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In this paper, we reconsider the defining but often overlooked 'hinge' function of megalopolises by analyzing how megalopolises have articulated national and international urban systems in the context of a globalizing knowledge economy. Taking the case of China's Yangtze River Delta (YRD) region, we particularly focus on knowledge circulation within and beyond the YRD region by analyzing the pattern and process of knowledge collaboration at different geographical scales during the 2004-2014 period. Results show that the structure of scientific knowledge collaboration as reflected by co-publications has been strongest at the national scale whereas that of technological knowledge collaboration as measured by co-patents has been strongest at the global scale. Despite this difference, the structure of both scientific and technological knowledge collaboration has been functionally polycentric at the megalopolitan scale but become less so at the national and global scales. The 'globally connected but locally disconnected' pattern of Shanghai's external knowledge collaboration suggests that the gateway role of the YRD megalopolis in promoting knowledge collaboration at different geographical scales will take time before it is fully realized. [ABSTRACT FROM AUTHOR]

Quantifying the urbanization effect on trends in climate extremes is important both for detection and attribution studies and for human adaptation; however, a fundamental problem is how to accurately estimate a trend and its statistical significance, especially for non-Gaussian and serially dependent data. In this paper, the choice of trend estimation and significance testing method is suggested as important for these kinds of studies, as illustrated by quantifying the urbanization effect on trends in seven hot-extreme indices for the megacity of Shanghai during 1961-2013. Both linear and nonlinear trend estimation methods were used. The trends and corresponding statistical significances were estimated by taking into account potential non-Gaussian and serial dependence in the extreme indices. A new method based on adaptive surrogate data is proposed to test the statistical significance of the ensemble empirical mode decomposition (EEMD) nonlinear trend. The urbanization contribution was found to be approximately 34 % (43 %) for the trend in the non-Gaussian distributed heat wave index based on nonparametric linear trend (EEMD nonlinear trend) estimation. For some of the other six hot-extreme indices analyzed, the urbanization contributions estimated based on linear and nonlinear trends varied greatly, with as much as a twofold difference between them. For the linear trend estimation itself, the ordinary least squares fit can give a substantially biased estimation of the urbanization contribution for some of the non-Gaussian extreme indices. [ABSTRACT FROM AUTHOR]

Urban forest has undergone rapid development in China over the last three decades because of the acceleration of urbanization. Urban forest thus plays an increasingly important role in carbon sequestration at a regional and national scale. As one of the most urbanized cities in China, Shanghai showed an increase of forest coverage from 3% in the 1990s to 13% in 2009. Based on CITY-green model and the second soil survey of Shanghai, the forest biomass carbon (FBC) was estimated to be 0.48 Tg in the urban area and, forest soil organic carbon (SOC) (0-100 cm soil depth) is 2.48 Tg in the urban and suburban areas, respectively. These values are relatively within the median and lower level compared with other Chinese megacities, with the FBC of 0.02 Tg in Harbin to 47.29 Tg in Chongqing and the forest SOC of 1.74 Tg in Nanjing to 418.67 Tg in Chongqing. For the different land-use types in Shanghai, the SOC density ranges from 13.8 (tidal field) to 38.6 t ha (agricultural land). On average, the forest SOC density (31.5 t ha) in Shanghai is lower than that in agricultural lands (38.6 t ha) and higher than that in lawns (26.5 t ha) and gardens (21.3 t ha). In Shanghai, the SOC density in newly established urban parks is generally lower than that in older parks. In the northern and southeastern suburban areas (e.g., Baoshan, Yangpu, and Nanhui districts), greenspace SOC density is higher than that in the central commercial areas (Hongkou, Putuo, Changning, and Zhabei districts) and in newly developed district (Pudong District). Uncertainties still exist in the estimation of urban forest carbon in Shanghai, as well as in other Chinese cities. Thus, future research directions are also discussed in this paper. [ABSTRACT FROM AUTHOR]

Given the important role of land ecosystem in social-economic progress at regional, national, and international scale and concurrent degradation of land ecosystems under rapid urbanization, a systematic diagnosis of land ecological security (eco-security) for sustainable development is needed. A catastrophe model for land ecological security assessment was developed in order to overcome the disadvantages in subjectivity and complexity of the currently used assessment methods. The catastrophe assessment index system was divided into hierarchical sub-systems under the pressure-state-response framework. The catastrophe model integrated multiple assessment indices of land eco-security according to the inherent contradictions and relative importance of indices without calculating weights. Specifically, membership degree of higher level index was calculated based on the membership degrees of lower level indices that were subjective to suitable model, such as cusp, fold, swallowtail and butterfly model. This model was applied to evaluate the state of land eco-security in Shanghai. Mann-Kendall's test was utilized to characterize its temporal trend between 1999 and 2008. Significant downward trend was identified for land eco-security, in terms of pressure sub-index, state sub-index, response sub-index and synthetic index. All these implied that land ecosystem conditions were not optimistic for Shanghai and such situation should draw the attention of policy makers. The calculation procedure presented in this paper does not require a high level of technical expertise to determine the membership degree, making it simple and operational. Being applicable to similar land ecosystems, the catastrophe model is thus believed to provide an alternative approach to land eco-security assessment. [ABSTRACT FROM AUTHOR]