Surface modelling of soil pH

In addition to classical methods, namely kriging, Inverse Distance Weighting (IDW) and splines, which have been frequently used for interpolating the spatial patterns of soil properties, a relatively more accurate surface modelling technique is being developed in recent years, namely high accuracy surface modelling (HASM). It has been used in the numerical tests, DEM construction and the interpolation of climate and ecosystem changes. In this paper, HASM was applied to interpolate soil pH for assessing its feasibility of soil property interpolation in a red soil region of Jiangxi Province, China. Soil pH was measured on 150 samples of topsoil (0-20 cm) for the interpolation and comparing the performance of HASM, kriging. IDW and splines. The mean errors (MEs) of interpolations indicate little bias of interpolation for soil pH by the four techniques. HASM has less mean absolute error (MAE) and root mean square error (RMSE) than kriging, IDW and splines. HASM is still the most accurate one when we use the mean rank and the standard deviation of the ranks to avoid the outlier effects in assessing the prediction performance of the four methods. Therefore, HASM can be considered as an alternative and accurate method for interpolating soil properties. Further researches of HASM are needed to combine HASM with ancillary variables to improve the interpolation performance and develop a user-friendly algorithm that can be implemented in a GIS package. (C) 2009 Elsevier B.V. All rights reserved.

Simulation study of China's net primary production

Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA, GEOPRO). Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process mechanism models of CASA, GLOPEM and CEVSA, the following conclusions could be made: (1) during the last 20 years, NPP change in China followed closely the seasonal change of climate affected by monsoon with an overall trend of increasing; (2) simulated average seasonal NPP was: 0.571 +/- 0.2 GtC in spring, 1.573 +/- 0.4 GtC in summer, 0.6 +/- 0.2 GtC in autumn, and 0.12 +/- 0.1 GtC in winter. Average annual NPP in China was 2.864 +/- 1 GtC. All the five models were able to simulate seasonal and spatial features of biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases.

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

The regional types of China's floating population: Identification methods and spatial patterns

With the rapid increase of the number and influence of floating population in China, it is urgently needed to understand the regional types of China's floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population, this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then, the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China's 2000 census data at county level. The results show: (1) The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously, and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. (2) The modified composite-index identification method, by using the share of a region's certain type of floating population to the total in China as weights, can effectively correct the over- or under-estimated errors due to the rather large or small total population of a region. (3) The spatial patterns of different regional types of China's floating population are closely related to the regional differentiation of their natural environment, population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation, more than 800 mm precipitation, rather higher population densities and economic development levels.

Analysis of arable land loss and its impact on rural sustainability in Southern Jiangsu Province of China

Rapid urbanization and industrialization in southern Jiangsu Province have consumed a huge amount of arable land. Through comparative analysis of land cover maps derived from TM images in 1990, 2000 and 2006, we identified the trend of arable land loss. It is found that most arable land is lost to urbanization and rural settlements development. Urban settlements, rural settlements, and industrial park-mine-transport land increased, respectively, by 87 997 ha (174.65%), 81 041 ha (104.52%), and 12 692 ha (397.99%) from 1990 to 2006. Most of the source (e.g., change from) land covers are rice paddy fields and dryland. These two covers contributed to newly urbanized areas by 37.12% and 73.52% during 1990-2000, and 46.39% and 38.86% during 2000-2006. However, the loss of arable land is weakly correlated with ecological service value, per capita net income of farmers, but positively with grain yield for some counties. Most areas in the study site have a low arable land depletion rate and a high potential for sustainable development. More attention should be directed at those counties that have a high depletion rate but a low potential for sustainable development. Rural settlements should be controlled and rationalized through legislative measures to achieve harmonious development between urban and rural areas, and sustainable development for rural areas with a minimal impact on the ecoenvironment. (C) 2009 Elsevier Ltd. All rights reserved.

Molecular determination of oxytetracycline-resistant bacteria and their resistance genes from mariculture environments of China

Aims: To assess the diversity of antibiotic-resistant bacteria and their resistance genes in typical maricultural environments. Methods nand Results: Multidrug-resistant bacteria and resistance genes from a mariculture farm of China were analysed via cultivation and polymerase chain reaction (PCR) methods. Oxytetracycline (OTC)-resistant bacteria were abundant in both abalone and turbot rearing waters, accounting for 3.7% and 9.9% of the culturable microbes. Multidrug resistance was common, with simultaneous resistance to OTC, chloramphenicol and ampicillin the most common resistance phenotype. 16S rDNA sequence analyses indicate that the typical resistant isolates belonged to marine Vibrio, Pseudoalteromonas or Alteromonas species, with resistance most common in Vibrio splendidus isolates. For OTC resistance, tet(A), tet(B) and tet(M) genes were detected in some multidrug-resistant isolates, with tet(D) being the most common molecular determinant. For chloramphenicol resistance, cat II was common, and floR was also detected, especially in marine Pseudoalteromonas strains. Conclusions: There is the risk of multidrug-resistant bacteria contamination in mariculture environments and marine Vibrio and Pseudoalteromonas species serve as reservoirs of specific antibiotic resistance determinants. Significance and Impact of the Study: This paper and similar findings from Korea and Japan indicate the potential for widespread distribution of antibiotic resistance genes in mariculture environments from the East Asian region of the world.