About

Serguei Saavedra was promoted to the rank of Associate Professor with Tenure effective July 1. His research seeks to understand the emergence, sustainability, and transformations of ecological systems under changing environments. His lab develops quantifiable and predictive tools to know if a group of species will have the capacity to adapt in a new environment and therefore assess which parts of an ecosystem (from megaherbivores to bacteria) are most threatened by climate change.

Research topics

• Biology
• Sociology
• Computer Science
• Ecology
• Artificial Intelligence
• Botany
• Data science
• Epistemology
• Environmental resource management
• Mathematics
• Environmental science
• Engineering

Selected publications

• An energetic unification of ecological theory

  2026-04-10

  articleOpen access1st authorCorresponding

  Ecological communities can persist for long periods despite strong competition and environmental variability, yet they can also reorganize or collapse abruptly after seemingly modest change. Explaining persistence, diversity, and collapse has produced several major traditions in ecology, including species-interaction models, consumer--resource theory, coexistence theory, feasibility analysis, and stability theory. These approaches are often developed separately, even though they all describe systems that capture energy from the environment, redistribute it through ecological interactions, and lose it through metabolism. Here I propose an energetic framework that helps place these traditions in a common language. The central idea is that ecological communities persist only when external energy supply can support both the maintenance of biomass and the losses associated with internal redistribution, while remaining within finite supply and throughput limits. For flux-based ecological models, this perspective yields an exact aggregate balance identity; for other model classes, the mapping is partial or reduced-form and depends on how the system boundary is defined. This framework clarifies why persistence is conditional on energetic compatibility, why enrichment need not always promote persistence, and how feasibility, coexistence, stability, and early warning signals can be interpreted as related aspects of the same underlying constraint. It also shows how finite supply and throughput can bound energetically compatible community states, while superlinear scaling of internal throughput provides one simple special case that yields transparent reduced-form limits on community size and, with additional assumptions, on ecological complexity. More broadly, the framework offers a physically grounded way to connect historically separate areas of ecological theory.

  PublisherOA PDFDOI

• Energetic constraints shape the diversity of feasible ecological networks

  PLoS Computational Biology · 2026-05-20

  articleOpen accessSenior author

  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.

  PublisherDOI

• The impact of strong activity disruption on building energetics

  EPJ Data Science · 2026-05-15

  articleOpen accessSenior authorCorresponding

  Evidence shows that biological organisms often exhibit sublinear (i.e., a scaling exponent $\alpha <1$, indicating that energy use increases less than proportionally with size) scaling of energy use with size. These scaling patterns observed in biological organisms have also been observed in the energy use of cities. However, at lower levels of organization where energetic interventions can be more manageable, such as buildings, this analysis has remained more elusive due to the difficulties in collecting fine-grained data. Here, we use the maintenance energy usage in buildings at the Massachusetts Institute of Technology (MIT) from 2009 to 2024 to analyze energetic trends at the scale of individual buildings and their sensitivity to strong external perturbations. We find that energy use scales sublinearly with building volume, implying that expected energy use per unit volume decreases with size. Because it has become debatable how to better measure building performance, this scaling pattern naturally establishes a size-dependent baseline, where deviations from the mean would imply relatively higher or lower energy use compared to expectation. This size-dependent pattern became more pronounced (i.e., more sublinear) until 2020. However, the strong activity disruption caused by the COVID-19 pandemic acted as a major shock, removing this trend and leading to a return toward earlier scaling behavior. This suggests that energetic patterns are contingent on relatively stable conditions.

  PublisherDOI

• Energetic constraints shape the diversity of feasible ecological networks

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-21

  articleOpen accessSenior authorCorresponding

  Abstract 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 Summary Why 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.

  PublisherOA PDFDOI

• Food-web architecture governs when predator advantage supports collective persistence

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-21

  articleOpen accessSenior author

  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.

  PublisherDOI

• From species-area relationships to biodiversity risk assessment

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-16

  articleOpen accessSenior author

  Abstract 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 Fisher’s 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.

  PublisherDOI

• Catalysts and inhibitors of critical transitions in ecological systems

  Proceedings of the National Academy of Sciences · 2026-01-09 · 1 citations

  articleOpen access

  Ecological systems can experience sudden and often irreversible regime shifts, also known as critical transitions, with major consequences such as desertification, locust outbreaks, and coral reef collapse. Anticipating these shifts is a central challenge, particularly under accelerating climate change. Although early warning signals of critical transitions have been widely studied, the mechanisms that drive or prevent them remain less well understood. Here, we develop a theoretical framework based on time-delayed dynamics that allows us to identify processes acting as catalysts or inhibitors of critical transitions in ecological systems. We show that a composite measure combining time-delayed species interactions with species abundances is a key modulator of critical transitions. Beyond the critical point, systems exhibit persistent abundance oscillations, substantially increasing the risk of large-scale destabilization and species extinctions. Additionally, we show that a high diversity of species interaction types can act as a buffer of critical transitions. Instead, strong species self-regulation effects can act as catalysts of such transitions, contrary to common expectations. We illustrate the framework with empirical data from microbial systems. Together, these results provide a formal platform for exploring and understanding the drivers of critical transitions in complex living systems.

  PublisherOA PDFDOI

• Author response for "Biodiversity forecasting in natural plankton communities reveals temperature and biotic interactions as key predictors"

  2025-04-16

  peer-review
  PublisherDOI

• Linking power, efficiency, and bifurcations in consumer–resource systems

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-18

  preprintOpen access1st authorCorresponding

  Abstract Three hypotheses help organize energetic thinking about living systems: Lotka’s Maximum Power Principle , Odum–Pinkerton’s Intermediate Efficiency Principle , and Morowitz’s 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 consumer’s 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.

  PublisherDOI

• A general allometric rule predicts sustainable growth across societies

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-19

  preprintOpen access

  Abstract 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.

  PublisherDOI

Recent grants

• EAGER: Bioforecasting: understanding and predicting species persistence in ecological communities under changing environments

  NSF · $199k · 2020–2023

Frequent coauthors

• Chuliang Song

  University of California, Los Angeles

  41 shared

• Rudolf P. Rohr

  University of Fribourg

  41 shared

• Ricard V. Solé

  39 shared

• Jordi Bascompte

  University of Zurich

  26 shared

• Yang‐Yu Liu

  Harvard University

  16 shared

• Artemy Kolchinsky

  15 shared

• Brian Uzzi

  McCormick (United States)

  15 shared

• Andrea Tabi

  University of Amsterdam

  15 shared

Education

• Ph.D., Engineering Science

  Oxford University

  2010