Somodi, Molnár, Czúcz, Bede-Fazekas, Bölöni, Pásztor, Laborczi & Zimmermann (2017)

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Imelda Somodi, Zsolt Molnár, Bálint Czúcz, Ákos Bede-Fazekas, János Bölöni, László Pásztor, Annamária Laborczi, Niklaus E. Zimmermann (2017): Implementation and application of Multiple Potential Natural Vegetation models – a case study of Hungary. Journal of Vegetation Science. DOI: 10.1111/jvs.12564


Multiple potential natural vegetation (MPNV) is a framework for the probabilistic and multilayer representation of potential vegetation in an area. How can an MPNV model be implemented and synthesized for the full range of vegetation types across a large spatial domain such as a country? What additional ecological and practical information can be gained compared to traditional potential natural vegetation (PNV) estimates?

MPNV was estimated by modelling the occurrence probabilities of individual vegetation types using gradient boosting models (GBM). Vegetation data from the Hungarian Actual Habitat Database (MÉTA) and information on the abiotic background (climatic data, soil characteristics, hydrology) were used as inputs to the models. To facilitate MPNV interpretation a new technique for model synthesis (re-scaling) enabling comprehensive visual presentation (synthetic maps) was developed which allows for a comparative view of the potential distribution of individual vegetation types.