Please use this identifier to cite or link to this item: https://biore.bio.bg.ac.rs/handle/123456789/424
Title: Associations between environmental variability and inversion polymorphism of Drosophila subobscura: Meta-analysis of populations from the Central Balkans
Authors: Stamenković Radak, Marina 
Kenig, Bojan
Djurakic, Marko
Jelić, Mihailo 
Eric, Katarina
Andjelkovic, Marko
Keywords: Adaptation;Chromosomal polymorphism;Climate;Thermal response
Issue Date: 14-Mar-2019
Rank: M22
Journal: Climate Research
Abstract: 
© Inter-Research 2019. Ecological and evolutionary factors, together with abiotic conditions, affect biogeographic patterns of genetic entities. The spatial and temporal variability of chromosomal inversions of Drosophila subobscura suggests that this species can serve as a good model for studying the effects of environmental change on the genetic structure of natural populations. A comprehensive meta-analysis of the association of environmental and climatic variables with inversion diversity patterns was performed on 20 D. subobscura populations from the central part of the Balkan Peninsula. Environmental data consisted of 3 sets of variables related to temperature and precipitation, extracted from 2 climatic databases, averaged over a 3 month period, and using biological instead of calendar dates of sampling. Arrangement frequency patterns are likely driven by a synergistic effect of factors related to temperature and precipitation. The frequencies of standard chromosomal arrangements tend to co-vary positively with precipitation, whereas parameters related to temperature appear to favor higher frequencies of the inverted and more complex chromosomal arrangements. A complex relationship among local environmental variables is evident from the results and reflects the probable effect of an altitudinal shift; the altitudinal gradient of inversions is different from their latitudinal gradient. The pattern of inversions is generally not associated with environmental variables, and a particular inversion cannot be a predictive genetic marker of global climate change. Populations in different habitats are subjected to habitat-specific selection regimes, while demographic factors and population history also affect the genetic variability pattern observed.
URI: https://biore.bio.bg.ac.rs/handle/123456789/424
ISSN: 0936-577X
DOI: 10.3354/cr01551
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