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  • 1
    Language: English
    In: The Science of the Total Environment, Jan 15, 2014, Vol.468-469, p.642(12)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.scitotenv.2013.08.047 Byline: Yan Zhang, Hongmei Zheng, Brian D. Fath, Hong Liu, Zhifeng Yang, Gengyuan Liu, Meirong Su Abstract: If cities are considered as "superorganisms", then disorders of their metabolic processes cause something analogous to an "urban disease". It is therefore helpful to identify the causes of such disorders by analyzing the inner mechanisms that control urban metabolic processes. Combining input-output analysis with ecological network analysis lets researchers study the functional relationships and hierarchy of the urban metabolic processes, thereby providing direct support for the analysis of urban disease. In this paper, using Beijing as an example, we develop a model of an urban metabolic system that accounts for the intensity of the embodied ecological elements using monetary input-output tables from 1997, 2000, 2002, 2005, and 2007, and use this data to compile the corresponding physical input-output tables. This approach described the various flows of ecological elements through urban metabolic processes and let us build an ecological network model with 32 components. Then, using two methods from ecological network analysis (flow analysis and utility analysis), we quantitatively analyzed the physical input-output relationships among urban components, determined the ecological hierarchy of the components of the metabolic system, and determined the distribution of advantage-dominated and disadvantage-dominated relationships, thereby providing scientific support to guide restructuring of the urban metabolic system in an effort to prevent or cure urban "diseases". Article History: Received 16 May 2013; Revised 8 August 2013; Accepted 17 August 2013 Article Note: (miscellaneous) Editor: Simon James Pollard
    ISSN: 0048-9697
    Source: Cengage Learning, Inc.
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  • 2
    Language: English
    In: Science of the Total Environment, 15 February 2016, Vol.544, pp.103-113
    Description: In this paper, we construct a spatially explicit model of carbon metabolism for the flows of carbon among the components of an urban area. We used the model to identify spatial heterogeneity in the ecological relationships within a carbon metabolic network. We combined land-use and cover type maps for Beijing from 1990 to 2010 with empirical coefficients and socioeconomic data to quantify the flows. We used utility analysis to determine the ecological relationships between the components of the system and analyzed their changes during urban development. We used ArcGIS to analyze their spatial variation. We found that the positive utilities in Beijing decreased over time and that negative relationships mostly outweighed positive relationships after 2000. The main ecological relationships were distributed throughout the entire urban area before 2000; subsequently, exploitation, control, and mutualism relationships became concentrated in the southeast, leaving competition relationships to dominate the northwest. Mutualism relationships were most common for natural components, but were not stable because they were easily disturbed by urban expansion. Transportation and industrial land and urban land were the most important contributors to exploitation and control relationships and may be important indicators of spatial adjustment. Increasing competition relationships unbalanced the carbon metabolism, and limitations on the area of land available for development and on the water resources led to increasingly serious competition. The results provide an objective basis for planning adjustments to Beijing's land-use patterns to improve its carbon metabolism and reduce carbon emission.
    Keywords: Urban Metabolism ; Ecological Relationships ; Ecological Network Analysis ; Spatial Analysis ; Land-Use and Cover Change ; Carbon Emission ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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  • 3
    Language: English
    In: Science of the Total Environment, 2010, Vol.408(20), pp.4702-4711
    Description: Using , we analyzed the network structure and ecological relationships in an urban water metabolic system. We developed an ecological network model for the system, and used Beijing as an example of analysis based on the model. We used network throughflow analysis to determine the flows among components, and measured both indirect and direct flows. Using a network utility matrix, we determined the relationships and degrees of mutualism among six compartments – 1) local environment, 2) rainwater collection, 3) industry, 4) agriculture, 5) domestic sector, and 6) wastewater recycling – which represent producer, consumer, and reducer trophic levels. The capacity of producers to provide water for Beijing decreased from 2003 to 2007, and consumer demand for water decreased due to decreasing industrial and agricultural demand; the recycling capacity of reducers also improved, decreasing the discharge pressure on the environment. The ecological relationships associated with the local environment or the wastewater recycling sector changed little from 2003 to 2007. From 2003 to 2005, the main changes in the ecological relationships among components of Beijing's water metabolic system mostly occurred between the local environment, the industrial and agricultural sectors, and the domestic sector, but by 2006 and 2007, the major change was between the local environment, the agricultural sector, and the industrial sector. The other ecological relationships did not change during the study period. Although Beijing's mutualism indices remained generally stable, the ecological relationships among compartments changed greatly. Our analysis revealed ways to further optimize this system and the relationships among compartments, thereby optimizing future urban water resources development.
