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Proceedings of the National Academy of... Dec 2022Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts...
Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.
Topics: Animals; Ecosystem; Population Dynamics; Climate Change; Arctic Regions; Weather; Arvicolinae; Population Density
PubMed: 36520669
DOI: 10.1073/pnas.2210144119 -
Philosophical Transactions of the Royal... Jan 2021One prominent feature of human culture is that different populations have different tools, technologies and cultural artefacts, and these unique toolkits can also differ... (Review)
Review
One prominent feature of human culture is that different populations have different tools, technologies and cultural artefacts, and these unique toolkits can also differ in size and complexity. Over the past few decades, researchers in the fields of prehistoric demography and cultural evolution have addressed a number of questions regarding variation in toolkit size and complexity across prehistoric and modern populations. Several factors have been proposed as possible explanations for this variation: in particular, the mobility of a population, the resources it uses, the volatility of its environment and the number of individuals in the population. Using a variety of methods, including empirical and ethnographic research, computational models and laboratory-based experiments, researchers have found disparate results regarding each hypothesis. These discordant findings have led to debate over the factors that most significantly influence toolkit size and composition. For instance, several computational, empirical and laboratory studies of food-producing populations have found a positive correlation between the number of individuals in a population and toolkit size, whereas similar studies of hunter-gatherer populations have found little evidence of such a link. In this paper, we conduct a comprehensive review of the literature in this field of study and propose corollaries and interdisciplinary approaches with the goal of reconciling dissimilar findings into a more comprehensive view of cultural toolkit variation. This article is part of the theme issue 'Cross-disciplinary approaches to prehistoric demography'.
Topics: Anthropology, Cultural; Cultural Evolution; Demography; Humans; Population Density
PubMed: 33250027
DOI: 10.1098/rstb.2019.0713 -
Heredity Jan 2022Linkage disequilibrium (LD) is the non-random association of alleles at different loci. Squared LD coefficients r (for phased genotypes) and [Formula: see text] (for...
Linkage disequilibrium (LD) is the non-random association of alleles at different loci. Squared LD coefficients r (for phased genotypes) and [Formula: see text] (for unphased genotypes) will converge to constants that are determined by the sample size, the recombination frequency, the effective population size and the mating system. LD can therefore be used for gene mapping and the estimation of effective population size. However, current methods work only with diploids. To resolve this problem, we here extend the linkage disequilibrium measures to include polysomic inheritance. We derive the values of r and [Formula: see text] at equilibrium state for various mating systems and different ploidy levels. For unlinked loci, [Formula: see text] for monoecious and dioecious (with random pairing) mating systems or [Formula: see text] for dioecious mating systems (with lifetime pairing), where f is the number of females in a half-sib family and η is a constant related to the ploidy level. We simulate the application of estimating N using unphased genotypes. We find that estimating N in polyploids requires similar sample sizes and numbers of loci as in diploids, with the main source of bias due to using 0.5 as the recombination frequency.
Topics: Genetics, Population; Genotype; Linkage Disequilibrium; Models, Genetic; Population Density
PubMed: 34983965
DOI: 10.1038/s41437-021-00482-1 -
Frontiers in Public Health 2021Saudi Arabia, a prominent Arabian country, has 35. 3 million persons living in 2.2 million square kilometers, undergone serious threats recently due to the COVID-19... (Review)
Review
BACKGROUND
Saudi Arabia, a prominent Arabian country, has 35. 3 million persons living in 2.2 million square kilometers, undergone serious threats recently due to the COVID-19 pandemic. With the built-in infrastructure and disciplined lifestyle, the country could address this pandemic.
AIMS
This analysis of COVID-19 cases in Saudi Arabia attempts to assess the situation, explore its global percentage share, percentage of population affected, and local distribution from the beginning of infection until recently, tracing historical developments and changes.
DATA AND METHODS
This analysis made use of data released by the Ministry of Health on a daily basis for a number of parameters. They are compiled on an excel sheet on a daily basis: the dataset has undergone rigorous analysis along with the trends and patterns; proportion to the world statistics and geographic distribution.
RESULTS
COVID-19 spread rapidly in the country with periodic variations, during June-August, 2020. But, recoveries accelerated in the period, thus bridging the gap of increasing infections. In comparison with the world statistics, the country proportions are lower, while the percentage of population affected is similar. It appears that the intensity varied across all 13 administrative areas.
