基于BIOME-BGC模型的青藏高原五道梁草地生态系统碳动态模拟

青藏高原是气候变化的敏感区,草地是该地区分布最广的植被,研究草地生态系统碳动态及其变化趋势对研究碳对气候变化的影响具有重要意义。本研究使用参数本地化的BIOME-BGC模型,对1961—2015年青藏高原五道梁草地生态系统植物碳、凋落物碳、土壤碳以及总碳进行模拟,结果研究发现:(1)五道梁土壤有机碳是总碳的主要部分,占总碳固持量的95%,凋落物碳和植物碳分别为4%和1%。(2)1961—2015总碳呈微弱下降趋势,变化率为-0.018%/a;植物碳呈显著上升趋势,增长率为0.187%/a;凋落物碳呈下降趋势,但对气候变化有明显滞后性;由于变暖土壤呼吸速率增加,土壤有机碳呈下降趋势(-0.019%/a),因抵抗外界干扰能力强变幅较小。结果表明,变暖导致植被碳增加,但土壤呼吸增强导致土壤有机碳减少抵消其影响,变暖导致总碳呈减少趋势。

Factors Acquisition and Content Estimation of Farmland Soil Organic Carbon Based upon Internet of Things

Aiming at the shortage of sufficient continuous parameters for using models to estimate farmland soil organic carbon(SOC) content, an acquisition method of factors influencing farmland SOC and an estimation method of farmland SOC content with Internet of Things(IOT) are proposed in this paper. The IOT sensing device and transmission network were established in a wheat demonstration base in Yanzhou Distict of Jining City, Shandong Province, China to acquire data in real time. Using real-time data and statistics data, the dynamic changes of SOC content between October 2012 and June 2015 was simulated in the experimental area with SOC dynamic simulation model. In order to verify the estimation results, potassium dichromate external heating method was applied for measuring the SOC content. The results show that: 1) The estimated value matches the measured value in the lab very well. So the method is feasible in this paper. 2) There is a clear dynamic variation in the SOC content at 0.2 m soil depth in different growing periods of wheat. The content reached the highest level during the sowing period, and is lowest in the flowering period. 3) The SOC content at 0.2 m soil depth varies in accordance with the amount of returned straw. The larger the amount of returned straw is, the higher the SOC content.

Spatiotemporal dynamic simulation of grassland carbon storage in China

Based on the Terrestrial Ecosystem Model(TEM 5.0), together with the data of climate(temperature, precipitation and solar radiation) and environment(grassland vegetation types, soil texture, altitude, longitude and latitude, and atmospheric CO2 concentration data), the spatiotemporal variations of carbon storage and density, and their controlling factors were discussed in this paper. The results indicated that:(1) the total carbon storage of China's grasslands with a total area of 394.93×104 km2 was 59.47 Pg C. Among them, there were 3.15 Pg C in vegetation and 56.32 Pg C in soil carbon. China's grasslands covering 7.0–11.3% of the total world's grassland area had 1.3–11.3% of the vegetation carbon and 9.7–22.5% of the soil carbon in the world grasslands. The total carbon storage increased from 59.13 to 60.16 Pg C during 1961–2013 with an increasing rate of 19.4 Tg C yr^(-1).(2) The grasslands in the Qinghai-Tibetan Plateau contributed most to the total carbon storage during 1961–2013, accounting for 63.2% of the total grassland carbon storage, followed by Xinjiang grasslands(15.8%) and Inner Mongolia grasslands(11.1%).(3) The vegetation carbon storage showed an increasing trend, with the average annual growth rate of 9.62 Tg C yr^(-1) during 1961–2013, and temperature was the main determinant factor, explaining approximately 85% of its variation. The vegetation carbon storage showed an increasing trend in most grassland regions, however, a decreasing trend in the central grassland in the southern China, the western and central parts of the Inner Mongolian grasslands as well as some parts on the Qinghai-Tibetan Plateau. The soil carbon storage showed a significantly increasing trend with a rate of 7.96 Tg C yr^(-1), which resulted from the interaction of more precipitation and low temperature in the 1980 s and 1990 s. Among them, precipitation was the main determinant factor of increasing soil carbon increases of China's grasslands.

Uncertainty and Sensitivity Analyses for Modeling Long-Term Soil Organic Carbon Dynamics of Paddy Soils Under Different Climate-Soil-Management Combinations

Reporting modeling results with uncertainty information can benefit decision making by decreasing the extent that variability exerts a disproportionate influence on the options selected. For making decisions with more confidence, the uncertainty interval should be as narrow as possible. Here, the soil organic carbon （SOC） dynamics of the major paddy soil subgroup from 4 different paddy field regions of China （located in 4 counties under different climate-soil-management combinations） were modeled using the DeNitrification- DeComposition （DNDC） model for the period from 1980 to 2008. Uncertainty intervals associated with the SOC dynamics for these 4 subgroups were estimated by a long-term global sensitivity and uncertainty analysis （i. e., the Sobolt method）, and their sensitivities to 7 influential factors were quantified using the total effect sensitivity index. The results, modeled with high confidence, indicated that in the past 29 years, the studied paddy soils in Xinxing, Yixing, and Zhongjiang counties were carbon （C） sinks, while the paddy soil in Helong County was a C source. The 3 C sinks sequestered 12.2 （5.4, 19.6）, 17.1 （8.9, 25.0）, and 16.9 （-1.2, 33.6） t C ha-1 （values in the parentheses are the 5th and 95th percentiles, respectively）. Conversely, the C source had a loss of -5.4 （-14.2, 0.06） t C ha-1 in the past 29 years. The 7 factors, which changed with the climate-soil-management context, exhibited variable influences on modeled SOC. Measures with potential to conserve or sequestrate more C into paddy soils, such as incorporating more crop residues into soils and reducing chemical fertilizer application rates, were recommended for specific soils based on the sensitivity analysis results.