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Climate change has led to significant fluctuations in marine ecosystems. As a component of the food web, the trophic diversity and spatiotemporal changes of fish communities are crucial for understanding ecosystems. In recent years, stable isotope analysis has been increasingly used as a comprehensive tool for quantitative assessment of trophic diversity to explore spatiotemporal variations in fish community diversity. This study is based on carbon (δ 13C) and nitrogen (δ 15N) stable isotope analysis using different biomass-weighted isotope diversity indices, including isotopic divergence index (IDiv), isotopic dispersion index (IDis), isotopic evenness index (IEve), and isotopic uniqueness index (IUni). The overall results indicate that IDis, IEve, and IUni values of fish communities were relatively low, while IDiv was relatively high in the Haizhou Bay ecosystem. IDiv, IDis, IEve, and IUni were lower in autumn than in spring; IDiv and IDis were relatively higher in offshore waters, while IEve and IUni were relatively higher in inshore waters. The changes in species composition and intensive pelagic–benthic coupling in Haizhou Bay may lead to significant spatiotemporal variations in the trophic diversity of fish communities in the area. These findings highlight the importance of incorporating trophic relationships into ecosystem models, which will help to enhance our understanding of the complexity of the trophic structure of fish communities. [ABSTRACT FROM AUTHOR]

Extensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science‐based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density‐dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual‐based model based on dynamic energy budget theory and full life‐history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual‐level processes. We demonstrated the utility of the model framework by applying it to an extensively enhanced species, Chinese prawn (Fenneropenaeus chinensis, Penaeidae). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade‐offs between the ecological and economic objectives, that is, pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement programme, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management. [ABSTRACT FROM AUTHOR]

Data-limited methods (DLMs) in stock assessment may provide potential critical information for data-limited stock management. However, the sensitivity of those methods to life-history parameters is largely unknown, resulting in extra uncertainty and consequent risks. In the present study, we designed six parallel workflows (WFs) to incorporate classic and state-of-the-art methods of estimating life-history parameters and examined their influences on the assessment of small yellow croaker (Larimichthys polyactis) in Haizhou Bay, China. The sensitivity was evaluated with three objectives: (i) the evaluation of stock status with the spawning potential ratio following different assumptions; (ii) the length-based harvest control rules derived from three management procedures; and (iii) the management performance of these harvest control rules with simulation of management strategy evaluation. The results showed considerable sensitivity regarding the three objectives to the estimations with different WFs, indicating the previous practice of credulously accepting empirical values and indiscriminately selecting references are inadvisable. We also identified the most appropriate WFs used for different purposes with limited data, aiming to provide more reliable inputs for effective fisheries management. Les methodes de traitement de donnees limitees (MDL) utilisees dans revaluation de stocks peuvent fournir de l'information potentiellement cle pour la gestion de stocks pour lesquels les donnees sont limitees. La sensibilite de ces methodes aux parametres du cycle biologique est generalement inconnue, ce qui se traduit par une incertitude accrue et les risques qui en decoulent. Nous avons concu six flux de travail (FT) paralleles pour incorporer des methodes classiques et de pointe d'estimation de parametres du cycle biologique et examine leur influence sur l'evaluation de la courbine jaune (Larimichthys polyactis) dans la baie de Haizhou (Chine). L'evaluation de la sensibilite avait trois objectifs, soit (i) revaluation de l'etat du stock par l'estimation du rapport du potentiel de frai pour differentes hypotheses; (ii) les regles de controle des prises basees sur la longueur decoulant de trois procedures de gestion; et (iii) le rendement de la gestion de ces regles de controle des prisesavec simulation de l'evaluation de strategies de gestion. Les resultats revelent une sensibilite considerable concernant ces trois objectifs aux estimations avec differents flux de travail, qui indique que la pratique passee de tenir pour acquises les valeurs empiriques et de choisir des references sans discrimination n'est pas recommandable. Nous avons egalement cerne les flux de travail les mieux adaptes pour differentes fins en presence de donnees limitees, dans le but de fournir des donnees d'entree plus fiables pour une gestion efficace des peches. [Traduit par la Redaction], Introduction Over 90% of the fish stocks in the world are managed without formal stock assessment, including the majority of fisheries in the developing countries (Costello et al. 2012). The [...]

