A new saikosaponin was isolated from Bupleurum chinense DC., and its structure was identified as 3β,16α,23,28,30_pentahydroxy_olean_11,13(18)_dien_3_O_β_D_glucopyranosyl(1→6)_[α_L_rhamnopyranosyl (1→4)]_β_D...A new saikosaponin was isolated from Bupleurum chinense DC., and its structure was identified as 3β,16α,23,28,30_pentahydroxy_olean_11,13(18)_dien_3_O_β_D_glucopyranosyl(1→6)_[α_L_rhamnopyranosyl (1→4)]_β_D_glucopyranoside on the basis of chemical and spectral evidence, named as saikosaponin q_1. In addition, two known saikosaponins, 3″_O_acetyl_saikosaponin d and 3″_O_acetyl_saikosaponin b 2, were also isolated and identified from this plant for the first time.展开更多
Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hil...Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hilly region with representative sensitivity to climate change and fragile ecology remains poorly understood.This study investigated the correlation and degree of control between R_(s) and its photosynthetic and environmental factors in five subalpine forest cover types.We examined the correlations between R_(s) and variables temperature(T_(10)) and soil moisture content at 10 cm depth(W_(10)),net photosynthetic rate(P_(n))and soil properties to establish multiple models,and the variables were measured for diurnal and monthly vari-ations from September 2018 to August 2019.The results showed that soil physical factors are not the main drivers of R_(s) dynamics at the diel scale;however,the trend in the monthly variation in R_(s) was consistent with that of T_(10)and P_(n).Further,R_(s) was significantly affected by pH,providing further evidence that coniferous forest leaves contribute to soil acidification,thus reducing R_(s).Significant exponential and linear correlations were established between R_(s) and T_(10)and W_(10),respectively,and R_(s) was positively correlated with P_(n).Accordingly,we established a two-factor model and a three-factor model,and the correlation coefficients(R_(2))was improved to different degrees compared with models based only on T_(10) and W_(10).Moreover,temperature sensitivity(Q_(10))was the highest in the secondary forest and lowest in the Larix principis-rupprechtii forest.Our findings suggest that the control of R_(s) by the environment(moisture and tempera-ture)and photosynthesis,which are interactive or comple-mentary effects,may influence spatial and temporal homeo-stasis in the region and showed that the models appropriately described the dynamic variation in R_(s) and the carbon cycle in different forest covers.In addition,total phosphorus(TP)and total potassium(TK)significantly affected the dynamic changes in R_(s).In summary,interannual and seasonal variations in forest R_(s) at multiple scales and the response forces of related ecophysiological factors,especially the interactive driving effects of soil temperature,soil moisture and photo-synthesis,were clarified,thus representing an important step in predicting the impact of climate change and formulating forest carbon management policies.展开更多
文摘A new saikosaponin was isolated from Bupleurum chinense DC., and its structure was identified as 3β,16α,23,28,30_pentahydroxy_olean_11,13(18)_dien_3_O_β_D_glucopyranosyl(1→6)_[α_L_rhamnopyranosyl (1→4)]_β_D_glucopyranoside on the basis of chemical and spectral evidence, named as saikosaponin q_1. In addition, two known saikosaponins, 3″_O_acetyl_saikosaponin d and 3″_O_acetyl_saikosaponin b 2, were also isolated and identified from this plant for the first time.
基金This work was supported financially by the National Key Research and Development Plan Projects of China(2017YFC0504604).
文摘Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hilly region with representative sensitivity to climate change and fragile ecology remains poorly understood.This study investigated the correlation and degree of control between R_(s) and its photosynthetic and environmental factors in five subalpine forest cover types.We examined the correlations between R_(s) and variables temperature(T_(10)) and soil moisture content at 10 cm depth(W_(10)),net photosynthetic rate(P_(n))and soil properties to establish multiple models,and the variables were measured for diurnal and monthly vari-ations from September 2018 to August 2019.The results showed that soil physical factors are not the main drivers of R_(s) dynamics at the diel scale;however,the trend in the monthly variation in R_(s) was consistent with that of T_(10)and P_(n).Further,R_(s) was significantly affected by pH,providing further evidence that coniferous forest leaves contribute to soil acidification,thus reducing R_(s).Significant exponential and linear correlations were established between R_(s) and T_(10)and W_(10),respectively,and R_(s) was positively correlated with P_(n).Accordingly,we established a two-factor model and a three-factor model,and the correlation coefficients(R_(2))was improved to different degrees compared with models based only on T_(10) and W_(10).Moreover,temperature sensitivity(Q_(10))was the highest in the secondary forest and lowest in the Larix principis-rupprechtii forest.Our findings suggest that the control of R_(s) by the environment(moisture and tempera-ture)and photosynthesis,which are interactive or comple-mentary effects,may influence spatial and temporal homeo-stasis in the region and showed that the models appropriately described the dynamic variation in R_(s) and the carbon cycle in different forest covers.In addition,total phosphorus(TP)and total potassium(TK)significantly affected the dynamic changes in R_(s).In summary,interannual and seasonal variations in forest R_(s) at multiple scales and the response forces of related ecophysiological factors,especially the interactive driving effects of soil temperature,soil moisture and photo-synthesis,were clarified,thus representing an important step in predicting the impact of climate change and formulating forest carbon management policies.
