Chemical aspects of mass spawning in corals. II. (-)-Epi-thunbergol,the sperm attractant in the eggs of the soft coral Lobophytum crassum (Cnidaria: Octocorallia)

Sea turtles migrate between feeding and nesting areas that are often geographically separated by hundreds or thousands of kilometers. Observations of their aggregations at sea and at nesting beaches have led to the hypothesis that sea turtles migrate in socially structured groups. While this migratory strategy is common to many marine vertebrates, socially facilitated behavior is not well documented in testudines. In 1990 and 1991, we attached satellite transmitters to olive ridleys (Lepidochelys olivacea Eschscholtz) found ovipositing together during a mass nesting at Nancite Beach, Costa Rica, to determine whether they migrate independently or in groups after they leave the nesting beach. Results showed that the turtles were not spatially associated during the internesting period, were capable of re-establishing themselves as a group during a subsequent nesting emergence, and were not spatially associated during their postnesting migrations to oceanic feeding areas. We suggested that what appear to be socially structured groups of L. olivacea are in fact individual turtles simultaneously using the same habitat.     

Response of marine phytoplankton to nitrogen deficiency: Decreased nitrate uptake vs enhanced ammonium uptake

The uptake of nitrate and ammonium was measured separately in uni-algal, nitrogen-deficient cultures of four species of marine phytoplankton. Nitrogen-deficient phytoplankton took up ammonium at initial rates which greatly exceeded those measured for nitrogen-sufficient phytoplankton. However, nitrate uptake by nitrogendeficient cultures was generally much slower than either nitrate or ammonium uptake by nitrogen-sufficient cultures or ammonium uptake by nitrogen-deficient cultures. Considerable species differences were observed in the degree to which nitrogen deficiency increased ammonium uptake or decreased nitrate uptake. Loss of ability to take up nitrate, but enhanced ability to take up ammonium, as a result of nitrogen deficiency may be an adaptation to the different mechanisms by which nitrate and ammonium are supplied to the euphotic zone. In areas with an intermittent supply of nitrogen, changes in the ability of some species to take up nitrogen as a result of nitrogen starvation will influence species composition and complicate interpretations of measurements of nitrogen uptake.Contribution no. 1249 from the Department of Oceanography, University of Washington, and contribution no. 82006 from the Bigelow Laboratory for Ocean Sciences     

Microbial activity and carbon, nitrogen, and phosphorus content in a subtropical seagrass estuary (Florida Bay): evidence for limited bacterial use of seagrass production

Bacterial abundance, production, and extracellular enzyme activity were determined in the shallow water column, in the epiphytic community of Thalassia testudinum, and at the sediment surface along with total carbon, nitrogen, and phosphorus in Florida Bay, a subtropical seagrass estuary. Data were statistically reduced by principle components analysis (PCA) and multidimensional scaling and related to T. testudinum leaf total phosphorus content and phytoplankton biomass. Each zone (i.e., pelagic, epiphytic, and surface sediment community) was significantly dissimilar to each other (Global R = 0.65). Pelagic aminopeptidase and sum of carbon hydrolytic enzyme (esterase, peptidase, and α- and β-glucosidase) activities ranged from 8 to 284 mg N m⁻² day⁻¹ and 113–1,671 mg C m⁻² day⁻¹, respectively, and were 1–3 orders of magnitude higher than epiphytic and sediment surface activities. Due to the phosphorus-limited nature of Florida Bay, alkaline phosphatase activity was similar between pelagic (51–710 mg P m⁻² day⁻¹) and sediment (77–224 mg P m⁻² day⁻¹) zones but lower in the epiphytes (1.1–5.2 mg P m⁻² day⁻¹). Total (and/or organic) C (111–311 g C m⁻²), N (9.4–27.2 g N m⁻²), and P (212–1,623 mg P m⁻²) content were the highest in the sediment surface and typically the lowest in the seagrass epiphytes, ranging from 0.6 to 8.7 g C m⁻², 0.02–0.99 g N m⁻², and 0.5–43.5 mg P m⁻². Unlike nutrient content and enzyme activities, bacterial production was highest in the epiphytes (8.0–235.1 mg C m⁻² day⁻¹) and sediment surface (11.5–233.2 mg C m⁻² day⁻¹) and low in the water column (1.6–85.6 mg C m⁻² day⁻¹). At an assumed 50% bacterial growth efficiency, for example, extracellular enzyme hydrolysis could supply 1.8 and 69% of epiphytic and sediment bacteria carbon demand, respectively, while pelagic bacteria could fulfill their carbon demand completely by enzyme-hydrolyzable organic matter. Similarly, previously measured T. testudinum extracellular photosynthetic carbon exudation rates could not satisfy epiphytic and sediment surface bacterial carbon demand, suggesting that epiphytic algae and microphytobenthos might provide usable substrates to support high benthic bacterial production rates. PCA revealed that T. testudinum nutrient content was related positively to epiphytic nutrient content and carbon hydrolase activity in the sediment, but unrelated to pelagic variables. Phytoplankton biomass correlated positively with all pelagic components and sediment aminopeptidase activity but negatively with epiphytic alkaline phosphatase activity. In conclusion, seagrass production and nutrient content was unrelated to pelagic bacteria activity, but did influence extracellular enzyme hydrolysis at the sediment surface and in the epiphytes. This study suggests that seagrass-derived organic matter is of secondary importance in Florida Bay and that bacteria rely primarily on algal/cyanobacteria production. Pelagic bacteria seem coupled to phytoplankton, while the benthic community appears supported by epiphytic and/or microphytobenthos production.     

