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Metagenomic screening of the virome of symptomatic tomato plants from La Réunion Island uncovers a complex of viruses including a newly identified whitefly-transmitted polerovirus
No full textInternational audienceUsing unbiased high-throughput sequencing for metagenomic screening of viruses in diseased tomato plants, we identified a viral complex that includes viruses previously reported in tomato crops on La Réunion Island as well as a novel polerovirus, tentatively named "tomato necrotic yellowing virus" (ToNYV, proposed species, "Polerovirus ToNYV"). Molecular characterization and phylogenetic analysis revealed that ToNYV is closely related to two recently described poleroviruses from Africa and the Middle East, one of which is transmitted by the whitefly Bemisia tabaci, a trait uncommon among poleroviruses. Our transmission experiments demonstrated that ToNYV is also transmitted by B. tabaci and is prevalent across major tomato-growing regions of La Réunion. These findings highlight the value of metagenomic virome analysis in diseased plants for identifying novel viruses potentially involved in emerging plant diseases, either individually or as components of viral complexes
Mediterranean alley-cropping agroforestry modifies arthropod temporal dynamics with divergent effects on trophic groups
No full textInternational audienceAgroforestry is promoted as a sustainable agricultural practice that enhances biodiversity and ecosystem services, including natural pest control. However, its effects on arthropod communities, particularly across different trophic groups and seasonal dynamics, remain poorly understood. In this study, we assessed the impact of a Mediterranean alley-cropping agroforestry system on the abundance, diversity, and community composition of eight arthropod trophic groups, in Southern France. Using pan traps and pitfall traps, we sampled arthropods in agroforestry alleys and tree rows at three dates in spring 2023 (April, March and May), comparing them to monocultures and tree plantations. After identification, invertebrate taxa were classified into eight trophic groups based on current ecological knowledge. Agroforestry influenced arthropod abundance and diversity, though responses varied among trophic groups. Community composition, as reflected through a Principal Coordinates Analysis, was primarily structured by phenology rather than habitat type, with pronounced seasonal shifts across most trophic groups. Effect size analysis showed that tree rows supported a higher abundance of certain beneficial arthropods, emphasizing their role in agroforestry system function. Further research on multi-trophic interactions and long-term dynamics is needed to optimize agroforestry as a strategy for ecological intensification
On L¹ and time-optimal state transitions in piecewise linear models of gene-regulatory networks
No full textInternational audienceIn this paper, we investigate optimal state transfers for a generic class of piecewise-linear models widely used to qualitatively describe gene-regulatory networks. Motivated by the main practical drawbacks of artificially regulating gene expression through chemical inducers, the optimality of the transitions is defined as the convex combination of the total time and the L¹ cost of the control. Solutions are studied through a Hybrid Pontryagin's Maximum Principle approach, which allows to characterize the optimal trajectories and control for the general formulation of the problem. Then, we focus on two practical examples of two-dimensional regulatory networks: the bistable switch, for which the objective is to induce optimal transitions between its two stable steady states, and the damped genetic oscillator, where the goal is to induce sustained oscillatory behaviors. The resulting optimal control strategies can be expressed in state feedback form, involving both bang arcs and inactive control periods, and are shown to slide over certain separatrices of the uncontrolled system that characterize the boundaries of the admissibility set
Minimum time problem for the double integrator with a loss-of-control region
No full textInternational audienceIn this paper we address the minimum time problem for the double integrator, but here, in contrast with the classical version of this problem, the control is constrained to remain constant as long as the state belongs to a given region of the state space called loss-of-control region. This situation prevents switches from occurring in the loss-of-control region and, therefore, a new analysis has to be performed. For this purpose we prove an appropriate version of the Pontryagin maximum principle in which the necessary conditions comprise two key components. The first is an averaged Hamiltonian gradient condition to determine the optimal constant values of the control in the loss-of-control region. The second is, similarly to hybrid maximum principles found in the literature, that the costate admits discontinuity jumps at the interface between the loss-of-control region and its complement. We then highlight the theoretical use of these necessary conditions by solving analytically the minimum time problem for the double integrator with an illustrative loss-of-control region (precisely, the left vertical half-space). New behaviors are observed such as the lack of dynamic programming principle, of feedback expression and of saturation of the control constraint set. Finally we further illustrate these aspects by solving numerically the same minimum time problem for the double integrator but with two other illustrative loss-of-control regions (first a sloped half-space, then a disk)
