Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

Non-lethal assessment of freshwater mussel physiological response to changes in environmental factors

USGS Publications Warehouse

Fritts, Andrea K.; Peterson, James T.; Wisniewski, Jason M.; Bringolf, Robert B.

2015-01-01

The development of effective nonlethal biomonitoring techniques is imperative for the preservation of imperiled freshwater mussel populations. Changes in hemolymph chemistry profiles and tissue glycogen are potential biomarkers for nonlethally monitoring stress in mussels. We sampled three species in the Flint River Basin over 2 years to evaluate how these hemolymph and tissue biomarkers responded to environmental changes. We used hierarchical linear models to evaluate the relationships between variation in the biomarkers and environmental factors and found that the responses of the hemolymph and tissue parameters were strongly related to stream discharge. Shifts in alanine aminotransferase and glycogen showed the largest relations with discharge at the time of sampling, while magnesium levels were most explained by the discharge for 5 days prior to sampling. Aspartate aminotransferase, bicarbonate, and calcium showed the strongest relations with mean discharge for 15 days prior to sampling. The modeling results indicated that biomarker responses varied substantially among individuals of different size, sex, and species and illustrated the value of hierarchical modeling techniques to account for the inherent complexity of aquatic ecosystems.

Assessing residential exposure to urban noise using environmental models: does the size of the local living neighborhood matter?

PubMed

Tenailleau, Quentin M; Bernard, Nadine; Pujol, Sophie; Houot, Hélène; Joly, Daniel; Mauny, Frédéric

2015-01-01

Environmental epidemiological studies rely on the quantification of the exposure level in a surface defined as the subject's exposure area. For residential exposure, this area is often the subject's neighborhood. However, the variability of the size and nature of the neighborhoods makes comparison of the findings across studies difficult. This article examines the impact of the neighborhood's definition on environmental noise exposure levels obtained from four commonly used sampling techniques: address point, façade, buffers, and official zoning. A high-definition noise model, built on a middle-sized French city, has been used to estimate LAeq,24 h exposure in the vicinity of 10,825 residential buildings. Twelve noise exposure indicators have been used to assess inhabitants' exposure. Influence of urban environmental factors was analyzed using multilevel modeling. When the sampled area increases, the average exposure increases (+3.9 dB), whereas the SD decreases (-1.6 dB) (P<0.01). Most of the indicators differ statistically. When comparing indicators from the 50-m and 400-m radius buffers, the assigned LAeq,24 h level varies across buildings from -9.4 to +22.3 dB. This variation is influenced by urban environmental characteristics (P<0.01). On the basis of this study's findings, sampling technique, neighborhood size, and environmental composition should be carefully considered in further exposure studies.

Human and bovine viruses and bacteria at three great lakes beaches: Environmental variable associations and health risk

USDA-ARS?s Scientific Manuscript database

Waterborne pathogens were detected in 96% of samples collected at three Lake Michigan beaches during the summer of 2010. Linear regression models were developed to explore environmental factors that may be influential for pathogen prevalence. Simulation of pathogen concentration using these models, ...

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Assessing the Application of a Geographic Presence-Only Model for Land Suitability Mapping

PubMed Central

Heumann, Benjamin W.; Walsh, Stephen J.; McDaniel, Phillip M.

2011-01-01

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1,300 sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the Maxent model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results. PMID:21860606

Estimating juvenile Chinook salmon (Oncorhynchus tshawytscha) abundance from beach seine data collected in the Sacramento–San Joaquin Delta and San Francisco Bay, California

USGS Publications Warehouse

Perry, Russell W.; Kirsch, Joseph E.; Hendrix, A. Noble

2016-06-17

Resource managers rely on abundance or density metrics derived from beach seine surveys to make vital decisions that affect fish population dynamics and assemblage structure. However, abundance and density metrics may be biased by imperfect capture and lack of geographic closure during sampling. Currently, there is considerable uncertainty about the capture efficiency of juvenile Chinook salmon (Oncorhynchus tshawytscha) by beach seines. Heterogeneity in capture can occur through unrealistic assumptions of closure and from variation in the probability of capture caused by environmental conditions. We evaluated the assumptions of closure and the influence of environmental conditions on capture efficiency and abundance estimates of Chinook salmon from beach seining within the Sacramento–San Joaquin Delta and the San Francisco Bay. Beach seine capture efficiency was measured using a stratified random sampling design combined with open and closed replicate depletion sampling. A total of 56 samples were collected during the spring of 2014. To assess variability in capture probability and the absolute abundance of juvenile Chinook salmon, beach seine capture efficiency data were fitted to the paired depletion design using modified N-mixture models. These models allowed us to explicitly test the closure assumption and estimate environmental effects on the probability of capture. We determined that our updated method allowing for lack of closure between depletion samples drastically outperformed traditional data analysis that assumes closure among replicate samples. The best-fit model (lowest-valued Akaike Information Criterion model) included the probability of fish being available for capture (relaxed closure assumption), capture probability modeled as a function of water velocity and percent coverage of fine sediment, and abundance modeled as a function of sample area, temperature, and water velocity. Given that beach seining is a ubiquitous sampling technique for many species, our improved sampling design and analysis could provide significant improvements in density and abundance estimation.

A preliminary investigation of the environmental impact of a thermal power plant in relation to PCB contamination.

PubMed

Gedik, Kadir; Imamoglu, Ipek

2011-07-01

The most significant application of polychlorinated biphenyls (PCBs) is in transformers and capacitors. Therefore, power plants are important suspected sources for entry of PCBs into the environment. In this context, the levels and distribution of PCBs in sediment, soil, ash, and sludge samples were investigated around Seyitömer thermal power plant, Kütahya, Turkey. Moreover, identity and contribution of PCB mixtures were predicted using the chemical mass balance (CMB) receptor model. United States Environmental Protection Agency methods were applied during sample preparation, extraction (3540C), cleanup (3660B, 3665A, 3630C), and analysis (8082A). ΣPCB concentrations in the region ranged from not detected to 385 ng/g dry weight, with relatively higher contamination in sediments in comparison to soil, sludge, and ash samples collected from around the power plant. Congener profiles of the sediment and soil samples show penta-, hexa-, and hepta-chlorobiphenyls as the major homolog groups. The results from the CMB model indicate that PCB contamination is largely due to Clophen A60/A40 and Aroclor 1254/1254(late)/1260 release into the sediment and sludge samples around the thermal power plant. Since there are no other sources of PCBs in the region and the identity of PCB sources estimated by the CMB model mirrors PCB mixtures contained in transformers formerly used in the plant, the environmental contamination observed especially in sediments is attributed to the power plant. Release of PCBs over time, as indicated by the significant concentrations observed even in surface samples, emphasizes the importance of the need for better environmental management.

Estimates of potential childhood lead exposure from contaminated soil using the US EPA IEUBK Model in Sydney, Australia.

PubMed

Laidlaw, Mark A S; Mohmmad, Shaike M; Gulson, Brian L; Taylor, Mark P; Kristensen, Louise J; Birch, Gavin

2017-07-01

Surface soils in portions of the Sydney (New South Wales, Australia) urban area are contaminated with lead (Pb) primarily from past use of Pb in gasoline, the deterioration of exterior lead-based paints, and industrial activities. Surface soil samples (n=341) were collected from a depth of 0-2.5cm at a density of approximately one sample per square kilometre within the Sydney estuary catchment and analysed for lead. The bioaccessibility of soil Pb was analysed in 18 samples. The blood lead level (BLL) of a hypothetical 24 month old child was predicted at soil sampling sites in residential and open land use using the United States Environmental Protection Agency (US EPA) Integrated Exposure Uptake and Biokinetic (IEUBK) model. Other environmental exposures used the Australian National Environmental Protection Measure (NEPM) default values. The IEUBK model predicted a geometric mean BLL of 2.0±2.1µg/dL using measured soil lead bioavailability measurements (bioavailability =34%) and 2.4±2.8µg/dL using the Australian NEPM default assumption (bioavailability =50%). Assuming children were present and residing at the sampling locations, the IEUBK model incorporating soil Pb bioavailability predicted that 5.6% of the children at the sampling locations could potentially have BLLs exceeding 5µg/dL and 2.1% potentially could have BLLs exceeding 10µg/dL. These estimations are consistent with BLLs previously measured in children in Sydney. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling the Sensitivity of Field Surveys for Detection of Environmental DNA (eDNA)

PubMed Central

Schultz, Martin T.; Lance, Richard F.

2015-01-01

The environmental DNA (eDNA) method is the practice of collecting environmental samples and analyzing them for the presence of a genetic marker specific to a target species. Little is known about the sensitivity of the eDNA method. Sensitivity is the probability that the target marker will be detected if it is present in the water body. Methods and tools are needed to assess the sensitivity of sampling protocols, design eDNA surveys, and interpret survey results. In this study, the sensitivity of the eDNA method is modeled as a function of ambient target marker concentration. The model accounts for five steps of sample collection and analysis, including: 1) collection of a filtered water sample from the source; 2) extraction of DNA from the filter and isolation in a purified elution; 3) removal of aliquots from the elution for use in the polymerase chain reaction (PCR) assay; 4) PCR; and 5) genetic sequencing. The model is applicable to any target species. For demonstration purposes, the model is parameterized for bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix) assuming sampling protocols used in the Chicago Area Waterway System (CAWS). Simulation results show that eDNA surveys have a high false negative rate at low concentrations of the genetic marker. This is attributed to processing of water samples and division of the extraction elution in preparation for the PCR assay. Increases in field survey sensitivity can be achieved by increasing sample volume, sample number, and PCR replicates. Increasing sample volume yields the greatest increase in sensitivity. It is recommended that investigators estimate and communicate the sensitivity of eDNA surveys to help facilitate interpretation of eDNA survey results. In the absence of such information, it is difficult to evaluate the results of surveys in which no water samples test positive for the target marker. It is also recommended that invasive species managers articulate concentration-based sensitivity objectives for eDNA surveys. In the absence of such information, it is difficult to design appropriate sampling protocols. The model provides insights into how sampling protocols can be designed or modified to achieve these sensitivity objectives. PMID:26509674

Modeling the Sensitivity of Field Surveys for Detection of Environmental DNA (eDNA).

PubMed

Schultz, Martin T; Lance, Richard F

2015-01-01

The environmental DNA (eDNA) method is the practice of collecting environmental samples and analyzing them for the presence of a genetic marker specific to a target species. Little is known about the sensitivity of the eDNA method. Sensitivity is the probability that the target marker will be detected if it is present in the water body. Methods and tools are needed to assess the sensitivity of sampling protocols, design eDNA surveys, and interpret survey results. In this study, the sensitivity of the eDNA method is modeled as a function of ambient target marker concentration. The model accounts for five steps of sample collection and analysis, including: 1) collection of a filtered water sample from the source; 2) extraction of DNA from the filter and isolation in a purified elution; 3) removal of aliquots from the elution for use in the polymerase chain reaction (PCR) assay; 4) PCR; and 5) genetic sequencing. The model is applicable to any target species. For demonstration purposes, the model is parameterized for bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix) assuming sampling protocols used in the Chicago Area Waterway System (CAWS). Simulation results show that eDNA surveys have a high false negative rate at low concentrations of the genetic marker. This is attributed to processing of water samples and division of the extraction elution in preparation for the PCR assay. Increases in field survey sensitivity can be achieved by increasing sample volume, sample number, and PCR replicates. Increasing sample volume yields the greatest increase in sensitivity. It is recommended that investigators estimate and communicate the sensitivity of eDNA surveys to help facilitate interpretation of eDNA survey results. In the absence of such information, it is difficult to evaluate the results of surveys in which no water samples test positive for the target marker. It is also recommended that invasive species managers articulate concentration-based sensitivity objectives for eDNA surveys. In the absence of such information, it is difficult to design appropriate sampling protocols. The model provides insights into how sampling protocols can be designed or modified to achieve these sensitivity objectives.

Using a Hydrological Model to Determine Environmentally Safer Windows for Herbicide Application

Treesearch

J.L. Michael; M.C. Smith; W.G. Knisel; D.G. Neary; W.P. Fowler; D.J. Turton

1996-01-01

A modification of the GLEAMS model was used to determine application windows which would optimise efficacy and environmental safety for herbicide application to a forest site. Herbicide/soil partition coefficients were determined using soil samples collected from the study site for two herbicides (imazapyr, Koc=46, triclopyr ester, K

Dispositional and Environmental Predictors of the Development of Internalizing Problems in Childhood: Testing a Multilevel Model.

PubMed

Hastings, Paul D; Helm, Jonathan; Mills, Rosemary S L; Serbin, Lisa A; Stack, Dale M; Schwartzman, Alex E

2015-07-01

This investigation evaluated a multilevel model of dispositional and environmental factors contributing to the development of internalizing problems from preschool-age to school-age. In a sample of 375 families (185 daughters, 190 sons) drawn from three independent samples, preschoolers' behavioral inhibition, cortisol and gender were examined as moderators of the links between mothers' negative parenting behavior, negative emotional characteristics, and socioeconomic status when children were 3.95 years, and their internalizing problems when they were 8.34 years. Children's dispositional characteristics moderated all associations between these environmental factors and mother-reported internalizing problems in patterns that were consistent with either diathesis-stress or differential-susceptibility models of individual-environment interaction, and with gender models of developmental psychopathology. Greater inhibition and lower socioeconomic status were directly predictive of more teacher reported internalizing problems. These findings highlight the importance of using multilevel models within a bioecological framework to understand the complex pathways through which internalizing difficulties develop.

A clustering algorithm for sample data based on environmental pollution characteristics

NASA Astrophysics Data System (ADS)

Chen, Mei; Wang, Pengfei; Chen, Qiang; Wu, Jiadong; Chen, Xiaoyun

2015-04-01

Environmental pollution has become an issue of serious international concern in recent years. Among the receptor-oriented pollution models, CMB, PMF, UNMIX, and PCA are widely used as source apportionment models. To improve the accuracy of source apportionment and classify the sample data for these models, this study proposes an easy-to-use, high-dimensional EPC algorithm that not only organizes all of the sample data into different groups according to the similarities in pollution characteristics such as pollution sources and concentrations but also simultaneously detects outliers. The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and finally modifying the clusters using a method similar to k-Means. The validity and accuracy of the algorithm are tested using both real and synthetic datasets, which makes the EPC algorithm practical and effective for appropriately classifying sample data for source apportionment models and helpful for better understanding and interpreting the sources of pollution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Streets, W.E.

As the need for rapid and more accurate determinations of gamma-emitting radionuclides in environmental and mixed waste samples grows, there is continued interest in the development of theoretical tools to eliminate the need for some laboratory analyses and to enhance the quality of information from necessary analyses. In gamma spectrometry the use of theoretical self-absorption coefficients (SACs) can eliminate the need to determine the SAC empirically by counting a known source through each sample. This empirical approach requires extra counting time and introduces another source of counting error, which must be included in the calculation of results. The empirical determinationmore » of SACs is routinely used when the nuclides of interest are specified; theoretical determination of the SAC can enhance the information for the analysis of true unknowns, where there may be no prior knowledge about radionuclides present in a sample. Determination of an exact SAC does require knowledge about the total composition of a sample. In support of the Department of Energy`s (DOE) Environmental Survey Program, the Analytical Chemistry Laboratory (ACL) at Argonne National Laboratory developed theoretical self-absorption models to estimate SACs for the determination of non-specified radionuclides in samples of unknown, widely-varying, compositions. Subsequently, another SAC model, in a different counting geometry and for specified nuclides, was developed for another application. These two models are now used routinely for the determination of gamma-emitting radionuclides in a wide variety of environmental and mixed waste samples.« less

Application of self-organizing maps for PCDD/F pattern recognition of environmental and biological samples to evaluate the impact of a hazardous waste incinerator.

PubMed

Mari, Montse; Nadal, Martí; Schuhmacher, Marta; Domingo, José L

2010-04-15

Kohonen's self-organizing maps (SOM) is one of the most popular artificial neural network models. In this study, SOM were used to assess the potential relationships between polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) congener profiles in environmental (soil, herbage, and ambient air) and biological (plasma, adipose tissue, and breast milk) samples, and the emissions of a hazardous waste incinerator (HWI) in Spain. The visual examination of PCDD/F congener profiles of most environmental and biological samples did not allow finding out any differences between monitors. However, the global SOM analysis of environmental and biological samples showed that the weight of the PCDD/F stack emissions of the HWI on the environmental burden and on the exposure of the individuals living in the surroundings was not significant in relation to the background levels. The results confirmed the small influence of the HWI emissions of PCDD/Fs on the environment and the population living in the neighborhood.

Extended Twin Study of Alcohol Use in Virginia and Australia.

PubMed

Verhulst, Brad; Neale, Michael C; Eaves, Lindon J; Medland, Sarah E; Heath, Andrew C; Martin, Nicholas G; Maes, Hermine H

2018-06-01

Drinking alcohol is a normal behavior in many societies, and prior studies have demonstrated it has both genetic and environmental sources of variation. Using two very large samples of twins and their first-degree relatives (Australia ≈ 20,000 individuals from 8,019 families; Virginia ≈ 23,000 from 6,042 families), we examine whether there are differences: (1) in the genetic and environmental factors that influence four interrelated drinking behaviors (quantity, frequency, age of initiation, and number of drinks in the last week), (2) between the twin-only design and the extended twin design, and (3) the Australian and Virginia samples. We find that while drinking behaviors are interrelated, there are substantial differences in the genetic and environmental architectures across phenotypes. Specifically, drinking quantity, frequency, and number of drinks in the past week have large broad genetic variance components, and smaller but significant environmental variance components, while age of onset is driven exclusively by environmental factors. Further, the twin-only design and the extended twin design come to similar conclusions regarding broad-sense heritability and environmental transmission, but the extended twin models provide a more nuanced perspective. Finally, we find a high level of similarity between the Australian and Virginian samples, especially for the genetic factors. The observed differences, when present, tend to be at the environmental level. Implications for the extended twin model and future directions are discussed.

Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods

DOE PAGES

Liu, Peigui; Elshall, Ahmed S.; Ye, Ming; ...

2016-02-05

Evaluating marginal likelihood is the most critical and computationally expensive task, when conducting Bayesian model averaging to quantify parametric and model uncertainties. The evaluation is commonly done by using Laplace approximations to evaluate semianalytical expressions of the marginal likelihood or by using Monte Carlo (MC) methods to evaluate arithmetic or harmonic mean of a joint likelihood function. This study introduces a new MC method, i.e., thermodynamic integration, which has not been attempted in environmental modeling. Instead of using samples only from prior parameter space (as in arithmetic mean evaluation) or posterior parameter space (as in harmonic mean evaluation), the thermodynamicmore » integration method uses samples generated gradually from the prior to posterior parameter space. This is done through a path sampling that conducts Markov chain Monte Carlo simulation with different power coefficient values applied to the joint likelihood function. The thermodynamic integration method is evaluated using three analytical functions by comparing the method with two variants of the Laplace approximation method and three MC methods, including the nested sampling method that is recently introduced into environmental modeling. The thermodynamic integration method outperforms the other methods in terms of their accuracy, convergence, and consistency. The thermodynamic integration method is also applied to a synthetic case of groundwater modeling with four alternative models. The application shows that model probabilities obtained using the thermodynamic integration method improves predictive performance of Bayesian model averaging. As a result, the thermodynamic integration method is mathematically rigorous, and its MC implementation is computationally general for a wide range of environmental problems.« less

Predicting risk of trace element pollution from municipal roads using site-specific soil samples and remotely sensed data.

PubMed

Reeves, Mari Kathryn; Perdue, Margaret; Munk, Lee Ann; Hagedorn, Birgit

2018-07-15

Studies of environmental processes exhibit spatial variation within data sets. The ability to derive predictions of risk from field data is a critical path forward in understanding the data and applying the information to land and resource management. Thanks to recent advances in predictive modeling, open source software, and computing, the power to do this is within grasp. This article provides an example of how we predicted relative trace element pollution risk from roads across a region by combining site specific trace element data in soils with regional land cover and planning information in a predictive model framework. In the Kenai Peninsula of Alaska, we sampled 36 sites (191 soil samples) adjacent to roads for trace elements. We then combined this site specific data with freely-available land cover and urban planning data to derive a predictive model of landscape scale environmental risk. We used six different model algorithms to analyze the dataset, comparing these in terms of their predictive abilities and the variables identified as important. Based on comparable predictive abilities (mean R 2 from 30 to 35% and mean root mean square error from 65 to 68%), we averaged all six model outputs to predict relative levels of trace element deposition in soils-given the road surface, traffic volume, sample distance from the road, land cover category, and impervious surface percentage. Mapped predictions of environmental risk from toxic trace element pollution can show land managers and transportation planners where to prioritize road renewal or maintenance by each road segment's relative environmental and human health risk. Published by Elsevier B.V.

The second Southern African Bird Atlas Project: Causes and consequences of geographical sampling bias.

PubMed

Hugo, Sanet; Altwegg, Res

2017-09-01

Using the Southern African Bird Atlas Project (SABAP2) as a case study, we examine the possible determinants of spatial bias in volunteer sampling effort and how well such biased data represent environmental gradients across the area covered by the atlas. For each province in South Africa, we used generalized linear mixed models to determine the combination of variables that explain spatial variation in sampling effort (number of visits per 5' × 5' grid cell, or "pentad"). The explanatory variables were distance to major road and exceptional birding locations or "sampling hubs," percentage cover of protected, urban, and cultivated area, and the climate variables mean annual precipitation, winter temperatures, and summer temperatures. Further, we used the climate variables and plant biomes to define subsets of pentads representing environmental zones across South Africa, Lesotho, and Swaziland. For each environmental zone, we quantified sampling intensity, and we assessed sampling completeness with species accumulation curves fitted to the asymptotic Lomolino model. Sampling effort was highest close to sampling hubs, major roads, urban areas, and protected areas. Cultivated area and the climate variables were less important. Further, environmental zones were not evenly represented by current data and the zones varied in the amount of sampling required representing the species that are present. SABAP2 volunteers' preferences in birding locations cause spatial bias in the dataset that should be taken into account when analyzing these data. Large parts of South Africa remain underrepresented, which may restrict the kind of ecological questions that may be addressed. However, sampling bias may be improved by directing volunteers toward undersampled regions while taking into account volunteer preferences.

Pattern recognition analysis and classification modeling of selenium-producing areas

USGS Publications Warehouse

Naftz, D.L.

1996-01-01

Established chemometric and geochemical techniques were applied to water quality data from 23 National Irrigation Water Quality Program (NIWQP) study areas in the Western United States. These techniques were applied to the NIWQP data set to identify common geochemical processes responsible for mobilization of selenium and to develop a classification model that uses major-ion concentrations to identify areas that contain elevated selenium concentrations in water that could pose a hazard to water fowl. Pattern recognition modeling of the simple-salt data computed with the SNORM geochemical program indicate three principal components that explain 95% of the total variance. A three-dimensional plot of PC 1, 2 and 3 scores shows three distinct clusters that correspond to distinct hydrochemical facies denoted as facies 1, 2 and 3. Facies 1 samples are distinguished by water samples without the CaCO3 simple salt and elevated concentrations of NaCl, CaSO4, MgSO4 and Na2SO4 simple salts relative to water samples in facies 2 and 3. Water samples in facies 2 are distinguished from facies 1 by the absence of the MgSO4 simple salt and the presence of the CaCO3 simple salt. Water samples in facies 3 are similar to samples in facies 2, with the absence of both MgSO4 and CaSO4 simple salts. Water samples in facies 1 have the largest selenium concentration (10 ??gl-1), compared to a median concentration of 2.0 ??gl-1 and less than 1.0 ??gl-1 for samples in facies 2 and 3. A classification model using the soft independent modeling by class analogy (SIMCA) algorithm was constructed with data from the NIWQP study areas. The classification model was successful in identifying water samples with a selenium concentration that is hazardous to some species of water-fowl from a test data set comprised of 2,060 water samples from throughout Utah and Wyoming. Application of chemometric and geochemical techniques during data synthesis analysis of multivariate environmental databases from other national-scale environmental programs such as the NIWQP could also provide useful insights for addressing 'real world' environmental problems.

Role of Significant Life Experiences in Building Environmental Knowledge and Behavior among Middle School Students

ERIC Educational Resources Information Center

Stevenson, Kathryn T.; Peterson, M. Nils; Carrier, Sarah J.; Strnad, Renee L.; Bondell, Howard D.; Kirby-Hathaway, Terri; Moore, Susan E.

2014-01-01

Significant life experience research suggests that the presence of role models, time outdoors, and nature-related media foster pro-environmental behavior, but most research is qualitative. Based on a random sample of middle school students in North Carolina, USA, we found limited positive associations between presence of a role model and time…

Acute Diarrheal Syndromic Surveillance

PubMed Central

Kam, H.J.; Choi, S.; Cho, J.P.; Min, Y.G.; Park, R.W.

2010-01-01

Objective In an effort to identify and characterize the environmental factors that affect the number of patients with acute diarrheal (AD) syndrome, we developed and tested two regional surveillance models including holiday and weather information in addition to visitor records, at emergency medical facilities in the Seoul metropolitan area of Korea. Methods With 1,328,686 emergency department visitor records from the National Emergency Department Information system (NEDIS) and the holiday and weather information, two seasonal ARIMA models were constructed: (1) The simple model (only with total patient number), (2) the environmental factor-added model. The stationary R-squared was utilized as an in-sample model goodness-of-fit statistic for the constructed models, and the cumulative mean of the Mean Absolute Percentage Error (MAPE) was used to measure post-sample forecast accuracy over the next 1 month. Results The (1,0,1)(0,1,1)7 ARIMA model resulted in an adequate model fit for the daily number of AD patient visits over 12 months for both cases. Among various features, the total number of patient visits was selected as a commonly influential independent variable. Additionally, for the environmental factor-added model, holidays and daily precipitation were selected as features that statistically significantly affected model fitting. Stationary R-squared values were changed in a range of 0.651-0.828 (simple), and 0.805-0.844 (environmental factor-added) with p<0.05. In terms of prediction, the MAPE values changed within 0.090-0.120 and 0.089-0.114, respectively. Conclusion The environmental factor-added model yielded better MAPE values. Holiday and weather information appear to be crucial for the construction of an accurate syndromic surveillance model for AD, in addition to the visitor and assessment records. PMID:23616829

Alpha1 LASSO data bundles Lamont, OK

DOE Data Explorer

Gustafson, William Jr; Vogelmann, Andrew; Endo, Satoshi; Toto, Tami; Xiao, Heng; Li, Zhijin; Cheng, Xiaoping; Krishna, Bhargavi (ORCID:000000018828528X)

2016-08-03

A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input includes model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

A new model for ancient DNA decay based on paleogenomic meta-analysis

PubMed Central

Ware, Roselyn; Smith, Oliver; Collins, Matthew

2017-01-01

Abstract The persistence of DNA over archaeological and paleontological timescales in diverse environments has led to a revolutionary body of paleogenomic research, yet the dynamics of DNA degradation are still poorly understood. We analyzed 185 paleogenomic datasets and compared DNA survival with environmental variables and sample ages. We find cytosine deamination follows a conventional thermal age model, but we find no correlation between DNA fragmentation and sample age over the timespans analyzed, even when controlling for environmental variables. We propose a model for ancient DNA decay wherein fragmentation rapidly reaches a threshold, then subsequently slows. The observed loss of DNA over time may be due to a bulk diffusion process in many cases, highlighting the importance of tissues and environments creating effectively closed systems for DNA preservation. This model of DNA degradation is largely based on mammal bone samples due to published genomic dataset availability. Continued refinement to the model to reflect diverse biological systems and tissue types will further improve our understanding of ancient DNA breakdown dynamics. PMID:28486705

Real-time subsecond voltammetric analysis of Pb in aqueous environmental samples.

PubMed

Yang, Yuanyuan; Pathirathna, Pavithra; Siriwardhane, Thushani; McElmurry, Shawn P; Hashemi, Parastoo

2013-08-06

Lead (Pb) pollution is an important environmental and public health concern. Rapid Pb transport during stormwater runoff significantly impairs surface water quality. The ability to characterize and model Pb transport during these events is critical to mitigating its impact on the environment. However, Pb analysis is limited by the lack of analytical methods that can afford rapid, sensitive measurements in situ. While electrochemical methods have previously shown promise for rapid Pb analysis, they are currently limited in two ways. First, because of Pb's limited solubility, test solutions that are representative of environmental systems are not typically employed in laboratory characterizations. Second, concerns about traditional Hg electrode toxicity, stability, and low temporal resolution have dampened opportunities for in situ analyses with traditional electrochemical methods. In this paper, we describe two novel methodological advances that bypass these limitations. Using geochemical models, we first create an environmentally relevant test solution that can be used for electrochemical method development and characterization. Second, we develop a fast-scan cyclic voltammetry (FSCV) method for Pb detection on Hg-free carbon fiber microelectrodes. We assess the method's sensitivity and stability, taking into account Pb speciation, and utilize it to characterize rapid Pb fluctuations in real environmental samples. We thus present a novel real-time electrochemical tool for Pb analysis in both model and authentic environmental solutions.

Longitudinal Effects on Early Adolescent Language: A Twin Study

PubMed Central

DeThorne, Laura Segebart; Smith, Jamie Mahurin; Betancourt, Mariana Aparicio; Petrill, Stephen A.

2016-01-01

Purpose We evaluated genetic and environmental contributions to individual differences in language skills during early adolescence, measured by both language sampling and standardized tests, and examined the extent to which these genetic and environmental effects are stable across time. Method We used structural equation modeling on latent factors to estimate additive genetic, shared environmental, and nonshared environmental effects on variance in standardized language skills (i.e., Formal Language) and productive language-sample measures (i.e., Productive Language) in a sample of 527 twins across 3 time points (mean ages 10–12 years). Results Individual differences in the Formal Language factor were influenced primarily by genetic factors at each age, whereas individual differences in the Productive Language factor were primarily due to nonshared environmental influences. For the Formal Language factor, the stability of genetic effects was high across all 3 time points. For the Productive Language factor, nonshared environmental effects showed low but statistically significant stability across adjacent time points. Conclusions The etiology of language outcomes may differ substantially depending on assessment context. In addition, the potential mechanisms for nonshared environmental influences on language development warrant further investigation. PMID:27732720

The importance of accounting for larval detectability in mosquito habitat-association studies.

PubMed

Low, Matthew; Tsegaye, Admasu Tassew; Ignell, Rickard; Hill, Sharon; Elleby, Rasmus; Feltelius, Vilhelm; Hopkins, Richard

2016-05-04

Mosquito habitat-association studies are an important basis for disease control programmes and/or vector distribution models. However, studies do not explicitly account for incomplete detection during larval presence and abundance surveys, with potential for significant biases because of environmental influences on larval behaviour and sampling efficiency. Data were used from a dip-sampling study for Anopheles larvae in Ethiopia to evaluate the effect of six factors previously associated with larval sampling (riparian vegetation, direct sunshine, algae, water depth, pH and temperature) on larval presence and detectability. Comparisons were made between: (i) a presence-absence logistic regression where samples were pooled at the site level and detectability ignored, (ii) a success versus trials binomial model, and (iii) a presence-detection mixture model that separately estimated presence and detection, and fitted different explanatory variables to these estimations. Riparian vegetation was consistently highlighted as important, strongly suggesting it explains larval presence (-). However, depending on how larval detectability was estimated, the other factors showed large variations in their statistical importance. The presence-detection mixture model provided strong evidence that larval detectability was influenced by sunshine and water temperature (+), with weaker evidence for algae (+) and water depth (-). For larval presence, there was also some evidence that water depth (-) and pH (+) influenced site occupation. The number of dip-samples needed to determine if larvae were likely present at a site was condition dependent: with sunshine and warm water requiring only two dips, while cooler water and cloud cover required 11. Environmental factors influence true larval presence and larval detectability differentially when sampling in field conditions. Researchers need to be more aware of the limitations and possible biases in different analytical approaches used to associate larval presence or abundance with local environmental conditions. These effects can be disentangled using data that are routinely collected (i.e., multiple dip samples at each site) by employing a modelling approach that separates presence from detectability.

A novel statistical methodology to overcome sampling irregularities in the forest inventory data and to model forest changes under dynamic disturbance regimes

Treesearch

Nikolay Strigul; Jean Lienard

2015-01-01

Forest inventory datasets offer unprecedented opportunities to model forest dynamics under evolving environmental conditions but they are analytically challenging due to irregular sampling time intervals of the same plot, across the years. We propose here a novel method to model dynamic changes in forest biomass and basal area using forest inventory data. Our...

ASSESSING ACCURACY OF NET CHANGE DERIVED FROM LAND COVER MAPS

EPA Science Inventory

Net change derived from land-cover maps provides important descriptive information for environmental monitoring and is often used as an input or explanatory variable in environmental models. The sampling design and analysis for assessing net change accuracy differ from traditio...

Evaluating the efficiency of environmental monitoring programs

USGS Publications Warehouse

Levine, Carrie R.; Yanai, Ruth D.; Lampman, Gregory G.; Burns, Douglas A.; Driscoll, Charles T.; Lawrence, Gregory B.; Lynch, Jason; Schoch, Nina

2014-01-01

Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.

The Earth Microbiome Project and modeling the planets microbial potential (Invited)

NASA Astrophysics Data System (ADS)

Gilbert, J. A.

2013-12-01

The understanding of Earth's climate and ecology requires multiscale observations of the biosphere, of which microbial life are a major component. However, to acquire and process physical samples of soil, water and air that comprise the appropriate spatial and temporal resolution to capture the immense variation in microbial dynamics, would require a herculean effort and immense financial resources dwarfing even the most ambitious projects to date. To overcome this hurdle we created the Earth Microbiome Project, a crowd-sourced effort to acquire physical samples from researchers around the world that are, importantly, contextualized with physical, chemical and biological data detailing the environmental properties of that sample in the location and time it was acquired. The EMP leverages these existing efforts to target a systematic analysis of microbial taxonomic and functional dynamics across a vast array of environmental parameter gradients. The EMP captures the environmental gradients, location, time and sampling protocol information about every sample donated by our valued collaborators. Physical samples are then processed using a standardized DNA extraction, PCR, and shotgun sequencing protocol to generate comparable data regarding the microbial community structure and function in each sample. To date we have processed >17,000 samples from 40 different biomes. One of the key goals of the EMP is to map the spatiotemporal variability of microbial communities to capture the changes in important functional processes that need to be appropriately expressed in models to provide reliable forecasts of ecosystem phenotype across our changing planet. This is essential if we are to develop economically sound strategies to be good stewards of our Earth. The EMP recognizes that environments are comprised of complex sets of interdependent parameters and that the development of useful predictive computational models of both terrestrial and atmospheric systems requires recognition and accommodation of sources of uncertainty.

Progressive Sampling Technique for Efficient and Robust Uncertainty and Sensitivity Analysis of Environmental Systems Models: Stability and Convergence

NASA Astrophysics Data System (ADS)

Sheikholeslami, R.; Hosseini, N.; Razavi, S.

2016-12-01

Modern earth and environmental models are usually characterized by a large parameter space and high computational cost. These two features prevent effective implementation of sampling-based analysis such as sensitivity and uncertainty analysis, which require running these computationally expensive models several times to adequately explore the parameter/problem space. Therefore, developing efficient sampling techniques that scale with the size of the problem, computational budget, and users' needs is essential. In this presentation, we propose an efficient sequential sampling strategy, called Progressive Latin Hypercube Sampling (PLHS), which provides an increasingly improved coverage of the parameter space, while satisfying pre-defined requirements. The original Latin hypercube sampling (LHS) approach generates the entire sample set in one stage; on the contrary, PLHS generates a series of smaller sub-sets (also called `slices') while: (1) each sub-set is Latin hypercube and achieves maximum stratification in any one dimensional projection; (2) the progressive addition of sub-sets remains Latin hypercube; and thus (3) the entire sample set is Latin hypercube. Therefore, it has the capability to preserve the intended sampling properties throughout the sampling procedure. PLHS is deemed advantageous over the existing methods, particularly because it nearly avoids over- or under-sampling. Through different case studies, we show that PHLS has multiple advantages over the one-stage sampling approaches, including improved convergence and stability of the analysis results with fewer model runs. In addition, PLHS can help to minimize the total simulation time by only running the simulations necessary to achieve the desired level of quality (e.g., accuracy, and convergence rate).

40 CFR Appendix IV to Part 600 - Sample Fuel Economy Labels for 2008 Through 2012 Model Year Vehicles

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 31 2013-07-01 2013-07-01 false Sample Fuel Economy Labels for 2008 Through 2012 Model Year Vehicles IV Appendix IV to Part 600 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR...

40 CFR Appendix IV to Part 600 - Sample Fuel Economy Labels for 2008 Through 2012 Model Year Vehicles

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 31 2012-07-01 2012-07-01 false Sample Fuel Economy Labels for 2008 Through 2012 Model Year Vehicles IV Appendix IV to Part 600 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND GREENHOUSE GAS EXHAUST EMISSIONS OF MOTOR...

Detection of the actinides and cesium from environmental samples

NASA Astrophysics Data System (ADS)

Snow, Mathew Spencer

Detection of the actinides and cesium in the environment is important for a variety of applications ranging from environmental remediation to safeguards and nuclear forensics. The utilization of multiple different elemental concentrations and isotopic ratios together can significantly improve the ability to attribute contamination to a unique source term and/or generation process; however, the utilization of multiple elemental "signatures" together from environmental samples requires knowledge of the impact of chemical fractionation for various elements under a variety of environmental conditions (including predominantly aqueous versus arid conditions). The research reported in this dissertation focuses on three major areas: 1. Improving the understanding of actinide-mineral interactions at ultra-low concentrations. Chapter 2 reports a batch sorption and modeling study of Np(V) sorption to the mineral goethite from attomolar to micromolar concentrations. 2. Improving the detection capabilities for Thermal Ionization Mass Spectrometry (TIMS) analyses of ultra-trace cesium from environmental samples. Chapter 4 reports a new method which significantly improves the chemical yields, purification, sample processing time, and ultimately, the detection limits for TIMS analyses of femtogram quantities of cesium from a variety of environmental sample matrices. 3. Demonstrating how actinide and cesium concentrations and isotopic ratios from environmental samples can be utilized together to determine a wealth of information including environmental transport mechanisms (e.g. aqueous versus arid transport) and information on the processes which generated the original material. Chapters1, 3 and 5 demonstrate these principles using Pu, Am, Np, and Cs concentrations and isotopic ratios from contaminated soils taken near the Subsurface Disposal Area (SDA) of Idaho National Laboratory (INL) (a low level radioactive waste disposal site in southeastern Idaho).

40 CFR Appendix II to Subpart E - Sampling Tables

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 25 2011-07-01 2011-07-01 false Sampling Tables II Appendix II to Subpart E Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS... II to Subpart E—Sampling Tables Table 1—Model Year Production Volume of 50-99 Vehicles Cumulative...

40 CFR Appendix II to Subpart E - Sampling Tables

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Sampling Tables II Appendix II to Subpart E Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS... II to Subpart E—Sampling Tables Table 1—Model Year Production Volume of 50-99 Vehicles Cumulative...

A new model for ancient DNA decay based on paleogenomic meta-analysis.

PubMed

Kistler, Logan; Ware, Roselyn; Smith, Oliver; Collins, Matthew; Allaby, Robin G

2017-06-20

The persistence of DNA over archaeological and paleontological timescales in diverse environments has led to a revolutionary body of paleogenomic research, yet the dynamics of DNA degradation are still poorly understood. We analyzed 185 paleogenomic datasets and compared DNA survival with environmental variables and sample ages. We find cytosine deamination follows a conventional thermal age model, but we find no correlation between DNA fragmentation and sample age over the timespans analyzed, even when controlling for environmental variables. We propose a model for ancient DNA decay wherein fragmentation rapidly reaches a threshold, then subsequently slows. The observed loss of DNA over time may be due to a bulk diffusion process in many cases, highlighting the importance of tissues and environments creating effectively closed systems for DNA preservation. This model of DNA degradation is largely based on mammal bone samples due to published genomic dataset availability. Continued refinement to the model to reflect diverse biological systems and tissue types will further improve our understanding of ancient DNA breakdown dynamics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Antecedents of willingness to pay for green products

NASA Astrophysics Data System (ADS)

Pratiwi, S. I.; Pratomo, L. A.

2018-01-01

The main purpose of this paper is to examine whether there is a positive influence of pro-environmental behavior and environmental locus of control toward the willingness to pay for green products. The data obtained by distributing online and offline questionnaires, reaching 419 respondents of 18 to ≥55 years old that have the knowledge and already bought a green product. The purposive sampling was used as the sampling technique, and the data were tested by Statistical Equation Modeling (SEM).The results show that environmental locus of control does not positively affect pro-environmental behavior. However, the environmental locus of control and pro-environmental behavior do have a positive influence on the willingness to pay. Based on the findings, it is essential for green product companies to improve customers’ pro-environmental behavior and environmental locus of control. To do so, the marketer of green products should increase consumers’ concern, awareness, and behavior of conserving nature through activities such as campaigns and demonstrations.

Patterns of Spatial Variation of Assemblages Associated with Intertidal Rocky Shores: A Global Perspective

PubMed Central

Cruz-Motta, Juan José; Miloslavich, Patricia; Palomo, Gabriela; Iken, Katrin; Konar, Brenda; Pohle, Gerhard; Trott, Tom; Benedetti-Cecchi, Lisandro; Herrera, César; Hernández, Alejandra; Sardi, Adriana; Bueno, Andrea; Castillo, Julio; Klein, Eduardo; Guerra-Castro, Edlin; Gobin, Judith; Gómez, Diana Isabel; Riosmena-Rodríguez, Rafael; Mead, Angela; Bigatti, Gregorio; Knowlton, Ann; Shirayama, Yoshihisa

2010-01-01

Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org). There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs); however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample) was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST) and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index) were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution), we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses. PMID:21179546

Rearing Environmental Influences on Religiousness: An Investigation of Adolescent Adoptees.

PubMed

Koenig, Laura B; McGue, Matt; Iacono, William G

2009-10-01

Religiousness is widely considered to be a culturally transmitted trait. However, twin studies suggest that religiousness is genetically influenced in adulthood, although largely environmentally influenced in childhood/adolescence. We examined genetic and environmental influences on a self-report measure of religiousness in a sample consisting of 284 adoptive families (two adopted adolescent siblings and their rearing parents); 208 biological families (two full biological adolescent siblings and their parents); and 124 mixed families (one adopted and one biological adolescent sibling and their parents). A sibling-family model was fit to the data to estimate genetic, shared environmental, and nonshared environmental effects on religiousness, as well as cultural transmission and assortative mating effects. Religiousness showed little evidence of heritability and large environmental effects, which did not vary significantly by gender. This finding is consistent with the results of twin studies of religiousness in adolescent and preadolescent samples.

Rearing Environmental Influences on Religiousness: An Investigation of Adolescent Adoptees

PubMed Central

Koenig, Laura B.; McGue, Matt; Iacono, William G.

2009-01-01

Religiousness is widely considered to be a culturally transmitted trait. However, twin studies suggest that religiousness is genetically influenced in adulthood, although largely environmentally influenced in childhood/adolescence. We examined genetic and environmental influences on a self-report measure of religiousness in a sample consisting of 284 adoptive families (two adopted adolescent siblings and their rearing parents); 208 biological families (two full biological adolescent siblings and their parents); and 124 mixed families (one adopted and one biological adolescent sibling and their parents). A sibling-family model was fit to the data to estimate genetic, shared environmental, and nonshared environmental effects on religiousness, as well as cultural transmission and assortative mating effects. Religiousness showed little evidence of heritability and large environmental effects, which did not vary significantly by gender. This finding is consistent with the results of twin studies of religiousness in adolescent and preadolescent samples. PMID:20161346

Evaluation of measured and predicted environmental concentrations of selected human pharmaceuticals and personal care products.

PubMed

Liebig, Markus; Moltmann, Johann F; Knacker, Thomas

2006-03-01

In the past few years, there was an increasing awareness of the occurrence of pharmaceuticals and personal care products (PPCPs) in surface water and drinking water resources, and measurements in surface water, sediment or waste water were done for a number of PPCPs. In the regulatory context, an environmental risk assessment (ERA) has become essential for new PPCPs. Reliably predicted or measured environmental concentrations (PECs or MECs) of chemicals are essential for the exposure assessment, which is one of the two main pillars of environmental risk assessment (ERA). This paper reports on measured data of selected PPCPs in surface waters and compares the measured values with predicted environmental concentrations from exposure models. Such models have been proposed by the European Agency for the Evaluation of Medicinal Products (EMEA) and the Technical Guidance Document on Risk Assessment for New Notified and Existing Chemical Substances (TGD). Four pharmaceuticals and one personal care product were in the scope of the investigation reported here: 17alpha-ethinylestradiol, carbamazepine, sulfamethoxazole and iopromide as well as tonalide. Measured environmental concentrations in surface waters for these PPCPs were reviewed in the scientific literature. The appropriateness of these data was evaluated according to criteria for monitoring data recommended by the TGD. A total of 38 references were evaluated with emphasis on the adequacy of chemical analysis and the representativeness of sampling. Measurements of concentrations in surface water (MECsw), which were found to be adequate for use in exposure assessment according to the monitoring quality criteria, were averaged and compared with respective PECs in surface water (PECsw) derived from exposure modelling (cf. EMEA and TGD). Measured environmental concentrations adequate for use in exposure assessment were found in 20 out of 38 references. Several of the measurements from Germany could be used for a comparison with calculated PECs. Average MECs(sw) in Germany were < 0.58 ng/L for 17alpha-ethinylestradiol, 454 ng/L for carbamazepine, 126 ng/L for sulfamethoxazole, 1105 ng/L for iopromide and 311 ng/L for tonalide. In comparison to the measured concentrations, PECs calculated with the model proposed by the EMEA in 2001 were in the same range, but slightly higher than the MECs. The EMEA model from 2001 is based on a production/use volume of the PPCPs. The more recent EMEA model (2003/2005) overestimated the PECs by more than one order of magnitude for carbamazepine and sulfamethoxazole, but underestimated the concentration of 17alpha-ethinylestradiol by a factor of almost 5 compared to the MECs. This model is based on maximum daily doses and the assumption that 1% of the population is consuming the pharmaceutical (default value). Calculations with the European Union System for the Evaluation of Substances (EUSES), which is part of the TGD describing the risk assessment of chemicals and biocides, resulted for the investigated pharmaceuticals in almost the same PECs as derived by the older EMEA model (2001). For the PCP tonalide, to which the recent EMEA model (2003/ 2005) cannot be applied, the PEC was overestimated by a factor of 3 with the older EMEA model (2001), but underestimated with EUSES by a factor of 5 compared to the averaged MECsw in Germany. Conclusions. It was shown that PEC calculations with exposure models provided by EMEA and the TGD, resulted in PECs very close to the corresponding MECs in most cases. However, environmental concentrations can be underestimated by models in cases, where, e.g. due to high lipophilicity, sorption to sewage sludge is assumed which does not occur to that extent under real conditions. Thus, it appears that the exposure models do not come up to the complexity of the real environment. However, the main factor with the highest impact on predicted environmental concentrations and a high degree of uncertainty is the production volume. Recommendations and Outlook. References and their data evaluated as not adequate for use in exposure assessment were mainly rejected due to missing or insufficient specifications related to the sampling procedure and/or representativeness of the samples. Several of the evaluated studies aimed at the introduction and establishment of a new analytical methodology. A detailed description of sampling frequency and pattern, for example, was therefore neglected. Often, a more accurate description of analytical procedure, sampling pattern and statistical analysis of data would be sufficient to provide an adequate basis for exposure assessment and hence establish confidence in environmental risk assessment procedures. For new substances, an exposure assessment is solely based on estimations using environmental fate models. To avoid unacceptable risks for the environment, PECs should not underestimate actual environmental concentrations. Since it was shown that under specific conditions the models applied in this study underestimated measured environmental concentrations, further development of the calculation models appears to be necessary.

Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States.

PubMed

Varughese, Eunice A; Brinkman, Nichole E; Anneken, Emily M; Cashdollar, Jennifer L; Fout, G Shay; Furlong, Edward T; Kolpin, Dana W; Glassmeyer, Susan T; Keely, Scott P

2018-04-01

Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition. In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment. The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample. Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive. Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR-based assessments of environmental samples. PCR inhibition measurements, viral recovery, and other assessments were incorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters. Published by Elsevier B.V.

Evaluating the environmental fate of short-chain chlorinated paraffins (SCCPs) in the Nordic environment using a dynamic multimedia model.

PubMed

Krogseth, Ingjerd S; Breivik, Knut; Arnot, Jon A; Wania, Frank; Borgen, Anders R; Schlabach, Martin

2013-12-01

Short chain chlorinated paraffins (SCCPs) raise concerns due to their potential for persistence, bioaccumulation, long-range transport and adverse effects. An understanding of their environmental fate remains limited, partly due to the complexity of the mixture. The purpose of this study was to evaluate whether a mechanistic, integrated, dynamic environmental fate and bioaccumulation multimedia model (CoZMoMAN) can reconcile what is known about environmental emissions and human exposure of SCCPs in the Nordic environment. Realistic SCCP emission scenarios, resolved by formula group, were estimated and used to predict the composition and concentrations of SCCPs in the environment and the human food chain. Emissions at the upper end of the estimated range resulted in predicted total concentrations that were often within a factor of 6 of observations. Similar model performance for a complex group of organic contaminants as for the well-known polychlorinated biphenyls strengthens the confidence in the CoZMoMAN model and implies a relatively good mechanistic understanding of the environmental fate of SCCPs. However, the degree of chlorination predicted for SCCPs in sediments, fish, and humans was higher than observed and poorly established environmental half-lives and biotransformation rate constants contributed to the uncertainties in the predicted composition and ∑SCCP concentrations. Improving prediction of the SCCP composition will also require better constrained estimates of the composition of SCCP emissions. There is, however, also large uncertainty and lack of coherence in the existing observations, and better model-measurement agreement will require improved analytical methods and more strategic sampling. More measurements of SCCP levels and compositions in samples from background regions are particularly important.

Functional enzyme-based modeling approach for dynamic simulation of denitrification process in hyporheic zone sediments: Genetically structured microbial community model

NASA Astrophysics Data System (ADS)

Song, H. S.; Li, M.; Qian, W.; Song, X.; Chen, X.; Scheibe, T. D.; Fredrickson, J.; Zachara, J. M.; Liu, C.

2016-12-01

Modeling environmental microbial communities at individual organism level is currently intractable due to overwhelming structural complexity. Functional guild-based approaches alleviate this problem by lumping microorganisms into fewer groups based on their functional similarities. This reduction may become ineffective, however, when individual species perform multiple functions as environmental conditions vary. In contrast, the functional enzyme-based modeling approach we present here describes microbial community dynamics based on identified functional enzymes (rather than individual species or their groups). Previous studies in the literature along this line used biomass or functional genes as surrogate measures of enzymes due to the lack of analytical methods for quantifying enzymes in environmental samples. Leveraging our recent development of a signature peptide-based technique enabling sensitive quantification of functional enzymes in environmental samples, we developed a genetically structured microbial community model (GSMCM) to incorporate enzyme concentrations and various other omics measurements (if available) as key modeling input. We formulated the GSMCM based on the cybernetic metabolic modeling framework to rationally account for cellular regulation without relying on empirical inhibition kinetics. In the case study of modeling denitrification process in Columbia River hyporheic zone sediments collected from the Hanford Reach, our GSMCM provided a quantitative fit to complex experimental data in denitrification, including the delayed response of enzyme activation to the change in substrate concentration. Our future goal is to extend the modeling scope to the prediction of carbon and nitrogen cycles and contaminant fate. Integration of a simpler version of the GSMCM with PFLOTRAN for multi-scale field simulations is in progress.

Improving three-tier environmental assessment model by using a 3D scanning FLS-AM series hyperspectral lidar

NASA Astrophysics Data System (ADS)

Samberg, Andre; Babichenko, Sergei; Poryvkina, Larisa

2005-05-01

Delay between the time when natural disaster, for example, oil accident in coastal water, occurred and the time when environmental protection actions, for example, water and shoreline clean-up, started is of significant importance. Mostly remote sensing techniques are considered as (near) real-time and suitable for multiple tasks. These techniques in combination with rapid environmental assessment methodologies would form multi-tier environmental assessment model, which allows creating (near) real-time datasets and optimizing sampling scenarios. This paper presents the idea of three-tier environmental assessment model. Here all three tiers are briefly described to show the linkages between them, with a particular focus on the first tier. Furthermore, it is described how large-scale environmental assessment can be improved by using an airborne 3-D scanning FLS-AM series hyperspectral lidar. This new aircraft-based sensor is typically applied for oil mapping on sea/ground surface and extracting optical features of subjects. In general, a sampling network, which is based on three-tier environmental assessment model, can include ship(s) and aircraft(s). The airborne 3-D scanning FLS-AM series hyperspectral lidar helps to speed up the whole process of assessing of area of natural disaster significantly, because this is a real-time remote sensing mean. For instance, it can deliver such information as georeferenced oil spill position in WGS-84, the estimated size of the whole oil spill, and the estimated amount of oil in seawater or on ground. All information is produced in digital form and, thus, can be directly transferred into a customer"s GIS (Geographical Information System) system.

Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

USGS Publications Warehouse

Smith, J. LaRue; Damar, Nancy A.; Charlet, David A.; Westenburg, Craig L.

2014-01-01

DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

Deep-sea benthic megafaunal habitat suitability modelling: A global-scale maximum entropy model for xenophyophores

NASA Astrophysics Data System (ADS)

Ashford, Oliver S.; Davies, Andrew J.; Jones, Daniel O. B.

2014-12-01

Xenophyophores are a group of exclusively deep-sea agglutinating rhizarian protozoans, at least some of which are foraminifera. They are an important constituent of the deep-sea megafauna that are sometimes found in sufficient abundance to act as a significant source of habitat structure for meiofaunal and macrofaunal organisms. This study utilised maximum entropy modelling (Maxent) and a high-resolution environmental database to explore the environmental factors controlling the presence of Xenophyophorea and two frequently sampled xenophyophore species that are taxonomically stable: Syringammina fragilissima and Stannophyllum zonarium. These factors were also used to predict the global distribution of each taxon. Areas of high habitat suitability for xenophyophores were highlighted throughout the world's oceans, including in a large number of areas yet to be suitably sampled, but the Northeast and Southeast Atlantic Ocean, Gulf of Mexico and Caribbean Sea, the Red Sea and deep-water regions of the Malay Archipelago represented particular hotspots. The two species investigated showed more specific habitat requirements when compared to the model encompassing all xenophyophore records, perhaps in part due to the smaller number and relatively more clustered nature of the presence records available for modelling at present. The environmental variables depth, oxygen parameters, nitrate concentration, carbon-chemistry parameters and temperature were of greatest importance in determining xenophyophore distributions, but, somewhat surprisingly, hydrodynamic parameters were consistently shown to have low importance, possibly due to the paucity of well-resolved global hydrodynamic datasets. The results of this study (and others of a similar type) have the potential to guide further sample collection, environmental policy, and spatial planning of marine protected areas and industrial activities that impact the seafloor, particularly those that overlap with aggregations of these conspicuously large single-celled eukaryotes.

Estimating effect of environmental contaminants on women's subfecundity for the MoBa study data with an outcome-dependent sampling scheme

PubMed Central

Ding, Jieli; Zhou, Haibo; Liu, Yanyan; Cai, Jianwen; Longnecker, Matthew P.

2014-01-01

Motivated by the need from our on-going environmental study in the Norwegian Mother and Child Cohort (MoBa) study, we consider an outcome-dependent sampling (ODS) scheme for failure-time data with censoring. Like the case-cohort design, the ODS design enriches the observed sample by selectively including certain failure subjects. We present an estimated maximum semiparametric empirical likelihood estimation (EMSELE) under the proportional hazards model framework. The asymptotic properties of the proposed estimator were derived. Simulation studies were conducted to evaluate the small-sample performance of our proposed method. Our analyses show that the proposed estimator and design is more efficient than the current default approach and other competing approaches. Applying the proposed approach with the data set from the MoBa study, we found a significant effect of an environmental contaminant on fecundability. PMID:24812419

Remedial investigation sampling and analysis plan for J-Field, Aberdeen Proving Ground, Maryland. Volume 1: Field Sampling Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benioff, P.; Biang, R.; Dolak, D.

1995-03-01

The Environmental Management Division (EMD) of Aberdeen Proving Ground (APG), Maryland, is conducting a remedial investigation and feasibility study (RI/FS) of the J-Field area at APG pursuant to the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended. J-Field is within the Edgewood Area of APG in Harford County, Maryland (Figure 1. 1). Since World War II activities in the Edgewood Area have included the development, manufacture, testing, and destruction of chemical agents and munitions. These materials were destroyed at J-Field by open burning and open detonation (OB/OD). Considerable archival information about J-Field exists as a result of effortsmore » by APG staff to characterize the hazards associated with the site. Contamination of J-Field was first detected during an environmental survey of the Edgewood Area conducted in 1977 and 1978 by the US Army Toxic and Hazardous Materials Agency (USATHAMA) (predecessor to the US Army Environmental Center [AEC]). As part of a subsequent USATHAMA -environmental survey, 11 wells were installed and sampled at J-Field. Contamination at J-Field was also detected during a munitions disposal survey conducted by Princeton Aqua Science in 1983. The Princeton Aqua Science investigation involved the installation and sampling of nine wells and the collection and analysis of surficial and deep composite soil samples. In 1986, a Resource Conservation and Recovery Act (RCRA) permit (MD3-21-002-1355) requiring a basewide RCRA Facility Assessment (RFA) and a hydrogeologic assessment of J-Field was issued by the US Environmental Protection Agency (EPA). In 1987, the US Geological Survey (USGS) began a two-phased hydrogeologic assessment in data were collected to model, groundwater flow at J-Field. Soil gas investigations were conducted, several well clusters were installed, a groundwater flow model was developed, and groundwater and surface water monitoring programs were established that continue today.« less

Understanding Phlebotomus perniciosus abundance in south-east Spain: assessing the role of environmental and anthropic factors.

PubMed

Risueño, José; Muñoz, Clara; Pérez-Cutillas, Pedro; Goyena, Elena; Gonzálvez, Moisés; Ortuño, María; Bernal, Luis Jesús; Ortiz, Juana; Alten, Bulent; Berriatua, Eduardo

2017-04-19

Leishmaniosis is associated with Phlebotomus sand fly vector density, but our knowledge of the environmental framework that regulates highly overdispersed vector abundance distributions is limited. We used a standardized sampling procedure in the bioclimatically diverse Murcia Region in Spain and multilevel regression models for count data to estimate P. perniciosus abundance in relation to environmental and anthropic factors. Twenty-five dog and sheep premises were sampled for sand flies using adhesive and light-attraction traps, from late May to early October 2015. Temperature, relative humidity and other animal- and premise-related data recorded on site and other environmental data were extracted from digital databases using a geographical information system. The relationship between sand fly abundance and explanatory variables was analysed using binomial regression models. The total number of sand flies captured, mostly with light-attraction traps, was 3,644 specimens, including 80% P. perniciosus, the main L. infantum vector in Spain. Abundance varied between and within zones and was positively associated with increasing altitude from 0 to 900 m above sea level, except from 500 to 700 m where it was low. Populations peaked in July and especially during a 3-day heat wave when relative humidity and wind speed plummeted. Regression models indicated that climate and not land use or soil characteristics have the greatest impact on this species density on a large geographical scale. In contrast, micro-environmental factors such as animal building characteristics and husbandry practices affect sand fly population size on a smaller scale. A standardised sampling procedure and statistical analysis for highly overdispersed distributions allow reliable estimation of P. perniciosus abundance and identification of environmental drivers. While climatic variables have the greatest impact at macro-environmental scale, anthropic factors may be determinant at a micro-geographical scale. These finding may be used to elaborate predictive distribution maps useful for vector and pathogen control programs.

Common genetic and environmental contributions to post-traumatic stress disorder and alcohol dependence in young women.

PubMed

Sartor, C E; McCutcheon, V V; Pommer, N E; Nelson, E C; Grant, J D; Duncan, A E; Waldron, M; Bucholz, K K; Madden, P A F; Heath, A C

2011-07-01

The few genetically informative studies to examine post-traumatic stress disorder (PTSD) and alcohol dependence (AD), all of which are based on a male veteran sample, suggest that the co-morbidity between PTSD and AD may be attributable in part to overlapping genetic influences, but this issue has yet to be addressed in females.MethodData were derived from an all-female twin sample (n=3768) ranging in age from 18 to 29 years. A trivariate genetic model that included trauma exposure as a separate phenotype was fitted to estimate genetic and environmental contributions to PTSD and the degree to which they overlap with those that contribute to AD, after accounting for potential confounding effects of heritable influences on trauma exposure. Additive genetic influences (A) accounted for 72% of the variance in PTSD; individual-specific environmental (E) factors accounted for the remainder. An AE model also provided the best fit for AD, for which heritability was estimated to be 71%. The genetic correlation between PTSD and AD was 0.54. The heritability estimate for PTSD in our sample is higher than estimates reported in earlier studies based almost exclusively on an all-male sample in which combat exposure was the precipitating traumatic event. However, our findings are consistent with the absence of evidence for shared environmental influences on PTSD and, most importantly, the substantial overlap in genetic influences on PTSD and AD reported in these investigations. Additional research addressing potential distinctions by gender in the relative contributions of genetic and environmental influences on PTSD is merited.

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

PubMed

Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C

2008-03-01

The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.

A multigear protocol for sampling crayfish assemblages in Gulf of Mexico coastal streams

Treesearch

William R. Budnick; William E. Kelso; Susan B. Adams; Michael D. Kaller

2018-01-01

Identifying an effective protocol for sampling crayfish in streams that vary in habitat and physical/chemical characteristics has proven problematic. We evaluated an active, combined-gear (backpack electrofishing and dipnetting) sampling protocol in 20 Coastal Plain streams in Louisiana. Using generalized linear models and rarefaction curves, we evaluated environmental...

Longitudinal Stability in Genetic Effects on Children's Conversational Language Productivity

ERIC Educational Resources Information Center

DeThorne, Laura Segebart; Harlaar, Nicole; Petrill, Stephen A.; Deater-Deckard, Kirby

2012-01-01

Purpose: The authors examined the longitudinal stability of genetic and environmental influences on children's productive language sample measures during the early school-age years. Method: Twin study methodology with structural equation modeling was used to derive univariate estimates of additive genetic (A), shared environmental (C), and…

Estimating Methylmercury Intake for the General Population of South Korea Using Physiologically Based Pharmacokinetic Modeling

EPA Science Inventory

The Korean National Environmental Health Survey (KoNEHS 2009–2011) tracks levels of environmental pollutants in biological samples from the adult Korean population (age 19–88). Recent survey results for blood mercury (Hg) suggest some exceedance above existing blood H...

Cohort change and the diffusion of environmental concern: A cross-national analysis

PubMed Central

Nawrotzki, Raphael J.; Pampel, Fred C.

2013-01-01

This study explores value change across cohorts for a multinational population sample. Employing a diffusion-of-innovations approach, we combine competing theories predicting the relationship between socio-economic status (SES) and environmentalism: post-materialism and affluence theories, and global environmentalism theory. The diffusion argument suggests that high-SES groups first adopt pro-environmental views, but as time passes by, environmentalism diffuses to lower-SES groups. We test the diffusion argument using a sample of 18 countries for two waves (years 1993 and 2000) from the International Social Survey Project (ISSP). Cross-classified multilevel modeling allows us to identify a non-linear interaction between cohort and education, our core measure of SES, in predicting environmental concern, while controlling for age and period. We find support for the diffusion argument and demonstrate that the positive effect of education on environmental concern first increases among older cohorts, then starts to level off until a bend-point is reached for individuals born around 1940 and becomes progressively weaker for younger cohorts. PMID:24179313

Cohort change and the diffusion of environmental concern: A cross-national analysis.

PubMed

Nawrotzki, Raphael J; Pampel, Fred C

2013-09-01

This study explores value change across cohorts for a multinational population sample. Employing a diffusion-of-innovations approach, we combine competing theories predicting the relationship between socio-economic status (SES) and environmentalism: post-materialism and affluence theories, and global environmentalism theory. The diffusion argument suggests that high-SES groups first adopt pro-environmental views, but as time passes by, environmentalism diffuses to lower-SES groups. We test the diffusion argument using a sample of 18 countries for two waves (years 1993 and 2000) from the International Social Survey Project (ISSP). Cross-classified multilevel modeling allows us to identify a non-linear interaction between cohort and education, our core measure of SES, in predicting environmental concern, while controlling for age and period. We find support for the diffusion argument and demonstrate that the positive effect of education on environmental concern first increases among older cohorts, then starts to level off until a bend-point is reached for individuals born around 1940 and becomes progressively weaker for younger cohorts.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Relationships of elevation, channel slope, and stream width to occurrences of native fishes at the Great Plains-Rocky Mountains interface

USGS Publications Warehouse

Brunger, Lipsey T.S.; Hubert, W.A.; Rahel, F.J.

2005-01-01

Environmental gradients occur with upstream progression from plains to mountains and affect the occurrence of native warmwater fish species, but the relative importance of various environmental gradients are not defined. We assessed the relative influences of elevation, channel slope, and stream width on the occurrences of 15 native warmwater fish species among 152 reaches scattered across the North Platte River drainage of Wyoming at the interface of the Great Plains and Rocky Mountains. Most species were collected in reaches that were lower in elevation, had lower channel slopes, and were wider than the medians of the 152 sampled reaches. Several species occurred over a relatively narrow range of elevation, channel slope, or stream width among the sampled reaches, but the distributions of some species appeared to extend beyond the ranges of the sampled reaches. We identified competing logistic-regression models that accounted for the occurrence of individual species using the information-theoretic approach. Linear logistic-regression models accounted for patterns in the data better than curvilinear models for all species. The highest ranked models included channel slope for seven species, elevation for six species, stream width for one species, and both channel slope and stream width for one species. Our results suggest that different environmental gradients may affect upstream boundaries of different fish species at the interface of the Great Plains and Rocky Mountains in Wyoming.

Predicting invertebrate assemblage composition from harvesting pressure and environmental characteristics on tropical reef flats

NASA Astrophysics Data System (ADS)

Jimenez, H.; Dumas, P.; Ponton, D.; Ferraris, J.

2012-03-01

Invertebrates represent an essential component of coral reef ecosystems; they are ecologically important and a major resource, but their assemblages remain largely unknown, particularly on Pacific islands. Understanding their distribution and building predictive models of community composition as a function of environmental variables therefore constitutes a key issue for resource management. The goal of this study was to define and classify the main environmental factors influencing tropical invertebrate distributions in New Caledonian reef flats and to test the resulting predictive model. Invertebrate assemblages were sampled by visual counting during 2 years and 2 seasons, then coupled to different environmental conditions (habitat composition, hydrodynamics and sediment characteristics) and harvesting status (MPA vs. non-MPA and islets vs. coastal flats). Environmental conditions were described by a principal component analysis (PCA), and contributing variables were selected. Permutational analysis of variance (PERMANOVA) was used to test the effects of different factors (status, flat, year and season) on the invertebrate assemblage composition. Multivariate regression trees (MRT) were then used to hierarchically classify the effects of environmental and harvesting variables. MRT model explained at least 60% of the variation in structure of invertebrate communities. Results highlighted the influence of status (MPA vs. non-MPA) and location (islet vs. coastal flat), followed by habitat composition, organic matter content, hydrodynamics and sampling year. Predicted assemblages defined by indicator families were very different for each environment-exploitation scenario and correctly matched a calibration data matrix. Predictions from MRT including both environmental variables and harvesting pressure can be useful for management of invertebrates in coral reef environments.

Evidence for the Trait-Impulsivity Etiological Model in a Clinical Sample: Bifactor Structure and Its Relation to Impairment and Environmental Risk.

PubMed

Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred

2018-05-01

The trait-impulsivity etiological model assumes that a general factor (trait-impulsivity) underlies attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and other externalizing disorders. We investigated the plausibility of this assumption by testing the factor structure of ADHD and ODD in a bifactor framework for a clinical sample of 1420 children between 6 and 18 years of age (M = 9.99, SD = 3.34; 85% male). Further, the trait-impulsivity etiological model assumes that ODD emerges only if environmental risk factors are present. Our results support the validity of the trait-impulsivity etiological model, as they confirm that ADHD and ODD share a strong general factor of disruptive behavior (DB) in this clinical sample. Furthermore, unlike the subdimensions of ADHD, we found that the specific ODD factor explained as much true score variance as the general DB factor. This suggests that a common scale of ADHD and ODD may prove to be as important as a separate ODD subscale to assess externalizing problems in school-age children. However, all other subscales of ADHD may not explain sufficient true score variance once the impact of the general DB factor has been taken into consideration. In accordance with the trait-impulsivity model, we also showed that all factors, but predominantly the general factor and specific inattention factor, predicted parent-rated impairment, and that predominantly ODD and impulsivity are predicted by environmental risk factors.

On the Effect of Preferential Sampling in Spatial Prediction

EPA Science Inventory

The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

40 CFR Appendix IV to Part 600 - Sample Fuel Economy Labels for 2008 and Later Model Year Vehicles

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sample Fuel Economy Labels for 2008 and Later Model Year Vehicles IV Appendix IV to Part 600 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Pt. 600, App. IV Appendix IV to Part 600...

A novel approach to assessing environmental disturbance based on habitat selection by zebra fish as a model organism.

PubMed

Araújo, Cristiano V M; Griffith, Daniel M; Vera-Vera, Victoria; Jentzsch, Paul Vargas; Cervera, Laura; Nieto-Ariza, Beatriz; Salvatierra, David; Erazo, Santiago; Jaramillo, Rusbel; Ramos, Luis A; Moreira-Santos, Matilde; Ribeiro, Rui

2018-04-01

Aquatic ecotoxicity assays used to assess ecological risk assume that organisms living in a contaminated habitat are forcedly exposed to the contamination. This assumption neglects the ability of organisms to detect and avoid contamination by moving towards less disturbed habitats, as long as connectivity exists. In fluvial systems, many environmental parameters vary spatially and thus condition organisms' habitat selection. We assessed the preference of zebra fish (Danio rerio) when exposed to water samples from two western Ecuadorian rivers with apparently distinct disturbance levels: Pescadillo River (highly disturbed) and Oro River (moderately disturbed). Using a non-forced exposure system in which water samples from each river were arranged according to their spatial sequence in the field and connected to allow individuals to move freely among samples, we assayed habitat selection by D. rerio to assess environmental disturbance in the two rivers. Fish exposed to Pescadillo River samples preferred downstream samples near the confluence zone with the Oro River. Fish exposed to Oro River samples preferred upstream waters. When exposed to samples from both rivers simultaneously, fish exhibited the same pattern of habitat selection by preferring the Oro River samples. Given that the rivers are connected, preference for the Oro River enabled us to predict a depression in fish populations in the Pescadillo River. Although these findings indicate higher disturbance levels in the Pescadillo River, none of the physical-chemical variables measured was significantly correlated with the preference pattern towards the Oro River. Non-linear spatial patterns of habitat preference suggest that other environmental parameters like urban or agricultural contaminants play an important role in the model organism's habitat selection in these rivers. The non-forced exposure system represents a habitat selection-based approach that can serve as a valuable tool to unravel the factors that dictate organisms' spatial distribution in connected ecosystems. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of dissolved organic matter on pre-equilibrium passive sampling: A predictive QSAR modeling study.

PubMed

Lin, Wei; Jiang, Ruifen; Shen, Yong; Xiong, Yaxin; Hu, Sizi; Xu, Jianqiao; Ouyang, Gangfeng

2018-04-13

Pre-equilibrium passive sampling is a simple and promising technique for studying sampling kinetics, which is crucial to determine the distribution, transfer and fate of hydrophobic organic compounds (HOCs) in environmental water and organisms. Environmental water samples contain complex matrices that complicate the traditional calibration process for obtaining the accurate rate constants. This study proposed a QSAR model to predict the sampling rate constants of HOCs (polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and pesticides) in aqueous systems containing complex matrices. A homemade flow-through system was established to simulate an actual aqueous environment containing dissolved organic matter (DOM) i.e. humic acid (HA) and (2-Hydroxypropyl)-β-cyclodextrin (β-HPCD)), and to obtain the experimental rate constants. Then, a quantitative structure-activity relationship (QSAR) model using Genetic Algorithm-Multiple Linear Regression (GA-MLR) was found to correlate the experimental rate constants to the system state including physicochemical parameters of the HOCs and DOM which were calculated and selected as descriptors by Density Functional Theory (DFT) and Chem 3D. The experimental results showed that the rate constants significantly increased as the concentration of DOM increased, and the enhancement factors of 70-fold and 34-fold were observed for the HOCs in HA and β-HPCD, respectively. The established QSAR model was validated as credible (R Adj. 2 =0.862) and predictable (Q 2 =0.835) in estimating the rate constants of HOCs for complex aqueous sampling, and a probable mechanism was developed by comparison to the reported theoretical study. The present study established a QSAR model of passive sampling rate constants and calibrated the effect of DOM on the sampling kinetics. Copyright © 2018 Elsevier B.V. All rights reserved.

Forecasting peak asthma admissions in London: an application of quantile regression models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-07-01

Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.

Forecasting peak asthma admissions in London: an application of quantile regression models

NASA Astrophysics Data System (ADS)

Soyiri, Ireneous N.; Reidpath, Daniel D.; Sarran, Christophe

2013-07-01

Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Environmental impact on young children's participation in home-based activities.

PubMed

Albrecht, Erin C; Khetani, Mary A

2017-04-01

To test the effect of child, family, and environmental factors on young children's participation in home-based activities. Caregivers of young children were recruited using convenience and snowball sampling. Participants were 395 caregivers of children (222 males, 173 females) aged from 1 month to 5 years and 11 months. Demographic items and the home section of the Young Children's Participation and Environment Measure were administered online, followed by completion of the daily activities, mobility, and social/cognitive domains of the Pediatric Evaluation of Disability Inventory Computer Adaptive Test by telephone interview. A structural equation model fitted the data well (comparative fit index=0.91) and explained 31.2% of the variance in perceived environmental support and 42.5% of the variance in home involvement. Functional limitations and performance had an indirect effect on young children's participation through their effect on perceived environmental support. Specifically, fewer functional limitations and higher task performance were associated with greater environmental support, which in turn predicted higher levels of home involvement. Results suggest the importance of a young child's functional abilities and task performance on caregiver perceptions of environmental support at home, and the impact of environmental support on a child's participation in home-based activities during the early childhood period. Results warrant replication with more diverse samples to evaluate model generalizability. © 2016 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.

Psychomotor development, environmental stimulation, and socioeconomic level of preschoolers in Temuco, Chile.

PubMed

Doussoulin Sanhueza, Arlette

2006-01-01

This research was designed to describe the psychomotor development, environmental stimulation, and the socioeconomic condition of preschool children attending three educational institutions in the city of Temuco, Chile. The sample included 81 boys and girls whose age ranged from three to four years. The Test de Desarrollo Psicomotor (The Psychomotor Development Test), or TEPSI, was used to assess psychomotor development; the Home Observation Measurement of the Environment (HOME) Scale was used to evaluate environmental stimulation; and the Socioeconomic Standardization Model was used to categorize children's socioeconomic status. The highest statistical correlation was observed between psychomotor development and environmental stimulation when comparing all three parameters across the sample. Environmental stimulation may be the most relevant parameter in the study of psychomotor development of children. Socioeconomic status alone does not seem to be strongly related to children's psychomotor development in the Temuco region of Chile.

Similarity in functional brain architecture between rest and specific task modes: A model of genetic and environmental contributions to episodic memory.

PubMed

Petrican, Raluca; Levine, Brian T

2018-06-21

The ability to keep a mental record of specific past events, dubbed episodic memory (EM), is key to lifespan adaptation. Nonetheless, the neural mechanisms underlying its typical inter-individual variability remain poorly understood. To address this issue, we tested whether individual differences in EM could be predicted from levels of functional brain re-organization between rest and task modes relevant to the transformation of perceptual information into mental representations (relational processing, meaning extraction, online maintenance versus updating of bound perceptual features). To probe the trait specificity of our model, we included three additional core mental functions, processing speed, abstract reasoning, and cognitive control. Finally, we investigated the extent to which our proposed model reflected genetic versus environmental contributions to EM variability. Hypotheses were tested by applying graph theoretical analysis and structural equation modeling to resting state and task fMRI data from two samples of participants in the Human Connectome Project (Sample 1: N = 338 unrelated individuals; Sample 2: N = 268 monozygotic vs. dizygotic twins [134 same-sex pairs]). Levels of functional brain reorganization between rest and the scrutinized task modes, particularly relational processing and online maintenance of bound perceptual features, contributed substantially to variations in both EM and abstract reasoning (but not in cognitive control or processing speed) among the younger adults in our sample, implying a substantial neurofunctional overlap, at least during this life stage. Similarity in functional organization between rest and each of the scrutinized task modes drew on distinguishable neural resources and showed differential susceptibility to genetic versus environmental influences. Our results suggest that variability on complex traits, such as EM, is supported by neural mechanisms comprising multiple components, each reflecting a distinct pattern of genetic versus environmental contributions and whose relative importance may vary across typical versus psychopathological development. Copyright © 2018. Published by Elsevier Inc.

Evaluating environmental modeling and sampling data with biomarker data to identify sources and routes of exposure

NASA Astrophysics Data System (ADS)

Shin, Hyeong-Moo; McKone, Thomas E.; Bennett, Deborah H.

2013-04-01

Exposure to environmental chemicals results from multiple sources, environmental media, and exposure routes. Ideally, modeled exposures should be compared to biomonitoring data. This study compares the magnitude and variation of modeled polycyclic aromatic hydrocarbons (PAHs) exposures resulting from emissions to outdoor and indoor air and estimated exposure inferred from biomarker levels. Outdoor emissions result in both inhalation and food-based exposures. We modeled PAH intake doses using U.S. EPA's 2002 National Air Toxics Assessment (NATA) county-level emissions data for outdoor inhalation, the CalTOX model for food ingestion (based on NATA emissions), and indoor air concentrations from field studies for indoor inhalation. We then compared the modeled intake with the measured urine levels of hydroxy-PAH metabolites from the 2001-2002 National Health and Nutrition Examination Survey (NHANES) survey as quantifiable human intake of PAH parent-compounds. Lognormal probability plots of modeled intakes and estimated intakes inferred from biomarkers suggest that a primary route of exposure to naphthalene, fluorene, and phenanthrene for the U.S. population is likely inhalation from indoor sources. For benzo(a)pyrene, the predominant exposure route is likely from food ingestion resulting from multi-pathway transport and bioaccumulation due to outdoor emissions. Multiple routes of exposure are important for pyrene. We also considered the sensitivity of the predicted exposure to the proportion of the total naphthalene production volume emitted to the indoor environment. The comparison of PAH biomarkers with exposure variability estimated from models and sample data for various exposure pathways supports that both indoor and outdoor models are needed to capture the sources and routes of exposure to environmental contaminants.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.

Environmental Predictors of US County Mortality Patterns on a National Basis.

PubMed

Chan, Melissa P L; Weinhold, Robert S; Thomas, Reuben; Gohlke, Julia M; Portier, Christopher J

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level.

Environmental Predictors of US County Mortality Patterns on a National Basis

PubMed Central

Thomas, Reuben; Gohlke, Julia M.; Portier, Christopher J.

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level. PMID:26629706

Examining the genetic and environmental associations among spelling, reading fluency, reading comprehension and a high stakes reading test in a combined sample of third and fourth grade students

PubMed Central

Little, Callie W.

2015-01-01

The present study is an examination of the genetic and environmental effects on the associations among reading fluency, spelling and earlier reading comprehension on a later reading comprehension outcome (FCAT) in a combined sample of 3rd and 4th grade students using data from the 2011-2012 school year of the Florida Twin project on Reading (Taylor et al., 2013). A genetically sensitive model was applied to the data with results indicating a common genetic component among all four measures, along with shared and non-shared environmental influences common between reading fluency, spelling and FCAT. PMID:26770052

Evidence of hepatitis A virus circulation in central Argentina: seroprevalence and environmental surveillance.

PubMed

Yanez, Laura A; Lucero, Noelia S; Barril, Patricia A; Díaz, María Del P; Tenaglia, María M; Spinsanti, Lorena I; Nates, Silvia V; Isa, María B; Ré, Viviana E

2014-01-01

Hepatitis A virus (HAV) has shown intermediate endemicity in Argentina, but notification of clinical cases has decreased since the introduction of the vaccine in 2005. In order to get insight into the local circulation of this virus after four years of the official introduction of the vaccine, the aims of this study were to provide information on HAV immune status of the adult population of Córdoba city and to conduct environmental surveillance of HAV in sewage and river samples in the same region. The prevalence of anti-HAV was determined by EIA in 416 samples of people (without prior vaccination) from Córdoba city (2009-2010). Spline regression models were estimated under generalized additive models. Environmental surveillance was conducted in river and sewage samples collected in the same period. Viral detection was performed by RT-Nested PCR of the 5'UTR. In Córdoba, the global prevalence of anti-HAV was 73.5%. It increased with age (p<0.0001) and it was associated with the low-income population (OR: 1.14; 95% CI 1.05-1.25). This prevalence decreased in younger age groups, especially in the high-income population. Environmental monitoring revealed the presence of HAV (IA) in 20.8% and 16.1% of wastewater and river samples, respectively. As a consequence of a decrease in HAV circulation due to improvements in immunization, socio-economic and hygienic conditions, young adults are becoming increasingly susceptible to HAV infections. Environmental monitoring demonstrated that HAV circulates in the local population; therefore, health care systems should consider the implementation of preventive measures for susceptible adults in order to reduce the risk of HAV infection. Copyright © 2013 Elsevier B.V. All rights reserved.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Developing a Comprehensive Model of Risk and Protective Factors That Can Predict Spelling at Age Seven: Findings from a Community Sample of Victorian Children

ERIC Educational Resources Information Center

Serry, Tanya Anne; Castles, Anne; Mensah, Fiona K.; Bavin, Edith L.; Eadie, Patricia; Pezic, Angela; Prior, Margot; Bretherton, Lesley; Reilly, Sheena

2015-01-01

The paper reports on a study designed to develop a risk model that can best predict single-word spelling in seven-year-old children when they were aged 4 and 5. Test measures, personal characteristics and environmental influences were all considered as variables from a community sample of 971 children. Strong concurrent correlations were found…

SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS

EPA Science Inventory

Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...

Bioenhanced dissolution of dense non-aqueous phase of trichloroethylene as affected by iron reducing conditions: model systems and environmental samples.

PubMed

Paul, Laiby; Smolders, Erik

2015-01-01

The anaerobic biotransformation of trichloroethylene (TCE) can be affected by competing electron acceptors such as Fe (III). This study assessed the role of Fe (III) reduction on the bioenhanced dissolution of TCE dense non-aqueous phase liquid (DNAPL). Columns were set up as 1-D diffusion cells consisting of a lower DNAPL layer, a layer with an aquifer substratum and an upper water layer that is regularly refreshed. The substrata used were either inert sand or sand coated with 2-line ferrihydrite (HFO) or two environmental Fe (III) containing samples. The columns were inoculated with KB-1 and were repeatedly fed with formate. In none of the diffusion cells, vinyl chloride or ethene was detected while dissolved and extractable Fe (II) increased strongly during 60 d of incubation. The cis-DCE concentration peaked at 4.0 cm from the DNAPL (inert sand) while it was at 3.4 cm (sand+HFO), 1.7 cm and 2.5 cm (environmental samples). The TCE concentration gradients near the DNAPL indicate that the DNAPL dissolution rate was larger than that in an abiotic cell by factors 1.3 (inert sand), 1.0 (sand+HFO) and 2.2 (both environmental samples). This results show that high bioavailable Fe (III) in HFO reduces the TCE degradation by competitive Fe (III) reduction, yielding lower bioenhanced dissolution. However, Fe (III) reduction in environmental samples was not reducing TCE degradation and the dissolution factor was even larger than that of inert sand. It is speculated that physical factors, e.g. micro-niches in the environmental samples protect microorganisms from toxic concentrations of TCE. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of potential influence factors on background urinary benzene concentration among a non-smoking, non-occupationally exposed general population sample.

PubMed

Campagna, Marcello; Satta, Giannina; Campo, Laura; Flore, Valeria; Ibba, Antonio; Meloni, Michele; Tocco, Maria Giuseppina; Avataneo, Giuseppe; Flore, Costantino; Fustinoni, Silvia; Cocco, Pierluigi

2014-01-01

Analytical difficulties and lack of a biological exposure index and reference values have prevented using unmetabolized urinary benzene (UB) excretion as a biomarker of low-level environmental exposure. To explore what environmental factors beyond active smoking may contribute to environmental exposure to benzene, we monitored UB excretion in a non-smoking, non-occupationally exposed sample of the general population. Two spot urine samples were obtained from 86 non-smoking, non-occupationally exposed subjects, selected among a random sample of the general population of the metropolitan area of Cagliari (Sardinia, Italy), at 8:00 a.m. (UBm) and 8:00 p.m. (UBe). UB was measured by headspace solid-phase microextraction (HS-SPME) followed by gas chromatography-mass spectrometry analysis. Questionnaire information on personal and environmental exposures during the sampling day was gathered with personal interviews. Multivariate analysis of variance and multiple regression model were applied to investigate the role of such variables on the level of UB. The ninety-fifth percentile of UBe in this population was 311.5 ng/L, which is tentatively proposed as the UB guidance value for unexposed populations. UBm and urban residence were the only predictors of a significant increase in UBe excretion. Self-reported residential vehicular traffic will not account for the excess median value among urban residents; commuting time among urban residents showed a suggestive nonsignificant linear correlation with UBe, but the small sample size prevented reliable inference to be drawn. Age, environmental tobacco smoking, employment status and body mass index did not affect UB excretion. Our findings support the use of unmetabolized UB as a specific and sensitive biomarker of low-level environmental exposure to benzene.

Approach for environmental baseline water sampling

USGS Publications Warehouse

Smith, K.S.

2011-01-01

Samples collected during the exploration phase of mining represent baseline conditions at the site. As such, they can be very important in forecasting potential environmental impacts should mining proceed, and can become measurements against which future changes are compared. Constituents in stream water draining mined and mineralized areas tend to be geochemically, spatially, and temporally variable, which presents challenges in collecting both exploration and baseline water-quality samples. Because short-term (daily) variations can complicate long-term trends, it is important to consider recent findings concerning geochemical variability of stream-water constituents at short-term timescales in designing sampling plans. Also, adequate water-quality information is key to forecasting potential ecological impacts from mining. Therefore, it is useful to collect baseline water samples adequate tor geochemical and toxicological modeling. This requires complete chemical analyses of dissolved constituents that include major and minor chemical elements as well as physicochemical properties (including pH, specific conductance, dissolved oxygen) and dissolved organic carbon. Applying chemical-equilibrium and appropriate toxicological models to water-quality information leads to an understanding of the speciation, transport, sequestration, bioavailability, and aquatic toxicity of potential contaminants. Insights gained from geochemical and toxicological modeling of water-quality data can be used to design appropriate mitigation and for economic planning for future mining activities.

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

PubMed

Syfert, Mindy M; Smith, Matthew J; Coomes, David A

2013-01-01

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

Can cloud point-based enrichment, preservation, and detection methods help to bridge gaps in aquatic nanometrology?

PubMed

Duester, Lars; Fabricius, Anne-Lena; Jakobtorweihen, Sven; Philippe, Allan; Weigl, Florian; Wimmer, Andreas; Schuster, Michael; Nazar, Muhammad Faizan

2016-11-01

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

Genetic and Environmental Contributions to the Development of Childhood Aggression

ERIC Educational Resources Information Center

Lubke, Gitta H.; McArtor, Daniel B.; Boomsma, Dorret I.; Bartels, Meike

2018-01-01

Longitudinal data from a large sample of twins participating in the Netherlands Twin Register (n = 42,827, age range 3-16) were analyzed to investigate the genetic and environmental contributions to childhood aggression. Genetic auto-regressive (simplex) models were used to assess whether the same genes are involved or whether new genes come into…

MID-ATLANTIC COASTAL STREAMS STUDY: STATISTICAL DESIGN FOR REGIONAL ASSESSMENT AND LANDSCAPE MODEL DEVELOPMENT

EPA Science Inventory

A network of stream-sampling sites was developed for the Mid-Atlantic Coastal Plain (New Jersey through North Carolina) a collaborative study between the U.S. Environmental Protection Agency and the U.S. Geological Survey. A stratified random sampling with unequal weighting was u...

MID-ATLANTIC COASTAL STREAMS STUDY: STATISTICAL DESIGN FOR REGIONAL ASSESSMENT AND LANDSCAPE MODEL DEVELOPMENT

EPA Science Inventory

A network of stream-sampling sites was developed for the Mid-Atlantic Coastal Plain (New Jersey through North Carolina) as part of collaborative research between the U.S. Environmental Protection Agency and the U.S. Geological Survey. A stratified random sampling with unequal wei...

Revisiting the environmental Kuznets curve and pollution haven hypotheses: MIKTA sample.

PubMed

Bakirtas, Ibrahim; Cetin, Mumin Atalay

2017-08-01

This study aims to examine the validity of the environmental Kuznets curve (EKC) and pollution haven hypotheses in Mexico, Indonesia, South Korea, Turkey, and Australia (MIKTA) countries from 1982 to 2011 by using a panel vector auto regressive (PVAR) model. Empirical findings imply that the EKC hypothesis is rejected by the MIKTA sample. However, PVAR estimations reveal Granger causality from income level, foreign direct investment (FDI) inward, and energy consumption to CO 2 emissions. Orthogonalized impulse-response functions are derived from PVAR estimations. According to the analysis results, the response of CO 2 emissions to a shock on FDI is positive. These results assert that FDI has a detrimental effect on environmental quality in MIKTA countries which means the pollution haven hypothesis is confirmed by the MIKTA sample. Therefore, MIKTA countries should revise their current economic growth plans to provide sustainable development and also re-organize their legal infrastructure to induce usage of renewable energy sources.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

A motivational model for environmentally responsible behavior.

PubMed

Tabernero, Carmen; Hernández, Bernardo

2012-07-01

This paper presents a study examining whether self-efficacy and intrinsic motivation are related to environmentally responsible behavior (ERB). The study analysed past environmental behavior, self-regulatory mechanisms (self-efficacy, satisfaction, goals), and intrinsic and extrinsic motivation in relation to ERBs in a sample of 156 university students. Results show that all the motivational variables studied are linked to ERB. The effects of self-efficacy on ERB are mediated by the intrinsic motivation responses of the participants. A theoretical model was created by means of path analysis, revealing the power of motivational variables to predict ERB. Structural equation modeling was used to test and fit the research model. The role of motivational variables is discussed with a view to creating adequate learning contexts and experiences to generate interest and new sensations in which self-efficacy and affective reactions play an important role.

An integrated modeling approach for estimating the water quality benefits of conservation practices at the river basin scale

USDA-ARS?s Scientific Manuscript database

The USDA initiated the Conservation Effects Assessment Project (CEAP) to quantify the environmental benefits of conservation practices at regional and national scales. For this assessment, a sampling and modeling approach is used. This paper provides a technical overview of the modeling approach use...

Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992–2010

USGS Publications Warehouse

Martin, Jeffrey D.; Eberle, Michael

2011-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ("spiked" QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as a percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in apparent environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report presents data and models related to the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as "pesticides") that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 through 2010 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Models of recovery, based on robust, locally weighted scatterplot smooths (lowess smooths) of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Predictive accuracy of combined genetic and environmental risk scores.

PubMed

Dudbridge, Frank; Pashayan, Nora; Yang, Jian

2018-02-01

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.

Predictive accuracy of combined genetic and environmental risk scores

PubMed Central

Pashayan, Nora; Yang, Jian

2017-01-01

ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508

Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone.

PubMed

Bennema, S C; Ducheyne, E; Vercruysse, J; Claerebout, E; Hendrickx, G; Charlier, J

2011-02-01

Fasciola hepatica, a trematode parasite with a worldwide distribution, is the cause of important production losses in the dairy industry. Diagnosis is hampered by the fact that the infection is mostly subclinical. To increase awareness and develop regionally adapted control methods, knowledge on the spatial distribution of economically important infection levels is needed. Previous studies modelling the spatial distribution of F. hepatica are mostly based on single cross-sectional samplings and have focussed on climatic and environmental factors, often ignoring management factors. This study investigated the associations between management, climatic and environmental factors affecting the spatial distribution of infection with F. hepatica in dairy herds in a temperate climate zone (Flanders, Belgium) over three consecutive years. A bulk-tank milk antibody ELISA was used to measure F. hepatica infection levels in a random sample of 1762 dairy herds in the autumns of 2006, 2007 and 2008. The infection levels were included in a Geographic Information System together with meteorological, environmental and management parameters. Logistic regression models were used to determine associations between possible risk factors and infection levels. The prevalence and spatial distribution of F. hepatica was relatively stable, with small interannual differences in prevalence and location of clusters. The logistic regression model based on both management and climatic/environmental factors included the factors: annual rainfall, mowing of pastures, proportion of grazed grass in the diet and length of grazing season as significant predictors and described the spatial distribution of F. hepatica better than the model based on climatic/environmental factors only (annual rainfall, elevation and slope, soil type), with an Area Under the Curve of the Receiver Operating Characteristic of 0.68 compared with 0.62. The results indicate that in temperate climate zones without large climatic and environmental variation, management factors affect the spatial distribution of F. hepatica, and should be included in future spatial distribution models. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Chemistry of groundwater discharge inferred from longitudinal river sampling

NASA Astrophysics Data System (ADS)

Batlle-Aguilar, J.; Harrington, G. A.; Leblanc, M.; Welch, C.; Cook, P. G.

