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Abstract
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.
| Item Type: | Journal article |
|---|---|
| Form of publication: | Publisher's Version |
| Keywords: | climate; forest inventory; height growth; soil; statistical model |
| Faculties: | Mathematics, Computer Science and Statistics > Statistics |
| Subjects: | 300 Social sciences > 310 Statistics 300 Social sciences > 330 Economics 500 Science > 570 Life sciences; biology |
| URN: | urn:nbn:de:bvb:19-epub-24155-0 |
| ISSN: | 1999-4907 |
| Language: | English |
| Item ID: | 24155 |
| Date Deposited: | 17. Mar 2015, 08:36 |
| Last Modified: | 04. Nov 2020, 13:05 |
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