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Updated: Feb 15, 2026
09:16
Methods of Soil Resampling to Monitor Changes in the Chemical Concentrations of Forest Soils
Published on: November 25, 2016
17.4K
A Canadian upland forest soil profile and carbon stocks database
Cindy Shaw1, Arlene Hilger1, Michelle Filiatrault1
1Canadian Forest Service, Northern Forestry Centre, 5320 122 Street, Edmonton, Alberta, T6H 4B4, Canada.
Ecology
|January 25, 2018
Summary
This study created a comprehensive Canadian forest soil carbon database, integrating soil properties and carbon stocks for improved national carbon accounting and ecosystem modeling. The database aids in refining predictions of soil carbon across diverse Canadian landscapes.
Area of Science:
- Soil Science
- Forest Ecology
- Carbon Sequestration
Background:
- Accurate modeling of forest soil carbon is crucial for national carbon accounting.
- Existing data gaps and variability in soil properties hinder precise carbon stock estimations.
- A unified database is needed to support national-scale ecological and climate change research.
Purpose of the Study:
- To compile a comprehensive database of Canadian upland forest soil profiles and carbon stocks.
- To support the development and refinement of national forest carbon accounting models.
- To enhance the accuracy of digital mapping for ecosite types and soil properties.
Main Methods:
- Compilation of data from 3,253 pedons over 10 years.
- Inclusion of soil organic carbon stocks (Mg/ha) for organic and mineral horizons to 100 cm depth.
- Integration of soil taxonomy, leading tree species, climate data, and location information.
Main Results:
- The database contains detailed soil profile data (16,167 records) and associated carbon stock estimates.
- Data includes soil chemical and physical properties, aiding in carbon stock calculations.
- The database facilitates the development of soil carbon model parameters linked to soil taxonomy and tree species.
Conclusions:
- The developed database is a valuable resource for national forest carbon accounting and modeling.
- Utilizing soil taxonomy and leading tree species improves the accuracy of modeled predictions.
- The database supports regional, national, and international efforts in digital mapping of soil properties and ecosite types.
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