Vitality Analysis Algorithm in the Study of Plant Individuals and Populations
Yulian Zlobin1, Ihor Kovalenko1, Hanna Klymenko1, Kateryna Kyrylchuk1, *, Liudmyla Bondarieva1, Olena Tykhonova1, Inna Zubtsova1
Identifiers and Pagination:Year: 2021
First Page: 119
Last Page: 129
Publisher Id: TOASJ-15-119
Article History:Received Date: 18/03/2021
Revision Received Date: 27/03/2021
Acceptance Date: 23/6/2021
Electronic publication date: 31/12/2021
Collection year: 2021
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The article presents an algorithm of the vitality analysis of plant individuals in the populations that enables the assessment of the prospects for the existence of species within certain phytocenoses and provides important information on the conditions of their growth. There are three basic stages of the algorithm: the first stage is the selection of qualitative characters, which characterize the viability of individuals; the second stage is the assessment of the vitality of specific plant individuals included in the sampling; the third stage is an integral assessment of the population vitality structure.
The goal of the study is to develop the basic algorithm for vitality analysis of populations based on the assessment of the vitality of plant individuals, as well as the authors’ algorithms for vitality analysis, considering the characteristic features of species, in particular, their different life strategies (C-type and R-type). The algorithm of the vitality analysis is demonstrated on the example of populations of the annual weed Persicaria scabra Moench (Polygonaceae), which grows in the pea crop planting (Sumy Region, Ukraine).
The algorithm of vitality analysis is based on the method of Yu. A. Zlobin, which includes 3 main stages. The vitality analysis of populations is carried out on the basis of the assessment of the vitality of certain individuals. The assessment of the vitality structure of populations is the third stage of vitality analysis, where the population belonging to the prosperous, equilibrium, or depressive types is determined depending on the ratio of individuals of different vitality classes (a, b, c). The calculation of the vitality analysis provides for the transformation of absolute values into unit fractions. It ensures the equivalence of the contribution of each of the features used in the assessment of the vitality of individuals and populations as a whole.
The article presents a basic algorithm for vitality analysis of plant populations. It also shows the algorithm for vitality analysis considering some biological and ecological characters of the studied species, which may be used in special and relatively rare cases. Some examples of analyses with a well-defined primary strategy ‒ competitors (C-type) or explerents (R-type) have been presented in the article. To calculate the morphoparameters of plant individuals and populations, the most convenient is the statistical package “Statistics”, which provides for the possibility of calculation automation via the command line. The division of populations into three types according to vitality is of general nature. The method of assessing the population vitality is inherently comparative, and this feature is considered to be its advantage.
Vitality analysis is useful in assessing the populations of rare plant species, meadow grasses, chemical contamination on the population of plants, identifying any changes in the status populations of forest herbs in the change of forest growth conditions, as well as a number of species of forest-forming tree species. The proposed variants of the algorithm to calculate the vitality of plant species and local populations are characterized by the high biological informative value and flexibility. The incorporated information on the vitality structure of populations in quantitative PVA models to predict their dynamics will significantly increase the reliability of forecasts regarding the prospects for the existence of phytopopulations of species in various plant communities.