Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands

Neighborhood competition is a critical driver of individual tree growth, and aboveground biomass (AGB) accumulation, which together play key roles in forest dynamics and carbon storage. Therefore, accurate biomass estimation is essential for understanding ecosystem functioning and informing forest m...

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Autores: Cudjoe, Eric, Ruiz-Peinado, Ricardo, Pretzsch, Hans, Ahmed, Shamim, Bravo, Felipe
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/395018
Acceso en línea:http://hdl.handle.net/10261/395018
https://api.elsevier.com/content/abstract/scopus_id/85218891861
Access Level:acceso abierto
Palabra clave:Biomass models
Competition effect
Forest dynamics
Mixed-species stands
Model accuracy
Sustainable forest management
Tree characteristics
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dc.title.none.fl_str_mv Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
title Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
spellingShingle Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
Cudjoe, Eric
Biomass models
Competition effect
Forest dynamics
Mixed-species stands
Model accuracy
Sustainable forest management
Tree characteristics
title_short Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
title_full Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
title_fullStr Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
title_full_unstemmed Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
title_sort Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest stands
dc.creator.none.fl_str_mv Cudjoe, Eric
Ruiz-Peinado, Ricardo
Pretzsch, Hans
Ahmed, Shamim
Bravo, Felipe
author Cudjoe, Eric
author_facet Cudjoe, Eric
Ruiz-Peinado, Ricardo
Pretzsch, Hans
Ahmed, Shamim
Bravo, Felipe
author_role author
author2 Ruiz-Peinado, Ricardo
Pretzsch, Hans
Ahmed, Shamim
Bravo, Felipe
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidad de Valladolid
Banco Santander
Agencia Estatal de Investigación (España)
Ministerio de Ciencia, Innovación y Universidades (España)
European Commission
Junta de Castilla y León
Cudjoe, Eric [0000-0003-1874-3569]
Ruiz-Peinado, Ricardo [0000-0003-0126-1651]
Pretzsch, Hans [0000-0002-4958-1868]
Ahmed, Shamim [0000-0003-2482-7195]
Bravo, Felipe [0000-0001-7348-6695]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Biomass models
Competition effect
Forest dynamics
Mixed-species stands
Model accuracy
Sustainable forest management
Tree characteristics
topic Biomass models
Competition effect
Forest dynamics
Mixed-species stands
Model accuracy
Sustainable forest management
Tree characteristics
description Neighborhood competition is a critical driver of individual tree growth, and aboveground biomass (AGB) accumulation, which together play key roles in forest dynamics and carbon storage. Therefore, accurate biomass estimation is essential for understanding ecosystem functioning and informing forest management strategies to mitigate climate change. However, integrating neighborhood competition into biomass estimation models, particularly for young mixed forest stands, remains unexplored. In this study, we examined how incorporating neighborhood competition improves biomass prediction accuracy and how the influence of neighborhood competition differs between Scots pine (Pinus sylvestris L.) and Pyrenean oak (Quercus pyrenaica Willd.), as well as the relative contributions of intra- and interspecific competition to AGB. Our findings revealed that including neighborhood competition alongside tree size variables (DBH and total tree height) significantly improved the predictive accuracy of AGB models for Scots pine. This addition reduced the root mean square error (RMSE) by 14% and improved the model efficiency factor (MEF) by 15%. Furthermore, intraspecific competition in Scots pine slightly reduced AGB, whereas interspecific competition had a significant negative effect on AGB. In contrast, DBH alone was the best predictor of AGB for Pyrenean oak, as neighborhood competition did not improve model performance. Also, intra- and interspecific competition in Pyrenean oak had positive but nonsignificant effects on AGB. These findings highlight the important role of competition in biomass models and suggest species-specific approaches in competition dynamics to inform sustainable forest management and climate change adaptation strategies.
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
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format article
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dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/395018
