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Temporal variability in abundance and composition of species in marine ecosystems results from a combination of internal processes, external drivers, and stochasticity. One way to explore the temporal variability in an ecosystem is through temporal stability, measured using the inverse of the coefficient of variation for biomass of single species. The effect of temperature and fisheries on the variability of the Barents Sea food web is still poorly understood. To address this question, we simulate the possible dynamics of Barents Sea food web under different temperature and fishery scenarios using a simple food‐web model (Non‐Deterministic Network Dynamic [NDND]). The NDND model, which is based on chance and necessity (CaN), defines the state space of the ecosystem using its structural constraints (necessity) and explores it stochastically (chance). The effects of temperature and fisheries on stability are explored both separately and combined. The simulation results suggest that increasing temperature has a negative effect on species biomass and increasing fisheries triggers compensatory dynamics of fish species. There is a major intra‐scenario variability in temporal stability, while individual scenarios of temperature and fisheries display a weak negative impact and no effect on stability, respectively. However, combined scenarios indicate that fisheries amplify the effects of temperature on stability, while increasing temperature leads to a shift from synergistic to antagonistic effects between these two drivers. [ABSTRACT FROM AUTHOR]

Climate change impacts are pronounced at high latitudes, where warming, reduced sea-ice-cover, and ocean acidification affect marine ecosystems. We review climate change impacts on two major gateways into the Arctic: the Bering and Chukchi seas in the Pacific and the Barents Sea and Fram Strait in the Atlantic. We present scenarios of how changes in the physical environment and prey resources may affect commercial fish populations and fisheries in these high-latitude systems to help managers and stakeholders think about possible futures. Predicted impacts include shifts in the spatial distribution of boreal species, a shift from larger, lipid-rich zooplankton to smaller, less nutritious prey, with detrimental effects on fishes that depend on high-lipid prey for overwinter survival, shifts from benthic- to pelagic-dominated food webs with implications for upper trophic levels, and reduced survival of commercially important shellfish in waters that are increasingly acidic. Predicted changes are expected to result in disruptions to existing fisheries, the emergence of new fisheries, new challenges for managing transboundary stocks, and possible conflicts among resource users. Some impacts may be irreversible, more severe, or occur more frequently under anthropogenic climate change than impacts associated with natural variability, posing additional management challenges. [ABSTRACT FROM AUTHOR]

The Barents Sea is a subarctic shelf sea which has experienced major changes during the past decades. From ecological time-series, three different food-web configurations, reflecting successive shifts of dominance of pelagic fish, demersal fish, and zooplankton, as well as varying trophic control have been identified in the last decades. This covers a relatively short time-period as available ecological time-series are often relatively short. As we lack information for prior time-periods, we use a chance and necessity model to investigate if there are other possible configurations of the Barents Sea food-web than those observed in the ecological time-series, and if this food-web is characterized by a persistent trophic control. We perform food-web simulations using the Non-Deterministic Network Dynamic model (NDND) for the Barents Sea, identify food-web configurations and compare those to historical reconstructions of food-web dynamics. Biomass configurations fall into four major types and three trophic pathways. Reconstructed data match one of the major biomass configurations but is characterized by a different trophic pathway than most of the simulated configurations. The simulated biomass displays fluctuations between bottom-up and top-down trophic control over time rather than persistent trophic control. Our results show that the configurations we have reconstructed are strongly overlapping with our simulated configurations, though they represent only a subset of the possible configurations of the Barents Sea food-web. [ABSTRACT FROM AUTHOR]

Norwegian spring‐spawning herring (NSSH, Clupea harengus) is a key species in the food‐web and for fisheries in the north‐east Atlantic. NSSH has been the focus of many ecological and fisheries studies over decades and several hypotheses have been put forward to explain variations in its recruitment. We conducted an extensive literature review of the processes that have been hypothesized to control recruitment at age‐2 years. From this review, we constructed a conceptual model to represent how these processes are inter‐connected. We then evaluated several of these hypothesized processes using quantile regression modelling and the most recent available data series as input. Most of the hypotheses were not supported by our analyses. Only two hypotheses were supported: the top‐down control of herring larval stage by Atlantic mackerel (Scomber scombrus) and the positive effect of temperature on recruitment. For the latter the interpretation of the results is nevertheless ambiguous when the latest years (1998–2018) of observations are included, as the correlation then changes from positive to negative. Furthermore, when retesting the hypotheses on age‐2 years estimates, we observe a benefitting effect of a consistent strong forcing of the Norwegian Coastal Current and a possible positive effect of the NSSH spawning stock on recruitment. How much these hypotheses can be used to make predictions about future recruitment of herring remains to be tested but based on our results, the relatively short time series available and the dispersion of the observations around the regression models, we can anticipate that such predictions would have limited use for the purpose of fisheries assessment and management. [ABSTRACT FROM AUTHOR]

We propose a trend estimation and classification (TREC) approach to estimating dominant common trends among multivariate time series observations. Our methods are based on two statistical procedures that includes trend modelling and discriminant analysis for classifying similar trend (common trend) classes. We use simulations to evaluate the proposed approach and compare it with a relevant dynamic factor analysis in the time domain, which was recently proposed to estimate common trends in fisheries time series. We apply the TREC approach to the multivariate short time series datasets investigated by the ICES integrated assessment working groups for the Norwegian Sea and the Barents Sea. The proposed approach is robust for application to short time series, and it directly identifies and classifies the dominant trends underlying observations. Based on the classified trend classes, we suggest that communication among stakeholders like marine managers, industry representatives, non-governmental organizations, and governmental agencies can be enhanced by finding the common tendency between a biological community in a marine ecosystem and the environmental factors, as well as by the icons produced by generalizing common trend patterns. [ABSTRACT FROM AUTHOR]

