We use the free software R (version 4.2.0) with R packages (foreach, nlme, plyr, dplyr) to analyse these datasets. R codes are also provided.Funding provided by: Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100019651Award Number: SMSEGL20SC02Funding provided by: Universitetet i BergenCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100005036Award Number: FILAMO mobility grantFunding provided by: Leverhulme TrustCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000275Award Number: RPG-2020-389Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: OCE-1736635

Conventional analyses suggest the metabolism of heterotrophs is thermally more sensitive than that of autotrophs, implying that warming leads to pronounced trophodynamic imbalances. However, these analyses inappropriately combine within- and across-taxa trends. We present a novel mathematic framework to separate these, revealing that the higher temperature sensitivity of heterotrophs is mainly caused by within-taxa responses which account for 92% of the difference between autotrophic and heterotrophic protists. This dataset contains both the datasets and R codes of per capita growth rates of autotrophic and heterotrophic protists as well as heterotrophic bacteria and insects.

The datasets of per capita growth rates against temperature were compiled from the literature. Experimental data were included if they met the following criteria: at least 3 data points with positive growth rate (µ) and at least 2 unique temperatures at which positive µ were measured. To calculate apparent activation energy, we also removed data points with nonpositive µ and those with temperatures above the optimal growth temperature (defined as the temperature corresponding to the maximal µ).