Theoretical Population Biology最新文献

{"title":"A mathematical framework for time-variant multi-state kinship modelling","authors":"Joe W.B. Butterick,&nbsp;Peter W.F. Smith,&nbsp;Jakub Bijak,&nbsp;Jason Hilton","doi":"10.1016/j.tpb.2025.02.002","DOIUrl":"10.1016/j.tpb.2025.02.002","url":null,"abstract":"<div><div>Recent research on kinship modelling in demography has extended age-structured models (i) to include additional characteristics, or “stages” (multi-state kinship), and (ii) to time-variant situations. A wide variety of population structures can affect kinship networks. However, only one prior model has comprehensively considered such effects, and under specific assumptions relating to the nature of individuals’ stages. As such, the leading multi-state framework for kin is theoretically limited in scope, and moreover, has yet to be implemented under time-variant demographic rates. Generalising kinship models to encompass arbitrary population characteristics and extending them to time-dependent processes remain open challenges in demography.</div><div>This research proposes a methodology to extend multi-state kinship. We present a model which theoretically accounts for any stage, both in time-variant and time-invariant environments. Drawing from Markov processes, a concise mathematical alternative to existing theory is developed.</div><div>The benefits of our model are illustrated by an application where we define stages as spatial locations, exemplified by clusters of local authority districts (LADs) in England and Wales. Our results elucidate how spatial distribution – a demographic characteristic ubiquitous across (and between) societies – can affect an individual’s network of relatives.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 1-12"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A matrix-analytical sampling formula for time-homogeneous coalescent processes under the infinite sites mutation model","authors":"Asger Hobolth ,&nbsp;Simon Boitard ,&nbsp;Andreas Futschik ,&nbsp;Raphael Leblois","doi":"10.1016/j.tpb.2025.03.002","DOIUrl":"10.1016/j.tpb.2025.03.002","url":null,"abstract":"<div><div>In this paper we develop a general framework for calculating the probability of a genetic sample under a time-homogeneous coalescent process and the infinite sites mutation model. The evolutionary model that we consider can be characterized as a two-step procedure: A coalescent process that describes the ancestral relatedness of the samples and a sprinkling of mutations in separate sites on the ancestral tree according to a Poisson process. The coalescent process is defined using multivariate phase-type theory. The requirements are a rate matrix that determines the transition rates between the ancestral states, an initial state probability vector, and a reward matrix that informs about the characteristics of the ancestral states. For example, the reward matrix could contain information about the number of singleton, doubleton or higher-order lineages in the ancestral states. We analyze the probability generating function for the evolutionary model as a function of the initial state probability vector, the transition rate matrix, the reward matrix, and the mutation rate. The matrix-analytical expression of the probability generating function allows us to develop a general method for calculating the probability of a population genetic data set. We demonstrate that the method is computationally attractive for a small number of mutations and provide a simple and easy-to-implement algorithm for determining the probability of a sample from the evolutionary model. The method is computationally stable and only involves a single inverse matrix operation, matrix multiplications and matrix additions. We provide comprehensive understanding of the procedure by detailed calculations and discussions of several elementary examples. These examples include different sample representations (labeled samples and the site frequency spectrum) and different demographic and genetic models (the structured coalescent and the Beta-coalescent). We apply the sampling formula to calculate probabilities of spectra for the Kingman coalescent and the Beta-coalescent. Even for a small number of samples and mutations we find that the probabilities for spectra vary in huge orders of magnitudes. We compare the probabilities of the spectra to the values of Tajima’s <span><math><mi>D</mi></math></span>-statistics, and find that the <span><math><mi>D</mi></math></span>-statistic is a poor predictor for the probability of a spectrum. Finally, we investigate how the probabilities of the spectra vary with the parametrization of the Beta-coalescent.