Dataset and codes for: Partitioning the apparent temperature sensitivity between autotrophic and heterotrophic protists
Cite this dataset
Chen, Bingzhang et al. (2022). Dataset and codes for: Partitioning the apparent temperature sensitivity between autotrophic and heterotrophic protists [Dataset]. Dryad. https://doi.org/10.5061/dryad.dr7sqvb1v
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).
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.
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Award: SMSEGL20SC02
Universitetet i Bergen, Award: FILAMO mobility grant
Leverhulme Trust, Award: RPG-2020-389
National Science Foundation, Award: OCE-1736635