Search

International audience; Identifying and protecting essential fish habitats like spawning grounds requires an accurate knowledge of fish spatio-temporal distribution. Commercial declarations coupled with Vessel Monitoring System provide fine scale information on the full year to map fish distribution and identify essential habitats. We developed an integrated framework to infer fish spatial distribution on a monthly time step by combining scientific and commercial data while explicitly considering the preferential sampling of fisher towards areas of higher biomass. We developed a method to identify areas of persistent aggregation of biomass during the spawning season and interpret these as spawning areas. The model is applied to infer maps of relative biomass for three species (sole, whiting and squids) in the Bay of Biscay on a monthly time step over a 9 year period. Integrating several fleets in inference provides a good coverage of the area and improves model predictions. The preferential sampling parameters give insights into the temporal dynamics of the targeting behavior of the different fleets. Last, persistent aggregation areas reveal consistent with the available literature on spawning grounds, highlighting the potential of our approach to identify reproduction areas.

Nearshore habitats are essential for many marine fish species but are subject to anthropogenic stressors. Assessing the consequences of essential fish habitat degradation on population dynamics and productivity is challenging. We address this by focusing on a metapopulation of the common sole Solea solea, a high-value, exploited flatfish in the Eastern English Channel (EEC). Multidisciplinary data and expert knowledge were compiled to build feasible restoration scenarios for the availability of suitable habitat (measured in habitat surface extent) and chemical quality of juvenile habitats in the highly anthropized Seine estuary, the largest estuary and potentially a sole nursery area of primary interest in the EEC. Scenarios were simulated with a spatially structured life-cycle model to investigate the consequences of local restoration on restricted nursery habitats in the estuary. Restoring surface extent and habitat quality in the Seine estuary dramatically enhances spawning stock biomass (+18%) and fishery catches (+13%) in the EEC. Restoring habitat quality has a greater effect than restoring habitat surface. Because of the low connectivity between subpopulations of sole in the EEC, most of the local restoration benefits remain regional and affect the subpopulation that directly depends on the Seine nursery, with only moderate spread to the entire EEC. Our study emphasizes the utility of spatial simulation models for integrating multidisciplinary knowledge and assessing the consequences of local anthropogenic pressures at wider metapopulation scales. We provide a means of building robust methods to assess the benefits of nearshore habitat restoration for enhancing fish populations and fisheries and integrate habitat value into the sustainable management of exploited species.

Anthropogenic pressures have resulted in declines in diadromous fish. Many diadromous fish which were commercially important are now threatened and protected. Little is known about their marine life history phases, and no observation-based Species Distribution Model exists for this group of species at sea. Yet, fisheries dependent and independent data could provide new insights into the distribution of diadromous fish at sea.We collated a database of 168 904 hauls from fisheries observer bycatch data and scientific fisheries surveys, from eastern Atlantic and Mediterranean waters. The distribution of eleven rare and data-poor diadromous fish (shads, lampreys, salmonids, the European eel, the thinlip mullet, smelt and the European flounder) were modelled. A Bayesian site occupancy model, that incorporates imperfect detection to account for repeat detections and non-detections, the non-random nature of fishing gear type and spatial autocorrelation was used. From the model outputs, we explored bycatch risk and the role of MPAs, required under the Marine Strategy Framework Directive and Habitat Directive and assessed.Diadromous fish were observed within relatively shallow coastal areas. Species specific gear bycatch trends were observed. Core distribution areas corresponded to their known water basin presence, indicating connectivity with their freshwater habitats. Numerous Habitat Directive Marine Protected Areas were found to be of relevance.Given the coastal distribution of these species, they are exposed to higher anthropogenic pressures from both terrestrial and marine environments. Risk of bycatch at sea for most species appears to be low. Nonetheless, for threatened individuals, even a small amount of bycatch may impact their populations, especially since misreporting is likely to be high. Differences in catchability between gears highlight potential benefits of limiting access of certain gears within protected areas to reduce bycatch.

Developing Species Distribution Models (SDM) for marine exploited species is a major challenge in fisheries ecology. Classical modelling approaches typically rely on fish research survey data. They benefit from a standardized sampling design and a controlled catchability, but they usually occur once or twice a year and they may sample a relatively small number of spatial locations. Spatial monitoring of commercial data (based on logbooks crossed with Vessel Monitoring Systems) can provide an additional extensive data source to inform fish spatial distribution. We propose a spatial hierarchical framework integrating both data sources while accounting for preferential sampling (PS) of commercial data. From simulations, we demonstrate that PS should be accounted for in estimation when PS is actually strong. When commercial data far exceed scientific data, the later bring little information to spatial predictions in the areas sampled by commercial data, but bring information in areas with low fishing intensity and provide a validation dataset to assess the integrated model consistency. We applied the framework to three demersal species (hake, sole, and squids) in the Bay of Biscay that emphasize contrasted PS intensity and we demonstrate that the framework can account for several fleets with varying catchabilities and PS behaviours.

While, quantifying trophic interactions is a critical path to understanding and forecasting ecosystem functioning, fitting trophic models to field data remains challenging. It requires flexible statistical tools to combine different sources of information from the literature and fieldwork samples. We present EcoDiet, a hierarchical Bayesian modeling framework to simultaneously estimate food-web topology and diet composition of all consumers in the food web, by combining (i) a priori knowledge from the literature on both food-web topology and diet proportions; (ii) stomach content analyses, with frequencies of prey occurrence used as the primary source of data to update the prior knowledge on the topological food-web structure; (iii) and biotracers data through a mixing model (MM). Inferences are derived in a Bayesian probabilistic rationale that provides a formal way to incorporate prior information and quantifies uncertainty around both the topological structure of the food web and the dietary proportions. EcoDiet was implemented as an open-source R package, providing a user-friendly interface to execute the model as well as examples and guidelines to familiarize with its use. We used simulated data to demonstrate the benefits of EcoDiet and how the framework can improve inferences on diet matrix by comparison with classical network MM. We applied EcoDiet to the Celtic Sea ecosystem, and showed how combining multiple data types within an integrated approach provides a more robust and holistic picture of the food-web topology and diet matrices than the literature or classical MM approach alone. EcoDiet has the potential to become a reference method for building diet matrices as a preliminary step of ecosystem modeling and to improve our understanding of prey-predator interactions.

Populations of Atlantic salmon Salmo salar have experienced precipitous declines in abundance since the 1970s. This decline has been associated with reduced numbers of adult salmon returning to freshwater from their marine migration, i.e., their marine return rates (MRR). Thus, understanding the factors that affect MRR is of crucial conservation importance. We used a state-space model with a 13-year time series of individually tagged salmon mark-recapture histories on the River Frome, southern England, to test the effect of smolt body length on their MRR. As well as smolt length, the model tested for the influence of environmental covariates that were representative of the conditions experienced by the smolts in the early stages of their seaward migration, i.e., from the lower river to the estuary exit. The model indicated that, even when accounting for environmental covariates, smolt body length was an important predictor of MRR. While larger smolts have a higher probability of returning to their natal river as adults than smaller smolts, and one-sea-winter salmon have a survival rate twice as high as multi-sea-winter salmon, the actual biological mechanisms underpinning this phenomenon remain uncertain. These results have important applications for salmon conservation, as efforts to bolster salmon populations in the freshwater environment should consider ways to improve smolt quality (i.e., body size) as well as smolt quantity. This article is protected by copyright. All rights reserved.

