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Woody encroachment is a widespread phenomenon in grassland ecosystems, driven by overgrazing, fire suppression, nitrogen deposition and climate change, among other environmental changes. The influence of woody encroachment on processes such as chemical weathering however is poorly understood. In particular, for fast reactions such as carbonate weathering, root traits associated with woody encroachment (e.g., coarser, deeper, and longer residence times) can potentially change fluxes of inorganic carbon into streams and back to the atmosphere, providing CO2-climate feedbacks. Here we examine the influence of deepening roots arising from woody encroachment on catchment water balance and carbonate weathering rates at Konza a tallgrass prairie within a carbonate terrain where woody encroachment is suspected to drive the groundwater alkalinity upwards. We use a watershed reactive transport model BioRT-Flux-PIHM to understand the ramifications of deepening roots. Stream discharge and evapotranspiration (ET) measurements were used to calibrate the hydrology model. The subsurface CO2 concentration, water quality data for groundwater, stream, soil water and precipitation were used to constrain the soil respiration and carbonate dissolution reaction rates. The hydrology model has a Nash-Sutcliffe Efficiency value of 0.88. Modelling results from numerical experiments indicate that woody encroachment results in overall lower stream flow due to higher ET, yet the groundwater recharge is higher due to deep macropore development from deepening roots. The deeper macropores enhance carbonate weathering rate as more acidic, CO2-rich water recharges the deeper calcite bedrock. Accounting for the change in inorganic carbon fluxes caused by such land use changes gives a better estimate of carbon fluxes in the biosphere. Such knowledge is essential for effective planning of climate change mitigation strategies. 

ABSTRACT Woody encroachment—the expansion of woody shrubs into grasslands—is a widely documented phenomenon with global significance for the water cycle. However, its effects on watershed hydrology, including streamflow and groundwater recharge, remain poorly understood. A key challenge is the limited understanding of how changes to root abundance, size and distribution across soil depths influence infiltration and preferential flow. We hypothesised that woody shrubs would increase and deepen coarse‐root abundance and effective soil porosity, thus promoting deeper soil water infiltration and increasing soil water flow velocities. To test this hypothesis, we conducted a study at the Konza Prairie Biological Station in Kansas, where roughleaf dogwood (Cornus drummondii) is the predominant woody shrub encroaching into native tallgrass prairie. We quantified the distribution of coarse and fine roots and leveraged soil moisture time series and electrical resistivity imaging to analyse soil water flow beneath shrubs and grasses. We observed a greater fraction of coarse roots beneath shrubs compared to grasses, which was concurrent with greater saturated hydraulic conductivity and effective porosity. Half‐hourly rainfall and soil moisture data show that the average soil water flow through macropores was 135% greater beneath shrubs than grasses at the deepest B horizon, consistent with greater saturated hydraulic conductivity. Soil‐moisture time series and electrical resistivity imaging also indicated that large rainfall events and greater antecedent wetness promoted more flow in the deeper layers beneath shrubs than beneath grasses. These findings suggest that woody encroachment alters soil hydrologic processes with cascading consequences for ecohydrological processes, including increased vertical connectivity and potential groundwater recharge. 

Abstract Understanding soil organic carbon (SOC) response to global change has been hindered by an inability to map SOC at horizon scales relevant to coupled hydrologic and biogeochemical processes. Standard SOC measurements rely on homogenized samples taken from distinct depth intervals. Such sampling prevents an examination of fine‐scale SOC distribution within a soil horizon. Visible near‐infrared hyperspectral imaging (HSI) has been applied to intact monoliths and split cores surfaces to overcome this limitation. However, the roughness of these surfaces can influence HSI spectra by scattering reflected light in different directions posing challenges to fine‐scale SOC mapping. Here, we examine the influence of prescribed surface orientation on reflected spectra, develop a method for correcting topographic effects, and calibrate a partial least squares regression (PLSR) model for SOC prediction. Two empirical models that account for surface slope, aspect, and wavelength and two theoretical models that account for the geometry of the spectrometer were compared using 681 homogenized soil samples from across the United States that were packed into sample wells and presented to the spectrometer at 91 orientations. The empirical approach outperformed the more complex geometric models in correcting spectra taken at non‐flat configurations. Topographically corrected spectra reduced bias and error in SOC predicted by PLSR, particularly at slope angles greater than 30°. Our approach clears the way for investigating the spatial distributions of multiple soil properties on rough intact soil samples.