Biology subjects

Arnoldi, J.-F.

Publications and source records attributed to Arnoldi, J.-F..

At least 19 recordsLinked to original sources

bioRxiv2026

Stable coexistence and higher productivity are intrinsically linked in multispecies communities

Why species coexist and how diversity sustains ecosystem functioning are usually studied apart. A long-established concept captures both: the complementarity effect---the additional biomass produced by species in mixture. Here, we demonstrate that mixtures of species with negative complementarity are almost always either unfeasible or unstable, whereas a strong positive complementarity indicates a large potential for coexistence. Because a community's total yield settles long before the community composition does, this signal can be read as a predictor in communities still in flux: our analyses of four long-term biodiversity experiments show that transient negative complementarity precedes species loss. Thus, stable coexistence and higher productivity are intrinsically linked in multispecies communities. Biodiversity does not merely have beneficial effects on average; biodiversity that endures can only improve ecosystem functioning.

ecology↗

bioRxiv2026

Biodiversity effects on ecosystem functioning: disentangling the roles of biomass and effect trait expression

O_LISpecies diversity potentially has a dual effect on communities: a generally positive effect on overall community biomass, reflecting the expression of species response and interaction traits, and a poorly characterised effect on mass-specific species contribution to ecosystem functions, reflecting the expression of their effect traits. Disentangling the effects of biodiversity on total biomass from those on effect trait expression would help settle a long-standing debate by clarifying how biodiversity relates to both facets of species effects on ecosystem functioning. C_LIO_LIFollowing the classical BEF approach, we calculate expected ecosystem function based on observed functioning in monoculture. We then derive a net biodiversity effect (NBE) and decompose it into four components: the classical complementarity and selection effects on total community biomass, and complementarity and selection effects on effect trait expression. The latter two reflect, respectively, a complementarity or facilitation in how effect traits influence the function, and how species with the highest potential for increasing the function become dominant in the community. C_LIO_LIWe illustrate this NBE decomposition with three ecosystem functions (nitrogen retention capacity, soil hydraulic conductivity improvement, and forage digestibility) measured in assembled communities under controlled experimental conditions of perennial grassland plants. Regarding nitrogen retention, we find a positive complementary effect via total biomass, but a negative biodiversity effect via effect trait expression. For hydraulic conductivity improvement, biodiversity effects are mostly mediated by total biomass. As for forage digestibility, we found a positive complementarity effect on trait expression, outweighed however by a negative selection effect. This analysis reveals how biodiversity may have contrasting effects on ecosystem functions via its impact on biomass and effect trait expression. C_LI SynthesisSeparating between the effect of biodiversity on plant community biomass and on effect trait expression at the community level is one important step towards understanding the pathways by which diverse plant communities drive ecosystem functioning.

ecology↗

bioRxiv2025

Beyond biomass: how interactions shape species' importance for ecosystem functioning

Assessing the functional role of species in a changing world is critical for effectively preserving ecosystems. Intuitively, this role should relate to how the loss of a species ultimately impacts a function. We introduce the notion of a species dynamic contribution, which takes into account biotic interactions as they develop in the community. Contrary to the static contribution --a measure of what a species directly does-- the dynamic contribution captures what the presence of the species causes. Using both model simulations and empirical data from a ciliate microcosm experiment, we demonstrate that dynamic and static contributions of species are generically unrelated. Our novel characterization of species functional contributions reveals that, due to biotic interactions, rare species that do not possess unique functional traits are just as likely as any other species to play an important role for ecosystem functioning.

ecology↗

bioRxiv2025

Revealing the organization of species stability in ecological communities

Ecological communities are often composed of many species, each interacting in complex ways. This complexity makes predictions of species responses to disturbances challenging. Here, we analyze dynamical community models and reveal an unexpectedly simple principle: species stability is governed by a single metric--self-regulation loss (SL). SL quantifies the importance of self-regulatory processes in species population dynamics. In effect, SL captures a collective outcome of species interactions, organizing how individual species respond to disturbances. When applied to data from protist community experiments, SL accurately forecasts species responses to temperature changes. Our work reveals that, despite the complexity of ecological systems, species stability follows a remarkably simple organizing principle.

