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 |
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| Format: | info dataset Journal |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4943061 |
Daftar Isi:
- 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, ranging from 1,000 to > 3,000 Pg of C within the top 1 m. Regional assessments may help validate or improve global maps because they can examine landscape controls on SOC stocks and offer a tractable means to retain regionally-specific information, such as soil taxonomy, during database creation and modeling. We compile a new transboundary SOC stock database for coastal watersheds of the North Pacific coastal temperate rainforest, using soil classification data to guide gap-filling and machine learning approaches used to explore spatial controls on SOC and predict regional stocks. Precipitation and topographic attributes controlling soil wetness were found to be the dominant controls of SOC, underscoring the dependence of C accumulation on high soil moisture. The random forest model predicted stocks of 4.5 Pg C (to 1 m) for the study region, 22% of which was stored in organic soil layers. Calculated stocks of 228 ± 111 Mg C ha-1 fell within ranges of several past regional studies and indicate 11-33 Pg C may be stored across temperate rainforest soils globally. Predictions compared very favorably to regionalized estimates from two spatially-explicit global products (Pearson's correlation: ρ = 0.73 vs. 0.34). Notably, SoilGrids250m was an outlier for estimates of total SOC, predicting 4-fold higher stocks (18 Pg C) and indicating bias in this global product for the soils of the temperate rainforest. In sum our study demonstrates that CTR ecosystems represent a moisture-dependent hotspot for SOC storage at mid-latitudes.
- McNicol-2019-NPCTR-SOC-mapThis raster [.tif] is the predicted soil organic carbon for the North Pacific coastal temperate rainforest. Content is displayed in megagrams of carbon per hectare (Mg ha-1) to 1 m in mineral soil, plus overlying organic horizons. Map values are the output of a random forest machine learning algorithm trained on pedon data from within British Columbia and southeast Alaska only, therefore confidence is low for predictions south of the US-Canada border and predictions in that region have not been validated. Lakes, glaciers and ice-fields have also not been masked from the map. More information on the map can be found in the associated manuscript.FluxProject_SOCmap.7zN Pacific coastal temperate rainforest pedon and soil carbon databaseThis database compiles pedon data (ca. 1300 soil profile descriptions) from various sources across coastal British Columbia and southeast Alaska. Each profile includes soil class and horizon designations, and some of the data required for soil carbon stock calculations (e.g. bulk density, carbon concentration, horizon depth and coarse fragment content). Missing data which were gap-filled are highlighted and annotated with comments, and were filled according to procedures outlined in the manuscript and supplement. Data formatting across the different sources were harmonized where possible. References, acknowledgements and field descriptors are provided, including comments on calculation steps. More detail is available in the manuscript supplement.McNicoletal-2018-NPCTR-Pedon-SOC-Database.xlsxFunding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 1557186