Global ecosystem restoration has unexpectedly low potential to mitigate climate change

Ecosystem restoration is increasingly recognized as a tool of climate change mitigation. Former global-scale studies predicted that ecosystem restoration can nearly offset human carbon emissions since the Industrial Revolution, but these were heavily criticized for their tree-centric view of global ecosystems or questionable modeling approaches, which hinders planning large-scale, long-term, ecologically appropriate restoration strategies. Here, we developed a model for the carbon capture potential of ecosystem restoration until 2100, and show that the maximum amount is 96.9 Gt of carbon, which is 17.6% of the 640 Gt emitted since 1750, and only 3.7–12.0% if taking into account future emissions until 2100. Thus, ecosystem restoration can play a minor role in climate change mitigation even if orchestrated with a pervasive shift toward sustainable, low-emission economies globally. In addition, if restoration targets are planned to match future climatic conditions and consider state transi..., , , # Global ecosystem restoration has unexpectedly low potential to mitigate climate change [https://doi.org/10.5061/dryad.ksn02v7g4](https://doi.org/10.5061/dryad.ksn02v7g4) ## Description of the data and file structure Data were collected from online open-access databases. ### Files and variables #### File: Global\_model\_of\_ecosystem\_restoration.zip **Description:** Scripts, input data, and output data of the paper \"Global ecosystem restoration has unexpectedly low potential to mitigate climate change\" by Tölgyesi et al., Nature Geoscience # Scripts ## 01\_prepare\_modeling.r R script that prepares the modeling. It creates a list of pieces of information (variable names, modeling parameters, etc.), loads the environmental dataset, and convert the environmental dataset to simple features (sf). ## 02\_train\_and\_evaluate\_models.r R script that trains and evaluates Random Forest models for the four studied ecosystem types, using 5-fold cross-validation. It iterates throug...,