Centre Occitanie-Toulouse

Flavescence dorée is a grapevine disease affecting European vineyards which has severe economic consequences and containing its spread is therefore considered as a major challenge for viticulture. Flavescence dorée is subject to mandatory pest control including removal of the infected vines and, in this context, automatic detection of Flavescence dorée symptomatic vines by unmanned aerial vehicle (UAV) remote sensing could constitute a key diagnosis instrument for growers. The objective of this paper is to evaluate the feasibility of discriminating the Flavescence dorée symptoms in red and white cultivars from healthy vine vegetation using UAV multispectral imagery. Exhaustive ground truth data and UAV multispectral imagery (visible and near-infrared domain) have been acquired in September 2015 over four selected vineyards in Southwest France. Spectral signatures of healthy and symptomatic plants were studied with a set of 20 variables computed from the UAV images (spectral bands, vegetation indices and biophysical parameters) using univariate and multivariate classification approaches. Best results were achieved with red cultivars (both using univariate and multivariate approaches). For white cultivars, results were not satisfactory either for the univariate or the multivariate. Nevertheless, external accuracy assessment show that despite problems of Flavescence dorée and healthy pixel misclassification, an operational Flavescence dorée mapping technique using UAV-based imagery can still be proposed.

Barnaud, C., E. Corbera, R. Muradian, N. Salliou, C. Sirami, A. Vialatte, J.-P. Choisis, N. Dendoncker, R. Mathevet, C. Moreau, V. Reyes-García, M. Boada, M. Deconchat, C. Cibien, S. Garnier, R. Maneja, and M. Antona. 2018. Ecosystem services, social interdependencies, and collective action: a conceptual framework. Ecology and Society 23(1):15. https://doi.org/10.5751/ES-09848-230115

Barnaud, C., and A. Van Paassen. 2013. Equity, power games, and legitimacy: dilemmas of participatory natural resource management. Ecology and Society 18(2): 21. https://doi.org/10.5751/ES-05459-180221

Among grapevine diseases affecting European vineyards, Flavescence dorée (FD) and Grapevine Trunk Diseases (GTD) are considered the most relevant challenges for viticulture because of the damage they cause to vineyards. Unmanned Aerial Vehicle (UAV) multispectral imagery could be a powerful tool for the automatic detection of symptomatic vines. However, one major difficulty is to discriminate different kinds of diseases leading to similar leaves discoloration as it is the case with FD and GTD for red vine cultivars. The objective of this paper is to evaluate the potentiality of UAV multispectral imagery to separate: symptomatic vines including FD and GTD (Esca and black dead arm) from asymptomatic vines (Case 1) and FD vines from GTD ones (Case 2). The study sites are localized in the Gaillac and Minervois wine production regions (south of France). A set of seven vineyards covering five different red cultivars was studied. Field work was carried out between August and September 2016. In total, 218 asymptomatic vines, 502 FD vines and 199 GTD vines were located with a centimetric precision GPS. UAV multispectral images were acquired with a MicaSense RedEdge® sensor and were processed to ultimately obtain surface reflectance mosaics at 0.10 m ground spatial resolution. In this study, the potentiality of 24 variables (5 spectral bands, 15 vegetation indices and 4 biophysical parameters) are tested. The vegetation indices are selected for their potentiality to detect abnormal vegetation behavior in relation to stress or diseases. Among the biophysical parameters selected, three are directly linked to the leaf pigments content (chlorophyll, carotenoid and anthocyanin). The first step consisted in evaluating the performance of the 24 variables to separate symptomatic vine vegetation (FD or/and GTD) from asymptomatic vine vegetation using the performance indicators from the Receiver Operator Characteristic (ROC) Curve method (i.e., Area Under Curve or AUC, sensibility and specificity). The second step consisted in mapping the symptomatic vines (FD and/or GTD) at the scale of the field using the optimal threshold resulting from the ROC curve. Ultimately, the error between the level of infection predicted by the selected variables (proportion of symptomatic pixels by vine) and observed in the field (proportion of symptomatic leaves by vine) is calculated. The same methodology is applied to the three levels of analysis: by vineyard, by cultivar (Gamay, Fer Servadou) and by berry color (all red cultivars). At the vineyard and cultivar levels, the best variables selected varies. The AUC of the best vegetation indices and biophysical parameters varies from 0.84 to 0.95 for Case 1 and 0.74 to 0.90 for Case 2. At the berry color level, no variable is efficient in discriminating FD vines from GTD ones (Case 2). For Case 1, the best vegetation indices and biophysical parameter are Red Green Index (RGI)/ Green-Red Vegetation Index (GRVI) (based on the green and red spectral bands) and Car (linked to carotenoid content). These variables are more effective in mapping vines with a level of infection greater than 50%. However, at the scale of the field, we observe misclassified pixels linked to the presence of mixed pixels (shade, bare soil, inter-row vegetation and vine vegetation) and other factors of abnormal coloration (e.g., apoplectic vines).

