Biology subjects

Massol, F.

Publications and source records attributed to Massol, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Biodiversity dynamics with complex genotype-to-phenotype architecture in multilayer networks

2The genotype-to-phenotype architecture (GPA), defined by complex interactions such as pleiotropy, epistasis, and regulatory control, is a fundamental yet often overlooked driver of biodiversity dynamics. While empirical evidence suggests that traits mediating species interactions (biotic) and environmental responses (abiotic) are frequently correlated, most eco-evolutionary theories treat these traits as independent, leaving a gap in our understanding of how genomic architecture influences community-level outcomes. In this study, we contrast two distinct GPAs, modular (independent trait evolution) and correlated (integrated trait evolution), within a spatially explicit multilayer network framework. We evaluate their impact on biodiversity across varying regimes of selection, migration, and biotic and environmental filtering. Our results reveal a hierarchy of drivers: selection strength dictates the absolute magnitude of the architectural effect, while migration and context-dependent biotic and abiotic effects determine which architecture yields a diversity advantage. Correlated GPAs enhance species coexistence and diversity in low-migration landscapes characterized by strong selection and moderate, balanced biotic and abiotic pressures. In these contexts, trait integration serves as a buffer against selective noise. Conversely, modular GPAs support higher diversity under high migration and strong biotic interactions, where the decoupling of trait modules provides the adaptive flexibility necessary to navigate spatially conflicting selective pressures. Our findings demonstrate that genomic architecture acts as a critical filter for environmental perturbations. Integrating complex GPAs into multispecies models is essential for quantifying the co-evolutionary feedbacks among traits, population adaptation, and species persistence. Our framework provides a path for predicting how biodiversity emerges and persists across biological scales, from genomics to communities and food webs, under the accelerating pressures of global change. 1 ConclusionsO_LIWe integrate trait architecture to spatial biodiversity to show biodiversity patterns are not merely products of ecological interactions, but are fundamentally constrained by Genotype-to-Phenotype Architecture (GPA). By linking GPA to biodiversity we show the interplay between the complexity of an organism and community structure in determining diversity patterns. C_LIO_LIThe hierarchy of Eco-Evolutionary Drivers: We establish a new conceptual hierarchy where selection strength acts as the fundamental governor of architectural impact, while the specific architecture predicting higher diversity (Correlational vs. Modular) is dictated by the interplay of migration scales and context-dependent biotic and abiotic dynamics. C_LIO_LISelection-Migration contingency for coexistence: We provide a new hypothesis for species coexistence: Correlational selection serves as a stabilizing force under dispersal limitation, whereas Modular trait architecture provides the adaptive flexibility to maintain diversity in high-migration, spatially heterogeneous landscapes. C_LIO_LIAdaptive decoupling as a diversity engine: We propose that trait modularity functions as a "buffer" against extinction by decoupling phenotypic responses. This allows populations to navigate conflicting selective pressures, effectively facilitating evolutionary rescue in complex biotic environments. C_LIO_LIMethodological framework for empirical inference: To bridge the gap between theory and data, we provide a novel likelihood-based framework. This enables researchers to infer latent trait architectures from population genomic samplings, turning GPA from a theoretical construct into a measurable sampling variable in natural populations. C_LIO_LIWe define a new roadmap for the next generation of eco-evolutionary modeling. By identifying the gaps between existing simulation engines, we provide a conceptual "blueprint" for a digital ecosystem that fully integrates complex genetic architecture with global bio-diversity dynamics. C_LI

evolutionary biology↗

bioRxiv2026

Nutrient heterogeneity emerges from dynamical abiotic-biotic feedback in a spatially explicit plant-herbivore occupancy model