ecology↗

bioRxiv2024

Unpacking sublinear growth: diversity, stability and coexistence

How can many species coexist in natural ecosystems remains a fundamental question in ecology. Theory suggests that competition for space and resources should maintain the number of coexisting species far below the staggering diversity commonly found in nature. A recent model finds that, when sublinear growth rates of species are coupled with competition, species diversity can stabilize community dynamics. This, in turn, is suggested to explain the coexistence of many species in natural ecosystems. In this brief note we clarify why the sublinear growth (SG) model does not solve the long standing paradox of species coexistence. This is because in the SG model coexistence emerges from an unrealistic property, in which species per-capita growth rate diverges at low abundance, preventing species from ever going extinct. When infinite growth at low abundance is reconciled with more realistic assumptions, the SG model recovers the expected paradox: increasing diversity leads to competitive exclusion and species extinctions.

ecology↗

bioRxiv2023

A taxonomy of multiple stable states in complex ecological communities

Many natural and man-made systems, from financial markets to ecosystems or the human brain, are built from multiple interconnected units. This complex high-dimensionality hinders our capacity to understand and predict the dynamics, functioning and fragility of these systems. One fragility scenario, particularly relevant to ecological communities of interacting species, concerns so-called regime shifts: abrupt and unexpected transitions from healthy, species-rich communities towards states of degraded ecosystem function and services. The accepted explanation for these shifts is that they arise as abrupt transitions between alternative stable states: multiple stable configurations of a system under the same internal and external conditions. These alternative states are well-understood in low-dimensional systems, but how they upscale with system complexity remains a debated question. In the present work we investigate the emergence of multiple stable states in a number of complex system models. We find that high-dimensional models with random interactions can unfold at least four different regimes of multistability, each emerging under a specific interaction scheme. More importantly, each multistability regime leaves a distinct and quantifiable fingerprint, providing a framework to analyze experimental evidence of abrupt shifts. By bridging previous results and studying multistability regimes, their fingerprints and their correlation with empirical evidence in ecology, our study helps define a common ground to understand and classify multiple stable states in complex systems.

ecology↗

bioRxiv2023

Identifying the limits where variation in consumer stable isotope values reflect variation in diet

O_LIAnalysis of stable isotopes in cosumbers is used commonly to study their ecological and/or environmental niche. There is, however, considerable debate regarding how isotopic values relate to diet and how other sources of variation confound this link, which can undermine the utility. C_LIO_LIFrom the analysis of a simple, but general, model of isotopic incorporation in consumer organisms, we examine the relationship between isotopic variance among individuals, and diet variability within a consumer population. C_LIO_LIWe show that variance in consumer isotope values is directly proportional to variation in diet (through Simpson indices), to the number of isotopically distinct food sources in the diet, and to the baseline variation within and among the isotope values of the food sources. Additionally, when considering temporal diet variation within a consumer we identify the interplay between diet turnover rates and tissue turnover rates that controls the sensitivity of stable isotopes to detect diet variation. C_LIO_LIOur work demonstrates that variation in the stable isotope values of consumers reflect variation in their diet. This relationship, however, can be confounded with other factors to the extent that they may mask the signal coming from diet. We show how simple quantitative corrections can recover a direct 1:1 correlation in some situations, and in others we can adjust our interpretation in light of the new understanding arising from our models. Our framework provides guidance for the design and analysis of empirical studies where the goal is to infer niche width from stable isotope data. C_LI

ecology↗

bioRxiv2022

How collectively integrated are ecological communities?

