Open AccessPotential Range of Bulbocodium versicolor (Ker-Gawl.) Spreng. (Colchicaceae, Liliopsida) in Russia
Author(s) -
А. С. Кашин,
А. С. Пархоменко,
L. K. Kulikova,
Н. А. Петрова,
И. В. Шилова,
М. В. Лаврентьев,
V.A. Shushunov
Publication year - 2020
Publication title -
povolžskij èkologičeskij žurnal
Language(s) - English
Resource type - Journals
eISSN - 2541-8963
pISSN - 1684-7318
DOI - 10.35885/1684-7318-2020-2-241-247
Subject(s) - quarter (canadian coin) , st petersburg , precipitation , range (aeronautics) , geography , physical geography , forestry , environmental science , archaeology , meteorology , russian federation , regional science , materials science , composite material
The article presents a bioclimatic model of the potential range of Bulbocodium versicolor in European Russia. To build the model, we analyzed a matrix containing 166 B. versicolor localities in the studied region; the analysis was carried out in the SDMtoolbox program using the climatic paramaters from the WorldClim open database. The model demonstrates that, given the available dataset on the modern climatic conditions, B. versicolor may occur in a wider geographical range comprising, at the very least, the Belgorod, Voronezh, Volgograd, Lipetsk, Penza, Rostov and Saratov provinces. Also, within European Russia, the most favorable conditions for B. versicolor are found in most of the Voronezh and Volgograd provinces as well as in some areas of the Right Bank and Left Bank of the Volga River adjacent to the Volga Upland (in the Saratov province). The maximum occurrence probability is 70–100% while the average occurrence probability is 40– 60%. The maximum contribution to the model is made by the precipitation of the warmest and most humid quarter (June–August); a smaller contribution is made by the average temperature of the coldest (December–February) and warmest (June – August) quarters as well as by the average annual precipitation. The least contribution is made by the precipitation of the most humid month (July) and the driest quarter (March–May). Finally, we conclude that bioclimatic model facilitates a better understanding of the geographical distribution of the species in question.