Spatial heterogeneity of abiotic resources is essential for species coexistence. Ecological theory often assumes predefined heterogeneity of resources that constrains community dynamics, but the recent developments of meta-ecosystem ecology and zoogeochemistry highlight nutrient patterns could result from the interactions between the activities and movements of organisms and their abiotic environment. Here we investigate the mechanisms by which biotic-abiotic feedbacks could generate nutrient spatial heterogeneity in a simple plant-herbivore occupancy model where populations forage, recycle, and disperse in a homogenous landscape. By systematically varying organisms ranges of foraging and dispersal, and recycling levels, we found that limited dispersal of plants plays a key role on the emergence of nutrient patchiness by favoring small clusters of vegetation that shape their environment through consumption and recycling. However, herbivores could also create nutrient spatial heterogeneity when large foraging and dispersal ranges, and high recycling, allow them to efficiently track plant hot spots and to increase population persistence. Unexpectedly, strong aggregation of herbivore populations did not necessarily result in nutrient clustering. Rather than via recycling, herbivores mainly affected nutrient distribution indirectly, through their top-down impact on plant distribution. When evenly spread in the landscape, herbivore populations with large foraging ranges created areas of strong herbivory pressure unfavorable to plant colonization where nutrient can accumulate. These results can help understand the dynamical feedback between biota and abiotic resources. In a context where human activities alter both nutrient distribution and species abundances, a better understanding of this biotic-abiotic feedback will be key to anticipate the response of ecosystems to current perturbations.

ecology↗

bioRxiv2026

Understanding and addressing under-sampling in plant-pollinator networks using stacked models for missing link prediction

Pollinator diversity and pollination are under threat from anthropogenic disturbances. Plant-pollinator networks are useful tools to study the consequences of these disturbances, but their links are often under-sampled, potentially biasing conclusions. We introduce a computational method that can be used to predict which unobserved links in a plant-pollinator network dataset are missing. This method extends a state-of-the-art machine learning approach to missing link prediction based on stacked generalization, which has been promising in other contexts, to the setting of bipartite plant-pollinator networks with species traits treated as node attributes. This approach predicts missing links using an ensemble of predictors based on both observed network topology and species traits. We demonstrate this approach on synthetic and empirical plant-pollinator networks. We take advantage of a unique empirical plant-pollinator dataset which samples from three sites using (a) records of observed visits of pollinators to plant species and (b) pollen analysis with detailed species trait annotations for both plant and pollinator nodes. Visit-based sampling under-samples the links in these networks, whereas pollen-based sampling identifies additional links, allowing us to investigate missing link prediction from realistic patterns of field under-sampling. We show that full plant-pollinator networks can be partially reconstructed from the under-sampled networks using our approach. Further, we show that this method can be used to identify which features are the most important for predicting missing links, which allows for investigation into mechanisms driving plant-pollinator link formation and observation. This method is broadly applicable to under-sampled plant-pollinator networks.

ecology↗

bioRxiv2025

Tracking community change via network coherence

Understanding how ecological communities respond to environmental change remains a key challenge for biodiversity monitoring. To characterize such responses, we need tools that capture how coherently species respond across a community, and to predict their consequences, we must account for ecological interactions. We first introduce the Ecological Coherence (EC) framework, which describes how species co-responses are structured within a community. Building on this foundation, we extend it to Ecological Network Coherence (ENC), which embeds co-responses within the network of interactions by restricting them to interacting species. Both are expressed through two complementary representations: a response correlation matrix and the distribution of its values. The first can reveal aspects such as coherent or incoherent modules and the roles species play in shaping coherence, whereas the second provides a profile whose shape may serve as an early-warning indicator of instability. These can be applied to both intrinsic responses (environmental performance) and realized responses (abundance dynamics), derived from currently available monitoring data. We illustrate this approach in two empirical systems: a tropical pollination network, where interacting mutualists were more coherent in their temperature responses than the broader community, and a marine food web, where coherence in abundance trends shifted during collapse. Using a Lotka-Volterra model, we further show that ENC distributions with higher variance--reflecting stronger positive and negative co-responses--increase the risk of instability or amplification in dynamics. We also find that species influential in both the correlation matrix and the interaction matrix are key drivers of major dynamic shifts. These results point to the importance of further exploring ENC distributions as potential early-warning indicators of ecological disruption.

ecology↗

bioRxiv2025

Shell-bound archives: uncovering nematode encapsulations in the Galapagos' largest radiation

