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The banana weevil Cosmopolites sordidus Germar is the most important pest of banana and plantain. In banana agroecosystems, cover cropping is a practice that prevents the use of herbicides and may provide natural habitats for generalist predators. Here, we assessed the effect of a cover crop, Paspalum notatum Flüggé on the ant community, dermapterans and C. sordidus. In investigating the dumps of Pheidole jelskii Mayr colonies, we found that most of carcasses belonged to other ant species (> 96%) and very few (< 1%) belonged to C. sordidus. In plots with banana plants and with and without a cover crop, the occurrences of almost all ant species were negatively correlated with each other, but the occurrence of ants was not correlated with weevil abundance. However, we found a negative relationship between the abundances of dermapterans and C. sordidus, both of which were negatively related to presence of the cover crop. These results indicate that dermapterans are probably the main biological control agents of C. sordidus and that cover cropping may increase C. sordidus regulation.

Soil health is defined as the soil's capacity to deliver ecosystem functions within environmental constraints. On tree plantations, clear-cutting and land preparation between two crop cycles cause severe physical disturbances to the soil and seriously deplete soil organic carbon and biodiversity. Rubber, one of the main tropical perennial crops worldwide, has a plantation life cycle of 25 to 40 years, with successive replanting cycles on the same plot. The aim of this study was to assess the effects of clear-cutting disturbance on three soil functions (carbon transformation, nutrient cycling and structure maintenance) and their restoration after the planting of the new rubber crop, in two contrasting soil situations (Arenosol and Ferralsol) in Côte d'Ivoire. In this 18-month diachronic study, we intensively measured soil functions under different scenarios as regards the management of logging residues and the use or not of a legume cover crop. We investigated the relationship between soil macrofauna diversity and soil heath. At both sites, clear-cutting and land preparation disturbed carbon transformation and nutrient cycling significantly and, to a lesser extent, structure maintenance function. When logging residues were applied, carbon transformation and structure maintenance functions were fully restored within 12 to 18 months after disturbance. By contrast, no restoration of nutrient cycling was observed over the study period. A legume cover crop mainly improved the restoration of carbon transformation. We found a strong relationship (P ≤ 0.001; R2 = 0.62–0.66) between soil macrofauna diversity and soil health. Our overall results were very similar at the two sites, despite their contrasting soil conditions. Keeping logging residues in the plots and sowing a legume in the inter-row at replanting accelerated the restoration of soil functions after major disturbance caused by clear-cutting and land preparation. Our results confirm the necessity of taking soil macrofauna diversity into account in the management of tropical perennial crops.

1 Understanding the effect of ground types on foraging movements of ground-dwelling arthropods is a key step to managing their spatial distribution as required for successful conservation biological control. Indeed, fine movements at the centimetre scale can strongly influence the foraging ability of pest predators. However, because RFID or harmonic tracking techniques are not yet suitable for small species and video tracking focuses on uniform and light backgrounds, foraging movements have rarely been studied in relation to ground types. 2 We present a method to track a ground-dwelling arthropod (the earwig Euborellia caraibea) at night, walking on two contrasted ground types : bare soil and soil partly covered with a stratum of banana plant residues allowing individuals to hide periodically. 3 The tracking of individuals within these ground types was achieved by infrared light, tagging individuals, video treatments and semi-automatic cleaning of trajectories. We tested different procedures to obtain segments with identical durations to quantify speeds and sinuosities. These procedures were characterised by the junction time gap between trajectory fragments, the rediscretisation time of trajectories, and whether or not to use interpolation to fill in missing points in the trajectories. 4 Earwigs exhibited significantly slower and more sinuous movements on soil with banana plant residues than on bare soil. Long time gaps for trajectory junction, extended rediscretisation times and interpolation were complementary means to integrate concealed movements in the trajectories. The highest slowdown in plant residues was detected when the procedure could account for longer periods under the residues. 5 These results suggest that earwigs spent a significant amount of time concealed by the residues. Additionally, the residues strongly decreased the earwigs’ movement. Since the technical solutions presented in this study are inexpensive, easy to set up and replicate, they represent valuable contributions to the emerging field of video monitoring.

In Montane Southeast Asia, deforestation and unsuitable combinations of crops and agricultural practices degrade soils at an unprecedented rate. Typically, smallholder farmers gain income from "available" land by replacing fallow or secondary forest by perennial crops. We aimed to understand how these practices increase or reduce soil erosion. Ten land uses were monitored in Northern Laos during the 2015 monsoon, using local farmers' fields. Experiments included plots of the conventional system(food crops and fallow), and land uses corresponding to new market opportunities (e.g. commercial tree plantations). Land uses were characterized by measuring plant cover and plant mean height per vegetation layer. Recorded meteorological variables included rainfall intensity, throughfall amount, throughfall kinetic energy (TKE), and raindrop size. Runoff coefficient, soil loss, and the percentage areas of soil surface types (free aggregates and gravel; crusts; macro-faunal, vegetal and pedestal features; plant litter) were derived from observations and measurements in 1-m(2) micro-plots. Relationships between these variables were explored with multiple regression analyses. Our results indicate that TKE induces soil crusting and soil loss. By reducing rainfall infiltration, crusted area enhances runoff, which removes and transports soil particles detached by splash over non-crusted areas. TKE is lower under land uses reducing the velocity of raindrops and/or preventing an increase in their size. Optimal vegetation structures combine minimum height of the lowest layer (to reduce drop velocity at ground level) and maximum coverage (to intercept the largest amount of rainfall), as exemplified by broom grass (Thysanolaena latifolia). In contrast, high canopies with large leaves will increase TKE by enlarging raindrops, as exemplified by teak trees (Tectona grandis), unless a protective understorey exists under the trees. Policies that ban the burning of multi-layered vegetation structure under tree plantations should be enforced. Shade-tolerant shrubs and grasses with potential economic return could be promoted as understorey.