Effective ecological indicators (EI) should reflect changes to ecosystem status in a timely manner to guide fisheries management; however, the robustness of EIs in the face of sampling uncertainty is not well understood and sampling errors may result in delayed or even unhelpful actions for management. In this study, we use a size-spectrum model to evaluate the effectiveness of EIs in detecting fishery-induced ecosystem changes given various levels of sampling uncertainty. We demonstrate that there is a time-lag that exists between changes in fishing pressure and EI response. The selectivity of survey gears can strongly determine the level of EI responses within certain size ranges. EIs may lose statistical power once sampling errors exceed a certain level, implying that several decades of monitoring data may be needed to be sure of detecting even a large change. Multivariate methods can strengthen the statistical powers of EIs, but only when the level of sampling noises is low. This study suggests the need for considering the impact of sampling uncertainty on the use of EIs in fisheries management. Les indicateurs ecologiques (IE) efficaces devraient refleter en temps opportun les modifications de l'etat des ecosystemes pour guider la gestion des peches. La robustesse des IE en presence d'incertitude associee a l'echantillonnage n'est toutefois pas bien comprise, et des erreurs d'echantillonnage peuvent se traduire par des mesures de gestion tardives, voire inutiles. Nous avons utilise un modele de spectre de tailles pour evaluer l'efficacite d'IE pour la detection de modifications d'ecosystemes induites par la peche pour differents degres d'incertitude associee a l'echantillonnage. Nous demontrons qu'il y a un decalage temporel entre les variations de la pression de peche et les reactions des IE. La selectivite des engins utilises pour revaluation peut etre un determinant important du degre de reaction des IE dans certaines fourchettes de tailles. Les IE peuvent perdre de leur efficacite statistique si les erreurs d'echantillonnage depassent un certain seuil, de sorte que des donnees de surveillance sur plusieurs decennies pourraient etre necessaries pour deceler des changements meme importants. Des methodes multivariees peuvent rehausser l'efficacite statistique des IE, mais seulement quand le bruit d'echantillonnage est faible. L'etude fait ressortir la necessite de tenir compte de l'incidence de l'incertitude associee a l'echantillonnage sur l'utilisation des IE en gestion des peches. [Traduit par la Redaction], Introduction The concept of 'ecosystem-based fisheries management' (EBFM) has been widely accepted in fisheries management with an increased recognition of fishing impacts on marine ecosystems (Hall and Mainprize 2004; Pikitch [...]

The management of mixed fisheries is complicated by the biological and technical interactions among fish species. We tested a multispecies total allowable catch approach to managing mixed fisheries while accounting for the interactions and changes within fish community. A multispecies size–spectrum model was developed to simulate the dynamic of fish community in North Yellow Sea, China. Three scenarios were evaluated: (1) business-as-usual (BAU); (2) Single-species TAC (SSTAC); and (3) Multispecies TAC (MSTAC, assigning an aggregated total TAC to a selected group of species). Our results showed that BAU reduced biomass of target species to a substantially low level, SSTAC led to loss of fishing opportunity by involving "choke species" with discard ban, while MSTAC had a potential for maintaining long-term yields and community structure. We demonstrated the ecological effects of varying levels of MSTACs on the target and non-target species. Species' responses to MSTAC were stronger when the species had similar feeding and habitat traits to the target species, implying intense competition. Particularly, a 20% decrease in MSTAC could cause an average 17% decline in the biomass of other species through biological interactions in the long-term. MSTAC could be a promising approach to achieving long-term sustainability in data deficient fisheries. [ABSTRACT FROM AUTHOR]

