A model for energetics and bioaccumulation in marine mammals with applications to the right whale.

We present a dynamic energy budget (DEB) model for marine mammals, coupled with a pharmacokinetic model of a lipophilic persistent toxicant. Inputs to the model are energy availability and lipid-normalized toxicant concentration in the environment. The model predicts individual growth, reproduction, bioaccumulation, and transfer of energy and toxicant from mothers to their young. We estimated all model parameters for the right whale; with these parameters, reduction in energy availability increases the age at first parturition, increases intervals between reproductive events, reduces the organisms' ability to buffer seasonal fluctuations, and increases its susceptibility to temporal shifts in the seasonal peak of energy availability. Reduction in energy intake increases bioaccumulation and the amount of toxicant transferred from mother to each offspring. With high energy availability, the toxicant load of offspring decreases with birth order. Contrary to expectations, this ordering may be reversed with lower energy availability. Although demonstrated with parameters for the right whale, these relationships between energy intake and energetics and pharmacokinetics of organisms are likely to be much more general. Results specific to right whales include energy assimilation estimates for the North Atlantic and southern right whale, influences of history of energy availability on reproduction, and a relationship between ages at first parturition and calving intervals. Our model provides a platform for further analyses of both individual and population responses of marine mammals to pollution, and to changes in energy availability, including those likely to arise through climate change.     

On the Estimation of Dispersal Kernels from Individual Mark-Recapture Data

We present a new method for estimating a distribution of dispersal displacements (a dispersal kernel) from mark-recapture data. One conventional method of calculating the dispersal kernel assumes that the distribution of displacements are Gaussian (e.g. resulting from a diffusion process) and that individuals remain within sampled areas. The first assumption prohibits an analysis of dispersal data that do not exhibit the Gaussian distribution (a common situation); the second assumption leads to underestimation of dispersal distance because individuals that disperse outside of sampling areas are never recaptured. Our method eliminates these two assumptions. In addition, the method can also accommodate mortality during a sampling period. This new method uses integrodifference equations to express the probability of spatial mark-recapture data; associated dispersal, survival, and recapture parameters are then estimated using a maximum likelihood method. We examined the accuracy of the estimators by applying the method to simulated data sets. Our method suggests designs for future mark-recapture experiments. Received: January 2004 / Revised: July 2005     

Outdoor/Indoor/Personal ozone exposures of children in Nashville, Tennessee

An ozone (O3) exposure study was conducted in Nashville, TN, using passive O3 samplers to measure six weekly outdoor, indoor, and personal O3 exposure estimates for a group of 10- to 12-yr-old elementary school children. Thirty-six children from two Nashville area communities (Inglewood and Hendersonville) participated in the O3 sampling program, and 99 children provided additional time-activity information by telephone interview. By design, this study coincided with the 1994 Nashville/Middle Tennessee Ozone Study conducted by the Southern Oxidants Study, which provided enhanced continuous ambient O3 monitoring across the Nashville area. Passive sampling estimated weekly average outdoor O3 concentrations from 0.011 to 0.O30 ppm in the urban Inglewood community and from 0.015 to 0.042 ppm in suburban Hendersonville. The maximum 1- and 8-hr ambient concentrations encountered at the Hendersonville continuous monitor exceeded the levels of the 1- and 8-hr metrics for the O3 National Ambient Air Quality Standard. Weekly average personal O3 exposures ranged from 0.0013 to 0.0064 ppm (7-31% of outdoor levels). Personal O3 exposures reflected the proportional amount of time spent in indoor and outdoor environments. Air-conditioned homes displayed very low indoor O3 concentrations, and homes using open windows and fans for ventilation displayed much higher concentrations.     

Climate change threatens polar bear populations: a stochastic demographic analysis

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in lambda in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log lambdas, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log lambdas approximately - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act.     

Field method comparison between passive air samplers and continuous monitors for Vocs and NO2 in El Paso, Texas

This study evaluates the performance of Model 3300 Ogawa Passive Nitrogen Dioxide (NO2) Samplers and 3M 3520 Organic Vapor Monitors (OVMs) by comparing integrated passive sampling concentrations to averaged hourly NO2 and volatile organic compound (VOC) measurements at two sites in El Paso, TX. Sampling periods were three time intervals (3-day weekend, 4-day weekday, and 7-day weekly) for three consecutive weeks. OVM concentrations were corrected for ambient pressure to account for higher elevation. Precise results (< 5% relative standard deviation, RSD) were found for NO2 measurements from collocated Ogawa samplers. Reproducibility was lower from duplicate OVMs for BTEX (benzene, toluene, ethylbenzene, and xylene isomers) VOCs (> or = 77% RSD for 2-day samples) with better precision for longer sampling periods. Comparison of Ogawa NO2 samplers with chemiluminescence measurements averaged over the same time period suggested potential calibration problems with the chemiluminescence analyzer. For BTEX species, generally good agreement was obtained between OVMs and automated-gas chromatograph (auto-GC) measurements. The OVMs successfully tracked increasing levels of VOCs recorded by the auto-GCs. However, except for toluene, OVM BTEX measurements generally exceeded their continuous counterparts with a mean bias of 5-10%. Although interpretation of the study results was limited due to small sample sizes, diffusion barrier influences caused by shelters that housed OVMs and differences in sampling heights between OVMs and auto-GC inlet may explain the overestimation.     

Social organization of female sperm whales and their offspring: constant companions and casual acquaintances

Summary Associations among female sperm whales, Physeter macrocephalus, and their dependent offspring, off the Galapagos Islands were studied between 1985 and 1989. The whales were found in groups containing about 23 individuals, with each individual having approximately 12 constant (over years) companions. These permanent units associated with one another for periods of 6.5 days, although the rate and duration of these associations seemed to vary between years, perhaps because of differences in the food supply. The principal function of the closed units may be care of the offspring, and units in the same general area may derive benefit from feeding in a coordinated manner.Offprint requests to: H. Whitehead     

Photocatalytic soot degradation under UV and visible light

Environmental Science and Pollution Research - Particulate matter is one of the most persistent global air pollutants that is causing health problems, climate disturbance and building...     

Analysis of coupled model uncertainties in source-to-dose modeling of human exposures to ambient air pollution: A PM2.5 case study

Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM_2.5) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3–4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.