based on theories of fish population dynamic and spatiotemporal statistics. The spatiotemporal model links species distribution and population dynamic models within a single statistical framework that is flexible enough to permit inference for each state variable through space and time. We illustrate the model with a simulation–estimation experiment tailored to two exploited marine species: snow crab (Chionoecetes opilio, Oregoniidae) in the Eastern Bering Sea and northern shrimp (Pandalus borealis, Pandalidae) in the Gulf of Maine. These two species have different types of life history. We compare the spatiotemporal model with a spatially aggregated model and systematically evaluate the spatiotemporal model based on simulation experiments. We show that the spatiotemporal model can recover spatial patterns in population and exploitation pressure as well as provide unbiased estimates of spatially aggregated population quantities. The spatiotemporal model also implicitly accounts for individual movement rates and can outperform spatially aggregated models by accounting for time‐and‐size varying selectivity caused by spatial heterogeneity. We conclude that spatiotemporal modelling framework is a feasible and promising approach to address the spatial structure of natural resource populations, which is a major challenge in understanding population dynamics and conducting resource assessments and management.     

Ecosystem models for fisheries management: finding the sweet spot

The advent of an ecosystem‐based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade‐offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single‐species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age‐structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short‐comings of the various modelling approaches being proposed for ecosystem‐based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single‐species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions.     

Biophysical modelling of larval drift, growth and survival for the prediction of anchovy (Engraulis encrasicolus) recruitment in the Bay of Biscay (NE Atlantic)

Fish recruitment is the result of the integration of small‐scale processes affecting larval survival over a season and large oceanic areas. A hydrodynamic model was used to explore and model these physical–biological interaction mechanisms and then to perform the integration from individual to population scales in order to provide recruitment predictions for fisheries management. This method was applied to the case of anchovy (Engraulis encrasicolus) in the Bay of Biscay (NE Atlantic). The main data available to investigate survival mechanisms were past growth (otolith) records of larvae and juveniles sampled at sea. The drift history of these individuals was reconstructed by a backtracking procedure using hydrodynamic simulations. The relationships between (real) growth variation and variations in physical parameters (estimated by hydrodynamic simulations) were explored along the individual trajectories obtained. These relationships were then used to build and adjust individual‐based growth and survival models. Thousands of virtual buoys were released in the hydrodynamic model in order to reproduce the space–time spawning dynamics. Along the buoy trajectories (representative of sub‐cohorts), the biophysical model was run to simulate growth and survival as a function of the environment encountered. The survival rate after 3 months of drift was estimated for each sub‐cohort. The sum of all these survival rates over the season constituted an annual recruitment index. This index was validated over a series of recruitment estimations. The modelling choices, model results and the potential use of the recruitment index for fisheries management are discussed.     

Does MPA mean ‘Major Problem for Assessments'? Considering the consequences of place‐based management systems

Marine protected areas (MPAs) have been increasingly proposed, evaluated and implemented as management tools for achieving both fisheries and conservation objectives in aquatic ecosystems. However, there is a challenge associated with the application of MPAs in marine resource management with respect to the consequences to traditional systems of monitoring and managing fisheries resources. The place‐based paradigm of MPAs can complicate the population‐based paradigm of most fisheries stock assessments. In this review, we identify the potential complications that could result from both existing and future MPAs to the science and management systems currently in place for meeting conventional fisheries management objectives. The intent is not to evaluate the effects of implementing MPAs on fisheries yields, or even to consider the extent to which MPAs may achieve conservation oriented objectives, but rather to evaluate the consequences of MPA implementation on the ability to monitor and assess fishery resources consistent with existing methods and legislative mandates. Although examples are drawn primarily from groundfish fisheries on the West Coast of the USA, the lessons are broadly applicable to management systems worldwide, particularly those in which there exists the institutional infrastructure for managing resources based on quantitative assessments of resource status and productivity.     

What constitutes effective governance of recreational fisheries?—A global review

The effectiveness of recreational fisheries governance has been mixed, with some countries boasting good governance practices that sustain productive recreational fisheries, while others lack any policies and governance structures specific to recreational fisheries. Here, we identify what constitutes effective governance of recreational fisheries by carrying out: (a) a desktop review of 227 country‐specific fisheries legislation, policies and strategies; and (b) a follow‐up questionnaire‐based survey covering 57 contacts in 29 selected countries. Our results show that while recreational fishing is referred to in the main legislation of 67% of the countries reviewed, only 86 of these 152 countries provide a definition for either “recreational” or “sport” fishing and not always in the main legislation. Recreational fisheries are not considered to be effectively managed in many countries, with less than a quarter of respondents claiming that management in their country is effective. Furthermore, the management efficacy, including compliance with regulations, was considered greater for the industrial and small‐scale fishing sectors than for recreational fisheries in most countries. From our findings, it appears that effective recreational fisheries governance requires explicit acknowledgement of recreational fisheries with a clear legal definition in Policy, a well‐developed Policy statement, extensive co‐management processes, clearly defined biological, economic and social monitoring structures and efficient and transparent cost recovery mechanisms. To ensure adaptation to rapidly changing conditions, policy should recognize all fishery sectors and proactively incorporate adaptive planning and contingency plans to effectively secure the diverse values of resources for all users.     

