The Analysis of ontogenetic spectrum of heterogeneous population

Nikolay V. Glotov; Georgy Yu. Sofronov; Sergey M. Ivanov; Yulia G. Suetina; Lyudmila V. Prokopyeva; Alexey A. Teplykh

The Analysis of ontogenetic spectrum of heterogeneous population

Nikolay V. Glotov^*, Georgy Yu. Sofronov, Sergey M. Ivanov, Yulia G. Suetina, Lyudmila V. Prokopyeva, Alexey A. Teplykh

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The distribution of discrete ontogenetic states of individuals is usually spatially and temporally different within a population. If a sample from the population sample consists of several subsamples, the comparison of their ontogenetic spectra reveals heterogeneity of samples, i.e. different subsamples cannot be described by the same polynomial distribution. Therefore, the comparison of the samples using the aggregate data is not correct and tends to result in false inferences of biological importance. The paper proposes three methods for comparison of ontogenetic spectra of heterogeneous samples: a randomized variant of ANOVA, principal components analysis and ordinal regression analysis. The following approaches are exemplified in natural populations of cowberry Vaccinium vitis-idaea L. and epiphytic lichens Hypogymnia physodes (L.) Nyl. and Pseudevernia furfuracea (L.) Zopf.

Original language	English
Title of host publication	Biological systems, biodiversity, and stability of plant communities
Editors	Larissa I. Weisfeld, Anatoly I. Opalko, Nina A. Bome, Sarra A Bekuzarova
Place of Publication	Canada
Publisher	Apple Academic Press
Pages	443-461
Number of pages	19
ISBN (Print)	9781482263794
Publication status	Published - 2015

Cite this

@inbook{fc316ea5789446639ca8242a419be9c0,

title = "The Analysis of ontogenetic spectrum of heterogeneous population",

abstract = "The distribution of discrete ontogenetic states of individuals is usually spatially and temporally different within a population. If a sample from the population sample consists of several subsamples, the comparison of their ontogenetic spectra reveals heterogeneity of samples, i.e. different subsamples cannot be described by the same polynomial distribution. Therefore, the comparison of the samples using the aggregate data is not correct and tends to result in false inferences of biological importance. The paper proposes three methods for comparison of ontogenetic spectra of heterogeneous samples: a randomized variant of ANOVA, principal components analysis and ordinal regression analysis. The following approaches are exemplified in natural populations of cowberry Vaccinium vitis-idaea L. and epiphytic lichens Hypogymnia physodes (L.) Nyl. and Pseudevernia furfuracea (L.) Zopf.",

author = "Glotov, {Nikolay V.} and Sofronov, {Georgy Yu.} and Ivanov, {Sergey M.} and Suetina, {Yulia G.} and Prokopyeva, {Lyudmila V.} and Teplykh, {Alexey A.}",

year = "2015",

language = "English",

isbn = "9781482263794",

pages = "443--461",

editor = "Weisfeld, {Larissa I.} and Opalko, {Anatoly I.} and Bome, {Nina A.} and Bekuzarova, {Sarra A}",

booktitle = "Biological systems, biodiversity, and stability of plant communities",

publisher = "Apple Academic Press",

}

The Analysis of ontogenetic spectrum of heterogeneous population. / Glotov, Nikolay V.; Sofronov, Georgy Yu.; Ivanov, Sergey M. et al.

Biological systems, biodiversity, and stability of plant communities. ed. / Larissa I. Weisfeld; Anatoly I. Opalko; Nina A. Bome; Sarra A Bekuzarova. Canada : Apple Academic Press, 2015. p. 443-461.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - The Analysis of ontogenetic spectrum of heterogeneous population

AU - Glotov, Nikolay V.

AU - Sofronov, Georgy Yu.

AU - Ivanov, Sergey M.

AU - Suetina, Yulia G.

AU - Prokopyeva, Lyudmila V.

AU - Teplykh, Alexey A.

PY - 2015

Y1 - 2015

N2 - The distribution of discrete ontogenetic states of individuals is usually spatially and temporally different within a population. If a sample from the population sample consists of several subsamples, the comparison of their ontogenetic spectra reveals heterogeneity of samples, i.e. different subsamples cannot be described by the same polynomial distribution. Therefore, the comparison of the samples using the aggregate data is not correct and tends to result in false inferences of biological importance. The paper proposes three methods for comparison of ontogenetic spectra of heterogeneous samples: a randomized variant of ANOVA, principal components analysis and ordinal regression analysis. The following approaches are exemplified in natural populations of cowberry Vaccinium vitis-idaea L. and epiphytic lichens Hypogymnia physodes (L.) Nyl. and Pseudevernia furfuracea (L.) Zopf.

AB - The distribution of discrete ontogenetic states of individuals is usually spatially and temporally different within a population. If a sample from the population sample consists of several subsamples, the comparison of their ontogenetic spectra reveals heterogeneity of samples, i.e. different subsamples cannot be described by the same polynomial distribution. Therefore, the comparison of the samples using the aggregate data is not correct and tends to result in false inferences of biological importance. The paper proposes three methods for comparison of ontogenetic spectra of heterogeneous samples: a randomized variant of ANOVA, principal components analysis and ordinal regression analysis. The following approaches are exemplified in natural populations of cowberry Vaccinium vitis-idaea L. and epiphytic lichens Hypogymnia physodes (L.) Nyl. and Pseudevernia furfuracea (L.) Zopf.

UR - http://www.scopus.com/inward/record.url?scp=85076655142&partnerID=8YFLogxK

M3 - Chapter

SN - 9781482263794

SP - 443

EP - 461

BT - Biological systems, biodiversity, and stability of plant communities

A2 - Weisfeld, Larissa I.

A2 - Opalko, Anatoly I.

A2 - Bome, Nina A.

A2 - Bekuzarova, Sarra A

PB - Apple Academic Press

CY - Canada

ER -

The Analysis of ontogenetic spectrum of heterogeneous population

Abstract

Other files and links

Fingerprint

Cite this