Effects of seven organic pollutants on soil nematode Caenorhabditis elegans

Caenorhabditis elegans is a free-living soil nematode that is commonly used as a model for toxicity tests. The aim of this study was to investigate the toxicity of seven organic pollutants: four azaarenes (quinoline, acridine, phenazine, and 1,10-phenanthroline), short-chain chlorinated paraffins, and two organochlorinated pesticides (toxaphene and hexachlorobenzene). The exposure to all chemicals was carried out in three test media (soil, agar, and aquatic medium), and adult mortality was evaluated after 24 and 48 h. Toxaphene was the most toxic substance with LC(50) (48 h) of 379 mg/kg in the soil and 0.2 mg/L in the aquatic medium. Quinoline was the most toxic chemical in agar test with LC(50) (48 h) of 10 mg/L. HCB showed a very low toxicity in all tests, maybe due to its very low water solubility. Longer than 24-h test duration was found necessary for getting more correct data on toxicity. In comparison with other studies, C. elegans was less sensitive than other soil invertebrates. Different response might be attributed to different exposure routes and shorter test duration. Equilibrium partitioning theory was used to calculate K(oc) from results of soil and aquatic tests but this approach was found not working. Our results suggest that the tests with nematode C. elegans should be included to the battery of tests for risk assessment of POPs in soil.     

The distribution of 210Pb in human bone and its impact on methods for the retrospective estimation of 222Rn exposure from in vivo measurements

It is possible to estimate radon exposure to man retrospectively by the in vivo measurement of the decay product (210)Pb, which accumulates in the bones. For in vivo methods, knowledge of the distribution of (210)Pb in the skeleton is needed to determine the optimal site for measurement, the skull or the knee. In this study the activity of (210)Pb in a variety of bone samples from 3 individuals have been measured in vitro using underground gamma-ray spectrometry. The individuals were unlikely to have had elevated intakes of Rn. These measurements give baseline data on the bone massic activity of (210)Pb. They show that the massic activity is similar for each of these people and there are similar massic activities of (210)Pb in the skull and the knee of the 2 individuals for which the skull was measured. Additionally for 2 of the individuals trabecular and cortical bone were separated and massic activities were found to be strongly correlated indicating that the (210)Pb is associated with the hydroxyapatite.     

Load Estimation Method Using Distributions with Covariates: A Comparison with Commonly Used Estimation Methods

Load estimates obtained using an approach based on statistical distributions with parameters expressed as a function of covariates (e.g., streamflow) (distribution with covariates hereafter called DC method) were compared to four load estimation methods: (1) flow‐weighted mean concentration; (2) integral regression; (3) segmented regression (the last two with Ferguson's correction factor); and (4) hydrograph separation methods. A total of 25 datasets (from 19 stations) of daily concentrations of total dissolved solids, nutrients, or suspended particulate matter were used. The selected stations represented a wide range of hydrological conditions. Annual flux errors were determined by randomly generating 50 monthly sample series from daily series. Annual and interannual biases and dispersions were evaluated and compared. The impact of sampling frequency was investigated through the generation of bimonthly and weekly surveys. Interannual uncertainty analysis showed that the performance of the DC method was comparable with those of the other methods, except for stations showing high hydrological variability. In this case, the DC method performed better, with annual biases lower than those characterizing the other methods. Results show that the DC method generated the smallest pollutant load errors when considering a monthly sampling frequency for rivers showing high variability in hydrological conditions and contaminant concentrations.     

Stack sampling for organic emissions

Along with increased activity in source sampling for organics, there have been many improvements in the methods of acquiring samples. Much has been learned about how best to proceed, and a number of potentially serious pitfalls have been discovered, characterized, and circumvented. Unfortunately, communication of all of this new technology has not always been effective.

