Dynamique de la végétation des savanes en lien avec l’usage des feux à Madagascar. Analyse par série temporelle d’images de télédétection

Bien que le feu soit reconnu comme un facteur d’influence dans la dynamique de végétation des savanes, son rôle n’est pas clairement défini. Cette thèse aborde le problème de l’étude de la relation entre l’usage des feux et la dynamique de végétation. L’approche choisie repose sur l’analyse de séries temporelles d’images de télédétection à moyenne résolution spatiale. Les savanes étudiées sont situées sur le bassin versant de Marovoay au nord-ouest de Madagascar. Dans la mesure où il n’existe pas de consensus quant aux méthodes à utiliser, les savanes de Madagascar offrent un contexte particulier, en raison de la dégradation très prononcée du couvert végétal et des changements recherchés, pour tester les méthodes existantes et en proposer des nouvelles. Le premier objectif de ce travail est d’identifier le régime des feux à travers le suivi des variations spatio-temporelles des surfaces brûlées en milieu de savane. Pour cela, une méthode de cartographie des surfaces brûlées a été développée : elle est basée sur le calcul d’un indicateur annuel indiquant le passage d’un feu pendant la saison sèche et d’un indicateur saisonnier traduisant la période de passage du feu. Cette méthode, appliquée au site d’étude, a permis de produire une série temporelle de données utilisées pour caractériser le régime des feux à partir de deux paramètres, la période d’occurrence et la fréquence de passage du feu. En parallèle, le deuxième objectif consiste à caractériser la dynamique de végétation par l’analyse des variations spatio-temporelles de l’activité végétale. Deux approches de détection des changements, basées sur le traitement de série temporelle de NDVI, ont été testées. La première repose sur l’analyse des variations inter annuelles d’un indicateur phénologique traduisant l’activité végétale pendant la phase de croissance des savanes. La deuxième utilise une technique de décomposition temporelle pour extraire la tendance d’une série de NDVI. Dans les deux cas, les résultats ont permis de caractériser la dynamique de végétation à travers trois classes d’évolution de l’activité végétale (séries progressive, régressive ou stable). Ces résultats ont été évalués par comparaison avec ceux issus de techniques de détection des changements basées sur l’analyse diachronique d’images à haute résolution spatiale. Enfin, dans la dernière étape du travail, nous avons étudié les relations entre les informations relatives aux régimes des feux et à la dynamique de végétation en utilisant des modèles de régression multivariée. L’objectif est d’estimer l’importance et le rôle du feu dans la dynamique de végétation. Les résultats ont amené à trois conclusions : a) Le feu est un facteur de maintien des savanes ; b) Dans les situations où la pression liée aux activités anthropiques est faible, le feu, en particulier par la fréquence de son usage, est un facteur déterminant de la dynamique de végétation ; c) Dans les autres situations, l’interprétation des résultats est complexe et difficile, très certainement en raison de l’interaction de multiples facteurs anthropiques. ABSTRACT : Fire is recognized to be an essential factor that explains savanna vegetation dynamics. But its role is not clearly defined. This work investigates the problem of studying the relation between fire usage and vegetation dynamic. This is addressed through the analysis of time series of medium spatial resolution remotely sensed images. We studied the savanna localized on the Marovoay watershed, on the northwest part of Madagascar. As no consensus exists on the adapted methods, the savanna of Madagascar offers a particular context to test existing methods or develop new ones, because of the advanced vegetation cover degradation and the nature of change to be detected. The first objective of this work is to identify fire regime by analyzing the spatio-temporal variations of burned areas in savanna areas. To this end, a burned area mapping method was developed. It is based on the definition of an annual indicator, which indicates the occurrence of a fire during the dry season, and a seasonal indicator, which gives the information on the date of the fire event. Applied to the study site, this method has lead to the production of a time series of data used for the characterization of the fire regime through two parameters, the period of occurrence and the frequency of fire. In parallel, the second objective consists on characterizing vegetation dynamic by monitoring spatiotemporal variations of vegetation activity. Two change detection approaches based on NDVI time series, were tested. The first consists on analyzing the inter annual variations of a phenological indicator related to vegetation activity during the active growth season. The second uses a temporal decomposition technique to extract the trend from an NDVI time series. In both cases, the vegetation dynamic is characterized through three classes linked to the evolution of the vegetation activity (progressive, regressive or stable series). Results were evaluated by a comparison with the results obtained from a diachronic change detection technique based of high spatial resolution images. Finally, in the last part of this work, we investigated the relation between fire regimes and vegetation activity change classes using multivariate regression models. The objective is to analyze to determine the importance and the role of fire into the vegetation dynamic. Results leaded to three conclusions: a) Fire is a factor that maintains savanna; b) In areas where pressure due to anthropogenic activities is low, fire frequency represents a determinant factor to explain vegetation dynamic; c) In others areas, the interpretation of results appears to be complex and difficult, probably because of the high level of interactions between multiple environmental factors