Beyond abiotic conditions, do population dynamics mostly depend on the species direct predators, preys and conspecifics? Or can indirect feedbacks that ripple across the whole community be equally important? Here we show that the spectral radius of a communitys interaction matrix controls the length of indirect interaction pathways that actually contribute to community-level dynamical patterns, such as the depth of a perturbations reach, or the contribution of biotic processes to realized species niches. The spectral radius is a measure of collectivity that integrates existing approaches to complexity, interaction structure and indirect interactions, while also being accessible from imperfect knowledge of biotic interactions. Our work provides an original perspective on the question of to what degree communities are more than loose collections of species or simple interaction motifs; and explains when reductionist approaches focusing on particular species and small interaction motifs, ought to suffice or fail when applied to ecological communities.

ecology↗

bioRxiv2022

Heating tolerance of ectotherms is explained by temperature's non-linear influence on biological rates

The capacity of ectotherms to adjust their thermal tolerance limits through evolution or acclimation seems relatively modest and highly variable, and we lack satisfying explanations for both findings given a limited understanding of what ultimately determines an organisms thermal tolerance. Here, we test if the amount of heating an ectotherm tolerates throughout a heating event until organismal failure scales with temperatures non-linear influence on biological rates. To account for the non-linear influence of temperature on biological rates on heating tolerance, we rescaled the duration of heating events of 316 ectothermic taxa acclimated to different temperatures and describe the biological rate-corrected heating duration. This rescaling reveals that the capacity of an organism to resist a heating event is in fact remarkably constant across any acclimation temperature, enabling high-precision estimates of how organismal thermal tolerance limits vary under different thermal regimes. We also find that faster heating consistently reduces biological rate-corrected heating durations, which helps further explain why thermal tolerance limits seem so variable on absolute temperature scales. Existing paradigms are that heating tolerances and thermal tolerance limits reflect incomplete metabolic compensatory responses, are constrained by evolutionary conservatism, or index failure of systems such as membrane function; our data provide a different perspective and show that an organisms thermal tolerance emerges from the interaction between the non-linear thermal dependence of biological rates and heating durations, which is an approximately-fixed property of a species.

ecology↗

bioRxiv2022

Stressor interactions at the community level: explaining qualitative mismatches between observations

Perturbations such as climate change, invasive species and pollution, impact the functioning and diversity of ecosystems. But because there is no unique way to measure functioning and diversity, this leads to a ubiquitous and overwhelming variability in community-level responses, that is often seen as a barrier to prediction in ecology. Here, we show that this variability can instead provide insights into hidden features of a communitys functions and responses to perturbations. By first analysing a dataset of global change experiments in microbial soil systems we show that variability of functional and diversity responses to a given perturbation is not random: aggregate properties that are thought to be mechanistically similar tend to respond similarly. We then formalise this intuitive observation to demonstrate that the variability of community-level responses to perturbations is not only predictable, but that it can also be used to access hidden and useful information about population-level responses to perturbations (i.e., response diversity and scaling by species biomass). Our theory offers a baseline expectation for the variability of community-level responses to perturbations and helps to explain the complexity of ecological responses to global change. Significance StatementMeasures of biodiversity and ecosystem functioning show highly variable responses to a given perturbation. This variability is traditionally thought of as reflecting our inability to predict ecological responses to global change. Our work, however, finds that variability of community-level responses is itself predictable and can even be used to gain insights about how species respond to perturbations and collectively contribute to ecosystem functions.

ecology↗

bioRxiv2020

Why scaling up uncertain predictions to higher levels of organisation will underestimate change

AO_SCPLOWBSTRACTC_SCPLOWUncertainty is an irreducible part of predictive science, causing us to over- or underestimate the magnitude of change that a system of interest will face. In a reductionist approach, we may use predictions at the level of individual system components (e.g. species biomass), and combine them to generate predictions for system-level properties (e.g. ecosystem function). Here we show that this process of scaling up uncertain predictions to higher levels of organization has a surprising consequence: it will systematically underestimate the magnitude of system-level change, an effect whose significance grows with the systems dimensionality. This stems from a geometrical observation: in high dimensions there are more ways to be more different, than ways to be more similar. This general remark applies to any complex system. Here we will focus on ecosystems thus, on ecosystem-level predictions generated from the combination of predictions at the species-level. In this setting, the ecosystems dimensionality is a measure of its diversity. We explain why dimensional effects do not play out when predicting change of a single linear aggregate property (e.g. total biomass), yet are revealed when predicting change of non-linear properties (e.g. absolute biomass change, stability or diversity), and when several properties are considered at once to describe the ecosystem, as in multi-functional ecology. Our findings highlight and describe the counter-intuitive effects of scaling up uncertain predictions, effects that will occur in any field of science where a reductionist approach is used to generate predictions.