Nearly 30 years ago, emerged the concept of deterministic chaos. With it came sensitivity to initial conditions, nonlinearities, and strange attractors. This constituted a paradigm shift that profoundly altered how numerical modellers approached dynamic systems. It also provided an opportunity to resolve a situation of mutual misunderstanding between scientists and non-scientists about uncertainties and predictability in natural systems. Our proposition is that this issue can be addressed in an original way which involves modelling based on the principles of chance and necessity (CaN). We outline the conceptual and mathematical principles of CaN models and present an application of the model to the Barents Sea food-web. Because CaN models rely on concepts easily grasped by all actors, because they are explicit about knowns and unknowns and because the interpretation of their results is simple without being prescriptive, they can be used in a context of participatory management. We propose that, three decades after the emergence of chaos theories, CaN can be a practical step to reconcile scientists and non-scientists around the modelling of structurally and dynamically complex natural systems, and significantly contribute to ecosystem-based fisheries management. [ABSTRACT FROM AUTHOR]

Anticipating future changes in marine social‐ecological systems (MSES) several decades into the future is essential in the context of accelerating global change. This is challenging in situations where actors do not share common understandings, practices, or visions about the future. We introduce a dedicated scenario method for the development of MSES scenarios in a participatory context. The objective is to allow different actors to jointly develop scenarios which contain their multiple visions of the future. The method starts from four perspectives: "fisheries management," "ecosystem," "ocean climate," and "global context and governance" for which current status and recent trends are summarized. Contrasted scenarios about possible futures are elaborated for each of the four single perspectives before being integrated into multiple‐perspective scenarios. Selected scenarios are then developed into storylines. Focusing on individual perspectives until near the end allows actors with diverse cultures, interests and horizons to confront their own notions of the future. We illustrate the method with the exploration of the futures of the Barents Sea MSES by 2050. We emphasize the following lessons learned: first, many actors are not familiar with scenario building and attention must be paid to explaining the purpose, methodology, and benefits of scenarios exercises. Second, although the Barents Sea MSES is relatively well understood, uncertainties about its future are significant. Third, it is important to focus on unlikely events. Fourth, all perspectives should be treated equally. Fifth, as MSES are continuously changing, we can only be prepared for future changes if we collectively keep preparing. [ABSTRACT FROM AUTHOR]

Multivariate analyses constitute an integral part of today's marine integrated ecosystem assessments (IEAs). Principal component analysis (PCA) is one of the most common of these techniques, and the method has been used repeatedly to summarize the dynamics of marine ecosystems. There seems to be little recognition of the potential pitfalls associated with performing PCA on time-series that are autocorrelated and/or non-stationary. We investigate how the descriptive performance of PCAs may be affected by the structure of the underlying timeseries and question whether such analyses can provide useful summaries of ecosystem trajectories. For this purpose, we reanalyse four datasets from the Barents, Norwegian, Baltic, and North Seas. We compare the results with those obtained from simulated datasets that share similar trend and autocorrelation properties, but in which the variables are unrelated. We show that most of the patterns revealed by the PCA can emerge from random time-series and that the fraction of the variance that cannot be accounted for by random processes is minimal. The Norwegian Sea dataset is a pathological case in which the variance explained by the first two components only exceeds what would be expected from randomly simulated time-series by 2%. We conclude that outputs from explorative multivariate analyses provide very little insight into ecosystem status, trajectories and functioning. IEA groups need to be equipped with methods that can provide better insight into how marine ecosystems function, the drivers of their changes and their possible future trajectories. [ABSTRACT FROM AUTHOR]

A food web topology describes the diversity of species and their trophic interactions, i.e. who eats whom, and structural analysis of food web topologies can provide insight into ecosystem structure and function. It appears simple, at first sight, to list all species and their trophic interactions. However, the very large number of species at low trophic levels and the impossibility to monitor all trophic interactions in the ocean makes it impossible to construct complete food web topologies. In practice, food web topologies are simplified by aggregating species into groups termed trophospecies. It is not clear though, how much simplified versions of food webs retain the structural properties of more detailed networks. Using the most comprehensive Barents Sea food web to date, we investigate the performance of methods to construct simplified food webs using three approaches: taxonomic, structural and regular clustering. We then evaluate how topological properties vary with the level of network simplification. Results show that alteration of food web structural properties due to aggregation are highly sensitive to the methodology used for grouping species and trophic links. In the specific case of the Barents Sea, we show that it is possible to preserve key structural properties of the original complex food web in simplified versions when using taxonomic or structural clustering combined with intermediate 25% linkage for trophic aggregation. [ABSTRACT FROM AUTHOR]

Beaked redfish (Sebastes mentella) is one of the few commercially important fish species producing living offspring. Like many other deep-water fishes, it is slow growing, late maturing and long-lived, getting as old as 65 years or even 75 years in some populations. The stock in the Norwegian and Barents Seas is analytically assessed since 2012, assuming a natural mortality (M) of 0.05 yr−1 across all ages, based on Hoenig's longevity related estimator. Since then, several reviews and new studies have been published, affording a re-evaluation of the natural mortality in the assessment model. We estimated natural mortality of beaked redfish using 48 different estimators in two categories, either estimating M across the population or dependent on age, length or weight. The obtained estimates were highly variable, ranging from 0.01 to 0.32 yr−1 for estimates across the population, and 0.05–0.62 yr−1 for age or size dependent median- M. These wide ranges demonstrate the sensitivity of SSB to the input parameters as well as the pitfalls of using estimators developed for distant taxa. Of the 48 estimates, 20 were considered as potential candidates for updating the stock assessment model, yet not all of these were realistic. The frequency distribution of the estimators showed a peak around a value of 0.07 yr−1, lowering the estimated spawning stock biomass in the last year by about 300 kt but keeping it above the precautionary reference point for the stock. Estimators across the life-history of beaked redfish indicate a potential underestimation of natural mortality for early and overestimation for late age classes. Age and size related estimators are promising for the older ages but tend to extreme estimates for the early ages, which deserves further investigation. [ABSTRACT FROM AUTHOR]

