Managing Overwhelming Complexity In Human-Landscape Interactions

Nicholas Magliocca

Abstract


Humans have been altering the natural landscape for millennia (e.g. Pyne, 2001; Fagan, 2004), but increasing population growth and technological innovations are out-pacing management of this landscape (e.g. Hooke, 1994; Haff, 2003). Today’s human-ecosystem interactions are overwhelmingly complex, reducing management agencies and policy solutions to ineffective, short-term interventions. The urban- “wildland” interface (UWI) of the Los Angeles basin is the focal research problem of this paper. A system of inquiry is proposed that focuses management efforts on strongly coupled human-landscape interactions and the emergent behaviors that result. This system of inquiry serves as the conceptual framework for a computer model used to examine the dynamic behavior of the urban-wildland boundary.
Current management strategy calls for the suppression of regular fires to minimize the loss of lives and property. However, this management strategy disrupts the natural dissipative processes that stabilize the urban-wildland boundary and creates delayed feedbacks. Management must recognize coupling between system components that may not be apparent in the short term but dominate system behavior on longer time scales. The accumulation of energy (fuel, development, suppression force, etc.) may lead to catastrophic events in the form of large fires and/or landslides. The perceived system behavior is a filtering-out of small, frequent fires on short time scales, and the emergence of catastrophic fire events on longer time scales.
The proposed system of inquiry can be used to focus management solutions on the emergent, synergistic interactions that are driving human-landscape problems. It is a tool that can enable stakeholders to properly manage the coupled interactions between society and the surrounding landscape on multiple time scales.

Keywords


Human-landscape interactions; urban-wildland interface (UWI);
emergent coupled behavior; delayed feedback.

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