Search

1. Theory in ecology and evolution often relies on the analysis of invasion processes, and general approaches exist to understand the early stages of an invasion. However, predicting the long-term transformations of communities following an invasion remains a challenging endeavour. 2. We propose a general analytical method that uses both resident community and invader dynamical features to predict whether an invasion causes large long-term impacts on the invaded community. 3. This approach reveals a direction in which classic invasion analysis, based on initial invasion growth rate, can be extended. Indeed, we explain how the density dependence of invasion growth, if properly defined, synthetically encodes the long-term biotic transformations caused by an invasion, and therefore predicts its ultimate outcome. This approach further clarifies how the density dependence of the invasion growth rate is as much a property of the invading population as it is one of the invaded community. 4. Our theory applies to any stable community model, and directs us towards new questions that may enrich the toolset of invasion analysis, and suggests that indirect interactions and dynamical stability are key determinants of invasion outcomes. Funding Agencies|H2020 European Research Council [666971]; Agence Nationale de la RechercheFrench National Research Agency (ANR)European Commission [ANR-10-LABX-41]; VetenskapsradetSwedish Research Council [VR-2017-05245]; Irish Research CouncilIrish Research Council for Science, Engineering and Technology [IRCLA/2017/186]

International audience; In the context of building acoustics and the acoustic diagnosis of an existing room, this paper introduces and investigates a new approach to estimate mean absorption coefficients solely from a room impulse response (RIR). This inverse problem is tackled via virtually-supervised learning, namely, the RIR-to-absorption mapping is implicitly learned by regression on a simulated dataset using artificial neural networks. We focus on simple models based on well-understood architectures. The critical choices of geometric, acoustic and simulation pa- rameters used to train the models are extensively discussed and studied, while keeping in mind conditions that are representative of the field of building acoustics. Estimation errors from the learned neural models are compared to those obtained with classical formulas thatrequire knowledge of the room's geometry and reverberation times. Extensive comparisons made on a variety of simulated test sets highlight different conditions under which the learned models can overcome the well-known limitations of the diffuse sound field hypothesis under-lying these formulas. Results obtained on real RIRs measured in an acoustically configurable room show that at 1 kHz and above, the proposed approach performs comparably to classical models when reverberation times can be reliably estimated, and continues to work even when they cannot.

Ground cover management (GCM) is an important agricultural practice used to reduce weed growth, erosion and runoff, and improve soil fertility. In the present study, an approach to account for GCM is proposed in the modeling of pesticide emissions to evaluate the environmental sustainability of agricultural practices. As a starting point, we include a cover crop compartment in the mass balance of calculating initial (within minutes after application) and secondary (including additional processes) pesticide emission fractions. The following parameters were considered: (i) cover crop occupation between the rows of main field crops, (ii) cover crop canopy density, and (iii) cover crop family. Two modalities of cover crop occupation and cover crop canopy density were tested for two crop growth stages, using scenarios without cover crops as control. From that, emission fractions and related ecotoxicity impacts were estimated for pesticides applied to tomato production in Martinique (French West Indies) and to grapevine cultivation in the Loire Valley (France). Our results demonstrate that, on average, the presence of a cover crop reduced the pesticide emission fraction reaching field soil by a factor of 3 compared with bare soil, independently of field crop and its growth stage, and cover crop occupation and density. When considering cover exported from the field, ecotoxicity impacts were reduced by approximately 65% and 90%, compared with bare soil for grapevine and tomato, respectively, regardless of the emission distribution used. Because additional processes may influence emission distributions under GCM, such as runoff, leaching, or preferential flow, further research is required to incorporate these processes consistently in our proposed GCM approach. Considering GCM in pesticide emission modeling highlights the potential of soil cover to reduce pesticide emissions to field soil and related freshwater ecotoxicity. Furthermore, the consideration of GCM as common farming practice allows the modeling of pesticide emissions in intercropping systems. Integr Environ Assess Manag 2021;00:1–15. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Societal Impact Statement. Oil palm is the first oil‐producing crop globally, representing nearly 20 million ha. In the recent past, oil palm cultivation has been controversial not only because of land utilisation at the expense of primary tropical forests or health concerns associated with palm oil, but also pollution caused by fertilization (including CO2 produced to synthesise fertilizers). Oil palm fields are heavily fertilized with potassium (K), and thus finding better, more parsimonious methods to monitor K nutrition is more important than ever. Here, we suggest that metabolomics and subsequent machine learning of metabolic signatures represent a promising tool to probe K requirements, opening avenues for precision agriculture in oil palm industry.

La cuenca del Ródano se enfrenta a corto y medio plazo a importantes descensos en el volumen de sus aguas y a cambios en la estacionalidad del régimen hidrológico, lo que generará importantes repercusiones económicas y ambientales. El análisis llevado a cabo en el presente artículo emplea un modelo hidrológico sobre valores climáticos del periodo actual que sirve de referencia para la comparación de cuatro escenarios futuros de Concentración de Gases de Efecto Invernadero (RCP). Los resultados demuestran que se puede producir un importante descenso de la capacidad de producción hídrica de la cuenca, llegando en las condiciones más desfavorables al 30 % del total. La comparación de estos efectos en diversos sistemas ambientales caracterizados por rasgos altitudinales, señala importantes diferencias en el balance hídrico final, siendo las áreas de alta montaña las zonas de la cuenca más sensibles al cambio climático. En conclusión, la evidente pérdida de recursos hídricos supone importantes desafíos y obliga a revisar los actuales sistemas de gestión del agua. In the short and medium term, Rhone basin will have significant discharge water decreases and changes in the seasonality of the hydrological regime, causing serious economic and environmental repercussions. The analysis is carried out through a hydrological model applied to the climatic values of observed period, used as reference in the comparison of two Representative Concentration Pathways (RCPs) scenarios in two future periods. Results have determined a significant decrease in water discharge capacity, being in some cases 30%. Environmental systems characterized by altitudinal features have established important differences in the final water balance, high mountain areas have been the most sensitive areas to climate change. Decrease in water resources will establish important adaptations to the new challenges imposed by these water scarcity scenarios. À court et moyen terme, le bassin du Rhône subit des baisses importantes du volume de ses eaux et des changements dans la saisonnalité du régime hydrologique, générant d'importantes répercussions économiques et environnementales. L'analyse est réalisée à travers un modèle hydrologique appliqué sur les valeurs climatiques de la période actuelle. Ces données serviront de référence dans la comparaison de deux scénarios de concentration de gaz à effet de serre (PCR) dans deux périodes futures. Les résultats ont déterminé une diminution significative de la capacité de production d'eau du bassin, en supposant dans certains cas 30% du total. Les analyses élaborées dans les systèmes environnementaux caractérisés par des caractéristiques altitudinales ont établi des différences importantes dans le bilan hydrique final, montrant les zones de haute montagne comme les zones les plus sensible au changement climatique. La perte de ressources en eau impliquera d'importantes adaptations aux nouveaux défis imposés par ces scénarios de rareté croissante de l'eau.