2014-02-01

We present an approach for identifying groundwater discharge chemistry and quantifying spatially distributed groundwater discharge into rivers based on longitudinal synoptic sampling and flow gauging of a river. The method is demonstrated using a 450 km reach of a tropical river in Australia. Results obtained from sampling for environmental tracers, major ions, and selected trace element chemistry were used to calibrate a steady state one-dimensional advective transport model of tracer distribution along the river. The model closely reproduced river discharge and environmental tracer and chemistry composition along the study length. It provided a detailed longitudinal profile of groundwater inflow chemistry and discharge rates, revealing that regional fractured mudstones in the central part of the catchment contributed up to 40% of all groundwater discharge. Detailed analysis of model calibration errors and modeled/measured groundwater ion ratios elucidated that groundwater discharging in the top of the catchment is a mixture of local groundwater and bank storage return flow, making the method potentially useful to differentiate between local and regional sourced groundwater discharge. As the error in tracer concentration induced by a flow event applies equally to any conservative tracer, we show that major ion ratios can still be resolved with minimal error when river samples are collected during transient flow conditions. The ability of the method to infer groundwater inflow chemistry from longitudinal river sampling is particularly attractive in remote areas where access to groundwater is limited or not possible, and for identification of actual fluxes of salts and/or specific contaminant sources.

Understanding Hong Kong Adolescents' Environmental Intention: The Roles of Media Exposure, Subjective Norm, and Perceived Behavioral Control

ERIC Educational Resources Information Center

Lee, Kaman

2011-01-01

This article explores how exposure to environment-related media content, subjective norm and perceived behavioral control play a role in Hong Kong adolescents' environmental intention. The author conducted a survey with a sample of 1,012 (465 male, 547 female) adolescents in Hong Kong. Structural equation modeling confirms that exposure to…

Modeling Environmental Influences in the Psyllaephagus bliteus (Hymenoptera: Encyrtidae)-Glycaspis brimblecombei (Hemiptera: Aphalaridae) Parasitoid-Host System.

PubMed

Margiotta, M; Bella, S; Buffa, F; Caleca, V; Floris, I; Giorno, V; Lo Verde, G; Rapisarda, C; Sasso, R; Suma, P; Tortorici, F; Laudonia, S

2017-04-01

Glycaspis brimblecombei Moore (Hemiptera: Aphalaridae) is an invasive psyllid introduced into the Mediterranean area, where it affects several species of Eucalyptus. Psyllaephagus bliteus Riek (Hymenoptera: Encyrtidae) is a specialized parasitoid of this psyllid that was accidentally introduced into Italy in 2011. We developed a model of this host-parasitoid system that accounts for the influence of environmental conditions on the G. brimblecombei population dynamics and P. bliteus parasitism rates in the natural ecosystem. The Lotka-Volterra-based model predicts non-constant host growth and parasitoid mortality rates in association with variation in environmental conditions. The model was tested by analyzing sampling data collected in Naples in 2011 (before the parasitoid was present) and defining several environmental patterns, termed Temperature-Rain or T-R patterns, which correspond to the host growth rate. A mean value of the host growth rate was assigned to each T-R pattern, as well as a variation of the parasitoid mortality rate based on temperature thresholds. The proposed model was applied in simulation tests related to T-R patterns carried out with a data series sampled between June 2014 and July 2015 in five Italian sites located in Campania, Lazio, Sicily, and Sardinia regions. The simulation results showed that the proposed model provides an accurate approximation of population trends, although oscillation details may not be apparent. Results predict a 64% reduction in G. brimblecombei population density owing to P. bliteus parasitoid activity. Our results are discussed with respect to features of the host-parasitoid interaction that could be exploited in future biological control programs. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Uncertainty quantification in Rothermel's Model using an efficient sampling method

Treesearch

Edwin Jimenez; M. Yousuff Hussaini; Scott L. Goodrick

2007-01-01

The purpose of the present work is to quantify parametric uncertainty in Rothermel’s wildland fire spread model (implemented in software such as BehavePlus3 and FARSITE), which is undoubtedly among the most widely used fire spread models in the United States. This model consists of a nonlinear system of equations that relates environmental variables (input parameter...

A Conceptual Framework for Evaluating the Domains of Applicability of Ecological Models and its Implementation in the Ecological Production Function Library - International Society for Ecological Modelling Conference

EPA Science Inventory

The use of computational ecological models to inform environmental management and policy has proliferated in the past 25 years. These models have become essential tools as linkages and feedbacks between human actions and ecological responses can be complex, and as funds for sampl...

Variability And Uncertainty Analysis Of Contaminant Transport Model Using Fuzzy Latin Hypercube Sampling Technique

NASA Astrophysics Data System (ADS)

Kumar, V.; Nayagum, D.; Thornton, S.; Banwart, S.; Schuhmacher2, M.; Lerner, D.

2006-12-01

Characterization of uncertainty associated with groundwater quality models is often of critical importance, as for example in cases where environmental models are employed in risk assessment. Insufficient data, inherent variability and estimation errors of environmental model parameters introduce uncertainty into model predictions. However, uncertainty analysis using conventional methods such as standard Monte Carlo sampling (MCS) may not be efficient, or even suitable, for complex, computationally demanding models and involving different nature of parametric variability and uncertainty. General MCS or variant of MCS such as Latin Hypercube Sampling (LHS) assumes variability and uncertainty as a single random entity and the generated samples are treated as crisp assuming vagueness as randomness. Also when the models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outputs. An improved systematic variability and uncertainty analysis can provide insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. The present study aims to introduce, Fuzzy Latin Hypercube Sampling (FLHS), a hybrid approach of incorporating cognitive and noncognitive uncertainties. The noncognitive uncertainty such as physical randomness, statistical uncertainty due to limited information, etc can be described by its own probability density function (PDF); whereas the cognitive uncertainty such estimation error etc can be described by the membership function for its fuzziness and confidence interval by ?-cuts. An important property of this theory is its ability to merge inexact generated data of LHS approach to increase the quality of information. The FLHS technique ensures that the entire range of each variable is sampled with proper incorporation of uncertainty and variability. A fuzzified statistical summary of the model results will produce indices of sensitivity and uncertainty that relate the effects of heterogeneity and uncertainty of input variables to model predictions. The feasibility of the method is validated to assess uncertainty propagation of parameter values for estimation of the contamination level of a drinking water supply well due to transport of dissolved phenolics from a contaminated site in the UK.

A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS

EPA Science Inventory

A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...

Nature and Nurture Strike (Out) Again.

ERIC Educational Resources Information Center

Scarr, Sandra; Weinberg, Richard A.

1979-01-01

A reply to Plomin's critique and some criticisms of Munsinger's review of adopted child literature are presented. Selective bias in adoptee samples, implicit assumptions in models that lead to heritability estimates, and problems produced by lack of an accepted model of environmental transmission are also discussed. (Author/RD)

EMMMA: A web-based system for environmental mercury mapping, modeling, and analysis

USGS Publications Warehouse

Hearn,, Paul P.; Wente, Stephen P.; Donato, David I.; Aguinaldo, John J.

2006-01-01

tissue, atmospheric emissions and deposition, stream sediments, soils, and coal) and mercuryrelated data (mine locations); 2) Interactively view and access predictions of the National Descriptive Model of Mercury in Fish (NDMMF) at 4,976 sites and 6,829 sampling events (events are unique combinations of site and sampling date) across the United States; and 3) Use interactive mapping and graphing capabilities to visualize spatial and temporal trends and study relationships between mercury and other variables.

Modeling abundance effects in distance sampling

USGS Publications Warehouse

Royle, J. Andrew; Dawson, D.K.; Bates, S.

2004-01-01

Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective of such studies is to evaluate the relationship between abundance or density and covariates that describe animal habitat or other environmental influences. However, little attention has been focused on methods of modeling abundance covariate effects in conventional distance-sampling models. In this paper we propose a distance-sampling model that accommodates covariate effects on abundance. The model is based on specification of the distance-sampling likelihood at the level of the sample unit in terms of local abundance (for each sampling unit). This model is augmented with a Poisson regression model for local abundance that is parameterized in terms of available covariates. Maximum-likelihood estimation of detection and density parameters is based on the integrated likelihood, wherein local abundance is removed from the likelihood by integration. We provide an example using avian point-transect data of Ovenbirds (Seiurus aurocapillus) collected using a distance-sampling protocol and two measures of habitat structure (understory cover and basal area of overstory trees). The model yields a sensible description (positive effect of understory cover, negative effect on basal area) of the relationship between habitat and Ovenbird density that can be used to evaluate the effects of habitat management on Ovenbird populations.

The oilspill risk analysis model of the U. S. Geological Survey

USGS Publications Warehouse

Smith, R.A.; Slack, J.R.; Wyant, Timothy; Lanfear, K.J.

1982-01-01

The U.S. Geological Survey has developed an oilspill risk analysis model to aid in estimating the environmental hazards of developing oil resources in Outer Continental Shelf (OCS) lease areas. The large, computerized model analyzes the probability of spill occurrence, as well as the likely paths or trajectories of spills in relation to the locations of recreational and biological resources which may be vulnerable. The analytical methodology can easily incorporate estimates of weathering rates , slick dispersion, and possible mitigating effects of cleanup. The probability of spill occurrence is estimated from information on the anticipated level of oil production and method of route of transport. Spill movement is modeled in Monte Carlo fashion with a sample of 500 spills per season, each transported by monthly surface current vectors and wind velocities sampled from 3-hour wind transition matrices. Transition matrices are based on historic wind records grouped in 41 wind velocity classes, and are constructed seasonally for up to six wind stations. Locations and monthly vulnerabilities of up to 31 categories of environmental resources are digitized within an 800,000 square kilometer study area. Model output includes tables of conditional impact probabilities (that is, the probability of hitting a target, given that a spill has occured), as well as probability distributions for oilspills occurring and contacting environmental resources within preselected vulnerability time horizons. (USGS)

The oilspill risk analysis model of the U. S. Geological Survey

USGS Publications Warehouse

Smith, R.A.; Slack, J.R.; Wyant, T.; Lanfear, K.J.

1980-01-01

The U.S. Geological Survey has developed an oilspill risk analysis model to aid in estimating the environmental hazards of developing oil resources in Outer Continental Shelf (OCS) lease areas. The large, computerized model analyzes the probability of spill occurrence, as well as the likely paths or trajectories of spills in relation to the locations of recreational and biological resources which may be vulnerable. The analytical methodology can easily incorporate estimates of weathering rates , slick dispersion, and possible mitigating effects of cleanup. The probability of spill occurrence is estimated from information on the anticipated level of oil production and method and route of transport. Spill movement is modeled in Monte Carlo fashion with a sample of 500 spills per season, each transported by monthly surface current vectors and wind velocities sampled from 3-hour wind transition matrices. Transition matrices are based on historic wind records grouped in 41 wind velocity classes, and are constructed seasonally for up to six wind stations. Locations and monthly vulnerabilities of up to 31 categories of environmental resources are digitized within an 800,000 square kilometer study area. Model output includes tables of conditional impact probabilities (that is, the probability of hitting a target, given that a spill has occurred), as well as probability distributions for oilspills occurring and contacting environmental resources within preselected vulnerability time horizons. (USGS)

A Conceptual Framework for Evaluating the Domains of Applicability of Ecological Models and its Implementation in the Ecological Production Function Library

EPA Science Inventory

The use of computational ecological models to inform environmental management and policy has proliferated in the past 25 years. These models have become essential tools as linkages and feedbacks between human actions and ecological responses can be complex, and as funds for sampl...

Alpha 2 LASSO Data Bundles

DOE Data Explorer

Gustafson, William Jr; Vogelmann, Andrew; Endo, Satoshi; Toto, Tami; Xiao, Heng; Li, Zhijin; Cheng, Xiaoping; Kim, Jinwon; Krishna, Bhargavi

2015-08-31

The Alpha 2 release is the second release from the LASSO Pilot Phase that builds upon the Alpha 1 release. Alpha 2 contains additional diagnostics in the data bundles and focuses on cases from spring-summer 2016. A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input include model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

Surveying Europe's Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA.

PubMed

Vörös, Judit; Márton, Orsolya; Schmidt, Benedikt R; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence.

Multiple site receptor modeling with a minimal spanning tree combined with a Kohonen neural network

NASA Astrophysics Data System (ADS)

Hopke, Philip K.

1999-12-01

A combination of two pattern recognition methods has been developed that allows the generation of geographical emission maps form multivariate environmental data. In such a projection into a visually interpretable subspace by a Kohonen Self-Organizing Feature Map, the topology of the higher dimensional variables space can be preserved, but parts of the information about the correct neighborhood among the sample vectors will be lost. This can partly be compensated for by an additional projection of Prim's Minimal Spanning Tree into the trained neural network. This new environmental receptor modeling technique has been adapted for multiple sampling sites. The behavior of the method has been studied using simulated data. Subsequently, the method has been applied to mapping data sets from the Southern California Air Quality Study. The projection of a 17 chemical variables measured at up to 8 sampling sites provided a 2D, visually interpretable, geometrically reasonable arrangement of air pollution source sin the South Coast Air Basin.

Presence of organophosphorus pesticide oxygen analogs in air samples

NASA Astrophysics Data System (ADS)

Armstrong, Jenna L.; Fenske, Richard A.; Yost, Michael G.; Galvin, Kit; Tchong-French, Maria; Yu, Jianbo

2013-02-01

A number of recent toxicity studies have highlighted the increased potency of oxygen analogs (oxons) of several organophosphorus (OP) pesticides. These findings were a major concern after environmental oxons were identified in environmental samples from air and surfaces following agricultural spray applications in California and Washington State. This paper reports on the validity of oxygen analog measurements in air samples for the OP pesticide, chlorpyrifos. Controlled environmental and laboratory experiments were used to examine artificial formation of chlorpyrifos-oxon using OSHA Versatile Sampling (OVS) tubes as recommended by NIOSH method 5600. Additionally, we compared expected chlorpyrifos-oxon attributable to artificial transformation to observed chlorpyrifos-oxon in field samples from a 2008 Washington State Department of Health air monitoring study using non-parametric statistical methods. The amount of artificially transformed oxon was then modeled to determine the amount of oxon present in the environment. Toxicity equivalency factors (TEFs) for chlorpyrifos-oxon were used to calculate chlorpyrifos-equivalent air concentrations. The results demonstrate that the NIOSH-recommended sampling matrix (OVS tubes with XAD-2 resin) was found to artificially transform up to 30% of chlorpyrifos to chlorpyrifos-oxon, with higher percentages at lower concentrations (<30 ng m-3) typical of ambient or residential levels. Overall, the 2008 study data had significantly greater oxon than expected by artificial transformation, but the exact amount of environmental oxon in air remains difficult to quantify with the current sampling method. Failure to conduct laboratory analysis for chlorpyrifos-oxon may result in underestimation of total pesticide concentration when using XAD-2 resin matrices for occupational or residential sampling. Alternative methods that can accurately measure both OP pesticides and their oxygen analogs should be used for air sampling, and a toxicity equivalent factor approach should be used to determine potential health risks from exposures.

Development and Validation of Pathogen Environmental Monitoring Programs for Small Cheese Processing Facilities.

PubMed

Beno, Sarah M; Stasiewicz, Matthew J; Andrus, Alexis D; Ralyea, Robert D; Kent, David J; Martin, Nicole H; Wiedmann, Martin; Boor, Kathryn J

2016-12-01

Pathogen environmental monitoring programs (EMPs) are essential for food processing facilities of all sizes that produce ready-to-eat food products exposed to the processing environment. We developed, implemented, and evaluated EMPs targeting Listeria spp. and Salmonella in nine small cheese processing facilities, including seven farmstead facilities. Individual EMPs with monthly sample collection protocols were designed specifically for each facility. Salmonella was detected in only one facility, with likely introduction from the adjacent farm indicated by pulsed-field gel electrophoresis data. Listeria spp. were isolated from all nine facilities during routine sampling. The overall Listeria spp. (other than Listeria monocytogenes ) and L. monocytogenes prevalences in the 4,430 environmental samples collected were 6.03 and 1.35%, respectively. Molecular characterization and subtyping data suggested persistence of a given Listeria spp. strain in seven facilities and persistence of L. monocytogenes in four facilities. To assess routine sampling plans, validation sampling for Listeria spp. was performed in seven facilities after at least 6 months of routine sampling. This validation sampling was performed by independent individuals and included collection of 50 to 150 samples per facility, based on statistical sample size calculations. Two of the facilities had a significantly higher frequency of detection of Listeria spp. during the validation sampling than during routine sampling, whereas two other facilities had significantly lower frequencies of detection. This study provides a model for a science- and statistics-based approach to developing and validating pathogen EMPs.

Development of property-transfer models for estimating the hydraulic properties of deep sediments at the Idaho National Engineering and Environmental Laboratory, Idaho

USGS Publications Warehouse

Winfield, Kari A.

2005-01-01

Because characterizing the unsaturated hydraulic properties of sediments over large areas or depths is costly and time consuming, development of models that predict these properties from more easily measured bulk-physical properties is desirable. At the Idaho National Engineering and Environmental Laboratory, the unsaturated zone is composed of thick basalt flow sequences interbedded with thinner sedimentary layers. Determining the unsaturated hydraulic properties of sedimentary layers is one step in understanding water flow and solute transport processes through this complex unsaturated system. Multiple linear regression was used to construct simple property-transfer models for estimating the water-retention curve and saturated hydraulic conductivity of deep sediments at the Idaho National Engineering and Environmental Laboratory. The regression models were developed from 109 core sample subsets with laboratory measurements of hydraulic and bulk-physical properties. The core samples were collected at depths of 9 to 175 meters at two facilities within the southwestern portion of the Idaho National Engineering and Environmental Laboratory-the Radioactive Waste Management Complex, and the Vadose Zone Research Park southwest of the Idaho Nuclear Technology and Engineering Center. Four regression models were developed using bulk-physical property measurements (bulk density, particle density, and particle size) as the potential explanatory variables. Three representations of the particle-size distribution were compared: (1) textural-class percentages (gravel, sand, silt, and clay), (2) geometric statistics (mean and standard deviation), and (3) graphical statistics (median and uniformity coefficient). The four response variables, estimated from linear combinations of the bulk-physical properties, included saturated hydraulic conductivity and three parameters that define the water-retention curve. For each core sample,values of each water-retention parameter were estimated from the appropriate regression equation and used to calculate an estimated water-retention curve. The degree to which the estimated curve approximated the measured curve was quantified using a goodness-of-fit indicator, the root-mean-square error. Comparison of the root-mean-square-error distributions for each alternative particle-size model showed that the estimated water-retention curves were insensitive to the way the particle-size distribution was represented. Bulk density, the median particle diameter, and the uniformity coefficient were chosen as input parameters for the final models. The property-transfer models developed in this study allow easy determination of hydraulic properties without need for their direct measurement. Additionally, the models provide the basis for development of theoretical models that rely on physical relationships between the pore-size distribution and the bulk-physical properties of the media. With this adaptation, the property-transfer models should have greater application throughout the Idaho National Engineering and Environmental Laboratory and other geographic locations.

The complexity of personality: advantages of a genetically sensitive multi-group design.

PubMed

Hahn, Elisabeth; Spinath, Frank M; Siedler, Thomas; Wagner, Gert G; Schupp, Jürgen; Kandler, Christian

2012-03-01

Findings from many behavioral genetic studies utilizing the classical twin design suggest that genetic and non-shared environmental effects play a significant role in human personality traits. This study focuses on the methodological advantages of extending the sampling frame to include multiple dyads of relatives. We investigated the sensitivity of heritability estimates to the inclusion of sibling pairs, mother-child pairs and grandparent-grandchild pairs from the German Socio-Economic Panel Study in addition to a classical German twin sample consisting of monozygotic- and dizygotic twins. The resulting dataset contained 1.308 pairs, including 202 monozygotic and 147 dizygotic twin pairs, along with 419 sibling pairs, 438 mother-child dyads, and 102 grandparent-child dyads. This genetically sensitive multi-group design allowed the simultaneous testing of additive and non-additive genetic, common and specific environmental effects, including cultural transmission and twin-specific environmental influences. Using manifest and latent modeling of phenotypes (i.e., controlling for measurement error), we compare results from the extended sample with those from the twin sample alone and discuss implications for future research.

Environmental Factors Affecting Asthma and Allergies: Predicting and Simulating Downwind Exposure to Airborne Pollen

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey; Estes, Sue; Sprigg, William A.; Nickovic, Slobodan; Huete, Alfredo; Solano, Ramon; Ratana, Piyachat; Jiang, Zhangyan; Flowers, Len; Zelicoff, Alan

2009-01-01

This slide presentation reviews the environmental factors that affect asthma and allergies and work to predict and simulate the downwind exposure to airborne pollen. Using a modification of Dust REgional Atmosphere Model (DREAM) that incorporates phenology (i.e. PREAM) the aim was to predict concentrations of pollen in time and space. The strategy for using the model to simulate downwind pollen dispersal, and evaluate the results. Using MODerate-resolution Imaging Spectroradiometer (MODIS), to get seasonal sampling of Juniper, the pollen chosen for the study, land cover on a near daily basis. The results of the model are reviewed.

Systems engineering approach to environmental risk management: A case study of depleted uranium at test area C-64, Eglin Air Force Base, Florida. Master`s thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carter, C.M.; Fortmann, K.M.; Hill, S.W.

1994-12-01

Environmental restoration is an area of concern in an environmentally conscious world. Much effort is required to clean up the environment and promote environmentally sound methods for managing current land use. In light of the public consciousness with the latter topic, the United States Air Force must also take an active role in addressing these environmental issues with respect to current and future USAF base land use. This thesis uses the systems engineering technique to assess human health risks and to evaluate risk management options with respect to depleted uranium contamination in the sampled region of Test Area (TA) C-64more » at Eglin Air Force Base (AFB). The research combines the disciplines of environmental data collection, DU soil concentration distribution modeling, ground water modeling, particle resuspension modeling, exposure assessment, health hazard assessment, and uncertainty analysis to characterize the test area. These disciplines are required to quantify current and future health risks, as well as to recommend cost effective ways to increase confidence in health risk assessment and remediation options.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, B.; Martino, L.

The White Phosphorus Burning Pits (WPP) Area of Concern (AOC) is a site of about 5.5 acres (2.2 ha) located in the J-Field Study Area, in the Edgewood Area of Aberdeen Proving Ground (APG), Maryland (Figure 1.1). Considerable information about the WPP exists as a result of efforts to characterize the hazards associated with J-Field. Contamination in the J-Field Study Area was first detected during an environmental survey of the APG Edgewood Area conducted in 1977 and 1978 (Nemeth et al. 1983) by the U.S. Army Toxic and Hazardous Materials Agency (USATHAMA; predecessor to the U.S. Army Environmental Center). Asmore » part of a subsequent USATHAMA environmental survey, 11 wells were installed and sampled at J-Field (three of them at the WPP) (Nemeth 1989). Contamination was also detected in 1983 during a munitions disposal survey conducted by Princeton Aqua Science (1984). The Princeton Aqua Science investigation involved installing and sampling nine wells (four at the WPP) and collecting and analyzing surficial and deep composite soil samples (including samples from the WPP area). In 1986, the U.S. Environmental Protection Agency (EPA) issued a Resource Conservation and Recovery Act (RCRA) Permit (MD3-21-002-1355) requiring a post-wide RCRA Facility Assessment (RFA) and a hydrogeologic assessment of J-Field. In 1987, the U.S. Geological Survey (USGS) began a two-phase hydrogeologic assessment in which data were collected to model groundwater flow at J-Field. Soil-gas investigations were conducted, several well clusters were installed (four at the WPP), a groundwater flow model was developed, and groundwater and surface water monitoring programs were established that continue today. The results of the USGS study were published by Hughes (1993).« less

Sub-millimeter scale magnetostratigraphy and environmental magnetism of ferromanganese crusts using a scanning SQUID microscope

NASA Astrophysics Data System (ADS)

Oda, H.; Noguchi, A.; Yamamoto, Y.; Usui, A.; Ito, T.; Kawai, J.; Takahashi, H.

2017-12-01

Ferromanganese crusts are chemical sedimentary rock composed mainly of iron-manganese oxide. Because the ferromanganese crusts grow very slowly on the sea floor at rates of 3-10 mm/Ma, long-term deep-sea environmental changes can be reconstructed from the ferromanganese crusts. Thus, it is important to provide reliable age model for the crusts. For the past decades 10Be/9Be dating method has been used extensively to give age models for crusts younger than 15 Ma. Alternatively, sub-millimeter scale magnetostratigraphic study on a ferromanganese crust sample using a scanning SQUID (superconducting quantum interference device) microscope (Kawai et al., 2016; Oda et al., 2016) has been applied successfully (e.g. Oda et al., 2011; Noguchi et al. 2017). Also, environmental magnetic mapping was successful for the ferromanganese crust from the Takuyo Daigo Seamount (Noguchi et al., 2017). The ferromanganese crust used in this study was sampled from the Hanzawa Seamount, Ryukyu trench and the Shotoku Seamount. The vertical component of the magnetic field above thin section samples of the ferromanganese crust was measured using the scanning SQUID microscope on 100 μm grids. Magnetic mapping of the Hanzawa Seamount shows sub-millimeter scale magnetic stripes parallel to lamina. By correlating the boundaries of magnetic stripes with known geomagnetic reversals, we estimated that average growth rate of the Hanzawa Seamount is 2.67 +/- 0.04 mm/Ma , which is consistent with that deduced from the 10Be/9Be dating method (2.56 +/- 0.04 mm/Ma). The crust sample from the Shotoku Seamount used by Oda et al. (2011) shows prominent periodical lamination. Further details are going to be discussed together with the environmental magnetic mapping.

Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

NASA Astrophysics Data System (ADS)

Gao, Jing; Burt, James E.

2017-12-01

This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

Examining the etiological associations among higher-order temperament dimensions

PubMed Central

Allan, Nicholas P.; Mikolajewski, Amy J.; Lonigan, Christopher J.; Hart, Sara A.; Taylor, Jeanette

2014-01-01

A multivariate independent pathway model was used to examine the shared and unique genetic and environmental influences of Positive Affect (PA), Negative Affect (NA), and effortful control (EC) in a sample of 686 twin pairs (M age = 10.07, SD = 1.74). There were common genetic influences and nonshared environmental influences shared across all three temperament dimensions and shared environmental influences in common to NA and EC. There were also significant independent genetic influences unique to PA and NA and significant independent shared environmental influences unique to PA. This study demonstrates that there are genetic and environmental influences that affect the covariance among temperament dimensions as well as unique genetic and environmental influences that influence the dimensions independently. PMID:24729641

40 CFR 600.211-08 - Sample calculation of fuel economy values for labeling.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sample calculation of fuel economy values for labeling. 600.211-08 Section 600.211-08 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Fuel Economy Regulations for 1977 and Later Model...

Preliminary synchrotron analysis of lead in hair from a lead smelter worker

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, R.R.; Kempson, I.M.; Naftel, S.J.

2008-06-09

Synchrotron X-ray fluorescence has been used to study the distribution of lead in a hair sample collected from a lead smelter worker. A mathematical model was used to imitate the transverse scan signal based on the analysis volume and concentration profiles. The results suggest that the Pb originates both from ingestion and environmental exposure, however direct deposition from the environment is the more important source of hair lead. The model could apply equally to any other analysis involving a thin cylindrical sample.

Sampling design for an integrated socioeconomic and ecological survey by using satellite remote sensing and ordination

PubMed Central

Binford, Michael W.; Lee, Tae Jeong; Townsend, Robert M.

2004-01-01

Environmental variability is an important risk factor in rural agricultural communities. Testing models requires empirical sampling that generates data that are representative in both economic and ecological domains. Detrended correspondence analysis of satellite remote sensing data were used to design an effective low-cost sampling protocol for a field study to create an integrated socioeconomic and ecological database when no prior information on ecology of the survey area existed. We stratified the sample for the selection of tambons from various preselected provinces in Thailand based on factor analysis of spectral land-cover classes derived from satellite data. We conducted the survey for the sampled villages in the chosen tambons. The resulting data capture interesting variations in soil productivity and in the timing of good and bad years, which a purely random sample would likely have missed. Thus, this database will allow tests of hypotheses concerning the effect of credit on productivity, the sharing of idiosyncratic risks, and the economic influence of environmental variability. PMID:15254298

Development and validation of a simulation method, PeCHREM, for evaluating spatio-temporal concentration changes of paddy herbicides in rivers.

PubMed

Imaizumi, Yoshitaka; Suzuki, Noriyuki; Shiraishi, Fujio; Nakajima, Daisuke; Serizawa, Shigeko; Sakurai, Takeo; Shiraishi, Hiroaki

2018-01-24

In pesticide risk management in Japan, predicted environmental concentrations are estimated by a tiered approach, and the Ministry of the Environment also performs field surveys to confirm the maximum concentrations of pesticides with risk concerns. To contribute to more efficient and effective field surveys, we developed the Pesticide Chemicals High Resolution Estimation Method (PeCHREM) for estimating spatially and temporally variable emissions of various paddy herbicides from paddy fields to the environment. We used PeCHREM and the G-CIEMS multimedia environmental fate model to predict day-to-day environmental concentration changes of 25 herbicides throughout Japan. To validate the PeCHREM/G-CIEMS model, we also conducted a field survey, in which river waters were sampled at least once every two weeks at seven sites in six prefectures from April to July 2009. In 20 of 139 sampling site-herbicide combinations in which herbicides were detected in at least three samples, all observed concentrations differed from the corresponding prediction by less than one order of magnitude. We also compared peak concentrations and the dates on which the concentrations reached peak values (peak dates) between predictions and observations. The peak concentration differences between predictions and observations were less than one order of magnitude in 66% of the 166 sampling site-herbicide combinations in which herbicide was detected in river water. The observed and predicted peak dates differed by less than two weeks in 79% of these 166 combinations. These results confirm that the PeCHREM/G-CIEMS model can improve the efficiency and effectiveness of surveys by predicting the peak concentrations and peak dates of various herbicides.

Application of PCA and SIMCA statistical analysis of FT-IR spectra for the classification and identification of different slag types with environmental origin.

PubMed

Stumpe, B; Engel, T; Steinweg, B; Marschner, B

2012-04-03

In the past, different slag materials were often used for landscaping and construction purposes or simply dumped. Nowadays German environmental laws strictly control the use of slags, but there is still a remaining part of 35% which is uncontrolled dumped in landfills. Since some slags have high heavy metal contents and different slag types have typical chemical and physical properties that will influence the risk potential and other characteristics of the deposits, an identification of the slag types is needed. We developed a FT-IR-based statistical method to identify different slags classes. Slags samples were collected at different sites throughout various cities within the industrial Ruhr area. Then, spectra of 35 samples from four different slags classes, ladle furnace (LF), blast furnace (BF), oxygen furnace steel (OF), and zinc furnace slags (ZF), were determined in the mid-infrared region (4000-400 cm(-1)). The spectra data sets were subject to statistical classification methods for the separation of separate spectral data of different slag classes. Principal component analysis (PCA) models for each slag class were developed and further used for soft independent modeling of class analogy (SIMCA). Precise classification of slag samples into four different slag classes were achieved using two different SIMCA models stepwise. At first, SIMCA 1 was used for classification of ZF as well as OF slags over the total spectral range. If no correct classification was found, then the spectrum was analyzed with SIMCA 2 at reduced wavenumbers for the classification of LF as well as BF spectra. As a result, we provide a time- and cost-efficient method based on FT-IR spectroscopy for processing and identifying large numbers of environmental slag samples.

Relations Between Environmental and Water-Quality Variables and Escherichia coli in the Cuyahoga River With Emphasis on Turbidity as a Predictor of Recreational Water Quality, Cuyahoga Valley National Park, Ohio, 2008

USGS Publications Warehouse

Brady, Amie M.G.; Plona, Meg B.

2009-01-01

During the recreational season of 2008 (May through August), a regression model relating turbidity to concentrations of Escherichia coli (E. coli) was used to predict recreational water quality in the Cuyahoga River at the historical community of Jaite, within the present city of Brecksville, Ohio, a site centrally located within Cuyahoga Valley National Park. Samples were collected three days per week at Jaite and at three other sites on the river. Concentrations of E. coli were determined and compared to environmental and water-quality measures and to concentrations predicted with a regression model. Linear relations between E. coli concentrations and turbidity, gage height, and rainfall were statistically significant for Jaite. Relations between E. coli concentrations and turbidity were statistically significant for the three additional sites, and relations between E. coli concentrations and gage height were significant at the two sites where gage-height data were available. The turbidity model correctly predicted concentrations of E. coli above or below Ohio's single-sample standard for primary-contact recreation for 77 percent of samples collected at Jaite.

Environmental determinants of Vibrio parahaemolyticus in the Chesapeake Bay.

PubMed

Davis, Benjamin J K; Jacobs, John M; Davis, Meghan F; Schwab, Kellogg J; DePaola, Angelo; Curriero, Frank C

2017-08-25

Vibrio parahaemolyticus naturally-occurs in brackish and marine waters and is one of the leading causes of seafood-borne illness. Previous work studying the ecology of V. parahaemolyticus is often limited in geographic extent and lacking a full range of environmental measures. This study used a unique, large dataset of surface water samples in the Chesapeake Bay ( n =1,385) collected from 148 monitoring stations from 2007 to 2010. Water was analyzed for over 20 environmental parameters with additional meteorological and surrounding land use data. V. parahaemolyticus -specific genetic markers thermolabile hemolysin ( tlh ), thermostable direct hemolysin ( tdh ), and tdh -related hemolysin ( trh ) were assayed using quantitative PCR (qPCR), and interval-censored regression models with non-linear effects were estimated to account for limits of detection and quantitation. tlh was detected in 19.6% of water samples; tdh or trh markers were not detected. Results confirmed previously reported positive associations for V. parahaemolyticus abundance with temperature and turbidity and negative associations with high salinity (> 10-23‰). Furthermore, the salinity relationship was determined to be a function of both low temperature and turbidity, with an increase of either nullifying the high salinity effect. Associations with dissolved oxygen and phosphate also appeared stronger when samples were taken nearby human developments. Renewed focus on the V. parahaemolyticus ecological paradigm is warranted to protect public health. Importance Vibrio parahaemolyticus is one of the leading causes of seafood-borne illness in the United States and across the globe. Exposure is often through consuming raw or undercooked shellfish. Given the natural presence of the bacterium in the marine environment, improved understanding of its environmental determinants is necessary for future preventative measures. This analysis of environmental Vibrio parahaemolyticus is one of only a few that utilize a large dataset measured over a wide geographic and temporal range. The analysis also includes a large number of environmental parameters for Vibrio modeling, many of which have previously only been tested sporadically, and some of which have not been considered before. The results of the analysis revealed previously unknown relationships between salinity, turbidity, and temperature that provide significant insight into the abundance and persistence of V. parahaemolyticus bacterium in the environment. This information will be essential for developing environmental forecast models for the bacterium. Copyright © 2017 American Society for Microbiology.

Surveillance of Salmonella enteritidis in layer houses: a retrospective comparison of the Food and Drug Administration's egg safety rule (2010-2011) and the California Egg Quality Assurance Program (2007-2011).

PubMed

Pitesky, Maurice; Charlton, Bruce; Bland, Mark; Rolfe, Dan

2013-03-01

Between July 2007 and December 2011, 2660 environmental drag swab samples were collected in total from California layer flocks on behalf of the California Egg Quality Assurance Program (CEQAP), the egg safety rule (21 CFR Parts 16 and 118) of the Food and Drug Administration (FDA), or both. The samples were processed by the California Animal Health and Food Safety Lab, and positive or negative results for Salmonella enterica serovar Enteritidis (SE) were recorded. This study retrospectively compares the differences between the FDA and CEQAP programs with respect to their SE environmental sampling surveillance results. To accomplish this comparison, two different CEQAP (new and old) data sets representing different SE environmental surveillance approaches in the life of the flock were compared against each other and against the FDA's SE environmental testing plan. Significant differences were noted between the CEQAP and FDA programs with respect to the prevalence of SE in the farm environment. Analyses of the prevalence of SE at different stages in the flock's life cycle (chick papers, preproduction, midproduction, postmolt, and premarket) found the highest prevalence of SE in premarket (11.9%), followed by postmolt (3.5%) and midproduction (3.4%), and there was a tie between chick papers and preproduction (2.1%). To assess the main effects of the presence of SE in the farm environment, backwards binary logistic regression was used. Of six independent variables examined (age of flock, year, season, owner, CEQAP membership, and analysis of pooled samples vs. individual swabs), only age of flock, owner, and year were determined to be significant factors in the final model. Although CEQAP membership and pooling vs. individuals swabs were not included in the final model, Pearson chi-square tests did show significantly higher odds of SE for non-CEQAP member farms and higher odds of SE in pooled samples vs. individual swabs.

DEVELOPMENT OF A PASSIVE, IN SITU, INTEGRATIVE ...

EPA Pesticide Factsheets

Until recently, hydrophobic, bioconcentratable compounds have been the primary focus of most environmental organic contaminant investigations, There is an increasing realization that a holistic hazard assessment of complex environmental contaminant mixtures requires data on the concentrations of hydrophilic organic contaminants as well. This group of compounds includes a wide variety of chemicals, including potentially endocrine disrupting and estrogenic contaminants which have been shown to contribute to numerous abnormalities such as impaired reproduction in aquatic organisms exposed in environmental waters. To address this issue, we developed a passive, in situ, sampling device (the Polar Organic Chemical Integrative Sampler or POCIS) which integratively concentrates trace levels of complex mixtures of hydrophilic environmental contaminants, enables the determination of their time-weighted average water concentrations and provides a screening assessment of the toxicological significance of the complex mixture of waterborne contaminants. Using a prototype sampler (effective membrane sampling surface area = 18.2 cm 2) linear uptake of selected herbicides and pharmaceuticals was observed for up to 56 days. Estimation of the ambient water concentrations of chemicals of interest is achieved by using appropriate uptake models and determination of POCIS chemical sampling rates. The research focused on in the subtasks is the development and application of state-of

Experimental and environmental factors affect spurious detection of ecological thresholds

USGS Publications Warehouse

Daily, Jonathan P.; Hitt, Nathaniel P.; Smith, David; Snyder, Craig D.

2012-01-01

Threshold detection methods are increasingly popular for assessing nonlinear responses to environmental change, but their statistical performance remains poorly understood. We simulated linear change in stream benthic macroinvertebrate communities and evaluated the performance of commonly used threshold detection methods based on model fitting (piecewise quantile regression [PQR]), data partitioning (nonparametric change point analysis [NCPA]), and a hybrid approach (significant zero crossings [SiZer]). We demonstrated that false detection of ecological thresholds (type I errors) and inferences on threshold locations are influenced by sample size, rate of linear change, and frequency of observations across the environmental gradient (i.e., sample-environment distribution, SED). However, the relative importance of these factors varied among statistical methods and between inference types. False detection rates were influenced primarily by user-selected parameters for PQR (τ) and SiZer (bandwidth) and secondarily by sample size (for PQR) and SED (for SiZer). In contrast, the location of reported thresholds was influenced primarily by SED. Bootstrapped confidence intervals for NCPA threshold locations revealed strong correspondence to SED. We conclude that the choice of statistical methods for threshold detection should be matched to experimental and environmental constraints to minimize false detection rates and avoid spurious inferences regarding threshold location.

Assessment of agricultural groundwater users in Iran: a cultural environmental bias

NASA Astrophysics Data System (ADS)

Salehi, Saeid; Chizari, Mohammad; Sadighi, Hassan; Bijani, Masoud

2018-02-01

Many environmental problems are rooted in human behavior. This study aimed to explore the causal effect of cultural environmental bias on `sustainable behavior' among agricultural groundwater users in Fars province, Iran, according to Klockner's comprehensive model. A survey-based research project was conducted to gathering data on the paradigm of environmental psychology. The sample included agricultural groundwater users ( n = 296) who were selected at random within a structured sampling regime involving study areas that represent three (higher, medium and lower) bounds of the agricultural-groundwater-vulnerability spectrum. Results showed that the "environment as ductile (EnAD)" variable was a strong determinant of sustainable behavior as it related to groundwater use, and that EnAE had the highest causal effect on the behavior of agricultural groundwater users. The adjusted model explained 41% variance of "groundwater sustainable behavior". Based on the results, the groundwater sustainable behaviors of agricultural groundwater users were found to be affected by personal and subjective norm variables and that they are influenced by casual effects of the "environment as ductile (EnAD)" variable. The conclusions reflect the Fars agricultural groundwater users' attitude or worldview on groundwater as an unrecoverable resource; thus, it is necessary that scientific disciplines like hydrogeology and psycho-sociology be considered together in a comprehensive approach for every groundwater study.

Environmental Management Competitive Pressure Effect on SME Environmental Innovation Activities: A Green Supply Chain Perspective

NASA Astrophysics Data System (ADS)

Rashid, A. A.; Sidek, A. A.; Suffian, S. A.; Daud, M. R. C.

2018-01-01

The idea of assimilating green supply chain is to integrate and establish environmental management into the supply chain practices. The study aims to explore how environmental management competitive pressure influences a SME company in Malaysia to incorporate green supply chain integration, which is an efficient platform to develop environmental innovation. This study further advances green supply chain management research in Malaysia by using the method of quantitative analysis to analyze the model developed which data will be collected based on a sample of SMEs in Malaysia in manufacturing sector. The model developed in this study illustrates how environmental management competitive pressure from main competitors affects three fundamental dimensions of green supply chain integration. The research findings suggest that environmental management competitive pressure is a vital driving force for a SME company to incorporate internal and external collaboration in developing green product innovation. From the analysis conducted, the study strongly demonstrated that the best way for a company to counteract competitor’s environmental management success is to first implement strong internal green product development process then move to incorporate external environmental management innovation between their suppliers and customers. The findings also show that internal integration of green product innovation fully mediates the relationship of environmental management competitive pressure and the external integration of green product innovation.

Undergraduate Research and Training in Ion-Beam Analysis of Environmental Materials

NASA Astrophysics Data System (ADS)

Vineyard, Michael F.; Chalise, Sajju; Clark, Morgan L.; LaBrake, Scott M.; McCalmont, Andrew M.; McGuire, Brendan C.; Mendez, Iseinie I.; Watson, Heather C.; Yoskowitz, Joshua T.

We have an active undergraduate research program at the Union College Ion-Beam Analysis Laboratory (UCIBAL) focused on the study of environmental materials. Accelerator-based ion-beam analysis (IBA) is a powerful tool for the study of environmental pollution because it can provide information on a broad range of elements with high sensitivity and low detection limits, is non-destructive, and requires little or no sample preparation. It also provides excellent training for the next generation of environmental scientists. Beams of protons and alpha particles with energies of a few MeV from the 1.1-MV tandem Pelletron accelerator (NEC Model 3SDH) in the UCIBAL are used to characterize environmental samples using IBA techniques such as proton-induced X-ray emission, Rutherford back-scattering, and proton-induced gamma-ray emission. Recent projects include the characterization of atmospheric aerosols in the Adirondack Mountains of upstate New York, the study of heavy metal pollutants in river sediment, measurements of Pb diffusion in sulfide minerals to help constrain the determination of the age of iron meteorites, and the search for heavy metals and toxins in artificial turf.

Re-evaluation of the sorption behaviour of Bromide and Sulfamethazine under field conditions using leaching data and modelling methods

NASA Astrophysics Data System (ADS)

Gassmann, Matthias; Olsson, Oliver; Höper, Heinrich; Hamscher, Gerd; Kümmerer, Klaus

2016-04-01

The simulation of reactive transport in the aquatic environment is hampered by the ambiguity of environmental fate process conceptualizations for a specific substance in the literature. Concepts are usually identified by experimental studies and inverse modelling under controlled lab conditions in order to reduce environmental uncertainties such as uncertain boundary conditions and input data. However, since environmental conditions affect substance behaviour, a re-evaluation might be necessary under environmental conditions which might, in turn, be affected by uncertainties. Using a combination of experimental data and simulations of the leaching behaviour of the veterinary antibiotic Sulfamethazine (SMZ; synonym: sulfadimidine) and the hydrological tracer Bromide (Br) in a field lysimeter, we re-evaluated the sorption concepts of both substances under uncertain field conditions. Sampling data of a field lysimeter experiment in which both substances were applied twice a year with manure and sampled at the bottom of two lysimeters during three subsequent years was used for model set-up and evaluation. The total amount of leached SMZ and Br were 22 μg and 129 mg, respectively. A reactive transport model was parameterized to the conditions of the two lysimeters filled with monoliths (depth 2 m, area 1 m²) of a sandy soil showing a low pH value under which Bromide is sorptive. We used different sorption concepts such as constant and organic-carbon dependent sorption coefficients and instantaneous and kinetic sorption equilibrium. Combining the sorption concepts resulted in four scenarios per substance with different equations for sorption equilibrium and sorption kinetics. The GLUE (Generalized Likelihood Uncertainty Estimation) method was applied to each scenario using parameter ranges found in experimental and modelling studies. The parameter spaces for each scenario were sampled using a Latin Hypercube method which was refined around local model efficiency maxima. Results of the cumulative SMZ leaching simulations suggest a best conceptualization combination of instantaneous sorption to organic carbon which is consistent with the literature. The best Nash-Sutcliffe efficiency (Neff) was 0.96 and the 5th and 95th percentile of the uncertainty estimation were 18 and 27 μg. In contrast, both scenarios of kinetic Br sorption had similar results (Neff =0.99, uncertainty bounds 110-176 mg and 112-176 mg) but were clearly better than instantaneous sorption scenarios. Therefore, only the concept of sorption kinetics could be identified for Br modelling whereas both tested sorption equilibrium coefficient concepts performed equally well. The reasons for this specific case of equifinality may be uncertainties of model input data under field conditions or an insensitivity of the sorption equilibrium method due to relatively low adsorption of Br. Our results show that it may be possible to identify or at least falsify specific sorption concepts under uncertain field conditions using a long-term leaching experiment and modelling methods. Cases of environmental fate concept equifinality arouse the possibility of future model structure uncertainty analysis using an ensemble of models with different environmental fate concepts.