This paper reviews some of the more important fundamental principles involved in stack sampling for organics, briefly describes and discusses recently developed equipment, and points out a few of the more serious pitfalls to be avoided. Extensive references are provided, many of which are often overlooked by newcomers to the field. The conclusion is reached that it is possible to consistently obtain high‐quality samples of organic materials from stationary source stacks, even though knowledge and caution are necessary.     

Traffic environment and demographic factors affecting impaired driving and crashes

IntroductionData availability has forced researchers to examine separately the role of alcohol among drivers who crashed and drivers who did not crash. Such a separation fails to account fully for the transition from impaired driving to an alcohol-related crash.MethodIn this study, we analyzed recent data to investigate how traffic-related environments, conditions, and drivers’ demographics shape the likelihood of a driver being either involved in a crash (alcohol impaired or not) or not involved in a crash (alcohol impaired or not). Our data, from a recent case–control study, included a comprehensive sampling of the drivers in nonfatal crashes and a matched set of comparison drivers in two U.S. locations. Multinomial logistic regression was applied to investigate the likelihood that a driver would crash or would not crash, either with a blood alcohol concentration (BAC) = .00 or with a BAC ≥ .05.ConclusionsTo our knowledge, this study is the first to examine how different driver characteristics and environmental factors simultaneously contribute to alcohol use by crash-involved and non-crash-involved drivers. This effort calls attention to the need for research on the simultaneous roles played by all the factors that may contribute to motor vehicle crashes.     

Network-based exploration and visualisation of ecological data

Networks – structured graphs consisting of sets of nodes connected by edges – provide a rich framework for data visualisation and exploratory analyses. Although rarely used for the visualisation of ecological data, networks are well suited to this purpose, including data that one might not normally think of as a network. We present a simple method for transforming a data matrix into network format, and show how this can be used as the basis for interactive exploratory analyses of ecological data.The method is demonstrated using a database of marine zooplankton samples acquired in the Southern Ocean. The network analyses revealed zooplankton community structures that are in good agreement with previously published results. Variations in community structure were observed to be related to the temporal and spatial pattern of sampling, as well as to physical environmental factors such as sea ice cover. The analyses also revealed a number of errors in the data, including taxon identification errors and instrument failures.The method allows the analyst to generate networks from different combinations of variables in the data set, and to examine the effects of varying parameters such as the scales of spatial, temporal, and taxonomic aggregation. This flexibility allows the analyst to rapidly gain a number of perspectives on the data and provides a powerful mechanism for exploration.     

Estimation of abundance from presence–absence maps using cluster models

A presence–absence map consists of indicators of the occurrence or nonoccurrence of a given species in each cell over a grid, without counting the number of individuals in a cell once it is known it is occupied. They are commonly used to estimate the distribution of a species, but our interest is in using these data to estimate the abundance of the species. In practice, certain types of species (in particular flora types) may be spatially clustered. For example, some plant communities will naturally group together according to similar environmental characteristics within a given area. To estimate abundance, we develop an approach based on clustered negative binomial models with unknown cluster sizes. Our approach uses working clusters of cells to construct an estimator which we show is consistent. We also introduce a new concept called super-clustering used to estimate components of the standard errors and interval estimators. A simulation study is conducted to examine the performance of the estimators and they are applied to real data.     

Catalyzing sustainable fisheries management through behavior change interventions

Small-scale fisheries are an important livelihood and primary protein source for coastal communities in many of the poorest regions in the world, yet many are overfished and thus require effective and scalable management solutions. Positive ecological and socioeconomic responses to management typically lag behind immediate costs borne by fishers from fishing pressure reductions necessary for fisheries recovery. These short-term costs challenge the long-term success of these interventions. However, social marketing may increase perceptions of management benefits before ecological and socioeconomic benefits are fully realized, driving new social norms and ultimately long-term sustainable behavior change. By conducting underwater visual surveys to quantify ecological conditions and by conducting household surveys with community members to quantify their perceptions of management support and socioeconomic conditions, we assessed the impact of a standardized small-scale fisheries management intervention that was implemented across 41 sites in Brazil, Indonesia, and the Philippines. The intervention combines TURF reserves (community-based territorial use rights for fishing coupled with no-take marine reserves) with locally tailored social-marketing behavior change campaigns. Leveraging data across 22 indicators and 4 survey types, along with data from 3 control sites, we found that ecological and socioeconomic impacts varied and that communities supported the intervention and were already changing their fishing practices. These results suggest that communities were developing new social norms and fishing more sustainably before long-term ecological and socioeconomic benefits of fisheries management materialized.     