Background and AimsImproved modelling of carbon assimilation and plant growth to low soil moisture requires evaluation of underlying mechanisms in the soil, roots, and shoots. The feedback between plants and their local environment throughout the whole spectrum soil-root-shoot-environment is crucial to accurately describe and evaluate the impact of environmental changes on plant development. This study presents a 3D functional structural plant model, in which shoot and root growth are driven by radiative transfer, photosynthesis, and soil hydrodynamics through different parameterisation schemes relating soil water deficit and carbon assimilation. The new coupled model is used to evaluate the impact of soil moisture availability on plant productivity for two different groups of flowering plants under different spatial configurations.MethodsIn order to address different aspects of plant development due to limited soil water availability, a 3D FSP model including root, shoot, and soil was constructed by linking three different well-stablished models of airborne plant, root architecture, and reactive transport in the soil. Different parameterisation schemes were used in order to integrate photosynthetic rate with root water uptake within the coupled model. The behaviour of the model was assessed on how the growth of two different types of plants, i.e. monocot and dicot, is impacted by soil water deficit under different competitive conditions: isolated (no competition), intra, and interspecific competition.Key ResultsThe model proved to be capable of simulating carbon assimilation and plant development under different growing settings including isolated monocots and dicots, intra, and interspecific competition. The model predicted that (1) soil water availability has a larger impact on photosynthesis than on carbon allocation; (2) soil water deficit has an impact on root and shoot biomass production by up to 90 % for monocots and 50 % for dicots; and (3) the improved dicot biomass production in interspecific competition was highly related to root depth and plant transpiration.ConclusionsAn integrated model of 3D shoot architecture and biomass development with a 3D root system representation, including light limitation and water uptake considering soil hydraulics, was presented. Plant-plant competition and regulation on stomatal conductance to drought were able to be predicted by the model. In the cases evaluated here, water limitation impacted plant growth almost 10 times more than the light environment.

L’objet du livre d’Alain Pavé, Comprendre la biodiversité. Vrais problèmes et idées fausses, paru en 2019 au Seuil, est de retracer l’histoire du concept de biodiversité qui exprime et concrétise l’inquiétude que suscite son déclin. Son propos est d’examiner comment ce terme polysémique est utilisé, parfois à tort et à travers, étant précisé que le concept intéresse à la fois les sciences de la nature et les sciences de l’homme et de la société dans un souci d’étude, de valorisation et de partage des avantages procurés aux sociétés par la biodiversité. Construit en huit chapitres, l’ouvrage part d’exemples et d’expériences, développe la question des inventaires de biodiversité et des méthodes et métriques utilisées pour la qualifier et la quantifier. L’évolution de la biodiversité au cours des 600 derniers millions d’années est abordée à partir de la phylogénétique moléculaire et le rôle du hasard dans les variations de biodiversité globale est souligné. Quant à la projection dans le futur, elle est abordée par une réflexion critique sur l’existence même d’un déclin de la biodiversité. La manière dont les écologues parlent de la biodiversité, l’étudient et prétendent la conserver est l’objet d’une sévère remise en cause de la démarche scientifique actuelle. D’où la nécessité d’une reconstruction de l’écologie scientifique, y compris dans le domaine de la conservation jugée pratiquée d’une façon passéiste, voire fixiste. Puis l’auteur revient sur le thème de la modélisation qui permet d’intégrer le hasard dans la compréhension de l’évolution des systèmes biologiques. L’ouvrage propose une lecture très personnelle du concept de biodiversité et dénonce le catastrophisme ambiant qui se nourrit d’affirmations jugées péremptoires et trop pessimistes, y compris quand on parle d’une 6e crise d’extinction de masse dont la réalité est contestée. Mais il est loin de faire justice d’une immense littérature qui traduit le dynamisme de la recherche en écologie et évolution. Cette très faible pénétration dans la littérature entraîne souvent le discours dans des considérations naïves et dépassées sur des concepts fondateurs de l’écologie. L’ouvrage paraît être victime du syndrome, bien connu des philosophes des sciences, de la fascination du chercheur pour son outil de travail et la culture de l’effet que ses écrits produisent dans le « grand cirque de la science ». Partielle et partiale, la bibliographie ne fait pratiquement jamais appel aux milliers d’articles publiés chaque année par des milliers d’auteurs dans les grandes revues internationales, y compris celles qui font périodiquement le point sur l’état des connaissances sur ces questions.

This research presents a modeling framework that allows checking the statistical requirements for producing noise maps based on mobile measurements. First, a sound field of reference is created based on a micro-simulation traffic modeling coupled with acoustic modeling, which outputs sound levels each second on a grid of receivers. The aggregated indicators ( L Aeq ) calculated from this sound field serve then as reference. Mobile targets performing measurements evolve within the simulation, aiming to estimate these indicators. The difference between the reference noise map and the one generated by the moving receivers, characterized by the Root Mean Square Error (RMSE), is computed for different aggregation radius of mobile receivers, and as a function of the number of passes-by and to the distance to its nearest cross street. It is observed that the mobile sampling is actually possible and the RMSE can be reduced by setting an optimal aggregation radius and a minimum number of passes-by. With the optimal parameters, 95% of the mobile samples fall within an estimation error interval of [−3.0, 2.2] dBA from the reference. It is also shown that the distance to the nearest cross street affects the estimation error depending on the traffic flow, producing a RMSE greater than 2 dB for distances lower than 30 m.

When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient from poorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes., Frontiers in Ecology and Evolution, 9, ISSN:2296-701X

International audience; In tropical forests, the high proportion of trees showing irregularities at the stem base complicates forest monitoring. For example, in the presence of buttresses, the height of the point of measurement (HPOM) of the stem diameter (DPOM) is raised from 1.3 m, the standard breast height, up to a regular part of the stem. While DPOM is the most important predictor for tree aboveground biomass (AGB) estimates, the lack of harmonized HPOM for irregular trees in forest inventory increases the uncertainty in plot-level AGB stock and stock change estimates. In this study, we gathered an original non-destructive three-dimensional (3D) data set collected with terrestrial laser scanning and close range terrestrial photogrammetry tools in three sites in central Africa. For the 228 irregularly shaped stems sampled, we developed a set of taper models to harmonize HPOM by predicting the equivalent diameter at breast height (DBH′) from a DPOM measured at any height. We analyzed the effect of using DBH′ on tree-level and plot-level AGB estimates. To do so, we used destructive AGB data for 140 trees and forest inventory data from eight 1-ha plots in the Republic of Congo. Our results showed that our best simple taper model predicts DBH′ with a relative mean absolute error of 3.7% (R2 = 0.98) over a wide DPOM range of 17–249 cm. Based on destructive AGB data, we found that the AGB allometric model calibrated with harmonized HPOM data was more accurate than the conventional local and pantropical models. At the plot level, the comparison of AGB stock estimates with and without HPOM harmonization showed an increasing divergence with the increasing share of irregular stems (up to −15%). The harmonization procedure developed in this study could be implemented as a standard practice for AGB monitoring in tropical forests as no additional forest inventory measurements is required. This would probably lead to important revisions of the AGB stock estimates in regions having a large number of irregular tree stems and increase their carbon sink estimates. The growing use of three-dimensional (3D) data offers new opportunities to extend our approach and further develop general taper models in other tropical regions.

In the last decade, humanity has faced many different pandemics such as SARS, H1N1, and presently novel coronavirus (COVID-19). On one side, scientists have developed vaccinations, and on the other side, there is a need to propose models that can help in understanding the spread of these pandemics as it can help governmental and other concerned agencies to be well prepared, especially for pandemics, which spreads faster like COVID-19. The main reason for some epidemic turning into pandemics is the connectivity among different regions of the world, which makes it easier to affect a wider geographical area, often worldwide. Also, the population distribution and social coherence in the different regions of the world are non-uniform. Thus, once the epidemic enters a region, then the local population distribution plays an important role. Inspired by these ideas, we propose two versions of our mobility-based SIR model, (i) fully-mixed and (ii) for complex networks, which especially takes into account real life interactions. To the best of our knowledge, this model is the first of its kind, which takes into account the population distribution, connectivity of different geographic locations across the globe, and individuals' network connectivity information. In addition to presenting the mathematical proof of our models, we have performed extensive simulations using synthetic data to demonstrate the generalization capability of our models. Finally, to demonstrate the wider scope of our model, we applied our model to forecast the COVID-19 cases at county level (Estonia) and regional level (Rhône-Alpes region in France).

