Changes to the Earth’s climate may affect the distribution of countless species. Understanding the potentialdistribution of known invasive species under an altered climate is vital to predicting impacts and developin...Changes to the Earth’s climate may affect the distribution of countless species. Understanding the potentialdistribution of known invasive species under an altered climate is vital to predicting impacts and developingmanagement policy. The present study employs ecological niche modeling to construct the global potential distributionrange of the yellow crazy ant (Anoplolepis gracilipes) using past, current and future climate scenarios.Three modeling algorithms, GARP, BioClim and Environmental Distance, were used in a comparative analysis.Output from the models suggest firstly that this insect originated from south Asia, expanded into Europe and theninto Afrotropical regions, after which it formed its current distribution. Second, the invasive risk of A. gracilipesunder future climatic change scenarios will become greater because of an extension of suitable environmentalconditions in higher latitudes. Third, when compared to the GARP model, BioClim and Environmental Distancemodels were better at modeling a species’ ancestral distribution. These findings are discussed in light of thepredictive accuracy of these models.展开更多
Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security bu...Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.展开更多
基金I would like to thank James K.Wetterer for providing raw data and two anonymous reviewers for providing insightful comments on earlier versions of this manuscript.Part of the work has been presented at the 2nd International Symposium of Integrative Zoology in Beijing(Dec,2007).
文摘Changes to the Earth’s climate may affect the distribution of countless species. Understanding the potentialdistribution of known invasive species under an altered climate is vital to predicting impacts and developingmanagement policy. The present study employs ecological niche modeling to construct the global potential distributionrange of the yellow crazy ant (Anoplolepis gracilipes) using past, current and future climate scenarios.Three modeling algorithms, GARP, BioClim and Environmental Distance, were used in a comparative analysis.Output from the models suggest firstly that this insect originated from south Asia, expanded into Europe and theninto Afrotropical regions, after which it formed its current distribution. Second, the invasive risk of A. gracilipesunder future climatic change scenarios will become greater because of an extension of suitable environmentalconditions in higher latitudes. Third, when compared to the GARP model, BioClim and Environmental Distancemodels were better at modeling a species’ ancestral distribution. These findings are discussed in light of thepredictive accuracy of these models.
文摘Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.
