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. 2019 Feb 8;10:671. doi: 10.1038/s41467-019-08602-6

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — Drivers of changes in woody cover in tropical savannas. a Relative weights of variables describing rainfall climatology as well as environmental variables explaining woody cover changes (1992–2012) from the LMG method based on a least squares regression model. Rainfall climatology: changes in annual rainfall, heavy rainfall frequency and rainy days; T&S: changes in mean annual air temperature and solar radiation (represented by cloud cover); management: changes in human population density and fire (burned area fraction); static includes variables: mean annual rainfall, coefficient of inter-annual rainfall variability, soil organic carbon, elevation and sand fraction. b Changes in rainfall climatology and woody cover were averaged along the mean annual rainfall gradient (50 mm yr⁻¹ steps); all variables were rescaled to 0–100. c Sensitivity of changes in woody cover towards changes in rainfall variables (expressed as slope from a linear regression; β_{woody-Rainfall}) for each rainfall region. Error bars indicate the 5–95 % confidence intervals. All rainfall climatology variables were normalized