International audience; In this paper, we develop an epidemiological model with both environmental (primary infection from the environmental spores reservoir) and direct transmission (secondary infection from an infected host to a susceptible pod). This model simulates the spatiotemporal evolution of cocoa black pod disease caused by Phytophthora megakarya. Since reliable parameter estimation is a central issue for modeling realistic biological systems, we used a mechanistic-statistical approach to estimate model parameters from real observations of a specific cocoa plot. In addition, to refine numerical simulations of the pathosystem, data describing the shade intensity all over the plot were exploited and led to increased model predictions accuracy and also highlighted a higher number of infected pods located in areas of the plot with higher shading intensity. Recommendations in terms of promoting cocoa farming in systems with low shading intensity may be evident if these results are confirmed. Our results also highlight the importance of the environmental spore reservoir in black pod disease dynamics.

The increasing severity of Striga gesnerioides attacks on cowpea across West Africa has been related to its prolificity, seed mobility and longevity, and adaptation to aridity, in a context of agricultural intensification. To understand this fast extension, we analyzed (1) the distributions of the crop and the witchweed with ecological niche modeling and multivariate climate analysis, and (2) the chronological information available from collections and the literature. The ecoclimatic envelope of S. gesnerioides attacks on cowpea is the same as on wild hosts. Consistently, the modeled distribution of cowpea infestations is closely similar to the simple superposition of the parasite model (involving all hosts) and the crop model. Striga gesnerioides infestations are restricted to the driest component of the cultivated cowpea ecoclimatic niche, corresponding to the Sahelian and Sudano-Sahelian belts and the Dahomey gap. Thus, the parasite distribution, determined by its own requirements, does not constrain cowpea cultivation under Guinean climates. The spatial and temporal distributions of S. gesnerioides field infestations are consistent with an earlier impact on cowpea production in eastern West Africa, related itself to a similar trend in cowpea cultivation intensification from Niger, Nigeria and Benin to Burkina Faso and Ghana. Mali and Senegal were affected later, and literature reports of Senegalese strains of S. gesnerioides from the wild developing virulence on cowpea offer a model for the diffusion of witchweed parasitism by multilocal evolution, through host-driven selection, instead of epidemic diffusion. A contrario, in Côte d’Ivoire, cowpea is much less widespread, so the parasite has remained confined to the wild compartment. Thus, both historical and ecogeographic analyses refute the vision of S. gesnerioides as an invader. Instead, they point to the increasing importance and intensification of the crop, and the consequent loss of biodiversity, as the main drivers of the extension and diversification of its crop-specific strains.

International audience; Potassium (K) is essential for a wide range of physiological functions in plants, and a limiting element for wood productivity in numerous forest ecosystems. However, the contribution of each of the K-sensitive physiological processes to the limitation of wood productivity is poorly known. In trees, K deficiency acts both on the source and the sinks of carbon making it difficult to disentangle its effects on wood productivity. Here, we review the literature dealing with the influence of K-limitation on tree physiological processes. Results from extensively studied tropical Eucalyptus plantations are used to illustrate the physiological processes the most impacted by K deficiency. We identify the main processes that limit the availability of K to the trees and influence the circulation of K ions in the ecosystem. Then, we describe the influence of K bioavailability on carbon assimilation, the water economy of trees, and carbon partitioning. We conclude this review by identifying the main priorities towards the process-based modelling of the influence of K on the carbon and water cycles in forest ecosystems. For each process modelling priority, we identify options that could be used in the current conceptual framework of most eco-physiological models.

International audience; Logistic regression models were developed from 5 years (2014 to 2018) of disease severity and weather data in an attempt to predict brown rust of sugarcane at the Everglades Research and Education Center in Belle Glade, Florida. Disease severity (percentage area of the top visible dewlap leaf covered by rust) was visually assessed in the field every 2 weeks for two varieties susceptible to brown rust. A total of 250 variables were derived from weather data for 10- to 40-day periods before each brown rust assessment day. A subset of these variables were then evaluated as potential predictors of severity of brown rust based on their individual correlation or their biological meaningfulness. Analyses of correlation and stepwise logistic regression allowed us to identify afternoon humid thermal ratio (AHTR), temperature-based duration variables, and their interaction terms as the most significant variables associated with brown rust epidemics of sugarcane in Florida. The nine best predictive models were identified based on model accuracy, sensitivity, specificity, and estimates of the prediction error. The prediction accuracy of these models ranged from 73 to 85%. Single-variable model BR2 (based on AHTR) classified 89% of the epidemic and 81% of the nonepidemic status of the disease. More than 83% of the epidemics and 81% of the nonepidemic status of sugarcane brown rust was correctly classified via multiple-variable models. These models can be used as components of a rust disease warning system to assist in the management of brown rust epidemics of sugarcane in south Florida.

This work is dedicated to Serge Quilici who has been leading prolific research on the tephritids of Reunion his whole career. This article has been reviewed and recommended by Peer Community in Ecology, https://doi.org/10.24072/pci.ecology.100080. The peer review history for this article is available at https://publo ns.com /publo n/10.1111/ele.13825.; International audience; The relative importance of ecological factors and species interactions for shaping species distributions is still debated. The realised niches of eight sympatric tephritid fruit flies were inferred from field abundance data using joint species distribution modelling and network inference, on the whole community and separately on three host plant groups. These estimates were then confronted the fundamental niches of seven fly species estimated through laboratory-measured fitnesses on host plants. Species abundances depended on host plants, followed by climatic factors, with a dose of competition between species sharing host plants. The relative importance of these factors mildly changed among the three host plant groups. Despite overlapping fundamental niches, specialists and generalists had almost distinct realised niches, with possible competitive exclusion of generalists by specialists on Cucurbitaceae. They had different assembly rules: Specialists were mainly influenced by their adaptation to host plants, while generalist abundances varied regardless of their fundamental host use.

Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments. Because physical urban water infrastructure has life expectancies of up to 100 years or more, contemporary urban drainage systems are strongly influenced by historical decisions and implementations. The current decisions taken in sewer asset management will, therefore, have a long-lasting impact on the functionality and quality of future services provided by these networks. These decisions can be supported by different approaches ranging from various inspection techniques, deterioration models to assess the probability of failure or the technical service life, to sophisticated decision support systems crossing boundaries to other urban infrastructure. This paper presents the state of the art in sewer asset management in its manifold facets spanning a wide field of research and highlights existing research gaps while giving an outlook on future developments and research areas. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Despite major management efforts initiated in 1987 and 2007 and decreasing emissions in the Gironde watershed, cadmium (Cd) levels in oysters from the downstream Gironde estuary are still higher to the consumption limit (5 mg/kg, dw, EC). Dissolved Cd concentrations were measured in surface water collected in the Gironde estuary during nine cruises (2014 – 2015). The obtained theoretical (Cdd0) concentrations and the daily net Cdd fluxes, using the Boyle’s method, confirm a decadal stepping decrease of the Cd pollution corresponding to that observed in the oysters from the long term national monitoring for priority contaminants at the estuary mouth. As this observation invalidates the previous estimating methods for estimating annual net Cdd fluxes, we propose an original empirical model applicable for the four last decades. This model is based on four exponential functions with defined boundaries for low water discharges. Each of them is representative of one distinct situation of Cd pollution in the watershed relative to major remediation processes implemented in the last four decades. These results allow to develop a direct estimation of the annual net Cdd fluxes only based on the data of the annual mean discharge. Thus, this study demonstrates the strength of the field research in geochemistry to obtain a better quantification of the exportation of dissolved bioavailable pollutants from the continental watersheds to the coastal ocean., Malgré d’importants efforts d’aménagement initiés en 1987 et 2007 et la diminution consécutive des émissions issues du bassin versant de la Gironde, les teneurs en cadmium (Cd) présentent dans les huîtres de l’aval de la Gironde restent supérieures à la norme de consommation (5 mg/kg, p.s., CE). Des concentrations en cadmium dissous ont été mesurées dans les eaux de surface collectées dans l’estuaire de la Gironde au cours de neuf campagnes océanographiques (2014–2015). Les concentrations théoriques en cadmium dissous (Cdd0) et les flux nets journaliers de Cdd ont été obtenus, selon la méthode de Boyle. Ils confirment une diminution de la pollution en Cd par paliers décennaux, correspondant à celle observée dans les huîtres girondines grâce au réseau national de surveillance des contaminants prioritaires. Cette observation invalidant les précédentes méthodes d’estimation des flux nets annuels, nous proposons un modèle empirique original appliqué aux quatre dernières décennies et basé sur quatre fonctions exponentielles tronquées. Chaque fonction est représentative d’une situation distincte de la pollution du bassin versant relative aux principaux processus de remédiation entrepris au cours des quatre dernières décennies. Les résultats nous ont permis de proposer un abaque de quantification des flux nets annuels de Cdd utilisant uniquement les données de débit moyen annuel. Ainsi, cette étude démontre l’efficacité de la géochimie de terrain pour obtenir une meilleure quantification de l’exportation de polluants dissous et biodisponibles, des bassins continentaux vers l’océan côtier.

