Biology subjects

Saavedra, S.

Publications and source records attributed to Saavedra, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Memory stabilizes complex ecological systems but delays full restoration

Memory effects--defined as the capacity of system states to exert long-lasting influence on subsequent dynamics--are widely recognized as central features of complex living systems. In ecological systems, however, their consequences for stability and recovery dynamics remain poorly understood. To fill this gap, we develop a general theoretical framework that incorporates memory into the dynamics of species-rich ecological systems with complex interaction structures. Our analyses reveal that memory effects expand the stability domain, enabling systems that would otherwise be unstable to persist following perturbations, particularly in cases where instability involves oscillatory behavior. At the same time, memory can accelerate short-term recovery, allowing systems to return more rapidly toward equilibrium in the early stages after perturbation. These apparent benefits, however, come at a cost: memory effects markedly slow long-term recovery, thereby delaying full restoration, as memory retains the influence of past perturbations and hinders a full return to equilibrium. We further support these results by integrating empirical data into the framework. Together, these results reveal fundamental trade-offs mediated by memory--enhanced stability and faster short-term recovery at the expense of delayed full restoration--highlighting the dual role of memory in shaping resilience in complex ecological systems and, more broadly, complex living systems.

ecology↗

bioRxiv2026

Food-web architecture governs when predator advantage supports collective persistence

A recurring question across biological systems is when gains accrued by one part of a system also benefit the whole, and when they instead impose a collective cost. In ecological communities, consumers can increase their energetic gains through trophic interactions, yet those same interactions also determine whether all species persist. Here we show that food-web architecture governs whether predator advantage supports collective persistence, and that omnivory is a key condition under which the two diverge. Using a Lotka- Volterra-type food-web model formulated in terms of energy fluxes, we compare predator output power with the probability of feasibility, which quantifies the range of growth conditions compatible with positive coexistence. In two-species systems, these objectives show no generic alignment. In trophic chains, by contrast, increasing encounter rates makes predator advantage and coexistence mutually reinforcing. Basal omnivory reverses this pattern by shifting the power optimum towards the boundary of coexistence, where the intermediate consumer is lost. This pattern persists in larger networks, under heterogeneous encounter rates, and with saturating functional responses. Our results identify food-web architecture as the determinant of whether local energetic advantage scales up as collective persistence or instead becomes a coexistence cost.

ecology↗

bioRxiv2026

From species-area relationships to biodiversity risk assessment

Biodiversity is commonly summarized by macroecological mean patterns, most prominently the species-area relationship (SAR) linking habitat area to expected species richness. Yet conservation, policy, and economic decisions increasingly require risk metrics: probabilities of rare but consequential biodiversity shortfalls, including local collapse. Such tail risks are central in finance and insurance but remain difficult to quantify in ecology because the data needed to estimate full richness distributions are rarely available at decision scales. Here we provide a mechanistic route from species-area relationships to biodiversity risk metrics. We show that when regional species abundances are well approximated by Fishers log-series, a minimal immigration-extinction mechanism yields a closed-form stationary distribution for local richness whose structure tightly couples the mean SAR to richness variability and lower-tail probabilities. This coupling implies exact fluctuation-response identities and an explicit integral transform that reconstructs collapse probabilities and other tail risk measures directly from the mean SAR. These results define ecological analogues of financial risk metrics--such as collapse probability and lower-tail quantiles--without requiring direct estimation of the full richness distribution. Using high-resolution ForestGEO tree censuses spanning tropical, subtropical, and temperate forests, we find empirical support for these predictions across spatial scales. Together, our results show how widely measurable species-area relationships can be elevated from descriptive averages to operational tools for biodiversity risk assessment and reliability-based conservation planning.

