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Carbon storage in China's forest ecosystems: estimation by different integrative methods

Carbon (C) storage for all the components, especially dead mass and soil organic carbon, was rarely reported and remained uncertainty in China's forest ecosystems. This study used field‐measured data published between 2004 and 2014 to estimate C storage by three forest type classifications and...

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Autores principales: Peng, Shunlei, Wen, Ding, He, Nianpeng, Yu, Guirui, Ma, Anna, Wang, Qiufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823146/
https://www.ncbi.nlm.nih.gov/pubmed/27092239
http://dx.doi.org/10.1002/ece3.2114
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author Peng, Shunlei
Wen, Ding
He, Nianpeng
Yu, Guirui
Ma, Anna
Wang, Qiufeng
author_facet Peng, Shunlei
Wen, Ding
He, Nianpeng
Yu, Guirui
Ma, Anna
Wang, Qiufeng
author_sort Peng, Shunlei
collection PubMed
description Carbon (C) storage for all the components, especially dead mass and soil organic carbon, was rarely reported and remained uncertainty in China's forest ecosystems. This study used field‐measured data published between 2004 and 2014 to estimate C storage by three forest type classifications and three spatial interpolations and assessed the uncertainty in C storage resulting from different integrative methods in China's forest ecosystems. The results showed that C storage in China's forest ecosystems ranged from 30.99 to 34.96 Pg C by the six integrative methods. We detected 5.0% variation (coefficient of variation, CV, %) among the six methods, which was influenced mainly by soil C estimates. Soil C density and storage in the 0–100 cm soil layer were estimated to be 136.11–153.16 Mg C·ha(−1) and 20.63–23.21 Pg C, respectively. Dead mass C density and storage were estimated to be 3.66–5.41 Mg C·ha(−1) and 0.68–0.82 Pg C, respectively. Mean C storage in China's forest ecosystems estimated by the six integrative methods was 8.557 Pg C (25.8%) for aboveground biomass, 1.950 Pg C (5.9%) for belowground biomass, 0.697 Pg C (2.1%) for dead mass, and 21.958 Pg C (66.2%) for soil organic C in the 0–100 cm soil layer. The R:S ratio was 0.23, and C storage in the soil was 2.1 times greater than in the vegetation. Carbon storage estimates with respect to forest type classification (38 forest subtypes) were closer to the average value than those calculated using the spatial interpolation methods. Variance among different methods and data sources may partially explain the high uncertainty of C storage detected by different studies. This study demonstrates the importance of using multimethodological approaches to estimate C storage accurately in the large‐scale forest ecosystems.
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spelling pubmed-48231462016-04-18 Carbon storage in China's forest ecosystems: estimation by different integrative methods Peng, Shunlei Wen, Ding He, Nianpeng Yu, Guirui Ma, Anna Wang, Qiufeng Ecol Evol Original Research Carbon (C) storage for all the components, especially dead mass and soil organic carbon, was rarely reported and remained uncertainty in China's forest ecosystems. This study used field‐measured data published between 2004 and 2014 to estimate C storage by three forest type classifications and three spatial interpolations and assessed the uncertainty in C storage resulting from different integrative methods in China's forest ecosystems. The results showed that C storage in China's forest ecosystems ranged from 30.99 to 34.96 Pg C by the six integrative methods. We detected 5.0% variation (coefficient of variation, CV, %) among the six methods, which was influenced mainly by soil C estimates. Soil C density and storage in the 0–100 cm soil layer were estimated to be 136.11–153.16 Mg C·ha(−1) and 20.63–23.21 Pg C, respectively. Dead mass C density and storage were estimated to be 3.66–5.41 Mg C·ha(−1) and 0.68–0.82 Pg C, respectively. Mean C storage in China's forest ecosystems estimated by the six integrative methods was 8.557 Pg C (25.8%) for aboveground biomass, 1.950 Pg C (5.9%) for belowground biomass, 0.697 Pg C (2.1%) for dead mass, and 21.958 Pg C (66.2%) for soil organic C in the 0–100 cm soil layer. The R:S ratio was 0.23, and C storage in the soil was 2.1 times greater than in the vegetation. Carbon storage estimates with respect to forest type classification (38 forest subtypes) were closer to the average value than those calculated using the spatial interpolation methods. Variance among different methods and data sources may partially explain the high uncertainty of C storage detected by different studies. This study demonstrates the importance of using multimethodological approaches to estimate C storage accurately in the large‐scale forest ecosystems. John Wiley and Sons Inc. 2016-04-03 /pmc/articles/PMC4823146/ /pubmed/27092239 http://dx.doi.org/10.1002/ece3.2114 Text en © 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Peng, Shunlei
Wen, Ding
He, Nianpeng
Yu, Guirui
Ma, Anna
Wang, Qiufeng
Carbon storage in China's forest ecosystems: estimation by different integrative methods
title Carbon storage in China's forest ecosystems: estimation by different integrative methods
title_full Carbon storage in China's forest ecosystems: estimation by different integrative methods
title_fullStr Carbon storage in China's forest ecosystems: estimation by different integrative methods
title_full_unstemmed Carbon storage in China's forest ecosystems: estimation by different integrative methods
title_short Carbon storage in China's forest ecosystems: estimation by different integrative methods
title_sort carbon storage in china's forest ecosystems: estimation by different integrative methods
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823146/
https://www.ncbi.nlm.nih.gov/pubmed/27092239
http://dx.doi.org/10.1002/ece3.2114
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