Certains décideurs considèrent avec méfiance l’arrivée de nouveaux « migrants ». Les journalistes et les politiques y ont très certainement un rôle à jouer : ils utilisent souvent une sémantique attisant les peurs. Sur le terrain, cet état d’esprit participe à la mise en danger des personnes déplacées. Le droit pourrait-il contribuer à proposer une vision plus claire et plus compréhensible de cette situation et favoriser ainsi la protection effective de ces personnes ? Le droit est conçu comme porteur de rationalité, il apparaît utile et pertinent. Toutefois, on peut légitimement se demander si la confusion existante à propos des mouvements de population n’est pas directement liée à une défaillance du droit. L’étude des interactions entre le droit et son environnement dans le cadre de la théorie interdisciplinaire des systèmes dynamiques complexes apportera des éléments de réponse., Some decision makers are wary of the arrival of new “migrants.” Journalists and politicians certainly have a share of responsibility for this situation, often fomenting fear through semantics. On the ground, this mindset places displaced persons at risk. Could the law help provide a clearer understanding of the situation, and contribute concretely to protecting the displaced? Given that the law is intended to be a voice of reason, it would seem so. But it is also legitimate to ask whether the confusion that exists around population movements is not directly related to a failure of law. Examining interactions between the law and its environment from the perspective of the interdisciplinary theory of complex dynamic systems may provide some answers., Algunos responsables de la toma de decisiones consideran con desconfianza la llegada de nuevos “migrantes”. Los periodistas y los políticos tienen, sin lugar a dudas, un papel que desempeñar en esto : a menudo utilizan la semántica que despierta temores. En el terreno, este estado de ánimo contribuye a poner en peligro a las personas desplazadas. ¿Podría el derecho ayudar a proponer una visión más clara y comprensible de esta situación y así promover la protección efectiva de estas personas ? El derecho está concebido como portador de racionalidad, parece útil y relevante. Sin embargo, es legítimo preguntarse si la confusión existente sobre los movimientos de población no está directamente relacionada con una deficiencia del derecho. El estudio de las interacciones entre el derecho y su entorno en el contexto de la teoría interdisciplinaria de los sistemas dinámicos complejos proporcionará algunas respuestas.

International audience; The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, reproducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) "trace" the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical researchers, (2) use a standardized notebook structure and terminology based on the existing TRACE documentation framework, and (3) use their notebooks to compile TRACE documents that supplement publications and reports. These practices have benefits for model developers, users, and stakeholders: improved and efficient model design, analysis, testing, and application; increased model acceptance and reuse; and replicability and reproducibility of the model and the simulation experiments. Using TRACE terminology and structure in modelling notebooks facilitates production of TRACE documents. We explain the rationale of TRACE, provide example TRACE documents, and suggest strategies for keeping "TRACE Modelling Notebooks."Highlights:• The quality and reproducibility of modelling would be increased by keeping modelling notebooks.• Simulation modellers have not yet developed a strong culture of keeping notebooks.• We propose a standard format for notebooks based on the TRACE document framework.• We make recommendations about the type of information to be included in the notebooks.• We describe existing tools to keep notebooks.

Studying spatial and temporal plant disease dynamics helps us to understand pathogen dispersal processes and improve disease control recommendations. In this study, three cacao plots devoid of primary inoculum of Phytophthora megakarya (causal agent of cacao black pod rot disease) upon establishment in 2006 were monitored for presence of disease on a weekly basis from 2009 to 2016. Ripley’s K(r) function, join count statistics, and Fisher’s Exact test were used to analyze spatial and temporal disease dynamics. Disease distribution maps showed aggregated disease patterns in all plots; however, for the years of disease onset, exogenous primary infections were mostly randomly distributed. The K(r) function confirmed these results indicating that inoculum generally disperses only over short distances. Moreover, significant positive spatial autocorrelations showed that diseased trees were often clustered up to a distance of 3 to 9 m. Temporal disease progression was low, meaning that endogenous inoculum failed to establish itself, which is partly explained by rigorous phytosanitation and partly by unfavorable microclimatic conditions for disease development. Because P. megakarya had difficulty establishing itself in the plots, proximity to already infected cacao plantations drove infection dynamics. Thus, isolation of newly established cacao plantations from infected ones and rigorous phytosanitation as a preventive strategy appears to be an effective approach to control cacao black pod rot disease for newly established cacao plantations.

Tree structural and biomass growth studies mainly focus on the shoot compartment. Tree roots usually have to be taken apart due to the difficulties involved in measuring and observing this compartment, particularly root growth. In the context of climate change, the study of tree structural plasticity has become crucial and both shoot and root systems need to be considered simultaneously as they play a joint role in adapting traits to climate change (water availability for roots and light or carbon availability for shoots). We developed a botanically accurate whole-plant model and its simulator (RoCoCau) with a linkable external module (TOY) to represent shoot and root compartment dependencies and hence tree structural plasticity in different air and soil environments. This paper describes a new deep neural network calibration trained on simulated data sets computed from a set of more than 360 000 random TOY parameter values and random climate values. These data sets were used for training and for validation. For this purpose, we chose VoxNet, a convolutional neural network designed to classify 3D objects represented as a voxelized scene. We recommend further improvements for VoxNet inputs, outputs and training. We were able to teach the network to predict the value of environment data well (mean error < 2 %), and to predict the value of TOY parameters for plants under water stress conditions (mean error < 5 % for all parameters), and for any environmental growing conditions (mean error < 20 %).

The recent technological advancements and emergence of the open data in environmental and life sciences are opening new research opportunities while creating new challenges around data management. They make available an unprecedented amount of data that can be exploited for studying complex phenomena. However, new challenges related to data management need to be addressed to ensure effective data sharing, discovery and reuse, especially when dealing with interdisciplinary research contexts. These issues are magnified in interdisciplinary context, by the fact that each discipline has its practices, e.g., specific formats and metadata standards. Moreover, the majority of current data management practices do not consider semantic heterogeneity existing among disciplines. For this reason, we introduce a flexible metadata model that describes the datasets of various disciplines using a common paradigm based on the observation concept. It provides a key vision for articulating the user point of view and underlying scientific domains. In this study, we therefore decide to mainly reuse the SOSA lightweight ontology (Sensor, Observation, Sample, and Actuator) to efficiently leverage others existing ontologies to improve datasets discovery and reuse coming from Earth and life observation. The main benefit of the proposed metadata model is that it extends the technical description, usually provided by existing metadata models, with the observation context description enabling the need of a user viewpoint. Moreover, following the FAIR principles, the metadata model specifies the semantics of its elements using ontologies and vocabularies, and reuses as much as possible ontological and terminological existing resources. We show the benefit and applicability of the model through a case study we identified as representative after interviewing researchers in environmental and life sciences.

