Soil organic carbon (SOC) has primary importance in terms of soil physics, fertility and even of climate change control. An intensively cultivated Cambisol was studied in order to quantify SOC redistribution under subhumid climate. One hundred soil samples were taken from the representative points of the solum along the slopes from the depth of 20-300 cm with a mean 1.2 % SOC content. They were measured by the simultaneous application of diffuse reflectance (240-1900 nm) and traditional physico-chemical methods in order to compare the results. On the basis of the results hierarchical cluster analyses were performed. The spatial pattern of the groups created were similar, and even though the classifications were not the same, diffuse reflectance has proven to be a suitable method for soil/sediment classification even within a given arable field. Both organic and inorganic carbon distribution was found a proper tool for estimations of past soil erosion process. Results show SOC enrichment on two sedimentary spots with different geomorphological positions. Soil organic matter compound also differs between the two spots due to selective deposition of the delivered organic matter. The components of low molecular weight reach the bottom of the slope and there can leach into the profile, while the more polymerised organic matter compounds are delivered and deposited even before, on a higher segment of the slope in an aggregated form. This spatial difference appears below the uppermost tilled soil layer as well; referring the lower efficiency of conventional ploughing tillage in spatial soil homogenisation.

The conservation of soil resources is increasingly becoming a critical issue worldwide, with growing interest in carbon stocks and water storage within the soil. Hungary is no exception, and there has been a demand for a country level soil erosion map that incorporates digital information available from the latest surveys and digital mapping campaigns. The map presented in this paper in based on the extremely wet year of 2010, and thus provides users a 1:100,000 scale 'worst case scenario' of soil erosion risk in Hungary (see Main Map). Results from both the Universal Soil Loss Equation and the Pan-European Soil Erosion Risk Assessment models were combined in order to achieve a map that can be used by a wide range of professionals. Both models estimate soil erosion by water in tonnes per hectare per year. ARTICLE HISTORY

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Landscape quality has become a fundamental issue in the development of renewable energy (henceforth abbreviated RE) projects. Rapid technological advances in RE production and distribution, coupled with changing policy frameworks, bring specific challenges during planning in order to avoid degradation of landscape quality. The current work provides a comprehensive review on RE landscapes and the impacts of RE systems on landscape for most European countries. It is based on a review by an interdisciplinary international team of experts of empirical research findings on landscape impacts of RE from thirty-seven countries that have participated in the COST Action TU1401 Renewable Energy and Landscape Quality (RELY).

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This study deals with spontaneous regeneration of fen and steppe meadows and corresponding soil properties on extensively managed ex-arable fields. Our first main aim was to analyse the nature of relations between various vegetation and soil parameters and time since abandonment and to determine the time needed for regeneration. Our second major goal was to determine the main environmental factors influencing regeneration success. Time since abandonment of the studied areas was determined with military maps, aerial photographs and the help of local rangers. Stands which were presumably not ploughed for over 150 years were taken as a reference. Vegetation surveys and soil sampling were carried out in 307 plots with different soil moisture conditions. The correlation with time was tested for relevant vegetation and soil parameters. The influence of different parameters on the species composition was tested with a generalized linear mixed model. We found that vegetation and soil parameters approach the level of long-term (permanent) grassland in a similar asymptotic curve. Numerous characteristic target vegetation species and legally protected species have colonized the old fields. The time frame needed for regeneration can be stated to be 20-40 years for the majority of sites, but the proportion of favourable species in the resulting grasslands is divergent. The most important finding among soil properties was a pronounced negative effect of plant available phosphorus on the species composition of regenerating grassland. We conclude that relying on spontaneous recolonization for grassland restoration in central Hungary is promising, particularly on sites which were not fertilized intensively with phosphorus prior to abandonment.

Soil erosion by water is one of the most significant forms of soil degradation globally, especially in Europe. A new soil erosion risk map of Hungary has been compiled and published recently, using the combined outputs of the Universal Soil Loss Equation and Pan‐European Soil Erosion Risk Assessment models. Our study aimed at providing evaluation of the map by using semiquantitative validation data obtained from the Hungarian Soil Degradation Subsystem of the National Environmental Information System. The Soil Degradation Subsystem database contained information at farm level as well as indicators based on laboratory data for 5‐ha representative plots. On the basis of the semiquantitative analysis, the map results align well with the farm‐based degradation data and provide viable information not only at the regional scale but also at the farm scale. However, indicators from representative plots did not support model results, indicating possible conflict between farm‐ and plot‐level data. Cross‐comparison of these indicators showed only limited correlation between farm‐ and plot‐level indicators.

As soil erosion is still a global threat to soil resources, the estimation of soil loss, particularly at a spatiotemporal setting, is still an existing challenge. The primary aim of our study is the assessment of changes in soil erosion potential in Hungary from 1990 to 2018, induced by the changes in land use and land cover based on CORINE Land Cover data. The modeling scheme included the application and cross-valuation of two internationally applied methods, the Universal Soil Loss Equation (USLE) and the Pan-European Soil Erosion Risk Assessment (PESERA) models. Results indicate that the changes in land cover resulted in a general reduction in predicted erosion rates, by up to 0.28 t/ha/year on average. Analysis has also revealed that the combined application of the two models has reduced the occurrence of extreme predictions, thus, increasing the robustness of the method. Random Forest regression analysis has revealed that the differences between the two models are mainly driven by their sensitivity to slope and land cover, followed by soil parameters. The resulting spatial predictions can be readily applied for qualitative spatial analysis. However, the question of extreme predictions still indicates that quantitative use of the output results should only be carried out with sufficient care.