Data from: Predictions of response to temperature are contingent on model choice and data quality

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 sub-optimal 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.

用于阐释包括生长速率与代谢速率在内的生物过程温度依赖性的各类方程，是我们预测全球生物地球化学、生物地理学如何响应全球气候变化而发生改变的核心基础。本研究综述并检验了12种用于模拟生物过程温度依赖性的方程的应用效果，这些方程覆盖了生物温度响应的全范围，包括超最优与亚最优温度区间。本研究以将这些方程拟合至浮游植物生长的热响应曲线为核心研究重点，同时也针对各类生物的多种性状对这些方程进行了测试。研究发现，诸多被调研的方程在数据拟合能力与对数据质量（测试温度点数、响应区间覆盖度）的要求上都不相上下，但在临界温度以及对应温度下的生物速率的估算结果上却存在显著差异。若将这些速率估算值用于生物地理学预测，即便拟合效果最优的模型，其估算结果之间的差异也可能超过全球变暖十年间预估的全球生物变化量。因此，针对温度全球变化下生物响应的相关研究，必须审慎考量模型选择以及用于这些模型参数化的数据质量。