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Corina Tarnita

Corina Tarnita

· Professor | EEBVerified

Princeton University · Ecology and Evolutionary Biology

Active 2009–2026

h-index38
Citations7.0k
Papers8632 last 5y
Funding$530k
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About

Corina Tarnita is a professor in the Department of Ecology & Evolutionary Biology at Princeton University. Her research examines the organization and emergent properties of complex adaptive systems at multiple scales, from single cells to entire ecosystems. Her approach is mainly theoretical, developing general frameworks that incorporate evolutionary dynamics, evolutionary game theory, and network theory. She combines these models with empirical data to identify and catalog patterns in nature, and tests predictions through eco-evolutionary experiments, molecular and genomic analyses, and field manipulations. Her research interests encompass a wide range of topics, including multicellularity, social behaviors in bacteria, insects, and humans, the effects of population structure and spatial patterns on ecological and evolutionary dynamics, and mutualistic interactions within multi-species networks of symbionts. She works collaboratively with experimental and field ecologists, molecular biologists, and evolutionary biologists to integrate modeling and empirical work, contributing to a deeper understanding of complex biological systems.

Research topics

  • Computer Science
  • Ecology
  • Biology
  • Evolutionary biology
  • Political Science
  • Genetics
  • Cell biology
  • Internet privacy
  • Psychology
  • Environmental science
  • Public relations
  • Physics
  • World Wide Web
  • Statistics
  • Chemistry
  • Social psychology
  • Data science

Selected publications

  • Direct benefits are not necessary for the evolution of multicellularity

    Nature Ecology & Evolution · 2026-04-20 · 1 citations

    articleSenior author
  • Trajectories of biodiversity loss and extinction from trade globalization

    Current Biology · 2025-08-04 · 2 citations

    articleSenior author
  • Zooplankton feeding behavioral signatures in the morphology of macroscale prey spatial distribution

    bioRxiv (Cold Spring Harbor Laboratory) · 2025-08-31

    preprintOpen access

    The problem of pattern and scale remains a central problem in ecology, bridging fundamental and applied questions. Marine microbial communities are a case in point. For instance, to understand the role of zooplankton in oceanic biogeochemistry, their response to changes in environmental conditions, and the implications for ecosystem services (e.g., fisheries), it is critical to understand zooplankton trophic interactions and how they change in a rapidly changing climate. This understanding, however, remains elusive because, unlike for phytoplankton, for which remote sensing of macroscale patterns can provide insight into their microscale dynamics and community composition, obtaining this information for zooplankton largely rests on quantifying the difficult-to-monitor microscale interactions among millions of individuals with different behaviors, and between individuals and their environment. Here, we investigate whether it is possible to obtain indirect information on zooplankton from the macroscale spatial distribution of their prey. To tackle this “problem of scale”, we develop a rigorous coarse-graining methodology that connects individual-level properties with macroscale spatial patterns. We demonstrate that the shape of the prey spatial distribution can indeed encode information about zooplankton feeding behavior and community dynamics. Specifically, we predict a change in dominant feeding behavior—from non-motile to motile feeding—as one moves from areas of high to areas of low prey density. These results thus suggest a novel application for remote sensing approaches: the potential tracking of consumer behavioral signatures in the large-scale patterns of the resource. Importantly, the scaling-up methodology that we developed to check whether those signatures exist is general, and can be used to link scales rigorously and systematically in any system in which the complexity of individual dynamics makes connecting scales intractable.

  • Reconciling ecology and evolutionary game theory or “When not to think cooperation”

    Proceedings of the National Academy of Sciences · 2025-03-31 · 4 citations

    articleOpen access1st authorCorresponding

    Evolutionary game theory (EGT)-overwhelmingly employed today for the study of cooperation in various systems, from microbes to cancer and from insect to human societies-started with the seminal 1973 paper by Maynard Smith and Price showing that limited animal conflict can be selected at the individual level. Owing to the explanatory potential of this paper and enabled by the powerful machinery of the soon-to-be-developed replicator dynamics, EGT took off at an accelerated pace and began to shape expectations across systems and scales. But, even as EGT has expanded its reach, and even as its mathematical foundations expanded with the development of adaptive dynamics and inclusion of stochastic processes, the replicator equation remains, half a century later, its most widely used equation. Owing to its early development and its staying power, the replicator dynamics has helped set both the baseline expectations and the terminology of the field. However, much like the original 1973 paper, replicator dynamics rests on the assumption that individual differences in reproduction are determined only by the payoff from the game (i.e., in isolation, all individuals, regardless of their strategy, have identical intrinsic growth rates). Here, we argue that this assumption limits the scope of replicator dynamics to such an extent as to warrant not just a more deliberative application process, but also a reconsideration of the broad predictions and terminology that it has generated. Simultaneously, we reestablish a dialog with ecology that can be mutually fruitful, e.g., by providing an explanation for how diverse ecological communities can assemble evolutionarily.

