ABoVE: Characterization of Burned and Unburned Boreal Forest Stands, SK, Canada, 2016 : Arctic-Boreal Vulnerability Experiment (ABoVE)

This dataset provides the results of field measurements and estimates of carbon stocks and combustion rates that characterize burned and unburned southern boreal forest stands near the La Ronge and Weyakwin communities in central Saskatchewan (SK), Canada. Measurements were completed in 2016 at 47 s...

Full description

Bibliographic Details
Main Authors: Dieleman, C., Rogers, B.M., Veraverbeke, S., Johnstone, J.F., Laflamme, J., Gelhorn, L., Solvik, K., Walker, X.J., Mack, M.C., Turetsky, M.R.
Format: Article in Journal/Newspaper
Language:English
Published: ORNL Distributed Active Archive Center 2020
Subjects:
Online Access:https://dx.doi.org/10.3334/ornldaac/1740
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1740
Description
Summary:This dataset provides the results of field measurements and estimates of carbon stocks and combustion rates that characterize burned and unburned southern boreal forest stands near the La Ronge and Weyakwin communities in central Saskatchewan (SK), Canada. Measurements were completed in 2016 at 47 stands that burned in the 2015 Saskatchewan wildfires (Egg, Philion, and Brady) and at 32 unburned stands in comparable adjacent areas. Stands were characterized through field observations and sampling of the vegetative community (i.e. tree species, abundance and biophysical measurements, stand age, coarse woody debris, history of fires or logging), soils (i.e., soil moisture class, unburned and burned soil organic layer depth, samples for bulk density and carbon analyses), and basic landscape geophysical traits. From these results, the pre-fire carbon stocks and carbon combustion values from both the above- and below-ground pools were estimated using a combination of linear and mixed-effects modeling and were calibrated against carbons stocks from the unburned stands. Estimates of uncertainty were generated for above- and below-ground carbon stocks and combustion values using a Monte Carlo framework paired with classic uncertainty propagation techniques.