Effects of land use change on soil carbon and nitrogen in purple paddy soil.

Rural land use patterns in southern China centered on household grain crop production have observed significant changes in the past few decades, profoundly affecting the release and fixation of carbon and nitrogen in the paddy soil of the region. This study selected different land use patterns developed in purple paddy soil on a decadal time scale, examined the changing rate of soil carbon and nitrogen of the purple paddy soil after abandonment, dry-farming, and fish-farming, and revealed the impact of land use changes on the balance of soil carbon and nitrogen. Results showed that the loss rates of soil organic carbon, readily oxidizable organic carbon and total nitrogen at the initial stage of dry-farming were most considerable, followed by abandonment and fish-farming. An average of 11.95-13.94 g kg-1 soil organic carbon loss and 0.90-1.03 g kg-1 total nitrogen loss of the cultivation horizon were observed when purple paddy soil was abandoned and dry farmed. In comparison, the net release of soil organic carbon and total nitrogen after fish-farming were 6.64 and -0.23 g kg-1. The changes of land use of rural area driven by rising labor cost and market demand have been inducing a continuous decline in soil C:N and significantly reducing the purple paddy soil's carbon sequestration ability. The promotion of no-tillage management, increase of organic manure application, and avoidance of over-use of nitrogen fertilizer in dryland farming need to be further considered to meet the dual pressures of China's resource constraints and carbon neutrality goals. A regression model may predict the changes in soil carbon after the change of paddy soil utilization, which provides a pathway for predicting changes in farmland carbon sequestration potential and carbon storage caused by changes in paddy soil utilization in the future.

[Difference in soil water holding capacity and the influencing factors under different land use types in the alpine region of Tibet, China]. / è¥¿è—é«˜å¯’åŒºä¸åŒåœŸåœ°åˆ©ç”¨æ–¹å¼ä¸‹åœŸå£¤æŒæ°´èƒ½åŠ›å·®å¼‚åŠå ¶å½±å“å› ç´ .

To investigate the variation of soil water holding capacity under different land use types can provide scientific basis for evaluating the change characteristics and regulation mechanism of water conservation capacity in alpine ecosystems. We collected soil samples at different depth intervals (0-10, 10-20 and 20-30 cm) under three land use types (farmland, forest, and grassland) in Tibet alpine region to measure the maximum water holding capacity, capillary water holding capacity, field capacity, and basic soil physicochemical properties. The associated environmental factors (mean annual precipitation, normalized difference vegetation index, altitude, slope gradient and surface roughness) were extracted to analyze the change characteristics and influencing factors of soil water holding capacity under different land use types. The results showed that soil water holding capacity (the maximum water holding capacity, capillary water holding capacity, and field capacity) of farmland, forest, and grassland all decreased with increasing soil depth. The mean values of the maximum water holding capacity, capillary water holding capacity, and field capacity in the 0-30 cm soil layer of grassland were 379.79, 329.57 and 194.39 g·kg-1, respectively, which were significantly higher than that of farmland (301.15, 259.67, and 154.91 g·kg-1) and forest (293.09, 251.49, and 117.01 g·kg-1). Results of the redundancy analysis showed that soil properties significantly influenced soil water holding capacity, with explanation rate of 44.6%, 42.7%, 37.6% and 35.8% for total porosity, soil organic matter, capillary porosity and soil bulk density, respectively. Results of the principal component analysis showed that mean annual precipitation, normalized difference vegetation index, altitude, slope gradient, and surface roughness were the main environmental factors affecting the spatial variation of soil water holding capacity, with a cumulative contribution of 72.4%. The grassland in the alpine region of Tibet had the highest water holding capacity and could effectively prevent soil erosion. Therefore, the implementation of returning farmland to grassland and the enclosure management of degraded grassland would be conducive to improve soil water conservation capacity in the alpine regions.

Pedogenic knowledge-aided modelling of soil inorganic carbon stocks in an alpine environment.

Accurate estimation of soil carbon is essential for accounting carbon cycling on the background of global environment change. However, previous studies made little contribution to the patterns and stocks of soil inorganic carbon (SIC) in large scales. In this study, we defined the structure of the soil depth function to fit vertical distribution of SIC based on pedogenic knowledge across various landscapes. Soil depth functions were constructed from a dataset of 99 soil profiles in the alpine area of the northeastern Tibetan Plateau. The parameters of depth functions were mapped from environmental covariates using random forest. Finally, SIC stocks at three depth intervals in the upper 1m depth were mapped across the entire study area by applying predicted soil depth functions at each location. The results showed that the soil depth functions were able to improve accuracy for fitting the vertical distribution of the SIC content, with a mean determination coefficient of R2=0.93. Overall accuracy for predicted SIC stocks was assessed on training samples. High Lin's concordance correlation coefficient values (0.84-0.86) indicate that predicted and observed values were in good agreement (RMSE: 1.52-1.67kgm-2 and ME: -0.33 to -0.29kgm-2). Variable importance showed that geographic position predictors (longitude, latitude) were key factors predicting the distribution of SIC. Terrain covariates were important variables influencing the three-dimensional distribution of SIC in mountain areas. By applying the proposed approach, the total SIC stock in this area is estimated at 75.41Tg in the upper 30cm, 113.15Tg in the upper 50cm and 190.30Tg in the upper 1m. We concluded that the methodology would be applicable for further prediction of SIC stocks in the Tibetan Plateau or other similar areas.

[Nitrogen budgets and source-sink characteristics of watershed in the hilly area of subtropical China].

The present study takes two small watersheds (F : forest, FA : forest/farmland) with different land uses as the study areas, which are located in the hilly area of subtropical China. The rain water and stream water samples were collected from March 2007 to February 2009 and were determined for NH4(+) -N and NO3(-) -N, to estimate nitrogen (N) budgets and source-sink characteristics of the two studied watersheds. The results show that inorganic N input in rain water is 16.72 kg x (hm2 x a)(-1), in which NH4(+)-N accounts for 56%; inorganic N output in stream water in the two small watersheds (F, FA) is 5.31 kg x (hm2 x a)(-1) and 8.21 kg x (hm2 x a)(-1) respectively, in which NO3(-) -N accounts for 75% -82%, indicating that agricultural activities in the watershed have increased N output in runoff. Total inorganic N input by atmospheric dry and wet deposition is 20.06-23.41 kg x (hm2 x a)(-1), which equals to approximately 13% -15% of the local N fertilizer application. The net production of H+ caused by N deposition and transformations in the two small watersheds (F, FA) is 355 mol x (hm2 x a)(-1) and 461 mol x (hm2 x a)(-1) respectively, indicating that agricultural activities lead to accelerated soil acidification. Based on N budgets, the net retention of N in the two small watersheds (F, FA) is 13.35-16.70 kg x (hm2 x a)(-1) and 17.89-23.38 kg x (hm2 x a)(-1) respectively. N retention efficiency in the FA watershed (33%-40%) as impacted by agricultural activities is much lower than that in the forested watershed (F) (65%-70%), indicating that the forest ecosystem in subtropical China is still a sink for N, but agricultural activities have decreased the nitrogen-sink potential of the ecosystem.