Evaluation of a spatially sex‐specific assessment method incorporating a habitat preference model for blue marlin (Makaira nigricans) in the Pacific Ocean

Blue marlin, widely distributed throughout the Pacific Ocean, are sexually dimorphic, have certain preferred habitats, and migrate seasonally. These characteristics have been ignored in previous stock assessment models. A population dynamics model that includes spatial structure, and sex and age structure was therefore constructed and fitted to fisheries data for blue marlin, along with information on the relative density of the population over space derived from a habitat preference model that uses the oceanographic and biological variables sea‐surface temperature, mixed layer depth, sea‐surface height anomaly, and chlorophyll‐a concentration. Monte Carlo simulation was then used to examine the estimation performance of the stock assessment method. Estimates of management‐related quantities including current spawning stock biomass are substantially biased when the assessment method ignores seasonal movement and sexual dimorphism. We also found that (i) uncertainty about the relationship between catch rate and abundance influences estimation performance to a larger extent than uncertainty in catches, (ii) the outcomes of the assessment are sensitive to the values assumed for natural mortality and stock‐recruitment steepness, and (iii) the ratio of current spawning stock biomass to that at pre‐exploitation equilibrium appears to be the most robust among the quantities considered. We conclude that assessment methods for blue marlin in the Pacific Ocean need to take account of seasonal migration and sex structure to improve stock assessments.     

Effects of no‐take area size and age of marine protected areas on fisheries yields: a meta‐analytical approach

Marine protected areas (MPAs) are often promoted as tools for biodiversity conservation as well as for fisheries management. Despite increasing evidence of their usefulness, questions remain regarding the optimal design of MPAs, in particular concerning their function as fisheries management tools, for which empirical studies are still lacking. Using 28 data sets from seven MPAs in Southern Europe, we developed a meta‐analytical approach to investigate the effects of protection on adjacent fisheries and asking how these effects are influenced by MPA size and age. Southern European MPAs showed clear effects on the surrounding fisheries, on the ‘catch per unit effort’ (CPUE) of target species, but especially on the CPUE of the marketable catch. These effects depended on the time of protection and on the size of the no‐take area. CPUE of both target species and the marketable catch increased gradually by 2–4% per year over a long time period (at least 30 years). The influence of the size of the no‐take area appeared to be more complex. The catch rates of the entire fishery in and around the MPA were higher when the no‐take areas were smaller. Conversely, catch rates of selected fisheries that were expected to benefit most from protection increased when the no‐take area was larger. Our results emphasize the importance of MPA size on its export functions and suggest that an adequate, often extended, time frame be used for the management and the evaluation of effectiveness of MPAs.     

The assessment of fishery status depends on fish habitats

At the crux of the debate over the global sustainability of fisheries is what society must do to prevent over‐exploitation and aid recovery of fisheries that have historically been over‐exploited. The focus of debates has been on controlling fishing pressure, and assessments have not considered that stock production may be affected by changes in fish habitat. Fish habitats are being modified by climate change, built infrastructure, destructive fishing practices and pollution. We conceptualize how the classification of stock status can be biased by habitat change. Habitat loss and degradation can result in either overly optimistic or overly conservative assessment of stock status. The classification of stock status depends on how habitat affects fish demography and what reference points management uses to assess status. Nearly half of the 418 stocks in a global stock assessment database use seagrass, mangroves, coral reefs and macroalgae habitats that have well‐documented trends. There is also considerable circumstantial evidence that habitat change has contributed to over‐exploitation or enhanced production of data‐poor fisheries, like inland and subsistence fisheries. Globally many habitats are in decline, so the role of habitat should be considered when assessing the global status of fisheries. New methods and global databases of habitat trends and use of habitats by fishery species are required to properly attribute causes of decline in fisheries and are likely to raise the profile of habitat protection as an important complementary aim for fisheries management.     

