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Graves, A. R., Burgess, P. J., Palma, J. H., Herzog, F., Moreno, G., Bertomeu, M., & Van den Briel, J. P. (2007). Development and Application of Bio-Economic Modelling to Compare Silvoarable, Arable, and Forestry Systems in Three European Countries. Ecological Engineering, 29, 434-449.
http://dx.doi.org/10.1016/j.ecoleng.2006.09.018

has been cited by the following article:

• TITLE: Modelling Financially Optimal Afforestation and Forest Management Scenarios Using a Bio-Economic Model

  AUTHORS: Mary Ryan, Cathal O’Donoghue, Henry Phillips

  KEYWORDS: Forestry, Bio-Economic Modelling, Afforestation, Optimisation

  JOURNAL NAME: Open Journal of Forestry, Vol.6 No.1, January 11, 2016

  ABSTRACT: The expansion of non-industrial private forests (NIPF) in Ireland is unique in the European context in which the almost doubling of forest cover within the last thirty years has taken place largely on farmland. This is not surprising as Ireland has some of the highest growth rates for conifers in Europe and also has a large proportion of land which is marginal for agriculture but highly productive under forests. However, in recent years, afforestation in Ireland as in many European countries has fallen well short of policy targets. As the farm afforestation decision essentially involves an inter-temporal land use change, farmers need comprehensive information on forest market returns under different environmental conditions and forest management regimes. This paper describes the systematic development of a cohort forest bio-economic model which examines financially optimal afforestation and management choices. Simulating a range of productivity and harvesting scenarios for Sitka spruce, we find that different objectives result in different outcomes. We see substantial differences between the biologically optimal rotation, the reduced rotation in common usage and the financially optimal rotation which maximises net present value and find that the results are particularly sensitive to the choice of management and methodological assumptions. Specifically, we find that better site productivity and thin versus no-thin options result in shorter rotations across all optimisations, reinforcing the usefulness of this type of financial modelling approach. This information is critical for future policy design to further incentivise afforestation of agricultural land.