How Certain Are Salmon Recovery Forecasts? A Watershed-scale Sensitivity Analysis

Complex relationships between landscape and aquatic habitat conditions and salmon (Oncorhynchus spp.) populations make science-based management decisions both difficult and essential. Due to a paucity of empirical data, models characterizing these relationships are often used to forecast future conditions. We evaluated uncertainties in a suite of models that predict possible future habitat conditions and fish responses in the Lewis River Basin, Washington, USA. We evaluated sensitivities of predictions to uncertainty in model parameters. Results were sensitive to 60% of model parameters but substantially so (|partial regression coefficients| >0.5) to <10%. We also estimated accuracy of several predictions using field surveys. Observations mostly fell within predicted ranges for riparian shade and fine-sediment deposition, but large woody debris estimates matched only half the time. We provide suggestions to modelers for improving model accountability, and describe how managers can incorporate prediction uncertainty into decision-making, thereby improving the odds of successful salmon habitat recovery.     

The mini mobile environmental monitoring unit: a novel bio-assessment tool

This paper introduces a new bio-assessment tool, the mini-mobile environmental monitoring unit (MMU). The MMU is a portable, lightweight, energy-efficient, miniaturized laboratory that provides a low-flow system for on-site exposure of aquatic animals to local receiving waters in a protected, controllable environment. Prototypes of the MMU were tested twice in week-long studies conducted during the summers of 2008 and 2009, and in a 12-day study in 2010. In 2008, fathead minnows and polar organic chemical integrative samplers (POCIS) were deployed downstream from the Hastings, Nebraska wastewater treatment plant (WWTP), a waterway known to contain estrogenic contaminants in biologically active concentrations. In 2009, minnows and POCIS were deployed downstream, upstream and within the Grand Island, Nebraska WWTP, a site where the estrogenic contaminants had been detected, but were found at levels below those necessary to directly impact fish. In 2010, an advanced prototype was tested at the Sauk Center, Minnesota WWTP to compare its performance with that of traditional fish exposure methods including caged fish and static-renewal laboratory testing of effluent. Results from the prototype illustrate the capabilities of the MMU and offer an inexpensive monitoring tool to integrate the effects of pollutant sources with temporally varying composition and concentration.     

Soil acidification and foliar nutrient status of Ontario's deciduous forest in 1986 and 2005

To assess the impacts of the decline in sulphur (S) deposition over the past 20 years in Ontario, soil chemistry and sugar maple (Acer saccharum Marsh) foliar chemistry were measured at 17 sites in south and central Ontario in 2005 and compared with archived samples collected in 1986. Foliar S concentrations were lower in 2005, reflecting the decline in S deposition whereas foliar N remained unchanged, reflecting the lack of change in N deposition in Ontario. Mineral soil pH, exchangeable base cations were lower in 2005 whereas total S, N and cation exchange capacity (CEC) were unchanged. Foliar concentrations of Ca were positively related to soil Ca levels in the A-horizon and were lower in 2005. Despite evidence of increasing soil acidity and losses of calcium, foliar base cation concentrations at most sites were adequate for sugar maple and forest health in terms of canopy appearance (Decline Index) improved.     

下辽河平原多熟种植农业生态模式知识库研建

本文以下辽河平原为背景,应用专家系统开发工具建立了多熟种植农业生态模式知识库,提出了建立该专家系统知识库的步骤：包括知识获取、知识表达、编码及证实。该专家系统知识库的建立能将有关多熟种植领域的专门知识和领域专家的经验以可接受的方式传递给农业决策者,从而提高农业决策的自动化和科学化。     

The detection of drowsiness using a driver monitoring system

Abstract

Objective: Drowsiness is a major cause of driver impairment leading to crashes and fatalities. Research has established the ability to detect drowsiness with various kinds of sensors. We studied drowsy driving in a high-fidelity driving simulator and evaluated the ability of an automotive production-ready driver monitoring system (DMS) to detect drowsy driving. Additionally, this feature was compared to and combined with signals from vehicle-based sensors.

