Biology subjects

Papaix, J.

Publications and source records attributed to Papaix, J..

14 recordsLinked to original sources

bioRxiv2026

Unraveling Environmental Drivers of Insect Pest Dynamics Across Multiple Landscapes

The persistence of pest populations during crop off-seasons is a major challenge for integrated pest management, yet the ecological processes underlying survival and re-infestation often remain unclear. We investigated the oriental fruit fly, Bactrocera dorsalis, a major mango pest, through a two-year demographic monitoring across 56 orchards in the two main mango production basins in Senegal: the Sahelian Niayes and the tropical Casamance. Using a framework combining mechanistic and machine learning models, we identified the main environmental drivers of two key demographic parameters: the local abundance during the mango off-season and the onset of population growth in orchards. In the Niayes, harsh dry-season conditions confined residual populations to micro-habitats providing humidity and shade, while alternative hosts such as citrus trees could act as catalysts for early outbreaks. In contrast, under tropical conditions in the Casamance basin, B.dorsalis populations were more abundant year-round, and higher off-season densities appear to delay outbreak onset, likely due to density-dependent processes such as competition and predation. These findings show that distinct ecological processes shape B. dorsalis off-season persistence across environments, thereby determining population carry-over and growth onset, and ultimately leading to contrasting population dynamics across environments. They support region-specific management strategies to effectively reduce pest pressure: targeting refuges and early host resources in the Niayes, and enhancing natural regulation in Casamance.

ecology↗

bioRxiv2026

Common molecular determinants underlie potyvirus host species jumps and resistance breakdown.

Given their rapid evolutionary dynamics, viruses offer a powerful system to investigate the mechanisms underlying host jumps. Here, we experimentally evolved endive necrotic mosaic virus (ENMV) in five plant hosts within the family Asteraceae: two putative ancestral hosts (Lactuca sativa and Tragopogon pratensis), and three alternative crop or weed species (Cichorium endivia, Zinnia elegans and Calendula arvensis). The resulting evolved viral populations, together with the ancestral strain, were then evaluated in a reciprocal cross-inoculation experiment across all five host species. ENMV exhibited clear adaptive responses in two hosts, Z. elegans and C. arvensis, with increased infection success and higher systemic viral accumulation compared to the ancestral virus. In contrast, no evidence of adaptation was detected in L. sativa, T. pratensis and C. endivia. Strikingly, strong cross-adaptation emerged between Z. elegans and C. arvensis: viral populations evolved in either host consistently outperformed those evolved in other hosts, as well as the ancestral strain, when infecting the reciprocal host. Sequencing of the VPg cistron in adapted populations revealed multiple nonsynonymous mutations, several of which arose independently across evolutionary lineages and in both Z. elegans and C. arvensis selection regimes. Functional assays using an infectious ENMV cDNA clone demonstrated that seven of these substitutions, individually or in combination, significantly increased the infection rate in both Z. elegans and C. arvensis. Notably, several of these substitutions also enhanced infectivity across four additional Asteraceae species among the eleven tested, without a clear relationship to host phylogenetic distance. Remarkably, all identified substitutions map to amino acid positions or adjacent residues in VPg previously implicated in the breakdown of recessive resistance genes against potyviruses in both crop and model plant systems. Together, these results suggest that adaptation to host resistance and host range expansion in potyviruses may rely, at least in part, on shared molecular pathways.

evolutionary biology↗

bioRxiv2026

Inferring the multi-host fitness landscape of endive necrotic mosaic virus from cross-inoculation experiments

