玉米秸秆分解期间土壤中有机碳数量的动态变化研究

通过室内培养实验 ,研究了玉米秸秆分解期间全土及其水溶性物质、轻组和重组的有机碳数量随时间的动态变化规律。结果表明 :随培养时间的延长 ,全土有机碳量呈下降的趋势 ;玉米秸秆的残留碳和残留率也呈下降的趋势 ,而分解率逐渐增加 ;水溶性物质数量呈下降的趋势 ;轻组碳量和追加复合量呈下降的趋势 ;重组碳量和原土复合量呈先增加后下降的变化趋势 。

Effects of Grazing Exclusion on Plant Productivity and Soil Carbon, Nitrogen Storage in Alpine Meadows in Northern Tibet, China

Grazing exclusion is widely adopted in restoring degraded alpine grasslands on the Qinghai-Tibetan Plateau. However, its effectiveness remains poorly understood. In this study, we investigated the effects of grazing exclusion on plant productivity, species diversity and soil organic carbon （SOC） and soil total nitrogen （STN） storage along a transect spanning from east to west of alpine meadows in northern Tibet, China. After six years of grazing exclusion, plant cover, aboveground biomass （AGB）, belowground biomass （BGB）, SOC and STN were increased, but species diversity indices declined. The enhancement of AGB and SOC caused by grazing exclusion was correlated positively with mean annual precipitation （MAP）. Grazing exclusion led to remarkable biomass increase of sedge species, especially Kobresia pygmaea, whereas decrease of biomass in forbs and no obvious change in grass, leguminous and noxious species. Root biomass was concentrated in the near surface layer （10 cm） after grazing exclusion. The effects of grazing exclusion on SOC storage were confined to shallow soil layer in sites with lower MAP. It is indicated that grazing exclusion is an effective measure to increase forage production and enhance soil carbon sequestration in the studied region. The effect is more efficient in sites with higher precipitation. However, the results revealed a tradeoff between vegetation restoration and ecological biodiversity. Therefore, carbon pools recover more quickly than plant biodiversity in the alpine meadows. We suggest that grazing exclusion should be combined with other measures to reconcile grassland restoration and biodiversitv conservation.

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.

Parameterizing soil organic carbon's impacts on soil porosity and thermal parameters for Eastern Tibet grasslands

This study investigates the stratification of soil thermal properties induced by soil organic carbon (SOC) and its impacts on the parameterization of the thermal properties. Soil parameters were measured for alpine grassland stations and North China flux stations, with a total of 34 stations and 77 soil profiles. Measured data indicate that the topsoils of alpine grasslands contain high SOC contents than underlying soil layers, which leads to higher soil porosity values and lower thermal conductivity and bulk density values in the topsoils. However, this stratification is not evident at the lowland stations due to low SOC contents. Evaluations against measured data show that three thermal conductivity schemes used in land surface models severely overestimate the values for soils with high SOC content (i.e. topsoils of alpine grassland), but they are better for soils with low SOC content. A new parameterization is then developed to take the impacts of SOC into account. The new one can well estimate the soil thermal conductivity values in both low and high SOC content cases, and therefore, it is a potential candidate of thermal conductivity scheme to be used in land surface models.

Estimates of Soil Organic Carbon Stocks in Zhejiang Province of China Based on 1:50000 Soil Database Using the PKB Method

Soil organic carbon(SOC) is an important component of farming systems and global carbon cycle. Accurately estimating SOC stock is of great importance for assessing soil productivity and modeling global climate change. A newly built 1:50 000 soil database of Zhejiang Province containing 2 154 geo-referenced soil profiles and a pedological professional knowledge-based(PKB) method were used to estimate SOC stock up to a depth of 100 cm for the Province. The spatial patterns of SOC stocks stratified by soil types,watershed(buffer analysis), topographical factors, and land use types were identified. Results showed that the soils in Zhejiang covered an area of 100 740 km2 with a total SOC stock of 831.49 × 106 t and a mean SOC density of 8.25 kg m-2, excluding water and urban areas. In terms of soil types, red soils had the highest SOC stock(259.10 × 106t), whereas mountain meadow soils contained the lowest(0.15 × 106t). In terms of SOC densities, the lowest value(5.11 kg m-2) was found in skel soils, whereas the highest value(45.30 kg m-2) was observed in mountain meadow soils. Yellow soils, as a dominant soil group, determined the SOC densities of different buffer zones in Qiantang River watershed because of their large area percentage and wide variation of SOC density values.The area percentages of various soil groups significantly varied with increasing elevation or slope when overlaid with digital elevation model data, thus influencing the SOC densities. The highest SOC density was observed under grassland, whereas the lowest SOC density was identified under unutilized land. The map of SOC density(0–100 cm depth) and the spatial patterns of SOC stocks in the Province would be helpful for relevant agencies and communities in Zhejiang Province, China.