ecology↗

bioRxiv2026

Energetic constraints shape the diversity of feasible ecological networks

The relationship between energy supply and biodiversity is a longstanding question in ecology. Although a monotonic increase in diversity with energy availability is often assumed, unimodal species-energy relationships have been widely documented across ecosystems, and their origin from first principles remains unclear. Here, we develop a geometric framework that recasts ecological feasibility in explicitly energetic terms. By treating total energy supply as a system-level constraint on an energy-based network model, we define nested feasibility domains in the space of energy capture rates and quantify feasibility probabilities as their volume ratios. We show that the probability of initializing a feasible network increases monotonically and saturates with energy supply, whereas the probability of sustaining steady-state biomass follows a unimodal relationship--revealing a bounded energetic window within which network maturation is most likely. Extending this analysis to all candidate subcommunities via feasibility partitions, we find that different community sizes are most feasible at different energy levels, and that average diversity itself peaks at intermediate supply. Together, these results suggest that energetic constraints determine the diversity of ecological networks not through energy scarcity alone, but through the geometric interplay between external energy supply and internal energy exchange. Author SummaryWhy do many ecosystems show the highest biodiversity not where energy is most abundant, but at intermediate levels? This unimodal species-energy relationship has been documented across grasslands, wetlands, and rainforests, yet its origin from first principles has remained unclear. We approached this question by developing a simplified model that treats ecological networks as energy-processing systems. In this model, each species captures energy from the environment and exchanges it with others, and the total energy available to the network is explicitly limited. By measuring how the likelihood of species coexistence changes with energy supply within this framework, we found that while a minimum energy threshold is needed for any community to persist, too much energy can paradoxically reduce the chance of long-term coexistence. This creates a bounded energy window most favorable for community persistence. When we extended the analysis to all possible subsets of species, we found that different-sized communities are most likely to persist at different energy levels, and that overall expected diversity peaks at intermediate supply. These results suggest a possible geometric origin for why more energy does not always support more species, providing a theoretical baseline for connecting the structure of energy flow within networks to observed biodiversity patterns.

ecology↗

bioRxiv2025

Modeling the effect of temperature on species coexistence

O_LITemperature reshapes organismal performance and species interactions, yet competition models rarely treat the declining warm side of thermal performance curves explicitly, even though that regime is likely to become increasingly important under climate warming. C_LIO_LIWe develop a density-dependent generalized Lotka-Volterra framework for pairwise exploitative competition in which effective competition coefficients depend on relative temperature-dependent consumption, and we analyse coexistence using the structural feasibility domain. C_LIO_LIWithin this model class, one result is robust: pairwise structural coexistence is maximized when competitors have equal effective consumption, so with symmetric overlap the temperature of maximal coexistence is the temperature at which their consumption thermal performance curves intersect. C_LIO_LIStronger ecological predictions are parameter dependent. In particular, whether coexistence declines more steeply under warming than under cooling, and whether the coexistence maximum for species with different thermal optima is shifted toward the lower optimum, depend on thermal-curve shape, relative peak heights, baseline competition, resource overlap, and any temperature dependence in carrying capacities. C_LIO_LIFor the illustrative asymmetric unimodal curves analysed here, shared optima produce maximal coexistence near the optimum and a steeper decline under warming than under cooling, whereas different optima produce an intermediate coexistence peak biased toward the lower optimum. A qualitative comparison with classic Drosophila pairwise competition experiments at 19{degrees}C and 25{degrees}C is consistent with these expectations. C_LIO_LIBecause the empirical comparison relies on broad thermal categories, unequal species groups, and binary pairwise outcomes, it should be interpreted as a proof of concept rather than a definitive quantitative test. More generally, our results clarify which aspects of temperature-dependent pairwise coexistence are robust consequences of thermal asymmetry and which are contingent on parameterization. C_LI

ecology↗

bioRxiv2025

On the energetic boundaries of trophic systems

Energy is the fundamental currency of life. Every organism requires a minimum intake to meet maintenance needs, and every trophic transfer dissipates part of the energy flow as heat. Classical theory has emphasized lower bounds on supply--the minimum resource level required for consumers to persist--yet the possible upper bounds and their role in limiting food-chain length remain unclear. We develop a thermodynamically grounded framework that reveals a triad of boundaries: (i) consumer thresholds, (ii) a basal protection limit that reframes the paradox of enrichment as a thermodynamic constraint, and (iii) environmental or physiological supply caps. We show that the intersection of these three boundaries determines the exact range of conditions under which a given ecosystem structure can occur, and that within this range trophic configurations arise as the unique solution that maximizes energy flow. As chain length increases, consumer thresholds rise while the basal protection limit falls, causing this range to contract and eventually disappear. Whether this limit is reached depends on the relative position of these two boundaries and the external supply cap. Their crossing defines an energetic ceiling: a thermodynamic bound on food-chain length beyond which no further level can be sustained. Our results show that feasibility conditions are directly shaped by thermodynamic laws, providing a mechanistic explanation for the emergence and limits of trophic systems.