Methods: The National Advanced Driving Simulator was used to expose drivers to long, monotonous drives. Twenty participants drove for about 4?h in the simulator between 10 p.m. and 2 a.m. They were allowed to use cruise control and traffic was sparse and semirandom, with both slower- and faster-moving vehicles. Observational ratings of drowsiness (ORDs) were used as the ground truth for drowsiness, and several dependent measures were calculated from vehicle and DMS signals. Drowsiness classification models were created that used only vehicle signals, only driver monitoring signals, and a combination of the 2 sources.

Results: The model that used DMS signals performed better than the one that used only vehicle signals; however, the combination of the two performed the best. The models were effective at discriminating low levels of drowsiness from moderate to severe drowsiness; however, they were not effective at telling the difference between moderate and severe levels. A binary model that lumped drowsiness into 2 classes had an area under the receiver operating characteristic (ROC) curve of 0.897.

Conclusions: Blinks and saccades have been shown to be predictive of microsleeps; however, it may be that detection of microsleeps and lane departures occurs too late. Therefore, it is encouraging that the model was able to distinguish mild from moderate drowsy driving. The use of automation may make vehicle-based signals useless for characterizing driver states, providing further motivation for a DMS. Future improvements in impairment detection systems may be expected through a combination of improved hardware, physiological measures from unobtrusive sensors and wearables, and the intelligent integration of environmental variables like time of day and time on task.     

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

As human activities expand beyond national jurisdictions to the high seas, there is an increasing need to consider anthropogenic impacts to species inhabiting these waters. The current scarcity of scientific observations of cetaceans in the high seas impedes the assessment of population‐level impacts of these activities. We developed plausible density estimates to facilitate a quantitative assessment of anthropogenic impacts on cetacean populations in these waters. Our study region extended from a well‐surveyed region within the U.S. Exclusive Economic Zone into a large region of the western North Atlantic sparsely surveyed for cetaceans. We modeled densities of 15 cetacean taxa with available line transect survey data and habitat covariates and extrapolated predictions to sparsely surveyed regions. We formulated models to reduce the extent of extrapolation beyond covariate ranges, and constrained them to model simple and generalizable relationships. To evaluate confidence in the predictions, we mapped where predictions were made outside sampled covariate ranges, examined alternate models, and compared predicted densities with maps of sightings from sources that could not be integrated into our models. Confidence levels in model results depended on the taxon and geographic area and highlighted the need for additional surveying in environmentally distinct areas. With application of necessary caution, our density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep‐sea mining and be used to delineate areas of special biological significance in international waters. Our approach is generally applicable to other marine taxa and geographic regions for which management will be implemented but data are sparse.     

Chemical characteristics of chromophoric dissolved organic matter in rainwater

Proton nuclear magnetic resonance (¹H-NMR), UV absorbance and excitation-emission matrix (EEM) fluorescence spectroscopy were used to define the chemical characteristics of chromophoric dissolved organic matter (CDOM) in whole and C₁₈ extracted rainwater. The average total recovery of fluorescence determined from the sum of extract and filtrate fractions relative to the whole was 86% suggesting that 14% of fluorescent CDOM in rainwater is comprised of very hydrophobic material that cannot be eluted from the column. Half the fluorescence of rainwater was recovered in the filtrate fraction which is important because it suggests that 50% of the chromophoric material present in precipitation is relatively hydrophilic. The average spectral slope coefficient was smaller in extracted samples (16.3 ± 9.0 μm^?1) relative to whole samples (18.9 ± 2.8 μm^?1) suggesting that the extracted material contains larger molecular weight material. Approximately one-third of the total dissolved organic carbon (DOC) in rainwater exists in the extract fraction suggesting that a large percentage of the uncharacterized DOC in rainwater can be accounted for by these hydrophobic macromolecular species. The fluorescence of extracted samples is strongly correlated with total NMR integration and is most sensitive to aromatic protons suggesting that molecules in this region are the most important in controlling the optical properties of rainwater. The lower removal efficiency of CDOM in rainwater relative to surface waters or the water-soluble fraction of aerosols during solid phase extraction (SPE) suggests that rainwater contains significantly more hydrophilic chromophoric compounds which are compositionally different than found in these other aquatic matrices.     

