Supplementary code and data for "The paradox of Predictability Provides a Bridge Between 1 Micro- and Macroevolution".
Masahito Tsuboi
Lund University
Web page: www.masahitotsuboi.com
ORCID: 0000-0002-0144-2893
Niklas Hohmann
Utrecht University
email: n.h.hohmann [at] uu.nl
Web page: www.uu.nl/staff/NHohmann
ORCID: 0000-0003-1559-1838
Kjetil L. Voje
ORCID: 0000-0003-2556-3080
Melanie Hopkins
ORCID: 0000-0002-3580-2172
Meghan Balk
ORCID: 0000-0003-2699-3066
Sophie Nilén
ORCID: 0009-0002-0996-0182
Erik I. Svensson
ORCID: 0000-0001-9006-016X
Lee Hsiang Liow
ORCID: 0000-0002-3732-6069
Gene Hunt
ORCID: 0000-0001-6430-5020
R (version >= 4) and the RStudio IDE
Download the code from GitHub. In RStudio, open the file paradox_of_predictability.Rproj
. This open the RProject, installs the renv
package (if it is not already installed), and set the working directory correctly. Next, run
renv::restore()
to install all required packages in the correct version. Now you are set up to interact with the code and data.
Then you can inspect and run the code in the directory code/
. The main analysis is contained in the script code/analysis.R
.
- code : folder with R code
- data : folder with raw and modified data
- contains various files with raw time series data, named after publication and year
- output : folder with data extracted from time series
- var_div_dat : folder with data extracted from time series, with added data on timescale (paleo or neo). This data was added manually
- figs : folder for figures
- renv :
renv
package folder - .gitignore : untracked files
- .Rprofile : R session settings
- LICENSE : Apache 2.0 license file
- paradox_of_predicability.Rproj : R Project file
- README.md : readme file
- renv.lock : lock file for
renv
package
Apache 2.0, see LICENSE file for details.
This work was funded by
- The Center for Advanced Studies in Norwegian Academy of Science and Letters to Thomas F. Hansen and Christophe Pélabon and
- The Japanese Society for the Promotion of Science, Overseas Research Fellowship to Masahito Tsuboi (Grant identification number: 202270014)