EVOP Subgroup Contributed Talks

Tuesday, June 15 at 06:45am (PDT)
Tuesday, June 15 at 02:45pm (BST)
Tuesday, June 15 10:45pm (KST)

SMB2021 SMB2021 Follow Monday (Tuesday) during the "CT03" time block.
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Glenn Young

Kennesaw State University
" The interplay between costly reproduction and unpredictable environments shape the evolution of cooperative breeding"
All sexually reproducing organisms are faced with a fundamental decision: to invest valuable resources and energy in reproduction or in their own survival. This trade-off between reproduction and survival represents the 'cost of reproduction' and occurs across a diverse range of organisms. It is widely assumed that cooperative breeding behavior in vertebrates — when individuals care for young who are not their own — results in part from costly parental care. When caring for young is too costly, parents need help from related or unrelated individuals to successfully raise their offspring. Cooperatively breeding birds and mammals are also more commonly found in unpredictable environments than non-cooperative species, suggesting that decisions about when to breed or help may represent complex yet critical choices that depend on the energy individuals have available to dedicate to reproduction given the harshness of the current environment. Here, we introduce a novel, socially-tiered model of a cooperatively breeding species that incorporates the influence environmental stochasticity. Through numerical and analytical methods, we use this model to show that costly reproduction and environmental variability are compounding factors in the evolution and maintenance of cooperation.

Linh Huynh

Case Western Reserve University
"Identifying Birth and Death Rates Separately to Disambiguate Mechanisms for the Same Observed Population Dynamics"
In studying the dynamics of drug resistance, many models have used net growth rates of cell populations. However, we have discovered that cell populations with the same net growth rate but different birth and death rates have dramatically different tendencies to escape extinction and develop drug resistance. Therefore, it is important to identify birth and death rates separately. We develop a method to parse out birth and death rates from cell count time series of populations that follow logistic birth-death processes. We validate our method on in-silico data generated using the tau-leaping approximation. With separate birth and death rates, we infer different underlying mechanisms and drug effects for the same observed population dynamics. From our results, we propose to replace a one-dimensional 'fitness' phenotype (net growth rate) with a two-dimensional 'fitness vector' phenotype (birth and death rates).

Enrico Sandro Colizzi

Leiden University, Origins Center
"Evolution of genome architecture to divide labor through mutations"
Some forms of reproductive division of labor, e.g. multicellular organisation in eukaryotes, are coordinated through differential gene expression. Recent experiments have shown an alternative mechanism in antibiotic producing bacteria, where division of labor is coordinated by mutations. Somatic cells are generated from a germline through genomic deletions. These mutants produce antibiotics but their replication rate is strongly reduced. To understand the evolutionary origin of these findings, we have built a spatial model of bacteria evolution. Bacteria are given a genome, represented as beads on a string, which determines replication and antibiotic production. We find that bacterial genomes evolve to incorporate several fragile sites which increases the rate of deletions. Concurrently, genomes become structured such that fragile sites-induced deletions generate antibiotic-producing mutants from a non-producing germline. These mutants protect their colony from competitors, but they are unable to grow because they lack growth-promoting genes. Altogether, our model suggests a novel mechanism for the evolution of reproductive division of labor in Streptomyces through genome reorganization. Through this mechanism, social conflicts become impossible because altruists lack the genetic means to replicate. These results also help conceptualise the many examples of division of labor through genome manipulation found in other microorganisms and multicellular life.

Anudeep Surendran

University of Montreal, Canada
"Population dynamics with spatial structure and an Allee effect"
Population dynamics including a strong Allee effect describe the situation where long-term population survival or extinction depends on the initial population density. A simple mathematical model of an Allee effect is one where initial densities below the threshold lead to extinction, whereas initial densities above the threshold lead to survival. Mean-field models of population dynamics neglect spatial structure that can arise through short-range interactions, such as competition and dispersal. The influence of non-mean-field effects has not been studied in the presence of an Allee effect. To address this, we develop an individual-based model that incorporates both short-range interactions and an Allee effect. To explore the role of spatial structure we derive a mathematically tractable continuum approximation of the IBM in terms of the dynamics of spatial moments. In the limit of long-range interactions where the mean-field approximation holds, our modelling framework recovers the mean-field Allee threshold. We show that the Allee threshold is sensitive to spatial structure neglected by mean-field models. For example, there are cases where the mean-field model predicts extinction but the population actually survives. Through simulations we show that our new spatial moment dynamics model accurately captures the modified Allee threshold in the presence of spatial structure.

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