The toxicology of climate change: Environmental contaminants in a warming world

Climate change induced by anthropogenic warming of the earth's atmosphere is a daunting problem. This review examines one of the consequences of climate change that has only recently attracted attention: namely, the effects of climate change on the environmental distribution and toxicity of chemical pollutants. A review was undertaken of the scientific literature (original research articles, reviews, government and intergovernmental reports) focusing on the interactions of toxicants with the environmental parameters, temperature, precipitation, and salinity, as altered by climate change. Three broad classes of chemical toxicants of global significance were the focus: air pollutants, persistent organic pollutants (POPs), including some organochlorine pesticides, and other classes of pesticides. Generally, increases in temperature will enhance the toxicity of contaminants and increase concentrations of tropospheric ozone regionally, but will also likely increase rates of chemical degradation. While further research is needed, climate change coupled with air pollutant exposures may have potentially serious adverse consequences for human health in urban and polluted regions. Climate change producing alterations in: food webs, lipid dynamics, ice and snow melt, and organic carbon cycling could result in increased POP levels in water, soil, and biota. There is also compelling evidence that increasing temperatures could be deleterious to pollutant-exposed wildlife. For example, elevated water temperatures may alter the biotransformation of contaminants to more bioactive metabolites and impair homeostasis. The complex interactions between climate change and pollutants may be particularly problematic for species living at the edge of their physiological tolerance range where acclimation capacity may be limited. In addition to temperature increases, regional precipitation patterns are projected to be altered with climate change. Regions subject to decreases in precipitation may experience enhanced volatilization of POPs and pesticides to the atmosphere. Reduced precipitation will also increase air pollution in urbanized regions resulting in negative health effects, which may be exacerbated by temperature increases. Regions subject to increased precipitation will have lower levels of air pollution, but will likely experience enhanced surface deposition of airborne POPs and increased run-off of pesticides. Moreover, increases in the intensity and frequency of storm events linked to climate change could lead to more severe episodes of chemical contamination of water bodies and surrounding watersheds. Changes in salinity may affect aquatic organisms as an independent stressor as well as by altering the bioavailability and in some instances increasing the toxicity of chemicals. A paramount issue will be to identify species and populations especially vulnerable to climate–pollutant interactions, in the context of the many other physical, chemical, and biological stressors that will be altered with climate change. Moreover, it will be important to predict tipping points that might trigger or accelerate synergistic interactions between climate change and contaminant exposures.     

Windsor, Ontario exposure assessment study: design and methods validation of personal, indoor, and outdoor air pollution monitoring

The Windsor, Ontario Exposure Assessment Study evaluated the contribution of ambient air pollutants to personal and indoor exposures of adults and asthmatic children living in Windsor, Ontario, Canada. In addition, the role of personal, indoor, and outdoor air pollution exposures upon asthmatic children's respiratory health was assessed. Several active and passive sampling methods were applied, or adapted, for personal, indoor, and outdoor residential monitoring of nitrogen dioxide, volatile organic compounds, particulate matter (PM; PM-2.5 pm [PM2.5] and < or =10 microm [PM10] in aerodynamic diameter), elemental carbon, ultrafine particles, ozone, air exchange rates, allergens in settled dust, and particulate-associated metals. Participants completed five consecutive days of monitoring during the winter and summer of 2005 and 2006. During 2006, in addition to undertaking the air pollution measurements, asthmatic children completed respiratory health measurements (including peak flow meter tests and exhaled breath condensate) and tracked respiratory symptoms in a diary. Extensive quality assurance and quality control steps were implemented, including the collocation of instruments at the National Air Pollution Surveillance site operated by Environment Canada and at the Michigan Department of Environmental Quality site in Allen Park, Detroit, MI. During field sampling, duplicate and blank samples were also completed and these data are reported. In total, 50 adults and 51 asthmatic children were recruited to participate, resulting in 922 participant days of data. When comparing the methods used in the study with standard reference methods, field blanks were low and bias was acceptable, with most methods being within 20% of reference methods. Duplicates were typically within less than 10% of each other, indicating that study results can be used with confidence. This paper covers study design, recruitment, methodology, time activity diary, surveys, and quality assurance and control results for the different methods used.