  • Reconciling ecology and evolutionary game theory or ‘When not to think cooperation’

    bioRxiv (Cold Spring Harbor Laboratory) · 2024-07-15 · 3 citations

    preprintOpen access1st authorCorresponding

    Abstract Evolutionary game theory (EGT)—overwhelmingly employed today for the study of cooperation in a variety of systems, from microbes to cancer and from insect to human societies—started with the seminal 1973 paper by John Maynard Smith and George Price [1], in which they probed the logic of limited war in animal conflict. If fighting was essential to get access to mates and territory, then why did fights rarely lead to serious injury? Maynard Smith and Price developed game theory to show that limited war can be selected at the individual level. Owing to the explanatory potential of this first paper, and enabled by the elegant and powerful machinery of the soon-to-be-developed replicator dynamics [2, 3], EGT took off at an accelerated pace and began to shape expectations across systems and scales. But, even as it expanded its reach from animals to microbes [4–8] and from microbes to cancer [9–11], the field did not revisit a fundamental assumption of that first paper, which subsequently got weaved into the very fabric of the framework—that individual differences in reproduction are determined only by payoff from the game (i.e. in isolation, all individuals, regardless of strategy, were assumed to have identical intrinsic growth rates). Here, we argue that this original assumption substantially limits the scope of EGT. But, because it is not explicitly presented as a caveat, predictions of EGT have been empirically tested broadly across real systems, where the intrinsic growth rates are generally not equal. That has, unsurprisingly, led to puzzling findings and contentious debates [7, 12–15]. Flagging the high potential for confusion to arise from applications of EGT to empirical systems that it is not designed to study and suggesting a way forward constitute our main motivation for this work. In the process, we reestablish a dialog with ecology that can be fruitful both ways, e.g., by providing a so-far-elusive explanation for how diverse ecological communities can assemble evolutionarily.

  • The evolution of private reputations in information-abundant landscapes

    Nature · 2024-09-25 · 17 citations

    articleSenior author
  • When do stereotypes undermine indirect reciprocity?

    PLoS Computational Biology · 2024-03-01 · 3 citations

    articleOpen accessCorresponding

    Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.

  • Self-organization in spatial ecology

    Current Biology · 2024-10-01 · 10 citations

    article1st authorCorresponding
  • Ecological principles for the evolution of communication in collective systems

    Proceedings of the Royal Society B Biological Sciences · 2024-10-01 · 1 citations

    articleOpen access

    Communication allows members of a collective to share information about their environment. Advanced collective systems, such as multicellular organisms and social insect colonies, vary in whether they use communication at all and, if they do, in what types of signals they use, but the origins of these differences are poorly understood. Here, we develop a theoretical framework to investigate the evolution and diversity of communication strategies under collective-level selection. We find that whether communication can evolve depends on a collective's external environment: communication only evolves in sufficiently stable environments, where the costs of sensing are high enough to disfavour independent sensing but not so high that the optimal strategy is to ignore the environment altogether. Moreover, we find that the evolution of diverse signalling strategies-including those relying on prolonged signalling (e.g. honeybee waggle dance), persistence of signals in the environment (e.g. ant trail pheromones) and brief but frequent communicative interactions (e.g. ant antennal contacts)-can be explained theoretically in terms of the interplay between the demands of the environment and internal constraints on the signal. Altogether, we provide a general framework for comparing communication strategies found in nature and uncover simple ecological principles that may contribute to their diversity.

  • Evolution of norms for judging social behavior

    Proceedings of the National Academy of Sciences · 2023-06-05 · 34 citations

    articleOpen access

    Reputations provide a powerful mechanism to sustain cooperation, as individuals cooperate with those of good social standing. But how should someone’s reputation be updated as we observe their social behavior, and when will a population converge on a shared norm for judging behavior? Here, we develop a mathematical model of cooperation conditioned on reputations, for a population that is stratified into groups. Each group may subscribe to a different social norm for assessing reputations and so norms compete as individuals choose to move from one group to another. We show that a group initially comprising a minority of the population may nonetheless overtake the entire population—especially if it adopts the Stern Judging norm, which assigns a bad reputation to individuals who cooperate with those of bad standing. When individuals do not change group membership, stratifying reputation information into groups tends to destabilize cooperation, unless individuals are strongly insular and favor in-group social interactions. We discuss the implications of our results for the structure of information flow in a population and for the evolution of social norms of judgment.

Recent grants

Frequent coauthors

Education

  • PhD, Mathematics

    Harvard University

    2009
  • MA, Mathematics

    Harvard University

    2008
  • AB, Mathematics

    Harvard University

    2006
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