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L'expertise universitaire, l'exigence journalistique
No full textInternational audienceChercheur en écologie forestière tropicale et changement climatique, Cirad À l'occasion de la parution dans la revue PNAS de notre article scientifique sur les origines des mutations héritables chez deux espèces d'arbres tropicaux de la forêt guyanaise, plongeons dans le processus fascinant de la mutation. Les mutations sont des modifications accidentelles de l'ADN. Bien qu'accidentelles, les mutations génétiques sont essentielles. En ce sens, la mutation peut même être considérée comme le terreau de l'évolution. Toutes ces modifications contribuent à accroître la diversité génétique des espèces. Les mutations chez les animauxLes arbres accumulent des mutations somatiques au cours de leur croissance. Pour les étudier chez des arbres tropicaux, des grimpeurs, dont Valentine Alt ici sur la photo, ont échantillonné différents échantillons au sein de deux arbres (ici l'angélique). Sylvain Schmitt, Fourni par l'auteur</div
Organisations complexes et conservation de la biodiversité : une approche systémique basée sur des études de cas d'entreprises multinationales et de l'agglomération parisienne
No full textInvolving multinational enterprises (MNEs) and world cities in biodiversity conservation is crucial. These organizations are complex, and how to integrate further biodiversity issues in their operations remains unclear. This thesis investigates four means of action to advance their consideration on the subject: regulation, supply practices, internal decision-making processes, and demand. The first study applies a transaction cost economics perspective to analyze the European Corporate Sustainability Reporting Directive's impact on biodiversity disclosure. It describes how the directive should result in increased information availability but low-quality information, poorly reflecting the firms' actual impacts on ecosystems. The second study describes how co-evolutionary dynamics support organizational adaptations to social, cultural, ecological, historical and economic specificities of its sourcing territories, ultimately facilitating social and ecological benefits. The third study investigates MNCs' decision-making processes based on a sample of 16 French MNEs. It reveals multi-level obstacles hindering effective biodiversity management while suggesting strategies to overcome them. The fourth study investigates demand-driven organizational transformation using Discrete Choice Experiments. It demonstrates the potential of integrating demand characteristics into greening policies to enhance social and ecological benefits.Il est essentiel d'impliquer les entreprises multinationales (MNE) et les villes mondiales dans la conservation de la biodiversité. Ces organisations sont complexes et la manière dont les questions liées à la biodiversité peuvent être intégrées dans leurs activités reste floue. Cette thèse étudie quatre leviers d'action pour faire avancer le sujet : la réglementation, les pratiques d'approvisionnement, le processus de prise de décisions et la demande. La première étude mobilise la théorie économique des coûts de transaction pour analyser l'impact de la directive européenne dite CSRD (Corporate Sustainability Reporting Directive) et montre comment la directive devrait se traduire par une plus grande disponibilité de données sur les MNE et la biodiversité, mais aussi par une information de faible qualité, reflétant mal l'impact réel des entreprises sur les écosystèmes. La deuxième étude décrit comment des dynamiques coévolutives favorise l'adaptation des organisations aux spécificités sociales, culturelles, écologiques, historiques et économiques des territoires d'approvisionnement des MNE, ce qui se facilite la création de bénéfices sociaux et écologiques. La troisième étude examine les processus décisionnels des multinationales à partir d'un échantillon de 16 multinationales françaises. Elle révèle des obstacles à plusieurs niveaux qui entravent une gestion efficace de la biodiversité, tout en suggérant des stratégies pour les surmonter. La quatrième étude examine la transformation organisationnelle induite par la demande à l'aide d'expériences de choix discret. Elle démontre que la prise en compte d'une demande hétérogène dans les politiques de renaturalisation peuvent accroître les avantages sociaux et écologiques généré
Networking the desert plant microbiome, bacterial and fungal symbionts structure and assortativity in co-occurrence networks
No full textInternational audienceIn nature, microbes do not thrive in seclusion but are involved in complex interactions within-and between-microbial kingdoms. Among these, symbiotic associations with mycorrhizal fungi and nitrogen-fixing bacteria are namely known to improve plant health, while providing resources to benefit other microbial members. Yet, it is not clear how these microbial symbionts interact with each other or how they impact the microbiota network architecture. We used an extensive co-occurrence network analysis, including rhizosphere and roots samples from six plant species in a natural desert in AlUla region (Kingdom of Saudi Arabia) and described how these symbionts were structured within the plant microbiota network. We found that the plant species was a significant driver of its