Abstracts (first author)


Complex response in life history traits of the bulb mites in elevated thermal conditions – an experimental evolution approach


Author(s): Plesnar-Bielak A, Jawor A, Kramarz P


Temperature is a key environmental factor affecting almost all the aspects of life histories in ectotherms. The theory predicts that organisms grow faster, reach smaller sizes and produce smaller offspring when temperature increases. In addition, temperature changes, through their effects on metabolism, may also influence the expression of alternative reproductive phenotypes (ARP). Although many studies investigated reaction norms of life history traits in relation to temperature change, little is known about how these reaction norms evolve. In our study we subjected the bulb mites to experimental evolution in two temperature treatments: control and elevated. After 18 generations we measured adult body size, eggs size and development time of both treatments at control as well as at elevated temperature. Thus, we were able to distinguish genetic changes (the effect of selection temperature) from environmental effects. The ARP expression was recorded in each generation. We found that mites developed faster and reached smaller sizes at increased temperature, but genetic effects of thermal adaptation were not always parallel to the observed reaction norms revealing quite complex patterns of life history traits response to temperature. Despite smaller body sizes females laid larger eggs at higher temperature. This effect was more pronounced in animals evolving at elevated temperature. Evolution at increased temperature affected also ARP expression with the proportion of armored fighters decreasing from generation to generation. We propose that this could be the consequence of temperature sensitiveness of cost to benefits ratio of expressing ARPs.


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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group