Journal article
Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks
Environmental pollution (1987), Vol.152(2), pp.267-273
2008
DOI: 10.1016/j.envpol.2007.06.057
PMID: 17706329
Abstract
Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0
million metric tons of carbon per year for the GIS and regression approaches respectively.
Large differences in estimates of soil organic carbon stocks and annual changes in stocks for Wisconsin forestlands indicate a need for validation from forthcoming forest surveys.
Details
- Title: Subtitle
- Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks
- Creators
- J Elliott Campbell - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USAJeremie C Moen - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USARichard A Ney - Sebesta Blomberg & Associates Inc., North Liberty, IA 52317, USAJerald L Schnoor - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Environmental pollution (1987), Vol.152(2), pp.267-273
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.envpol.2007.06.057
- PMID
- 17706329
- ISSN
- 0269-7491
- eISSN
- 1873-6424
- Language
- English
- Date published
- 2008
- Academic Unit
- Civil and Environmental Engineering; Occupational and Environmental Health
- Record Identifier
- 9983997977602771
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