Landscape Influences on Potential Soil Respiration Rates in a Forested Watershed of Southeastern Kentucky

• Published in: Environmental management (New York) 2004-07, Vol.33 (S1), p.S160-S167
• Main Authors: Abnee, Amanda C., Thompson, James A., Kolka, Randall K., D’Angelo, Elisa M., Coyne, Mark S.
• Format: Article
• Language: English
• Subjects: Environmental management; Forest watersheds
• ISSN: 0364-152X; 1432-1009
• DOI: 10.1007/s00267-003-9126-1

Soil respiration measurements conducted in the laboratory have been shown to be related to temperature and moisture, with maximum rates at soil temperatures between 25 and 40 degree C and soil moisture between -0.01 and -0.10 MPa. A preliminary study using forest soils from eastern Kentucky supported the previous research with soil respiration rates greater at 25 degree C than at 15 degree C, with differences in soil respiration rates related to sample site terrain characteristics. To further understand the factors that influence laboratory or potential respiration rates, we conducted a stratified sampling of soils from Robinson Experimental Forest in eastern Kentucky. Sampling was stratified by slope aspect, slope curvature, and landscape position. Potential soil respiration rates varied by slope aspect with NE aspects having greater rates than SW aspects. Rates did not vary by landscape position but did vary by slope curvature on SW aspects with concave curvatures having greater respiration rates than convex curvatures. Predictive soil respiration models based on both terrain attributes and soil chemical properties were created for both slope aspects. The relationships revealed that at this scale soil chemical properties play a more significant role in predicting soil respiration rates than terrain attributes. Models for the NE aspect were stronger than those for the SW aspect. The NE model created from a combination of terrain attributes and chemical properties included extractable Mg, extractable Zn, specific catchment area, and slope aspect (R super(2) sub(adj) = 0.620). The SW model created from a combination of terrain attributes and soil chemical properties included extractable P, extractable Zn, and tangential curvature (R super(2) sub(adj) = 0.413).