Data and knowledge mobilisation are significant challenges in ecology and resource management, with the journey from data collection through to management action often left incomplete due to difficulties sharing information across diverse and dispersed communities. This disconnect between science and management must be resolved if we are to successfully tackle the increasing impact of human activity on our ecosystems. Across their North Atlantic range, Atlantic salmon (Salmo salar L.) populations are in steep decline in many areas and urgent actions are required to curb this decline. Being commercially important this species has been subject to intense research, but management action often suffers from both a lack of access to this knowledge resource and support for its integration into effective management strategies. To respond to this challenge, the science and management communities must place higher priority on mobilising existing and emerging knowledge sources to inform current and future resource use and mitigation strategies. This approach requires a more complete picture of the current salmon ecology data and knowledge landscape, new mechanisms to enable data mobilisation and re-use, and new research to describe and parameterise the responses of wild populations to habitat changes. Here we present a unique interface for registering and linking data resources relevant to the Atlantic salmon life cycle that can address the data mobilisation aspect of these challenges. The Salmon Ecosystem Data Hub is a salmon-specific metadata catalogue, natively interoperable with many existing data portals, which creates a low resistance pathway to maximise visibility of data relevant to Atlantic salmon. This includes the capacity to annotate datasets with life-stage domains and variable classes, thereby permitting dispersed data to be formally contextualised and integrated to support hypotheses specific to scenario-based modelling and decision-making. The alignment and mobilisation of data within the Salmon Ecosystem Data Hub will help advance the development of appropriate environmentally driven forecast models and an ecosystem-based management approach for Atlantic salmon that optimises future management strategies.

Lampreys are ancestral jawless vertebrates with particularly complex life histories. Population declines resulting from increased anthropogenic pressure have been observed. For semelparous diadromous lampreys, the marine phase remains largely a black box, making targeted management and conservation measures difficult to implement. Here, we collated a database of 168904 hauls from both fisheries-dependent and fisheries-independent surveys between 1965 and 2019. Lampreys were observed in only 254 hauls (20 cm) and occurred in autumn, indicating inshore migration. Our observations provide insight into the ecology of lampreys at sea and highlight study locations and gear types, which may be more pertinent for future research. Greater awareness is needed during surveys to collate catch information on lampreys and improve understanding of their ecology and phenology at sea.

Estimation of abundance with wide spatiotemporal coverage is essential to the assessment and management of wild populations. But, in many cases, data available to estimate abundance time series have diverse forms, variable quality over space and time and they stem from multiple data collection procedures. We developed a hierarchical Bayesian modelling (HBM) approach that take full advantage of the diverse assemblage of data at hand to estimate homogeneous time series of abundances irrespective of the data collection procedure. We apply our approach to the estimation of adult abundances of 18 Atlantic salmon (Salmo salar) populations of Brittany (France) from 1987 to 2017 using catch statistics, environmental covariates, and fishing effort. Additional data of total or partial abundance collected in four closely monitored populations are also integrated into the analysis. The HBM framework allows the transfer of information from the closely monitored populations to the others. Our results reveal no clear trend in the abundance of adult returns in Brittany over the period studied. lations d'animaux sauvages. Dans de nombreux cas, toutefois, les donnees disponibles pour l'estimation de series chronologidifferentes procedures. Nous avons elabore une approche de modelisation bayesienne hierarchique (MBH) pour tirer pleinement parti de l'assemblage varie de donnees disponibles pour estimer des series chronologiques homogenes d'abondance, quelle que soit la procedure de collecte de donnees. Nous appliquons l'approche a l'estimation de l'abondance d'adultes dans 18 populations de saumon atlantique (Salmo salar) de Bretagne (France) de 1987 a 2017, en utilisant des statistiques sur les prises, des covariables faisant l'objet d'une surveillance etroite sont aussi integrees a l'analyse. Le cadre de MBH permet le transfert d'information l'abondance des adultes de retour en Bretagne au cours de la periode etudiee. [Traduit par la Redaction], L’estimation de l’abondance à vaste couverture spatiotemporelle est nécessaire pour l’évaluation et la gestion de populations d’animaux sauvages. Dans de nombreux cas, toutefois, les données disponibles pour l’estimation de séries chronologiques d’abondance prennent différentes formes, sont de qualité variable dans le temps et l’espace et ont été obtenues par différentes procédures. Nous avons élaboré une approche de modélisation bayésienne hiérarchique (MBH) pour tirer pleinement parti de l’assemblage varié de données disponibles pour estimer des séries chronologiques homogènes d’abondance, quelle que soit la procédure de collecte de données. Nous appliquons l’approche à l’estimation de l’abondance d’adultes dans 18 populations de saumon atlantique (Salmo salar) de Bretagne (France) de 1987 à 2017, en utilisant des statistiques sur les prises, des covariables environnementales et l’effort de pêche. D’autres données sur l’abondance totale ou partielle obtenues pour quatre populations faisant l’objet d’une surveillance étroite sont aussi intégrées à l’analyse. Le cadre de MBH permet le transfert d’information sur des populations étroitement surveillées aux autres populations. Nos résultats ne font ressortir aucune tendance nette de l’abondance des adultes de retour en Bretagne au cours de la période étudiée. [Traduit par la Rédaction]

International audience; The discrete kernel-based regression approach generally provides pointwise estimates of count data that do not account for uncertainty about both parameters and resulting estimates. This work aims to provide probabilistic kernel estimates of count regression function by using Bayesian approach and then allows for a readily quantification of uncertainty. Bayesian approach enables to incorporate prior knowledge of parameters used in discrete kernel-based regression. An application was proposed on count data of condition factor of fish (K) provided from an experimental project that analyzed various pond management strategies. The probabilistic distribution of estimates were contrasted by discrete kernels, as a support to theoretical results on the performance of kernels. More practically, Bayesian credibility intervals of K-estimates were evaluated to compare pond management strategies. Thus, similarities were found between performances of semi-intensive and coupled fishponds, with formulated feed, in comparison with extensive fishponds, without formulated feed. In particular, the fish development was less predictable in extensive fishpond, dependent on natural resources, than in the two other fishponds, supplied in formulated feed.

