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Understanding plantation transformation using a size-structured spatial population model

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Original languageEnglish
Pages (from-to)799-809
Number of pages11
JournalForest Ecology and Management
Volume261
Issue number3
DOIs
StatePublished - 1 Feb 2011

Abstract

Plantation transformation is a goal of increasing interest to silviculturalists. The target forest state is characterised by high variance in age and size, and an irregular spatial structure, which leads to inhomogeneous interactions between, and consequent development of, trees in the stand. This presents a difficulty for traditional methods such as yield tables, and demands a more careful consideration of stand dynamics. On the other hand, while forestry has a great heritage of simulation, the level of complexity implemented at an individual level generally precludes direct understanding of stand scale behaviours, and leads to difficulties in verification with appropriate data.

A promising approach is the application of relatively simple models developed by ecologists. These can be adapted to yield accurate representations of forest stands, while being highly amenable to analysis. Motivated by data from Scots pine (Pinus sylvestris L) stands, we here apply a simple spatial birth-death-growth model to the comparison and analysis of transformation strategies for plantation stands. The model captures the effects of neighbours in a way which retains the conceptual simplicity of a generic, analytically solvable model, while allowing insights into the driving factors of population dynamics.

Timing and intensity of management interventions, as opposed to their specific criteria, are of primary importance: thinnings of a moderate intensity performed over a long period produced the best results. Variation in the strategy applied leads to more subtle effects which transformation strategies must also take into account, such as the development of variation in size of the remaining trees (increased using spatially correlated thinnings), the survival chances of regeneration and "underplanted" trees, and the overall productivity of the stand (increased using spatially homogeneous crown thinning). Finally, we demonstrate the robustness of model predictions to fundamental choices of model formulation. (C) 2010 Elsevier B.V. All rights reserved.

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