[Research progress on urban carbon fluxes based on eddy covariance technique].

Land use change and fossil fuel consumption due to urbanization have made significant effect on global carbon cycle and climate change. Accurate estimating and understanding of the carbon budget and its characteristics are the premises for studying carbon cycle and its driving mechanisms in urban system. Based on the theory of eddy covariance (EC) technique, the characteristics atmospheric boundary layer and carbon cycle in urban area, this study systematically reviewed the principles of CO2 flux monitoring in urban system with EC technique, and then summarized the problems faced in urban CO2 flux monitoring and the method for data processing and further assessment. The main research processes on urban carbon fluxes with EC technique were also illustrated. The results showed that the urban surface was mostly acting as net carbon source. The CO2 exchange between urban surface and atmosphere showed obvious diurnal, weekly and seasonal variation resulted from the vehicle exhaust, domestic heating and vegetation respiration. However, there still exist great uncertainties in urban flux measurement and its explanation due to high spatial heterogeneity and complex distributions of carbon source/sink in urban environments. In the end, we suggested that further researches on EC technique and data assessment in complex urban area should be strengthened. It was also requisite to develop models of urban carbon cycle on the basis of the system principle, to investigate the influencing mechanism and variability of urban cycle at regional scale with spatial analysis technique.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP.

[Immune tolerance induced by bone marrow cell transplantation combined with use of cyclophosphamide in diabetic rats with pancreatic transplantation].

OBJECTIVE: To study the immune tolerance induced by bone marrow cell transplantation combined with short-term use of cyclophosphamide after pancreatic transplantation in diabetic rats. METHODS: Type I diabetes mellitus was induced in BN rats with streptozotocin (STZ) intraperitoneal injection at a single dose of 45 mg/kg. Pancreatic transplantations were performed with the SD rats as donors and the diabetic BN rats as recipients. Twenty BN rats with type I diabetes mellitus were randomly divided into four groups. The BN rats in Group I received pancreas transplantations only. The BN rats in Group II received intraperitoneal injection of 150 mg/kg cyclophosphamide on the first day after pancreas transplantations. The BN rats in Group 11 received injection of 2.0 x 10(8) donors' bone marrow cells via the portal vein during the pancreas transplantations. The BN rats in Group IV received injection 2.0 x 10(8) donors' bone marrow cells via the portal vein during the pancreas transplantations and an intraperitoneal injection of 150 mg/kg cyclophosphamide on the first day after pancreas transplantations. The blood glucose of the rats was measured after transplantations. The graft functional survival time (GFST) was recorded. Peripheral blood was obtained two weeks after the transplantations to prepare single cell suspension for detecting chimera formation rate and the level of Vbeta11+ T cell by flow cytometry. RESULTS: The average GFST of group IV was (18 +/- 2.2) d, significantly longer than those of group I (7.8 +/- 1.2) d, group II (8.2 +/- 1.6) d, and group III (8.8 +/- l.4) d (P < 0.05). The rats in group IV had significant lower level of Vbeta11+ T cells (2.5 +/- 0.3)% than those in the other groups (P < 0.05). Donors' bone marrow-derived cells could be detected in the peripheral blood of diabetic rats in group IV, with a chimeric rate of (10.0 +/- 2.3)%. No donors' bone marrow-derived cells were detected in the rats in other groups. CONCLUSION: Bone marrow cell transplantation combined with short-term use of cyclophosphamide promote chimerism formation and induce immune tolerance in rats with pancreatic transplantations, which prolongs pancreatic graft functional survival time.

[Effects of CO2 storage flux on carbon budget of forest ecosystem].

Carbon dioxide (CO2) storage flux in the air space below measurement height of eddy covariance is very important to correctly evaluate net ecosystem exchange of CO2 (NEE) between forest ecosystem and atmosphere. This study analyzed the dynamic variation of CO2 storage flux and its effects on the carbon budget of a temperate broad-leaved Korean pine mixed forest at Changbai Mountains, based on the eddy covariance flux data and the vertical profile of CO2 concentration data. The CO2 storage flux in this forest ecosystem had typical diurnal variation, with the maximum variation appeared during the transition from stable atmospheric layer to unstable atmospheric layer. The CO2 storage flux calculated by the change in CO2 concentration throughout a vertical profile was not significantly different from that calculated by the change in CO2 concentration at the measurement height of eddy covariance. The NEE of this forest ecosystem was underestimated by 25% and 19% at night and at daytime, respectively, without calculating the CO2 storage flux at half-hour scale, and was underestimated by 10% and 25% at daily scale and annual scale, respectively. Without calculating the CO2 storage flux in this forest ecosystem, the parameters of Michaelis-Menten equation and Lloyd-Taylor equation were underestimated, and the ecosystem apparent quantum yield (alpha) and the ecosystem respiration rate (Rref) at the reference temperature were mostly affected. The gross primary productivity (GPP) and ecosystem respiration (Re) of this forest ecosystem were underestimated about 20% without calculating the CO2 storage flux at half-hour, daily scale, and annual scale.

Spatio-temporal variability of soil respiration of forest ecosystems in China: influencing factors and evaluation model.

Understanding the influencing factors of the spatio-temporal variability of soil respiration (R (s)) across different ecosystems as well as the evaluation model of R (s) is critical to the accurate prediction of future changes in carbon exchange between ecosystems and the atmosphere. R (s) data from 50 different forest ecosystems in China were summarized and the influences of environmental variables on the spatio-temporal variability of R (s) were analyzed. The results showed that both the mean annual air temperature and precipitation were weakly correlated with annual R (s), but strongly with soil carbon turnover rate. R (s) at a reference temperature of 0°C was only significantly and positively correlated with soil organic carbon (SOC) density at a depth of 20 cm. We tested a global-scale R (s) model which predicted monthly mean R (s) (R (s,monthly)) from air temperature and precipitation. Both the original model and the reparameterized model poorly explained the monthly variability of R (s) and failed to capture the inter-site variability of R (s). However, the residual of R (s,monthly) was strongly correlated with SOC density. Thus, a modified empirical model (TPS model) was proposed, which included SOC density as an additional predictor of R (s). The TPS model explained monthly and inter-site variability of R (s) for 56% and 25%, respectively. Moreover, the simulated annual R (s) of TPS model was significantly correlated with the measured value. The TPS model driven by three variables easy to be obtained provides a new tool for R (s) prediction, although a site-specific calibration is needed for using at a different region.