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Discards represent one of the most important issues within current commercial fishing. It occurs for a range of reasons and is influenced by an even more complex array of factors. We address this issue by examining the data collected within the Danish discard observer program and describe the factors that influence discarding within the Danish Kattegat demersal fleet over the period 1997 to 2008. Generalised additive models were used to assess how discards of the 3 main target species, Norway lobster, cod and plaice, and their subcomponents (under and over minimum landings size) are influenced by important factors and their potential relevance to management. Our results show that discards are influenced by a range of different factors that are different for each species and portion of discards. We argue that knowledge about the factors influential to discarding and their use in relation to potential mitigation measures are essential for future fisheries management strategies.

Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. Thus, we suggest that disagreements among the ecosystem models will not impede their use for providing strategic advice on how to reach management objectives that go beyond the traditional maximum yield targets and for informing on the potential consequences of pursuing such objectives. This is especially true for scenarios aiming at exploiting forage fish sprat and herring, for which the agreement was the largest among our models. However, the quantitative response to altering fishing pressure differed among models. This was due to the diverse environmental covariates and the different number of trophic relationships and their functional forms considered in the models. This suggests that ecosystem models can be used to provide quantitative advice only after more targeted research is conducted to gain a deeper understanding into the relationship between trophic links and fish population dynamics in the Baltic Sea.

Fisheries can have a large impact on marine ecosystems, because the effects of removing large predatory fish may cascade down the food web. The implications of these cascading processes on system functioning and resilience remain a source of intense scientific debate. By using field data covering a 30-year period, we show for the Baltic Sea that the underlying mechanisms of trophic cascades produced a shift in ecosystem functioning after the collapse of the top predator cod. We identified an ecological threshold, corresponding to a planktivore abundance of ≈ 17 x 10₁₀ individuals, that separates 2 ecosystem configurations in which zooplankton dynamics are driven by either hydroclimatic forces or predation pressure. Abundances of the planktivore sprat above the threshold decouple zooplankton dynamics from hydrological circumstances. The current strong regulation by sprat of the feeding resources for larval cod may hinder cod recovery and the return of the ecosystem to a prior state. This calls for the inclusion of a food web perspective in management decisions.

Classifying movement behaviour of marine predators in relation to anthropogenic activity and environmental conditions is important to guide marine conservation. We studied the relationship between grey seal ( Halichoerus grypus ) behaviour and environmental variability in the southwestern Baltic Sea where seal-fishery conflicts are increasing. We used multiple environmental covariates and proximity to active fishing nets within a multivariate hidden Markov model (HMM) to quantify changes in movement behaviour of grey seals while at sea. Dive depth, dive duration, surface duration, horizontal displacement, and turning angle were used to identify travelling, resting and foraging states. The likelihood of seals foraging increased in deeper, colder, more saline waters, which are sites with increased primary productivity and possibly prey densities. Proximity to active fishing net also had a pronounced effect on state occupancy. The probability of seals foraging was highest <5 km from active fishing nets (51%) and decreased as distance to nets increased. However, seals used sites <5 km from active fishing nets only 3% of their time at sea highlighting an important temporal dimension in seal-fishery interactions. By coupling high-resolution oceanographic, fisheries, and grey seal movement data, our study provides a scientific basis for designing management strategies that satisfy ecological and socioeconomic demands on marine ecosystems.

