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Soil organic carbon stock and uncertainties, 1m depth, at 250m spatial resolution in Canada

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posted on 18.05.2021, 06:22 authored by Camile SotheCamile Sothe, Alemu Gonsamo, James SniderJames Snider, Joyce Arabian, Werner A. Kurz, Sarah FinkelsteinSarah Finkelstein
This project aimed to produce the first wall-to-wall estimate of C stocks in plants and soils of Canada at 250 m spatial resolution. This dataset contains the map with the soil organic carbon (SOC) in kg/m² for entire Canada in 1m depth, and the uncertainty in SOC predictions. The SOC stock map was produced using 6,533 ground soil samples, long-term climate data, remote sensing observations and a machine learning model. The soil samples containing the x and y coordinates, depth and SOC (in g/kg) information were overlaid with the stacked covariates (soil forming factors) to compose the regression matrix. Random forest models were trained using a recursive feature elimination scheme and a cross-validation assessment. The best model was used for spatial prediction of SOC over Canada in intermediate depths between 0 and 1 m. Afterwards, the SOC content maps were corrected with bulk density and coarse fragment information to compute the total carbon stock for each horizon. The horizons have been added to compose the 0-1m depth interval multiplied by root depths fraction to discount shallow soils. Water and ice/snow areas were removed using a mask based on the Land Cover of Canada map. The SOC stock uncertainty map was built using the first and third quantiles of RF quantile regression approach.


Carbon storage and distribution in terrestrial ecosystems of Canada WWF-Canada









McMaster University, School of Earth, Environment & Society, Canada World Wildlife Fund (WWF-Canada)