/spatial_ecoevo

Primary LanguageRGNU General Public License v3.0GPL-3.0

Computer code and data for the paper "The importance of species interactions in eco-evolutionary community dynamics under climate change" by Ă…kesson et al., published in Nature Communications.

  • Operating systems: CentOS 7, Ubuntu 19.10, Ubuntu 20.04, MacOS 10.13, Windows 10.
  • Software dependencies: R (has been tested with R 4.1.0).
  • Required R packages:
    • deSolve: Integrating differential equations.
    • tidyverse: Efficient data manipulation and plotting.
    • ggpmisc: Adding statistical information to plots.
    • Rcpp: Importing and compiling functions written in C/C++.
  • Required non-standard hardware: none.
  • Typical installation time on a normal desktop computer: no appreciable time if R is already installed. Otherwise, it is the installation time of R and the above three packages.

The following files are in the repository:

  • This README.

  • COPYING.txt: GNU General Public License, v3.0.

  • ecoevo_main.R: This script runs the eco-evolutionary model. It can either be run directly from within R, or via the command prompt, by entering the following: Rscript ecoevo.R [vbar] [dbar] [model] [replicate] [outfile] The input parameters are:

    • [vbar]: Average genetic variance (in units of degrees Celsius squared).
    • [dbar]: Average dispersal distance (expressed as the fraction of the pole-to-equator distance, 10,000 km).
    • [model]: Either baseline, trophic, Tdep, or Tdep_trophic, for the four model variants (baseline is without trophic interactions or temperature-dependent competition; trophic is with trophic interactions but no temperature-dependent competition; Tdep is with temperature-dependent competition but no trophic interactions; and Tdep_trophic is with both temperature-dependent competition and trophic interactions).
    • [replicate]: An integer, used to seed the random number generator with (so keeping replicate equal in two subsequent runs of the same model results in the exact same output).
    • [outfile]: Name (with path and extension) of file in which the generated data will be saved (e.g. cc_data.csv). The output is saved in csv format. If this argument is left blank, then the data are not saved, and instead a plot of the system's time evolution is created.

  • plotting_functions.R: Functions for visualizing model results and replicating the manuscript's figures.

  • rhs_eval.cpp: Routines for evaluating the right-hand side of the dynamical equations. They are written in C instead of R, because this is a major bottleneck in terms of speed.

  • data_10_replicates.rds: A compressed data file containing a subsample of 10 out of our 100 replicates (to keep the file size manageable). It can be loaded in R with e.g. dat <- readr::read_rds("data_10_replicates.rds"). After that, one can apply the functions in plotting_functions.R to this dataset to reproduce the figures in our manuscript (with the caveat that the file only contains 10 out of the 100 replicates).