Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1002/2016EF000480 |
Model prediction of biome-specific global soil respiration from 1960 to 2012 | |
Zhao, Zhengyong1; Peng, Changhui2,3; Yang, Qi1; Meng, Fan-Rui4; Song, Xinzhang5; Chen, Shutao6; Epule, Terence Epule2; Li, Peng3; Zhu, Qiuan3 | |
通讯作者 | Peng, Changhui ; Yang, Qi |
来源期刊 | EARTHS FUTURE |
ISSN | 2328-4277 |
出版年 | 2017 |
卷号 | 5期号:7页码:715-729 |
英文摘要 | Biome-specific soil respiration (Rs) has important yet different roles in both the carbon cycle and climate change from regional to global scales. To date, no comparable studies related to global biome-specific Rs have been conducted applying comprehensive global Rs databases. The goal of this study was to develop artificial neural network (ANN) models capable of spatially estimating global Rs and to evaluate the effects of interannual climate variations on 10 major biomes. We used 1976 annual Rs field records extracted from global Rs literature to train and test the ANN models. We determined that the best ANN model for predicting biome-specific global annual Rs was the one that applied mean annual temperature (MAT), mean annual precipitation (MAP), and biome type as inputs (r(2) = 0.60). The ANN models reported an average global Rs of 93.3 +/- 6.1 Pg C yr(-1) from 1960 to 2012 and an increasing trend in average global annual Rs of 0.04 Pg C yr(.)(-1) Estimated annual Rs increased with increases in MAT and MAP in cropland, boreal forest, grassland, shrubland, and wetland biomes. Additionally, estimated annual Rs decreased with increases in MAT and increased with increases in MAP in desert and tundra biomes, and only significantly decreased with increases in MAT (r(2) = 0.87) in the savannah biome. The developed biome-specific global Rs database for global land and soil carbon models will aid in understanding the mechanisms underlying variations in soil carbon dynamics and in quantifying uncertainty in the global soil carbon cycle. |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China ; Canada |
收录类别 | SCI-E |
WOS记录号 | WOS:000407785600007 |
WOS关键词 | ARTIFICIAL NEURAL-NETWORK ; VEGETATION TYPES ; ORGANIC-CARBON ; ECOSYSTEMS ; PATTERNS ; FORESTS ; QUANTIFICATION ; SIMULATIONS ; VARIABILITY ; EMISSIONS |
WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Meteorology & Atmospheric Sciences |
来源机构 | 西北农林科技大学 ; 南京信息工程大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/198373 |
作者单位 | 1.Guangxi Univ, Coll Forestry, Guangxi Key Lab Forest Ecol & Conservat, Nanning, Peoples R China; 2.Univ Quebec, Inst Environm Sci, Dept Biol Sci, Montreal, PQ, Canada; 3.Northwest A&F Univ, Coll Forestry, Ctr Ecol Forecasting & Global Change, Yangling, Peoples R China; 4.Univ New Brunswick, Fac Forestry & Environm Management, Fredericton, NB, Canada; 5.Zhejiang A&F Univ, State Key Lab Subtrop Silviculture, Nurturing Stn, Linan, Peoples R China; 6.Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Nanjing, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Zhengyong,Peng, Changhui,Yang, Qi,et al. Model prediction of biome-specific global soil respiration from 1960 to 2012[J]. 西北农林科技大学, 南京信息工程大学,2017,5(7):715-729. |
APA | Zhao, Zhengyong.,Peng, Changhui.,Yang, Qi.,Meng, Fan-Rui.,Song, Xinzhang.,...&Zhu, Qiuan.(2017).Model prediction of biome-specific global soil respiration from 1960 to 2012.EARTHS FUTURE,5(7),715-729. |
MLA | Zhao, Zhengyong,et al."Model prediction of biome-specific global soil respiration from 1960 to 2012".EARTHS FUTURE 5.7(2017):715-729. |
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