How macroevolution interacts with ecological networks remains a major question in eco-evolutionary science. We investigate this interplay in the Naesiotus snail radiation of the Galapagos Islands, which encapsulates parasitic nematodes within the shell--a recently discovered gastropod defense. Using a natural history collection, we examined dry shells from 47 species across 12 islands, quantified encapsulations, and sequenced nematode DNA to reconstruct a host-parasite network. Encapsulations were widespread and revealed high nematode diversity, including in snail hosts presumed extinct. Nematode diversity was shaped by habitat, while encapsulation load was better explained by host species identity, suggesting species-specific defenses. Neither trait showed phylogenetic signal, and shell brightness was unrelated to nematode interactions. Similarly, host diversification rate did not predict network position, suggesting that macroevolution may leave a weak or obscured imprint on this host-parasite network. This snail-nematode system in islands readily enables integration of ecological networks, phylogeny, functional traits, and biogeography.

ecology↗

bioRxiv2025

Phylogenetic signal dynamics during niche filling in food webs

Understanding how phylogenetic signal in ecological networks--the tendency for closely related species to resemble one another in ecological roles--emerges and persists remains a central challenge in community ecology. Here, we simulate food web evolution to track how the correspondence between phylogeny and trophic structure changes as communities assemble and niche space fills. By simulating trait evolution coupled with trait-matching for ecological interactions, we quantify how phylogenetic signal in trophic structure changes through time and examine how species network positions relate to their phylogenetic distinctiveness and diversification dynamics. We find that the signal declines over time, driven by emergent feedbacks between node extinction, link reorganization, and trait divergence. Species with high phylogenetic distinctiveness tend to be more specialized and occupy peripheral network positions, particularly in late-stage communities. Centrality consistently constrains diversification in intermediate consumers, emerges as a limiting factor for top predators after niche saturation, and shows nonlinear effects in basal species diversification. Applying our framework to empirical food webs from the Galapagos Islands, we find partial support for these predictions: phylogenetic signal in foraging and vulnerability roles declines with island age, but shows contrasting trends with island area and elevation. We also detect discrepancies between distance-based and clustering-based measures of phylogenetic signal, highlighting the need for robust methods to compare phylogenetic and network structures. Together, our results reveal how trophic interactions mediate the erosion of phylogenetic structure during community assembly and offer testable predictions for systems at different stages of diversification.

ecology↗

bioRxiv2025

Trapped in the web: network architectures spread coevolution and shape adaptation

Adaptation is critical for biodiversity to persist under global change. Within ecological communities, species often face trade-offs between adapting to shifting abiotic conditions and navigating the complex selective pressures imposed by interaction networks. We hypothesize that network architectures characterized by high interaction diversity and overlap constrain coevolutionary dynamics, with asymmetric outcomes for exploiters and victims. Specifically, we predict that exploiters, subject to spread and conflicting selection imposed by their victims, will evolve more slowly and show reduced capacity to track victims evolutionary responses, with these constraints strongest for generalist exploiters. In contrast, victims will show more variable dynamics depending on the coherence of selection (i.e., whether pressures from different exploiters push the victims trait in the same vs. different directions). To test this, we simulated trait evolution in coevolving communities of exploiters and victims across 91 empirical networks, and in artificial networks designed to isolate specific structural effects. Our results show that higher connectance, species richness, nestedness, and centrality homogenize biotic effects and increase fluctuations in trait matching, ultimately weakening coevolutionary coupling. Under these conditions, exploiters face conflicting selection that slows evolution, whereas victims either benefit from aligned selection that accelerates evolution or are constrained by multiple pressures. Together, our findings suggest that network architecture plays a fundamental role in shaping coevolution and adaptation, and raises broader questions about its influence on eco-evolutionary processes in more complex and environmentally variable systems.

ecology↗

bioRxiv2025

Ecological coherence in abundance dynamics across terrestrial and marine assemblages

