Folia Geobotanica

, Volume 49, Issue 3, pp 385–405

Regionalizing Indicator Values for Soil Reaction in the Bavarian Alps – from Averages to Multivariate Spectra

  • Tim Häring
  • Birgit Reger
  • Jörg Ewald
  • Torsten Hothorn
  • Boris Schröder
Article

Abstract

We present an approach to produce maps of Ellenberg values for soil reaction (R-value) in the Bavarian Alps. Eleven meaningful environmental predictors covering GIS-derived information on climatic, topographic and soil conditions were used to predict R-values. As dependent variables, Ellenberg indicator values for soil reaction were queried from plot records in the vegetation database WINALPecobase. We used an additive georegression model, which combines complex prediction models and the increased prediction accuracy of a boosting algorithm. In addition to environmental predictors we included spatial effects into the model to account for spatial autocorrelation. As we were particularly interested in the usefulness of averaged R-values for spatial prediction, we applied two different models: (1) a geo-additive regression model that estimates mean R-values and (2) a proportional odds model predicting the probability distribution over R-values 1 to 9. We found meaningful dependencies between the R-value and our predictors. Both models produced the same spatial pattern of predictions. Spatial effects had an impact only in the first model. The main drawback of mean R-values is the oversimplification of complex conditions of soil reaction, which is entailed by averaging and regression to mean values. Therefore, regionalized average indicator values provide only limited information on site-ecological characteristics. Model 1 failed to predict the range and shapes of original indicator spectra precisely. In contrast, the second model provided a more sophisticated picture of soil reaction. To make the multivariate output of model 2 comparable to that of model 1, we propose to plot the distribution in a three-dimensional color-space. In addition, comparison of both models based on a multiple linear regression model resulted in a R2 of 0.93. The proportional odds model is a promising approach also for other indicator values and different regions as well as for other ordinal-scaled ecological parameters.

Keywords

Boosting Geo-additive regression Proportional odds model Spatial effect Species distribution modeling 

Supplementary material

12224_2013_9157_MOESM1_ESM.pdf (63 kb)
ESM 1(PDF 62 kb)

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Copyright information

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

Authors and Affiliations

  • Tim Häring
    • 1
    • 2
  • Birgit Reger
    • 3
  • Jörg Ewald
    • 3
  • Torsten Hothorn
    • 4
  • Boris Schröder
    • 2
  1. 1.BASF SE, Environmental Fate – ModellingLimburgerhofGermany
  2. 2.Landscape EcologyTechnische Universität MünchenFreisingGermany
  3. 3.Faculty of ForestryUniversity of Applied Sciences Weihenstephan-TriesdorfFreisingGermany
  4. 4.Institut für Sozial- und PräventivmedizinUniversität ZürichZürichSwitzerland

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