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The Role of Economic Diversification in Forest Ecosystem Management

Knoke, Thomas, Messerer, Katharina, Paul, Carola
Curr Forestry Rep 2017 v.3 no.2 pp. 93-106
age structure, biodiversity, costs and returns, ecosystem management, ecosystem services, forest management, forests, landowners, risk reduction, trees, wood logs
PURPOSE OF REVIEW: We give an overview of economic drivers and consequences of diversification in forest management. Starting with formal portfolio-theory analyses of the optimal forest composition, we review other, often-disregarded factors that influence diversification. A special focus of our review is the interrelation between economic diversification and multifunctionality, asking if optimal economic diversification supports increased levels of multiple ecosystem services as a positive externality. RECENT FINDINGS: Analyses considering economic diversification in forest management mainly build on Markowitz’ theory of portfolio selection, which is essentially a statistical theory. They emphasize that the economic diversification of forest composition, regeneration and/or thinning strategies, quality of timber logs, or age classes can significantly reduce risks. Further studies assume that risk-averse landowners will provide benefits for the society as a by-product of their management strategies, because economic diversification is usually associated with enhanced biodiversity and higher levels of multiple ecosystem services. We identify drivers and consequences of economic diversification that have been seldom addressed in previous studies. These include the aim to achieve subsistence, to balance site-dependent marginal economic return among various stand types, to utilize synergistic effects between mixed tree species and to achieve averaging effects over time (time diversification). Another important factor influencing and influenced by diversification is multifunctionality, because economic diversification alone does not necessarily automatically provide a larger range of uncertain ecosystem services. Consequently, future research could extend classical portfolio approaches to multi-objective, robust optimization.