Murviel-lès-Montpellier, France
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Perronne R.,CNRS Agroecology Lab | Perronne R.,French National Institute for Agricultural Research | Munoz F.,UM2 | Munoz F.,French Institute of Pondicherry | And 4 more authors.
Perspectives in Plant Ecology, Evolution and Systematics | Year: 2017

One of the fundamental challenges in ecology is to identify the signature of assembly mechanisms resulting from patterns of community composition. For this purpose, the trait-based approach has promoted the analysis of functional trait distributions within communities. Until now, much attention has been paid to the design of appropriate null models and the definition of relevant functional metrics for inferring community assembly mechanisms from trait distributions. However, less consideration were given to the set of methodological choices preceding the statistical analysis – i.e. from designing a sampling scheme to measuring traits – and how likely they influence the conclusions drawn, as this may subject the analysis to methodological biases. In this regard, a comprehensive perspective on how the overall set of methodological choices influence the inference of community assembly mechanisms is needed. We extensively reviewed recent studies that have addressed animal and plant community assembly by applying a trait-based null model approach. We analyzed how the set of methodological choices in these studies depended on the mechanisms of interest and how they could influence the conclusions drawn by the authors. We found that methodological choices only weakly depended on the hypothesized assembly mechanisms studied by the authors, especially because the two main assembly mechanisms hypothesized, i.e. environmental filtering and limiting similarity, were often tested based on a common experimental design. In contrast, the detection of assembly mechanisms was strongly dependent on the sampling scale, the type of data, the origin of trait values and the delineation of the reference species pool, while less affected by the null model and the functional metrics chosen. These results underline plausible methodological biases in favor of the detection of certain mechanisms to the detriment of others. In addition, there was a significant relationship between the predominant mechanisms concluded by the authors and the type of organism used as biological model, suggesting either that the methodological choices depend on a common strategy used by the different authors when studying similar biological models, or that the methodological choices depended on certain particular properties of the organisms. From this extensive review, we highlight major conceptual and methodological issues that need to be addressed in trait-based null model approaches. We synthesize the methodological choices relevant to study several assembly mechanisms while minimizing methodological biases. We then derive practical guidelines and emphasize the importance of spatial structure in sampling strategy and null model design, because of the scale-dependent signatures of ecological processes. © 2017 Elsevier GmbH

Hublart P.,UM2 | Ruelland D.,French National Center for Scientific Research | Dezetter A.,IRD Montpellier | Jourde H.,UM2
Hydrology and Earth System Sciences | Year: 2015

The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modelling of a mesoscale Andean catchment (1515 km2) over a 30-year period (1982-2011). The modelling process was decomposed into six model-building decisions related to the following aspects of the system behaviour: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modelling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional (4-D) space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain eight model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modelling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations. © Author(s) 2015.

Destercke S.,CIRAD - Agricultural Research for Development | Destercke S.,French National Center for Scientific Research | Buche P.,French National Institute for Agricultural Research | Buche P.,French National Center for Scientific Research | Guillard V.,UM2
Fuzzy Sets and Systems | Year: 2011

In this paper, we propose an approach to query a database when the user preferences are bipolar (i.e., express both constraints and wishes about the desired result) and the data stored in the database are imprecise. Results are then completely ordered with respect to these bipolar preferences, giving priority to constraints over wishes. Additionally, we propose a treatment that allows us to guarantee that any query will return a result, even if no element satisfies all constraints specified by the user. Such a treatment may be useful when user's constraints are unrealistic (i.e., cannot be all satisfied simultaneously) and when the user desires a guaranteed result. The approach is illustrated on a real-world problem concerning the selection of optimal packaging for fresh fruits and vegetables. © 2011 Elsevier B.V. All rights reserved.

Hublart P.,UM2 | Ruelland D.,French National Center for Scientific Research | Dezetter A.,IRD Montpellier | Jourde H.,UM2
IAHS-AISH Proceedings and Reports | Year: 2014

Viticulture in semi-arid mountainous regions remains entirely dependent on surface water resources (SWR) to satisfy crop water needs through irrigation. Climate change is expected to increase the risk of water shortage by altering the timing and duration of both hydrological and phenological events while increasing crop evapotranspiration. This study focuses on the estimation of IWR in the Claro River Basin Chile (4196 km2) over the last decade (2002-2011). First, a process-oriented phenological model based on the accumulation of both chilling and forcing rates was built to predict the dates of budburst, full bloom and harvest events on the basin. Then a crop coefficient (Kc) was adapted to each phenological stage and water requirements were computed following a water balance approach. Analysis of the ratio between simulated IWR and observed SWR at a 10-day time step show that water needs have frequently been unsatisfied over the period considered. This work is a first step towards an in-depth analysis of the impact of hydro-climatic variability on the capacity of the river system to satisfy IWR under various climate change and water use scenarios. © Copyright 2014 IAHS Press.

