Effects of land use, climate, and imperviousness on urban stormwater quality: A meta-analysis.

Many natural and anthropogenic factors cause degradation of urban stormwater quality, resulting in negative consequences to receiving waters. In order to improve water quality models at a variety of scales, accurate estimates of pollutant (nutrients, total suspended solids, and heavy metal) concentrations are needed using potential explanatory variables. To this end, a meta-analysis was performed on aggregated stormwater quality data from the published literature from 360 urban catchments worldwide to understand how urban land use and land cover (LULC), climate (i.e., KÓ§ppen-Geiger zone), and imperviousness (1) affect runoff quality, and (2) whether they are able to predict stormwater pollutant concentrations. Runoff pollutant concentrations were more influenced by LULC and climate than imperviousness. Differences in LULC significantly affected the generation of metals and some nitrogen species. Road, city center, and commercial LULCs generally produced the most elevated pollutant concentrations. Changes in climate zones resulted in significant differences in concentrations of nutrients and metals. Continental and arid climate zones produced runoff with the highest pollutant concentrations. Rainfall patterns seemed to have a more important role in affecting runoff quality than seasonal temperature. Differences in imperviousness only significantly affected chromium and nickel concentrations, although increased imperviousness led to slightly (not significantly) elevated concentrations of nutrients, suspended solids, and other heavy metals. Multiple linear regression models were created to predict the quality of urban runoff. Predictive equations were significant (p < 0.05) for 67% of the pollutants analyzed (ammonia, total Kjeldahl nitrogen, total nitrogen, total phosphorus, cadmium, nickel, lead, and zinc) suggesting that LULC, climate, and imperviousness are useful predictors of stormwater quality when local field monitoring or modeling is not practical. This study provides useful relationships to better inform urban stormwater quality models and regulations such as total maximum daily loads.

Uncertainty in critical source area predictions from watershed-scale hydrologic models.

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or 'targeted' for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%-46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models.

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.

Natural Attenuation of Nonionic Surfactants Used in Hydraulic Fracturing Fluids: Degradation Rates, Pathways, and Mechanisms.

Hydraulic fracturing fluids are injected into shales to extend fracture networks that enhance oil and natural gas production from unconventional reservoirs. Here we evaluated the biodegradability of three widely used nonionic polyglycol ether surfactants (alkyl ethoxylates (AEOs), nonylphenol ethoxylates (NPEOs), and polypropylene glycols (PPGs)) that function as weatherizers, emulsifiers, wetting agents, and corrosion inhibitors in injected fluids. Under anaerobic conditions, we observed complete removal of AEOs and NPEOs from solution within 3 weeks regardless of whether surfactants were part of a chemical mixture or amended as individual additives. Microbial enzymatic chain shortening was responsible for a shift in ethoxymer molecular weight distributions and the accumulation of the metabolite acetate. PPGs bioattenuated the slowest, producing sizable concentrations of acetone, an isomer of propionaldehyde. Surfactant chain shortening was coupled to an increased abundance of the diol dehydratase gene cluster (pduCDE) in Firmicutes metagenomes predicted from the 16S rRNA gene. The pduCDE enzymes are responsible for cleaving ethoxylate chain units into aldehydes before their fermentation into alcohols and carboxylic acids. These data provide new mechanistic insight into the environmental fate of hydraulic fracturing surfactants after accidental release through chain shortening and biotransformation, emphasizing the importance of compound structure disclosure for predicting biodegradation products.

Multiple hypotheses explain variation in extra-pair paternity at different levels in a single bird family.

