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BRC4Env, the French Biological Resource Centre for Environment
No full textInternational audienceBRC4Env is the environmental pillar of the French Research Infrastructure RARe. (https://www.agrobrc-rare.org/), led by the French National Institute for Agriculture, Food and Environment (INRAE). BRC4Env manages various biological and genomic resources for agroecological research and environmental health.Since 2018, France has been engaged in the world challenge of Global Soil to preserve soil fertility. BRC4Env network includes the European Soil Conservatory, used to monitor soil health, from microbiome to pollutants. BRC4Env aims also at monitoring biodiversity in the aquatic ecosystem, holding 460.000 ichthyological samples collected for 50 years and, the terrestrial ecosystem with one million arthropod specimens collected worldwide for over a century. BRC4Env manage also living collections of parasitoid Trichogramma and arbuscular mycorrhizal fungi used in biocontrol and as biofertilizers, respectively.The catalogue of BRC4Env resources is accessible at the portal https://urgi.versailles.inrae.fr/brc4env/ and corresponding data (genomic, phenotypic, ...) are available for academic and socio-economic researchers. BRC4Env-linked publications are accessible at https://hal.inrae.fr/BRC4ENV.BRC4Env aims to provide a strategic delivery for academic and applied research in environmental health, support the agroecological transition and unravel mechanisms at stake in the adaption of species to climate and environmental changes such as pollution, emergence of pathogens or resistance
Meta-modeling of a physically-based pesticide runoff model with a Long-Short term Memory approach
No full textInternational audienceSurface water contamination by pesticides is widespread across the European Union (European Environment Agency, 2024). A primary pathway for pesticide transfer from agricultural fields to surface waters is surface runoff (Wauchope et al., 1995 [https://doi.org/10.1162/neco.1997.9.8.1735]; Louchart et al., 2001 [https://doi.org/10.2134/jeq2001.303982x]; Reichenberger et al., 2007 [https://doi.org/10.1016/j.scitotenv.2007.04.046]). This process is influenced by various spatial and temporal factors, including compound properties, topography, application date and methods, climate, soil properties, and agricultural practices (Shipitalo and Owens, 2003 [https://doi.org/doi: 10.1021/es020870b]). Richards-based models are valuable for predicting the temporal variability of pesticide runoff (Métayer et al., 2024 [https://doi.org/10.1016/j.scitotenv.2023.167357]), especially in regions with high rainfall intensity variability, such as the Mediterranean. However, their operational application is constrained by substantial computational demands and extensive data requirements. Meta-modeling approaches provide a means to reduce the computational time of an initial physically-based model. Among these, the Long Short-Term Memory (LSTM; Hochreiter and Schmidhuber, 1997 [https://doi.org/10.1162/neco.1997.9.8.1735]) model has demonstrated high efficiency in replicating hydrological (Kratzert et al., 2018 [https://doi.org/10.5194/hess-22-6005-2018]) and hydrochemical time series (Pyo et al., 2023 [https://doi.org/10.1016/j.wroa.2023.100207]), making them a promising meta-modeling strategy for pesticide runoff models. This study aimed to develop and evaluate a meta-modeling approach using LSTM models for a Richards-based model to simulate hourly variations in water and pesticide runoff over an entire year while minimizing computation times. The proposed approach was applied to a field-scale pesticide runoff model implemented in the fully spatially distributed hydrological model MHYDAS-Pesticide 1.0 (Crevoisier et al., 2021 [https://hal.inrae.fr/hal-04090048v1]) that integrates Richards and convection-dispersion equations, the uniform mixing cell concept, and an overland flow routine. This represents a challenge for at least the following three reasons: i) the time series contains mainly zero values of runoff discharge, ii) the prediction of pesticide runoff requires an efficient prediction of water runoff and ii) the order of magnitude of the targeted non-zero values of runoff concentration varies by several orders of magnitude. The LSTM meta-model was trained and validated using 560,560 annual time series simulations generated by the initial physically-based model. The training dataset comprised 70% of the simulations, with the remaining 30% reserved for validation. The resulting meta-model accounted for meteorological conditions, compound properties, and pesticide application date and rate. It demonstrated high accuracy in simulating hourly runoff and pesticide concentrations, achieving significant reductions in computation time. However, challenges remain, such as improving the precision of runoff occurrence simulation and enhancing the meta-model's generalizability by incorporating additional static parameters as inputs. The poster will focus on the methodology for the meta-model’s development and the results of its evaluation. The meta-model has been implemented within a fully spatially distributed physically-based hydrological model, MHYDAS Pesticide, to form an hybrid version