Understanding how communities respond to environmental change requires assessing not just overall variability but also the structure of co-variation among taxa. We frame this idea under the Ecological Coherence (EC) framework, which generalizes previous notions such as community synchrony or coherence. EC captures the structure of co-responses among taxa within assemblages and can be expressed through two complementary objects: (1) the co-response matrix C, which contains all pairwise correlations between taxa and can be used to identify clusters of taxa with coherent responses as well as the contributions of individual species to community-wide coherence; and (2) the EC distribution, which summarizes the overall profile of co-responses by capturing their shape, spread, and central tendency across the community. By combining these two views, EC moves beyond single summary metrics and provides a richer picture of how coherence is organized within communities. Analyzing the EC distribution across 341 terrestrial and 105 marine assemblages worldwide, we found a general prevalence of weak correlations and a few strong, directional correlations. We also found that it varies with community composition, sampling effort, and biogeographic region. Moreover, the C matrix consistently identified a small subset of taxa with strong correlations to many others, suggesting a promising path to detecting those that may play central roles in amplifying or buffering community responses to environmental change. Our findings on EC pave the way for deeper investigations into what drives the diversity of ecological responses to environmental changes and how it shapes community dynamics, while also underscoring the need for strategically distributing ecological monitoring across trophic guilds and functional roles.

ecology↗

bioRxiv2024

Predicting missing links in food webs using stacked models and species traits

Networks are a powerful way to represent the complexity of complex ecological systems. However, most ecological networks are incompletely observed, e.g., food webs typically contain only partial lists of species interactions. Computational methods for inferring such missing links from observed networks can facilitate field work and investigations of the ecological processes that shape food webs. Here, we describe a stacked generalization approach to predicting missing links in food webs that can learn to optimally combine both structural and trait-based predictions, while accounting for link direction and ecological assumptions. Tests of this method on synthetic food webs show that it performs very well on networks with strong group structure, strong trait structure, and various combinations thereof. Applied to a global database of 290 food webs, the method often achieves near-perfect performance for missing link prediction, and performs better when it can exploit both species traits and patterns in connectivity. Furthermore, we find that link predictability varies with ecosystem type, correlates with certain network characteristics like size, and is principally driven by a subset of ecologically-interpretable predictors. These results indicate broad applicability of stacked generalization for studying ecological interactions and understanding the processes that drive link formation in food webs.

ecology↗

bioRxiv2024

How does co-occurrence of Daphnia species affect their gut microbiome?

Species co-occurrence can lead to competitive interactions that influence fitness. Competition is typically assumed to be modulated by species niche, especially food-acquisition related traits. The influence of interspecific interactions on host microbiome communities has rarely been considered, and yet may provide an alternative mechanism regarding the effect of host species co-occurrence on their fitness. Here, we investigated whether the composition of the gut microbial community differs between two Daphnia species (D. magna and D. pulex), and whether the gut microbiome of one species depends on the presence of the other. We hypothesized the stronger filter-feeder D. magna to have a larger effect on the gut microbiome of the weaker filter-feeder D. pulex than vice versa. To this purpose, three D. magna and three D. pulex genotypes were first made axenic and then grown in monocultures or in cocultures in natural environmental bacterioplankton-enriched water, before assessing the community composition of the gut microbiomes and bacterioplankton. We found that the composition of the gut microbiome of the two Daphnia species did not significantly differ overall. However, subtle differences between mono- and cocultures were found at the Daphnia genotype level. For most genotype combinations (six out of nine), the microbiome of D. pulex changed more when grown in cocultures with D. magna than in monocultures. This provides limited support for our hypothesis that the stronger competitor has a larger effect on the gut microbiome of the weaker one than vice versa, and that this effect is possibly mediated via the bacterioplankton community.

ecology↗

bioRxiv2024

DoubleTrouble: Multiple infections and the coevolution of virulence-resistance in structured host-parasite populations.

