Predictions of response to temperature are contingent on model choice and data quality. Issue 23 (15th November 2017)

• Record Type: Journal Article
• Authors: Low‐Décarie, Etienne; Boatman, Tobias G.; Bennett, Noah; Passfield, Will; Gavalás‐Olea, Antonio; Siegel, Philipp; Geider, Richard J.
• Is Part Of: Ecology and evolution. Volume 7:Issue 23(2017:Dec.)
• Page Start: 10467
• Page End: 10481
• Publication Date: 2017-11-15
• Subjects: biogeography -- biotrait -- global change -- niche -- thermodynamic -- warming; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.3576
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra‐ and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms. We found that many of the surveyed equations have comparable abilities to fit data and equally high requirements for data quality (number of test temperatures and range of response captured) but lead to different estimates of cardinal temperatures and of the biological rates at these temperatures. When these rate estimates are used for biogeographic predictions, differences between the estimates of even the best‐fitting models can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models. Abstract : We review and test the use of 12 equations that model the temperature dependence of biological processes across the full range of their temperature response, including supra‐ and suboptimal temperatures. When rate estimates from these equations are used for biogeographic predictions, differences between the estimates of even the best‐fitting equations can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models.