Fitness landscapes offer a compact representation of adaptation, yet are rarely inferred from sparse multi-environment data. We present a Bayesian approach to infer an effective multi-host phenotypic fitness landscape from cross-inoculation assays by linking successful infection probabilities to Fishers geometrical model and to an explicit decomposition of establishment routes. The model estimates (i) the distance matrix among host-specific phenotypic optima, (ii) target-host permissiveness through the widths of fitness peaks, (iii) target-specific differences in the efficiency with which phenotypic suitability translates into successful infection, and (iv) the conditional probabilities that successful infections are attributed to direct establishment, rescue from standing variation in the source inoculum, or de novo rescue in the target host. We apply the approach to an experimental evolution dataset for endive necrotic mosaic virus evolved on five Asteraceae hosts and challenged in a full cross-inoculation design. The inferred landscape can be visualized as a phenotypic map of the host community, revealing pronounced heterogeneity in target-host permissiveness and a geometry broadly concordant with host phylogeny. By grounding assay-derived distances in an explicit mechanistic model, the approach provides a parsimonious representation of multi-host constraints that can be used to discuss establishment barriers and potential springboard hosts in heterogeneous communities. More broadly, it offers a general method for inferring effective fitness landscapes from sparse multi-environment data.

evolutionary biology↗

bioRxiv2025

Balancing disease control efficacy, resistance durability, and economic outcomes: Insights from a participatory modeling study integrating grapevine cultivar deployment timing with fungicide treatments

1In this study, we developed, assessed and compared strategies for deploying disease-resistant grapevine cultivars in partnership with a wine cooperative in South-West France. In four collaborative workshops, cooperative managers and multidisciplinary researchers jointly designed six feasible deployment strategies. These scenarios, implemented within real vineyards, involve planting resistant cultivars (RC) in vineyards (i) more than 30 years old, (ii) on 3.3% of the older plots each year or (iii) on plots located in no-treatment zone (due to proximity to watercourses or human dwellings), with and without a fixed maximum percentage of resistant cultivars in the vineyard. The strategies were evaluated with the landsepi model, which simulates the spread and evolution of pathogens across agricultural landscapes in response to host resistance deployment. The assessment criteria included downy mildew control efficacy, resistance durability, decrease in fungicide use, and economic benefits for individual vineyards and the cooperative. These scenarios led us to study more specifically the effects of two little-studied factors: (i) the presence or absence of fungicide applications and (ii) the massive or progressive introduction of resistant cultivars. Fungicide application substantially decreases the risk of resistance breakdown and complements the epidemiological control provided by resistant cultivars, particularly when the fitness costs of virulence are low. The probability of pathogens adapted to RC becoming established was generally lower with progressive than massive RC introduction; however, when establishment did occur, the time to establishment was shorter for progressive strategies at a cropping ratio [≥] 50%. Ultimately, the choice of RC introduction strategy had a minimal overall impact on disease control due to compensatory epidemiological and evolutionary processes, including dilution effects, and the probability and timing of resistance breakdown. These results are discussed in the broader framework of action-research approaches and the challenges and opportunities for resistant cultivar adoption by vine-growers. Our study highlights the potential of participatory approaches for developing practical, scientifically grounded strategies for sustainable viticulture.

evolutionary biology↗

bioRxiv2024

Combining single-gene-resistant and pyramided cultivars in agricultural landscape compromises the benefits of pyramiding in most, but not all, productions situations

ContextWhile resistant cultivars are valuable in safeguarding crops against diseases, they can be rapidly overcome by pathogens. Numerous strategies have been proposed to delay pathogen adaptation (evolutionary control), while still ensuring effective protection (epidemiological control). Resistance genes can be deployed in 1) single-gene-resistant cultivars sown in the same field (mixture strategy) or in different fields (mosaic strategy), 2) a pyramided cultivar (pyramiding strategy) or 3) hybrid strategies that combine the three previous strategies. In addition, the spatial scale at which resistant cultivars are deployed can affect the plant-pathogens interaction: small fields are thought to reduce pest density and disease transmission. ObjectivesWe aim to compare these strategies, focusing on the effects of the simultaneous deployment of single-gene-resistant and pyramided cultivars sharing resistance genes in an agricultural landscape. We also investigate the impact of field size. MethodsWe used the spatially-explicit stochastic model landsepi to compare the evolutionary and epidemiological control across spatial scales and deployment strategies for two major resistance genes. ResultsThe evolutionary control provided by the pyramiding strategy is at risk when single-gene-resistant cultivars are concurrently planted in the landscape (hybrid strategies). The probabilities of pathogen mutation and the corresponding fitness costs play a crucial role in determining the feasibility of planting pyramided cultivars alongside single-gene-resistant ones. Instead, field size did not affect strategies recommendation. ConclusionsPlanting pyramided cultivars alongside single-gene-resistant ones should be avoided. Socio-economic perspectives for the adoption of resistance management strategies are discussed.

