The impact of combined sewer outflows on urban water quality: Spatio-temporal patterns of fecal coliform in indianapolis.

Many urban waterways with older stormwater drainage systems receive a significant amount of untreated or poorly treated waste from Combined Sewer Outflow (CSO) systems during precipitation events. The input of effluent waste from CSO to urban water streams during storm events often leads to elevated fecal coliform, specifically Escherichia Coli (E. Coli) in these waterways. The aim of the study is to examine fecal coliform concentration, water chemistry, and water quality parameters to better understand spatio-temporal patterns of fecal coliform associated with CSO events in three waterways from Indianapolis, Indiana (USA). The waterways are Pleasant Run Creek (PRW), Fall Creek (FC) and White River (WR). The sampling occurred biweekly over one year for PRW, nine months for FC, and an intense (∼every three days) sub-analysis of the presumed peak period of fecal coliform growth (July) for WR. All PRW and FC sampling sites significantly exceeded the EPA contact standard limit of 200 CFU/100 mL for fecal coliform concentrations during the sampling period. We found no relationship between fecal coliform levels and the number or density of CSO outfalls above a given site. The most significant predictors of increased fecal coliform concentrations were precipitation on the sampling day and cumulative degree days. The most significant predictors of decreased fecal coliform were maximum precipitation during the ten-day window prior to sampling and median discharge during a three-day window prior to sampling. These findings suggest a push-pull balance within the system where CSO activation and seasonal gradients replenish and promote fecal coliform growth. At the same time, large hydrologic events act to flush and dilute fecal coliform concentrations. The results from this study help us to better understand how different drivers influence fecal coliform growth and how this information can be potentially used to predict and remediate the conditions of urban water streams.

Predictive modeling of indoor dust lead concentrations: Sources, risks, and benefits of intervention.

Lead (Pb) contamination continues to contribute to world-wide morbidity in all countries, particularly low- and middle-income countries. Despite its continued widespread adverse effects on global populations, particularly children, accurate prediction of elevated household dust Pb and the potential implications of simple, low-cost household interventions at national and global scales have been lacking. A global dataset (∼40 countries, n = 1951) of community sourced household dust samples were used to predict whether indoor dust was elevated in Pb, expanding on recent work in the United States (U.S.). Binned housing age category alone was a significant (p < 0.01) predictor of elevated dust Pb, but only generated effective predictive accuracy for England and Australia (sensitivity of ∼80%), similar to previous results in the U.S. This likely reflects comparable Pb pollution legacies between these three countries, particularly with residential Pb paint. The heterogeneity associated with Pb pollution at a global scale complicates the predictive accuracy of our model, which is lower for countries outside England, the U.S., and Australia. This is likely due to differing environmental Pb regulations, sources, and the paucity of dust samples available outside of these three countries. In England, the U.S., and Australia, simple, low-cost household intervention strategies such as vacuuming and wet mopping could conservatively save 70 billion USD within a four-year period based on our model. Globally, up to 1.68 trillion USD could be saved with improved predictive modeling and primary intervention to reduce harmful exposure to Pb dust sources.

Using Community Science to Better Understand Lead Exposure Risks.

Lead (Pb) is a neurotoxicant that particularly harms young children. Urban environments are often plagued with elevated Pb in soils and dusts, posing a health exposure risk from inhalation and ingestion of these contaminated media. Thus, a better understanding of where to prioritize risk screening and intervention is paramount from a public health perspective. We have synthesized a large national data set of Pb concentrations in household dusts from across the United States (U.S.), part of a community science initiative called "DustSafe." Using these results, we have developed a straightforward logistic regression model that correctly predicts whether Pb is elevated (>80 ppm) or low (<80 ppm) in household dusts 75% of the time. Additionally, our model estimated 18% false negatives for elevated Pb, displaying that there was a low probability of elevated Pb in homes being misclassified. Our model uses only variables of approximate housing age and whether there is peeling paint in the interior of the home, illustrating how a simple and successful Pb predictive model can be generated if researchers ask the right screening questions. Scanning electron microscopy supports a common presence of Pb paint in several dust samples with elevated bulk Pb concentrations, which explains the predictive power of housing age and peeling paint in the model. This model was also implemented into an interactive mobile app that aims to increase community-wide participation with Pb household screening. The app will hopefully provide greater awareness of Pb risks and a highly efficient way to begin mitigation.

Sediment Disturbance Negatively Impacts Methanogen Abundance but Has Variable Effects on Total Methane Emissions.

