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.     

Multispecies functional responses reveal reduced predation at high prey densities and varied responses among and within trophic groups

Understanding predator–prey interactions is critical for marine fisheries and ecosystem management as they shape community structure, regulate prey populations and present energy demands critical for community sustainability. We examined multispecies functional responses of 17 fishes (48 predator‐size combinations) spanning piscivores, planktivores and benthivores for the northeast US continental shelf. Similar to previous work, linear relationships between predation and prey density (Holling type I response) were not supported, since model estimates of handling time were greater than zero for the prey considered. Instead, a clear majority of the predators sampled were Holling type III feeders (sigmoidal; prey switching or learning). For piscivores, nearly all responses were Holling type III with the exception of one being Holling type II (hyperbolic; satiation). Planktivores and benthivores exhibited a combination of type IV (feeding confusion at high prey density) and Holling type III responses. The relationships were predator‐ and prey‐dependent, which is counter to assumptions that are often made of trophic groups. Decreased predation at high prey densities (type IV response) present among planktivores and benthivores suggests an overestimation of predation can occur if ignored. This contrasts with fish and squid prey which primarily invoked a Holling type III response. Functional responses are key to modelling trophic interactions for multispecies and ecosystem models. By refining these inputs in a multispecies context with empirical data, we can advance our understanding of whole‐shelf ecology and improve decision‐making tools for resource management.     

Incorporating cannibalism into an age-structured model for the Chilean hake

We incorporated predation equations from the multispecies virtual population analysis model MSVPA into an age-structured model for the Chilean hake (Merluccius gayi gayi) to estimate cannibalism. Two models, model I with constant natural mortality and the MSM, were fitted to the total annual catch, spawning biomass from acoustic surveys and length composition data from fishery and acoustic surveys. Model I fitted the data better than MSM. The majority of the MSM estimates of adult population and spawning biomass were larger than the model I estimates; probably due to the choice of residual mortality M1. High estimates of predation mortality were observed for age-0 hake. In spite of a decreasing fishing mortality, the spawning biomass decreased in the last years. Preliminary MSM results suggest that this might be due to an increase in cannibalism. A sensitivity analysis suggested all response variables were not sensible to the “other food” parameter but sensible to M1 and the predator annual ration. MSM is a promising approach that introduces the predation mortality equations into a statistical framework, allowing the incorporation of the uncertainty in the estimation of the parameters and the use of standard statistical tools in a multispecies context. This approach will contribute to provide useful information on the indirect effects of fishing on non-target species to fisheries managers.     

滆湖渔业资源系统的仿真研究

介绍了应用灰色理论,对滆湖渔业经济系统和生态系统进行灰色动态和灰色关联分析的思路和方法,还介绍了应用人工智能的神经网络技术对滆湖生态系统中能流、物流的发展变化态势进行网络模拟的设计思路和实现方法。灰色动态分析的结果表明：滆湖渔业经济要持续稳定地发展,其渔业资源繁殖保护及劳力等投资不能低于渔业产值的15％。灰色关联分析结果表明：影响该湖渔业经济的主要环境因子为苦草生物量、轮叶黑藻生物量和水生植物总生物量。人工智能模拟结果表明：要充分利用水草资源,提高滆潮草食性鱼类的经济和生态效益,就要增加团头鲂的放流量,优化放流鱼类的品种结构。最后讨论了应用神经网络模拟与灰色理论相结合的技术进行社会、经济和生态等复杂系统的动态仿真与智能控制的可能性。     

