Portail HAL Institut Agro Montpellier
Not a member yet
54878 research outputs found
Sort by
Beyond pesticide reduction: Exploring synergies between contrasted territorial scenarios
No full textInternational audiencePesticide use creates significant environmental, health and socioeconomic challenges and its reduction is hindered by sociotechnical lock-ins. The territorial level, combined with systemic approaches, is promising toovercome these systemic challenges. This research proposes an original methodological approach which, instead of aiming at creating consensus, explores contrasted pesticide reduction scenarios with local stakeholders based on existing initiatives in order to identify pathways for collective action. The study was conducted in the Western Plain of Montpellier, in Southern France, and involved a diversity of stakeholders from the territory and outside of the territory in 5 steps, using the Co-Click’Eau tool and workshops. The scenarios explored the potential of diversification for food production, biodiversity conservation and crop-livestock integration to meet pesticide reduction challenges. In addition to an important pesticide use reduction, each scenario proposed significant land-use and farming practices transformations. The analysis revealed that the approach was able to create spaces for dialogue through the formulation of synergies between these strategies by participants, especially on land-use management, technical levers, linking production to consumers and highlighted complementary contributions of biodiversity and livestock to the territory. Beyond its agronomic dimensions, the process opens the pathway to better coordination with the identification of synergies and tensions between different visions, helping to identify coherent strategies including agricultural production, biodiversity, and food objectives. By doing so, our approach contributes to embedding pesticide reduction into a broader, systemic reconfiguration of agroecosystems and territorial governance
Modelling genetic and epigenetic selection signatures from pool sequencing.
No full textInternational audienc
A step-by-step tutorial to local partial least squares analyses for near-infrared spectroscopic data analysis
No full textInternational audiencePartial least squares (PLS) methods are key algorithms in chemometrics, particularly in near-infrared spectroscopy. Their ability to handle multicollinearity and high-dimensional data makes them an effective tool for regression and discrimination tasks. Nevertheless, PLS performance can be limited when dealing with highly complex datasets. To address this, local PLS analyses were introduced. Instead of calibrating a model on the entire dataset and ignoring local variations, local PLS selects a subset of nearest neighbours for each new sample to predict and calibrate a PLS model on this subset. This ensures that each sample is predicted using a model trained on a more relevant local context. Such an approach is easy to implement and especially valuable with the growing availability of large spectroscopic datasets. Despite its advantages, local PLS remains underutilized, perhaps due to a lack of accessible resources. This tutorial aims to bridge that gap by providing a step-by-step framework for implementing local PLS, combining theoretical insights with hands-on applications. Readers will gain practical knowledge through detailed explanations, examples, and best practices for avoiding common mistakes. Ready-to-use scripts written in R and Julia languages are provided to facilitate adoption and integration into research workflows
LOS Ground Displacement Monitoring in Northeast Tunisia Using SBAS InSAR
No full textInternational audienceThe Lebna watershed in northeast Tunisia is marked by its important agricultural activities and its hydro-geological settings, enhancing its susceptibility to various geohazards including land subsidence and uplift. This study monitors the Line of Sight (LOS) deformation through the Interferometric Synthetic Aperture Radar (InSAR) technique. The main observations are LOS velocity maps derived from the Small Baseline Subset - InSAR, which were calculated from ESA Sentinel-1 satellites for the period 2015–2023. The SAR data resulted in velocities ranging between −1.05 and +0.80 cm/year. Both subsidence and uplifting trends were observed in different areas, indicating that the ground deformations in the study region could be dependent on geological and hydrogeological factors
Decision analysis rooted in Indigenous and Western scientific knowledge identifies cost‐effective strategies for managing hyperabundant deer to restore keystone places
No full textInternational audienceThe hyperabundance of herbivores—a result of altered human relationality with the land and the extirpation of predators—is leading to large‐scale degradation of keystone ecosystems across the globe. Designing and implementing socially acceptable and cost‐effective strategies that meaningfully reduce herbivore populations while allowing for the recovery of ecological function and cultural relationality is an inherently complex issue. As a result, decision paralysis is common, leading to delayed or avoided action and continued ecosystem loss and degradation. Using a structured decision‐making process that incorporated expert elicitation, population modelling and cost‐effectiveness analyses while honouring multiple knowledge systems, we identified five discrete and four portfolio strategies for managing hyperabundant black‐tailed deer ( Odocoileus hemionus columbianus ) in the Southern Gulf Islands of British Columbia, Canada, with consideration to benefit, feasibility and cost objectives. Hunting led by local Indigenous Nations was ranked the