Biology subjects

Allesina, S.

Publications and source records attributed to Allesina, S..

18 recordsLinked to original sources

bioRxiv2026

Emergent feasibility in random ecological systems with higher-order interactions

A recurring lesson from random ecological models is that coexistence is hard to come by: in the Generalized Lotka-Volterra (GLV) model with pairwise interactions, the probability that randomly sampled parameters admit a positive (feasible) equilibrium - a necessary condition for coexistence - is exactly 1/2n in n species, vanishing rapidly with diversity. This rarity is often read as evidence that coexistence demands specific ecological mechanisms. Real interactions, however, are rarely strictly pairwise: any nonlinear dependence of one species growth rate on anothers abundance, Taylor-expanded, generates higher-order interactions (HOIs) of increasing degree. Treating the interaction order d as a knob that indexes this nonlinearity, we map the random GLV with HOIs onto the Kostlan-Shub-Smale class of random polynomial systems and approximate the probability of feasibility (Pf ) analytically. We find a phase transition at d = 4: below this threshold, Pf decays with diversity as in the pairwise case; above it, the exponential proliferation of equilibria outpaces the probability that any given equilibrium is feasible, and the probability of feasibility increases with n, approaching one. The transition appears to be universal across symmetric coefficient distributions, but vanishes when sign symmetry of the parameter distribution is broken. This work uncovers a route by which feasibility emerges from nonlinearity alone, with no fine-tuning of parameters and no appeal to specific ecological mechanisms.

ecology↗

bioRxiv2026

Tipping points are typical in ecosystems with higher-order interactions

Whether species-rich communities erode gradually or collapse abruptly under environmental change is a central question in ecology [1]. Classical pairwise theory predicts that coexistence is always lost gradually, through smooth declines to extinction [2], yet real ecological interactions are often strongly state-dependent - shaped by nonlinearities that fixed pairwise coefficients cannot capture [3]. Here we show that higher-order (nonlinear) interactions make abrupt, irreversible loss of coexistence a typical route to community collapse: across diverse random communities, the equilibrium supporting coexistence disappears suddenly at a fold bifurcation. Using polynomial homotopy continuation [4] to track equilibria as environmental conditions change, we find that folds progressively dominate the boundary of the coexistence domain as nonlinearity strengthens, replacing the gradual extinctions of pairwise theory. Furthermore, the sign structure of higher-order interactions controls both the onset of tipping-points and whether biodiversity buffers or amplifies collapse. Because higher-order and nonlinear interactions are intimately linked, tipping points also arise generically in pairwise models with strong nonlinearity. Applying our continuation framework to a canonical model of plant-pollinator collapse [5], we formally resolve its bifurcation structure as fold-mediated, and we show that fold bifurcations are typical across published multispecies models spanning mutualistic, competitive, and consumer-resource interactions. These results challenge the expectation that monitoring abundances suffices to anticipate collapse, and unify structural-stability theory, which delineates the safe operating space for coexistence, with critical transition theory, which characterizes the nature of its boundaries.

ecology↗

bioRxiv2024

Robust coexistence in ecological competitive communities

Darwin already recognized that competition is fiercest among conspecifics, a principle that later made intraspecific competition central to ecological theory through concepts such as niche differentiation and limiting similarity. Beyond shaping coexistence, strong intraspecific competition can also stabilize community dynamics by ensuring that populations return to equilibrium after disturbance. Here we investigate a more fundamental question: how intraspecific competition influences the very existence of a steady state (feasibility) in large random ecological communities dominated by competition. We show that, analogous to classical results on stability, there is a critical level of intraspecific competition above which a feasible steady state is guaranteed to exist. We derive a general expression for the probability of feasibility and prove that, asymptotically (as species number grows), the transition to stability occurs before the transition to feasibility with probability one. Thus, in large competitive communities, any feasible equilibrium is automatically stable. This ordering persists even when many species in the initial pool cannot coexist and extinctions occur: the dynamics prune the community, shifting feasibility and stability thresholds but never reversing their order. These results imply that large competitive communities generically converge to a globally stable equilibrium, making sustained oscillations or chaos unlikely--consistent with experimental observations.