microbiota composition and also of the specificity of its interactions in networks at the microbial taxa level. Despite this specificity, a motif was conserved across all networks, i.e., mycorrhizal fungi highly covaried with other mycorrhizal fungi, especially in plant roots-this pattern is known as assortativity. This structural property might reflect their ecological niche preference or their ability to opportunistically colonize roots of plant species considered non symbiotic e.g., H. salicornicum, an Amaranthaceae. Furthermore, these results are consistent with previous findings regarding the architecture of the gut microbiome network, where a high level of assortativity at the level of bacterial and fungal orders was also identified, suggesting the existence of general rules of microbiome assembly. Otherwise, the bacterial symbionts Rhizobiales and Frankiales covaried with other bacterial and fungal members, and were highly structural to the intraand inter-kingdom networks. Our extensive co-occurrence network analysis of plant microbiota and study of symbiont assortativity, provided further evidence on the importance of bacterial and fungal symbionts in structuring the global plant microbiota network
Sterile Insect Technique in a Patch System: Influence of Migration Rates on Optimal Single-Patch Releases Strategies
No full textThe Sterile Insect Technique (SIT) is a biological control method used to reduce or eliminate pest populations or disease vectors. This technique involves releasing sterilized insects that, upon mating with the wild population, produce no offspring, leading to a decline or eventual eradication of the target species. We incorporate a spatial dimension by modeling the pest/vector population as being distributed across multiple patches, with both wild and released sterile insects migrating between these patches at predetermined rates.This study has two primary objectives: first, within an n-patch model, sufficient conditions are derived for achieving the elimination of the wild population through SIT, whether releases occur in a subset of patches or across all patches. Second, we focus on the two-patch scenario, showing that optimal SIT control within one patch can successfully reduce the wild population in that patch to a desired level within a finite time frame, provided that the migration rates between patches are sufficiently low. Numerical simulations are employed to illustrate these results and further analyze the outcomes
Fuel supply, woodland management and fruit tree resources in northern Catalonia (Perpignan) during the 15th-16th centuries: an archaeobotanical approach
No full textInternational audienceDuring the late Middle Ages, northern Catalonia (Pyrénées-Orientales, France) experienced a great economic and demographic growth, which led to greater pressure on the wooded landscape. In the county of Roussillon, creating new farmland was a key issue during the 12th-14th centuries, as rural areas became increasingly involved in the production of resources for Mediterranean trade, particularly with other Catalan counties (Cerdanya, Barcelona). For example in Roussillon, medieval textual archives describe how land clearance and the exploitation of inland wetlands allowed the extension of grazing areas and farmland. During this time, the city of Perpignan was developing rapidly: it became during the 13th century the capital of the Kingdom of Majorca, consolidating its position as the political, legal and economic centre of Roussillon over the following centuries. The city's expansion led to a growing demand for resources, necessitating the management of woodland for the production of fuel, timber and the cultivation of fruit trees. Little is known about this management during the 15th-16th century, or about the impact it may have had on the surrounding landscape. For this presentation, anthracological data from two late medieval/early modern settlements in Perpignan (15th-16th centuries) were processed in order to determine the composition and state of the woodlands exploited by the city. The obtained information shed new light on the exploitation of wood resources in post-medieval Catalonia, by comparing it with studies carried out on another major catalan urban site (Mercat del Born, Barcelona). Our study reveals the exploitation of a mixed sclerophyll oak woodland formation for fuel production, the town changing its supply area between the 10th and the 16th centuries, obtaining its fuel from preserved woodland areas in the hinterland rather than from the surrounding degraded plant landscapes. These results corroborate those from Mercat del Born, where the predominance of evergreen oak in the fuel is attributed to the targeted exploitation of different woodland areas, rather than that of a nearby woodland. The large proportion of charcoal fragments belonging to fruit trees (mainly olive trees, but also fig trees, pomegranates, grapevines and walnut trees) raises the question of whether they were grown locally (urban garden ?) or imported via the various existing trade networks
Exploring multidimensional and within-food group diversity for diet quality and long-term health in high-income countries