evolutionary biology↗

bioRxiv2023

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards

Implementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental drivers of spatio-temporal pest population dynamics remains challenging as numerous candidate factors can operate at a range of scales, from the field (e.g. agricultural practices) to the regional scale (e.g. weather variability). In such a context, data-driven approaches applied to pre-existing data may allow identifying patterns, correlations, and trends that may not be apparent through more restricted hypothesis-driven studies. The resulting insights can lead to the generation of novel hypotheses and inform future experimental work focusing on a limited and relevant set of environmental predictors. In this study, we developed an ecoinformatics approach to unravel the multi-scale environmental conditions that lead to the early re-infestation of mango orchards by a major pest in Senegal, the oriental fruit fly Bactrocera dorsalis (BD). We gathered abundance data from a three-year monitoring conducted in 69 mango orchards as well as environmental data (i.e. orchard management, landscape structure and weather variability) across a range of spatial scales. We then developed a flexible analysis pipeline centred on a recent machine learning algorithm, which allows the combination of gradient boosting and grouped random effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the onset of annual BD population growth in orchards. We found that physical factors (humidity, temperature), and to some extent landscape variables, were the main drivers of the spatio-temporal variability of the onset of population growth in orchards. These results suggest that favourable microclimate conditions could provide refuges for small BD populations that could survive, with little or no reproduction, during the mango off-season and, then, recolonize neighbouring orchards at the beginning of the next mango season. Confirmation of such a hypothesis could help to prioritize surveillance and preventive control actions in refuge areas.

ecology↗

bioRxiv2023

Effects of pathogen sexual reproduction on the evolutionary and epidemiological control provided by deployment strategies for two major resistance genes in agricultural landscapes.

O_LIResistant cultivars are of value for protecting crops from disease, but can be rapidly overcome by pathogens. Several strategies have been proposed to delay pathogen adaptation (evolutionary control), while maintaining effective protection (epidemiological control). Resistance genes can be i) combined in the same cultivar (pyramiding), ii) deployed in different cultivars sown in the same field (mixtures) or in different fields (mosaics), or iii) alternated over time (rotations). The outcomes of these strategies have been investigated principally in pathogens displaying pure clonal reproduction, but sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed. C_LIO_LIWe improved the spatially explicit stochastic model landsepi to include pathogen sexual reproduction, and then investigate the effect of sexual reproduction on evolutionary and epidemiological outcomes across deployment strategies for two major resistance genes. C_LIO_LISexual reproduction only favours the establishment of a superpathogen when single mutant pathogens are present together at a sufficiently high frequency, as in mosaic and mixture strategies. C_LIO_LIWe concluded that, although sexual reproduction may promote the establishment of a superpathogen, it did not affect the optimal strategy recommendations for a wide range of mutation probabilities, associated fitness costs, and landscape organisations (notably the cropping ratio of resistant fields). C_LI

evolutionary biology↗

bioRxiv2021

Dynamics of Aedes albopictus invasion. Insights from a spatio-temporal model

France displays a latitudinal range for the expansion of Aedes albopictus invasive populations that is not yet completely colonized providing a critical opportunity to address key invasion processes. We propose a spatio-temporal model (DISTIGRI) to describe and predict current and future expansion at both intra- and inter-annual scales of A. albopictus. This process-based model integrates mechanistic descriptions of the developmental cycle and the dispersal process of A. albopictus within a reaction-diffusion framework, depending on climatic suitability and photoperiod with a high spatio-temporal resolution. Using this model coupled with a climatic database, we propose several maps describing the current intra-annual distribution of A. albopictus, including the date of first emergence and the length of the period with significant adult presence. We also compute its future distribution over the next 10 years under several climatic scenarios, which shows a range expansion with a strong dependence on the climatic scenario. The outputs of the model may constitute a valuable asset for designing control and avoidance strategies, and to anticipate the biting nuisance with a high spatio-temporal resolution. These outputs also emphasize the importance of taking both dispersal and life cycle into account to obtain accurate descriptions of out-of-equilibrium processes such as ongoing invasions.