Extra-pair paternity (EPP), where offspring are sired by a male other than the social male, varies enormously both within and among species. Trying to explain this variation has proved difficult because the majority of the interspecific variation is phylogenetically based. Ideally, variation in EPP should be investigated in closely related species, but clades with sufficient variation are rare. We present a comprehensive multifactorial test to explain variation in EPP among individuals in 20 populations of nine species over 89 years from a single bird family (Maluridae). Females had higher EPP in the presence of more helpers, more neighbours or if paired incestuously. Furthermore, higher EPP occurred in years with many incestuous pairs, populations with many helpers and species with high male density or in which males provide less care. Altogether, these variables accounted for 48% of the total and 89% of the interspecific and interpopulation variation in EPP. These findings indicate why consistent patterns in EPP have been so challenging to detect and suggest that a single predictor is unlikely to account for the enormous variation in EPP across levels of analysis. Nevertheless, it also shows that existing hypotheses can explain the variation in EPP well and that the density of males in particular is a good predictor to explain variation in EPP among species when a large part of the confounding effect of phylogeny is excluded.

Aerobic biodegradation of organic compounds in hydraulic fracturing fluids.

Little is known of the attenuation of chemical mixtures created for hydraulic fracturing within the natural environment. A synthetic hydraulic fracturing fluid was developed from disclosed industry formulas and produced for laboratory experiments using commercial additives in use by Marcellus shale field crews. The experiments employed an internationally accepted standard method (OECD 301A) to evaluate aerobic biodegradation potential of the fluid mixture by monitoring the removal of dissolved organic carbon (DOC) from an aqueous solution by activated sludge and lake water microbial consortia for two substrate concentrations and four salinities. Microbial degradation removed from 57 % to more than 90 % of added DOC within 6.5 days, with higher removal efficiency at more dilute concentrations and little difference in overall removal extent between sludge and lake microbe treatments. The alcohols isopropanol and octanol were degraded to levels below detection limits while the solvent acetone accumulated in biological treatments through time. Salinity concentrations of 40 g/L or more completely inhibited degradation during the first 6.5 days of incubation with the synthetic hydraulic fracturing fluid even though communities were pre-acclimated to salt. Initially diverse microbial communities became dominated by 16S rRNA sequences affiliated with Pseudomonas and other Pseudomonadaceae after incubation with the synthetic fracturing fluid, taxa which may be involved in acetone production. These data expand our understanding of constraints on the biodegradation potential of organic compounds in hydraulic fracturing fluids under aerobic conditions in the event that they are accidentally released to surface waters and shallow soils.

Pyrosequencing reveals unique microbial signatures associated with healthy and failing dental implants.

AIM: Although it is established that peri-implantitis is a bacterially induced disease, little is known about the bacterial profile of peri-implant communities in health and disease. The purpose of the present investigation was to examine the microbial signatures of the peri-implant microbiome in health and disease. MATERIALS AND METHODS: Subgingival and submucosal plaque samples were collected from forty subjects with periodontitis, peri-implantitis, periodontal and peri-implant health and analysed using 16S pyrosequencing. RESULTS: Peri-implant biofilms demonstrated significantly lower diversity than subgingival biofilms in both health and disease, however, several species, including previously unsuspected and unknown organisms, were unique to this niche. The predominant species in peri-implant communities belonged to the genera Butyrivibrio, Campylobacter, Eubacterium, Prevotella, Selenomonas, Streptococcus, Actinomyces, Leptotrichia, Propionibacterium, Peptococcus, Lactococcus and Treponema. Peri-implant disease was associated with lower levels of Prevotella and Leptotrichia and higher levels of Actinomyces, Peptococcus, Campylobacter, non-mutans Streptococcus, Butyrivibrio and Streptococcus mutans than healthy implants. These communities also demonstrated lower levels of Prevotella, non-mutans Streptococcus, Lactobacillus, Selenomonas, Leptotrichia, Actinomyces and higher levels of Peptococcus, Mycoplasma, Eubacterium, Campylobacter, Butyrivibrio, S. mutans and Treponema when compared to periodontitis-associated biofilms. CONCLUSION: The peri-implant microbiome differs significantly from the periodontal community in both health and disease. Peri-implantitis is a microbially heterogeneous infection with predominantly gram-negative species, and is less complex than periodontitis.

Target region selection is a critical determinant of community fingerprints generated by 16S pyrosequencing.

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1-V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacter and Enterococcus predominated in the community generated by V4-V6 primers, and the most numerous genera in the V7-V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4-V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7-V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1-V3 and V7-V9 primers provided results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities.