跨学科期刊《理论种群生物学》发表了关于种群生物学理论方面的文章，特别是在人口学、生态学、流行病学、进化和遗传学领域。重点是发展数学理论和模型，以增强对生物现象的理解。文章强调了这项工作对于推进生物学进步的动机和意义，依靠大量的数学努力来获得生物学洞察力。该杂志还介绍了直接影响人口生物学理论问题的经验结果以及计算和统计方法。

Theoretical Population Biology is an interdisciplinary journal that publishes articles on the theory of population biology, particularly in the fields of demography, ecology, epidemiology, evolution, and genetics. The focus is on developing mathematical theories and models to enhance the understanding of biological phenomena. The articles emphasize the motivation and significance of this work in advancing biological knowledge, relying on substantial mathematical efforts to gain biological insights. The journal also presents empirical results that directly impact theoretical issues in population biology, along with computational and statistical methods.

《理论种群生物学》是一本跨学科的期刊，专注于种群生物学理论的研究，尤其在人口学、生态学、流行病学、进化和遗传学等领域。期刊强调发展数学理论和模型，以加深对生物现象的理解。文章不仅探讨了推动生物学进步的动机和意义，还依赖大量的数学工作来获得生物学的洞察。此外，期刊还介绍了直接影响种群生物学理论问题的实证结果以及相关的计算和统计方法。

Theoretical Population Biology

The coalescent is a stochastic process representing ancestral lineages in a population undergoing neutral genetic drift. Originally defined for a well-mixed population, the coalescent has been adapted in various ways to accommodate spatial, age, and class structure, along with other features of real-world populations. To further extend the range of population structures to which coalescent theory applies, we formulate a coalescent process for a broad class of neutral drift models with arbitrary—but fixed—spatial, age, sex, and class structure, haploid or diploid genetics, and any fixed mating pattern. Here, the coalescent is represented as a random sequence of mappings C=Ctt=0∞ from a finite set G to itself. The set G represents the "sites" (in individuals, in particular locations and/or classes) at which these alleles can live. The state of the coalescent, Ct:G→G, maps each site g∈G to the site containing g's ancestor, t time-steps into the past. Using this representation, we define and analyze coalescence time, coalescence branch length, mutations prior to coalescence, and stationary probabilities of identity-by-descent and identity-by-state. For low mutation, we provide a recipe for computing identity-by-descent and identity-by-state probabilities via the coalescent. Applying our results to a diploid population with arbitrary sex ratio r, we find that measures of genetic dissimilarity, among any set of sites, are scaled by 4r(1−r) relative to the even sex ratio case.

Benjamin Allen

Alex McAvoy

The coalescent in finite populations with arbitrary, fixed structure

有限群体中具有任意固定结构的溯祖过程

Mutation accumulation (MA) experiments play an important role in understanding evolution. For microbial populations, such experiments often involve periods of population growth, such that a single individual can make a visible colony, followed by severe bottlenecks. Previous work has quantified the effect of positive and negative selection on MA experiments, demonstrating for example that with 20 generations of growth between bottlenecks, big-benefit mutations can be over-represented by a factor of five or more (Wahl and Agashe, 2022). This previous work assumed a deterministic model for population growth. We now develop a fully stochastic model, including realistic offspring distributions that incorporate genetic drift and allow for the loss of rare lineages. We demonstrate that when stochastic offspring distributions are considered, selection bias is even stronger than previously predicted. We describe several analytical and numerical methods that offer an accurate correction for the effects of selection on the observed distribution of fitness effects, describe the practical considerations in implementing each method, and demonstrate the use of this correction on simulated MA data.

Mojgan Ezadian

Lindi M Wahl

Stochastic offspring distributions amplify selection bias in mutation accumulation experiments

随机后代分布放大了突变积累实验中的选择偏倚

We model natural selection for or against an anti-parasite (or anti-predator) defense allele in a host (or prey) population that is structured into many demes. The defense behavior has a fitness cost for the actor compared to non defenders ("cheaters") in the same deme and locally reduces parasite growth rates. Hutzenthaler et al. (2022) have analytically derived a criterion for fixation or extinction of defenders in the limit of large populations, many demes, weak selection and slow migration. Here, we use both individual-based and diffusion-based simulation approaches to analyze related models. We find that the criterion still leads to accurate predictions for settings with finitely many demes and with various migration patterns. A key mechanism of providing a benefit of the defense trait is genetic drift due to randomness of reproduction and death events leading to between-deme differences in defense allele frequencies and host population sizes. We discuss an inclusive-fitness interpretation of this mechanism and present in-silico evidence that under these conditions a defense trait can be altruistic and still spread in a structured population.