Methane emissions from aquatic ecosystems are increasingly recognized as substantial, yet variable, contributions to global greenhouse gas emissions. This is in part due to the challenge of modeling biologic parameters that affect methane emissions from a wide range of sediments. For example, the impacts of fish bioturbation on methane emissions in the literature have been shown to result in a gradient of reduced to enhanced emissions from sediments. However, it is likely that variation in experimental fish density, and consequently the frequency of bioturbation by fish, impacts this outcome. To explore how the frequency of disturbance impacts the levels of methane emissions in our previous work we quantified greenhouse gas emissions in sediment microcosms treated with various frequencies of mechanical disturbance, analogous to different levels of activity in benthic feeding fish. Greenhouse gas emissions were largely driven by methane ebullition and were highest for the intermediate disturbance frequency (disturbance every 7 days). The lowest emissions were for the highest frequency treatment (3 days). This work investigated the corresponding impacts of disturbance treatments on the microbial communities associated with producing methane. In terms of total microbial community structure, no statistical difference was observed in the total community structure of any disturbance treatment (0, 3, 7, and 14 days) or sediment depth (1 and 3 cm) measured. Looking specifically at methanogenic Archaea however, a shift toward greater relative abundance of a putatively oxygen-tolerant methanogenic phylotype (ca. Methanothrix paradoxum) was observed for the highest frequency treatments and at depths impacted by disturbance (1 cm). Notably, quantitative analysis of ca. Methanothrix paradoxum demonstrated no change in abundance, suggesting disturbance negatively and preferentially impacted other methanogen populations, likely through oxygen exposure. This was further supported by a linear decrease in quantitative abundance of methanogens (assessed by qPCR of the mcrA gene), with increased disturbance frequency in bioturbated sediments (1 cm) as opposed to those below the zone of bioturbation (3 cm). However, total methane emissions were not simply a function of methanogen populations and were likely impacted by the residence time of methane in the lower frequency disturbance treatments. Low frequency mechanical disruption results in lower methane ebullition compared to higher frequency treatments, which in turn resulted in reduced overall methane release, likely through enhanced methanotrophic activities, though this could not be identified in this work. Overall, this work contributes to understanding how animal behavior may impact variation in greenhouse gas emissions and provides insight into how frequency of disturbance may impact emissions.

International Analysis of Sources and Human Health Risk Associated with Trace Metal Contaminants in Residential Indoor Dust.

People spend increasing amounts of time at home, yet the indoor home environment remains understudied in terms of potential exposure to toxic trace metals. We evaluated trace metal (and metalloid) concentrations (As, Cu, Cr, Mn, Ni, Pb, and Zn) and health risks in indoor dust from homes from 35 countries, along with a suite of potentially contributory residential characteristics. The objective was to determine trace metal source inputs and home environment conditions associated with increasing exposure risk across a range of international communities. For all countries, enrichments compared to global crustal values were Zn > Pb > Cu > As > Cr > Ni; with the greatest health risk from Cr, followed by As > Pb > Mn > Cu > Ni > Zn. Three main indoor dust sources were identified, with a Pb-Zn-As factor related to legacy Pb sources, a Zn-Cu factor reflecting building materials, and a Mn factor indicative of natural soil sources. Increasing home age was associated with greater Pb and As concentrations (5.0 and 0.48 mg/kg per year of home age, respectively), as were peeling paint and garden access. Therefore, these factors form important considerations for the development of evidence-based management strategies to reduce potential risks posed by indoor house dust. Recent findings indicate neurocognitive effects from low concentrations of metal exposures; hence, an understanding of the home exposome is vital.

Mapping the Urban Lead Exposome: A Detailed Analysis of Soil Metal Concentrations at the Household Scale Using Citizen Science.

An ambitious citizen science effort in the city of Indianapolis (IN, USA) led to the collection and analysis of a large number of samples at the property scale, facilitating the analysis of differences in soil metal concentrations as a function of property location (i.e., dripline, yard, and street) and location within the city. This effort indicated that dripline soils had substantially higher values of lead and zinc than other soil locations on a given property, and this pattern was heightened in properties nearer the urban core. Soil lead values typically exceeded the levels deemed safe for children's play areas in the United States (<400 ppm), and almost always exceeded safe gardening guidelines (<200 ppm). As a whole, this study identified locations within properties and cities that exhibited the highest exposure risk to children, and also exhibited the power of citizen science to produce data at a spatial scale (i.e., within a property boundary), which is usually impossible to feasibly collect in a typical research study.