Trade-offs are manifestations of the complex dynamics in interdependent social-ecological systems. Addressing tradeoffs involves challenges of perception due to the dynamics of interdependence. We outline the challenges associated with addressing trade-offs and analyze knowledge coproduction as a practice that may contribute to tackling trade-offs in social-ecological systems. We discuss this through a case study in coastal Kenya in which an iterative knowledge coproduction process was facilitated to reveal social-ecological trade-offs in the face of ecological and socioeconomic change. Representatives of communities, government, and NGOs attended two integrative workshops in which methods derived from systems thinking, dialogue, participatory modeling, and scenarios were applied to encourage participants to engage and evaluate trade-offs. Based on process observation and interviews with participants and scientists, our analysis suggests that this process lead to increased appreciation of interdependences and the way in which trade-offs emerge from complex dynamics of interdependent factors. The process seemed to provoke a reflection of knowledge assumptions and narratives, and management goals for the social-ecological system. We also discuss how stakeholders link these insights to their practices.

Regards méthodologiques sur l’échantillonnage des coléoptères saproxyliques au moyen des pièges-vitres. — Les coléoptères saproxyliques constituent un groupe riche en espèces, souvent petites et cryptiques, et difficiles à échantillonner. Différentes méthodes sont traditionnellement utilisées pour les collecter : les techniques (i) de collecte active, (ii) d’élevage et (iii) de piégeage. Le piège-vitre est actuellement la méthode la plus fréquemment utilisée pour la capture des coléoptères saproxyliques aériens mobiles. Grâce à la combinaison de différents principes, les pièges-vitres comportent de multiples modèles. Cette étude concerne l’influence de 3 facteurs sur les captures de coléoptères saproxyliques, en comparant (i) des pièges plans bidirectionnels ou multidirectionnels en croix (effet de forme), (ii) des pièges transparents ou noirs (effet silhouette), (iii) des pièges suspendus à faible hauteur ou dans la canopée. Six jeux de données écologiques de plaine ou d’altitude, de forêts françaises feuillues ou résineuses, et comportant deux pièges différents appariés par placette, ont été compilés et analysés pour comparer l’efficacité respective des méthodes. La forme du piège a un fort effet significatif sur l’abondance et la richesse spécifique, à l’avantage des pièges plans. Néanmoins, en raison de contraintes pratiques ou fi nancières, les pièges-croix sont recommandés. Les pièges noirs ou transparents fournissent des échantillons comparables en termes d’abondance, de richesse et de composition. Nos résultats confirment la différenciation verticale des assemblages de coléoptères saproxyliques, les pièges bas capturant davantage d’individus et d’espèces que les pièges de la canopée. A l’exception des Melyridae, aucune espèce n’est associée aux strates hautes. Des analyses complémentaires fondées sur de plus amples jeux de données sont requises pour optimiser les méthodes d’échantillonnage.

