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Summary1. Approximate Bayesian computation (ABC), a type of likelihood-free inference, is a family of statistical techniques to perform parameter estimation and model selection. It is increasingly used in ecology and evolution, where the models used can be too complex to be handled with standard likelihood techniques. The essence of ABC techniques is to compare simulation outputs to observed data, in order to select the parameter values of the simulations which best fit the data. ABC techniques are thus computationally demanding. This constitutes a key limitation to their implementation. 2. We introduce the R package 'EasyABC' that enables one to launch a series of simulations from the R platform and to retrieve the simulation outputs in an appropriate format for post-processing. The 'EasyABC' package further implements several efficient parameter sampling schemes to speed up the ABC procedure: on top of the standard prior sampling, it implements various algorithms to perform sequential (ABC-sequential) and Markov chain Monte Carlo (ABC-MCMC) sampling schemes. The package functions can furthermore make use of parallel computing. 3. The R package 'EasyABC' complements the package 'abc' which enables various post-processing of simulation outputs. 'EasyABC' makes several state-of-the-art ABC implementations available to the large community of R users in the fields of ecology and evolution. It is a freely available R package under the GPL license, and it can be downloaded at http://cran.r-project.org/web/packages/EasyABC/index.html.

Open-cavity flows are known to exhibit a few well-defined peaks in the power spectral distribution of velocity or pressure signals recorded close to the impinging corner. The measured frequencies are in fact common to the entire flow, indicating some global organisation of the flow. The modal structures, i.e. the spatial distribution of the most characteristic frequencies in the flow, are experimentally investigated using time-resolved particle image velocimetry. Each spatial point, of the resulting twodimension-two-component (2D-2C) velocity fields, provides time-resolved series of the velocity components V x and V y , in a (x, y) streamwise plane orthogonal to cavity bottom. Each local time-series is Fourier-transformed, such as to provide the spectral distribution at any point of the PIV-plane. One finally obtains the spatial structure associated with any frequency of the Fourier spectrum. Some of the modal spatial structures are expected to represent the nonlinear saturation of the global modes, against which the stationary solution of the Navier-Stokes equations may have become linearly unstable. Following Rowley et al. (J Fluid Mech 641:115-127, 2009), our experimental modal structures may even correspond to the Koopman modes of this incompressible cavity flow.

Sensitivity analysis (SA) is a significant tool for studying the robustness of results and their sensitivity to uncertainty factors in life cycle assessment (LCA). It highlights the most important set of model parameters to determine whether data quality needs to be improved, and to enhance interpretation of results. Interactions within the LCA calculation model and correlations within Life Cycle Inventory (LCI) input parameters are two main issues among the LCA calculation process. Here we propose a methodology for conducting a proper SA which takes into account the effects of these two issues. This study first presents the SA in an uncorrelated case, comparing local and independent global sensitivity analysis. Independent global sensitivity analysis aims to analyze the variability of results because of the variation of input parameters over the whole domain of uncertainty, together with interactions among input parameters. We then apply a dependent global sensitivity approach that makes minor modifications to traditional Sobol indices to address the correlation issue. Finally, we propose some guidelines for choosing the appropriate SA method depending on the characteristics of the model and the goals of the study. Our results clearly show that the choice of sensitivity methods should be made according to the magnitude of uncertainty and the degree of correlation.

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The article describes a riverscape approach based on landscape ecology concepts, which aims at studying the multiscale relationships between the spatial pattern of stream fish habitat patches and processes depending on fish movements. A review of the literature shows that few operational methods are available to study this relationship due to multiple methodological and practical challenges inherent to underwater environments. We illustrated the approach with literature data on a cyprinid species (Barbus barbus) and an actual riverscape of the Seine River, France. We represented the underwater environment of fishes for different discharges using two-dimensional geographic information system-based maps of the resource habitat patches, defined according to activities (feeding, resting, and spawning). To quantify spatial patterns at nested levels (resource habitat patch, daily activities area, subpopulation area), we calculated their composition, configuration, complementation, and connectivity with multiple spatial analysis methods: patch metrics, moving-window analysis, and least cost modeling. The proximity index allowed us to evaluate habitat patches of relatively great value, depending on their spatial context, which contributes to the setting of preservation policies. The methods presented to delimit potential daily activities areas and subpopulation areas showed the potential gaps in the biological connectivity of the reach. These methods provided some space for action in restoration schemes.

Within the context of ongoing environmental changes, the life history of diadromous fish represents a real potential for exploring and colonizing new environments due to high potential dispersal abilities. The use of dynamic approaches to assess how these species will respond to climate change is a challenging issue and mechanistic models able to incorporate biological and evolutionary processes are a promising tool. To this end we developed an individual-based model, called GR3D (Global Repositioning Dynamics for Diadromous fish Distribution), combining climatic requirements and population dynamics with an explicit dispersal process to evaluate potential evolution of their distribution area in the context of climatic change. This paper describes thoroughly the model structure and presents an exploratory test case where the repositioning of a virtual allis shad (Alosa alosa L.) population between two river catchments under a scenario of temperature increase was assessed. The global sensitivity analysis showed that landscape structure and parameters related to sea lifespan and to survival at sea were crucial to determine the success of colonization. These results were consistent with the ecology of this species. The integration of climatic factors directly into the processes and the explicit dispersal process make GR3D an original and relevant tool to assess the repositioning dynamics and persistence of diadromous fish facing climate change.