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 62-79"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143781871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Patterson-Price-Reich's rule of population structure analysis from genetic marker data","authors":"Jinliang Wang","doi":"10.1016/j.tpb.2025.03.001","DOIUrl":"10.1016/j.tpb.2025.03.001","url":null,"abstract":"<div><div>Delineating population structure from the marker genotypes of a sample of individuals is now routinely conducted in the fields of molecular ecology, evolution and conservation biology. Various Bayesian and likelihood methods as well as more general statistical methods (e.g. PCA) have been proposed to detect population structure, to assign sampled individuals to discrete clusters (subpopulations), and to estimate the admixture proportions of each sampled individual. Regardless of the methods, the power of a structure analysis depends on the strength of population structure (measured by <em>F_ST</em>) relative to the amount of marker information (measured by <em>NL</em>, where <em>N</em> and <em>L</em> are the numbers of sampled individuals and loci respectively). Patterson, Price and Reich (2006) proposed that population structure is unidentifiable when data size <em>D</em> = <em>NL</em> is smaller than <span><math><mrow><mn>1</mn><mo>/</mo><msubsup><mi>F</mi><mrow><mi>S</mi><mi>T</mi></mrow><mn>2</mn></msubsup></mrow></math></span> and quickly becomes identifiable easily with an increasing <em>D</em> or <em>F_ST</em> when <span><math><mrow><mi>D</mi><mo>&gt;</mo><mn>1</mn><mo>/</mo><msubsup><mi>F</mi><mrow><mi>S</mi><mi>T</mi></mrow><mn>2</mn></msubsup></mrow></math></span>. In this study, I investigated this phase change PPR rule by analysing both simulated genomic data and empirical data by four likelihood admixture analysis methods. The results show that the PPR rule is largely valid, but the accuracy of a structure analysis is also affected by the number of subpopulations <em>K</em>. A more complicated population structure with a larger <em>K</em> requires a larger <span><math><mrow><mi>N</mi><mi>L</mi><msubsup><mi>F</mi><mrow><mi>S</mi><mi>T</mi></mrow><mn>2</mn></msubsup></mrow></math></span> to resolve accurately. For a given <span><math><mrow><mi>N</mi><mi>L</mi><msubsup><mi>F</mi><mrow><mi>S</mi><mi>T</mi></mrow><mn>2</mn></msubsup></mrow></math></span> above the PPR threshold value of 1, increasing <em>L</em> and decreasing <em>N</em> is advantageous over increasing <em>N</em> and decreasing <em>L</em> in improving admixture estimation accuracy.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 13-23"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eco-evolutionary dynamics of anthelmintic resistance in soil-transmitted helminths","authors":"Swati Patel ,&nbsp;Kelsey Lyberger ,&nbsp;Carolin Vegvari ,&nbsp;Hayriye Gulbudak","doi":"10.1016/j.tpb.2025.03.006","DOIUrl":"10.1016/j.tpb.2025.03.006","url":null,"abstract":"<div><div>Anthelmintic resistance (AR) of soil-transmitted helminth parasites against the most widely available drugs is an ongoing concern for both human-infecting and livestock-infecting species. There has been substantial evidence of AR in livestock but less in humans, which may be due to a variety of reasons. In this paper, we develop an eco-evolutionary model that couples the life cycle of these parasites with their underlying evolution in a single biallelic genetic locus that confers resistance to treatment drugs. We determine the critical treatment frequency needed to effectively eliminate the population, for a fixed drug efficacy (without evolution) and use this to classify three qualitative distinct behaviors of the eco-evolutionary model. Then, we describe how aspects of the life cycle influence which qualitative outcome is achieved and the rate of spread of the resistance allele, comparing across parameterized models of human-infecting and livestock-infecting species. For all but one species, we find that lower fecundity rates and lower contact rates speed the spread of resistance, while lower larval death slows it down. The life cycle parameters of <em>Ancylostoma duodenale</em> and <em>Ostertagia circumcincta</em> are associated with the fastest and slowest spread of resistance, respectively. We discuss the mechanistic reason for these results.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 80-90"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connectivity, conservation and catch: Understanding the effects of dispersal between harvested and protected patches","authors":"Femke N. Reurik ,&nbsp;Juan Segura ,&nbsp;Frank M. Hilker","doi":"10.1016/j.tpb.2025.03.005","DOIUrl":"10.1016/j.tpb.2025.03.005","url":null,"abstract":"<div><div>Overharvesting is a pressing global problem, and spatial management, such as protecting designated areas, is one proposed solution. This study examines how connectivity (in terms of dispersal rate) between protected and harvested areas affects the asymptotic total population size and the asymptotic yield, which are key questions for conservation management and the design of protected areas. We utilise a two-patch model with heterogeneous habitat qualities, symmetric dispersal and density-dependent growth functions in both discrete and continuous time. One patch is subject to proportional harvesting, while the other one is protected.