Understanding and predicting patterns arising from the dynamics of marine food webs is central to trophic and community ecology and numerical models of food webs constitute a primary tool to simulate these dynamics. Food web simulation models are often highly complex while at the same time often too constrained to reproduce the level of variability observed in real systems. The recently developed non-deterministic network dynamics (NDND) modelling framework has been suggested as a simulation alternative, which can generate multiple patterns of food web variability despite great structural simplicity. Two important aspects of the NDND modelling framework remain unexplored: first the derivation of model input parameters from empirical or theoretical studies and second the evaluation of the model simulations against observations. We provide a methodology for the derivation of model parameters based on empirical observations, the metabolic theory of ecology and life-history theory and apply it to the specific case of the Barents Sea food web. We then evaluate the ability of the NDND simulations to reproduce a wide range of patterns of food web dynamics against observations collected in the Barents Sea during 28 years. Patterns emerging from the simulations include trends and cycles in biomass, trophic levels and transfer efficiency, density-dependent growth, top-down vs bottom-up oscillations, ecosystem level stability and synchrony and trophic functional responses. The ability of the NDND to generate so many patterns observed empirically in the Barents Sea is remarkable given that it is based only on random trophic interactions operating within few constraints set by ecological rules. Our results show that investigations of food web dynamics in marine ecosystems, including the definition of reference states and responses to climate and exploitation pressures, may be achieved with models that are structurally simple and based on few well-established assumptions. [ABSTRACT FROM AUTHOR]

This paper explores the stochastic dynamics of a simple foodweb system using a network model that mimics interacting species in a biosystem. It is shown that the system can be described by a set of ordinary differential equations with real-valued uncertain parameters, which satisfy a set of linear inequality constraints. The constraints restrict the solution space to a bounded convex polytope. We present results from numerical experiments to show how the stochasticity and uncertainty characterizing the system can be captured by sampling the interior of the polytope with a prescribed probability rule, using the Hit-and-Run algorithm. The examples illustrate a parsimonious approach to modeling complex biosystems under vague knowledge. [ABSTRACT FROM AUTHOR]

• Complex ecological models are increasingly used for societal purpose. • It is challenging for users to appraise the performance of model applications. • The OPE protocol (Objectives, Patterns, Evaluation) documents model evaluation. • It promotes standardisation and transparency of model evaluation. • The OPE can guide modelling developments and reviews of ecological modelling studies. Numerical models of ecological systems are increasingly used to address complex environmental and resource management questions. One challenge for scientists, managers, and stakeholders is to appraise how well suited these models are to answer questions of scientific or societal relevance, that is, to perform, communicate, or access transparent evaluations of ecological models. While there have been substantial developments to support standardised descriptions of ecological models, less has been done to standardise and to report model evaluation practices. We present here a general protocol designed to guide the reporting of model evaluation. The protocol is organised in three major parts: the objective(s) of the modelling application, the ecological patterns of relevance and the evaluation methodology proper, and is termed the OPE (objectives, patterns, evaluation) protocol. We present the 25 questions of the OPE protocol which address the many aspects of the evaluation process and then apply them to six case studies based on a diversity of ecological models. In addition to standardising and increasing the transparency of the model evaluation process, we find that going through the OPE protocol helps modellers to think more deeply about the evaluation of their models. From this last point, we suggest that it would be highly beneficial for modellers to consider the OPE early in the modelling process, in addition to using it as a reporting tool and as a reviewing tool. [ABSTRACT FROM AUTHOR]

Using numerical models to project the state of marine ecosystems several decades into the future is commonly advocated, in particular for investigating the possible effects of climate change. Numerical models are useful to explore how ocean climate and other drivers may regulate the dynamics of marine ecosystems and constitute indispensable tools to test our conceptual representations of how marine systems function. However, I argue here that these models might be of limited use to project the future state of marine ecosystems decades into the future because several factors limit predictability. These include stochasticity, deterministic chaos, enablement vs. entailment, non-ergodicity, ecological surprises, irreducibility, and limits to upscaling. Many simulations of ecosystem states in the distant future may be no more than a "grande illusion" until explicit evaluations of how uncertainties increase with the time horizon of projection are performed. [ABSTRACT FROM AUTHOR]

Biodiversity is an increasingly important issue for the management of marine ecosystems. However, the proliferation of biodiversity indices and difficulties associated with their interpretation have resulted in a lack of clearly defined framework for quantifying biodiversity and biodiversity changes in marine ecosystems for assessment purpose. Recent theoretical and numerical developments in biodiversity statistics have established clear algebraic relationships between most of the diversity measures commonly used, and have highlighted those that most directly relates to the concept of biological diversity, terming them "true" diversity measures. In this study, we implement the calculation of these "true" diversity measures at the scale of a large-marine ecosystem, the Barents Sea. We applied hierarchical partitioning of biodiversity to an extensive dataset encompassing 10 years of trawl-surveys for both pelagic and demersal fish community. We quantify biodiversity and biodiversity changes for these two communities across the whole continental shelf of the Barents Sea at various spatial and temporal scales, explicitly identifying areas where fish communities are stable and variable. The method is used to disentangle areas where community composition is subject to random fluctuations from areas where the fish community is drifting over time. We discuss how our results can serve as a spatio-temporal biodiversity baseline against which new biodiversity estimates, derived from sea surveys, can be evaluated. [ABSTRACT FROM AUTHOR]

A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as ‘null models of food-webs’ as originally advocated. [ABSTRACT FROM AUTHOR]

Beaked redfish inhabits North Atlantic waters in the depth range 100–950 m, over the continental shelf, slope and the open ocean. Individuals can live demersal or pelagic, at various stages of their life cycle. The geographical distribution of the species extends to most of the Atlantic waters from Newfoundland and the Labrador basin in the west to the Barents Sea in the east. Monitoring beaked redfish is challenging because of the species wide geographical distribution and large scale migrations; deep distribution, which complicates trawling and hydroacoustic surveys; difficulties with tagging; and persistent difficulties in taxonomic identification. These challenges make it a particularly problematic species to observe with conventional research methods. We review these key challenges and provide recommendations for the coordinated observation of Sebastes mentella in the North Atlantic that would best contribute to the assessment and ecological research on this species. [ABSTRACT FROM AUTHOR]

