期刊
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
卷 121, 期 10, 页码 2576-2587出版社
AMER GEOPHYSICAL UNION
DOI: 10.1002/2016JG003437
关键词
drought; CO2 fluxes; water use efficiency; eddy covariance; CLM4; 5; subtropical forecast
资金
- National Natural Science Foundation of China [41575096, 41305066]
- Key Research Program of Frontier Sciences, CA [QYZDY-SSW-DQC012]
- National Key Research and Development Program of China [2016YFA0600203]
A severe drought occurred in central and southern China in the summer of 2013. The precipitation dropped to less than 25% of the long-term average, and temperatures were abnormally high for more than 2months with return periods of 125years and 301years, respectively, which induced significant changes in the terrestrial ecohydrological cycle. In this study, the impact of the severe drought on a subtropical forest ecosystem was investigated using measurements from a newly established flux tower and simulations performed by the Community Land Model version 4.5 (CLM4.5). Based on in situ observations, we found that both gross primary production (GPP) and evapotranspiration experienced strong reductions of 76% and 40%, respectively, during the prolonged dry and hot spell. There was an exponential relationship between ecosystem respiration (R-eco) and temperatures when soil moisture was not too dry, but R-eco decreased along with GPP when the temperature exceeded 32 degrees C and soil moisture was below 0.14m(3)m(-3). The ecosystem even switched to a net source of carbon in late August. The model captured the variations in water vapor fluxes well, with correlation coefficients r>0.88, but overestimated net ecosystem CO2 exchange because it did not adequately represent carbon fluxes responses to water stress and failed to capture the nonlinear relationship between GPP and R-eco during the drought period. The long-term simulation suggested that water availability severely limited carbon sequestration, and both the underlying water use efficiency and inherent water use efficiency reached their maximum values.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据