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Journal articles on the topic 'Population structure'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Fruet, Cecilia, Ella Linxia Müller, Claude Loverdo, and Anne-Florence Bitbol. "Spatial structure facilitates evolutionary rescue by drug resistance." PLOS Computational Biology 21, no. 4 (2025): e1012861. https://doi.org/10.1371/journal.pcbi.1012861.

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Bacterial populations often have complex spatial structures, which can impact their evolution. Here, we study how spatial structure affects the evolution of antibiotic resistance in a bacterial population. We consider a minimal model of spatially structured populations where all demes (i.e., subpopulations) are identical and connected to each other by identical migration rates. We show that spatial structure can facilitate the survival of a bacterial population to antibiotic treatment, starting from a sensitive inoculum. Specifically, the bacterial population can be rescued if antibiotic resis

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2

Frean, Marcus, Paul B. Rainey, and Arne Traulsen. "The effect of population structure on the rate of evolution." Proceedings of the Royal Society B: Biological Sciences 280, no. 1762 (2013): 20130211. http://dx.doi.org/10.1098/rspb.2013.0211.

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Ecological factors exert a range of effects on the dynamics of the evolutionary process. A particularly marked effect comes from population structure, which can affect the probability that new mutations reach fixation. Our interest is in population structures, such as those depicted by ‘star graphs’, that amplify the effects of selection by further increasing the fixation probability of advantageous mutants and decreasing the fixation probability of disadvantageous mutants. The fact that star graphs increase the fixation probability of beneficial mutations has lead to the conclusion that evolu

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3

Pfaff, Carrie L., Rick A. Kittles, and Mark D. Shriver. "Adjusting for population structure in admixed populations." Genetic Epidemiology 22, no. 2 (2002): 196–201. http://dx.doi.org/10.1002/gepi.0126.

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4

Toksanbaeva, Mairash, and Raisa Popova. "Labor resources as a characteristic of labor potential and their structure." Population 25, no. 4 (2022): 151–62. http://dx.doi.org/10.19181/population.2022.25.4.13.

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One of the characteristics of labor potential is the ability to work among its carriers indiv i duals, groups and the population, by which are also studied other characteristics (demography, health, social and economic activity, professional competencies, etc.). On the basis of working capacity is determined the most general indicator of the labor potential of population, namely, labor resources. This indicator is structured according to a number of qualitative parameters. They make it possible to identify labor resources used in public production, as well as unused reserves. Their involvement

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5

Nazarova, Inna, and Roman Nesterov. "Clients of a HIV-service NPO: structure, typology, behavioral features." Population 26, no. 2 (2023): 153–64. http://dx.doi.org/10.19181/population.2023.26.2.13.

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Every year the number of registered HIV-infected people is increasing, which by the end of 2021 made 851.8 thousand people. In this connection the organization of work on prevention and treatment of HIV infection is relevant. The survey of 6313 representatives of the key group, i.e. clients of HIV servicing NPOs — Russians (4793 people) and citizens of other countries (1520 people) identified the main risk groups, for which it is necessary to work out the principal activity strategies connected with treatment and prevention. Every tenth client of the Charitable Foundation is HIV-infected and h

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6

Mukherjee, B. N., K. C. Malhotra, M. Roy, S. banerjee, H. Walter, and R. Chakraborty. "Genetic heterogeneity and population structure in eastern India: Red cell enzyme variability in ten Assamese populations." Zeitschrift für Morphologie und Anthropologie 77, no. 3 (1989): 287–96. http://dx.doi.org/10.1127/zma/77/1989/287.

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7

Skotarczak, E., P. Ćwiertnia, and T. Szwaczkowski. "Pedigree structure of American bison (Bison bison) population." Czech Journal of Animal Science 63, No. 12 (2018): 507–17. http://dx.doi.org/10.17221/120/2017-cjas.

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An effective realization of breeding programs in zoos is strongly determined by completeness of animal pedigree information. The knowledge of pedigree structure allows to maintain optimal genetic variability of a given population. The aim of this study was to estimate the parameters describing the pedigree structure of American bison housed in zoos in the context of further management of the population. Finally, 4269 American bison were analysed (1883 males, 2217 females, and 169 with unknown sex). The registered animals were born between years 1874 and 2013. The following pedigree parameters

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8

Lehoczky, István, Desiré L. Dalton, József Lanszki, et al. "Assessment of population structure in Hungarian otter populations." Journal of Mammalogy 96, no. 6 (2015): 1275–83. http://dx.doi.org/10.1093/jmammal/gyv136.