Work plan for focused feasibility study of the toxic burning pits area at J-Field, Aberdeen Proving Ground, Maryland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biang, C.; Benioff, P.; Martino, L.

1995-03-01

The Environmental Management Division (EMD) of Aberdeen Proving Ground (APG), Maryland, is conducting a remedial investigation and feasibility study (RI/FS) of the J-Field area at APG pursuant to the Comprehensive Environmental Response, Compensation, and Liability Act, as amended (CERCIA). J-Field is within the Edgewood Area of APG in Harford County, Maryland. Since World War II, activities in the Edgewood Area have included the development, manufacture, testing, and destruction of chemical agents and munitions. These materials were destroyed at J-Field by open burning and open detonation (OB/OD). Considerable archival information about J-Field exists as a result of efforts by APG staffmore » to characterize the hazards associated with the site. Contamination of J-Field was first detected during an environmental survey of the Edgewood Area conducted in 1977 and 1978 by the US Army Toxic and Hazardous Materials Agency (USATHAMA)(predecessor to the US Army Environmental Center). As part of a subsequent USATHAMA environmental survey, 11 wells were installed and sampled at J-Field. Contamination at J-Field was also detected during a munitions disposal survey conducted by Princeton Aqua Science in 1983. The Princeton Aqua Science investigation involved the installation and sampling of nine wells and the collection and analysis of surficial and deep composite soil samples. In 1986, a Resource Conservation and Recovery Act (RCRA) permit (MD3-21-0021355) requiring a basewide RCRA Facility Assessment (RFA) and a hydrogeologic assessment of J-Field was issued by the US Environmental Protection Agency (EPA). In 1987, the US Geological Survey (USGS) began a two-phased hydrogeologic assessment in which data were collected to model groundwater flow at J-Field. Soil gas investigations were conducted, several well clusters were installed, a groundwater flow model was developed, and groundwater and surface water monitoring programs were established that continue today-« less

Contributions of Genes and Environment to Developmental Change in Alcohol Use.

PubMed

Long, E C; Verhulst, B; Aggen, S H; Kendler, K S; Gillespie, N A

2017-09-01

The precise nature of how genetic and environmental risk factors influence changes in alcohol use (AU) over time has not yet been investigated. Therefore, the aim of the present study is to examine the nature of longitudinal changes in these risk factors to AU from mid-adolescence through young adulthood. Using a large sample of male twins, we compared five developmental models that each makes different predictions regarding the longitudinal changes in genetic and environmental risks for AU. The best-fitting model indicated that genetic influences were consistent with a gradual growth in the liability to AU, whereas unique environmental risk factors were consistent with an accumulation of risks across time. These results imply that two distinct processes influence adolescent AU between the ages of 15-25. Genetic effects influence baseline levels of AU and rates of change across time, while unique environmental effects are more cumulative.

Forecasting extinction risk with nonstationary matrix models.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-02-01

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.

Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification.

PubMed

Shoari, Niloofar; Dubé, Jean-Sébastien; Chenouri, Shoja'eddin

2015-11-01

In environmental studies, concentration measurements frequently fall below detection limits of measuring instruments, resulting in left-censored data. Some studies employ parametric methods such as the maximum likelihood estimator (MLE), robust regression on order statistic (rROS), and gamma regression on order statistic (GROS), while others suggest a non-parametric approach, the Kaplan-Meier method (KM). Using examples of real data from a soil characterization study in Montreal, we highlight the need for additional investigations that aim at unifying the existing literature. A number of studies have examined this issue; however, those considering data skewness and model misspecification are rare. These aspects are investigated in this paper through simulations. Among other findings, results show that for low skewed data, the performance of different statistical methods is comparable, regardless of the censoring percentage and sample size. For highly skewed data, the performance of the MLE method under lognormal and Weibull distributions is questionable; particularly, when the sample size is small or censoring percentage is high. In such conditions, MLE under gamma distribution, rROS, GROS, and KM are less sensitive to skewness. Related to model misspecification, MLE based on lognormal and Weibull distributions provides poor estimates when the true distribution of data is misspecified. However, the methods of rROS, GROS, and MLE under gamma distribution are generally robust to model misspecifications regardless of skewness, sample size, and censoring percentage. Since the characteristics of environmental data (e.g., type of distribution and skewness) are unknown a priori, we suggest using MLE based on gamma distribution, rROS and GROS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Testing the influence of environmental heterogeneity on fish species richness in two biogeographic provinces.

PubMed

Massicotte, Philippe; Proulx, Raphaël; Cabana, Gilbert; Rodríguez, Marco A

2015-01-01

Environmental homogenization in coastal ecosystems impacted by human activities may be an important factor explaining the observed decline in fish species richness. We used fish community data (>200 species) from extensive surveys conducted in two biogeographic provinces (extent >1,000 km) in North America to quantify the relationship between fish species richness and local (grain <10 km(2)) environmental heterogeneity. Our analyses are based on samples collected at nearly 800 stations over a period of five years. We demonstrate that fish species richness in coastal ecosystems is associated locally with the spatial heterogeneity of environmental variables but not with their magnitude. The observed effect of heterogeneity on species richness was substantially greater than that generated by simulations from a random placement model of community assembly, indicating that the observed relationship is unlikely to arise from veil or sampling effects. Our results suggest that restoring or actively protecting areas of high habitat heterogeneity may be of great importance for slowing current trends of decreasing biodiversity in coastal ecosystems.

Overlapping Genetic and Child-Specific Nonshared Environmental Influences on Listening Comprehension, Reading Motivation, and Reading Comprehension

PubMed Central

Schenker, Victoria J.; Petrill, Stephen A.

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. PMID:26321677

Overlapping genetic and child-specific nonshared environmental influences on listening comprehension, reading motivation, and reading comprehension.

PubMed

Schenker, Victoria J; Petrill, Stephen A

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. Copyright © 2015 Elsevier Inc. All rights reserved.

A Degradome-Based Polymerase Chain Reaction to Resolve the Potential of Environmental Samples for 2,4-Dichlorophenol Biodegradation.

PubMed

Ibrahim, Eslam S; Kashef, Mona T; Essam, Tamer M; Ramadan, Mohammed A

2017-12-01

A clean way to overcome environmental pollution is biodegradation. In this perspective, at the intersection of biodegradation and metagenomics, the degradome is defined as the totality of genes related to the biodegradation of a certain compound. It includes the genetic elements from both culturable and uncultured microorganisms. The possibility of assessing the biodegradation potential of an environmental samples, using a degradome-based polymerase chain reaction, was explored. 2,4-Dichlorophenol (2,4-DCP) was chosen as a model and the use of tfdB gene as a biodegradation marker was confirmed by bioinformatics study of TfdB protein. Five primer pairs were designed for the detection of different tfdB gene families. A total of 16 environmental samples were collected from Egyptian agricultural soils and wastewaters and tested for the presence of 2,4-DCP. The biodegradation capacity of 2,4-DCP was determined, for all isolated consortia, to reach up to 350 mg/l. Metagenomic DNA was extracted directly from the soil samples while successive 2,4-DCP-degrading microbial communities were enriched, with increasing concentrations of 2,4-DCP, then their DNA was extracted. The extracted DNA was tested for the distribution of the tfdB gene using a degradome-based polymerase chain reaction. tfdB-1 and tfdB-2 were detected in 5 and 9 samples, respectively. However, the co-existence of both genes was detected only in five samples. All tfdB positive samples were capable of 2,4-DCP degradation. The developed approach of assessing the potential of different environments for degrading 2,4-DCP was successfully measured in terms of accuracy (81.25%) and specificity (100%).

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

PubMed

Colwell, Robert K; Gotelli, Nicholas J; Ashton, Louise A; Beck, Jan; Brehm, Gunnar; Fayle, Tom M; Fiedler, Konrad; Forister, Matthew L; Kessler, Michael; Kitching, Roger L; Klimes, Petr; Kluge, Jürgen; Longino, John T; Maunsell, Sarah C; McCain, Christy M; Moses, Jimmy; Noben, Sarah; Sam, Katerina; Sam, Legi; Shapiro, Arthur M; Wang, Xiangping; Novotny, Vojtech

2016-09-01

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness. © 2016 John Wiley & Sons Ltd/CNRS.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Validated predictive modelling of the environmental resistome

PubMed Central

Amos, Gregory CA; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

2015-01-01

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome. PMID:25679532

Validated predictive modelling of the environmental resistome.

PubMed

Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

2015-06-01

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

Enzymatic electrochemical detection coupled to multivariate calibration for the determination of phenolic compounds in environmental samples.

PubMed

Hernandez, Silvia R; Kergaravat, Silvina V; Pividori, Maria Isabel

2013-03-15

An approach based on the electrochemical detection of the horseradish peroxidase enzymatic reaction by means of square wave voltammetry was developed for the determination of phenolic compounds in environmental samples. First, a systematic optimization procedure of three factors involved in the enzymatic reaction was carried out using response surface methodology through a central composite design. Second, the enzymatic electrochemical detection coupled with a multivariate calibration method based in the partial least-squares technique was optimized for the determination of a mixture of five phenolic compounds, i.e. phenol, p-aminophenol, p-chlorophenol, hydroquinone and pyrocatechol. The calibration and validation sets were built and assessed. In the calibration model, the LODs for phenolic compounds oscillated from 0.6 to 1.4 × 10(-6) mol L(-1). Recoveries for prediction samples were higher than 85%. These compounds were analyzed simultaneously in spiked samples and in water samples collected close to tanneries and landfills. Published by Elsevier B.V.

Genetic and environmental structure of DSM-IV criteria for Antisocial Personality Disorder: a twin study

PubMed Central

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A.; Aggen, Steven H.; Krueger, Robert F.; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-01-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI = 40–67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct. PMID:28108863

Genetic and Environmental Structure of DSM-IV Criteria for Antisocial Personality Disorder: A Twin Study.

PubMed

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A; Aggen, Steven H; Krueger, Robert F; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-05-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40-67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct.

Chemometric comparison of polychlorinated biphenyl residues and toxicologically active polychlorinated biphenyl congeners in the eggs of Forster's Terns (Sterna fosteri)

USGS Publications Warehouse

Schwartz, Ted R.; Stalling, David L.

1991-01-01

The separation and characterization of complex mixtures of polychlorinated biphenyls (PCBs) is approached from the perspective of a problem in chemometrics. A technique for quantitative determination of PCB congeners is described as well as an enrichment technique designed to isolate only those congener residues which induce mixed aryl hydrocarbon hydroxylase enzyme activity. A congener-specific procedure is utilized for the determination of PCBs in whichn-alkyl trichloroacetates are used as retention index marker compounds. Retention indices are reproducible in the range of ±0.05 to ±0.7 depending on the specific congener. A laboratory data base system developed to aid in the editing and quantitation of data generated from capillary gas chromatography was employed to quantitate chromatographic data. Data base management was provided by computer programs written in VAX-DSM (Digital Standard MUMPS) for the VAX-DEC (Digital Equipment Corp.) family of computers.In the chemometric evaluation of these complex chromatographic profiles, data are viewed from a single analysis as a point in multi-dimensional space. Principal Components Analysis was used to obtain a representation of the data in a lower dimensional space. Two-and three-dimensional proections based on sample scores from the principal components models were used to visualize the behavior of Aroclor® mixtures. These models can be used to determine if new sample profiles may be represented by Aroclor profiles. Concentrations of individual congeners of a given chlorine substitution may be summed to form homologue concentration. However, the use of homologue concentrations in classification studies with environmental samples can lead to erroneous conclusions about sample similarity. Chemometric applications are discussed for evaluation of Aroclor mixture analysis and compositional description of environmental residues of PCBs in eggs of Forster's terns (Sterna fosteri) collected from colonies near Lake Poygan and Green Bay, Wisconsin. The application of chemometrics is extended to the comparison of: a) Aroclors and PCB-containing environmental samples; to b) fractions of Aroclors and of environmental samples that have been enriched in congeners which induce mixed aryl hydrocarbon hydroxylase enzyme activity.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Surveying Europe’s Only Cave-Dwelling Chordate Species (Proteus anguinus) Using Environmental DNA

PubMed Central

Márton, Orsolya; Schmidt, Benedikt R.; Gál, Júlia Tünde; Jelić, Dušan

2017-01-01

In surveillance of subterranean fauna, especially in the case of rare or elusive aquatic species, traditional techniques used for epigean species are often not feasible. We developed a non-invasive survey method based on environmental DNA (eDNA) to detect the presence of the red-listed cave-dwelling amphibian, Proteus anguinus, in the caves of the Dinaric Karst. We tested the method in fifteen caves in Croatia, from which the species was previously recorded or expected to occur. We successfully confirmed the presence of P. anguinus from ten caves and detected the species for the first time in five others. Using a hierarchical occupancy model we compared the availability and detection probability of eDNA of two water sampling methods, filtration and precipitation. The statistical analysis showed that both availability and detection probability depended on the method and estimates for both probabilities were higher using filter samples than for precipitation samples. Combining reliable field and laboratory methods with robust statistical modeling will give the best estimates of species occurrence. PMID:28129383

Where You Live Matters: Localising Environmental Impacts on Health, Nutrition and Poverty in Cambodia Using Small Area Estimation Techniques

NASA Astrophysics Data System (ADS)

Nilsen, K.; van Soesbergen, A.; Matthews, Z.

2016-12-01

Socioeconomic development depends on local environments. However, the scientific evidence quantifying the impact of environmental factors on health, nutrition and poverty at subnational levels is limited. This is because socioeconomic indicators are derived from sample surveys representative only at aggregate levels compared to environmental variables mostly available in high-resolution grids. Cambodia was selected because of its commitment to development in the context of a rapidly deteriorating environment. Having made considerable progress since 2005, access to health services is limited, a quarter of the population is still poor and 40% rural children are malnourished. Cambodia is also facing considerable environmental challenges including high deforestation rates, land degradation and natural hazards. Addressing existing gaps in the knowledge of environmental impacts on health and livelihoods, this study applies small area estimation (SAE) to quantify health, nutritional and poverty outcomes in the context of local environments. SAE produces reliable subnational estimates of socioeconomic outcomes available only from sample surveys by combining them with information from auxiliary sources (census). A model is used to explain common trades across areas and a random effect structure is applied to explain the observed extra heterogeneity. SAE models predicting health, nutrition and poverty outcomes excluding and including contextual environmental variables on natural hazards vulnerability, forest cover, climate, and agricultural production are compared. Results are mapped at regional and district levels to spatially assess the impacts of environmental variation on the outcomes. Inter and intra-regional inequalities are also estimated to examine the efficacy of health/socioeconomic policy targeting based on geographic location. Preliminary results suggest that localised environmental factors have considerable impacts on the indicators estimated and should therefore not be ignored. While there are large regional differences, pockets of malnutrition, poverty and inequitable health outcomes within regions are identified. The inequality decomposition shows under and over-coverage of geographical targeting when environmental factors are taken into account.

Measured and predicted environmental concentrations of carbamazepine, diclofenac, and metoprolol in small and medium rivers in northern Germany.

PubMed

Meyer, Wibke; Reich, Margrit; Beier, Silvio; Behrendt, Joachim; Gulyas, Holger; Otterpohl, Ralf

2016-08-01

This study evaluated the impact of secondary municipal effluent discharge on carbamazepine, diclofenac, and metoprolol concentrations in small and medium rivers in northern Germany and compared the measured environmental concentrations (MECs) to the predicted environmental concentrations (PECs) calculated with four well-established models. During a 1-year sampling period, secondary effluent grab samples were collected at four wastewater treatment plants (WWTPs) together with grab samples from the receiving waters upstream and downstream from the wastewater discharge points. The carbamazepine, diclofenac, and metoprolol concentrations were analyzed with high-performance liquid chromatography-tandem mass spectrometry (HPLC/MS-MS) after solid phase extraction. In the secondary effluents, 84-790 ng/L carbamazepine, 395-2100 ng/L diclofenac, and 745-5000 ng/L metoprolol were detected. The carbamazepine, diclofenac, and metoprolol concentrations analyzed in the rivers downstream from the secondary effluent discharge sites ranged from <5 to 68, 370, and 520 ng/L, respectively. Most of the downstream pharmaceutical concentrations were markedly higher than the corresponding upstream concentrations. The impact of wastewater discharge on the MECs in rivers downstream from the WWTPs was clearly demonstrated, but the correlations of the MECs with dilution factors were poor. The smallest rivers exhibited the largest maximum MECs and the widest ranges of MECs downstream from the wastewater discharge point. Three of the four tested models were conservative, as they showed higher PECs than the MECs in the rivers downstream from the WWTPs. However, the most detailed model underestimated the diclofenac concentrations.

Genetic and environmental influences on last-year major depression in adulthood: a highly heritable stable liability but strong environmental effects on 1-year prevalence.

PubMed

Kendler, K S; Gardner, C O

2017-07-01

This study seeks to clarify the contribution of temporally stable and occasion-specific genetic and environmental influences on risk for major depression (MD). Our sample was 2153 members of female-female twin pairs from the Virginia Twin Registry. We examined four personal interview waves conducted over an 8-year period with MD in the last year defined by DSM-IV criteria. We fitted a structural equation model to the data using classic Mx. The model included genetic and environmental risk factors for a latent, stable vulnerability to MD and for episodes in each of the four waves. The best-fit model was simple and included genetic and unique environmental influences on the latent liability to MD and unique wave-specific environmental effects. The path from latent liability to MD in the last year was constant over time, moderate in magnitude (+0.65) and weaker than the impact of occasion-specific environmental effects (+0.76). Heritability of the latent stable liability to MD was much higher (78%) than that estimated for last-year MD (32%). Of the total unique environmental influences on MD, 13% reflected enduring consequences of earlier environmental insults, 17% diagnostic error and 70% wave-specific short-lived environmental stressors. Both genetic influences on MD and MD heritability are stable over middle adulthood. However, the largest influence on last-year MD is short-lived environmental effects. As predicted by genetic theory, the heritability of MD is increased substantially by measurement at multiple time points largely through the reduction of the effects of measurement error and short-term environmental risk factors.

Electrical output of bryophyte microbial fuel cell systems is sufficient to power a radio or an environmental sensor.

PubMed

Bombelli, Paolo; Dennis, Ross J; Felder, Fabienne; Cooper, Matt B; Madras Rajaraman Iyer, Durgaprasad; Royles, Jessica; Harrison, Susan T L; Smith, Alison G; Harrison, C Jill; Howe, Christopher J

2016-10-01

Plant microbial fuel cells are a recently developed technology that exploits photosynthesis in vascular plants by harnessing solar energy and generating electrical power. In this study, the model moss species Physcomitrella patens , and other environmental samples of mosses, have been used to develop a non-vascular bryophyte microbial fuel cell (bryoMFC). A novel three-dimensional anodic matrix was successfully created and characterized and was further tested in a bryoMFC to determine the capacity of mosses to generate electrical power. The importance of anodophilic microorganisms in the bryoMFC was also determined. It was found that the non-sterile bryoMFCs operated with P. patens delivered over an order of magnitude higher peak power output (2.6 ± 0.6 µW m -2 ) than bryoMFCs kept in near-sterile conditions (0.2 ± 0.1 µW m -2 ). These results confirm the importance of the microbial populations for delivering electrons to the anode in a bryoMFC. When the bryoMFCs were operated with environmental samples of moss (non-sterile) the peak power output reached 6.7 ± 0.6 mW m -2 . The bryoMFCs operated with environmental samples of moss were able to power a commercial radio receiver or an environmental sensor (LCD desktop weather station).

Electrical output of bryophyte microbial fuel cell systems is sufficient to power a radio or an environmental sensor

PubMed Central

Dennis, Ross J.; Felder, Fabienne; Cooper, Matt B.; Royles, Jessica; Harrison, Susan T. L.; Smith, Alison G.; Howe, Christopher J.

2016-01-01

Plant microbial fuel cells are a recently developed technology that exploits photosynthesis in vascular plants by harnessing solar energy and generating electrical power. In this study, the model moss species Physcomitrella patens, and other environmental samples of mosses, have been used to develop a non-vascular bryophyte microbial fuel cell (bryoMFC). A novel three-dimensional anodic matrix was successfully created and characterized and was further tested in a bryoMFC to determine the capacity of mosses to generate electrical power. The importance of anodophilic microorganisms in the bryoMFC was also determined. It was found that the non-sterile bryoMFCs operated with P. patens delivered over an order of magnitude higher peak power output (2.6 ± 0.6 µW m−2) than bryoMFCs kept in near-sterile conditions (0.2 ± 0.1 µW m−2). These results confirm the importance of the microbial populations for delivering electrons to the anode in a bryoMFC. When the bryoMFCs were operated with environmental samples of moss (non-sterile) the peak power output reached 6.7 ± 0.6 mW m−2. The bryoMFCs operated with environmental samples of moss were able to power a commercial radio receiver or an environmental sensor (LCD desktop weather station). PMID:27853542

Re-occupancy of breeding territories by ferruginous hawks in Wyoming: Relationships to environmental and anthropogenic factors

Treesearch

Zachary P. Wallace; Patricia L. Kennedy; John R. Squires; Robert J. Oakleaf; Lucretia E. Olson; Katie M. Dugger

2016-01-01

Grassland and shrubland birds are declining globally due in part to anthropogenic habitat modification. Because population performance of these species is also influenced by nonanthropogenic factors, it is important to incorporate all relevant ecological drivers into demographic models.We used design-based sampling and occupancy models to test relationships of...

Fitting species-accumulation functions and assessing regional land use impacts on avian diversity

Treesearch

Curtis H. Flather

1996-01-01

As one samples species from a particular assemblage, the initial rapid rate with which new species are encountered declines with increasing effort. Nine candidate models to characterize species-accumulation functions were compared in a search for a model that consistently fit geographically extensive avian survey data from a wide range of environmental conditions....

Application of Influence Diagrams in Identifying Soviet Satellite Missions

DTIC Science & Technology

1990-12-01

Probabilities Comparison ......................... 58 35. Continuous Model Variables ............................ 59 36. Sample Inclination Data...diagramming is a method which allows the simple construction of a model to illustrate the interrelationships which exist among variables by capturing an...environmental monitoring systems. The module also contained an array of instruments for geophysical and astrophysical experimentation . 4.3.14.3 Soyuz. The Soyuz

The role of hydrodynamics, matrix and sampling duration in passive sampling of polar compounds with Empore SDB-RPS disks.

PubMed

Vermeirssen, Etiënne L M; Asmin, Josef; Escher, Beate I; Kwon, Jung-Hwan; Steimen, Irene; Hollender, Juliane

2008-01-01

There is an increasing need to monitor concentrations of polar organic contaminants in the aquatic environment. Integrative passive samplers can be used to assess time weighted average aqueous concentrations, provided calibration data are available and sampling rates are known. The sampling rate depends on environmental factors, such as temperature and water flow rate. Here we introduce an apparatus to investigate the sampling properties of passive samplers using river-like flow conditions and ambient environmental matrices: river water and treated sewage effluent. As a model sampler we selected Empore SDB-RPS disks in a Chemcatcher housing. The disks were exposed for 1 to 8 days at flow rates between 0.03 and 0.4 m s(-1). Samples were analysed using a bioassay for estrogenic activity and by LC-MS-MS target analysis of the pharmaceuticals sulfamethoxazole, carbamazepine and clarithromycin. In order to assess sampling rates of SDB disks, we also measured aqueous concentrations of the pharmaceuticals. Sampling rates increased with increasing flow rate and this relationship was not affected by the environmental matrix. However, SDB disks were only sampling in the integrative mode at low flow rates <0.1 m s(-1) and/or for short sampling times. The duration of linear uptake was particularly short for sulfamethoxazole (1 day) and longer for clarithromycin (5 days). At 0.03 m s(-1) and 12-14 degrees C, the sampling rate of SDB disks was 0.09 L day(-1) for clarithromycin, 0.14 L day(-1) for sulfamethoxazole and 0.25 L day(-1) for carbamazepine. The results show that under controlled conditions, SDB disks can be effectively used as passive sampling devices.

Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling

PubMed Central

Ye, Hao; Beamish, Richard J.; Glaser, Sarah M.; Grant, Sue C. H.; Hsieh, Chih-hao; Richards, Laura J.; Schnute, Jon T.; Sugihara, George

2015-01-01

It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner–recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts. PMID:25733874

Error and Uncertainty Analysis for Ecological Modeling and Simulation

DTIC Science & Technology

2001-12-01

management (LRAM) accounting for environmental, training, and economic factors. In the ELVS methodology, soil erosion status is used as a quantitative...Monte-Carlo approach. The optimization is realized through economic functions or on decision constraints, such as, unit sample cost, number of samples... nitrate flux to the Gulf of Mexico. Nature (Brief Communication) 414: 166-167. (Uncertainty analysis done with SERDP software) Gertner, G., G

Genetic signatures of natural selection in a model invasive ascidian

NASA Astrophysics Data System (ADS)

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-03-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

Late Holocene volcanic activity and environmental change in Highland Guatemala

NASA Astrophysics Data System (ADS)

Lohse, Jon C.; Hamilton, W. Derek; Brenner, Mark; Curtis, Jason; Inomata, Takeshi; Morgan, Molly; Cardona, Karla; Aoyama, Kazuo; Yonenobu, Hitoshi

2018-07-01

We present a record of late Holocene volcanic eruptions with elemental data for a sequence of sampled tephras from Lake Amatitlan in Highland Guatemala. Our tephrochronology is anchored by a Bayesian P_Sequence age-depth model based on multiple AMS radiocarbon dates. We compare our record against a previously published study from the same area to understand the record of volcanism and environmental changes. This work has implications for understanding the effects of climate and other environmental changes that may be related to the emission of volcanic aerosols at local, regional and global scales.

Tobacco advertising, environmental smoking bans, and smoking in Chinese urban areas.

PubMed

Yang, Tingzhong; Rockett, Ian R H; Li, Mu; Xu, Xiaochao; Gu, Yaming

2012-07-01

To evaluate whether cigarette smoking in Chinese urban areas was respectively associated with exposure to tobacco advertising and smoking bans in households, workplaces, and public places. Participants were 4735 urban residents aged 15 years and older, who were identified through multi-stage quota-sampling conducted in six Chinese cities. Data were collected on individual sociodemographics and smoking status, and regional tobacco control measures. The sample was characterized in terms of smoking prevalence, and multilevel logistic models were employed to analyze the association between smoking and tobacco advertising and environmental smoking restrictions, respectively. Smoking prevalence was 30%. Multilevel logistic regression analysis showed that smoking was positively associated with exposure to tobacco advertising, and negatively associated with workplace and household smoking bans. The association of smoking with both tobacco advertising and environmental smoking bans further justifies implementation of comprehensive smoking interventions and tobacco control programs in China. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Weighting Statistical Inputs for Data Used to Support Effective Decision Making During Severe Emergency Weather and Environmental Events

NASA Technical Reports Server (NTRS)

Gardner, Adrian

2010-01-01

National Aeronautical and Space Administration (NASA) weather and atmospheric environmental organizations are insatiable consumers of geophysical, hydrometeorological and solar weather statistics. The expanding array of internet-worked sensors producing targeted physical measurements has generated an almost factorial explosion of near real-time inputs to topical statistical datasets. Normalizing and value-based parsing of such statistical datasets in support of time-constrained weather and environmental alerts and warnings is essential, even with dedicated high-performance computational capabilities. What are the optimal indicators for advanced decision making? How do we recognize the line between sufficient statistical sampling and excessive, mission destructive sampling ? How do we assure that the normalization and parsing process, when interpolated through numerical models, yields accurate and actionable alerts and warnings? This presentation will address the integrated means and methods to achieve desired outputs for NASA and consumers of its data.

European-scale modeling of concentrations and distribution of polybrominated diphenyl ethers in the pentabromodiphenyl ether product.

PubMed

Prevedouros, K; Jones, K C; Sweetman, A J

2004-11-15

The results from a modeling exercise utilizing the European variant (EVn) BETR multimedia environmental fate model are presented for selected polybrominated diphenyl ethers (PBDEs) of the technical penta- (Pe-) bromodiphenyl ether (BDE) product. The objectives of this study were to test PeBDE emission estimates from the literature for Europe by investigating the consistency between model predictions and ambient measurements to address the ability of the model to predict spatial variability and differences between congeners. Concurrently sampled and analyzed passive sampling air data, together with soil and grass data, were used as key model validation tools. The model steady-state simulations gave generally good agreement with measured data for BDE-47 and -99 with greater discrepancies for heavier congeners (e.g., BDE-153). To predict future atmospheric concentration trends, the model was used in its fully dynamic mode over the period 1970--2010. It was predicted that atmospheric concentrations peaked around 1997, declining with an overall "disappearance" half-life of 4.8 years. Soil and grass levels were underestimated by the model; possible reasons for differences with measurement data are further explored. Finally, the importance of temporally and spatially resolved environmental data sets is highlighted, while improved quantification of degradation half-lives is essential to better understand and predict the behavior of BDE congeners in PeBDE.

A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium

PubMed Central

2012-01-01

Background Ticks are the most important pathogen vectors in Europe. They are known to be influenced by environmental factors, but these links are usually studied at specific temporal or spatial scales. Focusing on Ixodes ricinus in Belgium, we attempt to bridge the gap between current “single-sided” studies that focus on temporal or spatial variation only. Here, spatial and temporal patterns of ticks are modelled together. Methods A multi-level analysis of the Ixodes ricinus patterns in Belgium was performed. Joint effects of weather, habitat quality and hunting on field sampled tick abundance were examined at two levels, namely, sampling level, which is associated with temporal dynamics, and site level, which is related to spatial dynamics. Independent variables were collected from standard weather station records, game management data and remote sensing-based land cover data. Results At sampling level, only a marginally significant effect of daily relative humidity and temperature on the abundance of questing nymphs was identified. Average wind speed of seven days prior to the sampling day was found important to both questing nymphs and adults. At site level, a group of landscape-level forest fragmentation indices were highlighted for both questing nymph and adult abundance, including the nearest-neighbour distance, the shape and the aggregation level of forest patches. No cross-level effects or spatial autocorrelation were found. Conclusions Nymphal and adult ticks responded differently to environmental variables at different spatial and temporal scales. Our results can advise spatio-temporal extents of environment data collection for continuing empirical investigations and potential parameters for biological tick models. PMID:22830528

EPA Tools and Resources Webinar: EPA’s Environmental Sampling and Analytical Methods for Environmental Remediation and Recovery

EPA Pesticide Factsheets

EPA’s Environmental Sampling and Analytical Methods (ESAM) is a website tool that supports the entire environmental characterization process from collection of samples all the way to their analyses.

A multi-dimensional environment-health risk analysis system for the English regions

NASA Astrophysics Data System (ADS)

Vitolo, Claudia; Scutari, Marco; Ghalaieny, Mohamed; Tucker, Allan; Russell, Andrew

2017-04-01

There is an overwhelming body of evidence that environmental pollution, and air pollution in particular, is a significant threat to health worldwide. While in developed countries the introduction of environmental legislation and sustainable technologies aims to mitigate adverse effects, developing countries are at higher risk. Within the scope of the British Council funded KEHRA project, work is on-going to develop a reproducible and reliable system to assess health risks due to exposure to pollution under climate change and across countries. Our approach is based on the use of Bayesian Networks. We used these graphical models to explore and model the statistical dependence structure of the intricate environment-health nexus. We developed a robust modelling workflow in the R programming language to facilitate reproducibility and tested it on the English regions in the United Kingdom. Preliminary results are encouraging, showing that the model tests generally well in sample (training data spans the period 1981-2005) and has good predictive power when tested out of sample (testing data spans the period 2006-2014). We plan to show the results of this preliminary analysis as well as test the model under future climate change scenarios. Future work will also investigate the transferability of the model from a data-rich (England) to a data-poor environment (Kazakhstan).

Quantifying the potential impact of measurement error in an investigation of autism spectrum disorder (ASD).

PubMed

Heavner, Karyn; Newschaffer, Craig; Hertz-Picciotto, Irva; Bennett, Deborah; Burstyn, Igor

2014-05-01

The Early Autism Risk Longitudinal Investigation (EARLI), an ongoing study of a risk-enriched pregnancy cohort, examines genetic and environmental risk factors for autism spectrum disorders (ASDs). We simulated the potential effects of both measurement error (ME) in exposures and misclassification of ASD-related phenotype (assessed as Autism Observation Scale for Infants (AOSI) scores) on measures of association generated under this study design. We investigated the impact on the power to detect true associations with exposure and the false positive rate (FPR) for a non-causal correlate of exposure (X2, r=0.7) for continuous AOSI score (linear model) versus dichotomised AOSI (logistic regression) when the sample size (n), degree of ME in exposure, and strength of the expected (true) OR (eOR)) between exposure and AOSI varied. Exposure was a continuous variable in all linear models and dichotomised at one SD above the mean in logistic models. Simulations reveal complex patterns and suggest that: (1) There was attenuation of associations that increased with eOR and ME; (2) The FPR was considerable under many scenarios; and (3) The FPR has a complex dependence on the eOR, ME and model choice, but was greater for logistic models. The findings will stimulate work examining cost-effective strategies to reduce the impact of ME in realistic sample sizes and affirm the importance for EARLI of investment in biological samples that help precisely quantify a wide range of environmental exposures.

Using machine learning tools to model complex toxic interactions with limited sampling regimes.

PubMed

Bertin, Matthew J; Moeller, Peter; Guillette, Louis J; Chapman, Robert W

2013-03-19

A major impediment to understanding the impact of environmental stress, including toxins and other pollutants, on organisms, is that organisms are rarely challenged by one or a few stressors in natural systems. Thus, linking laboratory experiments that are limited by practical considerations to a few stressors and a few levels of these stressors to real world conditions is constrained. In addition, while the existence of complex interactions among stressors can be identified by current statistical methods, these methods do not provide a means to construct mathematical models of these interactions. In this paper, we offer a two-step process by which complex interactions of stressors on biological systems can be modeled in an experimental design that is within the limits of practicality. We begin with the notion that environment conditions circumscribe an n-dimensional hyperspace within which biological processes or end points are embedded. We then randomly sample this hyperspace to establish experimental conditions that span the range of the relevant parameters and conduct the experiment(s) based upon these selected conditions. Models of the complex interactions of the parameters are then extracted using machine learning tools, specifically artificial neural networks. This approach can rapidly generate highly accurate models of biological responses to complex interactions among environmentally relevant toxins, identify critical subspaces where nonlinear responses exist, and provide an expedient means of designing traditional experiments to test the impact of complex mixtures on biological responses. Further, this can be accomplished with an astonishingly small sample size.

Alternative modelling approaches for estimating pyrogenic carbon, soil organic carbon and total nitrogen in contrasting ecoregions within the United States

NASA Astrophysics Data System (ADS)

Jauss, Verena; Sullivan, Patrick; Lehmann, Johannes; Sanderman, Jonathan; Daub, Markus

2017-04-01

Given that turnover rates of pyrogenic carbon (PyC) in soil are substantially slower than those of other organic carbon input, it is considered an important carbon pool and its function and fate are relevant to global environmental change processes. Research on PyC has expanded greatly over recent years, but the analytical challenges of determining environmental core factors influencing its production, accumulation and dispersion still require elucidation across different scales. Mid-infrared spectroscopy and partial least-squares analysis were used in conjunction with ultraviolet photo-oxidation followed by nuclear magnetic resonance spectroscopy techniques, to quantify PyC, soil organic carbon (SOC) and total nitrogen (total N) amounts for samples we collected of surface and subsurface soils across the United States at National Science Foundation supported Long Term Ecological Research (LTER) sites as well as samples from a national soil sampling effort by the U.S. Geological Survey. In our study, we illustrate the impact of the aforementioned natural factors by examining their correlation with PyC content in soils under contrasting environmental conditions thus identifying the factors affecting PyC accumulation. Our central findings revealed a statistically significant relationship of PyC with environmental variables soil drainage, lignin content of the vegetation, mean annual temperature and mean annual precipitation as well as for the USGS sites total soil sulphur. During our investigations we evaluated PyC on different spatial scales. On a geographically smaller scale we examined samples from New England and New York. We developed a new and innovative Bayesian framework and applied three spatial models to the data in order to relate critical environmental covariates to changes in spatial density of PyC over the landscape. Akaike Information Criterion demonstrated that the Bayesian Multivariate Linear Regression model performed best (r2=0.6; p<<0.0001) in our analysis, giving global mean density estimates for PyC of 25.8 g kg-1 (12.2 Gg km-2) as opposed to the Ordinary Kriging model, which performed worst (r2=0.0; p>>0.05) with estimates of 11.0 g kg-1 (0.84 Gg km-2). On a larger scale, we looked at selected profiles at five diverse LTER sites as well as sites along a vegetation gradient in Oregon. At the LTER sites PyC content ranged from 9.8 mg g-1 (Coweeta, NC) to 56.4 mg g-1 (Bonanza, AK). Furthermore, we examined the multivariate relationships between environmental factors and our measurements of PyC, SOC and total N at the LTER sites through the application of a canonical correspondence analysis. Using our Oregon samples, we expanded on a previously established method to predict soil properties vertically in the soil profile using equal-area quadratic splines in order to calculate PyC stocks as well as to infer and visualize PyC contents, which were most prevalent in the first 0.2 m with 7-24% of SOC, and could be found in the subsoil of all locations. However, PyC contents did not change consistently with soil depth.

Environmental Determinants of the Distribution of Chagas Disease Vector Triatoma dimidiata in Colombia.

PubMed

Parra-Henao, Gabriel; Quirós-Gómez, Oscar; Jaramillo-O, Nicolas; Cardona, Ángela Segura

2016-04-01

Triatoma dimidiata (Hemiptera: Reduviidae) is a secondary vector of Trypanosoma cruzi in Colombia and represents an important epidemiological risk mainly in the central and oriental regions of the country where it occupies sylvatic, peridomestic, and intradomestic ecotopes, and because of this complex distribution, its distribution and abundance could be conditioned by environmental factors. In this work, we explored the relationship between T. dimidiata distribution and environmental factors in the northwest, northeast, and central zones of Colombia and developed predictive models of infestation in the country. The associations between the presence ofT. dimidiata and environmental variables were studied using logistic regression models and ecological niche modeling for a sample of villages in Colombia. The analysis was based on the information collected in field about the presence ofT. dimidiata and the environmental data for each village extracted from remote sensing images. The presence of Triatoma dimidiata(Latreille, 1811) was found to be significantly associated with the maximum vegetation index, minimum land surface temperature (LST), and the digital elevation for the statistical model. Temperature seasonality, annual precipitation, and vegetation index were the variables that most influenced the ecological niche model ofT. dimidiata distribution. The logistic regression model showed a good fit and predicted suitable habitats in the Andean and Caribbean regions, which agrees with the known distribution of the species, but predicted suitable habitats in the Pacific and Orinoco regions proposing new areas of research. Improved models to predict suitable habitats forT. dimidiata hold promise for spatial targeting of integrated vector management. © The American Society of Tropical Medicine and Hygiene.

Environmental Determinants of the Distribution of Chagas Disease Vector Triatoma dimidiata in Colombia

PubMed Central

Parra-Henao, Gabriel; Quirós-Gómez, Oscar; Jaramillo-O, Nicolas; Cardona, Ángela Segura

2016-01-01

Triatoma dimidiata (Hemiptera: Reduviidae) is a secondary vector of Trypanosoma cruzi in Colombia and represents an important epidemiological risk mainly in the central and oriental regions of the country where it occupies sylvatic, peridomestic, and intradomestic ecotopes, and because of this complex distribution, its distribution and abundance could be conditioned by environmental factors. In this work, we explored the relationship between T. dimidiata distribution and environmental factors in the northwest, northeast, and central zones of Colombia and developed predictive models of infestation in the country. The associations between the presence of T. dimidiata and environmental variables were studied using logistic regression models and ecological niche modeling for a sample of villages in Colombia. The analysis was based on the information collected in field about the presence of T. dimidiata and the environmental data for each village extracted from remote sensing images. The presence of Triatoma dimidiata (Latreille, 1811) was found to be significantly associated with the maximum vegetation index, minimum land surface temperature (LST), and the digital elevation for the statistical model. Temperature seasonality, annual precipitation, and vegetation index were the variables that most influenced the ecological niche model of T. dimidiata distribution. The logistic regression model showed a good fit and predicted suitable habitats in the Andean and Caribbean regions, which agrees with the known distribution of the species, but predicted suitable habitats in the Pacific and Orinoco regions proposing new areas of research. Improved models to predict suitable habitats for T. dimidiata hold promise for spatial targeting of integrated vector management. PMID:26856910

Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

PubMed

Williams, Tim D; Turan, Nil; Diab, Amer M; Wu, Huifeng; Mackenzie, Carolynn; Bartie, Katie L; Hrydziuszko, Olga; Lyons, Brett P; Stentiford, Grant D; Herbert, John M; Abraham, Joseph K; Katsiadaki, Ioanna; Leaver, Michael J; Taggart, John B; George, Stephen G; Viant, Mark R; Chipman, Kevin J; Falciani, Francesco

2011-08-01

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

Towards a System Level Understanding of Non-Model Organisms Sampled from the Environment: A Network Biology Approach

PubMed Central

Williams, Tim D.; Turan, Nil; Diab, Amer M.; Wu, Huifeng; Mackenzie, Carolynn; Bartie, Katie L.; Hrydziuszko, Olga; Lyons, Brett P.; Stentiford, Grant D.; Herbert, John M.; Abraham, Joseph K.; Katsiadaki, Ioanna; Leaver, Michael J.; Taggart, John B.; George, Stephen G.; Viant, Mark R.; Chipman, Kevin J.; Falciani, Francesco

2011-01-01

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations. PMID:21901081

From Environment to Mating Competition and Super-K in a Predominantly Urban Sample of Young Adults.

PubMed

Richardson, George B; Dariotis, Jacinda K; Lai, Mark H C

2017-01-01

Recent research suggests human life history strategy (LHS) may be subsumed by multiple dimensions, including mating competition and Super-K, rather than one. In this study, we test whether a two-dimensional structure best fit data from a predominantly urban sample of young adults ages 18-24. We also test whether latent life history dimensions are associated with environmental harshness and unpredictability as predicted by life history theory. Results provide evidence that a two-dimensional model best fit the data. Furthermore, a moderate inverse residual correlation between mating competition and Super-K was found, consistent with a life history trade-off. Our findings suggest that parental socioeconomic status may enhance investment in mating competition, that harshness might persist into young adulthood as an important correlate of LHS, and that unpredictability may not have significant effects in young adulthood. These findings further support the contention that human LHS is multidimensional and environmental effects on LHS are more complex than previously suggested. The model presented provides a parsimonious explanation of an array of human behaviors and traits and can be used to inform public health initiatives, particularly with respect to the potential impact of environmental interventions.

Physical and environmental factors affecting the persistence of explosives particles (Conference Presentation)

NASA Astrophysics Data System (ADS)

Papantonakis, Michael R.; Nguyen, Viet K.; Furstenberg, Robert; White, Caitlyn; Shuey, Melissa; Kendziora, Christopher A.; McGill, R. Andrew

2017-05-01

Knowledge of the persistence of trace explosives materials is critical to aid the security community in designing detection methods and equipment. The physical and environmental factors affecting the lifetimes of particles include temperature, airflow, interparticle distance, adlayers, humidity, particle field size and vapor pressure. We are working towards a complete particle persistence model that captures the relative importance of these effects to allow the user, with known environmental conditions, to predict particle lifetimes for explosives or other chemicals. In this work, particles of explosives are sieved onto smooth glass substrates using particle sizes and loadings relevant to those deposited by fingerprint deposition. The coupon is introduced into a custom flow cell and monitored under controlled airflow, humidity and temperature. Photomicroscopy images of the sample taken at fixed time intervals are analyzed to monitor particle sublimation and characterized as a size-independent radial sublimation velocity for each particle in the ensemble. In this paper we build on previous work by comparing the relationship between sublimation of different materials and their vapor pressures. We also describe the influence of a sebum adlayer on particle sublimation, allowing us to better model `real world' samples.

TECHNIQUES WITH POTENTIAL FOR HANDLING ENVIRONMENTAL SAMPLES IN CAPILLARY ELECTROPHORESIS

EPA Science Inventory

An assessment of the methods for handling environmental samples prior to capillary electrophoresis (CE) is presented for both aqueous and solid matrices. Sample handling in environmental analyses is the subject of ongoing research at the Environmental Protection Agency's National...

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Determining metal origins and availability in fluvial deposits by analysis of geochemical baselines and solid-solution partitioning measurements and modelling.

PubMed

Vijver, Martina G; Spijker, Job; Vink, Jos P M; Posthuma, Leo

2008-12-01

Metals in floodplain soils and sediments (deposits) can originate from lithogenic and anthropogenic sources, and their availability for uptake in biota is hypothesized to depend on both origin and local sediment conditions. In criteria-based environmental risk assessments, these issues are often neglected, implying local risks to be often over-estimated. Current problem definitions in river basin management tend to require a refined, site-specific focus, resulting in a need to address both aspects. This paper focuses on the determination of local environmental availabilities of metals in fluvial deposits by addressing both the origins of the metals and their partitioning over the solid and solution phases. The environmental availability of metals is assumed to be a key force influencing exposure levels in field soils and sediments. Anthropogenic enrichments of Cu, Zn and Pb in top layers could be distinguished from lithogenic background concentrations and described using an aluminium-proxy. Cd in top layers was attributed to anthropogenic enrichment almost fully. Anthropogenic enrichments for Cu and Zn appeared further to be also represented by cold 2M HNO3 extraction of site samples. For Pb the extractions over-estimated the enrichments. Metal partitioning was measured, and measurements were compared to predictions generated by an empirical regression model and by a mechanistic-kinetic model. The partitioning models predicted metal partitioning in floodplain deposits within about one order of magnitude, though a large inter-sample variability was found for Pb.

MicroRNA Biomarkers of Toxicity in Biological Matrices

EPA Science Inventory

Biomarker measurements that reliably correlate with tissue injury and can be measured from sampling accessible biofluids offer enormous benefits in terms of cost, time, and convenience when assessing environmental and drug-induced toxicity in model systems or human cohorts. Micro...

Incorporating imperfect detection into joint models of communites: A response to Warton et al.

