<p>Soil respiration (RS), consisting of soil autotrophic respiration (RA) and heterotrophic respiration (RH), is the largest outflux of CO<sub>2</sub> from terrestrial ecosystems to the atmosphere. The temperature sensitivity (Q<sub>10</sub>) of RS is a crucial role in benchmarking the intensity of terrestrial soil carbon-climate feedbacks. However, the heterogeneity of Q<sub>10</sub> of RS has not been well explored. To fill this substantial knowledge gap, gridded long-term Q<sub>10</sub> datasets of RS at 5 cm with a spatial resolution of 1 km were developed from 515 field observations using a random forest algorithm with the linkage of climate, soil and vegetation variables. Q<sub>10</sub> of RA and RH were estimated based on the linear correlation between Q<sub>10</sub> of RS and RA/RH. Field observations indicated that regardless of ecosystem types, Q<sub>10</sub> of RS ranged from 1.54 to 4.17 with an average of 2.52. Q<sub>10</sub> varied significantly among ecosystem types, with the highest mean value of 3.18 for shrubland, followed by wetland (2.66), grassland (2.49) and forest (2.48), whereas the lowest value of 2.14 was found in cropland. RF could well explain the spatial variability of Q<sub>10</sub> of RS (model efficiency = 0.5). Temporally, Q<sub>10</sub> of RS, RA and RH did not differ significantly (<em>p </em>= 0.386). Spatially, Q<sub>10</sub> of RS, RA and RH varied greatly. In different climatic zones, the plateau areas had the highest mean Q<sub>10</sub> value of 2.88, followed by tropical areas (2.63), temperate areas (2.52), while the subtropical region had the lowest Q<sub>10</sub> on average (2.37). The predicted mean Q<sub>10</sub> of RS, RA and RH were 2.52, 2.29, 2.64, respectively, with strong spatial patterns, indicating that the traditional and constant Q<sub>10</sub> of 2 may bring great uncertainties in understanding of soil carbon-climate feedbacks in a warming climate.</p>
Oleanolic acid (3β-hydroxyolean-12-en-28-oic acid) belongs to pentacyclic triterpenoid compounds which are widely found in natural plants. Oleanolic acid and its derivatives possess several promising pharmacological activities. The chemical modifications made in the oleanane backbone mainly at carbons C3, C12 and C28 carboxylic acid, have led to a series of new synthetic oleanane triterpenoids. The Oleanolic acid derivatives at C-3 position exhibited the most potent activity. Here, a review of the advances in research on pharmacological activities and synthesis of Oleanolic acid derivatives at C-3 position are presented. Keywords: C-3 position, oleanolic acid, oleanolic acid derivatives, pharmacological activities, research, synthesis.
Bismuth sulfide (Bi2S3) enabled us to transform light signals into electrical signals via the photoelectric effect, which exhibited tremendous prospects on constructing wireless electrical stimulation for accelerating nerve regeneration. However, too rapid recombination of photogenerated electron–hole pairs weakened its photocurrent. Herein, the Bi2S3/Ti3C2Tx heterojunction was synthesized by in situ growth of Bi2S3 nanoparticles on Ti3C2Tx nanosheets and then mixed with poly-l-lactic acid (PLLA) powder to fabricate the Bi2S3/Ti3C2Tx-PLLA conduit. At the heterojunction interfaces, Ti3C2Tx with a more positive Fermi energy level could form interfacial potential difference with Bi2S3 to promote electron–hole pair separation. Meanwhile, Ti3C2Tx with excellent conductivity could provide channels for photogenerated electron transmission, thus facilitating the generation of the photocurrent. Photoluminescence and electrochemical impedance spectroscopy analysis indicated that electron–hole pair separation and electron transfer were enhanced. As a consequence, under near-infrared light radiation, the output photocurrent of Bi2S3/Ti3C2Tx-PLLA was increased from 0.48 to 1.43 μA compared to that of Bi2S3-PLLA. The enhanced photocurrent effectively promoted the differentiation of rat pheochromocytoma (PC12) into functional neurons by upregulating extracellular Ca2+ influx. Therefore, the above results demonstrated that this work provided a new perspective for wireless electrical stimulated nerve regeneration.
