Temporal variability of the elemental composition in urban street dust

Urban Street dust is recognized as a source of urban air and runoff degradation. This paper takes a preliminary step toward a better understanding of temporal variability in street dust chemistry and of the controlling mechanisms. Street dust samples, collected over four seasons in the city of Hamilton, Canada, show a variability dependent on element and source-anthropogenic sources exhibiting the greatest temporal variability. In addition, elements attributed to common sources exhibit similar temporal patterns. The use of generic or even one-time samples may seriously misrepresent the elemental make-up of urban street dust. Based on the samples collected in this study, a number of questions/insights are posed to further the study of street dust temporal variability.     

Immunoassay monitoring of polychlorinated biphenyls (PCBs) in the Great Lakes

Although polychlorinated biphenyls (PCBs) are no longer manufactured, they are still entering the environment. In some compartments of the environment, PCB concentrations are a serious concern. This is especially true in compartments which accumulate PCBs, and in food items consumed by humans and wildlife. Also, there are situations in which management decisions require rapid, sensitive, accurate measurements, which can be made in real time under field conditions. Methods to use an enzyme-linked immunosorbent assay (ELISA) for PCBs were developed and applied to sediments and fish muscle homogenates collected from the Great Lakes. The extraction methods developed can be applied in the field with non-hazardous solvents, in the absence of sophisticated laboratory equipment. The method detection limit for PCBs in dimethyl sulfoxide (DMSO) extracts of sediment was 0.9 mg/kg. For PCBs in isopropanol extracts of fish tissue, the method detection limit was 0.6 mg/kg. The resolution of the ELISA was 0.83 mg/kg at 1.1 mg/kg and 1.6 mg/kg at 1.7 mg/kg, for sediment and fish tissue, respectively.     

Iowa Statewide Stream Nitrate Load Calculated Using In Situ Sensor Network

Various techniques exist to estimate stream nitrate loads when measured concentration data are sparse. The inherent uncertainty associated with load estimation, however, makes tracking progress toward water quality goals more difficult. We used high‐frequency, in situ nitrate sensors strategically deployed across the agricultural state of Iowa to evaluate 2016 stream concentrations at 60 sites and loads at 35 sites. The generated data, collected at an average of 225 days per site, show daily average nitrate‐N yields ranging from 12 to 198 g/ha, with annual yields as high as 53 kg/ha from the intensely drained Des Moines Lobe. Thirteen of the sites that capture water from 82.5% of Iowa's area show statewide nitrate‐N loading in 2016 totaled 477 million kg, or 41% of the load delivered to the Mississippi–Atchafalaya River Basin (MARB). Considering the substantial private and public investment being made to reduce nitrate loading in many states within the MARB, networks of continuous, in situ measurement devices as described here can inform efforts to track year‐to‐year changes in nitrate load related to weather and conservation implementation. Nitrate and other data from the sensor network described in this study are made publicly available in real time through the Iowa Water Quality Information System.     

Two sides of the same coin? Rare and pest plants native to the United States and Canada

Plant biodiversity is at risk, with as many as 10% of native species in the United States being threatened with extinction. Habitat loss has led a growing number of plant species to become rare or threatened, while the introduction or expansion of pest species has led some habitats to be dominated by relatively few, mostly nonindigenous, species. As humans continue to alter many landscapes and vegetation types, understanding how biological traits determine the location of species along a spectrum from vulnerability to pest status is critical to designing risk assessment protocols, setting conservation priorities, and developing monitoring programs. We used boosted regression trees to predict rarity (based on The Nature Conservancy global rankings) and pest status (defined as legal pest status) from data on traits for the native vascular flora of the United States and Canada including Hawaii, Puerto Rico, and the Virgin Islands (n approximately = 15,000). Categories were moderately to highly predictable (AUCpest = 0.87 on 25% holdout test set, AUCrarity = 0.80 on 25% holdout test set). Key predictors were chromosome number, ploidy, seed mass, and a suite of traits suggestive of specialist vs. generalist adaptations (e.g., facultative wetland habitat association and phenotypic variability in growth form and life history). Specifically, pests were associated with high chromosome numbers, polyploidy, and seed masses ranging from 0.1 to 100 mg, whereas rare species were associated with low chromosome numbers, low ploidy, and large (>1000 mg) seed masses. In addition, pest species were disproportionately likely to be facultatively associated with wetlands, and variable in growth form and life history, whereas rare species exhibited an opposite pattern. These results suggest that rare and pest species contrast along trait axes related to dispersal and performance in disturbed or novel habitats.     