USGS Publications Warehouse

Beissinger, Steven R.; Iknayan, Kelly J.; Guillera-Arroita, Gurutzeta; Zipkin, Elise; Dorazio, Robert; Royle, Andy; Kery, Marc

2016-01-01

Warton et al. [1] advance community ecology by describing a statistical framework that can jointly model abundances (or distributions) across many taxa to quantify how community properties respond to environmental variables. This framework specifies the effects of both measured and unmeasured (latent) variables on the abundance (or occurrence) of each species. Latent variables are random effects that capture the effects of both missing environmental predictors and correlations in parameter values among different species. As presented in Warton et al., however, the joint modeling framework fails to account for the common problem of detection or measurement errors that always accompany field sampling of abundance or occupancy, and are well known to obscure species- and community-level inferences.

A whole-cell bioreporter assay for quantitative genotoxicity evaluation of environmental samples.

PubMed

Jiang, Bo; Li, Guanghe; Xing, Yi; Zhang, Dayi; Jia, Jianli; Cui, Zhisong; Luan, Xiao; Tang, Hui

2017-10-01

Whole-cell bioreporters have emerged as promising tools for genotoxicity evaluation, due to their rapidity, cost-effectiveness, sensitivity and selectivity. In this study, a method for detecting genotoxicity in environmental samples was developed using the bioluminescent whole-cell bioreporter Escherichia coli recA::luxCDABE. To further test its performance in a real world scenario, the E. coli bioreporter was applied in two cases: i) soil samples collected from chromium(VI) contaminated sites; ii) crude oil contaminated seawater collected after the Jiaozhou Bay oil spill which occurred in 2013. The chromium(VI) contaminated soils were pretreated by water extraction, and directly exposed to the bioreporter in two phases: aqueous soil extraction (water phase) and soil supernatant (solid phase). The results indicated that both extractable and soil particle fixed chromium(VI) were bioavailable to the bioreporter, and the solid-phase contact bioreporter assay provided a more precise evaluation of soil genotoxicity. For crude oil contaminated seawater, the response of the bioreporter clearly illustrated the spatial and time change in genotoxicity surrounding the spill site, suggesting that the crude oil degradation process decreased the genotoxic risk to ecosystem. In addition, the performance of the bioreporter was simulated by a modified cross-regulation gene expression model, which quantitatively described the DNA damage response of the E. coli bioreporter. Accordingly, the bioluminescent response of the bioreporter was calculated as the mitomycin C equivalent, enabling quantitative comparison of genotoxicities between different environmental samples. This bioreporter assay provides a rapid and sensitive screening tool for direct genotoxicity assessment of environmental samples. Copyright © 2017. Published by Elsevier Ltd.

Citizen science contributes to our knowledge of invasive plant species distributions

USGS Publications Warehouse

Crall, Alycia W.; Jarnevich, Catherine S.; Young, Nicholas E.; Panke, Brendon; Renz, Mark; Stohlgren, Thomas

2015-01-01

Citizen science is commonly cited as an effective approach to expand the scale of invasive species data collection and monitoring. However, researchers often hesitate to use these data due to concerns over data quality. In light of recent research on the quality of data collected by volunteers, we aimed to demonstrate the extent to which citizen science data can increase sampling coverage, fill gaps in species distributions, and improve habitat suitability models compared to professionally generated data sets used in isolation. We combined data sets from professionals and volunteers for five invasive plant species (Alliaria petiolata, Berberis thunbergii, Cirsium palustre, Pastinaca sativa, Polygonum cuspidatum) in portions of Wisconsin. Volunteers sampled counties not sampled by professionals for three of the five species. Volunteers also added presence locations within counties not included in professional data sets, especially in southern portions of the state where professional monitoring activities had been minimal. Volunteers made a significant contribution to the known distribution, environmental gradients sampled, and the habitat suitability of P. cuspidatum. Models generated with professional data sets for the other four species performed reasonably well according to AUC values (>0.76). The addition of volunteer data did not greatly change model performance (AUC > 0.79) but did change the suitability surface generated by the models, making them more realistic. Our findings underscore the need to merge data from multiple sources to improve knowledge of current species distributions, and to predict their movement under present and future environmental conditions. The efficiency and success of these approaches require that monitoring efforts involve multiple stakeholders in continuous collaboration via established monitoring networks.

Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles.

PubMed

Sani-Kast, Nicole; Scheringer, Martin; Slomberg, Danielle; Labille, Jérôme; Praetorius, Antonia; Ollivier, Patrick; Hungerbühler, Konrad

2015-12-01

Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted. Copyright © 2014 Elsevier B.V. All rights reserved.

Environmental Conditions Associated with Elevated Vibrio parahaemolyticus Concentrations in Great Bay Estuary, New Hampshire.

PubMed

Urquhart, Erin A; Jones, Stephen H; Yu, Jong W; Schuster, Brian M; Marcinkiewicz, Ashley L; Whistler, Cheryl A; Cooper, Vaughn S

2016-01-01

Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary.

Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

PubMed

Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

2015-03-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

PubMed Central

Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

2015-01-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

Development and validation of the pro-environmental behaviour scale for women's health.

PubMed

Kim, HyunKyoung

2017-05-01

This study was aimed to develop and test the Pro-environmental Behavior Scale for Women's Health. Women adopt sustainable behaviours and alter their life styles to protect the environment and their health from environmental pollution. The conceptual framework of pro-environmental behaviours was based on Rogers' protection motivation theory and Weinstein's precaution adoption process model. The cross-sectional design was used for instrument development. The instrument development process consisted of a literature review, personal depth interviews and focus group interviews. The sample comprised 356 adult women recruited in April-May 2012 in South Korea using quota sampling. For construct validity, exploratory factor analysis was conducted to examine the factor structure, after which convergent and discriminant validity and known-group comparisons were tested. Principal component analysis yielded 17 items with four factors, including 'women's health protection,' 'chemical exposure prevention,' 'alternative consumption,' and 'community-oriented behaviour'. The Cronbach's α was 0·81. Convergent and discriminant validity were supported by performing correlations with other environmental-health and health-behaviour measures. Nursing professionals can reliably use the instrument to assess women's behaviours, which protect their health and the environment. © 2016 John Wiley & Sons Ltd.

9 CFR 147.12 - Procedures for collection, isolation, and identification of Salmonella from environmental samples...

Code of Federal Regulations, 2011 CFR

2011-01-01

..., and identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and... identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and meconium samples... chickens, waterfowl, exhibition poultry, and game birds. All samples and swabs described in this paragraph...

9 CFR 147.12 - Procedures for collection, isolation, and identification of Salmonella from environmental samples...

Code of Federal Regulations, 2012 CFR

2012-01-01

..., and identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and... identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and meconium samples... chickens, waterfowl, exhibition poultry, and game birds. All samples and swabs described in this paragraph...

9 CFR 147.12 - Procedures for collection, isolation, and identification of Salmonella from environmental samples...

Code of Federal Regulations, 2013 CFR

2013-01-01

..., and identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and... identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and meconium samples... chickens, waterfowl, exhibition poultry, and game birds. All samples and swabs described in this paragraph...

9 CFR 147.12 - Procedures for collection, isolation, and identification of Salmonella from environmental samples...

Code of Federal Regulations, 2014 CFR

2014-01-01

..., and identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and... identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and meconium samples... chickens, waterfowl, exhibition poultry, and game birds. All samples and swabs described in this paragraph...

9 CFR 147.12 - Procedures for collection, isolation, and identification of Salmonella from environmental samples...

Code of Federal Regulations, 2010 CFR

2010-01-01

..., and identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and... identification of Salmonella from environmental samples, cloacal swabs, chick box papers, and meconium samples... chickens, waterfowl, exhibition poultry, and game birds. All samples and swabs described in this paragraph...

The Views of Preservice Teachers for Problem Based Learning Model Supported by Geocaching in Environmental Education

ERIC Educational Resources Information Center

Adanali, Rukiye; Alim, Mete

2017-01-01

The purpose of this study is to investigate the usability of Problem-Based Learning model supported by Instructional Geocaching Game (PBL-IGG). The study was conducted in Turkey, in 2015-2016 spring term with 19 geography teacher candidates who chosen by convenience sampling method. In this study, within Educational Geocaching Game (IGG) which is…

The Role of Family Environment in Depressive Symptoms among University Students: A Large Sample Survey in China

PubMed Central

Yang, Yanjie; Chen, Lu; Qiu, Xiaohui; Qiao, Zhengxue; Zhou, Jiawei; Pan, Hui; Ban, Bo; Zhu, Xiongzhao; He, Jincai; Ding, Yongqing; Bai, Bing

2015-01-01

Objective To explore the relationship between family environment and depressive symptoms and to evaluate the influence of hard and soft family environmental factors on depression levels in a large sample of university students in China. Methods A multi-stage stratified sampling procedure was used to select 6,000 participants. The response rate was 88.8%, with 5,329 students completing the Beck Depression Inventory (BDI) and the Family Environment Scale Chinese Version (FES-CV), which was adapted for the Chinese population. Differences between the groups were tested for significance by the Student’s t-test; ANOVA was used to test continuous variables. The relationship between soft family environmental factors and BDI were tested by Pearson correlation analysis. Hierarchical linear regression analysis was conducted to model the effects of hard environmental factors and soft environmental factors on depression in university students. Results A total of 11.8% of students scored above the threshold of moderate depression(BDI≧14). Hard family environmental factors such as parent relationship, family economic status, level of parental literacy and non-intact family structure were associated with depressive symptoms. The soft family environmental factors—conflict and control—were positively associated with depression, while cohesion was negatively related to depressive symptom after controlling for other important associates of depression. Hierarchical regression analysis indicated that the soft family environment correlates more strongly with depression than the hard family environment. Conclusions Soft family environmental factors—especially cohesion, conflict and control—appeared to play an important role in the occurrence of depressive symptoms. These findings underline the significance of the family environment as a source of risk factors for depression among university students in China and suggest that family-based interventions and improvement are very important to reduce depression among university students. PMID:26629694

Glucocorticoid activity detected by in vivo zebrafish assay and in vitro glucocorticoid receptor bioassay at environmental relevant concentrations.

PubMed

Chen, Qiyu; Jia, Ai; Snyder, Shane A; Gong, Zhiyuan; Lam, Siew Hong

2016-02-01

Glucocorticoids are pharmaceutical contaminants of emerging concern due to their incomplete removal during wastewater treatment, increased presence in aquatic environment and their biological potency. The zebrafish is a popular model for aquatic toxicology and environmental risk assessment. This study aimed to determine if glucocorticoids at environmental concentrations would perturb expression of selected glucocorticoid-responsive genes in zebrafish and to investigate their potentials as an in vivo zebrafish assay in complementing in vitro glucocorticoid receptor bioassay. The relative expression of eleven glucocorticoid-responsive genes in zebrafish larvae and liver of adult male zebrafish exposed to three representative glucocorticoids (dexamethasone, prednisolone and triamcinolone) was determined. The expression of pepck, baiap2 and pxr was up-regulated in zebrafish larvae and the expression of baiap2, pxr and mmp-2 was up-regulated in adult zebrafish exposed to glucocorticoids at concentrations equivalent to total glucocorticoids reported in environmental samples. The responsiveness of the specific genes were sufficiently robust in zebrafish larvae exposed to a complex environmental sample detected with in vitro glucocorticoid activity equivalent to 478 pM dexamethasone (DEX-EQ) and confirmed to contain low concentration (0.2 ng/L or less) of the targeted glucocorticoids, and possibly other glucocorticoid-active compounds. The findings provided in vivo relevance to the in vitro glucocorticoid activity and suggested that the environmental sample can perturb glucocorticoid-responsive genes in its original, or half the diluted, concentration as may be found in the environment. The study demonstrated the important complementary roles of in vivo zebrafish and in vitro bioassays coupled with analytical chemistry in monitoring environmental glucocorticoid contaminants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Determinants of Pseudogymnoascus destructans within bat hibernacula: implications for surveillance and management of white-nose syndrome.

PubMed

Verant, Michelle L; Bohuski, Elizabeth A; Richgels, Katherine L D; Olival, Kevin J; Epstein, Jonathan H; Blehert, David S

2018-01-01

1. Fungal diseases are an emerging global problem affecting human health, food security and biodiversity. Ability of many fungal pathogens to persist within environmental reservoirs can increase extinction risks for host species and presents challenges for disease control. Understanding factors that regulate pathogen spread and persistence in these reservoirs is critical for effective disease management. 2. White-nose syndrome (WNS) is a disease of hibernating bats caused by Pseudogymnoascus destructans ( Pd ), a fungus that establishes persistent environmental reservoirs within bat hibernacula, which contribute to seasonal disease transmission dynamics in bats. However, host and environmental factors influencing distribution of Pd within these reservoirs are unknown. 3. We used model selection on longitudinally collected field data to test multiple hypotheses describing presence-absence and abundance of Pd in environmental substrates and on bats within hibernacula at different stages of WNS. 4. First detection of Pd in the environment lagged up to one year after first detection on bats within that hibernaculum. Once detected, the probability of detecting Pd within environmental samples from a hibernaculum increased over time and was higher in sediment compared to wall surfaces. Temperature had marginal effects on the distribution of Pd . For bats, prevalence and abundance of Pd were highest on Myotis lucifugus and on bats with visible signs of WNS. 5. Synthesis and applications . Our results indicate that distribution of Pseudogymnoascus destructans ( Pd ) within a hibernaculum is driven primarily by bats with delayed establishment of environmental reservoirs. Thus, collection of samples from Myotis lucifugus , or from sediment if bats cannot be sampled, should be prioritized to improve detection probabilities for Pd surveillance. Long-term persistence of Pd in sediment suggests that disease management for white-nose syndrome should address risks of sustained transmission from environmental reservoirs.

The Role of Family Environment in Depressive Symptoms among University Students: A Large Sample Survey in China.

PubMed

Yu, Yunmiao; Yang, Xiuxian; Yang, Yanjie; Chen, Lu; Qiu, Xiaohui; Qiao, Zhengxue; Zhou, Jiawei; Pan, Hui; Ban, Bo; Zhu, Xiongzhao; He, Jincai; Ding, Yongqing; Bai, Bing

2015-01-01

To explore the relationship between family environment and depressive symptoms and to evaluate the influence of hard and soft family environmental factors on depression levels in a large sample of university students in China. A multi-stage stratified sampling procedure was used to select 6,000 participants. The response rate was 88.8%, with 5,329 students completing the Beck Depression Inventory (BDI) and the Family Environment Scale Chinese Version (FES-CV), which was adapted for the Chinese population. Differences between the groups were tested for significance by the Student's t-test; ANOVA was used to test continuous variables. The relationship between soft family environmental factors and BDI were tested by Pearson correlation analysis. Hierarchical linear regression analysis was conducted to model the effects of hard environmental factors and soft environmental factors on depression in university students. A total of 11.8% of students scored above the threshold of moderate depression (BDI≧14). Hard family environmental factors such as parent relationship, family economic status, level of parental literacy and non-intact family structure were associated with depressive symptoms. The soft family environmental factors--conflict and control--were positively associated with depression, while cohesion was negatively related to depressive symptom after controlling for other important associates of depression. Hierarchical regression analysis indicated that the soft family environment correlates more strongly with depression than the hard family environment. Soft family environmental factors--especially cohesion, conflict and control--appeared to play an important role in the occurrence of depressive symptoms. These findings underline the significance of the family environment as a source of risk factors for depression among university students in China and suggest that family-based interventions and improvement are very important to reduce depression among university students.

Speciation of metal(loid)s in environmental samples by X-ray absorption spectroscopy: a critical review.

PubMed

Gräfe, Markus; Donner, Erica; Collins, Richard N; Lombi, Enzo

2014-04-25

Element specificity is one of the key factors underlying the widespread use and acceptance of X-ray absorption spectroscopy (XAS) as a research tool in the environmental and geo-sciences. Independent of physical state (solid, liquid, gas), XAS analyses of metal(loid)s in complex environmental matrices over the past two decades have provided important information about speciation at environmentally relevant interfaces (e.g. solid-liquid) as well as in different media: plant tissues, rhizosphere, soils, sediments, ores, mineral process tailings, etc. Limited sample preparation requirements, the concomitant ability to preserve original physical and chemical states, and independence from crystallinity add to the advantages of using XAS in environmental investigations. Interpretations of XAS data are founded on sound physical and statistical models that can be applied to spectra of reference materials and mixed phases, respectively. For spectra collected directly from environmental matrices, abstract factor analysis and linear combination fitting provide the means to ascertain chemical, bonding, and crystalline states, and to extract quantitative information about their distribution within the data set. Through advances in optics, detectors, and data processing, X-ray fluorescence microprobes capable of focusing X-rays to micro- and nano-meter size have become competitive research venues for resolving the complexity of environmental samples at their inherent scale. The application of μ-XANES imaging, a new combinatorial approach of X-ray fluorescence spectrometry and XANES spectroscopy at the micron scale, is one of the latest technological advances allowing for lateral resolution of chemical states over wide areas due to vastly improved data processing and detector technology. Copyright © 2014. Published by Elsevier B.V.

Context-dependent decision-making: a simple Bayesian model

PubMed Central

Lloyd, Kevin; Leslie, David S.

2013-01-01

Many phenomena in animal learning can be explained by a context-learning process whereby an animal learns about different patterns of relationship between environmental variables. Differentiating between such environmental regimes or ‘contexts’ allows an animal to rapidly adapt its behaviour when context changes occur. The current work views animals as making sequential inferences about current context identity in a world assumed to be relatively stable but also capable of rapid switches to previously observed or entirely new contexts. We describe a novel decision-making model in which contexts are assumed to follow a Chinese restaurant process with inertia and full Bayesian inference is approximated by a sequential-sampling scheme in which only a single hypothesis about current context is maintained. Actions are selected via Thompson sampling, allowing uncertainty in parameters to drive exploration in a straightforward manner. The model is tested on simple two-alternative choice problems with switching reinforcement schedules and the results compared with rat behavioural data from a number of T-maze studies. The model successfully replicates a number of important behavioural effects: spontaneous recovery, the effect of partial reinforcement on extinction and reversal, the overtraining reversal effect, and serial reversal-learning effects. PMID:23427101

Context-dependent decision-making: a simple Bayesian model.

PubMed

Lloyd, Kevin; Leslie, David S

2013-05-06

Many phenomena in animal learning can be explained by a context-learning process whereby an animal learns about different patterns of relationship between environmental variables. Differentiating between such environmental regimes or 'contexts' allows an animal to rapidly adapt its behaviour when context changes occur. The current work views animals as making sequential inferences about current context identity in a world assumed to be relatively stable but also capable of rapid switches to previously observed or entirely new contexts. We describe a novel decision-making model in which contexts are assumed to follow a Chinese restaurant process with inertia and full Bayesian inference is approximated by a sequential-sampling scheme in which only a single hypothesis about current context is maintained. Actions are selected via Thompson sampling, allowing uncertainty in parameters to drive exploration in a straightforward manner. The model is tested on simple two-alternative choice problems with switching reinforcement schedules and the results compared with rat behavioural data from a number of T-maze studies. The model successfully replicates a number of important behavioural effects: spontaneous recovery, the effect of partial reinforcement on extinction and reversal, the overtraining reversal effect, and serial reversal-learning effects.

A Random Forest approach to predict the spatial distribution of sediment pollution in an estuarine system

PubMed Central

Kreakie, Betty J.; Cantwell, Mark G.; Nacci, Diane

2017-01-01

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF) model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol) (TCS), in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies) and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high) for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC) (transport and fate proxy) was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry) and sand (transport and fate proxy) were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary), which was validated with independent test samples. This decision-support tool performed well at the sub-estuary extent and provided the means to identify areas of concern and prioritize bay-wide sampling. PMID:28738089

Emerging contaminants--pesticides, PPCPs, microbial degradation products and natural substances as inhibitors of multixenobiotic defense in aquatic organisms.

PubMed

Smital, Tvrtko; Luckenbach, Till; Sauerborn, Roberta; Hamdoun, Amro M; Vega, Rebecca L; Epel, David

2004-08-18

The environmental presence of chemosensitizers or inhibitors of the multixenobiotic resistance (MXR) defense system in aquatic organisms could cause increase in intracellular accumulation and toxic effects of other xenobiotics normally effluxed by MXR transport proteins (P-glycoprotein (P-gps), MRPs). MXR inhibition with concomitant detrimental effects has been shown in several studies with aquatic organisms exposed to both model MXR inhibitors and environmental pollutants. The presence of MXR inhibitors has been demonstrated in environmental samples from polluted locations at concentrations that could abolish P-gp transport activity. However, it is not clear whether the inhibition observed after exposure to environmental samples is a result of saturation of MXR transport proteins by numerous substrates present in polluted waters or results from the presence of powerful MXR inhibitors. And are potent environmental MXR inhibitors natural or man-made chemicals? As a consequence of these uncertainties, no official action has been taken to monitor and control the release and presence of MXR inhibitors into aquatic environments. In this paper we present our new results addressing these critical questions. Ecotoxicological significance of MXR inhibition was supported in in vivo studies that demonstrated an increase in the production of mutagenic metabolites by mussels and an increase in the number of sea urchin embryos with apoptotic cells after exposure to model MXR inhibitors. We also demonstrated that MXR inhibitors are present among both conventional and emerging man-made pollutants: some pesticides and synthetic musk fragrances show extremely high MXR inhibitory potential at environmentally relevant concentrations. In addition, we emphasized the biological transformation of crude oil hydrocarbons into MXR inhibitors by oil-degrading bacteria, and the risk potentially caused by powerful natural MXR inhibitors produced by invasive species.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use.

PubMed

Edwards, Alexis C; Maes, Hermine H; Prescott, Carol A; Kendler, Kenneth S

2015-02-01

Alcohol consumption is typically correlated with the alcohol use behaviors of one's peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. This study uses data from a sample of male twins (N = 1,790) who provided retrospective reports of their own alcohol consumption and their peers' alcohol-related behaviors, from adolescence into young adulthood (ages 12 to 25). Structural equation modeling was employed to compare 3 plausible models of genetic and environmental influences on the relationship between phenotypes over time. Model fitting indicated that one's own alcohol consumption and the alcohol use of one's peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Peers' alcohol use behaviors and one's own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. Copyright © 2015 by the Research Society on Alcoholism.

Multiple mechanisms influencing the relationship between alcohol consumption and peer alcohol use

PubMed Central

Edwards, Alexis C.; Maesr, Hermine H.; Prescott, Carol A.; Kendler, Kenneth S.

2014-01-01

Background Alcohol consumption is typically correlated with the alcohol use behaviors of one’s peers. Previous research has suggested that this positive relationship could be due to social selection, social influence, or a combination of both processes. However, few studies have considered the role of shared genetic and environmental influences in conjunction with causal processes. Methods The current study uses data from a sample of male twins (N=1790) who provided retrospective reports of their own alcohol consumption and their peers’ alcohol related behaviors, from adolescence into young adulthood (ages 12–25). Structural equation modeling was employed to compare three plausible models of genetic and environmental influences on the relationship between phenotypes over time. Results Model fitting indicated that one’s own alcohol consumption and the alcohol use of one’s peers are related through both genetic and shared environmental factors and through unique environmental causal influences. The relative magnitude of these factors, and their contribution to covariation, changed over time, with genetic factors becoming more meaningful later in development. Conclusions Peers’ alcohol use behaviors and one’s own alcohol consumption are related through a complex combination of genetic and environmental factors that act via correlated factors and the complementary causal mechanisms of social selection and influence. Understanding these processes can inform risk assessment as well as improve our ability to model the development of alcohol use. PMID:25597346

Parental knowledge is an environmental influence on adolescent externalizing.

PubMed

Marceau, Kristine; Narusyte, Jurgita; Lichtenstein, Paul; Ganiban, Jody M; Spotts, Erica L; Reiss, David; Neiderhiser, Jenae M

2015-02-01

There is evidence both that parental monitoring is an environmental influence serving to diminish adolescent externalizing problems and that this association may be driven by adolescents' characteristics via genetic and/or environmental mechanisms, such that adolescents with fewer problems tell their parents more, and therefore appear to be better monitored. Without information on how parents' and children's genes and environments influence correlated parent and child behaviors, it is impossible to clarify the mechanisms underlying this association. The present study used the Extended Children of Twins model to distinguish types of gene-environment correlation and direct environmental effects underlying associations between parental knowledge and adolescent (age 11-22 years) externalizing behavior with a Swedish sample of 909 twin parents and their adolescent offspring and a US-based sample of 405 White adolescent siblings and their parents. Results suggest that more parental knowledge is associated with less adolescent externalizing via a direct environmental influence independent of any genetic influences. There was no evidence of a child-driven explanation of the association between parental knowledge and adolescent externalizing problems. In this sample of adolescents, parental knowledge exerted an environmental influence on adolescent externalizing after accounting for genetic influences of parents and adolescents. Because the association between parenting and child development originates in the parent, treatment for adolescent externalizing must not only include parents but should also focus on altering their parental style. Thus, findings suggest that teaching parents better knowledge-related monitoring strategies is likely to help reduce externalizing problems in adolescents. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

Parental Knowledge is an Environmental Influence on Adolescent Externalizing

PubMed Central

Marceau, Kristine; Narusyte, Jurgita; Lichtenstein, Paul; Ganiban, Jody M.; Spotts, Erica L.; Reiss, David; Neiderhiser, Jenae M.

2014-01-01

Background There is evidence both that parental monitoring is an environmental influence serving to diminish adolescent externalizing problems and that this association may be driven by adolescents’ characteristics via genetic and/or environmental mechanisms, such that adolescents with fewer problems tell their parents more, and therefore appear to be better monitored. Without information on how parents’ and children’s genes and environments influence correlated parent and child behaviors, it is impossible to clarify the mechanisms underlying this association. Method The present study used the Extended Children of Twins model to distinguish types of gene-environment correlation and direct environmental effects underlying associations between parental knowledge and adolescent (age 11-22 years) externalizing behavior with a Swedish sample of 909 twin parents and their adolescent offspring and a US-based sample of 405 White adolescent siblings and their parents. Results Results suggest that more parental knowledge is associated with less adolescent externalizing via a direct environmental influence independent of any genetic influences. There was no evidence of a child-driven explanation of the association between parental knowledge and adolescent externalizing problems. Conclusions In this sample of adolescents, parental knowledge exerted an environmental influence on adolescent externalizing after accounting for genetic influences of parents and adolescents. Because the association between parenting and child development originates in the parent, treatment for adolescent externalizing must not only include parents but should focus on altering their parental style. Thus, findings suggest that teaching parents better knowledge-related monitoring strategies is likely to help reduce externalizing problems in adolescents. PMID:24975929

Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992-2006

USGS Publications Warehouse

Martin, Jeffrey D.; Stone, Wesley W.; Wydoski, Duane S.; Sandstrom, Mark W.

2009-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ('spiked' QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report examines temporal changes in the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as 'pesticides') that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 to 2006 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Temporal changes in pesticide recovery were investigated by calculating robust, locally weighted scatterplot smooths (lowess smooths) for the time series of pesticide recoveries in 5,132 laboratory reagent spikes; 1,234 stream-water matrix spikes; and 863 groundwater matrix spikes. A 10-percent smoothing window was selected to show broad, 6- to 12-month time scale changes in recovery for most of the 52 pesticides. Temporal patterns in recovery were similar (in phase) for laboratory reagent spikes and for matrix spikes for most pesticides. In-phase temporal changes among spike types support the hypothesis that temporal change in method performance is the primary cause of temporal change in recovery. Although temporal patterns of recovery were in phase for most pesticides, recovery in matrix spikes was greater than recovery in reagent spikes for nearly every pesticide. Models of recovery based on matrix spikes are deemed more appropriate for adjusting concentrations of pesticides measured in groundwater and stream-water samples than models based on laboratory reagent spikes because (1) matrix spikes are expected to more closely match the matrix of environmental water samples than are reagent spikes and (2) method performance is often matrix dependent, as was shown by higher recovery in matrix spikes for most of the pesticides. Models of recovery, based on lowess smooths of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

QA/QC requirements for physical properties sampling and analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Innis, B.E.

1993-07-21

This report presents results of an assessment of the available information concerning US Environmental Protection Agency (EPA) quality assurance/quality control (QA/QC) requirements and guidance applicable to sampling, handling, and analyzing physical parameter samples at Comprehensive Environmental Restoration, Compensation, and Liability Act (CERCLA) investigation sites. Geotechnical testing laboratories measure the following physical properties of soil and sediment samples collected during CERCLA remedial investigations (RI) at the Hanford Site: moisture content, grain size by sieve, grain size by hydrometer, specific gravity, bulk density/porosity, saturated hydraulic conductivity, moisture retention, unsaturated hydraulic conductivity, and permeability of rocks by flowing air. Geotechnical testing laboratories alsomore » measure the following chemical parameters of soil and sediment samples collected during Hanford Site CERCLA RI: calcium carbonate and saturated column leach testing. Physical parameter data are used for (1) characterization of vadose and saturated zone geology and hydrogeology, (2) selection of monitoring well screen sizes, (3) to support modeling and analysis of the vadose and saturated zones, and (4) for engineering design. The objectives of this report are to determine the QA/QC levels accepted in the EPA Region 10 for the sampling, handling, and analysis of soil samples for physical parameters during CERCLA RI.« less

Are Developmentally-Exposed C57BL/6 Mice Insensitive to Suppression of TDAR by PFOA?

EPA Science Inventory

Perfluorooctanoic acid (PFOA) is an environmentally persistent fluorinated compound that is present in biological samples worldwide and associated with multisystem toxicity in laboratory animal models. Several studies have reported suppression of T-cell-dependent antibody respons...

Compatible ecological niche signals between biological and archaeological datasets for late-surviving Neandertals.

PubMed

Bible, Rachael C; Peterson, A Townsend

2018-04-17

To assess ecological niche similarity for biological and archaeological samples representing late-surviving Neandertals in Europe to evaluate the validity of combining these two types of data in ecological niche modeling analyses. Tests of niche conservatism were used to assess niche similarity and niche identity of samples of morphologically diagnostic Neandertal remains and Middle Paleolithic (MP) archaeological sites dating to the time period leading up to Neandertal extinction. Paleoenvironmental reconstructions for the Pre-H4 (43.3-40.2 ky cal BP) were used as environmental space analyses. Null hypotheses of niche similarity and identity of the two types of samples could not be rejected. As primary and secondary evidence of Neandertal occurrence during the Pre-H4 show high levels of niche similarity and identity, combining the two types of occurrence data to create larger samples for niche analyses is justified without the concern that different environmental signals could complicate future research. © 2018 Wiley Periodicals, Inc.

Environmental factors and their role in community integration after spinal cord injury.

PubMed

Lysack, Cathy; Komanecky, Marie; Kabel, Allison; Cross, Katherine; Neufeld, Stewart

2007-01-01

The International Classification of Functioning, Disability and Health (ICF) model presents an opportunity to better understand previously neglected longterm social outcomes after traumatic spinal cord injury (SCI), especially the experience of participation. The study explored the relationship between perceived environmental barriers and perceived community integration (a participation proxy) in a sample of adults with traumatic SCI. The study interviewed African American and White women and men (n = 136) who had lived with SCI for an average of 11.5 years. Participants reported environmental barriers at twice the level indicated by previous studies; the natural environment and the policies of government were the most problematic. Levels of community integration were also high. Data suggest a significant relationship (p < .01) between perceived environmental barriers and community integration for adults with SCI, providing support for the ICF model. Improved measures and more sophisticated concepts and theories are needed to explicate the relationship between environmental factors and participation concepts in the ICE With respect to practice, occupational therapists need to be aware that removal of environmental barriers is only a first step in the more complex effort to facilitate optimal community integration after SCI.

Ecological tolerances of Miocene larger benthic foraminifera from Indonesia

NASA Astrophysics Data System (ADS)

Novak, Vibor; Renema, Willem

2018-01-01

To provide a comprehensive palaeoenvironmental reconstruction based on larger benthic foraminifera (LBF), a quantitative analysis of their assemblage composition is needed. Besides microfacies analysis which includes environmental preferences of foraminiferal taxa, statistical analyses should also be employed. Therefore, detrended correspondence analysis and cluster analysis were performed on relative abundance data of identified LBF assemblages deposited in mixed carbonate-siliciclastic (MCS) systems and blue-water (BW) settings. Studied MCS system localities include ten sections from the central part of the Kutai Basin in East Kalimantan, ranging from late Burdigalian to Serravallian age. The BW samples were collected from eleven sections of the Bulu Formation on Central Java, dated as Serravallian. Results from detrended correspondence analysis reveal significant differences between these two environmental settings. Cluster analysis produced five clusters of samples; clusters 1 and 2 comprise dominantly MCS samples, clusters 3 and 4 with dominance of BW samples, and cluster 5 showing a mixed composition with both MCS and BW samples. The results of cluster analysis were afterwards subjected to indicator species analysis resulting in the interpretation that generated three groups among LBF taxa: typical assemblage indicators, regularly occurring taxa and rare taxa. By interpreting the results of detrended correspondence analysis, cluster analysis and indicator species analysis, along with environmental preferences of identified LBF taxa, a palaeoenvironmental model is proposed for the distribution of LBF in Miocene MCS systems and adjacent BW settings of Indonesia.

Cadmium mobility in sediments and soils from a coal mining area on Tibagi River watershed: environmental risk assessment.

PubMed

Galunin, Evgeny; Ferreti, Jeferson; Zapelini, Iago; Vieira, Isadora; Ricardo Teixeira Tarley, César; Abrão, Taufik; Santos, Maria Josefa

2014-01-30

The risk of cadmium contamination in the Tibagi River watershed (Parana State, Brazil) affected by past coal mining activities was assessed through sorption-desorption modeling for sediment and soil samples. The acidic character of the samples resulted in more competition between the cadmium ions and protons, thereby influencing the cadmium sorption-desorption. The sorption isotherms were fitted to the Langmuir and Freundlich single models and to the dual-site Langmuir-Freundlich (or Sips) model. The single-site models indicated a low-energy character of sorption sites on the sample sorption sites, whereas the dual-site model explained the availability of higher-affinity and lower-affinity non-specific sites. The correlation of the sorption and desorption constants with the physicochemical and mineralogical characteristics of the samples showed that the cadmium sorption behavior was significantly affected by the pH, point of zero charge, and also by the magnesium, aluminum, calcium and manganese amounts. Besides, the desorption rate and hysteresis index suggested a high risk of cadmium mobilization along the Tibagi River basin. Copyright © 2013 Elsevier B.V. All rights reserved.

The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

PubMed Central

Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.

2012-01-01

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307

A simple method to predict body temperature of small reptiles from environmental temperature.

PubMed

Vickers, Mathew; Schwarzkopf, Lin

2016-05-01

To study behavioral thermoregulation, it is useful to use thermal sensors and physical models to collect environmental temperatures that are used to predict organism body temperature. Many techniques involve expensive or numerous types of sensors (cast copper models, or temperature, humidity, radiation, and wind speed sensors) to collect the microhabitat data necessary to predict body temperatures. Expense and diversity of requisite sensors can limit sampling resolution and accessibility of these methods. We compare body temperature predictions of small lizards from iButtons, DS18B20 sensors, and simple copper models, in both laboratory and natural conditions. Our aim was to develop an inexpensive yet accurate method for body temperature prediction. Either method was applicable given appropriate parameterization of the heat transfer equation used. The simplest and cheapest method was DS18B20 sensors attached to a small recording computer. There was little if any deficit in precision or accuracy compared to other published methods. We show how the heat transfer equation can be parameterized, and it can also be used to predict body temperature from historically collected data, allowing strong comparisons between current and previous environmental temperatures using the most modern techniques. Our simple method uses very cheap sensors and loggers to extensively sample habitat temperature, improving our understanding of microhabitat structure and thermal variability with respect to small ectotherms. While our method was quite precise, we feel any potential loss in accuracy is offset by the increase in sample resolution, important as it is increasingly apparent that, particularly for small ectotherms, habitat thermal heterogeneity is the strongest influence on transient body temperature.

Are there common familial influences for major depressive disorder and an overeating-binge eating dimension in both European American and African American female twins?

PubMed

Munn-Chernoff, Melissa A; Grant, Julia D; Agrawal, Arpana; Koren, Rachel; Glowinski, Anne L; Bucholz, Kathleen K; Madden, Pamela A F; Heath, Andrew C; Duncan, Alexis E

2015-05-01

Although prior studies have demonstrated that depression is associated with an overeating-binge eating dimension (OE-BE) phenotypically, little research has investigated whether familial factors contribute to the co-occurrence of these phenotypes, especially in community samples with multiple racial/ethnic groups. We examined the extent to which familial (i.e., genetic and shared environmental) influences overlapped between Major Depressive Disorder (MDD) and OE-BE in a population-based sample and whether these influences were similar across racial/ethnic groups. Participants included 3,226 European American (EA) and 550 African American (AA) young adult women from the Missouri Adolescent Female Twin Study. An adaptation of the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was administered to assess lifetime DSM-IV MDD and OE-BE. Quantitative genetic modeling was used to estimate familial influences between both phenotypes; all models controlled for age. The best-fitting model, which combined racial/ethnic groups, found that additive genetic influences accounted for 44% (95% CI: 34%, 53%) of the MDD variance and 40% (25%, 54%) for OE-BE, with the remaining variances due to non-shared environmental influences. Genetic overlap was substantial (rg  = .61 [.39, .85]); non-shared environmental influences on MDD and OE-BE overlapped weakly (re  = .26 [.09, .42]). Results suggest that common familial influences underlie MDD and OE-BE, and the magnitude of familial influences contributing to the comorbidity between MDD and OE-BE is similar between EA and AA women. If racial/ethnic differences truly exist, then larger sample sizes may be needed to fully elucidate familial risk for comorbid MDD and OE-BE across these groups. © 2014 Wiley Periodicals, Inc.

Are There Common Familial Influences for Major Depressive Disorder and an Overeating-Binge Eating Dimension in both European-American and African-American Female Twins?

PubMed Central

Munn-Chernoff, Melissa A.; Grant, Julia D.; Agrawal, Arpana; Koren, Rachel; Glowinski, Anne L.; Bucholz, Kathleen K.; Madden, Pamela A. F.; Heath, Andrew C.; Duncan, Alexis E.

2014-01-01

Objective Although prior studies have demonstrated that depression is associated with an overeating-binge eating dimension (OE-BE), phenotypically, little research has investigated whether familial factors contribute to the co-occurrence of these phenotypes, especially in community samples with multiple racial/ethnic groups. We examined the extent to which familial (i.e., genetic and shared environmental) influences overlapped between Major Depressive Disorder (MDD) and OE-BE in a population-based sample and whether these influences were similar across racial/ethnic groups Method Participants included 3226 European-American (EA) and 550 African-American (AA) young adult women from the Missouri Adolescent Female Twin Study. An adaptation of the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was administered to assess lifetime DSM-IV MDD and OE-BE. Quantitative genetic modeling was used to estimate familial influences between both phenotypes; all models controlled for age. Results The best-fitting model, which combined racial/ethnic groups, found that additive genetic influences accounted for 44% (95% CI: 34%, 53%) of the MDD variance and 40% (25%, 54%) for OE-BE, with the remaining variances due to non-shared environmental influences. Genetic overlap was substantial (rg = .61 [.39, .85]); non-shared environmental influences on MDD and OE-BE overlapped weakly (re = .26 [.09, .42]) Discussion Results suggest that common familial influences underlie MDD and OE-BE, and the magnitude of familial influences contributing to the comorbidity between MDD and OE-BE is similar between EA and AA women. If racial/ethnic differences truly exist, then larger sample sizes may be needed to fully elucidate familial risk for comorbid MDD and OE-BE across these groups. PMID:24659561

Evaluation of conventional and alternative monitoring methods for a recreational marine beach with nonpoint source of fecal contamination.

PubMed

Shibata, Tomoyuki; Solo-Gabriele, Helena M; Sinigalliano, Christopher D; Gidley, Maribeth L; Plano, Lisa R W; Fleisher, Jay M; Wang, John D; Elmir, Samir M; He, Guoqing; Wright, Mary E; Abdelzaher, Amir M; Ortega, Cristina; Wanless, David; Garza, Anna C; Kish, Jonathan; Scott, Troy; Hollenbeck, Julie; Backer, Lorraine C; Fleming, Lora E

2010-11-01

The objectives of this work were to compare enterococci (ENT) measurements based on the membrane filter, ENT(MF) with alternatives that can provide faster results including alternative enterococci methods (e.g., chromogenic substrate (CS), and quantitative polymerase chain reaction (qPCR)), and results from regression models based upon environmental parameters that can be measured in real-time. ENT(MF) were also compared to source tracking markers (Staphylococcus aureus, Bacteroidales human and dog markers, and Catellicoccus gull marker) in an effort to interpret the variability of the signal. Results showed that concentrations of enterococci based upon MF (<2 to 3320 CFU/100 mL) were significantly different from the CS and qPCR methods (p < 0.01). The correlations between MF and CS (r = 0.58, p < 0.01) were stronger than between MF and qPCR (r ≤ 0.36, p < 0.01). Enterococci levels by MF, CS, and qPCR methods were positively correlated with turbidity and tidal height. Enterococci by MF and CS were also inversely correlated with solar radiation but enterococci by qPCR was not. The regression model based on environmental variables provided fair qualitative predictions of enterococci by MF in real-time, for daily geometric mean levels, but not for individual samples. Overall, ENT(MF) was not significantly correlated with source tracking markers with the exception of samples collected during one storm event. The inability of the regression model to predict ENT(MF) levels for individual samples is likely due to the different sources of ENT impacting the beach at any given time, making it particularly difficult to to predict short-term variability of ENT(MF) for environmental parameters.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

Contribution of personal and environmental factors on positive psychological functioning in adolescents.

PubMed

Fadda, Daniela; Scalas, L Francesca; Meleddu, Mauro

2015-08-01

This study examined self-esteem as mediator in the relations of personal (extraversion, neuroticism) and environmental (maternal, paternal, peer-relationships) variables with domains of positive psychological functioning (PPF) in adolescence (Satisfaction with life, Mastery, Vigor, Social Interest, Social Cheerfulness). We compared one-sided and multidimensional models using a sample of 1193 high school students (592 males and 601 females). We examined variations in adolescent PPF as a function of parenting styles via independent examination of maternal and paternal bonding. Results supported the multidimensional models, which indicated direct effects of personality traits, maternal care and peer relationships, as well as indirect effects, mediated by self-esteem, of all predictors on most PPF dimensions. Overall, our study provided a broader picture of personal and environmental predictors on different dimensions of PPF, which supported the mediating role of self-esteem and emphasized the importance of considering multidimensional models to characterize PPF in adolescents. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Environmental management and labour productivity: The moderating role of capital intensity.

PubMed

Lannelongue, Gustavo; Gonzalez-Benito, Javier; Quiroz, Idaisa

2017-04-01

Recent years have seen firms improve their environmental practices, although the question still remains as to whether or not investing in such practices is or is not beneficial or simply a matter of image. This study focuses on labour productivity as a measure of performance, and we argue that the impact of greater environmental performance on that productivity is moderated by capital intensity. A sample of 2823 plants provides empirical evidence to support our approach. Specifically, the analyses, making use of estimates based on multiple regression models, reveal that environmental management has a positive impact on labour productivity in organisations with low capital intensity, although that impact becomes negative in cases of high capital intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design of a WSN for the Sampling of Environmental Variability in Complex Terrain

PubMed Central

Martín-Tardío, Miguel A.; Felicísimo, Ángel M.

2014-01-01

In-situ environmental parameter measurements using sensor systems connected to a wireless network have become widespread, but the problem of monitoring large and mountainous areas by means of a wireless sensor network (WSN) is not well resolved. The main reasons for this are: (1) the environmental variability distribution is unknown in the field; (2) without this knowledge, a huge number of sensors would be necessary to ensure the complete coverage of the environmental variability and (3) WSN design requirements, for example, effective connectivity (intervisibility), limiting distances and controlled redundancy, are usually solved by trial and error. Using temperature as the target environmental variable, we propose: (1) a method to determine the homogeneous environmental classes to be sampled using the digital elevation model (DEM) and geometric simulations and (2) a procedure to determine an effective WSN design in complex terrain in terms of the number of sensors, redundancy, cost and spatial distribution. The proposed methodology, based on geographic information systems and binary integer programming can be easily adapted to a wide range of applications that need exhaustive and continuous environmental monitoring with high spatial resolution. The results show that the WSN design is perfectly suited to the topography and the technical specifications of the sensors, and provides a complete coverage of the environmental variability in terms of Sun exposure. However these results still need be validated in the field and the proposed procedure must be refined. PMID:25412218

Habitat modeling for brown trout population in alpine region of Slovenia with focus on determination of preference functions, fuzzy rules and fuzzy sets

NASA Astrophysics Data System (ADS)

Santl, Saso; Carf, Masa; Preseren, Tanja; Jenic, Aljaz

2013-04-01

Water withdrawals and consequently reduction of discharges in river streams for different water uses (hydro power, irrigation, etc.) usually impoverish habitat suitability for naturally present river fish fauna. In Slovenia reduction of suitable habitats resulting from water abstractions frequently impacts local brown trout (Salmo truta) populations. This is the reason for establishment of habitat modeling which can qualitatively and quantitatively support decision making for determination of the environmental flow and other mitigation measures. Paper introduces applied methodology for habitat modeling where input data preparation and elaboration with required accuracy has to be considered. For model development four (4) representative and heterogeneous sampling sites were chosen. Two (2) sampling sections were located within the sections with small hydropower plants and were considered as sections affected by water abstractions. The other two (2) sampling sections were chosen where there are no existing water abstractions. Precise bathymetric mapping for chosen river sections has been performed. Topographic data and series of discharge and water level measurements enabled establishment of calibrated hydraulic models, which provide data on water velocities and depths for analyzed discharges. Brief field measurements were also performed to gather required data on dominant and subdominant substrate size and cover type. Since the accuracy of fish distribution on small scale is very important for habitat modeling, a fish sampling method had to be selected and modified for existing river microhabitats. The brown trout specimen's locations were collected with two (2) different sampling methods. A method of riverbank observation which is suitable for adult fish in pools and a method of electro fishing for locating small fish and fish in riffles or hiding in cover. Ecological and habitat requirements for fish species vary regarding different fish populations as well as eco and hydro morphological types of streams. Therefore, if habitat modeling for brown trout in Slovenia should be applied, it is necessary to determine preference requirements for the locally present brown trout populations. For efficient determination of applied preference functions and linked fuzzy sets/rules, beside expert determination, calibration according to field sampling must also be performed. After this final step a model is prepared for the analysis to support decision making in the field of environmental flow and other mitigation measures determination.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

Predictions of LDEF radioactivity and comparison with measurements

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.; Harmon, B. A.; Laird, C. E.

