How to assess Drosophila cold tolerance: chill coma temperature and lower lethal temperature are the best predictors of cold distribution limits

• Published in: Functional ecology 2015-01, Vol.29 (1), p.55-65
• Main Authors: Andersen, Jonas L., Manenti, Tommaso, Sørensen, Jesper G., MacMillan, Heath A., Loeschcke, Volker, Overgaard, Johannes
• Format: Article
• Language: English
• Subjects: Animal models; Animal physiological ecology; Cold; cold resistance; Cold tolerance; Coma; Correlation analysis; Drosophila; geographic distribution; Geographical distribution; insect; Insects; Low temperature; low temperature limit; Phylogeny; Recovery time; Regression analysis; stress tolerance; Supercooling; Temperature tolerance; Thermal stress; thermal tolerance
• ISSN: 0269-8463; 1365-2435
• DOI: 10.1111/1365-2435.12310

Summary Thermal tolerance may limit and therefore predict ectotherm geographic distributions. However, which of the many metrics of thermal tolerance best predict distribution is often unclear, even for drosophilids, which constitute a popular and well‐described animal model. Five metrics of cold tolerance were measured for 14 Drosophila species to determine which metrics most strongly correlate with geographic distribution. The species represent tropical to temperate regions but all were reared under similar (common garden) conditions (20 °C). The traits measured were: chill coma temperature (CTmin), lethal temperature (LTe50), lethal time at low temperature (LTi50), chill coma recovery time (CCRT) and supercooling point (SCP). Measures of CTmin, LTe50 and LTi50 proved to be the best predictors to describe the variation in realized latitudinal distributions (R2 = 0·699, R2 = 0·741 and 0·550, respectively) and estimated environmental cold exposure (R2 = 0·633, R2 = 0·641 and 0·511, respectively). Measures of CCRT also correlated significantly with estimated minimum temperature (R2 = 0·373), while the SCP did not. These results remained consistent after phylogenetically independent analysis or when applying nonlinear regression. Moreover, our findings were supported by a similar analysis based on existing data compiled from the Drosophila cold tolerance literature. Trait correlations were strong between LTe50, LTi50 and CTmin, respectively (0·83 > R2 > 0·55). However, surprisingly, there was only a weak correlation between the entrance into coma (CTmin) and the recovery from chill coma (CCRT) (R2 = 0·256). Considering the findings of the present study, data from previous studies and the logistical constraints of each measure of cold tolerance, we conclude that CTmin and LTe50 are superior measures when estimating the ecologically relevant cold tolerance of drosophilids. Of these two traits, CTmin requires less equipment, time and animals and thereby presents a relatively fast, simple and dynamic measure of cold tolerance. Lay Summary