[Spatial and temporal changes of farmland soil acidification and their influencing factors in different regions of Guangdong Province, Chin]. / å¹¿ä¸œçœä¸åŒåŒºåŸŸå†œç”°åœŸå£¤é ¸åŒ–æ—¶ç©ºå˜åŒ–åŠå ¶å½±å“å› ç´ .

Based on the three datasets from 1980s, 2010 and 2015 in Guangdong Province, we analyzed the spatial and temporal variations of soil pH in farmlands in different regions of Guangdong Province and analyzed the driving factors for such variations. The results showed that the spatial distribution of soil pH in Guangdong Province changed significantly in different periods. During 1980s to 2010, soil pH showed an acidification trend with a decline of 0.3, and increased by 0.09 from 2010 to 2015, with more uneven trend and more obvious acid base differentiation. From the perspective of each region, there was generally a trend of acidification from the 1980s to 2010. From 2010 to 2015, the average pH value of farmland soil in the Pearl River Delta increased by 0.27, while that on the east wing and west wing decreased by 0.05 and 0.15 respectively, showing a unapparent change of soil pH in the mountainous area. Our results showed that soil acidification in diffe-rent areas of Guangdong Province was affected by natural factors such as soil itself and precipitation. In addition, anthropogenic factors such as acid rain, unreasonable fertilization and the planting structure of high-yielding crops were also the main causes of soil acidification. Industrialization, urbanization, mining development, and the spread of soil testing formula fertilization increased soil pH in local areas. Our results could provide theoretical guidance for controlling and alleviating soil acidification and improving the quality of cultivated land in different areas.

[Prediction of Distribution of Soil Cd Concentrations in Guangdong Province, China].

Heavy metals are one of the principal soil pollution sources. Contaminated soils affect the quality of agricultural products, and then threaten human health. Prediction of the contaminants distribution in the soil is the foundation of pollution evaluation and risk control. A total of 1000 soil profiles were collected to investigate the spatial variation of soil cadmium (Cd) concentration in Guangdong province. These datasets were divided into two groups, about 900 samples for model training and the other 100 for model validation. Six frequently used GIS spatial interpolation methods including Spline, Natural Neighbor, Ordinary Kriging, Inverse Distance Weighted, Local Polynomial Interpolation and Radial Basis Function, and Cubist which is a type of rule-based model were compared to determine their suitability parameters for estimating soil Cd concentration. Nine different resolutions including 2000, 1500, 1000, 800, 500, 300, 200, 150, and 90 m were selected to calculate, evaluate and compare their accuracy. The results showed that, 1 Quantitative assessment of the continuous surfaces showed that there was a large difference in the accuracy of the seven methods. Cubist was superior to GIS-based spatial interpolation methods at all resolutions. Cubist was the best tool for mapping the spatial distribution of Cd in soils with thirty-seven specific predictors relevant to the source and behavior of Cd (parent material, land use, soil type, soil properties, population density, gross domestic product per capita, and the lengths and classes of the roads surrounding the sampling sites, climatic factors, etc.) at 300 m×300 m resolution. The second was Spline, its accuracy was optimal at the 1500 m×1500 m resolution. 2 Results of Cubist suggested that the soil Cd spatial distribution was primarily dependent on the properties of soil regional parent materials. And soil samples with higher Cd concentration mainly located in Carboniferous and Quaternary areas. 3 Spatially, Cd concentrations were higher in the Pearl River Delta region and north of Guangdong Province. Many hotspots existed throughout the Pearl River Delta region due to transportation and pollution of the river. The major anthropogenic inputs of heavy metals to soils and the environment were metalliferous mining and smelting in the north of Guangdong Province. The soil Cd geometric mean concentration of 0.147 mg·kg-1 was lower than that of China, however it varied from zero to 6.056 mg·kg-1. The areas with soil Cd concentrations greater than 1.0 and 3.0 mg·kg-1 were 160 km2 and 2140 km2 respectively, accounting for 0.09% and 1.18% of the total area of Guangdong Province.

[Hyperspectral inversion of paddy soil iron oxide in typical subtropical area with Pearl River Delta, China as illustration]. / äºšçƒ­å¸¦å ¸åž‹åŒºåŸŸæ°´ç¨»åœŸæ°§åŒ–é“é«˜å ‰è°±åæ¼”­­ä»¥ç 江三角洲为例.