1995-01-01

As part of the program to utilize LDEF data for evaluation and improvement of current ionizing radiation environmental models and related predictive methods for future LEO missions, calculations have been carried out to compare with the induced radioactivity measured in metal samples placed on LDEF. The predicted activation is about a factor of two lower than observed, which is attributed to deficiencies in the AP8 trapped proton model. It is shown that this finding based on activation sample data is consistent with comparisons made with other LDEF activation and dose data. Plans for confirming these results utilizing additional LDEF data sets, and plans for model modifications to improve the agreement with LDEF data, are discussed.

Control of a Clonal Outbreak of Multidrug-Resistant Acinetobacter baumannii in a Hospital of the Basque Country after the Introduction of Environmental Cleaning Led by the Systematic Sampling from Environmental Objects.

PubMed

Delgado Naranjo, Jesús; Villate Navarro, José Ignacio; Sota Busselo, Mercedes; Martínez Ruíz, Alberto; Hernández Hernández, José María; Torres Garmendia, María Pilar; Urcelay López, María Isabel

2013-01-01

Background. Between July 2009 and September 2010, an outbreak of multidrug-resistant (MDR) Acinetobacter baumannii was detected in one critical care unit of a tertiary hospital in the Basque Country, involving 49 infected and 16 colonized patients. The aim was to evaluate the impact of environmental cleaning and systematic sampling from environmental objects on the risk of infection by MDR A. baumannii. Methods. After systematic sampling from environmental objects and molecular typing of all new MDR A. baumannii strains from patients and environmental isolates, we analyzed the correlation (Pearson's r) between new infected cases and positive environmental samples. The risk ratio (RR) of infection was estimated with Poisson regression. Results. The risk increased significantly with the number of positive samples in common areas (RR = 1.40; 95%CI = 0.99-1.94) and positive samples in boxes (RR = 1.19; 95%CI = 1.01-1.40). The number of cases also positively correlated with positive samples in boxes (r = 0.50; P < 0.05) and common areas (r = 0.29; P = 0.18). Conclusion. Once conventional measures have failed, environmental cleaning, guided by systematic sampling from environmental objects, provided the objective risk reduction of new cases and enabled the full control of the outbreak.

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

NASA Astrophysics Data System (ADS)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Knowledge, Learning, Analysis System (KLAS)

USDA-ARS?s Scientific Manuscript database

The goal of KLAS is to develop a new scientific approach that takes advantage of the data deluge, defined here as both legacy data and new data acquired from environmental and biotic sensors, complex simulation models, and improved technologies for probing biophysical samples. This approach can be i...

Estimating species - area relationships by modeling abundance and frequency subject to incomplete sampling.

PubMed

Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-07-01

Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

USGS Publications Warehouse

Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-01-01

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Digital Curation of Earth Science Samples Starts in the Field

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Hsu, L.; Song, L.; Carter, M. R.

2014-12-01

Collection of physical samples in the field is an essential part of research in the Earth Sciences. Samples provide a basis for progress across many disciplines, from the study of global climate change now and over the Earth's history, to present and past biogeochemical cycles, to magmatic processes and mantle dynamics. The types of samples, methods of collection, and scope and scale of sampling campaigns are highly diverse, ranging from large-scale programs to drill rock and sediment cores on land, in lakes, and in the ocean, to environmental observation networks with continuous sampling, to single investigator or small team expeditions to remote areas around the globe or trips to local outcrops. Cyberinfrastructure for sample-related fieldwork needs to cater to the different needs of these diverse sampling activities, aligning with specific workflows, regional constraints such as connectivity or climate, and processing of samples. In general, digital tools should assist with capture and management of metadata about the sampling process (location, time, method) and the sample itself (type, dimension, context, images, etc.), management of the physical objects (e.g., sample labels with QR codes), and the seamless transfer of sample metadata to data systems and software relevant to the post-sampling data acquisition, data processing, and sample curation. In order to optimize CI capabilities for samples, tools and workflows need to adopt community-based standards and best practices for sample metadata, classification, identification and registration. This presentation will provide an overview and updates of several ongoing efforts that are relevant to the development of standards for digital sample management: the ODM2 project that has generated an information model for spatially-discrete, feature-based earth observations resulting from in-situ sensors and environmental samples, aligned with OGC's Observation & Measurements model (Horsburgh et al, AGU FM 2014); implementation of the IGSN (International Geo Sample Number) as a globally unique sample identifier via a distributed system of allocating agents and a central registry; and the EarthCube Research Coordination Network iSamplES (Internet of Samples in the Earth Sciences) that aims to improve sharing and curation of samples through the use of CI.

Statistical approaches to account for false-positive errors in environmental DNA samples.

PubMed

Lahoz-Monfort, José J; Guillera-Arroita, Gurutzeta; Tingley, Reid

2016-05-01

Environmental DNA (eDNA) sampling is prone to both false-positive and false-negative errors. We review statistical methods to account for such errors in the analysis of eDNA data and use simulations to compare the performance of different modelling approaches. Our simulations illustrate that even low false-positive rates can produce biased estimates of occupancy and detectability. We further show that removing or classifying single PCR detections in an ad hoc manner under the suspicion that such records represent false positives, as sometimes advocated in the eDNA literature, also results in biased estimation of occupancy, detectability and false-positive rates. We advocate alternative approaches to account for false-positive errors that rely on prior information, or the collection of ancillary detection data at a subset of sites using a sampling method that is not prone to false-positive errors. We illustrate the advantages of these approaches over ad hoc classifications of detections and provide practical advice and code for fitting these models in maximum likelihood and Bayesian frameworks. Given the severe bias induced by false-negative and false-positive errors, the methods presented here should be more routinely adopted in eDNA studies. © 2015 John Wiley & Sons Ltd.

Using habitat suitability models to target invasive plant species surveys.

PubMed

Crall, Alycia W; Jarnevich, Catherine S; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P < 0.01), and targeted sampling did detect more species than nontargeted sampling with less sampling effort (chi2 = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.

A practical guide to environmental association analysis in landscape genomics.

PubMed

Rellstab, Christian; Gugerli, Felix; Eckert, Andrew J; Hancock, Angela M; Holderegger, Rolf

2015-09-01

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. © 2015 John Wiley & Sons Ltd.

Direct toxicity assessment - Methods, evaluation, interpretation.

PubMed

Gruiz, Katalin; Fekete-Kertész, Ildikó; Kunglné-Nagy, Zsuzsanna; Hajdu, Csilla; Feigl, Viktória; Vaszita, Emese; Molnár, Mónika

2016-09-01

Direct toxicity assessment (DTA) results provide the scale of the actual adverse effect of contaminated environmental samples. DTA results are used in environmental risk management of contaminated water, soil and waste, without explicitly translating the results into chemical concentration. The end points are the same as in environmental toxicology in general, i.e. inhibition rate, decrease in the growth rate or in yield and the 'no effect' or the 'lowest effect' measurement points of the sample dilution-response curve. The measurement unit cannot be a concentration, since the contaminants and their content in the sample is unknown. Thus toxicity is expressed as the sample proportion causing a certain scale of inhibition or no inhibition. Another option for characterizing the scale of toxicity of an environmental sample is equivalencing. Toxicity equivalencing represents an interpretation tool which enables toxicity of unknown mixtures of chemicals be converted into the concentration of an equivalently toxic reference substance. Toxicity equivalencing, (i.e. expressing the toxicity of unknown contaminants as the concentration of the reference) makes DTA results better understandable for non-ecotoxicologists and other professionals educated and thinking based on the chemical model. This paper describes and discusses the role, the principles, the methodology and the interpretation of direct toxicity assessment (DTA) with the aim to contribute to the understanding of the necessity to integrate DTA results into environmental management of contaminated soil and water. The paper also introduces the benefits of the toxicity equivalency method. The use of DTA is illustrated through two case studies. The first case study focuses on DTA of treated wastewater with the aim to characterize the treatment efficacy of a biological wastewater treatment plant by frequent bioassaying. The second case study applied DTA to investigate the cover layers of two bauxite residue (red mud) reservoirs. Based on the DTA results the necessary toxicity attenuation rate of the cover layers was estimated. Copyright © 2016 Elsevier B.V. All rights reserved.

The big five personality traits: psychological entities or statistical constructs?

PubMed

Franić, Sanja; Borsboom, Denny; Dolan, Conor V; Boomsma, Dorret I

2014-11-01

The present study employed multivariate genetic item-level analyses to examine the ontology and the genetic and environmental etiology of the Big Five personality dimensions, as measured by the NEO Five Factor Inventory (NEO-FFI) [Costa and McCrae, Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO-FFI) professional manual, 1992; Hoekstra et al., NEO personality questionnaires NEO-PI-R, NEO-FFI: manual, 1996]. Common and independent pathway model comparison was used to test whether the five personality dimensions fully mediate the genetic and environmental effects on the items, as would be expected under the realist interpretation of the Big Five. In addition, the dimensionalities of the latent genetic and environmental structures were examined. Item scores of a population-based sample of 7,900 adult twins (including 2,805 complete twin pairs; 1,528 MZ and 1,277 DZ) on the Dutch version of the NEO-FFI were analyzed. Although both the genetic and the environmental covariance components display a 5-factor structure, applications of common and independent pathway modeling showed that they do not comply with the collinearity constraints entailed in the common pathway model. Implications for the substantive interpretation of the Big Five are discussed.

Genetic signatures of natural selection in a model invasive ascidian

PubMed Central

Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

2017-01-01

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta. PMID:28266616

Three-and-a-half-factor model? The genetic and environmental structure of the CBCL/6-18 internalizing grouping.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2014-05-01

In the present article, multivariate genetic item analyses were employed to address questions regarding the ontology and the genetic and environmental etiology of the Anxious/Depressed, Withdrawn, and Somatic Complaints syndrome dimensions of the Internalizing grouping of the Child Behavior Checklist/6-18 (CBCL/6-18). Using common and independent pathway genetic factor modeling, it was examined whether these syndrome dimensions can be ascribed a realist ontology. Subsequently, the structures of the genetic and environmental influences giving rise to the observed symptom covariation were examined. Maternal ratings of a population-based sample of 17,511 Dutch twins of mean age 7.4 (SD = 0.4) on the items of the Internalizing grouping of the Dutch CBCL/6-18 were analyzed. Applications of common and independent pathway modeling demonstrated that the Internalizing syndrome dimensions may be better understood as a composite of unconstrained genetic and environmental influences than as causally relevant entities generating the observed symptom covariation. Furthermore, the results indicate a common genetic basis for anxiety, depression, and withdrawn behavior, with the distinction between these syndromes being driven by the individual-specific environment. Implications for the substantive interpretation of these syndrome dimensions are discussed.

Associated pathways between neighborhood environment, community resource factors and leisure-time physical activity among Mexican-American adults in San Diego, CA

PubMed Central

Martinez, Suzanna M.; Ayala, Guadalupe X.; Patrick, Kevin; Arredondo, Elva M.; Roesch, Scott; Elder, John

2014-01-01

Purpose To examine pathways between individual, social, and environmental factors associated with leisure-time physical activity (LTPA) among Mexican-American adults. Design Cross-sectional design using random digit dialing to administer a structured telephone interview. Setting Mexican-American adults living in a U.S./Mexican border community in San Diego, CA (N=672). Measures Data were collected on LTPA, demographic characteristics, acculturation, and other psychosocial and environmental factors associated with LTPA. Analysis Structural equation modeling to test an a priori model of LTPA. Results Participants were mostly female (71%) with a mean age of 39 years (SD = 13). Only 32% of participants met PA guidelines in their leisure time, with men (39%) meeting the guidelines more than women (29%). Using structural equation modeling, neighborhood factors, both social and environmental, showed indirect relationships with meeting PA guidelines through community resource factors. Significant covariates included marital status and age. Conclusion Individual, social and environmental factors were associated with LTPA in this sample of Mexican-American adults. These findings can inform intervention studies that aim to increase LTPA in this population. PMID:22548422

Study on induced radioactivity of China Spallation Neutron Source

NASA Astrophysics Data System (ADS)

Wu, Qing-Biao; Wang, Qing-Bin; Wu, Jing-Min; Ma, Zhong-Jian

2011-06-01

China Spallation Neutron Source (CSNS) is the first High Energy Intense Proton Accelerator planned to be constructed in China during the State Eleventh Five-Year Plan period, whose induced radioactivity is very important for occupational disease hazard assessment and environmental impact assessment. Adopting the FLUKA code, the authors have constructed a cylinder-tunnel geometric model and a line-source sampling physical model, deduced proper formulas to calculate air activation, and analyzed various issues with regard to the activation of different tunnel parts. The results show that the environmental impact resulting from induced activation is negligible, whereas the residual radiation in the tunnels has a great influence on maintenance personnel, so strict measures should be adopted.

Is hyperactivity ubiquitous in ADHD or dependent on environmental demands? Evidence from meta-analysis

PubMed Central

Kofler, Michael J.; Raiker, Joseph S.; Sarver, Dustin E.; Wells, Erica L.; Soto, Elia F.

2016-01-01

Hyperactivity, or excess gross motor activity, is considered a core and ubiquitous characteristic of ADHD. Alternate models question this premise, and propose that hyperactive behavior reflects, to a large extent, purposeful behavior to cope with environmental demands that interact with underlying neurobiological vulnerabilities. The present review critically evaluates the ubiquity and environmental modifiability of hyperactivity in ADHD through meta-analysis of 63 studies of mechanically measured activity level in children, adolescents, and adults with ADHD relative to typically developing (TD) groups. Random effects models corrected for publication bias confirmed elevated gross motor activity in ADHD (d = 0.86); surprisingly, neither participant age (child vs. adult) nor the proportion of each ADHD sample diagnosed with the Inattentive subtype/presentation moderated this effect. In contrast, activity level assessed during high cognitive load conditions in general (d = 1.14) and high executive functioning demands in particular (d = 1.39) revealed significantly higher effect sizes than activity level during low cognitive load (d = 0.36) and in-class schoolwork (d = 0.50) settings. Low stimulation environments, more rigorous diagnostic practices, actigraph measurement of movement frequency and intensity, and ADHD samples that included fewer females were also associated with larger effects. Overall, the results are inconsistent with DSM-5 and ADHD models that a) describe hyperactivity as ubiquitous behavior, b) predict a developmental decline in hyperactivity, or c) differentiate subtypes/presentations according to perceived differences in hyperactive behavior. Instead, results suggest that the presence and magnitude of hyperactive behavior in ADHD may be influenced to a considerable extent by environmental factors in general, and cognitive/executive functioning demands in particular. PMID:27131918

Use of remote sensing and a geographical information system in a national helminth control programme in Chad.

PubMed Central

Brooker, Simon; Beasley, Michael; Ndinaromtan, Montanan; Madjiouroum, Ester Mobele; Baboguel, Marie; Djenguinabe, Elie; Hay, Simon I.; Bundy, Don A. P.

2002-01-01

OBJECTIVE: To design and implement a rapid and valid epidemiological assessment of helminths among schoolchildren in Chad using ecological zones defined by remote sensing satellite sensor data and to investigate the environmental limits of helminth distribution. METHODS: Remote sensing proxy environmental data were used to define seven ecological zones in Chad. These were combined with population data in a geographical information system (GIS) in order to define a sampling protocol. On this basis, 20 schools were surveyed. Multilevel analysis, by means of generalized estimating equations to account for clustering at the school level, was used to investigate the relationship between infection patterns and key environmental variables. FINDINGS: In a sample of 1023 schoolchildren, 22.5% were infected with Schistosoma haematobium and 32.7% with hookworm. None were infected with Ascaris lumbricoides or Trichuris trichiura. The prevalence of S. haematobium and hookworm showed marked geographical heterogeneity and the observed patterns showed a close association with the defined ecological zones and significant relationships with environmental variables. These results contribute towards defining the thermal limits of geohelminth species. Predictions of infection prevalence were made for each school surveyed with the aid of models previously developed for Cameroon. These models correctly predicted that A. lumbricoides and T. trichiura would not occur in Chad but the predictions for S. haematobium were less reliable at the school level. CONCLUSION: GIS and remote sensing can play an important part in the rapid planning of helminth control programmes where little information on disease burden is available. Remote sensing prediction models can indicate patterns of geohelminth infection but can only identify potential areas of high risk for S. haematobium. PMID:12471398

Groundwater vulnerability to pollution mapping of Ranchi district using GIS

NASA Astrophysics Data System (ADS)

Krishna, R.; Iqbal, J.; Gorai, A. K.; Pathak, G.; Tuluri, F.; Tchounwou, P. B.

2015-12-01

Groundwater pollution due to anthropogenic activities is one of the major environmental problems in urban and industrial areas. The present study demonstrates the integrated approach with GIS and DRASTIC model to derive a groundwater vulnerability to pollution map. The model considers the seven hydrogeological factors [Depth to water table ( D), net recharge ( R), aquifer media ( A), soil media ( S), topography or slope ( T), impact of vadose zone ( I) and hydraulic Conductivity( C)] for generating the groundwater vulnerability to pollution map. The model was applied for assessing the groundwater vulnerability to pollution in Ranchi district, Jharkhand, India. The model was validated by comparing the model output (vulnerability indices) with the observed nitrate concentrations in groundwater in the study area. The reason behind the selection of nitrate is that the major sources of nitrate in groundwater are anthropogenic in nature. Groundwater samples were collected from 30 wells/tube wells distributed in the study area. The samples were analyzed in the laboratory for measuring the nitrate concentrations in groundwater. A sensitivity analysis of the integrated model was performed to evaluate the influence of single parameters on groundwater vulnerability index. New weights were computed for each input parameters to understand the influence of individual hydrogeological factors in vulnerability indices in the study area. Aquifer vulnerability maps generated in this study can be used for environmental planning and groundwater management.

Groundwater vulnerability to pollution mapping of Ranchi district using GIS.

PubMed

Krishna, R; Iqbal, J; Gorai, A K; Pathak, G; Tuluri, F; Tchounwou, P B

2015-12-01

Groundwater pollution due to anthropogenic activities is one of the major environmental problems in urban and industrial areas. The present study demonstrates the integrated approach with GIS and DRASTIC model to derive a groundwater vulnerability to pollution map. The model considers the seven hydrogeological factors [Depth to water table ( D ), net recharge ( R ), aquifer media ( A ), soil media ( S ), topography or slope ( T ), impact of vadose zone ( I ) and hydraulic Conductivity( C )] for generating the groundwater vulnerability to pollution map. The model was applied for assessing the groundwater vulnerability to pollution in Ranchi district, Jharkhand, India. The model was validated by comparing the model output (vulnerability indices) with the observed nitrate concentrations in groundwater in the study area. The reason behind the selection of nitrate is that the major sources of nitrate in groundwater are anthropogenic in nature. Groundwater samples were collected from 30 wells/tube wells distributed in the study area. The samples were analyzed in the laboratory for measuring the nitrate concentrations in groundwater. A sensitivity analysis of the integrated model was performed to evaluate the influence of single parameters on groundwater vulnerability index. New weights were computed for each input parameters to understand the influence of individual hydrogeological factors in vulnerability indices in the study area. Aquifer vulnerability maps generated in this study can be used for environmental planning and groundwater management.

A data model for environmental scientists

NASA Astrophysics Data System (ADS)

Kapeljushnik, O.; Beran, B.; Valentine, D.; van Ingen, C.; Zaslavsky, I.; Whitenack, T.

2008-12-01

Environmental science encompasses a wide range of disciplines from water chemistry to microbiology, ecology and atmospheric sciences. Studies often require working across disciplines which differ in their ways of describing and storing data such that it is not possible to devise a monolithic one-size-fits-all data solution. Based on our experiences with Consortium of the Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) Observations Data Model, Berkeley Water Center FLUXNET carbon-climate work and by examining standards like EPA's Water Quality Exchange (WQX), we have developed a flexible data model that allows extensions without need to altering the schema such that scientists can define custom metadata elements to describe their data including observations, analysis methods as well as sensors and geographical features. The data model supports various types of observations including fixed point and moving sensors, bottled samples, rasters from remote sensors and models, and categorical descriptions (e.g. taxonomy) by employing user-defined-types when necessary. It leverages ADO .NET Entity Framework to provide the semantic data models for differing disciplines, while maintaining a common schema below the entity layer. This abstraction layer simplifies data retrieval and manipulation by hiding the logic and complexity of the relational schema from users thus allows programmers and scientists to deal directly with objects such as observations, sensors, watersheds, river reaches, channel cross-sections, laboratory analysis methods and samples as opposed to table joins, columns and rows.

[Contamination of health care institutions environmental objects by Legionella pneumophila].

PubMed

Shkarin, V V; Blagonravova, A S; Chubukova, O A; Korotaeva, S V

2011-01-01

AIM. The extent of environmental objects contamination by Legionella pneumophila in Nizhny Novgorod and Nizhny Novgorod region hospitals evaluation, and detection of potentially hazardous objects. 433 swabs of environmental objects, and 43 hot water supply and pool water samples from various departments of 4 multi-disciplinary hospitals were studies. DNA from environmental samples was detected by using real time PCR. L. pneumophila DNA was detected in 41 (9,47%) samples from environmental objects and in 2 (4,65%) samples from hot water supply. These bacteria were more frequently detected in environmental samples from physiotherapy departments. Repeated detection of legionellae from the same objects was registered. Circulation of legionellae in multidisciplinary hospitals was determined. Circulation high risk departments and risk objects--reservoirs of L. pneumophila in health care institutions were determined.

Genetic and environmental influences on female sexual orientation, childhood gender typicality and adult gender identity.

PubMed

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates--childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation.

Environmental determinants of radiolarian assemblages in the western Pacific since the last deglaciation

NASA Astrophysics Data System (ADS)

Hernández-Almeida, I.; Cortese, G.; Yu, P.-S.; Chen, M.-T.; Kucera, M.

2017-08-01

Radiolarians are a very diverse microzooplanktonic group, often distributed in regionally restricted assemblages and responding to specific environmental factors. These properties of radiolarian assemblages make the group more conducive for the development and application of basin-wide ecological models. Here we use a new surface sediment data set from the western Pacific to demonstrate that ecological patterns derived from basin-wide open-ocean data sets cannot be transferred on semirestricted marginal seas. The data set consists of 160 surface sediment samples from three tropical-subtropical regions (East China Sea, South China Sea, and western Pacific), combining 54 new assemblage counts with taxonomically harmonized data from previous studies. Multivariate statistical analyses indicate that winter sea surface temperature at 10 m depth (SSTw) was the most significant environmental variable affecting the composition of radiolarian assemblages, allowing the development of an optimal calibration model (Locally Weighted-Weighted Averaging regression inverse deshrinking, R2cv = 0.88, root-mean-square error of prediction = 1.6°C). The dominant effect of SSTw on radiolarian assemblage composition in the western Pacific is attributed to the East Asian Winter Monsoon (EAWM), which is particularly strong in the marginal seas. To test the applicability of the calibration model on fossil radiolarian assemblages from the marginal seas, the calibration model was applied to two downcore records from the Okinawa Trough, covering the last 18 ka. We observe that these assemblages find most appropriate analogs among modern samples from the marginal basins (East China Sea and South China Sea). Downcore temperature reconstructions at both sites show similarities to known regional SST reconstructions, providing proof of concept for the new radiolarian-based SSTw calibration model.

Integrated sampling and analysis unit for the determination of sexual pheromones in environmental air using fabric phase sorptive extraction and headspace-gas chromatography-mass spectrometry.

PubMed

Alcudia-León, M Carmen; Lucena, Rafael; Cárdenas, Soledad; Valcárcel, Miguel; Kabir, Abuzar; Furton, Kenneth G

2017-03-10

This article presents a novel unit that integrates for the first time air sampling and preconcentration based on the use of fabric phase sorptive extraction principles. The determination of Tuta absoluta sexual pheromone traces in environmental air has been selected as analytical problem. For this aim, a novel laboratory-built unit made up of commercial brass elements as holder of the sol-gel coated fabric extracting phase has been designed and optimized. The performance of the integrated unit was evaluated analyzing environmental air sampled in tomato crops. The unit can work under sampling and analysis mode which eliminates any need for sorptive phase manipulation prior to instrumental analysis. In the sampling mode, the unit can be connected to a sampling pump to pass the air through the sorptive phase at a controlled flow-rate. In the analysis mode, it is placed in the gas chromatograph autosampler without any instrumental modification. It also diminishes the risk of cross contamination between sampling and analysis. The performance of the new unit has been evaluated using the main components of the sexual pheromone of Tuta absoluta [(3E,8Z,11Z)-tetradecatrien-1-yl acetate and (3E,8Z)-tetradecadien-1-yl acetate] as model analytes. The limits of detection for both compounds resulted to be 1.6μg and 0.8μg, respectively, while the precision (expressed as relative standard deviation) was better than 3.7%. Finally, the unit has been deployed in the field to analyze a number of real life samples, some of them were found positive. Copyright © 2017 Elsevier B.V. All rights reserved.

Environmental and anthropogenic factors affecting the probability of occurrence of Oncomegas wageneri (Cestoda: Trypanorhyncha) in the southern Gulf of Mexico.

PubMed

Vidal-Martínez, Víctor M; Torres-Irineo, Edgar; Romero, David; Gold-Bouchot, Gerardo; Martínez-Meyer, Enrique; Valdés-Lozano, David; Aguirre-Macedo, M Leopoldina

2015-11-26

Understanding the environmental and anthropogenic factors influencing the probability of occurrence of the marine parasitic species is fundamental for determining the circumstances under which they can act as bioindicators of environmental impact. The aim of this study was to determine whether physicochemical variables, polyaromatic hydrocarbons or sewage discharge affect the probability of occurrence of the larval cestode Oncomegas wageneri, which infects the shoal flounder, Syacium gunteri, in the southern Gulf of Mexico. The study area included 162 sampling sites in the southern Gulf of Mexico and covered 288,205 km(2), where the benthic sediments, water and the shoal flounder individuals were collected. We used the boosted generalised additive models (boosted GAM) and the MaxEnt to examine the potential statistical relationships between the environmental variables (nutrients, contaminants and physicochemical variables from the water and sediments) and the probability of the occurrence of this parasite. The models were calibrated using all of the sampling sites (full area) with and without parasite occurrences (n = 162) and a polygon area that included sampling sites with a depth of 1500 m or less (n = 134). Oncomegas wageneri occurred at 29/162 sampling sites. The boosted GAM for the full area and the polygon area accurately predicted the probability of the occurrence of O. wageneri in the study area. By contrast, poor probabilities of occurrence were obtained with the MaxEnt models for the same areas. The variables with the highest frequencies of appearance in the models (proxies for the explained variability) were the polyaromatic hydrocarbons of high molecular weight (PAHH, 95 %), followed by a combination of nutrients, spatial variables and polyaromatic hydrocarbons of low molecular weight (PAHL, 5 %). The contribution of the PAHH to the variability was explained by the fact that these compounds, together with N and P, are carried by rivers that discharge into the ocean, which enhances the growth of hydrocarbonoclastic bacteria and the productivity and number of the intermediate hosts. Our results suggest that sites with PAHL/PAHH ratio values up to 1.89 promote transmission based on the high values of the prevalence of O. wageneri in the study area. In contrast, PAHL/PAHH ratio values ≥ 1.90 can be considered harmful for the transmission stages of O. wageneri and its hosts (copepods, shrimps and shoal flounders). Overall, the results indicate that the PAHHs affect the probability of occurrence of this helminth parasite in the southern Gulf of Mexico.

Natural variability of biochemical biomarkers in the macro-zoobenthos: Dependence on life stage and environmental factors.

PubMed

Scarduelli, Lucia; Giacchini, Roberto; Parenti, Paolo; Migliorati, Sonia; Di Brisco, Agnese Maria; Vighi, Marco

2017-11-01

Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding whether the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proven to be relevant across both space and time. In the present study, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered sampling sites in 2 different rivers, 8 sampling dates covering the whole seasonal cycle, 4 species from 3 different taxonomic groups (Plecoptera, Perla grandis; Ephemeroptera, Baetis alpinus and Epeorus alpicula; Tricoptera, Hydropsyche pellucidula), different life stages for each species, and 4 enzymes (acetylcholinesterase, glutathione S-transferase, alkaline phosphatase, and catalase). Biomarker levels were related to environmental (physicochemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. Environ Toxicol Chem 2017;36:3158-3167. © 2017 SETAC. © 2017 SETAC.

Monitoring abnormal bio-optical and physical properties in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Arnone, Robert; Jones, Brooke

2017-05-01

The dynamic bio-optical and physical ocean properties within the Gulf of Mexico (GoM) have been identified by the Ocean Weather Laboratory. Ocean properties from VIIRS satellite (Chlorophyll and Bio-Optics and SST) and ocean-circulation models (currents, SST and salinity) were used to identify regions of dynamic changing properties. The degree of environmental change is defined by the dynamic anomaly of bio-optical and physical environmental properties (DAP). A Mississippi River plume event (Aug 2015) that extended to Key West was used to demonstrate the anomaly products. Locations where normal and abnormal ocean properties occur determine ecological and physical hotspots in the GoM, which can be used for adaptive sampling of ocean processes. Methods are described to characterize the weekly abnormal environmental properties using differences with a previous baseline 8 week mean with a 2 week lag. The intensity of anomaly is quantified using levels of standard deviation of the baseline and can be used to recognize ocean events and provide decision support for adaptive sampling. The similarities of the locations of different environmental property anomalies suggest interaction between the bio-optical and physical properties. A coral bleaching event at the Flower Garden Banks Marine Protected Area is represented by the salinity anomaly. Results identify ocean regions for sampling to reduce data gaps and improve monitoring of bio-optical and physical properties.

[Environmental and genetic factors associated with psychoactive medication use in adult females. A population-based twin study].

PubMed

Rosagro Escámez, Francisco; González-Javier, Francisca; Ordoñana, Juan R

2013-01-01

Our objective is to determine the prevalence and factors associated to psychotropic medication consumption in a sample of adult females. Additionally, this study seeks to analyze the relative contribution of environmental and genetic factors to psychoactive medication use. Sample consists of a population-based cohort comprising 437 pairs of female twins born between 1940 and 1966. Information is collected through individual interviews, and it includes employment status, educational level, partner status, menopause, presence of mental disorders and psychoactive medication use. Logistic regression models are applied. The relative contribution of genetic and environmental factors to interindividual variation is analyzed through the classical twin design. In the past month, 34.0% of the women interviewed had consumed psychoactive medication. Consumption increases with age, in women out of the labor market, menopausal, and reporting a history of mental disorders. When controlling for age, all variables lost significance, except the presence of mental health problems. Heritability estimates for psychoactive medication use was 52%. This estimate is similar (46%) for consumption in the two categories studied. There is a high prevalence of psychoactive medication use in this sample. This consumption is mainly associated with age and presence of mental disorders. About half of the interindividual variation in psychotropic medication use is attributable to genetic factors, while the rest of the variance would be due to environmental factors unique to each individual.

Resource Utilization and Environmental and Spatio-Temporal Overlap of a Hilltopping Lycaenid Butterfly Community in the Colombian Andes

PubMed Central

Prieto, Carlos; Dahners, Hans W.

2009-01-01

Coexistence by a great number of species could reflect niche segregation at several resource axes. Differences in the use of a hilltop as mating site for a Eumaeini (Lycaenidae) community were measured to test whether niche segregation exists within this group. Specimens were collected throughout 21 samplings between July-October of 2004 and July-October of 2005. Two environmental variables and three temporal-spacial variables were analyzed utilizing null models with three randomization algorithms. Significant differences were found among the species with respect to utilization of vertical space, horizontal space, temporary distribution and environmental temperature. The species did not show significant differences with respect to light intensity. For all samplings, the niche overlap observed in the two environmental variables were higher or significantly higher than expected by chance, suggesting that niche segregation does not exist due to competition within these variables. Similar results were observed for temporal distribution. Some evidence of niche segregation was found in vertical space and horizontal space variables where some samples presented lower overlap than expected by chance. The results pointed out that community's assemblage could be mainly shaped in two ways. The first is that species with determined habitat requirements fit into unoccupied niche spaces. The second is by niche segregation in the vertical space distribution variable. PMID:19613456

Marine environmental impact assessment of abalone, Haliotis discus hannai, cage farm in Wan-do, Republic of Korea

NASA Astrophysics Data System (ADS)

Oh, Hyun-Taik; Jung, Rae-Hong; Cho, Yoon-Sik; Hwang, Dong-Woon; Yi, Yong-Min

2015-12-01

To assess the marine environmental impacts of abalone, Haliotis discus hannai, cage farms in Wan-do, we monitored the benthic environment on top of the sediment underneath cage farm stations and reference stations. We applied two methods for this assessment. One was the A- and B-investigation of the MOM system (Modeling-On fish farm-Monitoring) developed in Norway. The other was a general environmental monitoring method which is widely used. In this study, we found benthic animals in all samples that belonged to condition 1 which were based on group 1(presence of macrofauna) of the B-investigation method. The values of redox potential (group 2-pH, redox potential) in all samples were above +65 mV belonging to condition 1. Based on sensory results (group 3-gas, color, odor, thickness of deposits), five out of seven experiment samples showed condition 1 while stations 2 and 7 showed condition 2, which have been cultured for 10 years in semi-closed waters. As group 2 takes precedence over group 3, the level of the conditions for B-investigation results consequently showed condition 1 in all stations. We found that pollutants and trace metals in the sediment underneath cage farms were lower than the pollution standard. This led us to conclude that the environmental impacts of the cage farms in this study were not significant.

Measuring and mitigating inhibition during real-time, quantitative PCR analysis of viral nucleic acid extracts from large-volume environmental water samples

USDA-ARS?s Scientific Manuscript database

Naturally-occurring inhibitory compounds are a major concern during qPCR and RT-qPCR analysis of environmental samples, particularly large volume water samples. Here, a standardized method for measuring and mitigating sample inhibition in environmental water concentrates is described. Specifically, ...

Bird specimens track 135 years of atmospheric black carbon and environmental policy

NASA Astrophysics Data System (ADS)

DuBay, Shane G.; Fuldner, Carl C.

2017-10-01

Atmospheric black carbon has long been recognized as a public health and environmental concern. More recently, black carbon has been identified as a major, ongoing contributor to anthropogenic climate change, thus making historical emission inventories of black carbon an essential tool for assessing past climate sensitivity and modeling future climate scenarios. Current estimates of black carbon emissions for the early industrial era have high uncertainty, however, because direct environmental sampling is sparse before the mid-1950s. Using photometric reflectance data of >1,300 bird specimens drawn from natural history collections, we track relative ambient concentrations of atmospheric black carbon between 1880 and 2015 within the US Manufacturing Belt, a region historically reliant on coal and dense with industry. Our data show that black carbon levels within the region peaked during the first decade of the 20th century. Following this peak, black carbon levels were positively correlated with coal consumption through midcentury, after which they decoupled, with black carbon concentrations declining as consumption continued to rise. The precipitous drop in atmospheric black carbon at midcentury reflects policies promoting burning efficiency and fuel transitions rather than regulating emissions alone. Our findings suggest that current emission inventories based on predictive modeling underestimate levels of atmospheric black carbon for the early industrial era, suggesting that the contribution of black carbon to past climate forcing may also be underestimated. These findings build toward a spatially dynamic emission inventory of black carbon based on direct environmental sampling.

Bird specimens track 135 years of atmospheric black carbon and environmental policy

PubMed Central

DuBay, Shane G.; Fuldner, Carl C.

2017-01-01

Atmospheric black carbon has long been recognized as a public health and environmental concern. More recently, black carbon has been identified as a major, ongoing contributor to anthropogenic climate change, thus making historical emission inventories of black carbon an essential tool for assessing past climate sensitivity and modeling future climate scenarios. Current estimates of black carbon emissions for the early industrial era have high uncertainty, however, because direct environmental sampling is sparse before the mid-1950s. Using photometric reflectance data of >1,300 bird specimens drawn from natural history collections, we track relative ambient concentrations of atmospheric black carbon between 1880 and 2015 within the US Manufacturing Belt, a region historically reliant on coal and dense with industry. Our data show that black carbon levels within the region peaked during the first decade of the 20th century. Following this peak, black carbon levels were positively correlated with coal consumption through midcentury, after which they decoupled, with black carbon concentrations declining as consumption continued to rise. The precipitous drop in atmospheric black carbon at midcentury reflects policies promoting burning efficiency and fuel transitions rather than regulating emissions alone. Our findings suggest that current emission inventories based on predictive modeling underestimate levels of atmospheric black carbon for the early industrial era, suggesting that the contribution of black carbon to past climate forcing may also be underestimated. These findings build toward a spatially dynamic emission inventory of black carbon based on direct environmental sampling. PMID:29073051

Quality of volatile organic compound data from groundwater and surface water for the National Water-Quality Assessment Program, October 1996–December 2008

USGS Publications Warehouse

Bender, David A.; Zogorski, John S.; Mueller, David K.; Rose, Donna L.; Martin, Jeffrey D.; Brenner, Cassandra K.

2011-01-01

This report describes the quality of volatile organic compound (VOC) data collected from October 1996 to December 2008 from groundwater and surface-water sites for the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program. The VOC data described were collected for three NAWQA site types: (1) domestic and public-supply wells, (2) monitoring wells, and (3) surface-water sites. Contamination bias, based on the 90-percent upper confidence limit (UCL) for the 90th percentile of concentrations in field blanks, was determined for VOC samples from the three site types. A way to express this bias is that there is 90-percent confidence that this amount of contamination would be exceeded in no more than 10 percent of all samples (including environmental samples) that were collected, processed, shipped, and analyzed in the same manner as the blank samples. This report also describes how important native water rinsing may be in decreasing carryover contamination, which could be affecting field blanks. The VOCs can be classified into four contamination categories on the basis of the 90-percent upper confidence limit (90-percent UCL) concentration distribution in field blanks. Contamination category 1 includes compounds that were not detected in any field blanks. Contamination category 2 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is about an order of magnitude lower than the concentration distribution of the environmental samples. Contamination category 3 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is within an order of magnitude of the distribution in environmental samples. Contamination category 4 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is at least an order of magnitude larger than the concentration distribution of the environmental samples. Fifty-four of the 87 VOCs analyzed in samples from domestic and public-supply wells were not detected in field blanks (contamination category 1), and 33 VOC were detected in field blanks. Ten of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 10 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative of the sources of contamination bias affecting the environmental samples for these 10 VOCs. Seven VOCs had a 90-percent UCL concentration distribution of the field blanks that was within an order of magnitude of the concentration distribution of the environmental samples (contamination category 3). Sixteen VOCs had a 90-percent UCL concentration distribution in the field blanks that was at least an order of magnitude greater than the concentration distribution of the environmental samples (contamination category 4). Field blanks for these 16 VOCs appear to be nonrepresentative of the sources of contamination bias affecting the environmental samples because of the larger concentration distributions (and sometimes higher frequency of detection) in field blanks than in environmental samples. Forty-three of the 87 VOCs analyzed in samples from monitoring wells were not detected in field blanks (contamination category 1), and 44 VOCs were detected in field blanks. Eight of the 44 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than concentrations in environmental samples (contamination category 2). These eight VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Seven VOCs had a 90-percent UCL concentration distribution in field blanks that was of the same order of magnitude as the concentration distribution of the environmental samples (contamination category 3). Twenty-nine VOCs had a 90-percent UCL concentration distribution in the field blanks that was an order of magnitude greater than the distribution of the environmental samples (contamination category 4). Field blanks for these 29 VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples. Fifty-four of the 87 VOCs analyzed in surface-water samples were not detected in field blanks (category 1), and 33 VOC were detected in field blanks. Sixteen of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 16 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Ten VOCs had a 90-percent UCL concentration distribution in field blanks that was similar to the concentration distribution of environmental samples (contamination category 3). Seven VOCs had a 90-percent UCL concentration distribution in the field blanks that was greater than the concentration distribution in environmental samples (contamination category 4). Field-blank samples for these seven VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples. The relation between the detection of a compound in field blanks and the detection in subsequent environmental samples appears to be minimal. The median minimum percent effectiveness of native water rinsing is about 79 percent for the 19 VOCs detected in more than 5 percent of field blanks from all three site types. The minimum percent effectiveness of native water rinsing (10 percent) was for toluene in surface-water samples, likely because of the large detection frequency of toluene in surface-water samples (about 79 percent) and in the associated field-blank samples (46.5 percent). The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study. The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study.

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins

PubMed Central

Silberg, Judy L.; Gillespie, Nathan; Moore, Ashlee A.; Eaves, Lindon J.; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-01-01

Objective Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. Method We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Results Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. Conclusions There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children. PMID:25728588

Shared genetic and environmental influences on early temperament and preschool psychiatric disorders in Hispanic twins.

PubMed

Silberg, Judy L; Gillespie, Nathan; Moore, Ashlee A; Eaves, Lindon J; Bates, John; Aggen, Steven; Pfister, Elizabeth; Canino, Glorisa

2015-04-01

Despite an increasing recognition that psychiatric disorders can be diagnosed as early as preschool, little is known how early genetic and environmental risk factors contribute to the development of psychiatric disorders during this very early period of development. We assessed infant temperament at age 1, and attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and separation anxiety disorder (SAD) at ages 3 through 5 years in a sample of Hispanic twins. Genetic, shared, and non-shared environmental effects were estimated for each temperamental construct and psychiatric disorder using the statistical program MX. Multivariate genetic models were fitted to determine whether the same or different sets of genes and environments account for the co-occurrence between early temperament and preschool psychiatric disorders. Additive genetic factors accounted for 61% of the variance in ADHD, 21% in ODD, and 28% in SAD. Shared environmental factors accounted for 34% of the variance in ODD and 15% of SAD. The genetic influence on difficult temperament was significantly associated with preschool ADHD, SAD, and ODD. The association between ODD and SAD was due to both genetic and family environmental factors. The temperamental trait of resistance to control was entirely accounted for by the shared family environment. There are different genetic and family environmental pathways between infant temperament and psychiatric diagnoses in this sample of Puerto Rican preschool age children.

Implications of PCR and ELISA results on the routes of bulk-tank contamination with Mycobacterium avium ssp. paratuberculosis.

PubMed

Beaver, A; Cazer, C L; Ruegg, P L; Gröhn, Y T; Schukken, Y H

2016-02-01

Mycobacterium avium ssp. paratuberculosis (MAP), the etiologic agent of Johne's disease in dairy cattle, may enter the bulk tank via environmental contamination or direct excretion into milk. Traditionally, diagnostics to identify MAP in milk target either MAP antibodies (by ELISA) or the organism itself (by culture or PCR). High ELISA titers may be directly associated with excretion of MAP into milk but only indirectly linked to environmental contamination of the bulk tank. Patterns of bulk-milk ELISA and bulk-milk PCR results could therefore provide insight into the routes of contamination and level of infection or environmental burden. Coupled with questionnaire responses pertaining to management, the results of these diagnostic tests could reveal correlations with herd characteristics or on-farm practices that distinguish herds with high and low environmental bulk-tank MAP contamination. A questionnaire on hygiene, management, and Johne's specific parameters was administered to 292 dairy farms in New York, Oregon, and Wisconsin. Bulk-tank samples were collected from each farm for evaluation by real-time PCR and ELISA. Before DNA extraction and testing of the unknown samples, bulk-milk template preparation was optimized with respect to parameters such as MAP fractionation patterns and lysis. Two regression models were developed to explore the relationships among bulk-tank PCR, ELISA, environmental predictors, and herd characteristics. First, ELISA optical density (OD) was designated as the outcome in a linear regression model. Second, the log odds of being PCR positive in the bulk tank were modeled using binary logistic regression with penalized maximum likelihood. The proportion of PCR-positive bulk tanks was highest for New York and for organic farms, providing a clue as to the geographical patterns of MAP-positive bulk-tank samples and relationship to production type. Bulk-milk PCR positivity was also higher for large relative to small herds. The models revealed that bulk-milk PCR result could predict ELISA OD, with PCR-positive results corresponding to high bulk-milk ELISA titers. Similarly, ELISA was a predictor of PCR result, although the association was stronger for organic farms. Despite agreement between high bulk-milk ELISA titers and positive PCR results, a large proportion of high ELISA farms had PCR-negative bulk tanks, suggesting that farms are able to maintain satisfactory hygiene and management despite a presence of MAP in these herds. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT - GROUNDWATER SAMPLING TECHNOLOGIES - QED ENVIRONMENTAL SYSTEMS INC. WELL WIZARD DEDICATED SAMPLING SYSTEM

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology Verification Program (ETV) to facilitate the deployment of innovative or improved environmental technologies through performance verification and dissemination of information. The goal of the ...

Role of soil-to-leaf tritium transfer in controlling leaf tritium dynamics: Comparison of experimental garden and tritium-transfer model results.

PubMed

Ota, Masakazu; Kwamena, Nana-Owusua A; Mihok, Steve; Korolevych, Volodymyr

2017-11-01

Environmental transfer models assume that organically-bound tritium (OBT) is formed directly from tissue-free water tritium (TFWT) in environmental compartments. Nevertheless, studies in the literature have shown that measured OBT/HTO ratios in environmental samples are variable and generally higher than expected. The importance of soil-to-leaf HTO transfer pathway in controlling the leaf tritium dynamics is not well understood. A model inter-comparison of two tritium transfer models (CTEM-CLASS-TT and SOLVEG-II) was carried out with measured environmental samples from an experimental garden plot set up next to a tritium-processing facility. The garden plot received one of three different irrigation treatments - no external irrigation, irrigation with low tritium water and irrigation with high tritium water. The contrast between the results obtained with the different irrigation treatments provided insights into the impact of soil-to-leaf HTO transfer on the leaf tritium dynamics. Concentrations of TFWT and OBT in the garden plots that were not irrigated or irrigated with low tritium water were variable, responding to the arrival of the HTO-plume from the tritium-processing facility. In contrast, for the plants irrigated with high tritium water, the TFWT concentration remained elevated during the entire experimental period due to a continuous source of high HTO in the soil. Calculated concentrations of OBT in the leaves showed an initial increase followed by quasi-equilibration with the TFWT concentration. In this quasi-equilibrium state, concentrations of OBT remained elevated and unchanged despite the arrivals of the plume. These results from the model inter-comparison demonstrate that soil-to-leaf HTO transfer significantly affects tritium dynamics in leaves and thereby OBT/HTO ratio in the leaf regardless of the atmospheric HTO concentration, only if there is elevated HTO concentrations in the soil. The results of this work indicate that assessment models should be refined to consider the importance of soil-to-leaf HTO transfer to ensure that dose estimates are accurate and conservative. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

PubMed

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (P<0.01) clusters of fasciolosis. The low-risk clusters were mostly located in the southern regions of Ireland, whereas the high-risk clusters were mainly situated in the western part. Several climatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

You Can Run, But You Can't Hide Juniper Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.

