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Generic crop rotation pattern-matching algorithm revealed dominant rotational systems for France
No full textInternational audienceCrop rotations remain poorly documented at large spatial scale, despite their central role in agroecosystem sustainability. We present a generic pattern-matching algorithm to infer crop rotations from annual crop sequence datasets, such as those derived from the European Land Parcel Identification System, with minimal crop aggregation. This method identifies field-level rotations, quantifies their flexibility, and enables spatially-explicit assessment of dominant crop and grasslands rotational systems at various spatial and thematic levels. Applied to mainland France, the approach identified crop rotations on 90% of arable area, with four-year rotations -typically including two to three years of flexible crops-being the most common. Nationally, the top 20 rotations accounted for 30% of arable land, while the top 52 covered 50%. At the agricultural district scale, we distinguished 25 dominant rotational systems grouped into eight categories, including (i) maize grain monocropping, (ii) maize grain -winter wheat rotations, (iii) sunflower -winter wheat rotations, (iv) grass-based systems, (v) maize silage -winter wheat rotations, (vi) winter wheat -barley -rapeseed rotations, (vii) root crop-based rotations, and (viii) specialized production. At national scale, organic rotations were longer and more flexible than conventional ones. Rotations of larger farms were longer and temporally more diverse than smaller ones, but showed lower spatial diversity. This scalable, data-driven approach offers new insights into crop rotation patterns and their spatial variability. It can support the large-scale assessment of agroecosystems with quantitative evidences on dominant rotations, but also help at tracking and characterizing localized rotational innovations
The evolution of drought characteristics in semi-arid Africa over the last four decades
No full textInternational audiencetudy regionSemi-arid Africa, covering six subregions: the Mediterranean (MED), Sahel, North Eastern Africa (NEAF), South Eastern Africa (SEAF), Southern Africa (SAF), and Madagascar (MDG).Study focusWe analyse drought duration, intensity, and severity from 1979 to 2024 across semi-arid Africa. Using Climate Prediction Center (CPC, 0.5°) precipitation and temperature, we compute the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Trends are detected with the Mann–Kendall test and Theil–Sen slope estimator. Short-term droughts (3–6 months), strongly influenced by temperature variability, are distinguished from 12-month events driven by cumulative hydrological deficits.New hydrological insightsThree drought episodes emerge: the early 1990s, early 2000s, and the recent period beginning in 2022. Long time-scale indices (SPI-12, SPEI-12) capture the most persistent droughts, whereas short time-scale indices (SPEI-3, SPEI-6) reveal intense temperature-driven episodes. In MED, only 7–25 % of grid cells show significant SPI trends in duration, severity, and intensity, but up to 75 % exhibit drought intensification with SPEI, underscoring strong temperature sensitivity. Across NEAF, SEAF, SAF, and MDG, 25–55 % of pixels show significant increases in drought duration (up to +3 months per decade), severity (+3 units per decade), and intensity (+0.5 units per decade). Parts of the western Sahel and southern Madagascar display decreasing trends. Overall, the study delivers a continent-wide assessment of drought evolution and identifies hotspots where intensifying drought threatens water resources and food security
Stepwise recombination suppression around the mating-type locus associated with a diploid-like life cycle in Schizothecium fungi
No full textInternational audienceRecombination suppression often evolves around sex-determining loci and extends stepwise, resulting in adjacent regions with different levels of divergence between sex chromosomes, called evolutionary strata. In Ascomycota fungi, evolutionary strata around the mating-type (MAT) locus have been reported only in pseudo-homothallic species, which have a diploid-like life cycle with mycelia carrying nuclei of both mating types. In contrast, no recombination suppression has been observed in heterothallic fungi, where colonies contain only a single mating type. Here, we investigated the evolution of recombination suppression in a clade of dung fungi encompassing 16 pseudo-homothallic and three heterothallic sibling species from the Schizothecium genus (Ascomycota, Sordariales). The analysis of genetic divergence based on genome sequencing indicated recombination suppression around the MAT locus in all 13 pseudo-homothallic species examined. The nonrecombining region ranged from 600 kb to 1.6 Mb and harbored multiple evolutionary strata, varying in size and number among species. The clustering of alleles according to mating type in gene genealogies, the high linkage disequilibrium, and an inversion in one species supported the lack of recombination in the MAT-proximal region in pseudo-homothallic species. The overall lack of trans-specific polymorphism suggested multiple independent recombination suppression events or occasional recombination/genic conversion. In heterothallic species, progeny analyses showed that recombination occurs in regions at physical distances from the MAT locus similar to those in which it is lacking in the pseudo-homothallic species. We thus revealed here multiple, likely independent evolutionary strata, associated with an extended diploid-like stage in Schizothecium fungi
Method: Modelling resource acquisition and allocation – extension and calibration of a cow model to a sheep