ecology↗

bioRxiv2021

The emergence of a birth-dependent mutation rate in asexuals: causes and consequences

AO_SCPLOWBSTRACTC_SCPLOWIn unicellular organisms such as bacteria and in most viruses, mutations mainly occur during reproduction. Thus, genotypes with a high birth rate should have a higher mutation rate. However, standard models of asexual adaptation such as the replicator-mutator equation often neglect this generation-time effect. In this study, we investigate the emergence of a positive dependence between the birth rate and the mutation rate in models of asexual adaptation and the consequences of this dependence. We show that it emerges naturally at the population scale, based on a large population limit of a stochastic time-continuous individual-based model with elementary assumptions. We derive a reaction-diffusion framework that describes the evolutionary trajectories and steady states in the presence of this dependence. When this model is coupled with a phenotype to fitness landscape with two optima, one for birth, the other one for survival, a new trade-off arises in the population. Compared to the standard approach with a constant mutation rate, the symmetry between birth and survival is broken. Our analytical results and numerical simulations show that the trajectories of mean phenotype, mean fitness and the stationary phenotype distribution are in sharp contrast with those displayed for the standard model. The reason for this is that the usual weak selection limit does not hold in a complex landscape with several optima associated with different values of the birth rate. Here, we obtain trajectories of adaptation where the mean phenotype of the population is initially attracted by the birth optimum, but eventually converges to the survival optimum, following a hook-shaped curve which illustrates the antagonistic effects of mutation on adaptation.

evolutionary biology↗

bioRxiv2021

Spatio-temporal point processes as meta-models for population dynamics in heterogeneous landscapes

Landscape heterogeneity affects population dynamics, which determine species persistence, diversity and interactions. These relationships can be accurately represented by advanced spatially-explicit models (SEMs) allowing for high levels of detail and precision. However, such approaches are characterised by high computational complexity, high amount of data and memory requirements, and spatio-temporal outputs may be difficult to analyse. A possibility to deal with this complexity is to aggregate outputs over time or space, but then interesting information may be masked and lost, such as local spatio-temporal relationships or patterns. An alternative solution is given by meta-models and meta-analysis, where simplified mathematical relationships are used to structure and summarise the complex transformations from inputs to outputs. Here, we propose an original approach to analyse SEM outputs. By developing a meta-modelling approach based on spatio-temporal point processes (STPPs), we characterise spatio-temporal population dynamics and landscape heterogeneity relationships in agricultural contexts. A landscape generator and a spatially-explicit population model simulate hierarchically the pest-predator dynamics of codling moth and ground beetles in apple orchards over heterogeneous agricultural landscapes. Spatio-temporally explicit outputs are simplified to marked point patterns of key events, such as local proliferation or introduction events. Then, we construct and estimate regression equations for multi-type STPPs composed of event occurrence intensity and magnitudes. Results provide local insights into spatio-temporal dynamics of pest-predator systems. We are able to differentiate the contributions of different driver categories (i.e., spatio-temporal, spatial, population dynamics). We highlight changes in the effects on occurrence intensity and magnitude when considering drivers at global or local scale. This approach leads to novel findings in agroecology where the organisation of cultivated fields and semi-natural elements are known to play a crucial role for pest regulation. It aids to formulate guidelines for biological control strategies at global and local scale.

ecology↗

bioRxiv2021

More pests but less treatments: ambivalent effect of landscape complexity on Conservation Biological Control

In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and auxiliary species, the underlying landscape structure, and their interaction may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that SNH boost predator population, but predator movement from hedges to fields is fundamental for an efficient pest regulation by auxiliaries and to decrease pesticide treatments. Moreover landscape elements may lead to different effects on pest reduction depending on the considered scale. Integration of species behaviors and traits with landscape structure at multiple scales are needed to provide useful insights for CBC.

ecology↗

bioRxiv2021

A hierarchical Bayesian model to investigate trade-offs between growth and reproduction in a long-lived plant

