Environmental and management controls of soil carbon storage in grasslands of southwestern China.

In order to predict the effects of climate change on the global carbon cycle, it is crucial to understand the environmental factors that affect soil carbon storage in grasslands. In the present study, we attempted to explain the relationships between the distribution of soil carbon storage with climate, soil types, soil properties and topographical factors across different types of grasslands with different grazing regimes. We measured soil organic carbon in 92 locations at different soil depth increments, from 0 to 100 cm in southwestern China. Among soil types, brown earth soils (Luvisols) had the highest carbon storage with 19.5 ±â€¯2.5 kg m-2, while chernozem soils had the lowest with 6.8 ±â€¯1.2 kg m-2. Mean annual temperature and precipitation, exerted a significant, but, contrasting effects on soil carbon storage. Soil carbon storage increased as mean annual temperature decreased and as mean annual precipitation increased. Across different grassland types, the mean carbon storage for the top 100 cm varied from 7.6 ±â€¯1.3 kg m-2 for temperate desert to 17.3 ±â€¯2.9 kg m-2 for alpine meadow. Grazing/cutting regimes significantly affected soil carbon storage with lowest value (7.9 ±â€¯1.5 kg m-2) recorded for cutting grass, while seasonal (11.4 ±â€¯1.3 kg m-2) and year-long (12.2 ±â€¯1.9 kg m-2) grazing increased carbon storage. The highest carbon storage was found in the completely ungrazed areas (16.7 ±â€¯2.9 kg m-2). Climatic factors, along with soil types and topographical factors, controlled soil carbon density along a soil depth in grasslands. Environmental factors alone explained about 60% of the total variation in soil carbon storage. The actual depth-wise distribution of soil carbon contents was significantly influenced by the grazing intensity and topographical factors. Overall, policy-makers should focus on reducing the grazing intensity and land conversion for the sustainable management of grasslands and C sequestration.

Comparison of infrared canopy temperature in a rubber plantation and tropical rain forest.

Canopy temperature is a result of the canopy energy balance and is driven by climate conditions, plant architecture, and plant-controlled transpiration. Here, we evaluated canopy temperature in a rubber plantation (RP) and tropical rainforest (TR) in Xishuangbanna, southwestern China. An infrared temperature sensor was installed at each site to measure canopy temperature. In the dry season, the maximum differences (Tc - Ta) between canopy temperature (Tc) and air temperature (Ta) in the RP and TR were 2.6 and 0.1 K, respectively. In the rainy season, the maximum (Tc - Ta) values in the RP and TR were 1.0 and -1.1 K, respectively. There were consistent differences between the two forests, with the RP having higher (Tc - Ta) than the TR throughout the entire year. Infrared measurements of Tc can be used to calculate canopy stomatal conductance in both forests. The difference in (Tc - Ta) at three gc levels with increasing direct radiation in the RP was larger than in the TR, indicating that change in (Tc - Ta) in the RP was relatively sensitive to the degree of stomatal closure.

Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.

Correction to "Gut microbiota dysbiosis in Chinese children with type 1 diabetes mellitus: An observational study".

[This corrects the article on p. 2394 in vol. 27, PMID: 34040330.].

Gut microbiota dysbiosis in Chinese children with type 1 diabetes mellitus: An observational study.

BACKGROUND: Gut microbiota dysbiosis is reportedly actively involved in autoimmune diseases such as type 1 diabetes mellitus (T1DM). However, the alterations in the gut microbiota and their correlation with fasting blood glucose (FBG) in Chinese children with T1DM remain unclear. AIM: To investigate alterations in the gut microbiota in Chinese children with T1DM and their associations with clinical indicators. METHODS: Samples from 51 children with T1DM and 47 age-matched and gender-matched healthy controls were obtained, to explore the structural and functional alterations in the fecal microbiota. The V3-V4 regions of the 16S rRNA gene were sequenced on a MiSeq instrument, and the association with FBG were analyzed. RESULTS: We found that the bacterial diversity was significantly increased in the T1DM-associated fecal microbiota, and changes in the microbial composition were observed at different taxonomic levels. The T1DM-reduced differential taxa, such as Bacteroides vulgatus ATCC8482, Bacteroides ovatus, Bacteroides xylanisolvens, and Flavonifractor plautii, were negatively correlated with FBG, while the T1DM-enriched taxa, such as Blautia, Eubacterium hallii group, Anaerostipes hadrus, and Dorea longicatena, were positively correlated with FBG. Bacteroides vulgatus ATCC8482, Bacteroides ovatus, the Eubacterium hallii group, and Anaerostipes hadrus, either alone or in combination, could be used as noninvasive diagnostic biomarkers to discriminate children with T1DM from healthy controls. In addition, the functional changes in the T1DM-associated fecal microbiota also suggest that these fecal microbes were associated with altered functions and metabolic activities, such as glycan biosynthesis and metabolism and lipid metabolism, which might play vital roles in the pathogenesis and development of T1DM. CONCLUSION: Our present comprehensive investigation of the T1DM-associated fecal microbiota provides novel insights into the pathogenesis of the disease and sheds light on the diagnosis and treatment of T1DM.