Abstract. Soil carbon isotopes (δ13C) provide reliable insights at a long-term scale for studying soil carbon turnover. The Tibetan Plateau (TP), called “the third pole of the earth” is one of the most sensitive areas to global climate change and exhibits an early warning signal of global warming. Although many studies detected the variability of soil δ13C at site scales, a knowledge gap still exists in the spatial pattern of topsoil δ13C across the TP. To fill the substantial knowledge gap, we first compiled a database of topsoil δ13C with 396 observations from published literatures. Then we applied a Random Forest (RF) algorithm – a machine learning approach, to predict the spatial pattern of topsoil δ13C and β (indicating the decomposition rate of soil organic carbon (SOC), calculated by δ13C divided by logarithmically converted SOC). Finally, two datasets – topsoil δ13C and β with a fine spatial resolution of 1 km across the TP were developed. Results showed that topsoil δ13C varied significantly among different ecosystem types (p < 0.001). Topsoil δ13C was −26.3 ± 1.60 ‰ (mean ± standard deviation) for forests, 24.3 ± 2.00 ‰ for shrublands, −23.9 ± 1.84 ‰ for grasslands, −18.9 ± 2.37 ‰ for deserts, respectively. RF could well predict the spatial variability of topsoil δ13C with a model efficiency of 0.62 and root mean square error of 1.12 ‰, enabling to derive data-driven δ13C and β products. Data-driven topsoil δ13C varied from −28.26 ‰ to −16.95 ‰, with the highest topsoil δ13C in the north and northwest TP and the lowest δ13C in Southeast or South TP, indicating strong spatial variabilities in topsoil δ13C. Similarly, there were strong spatial variabilities in data-driven β, with the lowest β values at the east and middle TP, indicating a higher SOC turnover in the east and middle TP compared that of other regions in the TP. This study was the first attempt to develop a fine resolution product of topsoil δ13C and β across the TP, which could provide an independent data-driven benchmark for biogeochemical cycling models to study SOC turnover and terrestrial carbon-climate feedbacks over the TP under climate change. The data-driven δ13C and β datasets are public available at https://doi.org/10.6084/m9.figshare.16641292.v2 (Tang, 2021).
The hilly area of central Sichuan is one of the ecologically fragile regions in the upper reaches of the Yangtze River, and it is also the main part of ecological engineering construction. The ecological environment in the study area is related to the ecological security in the middle and lower reaches of the Yangtze River. Recent years have witnessed a great change in vegetation cover in this area as a result of climate change. Therefore, it is necessary to identify the changing patterns of vegetation cover and the impacts of climate change on the vegetation cover change in the study area. In this paper, the characteristics of vegetation cover change over the past 15 years were analyzed, based on the dataset of MODIS NDVI from 2001 to 2015 as well as the climate data from 55 meteorological stations, with methods such as maximum value composite (MVC), linear regression and correlation coefficient. The results showed that the annual maximum average NDVI in the hilly areas of central Sichuan has increased at a rate of 5.84/10a (P<0.01), while the summer average NDVI has increased at a rate of 1.6/10a (P>0.1). The spatial distribution of annual NDVI significantly increased (31.58%) was greater than the significantly decreasing trend (2.90%). Besides, areas with significantly positive correlation and significantly negative correlation between NDVI and precipitation in summer accounted for 16.91% and 2.5% of the total area, respectively. And, the correlation between NDVI and precipitation in summer was different in different regions.