LEON-BLOOM project - Origin, spatial and temporal dynamics of cyanobacteria blooms in lake Léon, France
No full textInternational audienceLake Léon (Landes) has recently experienced important cyanobacteria blooms, leading to severe restrictions on recreational activities of this popular tourist waterbody of the Atlantic coast in France. To investigate the origins of these algal blooms, the dynamics of biological patterns, and to provide management strategies for mitigation, the "Léon-Bloom" research project established a collaboration between environmental watershed managers and research scientists. The project aims to identify the potential sources of algal growth and gain a better understanding of their spatial and temporal dynamics. The project is structured in several workpackages, each investigating a potential mechanism. (1) Firstly, nutrient fluxes from the watershed are analyzed, including the use of passive phosphorus samplers. We also set up an experimental design to investigate the role temperature, light and phosphorus on the development of phytoplankton biomass. (2) Secondly, a chemical analysis of the lake’s sediments is carried out resorting to sediment coring and experimentation to measure the potential of phosphorus release under anoxic conditions. (3) Thirdly, the role of temperature and oxygen on phytoplankton composition will be assessed using a statistical modeling approach. We measured temperature and oxygen in several stations of the lake to calibrate these models using autonomous high-frequency sensors. (4) The phytoplankton community is studied both spatially and temporally, at the taxonomic and algal group level. Cyanotoxins are also regularly monitored. Finally, two modeling-based workpackages will focus on (5) analyzing the role of wind in the spatial distribution of the plankton community and physical parameters and (6) developing remote sensing methods for monitoring algal concentrations in this lake. Ultimately, we aim to decipher the relative contribution of wind, nutrients (fluxes and internal release), and environmental variables, to understand the conditions of cyanobacterial blooms emergence
Evaluating camera trap methods for monitoring population trends in ungulates: insights from simulation
No full textInternational audienceAbstract Camera traps have been widely used in the last decade to monitor abundance of unmarked animal populations. Most estimation methods rely either on the number of times animals pass through the detection zones, like random encounter models (REM) or on the number of capture occasions in a time-lapse program when animals were seen on the pictures, like the instantaneous sampling approach (IS). We simulated a setup of either 100 or 25 camera traps randomly distributed on a 2600-ha area (respectively ≈ 4 and 1 trap/km 2 ), along with the movements of a fictional population of 300 roe deer ( Capreolus capreolus ). We assessed the ability of these two classes of popular methods to estimate population size and detect a 20% decline over five years. Simulations were informed by field data on habitat, habitat selection and activity patterns of GPS-monitored roe deer. Both IS and REM estimated population size without bias, with a coefficient of variation only equal to about 15% (4 traps/km 2 ) or 30% (1trap/km 2 ). Despite a huge sampling effort and simplified assumptions (perfectly known day range, constant sensor sensitivity), both methods failed to detect the strong population decline in 2/3 to 3/4 of simulations (4 traps/km 2 ), and in about 4/5 of simulations (1 trap/km 2 ). We tested other sampling strategies to improve this sensitivity, which either led to an unchanged population size estimation precision (stratified sampling) or to biased estimated trends (sampling only in high-quality habitats). Simulating animals with a 10 times larger home-range, like red deer ( Cervus elaphus ), allowed to detect the decline more frequently (60% to 95% with 4 traps/km 2 , and 1/3 to 2/3 of the simulations with 1 trap/km 2 ). These results suggest that the key metric for camera trap use is the average number of different traps visited per animal, which in turn depends on trap density, home-range size and space use heterogeneity. We provide a R package allowing the reader to reproduce these simulations, and carry out their own
Martinique : première étude à l’échelle mondiale sur les diatomées épiphytes de l’espèce invasive Halophila stipulacea
No full textActualités scientifiques sur les herbiers des Outre-merLes diatomées sont un maillon essentiel du fonctionnement trophique de l’écosystème « herbier » et une source de nourriture importante pour de nombreuses espèces. En Martinique, du côté caraïbe, les herbiers sont généralement dominés par Halophila stipulacea. Sept échantillons de diatomées ont été prélevés sur les feuillesd’H. stipulacea. 98 taxons de diatomées de niveau spécifique ou infraspécifique ont été inventoriés. Parmi ces taxons, 32 n’avaient jamais été cités de la flore des diatomées marines de Martinique. Cette étude est la toute première concernant les diatomées épiphytes d’H. stipulacea, en dépit de sa large répartition et des forts enjeux de gestion liés à son caractère invasif
30 ans de suivi sanitaire des ongulés de montagnes dans les Réserves Nationales de Chasse et de Faune Sauvage : quelles leçons en tirer et quelles perspectives pour l'avenir ?
