Soil respiration(SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate...Soil respiration(SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO_2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests(Populus tomentosa(PT) and Robinia pseudoacacia(RP)), three artificial plantations(Armeniaca sibirica(AS), Punica granatum(PG) and Ziziphus jujuba(ZJ)) and one natural grassland(GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation(CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen(STN), soil organic carbon(SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q_(10)(temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO_2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO_2 emissions via SR at regional scales.展开更多
基金Under the auspices of Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA05060600)National Natural Science Foundation of China(No.51378306)
文摘Soil respiration(SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO_2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests(Populus tomentosa(PT) and Robinia pseudoacacia(RP)), three artificial plantations(Armeniaca sibirica(AS), Punica granatum(PG) and Ziziphus jujuba(ZJ)) and one natural grassland(GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation(CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen(STN), soil organic carbon(SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q_(10)(temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO_2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO_2 emissions via SR at regional scales.
