EVOP-MS18

Collective Behavior and Social Evolution

Thursday, June 17 at 04:15am (PDT)
Thursday, June 17 at 12:15pm (BST)
Thursday, June 17 08:15pm (KST)

SMB2021 SMB2021 Follow Tuesday (Wednesday) during the "MS18" time block.
Note: this minisymposia has multiple sessions. The second session is MS16-EVOP (click here).

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Organizers:

Daniel Cooney (University of Pennsylvania, USA) & Olivia Chu (Princeton University, USA)

Description:

A common theme across ecology, evolutionary biology, and social science is the key role that individual-level competition and cooperation play in determining emergent phenomena at the population level. In this minisymposium, our speakers will explore how rules governing social interactions help to shape the structure of populations across a variety of systems, from the development of complex social networks and life-history strategies in animal groups to overcome the risk of infectious disease to the establishment of regulatory institutions and ideological echo chambers in human populations. Many of the talks will utilize the frameworks of evolutionary game theory and adaptive dynamics, modeling how natural selection or social learning can help shape the distribution of traits in populations over time, through genetic or cultural evolution. Mathematically, our session will feature a variety of approaches ranging from individual-based stochastic modeling to mean-field descriptions by ordinary and partial differential equations, demonstrating how collective phenomena can arise across scales of biological organization. In particular, we are hoping to bring together researchers from the dynamical systems, collective behavior, and evolutionary game theory communities to highlight common research themes and the wide range of biological settings that comprise the field of social evolution.



Ricardo Martinez-Garcia

(ICTP South American Institute for Fundamental Research)
"The exploitative segregation of plant roots: a game-theory approach to below-ground plant growth"
Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. The study of below-ground competition, unlike above-ground shoot competition, is hampered by our inability to observe roots. We have few observations of intact root systems in soil and lack a comprehensive theory for root system responses to their environment and the presence of other individuals. In this presentation, I will first review previous efforts to explain plant below-ground interactions and discuss how they lead to seemingly contradictory predictions. Then, I will introduce our recent work and show how it resolves existing controversy and provides a unifying framework to study below-ground plant interactions. I will conclude by discussing future research lines that depart from our results and how they can be addressed with extensions of our original model.


Max Souza

(Fluminense Federal University)
"Stochastic evolution of finite populations: the fingerprints of fixation"
On the one hand, once we are given a finite population stochastic finite population model without mutations and a (possibly frequency dependent) fitness function, the computation of the corresponding fixation probability is straightforward. On the other hand, one might ask what the fixation probability can tell us about the underlying process. Starting from classical Moran and Wright-Fisher processes, we will discuss some qualitative properties of the corresponding fixation probability. We also address when the fixation probability uniquely characterises knowing the fixation characterises these processes. In particular, we will see that for each fixation probability vector that is strictly increasing, there is exactly one Moran process that realises it. For the Wright-Fisher process, however, the situation is more involved and almost any fixation pattern is attainable — though not necessarily in a unique way. If time allows, we will also address the corresponding inverse problem and some asymptotic results for large populations.


Nina Fefferman

(University of Tennessee)
"How infectious diseases may have shaped the evolution of social organization"
Sociality itself represents a tradeoff between pooled benefits and shared risks. Looking at societal organization in social species may reveal the footprints of selective pressures to find balance between two major constraints: mitigation of the transmission of infection and population-level efficiency of division of labor. In this talk, we'll discuss a simple model that abstracts the organization of collaborative roles from different social insect taxa and contrasts their performance under disease-free and outbreak scenarios. We'll explore how infectious diseases may have selected for organizational strategies that maintain cohort stability and show why this trait would be unlikely to have been maintained in the absence of outbreak risks.


Joseph Johnson

(University of Michigan)
"A Dynamical Model for the Origin of Anisogamy"
The vast majority of multi-cellular organisms are anisogamous, meaning that male and female sex cells differ in size. It remains an open question how this asymmetric state evolved, presumably from the symmetric isogamous state where all gametes are roughly the same size (drawn from the same distribution). Here, we use tools from the study of nonlinear dynamical systems to develop a simple mathematical model for this phenomenon. Unlike some prior work, we do not assume the existence of mating types. We also model frequency dependent selection via “mean-field coupling,” whereby the likelihood that a gamete survives is an increasing function of its size relative to the population’s mean gamete size. Using theoretical analysis and numerical simulation, we demonstrate that this mean-referenced competition will almost inevitably result in a stable anisogamous equilibrium, and thus isogamy may naturally lead to anisogamy.




SMB2021
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Virtual conference of the Society for Mathematical Biology, 2021.