The Sanjiang Plain, the largest inland freshwater marshland in China, was extensive reclaimed into agricultural land. To assess the effects of marshland reclamation on Collembola, we investigated collembolan communities in a chronosequence of soybean plantations (2, 15, and 25 years) in Sanjiang marshland, Northeastern China. We found that: 1) the densities and species richness of Collembola were promoted after short-term (2 years) cultivation of soybean, but significantly decreased after medium-term cultivation (15 years); 2) the densities of epi-edaphic Collembola increased while the densities of hemi-edaphic Collembola decreased as the elongation of soybean cultivation; 3) compared with S0, two species of Collembola appeared while five species disappeared in S25. The changes of plant communities and the soil traits were supposed to be the key factors affecting the composition of soil Collembola. We thus suggest that original marshland should be saved for preserving high diversity and densities of Collembola in the Sanjiang Plain.
With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries. 相似文献
Species turnover patterns can be inconsistent due to differences in the dispersal ability of different growth forms. Here, species of trees, shrubs, herbs, and bryophytes in the Xiaoqinling National Nature Reserve in China were analyzed to determine patterns of species turnover along an elevation and spatial gradient. Variance partitioning was used to assess the relative contribution of topographic heterogeneity and dispersal limitation to species turnover. Our results suggest that the effect of dispersal limitation is more important than topographic heterogeneity on species turnover in temperate mountane ecosystems in the study area. Dispersal limitation has a greater effect on trees species turnover than on shrubs, herbs or bryophytes species turnover. 相似文献
Based on the microorganism kinetic model, the formula for computing hydraulic retention time in a membrane bioreactor system (MBR) is derived. With considering HRT as an evaluation index a combinational approach was used to discuss factors which have an effect on MBR. As a result, the influencing factors were listed in order from strength to weakness as: maximum specific removal rate K, saturation constant Ks, maintenance coefficient m, maximum specific growth rate ,ua and observed yield coefficient Yobs. Moreover, the formula was simplified, whose parameters were experimentally determined in petrochemical wastewater treatment. The simplified formula is θ= 1.1( 1/β -1)(Ks S)/KXo , for oetroehemical wastewater treatment K and Ko eaualed 0.185 and 154.2, resoectively. 相似文献