Details zur Publikation |
Kategorie | Textpublikation |
Referenztyp | Zeitschriften |
DOI | 10.1016/j.mex.2023.102486 |
Lizenz ![]() |
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Titel (primär) | LandS: Vegetation modeling based on Ellenberg's Ecological Indicator Values |
Autor | Rumohr, Q.; Grimm, V.; Lennartz, G.; Schäffer, A.; Toschki, A.; Roß-Nickoll, M.; Hudjetz, S. |
Quelle | MethodsX |
Erscheinungsjahr | 2023 |
Department | OESA |
Band/Volume | 11 |
Seite von | art. 102486 |
Sprache | englisch |
Topic | T5 Future Landscapes |
Supplements | https://ars.els-cdn.com/content/image/1-s2.0-S221501612300482X-mmc1.docx |
Keywords | Vegetation development; species composition; plant sociology; modelling environmental conditions; semi-natural grassland |
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. |
dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=28235 |
Rumohr, Q., Grimm, V., Lennartz, G., Schäffer, A., Toschki, A., Roß-Nickoll, M., Hudjetz, S. (2023): LandS: Vegetation modeling based on Ellenberg's Ecological Indicator Values MethodsX 11 , art. 102486 10.1016/j.mex.2023.102486 |