Iron-rich Oklahoma clays as a natural source of chromium in monitoring wells

Water samples, drawn from groundwater monitoring wells located southeast of Oklahoma City, OK, were found to contain elevated concentrations of total chromium with an apparent source localized to the area surrounding each well. Since these monitoring wells are located in areas with no historic chromium usage, industrial sources of chromium were ruled out. Water testing was performed on twelve monitoring wells in the area that historically had elevated total chromium concentrations ranging from 10-4900 micrograms per litre. Filtered water samples were found to be free of chromium contamination, indicating that the source of the chromium is the suspended solids. Analysis of these solids by acid digestion and a sequential extraction technique revealed that the chromium was primarily associated with iron-containing solids. X-ray diffraction identified goethite, an iron oxide hydroxide, as the dominant iron-containing phase in the suspended solids. The mineralogy in this region is dominated by interbedded red-bed sandstone and mudstone whose mineral content includes mixed-layer illite-smectite, hematite, goethite, gypsum and dolomite. Elemental analysis of soil samples collected as a function of depth in the locale of the monitoring wells indicated that the iron rich clays contain a natural source of chromium. The elevated levels of total chromium are most likely due to the dissolution of silica and alumina from the chromium containing iron clays in the basic well water, resulting in the release of fine suspended solids that naturally have high chromium concentrations. These results should be applicable to other areas containing iron-rich clays.     

Monitoring fluvial water chemistry for trend detection: hydrological variability masks trends in datasets covering fewer than 12 years

This paper sub-samples four 35 year water quality time series to consider the potential influence of short-term hydrological variability on process inference derived from short-term monitoring data. The data comprise two time series for nitrate (NO(3)-N) and two for DOC (using water colour as a surrogate). The four catchments were selected not only because of their long records, but also because the four catchments are very different: upland and lowland, agricultural and non-agricultural. Multiple linear regression is used to identify the trend and effects of rainfall and hydrological 'memory effects' over the full 35 years, and then a moving-window technique is used to subsample the series, using window widths of between 6 and 20 years. The results suggest that analyses of periods between six and eleven years are more influenced by local hydrological variability and therefore provide misleading results about long-term trends, whereas periods of longer than twelve years tend to be more representative of underlying system behaviour. This is significant: if such methods for analysing monitoring data were used to validate changes in catchment management, a monitoring period of less than 12 years might be insufficient to demonstrate change in the underlying system.     

Advanced REACH Tool (ART): calibration of the mechanistic model

The mechanistic model of the Advanced Reach Tool (ART) provides a relative ranking of exposure levels from different scenarios. The objectives of the calibration described in this paper are threefold: to study whether the mechanistic model scores are accurately ranked in relation to exposure measurements; to enable the mechanistic model to estimate actual exposure levels rather than relative scores; and to provide a method of quantifying model uncertainty. Stringent data quality guidelines were applied to the collated data. Linear mixed effects models were used to evaluate the association between relative ART model scores and measurements. A random scenario and company component of variance were introduced to reflect the model uncertainty. Stratified analyses were conducted for different forms of exposure (abrasive dust, dust, vapours and mists). In total more than 2000 good quality measurements were available for the calibration of the mechanistic model. The calibration showed that after calibration the mechanistic model of ART was able to estimate geometric mean (GM) exposure levels with 90% confidence for a given scenario to lie within a factor between two and six of the measured GM depending upon the form of exposure.     

A field experiment characterizing variable detection rates during plant surveys

Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.     

Genomic erosion in a demographically recovered bird species during conservation rescue

The pink pigeon (Nesoenas mayeri) is an endemic species of Mauritius that has made a remarkable recovery after a severe population bottleneck in the 1970s to early 1990s. Prior to this bottleneck, an ex situ population was established from which captive-bred individuals were released into free-living subpopulations to increase population size and genetic variation. This conservation rescue led to rapid population recovery to 400–480 individuals, and the species was twice downlisted on the International Union for the Conservation of Nature (IUCN) Red List. We analyzed the impacts of the bottleneck and genetic rescue on neutral genetic variation during and after population recovery (1993–2008) with restriction site-associated sequencing, microsatellite analyses, and quantitative genetic analysis of studbook data of 1112 birds from zoos in Europe and the United States. We used computer simulations to study the predicted changes in genetic variation and population viability from the past into the future. Genetic variation declined rapidly, despite the population rebound, and the effective population size was approximately an order of magnitude smaller than census size. The species carried a high genetic load of circa 15 lethal equivalents for longevity. Our computer simulations predicted continued inbreeding will likely result in increased expression of deleterious mutations (i.e., a high realized load) and severe inbreeding depression. Without continued conservation actions, it is likely that the pink pigeon will go extinct in the wild within 100 years. Conservation rescue of the pink pigeon has been instrumental in the recovery of the free-living population. However, further genetic rescue with captive-bred birds from zoos is required to recover lost variation, reduce expression of harmful deleterious variation, and prevent extinction. The use of genomics and modeling data can inform IUCN assessments of the viability and extinction risk of species, and it helps in assessments of the conservation dependency of populations.     