Obviation of wheat resistance to the Hessian fly through systemic induced susceptibility.

Unlike most documented plant-insect interactions, Hessian fly-resistance [Mayetiola destructor (Say)] in wheat (Triticum aestivum L.) is initiated by a gene-for-gene recognition event in which plants carrying a specific R gene recognize salivary effectors encoded by a corresponding larval avirulence gene. However, dual infestation resulting from oviposition by virulent insects from 5 d before to 3 d after oviposition by avirulent insects on the same host plant, lead to systemic induced susceptibility, obviation of resistance, and ultimately the survival of both virulent and genetically avirulent progeny to adulthood. Simultaneous oviposition allowed greater survival of avirulent progeny than ovipositions separated by larger intervals. Because of the induction of plant resistance, hatch of avirulent larvae before virulent was more detrimental to rate of development than hatch of virulent before avirulent larvae. Obviation of resistance was not localized to the leaf being attacked by the virulent larvae, but also functioned across spatial distance into younger leaves. This research suggests that virulent Hessian fly larvae directly suppress the defense response of wheat, thus providing a refuge for avirulent genotypes, preserving diversity in field populations and increasing durability of deployed resistance genes.

Induced epidermal permeability modulates resistance and susceptibility of wheat seedlings to herbivory by Hessian fly larvae.

Salivary secretions of neonate Hessian fly larvae initiate a two-way exchange of molecules with their wheat host. Changes in properties of the leaf surface allow larval effectors to enter the plant where they trigger plant processes leading to resistance and delivery of defence molecules, or susceptibility and delivery of nutrients. To increase understanding of the host plant's response, the timing and characteristics of the induced epidermal permeability were investigated. Resistant plant permeability was transient and limited in area, persisting just long enough to deliver defence molecules before gene expression and permeability reverted to pre-infestation levels. The abundance of transcripts for GDSL-motif lipase/hydrolase, thought to contribute to cuticle reorganization and increased permeability, followed the same temporal profile as permeability in resistant plants. In contrast, susceptible plants continued to increase in permeability over time until the entire crown of the plant became a nutrient sink. Permeability increased with higher infestation levels in susceptible but not in resistant plants. The ramifications of induced plant permeability on Hessian fly populations are discussed.

Geographic distribution of phylogenetically-distinct legume pod borer, Maruca vitrata (Lepidoptera: Pyraloidea: Crambidae).

Maruca vitrata Fabricius is a pantropical lepidopteran pest of legumes. Phylogenetic analysis of a mitochondrial cytochrome c oxidase-I gene (cox1) fragment indicates that three Maruca sp. mitochondrial lineages have unique geographic distributions [lineages 1 and 2: Australia, Taiwan, and West Africa (Niger, Nigeria, and Burkina Faso), and lineage 3: Puerto Rico]. The haplotype (T30, T114) is specific to lineages 1&2 and was assayed by NsiI and SacI polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) within population samples; it was not observed in the Puerto Rican samples, but was nearly fixed among samples from West Africa, Australia and Taiwan (85.5-100%). Re-sequencing and phylogenetic analyses of PCR-RFLP defined cox1 haplotypes indicate that nucleotide diversity is highest among samples from West Africa. Phylogenetic reconstruction based upon ribosomal DNA (rDNA) internal transcribed spacer-2 (ITS-2) sequences provided additional evidence for three Maruca sp. clades. These data suggest that multiple unique Maruca species or subspecies are present worldwide, which has implications for the management of this pest species-complex.

A simplified arthropod genomic-DNA extraction protocol for polymerase chain reaction (PCR)-based specimen identification through barcoding.

Genomic DNA extraction protocols generally require the use of expensive and hazardous reagents necessary for decontamination of phenolic compounds from the extracts. In addition, they are lengthy, hindering large-scale sample extractions necessary for high-throughput analyses. Here we describe a simple, time and cost-efficient method for genomic DNA extraction from insects. The extracted DNA was successfully used in a Polymerase Chain Reaction (PCR), making it suitable for automation for large-scale genetic analysis and barcoding studies. The protocol employs a single purification step to remove polysaccharides and other contaminating compounds using a non-hazardous reagent buffer. In addition, we conducted a bioinformatics database analysis as proof of concept for the efficiency of the DNA extraction protocol by using universal barcoding primers specific for cytochrome c oxidase I gene to identify different arthropod specimens through Barcode of Life Database (BOLD) database search. The usefulness of this protocol in various molecular biology and biodiversity studies is further discussed.