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Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany)

1
Bavarian State Institute of Forestry (LWF), Hans-Carl-von-Carlowitz-Platz 1, Freising 85354, Germany
2
Statistisches Beratungslabor, Ludwig-Maximilians-Universität München, Akademiestr. 1, München 80799, Germany
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TUM School of Life Sciences Weihenstephan, Chair for Forest Growth and Yield, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, Freising 85354, Germany
*
Author to whom correspondence should be addressed.
Forests 2014, 5(11), 2626-2646; https://doi.org/10.3390/f5112626
Received: 22 August 2014 / Revised: 22 September 2014 / Accepted: 31 October 2014 / Published: 12 November 2014
Combining national forest inventory (NFI) data with digital site maps of high resolution enables spatially explicit predictions of site productivity. The aim of this study is to explore the possibilities and limitations of this database to analyze the environmental dependency of height-growth of Norway spruce and to predict site index (SI) on a scale that is relevant for local forest management. The study region is the German federal state of Bavaria. The exploratory methods comprise significance tests and hypervolume-analysis. SI is modeled with a Generalized Additive Model (GAM). In a second step the residuals are modeled using Boosted Regression Trees (BRT). The interaction between temperature regime and water supply strongly determined height growth. At sites with very similar temperature regime and water supply, greater heights were reached if the depth gradient of base saturation was favorable. Statistical model criteria (Double Penalty Selection, AIC) preferred composite variables for water supply and the supply of basic cations. The ability to predict SI on a local scale was limited due to the difficulty to integrate soil variables into the model. View Full-Text
Keywords: climate; forest inventory; height growth; soil; statistical model climate; forest inventory; height growth; soil; statistical model
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Brandl, S.; Falk, W.; Klemmt, H.-J.; Stricker, G.; Bender, A.; Rötzer, T.; Pretzsch, H. Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany). Forests 2014, 5, 2626-2646.

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