International audience; As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

Multiple factors can influence the public transport level of service. All take root in the network structure and the operating regime, i.e. how the bus lines are arranged atop the street network and how the service frequency is adjusted to meet urban mobility patterns. This is known as the bus network design problem and has been the subject of several studies. The problem is so challenging that most studies until now resort to strong assumptions such as a static description of the peak hour demand, homogeneous user behavior, and equal trip lengths. Potential effects of different types of user behavior and trip lengths patterns on the user and/or operator cost have not been investigated whatsoever. Moreover, none of the existing studies have considered the effects of bus network structure on private car users, the level of interactions between the modes, and the passenger mode choice that depends on traffic conditions. This paper aims to close this gap and provide a general framework considering multiple trip length patterns, two types of user behavior, and the effects that the bus network structure might have on the traffic performance and passenger mode choice. For modeling different trip length patterns, we use the trip length distribution as an intermediate level of abstraction. To capture complex modal interactions and quantify the operating speeds, we apply the recently proposed three-dimensional macroscopic fundamental diagram. We use the operating speed for each mode to determine the mode choice at the trip length level. This way, we are able to solve the optimal bus network design problem under the free-flow/saturated traffic conditions in an analytical way, while considering more realistic settings including a dynamic description of the peak hour demand, mixed traffic, and different mode choice decisions depending on trip lengths and walking preferences. Numerical analysis reveals that all the tested factors, including demand intensity, user behavior, and trip length patterns, have significant effects on the operator and user cost function. Results show that the probability of choosing any given mode follows certain distribution that varies across the trip length patterns, indicating the importance of modeling the mode choice at the trip length level. Furthermore, the results indicate that users can benefit if they are willing to adjust the number of transfers to minimize the walking distance at the origin and the destination. Moreover, we show that the optimal bus network design determined for the uniform trip pattern underestimates the number of required buses, which leads to passenger congestion at stops during the peak period. This, however, does not happen when we take into account the actual trip length distribution for the bus network design. A comparison with a simplified approach that considers the bus system only, reveals the value of accounting for the complex bi-modal interactions, especially for higher demand levels. Finally, we show that by allowing the design parameters to vary across cardinal directions we provide more flexibility for the bus system to serve the passenger demand while reducing the operator cost compared to the existing approaches. ISSN:0191-2615 ISSN:1879-2367

Over the past few decades, the digitalization of services and infrastructures has led to the emergence of a broad set of new information sources to characterize human mobility. These sources usually offer valuable significant population penetration rates but may also suffer from important temporal sparsity. Data generated by user activity, such as social networks or mobile phone data, especially fit this description. Although this temporal sparsity might prevent estimating individual travel speeds, we state that such low-frequency positioning data enable estimating the average urban traffic speed dynamics when considering an adequate network partitioning. In this sense, this article proposes a new method, based on the division of the urban area of a given city into regions and on the analysis of a limited set of basic characteristics of individual vehicle trips, such as the regional path. Our solution first involves estimating robust travel times from travelers sharing similar trip features and then jointly analyzing these travel times to deduce the underlying regional traffic speeds, using regression analysis. We apply this methodology on a set of trips derived from a large GPS dataset of vehicle tracks covering the city of Lyon. These data are purposely downsampled to reduce the sampling rate and reproduce bias and temporal features that are proper to sparser but larger-scale, mobility data sources dependent on user’s communication activities. Controlling the data downsampling process allows us to evaluate the impacts of the progressive information loss on the speed estimation, while the raw GPS data provide the ground truth speed reference against which to compare our results. Provided that the amount of observed individual trips is sufficient, the analysis returns satisfying speed estimation results, both at low and high downsampling levels. Thus, we successfully demonstrate that it is possible to estimate zonal traffic speeds from degraded trip data without evaluating individual travel speeds.

International audience; It is commonly accepted that species should move toward higher elevations and latitudes to track shifting isotherms as climate warms. However, temperature might not be the only limiting factor determining species distribution. Species might move to opposite directions to track changes in other climatic variables. Here, we used an extensive occurrence data set and an ensemble modelling approach to model the climatic niche and to predict the distribution of the seven baobab species (genus Adansonia) present in Madagascar. Using climatic projections from three global circulation models, we predicted species’ future distribution and extinction risk for 2055 and 2085 under two representative concentration pathways (RCPs) and two dispersal scenarios. We disentangled the role of each climatic variable in explaining species range shift looking at relative variable importance and future climatic anomalies. Four baobab species (Adansonia rubrostipa, Adansonia madagascariensis, Adansonia perrieri¸ and Adansonia suarezensis) could experience a severe range contraction in the future (>70% for year 2085 under RCP 8.5, assuming a zero-dispersal hypothesis). For three out of the four threatened species, range contraction was mainly explained by an increase in temperature seasonality, especially in the North of Madagascar, where they are currently distributed. In tropical regions, where species are commonly adapted to low seasonality, we found that temperature seasonality will generally increase. It is, thus, very likely that many species in the tropics will be forced to move equatorward to avoid an increase in temperature seasonality. Yet, several ecological (e.g., equatorial limit, or unsuitable deforested habitat) or geographical barriers (absence of lands) could prevent species to move equatorward, thus increasing the extinction risk of many tropical species, like endemic baobab species in Madagascar.

International audience; Ionic liquids (ILs) are promising alternative solvents for traditional organic compounds using selective separation. However, some environmental risks of ILs, resulting in a limitation of their applications in industry. In this work, the stability of ILs into multi-channel tubular ceramic membranes (ILM) provides a promising way to realize the use of ILs with environmental damages reducing. This novel process has been investigated for toluene removal from a toluene/air gas mixture based on 1-butyl-3-imidazolium bis(trifluoromethylsulfonyl)amide ([Bmim][NTf2]) as a liquid sorbent. In addition, the effects of operating conditions on toluene separation were studied and discussed by experiment and modeling. The absorption capacity of toluene by the ILM on proposed operating conditions was around 224.74 mg per gram of the ionic liquid. The support ceramic membrane can effectively prevent ILs leakage from causing secondary waste and ensure longtime operation. Regeneration of polluted ILM was available.

One of the main challenges for multi-regional application of the aggregated traffic models based on the Macroscopic Fundamental Diagram, lies in the identification and characterization of the most prevailing paths chosen by drivers. In this paper, we propose a methodological framework, based on two distinct methods, to determine these prevailing paths. The first method requires the information about travel patterns in the urban network as well as the information about the city network partitioning. The second method is more parsimonious, and consists on the direct calculation of shortest-cost paths on the aggregated network. For this, we propose four impedance functions that utilize topological features of the urban network and its partitioning. We test the performance of this methodological framework for determining the most prevailing paths on a network representing the metropolitan area of Lyon (France). We consider a set of real trajectories (i.e. GPS data) of drivers in this network as a benchmark. We show that the proposed methods are able to identify the most prevailing paths as the ones chosen by drivers, as evidenced by a large similarity value between the sets of paths. Based on a maximum likelihood estimation, we also show that the Weibull distribution is the one that better reproduces the functional form of the network-wide distribution of travel distances. However, the characterization of the functional form of such distributions characteristic to each region defining a path is not trivial, and depends on the complex topological features of the urban network concerning the definition of its partitioning. We also show that the Euclidean distance metrics provides good estimates of the average travel distances. Interestingly, we also show that the most prevailing paths are not necessarily the ones that have the lowest average travel distances.

Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the "soil14_psi" experiments), when the critical threshold value for inducing soil moisture stress was reduced ("soil14_p0"), and when plants were able to access soil moisture in deeper soil layers ("soil14_dr&z.ast;2"). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes.

