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Accurate quantifying the magnitudes and distributions of carbon budgets is helpful for strategies in mitigating global climate change. Based on spatial patterns of carbon fluxes (gross ecosystem productivity (GEP), ecosystem respiration (ER) and net ecosystem productivity (NEP)) and their drivers, we constructed geographical statistical assessment schemes and quantified the magnitudes of carbon fluxes in China. The optimal assessment scheme was then validated with observed eddy covariance data to analyze the spatial distributions of carbon fluxes. Using climate-based geographical statistical assessment schemes, our estimates of GEP, ER and NEP in China during 2000s were 7.51±0.51, 5.82±0.16 and 1.91±0.15PgCyr−1, corresponding to 4.29%–6.80%, 5.65%–6.06% and 9.10%–12.73% of global annual carbon fluxes, respectively. The spatial distributions of GEP, ER and NEP, generated from the optimal scheme, were similar, following a southeast–northwest decreasing gradient. The maximum values for GEP, ER and NEP were 1790, 1300 and 490gCm−2 yr−1, respectively, which occurred in Central subtropics and Southern subtropics. Climate-based geographical statistical assessment schemes provided an independent dataset for the regional carbon budget assessment, which can be deemed as the potential carbon fluxes. Meanwhile, most areas in China were potential carbon sink especially Eastern China and the largest potential carbon sink appeared in Central subtropics and Southern subtropics. [ABSTRACT FROM AUTHOR]

Abstract: As a weather element, clouds can affect CO2 exchange between terrestrial ecosystems and the atmosphere by altering environmental conditions, such as solar radiation received on the ground surface, temperature, and moisture. Based on the flux data measured at five typical ecosystems of China during mid-growing season (June–August) from 2003 to 2006, we analyzed the responses of net ecosystem exchange of carbon dioxide (NEE), light use efficiency (LUE, defined as Gross ecosystem photosynthesis (GEP)/Photosynthetically active radiation (PAR)), and water use efficiency (WUE, defined as GEP/Evapotranspiration (ET)) to the changes in cloudiness. The five ecological sites included Changbaishan temperate mixed forest (CBS), Dinghushan subtropical evergreen broad-leaved forest (DHS), Xishuangbanna tropical rainforest (XSBN), Inner Mongolia semi-arid Leymus chinensis steppe (NMG), and Haibei alpine frigid Potentilla fruticosa shrub (HB). Our analyses show that cloudy sky conditions with cloud index (k t) values between 0.4 and 0.6 increased NEE, LUE, and WUE of the ecosystems at CBS, DHS, NMG and HB from June to August. The LUE of tropical rainforest at XSBN was higher under cloudy than under clear sky conditions, but NEE and WUE did not decrease significantly under clear sky conditions from June to August. The increase in GEP with increasing diffuse radiation received by ecosystems under cloudy skies was the main reason that caused the increases in LUE and net carbon uptake in forest ecosystem at CBS, DHS, and alpine shrub ecosystem at HB, compared with clear skies. Moreover, for the ecosystem at CBS, DHS, and HB, when sky condition became from clear to cloudy, GEP increased and ET decreased with decreasing VPD, leading to the increase in WUE and NEE under cloudy sky conditions. The decrease in R e with decreasing temperature and increase in GEP with decreasing VPD under cloudy skies led to the increase in LUE, WUE, and net carbon uptake of semi-arid steppe at NMG, compared to clear skies. These different responses among the five ecosystems are attributable to the differences in canopy characteristics and water conditions. From June to August, the peaks of the k t frequency distribution in temperate ecosystems (e.g., CBS, NMG, and HB) were larger than 0.5, but they were smaller than 0.4 in subtropical/tropical forest ecosystems (e.g., DHS and XSBN). These results suggest that the pattern of cloudiness during the years from 2003 to 2006 in the five ecosystems was not the best condition for their net carbon uptake. This study highlights the importance of cloudiness factor in the prediction of net carbon absorption in the Asia monsoon region under climate change. [Copyright &y& Elsevier]