    Keywords: Urban Ecological Networks ; Urban Water Metabolism ; Throughflow Analysis ; Utility Analysis ; Ecological Network Analysis ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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  • 4
    Language: English
    In: Science of the Total Environment, 2010, Vol.408(12), pp.2425-2434
    Description: Due to the important role of cities for regional, national, and international economic development and the concurrent degradation of the urban environmental quality under rapid urbanization, a systematic diagnosis of urban ecosystem health for sustainable ecological management is urgently needed. This paper reviews the related research on urban ecosystem health assessment, beginning from the inception of urban ecosystem health concerns propelled by the development needs of urban ecosystems and the advances in ecosystem health research. Concepts, standards, indicators, models, and case studies are introduced and discussed. Urban ecosystem health considers the integration of ecological, economic, social and human health factors, and as such it is a value-driven concept which is strongly influenced by human perceptions. There is not an absolute urban ecosystem standard because of the uncertainty caused by the changing human needs, targets, and expectation of urban ecosystem over time; thus, suitable approaches are still needed to establish health standards of urban ecosystems. Several conceptual models and suitable indicator frameworks have been proposed to organize the multiple factors to represent comprehensively the health characteristics of an urban ecosystem, while certain mathematical methods have been applied to deal with the indicator information to get a clear assessment of the urban ecosystem health status. Instead of perceiving the urban ecosystem assessment as an instantaneous measurement of the health state, it is suggested to conceptualize the urban ecosystem health as a process, which impels us to focus more studies on the dynamic trends of health status and projecting possible development scenarios.
    Keywords: Urban Ecosystem Health ; Health Assessment ; Ecosystem Indicators ; Ecosystem Model ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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  • 5
    Language: English
    In: Science of the Total Environment, 15 January 2014, Vol.468-469, pp.642-653
    Description: If cities are considered as “superorganisms”, then disorders of their metabolic processes cause something analogous to an “urban disease”. It is therefore helpful to identify the causes of such disorders by analyzing the inner mechanisms that control urban metabolic processes. Combining input–output analysis with ecological network analysis lets researchers study the functional relationships and hierarchy of the urban metabolic processes, thereby providing direct support for the analysis of urban disease. In this paper, using Beijing as an example, we develop a model of an urban metabolic system that accounts for the intensity of the embodied ecological elements using monetary input–output tables from 1997, 2000, 2002, 2005, and 2007, and use this data to compile the corresponding physical input–output tables. This approach described the various flows of ecological elements through urban metabolic processes and let us build an ecological network model with 32 components. Then, using two methods from ecological network analysis (flow analysis and utility analysis), we quantitatively analyzed the physical input–output relationships among urban components, determined the ecological hierarchy of the components of the metabolic system, and determined the distribution of advantage-dominated and disadvantage-dominated relationships, thereby providing scientific support to guide restructuring of the urban metabolic system in an effort to prevent or cure urban “diseases”.
    Keywords: Beijing ; Ecological Network ; Physical Input–Output Table ; Urban Ecology ; Urban Metabolism ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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  • 6
    Language: English
    In: Science of the Total Environment, 10 January 2019, Vol.647, pp.1080-1087
    Description: Land-climate interactions are driven by causal relations that are difficult to ascertain given the complexity and high dimensionality of the systems. Many methods of statistical and mechanistic models exist to identify and quantify the causality in such highly-interacting systems. Recent advances in remote sensing development allowed people to investigate the land-climate interaction with spatially and temporally continuous data. In this study, we present a new approach to measure how climatic factors interact with each other under land cover change. The quantification method is based on the correlation analysis of the different order derivatives, with the canonical mathematical definitions developed from the theories of system dynamics and practices of the macroscopic observations. We examined the causal relationship between the interacting variables on both spatial and temporal dimensions based on macroscopic observations of land cover change and surface climatic factors through a comparative study in the different grassland ecosystems of China. The results suggested that the interaction of land-climate could be used to explain the temporal lag effect in the comparison of the three grassland ecosystems. Significant spatial correlations between the vegetation and the climatic factors confirmed feedback mechanisms described in the theories of eco-climatology, while the uncertain temporal synchronicity reflects the causality among the key indicators. This has been rarely addressed before. Our research show that spatial correlations and the temporal synchronicity among key indicators of the land surface and climatic factors can be explained by a novel method of causality quantification using derivative analysis.
    Keywords: Remote Sensing ; Grassland ; Land-Climate ; Cause-Effect ; Correlation Analysis ; Eco-Climatology ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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  • 7
    Language: English
    In: Science of the Total Environment, 2019, Vol.647, pp.1080-1087
    Description: Land-climate interactions are driven by causal relations that are difficult to ascertain given the complexity and high dimensionality of the systems. Many methods of statistical and mechanistic models exist to identify and quantify the causality in such highly-interacting systems. Recent advances...
    Keywords: Cause-Effect ; Correlation Analysis ; Eco-Climatology ; Grassland ; Land-Climate ; Remote Sensing
    ISSN: 0048-9697
    Source: NARCIS (National Academic Research and Collaborations Information System)
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