Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations

In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Sinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric...

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Autores: Dutca, I., Zianis, D., Petritan, I. C., Braga, C.I., Stefan, G., Yuste, J.C., Petrian, A.M.
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/51489
Acceso en línea:http://hdl.handle.net/10810/51489
Access Level:acceso abierto
Palabra clave:Bayesian networks
Biology
Forestry
Silver
Above ground biomass
Bayesian approaches
Biomass measurements
Diameters at breast heights
European beech (fagus sylvatica l.)
Informative Priors
Logarithmic transformations
Silver fir (Abies alba Mill.)
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repository_id_str
spelling Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observationsDutca, I.Zianis, D.Petritan, I. C.Braga, C.I.Stefan, G.Yuste, J.C.Petrian, A.M.Bayesian networksBiologyForestrySilverAbove ground biomassBayesian approachesBiomass measurementsDiameters at breast heightsEuropean beech (fagus sylvatica l.)Informative PriorsLogarithmic transformationsSilver fir (Abies alba Mill.)In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Sinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric biomass model development were also investigated. Developing site-specific allometric biomass models requires new measurements of biomass for a sample of trees from that specific site. Yet, measuring biomass is laborious, time consuming, and requires extensive logistics, especially for very large trees. The allometric biomass models were developed for a wide range of diameters at breast height, D (6–86 cm for European beech and 6–93 cm for silver fir) using a logarithmic transformation approach. Two alternative approaches were applied, i.e., random intercept model (RIM) and a Bayesian model with strong informative priors, to enhance the information of the site-specific sample (of biomass observations) by supplementing with a generic biomass sample. The appropriateness of each model was evaluated based on the aboveground biomass prediction of a 1 ha sample plot inS, inca forest. The results showed that models based on both D and tree height (H) to predict tree aboveground biomass (AGB) were more accurate predictors of AGB and produced plot-level estimates with better precision, than models based on D only. Furthermore, both RIM and Bayesian approach performed similarly well when a small local sample (of seven smallest trees) was used to calibrate the allometric model. Therefore, the generic biomass observations may e ectively be combined with a small local sample (of just a few small trees) to calibrate an allometric model to a certain site and to minimize the demand for site-specific biomass measurements. However, special attention should be given to the H-D ratio, since it can a ect the allometry and the performance of the reduced local sample approach.We want to express our special gratitude to Victor Mihaila, who, together with A.M.P.,coordinated the field and laboratory activities. We are also grateful to Vlad Cris,an, Costin Dumitru-Dobre,Monica Barti, and to employees from “Padurile Sincii” Forest District, for their help during fieldwork. We thank Sorin Urdea, the manager of “Padurile Sincii” Forest District, for o ering permission and logistics to collect the sample trees. DZ acknowledges University of Thessaly (former TEI of Thessaly) for his sabbatical leave in order to contribute in the present article. J.C.Y. was supported by the BC3 María de Maeztu excellence accreditation (MDM-2017-0714), financed by the Spanish Ministry of Science, Innovation and Universities. The Basque Government also supported this research through the BERC 2018–2021 program. We appreciate the constructive comments of the editor and of anonymous reviewers that helped improving the manuscript.ForestsSpanish Ministry of Science, Innovation and UniversitiesBasque Government202120212020info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/51489reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/MINECO/MDM-2017-0714/ES/1PE/MDM-2017-0714EUS/BERC/BERC.2018-2021https://dx.doi.org/10.3390/f11111136info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/3.0/es/© 2020 by the authors. Licensee MDPI, Basel, Switzerland.Atribución-NoComercial-CompartirIgual 3.0 Españaoai:addi.ehu.eus:10810/514892026-06-18T09:23:17Z
dc.title.none.fl_str_mv Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
title Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
spellingShingle Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
Dutca, I.
Bayesian networks
Biology
Forestry
Silver
Above ground biomass
Bayesian approaches
Biomass measurements
Diameters at breast heights
European beech (fagus sylvatica l.)
Informative Priors
Logarithmic transformations
Silver fir (Abies alba Mill.)
title_short Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
title_full Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
title_fullStr Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
title_full_unstemmed Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
title_sort Allometric biomass models for european beech and silver fir: Testing approaches to minimize the demand for site-specific biomass observations
dc.creator.none.fl_str_mv Dutca, I.
Zianis, D.
Petritan, I. C.
Braga, C.I.
Stefan, G.
Yuste, J.C.
Petrian, A.M.
author Dutca, I.
author_facet Dutca, I.
Zianis, D.
Petritan, I. C.
Braga, C.I.
Stefan, G.
Yuste, J.C.
Petrian, A.M.
author_role author
author2 Zianis, D.
Petritan, I. C.
Braga, C.I.
Stefan, G.
Yuste, J.C.
Petrian, A.M.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Spanish Ministry of Science, Innovation and Universities
Basque Government
dc.subject.none.fl_str_mv Bayesian networks
Biology
Forestry
Silver
Above ground biomass
Bayesian approaches
Biomass measurements
Diameters at breast heights
European beech (fagus sylvatica l.)
Informative Priors
Logarithmic transformations
Silver fir (Abies alba Mill.)
topic Bayesian networks
Biology
Forestry
Silver
Above ground biomass
Bayesian approaches
Biomass measurements
Diameters at breast heights
European beech (fagus sylvatica l.)
Informative Priors
Logarithmic transformations
Silver fir (Abies alba Mill.)
description In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Sinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric biomass model development were also investigated. Developing site-specific allometric biomass models requires new measurements of biomass for a sample of trees from that specific site. Yet, measuring biomass is laborious, time consuming, and requires extensive logistics, especially for very large trees. The allometric biomass models were developed for a wide range of diameters at breast height, D (6–86 cm for European beech and 6–93 cm for silver fir) using a logarithmic transformation approach. Two alternative approaches were applied, i.e., random intercept model (RIM) and a Bayesian model with strong informative priors, to enhance the information of the site-specific sample (of biomass observations) by supplementing with a generic biomass sample. The appropriateness of each model was evaluated based on the aboveground biomass prediction of a 1 ha sample plot inS, inca forest. The results showed that models based on both D and tree height (H) to predict tree aboveground biomass (AGB) were more accurate predictors of AGB and produced plot-level estimates with better precision, than models based on D only. Furthermore, both RIM and Bayesian approach performed similarly well when a small local sample (of seven smallest trees) was used to calibrate the allometric model. Therefore, the generic biomass observations may e ectively be combined with a small local sample (of just a few small trees) to calibrate an allometric model to a certain site and to minimize the demand for site-specific biomass measurements. However, special attention should be given to the H-D ratio, since it can a ect the allometry and the performance of the reduced local sample approach.
publishDate 2020
dc.date.none.fl_str_mv 2020
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/51489
url http://hdl.handle.net/10810/51489
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MINECO/MDM-2017-0714/
ES/1PE/MDM-2017-0714
EUS/BERC/BERC.2018-2021
https://dx.doi.org/10.3390/f11111136
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/3.0/es/
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Atribución-NoComercial-CompartirIgual 3.0 España
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/3.0/es/
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Atribución-NoComercial-CompartirIgual 3.0 España
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Forests
publisher.none.fl_str_mv Forests
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869403749441601536
score 15,300719

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