An assessment of the potential for 17 fish or shellfish stocks or stock groups to move from the sub- Arctic areas into the Arctic Ocean was conducted. A panel of 34 experts was convened to assess the impact of climate change on the potential movement of the 17 stocks or stock groups. The panel considered the exposure of species to climate change, the sensitivity of species to these changes and the adaptive capacity of each stock or stock group. Based on expert opinions, the potential for expansion or movement into the Arctic was qualitatively ranked (low potential, potential, high potential). It is projected that the Arctic Ocean will become ice-free during the summer season, and when this happens new areas will open up for plankton production, which may lead to new feeding areas for fish stocks. Five stocks had a low potential to move to, or expand in, the high Arctic. Six species are considered as potential candidate species to move to, or expand in, the high Arctic. Six stocks had a high potential of establishing viable resident populations in the region. These six stocks exhibit life history characteristics that allow them to survive challenging environmental conditions that will continue to prevail in the north. This study suggests that several life history factors should be considered when assessing the potentiality of a species moving in response to changing climate conditions. [ABSTRACT FROM AUTHOR]

Planque, B., Bellier, E., and Loots, C. 2011. Uncertainties in projecting spatial distributions of marine populations. – ICES Journal of Marine Science, 68: 1045–1050.Projection of future spatial distributions of marine populations is a central issue for ecologists and managers. The measure of projection uncertainty is particularly important, because projections can only be useful if they are given with a known and sufficiently high level of confidence. Uncertainties can arise for the observation process, conceptual and numerical model formulations, parameter estimates, model evaluation, appropriate consideration of spatial and temporal scales, and finally the potential of adaptation of living systems. Comprehensive analyses of these multiple sources of uncertainty have not been carried out so far, and how these uncertainties are considered in current studies has not yet been described. To analyse how these different sources of uncertainty are currently considered in marine research, we did a survey of published literature during the period 2005–2009. From the 75 publications selected, we calculated how frequently each type of uncertainty was considered. We found that little attention is given to most sources of uncertainty, except for uncertainty in parameter estimates. As a result, most current projections are expected to be far less reliable than usually assumed. The conclusion is that, unless uncertainty can be better accounted for, such projections may be of limited use, or even risky to use for management purposes. [ABSTRACT FROM PUBLISHER]

Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of species distribution as a function of environmental constraints, models of animal movements (MAMs) have focussed on the dynamic nature of spatial distribution of groups of individuals under a number of constraints external and internal to the population. Besides SDMs and MAMs, modelling the spatial distribution of fish populations can be achieved by models that are fundamentally static (like SDMs) but can also incorporate many hypotheses on the control of fish spatial distribution (like MAMs). The hypotheses underlying these models need to make sense at the population level - rather than at the individual or species level -we term these 'population distribution models' (PDMs). PDMs are statistical models that rely on several hypotheses, which include: (i) control through geographical attachment, (ii) environmental conditions, (iii) density-dependent habitat selection, (iv) spatial dependency, (v) population demographic structure, (vi) species interactions and (vii) population memory. We review the basis behind each of these conceptual models and we examine corresponding numerical applications. We argue that the conceptual models are complementary rather than competing, that existing numerical applications are still rarely compared and combined, and that PDMs can offer a statistical framework to achieve this. We recommend that the numerical models associated with different hypotheses be constructed within such a common general framework. This will permit evaluation, comparison and combination of the multiple hypotheses on fish spatial distribution. It will ultimately lead to a more comprehensive understanding of the factors controlling the spatial distribution of fish populations and to more accurate predictions in which model uncertainty is accounted for. [ABSTRACT FROM AUTHOR]

Abstract: Evidence has accumulated that climate variability influences the state and functioning of marine ecosystems. At the same time increasing pressure from exploitation and other human activities has been shown to impact exploited and non-exploited species and potentially modify ecosystem structure. There has been a tendency among marine scientists to pose the question as a dichotomy, i.e., whether (1) “natural” climate variability or (2) fishery exploitation bears the primary responsibility for population declines in fish populations and the associated ecosystem changes. However, effects of both climate and exploitation are probably substantially involved in most cases. More importantly, climate and exploitation interact in their effects, such that climate may cause failure in a fishery management scheme but that fishery exploitation may also disrupt the ability of a resource population to withstand, or adjust to, climate changes. Here, we review how exploitation, by altering the structure of populations and ecosystems, can modify their ability to respond to climate. The demographic effects of fishing (removal of large-old individuals) can have substantial consequences on the capacity of populations to buffer climate variability through various pathways (direct demographic effects, effects on migration, parental effects). In a similar way, selection of population sub-units within meta-populations may also lead to a reduction in the capacity of populations to withstand climate variability and change. At the ecosystem level, reduced complexity by elimination of species, such as might occur by fishing, may be destabilizing and could lead to reduced resilience to perturbations. Differential exploitation of marine resources could also promote increased turnover rates in marine ecosystems, which would exacerbate the effects of environmental changes. Overall (and despite the specificities of local situations) reduction in marine diversity at the individual, population and ecosystem levels will likely lead to a reduction in the resilience and an increase in the response of populations and ecosystems to future climate variability and change. Future management schemes will have to consider the structure and functioning of populations and ecosystems in a wider sense in order to maximise the ability of marine fauna to adapt to future climates. [Copyright &y& Elsevier]