1A trade-off between growth and fecundity, reflecting the inability of simultaneously investing in both functions when resources are limited, is a fundamental feature of life history theory. This particular trade-off is the result of evolutionary and environmental constrains shaping reproductive and growth traits, but it remains difficult to pinpoint in natural populations of long-lived plants. We developed a hierarchical Bayesian model to estimate the inter-individual correlation among growth and reproduction, using observations at individual level over several years combined with resource simulations from an ecophysiological-based model (CASTANEA). In the Bayesian model, the resource, simulated by CASTANEA and incorporated as a latent variable, is allocated to tree growth, reproductive buds initiation and fruit maturation. Then, we used individual random effects correlated among energetic sinks to investigate potential trade-offs. We applied this original approach to a Mediterranean coniferous tree, Atlas Cedar (Cedrus atlantica), at two contrasted levels of competition, high versus low density population. We found that trees initializing many reproductive buds had a higher growth. Moreover, a negative correlation was detected between growth and fruit survival during maturation. Finally, trees investing more resource to maturate fruits initiated less reproductive buds. The level of competition did not impact the sign of these three correlations, but changed the level of resource allocation: low density population favored growth whereas high density favored reproduction. The level of resource have an impact on individual strategies. This new modeling framework allowed us to detect various individual strategies of resource allocation to growth versus late-stage reproduction on the one hand, and to early-versus late-stage reproduction on the other hand. Moreover, the sign of the correlation between growth and reproductive traits depends on the stage of reproduction considered. Hence, we suggest that the investigation of potential trade-offs between growth and reproduction requires to integrate the dynamics of resource and sinks phenology, from initiation to maturation of reproductive organs.

ecology↗

bioRxiv2020

Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction

Where and when alien organisms are successfully introduced are central questions to elucidate biotic and abiotic conditions favorable to the introduction, establishment and spread of invasive species. We propose a modelling framework to analyze multiple introductions by several invasive genotypes or genetic variants, in competition with a resident population, when observations provide knowledge on the relative proportions of each variant at some dates and places. This framework is based on a mechanistic-statistical model coupling a reaction-diffusion model with a probabilistic observation model. We apply it to a spatio-temporal dataset reporting the relative proportions of five genetic variants of watermelon mosaic virus (WMV, genus Potyvirus, family Potyviridae) in infections of commercial cucurbit fields. Despite the parsimonious nature of the model, it succeeds in fitting the data well and provides an estimation of the dates and places of successful introduction of each emerging variant as well as a reconstruction of the dynamics of each variant since its introduction.

ecology↗

bioRxiv2018

When sinks become sources: adaptive colonization in asexuals

The successful establishment of a population into a new empty habitat outside of its initial niche is a phenomenon akin to evolutionary rescue in the presence of immigration. It underlies a wide range of processes, such as biological invasions by alien organisms, host shifts in pathogens or the emergence of resistance to pesticides or antibiotics from untreated areas.\n\nIn this study, we derive an analytically tractable framework to describe the coupled evolutionary and demographic dynamics of asexual populations in a source-sink system. In particular, we analyze the influence of several factors -- immigration rate, mutational parameters, and harshness of the stress induced by the change of environment -- on the establishment success in the sink (i.e. the formation of a self-sufficient population in the sink), and on the time until establishment. To this aim, we use a classic phenotype-fitness landscape (Fishers geometrical model in n dimensions) where source and sink habitats determine distinct phenotypic optima. The harshness of stress, in the sink, is determined by the distance between the fitness optimum in the sink and that of the source. The dynamics of the full distribution of fitness and of population size in the sink are analytically predicted under a strong mutation strong immigration limit where the population is always polymorphic.\n\nThe resulting eco-evolutionary dynamics depend on mutation and immigration rates in a non straightforward way. Below some mutation rate threshold, establishment always occurs in the sink, following a typical four-phases trajectory of the mean fitness. The waiting time to this establishment is independent of the immigration rate and decreases with the mutation rate. Beyond the mutation rate threshold, lethal mutagenesis impedes establishment and the sink population remains so, albeit with an equilibrium state that depends on the details of the fitness landscape. We use these results to get some insight into possible effects of several management strategies.

evolutionary biology↗