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The objective of this paper is to estimate the difference in wind erosion between two extreme situations: sandy soil permanently covered by grass and the nearby frequently ploughed area highly susceptible to wind erosion. The spatial pattern of soil erosion rate was investigated using Cs and Pb tracing technique. The spatial pattern of erosion rate obtained within the studied area reveal influence of topography as well as direction of prevailing winds on mobilization and transport of the soil particles. [ABSTRACT FROM AUTHOR]

This paper analyzes the spatial distribution of different soil types and soil systematic units in MU „Doroslovacke sume“. The most common soil type is chernozem, primarily of calcalourus type. Research has shown that the soil types secondary in prevalance are calcalourus gleyed and brownized, which is a finding that significantly differs from the previously available data. Calcalourus variety of chernozem, which is characterized by its automorphic genesis and high content of CaCO3, is a drier site type and therefore offers less favourable conditions for cultivation of tree species. The analysys of spacial distribution was followed by study of soil properties.

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R 2  = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2023 Elsevier B.V. All rights reserved.)