Temporal variation in the composition of species assemblages could be the result of deterministic processes driven by environmental change and/or stochastic processes of colonization and local extinction. Here, we analyzed the relative roles of deterministic and stochastic processes on bird assemblages in an agricultural landscape of southwestern France. We first assessed the impact of land cover change that occurred between 1982 and 2007 on (i) the species composition (presence/absence) of bird assemblages and (ii) the spatial pattern of taxonomic beta diversity. We also compared the observed temporal change of bird assemblages with a null model accounting for the effect of stochastic dynamics on temporal beta diversity. Temporal assemblage dissimilarity was partitioned into two separate components, accounting for the replacement of species (i.e. turnover) and for the nested species losses (or gains) from one time to the other (i.e. nestedness-resultant dissimilarity), respectively. Neither the turnover nor the nestedness-resultant components of temporal variation were accurately explained by any of the measured variables accounting for land cover change (r(2)<0.06 in all cases). Additionally, the amount of spatial assemblage heterogeneity in the region did not significantly change between 1982 and 2007, and site-specific observed temporal dissimilarities were larger than null expectations in only 1% of sites for temporal turnover and 13% of sites for nestedness-resultant dissimilarity. Taken together, our results suggest that land cover change in this agricultural landscape had little impact on temporal beta diversity of bird assemblages. Although other unmeasured deterministic process could be driving the observed patterns, it is also possible that the observed changes in presence/absence species composition of local bird assemblages might be the consequence of stochastic processes in which species populations appeared and disappeared from specific localities in a random-like way. Our results might be case-specific, but if stochastic dynamics are generally dominant, the ability of correlative and mechanistic models to predict land cover change effects on species composition would be compromised.

Vuillot, C., N. Coron, F. Calatayud, C. Sirami, R. Mathevet, and A. Gibon. 2016. Ways of farming and ways of thinking: do farmers’ mental models of the landscape relate to their land management practices?. Ecology and Society 21(1):35.http://dx.doi.org/10.5751/ES-08281-210135

Dendoncker, N., F. Boeraeve, E. Crouzat, M. Dufrêne, A. König, and C. Barnaud. 2018. How can integrated valuation of ecosystem services help understanding and steering agroecological transitions?. Ecology and Society 23(1):12. https://doi.org/10.5751/ES-09843-230112

BACKGROUND: The castor bean tick (Ixodes ricinus) transmits infectious diseases such as Lyme borreliosis, which constitutes an important ecosystem disservice. Despite many local studies, a comprehensive understanding of the key drivers of tick abundance at the continental scale is still lacking. We analyze a large set of environmental factors as potential drivers of I. ricinus abundance. Our multi-scale study was carried out in deciduous forest fragments dispersed within two contrasting rural landscapes of eight regions, along a macroclimatic gradient stretching from southern France to central Sweden and Estonia. We surveyed the abundance of I. ricinus, plant community composition, forest structure and soil properties and compiled data on landscape structure, macroclimate and habitat properties. We used linear mixed models to analyze patterns and derived the relative importance of the significant drivers. RESULTS: Many drivers had, on their own, either a moderate or small explanatory value for the abundance of I. ricinus, but combined they explained a substantial part of variation. This emphasizes the complex ecology of I. ricinus and the relevance of environmental factors for tick abundance. Macroclimate only explained a small fraction of variation, while properties of macro- and microhabitat, which buffer macroclimate, had a considerable impact on tick abundance. The amount of forest and the composition of the surrounding rural landscape were additionally important drivers of tick abundance. Functional (dispersules) and structural (density of tree and shrub layers) properties of the habitat patch played an important role. Various diversity metrics had only a small relative importance. Ontogenetic tick stages showed pronounced differences in their response. The abundance of nymphs and adults is explained by the preceding stage with a positive relationship, indicating a cumulative effect of drivers. CONCLUSIONS: Our findings suggest that the ecosystem disservices of tick-borne diseases, via the abundance of ticks, strongly depends on habitat properties and thus on how humans manage ecosystems from the scale of the microhabitat to the landscape. This study stresses the need to further evaluate the interaction between climate change and ecosystem management on I. ricinus abundance.

This paper presents a new method for buildings extraction in Very High Resolution (VHR) remotely sensed images based on binary mathematical morphology (MM) operators. The proposed approach involves several advanced morphological operators among which an adaptive hit-or-miss transform with varying sizes and shapes of the structuring element and a bidimensional granulometry intended to determine the optimal filtering parameters automatically. A clustering-based approach for image binarization is also introduced. This one avoids an empirical thresholding of input panchromatic images. Experiments made on a Quickbird VHR-image show the effectiveness of the method.