Review of hospital plastic waste management strategies for Pakistan

Environmental Science and Pollution Research - Healthcare waste management is considered one of the biggest challenges that the world is going to face in the future. This threat is becoming reality...     

An empirical evaluation of the insurance hypothesis in diversity-stability models

An important stabilizing mechanism in most diversity stability models is the insurance hypothesis, which involves correlation/covariance relationships among species. These models require that species do not fluctuate synchronously over time: that is, the correlation between pairs of species does not equal 1.0. However, the strength of this stabilizing mechanism increases as correlations decline away from 1.0, especially as they become more negative and also as the summed covariance across all species pairs becomes more negative. We evaluated the importance of the insurance hypothesis as a stabilizing mechanism by examining a variety of terrestrial assemblages using long-term data from the Global Population Dynamics Database, the Breeding Bird Survey, and a long-term site in southeastern Arizona, USA. We identified co-occurring assemblages of species and calculated the Spearman rank correlations of all pairs of species and the summed covariance of the entire assemblage. We found that, in most assemblages, positive correlations were two to three times more common than negative and that the magnitude of the positive correlations tended to be stronger than the negative correlations. For all but three assemblages, the summed covariance was positive. Data from larger spatial scales tended to exhibit more positive correlations, but even at the smallest spatial scales, positive correlations outnumbered negative. We suggest that species often covary positively because coexisting species respond similarly to fluctuations in their resource base driven by climatic fluctuations. As such, our review suggests that the insurance hypothesis may not be a strong mechanism stabilizing fluctuations in natural terrestrial communities.     

Combining a generic process-based productivity model and a statistical classification method to predict the presence and absence of tree species in the Pacific Northwest,U.S.A.

Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions. We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation in four climatic-related variables: water availability, deviations from an optimum temperature, atmospheric humidity deficits, and the frequency of frost. Rather than use climatic data directly to correlate with a species’ distribution, we assess the relative constraints of each of the four variables as they affect predicted monthly photosynthesis for Douglas-fir, the most widely distributed species in the region. We apply an automated regression-tree analysis to create a suite of rules, which differentially rank the relative importance of the four climatic modifiers for each species, and provide a basis for predicting a species’ presence or absence on 3737 uniformly distributed U.S. Forest Services’ Forest Inventory and Analysis (FIA) field survey plots. Results of this generalized rule-based approach were encouraging, with weighted accuracy, which combines the correct prediction of both presence and absence on FIA survey plots, averaging 87%. A wider sampling of climatic conditions throughout the full range of a species’ distribution should improve the basis for creating rules and the possibility of predicting future shifts in the geographic distribution of species.     

Low levels of toxic elements in Dead Sea black mud and mud-derived cosmetic products

Natural muds used as or in cosmetics may expose consumers to toxic metals and elements via absorption through the skin, inhalation of the dried product, or ingestion (by children). Despite the extensive therapeutic and cosmetic use of the Dead Sea muds, there apparently has been no assessment of the levels of such toxic elements as Pb, As, or Cd in the mud and mud-based products. Inductively coupled plasma mass spectrometry analysis of eight toxic elements in samples collected from three black mud deposits (Lisan Marl, Pleistocene age) on the eastern shore of the Dead Sea in Jordan revealed no special enrichment of toxic elements in the mud. A similar analysis of 16 different commercial Dead Sea mud cosmetics, including packaged mud, likewise revealed no toxic elements at elevated levels of concern. From a toxic element standpoint, the Dead Sea black muds and derivative products appear to be safe for the consumer. Whatever the therapeutic benefits of the mud, our comparison of the elemental fingerprints of the consumer products with those of the field samples revealed one disturbing aspect: Dead Sea black mud should not be a significant component of such items as hand creams, body lotions, shampoo, and moisturizer.