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Mapping essential juvenile habitats of exploited marine fish: Complementary insights from a scientific survey-based model, fishers’ knowledge and fisheries-dependent data
No full textInternational audienceIn the Bay of Biscay (BoB, Northeast Atlantic), a preexisting habitat suitability model (HSM) fitted on ecological scientific trawl survey data with restricted partial coverage revealed the concentration of Young of the Year (YoY) common sole (Solea solea) on restricted coastal and estuarine nurseries. To extend the nursery map of sole in the BoB to zones where survey data are lacking and fit with the sole population and stock management extent, we crossed HSM, fishers' ecological knowledge (FEK) and fisheries-based (FB) data. FB and FEK data also complemented knowledge on juvenile sole habitat and seasonal migration. Thirteen fishers with potential knowledge about the YoY sole distribution were directly interviewed. Direct interviews included both information about the location of juveniles and YoY distribution mapping. With good consensus among fishers, FEK allowed the identification of four new areas hosting essential juvenile habitat for the common sole, revealed the accuracy of the HSM model outside the spatial coverage of the ecological survey, and provided spatial refinement. The FB observation data confirmed the locations of the essential juvenile habitats given by FEK and the spatial distributions of YoY densities predicted from the scientific data. In addition, FB confirmed the seasonal migration of YoY sole, which was preliminarily hypothesized from a local and short-term survey-based study. Our results emphasized the local accuracy of FEK. These findings also underlined the interest in combining several sources of data and methods to map essential fish habitats outside areas well covered by ecological scientific surveys, on order to inform future spatial management measures
Mastitis has a cumulative and lasting effect on milk yield and lactose content in dairy cows
No full textInternational audienceMilk lactose content (LC) physiologically decreases with parity order in dairy cows, but also after udder health inflammation(s) and/or in presence of elevated milk SCC in subclinical cases. Therefore, the progressive decrease in milk LC observed along cows' productive life can be attributed to a combination of factors that altogether impair the epithelial integrity, resulting in weaker tight junctions, e.g., physiological aging of epithelium, mechanical epithelial stress due to milking, and experienced clinical or subclinical mastitis. Mastitis is known to affect the udder synthesis ability too, so our intention through this study was to evaluate if there is a cumulative and lasting effect of mammary gland inflammation(s) on milk yield (MY) and LC. For this purpose, we used diagnoses of clinical mastitis and milk data of Austrian Fleckvieh cows to evaluate the effect of cumulative mastitis events on LC and MY. Only mastitis diagnoses recorded by trained veterinarians were used. Finally, we investigated if cumulative mastitis is a heritable trait and whether it is genetically correlated with either LC or MY. Estimates were obtained using univariate and bivariate linear animal models. A significant reduction in LC and MY was observed in cows that suffered from mastitis compared with those that did not experience udder inflammation. The h2 of cumulative mastitis is promising and much greater (0.09) than the h2 of the binary event itself (≤0.03). The genetic correlations between cumulative mastitis with LC and MY were negative, suggesting that cows with a great genetic merit for MY and LC are expected to be more resistant to repeated inflammations and less recidivist. When we used number of lifetime SCC peaks (≥200,000 or 400,000 cells/mL) to calculate cumulative inflammation events, h2 was even higher (up to 0.38), implying that also subclinical mastitis has a relevant negative impact on both LC and MY. Finally, the present study demonstrated how repeated mastitis events can permanently affect the mammary gland epithelial integrity and synthesis ability, and that the number of cumulative mastitis is a promising phenotype to be used in selection index in combination with other indicator traits toward more resistant and resilient mammary glands
Améliorer la sélection et la précision des modèles de survie : une approche bayésienne spike and slab.