Biological reference points (BRPs) used in fisheries management do not include density‐dependent (DD) growth, with DD processes only considered in the stock recruitment relationship. Not accounting for DD on somatic growth has led to criticism that such BRPs underestimate the compensatory effects of DD at low stock size, and therefore risk foregone catch opportunities. Here, we analyse 81 stocks from the Northeast Atlantic for evidence of DD growth, defined as the process in which stock size affects somatic weight. We evaluate the following questions: (1) How many stocks have experienced instantaneous DD growth and do stocks of the same species display similar trends? (2) Is there a common instantaneous DD growth relationship shared by all stocks? (3) For stocks exhibiting significant instantaneous DD growth, can we quantify the strength of the relationship? (4) Is DD growth operating as an intra‐cohort process as opposed to an instantaneous effect? Results reveal that only the weight of recruits exhibits a common instantaneous DD growth while the other responses analysed show a positive, noncompensatory effect, suggesting that other processes are at work. All responses examined showed significant temporal autocorrelation, which, when not accounted for, suggest apparent instantaneous DD growth in several stocks. Comparison of instantaneous against intracohort DD growth showed an increase in the number of stocks with significant DD growth, although, as for instantaneous DD growth, this declined greatly when temporal autocorrelation was accounted for. Our results counteract the a priori assumption that DD growth compensation is related only to stock biomass or density, suggesting that DD growth should be dealt case‐by‐case. Consequently, management practices that aim to fish down stock biomass with the anticipation of triggering DD growth will be associated with greater asymmetric risks than keeping biomass at levels where replacement yield does not rely on it. Around 80% of the tested key productivity parameters exhibit a positive global effect in somatic growth expressed as weight at age as opposed to the classic negative density‐dependent relationship when instantaneous growth is analysed. The frequency and strength of density‐dependence in weight at age is low and weak at the stock level when instantaneous growth is analysed. Significant temporal autocorrelation exists, which when not accounted for, reveals apparent density‐dependence in several stocks when instantaneous growth is analysed. The frequency of detection of density‐dependent weight at age increases when intracohort growth is analysed. However, even when considering intracohort growth, spurious density‐dependence in several stocks is detected when temporal autocorrelation is not accounted for, with at best 15% of the stocks exhibiting significant classic negative density‐dependence. Consequently, management practices that aim to fish down stock biomass with the anticipation of triggering density‐dependent growth, will be associated with greater asymmetric risks than keeping biomass at levels where replacement yield does not rely on it.

Fisheries management has historically focused on the population elasticity of target fish based primarily on demographic modeling, with the key assumptions of stability in environmental conditions and static trophic relationships. The predictive capacity of this fisheries framework is poor, especially in closed systems where the benthic diversity and boundary effects are important and the stock levels are low. Here, we present a probabilistic model that couples key fish populations with a complex suite of trophic, environmental, and geomorphological factors. Using 41 years of observations we model the changes in eastern Baltic cod (Gadus morhua), herring (Clupea harengus), and Baltic sprat (Sprattus sprattus balticus) for the Baltic Sea within a Bayesian network. The model predictions are spatially explicit and show the changes of the central Baltic Sea from cod- to sprat-dominated ecology over the 41 years. This also highlights how the years 2004 to 2014 deviate in terms of the typical cod–environment relationship, with environmental factors such as salinity being less influential on cod population abundance than in previous periods. The role of macrozoobenthos abundance, biotopic rugosity, and flatfish biomass showed an increased influence in predicting cod biomass in the last decade of the study. Fisheries management that is able to accommodate shifting ecological and environmental conditions relevant to biotopic information will be more effective and realistic. Non-stationary modelling for all of the homogeneous biotope regions, while acknowledging that each has a specific ecology relevant to understanding the fish population dynamics, is essential for fisheries science and sustainable management of fish stocks.

Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes.

Unintentional mortality of higher trophic‐level species in commercial fisheries (bycatch) represents a major conservation concern as it may influence the long‐term persistence of populations. An increasingly common strategy to mitigate bycatch of harbor porpoises (Phocoena phocoena), a small and protected marine top predator, involves the use of pingers (acoustic alarms that emit underwater noise) and time‐area fishing closures. Although these mitigation measures can reduce harbor porpoise bycatch in gillnet fisheries considerably, inference about the long‐term population‐level consequences is currently lacking. We developed a spatially explicit individual‐based simulation model (IBM) with the aim to evaluate the effectiveness of these two bycatch mitigation measures. We quantified both the direct positive effects (i.e., reduced bycatch) and any indirect negative effects (i.e., reduced foraging efficiency) on the population size using the inner Danish waters as a biological system. The model incorporated empirical data on gillnet fishing effort and noise avoidance behavior by free‐ranging harbor porpoises exposed to randomized high‐frequency (20‐ to 160‐kHz) pinger signals. The IBM simulations revealed a synergistic relationship between the implementation of time‐area fishing closures and pinger deployment. Time‐area fishing closures reduced bycatch rates substantially but not completely. In contrast, widespread pinger deployment resulted in total mitigation of bycatch but frequent and recurrent noise avoidance behavior in high‐quality foraging habitat negatively affected individual survival and the total population size. When both bycatch mitigation measures were implemented simultaneously, the negative impact of pinger noise‐induced sub‐lethal behavioral effects on the population was largely eliminated with a positive effect on the population size that was larger than when the mitigation measures were used independently. Our study highlights that conservationists and policy makers need to consider and balance both the direct and indirect effects of harbor porpoise bycatch mitigation measures before enforcing their widespread implementation. Individual‐based simulation models, such as the one presented here, offer an efficient and dynamic framework to evaluate the impact of human activities on the long‐term survival of marine populations and can serve as a basis to design adaptive management strategies that satisfy both ecological and socioeconomic demands on marine ecosystems.