Organic matter source discrimination by humic acid characterization: Synchronous scan fluorescence spectroscopy and Ferrate(VI)

In this study, seven soil and sedimentary humic acid samples were analyzed by synchronous scan fluorescence (SSF) spectroscopy. The spectra of these humic acids were compared to each other and characterized, based on three major SSF peaks centered at approximately 281, 367 and 470 nm. Intensity ratios were calculated based on these peaks that were used to numerically assist in source discrimination. All humic acid samples were then reacted with Ferrate(VI) and were again analyzed with SSF. Upon the addition of Ferrate(VI) SSF spectra were obtained which more readily differentiated humic acid source. This method will assist geochemists and water management districts in tracing sources of organic matter to receiving water bodies and may aid in the elucidation of the chemical nature of humic acids.     

An Empirical Model to Predict Styrene Emissions from Fiber-Reinforced Plastics Fabrication Processes

ABSTRACT

Styrene is a designated hazardous air pollutant, per the 1990 Clean Air Act Amendments. It is also a tropospheric ozone precursor. Fiber-reinforced plastics (FRP) fabrication is the primary source of anthropogenic styrene emissions in the United States. This paper describes an empirical model designed to predict styrene emission factors for selected FRP fabrication processes. The model highlights 10 relevant parameters impacting styrene emission factors for FRP processes, and helps identify future areas of FRP pollution prevention (P2) research. In most cases, the number of these parameters with greatest impact on styrene emission factors can be limited to four or five. Seven different emission studies were evaluated and used as model inputs.     

Motor Vehicle Contributions to Ambient PM10 and PM2.5 at Selected Urban Areas in the USA

A source apportionment study was carried out to estimate the contribution of motor vehicles to ambient particulate matter (PM) in selected urban areas in the USA. Measurements were performed at seven locations during the period September 7, 2000 through March 9, 2001. Measurements included integrated PM_2.5 and PM₁₀ concentrations and polycyclic aromatic hydrocarbons (PAHs). Ambient PM_2.5 and PM₁₀ were apportioned to their local sources using the chemical mass balance (CMB) receptor model and compared with results obtained using scanning electron microscopy (SEM). Results indicate that PM_2.5 components were mainly from combustion sources, including motor vehicles, and secondary species (nitrates and sulfates). PM₁₀ consisted mainly of geological material, in addition to emissions from combustion sources. The fractional contributions of motor vehicles to ambient PM were estimated to be in the range from 20 to 76% and from 35 to 92% for PM_2.5 and PM₁₀, respectively.     

Introduction to the special issue: Place,identity and environmental behaviour

Research on identity has proliferated in recent decades, particularly within environmental psychology; the physical environment has been shown to have strong connections to a sense of self, and identity has proved to be an important mediator of behaviour. The concept of identity has been defined and measured, however, in a wide variety of ways. The goal of this special issue is to present some of the recent work tying identity to place and behaviour. In our opening essay we describe some of the distinctions among approaches to identity at different levels of specificity and scale and suggest some criteria to determine meaningful sources of identity, including impacts on cognitive processing, emotional responses, and behaviour. Although a monolithic framework is neither practical nor desirable, we encourage greater conceptual and methodological integration in future research on the interconnections among place, identity, and behaviour.     

An application of Bayesian variable selection to spatial concurrent linear models

Spatial concurrent linear models, in which the model coefficients are spatial processes varying at a local level, are flexible and useful tools for analyzing spatial data. One approach places stationary Gaussian process priors on the spatial processes, but in applications the data may display strong nonstationary patterns. In this article, we propose a Bayesian variable selection approach based on wavelet tools to address this problem. The proposed approach does not involve any stationarity assumptions on the priors, and instead we impose a mixture prior directly on each wavelet coefficient. We introduce an option to control the priors such that high resolution coefficients are more likely to be zero. Computationally efficient MCMC procedures are provided to address posterior sampling, and uncertainty in the estimation is assessed through posterior means and standard deviations. Examples based on simulated data demonstrate the estimation accuracy and advantages of the proposed method. We also illustrate the performance of the proposed method for real data obtained through remote sensing.