Changes in land use and agricultural practices have altered the resilience of plant communities and can lead to the emergence of invasive species. One of these is the perennial grass species Bothriochloa ischaemum (L.) Kleng., whose diversity-reducing effects are known from several studies. Our exploratory questions were as follows: How does the presence of B. ischaemum affect the diversity and ratio of the species of sandy grasslands? To what extent does this diversity change depend on site characteristics? The supporting studies were carried out in five low-lying sand dune slacks and six relatively higher areas in the upper-intermediate part of the dunes and on an abandoned old field located in the Hungarian Great Plain in the Carpathian Basin. The cover of vascular plant species was recorded in all sampling sites in twelve 2 by 2 m plots, and the dataset was analysed using agglomerative cluster analyses and a non-parametric Kruskal–Wallis test. Five significantly different groups were identified, separating the vegetation types of the sides of the sand dunes, the vegetation types of the dune slack and the old field, and a Stipa borysthenica Kolkov ex Prokudin-dominated vegetation type. Our results suggest that B. ischaemum is only present as small tussocks on the drier, more exposed sides of dunes, with 3.9–24.2% average coverage; is less able to outcompete Festuca vaginata Waldst. et Kit. ex Willd. and S. borysthenica; and is only able to form large tussocks mainly in the lower dune slacks, with 45.6–79.5% average coverage. Here, in the wetter areas, it achieves high cover with a considerable accumulation of litter, and it becomes a dominant species in this association. The diversity-reducing effect of B. ischaemum on old-field grasslands depends on the age of the site and on the stability of the vegetation.

Climate change and related weather extremes are increasingly having an impact on all aspects of life. The main objective of the research was to analyze the impact of the most important meteorological elements and the image data of various water bodies of the Kis-Balaton wetland, Hungary. The primary question was which meteorological elements have a positive or negative influence on vegetational surface cover. Drones have facilitated the visual surveying and monitoring of challenging-to-reach water bodies in the area, including a lake and multiple channels. The individual channels had different flow conditions. Aerial surveys were conducted monthly, based on pre-prepared flight plans. Images captured by a Mavic 3 drone flying at an altitude of 150 m and equipped with a multispectral sensor were processed. The time-series images were aligned and assembled into orthophotos. The image details relevant to the research were segregated and classified using Maximum Likelihood classification algorithm. The reliability of the image data used was checked by Shannon entropy and spectral fractal dimension measurements. The results of the classification were compared with the meteorological data collected by a QLC-50 automatic climate station of Keszthely. The investigations revealed that the surface cover of the examined water bodies was different in the two years but showed a kind of periodicity during the year. In those periods, where photosynthetic organisms multiplied in a higher proportion in the water body, higher monthly average air temperatures and higher monthly global solar radiation sums were observed.