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9

Garbutt, K., and F. A. Bazzaz. "Population niche structure." Oecologia 72, no. 2 (1987): 291–96. http://dx.doi.org/10.1007/bf00379281.

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10

Ragsdale, Corey S. "REGIONAL POPULATION STRUCTURE IN POSTCLASSIC MEXICO." Ancient Mesoamerica 28, no. 2 (2017): 357–69. http://dx.doi.org/10.1017/s0956536117000013.

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AbstractThe majority of our knowledge about population structure in Mexico during the Postclassic period (a.d. 900–1520) is based on archaeological data. During this time, populations were in contact with each other through extensive trade networks and via the expansion of powerful empires in central and west Mexico. Though archaeological data provides a wealth of information about these relationships, little is known about the effects of these processes on population structure and biological, morphological variation or whether these effects vary across geographic regions. In this study, denta

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11

Yamasaki, Masanori, and Osamu Ideta. "Population structure in Japanese rice population." Breeding Science 63, no. 1 (2013): 49–57. http://dx.doi.org/10.1270/jsbbs.63.49.

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12

Siegenthaler, Timothy B., Kurt Lamour, and Zachariah R. Hansen. "Population structure of Phytophthora capsici in the state of Tennessee." Mycological Progress 21, no. 1 (2022): 159–66. http://dx.doi.org/10.1007/s11557-021-01769-7.

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AbstractThe plant pathogen Phytophthora capsici can be found all throughout the USA, and the population genetics of this organism have been studied within many of these states. Until now, no work has been done in the state of Tennessee to investigate the population structure and genetics of P. capsici found there. The population structure of P. capsici was explored using 296 isolates collected from five counties in Tennessee in 2004, 2007, 2018, and 2019. Samples were genotyped using 39 single nucleotide polymorphism (SNP) genetic markers. Multiple analyses indicate that the population structu

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13

Pérez-González, J., A. C. Frantz, J. Torres-Porras, L. Castillo, and J. Carranza. "Population structure, habitat features and genetic structure of managed red deer populations." European Journal of Wildlife Research 58, no. 6 (2012): 933–43. http://dx.doi.org/10.1007/s10344-012-0636-0.

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14

Triviño, Narda Jimena, Juan Guillermo Perez, Maria Eugenia Recio, et al. "Genetic Diversity and Population Structure ofBrachiariaSpecies and Breeding Populations." Crop Science 57, no. 5 (2017): 2633–44. http://dx.doi.org/10.2135/cropsci2017.01.0045.

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15

JARNE, P., and A. THÉRON. "Genetic structure in natural populations of flukes and snails: a practical approach and review." Parasitology 123, no. 7 (2001): 27–40. http://dx.doi.org/10.1017/s0031182001007715.

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Several aspects of the coevolutionary dynamics in host-parasite systems may be better quantified based on analyses of population structure using neutral genetic markers. This includes, for example, the migration rates of hosts and parasites. In this respect, the current situation, especially in fluke-snail systems is unsatisfactory, since basic population genetics data are lacking and the appropriate methodology has rarely been used. After reviewing the forces acting on population structure (e.g. genetic drift or the mating system) and how they can be analysed in models of structured populatio

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16

Makar, Svetlana, and Aziza Yarasheva. "Consumer behavior of Russians: opportunities and priorities." Population 25, no. 4 (2022): 68–78. http://dx.doi.org/10.19181/population.2022.25.4.6.

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The article examines the dynamics of changes in the volume of monetary income as a means for life of Russians, including implementation of their consumption priorities. It shows distribution of the population's expenditures on consumption of food and non-food products, alcoholic beverages and payment for services. The analysis is based on government statistics on 20 percent income groups, it covers a four-year period, including two years on the eve of the coronavirus pandemic and two years of its development. In the structure of the use of monetary income of the entire (without breakdown into

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17

Patterson, Nick, Alkes L. Price, and David Reich. "Population Structure and Eigenanalysis." PLoS Genetics 2, no. 12 (2006): e190. http://dx.doi.org/10.1371/journal.pgen.0020190.

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18

Muzzio, Marina, Josefina M. B. Motti, Paula B. Paz Sepulveda, et al. "Population structure in Argentina." PLOS ONE 13, no. 5 (2018): e0196325. http://dx.doi.org/10.1371/journal.pone.0196325.

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19

Lörtscher, Mathias, Martin Clalüna, and Adolf Scholl. "Genetic population structure of." Aquatic Sciences 60, no. 2 (1998): 118. http://dx.doi.org/10.1007/s000270050029.

