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Abstract National nutrient inventories provide surplus phosphorus (P) estimates derived from county‐scale mass balance calculations using P inputs from manure and fertilizer sales and P outputs from crop yield data. Although bioavailable P and surplus P are often correlated at the field scale, few studies have investigated the relationship between measured soil P concentrations of large‐scale soil testing programs and inventory‐based surplus P estimates. In this study, we assessed the relationship between national surplus P data from the NuGIS dataset and laboratory‐measured soil test phosphorus (STP) at the county scale for Arkansas, North Carolina, and Oklahoma. For optimal periods of surplus P aggregation, surplus P was positively correlated with STP based on both Pearson (Arkansas:r = 0.65, North Carolina:r = 0.45, Oklahoma:r = 0.52) and Spearman correlation coefficients (Arkansas:ρ = 0.57, North Carolina:ρ = 0.28, and Oklahoma:ρ = 0.66). Based on Pearson correlations, the optimal surplus P aggregation periods were 10, 30, and 4 years for AR, NC, and OK, respectively. On average, STP was more strongly correlated with surplus P than with individual P inventory components (fertilizer, manure, and crop removal), except in North Carolina. In Arkansas and North Carolina, manure P was positively correlated with STP, and fertilizer P was negatively correlated with STP. Altogether, results suggest that surplus P moderately correlates with STP concentrations, but aggregation period and location‐specific factors influence the strength of the relationship. 

Abstract Predicting the partitioning between aqueous and gaseous C across landscapes is difficult because many factors interact to control carbon dioxide (CO₂) concentrations and removal as dissolved inorganic carbon (DIC). For example, carbonate minerals buffer soil pH and allow CO₂dissolution in porewaters, but nitrification of fertilizers may decrease pH so that carbonate weathering results in a gaseous CO₂efflux. Here, we investigate CO₂partitioning in an agricultural, first‐order, mixed‐lithology humid, temperate watershed. We quantified soil mineralogy and measured porewater chemistry, soil moisture, and soil pCO₂and pO₂as a function of depth at three hillslope positions. Variation of soil moisture along the hillslope was the dominant control on the concentration of soil CO₂, but mineralogy acted as a secondary control on the partitioning of CO₂between gaseous and aqueous phases. Regression slopes of pCO₂versus pO₂in the carbonate‐bearing soils indicate a deficit of aerobically respired CO₂relative to O₂(p < 0.05). Additionally, nitrification of upslope fertilizers did not lower soil pH and therefore did not cause a gaseous CO₂flux from carbonate weathering. We concluded that in the calcareous soils, up to 43% of respired C potentially dissolves and drains from the soil rather than diffusing out to the atmosphere. To explore the possible implications of the reactions we evaluated, we used databases of carbonate minerals and land uses to map types of soil degassing behaviors. Based on our maps, the partitioning of respired soil CO₂to the aqueous phase could be important in estimating ecosystem C budgets and models. 

Abstract Soils derived from different lithologies and their controls on preferential flow remain underexplored in forested landscapes. In the same lithology, the propensity for preferential flow occurrence at different hillslope positions also remains largely elusive. By utilizing a soil moisture response time method, we compared preferential flow occurrence between a shale site (Shale Hills, silt loam soils) and a sandstone site (Garner Run, sandy loam soils) at four hillslope positions: ridge‐top, North‐ and South‐facing mid‐slopes and toe slope, for over 2 years. The catchments are neighbouring and covered by temperate forest. For the four hillslope positions, Shale Hills had higher preferential flow frequencies compared to Garner Run. Between these two catchments, the South‐facing mid‐slope sites showed the highest contrasts in preferential flow frequency (33.5% of events at Shale Hills vs. 8.8% at Garner Run) while the ridge‐top sites showed the lowest contrasts (18.7 vs. 13.2%). Additionally, over the unfrozen period, for seven out of eight monitoring sites, drier antecedent conditions tended to be more favourable for preferential flows to occur, with significant (p < .01) relationships at two sites. Except for the South‐facing mid‐slope sites, both Shale Hills and Garner Run had two preferential flow pathways. The characteristic preferential flow pathways at Shale Hills were the B_wand C horizons, and for Garner Run, preferential flow moved from the E/AE horizon to the B_whorizon. This study shows that shale‐derived soils tended to have higher preferential flow occurrence than sandstone soils, but hillslope positions exhibit different levels of contrasts. More effort should be paid to study the impact of lithology on preferential flows in the context of land surface modelling and biogeochemical reactions to improve ecosystem services of headwater catchments.