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• The distal relationship between Taipei's resource inflows and nonrenewable resource production in Taiwan was investigated. • Cross-scale emergy synthesis revealed the reliance of Taipei's resource inflows on Taiwan. • The demand of construction materials in Taipei's peri-urbanization is the underlying driving force of the development in Taipei's remote areas. Urbanization not only causes environmental changes in metropolitan regions but also influences the ecological and socioeconomic changes of distant land areas due to increasing demands on resource use and waste emissions. Previous studies on the assessment of urban systems have focused on the city or metropolitan areas under study. There is a need to incorporate urban land teleconnections to investigate the relationship between a city and distant land areas during the process of urbanization. This paper analyzes the teleconnection of the energy and material flows associated with Taipei's peri-urbanization and remote areas in Taiwan. The cross-scale emergy synthesis of Taipei and Taiwan was examined first to investigate the relationships of the material and energy flows between Taipei and Taiwan. The exploitation of non-renewable resources in Taiwan during the 1990s was driven mainly by the construction and development taking place in Taipei. Furthermore, compared with Taiwan, the Taipei area relies heavily on external resources. The results of the emergy evaluation of materials flows in Taipei indicated that 85% of the construction materials used were imported from other remote areas during the past 30 years. The use of construction materials in Taipei had a higher intensity in the city center during 1982–1992 and in the peri-urban area during 2002−2014. The results of the emergy synthesis indicated that urban land teleconnections exist between peri-urban areas of Taipei and other distant areas in Taiwan. [ABSTRACT FROM AUTHOR]

The preparation of rare earth metal oxide (CeO 2 ) using bacteria with urea hydrolysis is reported. A urease-generated bacterium, Bacillus pasteurii (BP), was used to induce the precipitation of CeCO 3 OH crystals in aqueous solutions containing urea and Ce 3+ ions. The CeCO 3 OH crystals were subsequently converted to CeO 2 by its thermal decomposition. Hollow rod shaped (CeCO 3 OH and CeO 2 ) micro/nanostructure was prepared by simple method under ambient conditions. The 13 C cross polarization magic-angle spinning NMR spectra revealed the possible explanation of the interaction of organic–inorganic moieties and precipitation of ceria on cell wall of bacteria. This is a promising route of bacteria-templated metal oxide crystals to produce hollow micro/nanostructures with potential in various technical applications. The synthesis of bacteria-guided metal oxides is cheap, non-toxic and eco-friendly. [ABSTRACT FROM AUTHOR]

Accurate information provided by reliable models is essential for identifying hotspots and mitigating roadkill. However, existing methods, such as kernel density estimation (KDE) and maximum entropy modeling (ME) may individually identify only a subset of the suitable locations for mitigation, because KDE cannot detect hotspots once local abundances are depressed, and ME may only partially identify current hotspots due to imperfect discrimination skill. Here, we propose a hybrid consensus modeling (HCM) approach that leverages the strengths of both KDE and ME by using their consensus to identify the core subset of hotspots. We collected herpetofauna (amphibians and reptiles) roadkill data (N = 839) along four roads in Taiwan (R.O.C.) to evaluate the statistical performance and theoretical mitigation efficiency of HCM, KDE and ME, and to compare the allocation among roads, spatial clustering, and environmental conditions in the identified hotspots. HCM was applied on the herpetofauna dataset as well as separately on amphibians and reptiles. Although the discrimination skill of KDE and ME models for both target clades together was good to excellent (AUC KDE = 0.944, AUC ME = 0.822), the highest theoretical mitigation efficiency, was displayed by HCM Consensus (2.89), followed by KDE (2.58), and ME (1.91). Furthermore, we show that theoretical mitigation efficiency increases with decreasing spatial clustering (Moran's I). Given pervasive budget constraints, we recommend to limit permanent mitigation measures such as fenced culverts to HCM Consensus hotspots, temporary measures to KDE hotspots, and to target additional monitoring at ME hotspots. [Display omitted] • We propose hybrid consensus modeling (HCM) to identify roadkill hotspots based on kernel density estimation (KDE) and maximum entropy (ME). • HCM identifies and differentiates hotspots, and thence enables differential management. • We evaluate HCM using herpetofauna roadkill data and show that it improves theoretical mitigation efficiency compared to both KDE and ME. [ABSTRACT FROM AUTHOR]