PROCESS-ORIENTED ESTIMATION OF SUSPENDED SEDIMENT CONCENTRATION1

ABSTRACT: Least squares regression and ARIMA models were developed from suspended sediment data for the Ausable River, Southern Ontario, Canada. A poor correlation between discharge and suspended sediment concentration results from the dynamics of the physical system, including seasonality, antecedent conditions, and hysteresis. Regression model results were significantly improved by the division of the data set into seasons and the addition of simple. but physically meaningful variables. Misleading improvements obtained from the regression of sediment load and discharge are discussed. ARIMA models provided accurate forecasts of sediment concentration on a real-time basis, but the rigorous data requirements limit their use in modeling suspended sediment concentrations in Canadian rivers.     

Parent–offspring resource allocation in domestic pigs

Behavioural research on domestic pigs has included parent–offspring conflict, sibling competition, and the use of signals which influence resource allocation. In this paper, we review key sow–piglet behavioural studies and discuss their relevance to resource allocation theory. Sibling competition begins in the uterus and continues after birth, as piglets compete directly for access to the sow’s teats. This competition is made more severe by a unique dentition, which newborn piglets use to lacerate the faces of siblings during teat disputes. Competition often leads to the death of some littermates, especially those of low birth weight. Piglets also compete indirectly for milk, apparently by stimulating milk production at the teats that they habitually use at the expense of milk production by other teats. The complex nursing behavior of the sow appears designed to prevent the more vigorous piglets from monopolizing the milk. Sows give vocal signals which both attract piglets to suckle and synchronize their behavior during nursing episodes. Piglets give loud vocal signals when separated from the sow; calls which vary in intensity and appear to be honest signals of need. Udder massage by piglets may also serve as an honest signal of need. Parent–offspring conflict has been demonstrated experimentally in pigs. Specifically, when given the opportunity to control contact with their piglets, sows nurse less frequently, provide less milk, and lose less weight during lactation than sows that cannot control their level of contact. Because of this interesting natural history and because they are so amenable to experimentation, domestic pigs provide a rich system for testing ideas drawn from resource allocation theory. This contribution is part of the special issue “Sibling competition and cooperation in mammals” (guest editors: Robyn Hudson and Fritz Trillmich).     

Evaluating portable infrared spectrometers for measuring the silica content of coal dust

Miners face a variety of respiratory hazards while on the job, including exposure to silica dust which can lead to silicosis, a potentially fatal lung disease. Currently, field-collected filter samples of silica are sent for laboratory analysis and the results take weeks to be reported. Since the mining workplace is constantly moving into new and often different geological strata with changing silica levels, more timely data on silica levels in mining workplaces could help reduce exposures. Improvements in infrared (IR) spectroscopy open the prospect for end-of-shift silica measurements at mine sites. Two field-portable IR spectrometers were evaluated for their ability to quantify the mass of silica on filter samples loaded with known amounts of either silica or silica-bearing coal dust (silica content ranging from 10-200 μg/filter). Analyses included a scheme to correct for the presence of kaolin, which is a confounder for IR analysis of silica. IR measurements of the samples were compared to parallel measurements derived using the laboratory-based U.S. Mine Safety and Health Administration P7 analytical method. Linear correlations between Fourier transform infrared (FTIR) and P7 data yielded slopes in the range of 0.90-0.97 with minimal bias. Data from a variable filter array spectrometer did not correlate as well, mainly due to poor wavelength resolution compared to the FTIR instrument. This work has shown that FTIR spectrometry has the potential to reasonably estimate the silica exposure of miners if employed in an end-of-shift method.     

10-Daily soil erosion modelling over sub-Saharan Africa

Soil erosion is considered to be one of the greatest environmental problems of sub-Saharan Africa. This paper investigates the advantages and disadvantages of modelling soil erosion at the continental scale and suggests an operational methodology for mapping and quantifying 10-daily water runoff and soil erosion over this scale using remote sensing data in a geographical information system framework. An attempt is made to compare the estimates of this study with general data on the severity of soil erosion over Africa and with measured rates of soil loss at different locations over the continent. The results show that the measured and estimated rates of erosion are in some areas very similar and in general within the same order of magnitude. The importance and the potential of using the soil erosion estimates with simple models and easily accessible free data for various continental-scale environmental applications are also demonstrated.