No full textInternational audienceSimulation models are suitable to investigate how complex systems respond to changes. This is of particular interest regarding animal feed efficiency as this trait must be evaluated throughout the entire lifetime and thus is affected by trade-offs between physiological functions. The aim was to extend and calibrate the dynamic, mechanistic simulation model “Acquisition and Allocation” (AQAL) from dairy cows to reproductive ewes. This model was originally developed for investigating the effects of resource acquisition and allocation potentials on feed efficiency but also allows investigation of trade-offs between life functions. The model represents an individual female from birth to death or herd exit and uses four input parameters to describe the resource acquisition ability and allocation potential. The obtained energy is split between life functions such as maintenance, growth, reproduction and lactation. By including reproductive management rules, it allows for shifts between physiological stages, which then feedback and affect the current acquisition ability and resource allocation. To adapt the model to a reproductive ewe, we have included a litter size effect, an acquisition capacity linked to gestation, and a seasonal conception probability. The litter size is influenced by the proportion of fat in empty body weight at conception, and it affects the acquisition linked to gestation, the allocation to gestation and the allocation to lactation. We also incorporated the energetic costs of the gravid uterus depending on litter size. We use three different acquisition-allocation profiles to test the consistency of the litter size effect. We show that the model simulates consistent lifetime trajectories of reproductive ewes and that the effect of litter size adequately reflects the demands of increased litter size within the different acquisition/allocation profiles
The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity
No full textInternational audienceAccurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants
Bulletin de veille du réseau d'écotoxicologie terrestre et aquatique N°84
No full textINRAE, réseau ECOTOX → A paraîtreBulletin de veill
On the problem of minimizing the epidemic final size for SIR model by social distancing
No full textInternational audienceWe revisit the problem of minimizing the epidemic final size in the SIR model through social distancing of bounded intensity. In the existing literature, this problem has been considered imposing a priori interval structure on the time period when interventions are enforced. We show that when considering the more general class of controls with an L1 constraint on the confinement effort that reduces the infection rate, the support of the optimal control is still a single time interval. This shows that, for this problem, there is no benefit in splitting interventions on several disjoint time periods. However, if the infection rate is known beforehand to change with time once from one value to another one, then we show that the optimal solution could consist in splitting the interventions in at most two disjoint time periods
Datasets of 16S rRNA gene amplicon sequences, metabolites, and soluble immune components in bronchoalveolar lavage samples from severe asthmatic and age-matched control children
No full textInternational audienceSevere asthma (SA) is a heterogeneous condition characterized by multiple phenotypes, each characterized by different endotypes. Understanding the mechanisms occurring in the lungs of children with SA can help in understanding pathogenesis and in providing the most effective therapeutic strategies. This article describes microbiota, metabolites, and soluble immune components assessed in bronchoalveolar lavage (BAL) fluids from children with severe asthma (n = 20) and age-matched disease controls (n = 10). The article includes: (i) the protocol used to process BAL samples for 16S rRNA gene amplicon sequencing, metabolomic profiling and immune components assays; (ii) the bioinformatics steps applied to 16S rRNA and metabolomics dataset; (iii) an overview of the raw 16S rRNA gene amplicon sequencing data, presented as ASV and affiliation tables, raw data from untargeted metabolomics and the abundances of each of the eighty eight metabolites annotated with the highest confidence level, and concentrations of seventy three cytokines and of total IgG, IgA and IgE. Each dataset is available in the INRAE data repository (https://entrepot.recherche.data.gouv.fr/dataverse/inrae) with respective DOI: MICROBIOTA: 10.57745/LL3TFW, METABOLITES: 10.57745/1L8VRI, IMMUNE COMPONENTS: 10.57745/JOOGRQThese datasets provide valuable resources for further investigating the molecular mechanisms underlying severe asthma in children and its trajectories. They also offer the potential to identify a local signature of severe asthma through complementary multi-omics analyses and to discover local biomarkers associated with asthma endotypes. Datasets can also be reused to compare with other cohorts (children or adults) or to serve as reference datasets for other pulmonary diseases
Déploiement et Maillage de stations instrumentées en IoT sur le territoire pour diverses études_AG AnaEE 2026 "ECOLOGGING"
No full textInternational audienceIn this poster, we present the deployments of the different types of instrumented stations developed within the framework of the "ECOLOGGING” project, carried out during the year 2024/2025, as well as the main developments, the results obtained, and the conclusions. The “ECOLOGGING” stations are deployed according to the nature of the studies conducted and the associated specific scientific needs.Dans ce poster, nous présentons les déploiements des différents types de stations instrumentées développées dans le cadre du projet "ECOLOGGING", réalisés au cours de l’année 2024/2025, ainsi que les principales évolutions, les résultats obtenus et les conclusions. Les stations ECOLOGGING sont déployées en fonction de la nature des études menées et des besoins scientifiques spécifiques associés