Ukrainian Antarctic Journal

No 1(18) (2019): Ukrainian Antarctic Journal
Articles

Algorithm for the United Quality Latent Index of the plant adaptability and its application field in monitoring of Deschampsia antarctica È. Desv. populations

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  • N. Miryuta,
  • J. Smykla,
  • I. Parnikoza
N. Miryuta
State Institution National Antarctic Scientific Center, Ministry of Education and Science of Ukraine, 16 Taras Shevchenko Blv., Kyiv, 01601, Ukraine,
J. Smykla
Institute of Nature Conservation Polish Academy of Sciences, Mickiewicza, 33, 31—120, Kraków, Poland, University of North Carolina Wilmington, 601 S. College Rd., Wilmington, NC 28403-5915, USA
I. Parnikoza
State Institution National Antarctic Scientific Center, Ministry of Education and Science of Ukraine, 16 Taras Shevchenko Blv., Kyiv, 01601, Ukraine,Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, 150 Akad. Zabolotnogo Str., Kyiv, 03143, Ukraine
DOI: https://doi.org/10.33275/1727-7485.1(18).2019.139
Published December 13, 2019
Keywords
  • Deschampsia antarctica È. Desv.,
  • population dynamic,
  • United Quality Latent Index of Adaptability,
  • Argentine Islands,
  • maritime Antarctic
How to Cite
Miryuta, N., Smykla, J., & Parnikoza, I. (2019). Algorithm for the United Quality Latent Index of the plant adaptability and its application field in monitoring of Deschampsia antarctica È. Desv. populations. Ukrainian Antarctic Journal, (1(18), 152-168. https://doi.org/10.33275/1727-7485.1(18).2019.139
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

Main objective of the research was to develop an algorithm for the United Quality Latent Index of Adaptability (UQLI, Iq) and to demonstrate its application on the study of Deschampsia antarctica È. Desv. at the monitoring site of Galindez Island, Argentine Islands, maritime Antarctic in natural setups. Methods. Cover area of eleven populations of D. antarctica as well as measurements of their morphometric parameters were obtained for use in the analysis including: leaf length, inflorescence length, flower length (by lower glume), and flower count in an inflorescence. Protein densitometry profiles of seeds from eleven D. antarctica populations were also added to the dataset. Extreme grouping method was used to calculate the United Quality Latent Index of Adaptability (UQLI). The estimation of United Latent Quality Index of Adaptability (UQLI, Iq) was performed by pairwise comparisons of sets of spatial pair differences indices. Results. We described the use of the algorithm for UQLI estimation for eleven populations of D. antarctica from Galindez Island in the 2017/18 season. As an example of practical application, we presented the six-year UQLI trends for six experimental D. antarctica populations from Galindez Island. Conclusions. The developed algorithm for the UQLI calculation was applied to evaluate the complex adaptability in the six-year monitoring dynamics for six D. antarctica experimental populations from Galindez Island. Trends of the UQLI were obtained for all sampled population. The researched populations can be categorized by trends in the proposed adaptation index into three separate groups as follows: passing through maximum, passing through minimum or experiencing oscillations. It is suggested that such categorization is related to individual micro-habitat conditions. Further addition of the observation data will improve the explanation of the oscillating UQLI trends and will allow to study its relationship with other climatic indices. The UQLI index is proposed for reduction of dimensionality of source data at different organization levels that characterize sample populations. The UQLI can be used to compare a sets of populations sample of the same species growing under different conditions, especially during monitoring studies.

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