ecology↗

bioRxiv2025

Linking power, efficiency, and bifurcations in ecological systems

Three hypotheses help organize energetic thinking about living systems: Lotkas Maximum Power Principle, Odum-Pinkertons Intermediate Efficiency Principle, and Morowitzs Biological Cycling Principle. Here we show how these hypotheses fit together in consumer-resource systems, moving from qualitative principles to formal, testable statements. Using the Rosen-zweig-MacArthur model, we prove that the consumers maximum output power lies exactly on the Hopf boundary that separates stable points from cycles; at that point, the resulting power efficiency is intermediate. In the Rosenzweig-MacArthur model the Hopf is supercritical, so a stable limit cycle appears smoothly as the equilibrium loses stability. We treat the Hopf onset of time-periodic population oscillations as a population-level analogue of sustained cycling under energy flux. We then embed these energetic statements in adaptive dynamics: with convex trait costs, evolutionary singular strategies exist and are locally stable, but they coincide with the maximum-power state only under explicit marginal-cost conditions. Together, these results unify classic ideas in the concrete setting of consumer-resource systems and suggest measurements to evaluate when bifurcations, energetics, and evolution can converge.

ecology↗

bioRxiv2025

A general allometric rule predicts sustainable growth across societies

Balancing population growth against finite resources remains a foundational challenge in sustainability science. Although qualitative sustainability principles have matured over decades, translating these principles into universal quantitative rules has been challenging due to the diverse environmental and cultural contexts under which human societies develop. Here, we demonstrate that a general sustainability rule emerges naturally when population-resource feedbacks follow empirically observed allometric scaling laws, condensing ecological, technological, and social complexities into four fundamental parameters. This rule predicts "sustainability corridors" within which societies must remain to ensure long-term persistence. Testing our theoretically derived rule against ethnographic data from 299 hunter-gatherer societies across varied ecological and social environments, we find consistent alignment: these societies tend to occupy the predicted corridors despite substantial contextual differences. By grounding sustainability in biophysical scaling rather than context-specific variables, our approach bridges ecology and sustainability science, suggesting that despite cultural and technological differences, all societies face fundamental constraints for sustainable growth.

ecology↗

bioRxiv2025

Quantifying ecosystem degradation via energetic deficits

Ecosystem degradation is accelerating, threatening biodiversity and human economies. Quantifying this degradation relative to a reference baseline remains a key challenge. Yet, this quantification is essential to provide the necessary resources to regenerate ecosystems. We address this challenge by studying the energetics of population dynamics, where energy inputs such as sunlight and rainfall are transformed into other forms of energy embodied as biomass. This approach provides a unifying framework to quantify degradation across diverse ecosystems via the energetic ecodeficit: the extra energy supply the degraded ecosystem would require to regenerate to a reference state. This energetic deficit can then be translated into a monetary ecodeficit, representing the economic cost of regeneration, considering the local cost of embodied energy. Our analysis reveals nonlinear relationships between biomass loss and energetic ecodeficit, including points of no return beyond which restoration becomes economically infeasible. We showcase our methodology using the current mammal deficits across the African savanna, finding that the monetary ecodefict is about 100 times larger than current estimates. Our work demonstrates how integrating energetic principles into conservation planning can transform ecosystem valuation globally, linking ecosystems and economies sustainably.

ecology↗

bioRxiv2024

Biodiversity forecasting in natural plankton communities reveals temperature and biotic interactions as key predictors