Felix Jordan

Martin Hutzenthaler

Dirk Metzler

Selection for altruistic defense in structured populations

结构化种群中利他防御的选择

Infinitely many distinct trait values may arise in populations bearing quantitative traits, and modelling their population dynamics is thus a formidable task. While classical models assume fixed or infinite population size, models in which the total population size fluctuates due to demographic noise in births and deaths can behave qualitatively differently from constant or infinite population models due to density-dependent dynamics. In this paper, I present a stochastic field theory for the eco-evolutionary dynamics of finite populations bearing one-dimensional quantitative traits. I derive stochastic field equations that describe the evolution of population densities, trait frequencies, and the mean value of any trait in the population. These equations recover well-known results such as the replicator-mutator equation, Price equation, and gradient dynamics in the infinite population limit. For finite populations, the equations describe the intricate interplay between natural selection, noise-induced selection, eco-evolutionary feedback, and neutral genetic drift in determining evolutionary trajectories. My methods use ideas from statistical physics, calculus of variations, and SPDEs, providing alternative methods that complement the measure-theoretic martingale approach that is more common in the literature.

Ananda Shikhara Bhat

A stochastic field theory for the evolution of quantitative traits in finite populations

有限群体中数量性状演化的随机场论

Tree-killing bark beetle infestations are a cause of massive coniferous forest mortality impacting forest ecosystems and the ecosystem services they provide. Models predicting bark beetle outbreaks are crucial for forest management and conservation, necessitating studies of the effect of epidemiological traits on the probability and severity of outbreaks. Due to the aggregation behaviour of beetles and host tree defence, this epidemiological interaction is highly non-linear and outbreak behaviour remains poorly understood, motivating questions about when an outbreak can occur, what determines outbreak severity, and how aggregation behaviour modulates these quantities. Here, we apply the principle of distributed delays to create a novel and mathematically tractable model for beetle aggregation in an epidemiological framework. We derive the critical outbreak threshold for the beetle emergence rate, which is a quantity analogous to the basic reproductive ratio, R

Mahdi Salehzadeh

John M Stockie

Ailene MacPherson

Aggregation unveiled: A sequential modelling approach to bark beetle outbreaks

揭秘聚集：一种按序建模方法用于树皮甲虫爆发

Settlement is a critical transition in the life history of reef fish, and the timing of this event can have a strong effect on fitness. Key factors that influence settlement timing are predictable lunar cyclic variation in tidal currents, moonlight, and nocturnal predation risk as larvae transition from pelagic to benthic environments. However, populations typically display wide variation in the arrival of settlers over the lunar cycle. This variation is often hypothesized to result from unpredictable conditions in the pelagic environment and bet-hedging by spawning adults. Here, we consider the hypothesis that the timing of spawning and settlement is a strategic response to post-settlement competition. We use a game theoretic model to predict spawning and settlement distributions when fish face a tradeoff between minimizing density-independent predation risk while crossing the reef crest vs. avoiding high competitor density on settlement habitat. In general, we expect competition to spread spawning over time such that settlement is distributed around the lunar phase with the lowest predation risk, similar to an ideal free distribution in which competition spreads competitors across space. We examine the effects of overcompensating density dependence, age-dependent competition, and competition among daily settler cohorts. Our model predicts that even in the absence of stochastic variation in the larval environment, competition can result in qualitative divergence between spawning and settlement distributions. Furthermore, we show that if competitive strength increases with settler age, competition results in covariation between settler age and settlement date, with older larvae settling when predation risk is minimal. We predict that competition between daily cohorts delays peak settlement, with priority effects potentially selecting for a multimodal settlement distribution.

Abbreviation	Theor. Popul. Biol.
Journal Impact	1.06
Quartiles(Global)	MATHEMATICAL & COMPUTATIONAL BIOLOGY(Q4)

ISSN	0040-5809, 1096-0325
h-index	97

Publication Information	Publisher: Academic Press Inc.，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1970，Proportion of original research papers: 100.00%，Self Citation Rate:8.30%， Gold OA Rate: 54.55%
Average review cycle	网友分享经验：较慢,6-12周
Average recruitment ratio	网友分享经验：容易

Theoretical Population Biology

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The coalescent in finite populations with arbitrary, fixed structure

Stochastic offspring distributions amplify selection bias in mutation accumulation experiments

Selection for altruistic defense in structured populations

A stochastic field theory for the evolution of quantitative traits in finite populations

Aggregation unveiled: A sequential modelling approach to bark beetle outbreaks

Selection for altruistic defense in structured populations

Stochastic offspring distributions amplify selection bias in mutation accumulation experiments

Patterns of spawning and settlement of reef fishes as strategic responses to post-settlement competition

Aggregation unveiled: A sequential modelling approach to bark beetle outbreaks

A stochastic field theory for the evolution of quantitative traits in finite populations