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Статья

REDISCOVERY OF TRADITIONAL ECOLOGICAL KNOWLEDGE AS ADAPTIVE MANAGEMENT

Fikret BerkesNatural Resources Institute, University of Manitoba, Winnipeg, Manitoba R3T 2N2, CanadaJohan ColdingNatural Resources Management, Department of Systems Ecology, Stockholm University, S-10691 Stockholm, Sweden and Beijer International Institute of Ecological Economics, Royal Swedish Academy of Sciences, Box 50005, S-10405 Stockholm, SwedenCarl FolkeNatural Resources Management, Department of Systems Ecology, Stockholm University, S-10691 Stockholm, Sweden and Beijer International Institute of Ecological Economics, Royal Swedish Academy of Sciences, Box 50005, S-10405 Stockholm, Sweden
2000en
ABI

Аннотация

Indigenous groups offer alternative knowledge and perspectives based on their own locally developed practices of resource use. We surveyed the international literature to focus on the role of Traditional Ecological Knowledge in monitoring, responding to, and managing ecosystem processes and functions, with special attention to ecological resilience. Case studies revealed that there exists a diversity of local or traditional practices for ecosystem management. These include multiple species management, resource rotation, succession management, landscape patchiness management, and other ways of responding to and managing pulses and ecological surprises. Social mechanisms behind these traditional practices include a number of adaptations for the generation, accumulation, and transmission of knowledge; the use of local institutions to provide leaders/stewards and rules for social regulation; mechanisms for cultural internalization of traditional practices; and the development of appropriate world views and cultural values. Some traditional knowledge and management systems were characterized by the use of local ecological knowledge to interpret and respond to feedbacks from the environment to guide the direction of resource management. These traditional systems had certain similarities to adaptive management with its emphasis on feedback learning, and its treatment of uncertainty and unpredictability intrinsic to all ecosystems.

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