Applications of Circular Statistics in Plant Phenology: a Case Studies Approach

Detalhes bibliográficos
Autor(a) principal: Morellato, L. Patricia C. [UNESP]
Data de Publicação: 2010
Outros Autores: Alberti, L. F. [UNESP], Hudson, Irene L., Hudson, I. L., Keatley, M. R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-90-481-3335-2_16
http://hdl.handle.net/11449/245321
Resumo: Phenology is the study of recurring biological events and its relationship to climate. Circular statistics is an area of statistics not very much used by ecologists nor by other researchers from the biological sciences, and indeed not much visited, till recently in statistical science. Nevertheless, the connection between the evaluation of temporal, recurring events and the analysis of directional data have converged in several papers, and show circular statistics to be an outstanding tool by which to better understand plant phenology. The aim of this chapter is to assess applications for circular statistics in plant phenology and its potential for phenological data analysis in general. We do not discuss the mathematics of circular statistics, but discuss its actual and potential applications to plant phenology. We provide several examples at various levels of application: from generating circular phenological variables to the actual testing of hypotheses, say, for the existence of certain a priori seasonal patterns. Circular statistics has particular value and application when flowering onset (or fruiting) occurs almost continuously in an annual cycle and importantly in southern climates, where flowering time may not have a logical starting point, such as mid-winter dormancy. We conclude circular statistics applies well to phenological research where we want to test for relationships between flowering time and other phenological traits (e.g. shoot growth), or with functional traits such as plant height. It also allows us to group species into annual, supra-annual, irregular and continuous reproducers; to study seasonality in reproduction and growth; and to assess synchronization of species.
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spelling Applications of Circular Statistics in Plant Phenology: a Case Studies ApproachCircular statisticsPhenologyPhenological methodsSeasonalityVector analysisPhenology is the study of recurring biological events and its relationship to climate. Circular statistics is an area of statistics not very much used by ecologists nor by other researchers from the biological sciences, and indeed not much visited, till recently in statistical science. Nevertheless, the connection between the evaluation of temporal, recurring events and the analysis of directional data have converged in several papers, and show circular statistics to be an outstanding tool by which to better understand plant phenology. The aim of this chapter is to assess applications for circular statistics in plant phenology and its potential for phenological data analysis in general. We do not discuss the mathematics of circular statistics, but discuss its actual and potential applications to plant phenology. We provide several examples at various levels of application: from generating circular phenological variables to the actual testing of hypotheses, say, for the existence of certain a priori seasonal patterns. Circular statistics has particular value and application when flowering onset (or fruiting) occurs almost continuously in an annual cycle and importantly in southern climates, where flowering time may not have a logical starting point, such as mid-winter dormancy. We conclude circular statistics applies well to phenological research where we want to test for relationships between flowering time and other phenological traits (e.g. shoot growth), or with functional traits such as plant height. It also allows us to group species into annual, supra-annual, irregular and continuous reproducers; to study seasonality in reproduction and growth; and to assess synchronization of species.Univ Estadual Paulista, UNESP, Lab Fenol, Dept Bot,Grp Fenol & Dispersao Sementes, Rio Claro, SP, BrazilUniv S Australia, Sch Math & Stat, Adelaide, SA 5001, AustraliaUniv S Australia, Inst Sustainable Syst & Technol, Mawson Lakes, SA, AustraliaUniv Estadual Paulista, UNESP, Lab Fenol, Dept Bot,Grp Fenol & Dispersao Sementes, Rio Claro, SP, BrazilSpringerUniversidade Estadual Paulista (UNESP)Univ S AustraliaMorellato, L. Patricia C. [UNESP]Alberti, L. F. [UNESP]Hudson, Irene L.Hudson, I. L.Keatley, M. R.2023-07-29T11:51:31Z2023-07-29T11:51:31Z2010-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article339-359http://dx.doi.org/10.1007/978-90-481-3335-2_16Phenological Research: Methods for Environmental and Climate Change Analysis. New York: Springer, p. 339-359, 2010.http://hdl.handle.net/11449/24532110.1007/978-90-481-3335-2_16WOS:000273783300016Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPhenological Research: Methods For Environmental And Climate Change Analysisinfo:eu-repo/semantics/openAccess2023-07-29T11:51:31Zoai:repositorio.unesp.br:11449/245321Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-07-29T11:51:31Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
title Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
spellingShingle Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
Morellato, L. Patricia C. [UNESP]
Circular statistics
Phenology
Phenological methods
Seasonality
Vector analysis
title_short Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
title_full Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
title_fullStr Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
title_full_unstemmed Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
title_sort Applications of Circular Statistics in Plant Phenology: a Case Studies Approach
author Morellato, L. Patricia C. [UNESP]
author_facet Morellato, L. Patricia C. [UNESP]
Alberti, L. F. [UNESP]
Hudson, Irene L.
Hudson, I. L.
Keatley, M. R.
author_role author
author2 Alberti, L. F. [UNESP]
Hudson, Irene L.
Hudson, I. L.
Keatley, M. R.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Univ S Australia
dc.contributor.author.fl_str_mv Morellato, L. Patricia C. [UNESP]
Alberti, L. F. [UNESP]
Hudson, Irene L.
Hudson, I. L.
Keatley, M. R.
dc.subject.por.fl_str_mv Circular statistics
Phenology
Phenological methods
Seasonality
Vector analysis
topic Circular statistics
Phenology
Phenological methods
Seasonality
Vector analysis
description Phenology is the study of recurring biological events and its relationship to climate. Circular statistics is an area of statistics not very much used by ecologists nor by other researchers from the biological sciences, and indeed not much visited, till recently in statistical science. Nevertheless, the connection between the evaluation of temporal, recurring events and the analysis of directional data have converged in several papers, and show circular statistics to be an outstanding tool by which to better understand plant phenology. The aim of this chapter is to assess applications for circular statistics in plant phenology and its potential for phenological data analysis in general. We do not discuss the mathematics of circular statistics, but discuss its actual and potential applications to plant phenology. We provide several examples at various levels of application: from generating circular phenological variables to the actual testing of hypotheses, say, for the existence of certain a priori seasonal patterns. Circular statistics has particular value and application when flowering onset (or fruiting) occurs almost continuously in an annual cycle and importantly in southern climates, where flowering time may not have a logical starting point, such as mid-winter dormancy. We conclude circular statistics applies well to phenological research where we want to test for relationships between flowering time and other phenological traits (e.g. shoot growth), or with functional traits such as plant height. It also allows us to group species into annual, supra-annual, irregular and continuous reproducers; to study seasonality in reproduction and growth; and to assess synchronization of species.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01
2023-07-29T11:51:31Z
2023-07-29T11:51:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-90-481-3335-2_16
Phenological Research: Methods for Environmental and Climate Change Analysis. New York: Springer, p. 339-359, 2010.
http://hdl.handle.net/11449/245321
10.1007/978-90-481-3335-2_16
WOS:000273783300016
url http://dx.doi.org/10.1007/978-90-481-3335-2_16
http://hdl.handle.net/11449/245321
identifier_str_mv Phenological Research: Methods for Environmental and Climate Change Analysis. New York: Springer, p. 339-359, 2010.
10.1007/978-90-481-3335-2_16
WOS:000273783300016
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Phenological Research: Methods For Environmental And Climate Change Analysis
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 339-359
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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