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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dupraz C.; Wolz K. J.; Lecomte I.; Talbot G.; +15 Authors

    International audience; Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree-crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree-tree and tree-crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model's 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.

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    Article . 2019
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    Horizon / Pleins textes
    Other literature type . 2019
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    Sustainability
    Article . 2019
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    Article . 2019
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Peng, T.; Jermyn, I. H.; Prinet, V.; Zerubia, J.;

    International audience; This paper addresses the segmentation from an image of entities that have the form of a `network', \ie the region in the image corresponding to the entity is composed of branches joining together at junctions, \eg road or vascular networks. We present new phase field higher-order active contour (HOAC) prior models for network regions, and apply them to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much `noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing first an additional nonlinear nonlocal HOAC term, and then an additional linear nonlocal HOAC term to improve the computational speed. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection for these models, we perform a stability analysis of a long bar with a given width, and hence show how to choose the parameters of the energy functions. After adding a likelihood energy, we use both models to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The state-of-the-art results obtained demonstrate the superiority of our new models, the importance of strong prior knowledge in general, and of the new terms in particular.

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  • Authors: Hoegstrom, E.; Trofaier, A.M.; Gouttevin, I.; Bartsch, A.;

    [Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; Knowledge of surface hydrology is essential for many applications, including studies that aim to understand permafrost response to changing climate and the associated feedback mechanisms. Advanced remote sensing techniques make it possible to retrieve a range of land-surface variables, including radar retrieved soil moisture (SSM). It has been pointed out before that soil moisture retrieval from satellite data can be challenging at high latitudes, which correspond to remote areas where ground data are scarce and the applicability of satellite data of this type is essential. This study investigates backscatter variability other than associated with changing soil moisture in order to examine the possible impact on soil moisture retrieval. It focuses on issues specific to SSM retrieval in the Arctic, notably variations related to tundra lakes. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS, 120 m) data are used to understand and quantify impacts on Metop (AAdvanced Scatterometer (ASCAT, 25 km) soil moisture retrieval during the snow free period. Sites of interest are chosen according to ASAR WS availability, high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. Backscatter variations are analyzed with respect to the ASCAT footprint area. It can be shown that the low model agreement is related to water fraction in most cases.No difference could be detected between periods with floating ice (in snow off situation) and ice free periods at the chosen sites. The mean footprint backscatter is however impacted by partial short term surface roughness change. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas . Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed soil moisture related range (sensitivity) of 7 dB in the ASCAT data. The sensitivity is also positively correlated with water fraction in regions with low land-surface model agreement (R = 0.68). A precise quantification of the impact on soil moisture retrieval would, however, need to consider actual soil moisture changes and sensor differences. The study demonstrates that the usage of higher spatial resolution data than currently available for SSM is required in lowland permafrost environments.; La connaissance de l'hydrologie de surface est essentielle mais difficile aux hautes latitudes du fait de la rareté des observations. Les observations satellites offrent le moyen d'y pallier, mais encore faut-il s'assurer de la validité de ces approches dans ces régions. Par l'intermédiaire de deux jeux de données satellite de résolutions différentes, on étudie ici la sensibilité du signal de micro-ondes actives rétrodiffusées à des facteurs autres que l'humidité superficielle des sols.Les zones d'étude ont été ciblées pour correspondre à des régions où les modèles hydrologiques divergent des observations. Dans la plupart de ces zones, l'utilisation d'un produit satellite à fine résolution met en évidence l'impact des lacs sur le signal micro-onde observé, et utilisé pour inférer l'humidité superficielle dans les produits satellites. Il est donc nécessaire d'apporter des corrections aux produits satellitaires dans les régions où la forte concentration en étendues d'eau libre et l'occurrence de vents violents en limitent la validité pour l'hydrologie de surface.