Recent declines in Atlantic salmon Salmo salar populations are generally attributed to factors in their marine life-phase. However, it is postulated that factors affecting their freshwater life-phase might impact their marine survival, such as the influence of body size. While larger smolts are widely hypothesized to have higher marine survival rates, empirical support remains scant, in part due to inadequate data and ambiguous statistical analyses. Here, we test the influence of smolt body size on marine return rates, a proxy for marine survival, using a 12-year dataset of 3688 smolts tagged with passive integrated transponders in the River Frome, Southern England. State-space models describe the probability of smolts surviving their marine phase to return as 1 sea-winter (1SW) or multi-sea-winter adults as a function of their length, while accounting for imperfect detection and missing data. Models predicted that larger smolts had higher return rates; the most parsimonious model included the effect of length on 1SW return rate. This prediction is concerning, as freshwater juvenile salmon are decreasing in size on the River Frome, and elsewhere. Thus, to maximize adult returns, restoration efforts should focus on freshwater life-stages, and maximize both the number and the size of emigrating smolts.

This study provides new data on Atlantic salmon Salmo salar life-history traits across France. Using a long-term recreational angling database (1987-2013) covering 34 rivers in three regions (genetic units), a decline in individual length, mass and a delayed adult return to French rivers was reported. Temporal similarities in trait variations between regions may be attributed to common change in environmental conditions at sea. The relative rate of change in phenotypic traits was more pronounced in early maturing fish [1 sea-winter (1SW) fish] than in late maturing fish (2SW fish). Such contrasted response within populations highlights the need to account for the diversity in life histories when exploring mechanisms of phenotypic change in S. salar. Such detailed life-history data on returning S. salar have not previously been reported from France. This study on French populations also contributes to reducing the gap in knowledge by providing further empirical evidence of a global pattern in S. salar across its distribution range. Results are consistent with the hypothesis that the observed changes in life-history traits are primarily associated with environmental changes in the North Atlantic Ocean. They also emphasize the presence of less important, but still significant contrasts between region and life history.

Publisher's version (útgefin grein), The biological status of many commercially exploited fishes remains unknown, mostly due to a lack of data necessary for their assessment. Investigating the spatiotemporal dynamics of such species can lead to new insights into population processes and foster a path towards improved spatial management decisions. Here, we focused on striped red mullet (Mullus surmuletus), a widespread yet data-limited species of high commercial importance. Aiming to quantify range dynamics in this data-poor scenario, we combined fishery-dependent and -independent data sets through a series of Bayesian mixed-effects models designed to capture monthly and seasonal occurrence patterns near the species’ northern range limit across 20 years. Combining multiple data sets allowed us to cover the entire distribution of the northern population of M. surmuletus, exploring dynamics at different spatiotemporal scales and identifying key environmental drivers (i.e., sea surface temperature, salinity) that shape occurrence patterns. Our results demonstrate that even when process and (or) observation uncertainty is high, or when data are sparse, if we combine multiple data sets within a hierarchical modelling framework, accurate and useful spatial predictions can still be made., CP’s postdoc was funded by Ifremer and France Filière Peche. The authors thank Bruno Ernande for suggestions and comments that improved the work during the analysis. The authors also thank two anonymous reviewers for their comments, which helped to improve the manuscript.

International audience; Quantifying connectivity within fish metapopulations is an important component in understanding population dynamics and providing an evidence base for assessment and management. We investigate metapopulation connectivity of the common sole (Solea solea) in the Eastern English Channel (EEC). The EEC common sole stock is currently assessed as a single and spatially homogeneous population, but connectivity induced through adult movements within this stock and with nearby stocks remains unknown. To fill this knowledge gap, we developed a state-space mark-recovery model, designed to estimate adult connectivity using mark-recapture data from multiple release experiments from 1970 to 2018 across the EEC and adjacent management areas. The model estimates seasonal fish movements between five predefined areas, Western English Channel, Eastern English Channel (split into three discrete sub-areas), and North Sea. Over 32 000 fish were tagged, 4036 of which were recovered via fisheries. Our results suggest minimal large-scale adult movements between these areas; movements among spatial units within the EEC were very low with even lower levels of immigration from areas adjoining the EEC. Our results support the hypothesis of segregated populations within the EEC. The importance of accommodating population substructure in the fisheries management is considered.; La quantification de la connectivité au sein de métapopulations de poissons est un élément important pour comprendre la dynamique des populations et elle fournit des données probantes sur lesquelles baser l’évaluation et la gestion. Nous examinons la connectivité de métapopulations de sole (Solea solea) dans la Manche Est. Le stock de sole de la Manche Est est actuellement évalué en tant que population unique et homogène dans l’espace, mais une éventuelle connectivité induite par les déplacements d’adultes au sein de ce stock et par rapport à d’autres stocks à proximité demeure non caractérisée. Pour combler cette lacune, nous avons développé un modèle d’espace d’états de marquage-récupération conçu pour estimer la connectivité des adultes en utilisant des données de marquage-recapture de multiples expériences de remises à l’eau menées de 1970 à 2018 à la grandeur de la Manche Est et dans des aires de gestion attenantes. Le modèle estime les déplacements saisonniers de poissons entre cinq régions prédéfinies, soit la Manche Ouest, la Manche Est (subdivisée en trois sous-régions distinctes) et la mer du Nord. Plus de 32 000 poissons ont été marqués, dont 4036 ont été récupérés par la pêche. Nos résultats révèlent très peu de déplacements à grande échelle entre ces régions; les déplacements entre sous-régions de la Manche Est sont très faibles, et l’immigration en provenance de régions attenantes à la Manche Est, encore plus faible. Nos résultats appuient l’hypothèse de populations ségréguées dans la Manche Est. L’importance de la prise en compte de la sous-structure des populations dans la gestion des pêches est abordée.

