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The essential roles of Fe oxides in stabilizing long-term soil organic carbon (SOC), especially aromatic dissolved organic carbon (DOCaro), are well-established in forest soils and sediments. We chose to focus on these processes in agricultural soils in which the input and translocation of native DOC to deeper soils are impacted by management practices. We quantified SOC, Fe oxide bound SOC (Fe-bound OC), and the DOCaro sorption in a forest, a cropland, and a pasture soil at 0–10 and 10–25 cm. Significantly larger amounts of Fe oxides in the cropland soil were observed compared to the forest and pasture soils at both depths (p < 0.05). Land management practices and depth both significantly influenced the Fe-bound OC percentage (p < 0.05). Larger maximum sorptions of DOC in the cropland (315.0 mg kg−1) and pasture (395.0 mg kg−1) soils than the forest soil (96.6 mg kg−1) at 10–25 cm weres found. DOCaro sorption decreased in the three soils at 0–10 cm (slope of −0.002 to −0.014 L2 mg−2 m−1) as well as the forest soil at 10–25 cm (−0.016 L2 mg−2 m−1) with increasing equilibrium DOC concentration. Conversely, the cropland and pasture soils at 10–25 cm increased (0.012 to 0.014 L2 mg−2 m−1). The different sorption behaviors of DOCaro in these surface soils indicate that the forest, cropland, and pasture-managed soils may have more complex and various sorption behaviors in stabilizing DOCaro and non-DOCaro. [ABSTRACT FROM AUTHOR]

Soil organic C (SOC) pools have various stabilization mechanisms and turnover times, which change with depth and are highly influenced by land use. Total SOC (TOC), particulate organic carbon (POC), mineral-associated organic carbon (MOC), and carbon management index (CMI) were used as indicators to compare cropland with manure application (CM) and continuous pasture (CP) to a hardwood forest (HF) at soil 0–10 and 10–25 cm depths. Land use, depth, and their interactions had significant influences on TOC, POC, MOC, MOC/TOC ratio, and CMI except for land use main effect on TOC. Compared to HF and CP soils, CM showed significantly larger POC (12.4 g kg−1) and smaller MOC (8.36 g kg−1) at 10–25 cm; CM had significantly smaller TOC (32.3 g kg−1) and MOC at 0–10 cm (11.81 g kg−1). CM soil at 10–25 cm had higher soil quality and SOC lability as indicated by a significantly larger CMI value (419.2), while CP soil had lower soil quality and SOC lability at 0–10 cm (83.7) and 10–25 cm (73.6) compared to HF soil. This study implied high sensitivity of cropland and pasture surface SOC to degrade under disturbance, which implies that better management strategies are still needed to improve soil quality for these agricultural systems. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) and iron (Fe) have been observed to be the important contributors to surface water brownification. Additionally, the DOC quality influences water color by forming Fe-DOC complexes that provide additive effects and is influenced by dominant land use type within watersheds. However, the influence of quantity and quality of DOC on Fe and water color is poorly understood in headwater streams. The aim of this study was to investigate the effects of DOC and Fe on water color in forest (FC) and pasture (GFC) fine-scale watersheds to remove the confounding effects of climate and soil parent material. Significant differences of DOC, Fe, and water absorbance at 420 nm (a420) between FC and GFC were found (p < 0.05). A dominant contribution to water color was from DOC (95.5 − 63.7%) with a decreasing trend when Fe increased from 0.011 to 0.258 mg L−1. There were no significant interactions between FC and GFC and Fe on either a420/DOC (p = 0.06) or specific ultraviolet absorbance at 254 nm (SUVA254) (p = 0.30). Increasing values of a420/DOC and SUVA254 were significantly associated with increasing Fe concentration (p < 0.01). Significant interactions were found between FC and GFC and Fe on spectral slope ratio (S ratio) (p < 0.01). The response rate of S ratio with increasing Fe per unit was 0.235 for GFC while it was − 11.043 for FC. These differences indicate that land use may change the quality of DOC, influence Fe-DOC interactions, and thus affect water color. Linking the effects of soil Fe and DOC and headwater Fe and DOC may help identify optimal management practice to mitigate surface water brownification. [ABSTRACT FROM AUTHOR]

Red spruce (Picea rubens) ecosystems in the high elevations of the central Appalachians of the eastern United States are the focus of ongoing restoration efforts due to the valuable ecosystem services these forests provide. Recent research has shown that spodic materials still present in the soil represent the pedomemory of the historic extent of red spruce forests in the region. A dataset containing 221 points with varying spodic intensities and 29 environmental variables collected from the Monongahela National Forest in West Virginia, USA, was used to evaluate the utility of a species distribution model, Maximum Entropy (MaxEnt), for predicting the presence of spodic properties. MaxEnt was selected for evaluation because, as a presence-only model, it inherently omits absence locations and thereby reduces the risk of including false absences (i.e., herein, locations that have undergone some level of depodzolization) unlike other models previously used to predict pedomemory. Model outputs that employed three different spodic intensity class inputs—very weak to strong expression, weak to strong expression, and strong expression—resulted in similar spodic probability predictions, though there was less area mapped as transitional probabilities in the strong expression model than the two models that included weaker spodic intensity input data. Permutation importance indicated that no single or small subset of environmental variables controlled the three model outputs, perhaps because the environmental covariates may have been too coarse or not strongly enough associated with podzolization processes to be very important. When the output from the MaxEnt model using the full range of spodic intensities (very weak to strong) was compared to an output produced using a presence-absence model (random forests), there was approximately 62% agreement (where both models predicted presence or both predicted absence) for the cells in the top 40% of the predicted probabilities. • Novel use of Maximum Entropy (species distribution model) to model spodic intensity • Presence-only model reduces risks of potential false absences from depodzolization. • MaxEnt not overly sensitive to different degrees of spodic intensity class data [ABSTRACT FROM AUTHOR]