Elimination of 10 polybrominated diphenyl ether (PBDE) congeners and selected polychlorinated biphenyls (PCBs) from the freshwater mussel, Elliptio complanata

Mussel biomonitors are widely used as screening tools for polybrominated diphenyl ethers (PBDEs) in marine and aquatic environments. This study determined elimination rate coefficients (k(tot)) for eight PBDE and five PCB congeners in the freshwater mussel, Elliptio complanata, over a 120d depuration period. Elimination of BDE 15, 28, 47, 75 and 100 was similar to PCBs of equivalent hydrophobicity and negatively related to chemical K(OW). Rapid elimination of BDE 190 and an inferred rapid elimination of BDE 183 indicate mussels are capable of biotransformation of certain highly brominated PBDEs. Time to 90% steady state ranged from 48 to 66d for di- and tribromoDE congeners and from 91 to >250d for tetra- to hexabromoDE congeners. Given the long time periods required for steady state, mussel accumulated PBDE residues should be interpreted in the context of calibrated bioaccumulation models.     

Adsorption of arsenic(V) onto fly ash: a speciation-based approach

Arsenic (As) poses a significant water quality problem and challenge for the environmental engineers and scientists in the world. The large volume of coal fly ash produced around the world is a potentially significant anthropogenic source of arsenic. Currently the leaching behavior of arsenic from fly ash is not well understood. Batch methods were used in this study to investigate arsenic leaching using a raw ash, and arsenic adsorption using a clean, washed ash. Experimental results indicated that pH had a significant effect on arsenic leaching or adsorption. Between pH 3 and 7, less arsenic was in the dissolved phase. When pH was less than 3 or greater than 7, increasing amounts of arsenic were leached or desorbed from fly ash. The leaching and adsorption behavior of arsenic was interpreted with the speciation of surface sites and arsenic. In a new approach, a speciation-based model was developed to quantify the arsenic adsorption as a function of pH and surface acidity parameters. This work is important in offering insight into the leaching mechanism of arsenic from coal fly ash, and providing a robust model based upon specific, measurable parameters to quantify arsenic adsorption by other solid media in addition to fly ash.     

Making scents of defense: do fecal shields and herbivore-caused volatiles match host plant chemical profiles?

Many plant families have aromatic species that produce volatile compounds which they release when damaged, particularly after suffering herbivory. Monarda fistulosa (Lamiaceae) makes and stores volatile essential oils in peltate glandular trichomes on leaf and floral surfaces. This study examined the larvae of a specialist tortoise beetle, Physonota unipunctata, which feed on two M. fistulosa chemotypes and incorporate host compounds into fecal shields, structures related to defense. Comparisons of shield and host leaf chemistry showed differences between chemotypes and structures (leaves vs. shields). Thymol chemotype leaves and shields contained more of all compounds that differed than did carvacrol chemotypes, except for carvacrol. Shields had lower levels of most of the more volatile chemicals than leaves, but more than twice the amounts of the phenolic monoterpenes thymol and carvacrol and greater totals. Additional experiments measured the volatiles emitted from M. fistulosa in the absence and presence of P. unipunctata larvae and compared the flower and foliage chemistry of plants from these experiments. Flowers contained lower or equal amounts of most compounds and half the total amount, compared to leaves. Plants subjected to herbivory emitted higher levels of most volatiles and 12 times the total amount, versus controls with no larvae, including proportionally more of the low boiling point chemicals. Thus, chemical profiles of shields and volatile emissions are influenced by the amounts and volatilities of compounds present in the host plant. The implications of these results are explored for the chemical ecology of both the plant and the insect.     

One day is all it takes: circadian modulation of the retrieval of colour memories in honeybees

In this study, we examined how honeybees coped with successive tasks of colour discrimination with conflicting demands. Free-flying honeybees (Apis mellifera) were trained on tasks in which they had to choose one of three colours to obtain a reward of sugar water. In acquisition, the bees learned this task in about four trials of training. Colour memory was retained after 24-h delay in an unrewarded retention test. Integration experiments were then conducted in which the bees had to learn two successive tasks of colour discrimination with conflicting demands, task 1 for 20 trials and task 2 for ten trials. In task 1, one of three colours provided sugar water while the other two provided tap water, while in task 2 a different colour provided the reward. The bees were given unrewarded tests immediately after training on task 2 and then re-tested after 10 min, 22 h (circadian time of the start of task 1 training), or 24 h (circadian time of the end of task 2 training). Bees strongly preferred the rewarded colour for task 2 on immediate testing and after 10-min delay. After 22-h delay, they switched their preference to the rewarded colour for task 1. But after 24-h delay, the bees again strongly preferred the rewarded colour for task 2. Further tests at a number of delays between 0 and 22 h revealed a sigmoidal pattern of rise in the preference for the task 1 colour. We conclude that circadian time modulates the retrieval of colour memories in honeybees, even when all the training took place in a single day.     

ANALYZIIG RIPARIAN SITE CAPABILITY AND MANAGEMENT OPTIONS1

ABSTRACT: Riparian areas interact with aquatic and upland conditions and therefore help determine the degree of functionality (streambank stability, shade, sediment, and debris filtering) found in a watershed or catchment. Thus, conditions in riparian areas exert significant influence on water quality. Physical and biological factors (biophysical determinants) that influence these conditions and determine long‐term site ecology include topographic variables, geology, climate, soil texture, and others. These conditions are further modified by management infrastructure (roads, dikes, etc.). Our objective was to develop a system for evaluating site condition in relation to site capability. Since biophysical determinants and infrastructure interact with water quality, our first task was to acquire data concerning the spatial distribution of biophysical determinants and infrastructure constraints and to import them into a GIS system where they could be managed and processed. To expedite analysis, determinants and infrastructure constraints were placed into a hierarchy capable of isolating various site capability types. The hierarchy was designed to incorporate multiscale effects. Site capability areas are georeferenced in this process thereby enabling efficient monitoring and providing a way to focus management on those areas needing improvement. Study tasks included: (1) landscape characterization and hierarchy selection, (2) field assessment, (3) information management and data mining, and (4) information interpretation and adaptive management. This approach appears to be an effective way to isolate general ripananstandardsmaycon site conditions, to provide indications about water quality, and to create strategies necessary for alleviating water quality problems.     

Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.     

In situ net primary productivity and photosynthesis of Antarctic sea ice algal, phytoplankton and benthic algal communities

Primary production at Antarctic coastal sites is contributed from sea ice algae, phytoplankton and benthic algae. Oxygen microelectrodes were used to estimate sea ice and benthic primary production at several sites around Casey, a coastal area in eastern Antarctica. Maximum oxygen export from sea ice was 0.95 mmol O₂ m⁻² h⁻¹ (~11.7 mg C m⁻² h⁻¹) while from the sediment it was 6.08 mmol O₂ m⁻² h⁻¹ (~70.8 mg C m⁻² h⁻¹). When the ice was present O₂ export from the benthos was either low or negative. Sea ice algae assimilation rates were up to 3.77 mg C (mg Chl-a)⁻¹ h⁻¹ while those from the benthos were up to 1.53 mg C (mg Chl-a)⁻¹ h⁻¹. The contribution of the major components of primary productivity was assessed using fluorometric techniques. When the ice was present approximately 55–65% of total daily primary production occurred in the sea ice with the remainder unequally partitioned between the sediment and the water column. When the ice was absent, the benthos contributed nearly 90% of the primary production.