Comparative analysis of Deschampsia antarctica Desv. population adaptability in the natural environment of Admiralty Bay (King George Island, maritime Antarctic)

Plants inhabiting extreme environments may possess features allowing them to tolerate sudden abrupt changes in their environment, a phenomenon often known as ‘adaptability.’ However, ability or success in developing adaptability varies among plant populations. Adaptability can be quantified by measuring variation in the response to the same environmental challenges between plant populations. In this study, we evaluate the adaptability of the iconic Antarctic plant, Deschampsia antarctica, based on traits reflecting three levels of organization: the population level (S, D. antarctica land cover), individual level (Ph, biometrics), and cell level (relative DNA content, rcDNA, in cells of the leaf parenchyma). We sampled a total of six D. antarctica populations in the Admiralty Bay region, King George Island (South Shetland Islands, maritime Antarctic), during the austral summer of 2005–2006, and analyzed pairwise interrelations between various indices reflecting plant population adaptability. The results of these pairwise comparisons were then used to estimate a pooled measure of each population’s adaptability, designated as united latent quality indicator (ULQI). Our results demonstrated that the responses of individual adaptability indices were seldom synchronized, although one population from the central part of the Point Thomas oasis did show some degree of synchronicity. This population also demonstrated the highest ULQI, consistent with the relatively favorable microenvironmental conditions at this location. Two other populations located closer to the shoreline also demonstrated detectable synchronicity and moderate levels of ULQI, while the remaining populations revealed no synchronized responses and negative ULQI values. As the ULQI value obtained will be strongly influenced by the conditions experienced by any given population during a particular season, evaluation of population dynamics requires annual monitoring over multiple seasons.

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