Ruelland D.,French National Center for Scientific Research | Dezetter A.,IRD Montpellier | Hublart P.,UM2
IAHS-AISH Proceedings and Reports | Year: 2014

This study analyses the sensitivity of a hydrological model to different ways of interpolating climate forcing on the Elqui basin (5660 km2) in the Chilean Andes. A 36-year period (1976-2011) was chosen in order to account for the hydro-climatic variability. Precipitation and using the inverse distance weighted methods were interpolated on a 5 × 5 km grid based on 12 and eight stations, respectively. Elevation effects on precipitation and temperature distribution were considered using a digital elevation model. Two precipitation datasets (with and without a mean altitudinal gradient) and three temperature datasets (using constant or monthly lapse rates based on altitudinal bands) were computed. All dataset combinations were assessed through the calibration of the GR4j model including a snow reservoir. Calibration was performed by the succession of Rosenbrock and simplex algorithms using a multi-objective function. Results show that the dataset based on a constant lapse rate of 6.5°C/km for temperature and no elevation effects for precipitation is sufficient to accurately simulate discharge and the snowmelt regime of the catchment over the last 30 years. © Copyright 2014 1AHS Press.

Milano M.,UM2 | Ruelland D.,French National Center for Scientific Research | Fernandez S.,Plan Bleu | Dezetter A.,IRD Montpellier | And 2 more authors.
Comptes Rendus - Geoscience | Year: 2012

The Mediterranean basin has been identified as one of the world's most vulnerable regions to climatic and anthropogenic changes. A methodology accounting for the basin specific conditions is developed to assess the current and future water stress state of this region. The medium-term evolution of water stress is investigated using climatic scenarios and a water-use scenario based on efficiency improvements following the recommendations of the Mediterranean Strategy for Sustainable Development. Currently, the southern and eastern rims are experiencing high to severe water stress. By the 2050 horizon, a 30-50% decline in freshwater resources is simulated over most of the Mediterranean basin. While total water withdrawals would stabilize, or even decrease (10-40%), in several northern catchments, they would double in southern and eastern catchments. These changes should significantly increase water stress over the Mediterranean basin and exacerbate the disparities between rims. © 2012 Académie des sciences.

Siupka P.,University of Aarhus | Hamming O.J.,University of Aarhus | Fretaud M.,Institute Pasteur Paris | Fretaud M.,French National Center for Scientific Research | And 4 more authors.
Genes and Immunity | Year: 2014

The class II cytokine family consists of small -helical signaling proteins including the interleukin-10 (IL-10)/IL-22 family, as well as interferons (IFNs). They regulate the innate immune response and in addition have an important role in protecting epithelial tissues. Teleost fish possess a class II cytokine system surprisingly similar to that of humans, and thus zebrafish offers an attractive model organism for investigating the role of class II cytokines in inflammation. However, the evolution of class II cytokines is critical to understand if we are to take full advantage of zebrafish as a model system. The small size and fast evolution of these cytokines obscure phylogenetic analyses based purely on sequences, but one can overcome this obstacle by using information contained within the structure of those molecules. Here we present the crystal structure of IL-22 from zebrafish (zIL-22) solved at 2.1 Å, which displays a typical class II cytokine architecture. We generated a structure-guided alignment of vertebrate class II cytokines and used it for phylogenetic analysis. Our analysis suggests that IL-22 and IL-26 arose early during the evolution of the IL-10-like cytokines. Thus, we propose an evolutionary scenario of class II cytokines in vertebrates, based on genomic and structural data. © 2014 Macmillan Publishers Limited All rights reserved.