ecology↗

bioRxiv2023

Phylogeny structures species' interactions in experimental ecological communities

The advent of molecular phylogenetics provided a new perspective on the structure and function of ecological communities. In particular, the hypothesis that traits responsible for species interactions are largely determined by shared evolutionary history has suggested the possibility of connecting the phylogeny of ecological communities to their functioning. However, statistical tests of this link have yielded mixed results. Here we propose a novel framework to test whether phylogeny influences the patterns of coexistence and abundance of species assemblages, and apply it to analyze data from large biodiversity-ecosystem functioning experiments. In our approach, phylogenetic trees are used to parameterize species interactions, which in turn determine the abundance of species in a specified assemblage. We use a maximum likelihood-based approach to score models parameterized with a given phylogenetic tree. To test whether evolutionary history structures interactions, we fit and score ensembles of randomized trees, allowing us to determine if phylogenetic information helps to predict species abundances. Moreover, we can determine the contribution of each branch of the tree to the likelihood, revealing particular clades in which interaction strengths are closely tied to phylogeny. We find strong evidence of phylogenetic signal across a range of published experiments and a variety of models. The flexibility of our framework permits incorporation of ecological information beyond phylogeny, such as functional groups or traits, and provides a principled way to test hypotheses about which factors shape the structure and function of ecological communities.

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

Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics

Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.

ecology↗

bioRxiv2022

Habitat heterogeneity, environmental feedbacks, and species coexistence across timescales

A large body of ecological theory explains the coexistence of multiple species in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple, nested modeling framework that describes species coexistence in heterogeneous environments, as well as the evolution of this heterogeneity over time due to feedbacks from the biotic community. We derive analytical conditions for the coexistence of any number of species in environments with intrinsic heterogeneity or feedbacks, and identify essential differences between these scenarios. Our model is naturally simplified in the limit of very fast or very slow environmental feedbacks, allowing us to treat these two scenarios - which bookend the full range of dynamics - in detail. Among other results, we demonstrate how dispersal and environmental specialization interact to shape realized patterns of habitat association. We also show that environmental feedbacks can tune landscape conditions to promote stable coexistence, although feedbacks can give rise to complex dynamics such as limit cycles, priority effects, and episodic dynamics, as well. Our flexible modeling framework helps explain how and when each of these behaviors arise, and offers a generic mathematical platform for exploring the interplay between species and landscape diversity.

ecology↗

bioRxiv2022

Modeling ecological communities when composition is manipulated experimentally

O_LIIn an experimental setting, the composition of ecological communities can be manipulated directly. Starting from a pool of n species, one can co-culture species in different combinations, spanning mono-cultures, pairs of species, and all the way up to the full pool. Here we advance methods aimed at inferring species interactions from data sets reporting the density attained by species in a variety of sub-communities formed from the same pool. C_LIO_LIFirst, we introduce a fast and robust algorithm to estimate parameters for simple statistical models describing these data, which can be combined with likelihood maximization approaches. Second, we derive from consumer-resource dynamics statistical models with few parameters, which can be applied to study systems where only a small fraction of the potential sub-communities have been observed. Third, we show how a Weighted Least Squares (WLS) framework can be used to account for the fact that species abundances often display a strong relationship between means and variances. C_LIO_LITo illustrate our approach, we analyze data sets spanning plants, bacteria, phytoplankton, as well as simulations, recovering a good fit to the data and demonstrating the ability to predict experiments out-of-sample. C_LIO_LIWe greatly extend the applicability of recently proposed methods, opening the door for the analysis of larger pools of species. C_LI

ecology↗

bioRxiv2021

No robust coexistence in a canonical model of plant-soil feedbacks

Plant-soil feedbacks (PSFs) are considered a key mechanism generating frequency-dependent dynamics in plant communities. Negative feedbacks, in particular, are often invoked to explain coexistence and the maintenance of diversity in species-rich communities. However, the primary modeling framework used to study PSFs considers only two plant species, and we lack clear theoretical expectations for how these complex interactions play out in communities with natural levels of diversity. Here, we demonstrate that this canonical model for PSFs is equivalent to a well-studied model from evolutionary game theory, and use this equivalence to characterize the dynamics with an arbitrary number of plant species. Surprisingly, we find that coexistence of more than two species is virtually impossible, suggesting that alternative theoretical frameworks are needed to describe feedbacks observed in diverse natural communities. Drawing on our analysis, we discuss future directions for PSF models and implications for experimental study of PSF-mediated coexistence in the field.

