Folia Geobotanica

, Volume 49, Issue 3, pp 337–359 | Cite as

The TRM Model of Potential Natural Vegetation in Mountain Forests

  • Birgit Reger
  • Tim Häring
  • Jörg Ewald


Due to advances in spatial modeling and improved availability of digital geodata, traditional mapping of potential natural vegetation (PNV) can be replaced by ecological modeling approaches. We developed a new model to map forest types representing the potential natural forest vegetation in the Bavarian Alps. The TRM model is founded on a three-dimensional system of the ecological gradients temperature (T), soil reaction (R), and soil moisture (M). Within such a “site cube” forest types are defined as homogenous site units that give rise to forest communities with comparable species composition, structure, production and protective functions. The three gradients were modeled using regression algorithms with area-wide, high resolution geodata on climate, relief and soil as predictors and average Ellenberg indicator values for temperature, acidity and moisture of vegetation plots as dependent variables summarizing plant responses to ecological gradients. The resulting predictor-response relationships allowed us to predict gradient positions of each raster cell in the region from geodata layers. The three-dimensional system of gradients was partitioned into 26 forest types, which can be mapped for the whole region. TRM-based units are supplemented by 22 forest types of special sites defined by other ecological factors such as geomorphology, for which individual GIS rules were developed. The application of our model results in an intermediate-scale map of potential natural forest vegetation, which is based on an explicit function of temperature, reaction and moisture and is therefore consistent and repeatable in contrast to traditional PNV maps.


Bavarian Alps Forest type Predictive vegetation modeling Soil moisture Soil reaction Temperature 



This research was carried out within the project ‘Forest Information System for the Northern Alps’ (WINALP,, which was financially supported by the European Fund for Regional Development (EFRE) within the ‘INTERREG Bayern – Österreich 2007-2013’ program, the Bavarian Forest Administration and the Bavaria State Forest Enterprise (BaySF). We are indebted to the Bavarian Surveying Administration (LVG) for providing the digital elevation model, the German Meteorological Service (DWD) for providing climate data, and the Bavarian Environment Agency (LfU) for providing soil maps and geological maps. This research benefited greatly from all researchers who contributed their vegetation relevés to the database BERGWALD. We would also like to thank the Bavarian State Institute of Forestry’s ‘Maps for the future’ crew for their support. The map of potential natural forest vegetation for the Bavarian Alps is presented in an ArcGIS Viewer at (Ewald and Reger 2012). We further would like to thank the three reviewers and Radim Hédl for helpful comments on an earlier draft of the manuscript and Janet Ohmann for valuable editorial suggestions.


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Copyright information

© Institute of Botany, Academy of Sciences of the Czech Republic 2013

Authors and Affiliations

  1. 1.University of Applied Sciences Weihenstephan-TriesdorfFreisingGermany
  2. 2.BASF SE, Environmental Fate – ModelingLimburgerhofGermany

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