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20

Brown, Brielin C., Nicolas L. Bray, and Lior Pachter. "Expression reflects population structure." PLOS Genetics 14, no. 12 (2018): e1007841. http://dx.doi.org/10.1371/journal.pgen.1007841.

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21

Pritchard, Jonathan K. "Deconstructing maize population structure." Nature Genetics 28, no. 3 (2001): 203–4. http://dx.doi.org/10.1038/90026.

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22

Tomiuk, J., and K. Wöhrmann. "Population growth and population structure of natural populations of Macrosiphum rosae (L.) (Hemiptera, Aphididae)." Zeitschrift für Angewandte Entomologie 90, no. 1-5 (2009): 464–73. http://dx.doi.org/10.1111/j.1439-0418.1980.tb03554.x.

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23

Rybakovsky, Oleg. "Structural waves of the population of Russia and its regions: issues of assessment and comparison." Population 25, no. 1 (2022): 65–79. http://dx.doi.org/10.19181/population.2022.25.1.6.

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The article deals with methodological and methodological issues of comparative analysis of age structures of the population, identification of the level of their unevenness due to structural demographic waves. The benchmark for comparison is the age structure of the population, built on the series of "Numbers living in this age interval" from the "Tables of mortality and life expectancy" of Rosstat. The coefficients existing in the practice of socio-economic analysis for measuring the structural differences of the series are considered. These coefficients are studied from the standpoint of the

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24

Avdeev, Yury A., Zinaida I. Sidorkina, and Valentina L. Ushakova. "Demographic development trends in the Russian Eastern Arctic." POPULATION 23, no. 3 (2020): 130–44. http://dx.doi.org/10.19181/population.2020.23.3.12.

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The paper considers the features of the demographic processes in the Russian Arctic zone by the example of Chukotka Autonomous Okrug in the period from 1939 to 2017. The future of the Arctic depends in large part on its demographic potential. What should be the population of the territory, how the space is organized, whether the population is needed, or enough of the watch organization of production: what should be done (or what not to do) so that the way of life of the native and the indigenous population remained in harmony with the environment, and at the same time solved large-scale tasks

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25

Dr. S. S. Motebennur, Dr S. S. Motebennur, and Sri Siddarudha Nilaya. "Spatial Analysis of Population Structure in Dharwad District Karnataka State." Indian Journal of Applied Research 3, no. 8 (2011): 324–27. http://dx.doi.org/10.15373/2249555x/aug2013/101.

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26

Koop, Jennifer A. H., Karen E. DeMatteo, Patricia G. Parker, and Noah K. Whiteman. "Birds are islands for parasites." Biology Letters 10, no. 8 (2014): 20140255. http://dx.doi.org/10.1098/rsbl.2014.0255.

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Understanding the mechanisms driving the extraordinary diversification of parasites is a major challenge in evolutionary biology. Co-speciation, one proposed mechanism that could contribute to this diversity is hypothesized to result from allopatric co-divergence of host–parasite populations. We found that island populations of the Galápagos hawk ( Buteo galapagoensis ) and a parasitic feather louse species ( Degeeriella regalis ) exhibit patterns of co-divergence across variable temporal and spatial scales. Hawks and lice showed nearly identical population genetic structure across the Galápag

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27

Pugliese, Andrea, and Fabio Milner. "A structured population model with diffusion in structure space." Journal of Mathematical Biology 77, no. 6-7 (2018): 2079–102. http://dx.doi.org/10.1007/s00285-018-1246-6.

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28

Tong, Yue W., Bernard J. Lewis, Wang M. Zhou, et al. "Genetic Diversity and Population Structure of Natural Pinus koraiensis Populations." Forests 11, no. 1 (2019): 39. http://dx.doi.org/10.3390/f11010039.

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Studying the genetic diversity and population structure of natural forest populations is essential for evaluating their ability to survive under future environmental changes and establishing conservation strategies. Pinus koraiensis is a conifer species with high ecological and economic value in Northeast China. However, its natural forests have been greatly reduced in recent years, mostly due to over exploitation and over utilization. Here, we evaluated the genetic diversity and population structure of seven populations of P. koraiensis located throughout its native distribution. A total of 2

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29

El Chartouni, Lea, Benoît Tisserant, Ali Siah, et al. "Genetic diversity and population structure in French populations ofMycosphaerella graminicola." Mycologia 103, no. 4 (2011): 764–74. http://dx.doi.org/10.3852/10-184.

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30

Westoby, M., and J. Howell. "Influence of Population Structure on Self-Thinning of Plant Populations." Journal of Ecology 74, no. 2 (1986): 343. http://dx.doi.org/10.2307/2260259.