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    Authors: Latruffe, Laure; Mann, Stefan;

    In this paper we suggest that low labour availability on part-time farms may limit part-time farmers’ choice of production enterprises, and as a consequence those farmers may be forced to engage in less profitable enterprises. This proposition is illustrated by a conceptual framework based on the assumption that products with high returns to labour are labour intensive. An empirical analysis for the period 1996-2004 based on aggregated yearly data from the Swiss Farm Accountancy Data Network (FADN) did not fully confirm the proposition. This may suggest the existence of a joint determination of the choice of production enterprise and of the choice to work off the farm. In addition, our assumption that highly profitable enterprises are labour intensive may not hold for specific products or contexts. Bio-based and Applied Economics, Vol 4 No 2 (2015)

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    ProdInra
    Article . 2015
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    Article . 2015
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Martin Prchal; Antti Kause; Marc Vandeputte; David Gela; +6 Authors

    Correction(fichier annexe) : The genetics of overwintering performance in two-year old common carp and its relation to performance until market size (vol 13, e0191624, 2018); Using farmed common carp, we investigated the genetic background of the second year overwintering performance and its relation to the performance during the third growing season and at market size. The experimental stock was established by partial factorial design with a series of 4 factorial matings of 5 dams and 10 sires each. The families were reared communally and pedigree was re-constructed with 93.6% success using 12 microsatellites on 2008 offspring. Three successive recordings (second autumn, third spring, and third autumn—market size) covering two periods (second overwintering, third growing season) were included. Body weight, Fulton’s condition factor and percent muscle fat content were recorded at all times and headless carcass yield and fillet yield were recorded at market size. Specific growth rate, absolute and relative fat change and overall survival were calculated for each period. Heritability estimates were significantly different from zero and almost all traits were moderately to highly heritable (h2 = 0.36–1.00), except survival in both periods and fat change (both patterns) during overwintering (h2 = 0.12–0.15). Genetic and phenotypic correlations imply that selection against weight loss and fat loss during overwintering is expected to lead to a better winter survival, together with a positive effect on growth in the third growing season. Interestingly, higher muscle fat content was genetically correlated to lower survival in the following period (rg = -0.59; -0.53, respectively for winter and the third summer). On the other hand, higher muscle fat was also genetically linked to better slaughter yields. Moreover, selection for higher condition factor would lead to better performance during winter, growing season and at market size.

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    PLoS ONE
    Article . 2018
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    ProdInra
    Article . 2018
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    Article . 2018
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    Authors: Mercier, Audrey; Betbeder, Julie; Rumiano, Florent; Baudry, Jacques,; +8 Authors

    Monitoring forest–agriculture mosaics is crucial for understanding landscape heterogeneity and managing biodiversity. Mapping these mosaics from remotely sensed imagery remains challenging, since ecological gradients from forested to agricultural areas make characterizing vegetation more difficult. The recent synthetic aperture radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) time series provide a great opportunity to monitor forest–agriculture mosaics due to their high spatial and temporal resolutions. However, while a few studies have used the temporal resolution of S-2 time series alone to map land cover and land use in cropland and/or forested areas, S-1 time series have not yet been investigated alone for this purpose. The combined use of S-1 & S-2 time series has been assessed for only one or a few land cover classes. In this study, we assessed the potential of S-1 data alone, S-2 data alone, and their combined use for mapping forest–agriculture mosaics over two study areas: a temperate mountainous landscape in the Cantabrian Range (Spain) and a tropical forested landscape in Paragominas (Brazil). Satellite images were classified using an incremental procedure based on an importance rank of the input features. The classifications obtained with S-2 data alone (mean kappa index = 0.59–0.83) were more accurate than those obtained with S-1 data alone (mean kappa index = 0.28–0.72). Accuracy increased when combining S-1 and 2 data (mean kappa index = 0.55–0.85). The method enables defining the number and type of features that discriminate land cover classes in an optimal manner according to the type of landscape considered. The best configuration for the Spanish and Brazilian study areas included 5 and 10 features, respectively, for S-2 data alone and 10 and 20 features, respectively, for S-1 data alone. Short-wave infrared and VV and VH polarizations were key features of S-2 and S-1 data, respectively. In addition, the method enables defining key periods that discriminate land cover classes according to the type of images used. For example, in the Cantabrian Range, winter and summer were key for S-2 time series, while spring and winter were key for S-1 time series.

