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Aims: The objectives of the study were to analyze the relationship between decomposition rates and initial chemistry of leaf litter and to establish an optimal model to predict the decomposition rates of a large number of plant species in karst forests of China. Methods: We determined the decomposition rate of leaf litter from 21 representative species in karst forests through a litterbag experiment. Using Akaike information criteria, we selected an optimal model among 925 regression models of decomposition rate based on initial chemistry indexes to estimate annual leaf-litter-decomposition rate for an additional 96 important species. Results: Of the 21 representative species, Elaeocarpus decipiens and Phoebe sheareri exhibited the highest (62.85 %) and lowest (23.50 %) annual decomposition rates, respectively. In the first and second quarters, climatic conditions were not advantageous to decomposition, but 20 species reached their highest decomposition rate. Most of 117 tested species accumulated fewer nutrients and more non-easily-decomposed materials in their leaf litter than plant species in non-karst forests. The selected optimal model was: $$ \mathrm{annual} \ \mathrm{decomposition} \ \mathrm{rate}=111.838-0.114\;\left( {\mathrm{total} \ \mathrm{carbon}} \right)+0.021\;\left( {\mathrm{total} \ \mathrm{nitrogen}} \right)+0.068\;\left( {\mathrm{total} \ \mathrm{potassium}} \right)-0.027\;\left( {\mathrm{lignin}} \right)-0.398\;\left( {\mathrm{tannin}} \right)-0.015\;\left( {\mathrm{starch}} \right) $$. Predicted annual leaf-litter-decomposition rates of the additional 96 tree species were 20-80 %. Conclusions: This study enhances our understanding of leaf-litter decomposition for plant species in karst forests and provides a method for estimating annual leaf-litter-decomposition rates. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, in contrast to the usual rough estimation, we present a model to simulate and evaluate the direct, indirect economic and environmental impacts of the implementation of building energy efficiency standards on Chinese economic system and environment by 12 indicators in two scenarios. Four indicators are used to evaluate the direct economic impact degree, five indicators are used to evaluate the direct environmental impact degree, three indicators are used to evaluate the indirect economic impact degree of 34 sectors and the whole Chinese economic system. This research makes it possible to link developments in the implementation of building energy efficiency standards with environmental and economic structure change. The most important finding is that the implementation of building energy efficiency standards can reduce a large amount of pollutants emissions and increase the GDP at the same time. [Copyright &y& Elsevier]

In this paper a failure model of the mixed Inverse Weibull distributions(MIWD) is considered and its estimators for all unknown parameters based on type-II and type-I censored data are obtained by means of EM-Algorithm. Some simulations suggest that EM algorithm is effective to our model. [ABSTRACT FROM AUTHOR]