How to assess Drosophila heat tolerance: Unifying static and dynamic tolerance assays to predict heat distribution limits

Abstract

Abstract Thermal tolerance is a critical determinant of ectotherm distribution, which is likely to be influenced by future climate change. To predict such distributional changes, simple and comparable measures of heat tolerance are needed and these measures should ideally correlate with the characteristics of the species current thermal environments. A recent model (thermal tolerance landscapes—TTLs) uses the exponential relation between temperature and knockdown time to describe the thermal tolerance of ectotherms across time/temperature scales. Here, we established TTLs for 11 Drosophila species representing different thermal ecotypes by measuring knockdown time at 9–17 stressful temperatures (0.5°C intervals). These temperatures caused knockdown times ranging from <10 min to >12 hrs and all species displayed the expected exponential relation between temperature and knockdown time (average R2 = 0.98). Previous studies using TTLs have reported a trade‐off between tolerance to acute and chronic heat stress in ectotherms. The present study did not find evidence to support this trade‐off in drosophilids. Instead, we show how this “trade‐off” can arise as an analytical artefact caused by insufficient data collection and excessive data extrapolation. Dynamic assays represent an alternative method to describe heat tolerance of ectotherms, where animals are exposed to gradually increasing temperatures until knockdown. The comparability of static and dynamic assays has previously been questioned, but here we show that static and dynamic assays give comparable information on heat tolerance. Using the constants derived from static TTLs, we mathematically model the expected dynamic knockdown temperature and subsequently confirm this model by comparison to empirically obtained knockdown temperatures from all 11 species. Characterisation of heat tolerance in laboratory settings is an important tool in thermal biology, but more so if the measures correlate with the environmental gradients that characterise the fundamental niche of species. Here, we show that both static and dynamic assays were characterised by strong correlations to precipitation of the driest month and maximum temperature of the warmest month combined (R2 = 0.68–0.71). This demonstrates that both assay types offer simple measures of heat tolerance that are ecologically relevant for the tested drosophilids. A plain language summary is available for this article.