International audience; An accurate representation of the spatial structure of marine fish populations is a prerequisite for unbiased stock assessment, to build appropriate management measures. The common sole (Solea solea, L.) of the Eastern English Channel (EEC) is a commercial flatfish species, whose stock is currently assessed as a single homogeneous population and has been overexploited over the last decade. Previous studies have highlighted the stock's low connectivity and the lack of understanding in sub-adults and adults mixing between putative subunits, raising the issue of a potential spatial structure of this stock. Here, we examined evidence of spatial structure by analyzing spatiotemporal patterns of length and density-at-age using time series (1989–2015) obtained from a scientific survey (UK-BTS). We tested for various hypotheses of spatial structure, based on both scientific and expert knowledge, including three isolated subunits, their combination, and no spatial structure. We combined two sets of analyses: (1) a selection of the von Bertalanffy growth model with spatial effects capturing the most accurate spatial structure of the stock and the analysis of long-term spatial patterns (gradients, trends, synchrony) in growth parameters; and (2) an analysis of the synchrony among density-at-age time series between spatial subunits. Growth analysis revealed a spatial structure in three subunits (i.e. the southwestern, northeastern and English parts of the EEC) and an overall decline of length-at-age, suggesting Fishery-Induced Evolution. The synchrony analysis revealed high spatiotemporal integrity at the level of the southwestern subunit of the EEC. Our two analyses thus detected a lasting signal of spatial stock structure with a probable isolation of the southwestern subunit from the rest of the EEC. Future research should build on our study by investigating the connectivity of sole throughout its entire life cycle, to improve stock assessment and fishery management.; Une représentation exacte de la structure spatiale des populations de poissons de mer est une condition préalable à une évaluation impartiale des stocks, afin d'élaborer des mesures de gestion appropriées. La sole commune (Solea solea, L.) de la Manche orientale (CEE) est une espèce commerciale de poisson plat, dont le stock est actuellement évalué comme une seule population homogène et a été surexploité au cours de la dernière décennie. Des études antérieures ont mis en évidence la faible connectivité du stock et le manque de compréhension chez les sous-adultes et les adultes se mélangeant entre sous-unités putatives, ce qui soulève la question d'une structure spatiale potentielle de ce stock. Nous avons examiné ici les preuves de la structure spatiale en analysant les tendances spatio-temporelles de la longueur et de la densité selon l'âge à l'aide de séries chronologiques (1989-2015) obtenues à partir d'une enquête scientifique (UK-BTS). Nous avons vérifié diverses hypothèses de structure spatiale, fondées sur des connaissances scientifiques et spécialisées, y compris trois sous-unités isolées, leur combinaison et l'absence de structure spatiale. Nous avons combiné deux ensembles d'analyses : (1) une sélection du modèle de croissance de von Bertalanffy avec des effets spatiaux capturant la structure spatiale la plus précise du stock et l'analyse des modèles spatiaux à long terme (gradients, tendances, synchronie) des paramètres de croissance ; et (2) une analyse de la synchronisation entre les séries temporelles de densité à âge entre sous-unités spatiales. L'analyse de la croissance a révélé une structure spatiale dans trois sous-unités (c'est-à-dire les parties sud-ouest, nord-est et anglaise de la CEE) et un déclin global de la longueur selon l'âge, ce qui suggère une évolution induite par la pêche. L'analyse synchrone a révélé une grande intégrité spatio-temporelle au niveau de la sous-unité sud-ouest de la CEE. Nos deux analyses ont ainsi détecté un signal durable de la structure spatiale du stock avec un isolement probable de la sous-unité sud-ouest du reste de la CEE. Les recherches futures devraient s'appuyer sur notre étude en étudiant la connectivité de la sole tout au long de son cycle de vie, afin d'améliorer l'évaluation des stocks et la gestion des pêches.

Invited feature This work was funded by the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement No. 266445 for the project Vectors of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS). We are grateful to Sophie Pasquier for compiling references.; International audience; Exploited coastal-nursery-dependent fish species are subject to various stressors occurring at specific stages of the life cycle: climate-driven variability in hydrography determines the success of the first eggs/larvae stages; coastal nursery habitat suitability controls juvenile growth and survival; and fisheries target mostly adults. A life cycle approach was used to quantify the relative influence of these stressors on the Eastern English Channel (EEC) population of the common sole (Solea solea), a coastal-nursery-dependent flatfish population which sustains important fisheries. The common sole has a complex life cycle: after eggs hatch, larvae spend several weeks drifting in open water. Survivors go on to metamorphose into benthic fish. Juveniles spend the first two years of their life in coastal and estuarine nurseries. Close to maturation, they migrate to deeper areas, where different subpopulations supplied by different nurseries reproduce and are exploited by fisheries. A spatially structured age-and stage-based hierarchical Bayesian model integrating various aspects of ecological knowledge, data sources and expert knowledge was built to quantitatively describe this complex life cycle. The model included the low connectivity among three subpopulations in the EEC, the influence of hydrographic variability, the availability of suitable juvenile habitat and fisheries. Scenarios were designed to quantify the effects of interacting stressors on population renewal. Results emphasized the importance of coastal nursery habitat availability and quality for the population renewal. Realistic restoration scenarios of the highly degraded Seine estuary produced a two-third increase in catch potential for the adjacent subpopulation. Fisheries, however, remained the main source of population depletion. Setting fishing mortality to the maximum sustainable yield led to substantial increases in biomass (+100%) and catch (+33%) at the EEC scale. The approach also showed how climate-driven variability in hydrography is likely to interact with human pressures, e.g., overfishing increased the sensitivity to unfavourable conditions. Our results provided insights into the dynamics of numerous exploited coastal-nursery-dependent species while paving the way toward more robust advice for sustainable management of these resources.

The research leading to these results has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration (FP7/2007-2013) within the Ocean of Tomorrow call under Grant Agreement No.266445 for the project Vectors of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS). This work is also a contribution to the EU Cost Action FA1004 "Conservation Physiology". PS acknowledges support from the UK Natural Environment Research Council and Department for Environment, Food and Rural Affairs [grant number NE/L003279/1, Marine Ecosystems Research Programme. The authors wish to thank Drs. Jason Link, Elizabeth Fulton and Oivind Fiksen as well as an anonymous reviewer for their helpful comments on an earlier version of this manuscript. This work also benefitted from discussions among members of the ICES Working Group on Integrated Physical biological and Ecosystem Modelling (WGIPEM) and the ICES-PICES Strategic Initiative on Climate Change Impacts on Marine Ecosystems (SICCME). Academic press ltd- elsevier science ltd London Si Marine & Freshwater Biology; Oceanography Iences, v367, p2979 Iences, v367, p1607; International audience; We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

International audience; La gestion et la protection efficaces des populations d’animaux sauvages reposent sur une bonne compréhension de leurs cycles biologiques. Parce que la dynamique des populations dépend des interactions complexes de processus biologiques et écologiques à différentes échelles, de nouvelles approches sont nécessaires pour expliquer la variabilité des processus démographiques et des paramètres associés dans une hiérarchie d’échelles spatiales. Un modèle bayésien hiérarchique du cycle biologique des truites fario (Salmo trutta) résidentes a été élaboré pour évaluer l’influence relative de déterminants locaux et généraux de la mortalité. Le modèle a été calé sur un vaste ensemble de données provenant de 40 tronçons de rivière, qui combine des données d’abondance et de conditions du milieu (hydraulique, température de l’eau). La mortalité des juvéniles dépendante de la densité augmente à faibles températures et diminue quand la disponibilité d’abris augmente. Des températures de l’eau élevées accroissent la mortalité densité-dépendante chez les adultes. Le modèle pourrait aider à prédire la mortalité mensuelle des juvéniles et des adultes dans des scénarios de réchauffement climatique et de modifications de la disponibilité d’abris découlant de la dégradation ou de la restauration d’habit

We thank Michael Gras for actively answering questions about the initial model. We are also grateful to CEFAS for providing UK data. Special thanks to Beatriz Roel and Vladimir Laptikhovsky. French data come from DPMA, declarative data managed by Ifremer - SIH - Systeme d'Informations Halieutiques. Financial support for this work comes from Ifremer and from the "Conseil Regional de Normandie". We thank Pr. Andre Punt and an anonymous reviewer who gave their time and helped us enormously to improve this work.; International audience; Cuttlefish is a key commercial species in the English Channel fishery in terms of landings and value. Age based assessment methods are limited by time-consuming age determination with statoliths and the lack of stock assessment models tailored to this data-limited species. A two-stage biomass model is developed in the Bayesian state-space modelling framework that allows inferences to be made on the stock biomass at the start, middle and end of each fishing seasons between 1992 and 2014, while accounting for both process and measurement errors and to assimilate various sources of information. A method that uses ancillary length-frequency data is developed to provide an informative prior distribution for the biomass growth rate parameter g (E=0.89) and its annual variability (CV=0.1). The new model is a substantial improvement on the existing stock assessment method used by the International Council for the Exploration of the Seas. Taking into consideration a time-varying g parameter provides a more ecologically meaningful model with regard to the sensitivity of the cuttlefish population dynamics to environmental fluctuations and improves model fit. The model also provides predictions of the unexploited biomass in winter, which is based on survey data, and helps manage the stock in the event of strong depletion. (C) 2017 Elsevier B.V. All rights reserved.