No full textNational audienceIn precision medicine, the prediction of event occurrence rates over time relies on survival models whose flexibility is enabled by incorporating the effects of longitudinally measured predictors using nonparametric regression methods such as Generalized Additive Models (GAMs). Bayesian estimation with spike-and-slab priors for these models simultaneously enables variable selection, regularization of functional effects (via penalized splines), and uncertainty quantification. However, existing methods rely on approximating the rate using a piecewise Poisson model, which is computationally costly. The sparse Bayesian estimation algorithm for a GAM rate model that we propose avoids this Poisson approximation. We show that it provides improved computational efficiency for estimation in complex survival models, while ensuring accurate quantification of the associated uncertainty.En médecine de précision, la prédiction du taux de survenue d’évènements au cours du temps repose sur des modèles de survie dont la flexibilité est permise par l’intégration des effets de prédicteurs mesurés longitudinalement par des méthodes de régression non paramétrique de type Generalized Additive Model (GAM). L’estimation bayésienne à prior spike and slab de ces modèles permet simultanément la sélection de variables, la régularisation d’effets fonctionnels (via des splines pénalisées) et la quantification de l’incertitude. Cependant, les méthodes existantes reposent sur une approximation du taux par un modèle de Poisson par morceaux, qui est computationnellement couteuse. L’algorithme d’estimation bayésienne parcimonieuse d’un modèle GAM pour un taux que nous proposons s’affranchit de cette approximation Poissonienne. Nous montrons qu’il permet un gain d’efficacité pour l’estimation dans les modèles de survie complexes, tout en permettant une quantification correcte de l’incertitude associée aux estimations
Opportunities and Challenges in Combining Optical Sensing and Epidemiological Modelling
No full textInternational audiencePlant diseases impair yield and quality of crops and threaten the health of natural plant communities. Epidemiological models can predict disease and inform management. However, data are scarce, since traditional methods to measure plant diseases are resource intensive and this often limits model performance. Optical sensing offers a methodology to acquire detailed data on plant diseases across various spatial and temporal scales. Key technologies include multispectral, hyperspectral and thermal imaging, and light detection and ranging; the associated sensors can be installed on ground-based platforms, uncrewed aerial vehicles, aeroplanes and satellites. However, despite enormous potential for synergy, optical sensing and epidemiological modelling have rarely been integrated. To address this gap, we first review the state-of-the-art to develop a common language accessible to both research communities. We then explore the opportunities and challenges in combining optical sensing with epidemiological modelling. We discuss how optical sensing can inform epidemiological modelling by improving model selection and parameterisation and providing accurate maps of host plants. Epidemiological modelling can inform optical sensing by boosting measurement accuracy, improving data interpretation and optimising sensor deployment. We consider outstanding challenges in: A) identifying particular diseases; B) data availability, quality and resolution, C) linking optical sensing and epidemiological modelling, and D) emerging diseases. We conclude with recommendations to motivate and shape research and practice in both fields. Among other suggestions, we propose to standardise methods and protocols for optical sensing of plant health and develop open access databases including both optical sensing data and epidemiological models to foster cross-disciplinary work
Factors affecting investments in environmental assets by agricultural machinery cooperatives (CUMAs): Evidence from France
No full textInternational audienceAlthough cooperatives are major actors in the transformation of agricultural systems, very little attention has been paid to the conditions that facilitate or hinder their involvement in the sustainable transition. Drawing on theoretical and empirical approaches, we analyze the effect of social capital on the propensity and proportion of investment in environmental assets in the case of agricultural machinery cooperatives (CUMAs) in France. The number of producers within their CUMA is used as a proxy of the bonding social capital and the CUMA's relationships with external organizations as a proxy of the bridging social capital. Our results show a nonmonotonic relationship between the proxies of social capital and investment in environmental assets by CUMAs. However, the effect differs depending on the subdimension of social capital considered. Interestingly, our results show that the effect of social capital within CUMAs remains even when the cooperatives carry out investment renewals that involve less risk for members
Modelling of the concentration and drying steps for skim milk powder production using machine learning approaches
No full textInternational audienceIn the current context of natural resource depletion and global warming, process efficiency has become a major challenge for dairy manufacturers, and optimization through modeling and simulation is one way of achieving it. For the world production of dairy powders (12.7 million tons in 2023 (CNIEL. 2024)), vacuum concentration and drying are the main steps but their modelling is complex due to the lack of knowledge of mechanisms involved in the process operations, the complexity of raw material and the multiple process schemes and equipment configurations depending on the type of powder produced. This study is part of a wider project which aims to optimize the concentration and drying steps for skim milk powder production. The main objective is to minimize energy consumption of these steps keeping constant powder quality regarding water activity, density and dispersibility. Moreover, modelling employs artificial intelligence, specifically machine learning algorithms, which use computational and algorithmic methods to develop data-driven predictors, offering new insights to understand complex relationships in the food industry (Mavani et al., 2022). 