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    Remote Sensing
    Article . 2019
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    Authors: Mouysset, L; Doyen, L; Léger, F; Jiguet, F; +1 Authors

    It is possible to frame sustainability as occurring when the global or local system is within a set of limits and boundaries, such as the concept of safe operating spaces within planetary boundaries. However, such framings, whilst highly useful conceptually, have been difficult to translate into operation, especially in the development of policies. Here we show how it is possible to define a safe operating space, bounded by sets of constraints. These constraints can be of a variety of forms (e.g., income, or biodiversity), and, importantly, they need not all be converted to a single common metric such as money. The challenge is to identify a set of policy options that define the &ldquo such as would be the case if a single policy option were defined. Secondly, by allowing each boundary to be defined with its own scale of measurement, it avoids the necessity of having to value natural capital or ecosystem services in financial terms. This framework, therefore, has the potential to allow decision-makers to genuinely meet the needs of their people, now and in the future. which maintains the system within the safe operating space defined by boundaries. A formal methodology, Co-Viability Analysis (CVA), can be used to do this. This provides a coherent framework to operationalize sustainability and has a number of extra advantages. First, defining a safe policy space allows for a political choice of which policies and so is not prescriptive&mdash safe policy space&rdquo

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    Sustainability
    Article . 2018
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    ProdInra
    Article . 2018
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    Oskar Bordeaux
    Article . 2018
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    Authors: Jucker, T.; Caspersen, J.; Chave, J.; Antin, C.; +30 Authors

    Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. We thank the co-authors, field data collectors and funding agencies of the original data sources used in this study. We are also grateful to all curators of open-access databases from which we drew data for this study. In particular, we wish to thank Daniel Falster and Remko Duursma for compiling the biomass and allometry database (BAAD) for woody plants; Michael Keller and Maiza Nara for providing us access to data from the Sustainable Landscapes Brazil project; Kristina Anderson-Teixeira and her co-authors for archiving allometric data from the CTFS-ForestGEO forest dynamics plot at the Smithsonian Conservation Biology Institute (Virginia, USA); and KaDonna Randolph of the USDA forest service for her assistance in accessing the Forest Health Monitoring (FHM) database. We thank Bruno H?rault and an anonymous reviewer for their thoughtful and constructive comments on an earlier draft of our manuscript. T.J. was funded by NERC (grant number: NE/K016377/1). This work has benefited from ANR grants to J.C. (CEBA, ref. ANR-10-LABX-25-01 and TULIP, ref. ANR-10-LABX-0041). The Sustainable Landscapes Brazil project was supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, and USAID, and the US Department of State. Data collection for the UNECE ICP Forests PCC Collaborative Database was cofinanced by national or regional organizations and by the European Commission under regulations (EEC) No 2158/86, Forest Focus (EC) No 2152/200, FutMon (EC) LIFE07 ENV/D/218.

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    Horizon / Pleins textes
    Other literature type . 2017
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    Other literature type . 2017
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    Article . 2017
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    Article . 2016
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      Horizon / Pleins textes
      Other literature type . 2017
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      Apollo
      Other literature type . 2017
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      Article . 2017
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      Article . 2016
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    Authors: Métras, Raphaëlle; Fournié, Guillaume; Dommergues, Laure; Camacho, Anton; +6 Authors

    Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data. Author summary Rift Valley fever (RVF) is an arboviral hemorrhagic fever affecting primarily livestock in Africa and in the Arabian Peninsula. The conditions leading to RVF emergence are not fully understood, mainly because of data scarcity. Applied to the island of Mayotte (our ecosystem under study), for which 12 years RVF serological dataset are available, and by using a mechanistic model, we demonstrate that RVF epidemics related mainly to the introduction of infectious animals. Our work confirms that anthropogenic factors, such as livestock movements, need to be accounted for in order to understand the epidemiology of this disease. Our model should be tested elsewhere, with ecosystem-specific data.

