Is selenium affecting body condition and reproduction in boreal breeding scaup, scoters, and ring-necked ducks?

Elevated levels of selenium (Se) have been detected in wintering and spring-staging lesser scaup. Here, we compared spring scaup Se and mercury (Hg) levels to those of ring-necked ducks and white-winged scoters, species exhibiting increasing and decreasing boreal populations, respectively. Mercury concentrations were low in all three species. Geometric mean (95%CI) liver Se concentrations were 6.2 (5.5-7.0), 4.6 (4.0-5.4), and 32.6 (28.4-37.3)mg/kg dry weight (dw) in scaup, ringnecks and scoters, respectively. Only scoter livers (66%) were above 33 mg/kgdw Se. Scaup and ringneck Se levels were unrelated to breeding status or lipid and protein levels; breeding scoters and females with greater lipid mass had higher Se than non-breeders. Egg and follicle concentrations in scaup and scoters were normal (mean [95%CI]=2.3 [1.9-2.6] and 2.4 [2.1-2.7]mg/kgdw, respectively). Overall, we found no support for a relationship between selenium and boreal scaup and scoter declines, and discuss current Se threshold concentrations.     

The Impact of Mobile Data Terminal Use on Posture and Low-Back Discomfort When Combined With Simulated Prolonged Driving in Police Cruisers

The introduction of mobile computing within a constrained vehicle environment has led to changes in the task demands of occupational groups such as professional drivers and law enforcement officers. The purpose of this study was to examine how mobile data terminal (MDT) use interacts with prolonged driving to induce postural changes or low-back discomfort. Eighteen participants (9 male, 9 female) completed two 120-min simulated driving sessions. Time-varying lumbar spine and pelvis postures, seat pan interface pressures and ratings of perceived discomfort were recorded at 15-min intervals. The introduction of a computer interface decreased pelvic posterior rotation by an average of 15° with respect to upright standing and increased peak average discomfort in the neck (5.9 mm), left shoulder (6.8 mm), midback (10.9 mm), low back (10.6 mm) and pelvis (11.5 mm) compared to driving alone. The incorporation of mobile computing warrants consideration in the design of vehicle work environments.     

Field Measurements of Particulate Matter Emissions,Carbon Monoxide,and Exhaust Opacity from Heavy-Duty Diesel Vehicles

ABSTRACT

Diesel particulate matter (PM) is a significant contributor to ambient air PM₁₀ and PM_2.5 particulate levels. In addition, recent literature argues that submicron diesel PM is a pulmonary health hazard. There is difficulty in attributing PM emissions to specific operating modes of a diesel engine, although it is acknowledged that PM production rises dramatically with load and that high PM emissions occur during rapid load increases on turbocharged engines. Snap-acceleration tests generally identify PM associated with rapid transient operating conditions, but not with high load. To quantify the origin of PM during transient engine operation, continuous opacity measurements have been made using a Wager 650CP full flow exhaust opacity meter. Opacity measurements were taken while the vehicles were operated over transient driving cycles on a chassis dynamometer using the West Virginia University (WVU) Transportable Heavy Duty Vehicle Emissions Testing Laboratories. Data were gathered from Detroit Diesel, Cummins, Caterpillar, and Navistar heavy-duty (HD) diesel engines. Driving cycles used were the Central Business District (CBD) cycle, the WVU 5-Peak Truck cycle, the WVU 5-Mile route, and the New York City Bus (NYCB) cycle. Continuous opacity measurements, integrated over the entire driving cycle, were compared to total integrated PM mass. In addition, the truck was subjected to repeat snap-acceleration tests, and PM was collected for a composite of these snap-acceleration tests. Additional data were obtained from a fleet of 1996 New Flyer buses in Flint, MI, equipped with electronically controlled Detroit Diesel Series 50 engines. Again, continuous opacity, regulated gaseous emissions, and PM were measured. The relationship between continuous carbon monoxide (CO) emissions and continuous opacity was noted. In identifying the level of PM emissions in transient diesel engine operation, it is suggested that CO emissions may prove to be a useful indicator and may be used to apportion total PM on a continuous basis over a transient cycle. The projected continuous PM data will prove valuable in future mobile source inventory prediction.     

重型机动车实际排放特性与影响因素的实测研究

利用美国Sensors公司生产的SEMTECHD车载排放测试仪在上海随机选择了7辆重型柴油车开展实际道路的排放测试,该实验累积测试道路长度为186km,共取得29090个逐秒的有效工况点数据,其中城市主干道12979个,次干道12368个,快速干道3743个.给出了车辆在不同道路上的工况点分布,分析了速度、加速度对燃油消耗、尾气排放的影响.测试结果表明,在选定的城市道路上,车流的平均怠速工况比为17%,加速工况比23.6%,等速工况比为31.0%,减速工况比为28.5%.被测车辆的CO、THC、NOx平均排放因子分别为(4.41±2.46)g·km-1、(1.77±1.17)g·km-1和(6.96±1.93)g·km-1,车辆排放状况因车速、加速度等因素而不同.测试结果基本反映了目前上海道路的交通状况和柴油卡车的排放现状,同时也说明过低的车速和频繁加减速是加重机动车污染的重要原因.     

A new context-based approach to assess marine mammal behavioral responses to anthropogenic sounds

Acute effects of anthropogenic sounds on marine mammals, such as from military sonars, energy development, and offshore construction, have received considerable international attention from scientists, regulators, and industry. Moreover, there has been increasing recognition and concern about the potential chronic effects of human activities (e.g., shipping). It has been demonstrated that increases in human activity and background noise can alter habitats of marine animals and potentially mask communications for species that rely on sound to mate, feed, avoid predators, and navigate. Without exception, regulatory agencies required to assess and manage the effects of noise on marine mammals have addressed only the acute effects of noise on hearing and behavior. Furthermore, they have relied on a single exposure metric to assess acute effects: the absolute sound level received by the animal. There is compelling evidence that factors other than received sound level, including the activity state of animals exposed to different sounds, the nature and novelty of a sound, and spatial relations between sound source and receiving animals (i.e., the exposure context) strongly affect the probability of a behavioral response. A more comprehensive assessment method is needed that accounts for the fact that multiple contextual factors can affect how animals respond to both acute and chronic noise. We propose a three-part approach. The first includes measurement and evaluation of context-based behavioral responses of marine mammals exposed to various sounds. The second includes new assessment metrics that emphasize relative sound levels (i.e., ratio of signal to background noise and level above hearing threshold). The third considers the effects of chronic and acute noise exposure. All three aspects of sound exposure (context, relative sound level, and chronic noise) mediate behavioral response, and we suggest they be integrated into ecosystem-level management and the spatial planning of human offshore activities.     

A novel statistical method for classifying habitat generalists and specialists

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.     

APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.