Forest management consists in anthropogenic disturbances that are able to modulate ecological features, resource availability and successional patterns. Plant communities are thus expected to react differently to contrasted silvicultural systems. We compared plant species composition between stands submitted to a traditional management since many centuries (i.e. coppice-with-standards treatment, stands intensively but infrequently disturbed) and stands recently converted into a selective cutting system (stands moderately but frequently disturbed), over uniform edaphic and topographic conditions. We found significant differences in species composition between both systems. Despite a strong shift in species composition among different stages of the coppice cycle, coppice-with-standards stands supported the highest number of true forest species. Selectively-cut stands were more homogeneous and characterized by ruderal "generalist" species. These fast changes in vegetation composition were related to differences in a group of factors that are directly or indirectly linked to the silvicultureassociated disturbance regime, including soil moisture, soil fertility, forest microclimate, light and game predation. We conclude that the conversion of a silvicultural system which has patterned plant communities since many centuries, induces early major changes in vegetation composition. The most negatively impacted species are the so-called "true forest species" that may be better labelled "coppice-woodland species". disturbance / microclimate / forest management / plant diversity / true forest species Rsum -Changements de la composition floristique induits par la sylviculture dans une fort tempre caducifolie europenne. La sylviculture est une perturbation anthropogne capable de moduler les facteurs environnementaux, la disponibilit des ressources et la dynamique forestire. La vgtation spontane est donc susceptible de ragir diffremment des systmes sylviculturaux contrasts. La composition floristique de parcelles forestires traites en taillis-sous-futaie depuis plusieurs sicles a t compare celle de parcelles rcemment converties en futaie irrgulire coupe pied--pied , en conditions daphique et topographique uniformes. Malgr des diffrences importantes en fonction du temps coul depuis la dernire coupe, la partie de la fort traite en taillis-sous-futaie hbergeait un nombre plus important d'espces forestires. Les parcelles en futaie irrgulire taient plus homognes et caractrises par des espces rudrales gnralistes . Ces changements prcoces de la composition spcifique ont pu tre relis des modifications du contexte environnemental, directement ou indirectement induites par la sylviculture, incluant l'humidit et la fertilit du sol, le microclimat forestier, la lumire et la prdation par le chevreuil. La conversion d'un type sylvicultural, qui a faonn les communauts vgtales durant des sicles, induit donc rapidement des changements majeurs dans la composition floristique. Les espces les plus affectes sont les espces considres comme forestires, qu'il conviendrait plutt d'appeler espces des taillis . perturbation / microclimat / sylviculture / biodiversit vgtale / espces forestires vraies / taillis-sous-futaie

Bretagnolle, V., M. Benoit, M. Bonnefond, V. Breton, J. M. Church, S. Gaba, D. Gilbert, F. Gillet, S. Glatron, C. Guerbois, N. Lamouroux, M. Lebouvier, C. Mazé, J.-M. Mouchel, A. Ouin, O. Pays, C. Piscart, O. Ragueneau, S. Servain, T. Spiegelberger, and H. Fritz. 2019. Action-orientated research and framework: insights from the French long-term social-ecological research network. Ecology and Society 24(3):10. https://doi.org/10.5751/ES-10989-240310

A fast forward feature selection algorithm is presented in this paper. It is based on a Gaussian mixture model (GMM) classifier. GMM are used for classifying hyperspectral images. The algorithm selects iteratively spectral features that maximizes an estimation of the classification rate. The estimation is done using the k-fold cross validation (k-CV). In order to perform fast in terms of computing time, an efficient implementation is proposed. First, the GMM can be updated when the estimation of the classification rate is computed, rather than re-estimate the full model. Secondly, using marginalization of the GMM, submodels can be directly obtained from the full model learned with all the spectral features. Experimental results for two real hyperspectral data sets show that the method performs very well in terms of classification accuracy and processing time. Furthermore, the extracted model contains very few spectral channels.

A large-scale feature selection wrapper is discussed for the classification of high dimensional remote sensing. An efficient implementation is proposed based on intrinsic properties of Gaussian mixtures models and block matrix. The criterion function is split into two parts:one that is updated to test each feature and one that needs to be updated only once per feature selection. This split saved a lot of computation for each test. The algorithm is implemented in C++ and integrated into the Orfeo Toolbox. It has been compared to other classification algorithms on two high dimension remote sensing images. Results show that the approach provides good classification accuracies with low computation time.