48 skim milk powders were produced at semi-industrial scale using a 2-effect falling-film evaporator and a 1-stage dryer. Physico-chemical and functional properties of concentrates and powders were determined. Subsequently, various machine learning algorithms were tested to address different optimization objectives. Promising results were obtained for the concentration step. Our model predicted the concentration factor from vapour pressure, skim milk dry matter content and feed flow rate (R2=0,90 with a random forest regressor). Addition of experimental data produced during the concentration of various dairy products (whey…) broadened the value range of operating conditions and strengthened the model. The next steps of this work are i) to reinforce the model by integrating more experimental data and considering other variables like concentrate viscosity; ii) to develop predictive models for the drying step.Cniel, 2024. L'Economie laitière en chiffres - Edition 2024. Centre National Interprofessionnel de l’Industrie Laitière, Paris
Traction animale agricole : un regard vers le passé pour préparer l’avenir: Les stratégies de crédibilisation des paysans pour se réclamer modernes
No full textInternational audienceCes dernières décennies, la traction animale connaît un engouement chez les agriculteurs français. La pratique contemporaine s’appuie sur un héritage du passé, sur la tradition. Pour autant, les utilisateurs se sont modernisés, innovent et proposent une manière contemporaine de pratiquer la traction animale. Cet article se propose d’objectiver cette tension entre tradition et modernité autour de la traction animale, tout en rapprochant cette dynamique du cadre de la retro-innovation. Les agriculteurs actuels s’appuient sur une institutionnalisation progressive de la pratique depuis les années 1980, mais souffrent toujours d’une image dépassée. Cela a des conséquences concrètes sur les projets de ces paysans. Dès lors, ils mettent en place des stratégies de crédibilisation de la pratique dans le dessein de visibiliser leur caractère moderne et innovant. En fin de compte, cette rétro-innovation est une proposition politique de redéfinition du modèle agricole
Cascading effects of landscape, mediated by mesoclimate, on carabid communities and weed seed predation in winter cereals
No full textInternational audienceAgricultural intensification, landscape simplification, and climate change threaten biodiversity and ecosystem services in arable lands. Increasing semi-natural habitats and landscape heterogeneity can mitigate these impacts by providing diverse habitats, resources and modifying climate at the landscape scale. As effective natural enemies in arable lands, carabids play a key role in pest and weed seed regulation and are influenced by field management and landscape. This study hypothesized that field management directly influences carabid communities and weed seed predation, while landscape factors affect them directly and indirectly through air temperature at the landscape scale. We sampled 77 winter cereal fields across 20 landscape windows representing regional landscape heterogeneity and composition. We monitored air temperature, carabid communities, and weed seed predation during two sampling sessions in late spring and early summer 2023. Piecewise Structural Equation Models were built to test for the direct and indirect effects of field-scale factors, landscape and climate at the landscape scale on carabids and weed seed predation. For both sampling sessions, results showed that the amount of semi-natural habitats and landscape heterogeneity primarily influence carabid activity-density and composition, which in turn affect weed seed predation. Grasslands, by providing resources and refuges, favour carabids but also appear linked to higher maximum air temperature, possibly influencing carabid composition via thermotolerance traits. The study highlights the importance of semi-natural habitats and landscape heterogeneity in shaping carabid communities and their ecosystem services in arable fields. Furthermore, for the first time, we have highlighted the potential influence of landscape context on carabids mediated by air temperature, which may affect weed regulation services through seed predation
Chapter 21 - Perspectives on marine fish ecology research
No full textInternational audienceThe study of fish ecology has both benefited from and contributed to the advancements in ecological science. This book aims to provide a comprehensive synthesis of the current knowledge in this domain by bringing together contributions from a large number of global experts on the subject matter. This chapter endeavors to present, in a nonexhaustive manner, some future perspectives in the study of fish ecology. Looking ahead, the study of fish ecology holds immense potential for further discoveries and contributions to ecological science. As new technologies and analytical approaches emerge, our ability to investigate fish ecology at various spatial and temporal scales will continue to expand, unveiling new insights into the intricate relationships between fish and their environments
Evolution of hydrological knowledge and water management systems in Lebanon from antiquity to modern times
No full textInternational audienceThis work delves into the hydrological history of Lebanon. With its mountain-influenced Mediterranean climate and its geographic position, Lebanon has a rich history influenced by multiple civilizations (Romans, Arabs, Ottomans, etc.). The study, drawing from mythology, toponymy, archaeology, historical texts and maps, and grey and scientific literature, insists on the double epistemic and technological progress in terms of hydrological knowledge and of water management know how, with specific details about three old cities (Tyre, Beirut and Tripoli), rural settlements and agricultural irrigation. Curating hydrological data, information and knowledge from antiquity to the present is crucial in order to preserve legacy, feed knowledge capitalization and reinforce intelligence towards solutions for water security, in such a socio-hydrologically data-scarce and turbulent region. Insights into this corpus of retrospective water-related knowledge and management are further of interest for the wider Levant and Middle East, in line with Unsolved Problems in Hydrology (UPHs) 17 and 23. © 2025 IAHS