Soil carbon density can increase when Australian savanna is converted to pasture, but may not change under intense cropping systems

2021 ◽  
Vol 319 ◽  
pp. 107527
Author(s):  
S.J. Livesley ◽  
M. Bristow ◽  
S.P. Grover ◽  
J. Beringer ◽  
S.K. Arndt ◽  
...  
2012 ◽  
Vol 9 (11) ◽  
pp. 4477-4485 ◽  
Author(s):  
M. W. Warren ◽  
J. B. Kauffman ◽  
D. Murdiyarso ◽  
G. Anshari ◽  
K. Hergoualc'h ◽  
...  

Abstract. Estimation of belowground carbon stocks in tropical wetland forests requires funding for laboratory analyses and suitable facilities, which are often lacking in developing nations where most tropical wetlands are found. It is therefore beneficial to develop simple analytical tools to assist belowground carbon estimation where financial and technical limitations are common. Here we use published and original data to describe soil carbon density (kgC m−3; Cd) as a function of bulk density (gC cm−3; Bd), which can be used to rapidly estimate belowground carbon storage using Bd measurements only. Predicted carbon densities and stocks are compared with those obtained from direct carbon analysis for ten peat swamp forest stands in three national parks of Indonesia. Analysis of soil carbon density and bulk density from the literature indicated a strong linear relationship (Cd = Bd × 495.14 + 5.41, R2 = 0.93, n = 151) for soils with organic C content > 40%. As organic C content decreases, the relationship between Cd and Bd becomes less predictable as soil texture becomes an important determinant of Cd. The equation predicted belowground C stocks to within 0.92% to 9.57% of observed values. Average bulk density of collected peat samples was 0.127 g cm−3, which is in the upper range of previous reports for Southeast Asian peatlands. When original data were included, the revised equation Cd = Bd × 468.76 + 5.82, with R2 = 0.95 and n = 712, was slightly below the lower 95% confidence interval of the original equation, and tended to decrease Cd estimates. We recommend this last equation for a rapid estimation of soil C stocks for well-developed peat soils where C content > 40%.


Author(s):  
Linjing Qiu ◽  
Mengzhen Yu ◽  
Yiping Wu ◽  
Yingying Yao ◽  
Zhaosheng Wang ◽  
...  

2014 ◽  
Vol 34 (2) ◽  
Author(s):  
曹生奎 CAO Shengkui ◽  
陈克龙 CHEN Kelong ◽  
曹广超 CAO Guangchao ◽  
朱锦福 ZHU Jinfu ◽  
芦宝良 LU Baoliang ◽  
...  

2012 ◽  
Vol 9 (6) ◽  
pp. 7049-7071 ◽  
Author(s):  
M. W. Warren ◽  
J. B. Kauffman ◽  
D. Murdiyarso ◽  
G. Anshari ◽  
K. Hergoualc'h ◽  
...  

Abstract. Estimation of soil carbon stocks in tropical wetlands requires costly laboratory analyses and suitable facilities, which are often lacking in developing nations where most tropical wetlands are found. It is therefore beneficial to develop simple yet robust analytical tools to assess soil carbon stocks where financial and technical limitations are common. Here we use published and original data to describe soil carbon density (gC cm−3; Cd) as a function of bulk density (g dry soil cm−3; Bd), which can be used to estimate belowground carbon storage using Bd measurements only. Predicted carbon densities and stocks are compared with those obtained from direct carbon analysis for ten peat swamp forest stands in three national parks of Indonesia. Analysis of soil carbon density and bulk density from the literature indicated a strong linear relationship (Cd = Bd × 0.49 + 4.61, R2 = 0.96, n = 94) for soils with an organic C content >40%. As organic C content decreases, the relationship between Cd and Bd becomes less predictable as soil texture becomes an important determinant of Cd. The equation predicted soil C stocks to within 0.39% to 7.20% of observed values. When original data were included in the analysis, the revised equation: Cd = Bd × 0.48 + 4.28, R2 = 0.96, n = 678 was well within the 95% confidence intervals of the original equation, and tended to decrease Cd estimates slightly. We recommend this last equation for a rapid estimation of soil C stocks for well developed peat soils where C content >40%.


2016 ◽  
Vol 158 ◽  
pp. 186
Author(s):  
Martin Gauder ◽  
Norbert Billen ◽  
Sabine Zikeli ◽  
Moritz Laub ◽  
Simone Graeff-Hönninger ◽  
...  

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