Terrestrial evapotranspiration (ET) for each plant functional type (PFT) is a key variable for linking the energy, water and carbon cycles of the atmosphere, hydrosphere and biosphere. Process-based algorithms have been widely used to estimate global terrestrial ET, yet each ET individual algorithm has exhibited large uncertainties. In this study, the support vector machine (SVM) method was introduced to improve global terrestrial ET estimation by integrating three process-based ET algorithms: MOD16, PT-JPL and SEMI-PM. At 200 FLUXNET flux tower sites, we evaluated the performance of the SVM method and others, including the Bayesian model averaging (BMA) method and the general regression neural networks (GRNNs) method together with three process-based ET algorithms. We found that the SVM method was superior to all other methods we evaluated. The validation results showed that compared with the individual algorithms, the SVM method driven by tower-specific (Modern Era Retrospective Analysis for Research and Applications, MERRA) meteorological data reduced the root mean square error (RMSE) by approximately 0.20 (0.15) mm/day for most forest sites and 0.30 (0.20) mm/day for most crop and grass sites and improved the squared correlation coefficient (R2) by approximately 0.10 (0.08) (95% confidence) for most flux tower sites. The water balance of basins and the global terrestrial ET calculation analysis also demonstrated that the regional and global estimates of the SVM-merged ET were reliable. The SVM method provides a powerful tool for improving global ET estimation to characterize the long-term spatiotemporal variations of the global terrestrial water budget. (Resume d'auteur)

Soil organisms, including earthworms, are a key component of terrestrial ecosystems. However, little is known about their diversity, their distribution, and the threats affecting them. We compiled a global dataset of sampled earthworm communities from 6928 sites in 57 countries as a basis for predicting patterns in earthworm diversity, abundance, and biomass. We found that local species richness and abundance typically peaked at higher latitudes, displaying patterns opposite to those observed in aboveground organisms. However, high species dissimilarity across tropical locations may cause diversity across the entirety of the tropics to be higher than elsewhere. Climate variables were found to be more important in shaping earthworm communities than soil properties or habitat cover. These findings suggest that climate change may have serious implications for earthworm communities and for the functions they provide.

International audience; The aim of this paper is to provide a better understanding of potentialities of the new Sentinel-1 radar images for mapping the different crops in the Camargue region in the South France. The originality relies on deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. 50 Sentinel-1 images processed in order to produce an intensity radar data stack from May 2017 to September 2017. We revealed that even with classical machine learning approaches (K nearest neighbors, random forest, and support vector machine), good performance classification could be achieved with F-measure/Accuracy greater than 86 % and Kappa coefficient better than 0.82. We found that the results of the two deep recurrent neural network (RNN)-based classifiers clearly outperformed the classical approaches. Finally, our analyses of Camargue area results show that the same performance was obtained with two different RNN-based classifiers on the Rice class, which is the most dominant crop of this region, with a F-measure metric of 96 %. These results thus highlight that in the near future, these RNN-based techniques will play an important role in the analysis of remote sensing time series.

Cette étude vise à tester l’effet de systèmes de culture en semis direct sous couverture végétale permanente (SCV) pour contrôler l’érosion hydrique et améliorer le rendement de cultures pluviales sur versant des Hautes-Terres de Madagascar. L’essai a été entrepris sur un dispositif expérimental d’érosion à Andranomanelatra, sous pluies naturelles. Le dispositif comporte plusieurs traitements en SCV et en labour conventionnel (bêchage à l’angady) ainsi qu’un témoin avec sol nu et un autre en jachère herbacée spontanée. Pendant quatre campagnes, des mesures du ruissellement, des pertes en terre, de la hauteur de la pluie et de son intensité maximale ont été effectuées à chaque événement pluvial érosif. Des mesures de rendements ont également été réalisées à la fin de chaque campagne culturale.Dans le contexte étudié, les résultats obtenus ont confirmé l’effet positif du système SCV sur la réduction du ruissellement et de l’érosion. Les ruissellements sur les parcelles labourées et sur la parcelle nue sont respectivement huit et quatorze fois plus élevés que sur les parcelles SCV. Les pertes en terre sur les parcelles labourées et la parcelle nue sont respectivement de7,6 et 22,1 t/ha/an alors que sur les parcelles SCV, elles sont d’environ 0,13 t/ha/ an.En général, les rendements en maïs et en riz pluvial obtenus sur les parcelles labourées et en SCV sous couverture morte ne diffèrent pas significativement. Mais les rendements en maïs et riz pluvial sont significativement plus faibles en SCV avec couverture vivante de Brachiaria ruziziensis que pour les parcelles labourées. En revanche, le rendement moyen en haricot est nettement et significativement plus élevé sur les parcelles SCV que sur les parcelles labourées.