BACKGROUND: Production conditions of layer chicken can vary in terms of temperature or diet energy content compared to the controlled environment where pure-bred selection is undertaken. The aim of this study was to better understand the long-term effects of a 15%-energy depleted diet on egg-production, energy homeostasis and metabolism via a multi-tissue transcriptomic analysis. Study was designed to compare effects of the nutritional intervention in two layer chicken lines divergently selected for residual feed intake. RESULTS: Chicken adapted to the diet in terms of production by significantly increasing their feed intake and decreasing their body weight and body fat composition, while their egg production was unchanged. No significant interaction was observed between diet and line for the production traits. The low energy diet had no effect on adipose tissue and liver transcriptomes. By contrast, the nutritional challenge affected the blood transcriptome and, more severely, the hypothalamus transcriptome which displayed 2700 differentially expressed genes. In this tissue, the low-energy diet lead to an over-expression of genes related to endocannabinoid signaling (CN1R, NAPE-PLD) and to the complement system, a part of the immune system, both known to regulate feed intake. Both mechanisms are associated to genes related polyunsaturated fatty acids synthesis (FADS1, ELOVL5 and FADS2), like the arachidonic acid, a precursor of anandamide, a key endocannabinoid, and of prostaglandins, that mediate the regulatory effects of the complement system. A possible regulatory role of NR1H3 (alias LXRα) has been associated to these transcriptional changes. The low-energy diet further affected brain plasticity-related genes involved in the cholesterol synthesis and in the synaptic activity, revealing a link between nutrition and brain plasticity. It upregulated genes related to protein synthesis, mitochondrial oxidative phosphorylation and fatty acid oxidation in the hypothalamus, suggesting reorganization in nutrient utilization and biological synthesis in this brain area. CONCLUSIONS: We observed a complex transcriptome modulation in the hypothalamus of chicken in response to low-energy diet suggesting numerous changes in synaptic plasticity, endocannabinoid regulation, neurotransmission, lipid metabolism, mitochondrial activity and protein synthesis. This global transcriptomic reprogramming could explain the adaptive behavioral response (i.e. increase of feed intake) of the animals to the low-energy content of the diet.

Le concept de «système d’élevage» a été développé pour rendre compte et modéliser des interactions entre dimensions humaines et dimensions biotechniques de l’activité d’élevage. Après avoir rappelé l’origine et les bases des approches intégrées de l’élevage, et les applications centrées sur les liens décisions-pratiques-performances de troupeau, nous montrons comment ce concept évolue pour traiter des transformations de l’élevage, tant des attentes des éleveurs (pour un travail maîtrisé) que celles de la société (pour un plus grand respect de l’environnement). La problématique du développement durable appelle un renouvellement des approches des systèmes d’élevage vers l’étude des capacités adaptatives des systèmes socio-écologiques à l’échelle de territoires.

Spectral unmixing (SU) methods incorporating the spatial regularizations have demonstrated increasing interest. Although spatial regularizers that promote smoothness of the abundance maps have been widely used, they may overly smooth these maps and, in particular, may not preserve edges present in the hyperspectral image. Existing unmixing methods usually ignore these edge structures or use edge information derived from the hyperspectral image itself. However, this information may be affected by the large amounts of noise or variations in illumination, leading to erroneous spatial information incorporated into the unmixing procedure. This paper proposes a simple yet powerful SU framework that incorporates external data [i.e. light detection and ranging (LiDAR) data]. The LiDAR measurements can be easily exploited to adjust the standard spatial regularizations applied to the unmixing process. The proposed framework is rigorously evaluated using two simulated data sets and a real hyperspectral image. It is compared with methods that rely on spatial information derived from a hyperspectral image. The results show that the proposed framework can provide better abundance estimates and, more specifically, can significantly improve the abundance estimates for the pixels affected by shadows.

Salliou, N., and C. Barnaud. 2017. Landscape and biodiversity as new resources for agro-ecology? Insights from farmers’ perspectives. Ecology and Society 22(2):16. https://doi.org/10.5751/ES-09249-220216

Que sait-on aujourd'hui des impacts, positifs et négatifs, de l’agriculture sur la biodiversité ? Quels services la biodiversité peut-elle apporter à l’agriculture, et à quelle hauteur de performance ? Comment favoriser au champ les synergies entre agriculture et biodiversité ? Quels instruments de politiques publics, économiques et juridiques, faut-il mettre en place pour promouvoir ces interactions ? Ces questions ont mobilisé un groupe pluridisciplinaire d’experts (écologues, agronomes, microbiologistes, spécialistes de santé végétale, économistes, juristes, sociologues), de différentes institutions (Inra, CNRS, IRD, Universités, Ecoles supérieures agronomiques) en France et à l’étranger