Nutrient addition has a significant impact on plant growth and nutrient cycling. Yet, the understanding of how the addition of nitrogen (N) or phosphorus (P) significantly affects soil gross N transformations and N availability in temperate desert steppes is still limited. Therefore, a 15N tracing experiment was conducted to study these processes and their underlying mechanism in a desert steppe soil that had been supplemented with N and P for 4 years in northwestern China. Soil N mineralization was increased significantly by P addition, and N and P additions significantly promoted soil autotrophic nitrification, rather than NH4+-N immobilization. The addition of N promoted dissimilatory NO3− reduction to NH4+, while that of P inhibited it. Soil NO3−-N production was greatly increased by N added alone and by that of N and P combined, while net NH4+-N production was decreased by these treatments. Soil N mineralization was primarily mediated by pH, P content or organic carbon, while soil NH4+-N content regulated autotrophic nitrification mainly, and this process was mainly controlled by ammonia-oxidizing bacteria rather than archaea and comammox. NH4+-N immobilization was mainly affected by functional microorganisms, the abundance of narG gene and comammox Ntsp-amoA. In conclusion, gross N transformations in the temperate desert steppe largely depended on soil inorganic N, P contents and related functional microorganisms. Soil acidification plays a more key role in N mineralization than other environmental factors or functional microorganisms. 相似文献
Under rapid climate change, soil organic carbon (SOC) dynamic in frozen ground may significantly influence terrestrial carbon cycles. The aim of this study was to investigate the storage, spatial patterns, and influencing factors of SOC in frozen ground on the Qinghai-Tibet Plateau, which known as the earth’s Third Pole.
Materials and methods
Using the observed edaphic data from China’s Second National Soil Survey, we estimated the SOC storage (SOCS) of frozen ground (including permafrost, seasonally, and short time frozen ground) on the plateau with a depth of 0–3 m. Furthermore, the effect of vegetation and climate factors on spatial variance of SOC density (SOCD) was analyzed.
Results and discussion
The SOCD decreased from the southeastern to the northwestern part of the plateau, and increased with shorten of freezing duration. SOCS of permafrost, seasonally, and short time frozen ground were calculated as 40.9 (34.2–47.6), 26.7 (24.1–29.4), and 6 (5.6–6.4) Pg, making a total of 73.6 (63.9–83.3) Pg in 0–3 m depth on the plateau. Normalized difference vegetation index and mean annual precipitation could significantly affect the spatial distribution of SOC in permafrost and seasonally frozen ground.
Conclusions
The soil in plateau frozen ground contained substantial organic carbon, which could be affected by plant and climate variables. However, the heterogeneous landform may make the fate of carbon more complicated in the future.
Estimates of the amount of Soil Organic Carbon (SOC) at the regional scale are important to better understand the role of the SOC reservoir in global climate and environmental issues. This study presents a method for estimating the total SOC stock using data from Flanders (Belgium). More than 6900 SOC measurements from the national soil survey (database ‘Aardewerk’) are combined with a digital land use map and a digital soil map of Flanders. The spatial distribution of the SOC stock is studied in its relation to factors such as soil texture, soil moisture (drainage class) and land use. The resulting map with a resolution of 15 m consists of different classes forming a combination of these environmental factors. The results show that the lowest SOC amount (kg m? 2) is stored under cropland whereas the highest amount is found under grassland. Regarding the effect of soil properties, a significant correlation between SOC stock and depth of the ground water table is observed. Sandy loam soils stock the lowest SOC amount (kg m? 2), whereas clay soils retain the highest SOC amount. First, the mean SOC amounts of the land use–soil type classes are calculated and assigned to the corresponding cells in order to obtain a total SOC stock with its spatial distribution for Flanders. Then, a multiple regression model is applied to predict the SOC value of a particular land use–soil type class on the map. This model is based on the observed relationships between SOC and land use–soil type characteristics, using the entire dataset. The first approach does not allow to obtain a (reliable) SOC value for all land use–soil type classes due to a lack of samples in some classes. A major advantage of the regression model approach is the attribution of class specific SOC values to each land use–soil type class, regardless of the number of observations in the classes. Consequently, by applying the model approach instead of the mean approach, the area for which a reliable SOC estimate could be obtained increased by 8.1% (from 9420 km2 to 10179 km2) and the total predicted SOC stock increased by 10.1% (from 88.7 ± 5.6 Mt C to 97.6 ± 1.1 Mt C). 相似文献