Climate change particularly threatens the xeric limits of temperate-continental forests. In Hungary, annual temperatures have increased by 1.2 °C–1.8 °C in the last 30 years and the frequency of extreme droughts has grown. With the aim to gain stand-level prospects of sustainability, we have used local forest site variables to identify and project effects of recent and expected changes of climate. We have used a climatic descriptor (FAI index) to compare trends estimated from forest datasets with climatological projections; this is likely for the first time such a comparison has been made. Four independent approaches confirmed the near-linear decline of growth and vitality with increasing hot droughts in summer, using sessile oak as model species. The correlation between droughts and the expansion of pest and disease damages was also found to be significant. Projections of expected changes of main site factors predict a dramatic rise of future drought frequency and, consequently, a substantial shift of forest climate classes, especially at low elevation. Excess water-dependent lowland forests may lose supply from groundwater, which may change vegetation cover and soil development processes. The overall change of site conditions not only causes economic losses, but also challenges long-term sustainability of forest cover at the xeric limits.

Key message: Climate envelope analysis of nine tree species shows that Fagus sylvatica L. and Picea abies H. Karst could lose 58% and 40% of their current distribution range. Quercus pubescens Willd and Quercus cerris L. may win areas equal with 47% and 43% of their current ranges. The ratio of poorly predictable areas increases by 105% in southern and south-eastern Europe. Context: Climate change requires adaptive forest management implementations. To achieve climate neutrality, we have to maintain and expand forest areas. Impact assessments have great importance. Aims: The study estimates the potential climate envelopes of nine European tree species for a past period (1961–1990) and for three future periods (2011–2040, 2041–2070, 2071–2100) under two emission scenarios (RCP4.5 and RCP8.5) based on the current species distribution. Methods: Climate envelopes were estimated simultaneously using the random forest method. Multi-resolution segmentation was used to determine the climatic characteristics of each species and their combinations. Models were limited to the geographical area within which the climatic conditions correspond to the climatic range of the training areas. Results: Results showed remarkable changes in the extent of geographic areas of all the investigated species’ climate envelopes. Many of the tree species of Central Europe could lose significant portions of their distribution range. Adhering to the shift in climate, these tree species shift further north as well as towards higher altitudes. Conclusion: European forests face remarkable changes, and the results support climate envelope modelling as an important tool that provides guidelines for climate adaptation to identify threatened areas or to select source and destination areas for reproductive material.

This paper analyses the recent recurring dieback and growth decline of Black pine (P. nigra Arn. var austriaca) in the Keszthely mountains of south-west Hungary, and their relations to water deficits due to droughts. These relations were studied in five stands with low soil water storage capacity for the period 1981–2016. The vitality was assessed using 60 tree-ring samples and changes in remotely sensed vegetation activity indices, i.e., the normalized difference vegetation index (NDVI) and the normalized difference infrared index (NDII). Water deficit was estimated by using meteorological drought indices such the standardized precipitation–evapotranspiration index (SPEI) and the forestry aridity index (FAI), as well as the relative extractable water (REW), calculated by the Brook90 hydrological model. Results revealed a strong dependency of annual tree ring width on the amount of water deficit as measured by all the above estimators, with the highest correlation shown by the summer REW. Droughts also showed a long-term superimposed effect on tree growth. NDII seemed to be more sensitive to drought conditions than NDVI. The robust dependency of tree growth on the summer water availability combined with the projected increasing aridity might lead to decreasing growth of Black pine in Hungary towards the end of the century. We thus argue that the suggestion by several papers that Black pine can be a possible substitute species in the Alpine and Mediterranean region in the future should be revisited.

Illés, G., Kovács, G. and Heil, B. 2011. Comparing and evaluating digital soil mapping methods in a Hungarian forest reserve. Can. J. Soil Sci. 91: 615–626. To investigate applications of widespread digital soil mapping methods in forestry management, soil maps for a Hungarian forest reserve were developed using general discriminant and classification tree analysis as predictive tools. Soil samples were collected applying an unaligned semi-systematic grid. Second level units of the World Reference Base of Soil Resources and their yield capacity were determined. Terrain attributes were derived using a digital elevation model, and they were assigned to soil data to be used as predictors for second level units of the World Reference Base for Soil Resources (SLU) maps. A comparison was made of prediction accuracy. Both the discriminant analysis and the classification tree-based prediction were able to derive SLU maps; however, the classification accuracies were uneven. The methods used provided 63–65% average classification accuracy for dominant SLUs, but only 0–18% in the case of less common SLUs. One of the major issues of digital soil mapping that needs to be addressed is that the same inputs may result in different output maps depending on the use of spatial predictions. To overcome this problem we created a new combination of these methods in which the classification accuracies were used to select the most appropriate prediction. For each location, the method that gave higher prediction accuracy was used to extend the soil map to unknown areas. In this way we improved the overall accuracy of output maps as well as the prediction accuracies of individual SLUs.