2013-01-01

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We are modified the DREAM model to incorporate pollen transport. Pollen release is estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities are used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Astrophysics Data System (ADS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Prasad, A. K.; Pejanovic, G.; Vukovic, A.; Van De Water, P. K.; Budge, A.; Hudspeth, W. B.; Krapfl, H.; Toth, B.; Zelicoff, A.; Myers, O.; Bunderson, L.; Ponce-Campos, G.; Menache, M.; Crimmins, T. M.; Vujadinovic, M.

2012-12-01

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and concentrations of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen emission is based on MODIS-derived phenology of Juniperus spp. communities. Ground-based observational records of pollen release timing and quantities will be used as model verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China.

PubMed

Zhang, Han; Si, Yali; Wang, Xiaofeng; Gong, Peng

2017-07-14

Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk.

Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China

PubMed Central

Si, Yali; Gong, Peng

2017-01-01

Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk. PMID:28708077

Comparing decision making between cancer patients and the general population: thoughts, emotions, or social influence?

PubMed

Yang, Z Janet; McComas, Katherine A; Gay, Geri K; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy

2012-01-01

This study extends a risk information seeking and processing model to explore the relative effect of cognitive processing strategies, positive and negative emotions, and normative beliefs on individuals' decision making about potential health risks. Most previous research based on this theoretical framework has examined environmental risks. Applying this risk communication model to study health decision making presents an opportunity to explore theoretical boundaries of the model, while also bringing this research to bear on a pressing medical issue: low enrollment in clinical trials. Comparative analysis of data gathered from 2 telephone surveys of a representative national sample (n = 500) and a random sample of cancer patients (n = 411) indicated that emotions played a more substantive role in cancer patients' decisions to enroll in a potential trial, whereas cognitive processing strategies and normative beliefs had greater influences on the decisions of respondents from the national sample.

Can Landscape Evolution Models (LEMs) be used to reconstruct palaeo-climate and sea-level histories?

NASA Astrophysics Data System (ADS)

Leyland, J.; Darby, S. E.

2011-12-01

Reconstruction of palaeo-environmental conditions over long time periods is notoriously difficult, especially where there are limited or no proxy records from which to extract data. Application of landscape evolution models (LEMs) for palaeo-environmental reconstruction involves hindcast modeling, in which simulation scenarios are configured with specific model variables and parameters chosen to reflect a specific hypothesis of environmental change. In this form of modeling, the environmental time series utilized are considered credible when modeled and observed landscape metrics converge. Herein we account for the uncertainties involved in evaluating the degree to which the model simulations and observations converge using Monte Carlo analysis of reduced complexity `metamodels'. The technique is applied to a case study focused on a specific set of gullies found on the southwest coast of the Isle of Wight, UK. A key factor controlling the Holocene evolution of these coastal gullies is the balance between rates of sea-cliff retreat (driven by sea-level rise) and headwards incision caused by knickpoint migration (driven by the rate of runoff). We simulate these processes using a version of the GOLEM model that has been modified to represent sea-cliff retreat. A Central Composite Design (CCD) sampling technique was employed, enabling the trajectories of gully response to different combinations of driving conditions to be modeled explicitly. In some of these simulations, where the range of bedrock erodibility (0.03 to 0.04 m0.2 a-1) and rate of sea-level change (0.005 to 0.0059 m a-1) is tightly constrained, modeled gully forms conform closely to those observed in reality, enabling a suite of climate and sea-level change scenarios which plausibly explain the Holocene evolution of the Isle of Wight gullies to be identified.

Sorption Isotherm of Southern Yellow Pine-High Density Polyethylene Composites.

PubMed

Liu, Feihong; Han, Guangping; Cheng, Wanli; Wu, Qinglin

2015-01-20

Temperature and relative humidity (RH) are two major external factors, which affect equilibrium moisture content (EMC) of wood-plastic composites (WPCs). In this study, the effect of different durability treatments on sorption and desorption isotherms of southern yellow pine (SYP)-high density polyethylene (HDPE) composites was investigated. All samples were equilibriumed at 20 °C and various RHs including 16%, 33%, 45%, 66%, 75%, 85%, 93%, and100%. EMCs obtained from desorption and absorption for different WPC samples were compared with Nelson's sorption isotherm model predictions using the same temperature and humidity conditions. The results indicated that the amount of moisture absorbed increased with the increases in RH at 20 °C. All samples showed sorption hysteresis at a fixed RH. Small difference between EMC data of WPC samples containing different amount of ultraviolet (UV) stabilizers were observed. Similar results were observed among the samples containing different amount of zinc borate (ZB). The experimental data of EMCs at various RHs fit to the Nelson's sorption isotherm model well. The Nelson's model can be used to predicate EMCs of WPCs under different RH environmental conditions.

Sorption Isotherm of Southern Yellow Pine—High Density Polyethylene Composites

PubMed Central

Liu, Feihong; Han, Guangping; Cheng, Wanli; Wu, Qinglin

2015-01-01

Temperature and relative humidity (RH) are two major external factors, which affect equilibrium moisture content (EMC) of wood-plastic composites (WPCs). In this study, the effect of different durability treatments on sorption and desorption isotherms of southern yellow pine (SYP)-high density polyethylene (HDPE) composites was investigated. All samples were equilibriumed at 20 °C and various RHs including 16%, 33%, 45%, 66%, 75%, 85%, 93%, and100%. EMCs obtained from desorption and absorption for different WPC samples were compared with Nelson’s sorption isotherm model predictions using the same temperature and humidity conditions. The results indicated that the amount of moisture absorbed increased with the increases in RH at 20 °C. All samples showed sorption hysteresis at a fixed RH. Small difference between EMC data of WPC samples containing different amount of ultraviolet (UV) stabilizers were observed. Similar results were observed among the samples containing different amount of zinc borate (ZB). The experimental data of EMCs at various RHs fit to the Nelson’s sorption isotherm model well. The Nelson’s model can be used to predicate EMCs of WPCs under different RH environmental conditions. PMID:28787943

[Mobbing: a meta-analysis and integrative model of its antecedents and consequences].

PubMed

Topa Cantisano, Gabriela; Depolo, Marco; Morales Domínguez, J Francisco

2007-02-01

Although mobbing has been extensively studied, empirical research has not led to firm conclusions regarding its antecedents and consequences, both at personal and organizational levels. An extensive literature search yielded 86 empirical studies with 93 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported hypotheses regarding organizational environmental factors as main predictors of mobbing.

Measuring Children's Environmental Attitudes and Values in Northwest Mexico: Validating a Modified Version of Measures to Test the Model of Ecological Values (2-MEV)

ERIC Educational Resources Information Center

Schneller, A. J.; Johnson, B.; Bogner, F. X.

2015-01-01

This paper describes the validation process of measuring children's attitudes and values toward the environment within a Mexican sample. We applied the Model of Ecological Values (2-MEV), which has been shown to be valid and reliable in 20 countries, including one Spanish speaking culture. Items were initially modified to fit the regional dialect,…

The Bottlenose Dolphin (Tursiops truncatus) as a Model to Understand Variation in Stress and Reproductive Hormone Measures in Relation to Sampling Matrix, Demographics, and Environmental Factors

DTIC Science & Technology

2015-09-30

ranging individuals support the existence of these same stress response pathways in marine mammals. 2 While the HPA axis and physiological processes...relying upon methods which include capture-release health assessments. Stress and reproductive hormones (cortisol, aldosterone , thyroid, testosterone...Analyses Hormone concentrations (cortisol, aldosterone , reproductive and thyroid hormones) in serum samples were analyzed by Cornell’s Animal Health

The Bottlenose Dolphin (Tursiops truncatus) as a Model to Understand Variation in Stress and Reproductive Hormone Measures in Relation to Sampling Matrix, Demographics, and Environmental Factors

DTIC Science & Technology

2014-09-30

axis and physiological processes driven by the GCs are essential for an individual’s ability to respond and adapt to stress, prolonged elevation of...health assessments. Stress and reproductive hormones (cortisol, aldosterone , thyroid, testosterone, progesterone) have been routinely measured in blood...in South Carolina. Laboratory Analyses Hormone concentrations (cortisol, aldosterone , reproductive and thyroid hormones) in serum samples have

Homeland Security Research Improves the Nation's Ability to ...

EPA Pesticide Factsheets

Technical Brief Homeland Security (HS) Research develops data, tools, and technologies to minimize the impact of accidents, natural disasters, terrorist attacks, and other incidents that can result in toxic chemical, biological or radiological (CBR) contamination. HS Research develops ways to detect contamination, sampling strategies, sampling and analytical methods, cleanup methods, waste management approaches, exposure assessment methods, and decision support tools (including water system models). These contributions improve EPA’s response to a broad range of environmental disasters.

Validation of the ANSR Listeria method for detection of Listeria spp. in environmental samples.

PubMed

Wendorf, Michael; Feldpausch, Emily; Pinkava, Lisa; Luplow, Karen; Hosking, Edan; Norton, Paul; Biswas, Preetha; Mozola, Mark; Rice, Jennifer

2013-01-01

ANSR Listeria is a new diagnostic assay for detection of Listeria spp. in sponge or swab samples taken from a variety of environmental surfaces. The method is an isothermal nucleic acid amplification assay based on the nicking enzyme amplification reaction technology. Following single-step sample enrichment for 16-24 h, the assay is completed in 40 min, requiring only simple instrumentation. In inclusivity testing, 48 of 51 Listeria strains tested positive, with only the three strains of L. grayi producing negative results. Further investigation showed that L. grayi is reactive in the ANSR assay, but its ability to grow under the selective enrichment conditions used in the method is variable. In exclusivity testing, 32 species of non-Listeria, Gram-positive bacteria all produced negative ANSR assay results. Performance of the ANSR method was compared to that of the U.S. Department of Agriculture-Food Safety and Inspection Service reference culture procedure for detection of Listeria spp. in sponge or swab samples taken from inoculated stainless steel, plastic, ceramic tile, sealed concrete, and rubber surfaces. Data were analyzed using Chi-square and probability of detection models. Only one surface, stainless steel, showed a significant difference in performance between the methods, with the ANSR method producing more positive results. Results of internal trials were supported by findings from independent laboratory testing. The ANSR Listeria method can be used as an accurate, rapid, and simple alternative to standard culture methods for detection of Listeria spp. in environmental samples.

Using Performance Reference Compounds (PRCs) to measure dissolved water concentrations (Cfree) in the water column: Assessing equilibrium models

EPA Science Inventory

Equilibrium-based passive sampling methods are often used in aquatic environmental monitoring to measure hydrophobic organic contaminants (HOCs) and in the subsequent evaluation of their effects on ecological and human health. HOCs freely dissolved in water (Cfree) will partition...

Lead Sampling Technician Training Course. Trainer Manual.

ERIC Educational Resources Information Center

ICF, Inc., Washington, DC.

This document presents a model curriculum for use by trainers presenting training course in assessing and reporting dust and debris from deteriorated lead-based paint. The course, which was developed by the U.S. Environmental Protection Agency, is intended for use with housing quality standard inspectors, rehabilitation specialists, home…

Deviant Peer Affiliation and Antisocial Behavior: Interaction with Monoamine Oxidase A (MAOA) Genotype

ERIC Educational Resources Information Center

Lee, Steve S.

2011-01-01

Although genetic and environmental factors are separately implicated in the development of antisocial behavior (ASB), interactive models have emerged relatively recently, particularly those incorporating molecular genetic data. Using a large sample of male Caucasian adolescents and young adults from the National Longitudinal Study of Adolescent…

Living Green: Examining Sustainable Dorms and Identities

ERIC Educational Resources Information Center

Watson, Lesley; Johnson, Cathryn; Hegtvedt, Karen A.; Parris, Christie L.

2015-01-01

Purpose: The purpose of this study was to examine the effects of living in "green" dorms on students' environmentally responsible behaviors (ERBs), in concert with other factors, including individual identity and social context in the form of behavior modeling by peers. Design/methodology/approach: The sample of 243 consists of students…

Development of a quail embryo model for the detection of botulinum neurotoxin activity

USDA-ARS?s Scientific Manuscript database

Clostridium botulinum is a ubiquitous microorganism that under anaerobic conditions produces botulinum neurotoxins. In regards to both food-borne illness and the potential use of botulinum toxin as a biological weapon, the capability to assess the amount of toxin in a food or environmental sample e...

Toward an Integration of Cognitive and Genetic Models of Risk for Depression

PubMed Central

Gibb, Brandon E.; Beevers, Christopher G.; McGeary, John E.

2012-01-01

There is growing interest in integrating cognitive and genetic models of depression risk. We review two ways in which these models can be meaningfully integrated. First, information-processing biases may represent intermediate phenotypes for specific genetic influences. These genetic influences may represent main effects on specific cognitive processes or may moderate the impact of environmental influences on information-processing biases. Second, cognitive and genetic influences may combine to increase reactivity to environmental stressors, increasing risk for depression in a gene × cognition × environment model of risk. There is now growing support for both of these ways of integrating cognitive and genetic models of depression risk. Specifically, there is support for genetic influences on information-processing biases, particularly the link between 5-HTTLPR and attentional biases, from both genetic association and gene × environment (G × E) studies. There is also initial support for gene × cognition × environment models of risk in which specific genetic influences contribute to increased reactivity to environmental influences. We review this research and discuss important areas of future research, particularly the need for larger samples that allow for a broader examination of genetic and epigenetic influences as well as the combined influence of variability across a number of genes. PMID:22920216

Environmental Conditions Associated with Elevated Vibrio parahaemolyticus Concentrations in Great Bay Estuary, New Hampshire

PubMed Central

Urquhart, Erin A.; Jones, Stephen H.; Yu, Jong W.; Schuster, Brian M.; Marcinkiewicz, Ashley L.; Whistler, Cheryl A.; Cooper, Vaughn S.

2016-01-01

Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary. PMID:27144925

Genetic and Environmental Influences on Sleep, Pain, and Depression Symptoms in a Community Sample of Twins.

PubMed

Gasperi, Marianna; Herbert, Matthew; Schur, Ellen; Buchwald, Dedra; Afari, Niloofar

We used quantitative genetic methods to evaluate whether sleep quality, pain, and depression symptoms share a common genetic diathesis, to estimate the genetic and environmental sources of covariance among these symptoms, and to test for possible causal relationships. A community sample of 400 twins from the University of Washington Twin Registry completed standardized self-report questionnaires. We used biometric modeling to assess genetic and environmental contribution to the association between sleep quality measured by the Pittsburgh Sleep Quality Index, pain measured by the Brief Pain Inventory, and depression symptoms measured by the Brief Symptom Inventory. Trivariate Cholesky structural equation models were used to decompose correlations among the phenotypes. Heritability was estimated at 37% (95% confidence interval = 20%-51%) for sleep quality, 25% (9%-41%) for pain, and 39% (22%-53%) for depression. Nonshared environmental influences accounted for the remaining variance. The genetic correlation between sleep quality and pain had an rg value of .69 (95% confidence interval [CI] = 0.33-0.97), rg value of .56 (95% CI = 0.55-0.98) between pain and depression, and rg value of .61 (95% CI = 0.44-0.88) between depression and sleep quality. Nonshared environmental overlap was present between pain and sleep quality as well as depression and sleep quality. The link between sleep quality, pain, and depression was primarily explained by shared genetic influences. The genetic factors influencing sleep quality and pain were highly correlated even when accounting for depression. Findings support the hypothesis of a genetic link between depression and pain as well as potential causality for the association of sleep quality with pain and depression.

Quantifying Uncertainties from Presence Data Sampling Methods for Species Distribution Modeling: Focused on Vegetation.

NASA Astrophysics Data System (ADS)

Sung, S.; Kim, H. G.; Lee, D. K.; Park, J. H.; Mo, Y.; Kil, S.; Park, C.

2016-12-01

The impact of climate change has been observed throughout the globe. The ecosystem experiences rapid changes such as vegetation shift, species extinction. In these context, Species Distribution Model (SDM) is one of the popular method to project impact of climate change on the ecosystem. SDM basically based on the niche of certain species with means to run SDM present point data is essential to find biological niche of species. To run SDM for plants, there are certain considerations on the characteristics of vegetation. Normally, to make vegetation data in large area, remote sensing techniques are used. In other words, the exact point of presence data has high uncertainties as we select presence data set from polygons and raster dataset. Thus, sampling methods for modeling vegetation presence data should be carefully selected. In this study, we used three different sampling methods for selection of presence data of vegetation: Random sampling, Stratified sampling and Site index based sampling. We used one of the R package BIOMOD2 to access uncertainty from modeling. At the same time, we included BioCLIM variables and other environmental variables as input data. As a result of this study, despite of differences among the 10 SDMs, the sampling methods showed differences in ROC values, random sampling methods showed the lowest ROC value while site index based sampling methods showed the highest ROC value. As a result of this study the uncertainties from presence data sampling methods and SDM can be quantified.

Genetic and environmental influences on individual differences in emotion regulation and its relation to working memory in toddlerhood.

PubMed

Wang, Manjie; Saudino, Kimberly J

2013-12-01

This is the first study to explore genetic and environmental contributions to individual differences in emotion regulation in toddlers, and the first to examine the genetic and environmental etiology underlying the association between emotion regulation and working memory. In a sample of 304 same-sex twin pairs (140 MZ, 164 DZ) at age 3, emotion regulation was assessed using the Behavior Rating Scale of the Bayley Scales of Infant Development (BRS; Bayley, 1993), and working memory was measured by the visually cued recall (VCR) task (Zelazo, Jacques, Burack, & Frye, 2002) and several memory tasks from the Mental Scale of the BSID. Based on model-fitting analyses, both emotion regulation and working memory were significantly influenced by genetic and nonshared environmental factors. Shared environmental effects were significant for working memory, but not for emotion regulation. Only genetic factors significantly contributed to the covariation between emotion regulation and working memory.

Genetic and Environmental Influences on Individual Differences in Emotion Regulation and Its Relation to Working Memory in Toddlerhood

PubMed Central

Wang, Manjie; Saudino, Kimberly J.

2014-01-01

This is the first study to explore genetic and environmental contributions to individual differences in emotion regulation in toddlers, and the first to examine the genetic and environmental etiology underlying the association between emotion regulation and working memory. In a sample of 304 same-sex twin pairs (140 MZ, 164 DZ) at age 3, emotion regulation was assessed using the Behavior Rating Scale of the Bayley Scales of Infant Development (BRS; Bayley, 1993), and working memory was measured by the visually cued recall (VCR) task (Zelazo et al., 2002) and several memory tasks from the Mental Scale of BSID. Based on model-fitting analyses, both emotion regulation and working memory were significantly influenced by genetic and nonshared environmental factors. Shared environmental effects were significant for working memory, but not for emotion regulation. Only genetic factors significantly contributed to the covariation between emotion regulation and working memory. PMID:24098922

Evaluation of Scat Deposition Transects versus Radio Telemetry for Developing a Species Distribution Model for a Rare Desert Carnivore, the Kit Fox.

PubMed

Dempsey, Steven J; Gese, Eric M; Kluever, Bryan M; Lonsinger, Robert C; Waits, Lisette P

2015-01-01

Development and evaluation of noninvasive methods for monitoring species distribution and abundance is a growing area of ecological research. While noninvasive methods have the advantage of reduced risk of negative factors associated with capture, comparisons to methods using more traditional invasive sampling is lacking. Historically kit foxes (Vulpes macrotis) occupied the desert and semi-arid regions of southwestern North America. Once the most abundant carnivore in the Great Basin Desert of Utah, the species is now considered rare. In recent decades, attempts have been made to model the environmental variables influencing kit fox distribution. Using noninvasive scat deposition surveys for determination of kit fox presence, we modeled resource selection functions to predict kit fox distribution using three popular techniques (Maxent, fixed-effects, and mixed-effects generalized linear models) and compared these with similar models developed from invasive sampling (telemetry locations from radio-collared foxes). Resource selection functions were developed using a combination of landscape variables including elevation, slope, aspect, vegetation height, and soil type. All models were tested against subsequent scat collections as a method of model validation. We demonstrate the importance of comparing multiple model types for development of resource selection functions used to predict a species distribution, and evaluating the importance of environmental variables on species distribution. All models we examined showed a large effect of elevation on kit fox presence, followed by slope and vegetation height. However, the invasive sampling method (i.e., radio-telemetry) appeared to be better at determining resource selection, and therefore may be more robust in predicting kit fox distribution. In contrast, the distribution maps created from the noninvasive sampling (i.e., scat transects) were significantly different than the invasive method, thus scat transects may be appropriate when used in an occupancy framework to predict species distribution. We concluded that while scat deposition transects may be useful for monitoring kit fox abundance and possibly occupancy, they do not appear to be appropriate for determining resource selection. On our study area, scat transects were biased to roadways, while data collected using radio-telemetry was dictated by movements of the kit foxes themselves. We recommend that future studies applying noninvasive scat sampling should consider a more robust random sampling design across the landscape (e.g., random transects or more complete road coverage) that would then provide a more accurate and unbiased depiction of resource selection useful to predict kit fox distribution.

Preliminary ECLSS waste water model

NASA Technical Reports Server (NTRS)

Carter, Donald L.; Holder, Donald W., Jr.; Alexander, Kevin; Shaw, R. G.; Hayase, John K.

1991-01-01

A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.

Global habitat suitability for framework-forming cold-water corals.

PubMed

Davies, Andrew J; Guinotte, John M

2011-04-15

Predictive habitat models are increasingly being used by conservationists, researchers and governmental bodies to identify vulnerable ecosystems and species' distributions in areas that have not been sampled. However, in the deep sea, several limitations have restricted the widespread utilisation of this approach. These range from issues with the accuracy of species presences, the lack of reliable absence data and the limited spatial resolution of environmental factors known or thought to control deep-sea species' distributions. To address these problems, global habitat suitability models have been generated for five species of framework-forming scleractinian corals by taking the best available data and using a novel approach to generate high resolution maps of seafloor conditions. High-resolution global bathymetry was used to resample gridded data from sources such as World Ocean Atlas to produce continuous 30-arc second (∼1 km(2)) global grids for environmental, chemical and physical data of the world's oceans. The increased area and resolution of the environmental variables resulted in a greater number of coral presence records being incorporated into habitat models and higher accuracy of model predictions. The most important factors in determining cold-water coral habitat suitability were depth, temperature, aragonite saturation state and salinity. Model outputs indicated the majority of suitable coral habitat is likely to occur on the continental shelves and slopes of the Atlantic, South Pacific and Indian Oceans. The North Pacific has very little suitable scleractinian coral habitat. Numerous small scale features (i.e., seamounts), which have not been sampled or identified as having a high probability of supporting cold-water coral habitat were identified in all ocean basins. Field validation of newly identified areas is needed to determine the accuracy of model results, assess the utility of modelling efforts to identify vulnerable marine ecosystems for inclusion in future marine protected areas and reduce coral bycatch by commercial fisheries.

Parameterisation of Biome BGC to assess forest ecosystems in Africa

NASA Astrophysics Data System (ADS)

Gautam, Sishir; Pietsch, Stephan A.

2010-05-01

African forest ecosystems are an important environmental and economic resource. Several studies show that tropical forests are critical to society as economic, environmental and societal resources. Tropical forests are carbon dense and thus play a key role in climate change mitigation. Unfortunately, the response of tropical forests to environmental change is largely unknown owing to insufficient spatially extensive observations. Developing regions like Africa where records of forest management for long periods are unavailable the process-based ecosystem simulation model - BIOME BGC could be a suitable tool to explain forest ecosystem dynamics. This ecosystem simulation model uses descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns within vegetation functional types, or biomes. Undocumented parameters for larger-resolution simulations are currently the major limitations to regional modelling in African forest ecosystems. This study was conducted to document input parameters for BIOME-BGC for major natural tropical forests in the Congo basin. Based on available literature and field measurements updated values for turnover and mortality, allometry, carbon to nitrogen ratios, allocation of plant material to labile, cellulose, and lignin pools, tree morphology and other relevant factors were assigned. Daily climate input data for the model applications were generated using the statistical weather generator MarkSim. The forest was inventoried at various sites and soil samples of corresponding stands across Gabon were collected. Carbon and nitrogen in the collected soil samples were determined from soil analysis. The observed tree volume, soil carbon and soil nitrogen were then compared with the simulated model outputs to evaluate the model performance. Furthermore, the simulation using Congo Basin specific parameters and generalised BIOME BGC parameters for tropical evergreen broadleaved tree species were also executed and the simulated results compared. Once the model was optimised for forests in the Congo basin it was validated against observed tree volume, soil carbon and soil nitrogen from a set of independent plots.

Predicting fish community properties within estuaries: Influence of habitat type and other environmental features

NASA Astrophysics Data System (ADS)

França, Susana; Vasconcelos, Rita P.; Fonseca, Vanessa F.; Tanner, Susanne E.; Reis-Santos, Patrick; Costa, Maria José; Cabral, Henrique N.

2012-07-01

Statistical models predicting species distributions are essential not only to increase knowledge on species but for their application in conservation and ecologically-based management. The variation of fish species richness and abundance in the most representative habitats (saltmarsh, mudflat and subtidal) in five estuaries along the Portuguese coast was analysed through seasonal sampling surveys in 2009. Generalized additive models (GAM) were developed to describe the variation of species richness and abundances with a set of geomorphologic, hydrologic and environmental characteristics from the sampled estuaries and habitats. GAM were chosen as the complex interactions dominating these ecosystems and species distribution are non-linear. Final models built for each estuary and for all estuaries together performed well during the calibration phase and also during the validation phase, where an unused data sub-set from each estuary was used. There was not a similar combination of variables retained by the models for the studied estuaries but factors such as the area of the habitat, the distance to estuary mouth, percentage of mud in the sediment and depth were commonly retained. The partial effect of these predictor variables on the variation of species richness and abundance in the estuaries varied markedly and the importance of preserving the heterogeneity of habitats within estuaries was highlighted. Models for each individual estuary performed better than models for estuaries combined. Predictive models could be useful as a preliminary tool to prepare long-term conservation plans at different scales.

Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis.

PubMed

McNeill, Lorna Haughton; Wyrwich, Kathleen W; Brownson, Ross C; Clark, Eddie M; Kreuter, Matthew W

2006-02-01

Social ecological models suggest that conditions in the social and physical environment, in addition to individual factors, play important roles in health behavior change. Using structural equation modeling, this study tested a theoretically and empirically based explanatory model of physical activity to examine theorized direct and indirect effects of individual (e.g., motivation and self-efficacy), social environmental (e.g., social support), and physical environmental factors (e.g., neighborhood quality and availability of facilities). A community-based sample of adults (N = 910) was recruited from 2 public health centers (67% female, 43% African American, 43% < $20,000/year, M age = 33 years) and completed a self-administered survey assessing their current physical activity level, intrinsic and extrinsic motivation for physical activity, perceived social support, self-efficacy, and perceptions of the physical environment. Results indicated that (a) perceptions of the physical environment had direct effects on physical activity, (b) both the social and physical environments had indirect effects on physical activity through motivation and self-efficacy, and (c) social support influenced physical activity indirectly through intrinsic and extrinsic motivation. For all forms of activity, self-efficacy was the strongest direct correlate of physical activity, and evidence of a positive dose-response relation emerged between self-efficacy and intensity of physical activity. Findings from this research highlight the interactive role of individual and environmental influences on physical activity.

Emerging Environmental Contaminants and Soled Phase Microextraction: Janusz Pawliszyn's Legacy in the Environmental Arena

EPA Science Inventory

Solid phase microextraction (SPME) has revolutionized the way samples are extracted, enabling rapid, automated, and solventless extraction of many different sample types, including air, water, soil, and biological samples. As such, SPME is widely used for environmental, food, fo...

Detection of Mycobacterium avium subspecies paratuberculosis in tie-stall dairy herds using a standardized environmental sampling technique and targeted pooled samples.

PubMed

Arango-Sabogal, Juan C; Côté, Geneviève; Paré, Julie; Labrecque, Olivia; Roy, Jean-Philippe; Buczinski, Sébastien; Doré, Elizabeth; Fairbrother, Julie H; Bissonnette, Nathalie; Wellemans, Vincent; Fecteau, Gilles

2016-07-01

Mycobacterium avium ssp. paratuberculosis (MAP) is the etiologic agent of Johne's disease, a chronic contagious enteritis of ruminants that causes major economic losses. Several studies, most involving large free-stall herds, have found environmental sampling to be a suitable method for detecting MAP-infected herds. In eastern Canada, where small tie-stall herds are predominant, certain conditions and management practices may influence the survival and transmission of MAP and recovery (isolation). Our objective was to estimate the performance of a standardized environmental and targeted pooled sampling technique for the detection of MAP-infected tie-stall dairy herds. Twenty-four farms (19 MAP-infected and 5 non-infected) were enrolled, but only 20 were visited twice in the same year, to collect 7 environmental samples and 2 pooled samples (sick cows and cows with poor body condition). Concurrent individual sampling of all adult cows in the herds was also carried out. Isolation of MAP was achieved using the MGIT Para TB culture media and the BACTEC 960 detection system. Overall, MAP was isolated in 7% of the environmental cultures. The sensitivity of the environmental culture was 44% [95% confidence interval (CI): 20% to 70%] when combining results from 2 different herd visits and 32% (95% CI: 13% to 57%) when results from only 1 random herd visit were used. The best sampling strategy was to combine samples from the manure pit, gutter, sick cows, and cows with poor body condition. The standardized environmental sampling technique and the targeted pooled samples presented in this study is an alternative sampling strategy to costly individual cultures for detecting MAP-infected tie-stall dairies. Repeated samplings may improve the detection of MAP-infected herds.

Solving the ecological puzzle of mycorrhizal associations using data from annotated collections and environmental samples - an example of saddle fungi.

PubMed

Hwang, Jonathan; Zhao, Qi; Yang, Zhu L; Wang, Zheng; Townsend, Jeffrey P

2015-08-01

The relation between ecological and genetic divergence of Helvella species (saddle fungi) has been perplexing. While a few species have been clearly demonstrated to be ectomycorrhizal fungi, ecological roles of many other species have been controversial, alternately considered as either saprotrophic or mycorrhizal. We applied SATé to build an inclusive deoxyribonucleic acid sequence alignment for the internal transcribed spacers (ITS) of annotated Helvella species and related environmental sequences. Phylogenetic informativeness of ITS and its regions were assessed using PhyDesign. Mycorrhizal lineages present a diversity of ecology, host type and geographic distribution. In two Helvella clades, no Helvella ITS sequences were recovered from root tips. Inclusion of environmental sequences in the ITS phylogeny from these sequences has the potential to link these data and reveal Helvella ecology. This study can serve as a model for revealing the diversity of relationships between unculturable fungi and their potential plant hosts. How non-mycorrhizal life styles within Helvella evolved will require expanded metagenomic investigation of soil and other environmental samples along with study of Helvella genomes. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Quantifying the stability of trace explosives under different environmental conditions using electrospray ionization mass spectrometry.

PubMed

Sisco, Edward; Najarro, Marcela; Samarov, Daniel; Lawrence, Jeffrey

2017-04-01

This work investigates the stability of trace (tens of nanograms) deposits of six explosives: erythritol tetranitrate (ETN), pentaerythritol tetranitrate (PETN), cyclotrimethylenetrinitramine (RDX), cyclotetramethylenetetranitramine (HMX), 2,4,6-trinitrotoluene (TNT), and 2,4,6-trinitrophenylmethylnitramine (tetryl) to determine environmental stabilities and lifetimes of trace level materials. Explosives were inkjet printed directly onto substrates and exposed to one of seven environmental conditions (Laboratory, -4°C, 30°C, 47°C, 90% relative humidity, UV light, and ozone) up to 42 days. Throughout the study, samples were extracted and quantified using electrospray ionization mass spectrometry (ESI-MS) to determine the stability of the explosive as a function of time and environmental exposure. Statistical models were then fit to the data and used for pairwise comparisons of the environments. Stability was found to be exposure and compound dependent with minimal sample losses observed for HMX, RDX, and PETN while substantial and rapid losses were observed in all conditions except -4°C for ETN and TNT and in all conditions for tetryl. The results of this work highlight the potential fate of explosive traces when exposed to various environments. Published by Elsevier B.V.

Quantifying the Stability of Trace Explosives under Different Environmental Conditions using Electrospray Ionization Mass Spectrometry

PubMed Central

Sisco, Edward; Najarro, Marcela; Samarov, Daniel; Lawrence, Jeffrey

2017-01-01

This work investigates the stability of trace (tens of nanograms) deposits of six explosives: erythritol tetranitrate (ETN), pentaerythritol tetranitrate (PETN), cyclotrimethylenetrinitramine (RDX), cyclotetramethylenetetranitramine (HMX), 2,4,6-trinitrotoluene (TNT), and 2,4,6-trinitrophenylmethylnitramine (tetryl) to determine environmental stabilities and lifetimes of trace level materials. Explosives were inkjet printed directly onto substrates and exposed to one of seven environmental conditions (Laboratory, −4 °C, 30 °C, 47 °C, 90 % relative humidity, UV light, and ozone) up to 42 days. Throughout the study, samples were extracted and quantified using electrospray ionization mass spectrometry (ESI-MS) to determine the stability of the explosive as a function of time and environmental exposure. Statistical models were then fit to the data and used for pairwise comparisons of the environments. Stability was found to be exposure and compound dependent with minimal sample losses observed for HMX, RDX, and PETN while substantial and rapid losses were observed in all conditions except −4 °C for ETN and TNT and in all conditions for tetryl. The results of this work highlight the potential fate of explosive traces when exposed to various environments. PMID:28153227

Fe3O4@ionic liquid@methyl orange nanoparticles as a novel nano-adsorbent for magnetic solid-phase extraction of polycyclic aromatic hydrocarbons in environmental water samples.

PubMed

Liu, Xiaofei; Lu, Xin; Huang, Yong; Liu, Chengwei; Zhao, Shulin

2014-02-01

A novel nano-adsorbent, Fe3O4@ionic liquid@methyl orange nanoparticles (Fe3O4@IL@MO NPs), was prepared for magnetic solid-phase extraction (MSPE) of polycyclic aromatic hydrocarbons (PAHs) in environmental water samples. The Fe3O4@IL@MO NPs were synthesized by self-assembly of the ionic liquid 1-octadecyl-3-methylimidazolium bromide (C18mimBr) and methyl orange (MO) onto the surface of Fe3O4 silica magnetic nanoparticles, as confirmed by infrared spectroscopy, ultraviolet-visible spectroscopy and superconducting quantum interface device magnetometer. The extraction performance of Fe3O4@IL@MO NPs as a nano-adsorbent was evaluated by using five PAHs, fluorene (FLu), anthracene (AnT), pyrene (Pyr), benzo(a)anthracene (BaA) and benzo(a)pyrene (BaP) as model analytes. Under the optimum conditions, detection limits in the range of 0.1-2 ng/L were obtained by high performance liquid chromatography-fluorescence detection (HPLC-FLD). This method has been successfully applied for the determination of PAHs in environmental water samples by using the MSPE-HPLC-FLD. The recoveries for the five PAHs tested in spiked real water samples were in the range of 80.4-104.0% with relative standard deviations ranging from 2.3 to 4.9%. © 2013 Published by Elsevier B.V.

Combination of Competitive Quantitative PCR and Constant-Denaturant Capillary Electrophoresis for High-Resolution Detection and Enumeration of Microbial Cells

PubMed Central

Lim, Eelin L.; Tomita, Aoy V.; Thilly, William G.; Polz, Martin F.

2001-01-01

A novel quantitative PCR (QPCR) approach, which combines competitive PCR with constant-denaturant capillary electrophoresis (CDCE), was adapted for enumerating microbial cells in environmental samples using the marine nanoflagellate Cafeteria roenbergensis as a model organism. Competitive PCR has been used successfully for quantification of DNA in environmental samples. However, this technique is labor intensive, and its accuracy is dependent on an internal competitor, which must possess the same amplification efficiency as the target yet can be easily discriminated from the target DNA. The use of CDCE circumvented these problems, as its high resolution permitted the use of an internal competitor which differed from the target DNA fragment by a single base and thus ensured that both sequences could be amplified with equal efficiency. The sensitivity of CDCE also enabled specific and precise detection of sequences over a broad range of concentrations. The combined competitive QPCR and CDCE approach accurately enumerated C. roenbergensis cells in eutrophic, coastal seawater at abundances ranging from approximately 10 to 104 cells ml−1. The QPCR cell estimates were confirmed by fluorescent in situ hybridization counts, but estimates of samples with <50 cells ml−1 by QPCR were less variable. This novel approach extends the usefulness of competitive QPCR by demonstrating its ability to reliably enumerate microorganisms at a range of environmentally relevant cell concentrations in complex aquatic samples. PMID:11525983

Evaluation of Environmental Contamination and Estimated Radiation Doses for the Return to Residents’ Homes in Kawauchi Village, Fukushima Prefecture

PubMed Central

Taira, Yasuyuki; Hayashida, Naomi; Yamaguchi, Hitoshi; Yamashita, Shunichi; Endo, Yuukou; Takamura, Noboru

2012-01-01

To evaluate the environmental contamination and radiation exposure dose rates due to artificial radionuclides in Kawauchi Village, Fukushima Prefecture, the restricted area within a 30-km radius from the Fukushima Dai-ichi Nuclear Power Plant (FNPP), the concentrations of artificial radionuclides in soil samples, tree needles, and mushrooms were analyzed by gamma spectrometry. Nine months have passed since samples were collected on December 19 and 20, 2011, 9 months after the FNPP accident, and the prevalent dose-forming artificial radionuclides from all samples were 134Cs and 137Cs. The estimated external effective doses from soil samples were 0.42–7.2 µSv/h (3.7–63.0 mSv/y) within the 20-km radius from FNPP and 0.0011–0.38 µSv/h (0.010–3.3 mSv/y) within the 20–30 km radius from FNPP. The present study revealed that current levels are sufficiently decreasing in Kawauchi Village, especially in areas within the 20- to 30-km radius from FNPP. Thus, residents may return their homes with long-term follow-up of the environmental monitoring and countermeasures such as decontamination and restrictions of the intake of foods for reducing unnecessary exposure. The case of Kawauchi Village will be the first model for the return to residents’ homes after the FNPP accident. PMID:23049869

Associations of Perceived Social and Physical Environmental Supports With Physical Activity and Walking Behavior

PubMed Central

Addy, Cheryl L.; Wilson, Dawn K.; Kirtland, Karen A.; Ainsworth, Barbara E.; Sharpe, Patricia; Kimsey, Dexter

2004-01-01

We evaluated perceived social and environmental supports for physical activity and walking using multivariable modeling. Perceptions were obtained on a sample of households in a southeastern county. Respondents were classified according to physical activity levels and walking behaviors. Respondents who had good street lighting; trusted their neighbors; and used private recreational facilities, parks, playgrounds, and sports fields were more likely to be regularly active. Perceiving neighbors as being active, having access to sidewalks, and using malls were associated with regular walking. PMID:14998810

Longitudinal analysis of bioaccumulative contaminants in freshwater fishes

USGS Publications Warehouse

Sun, Jielun; Kim, Y.; Schmitt, C.J.

2003-01-01

The National Contaminant Biomonitoring Program (NCBP) was initiated in 1967 as a component of the National Pesticide Monitoring program. It consists of periodic collection of freshwater fish and other samples and the analysis of the concentrations of persistent environmental contaminants in these samples. For the analysis, the common approach has been to apply the mixed two-way ANOVA model to combined data. A main disadvantage of this method is that it cannot give a detailed temporal trend of the concentrations since the data are grouped. In this paper, we present an alternative approach that performs a longitudinal analysis of the information using random effects models. In the new approach, no grouping is needed and the data are treated as samples from continuous stochastic processes, which seems more appropriate than ANOVA for the problem.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".

INCORPORATING PRIOR KNOWLEDGE IN ENVIRONMENTAL SAMPLING: RANKED SET SAMPLING AND OTHER DOUBLE SAMPLING PROCEDURES

EPA Science Inventory

Environmental sampling can be difficult and expensive to carry out. Those taking the samples would like to integrate their knowledge of the system of study or their judgment about the system into the sample selection process to decrease the number of necessary samples. However,...

Microbial Characterization and Comparison of Isolates During the Mir and ISS Missions

NASA Technical Reports Server (NTRS)

Fontenot, Sondra L.; Castro, Victoria; Bruce, Rebekah; Ott, C. Mark; Pierson, Duane L.

2004-01-01

Spacecraft represent a semi-closed ecosystem that provides a unique model of microbial interaction with other microbes, potential hosts, and their environment. Environmental samples from the Mir Space Station (1995-1998) and the International Space Station (ISS) (2000-Present) were collected and processed to provide insight into the characterization of microbial diversity aboard spacecraft over time and assess any potential health risks to the crew. All microbiota were isolated using standard media-based methodologies. Isolates from Mir and ISS were processed using various methods of analysis, including VITEK biochemical analysis, 16s ribosomal identification, and fingerprinting using rep-PCR analysis. Over the first 41 months of habitation, the diversity of the microbiota from air and surface samples aboard ISS increased from an initial six to 53 different bacterial species. During the same period, fungal diversity increased from 2 to 24 species. Based upon rep-PCR analysis, the majority of isolates were unique suggesting the need for increased sampling frequency and a more thorough analysis of samples to properly characterize the ISS microbiota. This limited fungal and bacterial data from environmental samples acquired during monitoring currently do not indicate a microbial hazard to ISS or any trends suggesting potential health risks.

Environmental Technology (Laboratory Analysis and Environmental Sampling) Curriculum Development Project. Final Report.

ERIC Educational Resources Information Center

Hinojosa, Oscar V.; Guillen, Alfonso

A project assessed the need and developed a curriculum for environmental technology (laboratory analysis and environmental sampling) in the emerging high technology centered around environmental safety and health in Texas. Initial data were collected through interviews by telephone and in person and through onsite visits. Additional data was…

Quantitative assessment of the flow pattern in the southern Arava Valley (Israel) by environmental tracers and a mixing cell model

NASA Astrophysics Data System (ADS)

Adar, E. M.; Rosenthal, E.; Issar, A. S.; Batelaan, O.

1992-08-01

This paper demonstrates the implementation of a novel mathematical model to quantify subsurface inflows from various sources into the arid alluvial basin of the southern Arava Valley divided between Israel and Jordan. The model is based on spatial distribution of environmental tracers and is aimed for use on basins with complex hydrogeological structure and/or with scarce physical hydrologic information. However, a sufficient qualified number of wells and springs are required to allow water sampling for chemical and isotopic analyses. Environmental tracers are used in a multivariable cluster analysis to define potential sources of recharge, and also to delimit homogeneous mixing compartments within the modeled aquifer. Six mixing cells were identified based on 13 constituents. A quantitative assessment of 11 significant subsurface inflows was obtained. Results revealed that the total recharge into the southern Arava basin is around 12.52 × 10 6m3year-1. The major source of inflow into the alluvial aquifer is from the Nubian sandstone aquifer which comprises 65-75% of the total recharge. Only 19-24% of the recharge, but the most important source of fresh water, originates over the eastern Jordanian mountains and alluvial fans.

Determinants of Pseudogymnoascus destructans within bat hibernacula: Implications for surveillance and management of white-nose syndrome

USGS Publications Warehouse

Verant, Michelle L.; Bohuski, Elizabeth A.; Richgels, Katherine L. D.; Olival, Kevin J.; Epstein, Jonathan H.; Blehert, David

2018-01-01

Fungal diseases are an emerging global problem affecting human health, food security and biodiversity. Ability of many fungal pathogens to persist within environmental reservoirs can increase extinction risks for host species and presents challenges for disease control. Understanding factors that regulate pathogen spread and persistence in these reservoirs is critical for effective disease management.White-nose syndrome (WNS) is a disease of hibernating bats caused by Pseudogymnoascus destructans (Pd), a fungus that establishes persistent environmental reservoirs within bat hibernacula, which contribute to seasonal disease transmission dynamics in bats. However, host and environmental factors influencing distribution of Pdwithin these reservoirs are unknown.We used model selection on longitudinally collected field data to test multiple hypotheses describing presence–absence and abundance of Pd in environmental substrates and on bats within hibernacula at different stages of WNS.First detection of Pd in the environment lagged up to 1 year after first detection on bats within that hibernaculum. Once detected, the probability of detecting Pd within environmental samples from a hibernaculum increased over time and was higher in sediment compared to wall surfaces. Temperature had marginal effects on the distribution of Pd. For bats, prevalence and abundance of Pd were highest on Myotis lucifugus and on bats with visible signs of WNS.Synthesis and applications. Our results indicate that distribution of Pseudogymnoascus destructans (Pd) within a hibernaculum is driven primarily by bats with delayed establishment of environmental reservoirs. Thus, collection of samples from Myotis lucifugus, or from sediment if bats cannot be sampled, should be prioritized to improve detection probabilities for Pd surveillance. Long-term persistence of Pd in sediment suggests that disease management for white-nose syndrome should address risks of sustained transmission from environmental reservoirs.

Hurricane Katrina-linked environmental injustice: race, class, and place differentials in attitudes.

PubMed

Adeola, Francis O; Picou, J Steven

2017-04-01

Claims of environmental injustice, human neglect, and racism dominated the popular and academic literature after Hurricane Katrina struck the United States in August 2005. A systematic analysis of environmental injustice from the perspective of the survivors remains scanty or nonexistent. This paper presents, therefore, a systematic empirical analysis of the key determinants of Katrina-induced environmental injustice attitudes among survivors in severely affected parishes (counties) in Louisiana and Mississippi three years into the recovery process. Statistical models based on a random sample of survivors were estimated, with the results revealing significant predictors such as age, children in household under 18, education, homeownership, and race. The results further indicate that African-Americans were more likely to perceive environmental injustice following Katrina than their white counterparts. Indeed, the investigation reveals that there are substantial racial gaps in measures of environmental injustice. The theoretical, methodological, and applied policy implications of these findings are discussed. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.

2011-01-01

Pollen can be transported great distances. Van de Water et. al. reported Juniperus spp. pollen was transported 200-600 km. Hence local obse rvations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data produ cts to identify source regions and quantities of dust. We are modifyi ng the DREAM model to incorporate pollen transport. Pollen release wi ll be estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observations records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention?s Nat ional Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus spp. Pollen Phenology and Dispersal

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, Estelle; Huete, Alfredo; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].

