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How large is the difference in large-scale forest biomass estimations based on new climate-modified stand biomass models?

Authors :
He, Xiao
Lei, Xiang-Dong
Dong, Li-Hu
Source :
Ecological Indicators. Jul2021, Vol. 126, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• Climate-sensitive additive stand biomass models were developed. • The difference in biomass estimations when using the new models at a large scale was quantified. • Forecast combination method reduced the uncertainty from the biomass models. • About $8.3 million carbon services were underestimated using traditional models. • Climate-sensitive stand biomass models were recommended for carbon service accounting. Accurate forest carbon service accounting is essential for climate change mitigation. At present, the knowledge about whether and how climate-sensitive stand biomass models could reduce the uncertainty of forest biomass/carbon estimation is lacking. Hence, the aim of this study is to develop climate-sensitive stand biomass models and quantify their differences. Data containing 539 sample plots of larch plantations in northern and northeastern China were utilized to develop two basic and the corresponding climate-sensitive stand biomass models. Owing to the uncertainty from predictors, the forecast combination method was used to combine the two basic models (FCMs) and the two climate-sensitive models (CS-FCMs) and to quantify the difference in biomass estimations at the plot and regional scales. Results showed that the adjusted R 2 values of the stand biomass models were greater than 0.85 and the relative root mean square errors ranged from 5.51% to 22.62%. The CS-FCMs produced more accurate biomass estimates than the FCMs. The difference in biomass estimations derived from biomass models with and without climatic variables was 411,549 tons or 0.27% at the regional scale, but the carbon value difference amounted to about $8.3 million. This study underlined the importance of accurate carbon accounting based on climate-modified stand biomass models for forest carbon management. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1470160X
Volume :
126
Database :
Academic Search Index
Journal :
Ecological Indicators
Publication Type :
Academic Journal
Accession number :
150068629
Full Text :
https://doi.org/10.1016/j.ecolind.2021.107569