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    Article . 2017
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    Authors: Campos Brusamarello, Liziane; Gilard, Françoise; Brule, Lenaïg; Quillere, Isabelle; +5 Authors

    International audience; Maize roots can be colonized by free-living atmospheric nitrogen (N2)-fixing bacteria (diazotrophs). However, the agronomic potential of non-symbiotic N2-fixation in such an economically important species as maize, has still not been fully exploited. A preliminary approach to improve our understanding of the mechanisms controlling the establishment of such N2-fixing associations has been developed, using two maize inbred lines exhibiting different physiological characteristics. The bacterial-plant interaction has been characterized by means of a metabolomic approach. Two established model strains of Nif+ diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense and their Nif- couterparts defficient in nitrogenase activity, were used to evaluate the impact of the bacterial inoculation and of N2 fixation on the root and leaf metabolic profiles. The two N2-fixing bacteria have been used to inoculate two genetically distant maize lines (FV252 and FV2), already characterized for their contrasting physiological properties. Using a well-controlled gnotobiotic experimental system that allows inoculation of maize plants with the two diazotrophs in a N-free medium, we demonstrated that both maize lines were efficiently colonized by the two bacterial species. We also showed that in the early stages of plant development, both bacterial strains were able to reduce acetylene, suggesting that they contain functional nitrogenase activity and are able to efficiently fix atmospheric N2 (Fix+). The metabolomic approach allowed the identification of metabolites in the two maize lines that were representative of the N2 fixing plant-bacterial interaction, these included mannitol and to a lesser extend trehalose and isocitrate. Whilst other metabolites such as asparagine, although only exhibiting a small increase in maize roots following bacterial infection, were specific for the two Fix+ bacterial strains, in comparison to their Fix- counterparts. Moreover, a number of metabolites exhibited a maize-genotype specific pattern of accumulation, suggesting that the highly diverse maize genetic resources could be further exploited in terms of beneficial plant-bacterial interactions for optimizing maize growth, with reduced N fertilization inputs.

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    PLoS ONE
    Article . 2017
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    Authors: Dupraz C.; Wolz K. J.; Lecomte I.; Talbot G.; +15 Authors

    International audience; Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree-crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree-tree and tree-crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model's 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.

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    ProdInra
    Article . 2019
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    Other literature type . 2019
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    Sustainability
    Article . 2019
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    Article . 2019
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    Authors: Peng, T.; Jermyn, I. H.; Prinet, V.; Zerubia, J.;

    International audience; This paper addresses the segmentation from an image of entities that have the form of a `network', \ie the region in the image corresponding to the entity is composed of branches joining together at junctions, \eg road or vascular networks. We present new phase field higher-order active contour (HOAC) prior models for network regions, and apply them to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much `noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing first an additional nonlinear nonlocal HOAC term, and then an additional linear nonlocal HOAC term to improve the computational speed. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection for these models, we perform a stability analysis of a long bar with a given width, and hence show how to choose the parameters of the energy functions. After adding a likelihood energy, we use both models to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The state-of-the-art results obtained demonstrate the superiority of our new models, the importance of strong prior knowledge in general, and of the new terms in particular.

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  • Authors: Hoegstrom, E.; Trofaier, A.M.; Gouttevin, I.; Bartsch, A.;

