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Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests

BACKGROUND: Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity...

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Autores principales: Blujdea, Viorel N. B., Sikkema, Richard, Dutca, Ioan, Nabuurs, Gert-Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379742/
https://www.ncbi.nlm.nih.gov/pubmed/34417647
http://dx.doi.org/10.1186/s13021-021-00188-1
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author Blujdea, Viorel N. B.
Sikkema, Richard
Dutca, Ioan
Nabuurs, Gert-Jan
author_facet Blujdea, Viorel N. B.
Sikkema, Richard
Dutca, Ioan
Nabuurs, Gert-Jan
author_sort Blujdea, Viorel N. B.
collection PubMed
description BACKGROUND: Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. RESULTS: The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m(3) ha(−1), while the carbon stock in tree biomass will reach 76.5 tC ha(−1). The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. CONCLUSIONS: This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13021-021-00188-1.
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spelling pubmed-83797422021-08-23 Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests Blujdea, Viorel N. B. Sikkema, Richard Dutca, Ioan Nabuurs, Gert-Jan Carbon Balance Manag Research BACKGROUND: Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. RESULTS: The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m(3) ha(−1), while the carbon stock in tree biomass will reach 76.5 tC ha(−1). The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. CONCLUSIONS: This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13021-021-00188-1. Springer International Publishing 2021-08-21 /pmc/articles/PMC8379742/ /pubmed/34417647 http://dx.doi.org/10.1186/s13021-021-00188-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Blujdea, Viorel N. B.
Sikkema, Richard
Dutca, Ioan
Nabuurs, Gert-Jan
Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title_full Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title_fullStr Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title_full_unstemmed Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title_short Two large-scale forest scenario modelling approaches for reporting CO(2) removal: a comparison for the Romanian forests
title_sort two large-scale forest scenario modelling approaches for reporting co(2) removal: a comparison for the romanian forests
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379742/
https://www.ncbi.nlm.nih.gov/pubmed/34417647
http://dx.doi.org/10.1186/s13021-021-00188-1
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