International audience; Mapping ecosystem services (ES) over large scales is important for environmental monitoring but is often prohibitively expensive and difficult. We test a hybrid, low-cost method of mapping ES indicators over large scales in Para State, Brazil. Four ES indicators (vegetation carbon stocks, biodiversity index, soil chemical quality index and rates of water infiltration into soil) were measured in the field and then summarized spatially for regional land-cover classes derived from satellite imagery. The regionally mapped ES values correlated strongly with independent and local measures of ES. For example, regional estimates of the vegetation carbon stocks are strongly correlated with actual measures derived from field samples and validation data (significant anova test - p-value=4.51(e-9)) and differed on average by only 20Mg/ha from the field data. Our spatially-nested approach provides reliable and accurate maps of ES at both local and regional scales. Local maps account for the specificities of an area while regional maps provide an accurate generalization of an ES' state. Such up-scaling methods infuse large-scale ES maps with localized data and enable the estimation of uncertainty of at regional scales. Our approach is first step towards the spatial characterization of ES at large and potentially global scales

Globally, anthropogenic environmental change is exacerbating the already vulnerable conditions of many people and ecosystems. In order to obtain food, water, raw materials and shelter, rural people modify forests and other ecosystems, affecting the supply of ecosystem services that contribute to livelihoods and well-being. Despite widespread awareness of the nature and extent of multiple impacts of land-use changes, there remains limited understanding of how these impacts affect trade-offs among ecosystem services and their beneficiaries across spatial scales. We assessed how rural communities in two forested landscapes in Indonesia have changed land uses over the last 20 years to adapt their livelihoods that were at risk from multiple hazards. We estimated the impact of these adaptation strategies on the supply of ecosystem services by comparing different benefits provided to people from these land uses (products, water, carbon, and biodiversity), using forest inventories, remote sensing, and interviews. Local people converted forests to rubber plantations, reforested less productive croplands, protected forests on hillsides, and planted trees in gardens. Our results show that land-use decisions were propagated at the landscape scale due to reinforcing loops, whereby local actors perceived that such decisions contributed positively to livelihoods by reducing risks and generating co-benefits. When land-use changes become sufficiently widespread, they affect the supply of multiple ecosystem services, with impacts beyond the local scale. Thus, adaptation implemented at the local-scale may not address development and climate adaptation challenges at regional or national scale (e.g. as part of UN Sustainable Development Goals or actions taken under the UNFCCC Paris Agreement). A better understanding of the context and impacts of local ecosystem-based adaptation is fundamental to the scaling up of land management policies and practices designed to reduce risks and improve well-being for people at different scales.

Conservation agriculture (CA) is based on the principles of minimum soil disturbance, permanent soil cover and diversification of crop species grown in rotations and/or associations. CA was introduced in the late 90s in the Lake Alaotra region, Madagascar, in order to improve rainfed crop productivity which is commonly constrained by low soil fertility, soil water stress and weed infestation. The main objective of this study was to quantify and understand the impact of CA on rainfed rice productivity as compared to the practice of conventional tillage (CT). First, a review of literature was conducted on the agro-ecological functions of mulching with crop residues in relation to their quantity. The literature review showed that the optimal amount of residues required principally depends on the agro-ecological function searched for. Residue amounts of 2 to 3 t ha-1 had clear positive effects in terms of improving water infiltration and limiting water runoff and soil erosion. On the other hand, results on weed control, nutrient availability and soil fauna in relation to the amount of mulch were highly variable, suggesting the interaction of these agro-ecological functions with other factors, including residue type and soil-climate conditions. Second, two field experiments were monitored at the research center of FOFIFA in the Lake Alaotra region. A first experiment aiming at quantifying the physical effect of a mulch of crop residues on weed infestation, with amounts of surface residues ranging from 0 to 45 t ha-1 showed that the emergence and biomass of weeds on mulched plots depend mainly on the quantity and distribution of rainfall during the cropping season. Overall, weed emergence and biomass decreased with increasing amounts of mulch. However, a large quantity of residues, i.e. in the order of 10 t ha-1, was required to significantly (p

International audience

La notion de culture intermédiaire a clairement évolué historiquement, en fonction du service recherché, passant par exemple de la notion d’engrais vert à CIPAN (piège à nitrate) dans les années 1970 à 1990, et aujourd’hui nous proposons d’utiliser l’acronyme de CIMS pour parler de cultures intermédiaires multi-services). Ces CIMS sont utilisées pour produire des services écosystémiques en période d’interculture. Ce sont des cultures qui ne sont pas récoltées, elles sont enfouies ou laissées en surface du sol. Les CIMS permettent de produire simultanément différents services écosystémiques, avec plus ou moins d’efficacité en fonction des espèces ou du mélange d’espèces semées, de leur mode de gestion, de la situation pédo-climatique et de la succession de cultures de vente dans laquelle elles sont insérées. Les services produits concernent i) la gestion de l’azote (effet piège à nitrate), ii) la protection physique du sol, iii) le stockage de carbone, iv) la réduction des bio-agresseurs (mauvaises herbes, pathogènes), v) la pollinisation, vi) l’esthétique du paysage. Le bouquet de services qui peut être produit par la CIMS et l’éventuel compromis recherché entre les services produits doit être défini explicitement afin de choisir la bonne espèce ou de concevoir l’assemblage d’espèces à implanter. Un grand nombre de familles botaniques peuvent être utilisées comme CIMS (crucifères, graminées, légumineuses, composées, autres familles). Toutefois, il convient de choisir des espèces non hôtes des maladies et ravageurs des cultures principales, ceci pour limiter les éventuels dis-services. De plus, pour maximiser les services écosystémiques rendus par les mélanges d’espèces, il est nécessaire que l’association permette une bonne complémentarité de développement et de croissance. Enfin, nous faisons l’hypothèse que les CIMS, avec des espèces bien choisies et gérés avec des itinéraires techniques adaptés, peuvent être un levier efficace d’une écologisation des systèmes de culture français, sans nécessairement avoir besoin de transformer radicalement le système, ni le niveau de travail du sol, The notion of cover crop has clearly evolved historically, in particular in France and Europe, depending on the service provided, moving from the notion of green manure to catch crop, and today we are proposing the term of Multi-services cover crops (MSCC). These MSCC are used in agriculture to produce various ecosystem services during fallow period between two main cash crops. These MSCC are not harvested and their biomass is returning to the soil (incorporated or at soil surface). The provision of multi-services depend on the species, the mixtures of species, the management of the cover crop, the pedo-climat conditions and the cash crop succession in which the MSCC is inserted. E. Justes et G. The services produced are the following: i) nitrogen management (nitrate catch crop and green manuring), ii) soil protection, iii) carbon storage in the soil, iv) control and suppression of weeds, diseases and pests, v) pollinisation of plants and vi) landscape aesthetic. The trade-off between services produced by the MSCC must be explicitly defined before their setting up in order to correctly select the right species or the design of species assemblage appropriate to produce the targeted services and their level of expression. Many botanical families can be used as MSCC (cruciferous, grass, legume, other families). However, it is advisable to choose non-host species of diseases and pests of main cash crops, in order to limit the possible dis-services. In addition, to maximize the ecosystem services provided by species chosen, it is necessary for the association to achieve good complementarity of development and growth. Finally, we hypothesize that MSCC, with well-chosen species and well managed, can be an effective lever for an ecologization of French cropping systems, without necessarily having to radically transform the cropping system, nor the level of soil tillage.

