Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

16s rDNA based microbial diversity analysis of eleven acid mine drainages obtained from three Chinese copper mines

Eleven acid mine drainage （AMD） samples were obtained from southeast of China for the analysis of the microbial communities diversity, and the relationship with geochemical variables and spatial distance by using a culture-independent 16S rDNA gene phylogenetic analysis approach and multivariate analysis respectively. The principle component analysis （PCA） of geochemical variables shows that eleven AMDs can be clustered into two groups, relative high and low metal rich （RHMR and RLMR） AMDs. Total 1691 clone sequences are obtained and the detrended correspondence analysis （DCA） of operational taxonomic units （OTUs） shows that, ~,-Proteobacteria, Acidobacteria, Actinobacteria, Cyanobacteria, Firmicutes and Nitrospirae are dominant species in RHMR AMDs. In contrast, a-Proteobacteria, fl-Proteobacteria, Planctomycetes and Bacteriodetes are dominant species in RLMR AMD. Results also show that high-abundance putative iron-oxidizing and only putative sulfur-oxidizing microorganisms are found in RHMR AMD. Multivariate analysis shows that both geochemical variables （r=0.429 3, P=-0.037 7） and spatial distance （r=0.321 3, P=-0.018 1） are significantly positively correlated with microbial community and pH, Mg, Fe, S, Cu and Ca are key geochemistry factors in shaping microbial community. Variance partitioning analysis shows that geochemical variables and spatial distance can explain most （92%） of the variation.

Multi-objective particle swarm optimization by fusing multiple strategies

To improve the convergence and distributivity of multi-objective particle swarm optimization,we propose a method for multi-objective particle swarm optimization by fusing multiple strategies(MOPSO-MS),which includes three strategies.Firstly,the average crowding distance method is proposed,which takes into account the influence of individuals on the crowding distance and reduces the algorithm’s time complexity and computational cost,ensuring efficient external archive maintenance and improving the algorithm’s distribution.Secondly,the algorithm utilizes particle difference to guide adaptive inertia weights.In this way,the degree of disparity between a particle’s historical optimum and the population’s global optimum is used to determine the value of w.With different degrees of disparity,the size of w is adjusted nonlinearly,improving the algorithm’s convergence.Finally,the algorithm is designed to control the search direction by hierarchically selecting the globally optimal policy,which can avoid a single search direction and eliminate the lack of a random search direction,making the selection of the global optimal position more objective and comprehensive,and further improving the convergence of the algorithm.The MOPSO-MS is tested against seven other algorithms on the ZDT and DTLZ test functions,and the results show that the MOPSO-MS has significant advantages in terms of convergence and distributivity.

A model for integrated spatial land use characteristics linking to surface nutrient concentration

Quantifying land use heterogeneity helps better understand how it influences biophysical systems.Land use area proportions have been used conventionally to predict water quality variables.Lacking an insight into the combined effect of various spatial characteristics could lead to the statistical bias and confused understanding in previous studies.In this study,using spatial techniques and mathematical models,a diagnostic model was developed and applied for quantifying and incorporating three spatial components,namely,slope,distance to sampling spots,and arrangement.The upper catchment of Miyun Reservoir was studied as the test area.Total nitrogen,total phosphorus,and chemical oxygen demand of water samples from field measurements were used to characterize the surface water quality in 52 sub-watersheds.Using parameter calibrations and determinations,combined spatial characteristics were explored and detected.Adjusted land use proportions were calculated by spatial weights of discriminating the relative contribution of each location to water quality and used to build the integrated models.Compared with traditional methods only using area proportions,our model increased the explanatory power of land use and quantified the effects of spatial information on water quality.This can guide the optimization of land use configuration to control water eutrophication.