Large amplitude variations in recruitment of small pelagic fish result from interactions between a fluctuating environment and population dynamics processes such as spawning. The spatial extent and location of spawning, which is critical to the fate of eggs and larvae, can vary strongly from year to year, as a result of changing population structure and environmental conditions. Spawning habitat can be divided into ‘potential spawning habitat’, defined as habitat where the hydrographic conditions are suitable for spawning, ‘realized spawning habitat’, defined as habitat where spawning actually occurs, and ‘successful spawning habitat’, defined as habitat from where successful recruitment has resulted. Using biological data collected during the period 2000–2004, as well as hydrographic data, we investigate the role of environmental parameters in controlling the potential spawning habitat of anchovy and sardine in the Bay of Biscay. Anchovy potential spawning habitat appears to be primarily related to bottom temperature followed by surface temperature and mixed-layer depth, whilst surface and bottom salinity appear to play a lesser role. The possible influence of hydrographic factors on the spawning habitat of sardine seems less clear than for anchovy. Modelled relationships between anchovy and sardine spawning are used to predict potential spawning habitat from hydrodynamical simulations. The results show that the seasonal patterns in spawning are well reproduced by the model, indicating that hydrographic changes may explain a large fraction of spawning spatial dynamics. Such models may prove useful in the context of forecasting potential impacts of future environmental changes on sardine and anchovy reproductive strategy in the north-east Atlantic. [ABSTRACT FROM AUTHOR]

The spatial extent of small pelagic fish spawning habitat is influenced by environmental factors and by the state of the adult population. In return, the configuration of spawning habitat affects recruitment and therefore the future structure of the adult population. Interannual changes in spatial patterns of spawning reflect variations in adult population structures and their environment. The present study describes the historical changes in the spatial distribution of spawning of anchovy ( Engraulis encrasicolus) and sardine ( Sardina pilchardus) in the Bay of Biscay during two periods: 1967–72 and 2000–2004. Using data from egg surveys conducted in spring, the spatial distributions of anchovy and sardine eggs are characterized by means of geostatistics. For each survey, a map of probability of egg presence is constructed. The maps are then compared to define (1) recurrent spawning areas, (2) occasional spawning areas and (3) unfavourable spawning areas during each period. Sardine spawning habitat is generally fragmented and appears spatially limited by the presence of cold bottom water. It is confined to coastal or shelf break refuge areas in years of restricted spawning extent. For anchovy, recurrent spawning sites are found in Gironde and Adour estuaries whilst spawning can extend further offshore in years of more intense spawning. For both species, the mean pattern of spawning has changed between 1967–72 and 2000–2004. Noticeably, the spatial distribution of anchovy eggs in spring has expanded northward. This trend possibly results from changes in environmental conditions during the last four decades. [ABSTRACT FROM AUTHOR]

In the more than 50 years that the Continuous Plankton Recorder (CPR) survey has operated on a regular monthly basis in the north-east Atlantic and North Sea, large changes have been witnessed in the planktonic ecosystem. These changes have taken the form of long-term trends in abundance for certain species or stepwise changes for others, and in many cases are correlated with a mode of climatic variability in the North Atlantic, either: (1) the North Atlantic Oscillation (NAO), a basin-scale atmospheric alteration of the pressure field between the Azores high pressure cell and the Icelandic Low; or (2) the Gulf Stream Index (GSI), which measures the latitudinal position of the north wall of the Gulf Stream. Recent work has shown that the changes in the GSI are coupled with the NAO and Pacific Southern Oscillation with a 2 year lag. The plankton variability is also possibly linked to changes observed in the distribution and flux of water masses in the surface, intermediate and deep waters of the North Atlantic. For example, in the last two decades, the extent and location of the formation of North Atlantic Deep Water, Labrador Sea Intermediate Water and Norwegian Sea intermediate and upper-layer water has altered considerably. This paper discusses the extent to which observed changes in plankton abundance and distribution may be linked to this basin-scale variability in hydrodynamics. The results are also placed within the context of global climate warming and the possible effects of the observed melting of Arctic permafrost and sea ice on the subpolar North Atlantic. [ABSTRACT FROM AUTHOR]

Examines large scale spatial variations in the seasonal cycle of near-surface abundance of the copepod Calanus finmarchicus in the North Atlantic and the adjacent seas. Spatio-temporal dynamics of C. finmarchicus; Effect of temperature on seasonal pattern changes of food availability.

A food web is an ecological network and its topological description consists of the list of nodes, i.e., trophospecies, the list of links, i.e., trophic interactions, and the direction of interactions (who is the prey and who is the predator). Food web topologies are widely used in ecology to describe structural properties of communities or ecosystems. The selection of trophospecies and trophic interactions can be realized in different manners so that many different food webs may be constructed for the same community. In the Barents Sea, many simple food webs have been constructed. We present a comprehensive food web topology for the Barents Sea ecosystem, from plankton to marine mammals. The protocol used to compile the data set includes rules for the selection of taxa and for the selection and documentation of the trophic links. The resulting topology, which includes 244 taxa and 1589 trophic links, can serve as a basis for topological analyses, comparison with other marine ecosystems, or as a basis to build simulation models of the Barents Sea ecosystem. The data set consists of three related tables: (1) the hst of taxa, (2) the list of pairwise interactions, and (3) the list of bibliographical references. [ABSTRACT FROM AUTHOR]

Aim This study focuses on the influence of methodological choices on the predictive performance of macroecological models ( MEMs), i.e. statistical models designed to predict patterns of biodiversity using environmental predictors. We emphasize the influence of three methodological choices: (1) the choice of the currency in which the abundance of each species is measured, i.e. numbers of individuals or biomass; (2) the rules used to define the species assemblage under focus, i.e. broad communities or refined ecological guilds; and (3) the influence of rare over common species in the biodiversity measure. Location The effects of these choices are investigated using an exhaustive dataset on the fish fauna of the continental shelf of the Barents Sea. Methods We conducted an analysis of 220 models resulting from all possible combinations of the three methodological choices. For each, we evaluated the predictive performance through an iterative cross-validation process. Results All methodological choices we investigated strongly affected the predictive performance of MEMs. High predictive performances were obtained when using biomass instead of numbers of individuals, when focusing on narrow ecological guilds composed of species sharing the same ecological traits and when using diversity measures that give high weight to rare species. Main conclusions We recommend that future projections of biodiversity pay more attention to abundance currency, ecological homogeneity of focal species assemblages and the diversity metric used, and systematically investigate these methodological choices prior to producing biodiversity forecasts. Splitting a whole set of species into ecological guilds appears to be a promising practice, leading to a selected set of MEMs with high predictive performances and more detailed forecasts on the fate of diversity. [ABSTRACT FROM AUTHOR]

