The Kota of the Nilgiri hills: a demographic study

1976 ◽  
Vol 8 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Aloke Kumar Ghosh
Keyword(s):  
Total Population ◽  
Random Mating ◽  
High Rate ◽  
Moderate Intensity ◽  
Biological Study ◽  
Isolated Population ◽  
Demographic Structure ◽  
Effective Population ◽  
Mating Population ◽  
The Village

A population–biological study of the Kota of the Nilgiri Hills was undertaken between May 1966 and January 1968. This paper discusses the demographic structure of the tribe and its genetic implications.The Kota is a small tribe of 1203 individuals distributed in only seven villages; it is an isolated population with a low rate of fertility and a high rate of infant mortality. The Kota is not a random mating population. The rate of consanguineous marriages is high and the coefficient of inbreeding is almost equal to the highest recorded value. Besides cousin marriages, marriage within the village is very much preferred. The admixture rate (0·29%) among the Kota is very low. The effective population size is only 28·87% of the total population. The coefficient of breeding isolation is 1·01, which indicates that genetic drift may produce important differentiation in this population. The data show that selection is acting with moderate intensity in this population.

scholarly journals GENETIC DRIFT AND ESTIMATION OF EFFECTIVE POPULATION SIZE

Genetics ◽  
1981 ◽  
Vol 98 (3) ◽  
pp. 625-640
Author(s):  
Masatoshi Nei ◽  
Fumio Tajima
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Random Mating ◽  
Effective Size ◽  
Isolated Population ◽  
Effective Population ◽  
Dacus Oleae ◽  
Census Size ◽  
Mating Population ◽  
Frequency Changes

ABSTRACT The statistical properties of the standardized variance of gene frequency changes (a quantity equivalent to Wright's inbreeding coefficient) in a random mating population are studied, and new formulae for estimating the effective population size are developed. The accuracy of the formulae depends on the ratio of sample size to effective size, the number of generations involved (t), and the number of loci or alleles used. It is shown that the standardized variance approximately follows the Χ2 distribution unless t is very large, and the confidence interval of the estimate of effective size can be obtained by using this property. Application of the formulae to data from an isolated population of Dacus oleae has shown that the effective size of this population is about one tenth of the minimum census size, though there was a possibility that the procedure of sampling genes was improper.

scholarly journals Coalescent theory for a Monoecious Random Mating Population with a Varying Size

2010 ◽  
Vol 47 (01) ◽  
pp. 41-57 ◽  
Author(s):  
Edward Pollak
Keyword(s):  
Markov Chain ◽  
Population Size ◽  
Effective Population Size ◽  
Random Sample ◽  
Random Mating ◽  
Coalescent Theory ◽  
Effective Population ◽  
Diploid Population ◽  
Mating Population ◽  
Population Sizes

Consider a monoecious diploid population with nonoverlapping generations, whose size varies with time according to an irreducible, aperiodic Markov chain with states x 1 N,…,x K N, where K ≪ N. It is assumed that all matings except for selfing are possible and equally probable. At time 0 a random sample of n ≪ N genes is taken. Given two successive population sizes x j N and x i N, the numbers of gametes that individual parents contribute to offspring can be shown to be exchangeable random variables distributed as G ij . Under minimal conditions on the first three moments of G ij for all i and j, a suitable effective population size N e is derived. Then if time is recorded in a backward direction in units of 2N e generations, it can be shown that coalescent theory holds.

scholarly journals Coalescent theory for a Monoecious Random Mating Population with a Varying Size

2010 ◽  
Vol 47 (1) ◽  
pp. 41-57 ◽  
Author(s):  
Edward Pollak
Keyword(s):  
Markov Chain ◽  
Population Size ◽  
Effective Population Size ◽  
Random Sample ◽  
Random Mating ◽  
Coalescent Theory ◽  
Effective Population ◽  
Diploid Population ◽  
Mating Population ◽  
Population Sizes

Consider a monoecious diploid population with nonoverlapping generations, whose size varies with time according to an irreducible, aperiodic Markov chain with states x1N,…,xKN, where K ≪ N. It is assumed that all matings except for selfing are possible and equally probable. At time 0 a random sample of n ≪ N genes is taken. Given two successive population sizes xjN and xiN, the numbers of gametes that individual parents contribute to offspring can be shown to be exchangeable random variables distributed as Gij. Under minimal conditions on the first three moments of Gij for all i and j, a suitable effective population size Ne is derived. Then if time is recorded in a backward direction in units of 2Ne generations, it can be shown that coalescent theory holds.

Population fragmentation causes inadequate gene flow and increases extinction risk

2017 ◽  
Author(s):  
Richard Frankham ◽  
Jonathan D. Ballou ◽  
Katherine Ralls ◽  
Mark D. B. Eldridge ◽  
Michele R. Dudash ◽  
...  
Keyword(s):  
Gene Flow ◽  
Extinction Risk ◽  
Random Mating ◽  
Large Population ◽  
Isolated Population ◽  
Population Fragmentation ◽  
Single Population ◽  
Total Size ◽  
Limited Gene Flow

Most species now have fragmented distributions, often with adverse genetic consequences. The genetic impacts of population fragmentation depend critically upon gene flow among fragments and their effective sizes. Fragmentation with cessation of gene flow is highly harmful in the long term, leading to greater inbreeding, increased loss of genetic diversity, decreased likelihood of evolutionary adaptation and elevated extinction risk, when compared to a single population of the same total size. The consequences of fragmentation with limited gene flow typically lie between those for a large population with random mating and isolated population fragments with no gene flow.