Milano M.,UM2 | Ruelland D.,French National Center for Scientific Research | Dezetter A.,IRD Montpellier | Fabre J.,French National Center for Scientific Research | And 2 more authors.
Journal of Hydrology | Year: 2013

Worldwide studies have shown that the Mediterranean region is one of the most vulnerable areas to water crisis. The region is characterized by limited and unequally distributed water resources and increasing water demands. The Ebro catchment (85,000km2, Spain) is representative of this context. Since the late 1970s, a negative trend in river discharge has been observed, attributed to a decrease in mean precipitation, and a rise in mean temperature and in water consumption. Finally, over 230 storage dams regulate river discharge. In this context, an integrated water resources modeling framework was developed to evaluate the current and future capacity of water resources to meet domestic and agricultural water demands as well as environmental flow requirements. The approach was driven by a conceptual rainfall-runoff model generating water supplies and by a demand driven storage dam model. The approach defines current pressures on water resources and evaluates future changes in water allocation in the medium term under climatic and water use scenarios, considering changes in population and in irrigated areas. Currently, water demands in the Ebro catchment are satisfied. In 2050, water resources are projected to decrease by 15-35% during spring and summer, leading to growing competition among users and severe water shortages for irrigated agriculture. This study provides an original approach to identify the most vulnerable regions to water use conflicts. It also highlights the interest of integrated modeling for complete analysis of the ability of water resources to meet water demands in complex change scenarios as a support for decision making. © 2013 Elsevier B.V.

Hublart P.,UM2 | Ruelland D.,French National Center for Scientific Research | Dezetter A.,IRD Montpellier | Jourde H.,UM2
IAHS-AISH Proceedings and Reports | Year: 2013

This study aims to develop an integrated modelling approach to assess current and future trends in water availability for agricultural purposes on the upper Elqui basin (Chile). A hydrological model including a snow reservoir was combined with an agricultural water demand model to provide an index of the capacity to meet water needs. Particular account has been taken of flow regulation via a storage-dam by modelling the reservoir water balance and its operating rules, and by dividing the basin into two sub-basins located respectively upstream and downstream of the dam. The modelling chain was applied and tested over a long reference period (1979-2008) and then run over 2041-2060 under the constraint of four climate scenarios statistically downscaled from various GCMs. Simulations of the basin outlet discharge show a fair degree of realism over the reference period, despite a reproduction of peak flows which tends to deteriorate in validation. Although the dam model and the agricultural water demand model could be improved in the future, they already provide reliable simulations with regard to observed dam releases on the one hand, and to withdrawal authorizations for irrigation on the other. In spite of significant discrepancies, the climate scenarios all lead to a decrease in the capacity to meet water needs at the height of the irrigation period (from December to March). This can be notably explained by less abundant precipitation (-22 to 48%) according to three of the four climate scenarios and by earlier peak flows for two scenarios due to the impact of higher temperatures (+1.7 to 2.1°C) on the snowmelt regime. This study is a first step towards improving the efficiency of the different models and assessing the propagation of uncertainties through the modelling chain. © 2013 IAHS Press.

Huth G.,Montpellier University | Lesne A.,CNRS Condensed Matter Physics Laboratory | Munoz F.,UM2 | Pitard E.,Montpellier University
Physica A: Statistical Mechanics and its Applications | Year: 2014

Percolation offers acknowledged models of random media when the relevant medium characteristics can be described as a binary feature. However, when considering habitat modeling in ecology, a natural constraint comes from nearest-neighbor correlations between the suitable/unsuitable states of the spatial units forming the habitat. Such constraints are also relevant in the physics of aggregation where underlying processes may lead to a form of correlated percolation. However, in ecology, the processes leading to habitat correlations are in general not known or very complex. As proposed by Hiebeler (2000), these correlations can be captured in a lattice model by an observable aggregation parameter q, supplementing the density p of suitable sites. We investigate this model as an instance of correlated percolation. We analyze the phase diagram of the percolation transition and compute the cluster size distribution, the pair-connectedness function C(r) and the correlation function g(r). We find that while g(r) displays a power-law decrease associated with long-range correlations in a wide domain of parameter values, critical properties are compatible with the universality class of uncorrelated percolation. We contrast the correlation structures obtained respectively for the correlated percolation model and for the Ising model, and show that the diversity of habitat configurations generated by the Hiebeler model is richer than the archetypal Ising model. We also find that emergent structural properties are peculiar to the implemented algorithm, leading to questioning the notion of a well-defined model of aggregated habitat. We conclude that the choice of model and algorithm has strong consequences on what insights ecological studies can get using such models of species habitat. © 2014 Elsevier B.V. All rights reserved.

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