Spatio-temporal density-dependent processes are crucial regulatory factors for natural populations. However, there is a lack of studies addressing spatial density-dependence in fish growth. A previous investigation has suggested spatio-temporal density-dependence in body condition of Baltic sprat. Here, we used different techniques, such as centre of gravity, distance, and homogeneity indices, to better characterize the spatial and temporal variations in sprat density and body condition in the Baltic Proper. Our results evidenced a negative spatio-temporal co-variation between the centres of gravity of density and maximum condition. In the 1980s-early 1990s both centres were located in the middle of the Baltic Proper. From the mid 1990s the centres progressively separated in space, as the sprat population moved towards the north-eastern Baltic Proper, and the centre of maximum condition towards the south-western areas. Moreover, at low abundances, sprat density and condition were homogeneously distributed in space, whereas at high abundances both density and condition showed pronounced geographical gradients. The ecological processes potentially explaining the observed patterns were discussed in the light of the Ideal Free Distribution theory. We provide evidence that the shift in the spatial distribution of cod, the main predator of sprat, has been the main factor triggering the overall spatial changes in sprat density, and thus condition, during the past thirty years. The spatial indices shown here, synthesizing the spatio-temporal patterns of fish distribution, can support the implementation of the EU Marine Strategy Framework Directive.

To effectively future-proof the management of the European Union fishing fleets we have explored a suite of case studies encompassing the northeast and tropical Atlantic, the Mediterranean, Baltic and Black Seas. This study shows that European Union (EU) fisheries are likely resilient to climate-driven short-term stresses, but may be negatively impacted by long-term trends in climate change. However, fisheries’ long-term stock resilience can be improved (and therefore be more resilient to increasing changes in climate) by adopting robust and adaptive fisheries management, provided such measures are based on sound scientific advice which includes uncertainty. Such management requires regular updates of biological reference points. Such updates will delineate safe biological limits for exploitation, providing both high long-term yields with reduced risk of stock collapse when affected by short-term stresses, and enhanced compliance with advice to avoid higher than intended fishing mortality. However, high resilience of the exploited ecosystem does not necessarily lead to the resilience of the economy of EU fisheries from suffering shocks associated with reduced yields, neither to a reduced carbon footprint if fuel use increases from lower stock abundances. Fuel consumption is impacted by stock development, but also by changes in vessel and gear technologies, as well as fishing techniques. In this respect, energy-efficient fishing technologies already exist within the EU, though implementing them would require improving the uptake of innovations and demonstrating to stakeholders the potential for both reduced fuel costs and increased catch rates. A transition towards reducing fuel consumption and costs would need to be supported by the setup of EU regulatory instruments. Overall, to effectively manage EU fisheries within a changing climate, flexible, adaptive, well-informed and well-enforced management is needed, with incentives provided for innovations and ocean literacy to cope with the changing conditions, while also reducing the dependency of the capture fishing industry on fossil fuels. To support such management, we provide 10 lessons to characterize ‘win-win’ fishing strategies for the European Union, which develop leverages in which fishing effort deployed corresponds to Maximum Sustainable Yield targets and Common Fisheries Policy minimal effects objectives. In these strategies, higher catch is obtained in the long run, less fuel is spent to attain the catch, and the fisheries have a higher resistance and resilience to shock and long-term factors to face climate-induced stresses.