Spatio-temporal patterns and driving mechanisms of forest carbon dioxide (CO<SUB>2</SUB>) exchange are the key issues on terrestrial ecosystem carbon cycles, which are the basis for developing and validati...Spatio-temporal patterns and driving mechanisms of forest carbon dioxide (CO<SUB>2</SUB>) exchange are the key issues on terrestrial ecosystem carbon cycles, which are the basis for developing and validating ecosystem carbon cycle models, assessing and pr展开更多
以科尔沁沙质草地为研究对象,利用开路涡度相关系统和LI-8150土壤呼吸自动观测系统,分析了生长季生态系统二氧化碳(CO_2)净交换量(NEE)的变化特征,土壤呼吸(R_s)对生态系统呼吸(R_(eco))的贡献率,以及生态系统总初级生产力(GPP)的大小...以科尔沁沙质草地为研究对象,利用开路涡度相关系统和LI-8150土壤呼吸自动观测系统,分析了生长季生态系统二氧化碳(CO_2)净交换量(NEE)的变化特征,土壤呼吸(R_s)对生态系统呼吸(R_(eco))的贡献率,以及生态系统总初级生产力(GPP)的大小。结果表明:生长季NEE存在明显的月均日变化特征,总体呈单峰型,其中7月的日变化最为明显,NEE月均日最大吸收速率(-5.62μmol·m^(-2)·s^(-1))和最大释放速率(3.14μmol·m^(-2)·s^(-1))均出现在7月份;生长季内生态系统总体表现为碳汇,固碳量为25.85 g C·m^(-2);R_s对R_(eco)的贡献率为78.39%,R_(eco)对GPP的贡献率为90.62%,生长季内GPP总累积量为275.51g C·m^(-2)。展开更多
The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available dat...The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.展开更多
基金"115" Science and Technology Supporting Program of China (Grant No. 2006BAD03A0703)the National Natural Science Foundation of China (Grant Nos.30625010 and 30590381)
文摘Spatio-temporal patterns and driving mechanisms of forest carbon dioxide (CO<SUB>2</SUB>) exchange are the key issues on terrestrial ecosystem carbon cycles, which are the basis for developing and validating ecosystem carbon cycle models, assessing and pr
文摘以科尔沁沙质草地为研究对象,利用开路涡度相关系统和LI-8150土壤呼吸自动观测系统,分析了生长季生态系统二氧化碳(CO_2)净交换量(NEE)的变化特征,土壤呼吸(R_s)对生态系统呼吸(R_(eco))的贡献率,以及生态系统总初级生产力(GPP)的大小。结果表明:生长季NEE存在明显的月均日变化特征,总体呈单峰型,其中7月的日变化最为明显,NEE月均日最大吸收速率(-5.62μmol·m^(-2)·s^(-1))和最大释放速率(3.14μmol·m^(-2)·s^(-1))均出现在7月份;生长季内生态系统总体表现为碳汇,固碳量为25.85 g C·m^(-2);R_s对R_(eco)的贡献率为78.39%,R_(eco)对GPP的贡献率为90.62%,生长季内GPP总累积量为275.51g C·m^(-2)。
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 41775151, 41530533 and 41775152)
文摘The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.
文摘光能利用效率(LUE)是影响生态系统生产力大小和质量的主要因素。以位于北京市大兴区永定河沿河沙地的杨树(欧美107/108,Populus euramericana cv.)人工林生态系统作为研究对象,依托涡度相关观测系统,对该生态系统的LUE进行研究,从而确定LUE在不同时间尺度上的影响因子,并确定最大光能利用利用效率(LUEmax)。结果表明:LUE存在明显的季节变化趋势,4月份生长季开始后LUE迅速升高,到7—8月达到最大,而后逐渐降低;在生长季不同阶段,LUE日动态的影响因子不同:4月份气温(Ta)、蒸散比(EF)和饱和水汽压差(VPD)是影响LUE日动态的主要因子,7、8月份光合有效辐射(PAR)和冠层导度(gc)是主要影响因子,5—6月与9—10月LUE日动态则与土壤水分(VWC)有较大关系;而LUE月动态则与月蒸散比(EFm)和月平均土壤温度(Tsm)有关。由于该人工林各月光能利用最适宜环境条件不同,各月LUEmax也各有差异,该生态系统年LUEmax为0.44 g C/MJ PAR,7、8月LUEmax最大,分别为0.66和0.69 g C/MJ PAR。研究结果表明,在利用光能利用模型进行区域乃至全球初级生产力估算时需要根据研究的不同时间尺度确定LUEmax。