© 2017 The Author(s) Forest-driven water and energy cycles are poorly integrated into regional, national, continental and global decision-making on climate change adaptation, mitigation, land use and water management. This constrains humanity's ability to protect our planet's climate and life-sustaining functions. The substantial body of research we review reveals that forest, water and energy interactions provide the foundations for carbon storage, for cooling terrestrial surfaces and for distributing water resources. Forests and trees must be recognized as prime regulators within the water, energy and carbon cycles. If these functions are ignored, planners will be unable to assess, adapt to or mitigate the impacts of changing land cover and climate. Our call to action targets a reversal of paradigms, from a carbon-centric model to one that treats the hydrologic and climate-cooling effects of trees and forests as the first order of priority. For reasons of sustainability, carbon storage must remain a secondary, though valuable, by-product. The effects of tree cover on climate at local, regional and continental scales offer benefits that demand wider recognition. The forest- and tree-centered research insights we review and analyze provide a knowledge-base for improving plans, policies and actions. Our understanding of how trees and forests influence water, energy and carbon cycles has important implications, both for the structure of planning, management and governance institutions, as well as for how trees and forests might be used to improve sustainability, adaptation and mitigation efforts. publisher: Elsevier articletitle: Trees, forests and water: Cool insights for a hot world journaltitle: Global Environmental Change articlelink: http://dx.doi.org/10.1016/j.gloenvcha.2017.01.002 content_type: article copyright: © 2017 The Author(s). Published by Elsevier Ltd. ispartof: Global Environmental Change vol:43 pages:51-61 status: published

In this study, we propose a simple and efficient texture-based algorithm for image segmentation. This method constitutes computing textons and bag of words (BOWs) learned by support vector machine (SVM) classifiers. Textons are composed of local magnitude coefficients that arise from the Q-Shift Dual-Tree Complex Wavelet Transform (DT-CWT) combined with color components. In keeping with the needs of our research context, which addresses land cover mapping from remote images, we use a few small texture patches at the training stage, where other supervised methods usually train fully representative textures. We accounted for the scale and rotation invariance issue of the textons, and three different invariance transforms were evaluated on DT-CWT-based features. The largest contribution of this study is the comparison of three classification schemes in the segmentation algorithm. Specifically, we designed a new scheme that was especially competitive and that uses several classifiers, with each classifier adapted to a specific size of analysis window in texton quantification and trained on a reduced data set by random selection. This configuration allows quick SVM convergence and an easy parallelization of the SVM-bank while maintaining a high segmentation accuracy. We compare classification results with textons made using the well-known maximum response filters bank and speed up robust features features as references. We show that DT-CWT textons provide better distinguishing features in the entire set of configurations tested. Benchmarks of our different method configurations were made over two substantial textured mosaic sets, each composed of 100 grey or color mosaics made up of Brodatz or VisTex textures. Lastly, when applied to remote sensing images, our method yields good region segmentation compared to the ENVI commercial software, which demonstrates that the method could be used to generate land cover maps and is suitable for various purposes in image segmentation.