The processes that control the spatial distribution of North Sea whiting ( Merlangius merlangus) spawning adults are investigated using a statistical multi-model approach. Models of external and internal controls on the population, such as environmental conditions, spatial constraints, present or past spatial distribution, and demographic state of the population, are evaluated, compared and ranked to select those that are the best able to predict the observed distribution of spawning adults. Model selection is greatly influenced by the selection method, either based on data fitting or prediction, as well as by the threshold value used to stop the selection. Model selection based on prediction tends to select simpler models than selection based on data fitting. The hypotheses underlying the selected models are inferred to play a significant role in controlling North Sea whiting spatial distribution. The multi-model inference approach developed in this study enables comparison of several theoretical concepts and hypotheses and the results provide important clues on the processes involved in the control of the spatial distribution of whiting. We conclude that whiting has a high spatial fidelity to spawning site which can be linked to either geographical attachment or year-to-year persistence of the spatial distribution of the population. Environmental factors - temperature and salinity - appear to influence the geographical extent of spawning whiting distribution, whereas local abundance levels are primarily controlled by internal factors, i.e., population size and spatial segregation between ages. [ABSTRACT FROM AUTHOR]

Modelling habitat of species necessitates robust identification of relevant environmental variables linked to species distribution. To achieve this, we connect hierarchical patch theory and habitat modelling at multiple scales. We suggest discriminating between ‘circumstancial variables’ and ‘process variables’ on the basis of temporal evolution of the spatial links between species distribution and their environment at different scales. ‘Process variables’ are informative of the ecological processes driving the distribution of organisms at multiple scales. By opposition, ‘circumstantial variable’ provide little insight because their relationship with animal spatial distribution is subject to great variations through time. As a real case study, we investigate the relationships between auk distribution (mainly Uria aalge) and oceanographic landscapes over two scales (i.e. large ∼ 200 km and medium ∼ 50 km) during the wintering season in the Bay of Biscay. Surface salinity, mixed layer depth and chlorophyll a are identified as ‘process variables’ as they are invariably correlated with the spatial distribution of auks, whereas bottom temperature can be viewed as a ‘circumstantial variable’ since the correlation is non-constant through time at large scale. The process variables at large scale are used to model the potential habitat of auks in the Bay of Biscay during the wintering season. At medium scale, only the chlorophyll a is identified as ‘process variable’ and used to model preferential habitat of wintering auks in the Bay of Biscay. The analytical approach proposed here (i.e. multivariate factorial kriging in a temporal context) is an effective framework to model the potential and preferential habitat of a species and can be related to the ecological niche concept and by focusing explicitly on scale dependence, the distinction between the variables that can be used as niche descriptors into species distribution models. Then our method lead to the identification of variables that should be used to define the Grinnellian niche which is defined by environmental conditions on broad scales and the Eltonian niche which focuses on biotic interactions and resource–consumer dynamics that can be measured principally at local scales. [ABSTRACT FROM AUTHOR]

Loots, C., Vaz, S., Planque, B., and Koubbi, P. 2010. What controls the spatial distribution of the North Sea plaice spawning population? Confronting ecological hypotheses through a model selection framework. – ICES Journal of Marine Science, 67: 244–257.The spatial dynamics of spawning fish are crucial because they influence the survival rates of eggs and larvae and ultimately impact the reproductive success of populations. The factors that control these dynamics are complex and potentially many, and they interact. A model-selection-based approach was developed to confront various hypotheses of control of the spatial distribution of spawning population of North Sea plaice (Pleuronectes platessa). For each hypothesis or combination thereof, statistical models were constructed. These were then ranked and selected based on their ability to adjust and predict observed spatial distributions. The North Sea plaice population seems to have developed strong attachment to specific spawning sites, where geographic location and population memory are important controlling factors. Temporal changes in spatial distribution patterns appear to be influenced primarily by population size and demography. Variations in hydrographic conditions such as temperature and salinity do not appear to control interannual fluctuations in spatial distribution. This means that, for reproduction, applying conventional habitat models may falsely attribute major controlling effects to environmental conditions. It is concluded that a multiple-hypothesis approach is essential to understanding and predicting the present and future distribution of the North Sea plaice population during its spawning season. [ABSTRACT FROM PUBLISHER]

Overexploitation and climate change are increasingly causing unanticipated changes in marine ecosystems, such as higher variability in fish recruitment and shifts in species dominance. An ecosystem-based approach to fisheries attempts to address these effects by integrating populations, food webs and fish habitats at different scales. Ecosystem models represent indispensable tools to achieve this objective. However, a balanced research strategy is needed to avoid overly complex models. Ecosystem oceanography represents such a balanced strategy that relates ecosystem components and their interactions to climate change and exploitation. It aims at developing realistic and robust models at different levels of organisation and addressing specific questions in a global change context while systematically exploring the ever-increasing amount of biological and environmental data. [Copyright &y& Elsevier]

