Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.

Impression of the global climate change on the ornamental plant usage in Hungary

The climate modeling, which has adequate spatial and temporal resolution, shows that the future climate of the Carpathian Basin will be much more arid and hot than nowadays. The currently used and taught assortment of the ligneous ornamental plants should be urgently revised. It is aimed in my research to collect the species which will probably be introduced in the future. They can be gathered from the Hungarian botanical gardens and research centers and from the spatially analogous territories. The collected taxa should be examined with GIS software if they will really suffer our future climate.