Varying catchability is a common feature in fisheries and has great impacts on fisheries assessments and species distribution models. However, spatial variations in catchability have been rarely evaluated, especially in the multispecies context. We advocate that the need for multispecies models stands for both challenges and opportunities to handle spatial catchability. This study evaluated the influence of spatially varying catchability on the performance of a novel joint species distribution model, namely Hierarchical Modelling of Species Communities (HMSC). We implemented the model under nine simulation scenarios to account for diverse spatial patterns of catchability and conducted empirical tests using survey data from Yellow Sea, China. Our results showed that ignoring variability in catchability could lead to substantial errors in the inferences of species response to environment. Meanwhile, the models' predictive power was less impacted, yielding proper predictions of relative abundance. Incorporating a spatially autocorrelated structure substantially improved the predictability of HMSC in both simulation and empirical tests. Nevertheless, combined sources of spatial catchabilities could largely diminish the advantage of HMSC in inference and prediction. We highlight situations where catchability needs to be explicitly accounted for in modelling fish distributions, and suggest directions for future applications and development of JSDMs. [ABSTRACT FROM AUTHOR]

Sustainable fisheries management is built on effective management strategies and informative data that are usually well defined for data‐rich fisheries. However, their counterparts in data‐limited fisheries remain inadequately evaluated due to insufficient data for stock assessments. This raises two questions: (1) can data‐limited management strategies achieve sustainable fisheries and (2) are certain types of data more informative than others are in developing sustainable data‐limited fisheries? To address these questions, we performed management strategy evaluation with data‐rich stocks to simulate data‐limited fisheries management. The performance of data‐limited management procedures (MPs) was compared with the performance of management strategies that are based on data‐rich stock assessments. We examined the informative nature of six data categories in data‐limited situations by developing a tier system that mimicked different data availability levels and evaluating their contributions to management success. Our study showed that it is possible to achieve maximum sustainable yield (MSY) with limited data, given the proper choice of MPs. In addition, the data categories were not equally informative to the development of sustainable data‐limited fisheries management. In our case study, the MPs using the data on stock size and quantitative management targets (target proxy) demonstrated the highest management success rates. The most effective (100% management success rate) while least data‐demanding MPs included minlenLopt1, SPMSY, MCD, Itarget1, and ICI. We also confirmed that the performance of the data‐limited MPs was closely related to historical stock dynamics and levels of data availability. We suggest considering historical stock trends and data availability levels as critical prerequisites in the management of data‐limited fisheries. [ABSTRACT FROM AUTHOR]

Clustering is a group of unsupervised statistical techniques commonly used in many disciplines. Considering their applications to fish abundance data, many technical details need to be considered to ensure reasonable interpretation. However, the reliability and stability of the clustering methods have rarely been studied in the contexts of fisheries. This study presents an intensive evaluation of three common clustering methods, including hierarchical clustering (HC), K-means (KM), and expectation-maximization (EM) methods, based on fish community surveys in the coastal waters of Shandong, China. We evaluated the performances of these three methods considering different numbers of clusters, data size, and data transformation approaches, focusing on the consistency validation using the index of average proportion of non-overlap (APN). The results indicate that the three methods tend to be inconsistent in the optimal number of clusters. EM showed relatively better performances to avoid unbalanced classification, whereas HC and KM provided more stable clustering results. Data transformation including scaling, square-root, and log-transformation had substantial influences on the clustering results, especially for KM. Moreover, transformation also influenced clustering stability, wherein scaling tended to provide a stable solution at the same number of clusters. The APN values indicated improved stability with increasing data size, and the effect leveled off over 70 samples in general and most quickly in EM. We conclude that the best clustering method can be chosen depending on the aim of the study and the number of clusters. In general, KM is relatively robust in our tests. We also provide recommendations for future application of clustering analyses. This study is helpful to ensure the credibility of the application and interpretation of clustering methods. [ABSTRACT FROM AUTHOR]