Validation of a forage production index (FPI) derived from MODIS fcover time-series using high-resolution satellite imagery: methodology, results and opportunities

An index-based insurance solution was developed to estimate and monitor near real-time forage production using the indicator Forage Production Index (FPI) as a surrogate of the grassland production. The FPI corresponds to the integral of the fraction of green vegetation cover derived from moderate spatial resolution time series images and was calculated at the 6 km x 6 km scale. An upscaled approach based on direct validation was used that compared FPI with field-collected biomass data and high spatial resolution (HR) time series images. The experimental site was located in the Lot and Aveyron departments of southwestern France. Data collected included biomass ground measurements from grassland plots at 28 farms for the years 2012, 2013 and 2014 and HR images covering the Lot department in 2013 (n = 26) and 2014 (n = 22). Direct comparison with ground-measured yield led to good accuracy (R-2 = 0.71 and RMSE = 14.5%). With indirect comparison, the relationship was still strong (R-2 ranging from 0.78 to 0.93) and informative. These results highlight the effect of disaggregation, the grassland sampling rate, and irregularity of image acquisition in the HR time series. In advance of Sentinel-2, this study provides valuable information on the strengths and weaknesses of a potential index-based insurance product from HR time series images

A statistical approach for predicting grassland degradation in disturbance-driven landscapes

Maintaining a land base that supports safe and realistic training operations is a significant challenge for military land managers which can be informed by frequent monitoring of land condition in relation to management practices. This study explores the relationship between fire and trends in tallgrass prairie vegetation at military and non -military sites in the Kansas Flint Hills. The response variable was the longterm linear trend (2001-2010) of surface greenness measured by MODIS NDVI using BFAST time series trend analysis. Explanatory variables included fire regime (frequency and seasonality) and spatial strata based on existing management unit boundaries. Several non-spatial generalized linear models (GLM) were computed to explain trends by fire regime and/or stratification. Spatialized versions of the GLMs were also constructed. For non-spatial models at the military site, fire regime explained little (4%) of the observed surface greenness trend compared to strata alone (7% - 26%). The non-spatial and spatial models for the non -military site performed better for each explanatory variable and combination tested with fire regime. Existing stratifications contained much of the spatial structure in model residuals. Fire had only a marginal effect on surface greenness trends at the military site despite the use of burning as a grassland management tool. Interestingly, fire explained more of the trend at the nonmilitary site and models including strata improved explanatory power. Analysis of spatial model predictors based on management unit stratification suggested ways to reduce the number of strata while achieving similar performance and may benefit managers of other public areas lacking sound data regarding land usage

Identité sociale de femmes cadres en recherche d’emploi : action et projet

Cette recherche exploratoire étudie la dynamique identitaire de cadres féminins en recherche d’emploi, selon le modèle de l’égo-écologie de Zavalloni (2007) qui définit l’identité sociale dans une transaction entre le sujet-société. Nous avons choisi la méthode IMIS (Investigateur multistade de l’identité sociale) afin de mettre en évidence les mécanismes identitaires de femmes cadres en recherche d’emploi. Cette recherche exploratoire a également observé un lien entre la recherche active d’emploi et le projet de vie. En effet, l’action influencerait positivement le sentiment de capacité et faciliterait le déploiement d’un projet. D’autre part, l’IMIS nous est apparu un outil opératoire quant à l’émergence et l’appréhension du projet.Based on Zavalloni’s ego-ecology model (2007), which defines social identity as a trade-off between the individual and society, this exploratory research investigates the identity dynamics of executive job applicant women. The MISI (Multistage Investigator of Social Identity) was chosen to help identify the various psychological processes through which these women go when looking for a job. In this exploratory research a link has also been observed between active job application and one’s life project. Indeed, action would influence self-efficacy and would, therefore, facilitate the development of a given project. From a methodological standpoint, the MISI was found to be a tool that is well suited to capture the emergence and the approach of the project

Military training and fire regime impacts on tallgrass prairie vegetation degradation

The relationship between fire and long-term trends in tallgrass prairie vegetation was assessed at Fort Riley and Konza Prairie Biological Station (KPBS) in Kansas. Linear trends of surface greenness were previously estimated using BFAST and MODIS MOD13Q1 NDVI composite images from 2001 to 2010. To explain trends, fire frequency and seasonality (fire regime) was determined and each site was divided into spatial strata using administrative or management units. Generalized linear models (GLM) were used to explain trends by fire regime and/or stratification. Spatialized versions of GLMs were also computed address unexplained spatial components. Non-spatial models for FRK showed fire regime explained only 4% of trends compared to strata (7-26%). At KPBS, fire regime and spatial stratification explained 14% and 39%, respectively. At both sites, improvements in performance were minimal using both fire and strata as explanatory variables. Model spatialization resulted in a 5% improvement at FRK, but with weak spatial structure in the residuals, and was not necessary at KPBS as the existing stratification most of the spatial structure in model residuals. All models at KPBS performed better for each explanatory variable and combination tested. Fire has only a marginal effect on vegetation trends at FRK despite its widespread use as a grassland management tool to improve vegetation health, and explains much more of the trends at KPBS. Analysis of predictors from spatial models with existing stratification yielded an approach with fewer strata but similar performance and may provide insight about additional explanatory variables omitted from this analysis

