Mapping of the actual processes in landscapes (on the example of nature protected areas of St. Petersburg)

G. A. Isachenko, A. I. Reznikov

DOI: https://doi.org/10.31111/geobotmap/2022.36

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The study of actual processes in landscapes, including their mapping, is based on the idea of an elementary landscape as a unity of a stable component (landscape site) and more dynamic landscape states. Mapping of actual landscape processes is tackled through the example of the territory of the Gladyshevsky Nature Reserve (Karelian Isthmus, St. Petersburg). To study actual processes, materials of the landscapes and vegetation monitoring on the key plots, route studies, dendrochronology data, remote sensing data, forest survey materials, map of landscape sites and actual vegetation map were used. The succession of tree species were indicated by the presence of a young stand and abundant viable undergrowth of the tree species that did not coincide with the predominant stock species, as well as by the tree falls of the predominant species. An increase in the stock of dominant tree species was revealed in areas with a significant stock and relatively young trees (up to 80 years for conifers and up to 50 for deciduous). Reforestation processes are also common on former agricultural lands abandoned in the second half of the XX century. Processes unrelated to the dynamics of stands are represented by paludification and stabilization of mire plant communities, recreational digression and coastal processes. In total, 30 types of actual processes are highlighted on the map, represented by contours, and 2 types of processes indicated by linear signs (accumulation and erosion of the shores of the Gulf of Finland).

Key words: mapping, landscape, southern taiga, landscape site, actual processes, long-term dynamics, tree stand

Section: Articles

How to cite

Isachenko G. A., Reznikov A. I. 2022. Mapping of the actual processes in landscapes (on the example of nature protected areas of St. Petersburg). Geobotanical mapping 2022: 36–48. https://doi.org/10.31111/geobotmap/2022.36

Received December 15 2022

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