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“Complexity” is a multifaceted term. Scientists, managers, and the public may mean quite different things by the term, since they each have distinct personal experiences that influence ideas and processes. Complexity science and related theories derive from natural science disciplines such as physics and chemistry. There is a widely recognized fact that the practice of managing human-environment interactions is complex. Complexity science and theories have become increasingly influential in environmental management in the last decade or so, following in the footsteps of broader systems and ecosystem concepts that became influential in the 1960s and 1970s.
The earlier incorporation of systems and ecosystem approaches into environmental planning and management brought home the connected and hierarchical nature of human-environment systems: connections between ecosystems, economies and societies, and between levels of ecological or government systems, for example. It also underscored basic thermodynamic implications: every activity uses or transforms energy and matter and produces waste, which in turn must go somewhere, being transformed again and again but never actually going away.
Complex and Dynamic Interaction
As environmental research continued, most famously into forest-insect pest dynamics, fisheries management and weather and climate forecasting, it became clear that ecosystems and human-environment systems were much more complex and dynamic than assumed. This made them difficult or impossible to predict, and even harder to manage for specific, maximum, sustainable yields and similar optimum goals. Change is increasingly recognized as normal and common, and predictability as rare-whether we are looking at animal populations, weather changes, or the desired and undesired effects of new products or management approaches.
What is meant by complexity? To begin with, complexity may encompass many parts, but that in itself is complicated. And if there are many parts involved, then statistics and probability come into play and yield a form of predictability. Complexity in an environmental management context means more than a few (but not astronomically large) numbers of parts-what Gerald Weinberg called middle number systems. Complexity also entails extensive connectedness of a system.
These are connections between social, economic, and ecological structures and processes; between individuals and organizations; and across scales from the local to the global. Complexity approaches recognize that systems are not static or unchanging, or even necessarily stable. In fact, they may change in major, qualitative, and sudden ways, and exhibit patterns of change over time that are themselves very complicated or even complex; this is not the simple straight lines or even gradual oscillations on a traditional x-y graph that we base our thinking. Patterns of change may seem completely random, or “chaotic,” never repeating or showing any noticeable pattern at all.
The key natural science complexity theories that underlie these insights include chaos theory, self-organization, fractals, and others such as catastrophe theory that go back to the 1960s. All of these derive from looking at the structure and behavior of physical and chemical systems in space and time, and later from applications to biological, ecological, economic, and social systems with varied degrees of success and rigor.
The roots of chaos theory go back to the 19thcentury physics and dynamics work of Henri Poincare, which was first credited to Edward Lorenz’s work in forecasting weather and atmospheric dynamics. He found that small errors in describing an atmospheric system’s initial state rapidly amplified to large errors in a prediction of its future state. This has been called sensitive dependence on initial conditions. It is a result of nonlinear dynamics in the system, positive feedbacks, and other interactions that greatly amplify small differences as the system evolves in time. Self-organization ideas derive from work in complex chemical reactions that self-catalyze, and exhibit spatial and temporal patterns; or from the dynamics of lasers. Such systems dissipate energy and resources in maintaining their internal dynamics (like living organisms) through complex internal structure and connections. They go through periods of stability followed by instability in which their internal condition fluctuates, but ultimately “self-organizes” through internal nonlinear dynamics and amplification into a particular future state-which may well be a sudden, major transformation. Fractals are a form of complexity found in spatial, physical objectives-most famously in coastlines that get longer the finer the measuring stick you use, and which, like snowflakes, show similar patterns as different scales of resolution. The various complexity theories are connected at fairly deep, mathematical, and theoretical levels. For example, complex systems may exhibit complex, but not random patterns in time. These are called attractors, and mathematically, some are fractal in structure.
All of these theories are difficult to apply to humanenvironment systems in a quantitative way-it’s a challenge even in purely biophysical contexts such as ecological or atmospheric systems. So they have primarily had influence by analogy and metaphor, as inspirations for newer, more systems-oriented frameworks for analyzing and describing human-environment systems. They have been a strong influence in ecosystem approaches and ecosystem management. Adaptive management, which seeks to adapt to uncertainty by treating management as an experiment and designing and implementing management to ensure ongoing learning, was an early response.
- C. S. Holling and his colleagues have extended adaptive management into panarchy theory, which sees adaptive cycles of stability, disturbance, release, and reorganization in many human-environment systems. Fikret Berkes and colleagues write about resilience and social-ecological systems and their connectedness, changeability, and integral social, cultural, and institutional elements. Others have developed an Adaptive Methodology for Ecosystem System Sustainability and Health (AMESH) that draws deeply on complex systems ideas as well as the linked ideas of post-normal science.
Overall, the implications of complexity for human-environment systems include greater prominence for disturbance and change; greater recognition of how human intervention can alter natural processes that can have unintended consequences; greater recognition of the potential for sudden change in natural and human systems; and greater efforts to adapt to uncertainty through approaches such as adaptive management, adaptive governance, or precautionary management. An understanding of system dynamics is improved through nuanced notions of stability, including resilience and resistance, as well as more knowledge of the potentially complex, yet nonrandom patterns of system behavior. Researchers and managers are also increasingly driven to new approaches in science and human-environment systems intervention, driven by the complexities and uncertainties of the systems. While the implications of complexity for environmental planning and management are just beginning to be filtered, there are strong hints of the new understanding to be gained and the new approaches that are needed. These will extend traditional, single discipline-based prediction, master planning, and control to multiand trans-disciplinary, participatory, and action-oriented development of many smaller, and adaptable plans that seek to influence-rather than control-complex humanenvironment systems.
- Fikret Berkes, J. Colding, and C. Folke, , Navigating Social-Ecological Systems: Building Resilience for Complexity and Change (Cambridge University Press, 2003);
- John Gribbin, Deep Simplicity: Bringing Order to Chaos and Complexity (Random House, 2004);
- Lance H. Gunderson and C.S. Holling, , Panarchy: Understanding Transformations in Human and Natural Systems (Island Press, 2002);
- Michael Jackson, Systems Thinking: Creative Holism for Managers (John Wiley & Sons, 2003);
- Stuart Kauffman, At Home in the Universe: The Search for the Laws of Self-Organization and Complexity (Oxford University Press, 1995);
- Kai Lee, Compass and Gyroscope: Integrating Science and Politics for the Environment (Island Press, 1993);
- Nicolis and I. Prigogine, Exploring Complexity: An Introduction (W.H. Freeman & Company, 1989);
- David Waltner-Toews, Ecosystem Sustainability and Health: A Practical Approach (Cambridge University Press, 2004);
- Gerald M. Weinberg, An Introduction to General Systems Thinking (John Wiley & Sons, 1975).