Soil is the largest carbon pool, and our understanding of soil organic carbon (SOC) has been enhanced due to its role in mitigating climate change. However, fundamental uncertainty remains about the quantitative importance of tunnel excavation, one of the most common practices for road construction in mountainous areas, on the SOC dynamics. Therefore, the short-term effects of tunnel construction on SOC and its fraction, soil microbial carbon, and soil enzyme activity within 0–20 cm in two shrublands (dominated by Quercus aquifolioides and mixed with Q. aquifolioides, Rhododendron phaeochrysum and Betula platyphylla, respectively) in Eastern Tibet Plateau were investigated. The results showed that, regardless of vegetation type, SOC, dissolved organic carbon, and easily oxidizable carbon were 27.14 ± 2.87, 6.70 ± 0.74, and 0.29 ± 0.10 g kg−1 for tunnel-affected area of Q. aquifolioides and 47.96 ± 17.89, 11.19 ± 2.92, and 0.24 ± 0.04 g kg−1 for the mixture of Q. aquifolioides, R. phaeochrysum, and B. platyphylla, respectively. The values were not significantly different from those of tunnel unaffected areas (p > 0.05). Similarly, soil enzymes (except cellulase) were not significantly different between tunnel-affected and unaffected areas (p > 0.05), indicating that tunnel construction had a minor impact on the SOC fractions and soil enzymes in the early stage. The unchanged SOC and enzyme activities may be associated with no changes in vegetation production and soil water content in tunnel-affected areas. However, vegetation type had a significant impact on SOC and its fractions and soil enzymes (p < 0.05), demonstrating the importance of vegetation control on the SOC fraction and soil enzymes. This study would be one of the earliest studies to explore the effects of tunnel construction on soil carbon dynamics based on field experiment, which could provide a new concept on environmental sustainability during tunnel construction. However, a long-term study is encouraged to detect the effects of tunnel construction SOC and soil enzymes in the future.
<p>As a crucial process of global carbon cycle, soil respiration (RS) is one of the largest out flux of carbon dioxide from terrestrial ecosystems to atmosphere. The temperature sensitivity of RS (Q<sub>10</sub>) was considered as a benchmark in describing terrestrial soil carbon-climate responses. However, the spatiotemporal and dominant factors of Q<sub>10 </sub>were not explored well at regional scale. To bridge the knowledge gap, we derived a gridded dataset of Q<sub>10 </sub>from 1994 to 2016 across China (data-derived Q<sub>10</sub>) by using a random forest (RF) model with the linkage of 515 field observations and environmental variables. The model efficiency of RF was 0.5 with root mean squared error (RMSE) of 0.62. Spatially, data-derived Q<sub>10 </sub>varied a lot from 1.54 to 4.17 with an average of 2.52, and were higher in cold regions. Temporally, the annual change of data-derived Q<sub>10 </sub>was not significant (p = 0.28). To investigate the dominant factors, we used partial correlation analysis to detect the relationships between data-derived Q<sub>10 </sub>and annual mean temperature (MAT), annual mean precipitation (MAP) and soil organic carbon (SOC). Generally, SOC was the most dominant factor which covered 46 % of land surface across China, followed by MAT (29 %) and MAP (25 %). However, there was a strong spatial heterogeneity of the proportions of dominant factors in different climatic zones, ecosystem types, and climatic conditions. Among different ecosystems, the percentage of areas dominated by MAT in grasslands (34 %) and wetlands (31 %) were higher than that of other ecosystem types (less than 25 %). Under different MAP gradients, it can be observed that the percentage of areas dominated by MAP was higher when MAP is extremely high (> 1600 mm) or extremely low (0 ~ 200 mm), which were 31 % and 29 %, respectively, higher than that at 800 ~ 1000 mm (16 %). In our results, percentage of areas dominated by MAT was higher in cold regions. As MAT increased, the percentage of areas dominated by MAT gradually decreased, and it was 33 % at MAT <-5&#8451;, higher than when MAT at 15 ~ 20&#8451; (23 %). Similarly, this phenomenon was more intuitive along the Q<sub>10 </sub>gradient, the percentage of areas dominated by MAT gradually increased from 22 % (Q<sub>10 </sub>< 2) to 56 % (Q<sub>10 </sub>> 3.5). Also, this phenomenon could be observed across different climatic zones. Except for the smallest tropical regions, from subtropical to temperate to plateau regions, the local temperature gradually decreased while the percentage of areas dominated by MAT also gradually increased (from 24 % to 36 %). Our results showed that in colder regions, the temperature influenced Q<sub>10 </sub>more significantly, which may indicate that future Q<sub>10 </sub>variations in cold regions may be more notable than in warm regions in a warming climate. This study was supported by National Natural Science Foundation of China (31800365), State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2021K024).</p>
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