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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

Introduction 308Review of existing models and simulation tools 309Population and ecosystem modelling 309Non-spatial models and the efficacy of no-take zones 309 Metapopulation models 310Spatially explicit demographic models 312Multispecific and ecosystem approaches 318Modelling exploitation and management policies 320Dynamics of the spatial allocation of fishing effort 320 Mixed fisheries 321Bioeconomic modelling 323Policy modelling and fishers' response to management 323A generic simulation tool for policy evaluation 325Spatial and seasonal scales in the model 325 AbstractThis paper deals with the design of modelling tools suitable for investigating the consequences of alternative policies on the dynamics of resources and fisheries, such as the evaluation of marine protected areas (MPA). We first review the numerous models that have been developed for this purpose, and compare them from several standpoints: population modelling, exploitation modelling and management measure modelling. We then present a generic fisheries simulation model, Integration of Spatial Information for FISHeries simulation (ISIS-Fish). This spatially explicit model allows quantitative policy screening for fisheries with mixed-species harvests. It may be used to investigate the effects of combined management scenarios including a variety of policies: total allowable catch (TAC), licenses, gear restrictions, MPA, etc. Fisher's response to management may be accounted for by means of decision rules conditioned on population and exploitation parameters. An application to a simple example illustrates the relevance of this kind of tool for policy screening, particularly in the case of mixed fisheries. Finally, the reviewed models and ISIS-Fish are discussed and confronted in the light of the underlying assumptions and model objectives. In the light of this discussion, we identify desirable features for fisheries simulation models aimed at policy evaluation, and particularly MPA evaluation.

Marine ecosystems evolve under many interconnected and area-specific pressures. To fulfil society's intensifying and diversifying needs while ensuring ecologically sustainable development, more effective marine spatial planning and broader-scope management of marine resources is necessary. Integrated ecological-economic fisheries models (IEEFMs) of marine systems are needed to evaluate impacts and sustainability of potential management actions and understand, and anticipate ecological, economic and social dynamics at a range of scales from local to national and regional. To make these models most effective, it is important to determine how model characteristics and methods of communicating results influence the model implementation, the nature of the advice that can be provided and the impact on decisions taken by managers. This article presents a global review and comparative evaluation of 35 IEEFMs applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes although not all the models reviewed achieve that. Modellers must invest more time to make models user friendly and to participate in management fora where models and model results can be explained and discussed. Such involvement is beneficial to all parties, leading to improvement of models and more effective implementation of advice, but demands substantial resources which must be built into the governance process. It takes time to develop effective processes for using IEEFMs requiring a long-term commitment to integrating multidisciplinary modelling advice into management decision-making. K E Y W O R D Sbio-economic models, comparative model evaluation, fisheries management advice, integrated ecological-economic fisheries models, marine spatial planning and cross-sector management, performance criteria and scales and risks, use and acceptance and implementation and communication and flexibility and complexity | INTRODUCTIONThere is a growing need for tools to evaluate policies and assess tradeoffs in management of marine resources and provision of ecosystem services such as fishing, aquaculture, renewable energy, shipping, conservation and recreation (Cormier, Kannen, Elliott, & Hall, 2015;Degnbol & Wilson, 2008;EU 2014;Langlois, Fréon, Steyer, Delgenés, & Hélias, 2014;White et al., 2012). It is necessary to elaborate and apply common principles and broader, interdisciplinary management evaluation in the use of marine space involving several types of activities and sectors Soma et al., 2013;Stelzenmüller et al., 2013;Sundblad et al., 2014). Policymakers need to know the costs and benefits of conserving ecosystem goods and services to manage them sustainably. Moreover, according to an ecosystembased approach to management, specific pressures, associated uncertainties and risks need to be taken into account (Douvere, 2008;Ehler & Douvere, 2009;Gi...

This study assesses the impact species ecology, fish reactions, and natural behaviour have on visual strip transect counts of deepwater fish carried out with an ROV (remotely operated vehicle). Two terraces and one canyon were visited on the continental slope of the Bay of Biscay. Species such as rabbit fish (Chimaeridae) and North Atlantic codling (Lepidion eques) appear to have avoided the ROV. The vertical distance off the bottom provided evidence that some individuals, in particular slickheads (Alepocephalidae) might have been missed by being above the ROV. GLM modelling showed the importance of depth, current speed, and relative surveying direction on transect counts. Natural and reaction behaviour of deep-sea fish will lead to variable and biased population density estimates.