The understanding of the dynamics of fishing vessels is of great interest to characterize the spatial distribution of the fishing effort and to define sustainable fishing strategies. It is also a prerequisite for anticipating changes in fishermen's activity in reaction to management rules, economic context, or evolution of exploited resources. Analyzing the trajectories of individual vessels offers promising perspectives to describe the activity during fishing trips. A hidden Markov model with two behavioral states (steaming and fishing) is developed to infer the sequence of non-observed fishing vessel behavior along the vessel trajectory based on Global Positioning System (GPS) records. Conditionally to the behavior, vessel velocity is modeled with an autoregressive process. The model parameters and the sequence of hidden behavioral states are estimated using an expectation–maximization algorithm, coupled with the Viterbi algorithm that captures the most credible joint sequence of hidden states. A simulation approach was performed to assess the influence of contrast between the model parameters and of the path length on the estimation performances. The model was then fitted to four original GPS tracks recorded with a time step of 15 min derived from volunteer fishing vessels operating in the Channel within the IFREMER RECOPESCA project. Results showed that the fishing activity performed influenced the estimates of the velocity process parameters. Results also suggested future inclusion of variables such as tide currents within the ecosystem approach of fisheries. Copyright © 2014 John Wiley & Sons, Ltd.

Recruitment success in marine species is mostly driven by the high and variable mortality of first life stages, and the relationships between stock and recruitment are then largely dominated by residual variability. We show that analysing the residual variability may provide insights on the density-dependence process occurring during the recruitment. Following the seminal formulation of Minto et al. (Survival variability and population density in fish populations. Nature, 2008), we show that when recruitment is considered as a sequence of a pelagic stage with stochastic density-independent mortality followed by a second stage with stochastic density-dependent mortality, then the variability of the recruitment rate per spawning biomass (RPSB) should be a decreasing function of the spawning biomass. Using stock–recruit data of 148 stocks from the RAM legacy database, we provide a test of this hypothesis by showing that the variability of RPSB is lower for fish species with the higher concentration during juvenile stages. Second, a hierarchical Bayesian model (HBM) is built to derive a meta-analysis of stock–recruit data for 39 flatfish stocks, characterized by a high concentration of juveniles in coastal nursery habitats. Results of the HBM show that the variance of the RPSB decreases with the spawning biomass for almost all stocks, thus providing strong evidence of density-dependence during the recruitment process. Finally, we attempt to relate patterns in recruitment variance to relevant life-history traits of flatfish species.

International audience; We explore how alternative hypotheses on the degree of mixing among local subpopulations affect statistical inferences on the dynamics and stock assessment of a harvested flatfish population, namely, the common sole population in the Eastern Channel (ICES area VIId). The current paradigm considers a single, well-mixed, spatially homogeneous population with juveniles from all coastal nursery grounds along the French and UK coasts that contribute to a single adult population and one pool of eggs. Based on the available data and ecological knowledge, we developed a spatial Bayesian integrated life-cycle model that consists of three subpopulations (one near the UK coast and two near the French coast, denoted UK, West FR and East FR, respectively) supported by their respective local nurseries, with the connectivity among the three components limited to low exchanges during larval drift. Considering the population dynamics among three subpopulations (instead of a single homogeneous one) drastically changes our inferences on the productivity of nursery sectors and their relative contribution to total recruitment. Estimates of the East FR subpopulation’s contribution to total recruitment increase (29% in the single population model; 48% in the three subpopulation model), balanced by a decrease in the UK subpopulation’s contribution (53%; 34%). Whereas an assessment based on the hypothesis of a single spatially homogeneous population in the EC indicates exploitation far above MSY (current F/FMSY = 1.8), an assessment that considers a metapopulation with three loosely connected subpopulations revealed a different status, with the UK and East FR subpopulations being exploited above MSY (current F/FMSY = 1.9 and 2, respectively) and the West FR subpopulation approaching full exploitation (current F/FMSY = 1.05). This approach contributes to the quantitative assessment of spatial fishery and coastal habitat management plans.

Understanding fishing vessel dynamics at a fine spatial scale is of great interest for defining appropriate spatial management plans. Different models have been developed to detect fishing activity from Vessel Monitoring System (VMS) data. While mathematical and statistical methods differ, all rely on the idea that vessel speed over ground provides information on fishing vessel activity. However, trawling with constant speed relative to the water mass may as well prove a winning strategy for both technical (to ensure sufficient trawl opening) and biological (to limit escapement of fish) reasons. Therefore, considering speed through water instead of speed over ground might provide insights into fishing activities. We developed a method combining surface currents derived from ocean circulation models with VMS data to estimate vessel speed through water. We then used vessel speed through water as input to two previously published segmentation methods to infer fishing activity during a fishing trip. We illustrate the approach by analysing trajectories of trawlers operating in the Eastern English Channel. All vessels were equipped with VMS and part of the Obsmer national discard sampling programme. Overall, results showed that surface currents influenced fishing behaviour, and trawling preferentially occured parallel to surface currents. Speed over ground associated with trawling behaviour was much more variable than speed through water, suggesting that trawling occured at constant engine regimes. However, for both segmentation methods using speed through water instead of speed over ground did not improve our capacity to identify trawling sequences. In both cases the amount of time spent trawling during a trip was overestimated.

For many marine fish species, recruitment is strongly related to larval survival and dispersal to nursery areas. Simulating larval drift should help assessing the sensitivity of recruitment variability to early life history. An individual-based model (IBM) coupled to a hydrodynamic model was used to simulate common sole larval supply from spawning areas to coastal and estuarine nursery grounds at the population scale in the eastern Channel on a 14-yr time series, from 1991 to 2004. The IBM allowed each particle released to be transported by currents from the hydrodynamic model, to grow with temperature, to migrate vertically giving stage development, and possibly to die according to drift duration, representing the life history from spawning to metamorphosis. Despite sensitivity to the larval mortality rate, the model provided realistic simulations of cohort decline and spatio-temporal variability of larval supply. The model outputs were analysed to explore the effects of hydrodynamics and life history on the interannual variability of settled sole larvae in coastal nurseries. Different hypotheses of the spawning spatial distribution were also tested, comparing homogeneous egg distribution to observation and potential larval survival (PLS) maps. The sensitivity analyses demonstrated that larval supply is more sensitive to the life history along larval drift than to the phenology and volume of spawning, providing explanations for the lack of significant stock–recruitment relationship. Nevertheless, larval supply is sensitive to spawning distribution. Results also suggested a very low connectivity between supposed different sub-populations in the eastern Channel.

