Theoretical Population Biology最新文献

{"title":"Importance of environmental productivity and diet quality in intraguild predation","authors":"Toshiyuki Namba ,&nbsp;Yasuhiro Takeuchi ,&nbsp;Malay Banerjee","doi":"10.1016/j.tpb.2025.03.004","DOIUrl":"10.1016/j.tpb.2025.03.004","url":null,"abstract":"<div><div>In the intricate network of ecological interactions, intraguild predation emerges as a fundamental community module incorporating omnivory. Classical equilibrium theory predicts the exclusion of the intraguild predator and prey at low and high environmental productivity, respectively, with the coexistence of both species occurring only at intermediate productivity levels. However, empirical studies challenge this theoretical prediction, particularly concerning the extinction of intraguild prey in highly productive environments. To address this enigmatic issue, Diehl (2003), Abrams and Fung (2010a) explore the impact of food quality and propose that low nutritional quality of the basal resource stabilizes omnivorous systems. Yet, the influence of intermediate consumer quality remains inadequately explored. This study employs analytical and numerical bifurcation studies to investigate the effects of the quality of two diet types. Various bifurcations, including supercritical and subcritical Hopf bifurcations, saddle-node bifurcations of periodic solutions, and transcritical bifurcations of periodic solutions are observed. These bifurcations are directly linked to the destinies of intraguild prey and predators. The results reveal that, in highly productive environments, it may not be the intermediate consumer but the omnivore that faces extinction. This discovery holds significant implications for the conservation and management of omnivorous systems.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"163 ","pages":"Pages 24-35"},"PeriodicalIF":1.2,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630906","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":"2025-03-08","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":"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":"2025-03-05","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":"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":"2025-02-11","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}

{"title":"A stochastic field theory for the evolution of quantitative traits in finite populations","authors":"Ananda Shikhara Bhat","doi":"10.1016/j.tpb.2024.10.003","DOIUrl":"10.1016/j.tpb.2024.10.003","url":null,"abstract":"<div><div>Infinitely many distinct trait values may arise in populations bearing quantitative traits, and modeling 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 work uses 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.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 1-12"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142751658","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":"Stochastic offspring distributions amplify selection bias in mutation accumulation experiments","authors":"Mojgan Ezadian,&nbsp;Lindi M. Wahl","doi":"10.1016/j.tpb.2024.11.002","DOIUrl":"10.1016/j.tpb.2024.11.002","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 25-33"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142822826","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":"Effect of competition on emergent phases and phase transitions in competitive systems","authors":"Shikun Wang ,&nbsp;Yuanshi Wang ,&nbsp;Hong Wu","doi":"10.1016/j.tpb.2024.12.003","DOIUrl":"10.1016/j.tpb.2024.12.003","url":null,"abstract":"<div><div>This paper considers Lotka–Volterra competitive systems characterizing laboratory experiment by Hu et al. (Science, 378:85-89, 2022). Using dynamical systems theory and projection method, we give theoretical analysis and numerical simulation on the model with four species by demonstrating equilibrium stability, periodic oscillation and chaotic fluctuation in the systems. It is shown that varying one competition strength could lead to emergent phases and phase transitions between stable full coexistence, stable partial coexistence, stable persistence of a unique species, persistent periodic oscillation, and persistent chaotic fluctuation in a smooth fashion. Here, the stronger the competition is, the less the number of stable coexisting species, or the higher the amplitude of periodic oscillation, or the more irregular the fluctuation. Our results are consistent with experimental observation and provide new insight. This work is important in understanding effect of competition on emergent phases and phase transitions in competitive systems.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 34-41"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142907704","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 impact of simultaneous infections on phage-host ecology","authors":"Jaye Sudweeks ,&nbsp;Christoph Hauert","doi":"10.1016/j.tpb.2024.12.002","DOIUrl":"10.1016/j.tpb.2024.12.002","url":null,"abstract":"<div><div>Phages use bacterial host resources to replicate, intrinsically linking phage and host survival. To understand phage dynamics, it is essential to understand phage-host ecology. A key step in this ecology is infection of bacterial hosts. Previous work has explored single and multiple, sequential infections. Here we focus on the theory of simultaneous infections, where multiple phages simultaneously attach to and infect one bacterial host cell. Simultaneous infections are a relevant infection dynamic to consider, especially at high phage densities when many phages attach to a single host cell in a short time window. For high bacterial growth rates, simultaneous infection can result in bi-stability: depending on initial conditions phages go extinct or co-exist with hosts, either at stable densities or through periodic oscillations of a stable limit cycle. This bears important consequences for phage applications such as phage therapy: phages can <em>persist</em> even though they cannot <em>invade</em>. Consequently, through spikes in phage densities it is possible to infect a bacterial population even when the phage basic reproductive number is less than one. In the regime of stable limit cycles, if timed right, only small densities of phage may be necessary.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 42-49"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142899634","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":"Selection for altruistic defense in structured populations","authors":"Felix Jordan ,&nbsp;Martin Hutzenthaler ,&nbsp;Dirk Metzler","doi":"10.1016/j.tpb.2024.11.001","DOIUrl":"10.1016/j.tpb.2024.11.001","url":null,"abstract":"<div><div>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.</div><div>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 <em>in-silico</em> evidence that under these conditions a defense trait can be altruistic and still spread in a structured population.</div></div>","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 13-24"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819603","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":"","authors":"","doi":"10.1016/j.tpb.2024.12.001","DOIUrl":"10.1016/j.tpb.2024.12.001","url":null,"abstract":"","PeriodicalId":49437,"journal":{"name":"Theoretical Population Biology","volume":"161 ","pages":"Pages 50-51"},"PeriodicalIF":1.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142899627","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}