中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
PARTITIONING SOURCES OF ECOSYSTEM AND SOIL RESPIRATION IN AN ALPINE MEADOW OF TIBET PLATEAU USING REGRESSION METHOD

文献类型:SCI/SSCI论文

作者Fu G. ; Zhang X. Z. ; Zhou Y. T. ; Yu C. Q. ; Shen Z. X.
发表日期2014
关键词exponential relationship linear relationship microbial respiration plant respiration Tibetan Plateau microbial biomass organic-carbon inner-mongolia co2 exchange steppe efflux fluxes china
英文摘要Partitioning sources of ecosystem and soil respiration (R-eco and R-s) is important for understanding how climate change affects carbon cycling. Plant and microbial biomass analyses and daytime measurements of R-eco and R-s were performed for 25 plots in an alpine meadow at elevation 4313 m on the Tibetan Plateau. Plant and microbial biomass were determined by harvesting method and the chloroform fumigation-extraction method, respectively. Respiration fluxes were measured by an automated CO2 flux system (LI-8100, LI-COR Biosciences, Lincoln, NE, USA). Soil respiration can be estimated by a linear or exponential relationship between R-eco and aboveground plant biomass (AGB). Microbial respiration (R-m) can be estimated by a linear or exponential relationship between R-s and belowground plant biomass (BGB) or by a multiple relationship between R-eco and AGB and BGB. Soil respiration (or R-m) is respiration flux when AGB (or BGB) is extrapolated to zero for the linear and exponential regression methods. Similarly, R-m is respiration flux when both AGB and BGB are zero for the multiple regression method. Our findings suggest that the exponential regression method to partition sources of R-eco and R-s may be more appropriate compared to other methods for this alpine meadow of Tibet.
出处Polish Journal of Ecology
62
1
17-24
收录类别SCI
语种英语
ISSN号1505-2249
源URL[http://ir.igsnrr.ac.cn/handle/311030/29887]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Fu G.,Zhang X. Z.,Zhou Y. T.,et al. PARTITIONING SOURCES OF ECOSYSTEM AND SOIL RESPIRATION IN AN ALPINE MEADOW OF TIBET PLATEAU USING REGRESSION METHOD. 2014.

入库方式: OAI收割

来源:地理科学与资源研究所

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