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

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dc.contributor.authorMorellato, L. Patricia C. [UNESP]
dc.contributor.authorAlberti, L. F. [UNESP]
dc.contributor.authorHudson, Irene L.
dc.contributor.authorHudson, I. L.
dc.contributor.authorKeatley, M. R.
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniv S Australia
dc.date.accessioned2023-07-29T11:51:31Z
dc.date.available2023-07-29T11:51:31Z
dc.date.issued2010-01-01
dc.description.abstractPhenology 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.en
dc.description.affiliationUniv Estadual Paulista, UNESP, Lab Fenol, Dept Bot,Grp Fenol & Dispersao Sementes, Rio Claro, SP, Brazil
dc.description.affiliationUniv S Australia, Sch Math & Stat, Adelaide, SA 5001, Australia
dc.description.affiliationUniv S Australia, Inst Sustainable Syst & Technol, Mawson Lakes, SA, Australia
dc.description.affiliationUnespUniv Estadual Paulista, UNESP, Lab Fenol, Dept Bot,Grp Fenol & Dispersao Sementes, Rio Claro, SP, Brazil
dc.format.extent339-359
dc.identifierhttp://dx.doi.org/10.1007/978-90-481-3335-2_16
dc.identifier.citationPhenological Research: Methods for Environmental and Climate Change Analysis. New York: Springer, p. 339-359, 2010.
dc.identifier.doi10.1007/978-90-481-3335-2_16
dc.identifier.urihttp://hdl.handle.net/11449/245321
dc.identifier.wosWOS:000273783300016
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofPhenological Research: Methods For Environmental And Climate Change Analysis
dc.sourceWeb of Science
dc.subjectCircular statistics
dc.subjectPhenology
dc.subjectPhenological methods
dc.subjectSeasonality
dc.subjectVector analysis
dc.titleApplications of Circular Statistics in Plant Phenology: a Case Studies Approachen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer

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