Considerable effects of diversity indices and spatial scales on conclusions relating to ecological diversity

The relationships between ecological diversity and ecosystem functions such as stability and productivity have long been debated and have no final conclusion until now. It is ignored that the debate should be firstly based on the same diversity index, which should be theoretically complete, and on same observation scale. For the issue on the scale of ecotope observation, ecosystems should be distinguished according to intensity of human disturbance. For the issue on the scale of species observation, either number diversity or biomass diversity should be identified. This paper takes grassland ecosystems located within the Bayin Xile grassland of Xilin Gol League of Inner Mongolia Autonomous Region as an example to analyze effects of different diversity indices and spatial scales on the conclusions of ecological diversity and its relationships with ecosystem functions. The analysis results both on the scale of ecotope observation and on the scale of species observation show that different diversity indices might give different conclusions and spatial resolution has a great effect on the relative conclusions. (c) 2005 Elsevier B.V. All rights reserved.

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.

NDVI spatial pattern and its differentiation on the Mongolian Plateau

GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau. The results demonstrated that: (1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north, areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest, and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast. (2) The maximum NDVI values maintained for the past 22 years showed little variation. The average NDVI variance coefficient for the 22-year period was 15.2%. (3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale. NDVI patterns from the vegetation cover also demonstrated anisotropy; a higher positive spatial correlation was indicated in a NW-SE direction, which suggested that vegetation cover in a NW-SE direction maintained increased integrity, and vegetation assemblage was mainly distributed in the same specific direction. (4) The NDVI spatial distribution was mainly controlled by structural factors, 88.7% of the total spatial variation was influenced by structural and 11.3% by random factors. And the global autocorrelation distance was 1178 km, and the average vegetation patch length (NW-SE) to width (NE-SW) ratio was approximately 2.4:1.0.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Application of rough set-based analysis to extract spatial relationship indicator rules: An example of land use in Pearl River Delta

Spatial relations, reflecting the complex association between geographical phenomena and environments, are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization, an important geographical issue, is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter, the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong, located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan, Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan, Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.

Isolation, properties and spatial site analysis of gamma subunits of B-phycoerythrin and R-phycoerythrin

Polysiphonia urceolata R-phycoerythrin and Porphyridium cruentum B-phycoerythrin were degraded with proteinaseK, and then the nearly native gamma subunits were isolated from the reaction mixture. The process of degradation of phycoerythrin with proteinaseK showed that the gamma subunit is located in the central cavity of (alpha beta)(6) hexamer of phycoerythrin. Comparative analysis of the spectra of the native phycoerythrin, the phycoerythrin at pH 12 and the isolated gamma subunit showed that the absorption peaks of phycoerythrobilins on alpha or beta subunit are at 535 nm (or 545 nm) and 565 nm, the fluorescence emission maximum at 580 nm; the absorption peak of phycoerythrobilins on the isolated gamma subunit is at 589 nm, the fluorescence emission peak at 620 nm which overlaps the absorption maximum of C-phycocyanin and perhaps contributes to the energy transfer with high efficiency between phycoerythrin and phycocyanin in phycobilisome; the absorption maximum of phycourobilin on the isolated gamma subunit is at 498 nm, which is the same as that in native phycoerythrin, and the fluorescence emission maximum at 575 nm.

Molecular cloning and functional analysis of cathepsin B in nutrient metabolism during larval development in Meretrix meretrix

Seed rearing is an important part in large scale clam culture industry. Since the nutritional history affects early development in bivalve, the condition of larval nutrition plays a key role in successful seed rearing. So far, the molecular mechanism of nutrient uptake in bivalve larvae is unclear. As one of the important proteolytic enzymes, cathepsin B of several organisms has been reported to be involved in digestion. We intended to analyze whether cathepsin B is involved in larval nutrient metabolism in the economic bivalve, clam Meretrix meretrix. The full length of M. meretrix cathepsin B (MmeCB) cDNA was cloned, which is 1647 bp with an open reading frame of 1014 bp. The deduced amino acid sequence encoded a preproenzyme of 337 residues with Cys-114, His-282 and Asn-302 composing cathepsin B activity center. The temporal and spatial expressions of MmeCB mRNA were examined from trochophore to post larva stages by whole mount in situ hybridization. In trochophore stage, no detectable signal was found. In the later three stages, MmeCB mRNA was detected in the digestive gland, suggesting a possible role of MmeCB in digestion. Moreover, MmeCB mRNA was also observed in the epidermal cells in D-veligers. Cathepsin B specific inhibitor (CA074 methyl ester) was applied to block the activity of cathepsin B in unfed larvae. The average shell lengths of treated larvae were smaller than that in control groups. The results of mRNA epidermal distribution and inhibitor treatment in D-veligers indicated that MmeCB may be also associated with other pathway of nutrient metabolism in larval epidermis. The overall results in this paper revealed that MmeCB might play a role in larval nutrient metabolism. (C) 2008 Elsevier B.V. All rights reserved.