ecology↗

bioRxiv2021

Intraspecific variation stabilizes classic predator-prey dynamics

In 1920, Alfred J. Lotka found that, to his "considerable surprise", the dynamics of a simple predatorprey model he had devised led "to undamped, and hence indefinitely continued, oscillations" 1,2-- which he thought epitomized the "rhythm of Nature" dear to the Victorians. In 1926, the same model was proposed independently by mathematician Vito Volterra 3,4, who was inspired by the work of his son-in-law, fish biologist Umberto DAncona 5. For over a century, the equations that now bear their names have served as a template for the development of sophisticated models for population dynamics 6-10. Coexistence in this classic predator-prey model is fragile--stochasticity or temporal variability in parameter values result in extinctions. The dynamics can be stabilized by intraspecific competition or other forms of self-regulation, but the prevalence of these processes in large food webs has been questioned 11,12. Here we show that when we consider populations characterized by intraspecific variability, dynamics are stable--despite the absence of any direct self-regulation. Our results can be generalized further, defining a new class of consumer-resource models 8,13. By accounting for intraspecific variation, which is manifest in all biological populations, we obtain dynamics that differ qualitatively and quantitatively from those found for homogeneous populations--challenging a central assumption of many ecological models.

ecology↗

bioRxiv2021

Metapopulations with habitat modification

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant--modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.

ecology↗

bioRxiv2020

Effects of phylogeny on coexistence in model communities

A species traits influence the way in which it interacts with the environment. Thus, we expect traits to play a role in determining whether a given set of species coexists. Traits are, in turn, the outcome of an eco-evolutionary process summarized by a phylogenetic tree. Therefore, the phylogenetic tree associated with a set of species should encode information about the assembly properties of the community. Many studies have high-lighted the potentially complex ways in which phylogenetic information is translated into species ecological properties. However, much less emphasis has been placed on developing expectations for community properties under a particular hypothesis. In this work, we couple a simple model of trait evolution on a phylogenetic tree with local community dynamics governed by Lotka-Volterra equations. This allows us to derive properties of the community of coexisting species as a function of the number of traits, tree topology and the size of the species pool. Our results highlight how phylogenies and traits, in concert, affect the coexistence of a set of species. In this way, our work provides new baseline expectations for the ways in which phylogenetic information is reflected in the structure of and coexistence within local communities.

ecology↗

bioRxiv2020

Tractable models of ecological assembly

Ecological assembly, the way natural communities form under ecological time-scales, is a fundamental and yet poorly understood process. Recent theoretical and empirical approaches to assembly consider systems in which a group of species is introduced in a new environment, and dynamics prune the system down to a sub-community of coexisting species. This "top-down" assembly approach contrasts with the well-studied "bottom-up", or sequential, assembly, in which species from a pool enter the system one at a time, giving rise to priority effects and complex dynamics. Here we determine under which conditions the two approaches are equivalent, i.e., lead asymptotically to the same exact set of coexisting species. To achieve this result, we represent the assembly process as a network in which nodes are sub-communities and edges stand for invasions shifting the composition of the ecological community from a stable configuration to another. This abstraction makes it easy to determine which states the community can occupy, as well as highlight the potential for priority effects or cyclic species composition. We discuss how the equivalence between bottom-up and top-down assembly can advance our understanding of this challenging process from an empirical and theoretical point of view, informing the study of ecological restoration and the design and control of ecological communities.