Spatial conservation prioritization concerns trade-offs between marine conservation and resource exploitation. This approach has been increasingly used to devise spatial management strategies for fisheries because of its simplicity in the optimization model and less data requirement compared to complex dynamic models. However, most of the prioritization is based on static models or algorithms; whose solutions need to be evaluated in a dynamic approach, considering the high uncertainty and opportunity costs associated with their implementation. We developed a framework that integrates species distribution models, spatial conservation prioritization tools and a general grid-based dynamic model (Grid-DM) to support evaluation of ecological and economic trade-offs of candidate conservation plans. The Grid-DM is spatially explicit and has a tactical management focus on single species. We applied the Grid-DM to small yellow croaker (Larimichthys polyactis) in Haizhou Bay, China and validated its spatial and temporal performances against historical observations. It was linked to a spatial conservation prioritization tool Marxan to illustrate how the model can be used for conservation strategy evaluation. The simulation model demonstrated effectiveness in capturing the spatio-temporal dynamics of the target fishery as well as the socio-ecological effects of conservation measures. We conclude that the model has the capability and flexibility to address various forms of uncertainties, simulate the dynamics of a targeted fishery, and to evaluate biological and socioeconomic impacts of management plans. The modelling platform can further inform scientists and policy makers of management alternatives screening and adaptive conservation planning. [ABSTRACT FROM AUTHOR]

Keystone species play critical roles in ecological communities and ecosystem functions by interacting directly or indirectly with other species. Studies on keystone species will contribute to the understanding of community stability and mechanisms underlying ecosystem degradation. Based on a survey in Haizhou Bay and adjacent waters in 2011, the food web was constructed according to the predator–prey relationships of species. The binary network was analysed to calculate 11 network indices to identify keystone species, and removal analysis was conducted to examine the effects of the extinction of keystone species on the food web. Kendall rank correlation analysis showed that there were significant correlations between most pairs of the 11 network indices (P < 0.05). According to the results of principal component analysis of all these indices, several species, namely Leptochela gracilis , Loligo sp., Larimichthys polyactis , Alpheus japonicus and Oratosquilla oratoria , were identified as keystone species in the Haizhou Bay food web. Removal analysis suggested that the absence of keystone species may have considerable effects on the complexity and stability of the food web in Haizhou Bay. It is suggested that priority is given to the protection of keystone species in the marine ecosystem. Studies on keystone species will contribute to the understanding of community stability and mechanisms underlying ecosystem degradation. Leptochela gracilis , Loligo sp., Larimichthys polyactis , Alpheus japonicus and Oratosquilla oratoria were identified as keystone species in the Haizhou Bay food web, and their absence may have considerable effects on the complexity and stability of the Haizhou Bay food web. This study provides a scientific basis for the protection of maintenance of ecosystem health in Haizhou Bay. [ABSTRACT FROM AUTHOR]

Age‐structured data are commonly needed in stock assessments but are unavailable for the majority of existing fisheries, while fish size (length or weight) data are most readily accessible and carry critical information of population status. However, the performances of assessment methods based on size‐frequency data have been less well understood. This study evaluated the reliability of two size‐frequency‐based assessment methods in R package, s6model and TropFishR, for estimating the exploitation status of one data‐poor stock, Pholis fangi in Haizhou Bay, China. We used both simulation and empirical approaches to compare the performances of the two assessment methods in estimating F and Fmsy and examined their robustness to the stochasticity and amount of sampling data. In the simulation test, s6model and TropFishR yielded satisfactorily accurate and consistent estimates of F and Fmsy. In the empirical test, the estimated stock exploitation status varied substantially among seasons. TropfishR and s6model estimated the F/Fmsy to be 2.40 and 2.05 in spring, respectively, indicating remarkable overfishing, and 0.43 and 0.41 in fall, respectively, indicating an optimistic exploitation level. The reflected pattern was consistent with the fishery characteristics of this species. The s6model method was substantially influenced by sample size and might lead to unreasonable estimations in small samples, whereas TropFishR was relatively robust on the changes of sample size. This study highlighted the usefulness of size‐frequency methods in guiding fisheries management and provided references for their applications in data‐limited situations. [ABSTRACT FROM AUTHOR]

Systematic conservation planning (SCP) is an efficient tool to design marine protected area (MPA) networks. Although China has decades of experience in developing MPAs, its current MPA designs are limited to small spatial scales and are infrequently supported by a systematic planning approach.As one of few studies to incorporate biological and socio‐economic information in marine conservation prioritization in China, this study, targeting Haizhou Bay in China, provides a range of MPA network alternatives and evaluates the current design for four scenarios with different objectives. This corresponds to the major challenges for China's MPAs: conserve biodiversity; protect ecologically and economically important species; minimize socio‐economic costs; and reduce enforcement costs. Furthermore, this study considers the compatibility of aquaculture practices, economically critical to China's coastal regions, in MPA designs and implementations.This study determines that current MPA designs are inadequate to meet conservation objectives. For instance, existing MPAs cover less than 10% of the ranges of target species for conservation. There are substantial conservation gaps offshore.By constructing and analysing planning scenarios, this study demonstrates the trade‐offs in objectives as well as the importance of implementing SCP in China's MPA network design. Lessons learned from this study are also applicable to multi‐objective conservation prioritization in other countries. [ABSTRACT FROM AUTHOR]