Une approche historienne de la vulnérabilité : entretien avec Gregory Bankoff
No full textInternational audienceGreg Bankoff est un géohistorien qui s’est intéressé à la manière dont les sociétés et leurs environnements se façonnent mutuellement au fil du temps, avec une attention toute particulière aux modalités d’adaptation des populations aux aléas naturels récurrents. Depuis plus de trente ans, ses recherches, consacrées à l’Asie du Sud-Est, à l’Asie centrale, au Pacifique et à la mer du Nord, cherchent à comprendre comment les sociétés — passées et présentes — ont appris à normaliser les risques et à réagir face aux crises environnementales. Son approche, résolument interdisciplinaire, combine recherche en archives, travail de terrain, cartographie communautaire, enquêtes orales et groupes de discussion pour mettre en lumière l’expérience vécue de la vulnérabilité et de la résilience. Il est actuellement chercheur à l’Université et professeur émérite d’histoire environnementale à l’Université de Hull. La liste de ses publications compte plus de 120 articles parus dans des revues à comité de lecture et chapitres d’ouvrages. Il a récemment coédité l’ouvrage collectif Why Vulnerability Still Matters: The Politics of Disaster Risk Creation (2022)
Scalar-on-Distribution Regression for Assessing the Impact of Climate Change on Rice Yield in Vietnam
No full textInternational audienceIn econometrics, the impact of climate change on agricultural yield has often been modeled using linear functional regression, where crop yield, a scalar response, is regressed on the temperature distribution over a given time period, treated as an ordinary functional parameter, along with other covariates. We explore alternative models that respect the distributional nature of the temperature distribution parameter. Replacing functional observations with the corresponding distributional ones is appropriate for phenomena that are insensitive to the temporal order of events. Since classical addition and scalar multiplication are unsuitable for density functions, alternative operations, spaces and corresponding regression techniques are required. Moreover, compositional data analysis suggests that such covariates should undergo appropriate log-ratio transformations before inclusion in the model. We compare a discrete approach, where temperature histograms are treated as compositional vectors, with a functional scalar-on-density regression using a Bayes space representation of temperature densities. We evaluate the strengths of each method in modeling rice yield in Vietnam, using data on daily temperature extremes. Additionally, we propose modeling climate change scenarios with perturbations of the initial density along a change direction curve informed by IPCC scenarios. The resulting rice yield marginal impact is then quantified using a simple inner product between the density covariate parameter and the change direction curve. Our results indicate that while both approaches yield coherent findings, the scalar-on-density model outperforms the scalar-on-composition with an enhanced ability to accurately gauge the phenomenon’s scale. Supplementary materials accompanying this paper appear on-line
Émotions et dispositifs participatifs en recherche-action sur la transition écologique : risques de normalisation des émotions et de tarissement de la critique sociale ?
No full textInternational audienceCet article examine un dispositif participatif de recherche-action sous l’angle des émotions impliquées dans la transition écologique de la Camargue (Bouches-du-Rhône, France). Il questionne les éventuelles limites que ce type de dispositif impose à la prise en compte des émotions dans les débats et la réflexion collective. Différents processus micro-interactionnels et organisationnels sont pointés comme conduisant à un filtrage émotionnel avec pour conséquences de favoriser une conception technique et téléologique de la transition écologique, de limiter la critique sociale et d’inciter une normalisation des émotions citoyennes et de leurs modalités d’expression
How data and the digital technologies are shaping the data economy for agrifood systems
No full textInternational audienceThe agri-food sector faces urgent challenges such as food security, environmental sustainability, and equitable access to resources. The Data Economy for AgriFood Systems (DE4AFS) offers a transformative solution, leveraging data and digital technologies to address these issues while driving innovation and efficiency. By fostering interconnected ecosystems through federated data spaces, DE4AFS enables secure and trustworthy data sharing, promoting collaboration among stakeholders. Artificial intelligence (AI) further amplifies its potential by generating actionable insights, enhancing decision-making, and supporting sustainable practices like smart agriculture and supply chain optimization. However, challenges such as the digital divide, governance complexities, and environmental impacts remain critical barriers. This chapter outlines the technical and organizational dimensions of the DE4AFS, emphasizing the role of AI and federated data spaces in creating resilient, equitable, and sustainable agri-food systems. It highlights pathways for addressing these challenges and provides a roadmap for leveraging the digital transformation to achieve global sustainability goals in the agri-food sector