ecology↗

bioRxiv2020

Can biomass distribution across trophic levels predict trophic cascades?

The biomass distribution across trophic levels (biomass pyramid), and cascading responses to perturbations (trophic cascades), are archetypal representatives of the interconnected set of static and dynamical properties of food chains. A vast literature has explored their respective ecological drivers, sometimes generating correlations between them. Here we instead reveal a fundamental connection: both pyramids and cascades reflect the dynamical sensitivity of the food chain to changes in species intrinsic rates. We deduce a direct relationship between cascades and pyramids, modulated by what we call trophic dissipation - a synthetic concept that encodes the contribution of top-down propagation of consumer losses in the biomass pyramid. Predictable across-ecosystem patterns emerge when systems are in similar regimes of trophic dissipation. Data from 31 aquatic mesocosm experiments demonstrate how our approach can reveal the causal mechanisms linking trophic cascades and biomass distributions, thus providing a road map to deduce reliable predictions from empirical patterns.

ecology↗

bioRxiv2019

How indirect interactions shape long-term invasion dynamics in complex ecological communities

Many facets of ecological theory rely on the analysis of invasion processes, and general approaches exist to understand the early stages of an invasion. However, predicting the long-term transformations of communities following an invasion remains a challenging endeavour. We propose an analytical method that uses community structure and invader dynamical features to predict when these impacts can be large, and show it to be applicable across a wide class of dynamical models. Our approach reveals that short-term invasion success and long-term consequences are two distinct axes of variation controlled by different properties of both invader and resident community. Whether a species can invade is controlled by its invasion fitness, which depends on environmental conditions and direct interactions with resident species. But whether this invasion will cause significant transformations, such as extinctions or a regime shift, depends on a specific measure of indirect feedbacks that may involve the entire resident community. Our approach applies to arbitrarily complex communities, from few competing phenotypes in adaptive dynamics to large nonlinear food webs. It hints at new questions to ask as part of any invasion analysis, and suggests that long-term indirect interactions are key determinants of invasion outcomes.

ecology↗

bioRxiv2018

The variability spectrum of ecological communities: How common and rare species shape stability patterns

Empirical knowledge of ecosystem stability and diversity-stability relationships is mostly based on the analysis of temporal variability of population and ecosystem properties. Variability, however, often depends on external factors that act as disturbances, making it difficult to compare its value across systems and relate it to other stability concepts. Here we show how variability, when viewed as a response to stochastic perturbations, can reveal inherent stability properties of ecological communities, with clear connections with other stability notions. This requires abandoning one-dimensional representations, in which a single variability measurement is taken as a proxy for how stable a system is, and instead consider the whole set of variability values associated to a given community, reflecting the whole set of perturbations that can generate variability. Against the vertiginous dimensionality of the perturbation set, we show that a generic variability-abundance pattern emerges from community assembly, which relates variability to the abundance of perturbed species. As a consequence, the response to stochastic immigration is governed by rare species while common species drive the response to environmental perturbations. In particular, the contrasting contributions of different species abundance classes can lead to opposite diversity-stability patterns, which can be understood from basic statistics of the abundance distribution. Our work shows that a multidimensional perspective on variability allows one to better appreciate the dynamical richness of ecological systems and the underlying meaning of their stability patterns.

ecology↗

bioRxiv2018

The impact of spatial and temporal dimensions of disturbances on ecosystem stability