</div><div>Our results show that increased dispersal does not always increase the asymptotic total population size or the asymptotic yield. Depending on the circumstances, dispersal enables the protected patch to rescue the harvested patch from overexploitation, potentially increasing both total population size and yield. However, high levels of dispersal can also lead to a lower total population size or even cause extinction of both patches if harvesting pressure is strong. The population in the protected patch needs to have high reproductive potential and the protected patch needs to be the effectively larger patch in order to benefit monotonically from increased dispersal. These findings provide a fundamental understanding of how dispersal influences dynamics in fragmented landscapes under harvesting pressure.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 91-105"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143732485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial evolutionary public goods game theory applied to optimal resource allocation and defense strategies in herbaceous plants","authors":"Molly Creagar ,&nbsp;Richard Rebarber ,&nbsp;Brigitte Tenhumberg","doi":"10.1016/j.tpb.2025.02.003","DOIUrl":"10.1016/j.tpb.2025.02.003","url":null,"abstract":"<div><div>Empirical evidence suggests that the attractiveness of a plant to herbivores can be affected by the investment in defense by neighboring plants, as well as investment in defense by the focal plant. Thus, the payoff for allocating to defense may not only be influenced by the frequency and intensity of herbivory but also by defense strategies employed by other plants in the environment. We use a combination of spatial evolutionary game theory and stochastic dynamic programming to predict the proportion of plants in the population investing in defense (cooperators) and the proportion of plants that do not (defectors). Our model accounts for metabolic costs of maintenance of stored resources when predicting optimal resource allocation to growth, reproduction, and storage; this cost is not commonly accounted for in previous models. For both annual and perennial plants, our model predicts an evolutionarily stable proportion of cooperators and defectors (mixed stable strategy), but the proportion of cooperators is higher in a population of perennial plants than in a population of annual plants. We also show that including a metabolic cost of maintaining stored resources does not change the proportion of cooperators but does decrease plant fitness and allocation to overwinter storage.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 36-49"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exact calculation of the expected SFS in structured populations","authors":"Armando Arredondo ,&nbsp;Josué Corujo ,&nbsp;Camille Noûs ,&nbsp;Simon Boitard ,&nbsp;Lounès Chikhi ,&nbsp;Olivier Mazet","doi":"10.1016/j.tpb.2025.03.003","DOIUrl":"10.1016/j.tpb.2025.03.003","url":null,"abstract":"<div><div>The Site Frequency Spectrum (SFS), summary statistic of the distribution of derived allele frequencies in a sample of DNA sequences, provides information about genetic variation and can be used to make population inferences. The exact calculation of the expected SFS in a panmictic population under the infinite-site model of mutation has been known in the Markovian coalescent theory for decades, but its generalization to the structured coalescent is hampered by the almost exponential growth of the states space. We show here how to obtain this expected SFS as the solution of a linear system. More precisely, we propose a complete algorithmic procedure, from how to build a suitable state space and sort it, to how to take advantage of the sparsity of the rate matrix and to solve numerically the linear system using an iterative method. We then build a specialization for the simplest case of the symmetrical <span><math><mi>n</mi></math></span>-island model to arrive at a ready-to-use software called <em>SISiFS</em> from which a demographic parameters inference framework could easily be developed.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 50-61"},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catching a wave: On the suitability of traveling-wave solutions in epidemiological modeling","authors":"Anna M. Langmüller ,&nbsp;Joachim Hermisson ,&nbsp;Courtney C. Murdock ,&nbsp;Philipp W. Messer","doi":"10.1016/j.tpb.2024.12.004","DOIUrl":"10.1016/j.tpb.2024.12.004","url":null,"abstract":"<div><div>Ordinary differential equation models such as the classical SIR model are widely used in epidemiology to study and predict infectious disease dynamics. However, these models typically assume that populations are homogeneously mixed, ignoring possible variations in disease prevalence due to spatial heterogeneity. To address this issue, reaction–diffusion models have been proposed as an alternative approach to modeling spatially continuous populations in which individuals move in a diffusive manner. In this study, we explore the conditions under which such spatial structure must be explicitly considered to accurately predict disease spread, and when the assumption of homogeneous mixing remains adequate. In particular, we derive a critical threshold for the diffusion coefficient below which disease transmission dynamics exhibit spatial heterogeneity. We validate our analytical results with individual-based simulations of disease transmission across a two-dimensional continuous landscape. Using this framework, we further explore how key epidemiological parameters such as the probability of disease establishment, its maximum incidence, and its final epidemic size are affected by incorporating spatial structure into SI, SIS, and SIR models. We discuss the implications of our findings for epidemiological modeling and identify design considerations and limitations for spatial simulation models of disease dynamics.