R-code for random forest models related to article 'Arctic soil methane sink increases with drier conditions and higher ecosystem respiration'

• Main Authors: Voigt, Carolina, Kou, Dan
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2023
• Subjects: Climate change
• Online Access: https://doi.org/10.5281/zenodo.8152386

This folder contains two R-script to create Random Forest (RF) models that can be used to reproduce RF model outputs reported in thefollowing article: Voigt, C., Virkkala, A.-M., Hould Gosselin, G., Bennett, K.A., Black, T.A., Detto, M., Chevrier-Dion, C., Guggenberger, G., Hashmi, W., Kohl, L., Kou, D., Marquis, C., Marsh, P., Marushchak, M.E., Nesic, Z., Nykänen, H., Saarela, T., Sauheitl, L., Walker, B., Weiss, N., Wilcox, E.J., Sonnentag, O.(2023). Arctic soil methane sink increases with drier conditions and higher ecosystem respiration. Nature Climate Change. DOI:10.1038/s41558-023-01785-3 [in press]. The flux datasets used in this script areavailable on PANGAEA database under the following DOI: https://doi.org/10.1594/PANGAEA.953120 Example datasets (.csv) with a subset of data areincluded with theseR-scripts. Please cite our work accordingly when using this script or associated data. Script 1: RF models for all vegetation types at Trail Valley Creek, split between Shrub, Lichen, and Tussock Script2: RF models for individual chambers (18 chambers) at Trail Valley Creek, split by month (June, July, August).