Eumelanin-based colouration reflects local survival of juvenile feral pigeons in an urban pigeon house

International audienceUrbanisation introduces deep changes in habitats, eventually creating new urban ecosystems where ecological functions are driven by human activities. The higher frequency of some phenotypes in urban vs rural/wild areas has led to the assumption that directional selection in urban habitats occurs, which may thereby favour some behavioural and physiological traits in urban animal populations compared to rural ones. However, empirical evidence of directional selection on phenotypic traits in urban areas remains scarce. In this study we tested whether eumelanin-based colouration could be linked to survival in two urban populations of the feral pigeon Columba livia. A number of studies in different cities pointed out a higher frequency of darker individuals in more urbanised areas compared to rural ones. To investigate whether directional selection through survival on this highly heritable trait could explain such patterns, we conducted mark-recapture studies on two populations of feral pigeons in highly urbanized areas. We predicted that darker coloured individuals would exhibit higher survival and/or philopatry (integrated into 'local survival') than paler coloured ones. No difference in local survival was found between adults of different colouration intensities. However, on one site, we found that darker juveniles had a higher local survival probability than light ones. Juvenile local survival on that site was also negatively correlated with the number of chicks born. This suggests the existence of colour- and/or density-dependent selection processes acting on juvenile feral pigeons in urban environments, acting through differential mortality and/or dispersal

Detection of "Flavescence dorée" Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery

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

On the potentiality of UAV multispectral imagery to detect flavescence dorée and grapevine trunk diseases

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)

Evaluation of Multiorbital SAR and Multisensor Optical Data for Empirical Estimation of Rapeseed Biophysical Parameters

This article aims to evaluate the potential of multitemporal and multiorbital remote sensing data acquired both in the microwave and optical domain to derive rapeseed biophysical parameters (crop height, dry mass, fresh mass, and plant water content). Dense temporal series of 98 Landsat-8 and Sentinel-2 images were used to derive normalized difference vegetation index (NDVI), green fraction cover (fCover), and green area index (GAI), while backscattering coefficients and radar vegetation index (RVI) were obtained from 231 mages acquired by synthetic aperture radar (SAR) onboard Sentinel-1 platform. Temporal signatures of these remote sensing indicators (RSI) were physically interpreted, compared with each other to ground measurements of biophysical parameters acquired over 14 winter rapeseed fields throughout the 2017–2018 crop season. We introduced new indicators based on the cumulative sum of each RSI that showed a significant improvement in their predictive power. Results particularly reveal the complementarity of SAR and optical data for rapeseed crop monitoring throughout its phenological cycle. They highlight the potential of the newly introduced indicator based on the VH polarized backscatter coefficient to estimate height (R2 = 0.87), plant water content (R2 = 0.77, from flowering to harvest), and fresh mass (R2 = 0.73) and RVI to estimate dry mass (R2 = 0.82). Results also demonstrate that multiorbital SAR data can be merged without significantly degrading the performance of SAR-based relationships while strongly increasing the temporal sampling of the monitoring. These results are promising in view of assimilating optical and SAR data into crop models for finer rapeseed monitoring

Establishment and analysis of a reference transcriptome for Spodoptera frugiperda

International audienceBackground Spodoptera frugiperda (Noctuidae) is a major agricultural pest throughout the American continent. The highly polyphagous larvae are frequently devastating crops of importance such as corn, sorghum, cotton and grass. In addition, the Sf9 cell line, widely used in biochemistry for in vitro protein production, is derived from S. frugiperda tissues. Many research groups are using S. frugiperda as a model organism to investigate questions such as plant adaptation, pest behavior or resistance to pesticides.ResultsIn this study, we constructed a reference transcriptome assembly (Sf_TR2012b) of RNA sequences obtained from more than 35 S. frugiperda developmental time-points and tissue samples. We assessed the quality of this reference transcriptome by annotating a ubiquitous gene family - ribosomal proteins - as well as gene families that have a more constrained spatio-temporal expression and are involved in development, immunity and olfaction. We also provide a time-course of expression that we used to characterize the transcriptional regulation of the gene families studied.ConclusionWe conclude that the Sf_TR2012b transcriptome is a valid reference transcriptome. While its reliability decreases for the detection and annotation of genes under strong transcriptional constraint we still recover a fair percentage of tissue-specific transcripts. That allowed us to explore the spatial and temporal expression of genes and to observe that some olfactory receptors are expressed in antennae and palps but also in other non related tissues such as fat bodies. Similarly, we observed an interesting interplay of gene families involved in immunity between fat bodies and antennae