Using soil physical properties to predict C and N cycling in a northern hardwood forest

Background/Question/Methods

Soil physical structure is an important determinant of soil function, controlling water and gas transport, and thus mediating microbial transformations including mineralization and immobilization of C and N. A great deal of attention has been focused on the biological controls on C cycling in forest soils in light of greenhouse gas concerns, but much less emphasis has been placed on understanding the soil physics mediating the soil biogeochemical response. A prior study at the Hubbard Book Experimental Forest (HBEF), New Hampshire, USA suggested that clay fraction is a statistically significant predictor of root density. At other sites, particle size has been shown to correlate with nitrification. In this study, we hypothesized that soil C and N mineralization rates are coupled, and that the highest rates occur near small particles/pores where C, N, and soil moisture are highest. The overall objectives of our study were to (1) characterize soil architectures by measuring soil particle size distributions and estimating pore size distributions in different soil horizons; (2) measure C and N isotopes of different particle sizes and in soil extracts; and (3) establish relationships between soil C and N mineralization rates and soil physical measurements.

Results/Conclusions

We measured net nitrification and N mineralization potential for all soil horizons in three sets of paired plots in Watershed 3 at the HBEF. Each set of plots included an upslope and a downslope plot in close proximity but representing different soil profile types. For two of the plot pairs, nitrification was higher in the upslope plot. We found the both δ15N and δ13C tended to increase with decreasing particle size in the bulk soil and in the 5 particle size classes. The percent clay, measured by sieving and by laser diffraction, was less than 3% for all horizons. These data, combined with characterization of the physical structure using visual analysis of soil thin sections, can show linkages between soil physical properties and C and N cycling, which may provide insights useful in modeling C dynamics in forest ecosystems.