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  • Network Analysis
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  • 1
    Language: English
    In: Energy Policy, January 2016, Vol.88, pp.271-277
    Description: Oil trade is one of the most vital networks in the global economy. In this paper, we analyze the 1998–2012 oil trade networks using the point-wise mutual information (PMI) method and determine the pairwise trade preferences and dependencies. Using examples of the USA's trade partners, this research demonstrates the usefulness of the PMI method as an additional methodological tool to evaluate the outcomes from countries' decisions to engage in preferred trading partners. A positive PMI value indicates trade preference where trade is larger than would be expected. For example, in 2012 the USA imported 2,548.7 kbpd despite an expected 358.5 kbpd of oil from Canada. Conversely, a negative PMI value indicates trade dis-preference where the amount of trade is smaller than what would be expected. For example, the 15-year average of annual PMI between Saudi Arabia and the U.S.A. is −0.130 and between Russia and the USA −1.596. We reflect the three primary reasons of discrepancies between actual and neutral model trade can be related to position, price, and politics. The PMI can quantify the political success or failure of trade preferences and can more accurately account temporal variation of interdependencies.
    Keywords: Trade Dependency ; Point-Wise Mutual Information ; Crude Oil Trade ; Network Analysis ; Energy Policy ; Engineering ; Environmental Sciences ; Economics
    ISSN: 0301-4215
    E-ISSN: 1873-6777
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  • 2
    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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  • 3
    Language: English
    In: Ecological Modelling, 24 June 2015, Vol.306, pp.174-184
    Description: China's Shandong Lubei eco-industrial park was approved for construction in 2003, just after the first national eco-industrial demonstration parks were confirmed by China's State Environmental Protection Administration in 2002. It has therefore been recognized around the world as a successful example of an industrial symbiosis system. The park's success results from the harmonious and coordinated relationships among its members. Analyzing the ecological characteristics of these relationships and identifying the resulting advantages provide a basis for improving the park's efficiency and examining other parks. In this paper, we analyzed the flows of sulfur in the Lubei park (as an example of typical flows) using ecological network analysis to describe this industrial symbiosis system. The integrated analysis of the utility resulting from direct and indirect exchanges of byproducts and wastes can reflect the ecological relationships among members within the system. Based on these ecological relationships, members can be divided into producers, primary consumers, and secondary consumers; the integral flow weight for each level of the hierarchy can then be compared to reveal the system's overall ecological structure. By examining the exchanges of resources within the system, we can describe the ecological connotations of the symbiosis and how these ecological relationships influence the overall development and resource flows within the system.
    Keywords: Industrial Symbiosis ; Ecological Network Analysis ; Utility Analysis ; Lubei Eco-Industrial Park ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 4
    Language: English
    In: PLoS ONE, 01 January 2017, Vol.12(2), p.e0171184
    Description: Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks' redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks.
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 5
    Language: English
    In: Ecological Modelling, 24 June 2015, Vol.306, pp.160-173
    Description: Robustness is a universal feature of ecological systems which promotes sustainability over time. Robustness of an aquatic ecosystem, specifically an estuarine system, is investigated here using indicators derived from ecological network analysis. Estuaries provide us with many ecosystem services and these are consequently prone to face anthropogenic stresses. In South Africa, temporarily open/closed estuaries occupy a significant percentage of coastal boundaries. One of the South African estuaries, namely Mdloti, is studied here using network-based, Ecopath software. The estuarine energy flow networks are perturbed following different scenarios, which are assumed to be a result of selected anthropogenic stresses (eutrophication, overfishing) to the system. Several network indices such as total system throughput (TST), redundancy ( ), Finn’s Cycling Index (FCI) and ascendency over development capacity ratio ( / ) are calculated and analyzed for the original field-based network and three perturbed networks under different scenarios (change of autotrophic biomass, fish yield, and detritus import). The change of ecosystem robustness from the unperturbed network is more pronounced in the perturbed networks of fish biomass change and detritus import than change in autotrophic biomass scenario. These indicators reliably reflected the relative change of flow pattern if any changes occur and magnitude in the networks in different scenarios. From the present study, we show that certain common network indices as mentioned above provide a measure of robustness and can be used for the assessment of ecosystem organization and function. ENA properties and also robustness change depending on the type and magnitude of stress imposed on the system.
    Keywords: Network Analysis ; Ascendency ; Development Capacity ; Redundancy ; Perturbation ; Mdloti Estuary ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 6
    Language: English
    In: International Journal of Design & Nature and Ecodynamics, 2017, Vol.12(1), pp.1-15
    Description: One of the great advances of the 20th century was the rise of a formal systems science and systems thinking. This progress influenced ecology in ways that provided new insight to the structure and function of ecosystems using tools from thermodynamics, networks, information theory, and more. We have been able to increase our understanding of how ecosystems function in terms of using available energy to create complex structures to move away from thermodynamic equilibrium and how these self-organizing structures adapt to changing situations. Ecological goal functions can measure this orientation of ecosystem growth and development (EGD). This presentation addresses how these metrics attuned for ecosystems have relevant application in socio-economic systems. In particular, energy network science is a new paradigm that draws from thermodynamics, information theory, and network analysis to assess the organization, patterns, and dynamics of diverse systems such as ecosystems, financial systems, and urban metabolism. Our understanding of sustainable systems is informed by knowing how ecological and other far-from-thermodynamic equilibrium systems create, maintain, and sustain their functional activities. This approach builds from the seminal efforts of systems thinkers such as Gregory Bateson, Buzz Holling, Jane Jacobs, Sven Jorgensen, Donella Meadows, Jacob Moreno, Bernard Patten, Joseph Tainter, Robert Ulanowicz, and Ilya Prigogine.
