Fostering Industrial Symbiosis With Agent-Based Simulation and Participatory Modeling

The sciences of industrial ecology, complex systems, and adaptive management are intimately related, since they deal with flows and dynamic interdependencies between system elements of various kinds. As such, the tool kit of complex systems science could enrich our understanding of how industrial ecosystems might evolve over time. In this article, I illustrate how an important tool of complex systems science— agent-based simulation —can help to identify those potential elements of an industrial ecosystem that could work together to achieve more eco-efficient outcomes. For example, I show how agent-based simulation can generate cost-efficient energy futures in which groups of firms behave more eco-efficiently by introducing strategically located clusters of renewable, low-emissions, distributed generation. I then explain how role-playing games and participatory modeling can build trust and reduce conflict about the sharing of common-pool resources such as water and energy among small clusters of evolving agents. Collective learning can encourage potential industrial partners to gradually cooperate by exchanging by-products and/or sharing common infrastructure by dint of their close proximity. This kind of coevolutionary learning, aided by participatory modeling, could help to bring about industrial symbiosis.     

Exploring the Synergy Between Industrial Ecology and System of Systems to Understand Complexity

Two objectives are pursued in this article. First, from a methodological perspective, we explore the relationships among the constructs of complex adaptive systems, systems of systems, and industrial ecology. Through examination of central traits of each, we find that industrial ecology and system of systems present complementary frameworks for posing systemic problems in the context of sociotechnical applications. Furthermore, we contend that complexity science (the basis for the study of complex adaptive systems) provides a natural and necessary foundation and set of tools to analyze mechanisms such as evolution, emergence, and regulation in these applications. The second objective of the article is to illustrate the use of two tools from complexity sciences to address a network transition problem in air transportation framed from the system-of-systems viewpoint and shaped by an industrial ecology perspective. A stochastic simulation consisting of network theory analysis combined with agent-based modeling to study the evolution of an air transport network is presented. Patterns in agent behavior that lead to preferred outcomes across two scenarios are observed, and the implications of these results for decision makers are described. Furthermore, we highlight the necessity for future efforts to combine the merits of both system of systems and industrial ecology in tackling the issues of complexity in such large-scale, sociotechnical problems.     

Diversity and Connectance in an Industrial Context

The ecological metaphor of industrial ecology is a proven conceptual tool, having spawned an entire field of interdisciplinary research that explores the intimate linkages between industry and its underlying natural systems. Besides its name and a number of borrowed concepts, however, industrial ecology has no formal relationship with the ecological sciences. This study explores the potential for further interdisciplinary collaboration by testing whether some of the same quantitative analysis techniques used in community ecology research can have meaning in an industrial context. Specifically, we applied the ecological concepts of connectance and diversity to an analysis of Burnside Industrial Park in Halifax, Nova Scotia. Our results demonstrate that these ecological tools show promise for use in industrial ecology. We discuss the meaning of connectance and diversity concepts in an industrial context and suggest next steps for future studies. We hope that this research will help to lay the groundwork of an ecologically inspired tool kit for analyzing industrial ecosystems.     

耗散结构、等级系统理论与生态系统

耗散结构理论与其他热力学概念一起,可以解释生态学中的许多现象。生态系统是耗散系统,用耗散结构理论来分析和讨论生态平衡等问题更为合理、准确。等级系统理论是为理解和研究高度复杂系统而发展起来的系统理论。等级系统理论为研究生态系统的行为和特征提供了客观的、适用的概念构架和实践指南,并为生态系统科学的统一性理论的形成开辟了广阔前景。本文拟就耗散结构理论和等级系统理论的主要内容及其在生态学中的应用作一介绍和讨论。     

耗散结构,等级系统理论与生态系统

耗散结构理论与其他热力学概念一起,可以解释生态学中的许多现象。生态系统是耗散系统,用耗散结构理论来分析和讨论生态平衡等问题更为合理、准确。等级系统理论是为理解和研究高度复杂系统而发展起来的系统理论。等级系统理论为研究生态系统的行为和特征提供了客观的、适用的概念构架和实践指南,并为生态系统科学的统一性理论的形成开辟了广阔前景。本文拟就耗散结构理论和等级系统理论的主要内容及其在生态学中的应用作一介绍和讨论。     

Embedding Science in Politics: "Complex Utilization" and Industrial Ecology as Models of Natural Resource Use

Throughout the short history of industrial ecology, issues of implementation have been heavily emphasized. Less attention has been given to the ways in which the technical models of industrial ecology interact with social processes. Yet the practitioners of industrial ecology frequently encounter challenges pertaining to contextualization when embedding a general model in different local contexts. In addition, there are reasons to believe that the models of industrial ecological systems become politically meaningful only when they are carefully contextualized and linked to localized needs. In this article, we aim at a better understanding of the political embedding of industrial ecology. In order to demonstrate some general mechanisms of embedding, we first conduct a frame analysis of complex utilization—a scientific policy instrument analogous to industrial ecology, developed in the Kola Peninsula, Russia. We identify five frames in which complex utilization has been promoted between 1935 and 2005. These frames are then compared to six frames identified in the industrial symbiosis in Kalundborg, Denmark. We find that effective political embedding relies on frames that function both on a general level and in specific contexts. General frames, such as efficiency, economy, and environment, need to be aligned with localized perceptions of particular issues. What is more, sensitivity to purely context-specific frames is necessary for effective political embedding. Finally, the political processes of framing also shape the scientific-technical models that are being promoted.     

