Assessment of sediment contamination in Casco Bay, Maine, USA

The current status of contaminant concentrations in Casco Bay, decadal trends of these contaminants and changes in their geographical distribution are assessed using sediment samples collected approximately 10 years apart. In general, regulated contaminants appeared to be decreasing in concentration. Total PAH and dioxins/furans concentrations did not significantly change over this period. Total organochlorine pesticides, 4,4-DDE, 4,4-DDD, total DDT, PCB, tributyltin and total butyltin decreased in concentration. Trace element concentrations in sediments decreased at the majority of the sampling sites for chromium, nickel, and selenium while arsenic, cadmium, copper, lead, mercury, silver, and zinc remained relatively constant. None of the contaminants measured has increased by more than a factor of 2. Selected sites located in the Inner Bay, where concentrations are higher and new inputs were more likely, showed increased concentrations of contaminants. Most contaminants were not found at concentrations expected to adversely affect sediment biota based on ERL/ERM guidelines.     

Soil criteria to protect terrestrial wildlife and open-range livestock from metal toxicity at mining sites

Thousands of hard rock mines exist in the western USA and in other parts of the world as a result of historic and current gold, silver, lead, and mercury mining. Many of these sites in the USA are on public lands. Typical mine waste associated with these sites are tailings and waste rock dumps that may be used by wildlife and open-range livestock. This report provides wildlife screening criteria levels for metals in soil and mine waste to evaluate risk and to determine the need for site-specific risk assessment, remediation, or a change in management practices. The screening levels are calculated from toxicity reference values based on maximum tolerable levels of metals in feed, on soil and plant ingestion rates, and on soil to plant uptake factors for a variety of receptors. The metals chosen for this report are common toxic metals found at mining sites: arsenic, cadmium, copper, lead, mercury, and zinc. The resulting soil screening values are well above those developed by the US Environmental Protection Agency. The difference in values was mainly a result of using toxicity reference values that were more specific to the receptors addressed rather than the most sensitive receptor.     

Drinking water treatment is not associated with an observed increase in neural tube defects in mice

Disinfection by-products (DBPs) arise when natural organic matter in source water reacts with disinfectants used in the water treatment process. Studies have suggested an association between DBPs and birth defects. Neural tube defects (NTDs) in embryos of untreated control mice were first observed in-house in May 2006 and have continued to date. The source of the NTD-inducing agent was previously determined to be a component of drinking water. Tap water samples from a variety of sources were analyzed for trihalomethanes (THMs) to determine if they were causing the malformations. NTDs were observed in CD-1 mice provided with treated and untreated surface water. Occurrence of NTDs varied by water source and treatment regimens. THMs were detected in tap water derived from surface water but not detected in tap water derived from a groundwater source. THMs were absent in untreated river water and laboratory purified waters, yet the percentage of NTDs in untreated river water were similar to the treated water counterpart. These findings indicate that THMs were not the primary cause of NTDs in the mice since the occurrence of NTDs was unrelated to drinking water disinfection.     

The New Bedford Harbor Superfund site long-term monitoring program (1993–2009)

New Bedford Harbor (NBH), located in southeastern Massachusetts, was designated as a marine Superfund site in 1983 due to sediment contamination by polychlorinated biphenyls (PCBs). Based on risks to human health and the environment, the first two phases of the site cleanup involved dredging PCB-contaminated sediments from the harbor. Therefore, a long-term monitoring program (LTM) was developed to measure spatial and temporal chemical and biological changes in sediment, water, and biota to assess the effects and effectiveness of the remedial activities. A systematic, probabilistic sampling design was used to select sediment sampling stations. This unbiased design allowed the three segments of the harbor to be compared spatially and temporally to quantify changes resulting from dredging the contaminated sediments. Sediment was collected at each station, and chemical (e.g., PCBs and metals), physical (e.g., grain size), and biological (e.g., benthic community) measurements were conducted on all samples. This paper describes the overall NBH-LTM approach and the results from the five rounds of sample collections. There is a decreasing spatial gradient in sediment PCB concentrations from the northern boundary (upper harbor) to the southern boundary (outer harbor) of the site. Along this same transect, there is an increase in biological condition (e.g., benthic community diversity). Temporally, the contaminant and biological gradients have been maintained since the 1993 baseline collection; however, since the onset of full-scale remediation, PCB concentrations have decreased throughout the site, and one of the benthic community indices has shown significant improvement in the lower and outer harbor areas.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Measuring the effectiveness of landscape approaches to conservation and development

