Changing the scale of our thinking: landscape-level learning

Abstract

Developing sustainable forestry practices requires a perspective that encompasses whole and large landscapes; and a broad view of time and geographic space. However; understanding and visualizing the effects of different forest policies on ecological and socioeconomic conditions at such scales is a major challenge. Until recently; we lacked the conceptual framework and analytical tools to study the potential effects of different approaches to forest management over large areas and long periods. With advances in remote sensing; geographic information systems (GIS); and steadily increasing computing power; the ideas for taking the long and the large view can be matched with technologies capable of handling them. This science finding describes a new approach to evaluating sustainability that helps scientists; policymakers; and the public understand the potential consequences of different forest practices at broad landscape scales. The Coastal Landscape Analysis and Modeling Study (CLAMS) takes on the analysis of management and policy effects at broad scales. The study integrates remote sensing; inventory plots; GIS; landowner management intentions; and biophysical models to project potential ecological and socioeconomic consequences of different forest policies in a mapped format. The study is trying to anticipate future problems; rather than just focusing on resolving current ones.

Citation

Kirkland, John; Spies, Thomas. 2002. Changing the scale of our thinking: landscape-level learning. Science Findings 45. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 5 p.