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dc.contributor.authorXin, H
dc.contributor.authorJackson, Tobias
dc.contributor.authorCao, Y
dc.contributor.authorZhang, H
dc.contributor.authorLin, Y
dc.contributor.authorShenkin, A
dc.date.accessioned2022-01-05T00:30:59Z
dc.date.available2022-01-05T00:30:59Z
dc.date.issued2021-01-01
dc.identifier.issn1007-662X
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/331946
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>Analysis of spatial patterns to describe the spatial correlation between a tree location and marks (i.e., structural variables), can reveal stand history, population dynamics, competition and symbiosis. However, most studies of spatial patterns have concentrated on tree location and tree sizes rather than on crown asymmetry especially with direct analysis among marks characterizing facilitation and competition among of trees, and thus cannot reveal the cause of the distributions of tree locations and quantitative marks. To explore the spatial correlation among quantitative and vectorial marks and their implication on population dynamics, we extracted vertical and horizontal marks (tree height and crown projection area) characterizing tree size, and a vectorial mark (crown displacement vector characterizing the crown asymmetry) using an airborne laser scanning point cloud obtained from two forest stands in Oxfordshire, UK. Quantitatively and vectorially marked spatial patterns were developed, with corresponding null models established for a significance test. We analyzed eight types of univariate and bivariate spatial patterns, after first proposing four types. The accuracy of the pattern analysis based on an algorithm-segmented point cloud was compared with that of a truly segmented point cloud. The algorithm-segmented point cloud managed to detect 70–86% of patterns correctly. The eight types of spatial patterns analyzed the spatial distribution of trees, the spatial correlation between tree size and facilitated or competitive interactions of sycamore and other species. These four types of univariate patterns jointly showed that, at smaller scales, the trees tend to be clustered, and taller, with larger crowns due to the detected facilitations among trees in the study area. The four types of bivariate patterns found that at smaller scales there are taller trees and more facilitation among sycamore and other species, while crown size is mostly homogeneous across scales. These results indicate that interspecific facilitation and competition mainly affect tree height in the study area. This work further confirms the connection of tree size with individual facilitation and competition, revealing the potential spatial structure that previously was hard to detect.</jats:p>
dc.publisherSpringer Science and Business Media LLC
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSpatial pattern analysis of forest trees based on the vectorial mark
dc.typeArticle
dc.publisher.departmentDepartment of Plant Sciences
dc.date.updated2021-12-26T08:06:52Z
prism.endingPage15
prism.publicationDate2021
prism.publicationNameJournal of Forestry Research
prism.startingPage1
dc.identifier.doi10.17863/CAM.79395
dcterms.dateAccepted2021-08-23
rioxxterms.versionofrecord10.1007/s11676-021-01417-6
rioxxterms.versionVoR
dc.contributor.orcidJackson, Tobias [0000-0001-8143-6161]
dc.identifier.eissn1993-0607
rioxxterms.typeJournal Article/Review
pubs.funder-project-idNatural Environment Research Council (NE/S010750/1)
cam.issuedOnline2021-12-04
cam.depositDate2021-12-26
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International