Understanding and modelling insect pest dispersal is an important prerequisite for designing integrated pest management programs. Nevertheless, studies investigating the dispersal of small insects in natural conditions remain scarce mainly because of the difficulty of tracking the movements of these organisms. Here we propose to use Hierarchical Bayesian Modelling (HBM) framework to gain knowledge on hidden processes that cannot be observed directly in natura, such as insect landing and insect mortality, through the definition of latent variables. An HBM describing crop colonization by winged aphids was fitted to a large dataset of field observations issued from a long term survey at a wide scale of both aerial and field densities of the bird cherry-oat aphid Rhopalosiphum padi. This study provides the first evidence that suction trap data are reliable proxies of aphid colonizing rates in cereal fields in autumn and can be a nice alternative to the very time-consuming crop sampling. The proportion of winged aphids landing in cereal fields is shown to vary between regions according to the degree of investment of local R. padi population in sexual reproduction. Results also indicate that under autumnal field conditions, less than 5% of winged aphids survive more than 10 days after landing. This HBM provides the basis of a predictive model for aphid crop colonization that fully accounts for all sources of uncertainty. It should be of great value to improve the trust of users in any decision making systems.

Oceanic larvae of the European (Anguilla anguilla) and American (A. rostrata) eels have to cross the Atlantic Ocean from the Sargasso Sea to European or North American coasts before entering continental habitats. In some European rivers, eel recruitment is now

International audience; The migration duration of European eel (Anguilla anguilla) larvae (leptocephali) from the spawning areas in the Sargasso Sea to the European continental shelf remains highly controversial, with estimates varying from 6 months to more than 2 yr. We estimated the fastest migration period and the shortest distance travelled by eel larvae by simulating Lagrangian particles released in the Sargasso Sea and by simulating a range of larval behaviours (fixed-depth drift, vertical diurnal migration and active-depth selection to maximize current velocity). This enabled us to compute (i) a passive drift speed, and (ii) a hypothetic swimming speed needed for European eel larvae to cross the Atlantic in 6 months (i.e., the migration duration estimated from otolith daily growth increments). Our results show that the minimum travel time for an eel larva that is passively drifting was 10 months and 3 days. Active behaviours (vertical diurnal migration and rheotaxis) paradoxically increased the migration period. We found that for leptocephali to cross the Atlantic Ocean in 6 months, they would need to swim a minimum of 3.4 body lengths per second for 8200 km. No larvae have been observed with such swimming capabilities. These results provide evidence that leptocephali cannot cross the Atlantic in 6 months.

European eel decline is now widely observed and involves a large number of factors such as overfishing, pollution, habitat loss, dam construction, river obstruction, parasitism and environmental changes. In the present study, we analysed the influence of environmental conditions in the Sargasso Sea and Atlantic ocean circulation on European glass eel recruitment success. Over a recent 11-year period, we showed a strong positive correlation between an original index of glass eel recruitment and primary production in eel spawning area. Moreover, primary production was negatively correlated with temperature in the Sargasso Sea. Therefore, we used sea temperature as an inverse proxy of marine production. A close negative relationship has been found over the last four decades between long-term fluctuations in recruitment and in sea temperature. These findings were reinforced by the detection of a regime shift in sea temperature that preceded the start of the decline in glass eel recruitment in the early 1980s. By contrast, variations in integrative indices measuring ocean circulation, i.e.\ latitude and strength of the Gulf Stream, did not seem to explain variations in glass eel recruitment. Our results support the hypothesis of a strong bottom-up control of leptocephali survival and growth by primary production in the Sargasso Sea on short and long time-scales. We argue that sea warming in the eel spawning area since the early 1980s has modified marine production and eventually affected the survival rate of European eels at early life stages.

The Indian Ocean Tuna Tagging Program provided a unique opportunity to collect demographic data on the key commercially targeted tropical tuna species in the Indian Ocean. In this paper, we focused on estimating growth rates for one of these species, yellowfin (Thunnus albacares). Whilst most growth studies only draw on one data source, in this study we use a range of data sources: individual growth rates derived from yellowfin that were tagged and recaptured, direct age estimates obtained through otolith readings, and length-frequency data collected from the purse seine fishery between 2000 and 2010. To combine these data sources, we used an integrated Bayesian model that allowed us to account for the process and measurement errors associated with each data set. Our results indicate that the gradual addition of each data type improved the model's parameter estimations. The Bayesian framework was useful, as it allowed us to account for uncertainties associated with age estimates and to provide additional information on some parameters (e.g., asymptotic length). Our results support the existence of a complex growth pattern for Indian Ocean yellowfin, with two distinct growth phases between the immature and mature life stages. Such complex growth patterns, however, require additional information on absolute age of fish and transition rates between growth stanzas. This type of information is not available from the data. We suggest that bioenergetic models may address this current data gap. This modeling approach explicitly considers the allocation of metabolic energy in tuna and may offer a way to understand the underlying mechanisms that drive the observed growth patterns.

International audience

We developed a hierarchical Bayesian integrated life cycle model for Atlantic salmon that improves on the stock assessment approach currently used by ICES and provides some interesting insights about the population dynamics of a stock assemblage. The model is applied to the salmon stocks in eastern Scotland. It assimilates a 40-year (1971–2010) time-series of data compiled by ICES, including the catches in the distant water fisheries at Faroes and West Greenland and estimates of returning fish abundance. Our model offers major improvements in terms of statistical methodology for A. salmon stock assessment. Uncertainty about inferences is readily quantified in the form of Bayesian posterior distributions for parameters and abundance at all life stages, and the model could be adapted to provide projections based on the uncertainty derived from the estimation phase. The approach offers flexibility to improve the ecological realism of the model. It allows the introduction of density dependence in the egg-to-smolt transition, which is not considered in the current ICES assessment method. The results show that this modifies the inferences on the temporal dynamics of the post-smolt marine survival. In particular, the overall decrease in the marine survival between 1971 and 2010 and the sharp decline around 1988–1990 are dampened when density dependence is considered. The return rates of smolts as two-sea-winter (2SW) fish has declined in a higher proportion than return rates as one-sea-winter (1SW) fish. Our results indicate that this can be explained either by an increase in the proportion maturing as 1SW fish or by an increase in the mortality rate at sea of 2SW fish, but the data used in our analyses do not allow the likelihood of these two hypotheses to be gauged.

