Adapting through practice: Silviculture, innovation and forest governance for the age of extreme uncertainty

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Original languageEnglish
Pages (from-to)50-60
JournalForest Policy and Economics
Volume79
DOIs
StatePublished - 1 Jun 2017

Abstract

Adaptation in forest management is often framed as a scientific challenge, relying on more accurate modelling and better communication from science practice. However future scenarios of extreme uncertainty such as those characterising the Anthropocene may require a more flexible and interactive approach, drawing on a wider range of knowledge. The role of the practitioner in this is often highlighted, but little understood. This paper therefore seeks to contribute to empirical understanding of forest practice and its implications for adaptive forest governance. In the UK, devolved forest administrations are addressing new structures and politics, reduced budgets and staff, and several high impact tree health disasters. In the absence of scientific and operational guidance, foresters are finding new spaces in which to use their silvicultural knowledge, and work flexibly, generating new knowledge and practice through observation and local experiments. The capacity of state forestry organisations to learn and adapt is constrained by resource cuts, reorganisation, poor record keeping, increasingly top-down policy control, and de facto pre-eminence given to timber as the management objective. Individual relationships and personalities can nevertheless support communication and learning. The new circumstances are stimulating an approach which is both creative and grounded in silvicultural knowledge and experience. Important parts of the adaptive process lie with practice and innovation in the forest, rather than hierarchical, science-led approaches, but reality does not present us with a simple dichotomy between deterministic, reductionist forest management, and indeterministic, adaptive, ecosystem approaches. Further attention to practitioners' realities and contribution to knowledge is needed.

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© 2016 Published by Elsevier B.V.

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