DOI: 10.5683/sp3/d8kcyz
title: Soil organic carbon stock and uncertainties, 30cm and 1m depth, at 250m spatial resolution in Canada, version 3.0

description: 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 30cm and 1m depth, and the uncertainty in SOC predictions. The SOC stock map was produced using 39,323 ground samples of soil organic carbon concentration (g/kg) distributed in 6,533 sites, 11,068 ground samples of bulk density (kg/dm3) distributed in 2,157 sites, 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 (0cm, 5cm, 15cm, 30cm, 60cm, 100cm). Afterwards, the SOC stock of each depth increment was computed using SOC concentration and bulk density maps, and corrected with coarse fragment information. The depth increments have been added to compose the 0-30cm and 0-1m depth intervals multiplied by rooting depths fraction to discount shallow soils. Water and ice/snow areas were removed using a mask based on the Land Cover of Canada map. Ground ice in permafrost areas was discounted according to ice abundance using the ground ice map of Canada. The SOC stock uncertainty map is the difference between the first and third quantiles of a quantile regression forest approach of SOC concentration and bulk density prediction (90% confidence interval).
description: *** Carbon storage and distribution in terrestrial ecosystems of Canada ***
Authors: C. Sothe,1* A. Gonsamo,1 J. Arabian,2 W. A. Kurz,3 S. A. Finkelstein,4 J. Snider2
1School of Earth, Environment & Society, McMaster University, Hamilton, Ontario, Canada.
2World Wildlife Fund Canada, Toronto, Ontario, Canada.
3Canadian Forest Service, Natural Resources Canada, Victoria, British Columbia, Canada.
4Department of Earth Sciences, University of Toronto, Toronto, Ontario, Canada.

Corresponding author: Camile Sothe (sothec@mcmaster.ca) 

***General Introduction***
This dataset contains the updated version of maps with the spatial distribution of soil carbon stock in Canada and associated uncertainties.
It is being made public to act as supplementary data for the publication 'Large soil carbon storage in terrestrial ecosystems of Canada'.

The maps were produced in the Remote Sensing Lab, McMaster University, between January 2020 and October 2021.
This research project was made possible by a grant from the World Wildlife Fund (WWF)- Canada

***Purpose of the project***
This project aimed to produce the first wall-to-wall estimate of carbon stocks in plants and soils of Canada at 250 m spatial resolution 
using multisource satellite, climate and topographic data and a machine-learning algorithm.

***Methods***
To generate the soil carbon stock map, we used 39,323 ground samples of soil organic carbon concentration (g/kg) distributed in 6,533 sites, 11,068 ground samples of bulk density (kg/dm3) distributed in 2,157 sites, long-term climate data, multisource remote sensing data, topographic information, soil type, depth, and a 3D random forest regression model. 
The uncertainty map was generated using the random forest quantile regression approach difference between 95th and 5th quantiles (90% confidence interval) 
of soil organic carbon and bulk density predictions.

***Description of the data***
-250m spatial resolution 
-WGS-84 projection
-Area= 8.4 million km²
-Units= kg/m²
-0-30cm and 0-1m soil depth
-water and ice/snow areas were masked based on the 2015 Land Cover of Canada (https://open.canada.ca/data/en/dataset/4e615eae-b90c-420b-adee-2ca35896caf6)
-SOC stock in permafrost areas was discounted according to ice abundance using the 'Ground ice map of Canada' (O'Neill et al., 2020 - https://doi.org/10.4095/326885)
-shallow soils were discounted using the rooting depth fraction from the National Soil Database (http://sis.agr.gc.ca/cansis/nsdb/slc/index.html)