Solomon Ehosioke

and 11 more

The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in-situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Our Apparent electrical conductivity (ECa) maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m) and also detected additional soil units that were missed in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non-invasive characterization of soils in sampling-restricted sites where only non-invasive measurements are feasible. Results from ERT and GPR are consistent with the surficial geology of the study area and revealed variation in the vertical silty-clay and till sequence down to 3.5 m depth. These results indicate that multiple geophysical methods can be used to extrapolate soil properties and map stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

Ruth Whittington

and 1 more

With temperatures rising in Arctic regions at double the global average, decomposition rates and subsequent greenhouse gas release into the atmosphere are expected to rise, potentially shifting these regions from carbon sinks to carbon sources. General circulation models predict the relationship between respiration and temperature using exponential functions, showing a temperature-independent rate of increase to decomposition rates with temperature. However, enzymes catalyzing carbon depolymerization reactions have demonstrated departures from this predicted increase between 10 and 15 °C. Organic tundra soils were incubated across this range (4 to 20 °C, 4 °C increments) and harvested consecutively after carbon losses equivalent to those after 2, 4, 8, and 12 days at 20 °C. During each harvest, β-glucosidase (BG) and β-xylosidase (BX) activities were measured at both the incubation temperature and at 20 °C to determine temperature limitations to enzyme activity and production. While enzyme activities in soils incubated at different temperatures diverged significantly when measured at different temperatures, these differences were overcome when measured at 20 °C, suggesting enzyme activities are more limited than enzyme production. Two exceptions to this trend were the first harvest of the 4 and 8 °C incubations, which had significantly higher BG and BX activities when assayed at 20 °C than soils incubated at higher temperatures, indicating larger enzyme pool sizes in soils incubated at lower temperatures. For BG activities, increased enzyme pool size offset low temperature limitations to enzyme activity, resulting in no difference in measured rates when the 4 and 8 °C soils were compared with the 12 and 16 °C soils, respectively. However, in subsequent harvests, BG and BX activities measured at 20 °C declined and activities at 4 and 8 °C were significantly lower than in assays at 12, 16, and 20 °C. Declining activities of these enzymes in the 4 and 8 °C incubations may indicate limited substrate accessibility or nutrient availability at lower temperatures due to changes in the relative rates of other decomposition reactions with temperature. Improving our understanding of the multifaceted impacts of temperature on decomposition reactions will be important to better model and predict future carbon release.