海洋食物网拓扑学方法研究进展

基于生态系统的渔业管理(EBFM)对海洋食物网研究提出了新的理论和方法需求.作者针对食物网动态这一生态系统的核心问题,对其近期发展起来的研究领域——食物网拓扑学理论和方法进行综述.食物网拓扑学通过建立一系列拓扑学指标,定量描述食物网各个成员之间的联系紧密程度,以及各个成员对整个食物网的作用.评价渔业对食物网的影响或食物网对外界的响应,开发可持续的捕捞方案,需要建立并运用食物网的动态模型.鱼类生物的重要特点是其捕食关系在很大程度上由个体大小(体长、体重)决定.而体长结构的渔业种群动力学模型发展已经成熟.因此,建议将食物网拓扑学的动态建模、体长结构的渔业种群生物量模型、鱼类个体大小相关的捕捞过程研究结合起来,作为基于生态系统渔业管理的一个重要的、潜在解决方案.对此,下一步的研究重点是,选择食物网资料采集较为容易、渔业统计资料较为全面的海洋食物网,开展试点研究,从而逐步构建起完整的、具有实际应用能力的EBFM方法体系.     

Assessing spillover from marine protected areas and its drivers: A meta‐analytical approach

Overfishing may seriously impact fish populations and ecosystems. Marine protected areas (MPAs) are key tools for biodiversity conservation and fisheries management, yet the fisheries benefits remain debateable. Many MPAs include a fully protected area (FPA), restricting all activities, within a partially protected area (PPA) where potentially sustainable activities are permitted. An effective tool for biodiversity conservation, FPAs, can sustain local fisheries via spillover, that is the outward export of individuals from FPAs. Spillover refers to both: “ecological spillover”: outward net emigration of juveniles, subadults and/or adults from the FPA; and “fishery spillover”: the fraction of ecological spillover that directly benefits fishery yields and revenues through fishable biomass. Yet, how common is spillover remains controversial. We present a meta‐analysis of a unique global database covering 23 FPAs worldwide, using published literature and purposely collected field data, to assess the capacity of FPAs to export biomass and whether this response was mediated by specific FPA features (e.g. size, age) or species characteristics (e.g. mobility, economic value). Results show fish biomass and abundance outside FPAs was higher: (a) in locations close to FPA borders (<200 m) than further away (>200 m); (b) for species with a high commercial value; and (c) in the presence of PPA surrounding the FPA. Spillover was slightly higher in FPAs that were larger and older and for more mobile species. Based on the broadest data set compiled to date on marine species ecological spillover beyond FPAs' borders, our work highlights elements that could guide strategies to enhance local fishery management using MPAs.     

Is it possible to differentiate between environmental and fishery effects on abundance‐biomass variation? A case study of blackspot seabream (Pagellus bogaraveo) in the Strait of Gibraltar

We assessed the potential for simulation and modelling of the blackspot seabream (Pagellus bogaraveo) population in the Strait of Gibraltar to discriminate the environmental effects of fishery impacts. A discrete biomass–abundance dynamic model was implemented to obtain a simulated monthly time series of blackspot seabream biomass. On this simulated time series, autoregressive integrated moving average (ARIMA) models were fitted. The best ARIMA fit provided a significant correlation of 0.76 and persistence index higher than 0.85. The proportion of variance non‐explained by the ARIMA models was correlated with a time series of sea surface temperature (SST) and North Atlantic Oscillation (NAO). The analysis of global, annual and winter correlation between the proportion of variance not explained by the ARIMA models and environmental variables showed that significant associations were not detected over the full time series. Our analysis therefore suggests that overexploitation is the main factor responsible for the commercial depletion of blackspot seabream in the Strait of Gibraltar.     

A delay-differential model for representing small pelagic fish stock dynamics and its application for assessing alternative management strategies under environmental uncertainty

We present a novel adaptation of the classic discrete delay-difference model, a continuous delay-differential model (cDDM), which can adequately represent population dynamics of stocks that turn over rapidly and continuously over time (e.g., small pelagic fish, small tunas, and shrimps). We used the Northern-Central Peruvian anchoveta stock (Engraulis ringens, Engraulidae) as a case study for implementing the cDDM and conducted a management strategy evaluation (MSE) through stochastic optimization in policy space (SOPS). Our results showed that cDDM integrated with SOPS efficiently searches optimum and near-optimum harvest control rules (HCR) and is an alternative to pre-setting arbitrary HCRs as in traditional MSE. The cDDM showed comparable stock biomass and recruitment estimate reconstructions to more complex stock assessment models described for anchoveta. We concluded that the anchoveta stock is sustainably managed and is an example of adaptive fisheries management under high ocean-climate variability and uncertainty. Contrary to fishery textbooks, the anchoveta's collapse was not entirely due to the 1972 El Niño (EN) but a recruitment failure preceding EN. Our reconstructions revealed that low recruitment (or recruitment failure) could still occur at high stock biomass. Anchoveta's stock biomass is larger than pre-collapse, likely due to favourable environmental conditions (a cooling trend) and management, despite more frequent and stronger EN events. SOPS quickly revealed that harvest strategies with large base biomass (>5 mmt) lead to higher interannual stock variability and would not produce substantial increases in long-term yield. Alternative HCRs with lower base biomass, while adjusting for productivity regimes, have similar long-term yields without affecting the long-term average stock.     

Harvest models and stock co‐occurrence: probabilistic methods for estimating bycatch

A primary goal of ecosystem‐based fishery management is to reduce non‐target stock impacts, such as incidental harvest, during targeted fisheries. Quantifying incidental harvest has generally incorporated fishery‐dependent catch data, yet such data may be biased by gear non‐retention, observation difficulties, and non‐random harvest patterns that collectively lead to an impartial understanding of non‐target stock capture. To account for such issues and explicitly recognize the combined influence of ecological and harvest factors contributing to incidental capture within targeted fisheries, we demonstrate a probabilistic modelling framework that incorporates: (i) background rates of target and non‐target stock co‐occurrence as the primary ecological basis for incidental harvest; (ii) the probability of harvesting at localities exhibiting co‐occurrences; (iii) the probability of selecting for non‐target species with fishery gear; and, (iv) as a function of harvest effort, the overall probability of incidental capture for any non‐target stock contained in the species pool available for harvest. To illustrate application of the framework, simulation models were based on fishery‐independent data from a freshwater fishery in Ontario, Canada. Harvest simulations of empirical stock data indicated that greatest species‐specific capture values were over 4000 times more likely than for species with lowest values, indicating highly variable capture probabilities because of the combined influence of stock heterogeneity and harvest dynamics. Estimated bycatch–effort relationships will allow forecasting incidental harvest on the basis of effort to evaluate future shifts in fishing activity against specific ecosystem‐based fishery management objectives, such as reducing the overall probability of bycatch while maintaining target landings.     

Frontiers in modelling social–ecological dynamics of recreational fisheries: A review and synthesis

Recreational fisheries are culturally and economically important around the world. Recent research emphasizes that understanding and managing these systems requires a social–ecological perspective. We systematically reviewed quantitative social–ecological models of marine and freshwater recreational fisheries to summarize their conceptualization of social, ecological, and social–ecological dynamics and identify research frontiers. From a candidate set of 626 studies published between 1975 and 2018, 49 met criteria for inclusion in our review. These studies, though diverse in terms of focal species and processes considered, were geographically limited to a few locations and ignored large regions of the globe where recreational fishing is important. There were also important gaps in the social and ecological processes that were included in published models. Reflecting on these patterns in the context of previous conceptual frameworks, we define five key frontiers for future work: 1) exploring the implications of social and behavioural processes like heuristics, social norms, and information sharing for angler decisions and fishery dynamics; 2) modelling governance with more realistic complexity; 3) incorporating ideas from resilience thinking and complex adaptive systems, including slow variables, destabilizing feedbacks, surprises and diversity; 4) considering key ideas in fisheries systems, including spatial and temporal effort dynamics, catch hyperstability, and stocking; and 5) thinking synthetically about the models that we use to describe social–ecological dynamics in recreational fisheries, via explicit comparisons and formal integration with data. Exploration of these frontiers, while remembering the distinction between model complexity and model usefulness, will improve our ability to understand and sustain recreational fisheries.