Parasite competition is a key factor driving the epidemiology and evolution of parasites, and is expected to modulate the selective pressures acting upon the host, and to alter its response to infection. Using a nested co-evolutionary model where epidemiological traits (transmission, virulence and recovery) are derived from within-host interactions between parasite strains, we analyse using adaptive dynamics methodology the joint evolution of parasite virulence and host resistance. We compare the predicted coevolutionarily stable states under different competition regimes, including single infections (preemption), superinfection (strain dominance) and coinfections (transient strain coexistence). We find that coinfections select for lower virulence compared to superinfection, while the opposite trend is observed for host resistance. The local coexistence of parasites in coinfected hosts creates a kin selection effect that reduces both parasite virulence and host response. We show that the magnitude of this effect depends on the ecological context, and notably the degree of coupling between hosts. Our work contributes to building the gap between metapopulation ecology and epidemiology.

evolutionary biology↗

bioRxiv2024

Drivers of plant-associated invertebrate community structure in West-European coastal dunes

The organisation of species assemblages is affected by environmental factors acting at different spatial scales. To understand the drivers behind the community structure of invertebrates associated with marram grass -the dominant dune-building ecosystem engineer in European coastal dunes-, we set up a stratified sampling scheme in six biogeographic sectors along the North Sea. We tested to which degree local invertebrate species composition is affected by the spatial organisation of marram grass tussocks. We used distance-based RDA and a joint species distribution modelling approach to understand how species traits and their phylogeny contribute to invertebrate community composition. We show biogeography to be the most important driver, followed by species-specific responses to marram grass cover and vitality. Traits and phylogeny had a minor influence on the species distribution patterns. The residual species covariation suggests negative interactions between groups of specialist and generalist species. From an applied perspective, our research indicates that the biological value of nature-based solutions for the restoration and design of coastal dunes can be optimized by the design of a heterogeneous marram grass planting scheme and/or development.

ecology↗

bioRxiv2023

Coexistence of many species under a random competition-colonization trade-off

The competition-colonization trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarity. To investigate whether diverse metacommunities can assemble in a competition-colonization trade-off model, we study their assembly from a probabilistic perspective. From a pool of species with parameters (corresponding to traits) sampled at random, we compute the probability that any number of species coexist and characterize the set of species that emerges through assembly. Remarkably, almost exactly half of the species in a large pool typically coexist, with no saturation as the size of the pool grows, and with little dependence on the underlying distribution of traits. Through a mix of analytical results and simulations, we show that this unlimited niche packing emerges as assembly actively moves communities toward overdispersed configurations in niche space. Our findings also apply to a realistic assembly scenario where species invade one-at-a-time from a fixed regional pool. When diversity arises de novo in the metacommunity, richness still grows without bound, but more slowly. Together, our results suggest that the competition-colonization trade-off can support the robust emergence of diverse communities, even when coexistence of the full species pool is exceedingly unlikely.

ecology↗

bioRxiv2022

Coevolution of species colonization rates controls food-chain length in spatially structured food webs

The complexity of food webs and how it depends on environmental variables is a long-standing question in ecology. Food-chain length depends on many factors, such as productive space, disturbance and spatial processes. It is not clear though how food-chain length should vary with adaptive evolutionary changes of the constitutive species. Assuming that each trophic level is subject to a competition-colonization trade-off, we model the adaptive evolution of their colonization rates and its consequences on equilibrium occupancies and food-chain length. When colonization rates are allowed to evolve, longer food chains can persist. Extinction, perturbation and habitat loss all affect the evolutionary-stable colonization rates, but trade-off strength (costs of dispersal) has a major role: weaker trade-offs yield longer chains. Our results suggest a strong link between within-trophic level competition, spatial occupancies and food-chain length. Although these eco-evo dynamics partly alleviate the constraint on food-chain length in metacommunities, we show it is no magic bullet: the highest, most vulnerable, trophic levels are also those that least benefit from evolution. Our model generates qualitative predictions regarding how trait evolution affects the response of communities to disturbance and habitat loss. This highlights the importance of eco-evolutionary dynamics at metacommunity level in determining food-chain length.

