Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data

Key message: Developed species-specific allometric equations using terrestrial laser scanning (TLS). Found significant species-specific differences in branch biomass allocation. Introduced a non-destructive method for estimating urban tree biomass. Abstract: Urban trees contribute to climate change...

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Autores: Parhizgar, Leila, Pattnaik, Nayanesh, Yazdi, Hadi, Qiguan, Shu, Pauleit, Stephan, Rahman, Mohammad A., Ludwig, Ferdinand, Pretzsch, Hans, Rötzer, Thomas
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2025
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/397749
Acesso em linha:http://hdl.handle.net/10261/397749
https://api.elsevier.com/content/abstract/scopus_id/105007549635
Access Level:Acceso aberto
Palavra-chave:Urban Trees
Allometric Relationships
Branch Biomass
QSM
TLS
TreeML-Data
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repository_id_str
spelling Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) dataParhizgar, LeilaPattnaik, NayaneshYazdi, HadiQiguan, ShuPauleit, StephanRahman, Mohammad A.Ludwig, FerdinandPretzsch, HansRötzer, ThomasUrban TreesAllometric RelationshipsBranch BiomassQSMTLSTreeML-DataKey message: Developed species-specific allometric equations using terrestrial laser scanning (TLS). Found significant species-specific differences in branch biomass allocation. Introduced a non-destructive method for estimating urban tree biomass. Abstract: Urban trees contribute to climate change adaptation by providing multiple ecosystem services, including carbon sequestration. Yet accurate information about above-ground biomass, particularly branch biomass, is scarce. This study aimed to develop allometric models for estimating branch biomass for ten common European urban tree species using terrestrial laser scanning (TLS) and quantitative structure models (QSM) data. Conducted in Munich, the study analyzed 3,283 trees, using structural variables such as diameter at breast height (dbh), height, and crown diameter. The dbh of trees in the dataset reached up to 0.8 m, with mean above-ground biomass ranging from 550 to 1.496 kg C, and branch biomass from 32.2 to 164.5 kg C. The results confirmed that dbh was the strongest predictor of branch biomass (r = 0.69–0.9), and adding height improved model accuracy (R<sup>2</sup> = 0.69–0.93). Species-specific models revealed significant variations, with R. pseudoacacia showing the highest branch biomass when standardized by tree height, and P. nigra 'italica' the lowest. Conversely, when standardized by dbh, P. acerifolia showed the highest branch biomass and C. betulus the lowest. Comparisons with established forest tree models revealed that the developed allometric models tend to underestimate branch biomass for most species, with deviations ranging from 1 to 36%, reflecting unique growth forms and urban environmental conditions. The study highlights the need for species-specific allometric models to improve assessments of ecosystem services provided by urban trees.We thank the Deutsche Forschungsgemeinschaft (DFG) for funding the project Research Training Group Urban Green Infrastructure (Grant Number: 437788427 – RTG 2679; RTG UGI). We thank our colleagues and collaborators for their contributions.Peer reviewedSpringerGerman Research FoundationParhizgar, Leila [0009-0003-2875-5376]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/397749https://api.elsevier.com/content/abstract/scopus_id/105007549635reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1007/s00468-025-02637-7https://doi.org/10.1007/s00468-025-02637-7Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3977492026-05-22T06:33:51Z
dc.title.none.fl_str_mv Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
title Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
spellingShingle Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
Parhizgar, Leila
Urban Trees
Allometric Relationships
Branch Biomass
QSM
TLS
TreeML-Data
title_short Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
title_full Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
title_fullStr Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
title_full_unstemmed Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
title_sort Branch biomass allometries for urban tree species based on terrestrial laser scanning (TLS) data
dc.creator.none.fl_str_mv Parhizgar, Leila
Pattnaik, Nayanesh
Yazdi, Hadi
Qiguan, Shu
Pauleit, Stephan
Rahman, Mohammad A.
Ludwig, Ferdinand
Pretzsch, Hans
Rötzer, Thomas
author Parhizgar, Leila
author_facet Parhizgar, Leila
Pattnaik, Nayanesh
Yazdi, Hadi
Qiguan, Shu
Pauleit, Stephan
Rahman, Mohammad A.
Ludwig, Ferdinand
Pretzsch, Hans
Rötzer, Thomas
author_role author
author2 Pattnaik, Nayanesh
Yazdi, Hadi
Qiguan, Shu
Pauleit, Stephan
Rahman, Mohammad A.
Ludwig, Ferdinand
Pretzsch, Hans
Rötzer, Thomas
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv German Research Foundation
Parhizgar, Leila [0009-0003-2875-5376]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Urban Trees
Allometric Relationships
Branch Biomass
QSM
TLS
TreeML-Data
topic Urban Trees
Allometric Relationships
Branch Biomass
QSM
TLS
TreeML-Data
description Key message: Developed species-specific allometric equations using terrestrial laser scanning (TLS). Found significant species-specific differences in branch biomass allocation. Introduced a non-destructive method for estimating urban tree biomass. Abstract: Urban trees contribute to climate change adaptation by providing multiple ecosystem services, including carbon sequestration. Yet accurate information about above-ground biomass, particularly branch biomass, is scarce. This study aimed to develop allometric models for estimating branch biomass for ten common European urban tree species using terrestrial laser scanning (TLS) and quantitative structure models (QSM) data. Conducted in Munich, the study analyzed 3,283 trees, using structural variables such as diameter at breast height (dbh), height, and crown diameter. The dbh of trees in the dataset reached up to 0.8 m, with mean above-ground biomass ranging from 550 to 1.496 kg C, and branch biomass from 32.2 to 164.5 kg C. The results confirmed that dbh was the strongest predictor of branch biomass (r = 0.69–0.9), and adding height improved model accuracy (R<sup>2</sup> = 0.69–0.93). Species-specific models revealed significant variations, with R. pseudoacacia showing the highest branch biomass when standardized by tree height, and P. nigra 'italica' the lowest. Conversely, when standardized by dbh, P. acerifolia showed the highest branch biomass and C. betulus the lowest. Comparisons with established forest tree models revealed that the developed allometric models tend to underestimate branch biomass for most species, with deviations ranging from 1 to 36%, reflecting unique growth forms and urban environmental conditions. The study highlights the need for species-specific allometric models to improve assessments of ecosystem services provided by urban trees.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/397749
https://api.elsevier.com/content/abstract/scopus_id/105007549635
url http://hdl.handle.net/10261/397749
https://api.elsevier.com/content/abstract/scopus_id/105007549635
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1007/s00468-025-02637-7
https://doi.org/10.1007/s00468-025-02637-7
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.228081

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