A climate-sensitive empirical growth and yield model for forest management planning of even-aged beech stands

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• 作者：Antoni Trasobares ; Andreas Zingg ; Lorenz Walthert…
• 关键词：Climate change ; Soil water holding capacity ; Forest site evaluation ; Mixed models ; Simulation ; Optimization
• 刊名：European Journal of Forest Research
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：135
• 期：2
• 页码：263-282
• 全文大小：1,328 KB
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• 作者单位：Antoni Trasobares (1)
  Andreas Zingg (2)
  Lorenz Walthert (2)
  Christof Bigler (1)
  
  1. Forest Ecology, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zurich, 8092, Zurich, Switzerland
  2. Swiss Federal Institute for Forest, Snow and Landscape Research, 8903, Birmensdorf, Switzerland
  
• 刊物主题：Forestry; Plant Sciences; Plant Ecology;
• 出版者：Springer Berlin Heidelberg
• ISSN：1612-4677

文摘

The optimization of forest management under climate change uncertainty requires a comparison of many alternative management options under different climate scenarios and the use of stochastic and adaptive approaches. Empirical growth and yield models are highly suitable for this, provided they include sensitivity to environmental influences. Here, we present a climate-sensitive empirical growth and yield model that is based on the direct integration of environmental effects in dynamic growth and survival functions, which allows for the evaluation of changing site conditions over time. Individual-tree diameter and height growth and the probability of a tree to survive any 5-year period were modelled for even-aged beech (Fagus sylvatica) stands in Switzerland using a distance-independent approach. Changing site conditions were based on a drought index (locally adjusted water balance) and sum of degree-days. The data for fitting the model were taken from 30 permanent yield plots repeatedly measured from 1930 to 2010. Reasonable results were obtained in the model evaluation: (1) validation against independent National Forest Inventory data indicated that the incorporation of drought and sum of degree-days in the model was appropriate; (2) accurate simulations over around 50 years of past stand development were achieved (for changes in basal area over 5-year measurements in all plots, the bias was 3 % and the root mean square error 32 %); and (3) the impact of climate change may vary considerably along the range of current site conditions. We thus conclude that the model can be used in management planning under climate change uncertainty.