Landscape approaches attempt to achieve balance amongst multiple goals over long time periods and to adapt to changing conditions. We review project reports and the literature on integrated landscape approaches, and found a lack of documented studies of their long-term effectiveness. The combination of multiple and potentially changing goals presents problems for the conventional measures of impact. We propose more critical use of theories of change and measures of process and progress to complement the conventional impact assessments. Theories of change make the links between project deliverables, outputs, outcomes, and impacts explicit, and allow a full exploration of the landscape context. Landscape approaches are long-term engagements, but short-term process metrics are needed to confirm that progress is being made in negotiation of goals, meaningful stakeholder engagement, existence of connections to policy processes, and effectiveness of governance. Long-term impact metrics are needed to assess progress on achieving landscapes that deliver multiple societal benefits, including conservation, production, and livelihood benefits. Generic criteria for process are proposed, but impact metrics will be highly situation specific and must be derived from an effective process and a credible theory of change.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Antioxidants in Capsicum chinense: Variation among countries of origin

The main objective of this investigation was to evaluate fruits of C. chinense accessions for their concentration of β -carotene, ascorbic acid, and phenols for use as parents in breeding for these phytochemicals. Mature fruits of 63 accessions of C. chinense originally acquired from Belize, Brazil, Colombia, Ecuador, Mexico, Peru, Puerto Rico, and the United States were analyzed for their chemical composition. Fruits of C. chinense accessions PI-152452 (Brazil) and PI-360726 (Ecuador) contained the greatest concentrations of ascorbic acid (1.2 and 1.1 mg g^?1 fresh fruit, respectively), while PI-438648 (Mexico) contained the greatest concentration of total phenols content (349 μ g g^?1 fresh fruit) among the other 63 accessions tested. Accession PI-355817 from Ecuador contained the greatest concentrations of β -carotene (8 mg g^?1fresh fruit). These accessions were identified as potential candidates for mass production of antioxidants with health-promoting properties.     

Screening Capsicum chinense fruits for heavy metals bioaccumulation

Elevated concentrations of heavy metals in edible plants could expose consumers to excessive levels of potentially hazardous chemicals. Sixty-three accessions (genotypes) of Capsicum chinense Jacq, collected from 8 countries of origin were grown in a silty-loam soil under field conditions. At maturity, fruits were collected and analyzed for seven heavy metals (Cd, Cr, Ni, Pb, Zn, Cu, and Mo) concentrations. The main objectives of this investigation were: 1) to determine the concentrations of seven heavy metals in the soil and monitor their accumulation in mature fruits, 2) to categorize the pepper accessions as low or high heavy metal accumulators, and 3) to determine if heavy metal content of the pepper fruit was lower than the permitted limits. Concentrations and relative proportions of heavy metals in pepper fruits of C. chinense varied among accessions. Fruits of Plant Introduction (PI) 355820 accumulated significant concentrations of Cd (0.47 μ g g^?1dry fruit). PI-260522 accumulated the highest concentration of Pb (2.12 μ g g^?1 dry fruit) among the 63 accessions tested. This accession (PI-260522) contained about twice the Pb limit on a fresh weight basis. Among the 63 accessions analyzed, PI-238051 contained the highest levels of Ni (17.2 μ g g^?1). We concluded that high accumulator genotypes may be useful for phytoremediation, while, low accumulator accessions might be appropriate selections for growing on Cd-, Pb-, or Ni-contaminated soils to prevent potential human exposure to heavy metals and health hazards through the food chain.