most cost‐effective strategy when benefits considered well‐being of peoples and place holistically, and accounted for both Indigenous and Western science worldviews. When only Western perspectives were included, increased licensed hunting by local communities and hiring professional deer reduction specialists were ranked the most cost‐effective. However, while increased licensed hunting had a >50% likelihood of project uptake and success (i.e. feasibility), the strategy had <50% likelihood of achieving any benefit objective. In comparison, Indigenous‐led hunting, professional deer reduction specialists, and all portfolio strategies had >50% likelihood of meeting at least one benefit objective, although only Indigenous‐led hunting also had >50% likelihood of achieving feasibility objectives. Synthesis and applications . We provide a roadmap for decision‐makers across the globe to robustly and transparently assess the problem of herbivore hyperabundance and inform solutions within their context. Within the Salish Sea, our work highlights the need to support hunting, and in particular, Indigenous‐led hunting, as cost‐effective strategies to promote revitalization of well‐being of peoples and place. Read the free Plain Language Summary for this article on the Journal blog
Spatial externalities in renewable resource management: Experimental evidence on fragmented property rights
No full textWe study how spatial connectivity and fragmented ownership affect the management of mobile common-pool resources. We develop a dynamic two-patch model of a mobile renewable resource: it predicts that (i) management efficiency in a given patch declines when the neighboring patch is managed by multiple agents rather than a single owner, and (ii) greater resource mobility amplifies inefficiencies at the global scale, especially under mixed ownership. We test these predictions in a preregistered laboratory experiment with 294 participants by varying mobility rates and ownership structures. Consistent with theory, shared management in one patch reduces efficiency at the local scale (in the adjacent patch) through spillover effects, and higher resource mobility further erodes efficiency at the global scale. Using group extraction trajectories, we identify three robust behavioral patterns: early over-extractors, mid-period preemptive groups, and late preservers. Mixed ownership and higher mobility shift the distribution toward early over-extraction and away from late conservation. Beyond these institutional and ecological effects, cognitive ability is strongly associated with more forward-looking extraction paths and higher payoffs
Nonparametric Kernel Clustering with Bandit Feedback
No full textClustering with bandit feedback refers to the problem of partitioning a set of items, where the clustering algorithm can sequentially query the items to receive noisy observations. The problem is formally posed as the task of partitioning the arms of an N-armed stochastic bandit according to their underlying distributions, grouping two arms together if and only if they share the same distribution, using samples collected sequentially and adaptively. This setting has gained attention in recent years due to its applicability in recommendation systems and crowdsourcing. Existing works on clustering with bandit feedback rely on a strong assumption that the underlying distributions are sub-Gaussian. As a consequence, the existing methods mainly cover settings with linearly-separable clusters, which has little practical relevance. We introduce a framework of ``nonparametric clustering with bandit feedback'', where the underlying arm distributions are not constrained to any parametric, and hence, it is applicable for active clustering of real-world datasets. We adopt a kernel-based approach, which allows us to reformulate the nonparametric problem as the task of clustering the arms according to their kernel mean embeddings in a reproducing kernel Hilbert space (RKHS). Building on this formulation, we introduce the KABC algorithm with theoretical correctness guarantees and analyze its sampling budget. We introduce a notion of signal-to-noise ratio for this problem that depends on the maximum mean discrepancy (MMD) between the arm distributions and on their variance in the RKHS. Our algorithm is adaptive to this unknown quantity: it does not require it as an input yet achieves instance-dependent guarantees
A Comprehensive Database of Leaf Temperature, Water, and CO 2 Fluxes in Young Oil Palm Plants Across Diverse Climate Scenarios
No full textData and code availability: The raw data and scripts used to generate the final database are detailed and accessible on Zenodo (Vezy et al., 2025), the code is also accessible via a Github repository (https://github.com/PalmStudio/Biophysics_database_palm), and we also provide a companion website (https://palmstudio.github.io/Biophysics_database_palm) showing how computations were made and the main results. The code to trigger the FLIR camera and for logging the precision scale data is also available on dedicated Zenodo repositories (Vezy, 2025a, 2025b).Functional-structural plant models (FSPM) replicate plants' responses to their environment and are useful for predicting behavior in a changing climate. However, they rely on detailed measurements of traits, which are difficult to collect consistently across scales, often limiting model parameterization and thorough evaluation, and thereby reducing confidence in model predictions.Here, we provided a comprehensive dataset of structural and biophysical measurements from four oil palm plants (Elaeis guinnensis) grown under multiple controlled environmental scenarios, including varying CO2 concentrations, light, temperature and humidity