Ecosystem Responses to Extreme Natural Events: Impacts of Three Sequential Hurricanes in Fall 1999 on Sediment Quality and Condition of Benthic Fauna in the Neuse River Estuary, North Carolina

A study was conducted in November 1999 to assess sediment quality and condition of benthic fauna in the Neuse River Estuary (NRE), North Carolina, USA, following the passage of three Atlantic hurricanes during the two months prior. Samples for analysis of macroinfauna (>0.5 mm sieve size), chemical contamination of sediments, and other abiotic environmental variables (salinity, dissolved oxygen, pH, depth, sediment granulometry) were collected at 20 sites from the mouth of the Neuse River at Pamlico Sound to approximately 90 km upstream. Results were compared to those obtained from the same area in July 1998 using similar protocols. Depressed salinity, caused by extreme rainfall and associated high freshwater flow, persisted throughout much of the estuary, which had experienced periods of water-column stratification and hypoxia of underlying waters. Fifteen of the 20 sites, representing 299 km² (76% of the survey area), also showed signs of benthic stress based on a multi-metric benthic index of biotic integrity (B-IBI). Benthic impacts included reductions in the abundance, diversity, and numbers of species and shifts in taxonomic composition, with a notable increase in dominance of the opportunistic polychaete Mediomastus ambiseta as other former dominant species declined. There was no significant increase in the extent of chemical contamination compared to pre-hurricane conditions. Storm-related reductions in dissoved oxygen and salinity were the more likely causes of the observed benthic impacts, though it was not possible, based on these results, to separate storm effects from seasonal changes in the benthos and annual episodes of summer anoxia and hypoxia.     

Upland disturbance affects headwater stream nutrients and suspended sediments during baseflow and stormflow

Because catchment characteristics determine sediment and nutrient inputs to streams, upland disturbance can affect stream chemistry. Catchments at the Fort Benning Military Installation (near Columbus, Georgia) experience a range of upland disturbance intensities due to spatial variability in the intensity of military training. We used this disturbance gradient to investigate the effects of upland soil and vegetation disturbance on stream chemistry. During baseflow, mean total suspended sediment (TSS) concentration and mean inorganic suspended sediment (ISS) concentration increased with catchment disturbance intensity (TSS: R2= 0.7, p = 0.005, range = 4.0-10.1 mg L(-1); ISS: R2= 0.71, p = 0.004, range = 2.04-7.3 mg L(-1)); dissolved organic carbon (DOC) concentration (R2= 0.79, p = 0.001, range = 1.5-4.1 mg L(-1)) and soluble reactive phosphorus (SRP) concentration (R2= 0.75, p = 0.008, range = 1.9-6.2 microg L(-1)) decreased with increasing disturbance intensity; and ammonia (NH4+), nitrate (NO3-), and dissolved inorganic nitrogen (DIN) concentrations were unrelated to disturbance intensity. The increase in TSS and ISS during storms was positively correlated with disturbance (R2= 0.78 and 0.78, p = 0.01 and 0.01, respectively); mean maximum change in SRP during storms increased with disturbance (r = 0.7, p = 0.04); and mean maximum change in NO3- during storms was marginally correlated with disturbance (r = 0.58, p = 0.06). Soil characteristics were significant predictors of baseflow DOC, SRP, and Ca2+, but were not correlated with suspended sediment fractions, any nitrogen species, or pH. Despite the largely intact riparian zones of these headwater streams, upland soil and vegetation disturbances had clear effects on stream chemistry during baseflow and stormflow conditions.     

Increased wind erosion from forest wildfire: implications for contaminant-related risks

Assessments of contaminant-related human and ecological risk require estimation of transport rates, but few data exist on wind-driven transport rates in nonagricultural systems, particularly in response to ecosystem disturbances such as forest wildfire and also relative to water-driven transport. The Cerro Grande wildfire in May of 2000 burned across ponderosa pine (Pinus ponderosa Douglas ex P.&C. Lawson var. scopulorum Englem.) forest within Los Alamos National Laboratory in northern New Mexico, where contaminant transport and associated post-fire inhalation risks are of concern. In response, the objectives of this study were to measure and compare wind-driven horizontal and vertical dust fluxes, metrics of transport related to wind erosion, for 3 yr for sites differentially affected by the Cerro Grande wildfire: unburned, moderately burned (fire mostly confined to ground vegetation), and severely burned (crown fire). Wind-driven dust flux was significantly greater in both types of burned areas relative to unburned areas, by more than one order of magnitude initially and by two to three times 1 yr after the fire. Unexpectedly, the elevated dust fluxes did not decrease during the second and third years in burned areas, apparently because ongoing drought delayed post-fire recovery. Our estimates enable assessment of amplification in contaminant-related risks following a major type of disturbance-wildfire, which is expected to increase in intensity and frequency due to climate change. More generally, our results highlight the importance of considering wind- as well as water-driven transport and erosion, particularly following disturbance, for ecosystem biogeochemistry in general and human and ecological risk assessment in particular.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Influence of sub-lethal crude oil concentration on growth,water relations and photosynthetic capacity of maize (Zea mays L.) plants

Environmental Science and Pollution Research - Maize tolerance potential to oil pollution was assessed by growing Zea mays in soil contaminated with varying levels of crude oil (0, 2.5 and...     