CONCLUSION
COVID-19 transmission since March 2020 is considered to be widespread, creating excess burden on the public health system, delineated into stages (early infection, rapid spread, declining, stabilizing, and second wave). Control measures are set, stage-wise, without impinging upon normal life but to ensure that the proportion of globally affected persons is lesser than the population share: credit goes to the Ministry of Health. Area-wise spread depends largely on population density and development infrastructure dimensions. Ultimately, the disciplined life in compliance with law and order paved the way for effective program implementation and epidemic control.
Topics: COVID-19; Humans; Pandemics; Population Density; SARS-CoV-2; Saudi Arabia
PubMed: 35186861
DOI: 10.3389/fpubh.2021.736942 -
PloS One 2020Human societies exhibit a diversity of social organizations that vary widely in size, structure, and complexity. Today, human sociopolitical complexity ranges from... (Comparative Study)
Comparative Study
Human societies exhibit a diversity of social organizations that vary widely in size, structure, and complexity. Today, human sociopolitical complexity ranges from stateless small-scale societies of a few hundred individuals to complex states of millions, most of this diversity evolving only over the last few hundred years. Understanding how sociopolitical complexity evolved over time and space has always been a central focus of the social sciences. Yet despite this long-term interest, a quantitative understanding of how sociopolitical complexity varies across cultures is not well developed. Here we use scaling analysis to examine the statistical structure of a global sample of over a thousand human societies across multiple levels of sociopolitical complexity. First, we show that levels of sociopolitical complexity are self-similar as adjacent levels of jurisdictional hierarchy see a four-fold increase in population size, a two-fold increase in geographic range, and therefore a doubling of population density. Second, we show how this self-similarity leads to the scaling of population size and geographic range. As societies increase in complexity population density is reconfigured in space and quantified by scaling parameters. However, there is considerable overlap in population metrics across all scales suggesting that while more complex societies tend to have larger and denser populations, larger and denser populations are not necessarily more complex.
Topics: Civilization; Cultural Diversity; Ethnology; Government; Humans; Leadership; Models, Organizational; Politics; Population Density; Social Sciences; Social Theory
PubMed: 32614836
DOI: 10.1371/journal.pone.0234615 -
Trends in Ecology & Evolution Oct 2023Our ability to assess the threat posed by the genetic load to small and declining populations has been greatly improved by advances in genome sequencing and... (Review)
Review
Our ability to assess the threat posed by the genetic load to small and declining populations has been greatly improved by advances in genome sequencing and computational approaches. Yet, considerable confusion remains around the definitions of the genetic load and its dynamics, and how they impact individual fitness and population viability. We illustrate how both selective purging and drift affect the distribution of deleterious mutations during population size decline and recovery. We show how this impacts the composition of the genetic load, and how this affects the extinction risk and recovery potential of populations. We propose a framework to examine load dynamics and advocate for the introduction of load estimates in the management of endangered populations.
Topics: Genetics, Population; Genetic Load; Population Density; Inbreeding; Genetic Variation
PubMed: 37344276
DOI: 10.1016/j.tree.2023.05.008 -
Systematic Biology Aug 2022Balance indices that quantify the symmetry of branching events and the compactness of trees are widely used to compare evolutionary processes or tree-generating...
Balance indices that quantify the symmetry of branching events and the compactness of trees are widely used to compare evolutionary processes or tree-generating algorithms. Yet, existing indices are not defined for all rooted trees, are unreliable for comparing trees with different numbers of leaves, and are sensitive to the presence or absence of rare types. The contributions of this article are twofold. First, we define a new class of robust, universal tree balance indices. These indices take a form similar to Colless' index but can account for population sizes, are defined for trees with any degree distribution, and enable meaningful comparison of trees with different numbers of leaves. Second, we show that for bifurcating and all other full m-ary cladograms (in which every internal node has the same out-degree), one such Colless-like index is equivalent to the normalized reciprocal of Sackin's index. Hence, we both unify and generalize the two most popular existing tree balance indices. Our indices are intrinsically normalized and can be computed in linear time. We conclude that these more widely applicable indices have the potential to supersede those in current use. [Cancer; clone tree; Colless index; Sackin index; species tree; tree balance.].
Topics: Algorithms; Biological Evolution; Phylogeny; Population Density
PubMed: 35412638
DOI: 10.1093/sysbio/syac027 -
PLoS Computational Biology Apr 2022Population size has long been considered an important driver of cultural diversity and complexity. Results from population genetics, however, demonstrate that in...