conditions. The dataset included detailed reconstructions of the three-dimensional plant structures derived from terrestrial LiDAR point clouds, and enabled the parametrization of biophysical processes at the leaf scale such as photosynthesis and stomatal conductance, as well as the collection of plant-scale measurements (gas exchange measurements of CO2 and H20), which can be compared with FSPM simulations. The tree-dimensional reconstructions effectively represented the architecture of the plants and showed strong correlation with the measured total leaf area. Hence, future comparisons between simulated and observed physiological traits could be used to evaluate the quality of the physiological formalisms independently. By bridging the scales from individual leaves to the entire plant, this database allows modellers to both calibrate their biophysical models at a fine spatial resolution and evaluate their predictive accuracy at the plant scale. The provided data will facilitate benchmarking of biophysical models, help identify sources of model uncertainty, and ultimately enhance model predictions, which can be applied in various fields, from cognitive studies to decision support applications
Growth and phosphorus uptake of micropropagated southern highbush blueberry plants inoculated with ericoid endophytic and mycorrhizal fungi in varied growth substrates
No full textInternational audiencePhosphorus (P) acquisition and use by southern highbush blueberry Vaccinium corymbosum L. plants is critical during early stages of development and impair root development, especially for growth substrates with poor nutrient contents. However, inoculation of blueberry plants with ericoid mycorrhizal fungi (ErMF) or dark septate endophytes (DSE) can improve P during the plants acclimation stages and reduce plant mortality, especially in dry northern Mediterranean climate conditions. Herein, we grew southern highbush blueberry micro-cuttings in conditions without inoculation (control) or in inoculated with four strains: two Ericoid mycorrhizal sp. (D01), and (C01), E. endophyte (C31), and Phialocephala fortinii Wang & Wilcox in sandy (S), fresh field (FF), and FF+S soil mix substrates for 10 months before harvest. At harvest, root colonization levels, plant height, leaf area, the fresh matter of roots and shoots, root-to-shoot ratio, P content, and P utilization efficiency (PUE) were measured. We found that the root colonization levels were inhibited in the S for the different inoculated F treatments, owing to the elevated carbonate and salt concentrations present. The average P uptake responses from the different F inoculated strains were 52.2 %, 29.6 %, and 22.4 % in the S, FF, and FF+S substrates. Inoculation of blueberry plants with C31 strain exhibited the highest (59.1 %) P uptake average response, inoculation with P. fortinii strain showed the lowest (15.8 %) response. The root growth responses were inhibited in the FF+S (-0.2 %), increased in the S (8.4 %), and FF (6.2 %) substrates. Our findings therefore describe responses under controlled nursery conditions with single-strain inoculation and three substrate types. Because blueberry roots in the field are commonly co-colonized by multiple ericoid and endophytic fungi, interactions among partners may amplify or dampen the effects observed here; future work should test coinoculation consortia and validate performance under field conditions.</div
Comparative genomic analysis of QTL for resistance to Aphanomyces euteiches between pea, lentil, faba bean, and the model species Medicago truncatula
No full textInternational audienceKey message: QTL mapping and GWAS detected resistance QTL to Aphanomyces euteiches in faba bean, lentil, and Medicago truncatula. Weak genomic conservation between resistance QTL was identified between these legumes and pea.Abstract: QTL mapping and GWAS detected resistance QTL to Aphanomyces euteiches in faba bean, lentil, and Medicago truncatula. Weak genomic conservation between resistance QTL was identified between these legumes and pea. Aphanomyces root rot, caused by Aphanomyces euteiches, is a damaging disease affecting various legume species. Quantitative trait loci (QTL) for partial resistance have been mainly identified in pea, and to a lesser extent in lentil and Medicago truncatula. This study aimed to identify novel resistance loci from available lentil and faba bean populations, and examine genomic conservation of resistance QTL across legume host species. QTL mapping in the Pop2 faba bean recombinant inbred line (RIL) population and genome-wide association study (GWAS) in the AGILE lentil diversity panel were performed for resistance to A. euteiches under controlled conditions, using genotyping data previously reported. A previous QTL mapping in the LR3 M. truncatula RIL population was updated using 1,536 new SNPs (single-nucleotide polymorphisms). Synteny between resistance QTL to A. euteiches was analyzed based on gene orthology in QTL regions projected onto genomes, using the OrthoLegKB graph database. Four loci, including a major-effect QTL on chromosome 3, Ae-Vf3.1, were associated with resistance in faba bean. In lentil, six minor-effect GWAS-SNPs and two favorable haplotypes at Ae-Lc1.1 and Ae-Lc2.1 loci were identified. Updated analyses in M. truncatula narrowed to 8 Kb the interval of the major-effect locus AER1 and revealed three candidate genes. No synteny between major-effect QTL, detected in this study or previously reported in the literature, was identified across grain legume genomes. These results pave the way for translational genomics approaches facilitating resistance gene discovery and for resistance QTL deployment strategies in legume rotations to preserve their durability