No full textSteep slopes, shallow angles; mountain ungulates create their own topography through movements
No full textInternational audienceTravel is considered to account for a substantial proportion of endothermic species energy expenditure. However, transport costs depend on speed of the animal and slope angle of the terrain. We used biologging data from six ungulate species within the French mountains, combined with mapping data, to examine how these different species reacted to slopes by varying travel speed, and chosen ascent and descent angles, in relation to vectoral dynamic body acceleration (VeDBA; as a proxy for energy expenditure). As predicted by theory and as seen in pumas, animals travelled obliquely so that the angle that any individual experienced was lower than that of the topography. Travel speed affected the VeDBA-based proxy for Cost Of Transport (COT) even though most species moved slower on steeper inclines. Models that considered speed, COT, slope and habitat type showed clear relationships between COT and slope with variation across habitat types and according to species. Species-specific choice of travel speeds and ACS underpins fundamental differences in species physiology and ecology via links in heat production and time spent per altitude. Understanding these interrelations points to the complexity of factors affecting space use by mountain ungulates and is crucial for conservation efforts, especially in fast-changing environments where energy expenditure, temperature changes and resource accessibility impact population wellbeing
Efficiency of a macroroughness block ramp in reducing the impact of low-head dams on riverine fish dispersion
No full textInternational audienceMacroroughness ramps ( e.g. with a rough bed and protruding blocks evenly distributed in staggered rows) are nature-like fishways offering a wide range of flow conditions and are expected to be very efficient tools to reduce the impact of weirs on the free movements of most life-stages of riverine fish species. However, their in situ efficiency has not been evaluated yet. Here, we used Radio Frequency Identification (RFID) telemetry to monitor during two years the displacement of eleven fish species, on such a macroroughness ramp located on a tributary of the Loire River in France. We (1) evaluated the migration rates of tagged fish species, poorly documented so far; (2) quantified macroroughness ramp attraction and efficiency; and (3) assessed the influence of fish species, fish length and environmental conditions (river discharge and temperature) on these efficiency estimates. All the species detected downstream of the weir successfully crossed the ramp, although at varying rates. Depending on the analytical approach (considering the whole study duration or taking into account different fish attempts), the ramp attraction efficiency ranged between 65.5% and 52.9%, the ramp passage efficiency between 81.8% and 77.0% and the overall efficiency between 53.6% and 41.6%. Fish between 70 and 451 mm in total length were detected crossing the ramp, usually within a short time. In comparison with the efficiency results available for other types of fishways, the macroroughness ramp studied here ranks among the most efficient devices for fish movement restoration
La complémentarité des outils d'accompagnement des acteurs pour la gestion des adventices économe en herbicides
No full textDéveloppement d'outils d'aide à la décisionCe volume fait suite au carrefour de l'innovation Inrae, organisé par Inrae, Agreenium et l'Institut Agro Dijon, les 26 et 27 novembre 2024 de restitution du projet sur les Connaissances et outils pour des démarches préventives et opérationnelles en gestion agroécologique des adventices (COPRAA).National audienceThis paper presents 4 tools for designing herbicide-sparse cropping systems. The “virtual field” model FLORSYS was built from experiments, and can be used to test cropping systems in the long term, with different pedoclimates and weed floras. It predicts many virtual “measurements” on crops, weeds and soil, as well as indicators of weed impact on crop production and biodiversity. Two decision-support systems co-developed with future users (farmers, crop advisors…) also allow comparing cropping systems, one interms of weed risk for a series of harmful weed species (OdERA), the other (DECIFLORSYS) with the same weed-impact indicators as FLORSYS. Finally, OPTIFLORSYS combines FLORSYS with optimization algorithms to propose cropping systems that meet the user's production and/or biodiversity objectives.Cet article présente 4 outils pour concevoir des systèmes de culture à zéro/faible usage d'herbicides. Le modèle « parcelle virtuelle » FLORSYS construit à partir d'expérimentations permet de tester les systèmes de culture à long-terme, avec différents pédoclimats et flores adventices. Il prédit de nombreuses « mesures » virtuelles sur les cultures, les adventices et le milieu, ainsi que des indicateurs d'impact des adventices sur la production des cultures et la biodiversité. Deux outils d'aide à la décision co-construits avec des acteurs de terrain permettent également de comparer des systèmes de culture, l'un en termes de risque malherbologique pour une série d'espèces adventices préoccupantes (OdERA), l'autre (DECIFLORSYS) avec les mêmes indicateurs d'impacts des adventices que FLORSYS. Enfin, OPTIFLORSYS combine FLORSYS à des algorithmes d'optimisation pour proposer des systèmes de culture répondant aux objectifs de production et/ou de biodiversité recherchés par l'utilisateur
Model-based management of macrophytes in shallow lakes under warming
No full textInternational audienceMacrophytes are a critical component of freshwater ecosystems, harboring significant biodiversity and providing essential resources and services. However, their habitat faces multifaceted challenges from climate change, local anthropogenic disturbance, and biological invasions. Here, we aim to provide local management suggestions under both current and future higher temperature regimes. Using joint species distribution modeling (JSDM), we integrate comprehensive presence-absence data with environmental variables and ecological traits to predict the distributions and diversity of 44 vascular aquatic plant and charophyte species in three shallow lakes (435 sites in total) in southwestern France. The environmental variables considered included physical properties (including current surface temperature and a 2 °C warming scenario), anthropogenic disturbance, shoreline curvature, underwater topography, and the occurrence rate (temporary or permanent) of water and wetness. Subsequently, we use percentile-threshold-based spatial prioritization to identify conservation management hotspots. Our results show that macrophyte habitat suitability is largely influenced by land-use and human accessibility. Moreover, macrophyte habitat suitability and native species diversity generally decrease across lakes under warming. However, the decrease in habitat suitability is greater for native isoetid species than for invasive species—suggesting a potential forthcoming cascade of changing community composition, higher lacustrine trophic states, and impaired provisioning of ecosystem services. Therefore, we suggest immediately adopting adaptive management principles at the identified conservation management hotspots, including the control of and targeted monitoring for invasives as well as conservation and restoration measures for native species, in particular isoetids