Using scenarios to project the changing profitability of fisheries under climate change

Over‐exploitation and economic underperformance are widespread in the world's fisheries. Global climate change is further affecting the distribution of marine species, raising concern for the persistence of biodiversity and presenting additional challenges to fisheries management. However, few studies have attempted to extend bioclimatic projections to assess the socio‐economic impacts of climate‐induced range shifts. This study investigates the potential implications of changes in relative environmental suitability and fisheries catch potential on UK fisheries by linking species distribution modelling with cost‐benefit analyses. We develop scenarios and apply a multimodel approach to explore the economic sensitivity of UK fisheries and key sources of uncertainty in the modelling procedure. We projected changes in maximum potential catch of key species and the resulting responses in terms of net present value (NPV) over a 45‐year period under scenarios of change in fuel price, discount rate and government subsidies. Results suggest that total maximum potential catch will decrease within the UK EEZ by 2050, resulting in a median decrease in NPV of 10%. This value decreases further when trends of fuel price change are extrapolated into the future, becoming negative when capacity‐enhancing subsidies are removed. Despite the variation in predictions from alternative models and data input, the direction of change in NPV is robust. This study highlights key factors influencing future profitability of UK fisheries and the importance of enhancing adaptive capacity in UK fisheries.     

Modelling the oceanic habitats of two pelagic species using recreational fisheries data

Defining the oceanic habitats of migratory marine species is important for both single species and ecosystem‐based fisheries management, particularly when the distribution of these habitats vary temporally. This can be achieved using species distribution models that include physical environmental predictors. In the present study, species distribution models that describe the seasonal habitats of two pelagic fish (dolphinfish, Coryphaena hippurus and yellowtail kingfish, Seriola lalandi), are developed using 19 yr of presence‐only data from a recreational angler‐based catch‐and‐release fishing programme. A Poisson point process model within a generalized additive modelling framework was used to determine the species distributions off the east coast of Australia as a function of several oceanographic covariates. This modelling framework uses presence‐only data to determine the intensity of fish (fish km^?2), rather than a probability of fish presence. Sea surface temperature (SST), sea level anomaly, SST frontal index and eddy kinetic energy were significant environmental predictors for both dolphinfish and kingfish distributions. Models for both species indicate a greater fish intensity off the east Australian coast during summer and autumn in response to the regional oceanography, namely shelf incursions by the East Australian Current. This study provides a framework for using presence‐only recreational fisheries data to create species distribution models that can contribute to the future dynamic spatial management of pelagic fisheries.     

Modelling the effects of reserve size and fishing mortality for Caribbean queen conch Strombus gigas

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Realizing the potential of trait‐based approaches to advance fisheries science

Analysing how fish populations and their ecological communities respond to perturbations such as fishing and environmental variation is crucial to fisheries science. Researchers often predict fish population dynamics using species‐level life‐history parameters that are treated as fixed over time, while ignoring the impact of intraspecific variation on ecosystem dynamics. However, there is increasing recognition of the need to include processes operating at ecosystem levels (changes in drivers of productivity) while also accounting for variation over space, time and among individuals. To address similar challenges, community ecologists studying plants, insects and other taxa increasingly measure phenotypic characteristics of individual animals that affect fitness or ecological function (termed “functional traits”). Here, we review the history of trait‐based methods in fish and other taxa, and argue that fisheries science could see benefits by integrating trait‐based approaches within existing fisheries analyses. We argue that measuring and modelling functional traits can improve estimates of population and community dynamics, and rapidly detect responses to fishing and environmental drivers. We support this claim using three concrete examples: how trait‐based approaches could account for time‐varying parameters in population models; improve fisheries management and harvest control rules; and inform size‐based models of marine communities. We then present a step‐by‐step primer for how trait‐based methods could be adapted to complement existing models and analyses in fisheries science. Finally, we call for the creation and expansion of publicly available trait databases to facilitate adapting trait‐based methods in fisheries science, to complement existing public databases of life‐history parameters for marine organisms.     

The evolution of a discard policy in Europe

Ocean sustainability is a widespread public concern in Europe, and the issue of fisheries discards is one that is now widely known. With this increase in public awareness comes the need to adapt fisheries management policies to manage issues like fisheries discards that were not previously taken into account. In this context, this study analyses the evolution of the European Union's discard policy since its inception in 2006 until the present day and the events that shaped its current format. It analyses the policy's advantages and disadvantages, and its political, environmental and scientific consequences. It argues that an increase in public awareness, due to public campaigns against fisheries discards, has focused managers' attention onto a symptom of fisheries mismanagement, rather than on its underlying causes of over‐exploitation and lack of fisheries control. This has distorted the discussion of the reform of the Common Fisheries Policy and potentially undermined its provisions relating to discards.