Why do traditional dispersion indices used for analysis of spatial distribution of plants tend to become obsolete?

It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subje...

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Published inPopulation ecology Vol. 64; no. 2; pp. 80 - 92
Main Authors Freitas Alves, Gabriella, Santana, Denise Garcia
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.04.2022
Blackwell Publishing Ltd
Subjects
Online AccessGet full text
ISSN1438-3896
1438-390X
DOI10.1002/1438-390X.12105

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Abstract It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subject is not recent, especially regarding the dispersion indices. The aim of this review was to conduct a critical and temporal analysis of these dispersion indices and test their effectiveness in determining the spatial distribution of Paepalanthus chiquitensis Herzog (Eriocaulaceae). This species is a meaningful model due to its occurrence in specific sites. The Lexis, Charlier, dispersion, relative variance, aggregation, Green, inverse of k of the negative binomial, Morisita, and standardized Morisita indices were limited to indicating that the individuals of the species are aggregate and did not provide information on neither spatial dimension (scale) where the aggregation occurs, nor the factors related to this aggregation. Although they have distinct magnitudes, the algebraic expressions of dispersion, relative variance, aggregation, Green, inverse of k, Morisita, and standardized Morisita indices exhibited a close relationship with each other and little progress from their precursors Lexis and Charlier. By disregarding the possibility of spatial dependence, these indices make it impossible to generate important hypotheses for the investigation of factors related to spatial structure. Therefore, they became obsolete and are falling into disuse. It should be noted that these measurements accomplished their role and contributed to science in times of limited technologies for spatial data. This review analyzed the main dispersion indices and coefficients published between 1915 and 1975 and applied to the analysis of the spatial distribution of plant species. Despite a long history in ecological studies, these measurements do not meet the growing interest of ecologists in identifying factors related to distribution patterns. By disregarding the possibility of spatial dependence and did not providing information on the spatial dimension (scale) where the patterns occur, these indices make it impossible to generate important hypotheses for the investigation of these factors and, therefore became obsolete.
AbstractList It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subject is not recent, especially regarding the dispersion indices. The aim of this review was to conduct a critical and temporal analysis of these dispersion indices and test their effectiveness in determining the spatial distribution of Paepalanthus chiquitensis Herzog (Eriocaulaceae). This species is a meaningful model due to its occurrence in specific sites. The Lexis, Charlier, dispersion, relative variance, aggregation, Green, inverse of k of the negative binomial, Morisita, and standardized Morisita indices were limited to indicating that the individuals of the species are aggregate and did not provide information on neither spatial dimension (scale) where the aggregation occurs, nor the factors related to this aggregation. Although they have distinct magnitudes, the algebraic expressions of dispersion, relative variance, aggregation, Green, inverse of k , Morisita, and standardized Morisita indices exhibited a close relationship with each other and little progress from their precursors Lexis and Charlier. By disregarding the possibility of spatial dependence, these indices make it impossible to generate important hypotheses for the investigation of factors related to spatial structure. Therefore, they became obsolete and are falling into disuse. It should be noted that these measurements accomplished their role and contributed to science in times of limited technologies for spatial data.
It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subject is not recent, especially regarding the dispersion indices. The aim of this review was to conduct a critical and temporal analysis of these dispersion indices and test their effectiveness in determining the spatial distribution of Paepalanthus chiquitensis Herzog (Eriocaulaceae). This species is a meaningful model due to its occurrence in specific sites. The Lexis, Charlier, dispersion, relative variance, aggregation, Green, inverse of k of the negative binomial, Morisita, and standardized Morisita indices were limited to indicating that the individuals of the species are aggregate and did not provide information on neither spatial dimension (scale) where the aggregation occurs, nor the factors related to this aggregation. Although they have distinct magnitudes, the algebraic expressions of dispersion, relative variance, aggregation, Green, inverse of k, Morisita, and standardized Morisita indices exhibited a close relationship with each other and little progress from their precursors Lexis and Charlier. By disregarding the possibility of spatial dependence, these indices make it impossible to generate important hypotheses for the investigation of factors related to spatial structure. Therefore, they became obsolete and are falling into disuse. It should be noted that these measurements accomplished their role and contributed to science in times of limited technologies for spatial data.
It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subject is not recent, especially regarding the dispersion indices. The aim of this review was to conduct a critical and temporal analysis of these dispersion indices and test their effectiveness in determining the spatial distribution of Paepalanthus chiquitensis Herzog (Eriocaulaceae). This species is a meaningful model due to its occurrence in specific sites. The Lexis, Charlier, dispersion, relative variance, aggregation, Green, inverse of k of the negative binomial, Morisita, and standardized Morisita indices were limited to indicating that the individuals of the species are aggregate and did not provide information on neither spatial dimension (scale) where the aggregation occurs, nor the factors related to this aggregation. Although they have distinct magnitudes, the algebraic expressions of dispersion, relative variance, aggregation, Green, inverse of k, Morisita, and standardized Morisita indices exhibited a close relationship with each other and little progress from their precursors Lexis and Charlier. By disregarding the possibility of spatial dependence, these indices make it impossible to generate important hypotheses for the investigation of factors related to spatial structure. Therefore, they became obsolete and are falling into disuse. It should be noted that these measurements accomplished their role and contributed to science in times of limited technologies for spatial data. This review analyzed the main dispersion indices and coefficients published between 1915 and 1975 and applied to the analysis of the spatial distribution of plant species. Despite a long history in ecological studies, these measurements do not meet the growing interest of ecologists in identifying factors related to distribution patterns. By disregarding the possibility of spatial dependence and did not providing information on the spatial dimension (scale) where the patterns occur, these indices make it impossible to generate important hypotheses for the investigation of these factors and, therefore became obsolete.
Author Santana, Denise Garcia
Freitas Alves, Gabriella
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Notes The copyright line for this article was changed on 11 March 2022 after original online publication.
Gabriella de Freitas Alves and Denise Garcia de Santana should be considered joint first author.
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Snippet It is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher...
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SubjectTerms Agglomeration
aggregate distribution
Aggregates
Aggregation
Dimensions
Dispersion
Distribution
Geographical distribution
Identification methods
Lexian Dispersion Theory
Morisita index
Paepalanthus
Paepalanthus chiquitensis
population ecology
researchers
Spatial analysis
Spatial data
spatial dependence
Spatial distribution
Variance
Title Why do traditional dispersion indices used for analysis of spatial distribution of plants tend to become obsolete?
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2F1438-390X.12105
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https://www.proquest.com/docview/2661046777
Volume 64
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