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31

SÁNCHEZ NAVARRO, BEATRIZ, JUKKA JOKELA, NICO K. MICHIELS, and THOMAS G. D’SOUZA. "Population genetic structure of parthenogenetic flatworm populations with occasional sex." Freshwater Biology 58, no. 2 (2012): 416–29. http://dx.doi.org/10.1111/fwb.12070.

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32

Qiao, R., X. Li, X. Han, et al. "Population structure and genetic diversity of four Henan pig populations." Animal Genetics 50, no. 3 (2019): 262–65. http://dx.doi.org/10.1111/age.12775.

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33

Presley, Steven J. "Sex-based population structure of ectoparasites from Neotropical bats: SEX-BASED POPULATION STRUCTURE." Biological Journal of the Linnean Society 107, no. 1 (2012): 56–66. https://doi.org/10.5281/zenodo.13510869.

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34

Presley, Steven J. "Sex-based population structure of ectoparasites from Neotropical bats: SEX-BASED POPULATION STRUCTURE." Biological Journal of the Linnean Society 107, no. 1 (2012): 56–66. https://doi.org/10.5281/zenodo.13510869.

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35

Presley, Steven J. "Sex-based population structure of ectoparasites from Neotropical bats: SEX-BASED POPULATION STRUCTURE." Biological Journal of the Linnean Society 107, no. 1 (2012): 56–66. https://doi.org/10.5281/zenodo.13510869.

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36

Presley, Steven J. "Sex-based population structure of ectoparasites from Neotropical bats: SEX-BASED POPULATION STRUCTURE." Biological Journal of the Linnean Society 107, no. 1 (2012): 56–66. https://doi.org/10.5281/zenodo.13510869.

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37

Migranova, Lyudmila, and Vladislav Zharomsky. "Methods of estimating the Level and differentiation of population income." Population 23, no. 4 (2020): 26–39. http://dx.doi.org/10.19181/population.2020.23.4.3.

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On the basis of data for 2013-2017, the article shows changes in the level, structure and differentiation of the Russian population monetary income after the introduction by Rosstat in 2018 of a new methodology for calculating macro-economic indicators of population monetary income by separate income sources. Comparative analysis of the calculations made by the 1996 and 2018 methods shows significant changes only in the structure of population monetary income, mainly in such income items as work remuneration of employees and other cash receipts. Average per capita income changed slightly (+/-1

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38

Natsak, Organa. "Gender and demographic features of the labor market of the Republic of Tuva: trends and prospects." Population 24, no. 2 (2021): 120–30. http://dx.doi.org/10.19181/population.2021.24.2.11.

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The article analyzes the gender and demographic features of the labor market of the Republic of Tuva: the structure and rate of employment and unemployment in gender dimension and historic retrospect covering the period of Tuva People's Republic (1921-1944), the Soviet and post-Soviet stages of history. On the basis of statistical data it is shown that from 1945 began predominance of female population in the demographic structure of the republic that is characteristic of modern Tuva. The author makes an attempt to give a historic explanation of this turn. The article shows changes in the ratio

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39

Rybakovsky, Oleg. "The age structure of the population of the regions of Russia at the beginning of the 21st century: components of the formation." Population 26, no. 1 (2023): 4–15. http://dx.doi.org/10.19181/population.2023.26.1.1.

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In order to improve the management system of demographic processes, the article proposes and tests a non-standard methodology for studying the results of the demographic dynamics of the population of territories in the age context. The structure of their formation due to the main demographic components is disclosed. The main specific task is to assess as of mid-2021 for all regions of Russia — cumulative results of the demographic movement of the population accumulated over 28 years, which had an age of zero years in mid-1993. The proposed and tested methodology in the article allows us to cle

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40

Whitlock, Michael C. "Fixation Probability and Time in Subdivided Populations." Genetics 164, no. 2 (2003): 767–79. http://dx.doi.org/10.1093/genetics/164.2.767.

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AbstractNew alleles arising in a population by mutation ultimately are either fixed or lost. Either is possible, for both beneficial and deleterious alleles, because of stochastic changes in allele frequency due to genetic drift. Spatially structured populations differ from unstructured populations in the probability of fixation and the time that this fixation takes. Previous results have generally made many assumptions: that all demes contribute to the next generation in exact proportion to their current sizes, that new mutations are beneficial, and that new alleles have additive effects. In

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41

Hrytsenko, Yana, Noah M. Daniels, and Rachel S. Schwartz. "Determining population structure from k-mer frequencies." PeerJ 13 (March 5, 2025): e18939. https://doi.org/10.7717/peerj.18939.

