Nicholas R. Patton

Predicting soil thickness on soil mantled hillslopes

Soil thickness is a fundamental variable in many earth science disciplines due to its critical role in many hydrological and ecological processes, but it is difficult to predict. Here we show a strong linear relationship (r2 = 0.87, RMSE = 0.19 m) between soil thickness and hillslope curvature across both convergent and divergent parts of the landscape at a field site in Idaho. We find similar linear relationships across diverse landscapes (n = 6) with the slopes of these relationships varying as a function of the standard deviation in catchment curvatures. This soil thickness-curvature approach is significantly more efficient and just as accurate as kriging-based methods, but requires only high-resolution elevation data and as few as one soil profile. Efficiently attained, spatially continuous soil thickness datasets enable improved models for soil carbon, hydrology, weathering, and landscape evolution.Soil thickness is a key parameter in earth system models, yet how it varies spatially at catchment scales is largely unknown due to measurement challenges. Here, the authors show that a continuous field of thicknesses can be predicted using high-resolution topography and a few soil thickness measurements.

Controls on gross production in an aspen-sagebrush vegetation mosaic: Controls on gross production in an aspen-sagebrush mosaic

The critical zone (CZ; defined as the zone between the top of the vegetation canopy and the groundwater) mediates the impact of precipitation amount and timing on water availability and plant productivity. However, CZ structure, including soil and subsurface properties, are almost always unknown, leading to considerable uncertainty in the links between precipitation, plant water availability, and gross production. Using multiyear records of gross ecosystem CO2 exchange (GEE), micrometeorology, and streamflow, we examined the sensitivity of GEE to environmental controls in a sagebrush shrubland and an aspen forest. The sites were within 500 m of each other and had similar precipitation and temperature but marked differences in CZ structure. Cumulative growing season GEE was approximately two times greater at the aspen compared with the sagebrush, underscoring the importance of CZ properties in structuring spatial “hot spots” for carbon cycling. Larger soil water holding capacity and topography that produced lateral subsurface flow to the aspen enabled marked difference in plant functional type. Annual variability in growing season GEE within each site was not driven by annual precipitation; this lack of relationship was attributed to the CZs limited ability to store water and an associated increase in water yield. Instead, both seasonal timing and cumulative growing season GEE for the sagebrush varied with spring and summer rain, whereas aspen GEE responded to spring snowpack conditions. These results emphasized how mapping and understanding CZ structure will help predict the spatial variability in plant functional type and temporal sensitivity of growing season GEE.