Biomass carbon stocks and their changes in northern China's grasslands during 1982-2006

Grassland covers approximately one-third of the area of China and plays an important role in the global terrestrial carbon (C) cycle. However, little is known about biomass C stocks and dynamics in these grasslands. During 2001-2005, we conducted five consecutive field sampling campaigns to investigate above-and below-ground biomass for northern China's grasslands. Using measurements obtained from 341 sampling sites, together with a NDVI (normalized difference vegetation index) time series dataset over 1982-2006, we examined changes in biomass C stock during the past 25 years. Our results showed that biomass C stock in northern China's grasslands was estimated at 557.5 Tg C (1 Tg=10(12) g), with a mean density of 39.5 g C m(-2) for above-ground biomass and 244.6 g C m(-2) for below-ground biomass. An increasing rate of 0.2 Tg C yr(-1) has been observed over the past 25 years, but grassland biomass has not experienced a significant change since the late 1980s. Seasonal rainfall (January-July) was the dominant factor driving temporal dynamics in biomass C stock; however, the responses of grassland biomass to climate variables differed among various grassland types. Biomass in arid grasslands (i.e., desert steppe and typical steppe) was significantly associated with precipitation, while biomass in humid grasslands (i.e., alpine meadow) was positively correlated with mean January-July temperatures. These results suggest that different grassland ecosystems in China may show diverse responses to future climate changes

Challenging National Narratives: On the Origins of Sweet Potato in China as Global Commodity During the Early Modern Period

The introduction of American cereal crops is probably one of the most important events in China¿s agricultural history, having a great effect on the agriculture production, national life, the transformation of consumer behaviour and, to some extent, the nationalization of consumption. The sweet potato (Ipomoea Batatas L.), in Chinese g¿nsh¿ ¿¿, is a staple food crop for ancient Chinese society. Today it still plays an important role in Chinese daily life, as well as guaranteeing national food security.GECEM Project, Global Encounters between China and Europe: Trade Networks, Consumption and Cultural Exchanges in Macau and Marseille (1680-1840), ERC (European Research Council)- Starting Grant, programa Horizon 2020, número de ref. 679371, www.gecem.eu.Versión del edito

Decadal soil carbon accumulation across Tibetan permafrost regions

Acknowledgements We thank the members of Peking University Sampling Teams (2001–2004) and IBCAS Sampling Teams (2013–2014) for assistance in field data collection. We also thank the Forestry Bureau of Qinghai Province and the Forestry Bureau of Tibet Autonomous Region for their permission and assistance during the sampling process. This study was financially supported by the National Natural Science Foundation of China (31670482 and 31322011), National Basic Research Program of China on Global Change (2014CB954001 and 2015CB954201), Chinese Academy of Sciences-Peking University Pioneer Cooperation Team, and the Thousand Young Talents Program.Peer reviewedPostprintPostprin

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001-2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37 +/- 180.84Tg (i.e., 532.02 +/- 99.71 g/m(2)) during 2001-2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo >DATsrc>MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo. (C) 2015 Elsevier Ltd. All rights reserved

Auto311: A Confidence-Guided Automated System for Non-emergency Calls

Emergency and non-emergency response systems are essential services provided by local governments and critical to protecting lives, the environment, and property. The effective handling of (non-)emergency calls is critical for public safety and well-being. By reducing the burden through non-emergency callers, residents in critical need of assistance through 911 will receive a fast and effective response. Collaborating with the Department of Emergency Communications (DEC) in Nashville, we analyzed 11,796 non-emergency call recordings and developed Auto311, the first automated system to handle 311 non-emergency calls, which (1) effectively and dynamically predicts ongoing non-emergency incident types to generate tailored case reports during the call; (2) itemizes essential information from dialogue contexts to complete the generated reports; and (3) strategically structures system-caller dialogues with optimized confidence. We used real-world data to evaluate the system's effectiveness and deployability. The experimental results indicate that the system effectively predicts incident type with an average F-1 score of 92.54%. Moreover, the system successfully itemizes critical information from relevant contexts to complete reports, evincing a 0.93 average consistency score compared to the ground truth. Additionally, emulations demonstrate that the system effectively decreases conversation turns as the utterance size gets more extensive and categorizes the ongoing call with 94.49% mean accuracy

