Landscape diversity mapping allows assessment of the hemeroby of bird species in a modern industrial metropolis
Landscape diversity mapping allows assessment of the hemeroby of bird species in a modern industrial metropolis

Summary/Abstract: The article proposes a methodology for identifying the hemeroby of avifauna inhabiting a contemporary industrial metropolis. The Landsat 8-9 OLI/TIRS satellite image of the city of Dnipro (Ukraine) dated 14 July 2024 was employed for further analysis. The classification of land cover types was performed in SAGA-9 without training using the k-means procedure. The classification was performed on the basis of geospatial layers represented by spectral indices and road network density. For each cluster, the average value of the hemeroby level was calculated, which was rounded to a whole value and used as an indicator of hemeroby that is typical for the respective cover type. The hemeroby values were extracted from the geospatial data layer obtained using landscape metrics at the points of bird species encounters. The mean value and standard deviation of hemeroby during bird encounters were calculated based on the data obtained. These values were considered indicators of bird species hemeroby and their tolerance to hemeroby. The surface temperature within the city exhibited a range of 29.4 to 33.6°C. The highest temperatures were recorded in the city centre and in the eastern and northern districts, with the lowest temperatures observed in the eastern region. The principal component analysis enabled the extraction of three principal components with eigenvalues exceeding one. Principal component 1 exhibited a positive correlation with the spectral indices that indicate anthropogenic surfaces and a negative correlation with indices that are sensitive to vegetation density, surface moisture and rock or soil composition. Therefore, Principal component 1 can be interpreted in a meaningful manner as an aspect of hemeroby induced by a decrease in vegetation cover due to an increase in the presence of anthropogenic objects. Principal component 2 was found to be positively correlated with surface temperature and indices that are sensitive to anthropogenic surfaces, as well as road network density. This principal component can be interpreted as an aspect of hemeroby related to thermal pollution. The most significant indicator of principal component 3 is road network density. Therefore, all of the primary extracted principal components are associated with hemeroby, and an integrated hemeroby indicator was calculated. The classification procedure, based on spectral indices and road network density, yielded 20 land cover types and one additional category representing water bodies. The hemeroby of birds exhibited considerable variation, with values ranging from 15 to 89. The birds were classified into the following categories based on the extent of their hemeroby. The ahemerobic group comprised 15 species, the oligohemerobic group 11, the mesohemerobic group 8, the beta-euhemerobic group 8, the alphaeuhemerobic group 10, the polyhemerobic group 9 and the metahemerobic group 5. The stenotopic group comprises 30 species, the mesotopic group 17 species, and the eurytopic group 19 species of birds. In the case of 34 species of bird fauna in the city of Dnipro, estimates have been obtained for the European bird fauna on the basis of the mean hemeroby score, which was calculated for the European avifauna. A statistically significant correlation was observedbetween the hemeroby scores and the mean hemeroby score.

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