    [Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; Knowledge of surface hydrology is essential for many applications, including studies that aim to understand permafrost response to changing climate and the associated feedback mechanisms. Advanced remote sensing techniques make it possible to retrieve a range of land-surface variables, including radar retrieved soil moisture (SSM). It has been pointed out before that soil moisture retrieval from satellite data can be challenging at high latitudes, which correspond to remote areas where ground data are scarce and the applicability of satellite data of this type is essential. This study investigates backscatter variability other than associated with changing soil moisture in order to examine the possible impact on soil moisture retrieval. It focuses on issues specific to SSM retrieval in the Arctic, notably variations related to tundra lakes. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS, 120 m) data are used to understand and quantify impacts on Metop (AAdvanced Scatterometer (ASCAT, 25 km) soil moisture retrieval during the snow free period. Sites of interest are chosen according to ASAR WS availability, high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. Backscatter variations are analyzed with respect to the ASCAT footprint area. It can be shown that the low model agreement is related to water fraction in most cases.No difference could be detected between periods with floating ice (in snow off situation) and ice free periods at the chosen sites. The mean footprint backscatter is however impacted by partial short term surface roughness change. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas . Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed soil moisture related range (sensitivity) of 7 dB in the ASCAT data. The sensitivity is also positively correlated with water fraction in regions with low land-surface model agreement (R = 0.68). A precise quantification of the impact on soil moisture retrieval would, however, need to consider actual soil moisture changes and sensor differences. The study demonstrates that the usage of higher spatial resolution data than currently available for SSM is required in lowland permafrost environments.; La connaissance de l'hydrologie de surface est essentielle mais difficile aux hautes latitudes du fait de la rareté des observations. Les observations satellites offrent le moyen d'y pallier, mais encore faut-il s'assurer de la validité de ces approches dans ces régions. Par l'intermédiaire de deux jeux de données satellite de résolutions différentes, on étudie ici la sensibilité du signal de micro-ondes actives rétrodiffusées à des facteurs autres que l'humidité superficielle des sols.Les zones d'étude ont été ciblées pour correspondre à des régions où les modèles hydrologiques divergent des observations. Dans la plupart de ces zones, l'utilisation d'un produit satellite à fine résolution met en évidence l'impact des lacs sur le signal micro-onde observé, et utilisé pour inférer l'humidité superficielle dans les produits satellites. Il est donc nécessaire d'apporter des corrections aux produits satellitaires dans les régions où la forte concentration en étendues d'eau libre et l'occurrence de vents violents en limitent la validité pour l'hydrologie de surface.

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    Authors: Latruffe, Laure; Mann, Stefan;

    In this paper we suggest that low labour availability on part-time farms may limit part-time farmers’ choice of production enterprises, and as a consequence those farmers may be forced to engage in less profitable enterprises. This proposition is illustrated by a conceptual framework based on the assumption that products with high returns to labour are labour intensive. An empirical analysis for the period 1996-2004 based on aggregated yearly data from the Swiss Farm Accountancy Data Network (FADN) did not fully confirm the proposition. This may suggest the existence of a joint determination of the choice of production enterprise and of the choice to work off the farm. In addition, our assumption that highly profitable enterprises are labour intensive may not hold for specific products or contexts. Bio-based and Applied Economics, Vol 4 No 2 (2015)

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    ProdInra
    Article . 2015
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    Authors: Martin Prchal; Antti Kause; Marc Vandeputte; David Gela; +6 Authors

    Correction(fichier annexe) : The genetics of overwintering performance in two-year old common carp and its relation to performance until market size (vol 13, e0191624, 2018); Using farmed common carp, we investigated the genetic background of the second year overwintering performance and its relation to the performance during the third growing season and at market size. The experimental stock was established by partial factorial design with a series of 4 factorial matings of 5 dams and 10 sires each. The families were reared communally and pedigree was re-constructed with 93.6% success using 12 microsatellites on 2008 offspring. Three successive recordings (second autumn, third spring, and third autumn—market size) covering two periods (second overwintering, third growing season) were included. Body weight, Fulton’s condition factor and percent muscle fat content were recorded at all times and headless carcass yield and fillet yield were recorded at market size. Specific growth rate, absolute and relative fat change and overall survival were calculated for each period. Heritability estimates were significantly different from zero and almost all traits were moderately to highly heritable (h2 = 0.36–1.00), except survival in both periods and fat change (both patterns) during overwintering (h2 = 0.12–0.15). Genetic and phenotypic correlations imply that selection against weight loss and fat loss during overwintering is expected to lead to a better winter survival, together with a positive effect on growth in the third growing season. Interestingly, higher muscle fat content was genetically correlated to lower survival in the following period (rg = -0.59; -0.53, respectively for winter and the third summer). On the other hand, higher muscle fat was also genetically linked to better slaughter yields. Moreover, selection for higher condition factor would lead to better performance during winter, growing season and at market size.