The measurement of place attachment: Personal,community, and environmental connections

Place attachment has been researched extensively in the social and behavioural sciences over the past two decades. However, it is challenging for researchers to assimilate the mixed messages presented in the place attachment literature and to understand the multiple place attachment terms. In this study, a four-dimensional model of rural landholder attachments to their natural resource management region was conceptually and empirically developed with the aim of developing an integrated approach to the measurement of place attachment that clearly distinguishes between different elements of place scholarship. A 29-item place attachment scale with the dimensions of place identity, place dependence, nature bonding, and social bonding was tested on a random sample of rural landholders in the Adelaide and Mount Lofty Ranges in South Australia (N = 320). The majority of respondents were male (69.3%) and the average age was 59 years. The scale was reduced to 20-items and then administered simultaneously and in the same response format to rural landholders in two other areas of South Australia: the Northern and Yorke region (N = 664) and South Australian Murray-Darling Basin region (N = 659). In both studies, the majority of respondents were male (85%) and the average age was 55 years. Exploratory factor and reliability analyses of Adelaide and Mount Lofty Ranges and Northern and Yorke datasets produced a five-dimensional model of place attachment with high reliabilities. Social bonding divided into the constructs of family bonding and friend bonding. The refined five-dimensional model was then examined for convergent validity, with moderate but significant correlations found between individual attachment constructs and dependent variables expected to be related to the construct, such as place identity and length of residence, and nature bonding and time currently spent in nature. We used confirmatory factor analysis to test the goodness-of-fit of the South Australian Murray-Darling Basin (SAMDB) dataset to the proposed five-dimensional model and then compared its fit to the traditional two-dimensional model of place identity and place dependence. The five-dimensional model provided moderate fit for the SAMDB data. We conclude with a discussion of the validity and reliability of the five-dimensional model and its future role in place attachment research.     

Effects of 4-methylbenzylidene camphor (4-MBC) on neuronal and muscular development in zebrafish (<Emphasis Type="Italic">Danio rerio</Emphasis>) embryos

The negative effects of overexposure to ultraviolet (UV) radiation in humans, including sunburn and light-induced cellular injury, are of increasing public concern. 4-Methylbenzylidene camphor (4-MBC), an organic chemical UV filter, is an active ingredient in sunscreen products. To date, little information is available about its neurotoxicity during early vertebrate development. Zebrafish embryos were exposed to various concentrations of 4-MBC in embryo medium for 3 days. In this study, a high concentration of 4-MBC, which is not being expected at the current environmental concentrations in the environment, was used for the purpose of phenotypic screening. Embryos exposed to 15 μM of 4-MBC displayed abnormal axial curvature and exhibited impaired motility. Exposure effects were found to be greatest during the segmentation period, when somite formation and innervation occur. Immunostaining of the muscle and axon markers F59, znp1, and zn5 revealed that 4-MBC exposure leads to a disorganized pattern of slow muscle fibers and axon pathfinding errors during the innervation of both primary and secondary motor neurons. Our results also showed reduction in AChE activity upon 4-MBC exposure both in vivo in the embryos (15 μM) and in vitro in mammalian Neuro-2A cells (0.1 μM), providing a possible mechanism for 4-MBC-induced muscular and neuronal defects. Taken together, our results have shown that 4-MBC is a teratogen and influences muscular and neuronal development, which may result in developmental defects.