ecology↗

bioRxiv2022

Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity

Mycobacterium tuberculosis (Mtb) infections result in a wide spectrum of clinical presentations but without proven Mtb genetic determinants. Herein, 234 pulmonary tuberculosis (TB) patients were stratified according to TB disease severity and Mtb genetic features were explored using whole genome sequencing, including heterologous single nucleotide polymorphism (SNP) calling to explore micro-diversity. Clinical isolates from patients with mild TB carried mutations in genes associated with host-pathogen interaction, while those from patients with moderate/severe TB carried mutations associated with regulatory mechanisms. Genome-wide association study identified a SNP in the promoter of the gene coding for the virulence regulator EspR associated with moderate/severe disease. Structural equation modelling and model comparisons indicated that TB severity was associated with the detection of Mtb micro-diversity within clinical isolates and to the espR SNP. Taken together, these results provide a new insight to better understand TB pathophysiology and could provide new prognosis tool for pulmonary TB severity.

microbiology↗

bioRxiv2021

Within-host genetic micro-diversity of Mycobacterium tuberculosis and the link with tuberculosis disease features

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) complex, is still the number one deadly contagious disease. Mtb infection results in a wide spectrum of clinical presentations and severity symptoms, but without proven Mtb genetic determinants. Thanks to a collection of 355 clinical isolates with associated patients clinical data, we showed that Mtb micro-diversity within patient isolates is strongly correlated with TB-associated severity scores. Interestingly, this diversity is driven by a selection pressure to adapt to different lifestyles related to the infection site. Taken together, these results provide a new insight to better understand TB pathophysiology. Furthermore, Mtb micro-diversity could be envisioned as a new prognostic tool to improve the management of TB patients.

microbiology↗

bioRxiv2020

Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of community structure in fruit flies

AO_SCPLOWBSTRACTC_SCPLOWThe relative importance of ecological factors and species interactions for phytophagous insect species distributions has long been a controversial issue. Using field abundances of eight sympatric Tephritid fruit flies on 21 host plants, we inferred flies realized niches using joint species distribution modelling and network inference, on the community as a whole and separately on three groups of host plants. These inferences were then confronted to flies fundamental niches estimated through laboratory-measured fitnesses on host plants. Species abundances were mainly determined by host plants followed by climatic factors, with a minor role for competition between species sharing host plants. The relative importance of these factors mildly changed when we focused on particular host plant groups. Despite overlapping fundamental niches, specialists and generalists had almost distinct realized niches, with possible competitive exclusion of generalists by specialists on Cucurbitaceae, and different assembly rules: specialists were mainly influenced by their adaptation to host plants while generalist abundances varied regardless of their fundamental host use.

ecology↗

bioRxiv2020

Once upon a time in the south: local drivers of plant invasion in the harsh sub-Antarctic islands

AimHere, we aim to: (i) investigate the local effect of environmental and human-related factors on alien plant invasion in sub-Antarctic islands; (ii) explore the relationship between alien species features and their dependence on anthropogenic propagule pressure; and (iii) unravel key traits conferring invasiveness in the sub-Antarctic. LocationPossession Island, Crozet archipelago (French sub-Antarctic islands). TaxonNon-native vascular plants (Poaceae, Caryophyllaceae, Juncaceae). MethodsSingle-species distribution models were used to explore the effect of high-resolution topoclimatic and human-related variables on the occurrence of six of the most aggressive alien plants colonizing French sub-Antarctic islands. Furthermore, the interaction between alien species traits and their response to anthropogenic propagule pressure was analysed by means of a multi-species distribution model. This allowed identifying the features of species that were associated to low dependence on human-assisted introductions, and were thus potentially more invasive. ResultsWe observed two main invasion patterns: low-spread species strongly dependent on anthropogenic propagule pressure and high-spread species limited mainly by harsh climatic conditions. Differences in invasiveness across species mostly related to their residence time, life history and plant height, with older introductions, perennial and low-stature species being more invasive. Main conclusionsThe availability of high-resolution data improved our understanding of the role of environmental and human-related factors in driving alien species distribution on sub-Antarctic islands. At the same time, the identification of alien species features conferring invasiveness may help anticipating future problematic invasions.

ecology↗