In the field of hydrology, the Geomorphological Instantaneous Unit Hydrograph (GIUH) is central to describing a watershed response. The application of GIUH is extended to individual hydrological events by accounting for the influence of rainfall spatial distribution. A method is proposed herein to identify the Geomorphological Instantaneous Unit Hydrograph specific to each flood event (i.e. E-GIUH), when runoff of effective rainfall is the dominant process. The E-GIUH is derived from observational data, namely: rainfall field time series, and a hydrograph. Such an identification process is formulated as an inverse problem with parameters such as the E-GIUH velocity and coefficient of dispersion, as well as the hyetograph of rainfall excess. The proposed method is applied to several flood events across two mountainous catchments within the Cevennes-Vivarais Mediterranean Hydrometeorological Observatory territory prone to flash flooding. Results indicate that the E-GIUHs display significant variability over the two basins, and the E-GIUH parameters appear to be correlated with the flood event magnitude. The E-GIUH synthetizes the basin response to rain forcing and can be considered as a signature of flood events. A sensitivity study suggests that E-GIUH identification is fairly robust, even with respect to the a priori hyetograph of effective rainfall.

Urban road transportation performance is the result of a complex interplay between the network supply and the travel demand. Fortunately, the framework around the macroscopic fundamental diagram (MFD) provides an efficient description of network-wide traffic performance. In this paper, we show how temporal patterns of vehicle traffic define the performance of urban road networks. We present two high-resolution traffic datasets covering a year each. We introduce a methodology to quantify the similarity of macroscopic traffic patterns. We do so by using the concepts of the MFD and a dynamic time warping (DTW) based algorithm for time series. This allows us to derive a few representative MFD clusters that capture the essential macroscopic traffic patterns. We then provide an in-depth analysis of traffic heterogeneity in the network which is indicative of the previously found clusters. Thereupon, we define a parsimonious classification approach to predict the expected MFD clusters early in the morning with high accuracy.

COMPLEX NETWORKS 2020, The Ninth International Conference on Complex Networks and their Applications, Madrid, ESPAGNE, 01-/12/2020 - 03/12/2020; With the recent and continuous growth of large metropolis, the development, management and improvement of their urban multi-modal transport networks become a compelling need. Although the creation of a new transport mode often appears as a solution, it is usually impossible to construct at once a full networked public transport. Therefore, there is a need for efficient solutions aimed at prioritizing the order of construction of the multiple lines or transport modes. Hence, the proposed work aims at developing a simple and quick-to-compute methodology aimed at prioritizing the order of construction of the lines of a newly designed transport mode by maximizing the network performance gain, as described by complex networks metrics. In a resilience context, the proposed methodology could also be helpful to support the rapid and quick response to disruptions by setting up or reinforcing an adapted emergency transport line (e.g., bus service) over a set of predefined itineraries.

The estimation of trip lengths has been proven to be a key feature for the application of aggregated traffic models based on the Macroscopic Fundamental Diagram. The paths and distances to be traveled by vehicles in regional networks vary over time, due to changes in the traffic conditions. In this paper, we develop a methodological framework to explicitly determine traffic-dependent regional paths and estimate their travel distances. This framework is incorporated into a dynamic traffic assignment module designed to target the Deterministic and Stochastic User Equilibrium in regional networks. We first discuss how regional paths and their characteristic trip lengths are influenced by changes in the regional traffic dynamics. We then test the proposed methodology for estimating traffic-dependent travel distances on small and medium-sized networks, considering a simulation environment. We show that our methodology provides good estimations of the traffic-dependent trip lengths. Our results also shed light on the importance of how time-dependent trip lengths influence the traffic dynamics in the regions.

IEEE ITSC 2020, 23rd IEEE International Conference on Intelligent Transportation Systems, Rhodes, GRECE, 20-/09/2020 - 23/09/2020; This work contributes to the operational design of dynamic HOV lanes on French urban freeways. We propose a framework to estimate the acceptable dynamic maximal speed of the HOV lane, knowing the current origin speed. The aim is to ensure safety of lane changes while maintaining an acceptable duration of the period before gap acceptance. It is recognized that the longer the time a driver waits before accepting a gap, the lower he/she places the threshold for next gap acceptance. That may lead to inappropriate behaviors, such as unsafe lane changes. The key variables for lane changing realization are speeds and headways on origin and target lanes (estimated here with individual loop data). Both variables play an important role in lane change maneuver safety. We present in this paper two lane change realization models combining simple rules and observed data, one pessimistic and one optimistic. From this, we determine the maximal and minimal boundaries of two indicators: the number of rejected gaps and the waiting time to safe lane change. Those indicators lead to an appraisal of lane change realization safety. The results tend to show that a speed regulation lower than usual speed may increase safety while not degrading the service provided by this lane to its specific users. Having in mind the perspective of lanes dedicated to connected automated cruise control vehicles, we extend the proposed method to provide an analysis of the impact of uniforms inter-vehicular time gap on lane change safety.

The quinoa pest Copitarsia incommoda (Walker, Lepidoptera: Noctuidae) is a cause of significant damage, and it is thus critical for Andean countries to have access to phenological models to maintain production and food safety. These models are key components in pest control strategies in the context of global warming and in the development of sustainable production integrating agroecological concepts. Phenological models are mainly based on outlining the relationship between temperature and development rate. In this study, we investigated the combined effect of protein content within the diet (artificial diet; artificial diet with −20% protein; artificial diet with +20% protein; natural quinoa diet) and temperature (12, 16.9, 19.5, 22.7, 24.6°C) as drivers of the development rate. Our study supports the literature, since temperature was found to be the main driver of the development rate. It highlights the significant role played by protein content and its interaction with temperature (significant effects of temperature, diet, and diet:temperature on development time using GLMs for all foraging life stages). We discuss the implications of such drivers of the development rate for implementing and applying phenological models that may benefit from including factors other than temperature. While performance curves such as development rate curves obtained from laboratory experiments are still a useful basis for phenological development, we also discuss the need to take into account the heterogeneity of the insect response to environmental factors. This is critical if pest control practices are to be deployed at the optimal time.

International audience; Phenology—the timing of life-history events—is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current practice of manually harvesting data from individual specimens, however, greatly restricts our ability to scale-up data collection. Recent investigations have demonstrated that machine-learning approaches can facilitate this effort. However, present attempts have focused largely on simplistic binary coding of reproductive phenology (e.g., presence/absence of flowers). Here, we use crowd-sourced phenological data of buds, flowers, and fruits from >3,000 specimens of six common wildflower species of the eastern United States (Anemone canadensis L., A. hepatica L., A. quinquefolia L., Trillium erectum L., T. grandiflorum (Michx.) Salisb., and T. undulatum Wild.) to train models using Mask R-CNN to segment and count phenological features. A single global model was able to automate the binary coding of each of the three reproductive stages with >87% accuracy. We also successfully estimated the relative abundance of each reproductive structure on a specimen with ≥90% accuracy. Precise counting of features was also successful, but accuracy varied with phenological stage and taxon. Specifically, counting flowers was significantly less accurate than buds or fruits likely due to their morphological variability on pressed specimens. Moreover, our Mask R-CNN model provided more reliable data than non-expert crowd-sourcers but not botanical experts, highlighting the importance of high-quality human training data. Finally, we also demonstrated the transferability of our model to automated phenophase detection and counting of the three Trillium species, which have large and conspicuously-shaped reproductive organs. These results highlight the promise of our two-phase crowd-sourcing and machine-learning pipeline to segment and count reproductive features of herbarium specimens, thus providing high-quality data with which to investigate plant responses to ongoing climatic change.