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Background Understanding population structure within species provides information on connections among different populations and how they evolve over time. This knowledge is important for studies ranging from evolutionary biology to large-scale variant-trait association studies. Current approaches to determining population structure include model-based approaches, statistical approaches, and distance-based ancestry inference approaches. Methods In this work, we identify population structure from DNA sequence data using an alignment-free approach. We use the frequencies of short DNA substrings

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42

Ying, Yiping, Yong Chen, Longshan Lin, and Tianxian Gao. "Risks of ignoring fish population spatial structure in fisheries management." Canadian Journal of Fisheries and Aquatic Sciences 68, no. 12 (2011): 2101–20. http://dx.doi.org/10.1139/f2011-116.

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Ignorance of spatial structures in fisheries management may lead to unexpected risks of overexploitation. Based on the information about small yellow croaker ( Larimichthys polyactis ) off the coast of China, we simulated a fish population consisting of three subpopulations mixing at intermediate levels, which was considered in the “true” spatial structure of the population in this study. Three scenarios of population spatial structure were assumed in assessing and managing this simulated fishery: (i) metapopulation, which has the same structure as the “true” population; (ii) three independent

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43

Williams, Samuel M., Michael B. Bennett, Julian G. Pepperell, Jess A. T. Morgan, and Jennifer R. Ovenden. "Spatial genetic subdivision among populations of the highly migratory black marlin Istiompax indica within the central Indo-Pacific." Marine and Freshwater Research 67, no. 8 (2016): 1205. http://dx.doi.org/10.1071/mf14370.

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The black marlin Istiompax indica is a highly migratory species and as a result is expected to show little genetic population structure throughout its broad geographic range. Tissue samples from 183 I. indica were collected from three geographic regions within the central Indo-Pacific and analysed using mitochondrial and nuclear DNA markers. Nuclear genetic heterogeneity was found among populations in the south-western Pacific Ocean, eastern Indian Ocean and South China Sea (significant FST values of 0.013–0.037). Combining information from nuclear markers with published movement and reproduct

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44

Baltălungă, Monica Carmen. "Population Structure in the Ialomiţa Subcarpathians." Annals of Valahia University of Targoviste, Geographical Series 17, no. 1 (2017): 70–82. http://dx.doi.org/10.1515/avutgs-2017-0007.

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Abstract The analyisis of the demographic structures along with that of the main geo-demographic indicators is obligatory in any human geography study regarding a physical-geographic or administrative-territorial unit. The relation between various age groups, the dynamics of the ethnic, linguistic, or confessional structures, the variation of the socio-economic structure offers essential milestones for explaining the social, economic and cultural evolution of a region. Several specific indicators that can be calculated based on these types of structures lay at the basis of the demographic poli

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45

Okon, Emmanuel Okokondem. "Population structure and environmental degradation." Bussecon Review of Social Sciences (2687-2285) 1, no. 2 (2019): 18–27. http://dx.doi.org/10.36096/brss.v1i2.110.

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The primary objective of this paper is to test the hypothesis that the population age structure could contribute to carbon dioxide emission levels (environmental degradation) in Nigeria. Real income (Gross Domestic Product) was used as another determinant of CO2 emissions to test the EKC hypothesis in this study. Also, the autoregressive distributed lag (ARDL) econometric technique was applied in this paper to annual time series data from 1970 to 2018. The results show that age structure’s influence on the environment is significant. As expected, young adults (LOGYONG, i.e., ages 15-64) and ch

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46

Chirkov, S. N., and Yu N. Prikhod’ko. "GENETIC DIVERSITY AND POPULATION STRUCTURE." Sel'skokhozyaistvennaya Biologiya 50, no. 5 (2015): 529–39. http://dx.doi.org/10.15389/agrobiology.2015.5.529eng.

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47

Rejmanek, Marcel, and J. White. "The Population Structure of Vegetation." Bulletin of the Torrey Botanical Club 113, no. 4 (1986): 443. http://dx.doi.org/10.2307/2996439.

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48

Szathmáry, László, and Antónia Marcsik. "Symbolic trephinations and population structure." Memórias do Instituto Oswaldo Cruz 101, suppl 2 (2006): 129–32. http://dx.doi.org/10.1590/s0074-02762006001000019.

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49

Peter, Benjamin M. "Admixture, Population Structure, andF-Statistics." Genetics 202, no. 4 (2016): 1485–501. http://dx.doi.org/10.1534/genetics.115.183913.

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50

Watkinson, A. R., and J. White. "The Population Structure of Vegetation." Journal of Ecology 74, no. 4 (1986): 1221. http://dx.doi.org/10.2307/2260252.

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