TY - JOUR AB - There is currently unprecedented interest in quantifying variation in thermal physiologyamong organisms, especially in order to understand and predict the biological impactsof climate change. A key parameter in this quantification of thermal physiologyis the performance or value of a rate, across individuals or species, at a commontemperature (temperature normalisation). An increasingly popular model for fittingthermal performance curves to data—the Sharpe-Schoolfield equation—can yieldstrongly inflated estimates of temperature-normalised rate values. These deviationsoccur whenever a key thermodynamic assumption of the model is violated, i.e., whenthe enzyme governing the performance of the rate is not fully functional at the chosenreference temperature. Using data on 1,758 thermal performance curves across awide range of species, we identify the conditions that exacerbate this inflation. Wethen demonstrate that these biases can compromise tests to detect metabolic coldadaptation, which requires comparison of fitness or rate performance of differentspecies or genotypes at some fixed low temperature. Finally, we suggest alternativemethods for obtaining unbiased estimates of temperature-normalised rate values formeta-analyses of thermal performance across species in climate change impact studies. AU - Kontopoulos,DG AU - GarcĂ­a-Carreras,B AU - Sal,S AU - Smith,TP AU - Pawar,S DO - 10.7717/peerj.4363 PY - 2018/// SN - 2167-8359 TI - Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits T2 - PeerJ UR - http://dx.doi.org/10.7717/peerj.4363 UR - https://peerj.com/articles/4363/ UR - http://hdl.handle.net/10044/1/56920 VL - 6 ER -