Ce numéro est constitué d’articles issus du colloque CIMS : Des Cultures Intermédiaires Multi-Services pour une production agroécologique performante, organisé le 4 octobre 2017 à Auzeville.; The notion of cover crop has clearly evolved historically, in particular in France and Europe, dependingon the service provided, moving from the notion of green manure to catch crop, and today we areproposing the term of Multi-services cover crops (MSCC). These MSCC are used in agriculture toproduce various ecosystem services during fallow period between two main cash crops. These MSCCare not harvested and their biomass is returning to the soil (incorporated or at soil surface). Theprovision of multi-services depend on the species, the mixtures of species, the management of thecover crop, the pedo-climat conditions and the cash crop succession in which the MSCC is inserted. E. Justes et G. The services produced are the following: i) nitrogen management (nitrate catch crop and greenmanuring), ii) soil protection, iii) carbon storage in the soil, iv) control and suppression of weeds,diseases and pests, v) pollinisation of plants and vi) landscape aesthetic. The trade-off betweenservices produced by the MSCC must be explicitly defined before their setting up in order to correctlyselect the right species or the design of species assemblage appropriate to produce the targetedservices and their level of expression. Many botanical families can be used as MSCC (cruciferous,grass, legume, other families). However, it is advisable to choose non-host species of diseases andpests of main cash crops, in order to limit the possible dis-services. In addition, to maximize theecosystem services provided by species chosen, it is necessary for the association to achieve goodcomplementarity of development and growth. Finally, we hypothesize that MSCC, with well-chosenspecies and well managed, can be an effective lever for an ecologization of French cropping systems,without necessarily having to radically transform the cropping system, nor the level of soil tillage.; La notion de culture intermédiaire a clairement évolué historiquement, en fonction du service recherché,passant par exemple de la notion d’engrais vert à CIPAN (piège à nitrate) dans les années 1970 à1990, et aujourd’hui nous proposons d’utiliser l’acronyme de CIMS pour parler de culturesintermédiaires multi-services). Ces CIMS sont utilisées pour produire des services écosystémiques enpériode d’interculture. Ce sont des cultures qui ne sont pas récoltées, elles sont enfouies ou laissées ensurface du sol. Les CIMS permettent de produire simultanément différents services écosystémiques,avec plus ou moins d’efficacité en fonction des espèces ou du mélange d’espèces semées, de leurmode de gestion, de la situation pédo-climatique et de la succession de cultures de vente dans laquelleelles sont insérées. Les services produits concernent i) la gestion de l’azote (effet piège à nitrate), ii) laprotection physique du sol, iii) le stockage de carbone, iv) la réduction des bio-agresseurs (mauvaisesherbes, pathogènes), v) la pollinisation, vi) l’esthétique du paysage. Le bouquet de services qui peutêtre produit par la CIMS et l’éventuel compromis recherché entre les services produits doit être définiexplicitement afin de choisir la bonne espèce ou de concevoir l’assemblage d’espèces à implanter. Ungrand nombre de familles botaniques peuvent être utilisées comme CIMS (crucifères, graminées,légumineuses, composées, autres familles). Toutefois, il convient de choisir des espèces non hôtes desmaladies et ravageurs des cultures principales, ceci pour limiter les éventuels dis-services. De plus,pour maximiser les services écosystémiques rendus par les mélanges d’espèces, il est nécessaire quel’association permette une bonne complémentarité de développement et de croissance. Enfin, nousfaisons l’hypothèse que les CIMS, avec des espèces bien choisies et gérés avec des itinérairestechniques adaptés, peuvent être un levier efficace d’une écologisation des systèmes de culturefrançais, sans nécessairement avoir besoin de transformer radicalement le système, ni le niveau detravail du sol

Although vegetation is increasingly used to mitigate landslide risks, how vegetation affects the temporal variability of slope stability is poorly understood, especially in earthquake-prone regions. We combined 3-year long soil moisture monitoring, measurements of soil physical properties and plant functional traits, and numerical modeling to compare slope stability under paired land uses with and without trees in tropical, sub-tropical, and temperate landslide- and earthquake-prone regions. Trees improved stability for 5-12 months per year from drawdown of soil moisture and resulted in less interannual variability in the duration of high-stability periods compared to slopes without trees. Our meta-analysis of published data also showed that slopes with woody vegetation were more stable and less sensitive to climate and soil factors than slopes with herbaceous vegetation. However, estimates of earthquake magnitude necessary to destabilize slopes at our sites suggest that large additional stabilization from trees is necessary for meaningful protection against external triggers.

The influence of vegetation on slope stability is well understood at the slope level but scaling up to the catchment level is still a challenge, partially because of a lack of suitable data to validate models. We tested the physical landslide model, LAPSUS_LS, which models slope stability at the catchment scale. LAPSUS_LS combines a hydrological model with a Limit Equilibrium Method model, and calculates the factor of safety of individual cells based on their hydrological and geomorphological characteristics. We tested two types of vegetation on slope stability: (i) coffee monoculture (Coffea arabica) and (ii) a mixed plantation of coffee and deep rooting Erythrina (Erythrina poeppigiana) trees. Using soil and root data from Costa Rica, we performed simulations to test the response of LAPSUS_LS to root reinforcement, soil bulk density, transmissivity, internal friction angle and depth of shear plane. Furthermore, we modified the model to include biomass surcharge effect in the calculations. Results show that LAPSUS_LS was most sensitive to changes in additional cohesion from roots. When the depth of the shear plane was fixed at 1.0 m, slopes were not unstable. However, when the shear plane was fixed to 1.5 m, the mixed plantation of coffee and trees stabilized slopes, but the coffee monoculture was highly unstable, because root reinforcement was low at a depth of 1.5 m. Soil transmissivity had a limited impact on the results compared to bulk density and internal friction angle. Biomass surcharge did not have any significant effect on the simulations. In conclusion, LAPSUS_LS responded well to the soil and vegetation input data, and is a suitable candidate for modeling the stability of vegetated slopes at the catchment level.

Accurate cropland maps at the global and local scales are crucial for scientists, government and nongovernment agencies, farmers and other stakeholders, particularly in food-insecure regions, such as Sub-Saharan Africa. In this study, we aim to qualify the crop classes of the MODIS Land Cover Product (LCP) in Sub-Saharan Africa using FAO (Food and Agricultural Organisation) and AGRHYMET (AGRiculture, Hydrology and METeorology) statistical data of agriculture and a sample of 55 very-high-resolution images. In terms of cropland acreage and dynamics, we found that the correlation between the statistical data and MODIS LCP decreases when we localize the spatial scale (from R2 = 0.86 *** at the national scale to R2 = 0.26 *** at two levels below the national scale). In terms of the cropland spatial distribution, our findings indicate a strong relationship between the user accuracy and the fragmentation of the agricultural landscape, as measured by the MODIS LCP; the accuracy decreases as the crop fraction increases. In addition, thanks to the Pareto boundary method, we were able to isolate and quantify the part of the MODIS classification error that could be directly linked to the performance of the adopted classification algorithm. Finally, based on these results, (i) a regional map of the MODIS LCP user accuracy estimates for cropland classes was produced for the entire Sub-Saharan region; this map presents a better accuracy in the western part of the region (43%–70%) compared to the eastern part (17%–43%); (ii) Theoretical user and producer accuracies for a given set of spatial resolutions were provided; the simulated future Sentinel-2 system would provide theoretical 99% user and producer accuracies given the landscape pattern of the region.