No full textInternational audienceDietary diversity is a crucial component of healthy eating patterns because it ensures nutritional adequacy. Yet, concerns have been raised about the potential risks of its increase, which may reflect excessive consumption of unhealthy foods and higher obesity or cardiometabolic risk, particularly in high-income countries. However, the links between dietary diversity and different health outcomes remain inconclusive because of methodological differences in assessing dietary diversity. Numerous studies, mostly cross-sectional, have assessed dietary diversity using different indicators usually based only on the number of foods or food groups consumed. In this perspective, we emphasize that dietary diversity is a multidimensional concept encompassing the number of foods in the diet (food coverage) but also their relative proportions (food evenness) and the nutritional dissimilarity of foods consumed over time (food complementarity). Consequently, a comprehensive assessment of dietary diversity reflecting all its dimensions, both between and within-food groups, is needed to determine the optimal level of complementarity between and within-food groups required to improve health and diet quality. Moreover, given the prevailing context of abundant highly processed and energy-dense foods in high-income countries, promoting dietary diversity should prioritize nutrient-dense food groups. Until recently, within-food group diversity has received limited attention in research and public health recommendations. Still, it may play a role in improving diet quality and long-term health. This perspective aims to clarify the concept of dietary diversity and suggest research avenues that should be explored to better understand its associations with nutritional adequacy and health among adults in high-income countries
Exploration des approches d'apprentissage profond et des séries temporelles encodées en images pour l'analyse de la cartographie d'occupation du sol
No full textIn this thesis, the potential of machine learning (ML) in enhancing the mapping of complex Land Use and Land Cover (LULC) patterns using Earth Observation data is explored. Traditionally, mapping methods relied on manual and time-consuming classification and interpretation of satellite images, which are susceptible to human error. However, the application of ML, particularly through neural networks, has automated and improved the classification process, resulting in more objective and accurate results. Additionally, the integration of Satellite Image Time Series(SITS) data adds a temporal dimension to spatial information, offering a dynamic view of the Earth's surface over time. This temporal information is crucial for accurate classification and informed decision-making in various applications. The precise and current LULC information derived from SITS data is essential for guiding sustainable development initiatives, resource management, and mitigating environmental risks. The LULC mapping process using ML involves data collection, preprocessing, feature extraction, and classification using various ML algorithms. Two main classification strategies for SITS data have been proposed: pixel-level and object-based approaches. While both approaches have shown effectiveness, they also pose challenges, such as the inability to capture contextual information in pixel-based approaches and the complexity of segmentation in object-based approaches. To address these challenges, this thesis aims to implement a method based on multi-scale information to perform LULC classification, coupling spectral and temporal information through a combined pixel-object methodology and applying a methodological approach to efficiently represent multivariate SITS data with the aim of reusing the large amount of research advances proposed in the field of computer vision.Cette thèse explore le potentiel de l'apprentissage automatique pour améliorer la cartographie de modèles complexes d'utilisation des sols et de la couverture terrestre à l'aide de données d'observation de la Terre. Traditionnellement, les méthodes de cartographie reposent sur la classification et l'interprétation manuelles des images satellites, qui sont sujettes à l'erreur humaine. Cependant, l'application de l'apprentissage automatique, en particulier par le biais des réseaux neuronaux, a automatisé et amélioré le processus de classification, ce qui a permis d'obtenir des résultats plus objectifs et plus précis. En outre, l'intégration de données de séries temporelles d'images satellitaires (STIS) ajoute une dimension temporelle aux informations spatiales, offrant une vue dynamique de la surface de la Terre au fil du temps. Ces informations temporelles sont essentielles pour une classification précise et une prise de décision éclairée dans diverses applications. Les informations d'utilisation des sols et de la couverture terrestre précises et actuelles dérivées des données STIS sont essentielles pour guider les initiatives de développement durable, la gestion des ressources et l'atténuation des risques environnementaux. Le processus de cartographie de d'utilisation des sols et de la couverture terrestre à l'aide du l'apprentissage automatique implique la collecte de données, le prétraitement, l'extraction de caractéristiques et la classification à l'aide de divers algorithmes l'apprentissage automatique . Deux stratégies principales de classification des données STIS ont été proposées : l'approche au niveau du pixel et l'approche