https://api.elsevier.com/content/abstract/scopus_id/85218891861
url http://hdl.handle.net/10261/395018
https://api.elsevier.com/content/abstract/scopus_id/85218891861
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126275OB-C21
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126275OB-C22
The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.fecs.2025.100317
https://doi.org/10.1016/j.fecs.2025.100317
Sí
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dc.publisher.none.fl_str_mv Elsevier BV
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instname:Consejo Superior de Investigaciones Científicas (CSIC)
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spelling Neighborhood competition improves biomass estimation for Scots pine (Pinus sylvestris L.) but not Pyrenean oak (Quercus pyrenaica Willd.) in young mixed forest standsCudjoe, EricRuiz-Peinado, RicardoPretzsch, HansAhmed, ShamimBravo, FelipeBiomass modelsCompetition effectForest dynamicsMixed-species standsModel accuracySustainable forest managementTree characteristicsNeighborhood competition is a critical driver of individual tree growth, and aboveground biomass (AGB) accumulation, which together play key roles in forest dynamics and carbon storage. Therefore, accurate biomass estimation is essential for understanding ecosystem functioning and informing forest management strategies to mitigate climate change. However, integrating neighborhood competition into biomass estimation models, particularly for young mixed forest stands, remains unexplored. In this study, we examined how incorporating neighborhood competition improves biomass prediction accuracy and how the influence of neighborhood competition differs between Scots pine (Pinus sylvestris L.) and Pyrenean oak (Quercus pyrenaica Willd.), as well as the relative contributions of intra- and interspecific competition to AGB. Our findings revealed that including neighborhood competition alongside tree size variables (DBH and total tree height) significantly improved the predictive accuracy of AGB models for Scots pine. This addition reduced the root mean square error (RMSE) by 14% and improved the model efficiency factor (MEF) by 15%. Furthermore, intraspecific competition in Scots pine slightly reduced AGB, whereas interspecific competition had a significant negative effect on AGB. In contrast, DBH alone was the best predictor of AGB for Pyrenean oak, as neighborhood competition did not improve model performance. Also, intra- and interspecific competition in Pyrenean oak had positive but nonsignificant effects on AGB. These findings highlight the important role of competition in biomass models and suggest species-specific approaches in competition dynamics to inform sustainable forest management and climate change adaptation strategies.This research was developed within the framework of the PhD program, Conservación y Uso Sostenible de Sistemas Forestales de la Universidad de Valladolid. We extend our gratitude to the 2019 call for the predoctoral contract at the University of Valladolid cofinanced by Banco de Santander and projects ‘CLU-2019-01 - Unidad de Excelencia Instituto iuFOR’, ‘PID2021-126275OB-C21’ and ‘PID2021-126275OB-C22’ - Integrated Forest Management along complexity gradients (IMFLEX) ‘MCIN/AEI/10.13039/501100011033/FEDER, UE’, which received financial support from the Regional Government of Castilla and León, Spain, and the European Regional Development Fund (ERDF). We also wish to express our gratitude to the members of the forest service who provided technical support during the tree-felling operations. We would also like to thank José Carlos Porto Rodríguez for his invaluable assistance in preparing.Peer reviewedElsevier BVUniversidad de ValladolidBanco SantanderAgencia Estatal de Investigación (España)Ministerio de Ciencia, Innovación y Universidades (España)European CommissionJunta de Castilla y LeónCudjoe, Eric [0000-0003-1874-3569]Ruiz-Peinado, Ricardo [0000-0003-0126-1651]Pretzsch, Hans [0000-0002-4958-1868]Ahmed, Shamim [0000-0003-2482-7195]Bravo, Felipe [0000-0001-7348-6695]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/10261/395018https://api.elsevier.com/content/abstract/scopus_id/85218891861reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126275OB-C21info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126275OB-C22The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.fecs.2025.100317https://doi.org/10.1016/j.fecs.2025.100317Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3950182026-05-22T06:33:51Z
score 15,81155

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