This paper proposes a hierarchical Bayesian framework for modeling the life cycle of marine exploited fish with a spatial perspective. The application was developed for a nursery-dependent fish species, the common sole (Solea solea), on the Eastern Channel population (Western Europe). The approach combined processes of different natures and various sources of observations within an integrated framework for life-cycle modeling: (1) outputs of an individual-based model for larval drift and survival that provided yearly estimates of the dispersion and mortality of eggs and larvae, from spawning grounds to settlement in several coastal nurseries; (2) a habitat suitability model, based on juvenile trawl surveys coupled with a geographic information system, to estimate juvenile densities and surface areas of suitable juvenile habitat in each nursery sector; (3) a statistical catch-at-age model for the estimation of the numbers-at-age and the fishing mortality on subadults and adults. The approach provided estimates of hidden variables and parameters of key biological significance. A simulation approach provided insight to the robustness of the approach when only weak data are available. Estimates of spawning biomass, fishing mortality, and recruitment were close to the estimations derived from stock-assessment working groups. In addition, the model quantified mortality along the life cycle, and estimated site-specific density-dependent mortalities between settled larvae and age-0 juveniles in each nursery ground. This provided a better understanding of the productivity and the specific contribution of each nursery ground toward recruitment and population renewal. Perspectives include further development of the modeling framework on the common sole and applications to other fish species to disentangle the effects of multiple interacting stress factors (e.g., estuarine and coastal nursery habitat degradation, fishing pressure) on population renewal and to develop risk analysis in the context of marine spatial planning for sustainable management of fish resources.

Rougier, T., Lambert, P., Drouineau, H., Girardin, M., Castelnaud, G., Carry, L., Aprahamian, M., Rivot, E., and Rochard, E. 2012. Collapse of allis shad, Alosa alosa, in the Gironde system (southwest France): environmental change, fishing mortality, or Allee effect? – ICES Journal of Marine Science, 69: 1802–1811. At the end of the 20th century the allis shad population in the Gironde was the largest in Europe. During the first decade of the 21st century, catches declined dramatically by two orders of magnitude, and a fishery moratorium was implemented in 2008. This deterioration in the status of the stock was confirmed by three independent assessments (abundance of juveniles and of potential and effective spawners). Three hypotheses on the cause of the collapse were examined: (i) an environmental change in freshwater and/or in the estuary; (ii) an increase in marine and/or estuarine mortality; and (iii) the presence of an Allee effect. Changes in flow, temperature, and water quality over the period were inconclusive, but remain a possible causative factor. The instantaneous rate of marine (mean: 0.7 year−1, s.e. 0.1 year−1) and estuarine (mean: 2.6 year−1, s.e. 0.1 year−1) mortalities showed no trend between 1991 and 2003. Nevertheless, the past high estuarine (fishing) mortalities combined with a demographic Allee effect in the reproduction dynamics could explain the population collapse and hamper the stock recovery under the moratorium. This conclusion is, however, tentative as it was not possible to prove the presence of the density-dependent mechanism associated with the demographic Allee effect.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]QUASAREViewpoint article; We, members of the Association Francaise d'Halieumetrie, share the conviction that European fisheries have a future. It is time to get off the wrong track. Radical change is required to embark on the path of sustainable development and truly implement the ecosystem approach to fisheries. Today, high fishing pressure is deployed to catch a rare resource, which in return is responsible for the rarity. We must reverse the situation: an abundant resource that affords high catches applying moderate fishing pressure. All management tools and especially all actors must be mobilized. The transition is not simple, and European solidarity must accompany the changes. It is well worth the effort. By reducing fishing pressure, it will be possible in the medium term to restore fish stocks, to make ecosystems return to good ecological status, to stabilize and even increase catches and to considerably improve economic efficiency. This is obviously in the interest of fishers but it is also in the interest of future generations and all users of this common heritage that is the sea. (C) 2011 Elsevier B.V. All rights reserved.

Sp. Iss. SI Proceedings of the Seventh International Symposium on Flatfish Ecology, Part I; Estuaries and coastal waters are essential nursery habitats for many marine species, and especially for flatfishes. Thus, investigating how anthropogenic disturbances affect the quality of these habitats is of major importance to understand their consequences on the population renewal of marine species. The aim of the present study was to analyse the effects of estuarine habitat degradation on the population of the common sole in the Eastern Channel, a key species in the fish community and fisheries in this area. We especially focused on the drastic drop in the surface area and on the low water quality of the Seine estuary, the main river of the Eastern Channel. A geographic Information System (GIS) was used to develop quantitative maps of sole nursery habitats in the Eastern Channel by using a habitat suitability model based on bathymetry and sediment structure. This approach indicated that juvenile densities are low in the Seine estuary with regards to other nursery sectors. Then, thanks to historical maps of the Seine estuary, habitat suitability maps were built for key dates in the modifications of this estuary since 1850. This backward predictive approach suggests that habitat loss in the Seine estuary has led to a 42% decrease of its nursery capacity. As the density of juvenile sole in the Seine estuary is low in comparison to other sectors, this represents only a 3% loss at the sole population scale, in the Eastern Channel. However, when we assumed that prior to anthropogenic disturbance the juvenile density in the Seine estuary might have been equivalent to the current density of adjacent sectors with higher quality, the loss in abundance could be nearly 23% (8-36%). Results suggest that the loss in habitat surface combined with habitat degradation has led to an important loss in the contribution of the Seine estuary nursery to the whole sole population in the Eastern Channel. (C) 2009 Elsevier BM. All rights reserved.

Robert, M., Faraj, A., McAllister, M. K., and Rivot, E. 2010. Bayesian state-space modelling of the De Lury depletion model: strengths and limitations of the method, and application to the Moroccan octopus fishery. – ICES Journal of Marine Science, 67: 1272–1290. The strengths and limitations of a Bayesian state-space modelling framework are investigated for a De Lury depletion model that accommodates two recruitment pulses per year. The framework was applied to the Moroccan fishery for common octopus (Octopus vulgaris) between 1982 and 2002. To allow identifiability, natural mortality (M) and the recruitment rhythm were fixed, and the variance of both process and observation errors were assumed to be equal. A simulation–estimation (SE) approach was derived to test the performance of the method. If the data showed responses to harvest, the estimates of the most important figures, i.e. the initial abundance and the second recruitment pulse, were accurate, with relatively small bias. Results confirm that greater depletion yields smaller bias and uncertainty and that inferences are sensitive to the mis-specification of M. The 21 depletion series in the Moroccan dataset were jointly treated in a hierarchical model including random walk to capture the systematic fluctuations in estimates of catchability and initial abundance. The model provides estimates of the annual recruitment and monthly octopus population size. The recruitment estimates could be used to investigate the link between recruitment variability and the coastal North African upwelling regime to improve understanding of the dynamics and management of octopus stocks.

