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The soil carbon reservoir is the largest carbon reservoir in terrestrial ecosystems and consists of soil organic and inorganic carbon stocks. Previous studies have mainly focused on the soil organic carbon (SOC) stock, and limited information is available about the soil inorganic carbon (SIC) stock. The Chinese Loess Plateau (CLP), which is located in the arid and semi-arid region of China, is an important inorganic carbon reservoir, with a thick soil layer that is rich in calcium carbonate. However, there are few reports on the SIC stock and its spatial distribution in this region. In the current study, the SIC densities and stocks for various soil types and land use patterns were evaluated based on 495 profiles with 2470 soil samples across the CLP, which were collected from the Chinese Second National Soil Survey. The results showed that in the top 1 m of soil across the CLP, the average SIC density is 17.04 kg/m(2), and the total SIC stock is approximately 10.20 Pg C (1 Pg = 10(15) g). The SIC stock of the CLP accounts for approximately 18.4% of the total SIC stock throughout China. The average values of the SIC stock in the 0-20, 20-50 and 50-100 cm depths of the CLP are 2.39, 2.92 and 4.89 Pg, respectively. Under different land use patterns, the order of the average SIC density is farmland approximate to grassland > forest in all soil layers. For the various soil types, the SIC density in the 0-100 cm layer is the highest in alkaline soil and lowest in subalpine meadow soil, whereas the SIC stock is highest in loessial soil, eolian sandy soil and sierozem, and the lowest in subalpine meadow soil. These differences are largely a result of the area occupied by each soil type and the climate conditions. The results of this study provide basic information about carbon reservoir in China and contribute to our understanding of the SIC stock on the CLP as it relates to the carbon balance of terrestrial ecosystems. (C) 2014 Elsevier B.V. All rights reserved.

For over 40 years, the universal soil loss equation (USLE) and its revised version the revised universal soil loss equation (RUSLE) have been used all over the world for soil mean annual loss per area unit. Because of the watershed erosion models are under developing, many researchers applied the USLE and RUSLE to estimate soil loss in watershed estimations. However, a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the slope length for USLE and RUSLE model also have limitations. A series of ARC/INFO AML program was created that can calculate LS factor for the USLE, however the program need a very long time to run in wide-ranging areas. The flowpath and cumulative cell length-based method (FCL) overcomes this disadvantage but does not consider the following questions: (1) Some original AML program functions are not achieved, so results are different. (2) Using USLE to calculate LS factor that do not adapt to the erosion environment of China. (3) There isnt a friendly graphic user interface. The purpose of this research was to overcome these limitations and extend the FCL method through Integrating CSLE equation. We developed a LS calculation tool (LS-TOOL) in Microsofts .NET environment using C# with a user-friendly interface. Comparing the LS factor calculated with the FCL method and AML method, LS factor values generated by using LS-TOOL method delivers improved results. The LS-TOOL algorithm can automatically calculate slope length, slope steepness, L factor, S factor, and LS factors, providing the results as ASCII files which can be easily used in some GIS software. This study is an important step forward in conducting fast large-scale erosion evaluation.

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 fanning, 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. (C) 2005 Elsevier B.V. All rights reserved.

Poor vegetation cover as a result of irrational land use is generally considered to be the major factor of soil erosion in the Loess Plateau in China. However, there is lack of knowledge concerning the dynamics of land use and the complex role of socio-economic policy factors in inducing changes in land use, especially at detailed scale levels such as in individual small catchments. This study analyzes the process of human-induced landscape change in a small catchment in the northern part of the Chinese Loess Plateau from 1958 to 1999. During this period, a significant reduction of the area of farmland on steeper slopes and an increase in woodland took place. Household questionnaires among the local farmers, a review of the historic events and literature allowed the assessment of socio-economic and policy forces that caused these changes. The research showed that the changes of agricultural landscape pattern are mainly the result of the dissolution of People’s Communes in 1979 (established in 1956), the introduction of a Household Responsibility System (in 1978), the implementation of the Family Planning policy (in 1978), and the adoption of a market-directed economic system (in 1992), as well as the execution of an integrated soil erosion control project (begun in 1981). The changes of the agricultural landscape show the benefits in both ecological and economic respects.

This article proposed an approach to construct high-order balanced M-band (M>2) orthogonal multiwavelets with symmetric property, and demonstrated the advantages of our constructed multiwavelet systems in digital elevation model (DEM) generalization application over some other wavelet systems. We studied the theories related to the key properties of M-band multiwavelets, such as orthogonality, symmetry, flipping and the particular issue and balancing. According to the theories, we then discussed the construction procedures of the M-band multiwavelet systems integrating all the key properties, and presented their realization process based on Grobner base technique. Three families of orthogonal multiwavelets were achieved in this way, including three-band symmetric family, three-band flipped family and four-band symmetric family. Each family was indexed by a increasingly balanced order ρ (ρ∈{1,2,3}), and supported with the minimal length according to every balanced order. We finally tested their practical performance in DEM generalization application. The results show the superiority of the constructed M-band multiwavelet systems over other widely-used wavelet systems, including multiwavelet of two-band and scalar wavelets of M-band and 2-band, and justified the effectiveness of high-order balanced property of these proposed multiwavelet systems in preserving main trend features of signals. Key words: Multiwavelet, M-band, balancing, symmetry, flipping, DEM generalization.

Based on land use data of 1994 and 2004 in Wangdonggou watershed, through developing dynamic model of LUCC and indices of regional ecological environment, this paper quantified the characteristics of LUCC and its ecological effect. The results showed that from 1994 to 2004, farmland decreased while grassland and orchard increased greatly, forest and nonproductive land changed little. The speed of individual land use changes was in the order of grasslandorchardnonproductive landfarmlandforest land. As to the spatial change, a total of 11 major land use change types were identified, among which the change from farmland to others and form others to forest were the most important land use change. The gravitational center of farmland and orchard moved to the northwest tableland, while those of forest land and grassland moved to the southeast gully land. From 1994 to 2004, owing to LUCC, the ecological environment was improved, but the type of land use and their change took effect differently with both improving and decreasing effect. The decrease of farmland affected ecological environment negatively, while the increase of forest and grassland and orchard improved the ecological environment and its ecosystem service values. Those improving the ecological environment were from other types of land use to forest and orchard, while those worsening the ecological environment were from forest to others and from farmland to nonproductive land.

Landscape ecology emphasizes large areas and ecological effects of the spatial patterning of ecosystem. Recent developments in landscape ecology have emphasized the important relationship between spatial patterns and many ecological processes. Quantitative methods in landscape ecology link spatial patterns and ecological processes at broad spatial and temporal scales. In turn the increased attention on temporal change of ecosystem has highlighted the need for quantitative methods that can analyze patterns. This research applies quantitative methods--change detection to assess the ecosystem temporal change in the arid and semiarid area. Remote sensing offers the temporal change of ecosystem on landscape characteristics.