Framework for Applying a Complex Adaptive System Approach to Model the Operation of Eco‐Industrial Parks

Models of eco‐industrial parks (EIPs) might help us transform our production systems by fostering the emergence of sustainable EIPs since such models have the potential to support the decision‐making processes of cooperative companies that participate and to decrease operational uncertainties. In this article, a conceptual framework for modeling the operation of EIPs is presented. The framework is underpinned by complex adaptive systems theory, industrial ecology, and an analysis of the experiences of existing EIPs. The proposed framework draws on the observed strengths of two types of industrial symbiosis models—planned eco‐industrial parks (PEIPs) and EIPs that developed through self‐organizing symbiosis (SOS)—as well as their observed weaknesses and the features of complex adaptive systems. From this analysis, five key properties to be modeled are deduced: functionality, reliability, life span, theoretical knowledge, and adaptability. It is proposed that the properties of functionality and theoretical knowledge are determined by the goals of the EIP and its member companies, while the property of adaptability is determined by the understanding that the companies in an EIP have of the environment surrounding the EIP, while the properties of reliability and life span are determined by the internal and external relationships of the companies that make up an EIP.     

中国产业生态学发展的回顾与展望

作为一门探讨产业发展与生态环境之间相互关系的学科,产业生态学需要对我国生态化转型重大战略选择做出贡献。本文回顾与评述了产业生态学在我国的发展,指出产业生态学在我国的起源具有多源性,既有着中国传统哲学的传承,也有着多种工程学科的经验升华,还有着前苏联经验的烙印。在进入新世纪后,我国产业生态学的发展开始深受西方学术的影响,逐渐建立起较为系统的教育、研究和组织体系。这些成果体现在课程开设、学科建设、机构成立和研究发表等方面。本专栏评述了其中的代表性领域并收录了相关成果,例如生命周期评价和产业共生等。在探讨产业生态学学科发展的现实性、理论性及政治性基础上,提出了需要进一步观察、总结和提炼过去的发展实践,需要关注中国根本性和战略性的核心问题,需要建构产业生态学的中国学派,需要加速建设产业生态学的教育和学科发展体系,并接受生态文明转型这一历史使命的挑战,为中国乃至世界产业生态学发展以及产业生态化做出贡献。     

国家重点森林生态功能区产业生态化水平测度与产业-生态的协调发展

以9个国家重点森林生态功能区作为实证研究区域,构建产业化和生态化两个子系统及产业生态化系统发展水平评价指标体系,运用熵值法、耦合协调度模型、剪刀差模型、耦合度模型、Dagum基尼系数和MGWR模型等方法,从县域尺度测度生态功能区建设12年来产业化水平、生态化水平及产业生态化水平发展变化,分析产业化、生态化两个子系统协调发展水平、发展速度差异及动态演化趋势,剖析影响产业生态化发展因素为产业生态化健康发展提供科学支撑。结果表明:(1)12年间产业生态化呈低水平的小幅上升态势,9个功能区间的最大差距呈先下降后上升的波动发展态势。不同功能区间产业生态化水平及产业化水平、生态化水平差异均较大,不同功能区产业生态化水平发展变化的主要内部动因存在较大差异;产业化水平和生态化水平总体均呈小幅上升态势,产业化总体水平低于生态化水平,9个功能区间的最大差距均呈先下降收敛后上升发散的态势;产业生态化、产业化、生态化水平均表现为前一阶段增长快于后一阶段,且后一阶段增速下滑幅度大。(2)12年间产业化与生态化系统二者协调度实现由初级协调到中级协调的提升,9个功能区间协调水平最大差距呈持续上升发展态势。186个县域样本总体协调水平分布呈以初级、中级协调为主,濒临失调、勉强协调和良好协调县份少的"纺锤"形态;产业化增长速率快于生态化增长速率,产业化与生态化发展速率的剪刀差呈小幅下降态势,产业化与生态化发展间差异逐渐缩小,趋向于共同发展阶段。(3)城镇化率、人口密度、人均城乡居民储蓄存款余额、第三产业增加值/第二产业增加值、财政自给率、城镇居民人均可支配收入、每万人医院和卫生院床位数对产业生态化水平呈正向影响,且城镇化率为影响产业生态化水平的正向主导因素。     