    Keywords: Ecology ; Thermodynamics ; Ecosystems ; Meadows ; Energy ; Socioeconomics ; Sustainability ; Metabolism ; Energy ; Autocatalysis ; Ecological Goal Functions ; Network Analysis ; Succession ; Sustainability ; Systems Ecology ; Thermodynamics;
    ISSN: 1755-7437
    E-ISSN: 1755-7445
    Source: CrossRef
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  • 7
    In: Ecological Questions, 01/1/2012, Vol.16(1)
    Description: Abstract Network Environ Analysis, based on network theory, reveals the quantitative and qualitative relations between ecological objects interacting with each other in a system. The primary result from the method provides input and output “environs”, which are internal partitions of the objects within system flows. In addition, application of Network Environ Analysis on empirical datasets and ecosystem models has revealed several important and non-intuitive results that have been identified and summarized in the literature as network environ properties. Network Environ Analysis requires data including the inter-compartmental flows, compartmental storages, and boundary input and output flows. Software is available to perform this analysis on the collected data. This article reviews the theoretical underpinning of the analysis and briefly introduces some the main properties such as indirect effects ratio, network homogenization, and network mutualism.
    Keywords: Ecology;
    ISSN: 1644-7298
    E-ISSN: 20835469
    Source: CrossRef
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  • 8
    Language: English
    In: Ecological Modelling, 2010, Vol.221(16), pp.1865-1879
    Description: Urban metabolism research faces difficulties defining ecological trophic levels and analyzing relationships among the metabolic system's energy components. Here, we propose a new way to perform such research. By integrating throughflow analysis with ecological network utility analysis, we used network flows to analyze the metabolic system's network structure and the ecological relationships within the system. We developed an ecological network model for the system, and used four Chinese cities as examples of how this approach provides insights into the flows within the system at both high and low levels of detail. Using the weight distribution in the network flow matrix, we determined the structure of the urban energy metabolic system and the trophic levels; using the sign distribution in the network utility matrix, we determined the relationships between each pair of the system's compartments and their degrees of mutualism. The model uses compartments based on 17 sectors (energy exploitation; coal-fired power; heat supply; washed coal; coking; oil refinery; gas generation; coal products; agricultural; industrial; construction; communication, storage, and postal service; wholesale, retail, accommodation, and catering; household; other consuming; recovery; and energy stocks). Analyzing the structure and functioning of the urban energy metabolic system revealed ways to optimize its structure by adjusting the relationships among compartments, thereby demonstrating how ecological network analysis can be used in future urban system research.
    Keywords: Urban Metabolism ; Energy Metabolism ; Network Analysis ; Throughflow Analysis ; Utility Analysis ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 9
    Language: English
    In: Ecological Modelling, 2009, Vol.220(22), pp.3210-3218
    Description: This research compares two existing methodologies, mixed trophic impact analysis and utility analysis, which use network analysis to evaluate the direct, pair-wise, and indirect, holistic, ecological relations between ecosystem compartments. The two approaches have many similarities, but differ in some key assumptions which affect both the final results and interpretations. Here, we briefly introduce both methodologies through a series of two simple examples; a 3-compartment competition model and a 3-compartment food chain model, and then apply the methodologies to a 15-compartment ecosystem model of the Chesapeake Bay. This example demonstrates how implementing the various conceptual and methodological assumptions lead to differing results. Notably, the overall number of positive relations is greatly affected by the treatment of the self-interactions and the handling of detritus compartments lead to a distinction between ecological or trophic relations. We recommend slight changes to both methodologies, not necessarily in order to bring them completely together, but because each has some points which are stronger and better defensible.
    Keywords: Ecological Network Analysis ; Flow Analysis ; Mutualism ; Competition ; Indirect Effects ; Food Webs ; Ecological Relations ; Trophic Relations ; Predator–Prey Relations ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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  • 10
    Language: English
    In: Ecological Modelling, 2007, Vol.208(1), pp.17-24
    Description: Standard ecology textbooks typically maintain that nutrients cycle, but energy flows in unidirectional chains. However, here we use a new metric that allows for the identification and quantification of cyclic energy pathways. Some of these important pathways occur due to the contribution of dead organic matter to detrital pools and those organisms that feed on them, reintroducing some of that energy back into the food web. Recognition of these cyclic energy pathways profoundly impacts many aspects of ecology such as trophic levels, control, and the importance of indirect effects. Network analysis, specifically the maximum eigenvalue of the connectance matrix, is used to identify both the presence and strength of these structural cycles.
    Keywords: Cycling ; Detritus ; Energy Flow ; Food Webs ; Network Analysis ; Trophic Dynamics ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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