US exposure to multiple landscape stressors and climate change

Regional Environmental Change - We examined landscape exposure to wildfire potential, insects and disease risk, and urban and exurban development for the conterminous US (CONUS). Our analysis...     

Acid generation upon thermal concentration of natural water: The critical water content and the effects of ionic composition

Thermal evaporation of a variety of simulated pore waters from the region of Yucca Mountain, Nevada, produced acidic liquids and gases during the final stages of evaporation. Several simulated pore waters were prepared and then thermally distilled in order to collect and analyze fractions of the evolved vapor. In some cases, distillates collected towards the end of the distillation were highly acidic; in other cases the pH of the distillate remained comparatively unchanged during the course of the distillation. The results suggest that the pH values of the later fractions are determined by the initial composition of the water. Acid production stems from the hydrolysis of magnesium ions, especially at near dryness. Near the end of the distillation, magnesium nitrate and magnesium chloride begin to lose water of hydration, greatly accelerating their thermal decomposition to form acid. Acid formation is promoted further when precipitated calcium carbonate is removed. Specifically, calcium chloride-rich pore waters containing moderate (10–20 ppm) levels of magnesium and nitrate and low levels of bicarbonate produced mixtures of nitric and hydrochloric acid, resulting in a precipitous drop in pH to values of 1 or lower after about 95% of the original volume was distilled. Waters with either low or moderate magnesium content coupled with high levels of bicarbonate produced slightly basic fractions (pH 7–9). If calcium was present in excess of bicarbonate, waters containing moderate levels of magnesium produced acid even in the presence of bicarbonate, due to the precipitation of calcium carbonate. Other salts such as halite and anhydrite promote the segregation of acidic vapors from residual basic solids. The concomitant release of wet acid gas has implications for the integrity of the alloys under consideration for containers at the Yucca Mountain nuclear waste repository. Condensed acid gases at very low pH, especially mixtures of nitric and hydrochloric acid, are capable of corroding even alloys, such as nickel-based Alloy 22, which are considered to be corrosion-resistant under milder conditions.     

Measurement of gas-phase total peroxides at the summit of Mount Tai in China

Measurement of ambient gas-phase total peroxides was performed at the summit of Mount Tai (Mt. Tai, 1534 m above sea level) in central-eastern China during March 22–April 24 and June 16–July 20, 2007. The hourly averaged concentration of peroxides was 0.17 ppbv (± 0.16 ppbv, maximum: 1.28 ppbv) and 0.55 ppbv (± 0.67 ppbv, maximum: 3.55 ppbv) in the spring and summer campaigns, respectively. The average concentration of peroxides at Mt. Tai, which is in a heavily polluted region, was much lower than hydrogen peroxide measurements made at some rural mountain sites, suggesting that significant removal processes took place in this region. An examination of diurnal variation and a correlation analysis suggest that these removal processes could include chemical suppression of peroxide production due to the scavenging of peroxy and hydroxy radicals by high NO_x, wet removal by clouds/fogs rich in dissolved sulfur dioxide which reacts quickly with peroxides, and photolysis. These sinks competed with photochemical sources of peroxides, resulting in different mean concentrations and diurnal pattern of peroxides in the spring and summer. A principal component analysis was conducted to quantify the major processes that influenced the variation of peroxide concentrations. This analysis shows that in the spring photochemical production was an important source of peroxides, and the major sink was scavenging during upslope transport of polluted and humid air from the lower part of the planetary boundary layer (PBL) and wet removal by synoptic scale clouds. During the summer, highly polluted PBL air (with high NO_x) was often associated with very low peroxides due to the chemical suppression of HO₂ by high NO_x and wet-removal by clouds/fogs in this sulfur-rich atmosphere, especially during the daytime. Higher concentrations of peroxides, which often appeared at mid-nighttime, were mainly associated with subsidence of air masses containing relatively lower concentrations of NO_y.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.     

Approximating the distribution of recreational visits from on-site survey data

While convenient and often used, on-site surveys are biased by the fact that users who visit the site more often are proportionately more likely to be sampled. This so-called avidity or size biased sampling results in over-estimating the visitation patterns of the average user. This analysis develops a rule of thumb method that may easily be applied by recreation site managers to visitation data collected on-site in order to infer behavior of the average user of the site. The key assumption that drives the derivation is that the visitation data of users is logarithmically distributed. To evaluate the methodology, we analyze several data sets of recreational users assuming that they reflect the populations of users and from these construct hypothetical on-site samples.