WoodyEncroachmentHub

Description

This repo contains data and code for the manuscript "Woody plant encroachment intensifies under climate change across tundra and savanna biomes".

Authors

Mariana García Criado, Isla H. Myers-Smith, Anne D. Bjorkman, Caroline E.R. Lehmann and Nicola Stevens

Contact: Mariana García Criado, mariana.garcia.criado@gmail.com

Data use guidelines

Data are publicly available using a Creative Commons Attribution 4.0 International copyright (CC BY 4.0; see license.txt). Data are fully public but should be appropriately referenced by citing the paper. Although not mandatory, we additionally suggest that data users contact and collaborate with data contributors if this dataset will contribute a substantial proportion of observations used in a particular paper or analysis. DOI for this dataset is 10.5281/zenodo.3601454

Data availability & access

The data and code for this manuscript will be mantained at this GitHub repository (https://github.com/marianagarciacriado/WoodyEncroachmentHub).

Citation

García Criado, M., Myers-Smith, I.H., Bjorkman, A.D., Lehmann, C.E.R. and Stevens, N. 2020. Woody plant encroachment intensifies under climate change across tundra and savanna biomes. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13072

Acknowledgments from the manuscript

M.G.C. was supported by the Principal Career’s Development PhD Scholarship from The University of Edinburgh. I.M.S. was supported by the NERC Shrub Tundra grant (NE/M016323/1). We thank all tundra and savanna data collectors, including members of the International Tundra Experiment Network (ITEX), for their efforts in data collection and for making their data accessible. We are grateful to Jakob Assmann for his assistance in extracting and manipulating the CHELSA climatic data. We thank local and indigenous peoples of the tundra and savanna biomes for the opportunity to work with data collected on their lands.

Data

All data for our analyses can be found in the mastersheets folder.

Scripts

All the analyses undertaken for this manuscript are split between multiple R scripts within the scriptsfolder. They can be followed in a sequential order (i.e., 01 to 12), but I recommend not to run scripts #5 and #6 as they deal with the extraction and manipulation of raster data from CHELSA (http://chelsa-climate.org/). Both the climatologies and time series are large files and are thus stored in a hard drive so it is not possible to run the scripts without access to the climatic raster files.

Figures

The figures generated in R are stored in the figures folder.

Model outputs

Full model outputs for statistical analyses are stored in the models folder.

Software requirements

R version 3.4.3 or greater.

R packages: tidyverse, proj4, scales, ggalt, ggplot2, dplyr, cowplot, MCMCglmm, ggbpubr, raster, rgdal, rasterVis, sp, tidyr, readr, broom, stargazer