Population size has long been considered an important driver of cultural diversity and complexity. Results from population genetics, however, demonstrate that in populations with complex demographic structure or mode of inheritance, it is not the census population size, N, but the effective size of a population, Ne, that determines important evolutionary parameters. Here, we examine the concept of effective population size for traits that evolve culturally, through processes of innovation and social learning. We use mathematical and computational modeling approaches to investigate how cultural Ne and levels of diversity depend on (1) the way traits are learned, (2) population connectedness, and (3) social network structure. We show that one-to-many and frequency-dependent transmission can temporally or permanently lower effective population size compared to census numbers. We caution that migration and cultural exchange can have counter-intuitive effects on Ne. Network density in random networks leaves Ne unchanged, scale-free networks tend to decrease and small-world networks tend to increase Ne compared to census numbers. For one-to-many transmission and different network structures, larger effective sizes are closely associated with higher cultural diversity. For connectedness, however, even small amounts of migration and cultural exchange result in high diversity independently of Ne. Extending previous work, our results highlight the importance of carefully defining effective population size for cultural systems and show that inferring Ne requires detailed knowledge about underlying cultural and demographic processes.
Topics: Biological Evolution; Computer Simulation; Genetics, Population; Phenotype; Population Density
PubMed: 35395004
DOI: 10.1371/journal.pcbi.1009430 -
Biological Reviews of the Cambridge... Apr 2022Dispersal is a key demographic process involving three stages: emigration, transience and settlement; each of which is influenced by individual, social and environmental... (Review)
Review
Dispersal is a key demographic process involving three stages: emigration, transience and settlement; each of which is influenced by individual, social and environmental determinants. An integrated understanding of species dispersal is essential for demographic modelling and conservation planning. Here, we review the dispersal patterns and determinants documented in the scientific literature for the grey wolf (Canis lupus) across its distribution range. We showed a surprisingly high variability within and among study areas on all dispersal parameters - dispersal rate, direction, distance, duration and success. We found that such large variability is due to multiple individual, social and environmental determinants, but also due to previously overlooked methodological research issues. We revealed a potential non-linear relationship between dispersal rate and population density, with dispersal rate higher at both ends of the gradient of population density. We found that human-caused mortality reduces distance, duration and success of dispersal events. Furthermore, dispersers avoid interaction with humans, and highly exposed areas like agricultural lands hamper population connectivity in many cases. We identified numerous methodological research problems that make it difficult to obtain robust estimates of dispersal parameters and robust inferences on dispersal patterns and their determinants. In particular, analyses where confounding factors were not accounted for led to substantial knowledge gaps on all aspects of dispersal in an otherwise much-studied species. Our understanding of wolf biology and management would significantly benefit if wolf dispersal studies reported the results and possible factors affecting wolf dispersal more transparently.
Topics: Animals; Population Density; Wolves
PubMed: 34664396
DOI: 10.1111/brv.12807 -
Philosophical Transactions of the Royal... Mar 2023The emergence of human societies with complex language and cumulative culture is considered a major evolutionary transition. Why such a high degree of cumulative culture...
The emergence of human societies with complex language and cumulative culture is considered a major evolutionary transition. Why such a high degree of cumulative culture is unique to humans is perplexing given the potential fitness advantages of cultural accumulation. Here, Boyd & Richerson's (1996 Why culture is common, but cultural evolution is rare. , 77-93) discrete-cultural-trait model is extended to incorporate arbitrarily strong selection; conformist, anti-conformist and unbiased frequency-dependent transmission; random and periodic environmental variation; finite population size; and multiple 'skill levels.' From their infinite-population-size model with success bias and a single skill level, Boyd and Richerson concluded that social learning is favoured over individual learning under a wider range of conditions when social learning is initially common than initially rare. We find that this holds only if the number of individuals observed by a social learner is sufficiently small, but with a finite population and/or a combination of success-biased and conformist or unbiased transmission, this result holds with larger . Assuming social learning has reached fixation, the increase in a population's mean skill level is lower if cumulative culture is initially absent than initially present, if population size is finite, or if cultural transmission has a frequency-dependent component. Hence, multiple barriers to cultural accumulation may explain its rarity. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.
Topics: Humans; Cultural Evolution; Learning; Social Learning; Biological Evolution; Population Density
PubMed: 36688392
DOI: 10.1098/rstb.2021.0400