The new generation Earth observation missions such as Sentinel-2 (a twin-satellite initiative prepared by the European Space Agency, ESA, in the frame of the Copernicus programme, previously known as Global Monitoring for Environment and Security or GMES) and Venμs, jointly developed by the French Space Agency (Centre National d’Études Spatiales, CNES) and the Israeli Space Agency (ISA), will revolutionize present-day environmental monitoring with the yielding of unseen volumes of data in terms of spectral richness, temporal revisit and spatial resolution. Venμs will deliver images in 12 spectral bands from 412 to 910 nm, a repetitivity of 2 days, and a spatial resolution of 10 m; the twin Sentinel-2 satellites will provide coverage in 13 spectral bands from 443 to 2200 nm, with a repetitivity of 5 days, and spatial resolutions of 10 to 60m.The efficient production of land cover maps based on the exploitation of such volumes of information for large areas is challenging both in terms of processing costs and data variability. In general, conventional methods either make use of supervised approaches (too costly in terms of manual work for large areas), target specialised local models for precise problem areas (not applicable to other terrains or applications), or include complex physical models with inhibitory processing costs. These existent present-day approaches are thus inefficient for the exploitation of the new type of data that the new missions will provide, and a need arises for the implementation of accurate, fast and minimally supervised methods that allow for generalisation to large scale areas with high resolutions.In order to allow for the exploitation of the previously described volumes of data, the objective of this thesis is the conception, design, and validation of a fully automatic approach that allows the estimation of large-area land cover with high spatial, spectral and temporal resolution Earth observation imagery, being generalisable to different landscapes, and offering operational computation times with simulated satellite data sets, in preparation of the coming missions. This approach is based on the integration of data processing algorithms, such as model learning and classification techniques, and land cover background knowledge on ecological and agricultural issues such as vegetation growth impact variables and practices. For example, the new introduction of temperature as a temporal axis for subsequent model learning incorporates an established vegetation growth factor to machine learning techniques for characterization across landscapes.In particular, attention is paid to deal with different issues, such as automation, missing information (determined by satellite tracks, cloud reflectance effects, shadows and snow presence), limited learning and validation data, irregular time sampling (different number of images available for each period and region, and unevenly distributed in time), data variability, and the possibility of working with different data sets and nomenclatures. To this aim, a processing methodology has been devised, automatic and not requiring any date selection or user manual work, and allowing the use of different nomenclatures and data sets. Thus, the developed methodology demonstrates the feasibility of automatic production of large scale land cover maps, dealing with data volume and variability, limited reference data and missing information, and integrating specialised knowledge and different data processing algorithms.This work is framed by the research support programme Terre, Océan, Surfaces Continentales, Atmosphère (TOSCA) of the Centre National d'Études Spatiales, in relation to three research proposals: Production de cartes d’occupation des sols à échelle régionale a partir de données SPOT HRV multitemporelles by Jordi Inglada, and Traitement et utilisation de séries temporelles d’images LANDSAT pour préparer le traitement et les applications de Venμs et Sentinel-2 and Centre D'ALgorithmie et de VAlidation des Données Venμs et Sentinel-2 (CALVADOVS) by Olivier Hagolle. It is dependent of the doctoral school Sciences de l'Univers, de l'Environnement et de l'Espace (SDU2E) of Paul Sabatier University and it has been developed in the laboratory Centre d’Études Spatiales de la BIOsphère (CESBIO) in Toulouse, France.; Les missions spatiales d'observation de la Terre de nouvelle génération telles que Sentinel-2 (préparé par l'Agence Spatiale Européenne ESA dans le cadre du programme Copernicus, auparavant appelé Global Monitoring for Environment and Security ou GMES) ou Venμs, conjointement développé par l'Agence Spatiale Française (Centre National d 'Études Spatiales CNES) et l'Agence Spatiale Israélienne (ISA), vont révolutionner la surveillance de l'environnement d' aujourd'hui avec le rendement de volumes inédits de données en termes de richesse spectrale, de revisite temporelle et de résolution spatiale. Venμs livrera des images dans 12 bandes spectrales de 412 à 910 nm, une répétitivité de 2 jours et une résolution spatiale de 10 m; les satellites jumeaux Sentinel-2 assureront une couverture dans 13 bandes spectrales de 443 à 2200 nm, avec une répétitivité de 5 jours, et des résolutions spatiales de 10 à 60m.La production efficace de cartes d'occupation des sols basée sur l'exploitation de tels volumes d'information pour grandes surfaces est un défi à la fois en termes de coûts de traitement mais aussi de variabilité des données. En général, les méthodes classiques font soit usage des approches surveillées (trop coûteux en termes de travaux manuels pour les grandes surfaces), ou soit ciblent des modèles locaux spécialisés pour des problématiques précises (ne s'appliquent pas à autres terrains ou applications), ou comprennent des modèles physiques complexes avec coûts de traitement rédhibitoires. Ces approches existantes actuelles sont donc inefficaces pour l'exploitation du nouveau type de données que les nouvelles missions fourniront, et un besoin se fait sentir pour la mise en œuvre de méthodes précises, rapides et peu supervisées qui permettent la généralisation à l'échelle de grandes zones avec des résolutions élevées.Afin de permettre l'exploitation des volumes de données précédemment décrits, l'objectif de ce travail est la conception et validation d'une approche entièrement automatique qui permet l'estimation de la couverture terrestre de grandes surfaces avec imagerie d'observation de la Terre de haute résolution spatiale, spectrale et temporelle, généralisable à des paysages différents, et offrant un temps de calcul opérationnel avec ensembles de données satellitaires simulés, en préparation des prochaines missions. Cette approche est basée sur l'intégration d'algorithmes de traitement de données, tels que les techniques d'apprentissage de modèles et de classification, et des connaissances liées à l'occupation des sols sur des questions écologiques et agricoles, telles que les variables avec un impact sur la croissance de la végétation ou les pratiques de production. Par exemple, la nouvelle introduction de température comme axe temporel pour un apprentissage des modèles ultérieurs intègre un facteur établi de la croissance de la végétation à des techniques d'apprentissage automatiques pour la caractérisation des paysages.Une attention particulière est accordée au traitement de différentes questions, telles que l'automatisation, les informations manquantes (déterminées par des passages satellitaires, des effets de réflexion des nuages, des ombres ou encore la présence de neige), l'apprentissage et les données de validation limitées, les échantillonnages temporels irréguliers (différent nombre d'images disponible pour chaque période et région, données inégalement réparties dans le temps), la variabilité des données, et enfin la possibilité de travailler avec différents ensembles de données et nomenclatures. Dans ce but, une méthodologie de traitement a été mise au point, totalement automatique, où aucune sélection de date ou travail manuel de l'utilisateur est nécessaire, et permettant donc l'utilisation de nomenclatures et ensembles de données différentes. Ainsi, la méthodologie développée démontre la faisabilité de la production automatique de cartes d'occupation du sol à grande échelle, traitant le volume et la variabilité des données, les données de référence limitées et les informations manquantes, en intégrant des connaissances spécialisées et différents algorithmes de traitement de données.Ce travail est encadré par le programme de soutien à la recherche «Terre, Océan, Surfaces Continentales, Atmosphère» (TOSCA) du Centre National d'Études Spatiales, par rapport à trois projets de recherche: Production de cartes d'occupation des sols à échelle régionale a partir de données SPOT HRV multitemporelles par Jordi Inglada, et Traitement et utilisation de séries temporelles d'images LANDSAT pour préparer le traitement et les applications de Venμs et Sentinel-2 et Centre D'ALgorithmie et de VAlidation des Données Venμs et Sentinel-2 (CALVADOVS) par Olivier Hagolle. Il dépend de l'école doctorale Sciences de l'Univers, de l'Environnement et de l'Espace (SDU2E) de l'Université Paul Sabatier et il a été développé au laboratoire Centre d'Études Spatiales de la BIOsphère (CESBIO) de Toulouse, France.