工业生态学的内涵与发展

作为一门发展不到20a的综合性交叉学科,工业生态学目前需要界定其学术范畴和理论基础.首先评述了工业生态学的4个主要领域:(1)社会代谢是工业生态学起源最早也是发展最为成熟的领域.它提供了宏观层次上观察和测量经济发展与物质流动关系的方法和工具,但需要进一步细化物质流动图景和加强流动机制的解释;(2)工业共生是工业生态学最具特征的领域.它实质上是人们出于观察视角的转变而对工业体系的重新认识.逻辑严谨且规则统一的解释框架有助于工业共生理论的发展和实践;(3)基础设施与产业相互选择且协同演进,二者共同构成了城市的物质基础,而城市又是更大范围内区域经济系统的子集.这一组工业生态学的研究对象需要处理产业全球化与社会和生态要素本土化的矛盾;(4)工业发展的可持续性是工业生态学关注的核心目标,而多样性和复杂性给其研究带来了很大的挑战.这提醒我们要避免陷入简单化、还原论或机械论的陷阱,多开展实证研究.最后,从本体论、方法论和隐喻3个标准给出了工业生态学的初步界定,并指出4个重要的努力方向.     

Simulation modelling of ecological hierarchies in constructive dynamical systems

Organized complexity is a characteristic feature of ecological systems with heterogeneous components interacting at several spatio-temporal scales. The hierarchy theory is a powerful epistemological framework to describe such systems by decomposing them vertically into levels and horizontally into holons. It was at first developed in a temporal and functional perspective and then, in the context of landscape ecology, extended to a spatial and structural approach. So far, most ecological applications of this theory were restricted to observational purposes, using multi-scale analysis to describe hierarchies. In spite of an increasing attention to dynamics of hierarchically structured ecological systems, current simulation models are still very limited in their representation of self-organization in complex adaptive systems. An ontological conceptualization of the hierarchy theory is outlined, focusing on key concepts, such as levels of organization and the compound and component faces of the holons. Various existing formalisms are currently used in simulation modelling, such as system dynamics, discrete event and agent based paradigms. Their ability to express the hierarchical organization of dynamical ecological systems is discussed. It turns out that a multi-modelling approach linking all these formalisms and oriented toward the specification of a constructive dynamical system would be able to express the dynamical structure of the hierarchy (creation, destruction and change of holons) and the functional and structural links between levels of organization.     

Biodiversity in the context of ecosystem services: the applied need for systems approaches

Recent evidence strongly suggests that biodiversity loss and ecosystem degradation continue. How might a systems approach to ecology help us better understand and address these issues? Systems approaches play a very limited role in the science that underpins traditional biodiversity conservation, but could provide important insights into mechanisms that affect population growth. This potential is illustrated using data from a critically endangered bird population. Although species-specific insights have practical value, the main applied challenge for a systems approach is to help improve our understanding of the role of biodiversity in the context of ecosystem services (ES) and the associated values and benefits people derive from these services. This has profound implications for the way we conceptualize and address ecological problems. Instead of focusing directly on biodiversity, the important response variables become measures of values and benefits, ES or ecosystem processes. We then need to understand the sensitivity of these variables to biodiversity change relative to other abiotic or anthropogenic factors, which includes exploring the role of variability at different levels of biological organization. These issues are discussed using the recent UK National Ecosystems Assessment as a framework.     

产业生态学的回顾与展望

对产业生态学的基本概念、研究方法和研究热点进行了总结与评述,认为产业生态学是研究人类产业活动与自然环境相互关系的一门综合性、垮学科的应用科学。它采用工业代谢、生命周期评价和区域生态建设的方法对产业活动全过程(包括原材料采掘、原材料生产、产品制造、产品使用、产品用后处理)进行定性描述和定量模拟。产业生态学着眼于人类和生态系统的长远利益,追求经济效益、生态效益和社会效益的统一。     

基于现代物种共存理论的入侵生态学概念框架

在入侵生态学60多年的发展历程中, 生态学家提出了多种多样的假说来解释生物入侵的机制。这些纷繁复杂的假说在丰富我们对生物入侵认知的同时, 也给入侵生态学概念的整合带来了困难。其中, 外来种和土著种是否存在生态学差异, 以及这种差异如何影响生物入侵, 是入侵生态学研究和争论的焦点问题。现代物种共存理论通过将外来种和土著种的生态学差异划分为生态位差异和适合度差异, 为入侵生态学概念的整合提供了新的视角。依据该理论, 外来种可以通过两种策略实现成功入侵: 一是扩大与土著种的生态位差异, 二是提高自身相较于土著种的适合度优势。因此, 外来种-土著种的生态位差异和适合度差异共同决定了入侵的成败与危害程度。通过对经典入侵假说进行梳理, 我们发现大部分假说都可以在该理论框架下进行解读, 不同假说的主要差别在于强调不同生态学过程对生态位和适合度差异的影响。同时, 这一理论框架很好地解释了为什么外来种-土著种的亲缘关系和性状差异会对生物入侵产生复杂的影响, 为达尔文归化谜团的和解以及外来种-土著种功能性状的比较研究提供了新的思路。目前, 现代物种共存理论还处于快速发展的阶段, 依旧存在很多不足, 但将其运用到生物入侵的实证研究中将是入侵生态学今后一个重要的发展方向。     

Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology

Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.     

