Data from: Large, climate-sensitive soil carbon stocks mapped with pedology-informed machine learning in the North Pacific coastal temperate rainforest ...

• Main Authors: McNicol, Gavin, Bulmer, Chuck, D'Amore, David, Sanborn, Paul, Saunders, Sari, Giesbrecht, Ian, Arriola, Santiago Gonzalez, Bidlack, Allison, Butman, David, Buma, Brian
• Format: Dataset
• Language: English
• Published: Dryad 2018
• Subjects: Anthropocene; Soil carbon; Pedology; Holocene; temperate rainforest; British Columbia; Canada; Pacific; glaciers; Alaska
• Online Access: https://dx.doi.org/10.5061/dryad.5jf6j1r; https://datadryad.org/stash/dataset/doi:10.5061/dryad.5jf6j1r

Accurate soil organic carbon (SOC) maps are needed to predict the terrestrial SOC feedback to climate change, one of the largest remaining uncertainties in Earth system modeling. Over the last decade, global scale models have produced varied predictions of the size and distribution of SOC stocks, ra...