High resolution and low uncertainty deforestation maps covering large spatial areas in tropical countries are needed to plan efficient forest conservation and management programs such as REDD + (Reducing Emissions from Deforestation and Forest Degradation). Using an open-source free software (R, GRASS and QGis) and an original statistical approach combining multi-date land cover observations based on Landsat satellite images and the random forests classifier, we obtained up-to-date deforestation maps for the periods 2000–2005 and 2005–2010 with a minimum mapping unit of 0.36 ha for 7.7 M hectares, i.e. 40.3% of the tropical humid forest and 20.6% of the tropical dry forest in Madagascar. Uncertainty in deforestation on the maps was calculated by comparing the results of the classification to more than 30,000 visual interpretation points on a regular grid. We assessed accuracy on a per-pixel basis (confusion matrix) and by measuring the relative surface difference between wall-to-wall approach and point sampling. At the pixel level, user accuracy was 84.7% for stable land cover and 60.7% for land cover change. On average for the whole study area, we obtained a relative difference of 2% for stable land cover categories and 21.1% land cover change categories respectively between the wall-to-wall and the point sampling approach. Depending on the study area, our conservative assessment of annual deforestation rates ranged from 0.93 to 2.33%·yr− 1 for the humid forest and from 0.46 to 1.17%·yr− 1 for the dry forest. Here we describe an approach to obtain deforestation maps with reliable uncertainty estimates that can be transposed to other regions in the tropical world.

International audience; Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (epsilon(msh)) was 2.63 to 4.59 times that of sunlit leaves (epsilon(msu)). Generally, the relationships of epsilon(msh) and epsilon(msu) with epsilon(max) were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

Summary Protected areas such as nature reserves have been found to be effective in preventing habitat destruction and protecting ecosystems within their borders. Recent studies however found extensive loss of tropical forest habitat around protected areas, vastly contributing to increase the levels of ecological isolation. Using high-resolution satellite data we investigated the isolation trend occurring in the W-Arly-Pendjari (WAP) ecological complex in West Africa. A land-cover change analysis was performed for the period 1984–2002: savanna vegetation extension and loss were derived within the complex and in a 30 km peripheral buffer. Sample regions in the buffer were also analysed using selected spatial indicators to quantify temporal trends in habitat fragmentation. Implications for change in relative capacity to conserve biodiversity were discussed through the calculation of the species richness capacity (SRC). More than 14.5% of savanna habitat was lost in the WAP peripheral areas, while 0.3% was converted inside the complex. The degree of fragmentation of remnant savanna habitat has also drastically increased. Despite the effectiveness of the park conservation programme, we found through the SRC approach that the WAP complex is decreasing its potential capacity to conserve species richness. This process is mainly due to the rapid and extended agricultural expansion taking place around the complex. A better understanding of the ecological dynamics occurring in the peripheral regions of reserves and the consideration of development needs are key variables to achieve conservation goals in protected areas.