Recent advances in technologies have lead to a vast influx of data on movements, based on discrete recorded position of animals or fishing boats, opening new horizons for future analyses. However, most of the potential interest of tracking data depends on the ability to develop suitable modelling strategies to analyze trajectories from discrete recorded positions. A serious modelling challenge is to infer the evolution of the true position and the associated spatio-temporal distribution of behavioural states using discrete, error-prone and incomplete observations. In this paper, a Bayesian Hierarchical Model (HBM) using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from satellite-based vessel monitoring systems (VMS). The analysis seeks to enhance the definition of the fishing pressure exerted on fish stocks, by discriminating between the different behavioural states of a fishing trip, and also by quantifying the relative importance of each of these states during a fishing trip. The HBM approach is tested to analyse the behaviour of pelagic trawlers in the Bay of Biscay. A hidden Markov chain with a regular discrete time step is used to model transitions between successive behavioural states (e.g., fishing, steaming, stopping (at Port or at sea)) of each vessel. The parameters of the movement process (speed and turning angles) are defined conditionally upon the behavioural states. Bayesian methods are used to integrate the available data (typically VMS position recorded at discrete time) and to draw inferences on any unknown parameters of the model. The model is first tested on simulated data with different parameters structures. Results provide insights on the potential of HBM with HMP to analyze VMS data. They show that if VMS positions are recorded synchronously with the instants at which the process switch from one behavioural state to another, the estimation method provides unbiased and precise inferences on behavioural states and on associated movement parameters. However, if the observations are not gathered with a sufficiently high frequency, the performance of the estimation method could be drastically impacted when the discrete observations are not synchronous with the switching instants. The model is then applied to real pathways to estimate variables of interest such as the number of operations per trip, time and distance spent fishing or travelling. (C) 2010 Elsevier B.V. All rights reserved.

National audience; Pour la première fois, un modèle permet de prévoir les infestations de champs cultivés par un ravageur à partir de données issues de pièges à aspiration du réseau Agraphid. Il s’agit précisément des infestations d’orges d’hiver à l’automne par le puceron Rhopalosiphum padi vecteur de la JNO. Ce résultat laisse espérer pouvoir faire fonctionner divers OAD (modèles de prévision des risques liés à des ravageurs ailés voire simples seuils de traitement) à partir de données recueillies automatiquement et journellement par de tels pièges, au lieu d’exiger des données issues de comptages de terrain difficiles à fournir. Cela rendrait utilisables certains OAD négligés aujourd’hui car trop difficiles à « nourrir » et pourrait concerner d’autres espèces de pucerons, sur maïs par exemple, voire d’autres insectes. Mais pour que ces OAD, une fois étalonnés, puissent fonctionner à partir des jeux de données issues des pièges à aspiration, encore faut-il que ces pièges perdurent. Il faut donc relancer le réseau Agraphid dont seuls deux pièges fonctionnent aujourd’hui.

International audience; Using Lagrangian simulations, based on circulation models over three different hydroclimatic periods in the last 45 years in the North Atlantic Ocean, the trans-Atlantic migration of the European eel Anguilla anguilla leptocephali was simulated via the passive drift of particles released in the spawning area. Three different behaviours were modelled: drifting at fixed depth, undergoing a vertical migration or choosing the fastest currents. Simulations included mortality hypotheses to estimate a realistic mean migration duration and relative survival of A. anguilla larvae. The mean migration duration was estimated as 21 months and the mortality rate as 3·8 per year, i.e. < 0·2% of A. anguilla larvae may typically survive the trans-Atlantic migration.

Glass eel abundances are declining worldwide. This has mostly been attributed to direct impacts of human activities such as overfishing or habitat loss and degradation, whilst the potential influence of changes in oceanic conditions has received less attention. Eel are characterized by a complex and still enigmatic life cycle that includes a trans-oceanic spawning and larval migration. The apparent synchrony in the decline of eel populations worldwide suggests that the oceanic mechanisms involved are similar for all populations. We analyse the relationships between oceanic conditions in eel spawning areas and glass eel recruitment success of the 3 most commercially important species of the genus Anguilla: A. anguilla, A. rostrata, and A. japonica. We provide evidence that the survival of eel larvae is strongly correlated with food availability during their early life stages. Over the last 4 decades, changes in the marine production related to global warming may have led to the decline of European, American and Japanese eel populations. In the Pacific and Atlantic Oceans, the shifts in the temperature regime detected in the late 1970s were followed by shifts in the recruitment regime of glass eel for the 3 species. The decrease in primary production through climate-driven processes has therefore affected the recruitment of eel populations.

International audience; Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i) an emotive simulated example, ii) application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife.

The Bayesian state-space modelling framework allows us to derive inferences on stochastic stage-structured population dynamics models from multiple series of sequential observations with measurement or sampling errors. A state-space model works from the coupling of two models. The first one mimics the dynamics by conditional Markovian transitions between successive hidden states. The second model describes the observation process with random errors. Statistical inferences on states variables and parameters are easily performed via Bayesian Monte Carlo Markov chains (MCMC) methods. The flexibility of MCMC methods allows us to analyse a wide range of state-space models with non-linear relationships in the dynamic and observation equations, and non-Gaussian error structure just as well. The Bayesian paradigm is efficient for deriving quantitative diagnostics on a probability based rationale. We illustrate the value of this framework by fitting a stage-structured life cycle model for Atlantic salmon (Salmo salar) to a data set resulting from the survey of the population of the river Oir (Lower Normandy, France) between 1984 and 2001. The system dynamics includes non-linear regulation and has a probabilistic structure accommodating for both the environmental and the demographic stochasticity. The observation model consists in capture-mark-recapture experiments for the evaluation of the runs of downstream migrating juveniles (smolts) and upstream migrating spawners, and random sampling for demographic features. A full Bayesian treatment of the model is carried out by means of Gibbs sampling. Outputs of main interest consist in the joint posterior distribution of all the model parameters and state variables such as the smolt and spawner runs.

International audience; The understanding of the dynamics of fishing vessels is of great interest to characterize the spatial distribution of the fishing effort and to define sustainable fishing strategies. It is also a prerequisite for anticipating changes in fishermen's activity in reaction to management rules, economic context, or evolution of exploited resources. Analyzing the trajectories of individual vessels offers promising perspectives to describe the activity during fishing trips. A hidden Markov model with two behavioral states (steaming and fishing) is developed to infer the sequence of non‐observed fishing vessel behavior along the vessel trajectory based on Global Positioning System (GPS) records. Conditionally to the behavior, vessel velocity is modeled with an autoregressive process. The model parameters and the sequence of hidden behavioral states are estimated using an expectation–maximization algorithm, coupled with the Viterbi algorithm that captures the most credible joint sequence of hidden states. A simulation approach was performed to assess the influence of contrast between the model parameters and of the path length on the estimation performances. The model was then fitted to four original GPS tracks recorded with a time step of 15 min derived from volunteer fishing vessels operating in the Channel within the IFREMER RECOPESCA project. Results showed that the fishing activity performed influenced the estimates of the velocity process parameters. Results also suggested future inclusion of variables such as tide currents within the ecosystem approach of fisheries.