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    PLoS ONE
    Article . 2018
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    Authors: Mercier, Audrey; Betbeder, Julie; Rumiano, Florent; Baudry, Jacques,; +8 Authors

    Monitoring forest–agriculture mosaics is crucial for understanding landscape heterogeneity and managing biodiversity. Mapping these mosaics from remotely sensed imagery remains challenging, since ecological gradients from forested to agricultural areas make characterizing vegetation more difficult. The recent synthetic aperture radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) time series provide a great opportunity to monitor forest–agriculture mosaics due to their high spatial and temporal resolutions. However, while a few studies have used the temporal resolution of S-2 time series alone to map land cover and land use in cropland and/or forested areas, S-1 time series have not yet been investigated alone for this purpose. The combined use of S-1 & S-2 time series has been assessed for only one or a few land cover classes. In this study, we assessed the potential of S-1 data alone, S-2 data alone, and their combined use for mapping forest–agriculture mosaics over two study areas: a temperate mountainous landscape in the Cantabrian Range (Spain) and a tropical forested landscape in Paragominas (Brazil). Satellite images were classified using an incremental procedure based on an importance rank of the input features. The classifications obtained with S-2 data alone (mean kappa index = 0.59–0.83) were more accurate than those obtained with S-1 data alone (mean kappa index = 0.28–0.72). Accuracy increased when combining S-1 and 2 data (mean kappa index = 0.55–0.85). The method enables defining the number and type of features that discriminate land cover classes in an optimal manner according to the type of landscape considered. The best configuration for the Spanish and Brazilian study areas included 5 and 10 features, respectively, for S-2 data alone and 10 and 20 features, respectively, for S-1 data alone. Short-wave infrared and VV and VH polarizations were key features of S-2 and S-1 data, respectively. In addition, the method enables defining key periods that discriminate land cover classes according to the type of images used. For example, in the Cantabrian Range, winter and summer were key for S-2 time series, while spring and winter were key for S-1 time series.

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    Remote Sensing
    Article . 2019
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    Article . 2019
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    Authors: Mouysset, L; Doyen, L; Léger, F; Jiguet, F; +1 Authors

    It is possible to frame sustainability as occurring when the global or local system is within a set of limits and boundaries, such as the concept of safe operating spaces within planetary boundaries. However, such framings, whilst highly useful conceptually, have been difficult to translate into operation, especially in the development of policies. Here we show how it is possible to define a safe operating space, bounded by sets of constraints. These constraints can be of a variety of forms (e.g., income, or biodiversity), and, importantly, they need not all be converted to a single common metric such as money. The challenge is to identify a set of policy options that define the &ldquo such as would be the case if a single policy option were defined. Secondly, by allowing each boundary to be defined with its own scale of measurement, it avoids the necessity of having to value natural capital or ecosystem services in financial terms. This framework, therefore, has the potential to allow decision-makers to genuinely meet the needs of their people, now and in the future. which maintains the system within the safe operating space defined by boundaries. A formal methodology, Co-Viability Analysis (CVA), can be used to do this. This provides a coherent framework to operationalize sustainability and has a number of extra advantages. First, defining a safe policy space allows for a political choice of which policies and so is not prescriptive&mdash safe policy space&rdquo

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    Sustainability
    Article . 2018
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    ProdInra
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    Oskar Bordeaux
    Article . 2018
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    Authors: Jucker, T.; Caspersen, J.; Chave, J.; Antin, C.; +30 Authors

    Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. We thank the co-authors, field data collectors and funding agencies of the original data sources used in this study. We are also grateful to all curators of open-access databases from which we drew data for this study. In particular, we wish to thank Daniel Falster and Remko Duursma for compiling the biomass and allometry database (BAAD) for woody plants; Michael Keller and Maiza Nara for providing us access to data from the Sustainable Landscapes Brazil project; Kristina Anderson-Teixeira and her co-authors for archiving allometric data from the CTFS-ForestGEO forest dynamics plot at the Smithsonian Conservation Biology Institute (Virginia, USA); and KaDonna Randolph of the USDA forest service for her assistance in accessing the Forest Health Monitoring (FHM) database. We thank Bruno H?rault and an anonymous reviewer for their thoughtful and constructive comments on an earlier draft of our manuscript. T.J. was funded by NERC (grant number: NE/K016377/1). This work has benefited from ANR grants to J.C. (CEBA, ref. ANR-10-LABX-25-01 and TULIP, ref. ANR-10-LABX-0041). The Sustainable Landscapes Brazil project was supported by the Brazilian Agricultural Research Corporation (EMBRAPA), the US Forest Service, and USAID, and the US Department of State. Data collection for the UNECE ICP Forests PCC Collaborative Database was cofinanced by national or regional organizations and by the European Commission under regulations (EEC) No 2158/86, Forest Focus (EC) No 2152/200, FutMon (EC) LIFE07 ENV/D/218.

