Modeling soil respiration based on carbon, nitrogen, and root mass across diverse Great Lake forests

The variability in the net ecosystem exchange of carbon (NEE) is a major source of uncertainty in quantifying global carbon budget and atmospheric CO2. Soil respiration, which is a large component of NEE, could be strongly influential to NEE variability. Vegetation type, landscape position, and site history can influence soil properties and therefore drive the microbial and root production of soil CO2. This study measured soil respiration and soil chemical, biological and physical properties on various types of temperate forest stands in Northern Wisconsin (USA), which included ash elm, aspen, northern hardwood, red pine forest types, clear-cuts, and wetland edges. Soil respiration at each of the 19 locations was measured six times during 1 year from early June to mid-November. These data were combined with two additional data sets from the same landscape that represent two smaller spatial scales. Large spatial variation of soil respiration occurred within and among each forest type, which appeared to be from differences in soil moisture, root mass and the ratio of soil carbon to soil nitrogen (C:N). A soil climate driven model was developed that contained quadratic functions for root mass and the ratio of soil carbon to soil nitrogen. The data from the large range of forest types and site conditions indicated that the range of root mass and C:N on the landscape was also large, and that trends between C:N, root mass, and soil respiration were not linear as previously reported, but rather curvilinear. It should be noted this function appeared to level off and decline at C:N larger than 25, approximately the value where microbial nitrogen immobilization limits free soil nitrogen. Weak but significant relationships between soil water and soil C:N, and between soil C:N and root mass were observed indicating an interrelatedness of (1) topographically induced hydrologic patterns and soil chemistry, and (2) soil chemistry and root production. Future models of soil respiration should address multiple spatial and temporal factors as well as their co-dependence.