As natural ecosystems experience unprecedented human-made degradation, it is urgent to deliver quantitative anticipatory forecasts of biodiversity change and identify relevant biotic and abiotic predictors. Forecasting natural ecosystems has been challenging due to their complexity, chaotic nonlinear nature and the availability of adequate data. Here, we use four years of daily abundance of a complex lake planktonic ecosystem and its abiotic environment to model and forecast biodiversity metrics. Using a state-of-the-art equation-free modelling technique, we forecast community richness and turnover with a proficiency greater than the constant predictor several generations ahead (30 days). Short-term forecasts improve substantially using biotic predictors (i.e., autoregressive term or community richness). Long-term forecasts require a more complex set of variables (i.e., biotic interactions), and the forecast proficiency depends strongly on including abiotic predictors such as water temperature. Depending on the forecast horizon, biotic and abiotic predictors can interact nonlinearly and synergistically, enhancing each others effects on biodiversity metrics. Our findings showcase the challenges of forecasting biodiversity in natural ecosystems and stress the importance of monitoring focal biotic and abiotic predictors to anticipate undesired changes.

ecology↗

bioRxiv2024

The development of ecological systems along paths of least resistance

A long-standing question in biology is whether there are common principles that characterize the development of ecological systems (the appearance of a group of taxa), regardless of organismal diversity and environmental context. Classic ecological theory holds that these systems develop following a sequenced orderly process that generally proceeds from fast-growing to slow-growing taxa and depends on life-history trade-offs. However, it is also possible that this developmental order is simply the path with the least environmental resistance for survival of the component species and hence favored by probability alone. Here, we use theory and data to show that the order from fast-to slow-growing taxa is the most likely developmental path for diverse systems when local taxon interactions self-organize to minimize environmental resistance. First, we demonstrate theoretically that a sequenced development is more likely than a simultaneous one, at least until the number of iterations becomes so large as to be ecologically implausible. We then show that greater diversity of taxa and life histories improves the likelihood of a sequenced order from fast-to slow-growing taxa. Using data from bacterial and metazoan systems, we present empirical evidence that the developmental order of ecological systems moves along the paths of least environmental resistance. The capacity of simple principles to explain the trend in the developmental order of diverse ecological systems paves the way to an enhanced understanding of the collective features characterizing the diversity of life.

ecology↗

bioRxiv2023

Assembly archetypes in ecological communities

An instrumental discovery in comparative and developmental biology is the existence of assembly archetypes that synthesize the vast diversity of organisms body plans--from legs and wings to human arms--into simple, interpretable, and general design principles. Here we combine a novel mathematical formalism based on Category Theory with experimental data to show that similar "assembly archetypes" exist at the larger organization scale of ecological communities when assembling a species pool across diverse environmental contexts, particularly when species interactions are highly structured. We applied our formalism to clinical data discovering two assembly archetypes that differentiate between healthy and unhealthy human gut microbiota. The concept of assembly archetypes and the methods to synthesize them can pave the way to discovering the general assembly principles of the ecological communities we observe in nature.

ecology↗

bioRxiv2023

Feasibility in MacArthur's Consumer-Resource Model

Finding the conditions that ensure the survival of species has occupied ecologists for decades. Theoretically, for mechanistic models such as MacArthurs consumer-resource model, most of the efforts have concentrated on proving the stability of an equilibrium assuming that it is feasible, but overlooking the conditions that ensure its feasibility. Here we address this gap by finding the range of conditions that lead to a feasible equilibrium of MacArthurs consumer-resource model and study how changes in the systems structural and parametric properties affect those ranges. We characterize the relationship between the loss of feasibility and the increase in complexity (measured by the systems richness and connectance) by a power law that can be extended to random competition matrices. Focusing on the pool of consumers, we find that while the feasibility of the entire system decreases with the size of the pool, the expected fraction of feasible consumers increases --safety in consumer numbers. Focusing on the pool of resources, we find that if resources grow linearly, the larger the pool of resources, the lower the feasibility of the system and the expected fraction of feasible consumers --danger in resource numbers. However, if resources grow logistically, this pattern is reversed with a sublinear increase in feasibility, as it has been previously reported in experimental work. This work provides testable predictions for consumer-resource systems and is a gateway to exploring feasibility in other mechanistic models.

ecology↗

bioRxiv2023

Integrating coexistence and invasion theories under a probabilistic framework

The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while survival probability in coexistence dynamics can be fairly closely translated into colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.

