LandS: Vegetation modeling based on Ellenberg's ecological indicator values
- PMID: 38076710
- PMCID: PMC10709510
- DOI: 10.1016/j.mex.2023.102486
LandS: Vegetation modeling based on Ellenberg's ecological indicator values
Abstract
We present LandS, a new version of the Gras Model. The Gras Model was designed to simulate grassland development at local scales based on Ecological Indicator Values (EIVs) for different grassland management practices. In LandS, we complemented the existing set of EIVs with a second set representing several environmental factors: light, moisture, temperature, soil pH and nitrogen, also known as Ellenberg's EIVs. These new EIVs make the model more versatile and applicable to a wide range of sites across Central Europe. For example, it can be used on sites with dry or moist, acidic or calcareous soils in grassland or forest environments. We have also improved the implementation of the model by introducing version control and moving species and site-specific variables to data input files, so that species sets can be easily swapped for application in new study sites. We demonstrate the use and behavior of the model in two simulation experiments exploring interactions mediated by Ellenberg's EIVs, using input files to apply the model to different landscapes. We also provide detailed guidance on species selection and calibration, and discuss model limitations.•LandS is an improved version of the GraS Model for simulating vegetation development at the local scale.•It includes Ellenberg-like indicator values for environmental variables for inverse prediction of species occurrence and composition.•The model is now flexible enough to be used for study sites throughout Central Europe, using data input files for species initialization.
Keywords: LandS Model (Landscape Succession Model); Modeling environmental conditions; Plant sociology; Semi-natural grassland; Species composition; Vegetation development.
© 2023 The Authors.
Conflict of interest statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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