Towards understanding the organisation of metacommunities in highly dynamic ecological systems

Community ecology recognises today that local biological communities are not only affected by local biotic interactions and abiotic environmental conditions, but also by regional processes (e.g. dispersal). While much is known about how metacommunities are organised in space in terrestrial, marine and freshwater ecological systems, their temporal variations remain poorly studied. Here, we address the question of the dynamics of metacommunities in highly variable systems, using intermittent rivers (IRs), those rivers which temporarily stop flowing or dry up, as a model system. We first review how habitat heterogeneity in space and time influences metacommunity organisation. Second, we compare the metacommunities in IRs to those in perennial rivers (PRs) and develop the idea that IRs could undergo highly dynamic shifts due to the temporal variability in local and regional community processes. Third, we develop the idea that in IRs, metacommunities of the wet and dry phases of IRs are closely intertwined, thereby increasing even more their respective temporal dynamics. Last, we provide a roadmap to stimulate further conceptual and empirical developments of metacommunity research and identify possible applications for improving the management of IRs and other highly dynamic ecological systems. Synthesis Extensive research has examined the importance of local biotic interactions, environmental filtering, and regional processes on community assembly. Movement of organisms between sites, i.e. dispersal, is a major set of processes within this framework. However, subsequent metacommunity organisation also varies over time in ecosystems because habitat characteristics such as configuration and composition continuously shift. Intermittent rivers are an ideal set of systems to examine these ideas because these freshwater systems temporarily cease flowing thereby limiting dispersal events. We proposed the hypothesis that metacommunities in dynamic ecosystems will undergo frequent shifts in structure and composition in response to the temporal variability in environmental filtering and dispersal. In addition to providing a roadmap for developing a more dynamic perspective for community ecology, these framework provides direct insights for the management of intermittent rivers.     

产业生态学的回顾与展望

对产业生态学的基本概念、研究方法和研究热点进行了总结与评述,认为产业生态学是研究人类产业活动与自然环境相互关系的一门综合性、垮学科的应用科学．它采用工业代谢、生命周期评价和区域生态建设的方法对产业活动全过程（包括原材料采掘、原材料生产、产品制造、产品使用、产品用后处理）进行定性描述和定量模拟．产业生态学着眼于人类和生态系统的长远利益,追求经济效益、生态效益和社会效益的统一．     

产业生态系统新型定量研究方法综述

产业生态系统研究已成为当今学术界、产业界的研究重点和热点,对于充分利用资源、减轻环境压力、改造升级传统产业都具有不可估量的科学指导意义。目前,国内外对产业生态系统的研究定性较多,包括概念,特点,建设原则和经营理念的描述,而定量较少。然而,产业生态系统在发展当中也出现了大量的实际问题,急需加强对其定量研究,从而发现、提高和改进产业生态系统的结构及效率,增强可持续性。从近些年生态学的先进理论成果入手探讨了定量研究产业生态系统的一些方法——能值、(火用)、生态足迹和生态信息的方法。对这些方法的理论基础、发展历程、实践应用和适用特点依次进行了详细的梳理和归纳,并基于3个基本原则(生态维度和经济维度的整合,系统长期的恢复力,系统的广度和强度性质)对各个方法进行了综合比较分析,旨在为产业生态系统研究提供方向和理论指导。     

Motivation and Benefits of Complex Systems Approaches in Ecology

Studies of complex systems in other disciplines provide models and analytical strategies for understanding ecosystems and landscapes. The emphasis is on invariant properties, particularly processes that create scaling relations over wide ranges of scale, both in time and space. Translations between levels of ecological organization may be accomplished by succinct characterizations of processes that operate at fine scales, followed by renormalization group analysis to reveal patterns at broad scales. The self-organized patterns found in simple ecosystem, landscape, and forest-fire models may be explained as feedback between the system state and control parameters. Critical phenomena and phase transitions are expected in open, dissipative systems where long-range correlations defy predictions based on average population densities, a concept that becomes irrelevant as nonstationary conditions prevail. Thus, complexity theory for open systems relates to the ecology of self-entailing ecosystems that function as their own environments and thereby create constraints through emergence. Received: 14 April 1998; accepted 26 May 1998