scholarly journals Average Number of Nucleotide Differences in a Sample From a Single Subpopulation: A Test for Population Subdivision

Genetics ◽  
1987 ◽  
Vol 117 (1) ◽  
pp. 149-153
Author(s):  
Curtis Strobeck
Keyword(s):  
Monte Carlo Simulation ◽  
Population Structure ◽  
Random Mating ◽  
Population Subdivision ◽  
Expected Number ◽  
Migration Rates ◽  
Mating Population ◽  
Unbiased Estimates ◽  
Increasing Function ◽  
Stepping Stone Model

ABSTRACT Unbiased estimates of θ = 4Nµ in a random mating population can be based on either the number of alleles or the average number of nucleotide differences in a sample. However, if there is population structure and the sample is drawn from a single subpopulation, these two estimates of θ behave differently. The expected number of alleles in a sample is an increasing function of the migration rates, whereas the expected average number of nucleotide differences is shown to be independent of the migration rates and equal to 4N  Tµ for a general model of population structure which includes both the island model and the circular stepping-stone model. This contrast in the behavior of these two estimates of θ is used as the basis of a test for population subdivision. Using a Monte-Carlo simulation developed so that independent samples from a single subpopulation could be obtained quickly, this test is shown to be a useful method to determine if there is population subdivision.

scholarly journals Estimating effective population size from samples of sequences: a bootstrap Monte Carlo integration method

1992 ◽  
Vol 60 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Joseph Felsenstein
Keyword(s):  
Monte Carlo ◽  
Maximum Likelihood ◽  
Population Size ◽  
Effective Population Size ◽  
Random Mating ◽  
Computational Effort ◽  
Monte Carlo Integration ◽  
Bootstrap Sampling ◽  
Effective Population ◽  
Full Data

SummaryWe would like to use maximum likelihood to estimate parameters such as the effective population size Ne, or, if we do not know mutation rates, the product 4Neμof mutation rate per site and effective population size. To compute the likelihood for a sample of unrecombined nucleotide sequences taken from a random-mating population it is necessary to sum over all genealogies that could have led to the sequences, computing for each one the probability that it would have yielded the sequences, and weighting each one by its prior probability. The genealogies vary in tree topology and in branch lengths. Although the likelihood and the prior are straightforward to compute, the summation over all genealogies seems at first sight hopelessly difficult. This paper reports that it is possible to carry out a Monte Carlo integration to evaluate the likelihoods pproximately. The method uses bootstrap sampling of sites to create data sets for each of which a maximum likelihood tree is estimated. The resulting trees are assumed to be sampled from a distribution whose height is proportional to the likelihood surface for the full data. That it will be so is dependent on a theorem which is not proven, but seems likely to be true if the sequences are not short. One can use the resulting estimated likelihood curve to make a maximum likelihood estimate of the parameter of interest, Ne or of 4Neμ. The method requires at least 100 times the computational effort required for estimation of a phylogeny by maximum likelihood, but is practical on today's work stations. The method does not at present have any way of dealing with recombination.

scholarly journals Detecting Linkage between a Trait and a Marker in a Random Mating Population without Pedigree Record

PLoS ONE ◽  
2009 ◽  
Vol 4 (3) ◽  
pp. e4956
Author(s):  
Shuhei Mano ◽  
Takaho A. Endo ◽  
Akira Oka ◽  
Akira Ozawa ◽  
Takashi Gojobori ◽  
...  
Keyword(s):  
Random Mating ◽  
Random Mating Population ◽  
Mating Population

scholarly journals Hubungan antara pendapatan disposebel dan pengeluaran konsumsi terhadap tabungan di Desa Sumokembangsri RW 01, Kecamatan Balongbendo Kabupaten Sidoarjo

2017 ◽  
Vol 1 (1) ◽  
pp. 73-78
Author(s):  
Mohamad Johan Efendi
Keyword(s):  
Path Analysis ◽  
Random Sampling ◽  
Total Population ◽  
Household Consumption ◽  
Disposable Income ◽  
Consumption Expenditure ◽  
Goods And Services ◽  
Analysis Technique ◽  
The Village ◽  
Practical Implications

This study aims to determine the correlation between income variable disposebel and consumption expenditure on savings variables in the village of sumokembangsri subdistrict balongbendo, district sidoarjo. Disposebel income is income for household consumption financing. Saving is one means of saving, whereas consume is the activity of purchasing goods and services that are based on the needs and desires with a predetermined exchange. total population of 504 heads of sample households with random sampling or random use of 20% of the population. with a sample of 101 family heads. Answering the problem of research and testing of research hypothesis used path analysis technique, with tool of application of SPSS version 16.0 The result of this research shows regression value that disposebel income have significant effect to consumption expenditure with value 0, 478, disposebel income have significant effect to saving with value 0, 401, consumption expenditure has significant effect on saving with value 0, 425. Practical implications The results of the study found that disposable income has a positive and significant effect on consumption and savings expenditure. This result indicates that the more disposebel income the consumption expenditure will increase as well as the household's inclination to save also increases.

Sign in / Sign up

Export Citation Format

Share Document