A method for estimating distributions of mass transfer rate coefficients with application to purging and batch experiments

Mass transfer between aquifer material and groundwater is often modeled as first-order rate-limited sorption or diffusive exchange between mobile zones and immobile zones with idealized geometries. Recent improvements in experimental techniques and advances in our understanding of pore-scale heterogeneity demonstrate that two (or even a few) rate coefficients are insufficient in many cases. Here, we investigate a piece-wise linear model for a continuous distribution of rate coefficients, that has several advantages over previously used ‘statistical' distribution models (with functional form from gamma or lognormal PDF's): (1) distributions of arbitrary, even bimodal, shapes can be represented; (2) linear estimation methods can be applied to determine the distribution from experimental data; (3) the uncertainty in the distribution can be determined for each of its sections; and (4) the relationship between the time scales of available data and those of estimatable mass transfer processes can be investigated. A statistical model refinement algorithm is presented that reduces the number of parameters (sections of the piece-wise linear model) to the admissible minimum. We show that purging experiments allow estimation of a wider zone of the rate distribution than do batch experiments, and hence will provide predictions that are accurate over a wider range of time scales. Finally, in an application to TCE gas-purging desorption data, the piece-wise linear rate-distribution model has a higher probability of being adequate than those using a gamma or lognormal distribution or a single rate coefficient.     

Towards an ecologically meaningful classification of the flow biotope for river inventory, rehabilitation, design and appraisal purposes

Recent research into the physical and ecological status of rivers has focused upon rapid field-based assessments of mesoscale habitat features in order to satisfy international regulatory requirements for habitat inventory and appraisal. Despite the low cost and time efficient nature of rapid field surveys, the robustness of such techniques remains uncertain. This paper uses data from over 4000 surveyed UK river reaches in the UK River Habitat Survey (RHS) database in order to seek linkages between surface flow conditions (flow biotopes), local channel morphology (physical biotopes) and biologically distinct vegetative and minerogenic habitat units (functional habitats). Attempts to identify one-to-one connections between surface flow types, units of channel morphology and functional habitats oversimplify a complex and dynamic hydraulic environment. Instead, a nested hierarchy of reach-scale physical and ecological habitat structures exists, characterised by transferable assemblages of habitat units. Five flow biotopes show strong correlations with functional habitats, and differing combinations of three of these account for over 60% of the distribution for all functional habitats. On this basis, a classification of environments for ecological purposes is proposed. Principal components analysis and agglomerative hierarchical clustering analysis are employed to objectively validate the proposed classification. Flow biotope assemblages may also represent reach-scale channel morphologies (step-pool, riffle-pool and glide-pool), although functional habitats exhibit differing 'preferences' for rougher or more tranquil environments within these. While the data and analysis are specific to the UK RHS, the methods and findings have wider application in situations, where rapid field appraisal methods and associated databases are deployed in water resource inventory and river rehabilitation design.     

Stakeholder analysis for industrial waste management systems

Stakeholder approaches have been applied to the management of companies with a view to the improvement of all areas of performance, including economic, health and safety, waste reduction, future policies, etc. However no agreement exists regarding stakeholders, their interests and levels of importance. This paper considers stakeholder analysis with particular reference to environmental and waste management systems. It proposes a template and matrix model for identification of stakeholder roles and influences by rating the stakeholders. A case study demonstrates the use of these and their ability to be transferred to other circumstances and organizations is illustrated by using a large educational institution.     

Effects of population-related variation in plant primary and secondary metabolites on aboveground and belowground multitrophic interactions

Insects feeding on aboveground and belowground tissues can influence each other through their shared plant and this is often mediated by changes in plant chemistry. We examined the effects of belowground root fly (Delia radicum) herbivory on the performance of an aboveground herbivore (Plutella xylostella) and its endoparasitoid wasp (Cotesia vestalis). Insects were reared on three populations of wild cabbage (Brassica oleracea) plants, exhibiting qualitative and quantitative differences in root and shoot defense chemistry, that had or had not been exposed to root herbivory. In addition, we measured primary (amino acids and sugars) and secondary [glucosinolate (GS)] chemistry in plants exposed to the various plant population-treatment combinations to determine to what extent plant chemistry could explain variation in insect performance variables using multivariate statistics. In general, insect performance was more strongly affected by plant population than by herbivory in the opposite compartment, suggesting that population-related differences in plant quality are larger than those induced by herbivory. Sugar profiles were similar in the three populations and concentrations only changed in damaged tissues. In addition to population-related differences, amino acid concentrations primarily changed locally in response to herbivory. Whether GS concentrations changed in response to herbivory (indole GS) or whether there were only population-related differences (aliphatic GS) depended on GS class. Poor correlations between performance and chemical attributes made biological interpretation of these results difficult. Moreover, trade-offs between life history traits suggest that factors other than food nutritional quality contribute to the expression of life history traits.     

How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes.     

