Projected Changes of the Forestry Aridity Index Indicating Regional Climatic Change in Central/Eastern Europe

Climate change affects several sectors, i.e., agriculture, energy supply, tourism, transportation, healthcare. In addition, it also affects the natural vegetation, as the changing climatic conditions may induce the shifting or shrinking of the area where certain species can be found – or in the worst case even extinction. In order to be prepared to the projected changes, and preferably – if possible – to build adaptation strategies in time, special investigations are needed.

For this purpose, the present study analyzes the so-called Forestry Aridity Index (FAI) for an Eastern/Central European country, Hungary (~45.7–48.6°N; 16–23°E), and compares the results for a historical period (1971–2020) and the future (2021–2100). The observation-based, homogenized and interpolated HuClim data sets (created by the Hungarian Meteorological Service, thus ensuring the high-quality reliability) are used to analyze the last three decades of the 20^th century. For the analysis of the future decades until the end of the 21^st century, six regional climate model simulations are used from the EURO-CORDEX data portal, taking into account the RCP4.5 and the RCP8.5 scenarios as well. To calculate the FAI, monthly temperature and precipitation data are needed from May to August as input. Then, different categories can be distinguished, which are favorable for certain vegetation species based on this index, namely, beech (FAI < 4.75), hornbeam-oak (4.75 ≤ FAI < 6), sessile oak and Turkey oak (6 ≤ FAI ≤ 7.25), forest-steppe (7.25 < FAI < 8.5), and steppe (8.5 < FAI). According to our results, by the end of the 21^st century, steppe category will be dominant in Hungary. Moreover, if the RCP8.5 scenario is followed, the optimal climatic conditions for beech may entirely disappear from the country by 2081–2100.

Acknowledgements: Research leading to this study has been supported by the Hungarian National Research, Development and Innovation Fund (under grants PD-138023 and K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).