Aerosol- and cloud-induced changes in diffuselight have important impacts on the global land carbon cy-cle, as they alter light distribution and photosynthesis in veg-etation canopies. However, this effect remains poorly rep-resented or evaluated in current land surface models. Here,we add a light partitioning module and a new canopy lighttransmission module to the ORCHIDEE (Organising Car-bon and Hydrology In Dynamic Ecosystems) land surfacemodel (trunk version, v5453) and use the revised model, OR-CHIDEE_DF, to estimate the fraction of diffuse light andits effect on gross primary production (GPP) in a multilayercanopy. We evaluate the new parameterizations using fluxobservations from 159 eddy covariance sites over the globe.Our results show that, compared with the original model,ORCHIDEE_DF improves the GPP simulation under sunnyconditions and captures the observed higher photosynthe-sis under cloudier conditions in most plant functional types(PFTs). Our results also indicate that the larger GPP undercloudy conditions compared with sunny conditions is mainlydriven by increased diffuse light in the morning and in theafternoon as well as by a decreased vapor pressure deficit(VPD) and decreased air temperature at midday. The obser-vations show that the strongest positive effects of diffuse lighton photosynthesis are found in the range from 5 to 20◦C andat a VPD < 1 kPa. This effect is found to decrease when theVPD becomes too large or the temperature falls outside of theabovementioned range, which is likely due to the increasingstomatal resistance to leaf CO2uptake. ORCHIDEE_DF un-derestimates the diffuse light effect at low temperature in allPFTs and overestimates this effect at high temperature and ata high VPD in grasslands and croplands. The new model hasthe potential to better investigate the impact of large-scaleaerosol changes and long-term changes in cloudiness on theterrestrial carbon budget, both in the historical period and inthe context of future air quality policies and/or climate engi-neering This research has been supported by the Eu- ropean Research Council (grant no. SyG-2013-610028), the ANR CLAND Convergence Institute (grant no. 16-CONV-0003), the ANR China Trend Stream and the new 4C project. Bogdan Cho-jnicki was supported by the National Science Foundation, Poland (grant no. UMO-2017/27/B/ST10/02228), within the framework of the “Carbon dioxide uptake potential of sphagnum peatlands in the context of atmospheric optical parameters and climate changes” (KUSCO2) project.

International audience; The vulnerability of the French Riviera territories to hydro-meteorological hazards has been highlighted by the flash flood of the 3rd of October 2015, which had catastrophic consequences. In the view of the speed and violence of these phenomena, the development of warning systems able to provide real-time flood mapping should make it possible to limit their impacts. In this context, the main objective of this work is to study the feasibility of using a 2D hydraulic modelling tool with adaptive grid refinement, the Basilisk calculation code – http://basilisk.fr/, which is based on state-of-the-art finite volume methods. This code has been used to model the October $2015$ flood event on one French Riviera coastal catchment, the Brague River catchment. Results obtained with Basilisk were compared with available information from post-event surveys, showing promising performances in terms of simulated peak discharges, inundation extent and water levels in the floodplain. These results highlight that forecasting inundation extents generated by flash flood events on small watersheds (less than 100km²) is possible at a moderate computational cost.

This work attempts to validate the dynamic outputs of bi-modal MFD-based models, also referred to as 3D-MFD models, using empirical data. A previous study (Loder et al., 2017) gathered cars and public transport vehicles data in two different regions of Zurich city and showed that a well-defined 3D-MFD exists by proposing a functional form relating overall travel production to the accumulations of cars and public transport vehicles. This work aims to go one step further with the same data set to investigate if 3D-MFD embedded in dynamic conservation laws can predict the time evolution of the network traffic states. Two different approaches to estimate the inflow demand using outflow and mean speed evolutions are presented. The mean trip lengths are estimated using a network exploration technique. Accumulation-based, trip-based and accumulation-based with outflow delay models are considered in the validation study. It is concluded that a single bi-linear 3D-MFD fit is insufficient to predict the evolution of traffic states accurately. The current work proposes multi bi-linear 3D-MFD fits segregated depending on the time of the day. The proposed approach significantly improved the simulation results, where good correspondence with empirical data is obtained. Finally, it is shown that in multi-modal networks like the city of Zurich, it is essential to consider the effect of public transport vehicles, when considering aggregated simulations. It is also shown that using a 2D-MFD by treating public transport vehicles and private cars alike, result in poor accordance with the field observations.

International audience; In this paper a new method is proposed that solves for the steady state of pressure-dependent models (PDMs) with flow control valves. Rather than model flow devices individually, the method solves the more general problem in which a water distribution system (WDS) has some link flows constrained to lie between upper and lower, or possibly equal, set limits. No heuristics are used to determine device states. The method is shown to be fast, and its effectiveness is demonstrated on PDM WDSs with up to about 20,000 links and 18,000 nodes and 60 link flow constraints, some of which prescribe a fixed flow. The method has applications in network management, network design, and flow control to deal with water distribution where there is insufficient supply.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI [ADD1_IRSTEA]Gestion intégrée de la ressource et des infrastructures; International audience; To date, the hydraulics of water distribution networks are calculated using deterministic models. Because many of the parameters in these models are not known exactly, it is important to evaluate the effects of their uncertainties on the results through uncertainty analysis. For the propagation of uncertain parameters, this article for the first time applies the polynomial chaos expansion to a hydraulic model and compares the results with those from classical approaches like the first-order second-moment method and Monte Carlo simulations. Results presented in this article show that the accuracy of the polynomial chaos expansion is on the same level as the Monte Carlo simulation. Further, it is concluded that due to its computational efficiency, polynomial chaos expansion is superior to the Monte Carlo simulation.

This chapter presents the theoretical and practical aspects for estimating evapotranspiration and its key components in the Mediterranean region at local and regional scales. First, the importance of computing this term in various landscapes is outlined: natural ecosystems to assess their vulnerability to drought, rainfed, and irrigated landscapes for a sustainable management of water resources. The main factors governing evapotranspiration at the intersection between the surface energy budget and the terrestrial water budget are reviewed, with insight on how to get information from in-situ, reanalysis, or remote sensing data. This leads to what and how the various specificities of the Mediterranean landscapes are to be taken into account to understand better the various processes involved for the transpiration and the evaporation of the soil. The chapter ends with various case studies presenting local-scale or regional-scale applications, ranging from land surface modeling to remote sensing estimation of evapotranspiration.

International audience; Carbon (delta C-13) and nitrogen (delta N-15) stable isotope analyses are used in marine ecology to study trophic relationships and migrations of species since they reflect dietary sources consumed which may vary geographically. However, better estimations of isotope incorporation rates and trophic discrimination factors (TDF) under controlled conditions are required. Moreover, variability of isotope incorporation rates and TDF among and within populations has been poorly described, especially in fish scales, whereas the use of non-lethal method is becoming a standard. This study aimed to experimentally assess whether carbon and nitrogen isotope incorporation rates (lambda C and lambda N, respectively) and TDF of scales vary in the European sea bass (Dicentrarchus labrax) among (1) Atlantic, West Mediterranean and East Mediterranean populations, (2) sexes and (3) individuals. Fish were reared under controlled conditions and switched from a diet 1 to a diet 2 with different delta C-13 and delta N-15 values. Scales were sampled repeatedly on 16 fish within the three populations, from the day of diet change (day 0) to the end of the experiment (day 217). Isotope incorporation rates of scales and TDF were determined using a time-dependent model. Isotopic carbon and nitrogen half-lives (t(50)C and t(50)N) were similar among the three populations but males had significantly lower t(50)C and t(50)N than females (29 +/- 2 and 35 +/- 2 days vs. 53 +/- 7 and 80 +/- 11 days, respectively). Females had higher growth rates but lower catabolic rates than males. Variability of lambda C . and lambda N was large within sexes: t(50)C ranged from 17 to 159 days and t(50)N ranged from 18 to 342 days among individuals. Thus, variability between sexes and among individuals must be considered to avoid misinterpretation in field-based studies. For the 48 fish, TDF were 4.91 +/- 0.03 and 2.46 +/- 0.06 parts per thousand for carbon and nitrogen, respectively, and similar between sexes and among populations. Besides, TDF varied among individuals from 2.95 to 5.59 parts per thousand and from 0.93 to 3.55 parts per thousand for carbon and nitrogen, respectively. Empirical mixing models were run to estimate how different TDF influenced estimation of the contributions of food sources to diet of their consumer. The output differed considerably when using TDF from fish literature or those estimated herein, which confirms that a tissue-specific TDF must be used to avoid misinterpretation in field-based studies. Individual variation in TDF did not, however, influence estimation of the contributions of food sources, confirming that scales are a valid tissue for non-lethal sampling.