Estimates of grassland biomass and turnover time on the Tibetan Plateau

The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world's grasslands and 44% of China's grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 1012g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 106 km2. The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance

Significant soil acidification across northern China’s grasslands during 1980s-2000s

Anthropogenic acid deposition may lead to soil acidification, with soil buffering capacity regulating the magnitude of any soil pH change. However, little evidence is available from large-scale observations. Here, we evaluated changes in soil pH across northern China's grasslands over the last two decades using soil profiles obtained from China's Second National Soil Inventory during the 1980s and a more recent regional soil survey during 20012005. A transect from the central-southern Tibetan Plateau to the eastern Inner Mongolian Plateau, where Kriging interpolation provided robust predictions of the spatial distribution of soil pH, was then selected to examine pH changes during the survey period. Our results showed that soil pH in the surface layer had declined significantly over the last two decades, with an overall decrease of 0.63 units (95% confidence interval similar to=similar to 0.540.73 units). The decline of soil pH was observed in both alpine grasslands on the Tibetan Plateau and temperate grasslands on the Inner Mongolian Plateau. Soil pH decreased more intensively in low soil carbonate regions, while changes of soil pH showed no significant associations with soil cation exchange capacity. These results suggest that grassland soils across northern China have experienced significant acidification from the 1980s to 2000s, with soil carbonates buffering the increase in soil acidity. The buffering process may induce a large loss of carbon from soil carbonates and thus alter the carbon balance in these globally important ecosystems.Biodiversity ConservationEcologyEnvironmental SciencesSCI(E)0ARTICLE72292-23001

Long-term changes in soil pH across major forest ecosystems in China

Atmospheric acidic deposition has been a major environmental problem since the industrial revolution. However, our understanding of the effect of acidic deposition on soil pH is inconclusive. Here we examined temporal variations in topsoil pH and their relationships with atmospheric sulfur and nitrogen deposition across China's forests from the 1980s to the 2000s. To accomplish this goal, we conducted artificial neural network simulations using historical soil inventory data from the 1980s and a data set synthesized from literature published after 2000. Our results indicated that significant decreases in soil pH occurred in broadleaved forests, while minor changes were observed in coniferous and mixed coniferous and broadleaved forests. The magnitude of soil pH change was negatively correlated with atmospheric sulfur and nitrogen deposition. This relationship highlights the need for stringent measures that reduce sulfur and nitrogen emissions so as to maintain ecosystem structure and function

Large-scale pattern of biomass partitioning across China's grasslands

Aim To investigate large-scale patterns of above-ground and below-ground biomass partitioning in grassland ecosystems and to test the isometric theory at the community level. Location Northern China, in diverse grassland types spanning temperate grasslands in arid and semi-arid regions to alpine grasslands on the Tibetan Plateau. Methods We investigated above-ground and below-ground biomass in China's grasslands by conducting five consecutive sampling campaigns across the northern part of the country during 2001-05. We then documented the root : shoot ratio (R/S) and its relationship with climatic factors for China's grasslands. We further explored relationships between above-ground and below-ground biomass across different grassland types. Results Our results indicated that the overall R/S of China's grasslands was larger than the global average (6.3 vs. 3.7). The R/S for China's grasslands did not show any significant trend with either mean annual temperature or mean annual precipitation. Above-ground biomass was nearly proportional to below-ground biomass with a scaling exponent (the slope of log-log linear relationship between above-ground and below-ground biomass) of 1.02 across various grassland types. The slope did not differ significantly between temperate and alpine grasslands or between steppe and meadow. Main conclusions Our findings support the isometric theory of above-ground and below-ground biomass partitioning, and suggest that above-ground biomass scales isometrically with below-ground biomass at the community level