No abstract

Soil erosion is a serious problem in the Loess Plateau of China, and assessment of soil erosion at large watershed scale is urgently need. This study used RUSLE and GIS to assess soil loss in the Yanhe watershed. All factors used in the RUSLE were calculated for the watershed using local data. RUSLE-factor maps were made. The mean values of the R-factor, K-factor, LSfactor, C-factor and P-factor were 970 209 MJ km À2 h À1 a À1 , 0Á0195 Mg h MJ À1 mm À1 , 10Á27, 0Á33359 and 0Á2135 respectively. The mean value of the annual average soil loss was found to be 14 458 Mg km À2 per year, and the soil loss rate in most areas was between 5000 and 20 000 Mg km À2 per year. There is more erosion in the centre and southeast than in the northwest of Yanhe watershed. Because of the limitations of the RUSLE and spatial heterogeneity, more work should be done on the RUSLE-factor accuracy, scale effects, etc. Furthermore, it is necessary to apply some physical models in the future, to identify the transport and deposition processes of sediment at a large scale.

No abstract

No abstract

No abstract

Background: Plague is a rapidly progressing, serious illness in humans that is likely to be fatal if not treated. It remains a public health threat, especially in sub-Saharan Africa. In spite of plague's highly focal nature, a thorough ecological understanding of the general distribution pattern of plague across sub-Saharan Africa has not been established to date. In this study, we used human plague data from sub-Saharan Africa for 1970-2007 in an ecological niche modeling framework to explore the potential geographic distribution of plague and its ecological requirements across Africa.

Land evaluation is an important basis for landscape and land use planning. A framework was developed for land evaluation in an area of severe erosion, focusing on integrative, process and ecological analyses. Two classification systems, soil quality and erosion risk, were combined in the land evaluation framework. The Quanjiagou catchment, with typical loess hill and gully topography, in the loess plateau of China was selected as the study area. A geographical information system (GIS) was used for data storage, analysis and display. The soil quality classification was based on the main characteristics of the soils (soil organic matter, effective depth of soil and soil moisture); four soil quality classes were defined in the study area. Slope, micro-landform type and the type and processes of soil erosion were integrated to classify the erosion risk. The soil qualities and erosion risk for each site were combined using the GIS to evaluate the suitability of the land for farmland, grassland and forest. By comparing these results with the current land use, measures for better land use and conservation are suggested.

We sought to detect the temporal change (1958 -1999) in land use patterns and its relationship to physical landscape parameters in a small catchment in the semi-arid hilly area of the Chinese Loess Plateau. Degree of slope and soil type were selected as stable discriminating parameters that might constrain land use. With the help of GIS and canonical correspondence analysis, the relationship between rural land use distribution or transformation and the selected physical parameters was examined. The land use had undergone a general shift from farmland to woodland or grassland. Canonical correspondence analyses (CCA) indicated that a relationship between land use and the selected physical parameters was evident, farmland coincided with favorable conditions of fertile soil and gentle slope, while grassland and woodland were associated with conditions of poorer soil and steep slope. In the more favorable conditions the main land use change process was the intensification of farming, while in the less favourable conditions it was the abandonment of farmland. A thorough understanding of the relationship between land use temporal or spatial patterns and landscape physical parameters in the Loess Plateau of China, like degree of slope and soil type, will enhance our capability to predict landscape dynamics and lead to more sound and effective land use management strategies. D