Although emission models have been designed using vehicle data over driving cycles of a few minutes, they are often applied at large scale to estimate total emission (inventories). In between, there is a range of scales in use in traffic and environmental studies (road sections, sub-areas, etc.). Coupling a traffic microsimulation with COPERT emission factors at different scales reveals scaling biases. We compare network fuel consumption (FC) and nitrogen oxide (NOx) emissions resulting from emission calculations based on different spatial decompositions. The results show that for an area of Paris covering 3 km2, the differences due to the aggregation scale for emissions range from 5 to 17% depending on the pollutant, spatial partitioning and traffic conditions. These discrepancies can be reduced using a distance-weighted mean speed, which is not a scale-consistent definition of mean travel speed. They can almost be cancelled by using a correction term derived analytically in this paper, thus consistency can be guaranteed between emissions assessed at different scales. Finally, a case study shows that it is possible to evaluate FC and NOx emissions on a large-scale network from a sample of traffic data (probes), and obtain the corrective term to be applied to remove scaling bias. The most critical step is the accurate estimation of the total travel distance. The gaps were successfully reduced to a maximum of 8% in congestion for a penetration rate of about 20%.

International audience; As part of a study focusing on the settlement strategies of farming communities, a spatial model is developed in order to overcome the repartition map’s biases. This model integrates as parameters the state of archaeological investigation, the taphonomical processes and an attractiveness criterion. The aim of the model is to understand which parameters influence the establishement of settlements as well as the conservation and discovery of their remains. Although this model has a few limitations, it produces new results that are detailed through the case study of the Kochersberg region in Alsace (Grand-Est, France).; Dans le cadre d’une étude portant sur les stratégies d’implantation des communautés agricoles, un modèle spatial est développé afin de mieux intégrer les biais de la carte de répartition des sites connus. Les paramètres inclus dans la modélisation sont l’état de la recherche archéologique, les processus post-déposition et un critère d’attractivité. L’objectif de ce modèle est de mieux comprendre quels facteurs favorisent l’implantation, la conservation, la découverte des vestiges et in fine la carte de répartition des sites archéologiques. Malgré quelques limites inhérentes à l’exercice de la modélisation spatiale, le modèle produit de nouveaux résultats qui sont détaillés via un exemple concernant la micro-région du Kochersberg en Alsace (Grand-Est, France).

International audience; The development of computer science in archaeology allows to manage large quantities of disparate data. We propose here a statistical based on the study of small artefacts, in order to highlight regional groups in eastern Gaul during La Tène D1 (150 to 75 BC). This method is based on dividing the study area into a grid and calculating a typological profile for each of its cells. This article presents the different steps of this modelling, as well as the first results of a work in progress.; Le développement de l’informatique en archéologie permet aujourd’hui de réfléchir sur de grandes quantités de données disparates. Nous proposons ici une modélisation statistique, à travers l’étude du petit mobilier, pour mettre en évidence des groupes régionaux dans l’est de la Gaule à La Tène D1 (150 à 75 av. J.-C.). Cette méthode se fonde sur la division de la zone d’étude en une grille et le calcul pour chacune de ses mailles d’un profil typologique. Cet article présente les différentes étapes de cette modélisation ainsi que les premiers résultats d’un travail en cours.

The Safe Set Problem is a type of partitioning problem with particular constraints on the weight of adjacent partition components. Several theoretical results exist in the literature along with a mixed integer linear formulation. We propose a new, more compact, Mixed Integer Linear Program for the (Weighted) Safe Set Problem and Connected Safe Set Problem with a polynomial number of variables and constraints, based on a flow from an additional fictitious node. The model is enriched by symmetry-breaking considerations and a variable reduction subproblem. We test the model on a benchmark of small instances which underline the difficulty of solving the Safe Set Problem through mathematical programming approaches. We also compare it with the only existing formulation in the literature and find that our approach is usually more efficient on a set of benchmark instances.

The majority of Mediterranean basins are overexploiting their water resources, and the situation is likely to worsen with the impact of climate change. Population growth, human development, and climate change are today the main drivers that increase the pressure on water resources, in both quantity and quality. At the same time, services such as hydropower and recreation are required from the hydrosystem, while the ecosystem is threatened. In a context of scarcity, water resource management can no longer be segmented between economic sectors. On the contrary, each stakeholder must share a common vision of the system so that water managers can respond to the many and often conflicting demands, and prepare for the future while taking into account extreme events such as droughts or floods. The task of Integrated Water Resources Management (IWRM) has evolved into a comprehensive framework involving stakeholders in different phases to build well-informed decisions together. The tools that can help the process are Decision Support Systems (DSS), which integrate science and models into a holistic approach. The purpose of this chapter is to introduce water managers to numerical methods and tools that can facilitate the assessment of alternatives and the development of plans in the context of increasingly limited water resources around the Mediterranean. After an introduction to IWRM concepts, we will discuss the main topics and issues regarding integrated modeling for DSS. We will then describe the current scenario of integrated modeling around the Mediterranean area and will examine two examples of model implementations. Firstly, in Morocco, an assessment and scenario of water resources for agriculture is based on the use of remote sensing time series. Secondly, in Tunisia, assessment and scenario of water pollutants and erosion are carried out. At the end of the chapter, we will try to identify some key points that limit the use of integrated modeling by water planners.

International audience; Grasslands offer many environmental and economic advantages that put them at the heart of future sustainable ruminant production systems. This study aimed to quantify and map the dry matter yield (DMY) and nitrogen yield (NY) of French grasslands resulting from cutting and grazing practices, based on the existing diversity of grassland vegetation, management, soil and climate conditions, using a research version of the STICS crop model called PâturSTICS. This model simulates daily dry matter (DM), nitrogen (N) and water fluxes involved in the functioning of grasslands and crops in response to management and environmental conditions. It was improved to represent deposition of animal waste on grassland soils during grazing and to simulate DM production and N content of grasses and legumes more accurately. Simulations were performed for locations across France on a highresolution grid composed of pedoclimatic units (PCU) obtained by combining the spatial resolutions of climate and soil. The main grassland types and associated management types were determined for each PCU and then simulated over 30 years (1984-2013). Using the simulated values, predictive metamodels of annual grassland DMY and NY were developed from easily accessible explanatory variables using a random forest approach. Annual model predictions were aggregated and averaged at the PCU scale, then compared to regional observations. Predicted DMY agreed with available observations, except in semi-mountainous and mountainous regions, where PâturSTICS tended to overpredict DMY, probably because it ignores effects of snow, frost and slope, and due to how it represents effects of temperature and water stress on plant growth. According to results, three-quarters of French grasslands produce and export at least 7.6 t DM ha-1 yr-1 and 172 kg N ha-1 yr-1, respectively. One-quarter of French grasslands produce and export at least 10.7 t DM ha-1 yr-1 and 254 kg N ha-1 yr-1, respectively. The latter are located mainly in northwestern France, the north-western Massif Central, the French Alps and the western Pyrénées, all of which have environmental conditions favourable for grass growth. The metamodels developed are interesting proxies for PâturSTICS' predictions of grassland DMY and NY. Our results provided valuable knowledge that promotes better use of the potential forage production of French and European grasslands to improve protein selfsufficiency and N fertilisation management in ruminant livestock systems.