Social evolution under demographic stochasticity

McLeod, David V.; Day, Troy

doi:10.1371/journal.pcbi.1006739

Cited by 8 publications

(41 citation statements)

References 35 publications

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“…We wish to use to understand how selection, stochasticity, and epidemiology interact to shape the evolution of sterility virulence. To do so, we adopt the approach we used elsewhere (McLeod and Day ), and ask what is the likelihood of observing the stochastic process in a particular state? If we are more likely to observe the process in a state in which strain i is most frequent, then we will say strain i is favored.…”

Section: Resultsmentioning

confidence: 99%

Why is sterility virulence most common in sexually transmitted infections? Examining the role of epidemiology

McLeod

Day

2019

Evolution

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Sterility virulence, or the reduction in host fecundity due to infection, occurs in many host–pathogen systems. Notably, sterility virulence is more common for sexually transmitted infections (STIs) than for directly transmitted pathogens, while other forms of virulence tend to be limited in STIs. This has led to the suggestion that sterility virulence may have an adaptive explanation. By focusing upon finite population models, we show that the observed patterns of sterility virulence can be explained by consideration of the epidemiological differences between STIs and directly transmitted pathogens. In particular, when pathogen transmission is predominantly density invariant (as for STIs), and mortality is density dependent, sterility virulence can be favored by demographic stochasticity, whereas if pathogen transmission is predominantly density dependent, as is common for most directly transmitted pathogens, sterility virulence is disfavored. We show these conclusions can hold even if there is a weak selective advantage to sterilizing.

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Section: Resultsmentioning

confidence: 99%

Why is sterility virulence most common in sexually transmitted infections? Examining the role of epidemiology

McLeod

Day

2019

Evolution

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“…This information is particularly valuable when examining population forecasts of species to climate extremes (Thibault and Brown 2008), and selection for optimal life history strategies for a given environment (Tuljapurkar et al 2009). As such, we argue that our second derivative approach is particularly valuable for active research in human demography ( e.g ., McLeod and Day (2019)), population ecology ( e.g ., Feng et al (2022)), and comparative biology ( e.g ., Compagnoni et al (2021)). We emphasize the applicability of second-order perturbation theory, such as Kato’s theory (Kato 2013), in describing the nonlinear response in structured populations.…”

Section: Discussionmentioning

confidence: 99%

From disturbances to nonlinear fitness and back

Tuljapurkar,

Jaggi,

Gascoigne

et al. 2023

Preprint

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A fundamental goal of Ecology is to predict how natural populations respond to disturbances. Accordingly, the last decades have witnessed key theoretical developments in stochastic demography and transient dynamics. However, both areas, have to date been largely disconnected. Here, we introduce an expression for the second derivatives of population growth rate with respect to demographic rates (e.g. survival-dependent state transitions and reproduction) with direct links to transient dynamics. We use this connection to develop a new mathematical framework showing how transient responses to pulse disturbances lead to a quantitative description of press disturbances. Second-derivatives of population growth rate with respect to said demographic rates are valuable as they quantify the degree of non-linear selection acting on demographic rates and how environments shape the long-term performance of populations. Whilst valuable, previous methods to quantify second-order derivatives have heavily relied on vector calculus- potentially obscuring important demographic processes connected to second-order derivatives. Here we offer an intuitive method using perturbation theory and our approach is valid for any discrete-time, st(age)-based structured population model. Importantly, our new method implicates an intimate relationship between the non-linear selection pressures acting on demographic rates with the emergent transient dynamics of populations over time. We showcase these relationships through mathematical proofs, connecting to Cohen's cumulative distance, and identifying a strong relationship between generation time across 439 unique plant and animal species (2690 population models). As such, this new method represents a valuable tool for population ecologists, comparative demographers, and conservation biologists to understand and protect structured populations in a changing world.

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“…In this case, an individual’s relative fitness ( Ω i ) is a distribution with the expected value, variance, and higher moments all contributing to evolution. (Eq 15 –see Methods) [7,37,57]. Consider, for purposes of illustration, a case in which the relative and absolute fitness variation of cooperators is completely independent of the fitness variation of non-cooperators so that , and the variances of each are equal ().…”

Section: Discussionmentioning

confidence: 99%

“…We could easily expand the right side of Eq 15 to higher central moments ( k = 2, 3 etc.). All else held equal, the k = 2 term () will be negative and potentially beneficial to the evolution of cooperation if it were a large, positive probability covariance [37,57]. The k = 3 term () will be positive, potentially boosting cooperation if a highly negative covariance.…”

Section: Methodsmentioning

confidence: 99%

Stochasticity and non-additivity expose hidden evolutionary pathways to cooperation

Fumagalli

Rice

2019

PLoS ONE

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Cooperation is widespread across the tree of life, with examples ranging from vertebrates to lichens to multispecies biofilms. The initial evolution of such cooperation is likely to involve interactions that produce non-additive fitness effects among small groups of individuals in local populations. However, most models for the evolution of cooperation have focused on genealogically related individuals, assume that the factors influencing individual fitness are deterministic, that populations are very large, and that the benefits of cooperation increase linearly with the number of cooperative interactions. Here we show that stochasticity and non-additive interactions can facilitate the evolution of cooperation in small local groups. We derive a generalized model for the evolution of cooperation and show that if cooperation reduces the variance in individual fitness (separate from its effect on average fitness), this can aid in the evolution of cooperation through directional stochastic effects. In addition, we show that the potential for the evolution of cooperation is influenced by non-additivity in benefits with cooperation being more likely to evolve when the marginal benefit of a cooperative act increases with the number of such acts. Our model compliments traditional cooperation models (kin selection, reciprocal cooperation, green beard effect, etc.) and applies to a broad range of cooperative interactions seen in nature.

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Social evolution under demographic stochasticity

Cited by 8 publications

References 35 publications

Why is sterility virulence most common in sexually transmitted infections? Examining the role of epidemiology

Why is sterility virulence most common in sexually transmitted infections? Examining the role of epidemiology

From disturbances to nonlinear fitness and back

Stochasticity and non-additivity expose hidden evolutionary pathways to cooperation

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