Understanding the patterns of spatial and temporal variations in animal abundance is a fundamental question in ecology. Here, we propose a method to quantify temporal variations in animal spatial patterns and to determine the spatial scale at which such temporal variability is expressed. The methodology extends from the approach proposed by Taylor (Taylor, L. R. 1961. Aggregation, variance and the mean. Nature 189: 732–735) and relies on models of the relationship between temporal mean and variance in animal abundance. Repeated observations of the spatial distribution of populations are used to construct spatially explicit models of Taylor's power law. The resulting slope parameters of the Taylor power law provide local measures of the temporal variability in animal abundance. We investigate if the value of the slope varies significantly with spatial location and with spatial scale. The method is applied to seabirds distribution in the Bay of Biscay. We study four taxa (northern gannets, large gulls, auks and kittiwakes) that display distinct geographical distribution, spatial structure and foraging strategy. Our results show that the temporal variability associated to the spatial distribution of northern gannets is high and spatially homogeneous. By contrast, kittiwakes present large geographical areas associated with high and low variability. The temporal variability of auk's spatial distribution is strongly scale-dependent: at fine scale high variability is associated to high abundance, but at large scale high variability is associated to the external border of their distribution range. The method provides satisfactory results and useful information on species spatio-temporal distribution. [ABSTRACT FROM AUTHOR]

Many marine species exhibit poleward migrations following climate change. The Barents Sea, a doorstep to the fast‐warming Arctic, is experiencing large scale changes in its environment and its communities. Tracking and anticipating changes for management and conservation purposes at the scale of the ecosystem necessitate quantitative knowledge on individual species distribution drivers. This paper aims at identifying the factors controlling demersal habitats in the Barents Sea, investigating for which species we can predict current and future habitats and inferring those most likely to respond to climate change. We used non‐linear quantile regressions (QGAM) to model the upper quantile of the biomass response of 33 fish species to 10 environmental gradients and revealed three environmental niche typologies. Four main predictors seem to be limiting species habitat: bottom and surface temperature, salinity, and depth. We highlighted three cases of present and future habitat predictability: (a) Habitats of widespread species are not likely to be limited by the existing conditions within the Barents Sea. (b) Habitats limited by a single factor are predictable and could shift if impacted by climate change. If the factor is depth, the habitat may stagnate or shrink if the environment becomes unsuitable. (c) Habitats limited by several factors are also predictable but need to be predicted from QGAM applied on projected environmental maps. These modeled suitable habitats can serve as input to species distribution forecasts and end‐to‐end models, and inform fisheries and conservation management. [ABSTRACT FROM AUTHOR]

Large‐scale patterns in species diversity and community composition are associated with environmental gradients, but the implications of these patterns for food‐web structure are still unclear. Here, we investigated how spatial patterns in food‐web structure are associated with environmental gradients in the Barents Sea, a highly productive shelf sea of the Arctic Ocean. We compared food webs from 25 subregions in the Barents Sea and examined spatial correlations among food‐web metrics, and between metrics and spatial variability in seawater temperature, bottom depth and number of days with ice cover. Several food‐web metrics were positively associated with seawater temperature: connectance, level of omnivory, clustering, cannibalism, and high variability in generalism, while other food‐web metrics such as modularity and vulnerability were positively associated with sea ice and negatively with temperature. Food‐web metrics positively associated with habitat heterogeneity were: number of species, link density, omnivory, path length, and trophic level. This finding suggests that habitat heterogeneity promotes food‐web complexity in terms of number of species and link density. Our analyses reveal that spatial variation in food‐web structure along the environmental gradients is partly related to species turnover. However, the higher interaction turnover compared to species turnover along these gradients indicates a consistent modification of food‐web structure, implying that interacting species may co‐vary in space. In conclusion, our study shows how environmental heterogeneity, via environmental filtering, influences not only turnover in species composition, but also the structure of food webs over large spatial scales. [ABSTRACT FROM AUTHOR]

Identification of cryptic species can have profound implications in fishery management, conservation and biodiversity contexts. In the North Atlantic, the genus Sebastes is currently represented by four species, although additional cryptic species have been assumed. The connectivity of the gene-pools within the genus in Greenland waters, in particular, remains largely unexplored. Using a panel of 13 microsatellite markers for 720 fish, we explored the species complex of Sebastes norvegicus in Greenland waters. Genetic analyses provided evidence for three cryptic species in samples that were morphologically identified as S. norvegicus. They were termed S. norvegicus -A, S. norvegicus -B, and S. norvegicus- giants. A few phenotypic features exist to identify adult S. norvegicus giants, but no characteristics have been identified for the two other cryptic species. The proposed cryptic species should be recognized in the management regime to ensure sustainable exploitation and conservation of Sebastes species in Greenland waters. [ABSTRACT FROM AUTHOR]

Genetic population structure is often used to identify management units in exploited species, but the extent of genetic differentiation may be inflated by geographic variation in the level of hybridization between species. We identify the genetic population structure of Sebastes mentella and investigate possible introgression within the genus by analyzing 13 microsatellites in 2,562 redfish specimens sampled throughout the North Atlantic. The data support an historical divergence between the 'shallow' and 'deep' groups, beyond the Irminger Sea where they were described previously. A third group , 'slope,' has an extended distribution on the East Greenland Shelf, in addition to earlier findings on the Icelandic slope. Furthermore, S. mentella from the Northeast Arctic and Northwest Atlantic waters are genetically different populations. In both areas, interspecific introgression may influence allele frequency differences among populations. Evidence of introgression was found for almost all the identified Sebastes gene pools, but to a much lower extent than suggested earlier. Greenland waters appear to be a sympatric zone for many of the genetically independent Sebastes groups. This study illustrates that the identified groups maintain their genetic integrity in this region despite introgression. [ABSTRACT FROM AUTHOR]

The identification of isolated populations in widely distributed marine species is often impeded by low levels of genetic differentiation. However, modern genetic approaches now allow for the efficient detection of potentially large numbers of novel genetic variations, thereby improving the power to identify biologically meaningful management units. To investigate the genetic structuring of saithe (Pollachius virens L.), we applied seascape genetic approaches to 131 single nucleotide polymorphism loci genotyped in 584 fish collected from 11 locations across the North Atlantic. Wombling analysis and the Monmonier algorithm revealed four genetic clusters (Barents Sea, Central Northeast Atlantic, Rockall, and Canada) across the species distribution range. These results imply that genetic structuring in saithe maybe influenced by abiotic factors such as geographical distance, and bathymetry as well as biotic factors such as sex-biased migration, and natal homing. The results suggest a potential mismatch between management and biological units across the Northeast Atlantic, which may have implications for sustainable exploitation of the species. [ABSTRACT FROM AUTHOR]