ecology↗

bioRxiv2023

Linking metabolic scaling and coexistence theories

Metabolic scaling theory has been pivotal in formalizing the expected energy expenditures across populations as a function of body size. Coexistence theory has provided a mathematization of the environmental conditions compatible with multispecies coexistence. Yet, it has been challenging to explain how observed community-wide patterns, such as the inverse relationship between population abundance density and body size, can be unified under both theories. Here, we provide the foundation for a tractable, scalable, and extendable framework to study the coexistence of resource-mediated competing populations as a function of their body size. For a given thermal domain and response, this integration reveals that the metabolically predicted 1/4 power dependence of carrying capacity of biomass density on body size can be understood as the average distribution of carrying capacities across feasible environmental conditions, especially for large communities. In line with empirical observations, our integration predicts that such average distribution leads to communities in which population biomass densities at equilibrium are independent from body size, and consequently, population abundance densities are inversely related to body size. This integration opens new opportunities to increase our understanding of how metabolic scaling relationships at the population level can shape processes at the community level under changing environments.

ecology↗

bioRxiv2022

Understanding the state-dependent impact of species correlated responses on community sensitivity to perturbations

Understanding how communities respond to perturbations requires us to consider not only changes in the abundance of individual species, but also correlated changes that can emerge through interspecific effects. However, our knowledge of this phenomenon is mostly constrained to populations at equilibrium, where interspecific effects are fixed. Here, we introduce a framework to disentangle the impact of species correlated responses on community sensitivity to perturbations when interspecific effects change over time due to non-equilibrium dynamics. We partition the volume expansion rate of perturbed abundances (community sensitivity) into contributions of individual species and of species correlations by converting the time-varying Jacobian matrix containing interspecific effects into a time-varying covariance matrix. Using population dynamics models, we demonstrate that species correlations change considerably across time and continuously alternate between reducing and having no impact on community sensitivity. Importantly, these alternating impacts depend on the abundance of particular species and can be detected even from noisy time series. We showcase our framework using two experimental predator-prey time series and find that the impact of species correlations is modulated by prey abundance--as theoretically expected. Our results provide new insights into how and when species interactions can dampen community sensitivity when abundances fluctuate over time.

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

Understanding the variability of pairwise coexistence within multispecies systems

The persistence of virtually every single species depends on both the presence of other species and the specific environmental conditions in a given location. Because in natural settings many of these conditions are unknown, research has been centered on finding the fraction of possible conditions (probability) leading to species coexistence. The focus has been on the persistence probability of an entire multispecies community (formed of either two or more species). However, the methodological and philosophical question has always been whether we can observe the entire community and, if not, what the conditions are under which an observed subset of the community can persist as part of a larger multispecies system. Here, we derive long-term (using analytical calculations) and short-term (using simulations and experimental data) system-level indicators of the effect of third-party species on the coexistence probability of a pair (or subset) of species under unknown environmental conditions. We demonstrate that the fraction of conditions incompatible with the possible coexistence of a pair of species tends to become vanishingly small within systems of increasing numbers of species. Yet, the probability of pairwise coexistence in isolation remains approximately the expected probability of pairwise coexistence in more diverse assemblages. In addition, we found that when third-party species tend to reduce (resp. increase) the coexistence probability of a pair, they tend to exhibit slower (resp. faster) rates of competitive exclusion. Long-term and short-term effects of the remaining third-party species on all possible specific pairs in a system are not equally distributed, but these differences can be mapped and anticipated under environmental uncertainty. Author SummaryIt is debated whether the frequency with which two species coexist in isolation or within a single environmental context is representative of their coexistence expectation within larger multispecies systems and across different environmental conditions. Here, using analytical calculations, simulations, and experimental data, we show why and how third-party species can provide the opportunity for pairwise coexistence regardless of whether a pair of species can coexist in isolation across different environmental conditions. However, we show that this opportunity is not homogeneously granted across all pairs within the same system. We provide a framework to understand and map the long-term and short-term effects that third-party species have on the coexistence of each possible subset in a multispecies system.

ecology↗