ecology↗

bioRxiv2019

Transcriptome dynamics predict thermotolerance in Caenorhabditis elegans

BackgroundThe detrimental effects of a short bout of stress can persist, and potentially turn lethal, long after the return to normal conditions. Thermotolerance, which is the capacity of an organism to withstand relatively extreme temperatures, is influenced by the response during stress exposure, as well as the recovery process afterwards. While heat-shock response mechanisms have been studied intensively, predicting thermal tolerance remains a challenge.\n\nResultsHere, we use the nematode Caenorhabditis elegans to measure transcriptional resilience to heat stress and predict thermotolerance. Using high dimensionality reduction techniques in combination with genome-wide gene expression profiles collected in three high resolution time-series during control, heat stress and recovery conditions, we infer a quantitative scale capturing the extent of stress-induced transcriptome dynamics in a single value. This scale provides a basis for evaluating transcriptome resilience, defined here as the ability to depart from stress-expression dynamics during recovery. Independent replication across multiple highly divergent genotypes reveals that the transcriptional resilience parameter measured after a spike in temperature is quantitatively linked to long-term survival after heat stress.\n\nConclusionOur findings imply that thermotolerance is an intrinsic property that pre-determines long term outcome of stress and can be predicted by the transcriptional resilience parameter. Inferring the transcriptional resilience parameters of higher organisms could aid in evaluating rehabilitation strategies after stresses such as disease and trauma.

genomics↗

bioRxiv2019

Predicting coexistence in experimental ecologicalcommunities

The study of experimental communities is fundamental to the development of ecology. Yet, for most ecological systems, the number of experiments required to build, model, or analyze the community vastly exceeds what is feasible using current methods. Here, we address this challenge by presenting a statistical approach that uses the results of a limited number of experiments to predict the outcomes (coexistence and species abundances) of all possible assemblages that can be formed from a given pool of species. Using three well-studied experimental systems--encompassing plants, protists, and algae with grazers--we show that this method predicts with high accuracy the results of unobserved experiments, while making no assumptions about the dynamics of the systems. These results suggest a fundamentally different study design for building and quantifying experimental systems, requiring a small number of experiments relative to traditional approaches. By providing a scalable method for navigating large systems, this work provides an efficient way to study highly diverse experimental communities.

ecology↗

bioRxiv2018

Ecological networks: Pursuing the shortest path, however narrow and crooked

Representing data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade and making use of shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point check-list to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies.

ecology↗

bioRxiv2017

From foodwebs to gene regulatory networks (GRNs) - weak repressions by microRNAs confer system stability

More than 30% of mRNAs are repressed by microRNAs (miRNAs) but most repressions are too weak to have a phenotypic consequence. The diffuse actions have been a central conundrum in understanding the functions of miRNAs. By applying the May-Wigner theory used in foodweb studies, we show that i) weak repressions cumulatively enhance the stability of gene regulatory network (GRN), and ii) broad and weak repressions confer greater stability than a few strong ones. Transcriptome data show that yeast cells, which do not have miRNAs, use strong and non-specific mRNA degradation to stabilize their GRN; in contrast, human cells use miRNAs to increase degradation more modestly and selectively. Simulations indicate that miRNA repressions should be distributed broadly to >25% of mRNAs, in agreement with observations. As predicted, extremely highly expressed genes are avoided and transcription factors are preferred by miRNAs. In conclusion, the diffuse repression by miRNAs is likely a system-level strategy for enhancing GRN stability. This stability control may be the mechanistic basis of \"canalization\" (i.e., developmental homeostasis within each species), sometimes hypothesized to be a main function of miRNAs.

evolutionary biology↗

bioRxiv2017

A Point Of No Return Leading To Death During Heat-Shock In C. elegans

There is considerable insight into pathways and genes associated with heat-stress conditions. Most genes involved in stress response have been identified using mutant screens or gene knockdowns. Yet, there is limited understanding of the temporal dynamics of global gene expression in stressful environments. Here, we studied global gene expression profiles during 12 hours of heat stress in the nematode C. elegans. Using a high-resolution time series of increasing stress exposures, we found a distinct shift in gene expression patterns between 3-4 hours into the stress response, separating an initially highly dynamic phase from a later relatively stagnant phase. This turning point in expression dynamics coincided with a phenotypic turning point, as shown by a strong decrease in movement, survival and, progeny count in the days following the stress. Both detectable at transcriptional and phenotypic level, this study pin-points a relatively small time frame during heat stress at which enough damage is accumulated, making it impossible to recover the next few days.

genomics↗