Impact of extreme hydrologic disturbance upon the sediment carbon quality in agriculturally impacted temperate streams

Abstract

The impact of extreme hydrologic disturbances on the quality of fine particulate organic carbon (FPOC) associated with sediments in low-gradient, agriculturally impacted streams remains poorly understood despite the significance of the FPOC pool to benthic food webs, organic matter budgets and nutrient cycles. We estimated immediate and long-term impacts of an extreme flow disturbance on FPOC quality using a 5-year dataset of the stable carbon isotopic signature and a new metric for carbon quality. Results of the study show that the stable isotopic signature of sediment carbon is significantly enriched in the year following the extreme event, which reflects the streams response to accrual of degraded soil carbon. Further, our FPOC metric was found to be inversely proportional to the isotopic signature, suggesting an immediate shift of the benthic ecosystem to lower quality carbon that is retained for more than 1 year before recovering to the pre-disturbance state. Following recovery, results show that the benthic ecosystem exports FPOC with quality that oscillates seasonally -the lowest quality observed in late spring and the highest quality in late fall. Although studies have addressed the response of high-quality algal biomass to fluvial shearing, this study is the first to assess the response of high-quality FPOC to an extreme hydrologic disturbance characterized by sediment deposition in an agriculturally impacted stream.

Reducing equifinality using isotopes in a process‐based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

“…High rates of fixation are reflective of the highly productive nature of open‐canopy, high nutrient streams in the watershed that create nonrate‐limiting conditions for algal growth [ Griffiths et al ., ; Ford and Fox , ]. High rates of denitrification are likely supported by high quality carbon pools associated with algal biomass and detritus accrued in the SFGL of the agroecosystem streams [ Martinelli et al ., 2011; Lane et al ., ; Ford et al ., ].…”

“…Particulate nitrogen includes fine and coarse nitrogen pools comprised primarily of benthic algal biomass and fine particulate sediment particles and aggregates from upland sediment sources [ Ford and Fox , ]. The nature of low‐gradient, human disturbed systems suggests relatively minor inputs from leaf litter and detritus since they are small relative to algae and fine particulate nitrogen (FPN) [ Griffiths et al ., ; Ford et al ., ]. TRANSFER simulates coarse particulate N to be composed soley of algal particulate N ( APN ).…”

“…For this reason, most of the DIN transported in the main stem of the watershed will be a mix of upland fertilizers and soils. During 2008, the watershed had extensive drought conditions during summer and early fall, thus minimizing the ability of the upland sources to deliver NO 3 to the stream [ Ford and Fox , ; Ford et al ., ]. For this reason, we suspect connectivity of DIN to upland soils and fertilizers is diminished and mineralization from upland tributaries becomes prominent.…”

Isotope‐based Fluvial Organic Carbon (ISOFLOC) Model: Model formulation, sensitivity, and evaluation

“…Two primary ISOFLOC response variables are C FPOC-T(av) and d 13 C FPOC-T(av) because: (i) it is important to understand how the new isotope submodels add additional information to the carbon mass-balance model; (ii) C FPOC-T(av) and d 13 C FPOC-T(av) have been previously shown to have seasonal and annual oscillations at the watershed scale indicative of source variability and in-stream processes [Ford and Fox, 2014;Ford et al, 2015]; and (iii) the impact of highly nonlinear feedbacks between physical and biological processes, and subsequently parameters, on C FPOC-T(av) and d 13 C FPOC-T(av) are not intuitive and the sensitivity analysis helps to better understand these linkages. ISOFLOC sensitivity analysis uses quantitative apportionment based on a variance-based sensitivity analysis.…”

Quantifying Nitrate Dynamics of a Confluence Floodplain Wetland in a Disturbed Appalachian Watershed: High-Resolution Sensing and Modeling

“…As previously highlighted, the maximum removal solution in our uncertainty analysis reflected measured nitrate concentrations well during periods of inundation, and the minimum removal solution reflected measured nitrate concentration dynamics well during periods when flow was restricted to the main stream channel. The higher removal rates in the floodplain are likely reflective of several interacting processes, including wetting-drying dynamics in the floodplain that enhance biochemical reactivity (BryantMason et al, 2013), perirheic mixing of tributary and riverine waters with ponded waters with steep redox gradients (Mertes, 1997;Jones et al, 2014Jones et al, , 2015, and dynamic organic matter quantity and quality, which is well recognized to influence rates of microbial reactivity (Ford and Fox, 2015b).…”