Landscape modeling of in situ soil respiration in a forested watershed of southeastern Kentucky, USA

Data on carbon fluxes such as soil respiration are needed to develop strategies for increased carbon sequestration and reduced levels of atmospheric trace gases. Soil respiration is driven by proximal factors (e. g., soil temperature and soil moisture), which affect soil respiration by regulating microbial and root activity, and distal factors (e. g., topography), which affect soil respiration by influencing proximal factors. The objectives of this study were: (1) to relate measured carbon dioxide flux from forest soils to proximal and distal factors; and (2) to develop predictive soil-landscape models of soil respiration across a forested watershed. Carbon dioxide flux from the soil surface was measured monthly for 12 months at sampling points selected using a random stratified approach, with strata established based on slope aspect (NE and SW), slope shape (concave and convex), and slope position (upper, middle, and lower backslope). We generated empirical models using robust linear regression techniques to examine relationships between soil respiration and both proximal (soil physical and chemical properties) and distal factors (terrain attributes calculated from a 30-m digital elevation model). In situ soil respiration rates were greater on the NE-facing slopes than the SW-facing slopes. The models that we developed and validated explain up to 66% of variability in measured soil respiration, although seasonal model relationships varied. Soil temperature was the most consistent proximal factor for predicting soil respiration rates, while slope aspect was the most consistent distal factor among the models.