NAMES OF SOME WIDESPREAD SHRUBS IN THE FINNO-UGRIC LANGUAGES (JUNIPER, HAZEL, BIRD CHERRY)

In this paper, the author examines the names of widespread shrubs in the Finno-Ugric languages. Since natural and climatic conditions including flora in the places of residence of the Ugric peoples (Khanty, Mansi, Hungarians) are significantly different from those of the peoples who speak languages of the Finno-Permic branch, this article mainly discusses the plant names of Finno-Permic languages (Baltic-Finnic, Mordvin, Mari and Permic). The plants included in this study are juniper, hazel and bird cherry. The aim of this paper is to examine all folk names of these shrubs as a group of nominal vocabulary, to study the origin and territorial distribution of phytonyms, as well as the nomination of shrubs in the Finno-Permic languages. The Finno-Ugric folk names of shrubs are numerous and in most cases have been formed separately in every language. This trend is more typical for the names of herbaceous plants, while the names of trees are usually older and fewer in number. Zoosemisms (animals' names) are found in the complex names of shrubs; most often they are the names of dogs and goats, but in the names of the shrubs considered in this article we could only find zoosemisms with the meanings.bear' and.magpie'. For this article, the material was collected by the method of controlled selection of vocabulary in printed publications (lexicographic and other works). The study of lexis is carried out by descriptive and comparative-historical methods. When studying the nomination of plants, the method of component analysis and the method of semantic analysis are used. In total, the study includes more than one hundred and fifty different folk phytonyms (including phonetic variations), most of which are complex nouns, usually consisting of two components. The origin of these names is determined fairly accurately in almost all cases, including the cases of borrowing. For the convenience of semantic analysis, all the phytonyms examined are combined into lexicalsemantic nests corresponding to nomination models. A total of 24 such nests have been allocated.