basée sur l'objet. Bien que ces deux approches se soient révélées efficaces, elles posent également des problèmes, tels que l'incapacité à capturer les informations contextuelles dans les approches basées sur les pixels et la complexité de la segmentation dans les approches basées sur les objets. Pour relever ces défis, cette thèse vise à mettre en uvre une métho basée sur des informations multi-échelles pour effectuer la classification de l'utilisation des terres et de la couverture terrestre, en couplant les informations spectrales et temporelles par le biais d'une méthodologie combinée pixel-objet et en appliquant une approche méthodologique pour représenter efficacement les données multi-variées SITS dans le but de réutiliser la grande quantité d'avancées de la recherche proposées dans le domaine de la vision par ordinateur
Life-history traits of Dacus frontalis Becker (Diptera: Tephritidae) reared at four constant temperatures
No full textInternational audienc
Building eco-resilience of oil palm with omics tools towards a fertilization sustainable plantation system
No full textInternational audienceIntroductionSince 2000, oil palm cultivation has generated considerable controversy, as the >20 million ha of plantations linked with deforestation, burning, a high carbon footprint, biodiversity loss and environmental pollution from the with palm oil industry. The effects of palm oil on human health have also been critiqued, with palm oil used in various fast foods and iconic products like donuts and Nutella. Despite these concerns, the high continuous fruit production (of >35 t FFB/ha) and high oil yield (>28% of extraction rate) of oil palm make it a cheap and high-quality resource for increasing global demand for edible oil. Thus, the oil palm chain, from planters to industry, has sought to improve the environmental impacts of oil palm and engaged the R&D sector to minimize negative impacts of oil palm production. Under pressure of environmental lobbyists, such as WWF, there have been environmental improvements due to the establishment of international obligations for planters to obtain eco-certification (like RSPO Round Table for Palm Oil) and the preference of buyers to purchase “green oil” with certified origin. At the same time, the development of genomics and transcriptomics technologies for oil palm since 2013 has allowed researchers to select varieties with a high yield potential (along with markers for other desirable traits such as drought tolerance, pathogen resistance, and oil composition) and then restrict new planting extension by reducing some local yield gaps. Recently, oil palm agronomists have focused on reducing greenhouse gas emissions from plantations by modifying fertilizer use (decreasing the quantity, choice of some fertilizer type) especially the addition of potassium (KCl: until 300 kg/ha/year) that is commonly used to increase fruit production. Recent metabolomics and proteomics studies have highlighted the potential of using oil palm metabolism data to improve fertilizer efficiency management. A better definition of the nutritional status of individual trees is required to optimize the mineral diagnosis system, which is used to manage fertilizer applications in plantation, and “-omics” tools, in addition with mineral data represent a great potential solution. The iPALMS (Identifying Practicable functionAL biomarkers to Monitor nutritional requirements in oil palm agroSystems, 4)) has been elaborate to test the omics solution for fertilizer management.Materials and MethodsTwo set of data (one coming from important mineral analyses (1) under KCl gradient) and other (metabolomics (3) coming from same plantation were matched and submitted to multivariate analyses in order to identify best mixed bio-indicators (the excercice have been done for K on K0/K3 trials) and for a futur building K-bio-Index able to integrate K and metabolic palm status precisely.ResultsSome evidence shown that high K level might be well correlated to K rachis and K rachis mass and dopamine-leaf as well as sucrose-leaf levels when less evidently low K seems related to phosphate-leaf , N-rachis level and Mg-leaf (see figure).DiscussionThe main point will be to discuss if these kind of bio-mixed indicators might be applicable in the field to manage LD (Leaf Diagnosis) method used in the « French system » to apply fertilizer related to oil palm trees requirements (see Figure)FigureReferences(1) Lamade and Tcherkez, 2023 Revisiting foliar diagnosis for oil palm potassium nutrition. European Journal of Agronomy. 143:126694, 14 p.(2) Mirande-Ney et al. 2019 C. Mirande-Ney, G. Tcherkez, F. Gilard, J. Ghashghaie, E. Lamade . Effects of potassium fertilization on oil palm fruit metabolism and mesocarp lipid accumulation. Journal of Agricultural and Food Chemistry (2019) 67 pp 9432-9440.(3) Mirande-Ney C., Tcherkez G., Balliau, T., Zivy M. Gilard F., Cui J. Ghashghaie J., Lamade E. 2020. Metabolic leaf responses to potassium availability in oil palm (Elaeis guineensis Jacq.) trees grown in field. Environmental and Experimental Botany, 175 :10 p.(4) iPALMS project (2022-2025): Identifying Practicable functionAL biomarkers toMonitor nutritional requirements in oil palm agroSystems, awarded by EuropeanMarie Curie funds (beneficiary : E. Lamade)This work has been totally founded by CIRAD UPR 80 (UMR ABSys)