Assessing site productivity based on national forest inventory data and its dependence on site conditions for spruce dominated forests in Germany

Susanne Brandl, Wolfgang Falk, Thomas Rötzer, Hans Pretzsch

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Aim of study: (i) To estimate site productivity based on German national forest inventory (NFI) data using above-ground wood biomass increment (ΔB) of the stand and (ii) to develop a model that explains site productivity quantified by ΔB in dependence on climate and soil conditions as well as stand characteristics for Norway spruce (Picea abies (L.) Karst.). Area of study: Germany, which ranges from the North Sea to the Bavarian Alps in the south encompassing lowlands in the north, uplands in central Germany and low mountain ranges mainly in southern Germany. Material and methods: Biomass increment of the stand between the 2nd and 3rd NFI was calculated as measure for site productivity. Generalized additive models were fitted to explain biomass increment in dependence on stand age, stand density and environmental variables. Main results: Great part of the variation in biomass increment was due to differences in stand age and stand density. Mean annual temperature and summer precipitation, temperature seasonality, base saturation, C/N ratio and soil texture explained further variation. External validation of the model using data from experimental plots showed good model performance. Research highlights: The study outlines both the potential as well as the restrictions in using biomass increment as a measure for site productivity and as response variable in statistical site-productivity models: biomass increment of the stand is a comprehensive measure of site potential as it incorporates both height and basal area increment as well as stem number. However, it entails the difficulty of how to deal with the influence of management on stand density.

Original languageEnglish
Article numbere007
JournalForest Systems
Volume28
Issue number2
DOIs
StatePublished - 2019

Keywords

  • Biomass increment
  • Climate
  • Site index
  • Site potential
  • Statistical model

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