Water use efficiency in a primary subtropical evergreen forest in Southwest China.

We calculated water use efficiency (WUE) using measures of gross primary production (GPP) and evapotranspiration (ET) from five years of continuous eddy covariance measurements (2009-2013) obtained over a primary subtropical evergreen broadleaved forest in southwestern China. Annual mean WUE exhibited a decreasing trend from 2009 to 2013, varying from ~2.28 to 2.68 g C kg H2O-1. The multiyear average WUE was 2.48 ± 0.17 (mean ± standard deviation) g C kg H2O-1. WUE increased greatly in the driest year (2009), due to a larger decline in ET than in GPP. At the diurnal scale, WUE in the wet season reached 5.1 g C kg H2O-1 in the early morning and 4.6 g C kg H2O-1 in the evening. WUE in the dry season reached 3.1 g C kg H2O-1 in the early morning and 2.7 g C kg H2O-1 in the evening. During the leaf emergence stage, the variation of WUE could be suitably explained by water-related variables (relative humidity (RH), soil water content at 100 cm (SWC_100)), solar radiation and the green index (Sgreen). These results revealed large variation in WUE at different time scales, highlighting the importance of individual site characteristics.

[Net photosynthesis and its affecting factors in a tropical seasonal rainforest ecosystem in southwest China].

By using eddy covariance technique, this paper quantitatively analyzed the photosynthetic characteristics of tropical seasonal rainforest ecosystem and related environmental controlling factors in Xishuangbanna in 2003-2006. In the study period, less interannual difference was observed in the net photosynthesis of the ecosystem, with the maximum photosynthesis rate (P(eco,opt)), respiration at daytime (R(eco,d)), and apparent quantum yield (alpha) averaged by 0.813 mg x m(-2) x s(-1), 0.238 mg x m(-2) x s(-1), and 0.0023 mg x micromol(-1), respectively. As affected by the interaction of air temperature (Ta) and vapor pressure deficit (VPD), the photosynthetic characteristics had some seasonal differences. In rainy season, the ecosystem had the strongest photosynthetic capacity because of the higher precipitation and warmer air temperature; in foggy and cool season, fog drip played an important role in the water relations of plants, and thereby, the ecosystem photosynthetic capacity was still higher; in dry and hot season, due to the limited precipitation and high temperature, the Ta and VPD increased, inducing a decrease of ecosystem alpha and P(eco,opt). The net CO2 exchange of the ecosystem strongly depended on the Ta above 20 degrees C and the VPD above 1 kPa.

[Characteristics of CO2 exchange at leaf and canopy levels in tropical seasonal rain forest of Xishuangbanna].

By the methods of chamber-based and eddy covariance measurements, the CO2 exchange of dominant tree species Pometia tomentosa and Gironniera subaequalis at leaf and canopy levels in the tropical seasonal rain forest of Xishuangbanna was measured in different seasons of 2004. The results showed that for the two tree species, the maximum net photosynthesis (P(max A)) of canopy based on chamber-based measurement ranked in the order of rainy season (RS) > end of rainy season (ERS) > foggy-cool season (FS) > dry-hot season (DS), and the dark respiration rate (Rd) of leaf was RS > ERS > DS > FS. The P(max B) based on eddy covariance measurement was in the same order as that based on chamber-based measurement, while the canopy respiration rate (Re) was RS > DS > FS > ERS. The maximum net photosynthetic rate of canopy in different seasons measured by the two methods had a comparatively small difference, ranging from 0.9 to 2.0 micromol m(-2) s(-1).