Optimal management of naturally regenerating uneven-aged forests

Ankur Sinha, Janne Rämö, Pekka Malo, Markku Kallio and Olli Tahvonen

European Journal of Operational Research, 2017, vol. 256, issue 3, 886-900

Abstract: A shift from even-aged forest management to uneven-aged management practices leads to a problem rather different from the existing straightforward practice that follows a rotation cycle of artificial regeneration, thinning of inferior trees and a clearcut. A lack of realistic models and methods suggesting how to manage uneven-aged stands in a way that is economically viable and ecologically sustainable creates difficulties in adopting this new management practice. To tackle this problem, we make a two-fold contribution in this paper. The first contribution is the proposal of an algorithm that is able to handle a realistic uneven-aged stand management model that is otherwise computationally tedious and intractable. The model considered in this paper is an empirically estimated size-structured ecological model for uneven-aged spruce forests. The second contribution is on the sensitivity analysis of the forest model with respect to a number of important parameters. The analysis provides us an insight into the behavior of the uneven-aged forest model.

Keywords: Natural resources; Forest management; Nonlinear programing; Evolutionary algorithms (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:256:y:2017:i:3:p:886-900

DOI: 10.1016/j.ejor.2016.06.071

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