Assessing the vulnerability of biological communities to anthropic pressures in marine systems may be challenging because of the difficulty to properly model each species' response to the pressure due to lack of information. One solution is to apply factor-mediated vulnerability assessment which combines (i) information on species ecological traits and conservation status organized in a matrix of so-called "vulnerability factors", (ii) a conceptual model of how these factors affect species vulnerability, and (iii) data on the spatial distribution and abundance of each species issued from at-sea surveys. Such factor-mediated vulnerability assessment was originally introduced in the seabird-wind farm context by Garthe and Hüppop (2004. Scaling possible adverse effects of marine wind farms on seabirds: developing and applying a vulnerability index. Journal of Applied Ecology, 41: 724-734) and has since then been expanded to many case studies. However, the mathematical formulations that were proposed at that time are overly simplistic and may overlook critical components of the impact assessment. Our study briefly reviews the original approach and highlights its hidden assumptions and associated interpretation problems, for example, the overestimation of disturbance pressure to the detriment of collision, or the very high contribution of log abundances in vulnerability maps. Then, we propose a revised framework that solves these issues and permits easy transposition to other community-pressure case studies. To illustrate the usefulness and generality of the revised framework, we apply it to two case studies, one concerning the vulnerability assessment of a seabird community to offshore wind farms in the Bay of Biscay, and another focusing on the vulnerability assessment of the benthic megafauna community to trawling pressure in the Barents Sea. [ABSTRACT FROM AUTHOR]

Scientific interest in deep-water marine resources has increased dramatically over the last 10–20 years as management bodies have sought advice on how to manage deep-water fisheries and protect deep-water ecosystems. The strengths and weaknesses of the management and monitoring of deep-water stocks, fisheries, and ecosystems in various areas of the world are described, with the objective of informing the EU FP7 DEEPFISHMAN project so that it can fulfill its primary aim, which is to develop strategic options for a short- and long-term management and monitoring ecosystem-based framework for the northeast Atlantic. To provide a baseline, the current monitoring and management regime in the northeast Atlantic is reviewed, followed by a brief description of the regimes applying to deep-water fisheries in the northwest Atlantic, the southeast Atlantic, off Brazil, in the Antarctic, off Australia and New Zealand, and in the Mediterranean. The strengths and weaknesses of these are discussed, taking into account additional information available from DEEPFISHMAN case study stocks, outcomes from consultations with stakeholders in the deep-water fishing industry in the northeast Atlantic, and the requirements of EU regulations and developing policy that will likely impact deep-water fisheries in the northeast Atlantic. [ABSTRACT FROM AUTHOR]

Cadrin, S. X., Bernreuther, M., Daníelsdóttir, A. K., Hjörleifsson, E., Johansen, T., Kerr, L., Kristinsson, K., Mariani, S., Nedreaas, K., Pampoulie, C., Planque, B., Reinert, J., Saborido-Rey, F., Sigurðsson, T., and Stransky, C. 2010. Population structure of beaked redfish, Sebastes mentella: evidence of divergence associated with different habitats. – ICES Journal of Marine Science, 67: 1617–1630.Throughout their range, Sebastes spp. are adapted to a diversity of ecological niches, with overlapping spatial distributions of different species that have little or no morphological differences. Divergence of behavioural groups into depth-defined adult habitats has led to reproductive isolation, adaptive radiation, and speciation in the genus Sebastes. Recent genetic research, supported by life-history information, indicates four biological stocks of Sebastes mentella in the Irminger Sea and adjacent waters: a western stock, a deep-pelagic stock, a shallow-pelagic stock, and an Iceland slope stock. Congruent differences in fatty acids and parasites suggest that these genetically distinct populations are adapted to disparate trophic habitats in pelagic waters (shallower and deeper than the deep-scattering layer) and in demersal habitats on the continental slope. Morphology of pelagic forms is also more streamlined than demersal forms. Although genetic differences and evidence for reproductive isolation are clear, these populations appear to share common nursery habitats on the Greenland shelf. We propose a redefinition of practical management units near the Irminger Sea based on geographic proxies for biological stocks and minimizing mixed-stock catches according to the spatial patterns of the recent fishery. [ABSTRACT FROM PUBLISHER]

Abstract: Modern fisheries research and management must understand and take account of the interactions between climate and fishing, rather than try to disentangle their effects and address each separately. These interactions are significant drivers of change in exploited marine systems and have ramifications for ecosystems and those who depend on the services they provide. We discuss how fishing and climate forcing interact on individual fish, marine populations, marine communities, and ecosystems to bring these levels into states that are more sensitive to (i.e. more strongly related with) climate forcing. Fishing is unlikely to alter the sensitivities of individual finfish and invertebrates to climate forcing. It will remove individuals with specific characteristics from the gene pool, thereby affecting structure and function at higher levels of organisation. Fishing leads to a loss of older age classes, spatial contraction, loss of sub-units, and alteration of life history traits in populations, making them more sensitive to climate variability at interannual to interdecadal scales. Fishing reduces the mean size of individuals and mean trophic level of communities, decreasing their turnover time leading them to track environmental variability more closely. Marine ecosystems under intense exploitation evolve towards stronger bottom–up control and greater sensitivity to climate forcing. Because climate change occurs slowly, its effects are not likely to have immediate impacts on marine systems but will be manifest as the accumulation of the interactions between fishing and climate variability — unless threshold limits are exceeded. Marine resource managers need to develop approaches which maintain the resilience of individuals, populations, communities and ecosystems to the combined and interacting effects of climate and fishing. Overall, a less-heavily fished marine system, and one which shifts the focus from individual species to functional groups and fish communities, is likely to provide more stable catches with climate variability and change than would a heavily fished system. [Copyright &y& Elsevier]