News Release 

A better model for predicting death by heat in nature?

American Association for the Advancement of Science

Research News

A mathematical model that better accounts for temperature impacts from duration of exposure is helping scientists improve their grasp of how future climate warming will affect the survival of natural Drosophila populations. Instead of critical temperatures, which this work highlights as unreliable predictors of heat mortality, the model accounts for the dynamic and cumulative effects of warming conditions. The approach, say the authors, is readily applicable to other small ectotherms whose survival can be adequately measured in lab settings. In general, critical temperature limits derived from laboratory experiments - which inform how hot an organism can get, and for how long, before it dies - are used to estimate the temperature mortality of natural populations. However, in the highly variable natural environment, predicting heat death is more complicated. Critical limits largely neglect the cumulative effects of thermal stress on an animal's survival and how it varies with temperature and time. Building on previous research, Enrico Rezende and colleagues developed a dynamic model capable of predicting fruit fly mortality under variable temperatures and exposure times using a handful of fixed-temperature heat tolerance laboratory measurements. According to Rezende et al., the model-based theoretical predictions of lethal temperatures for 11 different Drosophila species under different warming conditions were nearly identical to empirical findings; that is, the model correctly predicted similar death times for flies in real-world heat conditions, where temperatures ramped up. "The correspondence of mortality predictions with field observations suggest that this model captures real-world phenomena. And, perhaps most important, the model suggests that relatively low field temperatures... can cause substantial mortality and population collapse," write Raymond Huey and Michael Kearney in a related Perspective.


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