Master

International audience; Landscape dynamics result from forestry and farming practices, both of which are expected to have diverse impacts on ecosystem services (ES). In this study, we investigated this general statement for regulating and supporting services via an assessment of ecosystem functions: climate regulation via carbon sequestration in soil and plant biomass, water cycle and soil erosion regulation via water infiltration in soil, and support for primary production via soil chemical quality and water storage. We tested the hypothesis that patterns of land-cover composition and structure significantly alter ES metrics at two different scales. We surveyed 54 farms in two Amazonian regions of Brazil and Colombia and assessed land-cover composition and structure from remote sensing data (farm scale) from 1990 to 2007. Simple and well-established methods were used to characterize soil and vegetation from five points in each farm (plot scale). Most ES metrics were significantly correlated with land-use (plot scale) and land-cover (farm scale) classifications; however, spatial variability in inherent soil properties, alone or in interaction with land-use or land-cover changes, contributed greatly to variability in ES metrics. Carbon stock in above-ground plant biomass and water infiltration rate decreased from forest to pasture land covers, whereas soil chemical quality and plant-available water storage capacity increased. Land-cover classifications based on structure metrics explained significantly less ES metric variation than those based on composition metrics. Land-cover composition dynamics explained 45 % (P < 0.001) of ES metric variance, 15 % by itself and 30 % in interaction with inherent soil properties. This study describes how ES evolve with landscape changes, specifying the contribution of spatial variability in the physical environment and highlighting trade-offs and synergies among ES.

Background Buruli ulcer (BU) is an extensively damaging skin infection caused by Mycobacterium ulcerans, whose transmission mode is still unknown. The focal distribution of BU and the absence of interpersonal transmission suggest a major role of environmental factors, which remain unidentified. This study provides the first description of the spatio-temporal variations of BU in an endemic African region, in Akonolinga, Cameroon. We quantify landscape-associated risk of BU, and reveal local patterns of endemicity. Methodology/Principal Findings From January 2002 to May 2012, 787 new BU cases were recorded in 154 villages of the district of Akonolinga. Incidence per village ranged from 0 (n = 59 villages) to 10.4 cases/1000 person.years (py); median incidence was 0.4 cases/1,000py. Villages neighbouring the Nyong River flood plain near Akonolinga town were identified as the highest risk zone using the SPODT algorithm. We found a decreasing risk with increasing distance to the Nyong and identified 4 time phases with changes in spatial distribution. We classified the villages into 8 groups according to landscape characteristics using principal component analysis and hierarchical clustering. We estimated the incidence ratio (IR) associated with each landscape using a generalised linear model. BU risk was highest in landscapes with abundant wetlands, especially cultivated ones (IR = 15.7, 95% confidence interval [95%CI] = 15.7[4.2–59.2]), and lowest in reference landscape where primary and secondary forest cover was abundant. In intermediate-risk landscapes, risk decreased with agriculture pressure (from IR[95%CI] = 7.9[2.2–28.8] to 2.0[0.6–6.6]). We identified landscapes where endemicity was stable and landscapes where incidence increased with time. Conclusion/Significance Our study on the largest series of BU cases recorded in a single endemic region illustrates the local evolution of BU and identifies the Nyong River as the major driver of BU incidence. Local differences along the river are explained by wetland abundance and human modification of the environment., Author Summary Buruli ulcer (BU) remains a mysterious disease without efficient prevention since the mode of transmission of its agent, Mycobacterium ulcerans, is still unknown. The disease is highly localised within countries and even at the village scale within endemic regions, but environmental factors explaining this focal distribution have not been described yet. In this article, we rely on a large series of cases originating from Akonolinga region, Centre region, Cameroon, and recorded at the BU treatment center of the hospital of Akonolinga. The series of 787 patients over 10 years allows us to describe the distribution of BU incidence in the region and its changes over time and space. We identify the Nyong River as a major risk factor, and identify environmental factors along the river that further increase the risk of BU, such as the high proportion of swamps, the degradation of forests and cultivation of lands by human populations. These results will help to locate where the transmission is most likely to happen, and provide useful elements for targeting case search, prevention actions and future research on M. ulcerans transmission.

Background An understanding of the factors driving the distribution of pathogens is useful in preventing disease. Often we achieve this understanding at a local microhabitat scale; however the larger scale processes are often neglected. This can result in misleading inferences about the distribution of the pathogen, inhibiting our ability to manage the disease. One such disease is Buruli ulcer, an emerging neglected tropical disease afflicting many thousands in Africa, caused by the environmental pathogen Mycobacterium ulcerans. Herein, we aim to describe the larger scale landscape process describing the distribution of M. ulcerans. Methodology Following extensive sampling of the community of aquatic macroinvertebrates in Cameroon, we select the 5 dominant insect Orders, and conduct an ecological niche model to describe how the distribution of M. ulcerans positive insects changes according to land cover and topography. We then explore the generalizability of the results by testing them against an independent dataset collected in a second endemic region, French Guiana. Principal Findings We find that the distribution of the bacterium in Cameroon is accurately described by the land cover and topography of the watershed, that there are notable seasonal differences in distribution, and that the Cameroon model does not predict the distribution of M. ulcerans in French Guiana. Conclusions/Significance Future studies of M. ulcerans would benefit from consideration of local structure of the local stream network in future sampling, and further work is needed on the reasons for notable differences in the distribution of this species from one region to another. This work represents a first step in the identification of large-scale environmental drivers of this species, for the purposes of disease risk mapping., Author Summary Many pathogens persist in the environment, and an understanding of where they are can assist in disease control, allowing us to identify areas of risk to local human populations. Herein, we use general linear models to describe the distribution of a particular environmental pathogen, Mycobacterium ulcerans, describing the landscape conditions correlated with the presence of this pathogen in local biota, and mapping the distribution of these habitats in a region of Cameroon, Africa. Our findings identify the importance of the watershed as a factor determining the distribution of the bacterium, where landscape conditions upstream of the sample site can influence the abundance of the bacterium in downstream sites. We find that the bacterium has notable seasonal changes in its distribution, between the wet and dry seasons, which may have implications for human health. We also discuss sensitivity of these models to extrapolation, finding that they work well in the African region and underperforming when extrapolated to another region in South America.