Crab species are economically and ecologically important in coastal ecosystems, and their spatial distributions are pivotal for conservation and fisheries management. This study was focused on modelling the spatial distributions of three Portunidae crabs (Charybdis bimaculata, Charybdis japonica, and Portunus trituberculatus) in Haizhou Bay, China. We applied three analytical approaches (Generalized additive model (GAM), random forest (RF), and artificial neural network (ANN)) to spring and fall bottom trawl survey data (2011, 2013–2016) to develop and compare species distribution models (SDMs). Model predictability was evaluated using cross-validation based on the observed species distribution. Results showed that sea bottom temperature (SBT), sea bottom salinity (SBS), and sediment type were the most important factors affecting crab distributions. The relative importance of candidate variables was not consistent among species, season, or model. In general, we found ANNs to have less stability than both RFs and GAMs. GAMs overall yielded the least complex response curve structure. C. japonica was more pronounced in southwestern portion of Haizhou Bay, and C. bimaculata tended to stay in offshore areas. P. trituberculatus was the least region-specific and exhibited substantial annual variations in abundance. The comparison of multiple SDMs was informative to understand species responses to environmental factors and predict species distributions. This study contributes to better understanding the environmental niches of crabs and demonstrates best practices for the application of SDMs for management and conservation planning. [ABSTRACT FROM AUTHOR]

Stratified random sampling (StRS) can lead to improved precision and accuracy in estimating key fisheries population parameters, particularly when the spatial distributions of target fish populations have high heterogeneity among different strata and homogeneities within a stratum in the survey area. As the spatial distributions of many fish populations might shift in response to environmental changes and fishing activities, survey designs developed based on previous fish distribution patterns may need to be re-examined. A simulation study was conducted to evaluate the performances and consistency of 12 stratification designs for achieving multiple survey objectives, including the abundance indices of fish species and species diversity indices, for a fishery-independent survey in the coastal waters. Relative estimation error (REE), relative bias (RB) and coefficient of variation (CV) were used to measure the precision and accuracy of mean estimates values for the 12 stratification schemes. The performances of different stratification designs were likely to differ for various survey objectives. As for a multispecies survey, though the current stratification design (design 10) did not always have the lowest REE and absolute RB values, it had the most stable performances for all indices over 3 years. It indicated that the current survey design was still the optimal design according to these measurements. Thus, even though the distribution of fish populations and community composition changed over seasons and years, the current stratification design was robust and could still capture key characteristics of target fish populations and community composition. [ABSTRACT FROM AUTHOR]

Biotic interactions have been rarely included in traditional species distribution models, wherein joint species distribution models (JSDMs) emerge as a feasible approach to incorporate environmental factors and interspecific interactions simultaneously, making it a powerful tool for analyzing the structure and assembly processes of biotic communities. However, the predictability and statistical robustness of JSDMs are largely unknown because of the lack of research efforts for those newly developed models. This study systematically evaluated the performances of five JSDMs in predicting the occurrence and biomass of multiple species, with a particular focus on diverse characteristics of sampling data, including type of response variables, number of sampling sites, and the number of species included in models. In general, most models yielded satisfactory performances on fitting to observed data and on the estimation of environmental effects; however, they showed less well performances in evaluating species associations, and their predictability had large variations. The JSDMs showed inconsistent performances between the goodness‐of‐fit and predictability in cross‐validation, and the Boral model was relatively robust than others. The predictability of JSDMs was less influenced by sample sizes and substantially improved by incorporating rare species. This study contributes to an appropriate model selection and application of JSDMs. [ABSTRACT FROM AUTHOR]