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    Other literature type . 2017
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    MPG.PuRe
    Article . 2017
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    MPG.PuRe
    Article . 2017
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    Apollo
    Article . 2016
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      Other literature type . 2017
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      MPG.PuRe
      Article . 2017
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      Apollo
      Other literature type . 2017
      Data sources: Apollo
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      MPG.PuRe
      Article . 2017
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      Apollo
      Article . 2016
      Data sources: Datacite
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    Authors: Métras, Raphaëlle; Fournié, Guillaume; Dommergues, Laure; Camacho, Anton; +6 Authors

    Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data. Author summary Rift Valley fever (RVF) is an arboviral hemorrhagic fever affecting primarily livestock in Africa and in the Arabian Peninsula. The conditions leading to RVF emergence are not fully understood, mainly because of data scarcity. Applied to the island of Mayotte (our ecosystem under study), for which 12 years RVF serological dataset are available, and by using a mechanistic model, we demonstrate that RVF epidemics related mainly to the introduction of infectious animals. Our work confirms that anthropogenic factors, such as livestock movements, need to be accounted for in order to understand the epidemiology of this disease. Our model should be tested elsewhere, with ecosystem-specific data.

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    DOAJ
    Article . 2017
    Data sources: DOAJ
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    Authors: Campos Brusamarello, Liziane; Gilard, Françoise; Brule, Lenaïg; Quillere, Isabelle; +5 Authors

    International audience; Maize roots can be colonized by free-living atmospheric nitrogen (N2)-fixing bacteria (diazotrophs). However, the agronomic potential of non-symbiotic N2-fixation in such an economically important species as maize, has still not been fully exploited. A preliminary approach to improve our understanding of the mechanisms controlling the establishment of such N2-fixing associations has been developed, using two maize inbred lines exhibiting different physiological characteristics. The bacterial-plant interaction has been characterized by means of a metabolomic approach. Two established model strains of Nif+ diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense and their Nif- couterparts defficient in nitrogenase activity, were used to evaluate the impact of the bacterial inoculation and of N2 fixation on the root and leaf metabolic profiles. The two N2-fixing bacteria have been used to inoculate two genetically distant maize lines (FV252 and FV2), already characterized for their contrasting physiological properties. Using a well-controlled gnotobiotic experimental system that allows inoculation of maize plants with the two diazotrophs in a N-free medium, we demonstrated that both maize lines were efficiently colonized by the two bacterial species. We also showed that in the early stages of plant development, both bacterial strains were able to reduce acetylene, suggesting that they contain functional nitrogenase activity and are able to efficiently fix atmospheric N2 (Fix+). The metabolomic approach allowed the identification of metabolites in the two maize lines that were representative of the N2 fixing plant-bacterial interaction, these included mannitol and to a lesser extend trehalose and isocitrate. Whilst other metabolites such as asparagine, although only exhibiting a small increase in maize roots following bacterial infection, were specific for the two Fix+ bacterial strains, in comparison to their Fix- counterparts. Moreover, a number of metabolites exhibited a maize-genotype specific pattern of accumulation, suggesting that the highly diverse maize genetic resources could be further exploited in terms of beneficial plant-bacterial interactions for optimizing maize growth, with reduced N fertilization inputs.

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    PLoS ONE
    Article . 2017
    Data sources: DOAJ-Articles
    DOAJ
    Article . 2017
    Data sources: DOAJ
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