Iron oxide is the main form of iron element existing in the soil. In subtropical areas, the high-content iron oxide constitutes the soil's important coloring components, or its mineral substances, such as goethite and hematite, making the soil color apparently different from that in other climatic zones. The present paper, with the Pearl River Delta, a typical subtropical area, as illustration, and through analysis of the correlation between different spectral forms and the content of soil iron oxide, created inversion models of soil iron oxide by extracting characteristic spectral bands. The findings showed that there was a negative correlation between the content of soil iron oxide and the reflection spectrum, and the sensitive bands were mainly found in such visible near-infrared regions such as 404, 574, 784, 854 and 1204 nm. The correlation between the spectrum through differential processing and the soil iron oxide was significantly improved. On the basis of the correlation-prominent bands, the methods of both multiple linear regression and principal component analysis were adopted so as to remove collinear bands, and finally, characteristic bands were selec-ted to serve as the input parameters of inversion models. A comparison of the results revealed that the best inversion model of soil iron oxide content in the Pearl River Delta was BP artificial neural network (i.e., RMSEC=0.22, RMSEP=0.81, R2=0.93, RPD=12.20). It was applicable with excellent stability to the fast estimation of the iron oxide content in the soil and could hopefully serve as the research basis for the measure of the spatial distribution of the soil iron oxide.

[Dynamic changes of the epididymal size after vasectomy: An ultrasonographic observation].

OBJECTIVE: To investigate the dynamic changes of the epididymal size 1 year after vasectomy. METHODS: Fifty male volunteers received vasoligation. Before and at 1, 2, 3, 6, and 12 months after operation, we measured the size and detected the internal echoes of the epididymis using color Doppler ultrasonography. RESULTS: The bilateral epididymides were both thickened post-operatively in all the 50 cases, with statistically significant differences between the baseline and the 1st month, the 1st and the 2nd month, the 2nd and the 3rd month, or the 3rd and the 6th month after surgery (all P < 0.01), but not between the 6th and the 12th month (P > 0.05). CONCLUSION: Within 6 months after vasectomy, the bilateral epididymides manifested a progressive thickening, but basically restored their balance of secretion-absorption after 6 months.

[Impact of changes in land use and climate on the runoff in Liuxihe Watershed based on SWAT model].

SWAT model, an extensively used distributed hydrological model, was used to quantitatively analyze the influences of changes in land use and climate on the runoff at watershed scale. Liuxihe Watershed' s SWAT model was established and three scenarios were set. The calibration and validation at three hydrological stations of Wenquan, Taipingchang and Nangang showed that the three factors of Wenquan station just only reached the standard in validated period, and the other two stations had relative error (RE) < 15%, correlation coefficient (R2) > 0.8 and Nash-Sutcliffe efficiency valve (Ens) > 0.75, suggesting that SWAT model was appropriate for simulating runoff response to land use change and climate variability in Liuxihe watershed. According to the integrated scenario simulation, the annual runoff increased by 11.23 m3 x s(-1) from 2001 to 2010 compared with the baseline period from 1991 to 2000, among which, the land use change caused an annual runoff reduction of 0.62 m3 x s(-1), whereas climate variability caused an annual runoff increase of 11.85 m3 x s(-1). Apparently, the impact of climate variability was stronger than that of land use change. On the other hand, the scenario simulation of extreme land use showed that compared with the land use in 2000, the annual runoff of the farmland scenario and the grassland scenario increased by 2.7% and 0.5% respectively, while that of the forest land scenario were reduced by 0.7%, which suggested that forest land had an ability of diversion closure. Furthermore, the scenario simulation of climatic variability indicated that the change of river runoff correlated positively with precipitation change (increase of 11.6% in annual runoff with increase of 10% in annual precipitation) , but negatively with air temperature change (reduction of 0.8% in annual runoff with increase of 1 degrees C in annual mean air temperature), which showed that the impact of precipitation variability was stronger than that of air temperature change. Therefore, in face of climate variability, we need to pay attention to strong rainfall forecasts, optimization of land use structure and spatial distribution, which could reduce the negative hydrological effects (such as floods) induced by climate change.