Yongdong Wang

Dynamics of soil organic carbon mineralization in tea plantations converted from farmland at Western Sichuan, China

Climate warming and land use change are some of the drivers affecting soil organic carbon (SOC) dynamics. The Grain for Green Project, local natural resources, and geographical conditions have resulted in farmland conversion into tea plantations in the hilly region of Western Sichuan. However, the effect of such land conversion on SOC mineralization remains unknown. In order to understand the temperature sensitivity of SOC decomposition in tea plantations converted from farmland, this study considered the different years (i.e., 2–3, 9–10, and 16–17 years) of tea plantations converted from farmland as the study site, and soil was incubated for 28 days at 15°C, 25°C, and 35°C to measure the soil respiration rate, amount, and temperature coefficient (Q10). Temperature and land use type interactively affected the SOC mineralization rate, and the cumulative amount of SOC mineralization in all the plots was the largest at 35°C. SOC mineralization was greater and more sensitive to temperature changes in the farmland than in the tea plantations. Compared with the control, tea plantation soils showed lower SOC mineralization rate and cumulative mineralization amount. The 16–17-year-old tea plantation with a low SOC mineralization amount and high SOC content revealed the benefits of carbon sequestration enhancement obtained by converting farmland into tea plantations. The first-order kinetic equation described SOC mineralization dynamics well. Farmland conversion into tea plantations appeared to reduce the potentially mineralizable carbon pool, and the age of tea plantations also had an effect on the SOC mineralization and sequestration. The relatively weak SOC mineralization temperature sensitivity of the tea plantation soils suggested that the SOC pool of the tea plantation soils was less vulnerable to warming than that of the control soils.

Establishment on Information System Data Base of Provincial-level Farmland Quality Management

Data standardization and unification is the necessary condition of establishing basic data base of farmland base, if we want to use one data base, the same standard and model to manage farmland quality and data of each country as well as realize data sharing of farmland quality, we must use data standardization and unification. Introduction The standardization and unification of data is the necessary condition of establishing data base of farmland base, the basic data managed by this system is from each country, it must have uniform principle on data standardization. Farmland grade chart is the result on evaluation of farmland resources it also must have geographical element such as administrative division map, road and water area, so that it reflects the distribution condition of attribute data in each country. For standardization of attribute data, we should possibly use requirement of data dictionary of farmland land fertility evaluation, reduce work load of standard data, which is favorable for system generality. Data base of space Space data base is the storage place of GIS space data, design and realization of one space data base with rich content and reasonable structure is the key factor [2-8] of the whole system. This system is the 5-level information search system of province, city, country, town and village, of which provincial-level administrative division map and city-level administrative map is the foundation framework of space data, management of farmland quality uses country-level as basic unit, adopts search model of country, town and village, including farmland quality chart, country boundary map and village boundary map. Space data base uses MS Sqlserver 2005 as closed basic data base, space data uses Krassowski eliipsoid of 1938 as parameter, Beijing 54 Coordinate System, 6 degree zone projection of Gauss Kruger, Yellow Sea altitude of 1956, and vector data is the shp form of data base of relationship type. International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2015)

Spatial variability characteristics of soil available N, P, and K and their influencing factors at the county scale

Spatial variability, a major feature of soils, was generally influenced by various factors, relative studies on which laid solid foundations for precision agriculture. In this investigation, method of geostatistics combined with GIS was used to analyze the spatial variability characteristics of soil available nitrogen (SAN), soil available phosphorus (SAP) and soil available potassium (SAK) and their influencing factors in Shuangliu county Sichuan province, China. The results showed that, SAP and SAK were normally distributed through naturally logarithmic transformation. Semivariogram analysis revealed that SAN and SAK were highly spatial correlated, while SAP moderately spatial correlated, and the spatially dependent ranges of SAN, SAK and SAP contents were 21590m, 76903m and 23300m, respectively. Through ordinary Kriging interpolation, SAN, SAP and SAK presented different varying tendencies in the study area. SSR test indicated that SAN was significantly different depending on different soil types; SAP was significantly different depending on terrain conditions and soil parental materials; SAK was strongly affected by soil parental materials. The fertilizer application rate at the regions with high soil available N, P and K contents was obviously higher than that with low soil available nutrient contents.