Ecosystems constantly face disturbances which vary in their spatial and temporal features, yet little is known on how these features affect ecosystem recovery and persistence, i.e. ecosystem stability. We address this issue by considering three ecosystem models with different local dynamics, and ask how their stability properties depend on the spatial and temporal properties of disturbances. We measure the spatial dimension of disturbances by their spatial extent while controlling for their overall strength, and their temporal dimension by the average frequency of random disturbance events. Our models show that the return to equilibrium following a disturbance depends strongly on the disturbances extent, due to rescue effects mediated by dispersal. We then reveal a direct relation between the temporal variability caused by repeated disturbances and the recovery from an isolated disturbance event. Although this could suggest a trivial dependency of ecosystem response on disturbance frequency, we find that this is true only up to a frequency threshold, which depends on both the disturbance spatial features and the ecosystem dynamics. Beyond this threshold the response changes qualitatively, displaying spatial clusters of disturbed regions, causing an increase in variability, and even the loss of persistence for ecosystems with alternative stable states. Thus, spanning the spatial dimension of disturbances can allow probing of the underlying dynamics of the ecosystem. Furthermore, considering spatial and temporal dimensions of disturbances in conjunction is necessary to predict the type of ecosystem responses that can have dramatic consequences, such as regime shifts.

ecology↗

bioRxiv2018

Tannin evolution by niche construction: a spatial stoichiometric model

Among plant traits, plant secondary metabolites such as tannins mediate plant-herbivore interactions but also have after-life effects on litter decomposition and nutrient cycling, which could influence their evolution. By modeling the flow of nitrogen and carbon through plants and soil in a spatially explicit context, we explored the relative contribution of herbivory and plant-soil feedbacks as drivers of tannin evolution. We assumed soil nitrogen to be composed of labile and recalcitrant compartments, the latter made of tannin-protein complexes accessible by plants via associations with mycorrhizal fungi. In unproductive environments and for plants with low biomass turnover rates, we show that when tannins modify soil properties locally, plant-soil feedbacks alone can drive their evolution. We further predict the existence of positive coevolutionary feedbacks between associations with mycorrhizae and tannins, possibly triggered by the evolution of the latter as protection against herbivores. In line with our theoretical results, tannins are mostly present in conservative plants, associated with mycorrhizae and inhabiting unproductive environments. Our work suggests that plant-soil feedbacks can enable niche construction mechanisms which can be key to the evolution of plant traits.

ecology↗

bioRxiv2018

The three regimes of spatial recovery

An enduring challenge for ecology is identifying the drivers of ecosystem and population stability. In a spatially explicit context, key features to consider are landscape spatial structure, local interactions, and dispersal. Substantial work has been done on each of these features as a driver of stability, but little is known on the interplay between them. Missing has been a more integrative approach, able to map and identify different dynamical regimes, and thus to predict a systems response to perturbations. Here we first consider a simple scenario, i.e. the recovery of a homogeneous metapopulation from a single localized pulse disturbance. The analysis of this scenario reveals three fundamental recovery regimes: Isolated Regime when dispersal is not significant, Rescue Regime when dispersal mediates recovery, and Mixing Regime when perturbations spread throughout the system. Despite its simplicity, our approach leads to remarkably general predictions. These include the qualitatively different outcomes of various scenarios of habitat fragmentation, the surprising benefits of local extinctions on population persistence at the transition between regimes, and the productivity shifts of metacommunities in a changing environment. This study thus provides context to known results and insight into future directions of research.

ecology↗

bioRxiv2017

The cavity method for community ecology

This article is addressed to researchers and students in theoretical ecology, as an introduction to \"disordered systems\" approaches from statistical physics, and how they can help understand large ecological communities. We discuss the relevance of these approaches, and how they fit within the broader landscape of models in community ecology. We focus on a remarkably simple technique, the cavity method, which allows to derive the equilibrium properties of Lotka-Volterra systems. We present its predictions, the new intuitions it suggests, and its technical underpinnings. We also discuss a number of new results concerning possible extensions, including different functional responses and community structures.

ecology↗