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"162 ","pages":"Pages 1-12"},"PeriodicalIF":1.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Species coexistence as an emergent effect of interacting mechanisms","authors":"Thomas Seidelmann,&nbsp;Sanaz Mostaghim","doi":"10.1016/j.tpb.2024.12.005","DOIUrl":"10.1016/j.tpb.2024.12.005","url":null,"abstract":"<div><div>Although extensively studied, the maintenance of biodiversity remains a highly debated and investigated topic of contemporary research in ecology. Several studies have quantified the contributions of various coexistence mechanisms to biodiversity. However, often stochastic individual-level interactions are abstracted away, or mechanisms are studied in isolation. The intertwined nature and reciprocal influences between mechanisms, as they arise from individual-level interactions, are therefore rarely considered. We propose a novel mechanistic simulation model grounded in neutral theory to capture and quantify emergent effects arising from such mechanism interactions. Three coexistence mechanisms are supported: storage effect, intransitivity, and resource partitioning. We show that basic neutral dynamics and related models of isolated mechanisms can be replicated. Beyond that, we observe difficult to predict, yet significant emergent effects for mechanism combinations. In some cases, coexistence times could be extended more than tenfold compared to the individual mechanisms’ performances. Our findings suggest that studies of individual coexistence mechanisms might be insufficient and indeed misleading for quantifying their overall impact on biodiversity. The particular combination of mechanisms and their interactions appear to be of vital importance.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"162 ","pages":"Pages 13-21"},"PeriodicalIF":1.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The central limit theorem for the number of mutations in the genealogy of a sample from a large population","authors":"Yun-Xin Fu","doi":"10.1016/j.tpb.2025.02.001","DOIUrl":"10.1016/j.tpb.2025.02.001","url":null,"abstract":"<div><div>The number <span><math><mi>K</mi></math></span> of mutations identifiable in a sample of <span><math><mi>n</mi></math></span> sequences from a large population is one of the most important summary statistics in population genetics and is ubiquitous in the analysis of DNA sequence data. <span><math><mi>K</mi></math></span> can be expressed as the sum of <span><math><mrow><mi>n</mi><mo>−</mo><mn>1</mn></mrow></math></span> independent geometric random variables. Consequently, its probability generating function was established long ago, yielding its well-known expectation and variance. However, the statistical properties of <span><math><mi>K</mi></math></span> is much less understood than those of the number of distinct alleles in a sample. This paper demonstrates that the central limit theorem holds for <span><math><mi>K</mi></math></span>, implying that <span><math><mi>K</mi></math></span> follows approximately a normal distribution when a large sample is drawn from a population evolving according to the Wright-Fisher model with a constant effective size, or according to the constant-in-state model, which allows population sizes to vary independently but bounded uniformly across different states of the coalescent process. Additionally, the skewness and kurtosis of <span><math><mi>K</mi></math></span> are derived, confirming that <span><math><mi>K</mi></math></span> has asymptotically the same skewness and kurtosis as a normal distribution. Furthermore, skewness converges at speed <span><math><mrow><mn>1</mn><mo>/</mo><msqrt><mrow><mo>ln</mo><mrow><mo>(</mo><mi>n</mi><mo>)</mo></mrow></mrow></msqrt></mrow></math></span> and while kurtosis at speed <span><math><mrow><mn>1</mn><mo>/</mo><mo>ln</mo><mrow><mo>(</mo><mi>n</mi><mo>)</mo></mrow></mrow></math></span>. Despite the overall convergence speed to normality is relatively slow, the distribution of <span><math><mi>K</mi></math></span> for a modest sample size is already not too far from normality, therefore the asymptotic normality may be sufficient for certain applications when the sample size is large enough.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"162 ","pages":"Pages 22-28"},"PeriodicalIF":1.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}