Spatial monitoring campaigns of volatile organic compounds were carried out in two similarly sized urban industrial cities, Windsor and Sarnia, ON, Canada. For Windsor, data were obtained for all four seasons at approximately 50 sites in each season (winter, spring, summer, and fall) over a three-year period (2004, 2005, and 2006) for a total of 12 sampling sessions. Sampling in Sarnia took place at 37 monitoring sites in fall 2005. In both cities, passive sampling was done using 3M 3500 organic vapor samplers. This paper characterizes benzene, toluene, ethylbenzene, o, and (m + p)-xylene (BTEX) concentrations and relationships among BTEX species in the two cities during the fall sampling periods. BTEX concentration levels and rank order among the species were similar between the two cities. In Sarnia, the relationships between the BTEX species varied depending on location. Correlation analysis between land use and concentration ratios showed a strong influence from local industries. Use one of the ratios between the BTEX species to diagnose photochemical age may be biased due to point source emissions, for example, 53 tonnes of benzene and 86 tonnes of toluene in Sarnia. However, considering multiple ratios leads to better conclusions regarding photochemical aging. Ratios obtained in the sampling campaigns showed significant deviation from those obtained at central monitoring stations, with less difference in the (m + p)/E ratio but better overall agreement in Windsor than in Sarnia.

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Environmental variation influences resource distribution, thereby affecting animal movement and foraging decisions. Climate change is altering environmental processes worldwide, but particularly in the Arctic, where changes in the phenology of sea ice have been redistributing resources across space and time. How polar marine predators such as ringed seals Pusa hispida hispida, whose ecology is tightly tied to sea ice, respond to different sea ice dynamics across large spatial scales is generally unknown. Here, behavioural states (resident and traveling) were estimated using state−space models on adult (n = 45) and subadult (n = 85) ringed seal satellite telemetry tracks from 6 Arctic locations. Tagged ringed seals spanned a wide latitudinal (56.54° to 75.58°N) and sea ice phenological range from short (1 to 2 mo) to longer (6 mo) ice-free periods. We assessed the influences of age class and several intra-and inter-annual environmental variables on ringed seal movement ecology. Both adults and subadults spent most of the icefree season in a resident state (93 and 77%, respectively). A latitudinal gradient was characterised, where longer ice-free seasons and less inter-annual variability in sea ice phenology at lower latitudes were related to ringed seals spending more time in a resident state than their conspecifics at higher latitudes (90 versus 58%, respectively), where the ice-free season was shorter and sea ice phenology between years was less synchronous. Ringed seals are responding to latitudinal differences in sea ice phenology which affect prey distribution, suggesting plasticity in their foraging decisions and spatiotemporal differences in prey distribution across the rapidly changing Arctic.

1Regulatory monitoring data and land-use regression (LUR) models have been widely used for estimating individual exposure to ambient air pollution in epidemiologic studies. However, LUR models lack fine-scale temporal resolution for predicting acute exposure and regulatory monitoring provides daily concentrations, but fails to capture spatial variability within urban areas. This study coupled LUR models with continuous regulatory monitoring to predict daily ambient nitrogen dioxide (NO 2 ) and particulate matter (PM 2.5 ) at 50 homes in Windsor, Ontario. We compared predicted versus measured daily outdoor concentrations for 5 days in winter and 5 days in summer at each home. We also examined the implications of using modeled versus measured daily pollutant concentrations to predict daily lung function among asthmatic children living in those homes. Mixed effect analysis suggested that temporally refined LUR models explained a greater proportion of the spatial and temporal variance in daily household-level outdoor NO 2 measurements compared with daily concentrations based on regulatory monitoring. Temporally refined LUR models captured 40% (summer) and 10% (winter) more of the spatial variance compared with regulatory monitoring data. Ambient PM 2.5 showed little spatial variation; therefore, daily PM 2.5 models were similar to regulatory monitoring data in the proportion of variance explained. Furthermore, effect estimates for forced expiratory volume in 1 s (FEV 1 ) and peak expiratory flow (PEF) based on modeled pollutant concentrations were consistent with effects based on household-level measurements for NO 2 and PM 2.5 . These results suggest that LUR modeling can be combined with continuous regulatory monitoring data to predict daily household-level exposure to ambient air pollution. Temporally refined LUR models provided a modest improvement in estimating daily householdlevel NO 2 compared with regulatory monitoring data alone, suggesting that this approach could potentially improve exposure estimation for spatially heterogeneous pollutants. These findings have important implications for epidemiologic studies -in particular, for research focused on short-term exposure and health effects.

The application of stable isotopes to characterize the complexities of a species foraging behavior and trophic relationships is dependent on assumptions of δ15N diet-tissue discrimination factors (∆15N). As ∆15N values have been experimentally shown to vary amongst consumers, tissues and diet composition, resolving appropriate species-specific ∆15N values can be complex. Given the logistical and ethical challenges of controlled feeding experiments for determining ∆15N values for large and/or endangered species, our objective was to conduct an assessment of a range of reported ∆15N values that can hypothetically serve as surrogates for describing the predator-prey relationships of four shark species that feed on prey from different trophic levels (i.e., different mean δ15N dietary values). Overall, the most suitable species-specific ∆15N values decreased with increasing dietary-δ15N values based on stable isotope Bayesian ellipse overlap estimates of shark and the principal prey functional groups contributing to the diet determined from stomach content analyses. Thus, a single ∆15N value was not supported for this speciose group of marine predatory fishes. For example, the ∆15N value of 3.7‰ provided the highest percent overlap between prey and predator isotope ellipses for the bonnethead shark (mean diet δ15N = 9‰) whereas a ∆15N value < 2.3‰ provided the highest percent overlap between prey and predator isotope ellipses for the white shark (mean diet δ15N = 15‰). These data corroborate the previously reported inverse ∆15N-dietary δ15N relationship when both isotope ellipses of principal prey functional groups and the broader identified diet of each species were considered supporting the adoption of different ∆15N values that reflect the predators’ δ15N-dietary value. These findings are critical for refining the application of stable isotope modeling approaches as inferences regarding a species’ ecological role in their community will be influenced with consequences for conservation and management actions.