Sterol production and phytosterol bioconversion in two species of heterotrophic protists, Oxyrrhis marina and Gyrodinium dominans

The kinetics and efficiency of sterol production and bioconversion of phytosterols in two heterotrophic protists Oxyrrhis marina and Gyrodinium dominans were examined by feeding them two different algal species (Rhodomonas salina and Dunaliella tertiolecta) differing in sterol profiles. R. salina contains predominantly brassicasterol (≅99%) and <2% cholesterol. The major sterols in D. tertiolecta are ergosterol (45–49%), 7-dehydroporiferasterol (29–31%) and fungisterol (21–26%). O. marina fed R. salina metabolized dietary brassicasterol to produce 22-dehydrocholesterol and cholesterol. O. marina fed D. tertiolecta metabolized dietary sterols to produce cholesterol, 22-dehydrocholesterol, brassicasterol and stigmasterol. G. dominans fed either R. salina or D. tertiolecta metabolized dietary sterols to make cholesterol, brassicasterol and a series of unknown sterols. When protists were fed R. salina, which contains cholesterol, the levels of cholesterol were increased to a magnitude of nearly 5- to 30-fold at the phytoplankton-heterotrophic protist interface, equivalent to a production of 172.5 ± 16.2 and 987.7 ± 377.7 ng cholesterol per mg R. salina carbon consumed by O. marina and G. dominans, respectively. When protists were fed D. tertiolecta, which contains no cholesterol, a net production of cholesterol by the protists ranged from 123.2 ± 30.6 to 871.8 ± 130.8 ng per mg algal C consumed. Cholesterol is not only the dominant sterol, but a critical precursor for many physiologically functional biochemicals in higher animal. As intermediates, these heterotrophic protists increase the amount of cholesterol at the phytoplankton–zooplankton interface available to higher trophic levels relative to zooplankton feeding on algae directly.     

Remote Antarctic feeding ground important for east Australian humpback whales

Understanding the dynamics of population recovery is particularly complex when an organism has multiple, remote breeding and feeding grounds separated by one of the longest known migration routes. This study reports on the most comprehensive assessment of humpback whale (Megaptera novaeangliae) movements between remote Antarctic waters south of New Zealand and east Australia (EA), and the migratory corridors and breeding grounds of Australia and Oceania. A total of 112 individual whales were identified; 57 from microsatellites and 61 by fluke with 23 % (n = 26) matched to sites outside Antarctica. Despite large datasets from other southern regions being included in the comparison, the whales were predominantly linked to EA (n = 24). Only two matches to the Oceania catalogues directly north was surprising; therefore the primary feeding grounds of these endangered whales still remain unknown. The confirmation of the Balleny Islands as an important feeding ground for EA whales could provide an insight into reasons behind the rapid recovery of this population. Determining the feeding grounds of Oceania’s whales may explain whether prey energetics or migration length are limiting factors to their recovery and will allow an understanding of future ecosystem changes in these whales.     

Consequences of resource competition for sex allocation and discriminative behaviors in a hyperparasitoid wasp

Population-wide mating patterns can select for equal parental investment in both sexes, but limiting resources, such as mates or developmental substrates, can increase competition leading to biased sex ratios in favor of either sex. Such competition for resources typically occurs in spatially structured populations, where dispersal is limited. In this laboratory study, we investigate if and how resource competition affects sex allocation, discriminative behaviors and competitive interactions of the wingless hyperparasitoid Gelis acororum, which exploits patchily distributed hosts. We show that G. acororum sex ratios are male-biased and that this is not a consequence of constrained reproduction by virgin females. Our results suggest that this pattern of reproductive investment, which is only rarely observed in parasitoids, is a consequence of resource limitation, in terms of hosts rather than mates. Further, G. acororum appears not to respond to intrinsic host quality or to prior oviposition in its host. When competing inter-specifically for host resources, G. acororum outcompetes its congener Gelis agilis, but does so mainly when ovipositing on the host first. Overall, our results suggest that host resource limitation could be an important environmental factor shaping sex allocation in G. acororum, with competition taking place both intra- and inter-specifically.     

Exposure to Inorganic Arsenic in Soil Increases Urinary Inorganic Arsenic Concentrations of Residents Living in Old Mining Areas

The short term human exposure studies conducted on populations exposed to high concentrations of inorganic arsenic in soil have been inconsistent in demonstrating a relationship between environmental concentrations and exposure measures. In Australia there are many areas with very high arsenic concentrations in residential soil most typically associated with gold mining activities in rural areas. This study aimed to investigate the relationship between environmental arsenic and urinary inorganic arsenic concentrations in a population living in a gold mining area (soil arsenic concentrations between 9 and 9900 mg kg(-1)), and a control population with low arsenic levels in soil (between 1 and 80 mg kg(-1)). Risk factors for increased urinary arsenic concentrations were also explored. There was a weak but significant relationship between soil arsenic concentrations and inorganic urinary arsenic concentration with a Spearman correlation coefficient of 0.39. When participants with greater than 100 mg kg(-1) arsenic in residential soil were selected, the coefficient increased to 0.64. The geometric mean urinary inorganic arsenic concentration for the exposed group was 1.64 microg L(-1) (相似文献