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Titolo:
MEASUREMENT OF GENETIC-STRUCTURE WITHIN POPULATIONS USING MORANS SPATIAL AUTOCORRELATION STATISTICS
Autore:
EPPERSON BK; LI TQ;
Indirizzi:
MICHIGAN STATE UNIV,DEPT FORESTRY E LANSING MI 48824
Titolo Testata:
Proceedings of the National Academy of Sciences of the United Statesof America
fascicolo: 19, volume: 93, anno: 1996,
pagine: 10528 - 10532
SICI:
0027-8424(1996)93:19<10528:MOGWPU>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
AUTO-CORRELATION ANALYSIS; BY-DISTANCE MODEL; IMPATIENS-CAPENSIS; INFERENTIAL TOOL; GENOTYPES; PATTERNS; PLANT; FREQUENCIES; SELECTION; EUROPE;
Keywords:
SPATIAL PATTERNS; POPULATION STRUCTURE; DISPERSAL; GENE FLOW;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
42
Recensione:
Indirizzi per estratti:
Citazione:
B.K. Epperson e T.Q. Li, "MEASUREMENT OF GENETIC-STRUCTURE WITHIN POPULATIONS USING MORANS SPATIAL AUTOCORRELATION STATISTICS", Proceedings of the National Academy of Sciences of the United Statesof America, 93(19), 1996, pp. 10528-10532

Abstract

Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, canbe analyzed in detail by using spatial autocorrelation statistics, This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesistests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

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Documento generato il 29/11/20 alle ore 00:33:22