PubMed

Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin

2016-10-01

In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

A model to environmental monitoring based on glutathione-S-transferase activity and branchial lesions in catfish

NASA Astrophysics Data System (ADS)

Neta, Raimunda Nonata Fortes Carvalho; Torres, Audalio Rebelo

2017-11-01

In this work, we validate the glutathione-S-transferase and branchial lesions as biomarkers in catfish Sciades herzbergii to obtain a predictive model of the environmental impact effects in a harbor of Brazil. The catfish were sampled from a port known to be contaminated with heavy metals and organic compounds and from a natural reserve in São Marcos Bay, Maranhão. Two biomarkers, hepatic glutathione S-transferase (GST) activity and branchial lesions were analyzed. The values for GST activity were modeled with the occurrence of branchial lesions by fitting a third order polynomial. Results from the mathematical model indicate that GST activity has a strong polynomial relationship with the occurrence of branchial lesions in both the wet and the dry seasons, but only at the polluted port site. Our mathematic model indicates that when the GST ceases to act, serious branchial lesions are observed in the catfish of the contaminated port area.

Assessing environmental DNA detection in controlled lentic systems.

PubMed

Moyer, Gregory R; Díaz-Ferguson, Edgardo; Hill, Jeffrey E; Shea, Colin

2014-01-01

Little consideration has been given to environmental DNA (eDNA) sampling strategies for rare species. The certainty of species detection relies on understanding false positive and false negative error rates. We used artificial ponds together with logistic regression models to assess the detection of African jewelfish eDNA at varying fish densities (0, 0.32, 1.75, and 5.25 fish/m3). Our objectives were to determine the most effective water stratum for eDNA detection, estimate true and false positive eDNA detection rates, and assess the number of water samples necessary to minimize the risk of false negatives. There were 28 eDNA detections in 324, 1-L, water samples collected from four experimental ponds. The best-approximating model indicated that the per-L-sample probability of eDNA detection was 4.86 times more likely for every 2.53 fish/m3 (1 SD) increase in fish density and 1.67 times less likely for every 1.02 C (1 SD) increase in water temperature. The best section of the water column to detect eDNA was the surface and to a lesser extent the bottom. Although no false positives were detected, the estimated likely number of false positives in samples from ponds that contained fish averaged 3.62. At high densities of African jewelfish, 3-5 L of water provided a >95% probability for the presence/absence of its eDNA. Conversely, at moderate and low densities, the number of water samples necessary to achieve a >95% probability of eDNA detection approximated 42-73 and >100 L, respectively. Potential biases associated with incomplete detection of eDNA could be alleviated via formal estimation of eDNA detection probabilities under an occupancy modeling framework; alternatively, the filtration of hundreds of liters of water may be required to achieve a high (e.g., 95%) level of certainty that African jewelfish eDNA will be detected at low densities (i.e., <0.32 fish/m3 or 1.75 g/m3).

Environmental stress cracking performance of polyether and PDMS-based polyurethanes in an in vitro oxidation model.

PubMed

Gallagher, Genevieve; Padsalgikar, Ajay; Tkatchouk, Ekaterina; Jenney, Chris; Iacob, Ciprian; Runt, James

2017-08-01

Environmental stress cracking (ESC) was replicated in vitro on Optim™ (OPT) insulation, a polydimethylsiloxane-based polyurethane utilized clinically in cardiac leads, using a Zhao-type oxidation model. OPT performance was compared to that of two industry standard polyether urethanes: Pellethane ® 80A (P80A), and Pellethane ® 55D (P55D). Clinically relevant specimen configurations and strain states were utilized: low-voltage cardiac lead segments were held in a U-shape by placing them inside of vials. To study whether aging conditions impacted ESC formation, half of the samples were subjected to a pretreatment in human plasma for 7 days at 37°C; all samples were then aged in oxidative solutions containing 0.9% NaCl, 20% H 2 O 2 , and either 0 or 0.1M CoCl 2 , with or without glass wool for 72 days at 37°C. Visual and SEM inspection revealed significant surface cracking consistent with ESC on all P80A and P55D samples. Sixteen of twenty P80A and 10/20 P55D samples also exhibited breaches. Seven of 20 OPT samples exhibited shallow surface cracking consistent with ESC. ATR-FTIR confirmed surface changes consistent with oxidation for all materials. The number average molecular weight decreased an average of 31% for OPT, 86% for P80A, and 56% for P55D samples. OPT outperformed P80A and P55D in this Zhao-type in vitro ESC model. An aging solution of 0.9% NaCl, 20% H 2 O 2 , and 0.1M CoCl 2 , with glass wool provided the best combination of ESC replication and ease of use. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 1544-1558, 2017. © 2016 Wiley Periodicals, Inc.

Perceived sexual harassment at work: meta-analysis and structural model of antecedents and consequences.

PubMed

Topa Cantisano, Gabriela; Morales Domínguez, J F; Depolo, Marco

2008-05-01

Although sexual harassment has been extensively studied, empirical research has not led to firm conclusions about its antecedents and consequences, both at the personal and organizational level. An extensive literature search yielded 42 empirical studies with 60 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported the hypotheses regarding organizational environmental factors as main predictors of harassment.

The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

NASA Astrophysics Data System (ADS)

Makahinda, T.

2018-02-01

The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

Using occupancy modelling to compare environmental DNA to traditional field methods for regional-scale monitoring of an endangered aquatic species.

PubMed

Schmelzle, Molly C; Kinziger, Andrew P

2016-07-01

Environmental DNA (eDNA) monitoring approaches promise to greatly improve detection of rare, endangered and invasive species in comparison with traditional field approaches. Herein, eDNA approaches and traditional seining methods were applied at 29 research locations to compare method-specific estimates of detection and occupancy probabilities for endangered tidewater goby (Eucyclogobius newberryi). At each location, multiple paired seine hauls and water samples for eDNA analysis were taken, ranging from two to 23 samples per site, depending upon habitat size. Analysis using a multimethod occupancy modelling framework indicated that the probability of detection using eDNA was nearly double (0.74) the rate of detection for seining (0.39). The higher detection rates afforded by eDNA allowed determination of tidewater goby occupancy at two locations where they have not been previously detected and at one location considered to be locally extirpated. Additionally, eDNA concentration was positively related to tidewater goby catch per unit effort, suggesting eDNA could potentially be used as a proxy for local tidewater goby abundance. Compared to traditional field sampling, eDNA provided improved occupancy parameter estimates and can be applied to increase management efficiency across a broad spatial range and within a diversity of habitats. © 2015 John Wiley & Sons Ltd.

The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.

A General Model of Dioxin Contamination in Breast Milk: Results from a Study on 94 Women from the Caserta and Naples Areas in Italy

PubMed Central

Rivezzi, Gaetano; Piscitelli, Prisco; Scortichini, Giampiero; Giovannini, Armando; Diletti, Gianfranco; Migliorati, Giacomo; Ceci, Roberta; Rivezzi, Giulia; Cirasino, Lorenzo; Carideo, Pietro; Black, Dennis M.; Garzillo, Carmine; Giani, Umberto

2013-01-01

Background: The Caserta and Naples areas in Campania Region experience heavy environmental contamination due to illegal waste disposal and burns, thus representing a valuable setting to develop a general model of human contamination with dioxins (PCDDs-PCDFs) and dioxin-like-PCBs (dl-PCBs). Methods: 94 breastfeeding women (aged 19–32 years; mean age 27.9 ± 3.0) were recruited to determine concentrations of PCDDs-PCDFs and dl-PCBs in their milk. Individual milk samples were collected and analyzed according to standard international procedures. A generalized linear model was used to test potential predictors of pollutant concentration in breast milk: age, exposure to waste fires, cigarette smoking, diet, and residence in high/low risk area (defined at high/low environmental pressure by a specific 2007 WHO report). A Structural Equation Model (SEM) analysis was carried out by taking into account PCDDs-PCDFs and dl-PCBs as endogenous variables and age, waste fires, risk area and smoking as exogenous variables. Results: All milk samples were contaminated by PCDDs-PCDFs (8.6 pg WHO-TEQ/98g fat ± 2.7; range 3.8–19) and dl-PCBs (8.0 pg WHO-TEQ/98g fat ± 3.7; range 2.5–24), with their concentrations being associated with age and exposure to waste fires (p < 0.01). Exposure to fires resulted in larger increases of dioxins concentrations in people living in low risk areas than those from high risk areas (p < 0.01). Conclusions: A diffuse human exposure to persistent organic pollutants was observed in the Caserta and Naples areas. Dioxins concentration in women living in areas classified at low environmental pressure in 2007 WHO report was significantly influenced by exposure to burns. PMID:24217180

Evaluation of environmental sampling methods for detection of Salmonella enterica in a large animal veterinary hospital.

PubMed

Goeman, Valerie R; Tinkler, Stacy H; Hammac, G Kenitra; Ruple, Audrey

2018-04-01

Environmental surveillance for Salmonella enterica can be used for early detection of contamination; thus routine sampling is an integral component of infection control programs in hospital environments. At the Purdue University Veterinary Teaching Hospital (PUVTH), the technique regularly employed in the large animal hospital for sample collection uses sterile gauze sponges for environmental sampling, which has proven labor-intensive and time-consuming. Alternative sampling methods use Swiffer brand electrostatic wipes for environmental sample collection, which are reportedly effective and efficient. It was hypothesized that use of Swiffer wipes for sample collection would be more efficient and less costly than the use of gauze sponges. A head-to-head comparison between the 2 sampling methods was conducted in the PUVTH large animal hospital and relative agreement, cost-effectiveness, and sampling efficiency were compared. There was fair agreement in culture results between the 2 sampling methods, but Swiffer wipes required less time and less physical effort to collect samples and were more cost-effective.

Estimating true human and animal host source contribution in quantitative microbial source tracking using the Monte Carlo method.

PubMed

Wang, Dan; Silkie, Sarah S; Nelson, Kara L; Wuertz, Stefan

2010-09-01

Cultivation- and library-independent, quantitative PCR-based methods have become the method of choice in microbial source tracking. However, these qPCR assays are not 100% specific and sensitive for the target sequence in their respective hosts' genome. The factors that can lead to false positive and false negative information in qPCR results are well defined. It is highly desirable to have a way of removing such false information to estimate the true concentration of host-specific genetic markers and help guide the interpretation of environmental monitoring studies. Here we propose a statistical model based on the Law of Total Probability to predict the true concentration of these markers. The distributions of the probabilities of obtaining false information are estimated from representative fecal samples of known origin. Measurement error is derived from the sample precision error of replicated qPCR reactions. Then, the Monte Carlo method is applied to sample from these distributions of probabilities and measurement error. The set of equations given by the Law of Total Probability allows one to calculate the distribution of true concentrations, from which their expected value, confidence interval and other statistical characteristics can be easily evaluated. The output distributions of predicted true concentrations can then be used as input to watershed-wide total maximum daily load determinations, quantitative microbial risk assessment and other environmental models. This model was validated by both statistical simulations and real world samples. It was able to correct the intrinsic false information associated with qPCR assays and output the distribution of true concentrations of Bacteroidales for each animal host group. Model performance was strongly affected by the precision error. It could perform reliably and precisely when the standard deviation of the precision error was small (≤ 0.1). Further improvement on the precision of sample processing and qPCR reaction would greatly improve the performance of the model. This methodology, built upon Bacteroidales assays, is readily transferable to any other microbial source indicator where a universal assay for fecal sources of that indicator exists. Copyright © 2010 Elsevier Ltd. All rights reserved.

Understanding environmental DNA detection probabilities: A case study using a stream-dwelling char Salvelinus fontinalis

USGS Publications Warehouse

Wilcox, Taylor M; Mckelvey, Kevin S.; Young, Michael K.; Sepulveda, Adam; Shepard, Bradley B.; Jane, Stephen F; Whiteley, Andrew R.; Lowe, Winsor H.; Schwartz, Michael K.

2016-01-01

Environmental DNA sampling (eDNA) has emerged as a powerful tool for detecting aquatic animals. Previous research suggests that eDNA methods are substantially more sensitive than traditional sampling. However, the factors influencing eDNA detection and the resulting sampling costs are still not well understood. Here we use multiple experiments to derive independent estimates of eDNA production rates and downstream persistence from brook trout (Salvelinus fontinalis) in streams. We use these estimates to parameterize models comparing the false negative detection rates of eDNA sampling and traditional backpack electrofishing. We find that using the protocols in this study eDNA had reasonable detection probabilities at extremely low animal densities (e.g., probability of detection 0.18 at densities of one fish per stream kilometer) and very high detection probabilities at population-level densities (e.g., probability of detection > 0.99 at densities of ≥ 3 fish per 100 m). This is substantially more sensitive than traditional electrofishing for determining the presence of brook trout and may translate into important cost savings when animals are rare. Our findings are consistent with a growing body of literature showing that eDNA sampling is a powerful tool for the detection of aquatic species, particularly those that are rare and difficult to sample using traditional methods.

Stressor-Response Models Relating Nutrient Enrichment to Algal Communities in Pacific Northwest Streams and Rivers

NASA Astrophysics Data System (ADS)

Sobota, D. J.; Hubler, S.; Paul, M. J.; Labiosa, R.

2015-12-01

Excessive algal growth in streams and rivers from nutrient enrichment can cause costly human health and environmental problems. As part of the US Environmental Protection Agency's Nutrient Scientific Technical Exchange Partnership and Support (N-STEPS) program, we have been developing stressor-response (S-R) models relating nutrients to attached algal (periphyton) communities to help prioritize monitoring for water quality impairments in Oregon (Pacific Northwest, USA) streams and rivers. Existing data from the state and neighboring states were compiled and standardized from the Oregon Department of Environmental Quality, US Environmental Protection Agency, and the US Geological Survey. To develop S-R models, algal community and biomass metrics were compared with nitrogen (N) and phosphorus (P) concentration data, including total, dissolved, and inorganic forms of these nutrients. In total, 928 paired algal-nutrient samples were compiled from the 8 Level-III Ecoregions occurring in Oregon. Relationships between algal biomass metrics and nutrient concentrations were weak, with only ash-free dry mass and standing stock of chlorophyll a showing slight positive relationships across gradients of total N and soluble reactive P concentrations, respectively. In contrast, metrics describing algal community composition, including percent diatoms and abundance of nutrient-sensitive species, showed very strong nonlinear relationships with total N or P concentrations. This suggests that data describing algal community composition can help identify specific nutrient stressors across environmentally-diverse streams and rivers in the Pacific Northwest. Future analyses will examine if nutrient-algal S-R models vary across different hydrological, physiographical, and ecological settings in the region.

Testing mixing models of old and young groundwater in a tropical lowland rain forest with environmental tracers

NASA Astrophysics Data System (ADS)

Solomon, D. Kip; Genereux, David P.; Plummer, L. Niel; Busenberg, Eurybiades

2010-04-01

We tested three models of mixing between old interbasin groundwater flow (IGF) and young, locally derived groundwater in a lowland rain forest in Costa Rica using a large suite of environmental tracers. We focus on the young fraction of water using the transient tracers CFC-11, CFC-12, CFC-113, SF6, 3H, and bomb 14C. We measured 3He, but 3H/3He dating is generally problematic due to the presence of mantle 3He. Because of their unique concentration histories in the atmosphere, combinations of transient tracers are sensitive not only to subsurface travel times but also to mixing between waters having different travel times. Samples fall into three distinct categories: (1) young waters that plot along a piston flow line, (2) old samples that have near-zero concentrations of the transient tracers, and (3) mixtures of 1 and 2. We have modeled the concentrations of the transient tracers using (1) a binary mixing model (BMM) of old and young water with the young fraction transported via piston flow, (2) an exponential mixing model (EMM) with a distribution of groundwater travel times characterized by a mean value, and (3) an exponential mixing model for the young fraction followed by binary mixing with an old fraction (EMM/BMM). In spite of the mathematical differences in the mixing models, they all lead to a similar conceptual model of young (0 to 10 year) groundwater that is locally derived mixing with old (>1000 years) groundwater that is recharged beyond the surface water boundary of the system.

POWERFUL NEW TOOLS FOR ANALYZING ENVIRONMENTAL CONTAMINATION: MASS PEAK PROFILING FROM SELECTED-ION RECORDING DATA AND A PROFILE GENERATION MODEL

EPA Science Inventory

Capillary gas chromatography with mass spectrometric detection is the most commonly used technique for analyzing samples from Superfund sites. While the U.S. EPA has developed target lists of compounds for which library mass spectra are available on most mass spectrometer data s...

Performance-Based Task Assessment of Higher-Order Proficiencies in Redesigned STEM High Schools

ERIC Educational Resources Information Center

Ernst, Jeremy V.; Glennie, Elizabeth; Li, Songze

2017-01-01

This study explored student abilities in applying conceptual knowledge when presented with structured performance tasks. Specifically, the study gauged proficiency in higher-order applications of students enrolled in earth and environmental science or biology. The student sample was drawn from a Redesigned STEM high school model where a tested…

Increasing Teacher Confidence in Teaching and Technology Use through Vicarious Experiences within an Environmental Education Context

ERIC Educational Resources Information Center

Willis, Jana; Weiser, Brenda; Smith, Donna

2016-01-01

Providing teacher candidates opportunities to engage in experiences modeling effective technology integration could improve confidence/comfort in using technology and support skill development and transfer. A purposeful sample of 424 candidates in an educational technology course was administered the Technology and Teaching Efficacy Scale to…

Examining the Diet of Post-Migrant Hispanic Males Using the Precede-Proceed Model: Predisposing, Reinforcing, and Enabling Dietary Factors

ERIC Educational Resources Information Center

Castellanos, Diana Cuy; Downey, Laura; Graham-Kresge, Susan; Yadrick, Kathleen; Zoellner, Jamie; Connell, Carol L.

2013-01-01

Objective: To examine socio-environmental, behavioral, and predisposing, reinforcing, and enabling (PRE) factors contributing to post-migration dietary behavior change among a sample of traditional Hispanic males. Design: In this descriptive study, semistructured interviews, a group interview, and photovoice, followed by group interviews, were…

Influence of Environmental Factors and Human Activity on the Presence of Salmonella Serovars in a Marine Environment

PubMed Central

Martinez-Urtaza, Jaime; Saco, Montserrat; de Novoa, Jacobo; Perez-Piñeiro, Pelayo; Peiteado, Jesus; Lozano-Leon, Antonio; Garcia-Martin, Oscar

2004-01-01

The temporal and spatial distribution of Salmonella contamination in the coastal waters of Galicia (northwestern Spain) relative to contamination events with different environmental factors (temperature, wind, hours of sunlight, rainfall, and river flow) were investigated over a 4-year period. Salmonellae were isolated from 127 of 5,384 samples of molluscs and seawater (2.4%), and no significant differences (P < 0.05) between isolates obtained in different years were observed. The incidence of salmonellae was significantly higher in water column samples (2.9%) than in those taken from the marine benthos (0.7%). Of the 127 strains of Salmonella isolated, 20 different serovars were identified. Salmonella enterica serovar Senftenberg was the predominant serovar, being represented by 54 isolates (42.5%), followed by serovar Typhimurium (19 isolates [15%]) and serovar Agona (12 isolates [9.4%]). Serovar Senftenberg was detected at specific points on the coast and could not be related to any of the environmental parameters analyzed. All serovars except Salmonella serovar Senftenberg were found principally in the southern coastal areas close to the mouths of rivers, and their incidence was associated with high southwestern wind and rainfall. Using multiple logistic regression analysis models, the prevalence of salmonellae was best explained by environmental parameters on the day prior to sampling. Understanding this relationship may be useful for the control of molluscan shellfish harvests, with wind and rainfall serving as triggers for closure. PMID:15066800

Using habitat suitability models to target invasive plant species surveys

USGS Publications Warehouse

Crall, Alycia W.; Jarnevich, Catherine S.; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P 2) = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.

Estimating thermal performance curves from repeated field observations

USGS Publications Warehouse

Childress, Evan; Letcher, Benjamin H.

2017-01-01

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models

USGS Publications Warehouse

Miller, David A.W.

2012-01-01

Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.

Microfluidic device for a rapid immobilization of zebrafish larvae in environmental scanning electron microscopy.

PubMed

Akagi, Jin; Zhu, Feng; Skommer, Joanna; Hall, Chris J; Crosier, Philip S; Cialkowski, Michal; Wlodkowic, Donald

2015-03-01

Small vertebrate model organisms have recently gained popularity as attractive experimental models that enhance our understanding of human tissue and organ development. Despite a large body of evidence using optical spectroscopy for the characterization of small model organism on chip-based devices, no attempts have been so far made to interface microfabricated technologies with environmental scanning electron microscopy (ESEM). Conventional scanning electron microscopy requires high vacuum environments and biological samples must be, therefore, submitted to many preparative procedures to dehydrate, fix, and subsequently stain the sample with gold-palladium deposition. This process is inherently low-throughput and can introduce many analytical artifacts. This work describes a proof-of-concept microfluidic chip-based system for immobilizing zebrafish larvae for ESEM imaging that is performed in a gaseous atmosphere, under low vacuum mode and without any need for sample staining protocols. The microfabricated technology provides a user-friendly and simple interface to perform ESEM imaging on zebrafish larvae. Presented lab-on-a-chip device was fabricated using a high-speed infrared laser micromachining in a biocompatible poly(methyl methacrylate) thermoplastic. It consisted of a reservoir with multiple semispherical microwells designed to hold the yolk of dechorionated zebrafish larvae. Immobilization of the larvae was achieved by a gentle suction generated during blotting of the medium. Trapping region allowed for multiple specimens to be conveniently positioned on the chip-based device within few minutes for ESEM imaging. © 2014 International Society for Advancement of Cytometry.

Comparison of in vitro and in vivo bioassays to measure thyroid hormone disrupting activity in water extracts.

PubMed

Leusch, Frederic D L; Aneck-Hahn, Natalie H; Cavanagh, Jo-Anne E; Du Pasquier, David; Hamers, Timo; Hebert, Armelle; Neale, Peta A; Scheurer, Marco; Simmons, Steven O; Schriks, Merijn

2018-01-01

Environmental chemicals can induce thyroid disruption through a number of mechanisms including altered thyroid hormone biosynthesis and transport, as well as activation and inhibition of the thyroid receptor. In the current study six in vitro bioassays indicative of different mechanisms of thyroid disruption and one whole animal in vivo assay were applied to 9 model compounds and 4 different water samples (treated wastewater, surface water, drinking water and ultra-pure lab water; both unspiked and spiked with model compounds) to determine their ability to detect thyroid active compounds. Most assays correctly identified and quantified the model compounds as agonists or antagonists, with the reporter gene assays being the most sensitive. However, the reporter gene assays did not detect significant thyroid activity in any of the water samples, suggesting that activation or inhibition of the thyroid hormone receptor is not a relevant mode of action for thyroid endocrine disruptors in water. The thyroperoxidase (TPO) inhibition assay and transthyretin (TTR) displacement assay (FITC) detected activity in the surface water and treated wastewater samples, but more work is required to assess if this activity is a true measure of thyroid activity or matrix interference. The whole animal Xenopus Embryonic Thyroid Assay (XETA) detected some activity in the unspiked surface water and treated wastewater extracts, but not in unspiked drinking water, and appears to be a suitable assay to detect thyroid activity in environmental waters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Development and validation of a stochastic model for potential growth of Listeria monocytogenes in naturally contaminated lightly preserved seafood.

PubMed

Mejlholm, Ole; Bøknæs, Niels; Dalgaard, Paw

2015-02-01

A new stochastic model for the simultaneous growth of Listeria monocytogenes and lactic acid bacteria (LAB) was developed and validated on data from naturally contaminated samples of cold-smoked Greenland halibut (CSGH) and cold-smoked salmon (CSS). During industrial processing these samples were added acetic and/or lactic acids. The stochastic model was developed from an existing deterministic model including the effect of 12 environmental parameters and microbial interaction (O. Mejlholm and P. Dalgaard, Food Microbiology, submitted for publication). Observed maximum population density (MPD) values of L. monocytogenes in naturally contaminated samples of CSGH and CSS were accurately predicted by the stochastic model based on measured variability in product characteristics and storage conditions. Results comparable to those from the stochastic model were obtained, when product characteristics of the least and most preserved sample of CSGH and CSS were used as input for the existing deterministic model. For both modelling approaches, it was shown that lag time and the effect of microbial interaction needs to be included to accurately predict MPD values of L. monocytogenes. Addition of organic acids to CSGH and CSS was confirmed as a suitable mitigation strategy against the risk of growth by L. monocytogenes as both types of products were in compliance with the EU regulation on ready-to-eat foods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nonparametric estimation of benchmark doses in environmental risk assessment

PubMed Central

Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

2013-01-01

Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay.

PubMed

Jacobs, J M; Rhodes, M; Brown, C W; Hood, R R; Leight, A; Long, W; Wood, R

2014-11-01

To construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters of Chesapeake Bay for implementation in ecological forecasting systems. We evaluated and applied previously published qPCR assays to water samples (n = 1636) collected from Chesapeake Bay from 2007-2010 in conjunction with State water quality monitoring programmes. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Use of magnetic effervescent tablet-assisted ionic liquid dispersive liquid-liquid microextraction to extract fungicides from environmental waters with the aid of experimental design methodology.

PubMed

Yang, Miyi; Wu, Xiaoling; Jia, Yuhan; Xi, Xuefei; Yang, Xiaoling; Lu, Runhua; Zhang, Sanbing; Gao, Haixiang; Zhou, Wenfeng

2016-02-04

In this work, a novel effervescence-assisted microextraction technique was proposed for the detection of four fungicides. This method combines ionic liquid-based dispersive liquid-liquid microextraction with the magnetic retrieval of the extractant. A magnetic effervescent tablet composed of Fe3O4 magnetic nanoparticles, sodium carbonate, sodium dihydrogen phosphate and 1-hexyl-3-methylimidazolium bis(trifluoromethanesulfonimide) was used for extractant dispersion and retrieval. The main factors affecting the extraction efficiency were screened by a Plackett-Burman design and optimized by a central composite design. Under the optimum conditions, good linearity was obtained for all analytes in pure water model and real water samples. Just for the pure water, the recoveries were between 84.6% and 112.8%, the limits of detection were between 0.02 and 0.10 μg L(-1) and the intra-day precision and inter-day precision both are lower than 4.9%. This optimized method was successfully applied in the analysis of four fungicides (azoxystrobin, triazolone, cyprodinil, trifloxystrobin) in environmental water samples and the recoveries ranged between 70.7% and 105%. The procedure promising to be a time-saving, environmentally friendly, and efficient field sampling technique. Copyright © 2015 Elsevier B.V. All rights reserved.

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Detection and Molecular Characterization of Gemycircularvirus from Environmental Samples in Brazil.

PubMed

da Silva Assis, Matheus Ribeiro; Vieira, Carmen Baur; Fioretti, Julia Monassa; Rocha, Mônica Simões; de Almeida, Pedro Ivo Neves; Miagostovich, Marize Pereira; Fumian, Tulio Machado

2016-12-01

Gemycircularvirus (GemyCV) is a group of viruses which has been recently proposed as a new viral genus detected in fecal and environmental samples around the world. GemyCVs have been detected in human blood, brain tissue, cerebrospinal fluid, and stool sample. In the present study, we demonstrate for the first time, through molecular detection and characterization, the presence of GemyCVs in environmental samples from Brazil. Our results show a percentage of positivity ranging from 69 (25/36) to 97 % (35/36) in river water samples collected in Manaus, Amazon region, and wastewater from a wastewater treatment plant located in Rio de Janeiro, respectively, revealing GemyCVs as an important environmental contaminant.

Species distribution modelling for Rhipicephalus microplus (Acari: Ixodidae) in Benin, West Africa: comparing datasets and modelling algorithms.

PubMed

De Clercq, E M; Leta, S; Estrada-Peña, A; Madder, M; Adehan, S; Vanwambeke, S O

2015-01-01

Rhipicephalus microplus is one of the most widely distributed and economically important ticks, transmitting Babesia bigemina, B. bovis and Anaplasma marginale. It was recently introduced to West Africa on live animals originating from Brazil. Knowing the precise environmental suitability for the tick would allow veterinary health officials to draft vector control strategies for different regions of the country. To test the performance of modelling algorithms and different sets of environmental explanatory variables, species distribution models for this tick species in Benin were developed using generalized linear models, linear discriminant analysis and random forests. The training data for these models were a dataset containing reported absence or presence in 104 farms, randomly selected across Benin. These farms were sampled at the end of the rainy season, which corresponds with an annual peak in tick abundance. Two environmental datasets for the country of Benin were compared: one based on interpolated climate data (WorldClim) and one based on remotely sensed images (MODIS). The pixel size for both environmental datasets was 1 km. Highly suitable areas occurred mainly along the warmer and humid coast extending northwards to central Benin. The northern hot and drier areas were found to be unsuitable. The models developed and tested on data from the entire country were generally found to perform well, having an AUC value greater than 0.92. Although statistically significant, only small differences in accuracy measures were found between the modelling algorithms, or between the environmental datasets. The resulting risk maps differed nonetheless. Models based on interpolated climate suggested gradual variations in habitat suitability, while those based on remotely sensed data indicated a sharper contrast between suitable and unsuitable areas, and a patchy distribution of the suitable areas. Remotely sensed data yielded more spatial detail in the predictions. When computing accuracy measures on a subset of data along the invasion front, the modelling technique Random Forest outperformed the other modelling approaches, and results with MODIS-derived variables were better than those using WorldClim data. The high environmental suitability for R. microplus in the southern half of Benin raises concern at the regional level for animal health, including its potential to substantially alter transmission risk of Babesia bovis. The northern part of Benin appeared overall of low environmental suitability. Continuous surveillance in the transition zone however remains relevant, in relation to important cattle movements in the region, and to the invasive character of R. microplus. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Environmental pollution of polybrominated diphenyl ethers from industrial plants in China: a preliminary investigation.

PubMed

Deng, Chao; Chen, Yuan; Li, Jinhui; Li, Ying; Li, Huafen

2016-04-01

Although numerous studies have shown the presence of polybrominated diphenyl ethers (PBDEs) in various environmental media, attention to their distribution in the environmental media surrounding industrial facilities is limited. In this study, eight PBDEs congeners (BDE-28, -47, -99, -100, -153, -154, -183, -209) were investigated in surface soils and water samples collected from commercial PBDE manufacturers, flame-retardant plastic modification plants and waste electrical and electronic equipment recycling facilities in China. Analysis of target compounds was performed using the model NCI GC-MS in SIM mode. The concentrations of ∑8PBDEs varied from 193.1 to 22,004.3 ng/L in water samples and from 1209.3 to 226,906 ng/g dry wt in surface soils, respectively. More severe PBDE contamination, when compared with previously reported data, was found in industrial areas in this study. This indicates that these industrial areas are highly polluted with PBDEs. BDE-209 was the predominant congener, accounting for more than 94% in this study, except for a 68.75% portion at one site. Our results show that PBDE manufacturing and flame-retardant plastic modification plants, easily overlooked by the public, are two primary PBDE pollution sources although they affect surrounding areas. Further research is needed, aimed at managing industrial PBDE emissions and eliminating environmental PBDE pollution, to investigate the material flows and environmental fates of PBDEs in all stages of the life cycle.

Suspect screening of large numbers of emerging contaminants in environmental waters using artificial neural networks for chromatographic retention time prediction and high resolution mass spectrometry data analysis.

PubMed

Bade, Richard; Bijlsma, Lubertus; Miller, Thomas H; Barron, Leon P; Sancho, Juan Vicente; Hernández, Felix

2015-12-15

The recent development of broad-scope high resolution mass spectrometry (HRMS) screening methods has resulted in a much improved capability for new compound identification in environmental samples. However, positive identifications at the ng/L concentration level rely on analytical reference standards for chromatographic retention time (tR) and mass spectral comparisons. Chromatographic tR prediction can play a role in increasing confidence in suspect screening efforts for new compounds in the environment, especially when standards are not available, but reliable methods are lacking. The current work focuses on the development of artificial neural networks (ANNs) for tR prediction in gradient reversed-phase liquid chromatography and applied along with HRMS data to suspect screening of wastewater and environmental surface water samples. Based on a compound tR dataset of >500 compounds, an optimized 4-layer back-propagation multi-layer perceptron model enabled predictions for 85% of all compounds to within 2min of their measured tR for training (n=344) and verification (n=100) datasets. To evaluate the ANN ability for generalization to new data, the model was further tested using 100 randomly selected compounds and revealed 95% prediction accuracy within the 2-minute elution interval. Given the increasing concern on the presence of drug metabolites and other transformation products (TPs) in the aquatic environment, the model was applied along with HRMS data for preliminary identification of pharmaceutically-related compounds in real samples. Examples of compounds where reference standards were subsequently acquired and later confirmed are also presented. To our knowledge, this work presents for the first time, the successful application of an accurate retention time predictor and HRMS data-mining using the largest number of compounds to preliminarily identify new or emerging contaminants in wastewater and surface waters. Copyright © 2015 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hinwood, A.L., E-mail: a.hinwood@ecu.edu.au; Callan, A.C.; Ramalingam, M.

Recent literature suggests that exposure to low concentrations of heavy metals may affect both maternal and child health. This study aimed to determine the biological heavy metals concentrations of pregnant women as well as environmental and dietary factors that may influence exposure concentrations. One hundred and seventy three pregnant women were recruited from Western Australia, each providing a sample of blood, first morning void urine, residential soil, dust and drinking water samples. Participants also completed a questionnaire which included a food frequency component. All biological and environmental samples were analysed for heavy metals using ICP-MS. Biological and environmental concentrations ofmore » lead and mercury were generally low (Median Pb Drinking Water (DW) 0.04 µg/L; Pb soil <3.0 µg/g; Pb dust 16.5 µg/g; Pb blood 3.67 µg/L; Pb urine 0.55; µg/L Hg DW <0.03; Hg soil <1.0 µg/g; Hg dust <1.0 µg/g; Hg blood 0.46 µg/L; Hg urine <0.40 µg/L). Cadmium concentrations were low in environmental samples (Median CdDW 0.02 µg/L; Cdsoil <0.30 ug/g; Cddust <0.30) but elevated in urine samples (Median 0.55 µg/L, creatinine corrected 0.70 µg/g (range <0.2–7.06 µg/g creatinine) compared with other studies of pregnant women. Predictors of increased biological metals concentrations in regression models for blood cadmium were residing in the Great Southern region of Western Australia and not using iron/folic acid supplements and for urinary cadmium was having lower household annual income. However, these factors explained little of the variation in respective biological metals concentrations. The importance of establishing factors that influence low human exposure concentrations is becoming critical in efforts to reduce exposures and hence the potential for adverse health effects. -- Highlights: • Biological heavy metals concentrations in women in their 3rd trimester of pregnancy. • Exposure assessment including environmental, lifestyle and activity data. • Urinary cadmium concentrations were elevated in this group of pregnant women. • Blood lead and mercury concentrations were below recommended biological guideline values.« less

Environmental factors and flow paths related to Escherichia coli concentrations at two beaches on Lake St. Clair, Michigan, 2002–2005

USGS Publications Warehouse

Holtschlag, David J.; Shively, Dawn; Whitman, Richard L.; Haack, Sheridan K.; Fogarty, Lisa R.

2008-01-01

Regression analyses and hydrodynamic modeling were used to identify environmental factors and flow paths associated with Escherichia coli (E. coli) concentrations at Memorial and Metropolitan Beaches on Lake St. Clair in Macomb County, Mich. Lake St. Clair is part of the binational waterway between the United States and Canada that connects Lake Huron with Lake Erie in the Great Lakes Basin. Linear regression, regression-tree, and logistic regression models were developed from E. coli concentration and ancillary environmental data. Linear regression models on log10 E. coli concentrations indicated that rainfall prior to sampling, water temperature, and turbidity were positively associated with bacteria concentrations at both beaches. Flow from Clinton River, changes in water levels, wind conditions, and log10 E. coli concentrations 2 days before or after the target bacteria concentrations were statistically significant at one or both beaches. In addition, various interaction terms were significant at Memorial Beach. Linear regression models for both beaches explained only about 30 percent of the variability in log10 E. coli concentrations. Regression-tree models were developed from data from both Memorial and Metropolitan Beaches but were found to have limited predictive capability in this study. The results indicate that too few observations were available to develop reliable regression-tree models. Linear logistic models were developed to estimate the probability of E. coli concentrations exceeding 300 most probable number (MPN) per 100 milliliters (mL). Rainfall amounts before bacteria sampling were positively associated with exceedance probabilities at both beaches. Flow of Clinton River, turbidity, and log10 E. coli concentrations measured before or after the target E. coli measurements were related to exceedances at one or both beaches. The linear logistic models were effective in estimating bacteria exceedances at both beaches. A receiver operating characteristic (ROC) analysis was used to determine cut points for maximizing the true positive rate prediction while minimizing the false positive rate. A two-dimensional hydrodynamic model was developed to simulate horizontal current patterns on Lake St. Clair in response to wind, flow, and water-level conditions at model boundaries. Simulated velocity fields were used to track hypothetical massless particles backward in time from the beaches along flow paths toward source areas. Reverse particle tracking for idealized steady-state conditions shows changes in expected flow paths and traveltimes with wind speeds and directions from 24 sectors. The results indicate that three to four sets of contiguous wind sectors have similar effects on flow paths in the vicinity of the beaches. In addition, reverse particle tracking was used for transient conditions to identify expected flow paths for 10 E. coli sampling events in 2004. These results demonstrate the ability to track hypothetical particles from the beaches, backward in time, to likely source areas. This ability, coupled with a greater frequency of bacteria sampling, may provide insight into changes in bacteria concentrations between source and sink areas.

Preliminary assessment of factors influencing riverine fish communities in Massachusetts.

USGS Publications Warehouse

Armstrong, David S.; Richards, Todd A.; Brandt, Sara L.

2010-01-01

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation (MDCR), Massachusetts Department of Environmental Protection (MDEP), and the Massachusetts Department of Fish and Game (MDFG), conducted a preliminary investigation of fish communities in small- to medium-sized Massachusetts streams. The objective of this investigation was to determine relations between fish-community characteristics and anthropogenic alteration, including flow alteration and impervious cover, relative to the effect of physical basin and land-cover (environmental) characteristics. Fish data were obtained for 756 fish-sampling sites from the Massachusetts Division of Fisheries and Wildlife fish-community database. A review of the literature was used to select a set of fish metrics responsive to flow alteration. Fish metrics tested include two fish-community metrics (fluvial-fish relative abundance and fluvial-fish species richness), and five indicator species metrics (relative abundance of brook trout, blacknose dace, fallfish, white sucker, and redfin pickerel). Streamflows were simulated for each fish-sampling site using the Sustainable Yield Estimator application (SYE). Daily streamflows and the SYE water-use database were used to determine a set of indicators of flow alteration, including percent alteration of August median flow, water-use intensity, and withdrawal and return-flow fraction. The contributing areas to the fish-sampling sites were delineated and used with a Geographic Information System (GIS) to determine a set of environmental characteristics, including elevation, basin slope, percent sand and gravel, percent wetland, and percent open water, and a set of anthropogenic-alteration variables, including impervious cover and dam density. Two analytical techniques, quantile regression and generalized linear modeling, were applied to determine the association between fish-response variables and the selected environmental and anthropogenic explanatory variables. Quantile regression indicated that flow alteration and impervious cover were negatively associated with both fluvial-fish relative abundance and fluvial-fish species richness. Three generalized linear models (GLMs) were developed to quantify the response of fish communities to multiple environmental and anthropogenic variables. Flow-alteration variables are statistically significant for the fluvial-fish relative-abundance model. Impervious cover is statistically significant for the fluvial-fish relative-abundance, fluvial-fish species richness, and brook trout relative-abundance models. The variables in the equations were demonstrated to be significant, and the variability explained by the models, as measured by the correlation between observed and predicted values, ranges from 39 to 65 percent. The GLM models indicated that, keeping all other variables the same, a one-unit (1 percent) increase in the percent depletion or percent surcharging of August median flow would result in a 0.4-percent decrease in the relative abundance (in counts per hour) of fluvial fish and that the relative abundance of fluvial fish was expected to be about 55 percent lower in net-depleted streams than in net-surcharged streams. The GLM models also indicated that a unit increase in impervious cover resulted in a 5.5-percent decrease in the relative abundance of fluvial fish and a 2.5-percent decrease in fluvial-fish species richness.

Nematode distributions as spatial null models for macroinvertebrate species richness across environmental gradients: A case from mountain lakes.

PubMed

de Mendoza, Guillermo; Traunspurger, Walter; Palomo, Alejandro; Catalan, Jordi

2017-05-01

Nematode species are widely tolerant of environmental conditions and disperse passively. Therefore, the species richness distribution in this group might largely depend on the topological distribution of the habitats and main aerial and aquatic dispersal pathways connecting them. If so, the nematode species richness distributions may serve as null models for evaluating that of other groups more affected by environmental gradients. We investigated this hypothesis in lakes across an altitudinal gradient in the Pyrenees. We compared the altitudinal distribution, environmental tolerance, and species richness, of nematodes with that of three other invertebrate groups collected during the same sampling: oligochaetes, chironomids, and nonchironomid insects. We tested the altitudinal bias in distributions with t -tests and the significance of narrow-ranging altitudinal distributions with randomizations. We compared results between groups with Fisher's exact tests. We then explored the influence of environmental factors on species assemblages in all groups with redundancy analysis (RDA), using 28 environmental variables. And, finally, we analyzed species richness patterns across altitude with simple linear and quadratic regressions. Nematode species were rarely biased from random distributions (5% of species) in contrast with other groups (35%, 47%, and 50%, respectively). The altitudinal bias most often shifted toward low altitudes (85% of biased species). Nematodes showed a lower portion of narrow-ranging species than any other group, and differed significantly from nonchironomid insects (10% and 43%, respectively). Environmental variables barely explained nematode assemblages (RDA adjusted R 2  = 0.02), in contrast with other groups (0.13, 0.19 and 0.24). Despite these substantial differences in the response to environmental factors, species richness across altitude was unimodal, peaking at mid elevations, in all groups. This similarity indicates that the spatial distribution of lakes across altitude is a primary driver of invertebrate richness. Provided that nematodes are ubiquitous, their distribution offers potential null models to investigate species richness across environmental gradients in other ecosystem types and biogeographic regions.

Family Socioeconomic Status and Consistent Environmental Stimulation in Early Childhood

PubMed Central

Crosnoe, Robert; Leventhal, Tama; Wirth, R. J.; Pierce, Kim M.; Pianta, Robert

2010-01-01

The transition into school occurs at the intersection of multiple environmental settings. This study applied growth curve modeling to a sample of 1,364 American children, followed from birth through age six, who had been categorized by their exposure to cognitive stimulation at home and in preschool child care and first grade classrooms. Of special interest was the unique and combined contribution to early learning of these three settings. Net of socioeconomic selection into different settings, children had higher math achievement when they were consistently stimulated in all three, and they had higher reading achievement when consistently stimulated at home and in child care. The observed benefits of consistent environmental stimulation tended to be more pronounced for low-income children. PMID:20573117

Egoistic, altruistic, and biospheric environmental concerns: a path analytic investigation of their determinants.

PubMed

Swami, Viren; Chamorro-Premuzic, Tomas; Snelgar, Rosemary; Furnham, Adrian

2010-04-01

Previous studies have shown that environmental concerns (ECs) can be reduced to a three-factor model - comprising altruistic, biospheric, and egoistic concerns - but there have been few studies examining individual difference predictors of ECs. In this study with 203 individuals from a British community sample, we show that biospheric concern was significantly associated with participants' age, political orientation, Machiavellianism, and the Big Five personality traits of Agreeableness, Emotional Stability, and Conscientiousness. Altruistic concern was significantly associated with sex, age, political orientation, and Machiavellianism, but not the Big Five traits, whereas egoistic concern was not significantly associated with any of these predictors except sex. These results are discussed in relation to previous work on ECs and pro-environmental behavior.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuenge, Jason R.; Hollomon, Brad; Dillon, Heather E.

This report covers the third part of a larger U.S. Department of Energy (DOE) project to assess the life-cycle environmental and resource impacts in the manufacturing, transport, use, and disposal of light-emitting diode (LED) lighting products in relation to incumbent lighting technologies. All three reports are available on the DOE website (www.ssl.energy.gov/tech_reports.html). • Part 1: Review of the Life-Cycle Energy Consumption of Incandescent, Compact Fluorescent and LED Lamps; • Part 2: LED Manufacturing and Performance; • Part 3: LED Environmental Testing. Parts 1 and 2 were published in February and June 2012, respectively. The Part 1 report included a summarymore » of the life-cycle assessment (LCA) process and methodology, provided a literature review of more than 25 existing LCA studies of various lamp types, and performed a meta-analysis comparing LED lamps with incandescent and compact fluorescent lamps (CFLs). Drawing from the Part 1 findings, Part 2 performed a more detailed assessment of the LED manufacturing process and used these findings to provide a comparative LCA taking into consideration a wider range of environmental impacts. Both reports concluded that the life-cycle environmental impact of a given lamp is dominated by the energy used during lamp operation—the upstream generation of electricity drives the total environmental footprint of the product. However, a more detailed understanding of end-of-life disposal considerations for LED products has become increasingly important as their installation base has grown. The Part 3 study (reported herein) was undertaken to augment the LCA findings with chemical analysis of a variety of LED, CFL, and incandescent lamps using standard testing procedures. A total of 22 samples, representing 11 different models, were tested to determine whether any of 17 elements were present at levels exceeding California or Federal regulatory thresholds for hazardous waste. Key findings include: • The selected models were generally found to be below thresholds for Federally regulated elements; • All CFLs and LED lamps and most incandescent lamps exceeded California thresholds for Copper; • Most CFL samples exceeded California thresholds for Antimony and Nickel, and half of the LED samples exceeded California thresholds for Zinc; • The greatest contributors were the screw bases, drivers, ballasts, and wires or filaments; • Overall concentrations in LED lamps were comparable to cell phones and other types of electronic devices, and were generally attributable to components other than the internal LED light sources; • Although the life-cycle environmental impact of the LED lamps is favorable when compared to CFLs and incandescent lamps, recycling will likely gain importance as consumer adoption increases. This study was exploratory in nature and was not intended to provide a definitive indication of regulatory compliance for any specific lamp model or technology. Further study would be needed to more broadly characterize the various light source technologies; to more accurately and precisely characterize a specific model; or to determine whether product redesign would be appropriate.« less

Reevaluation of 1999 Health-Based Environmental Screening Levels (HBESLs) for Chemical Warfare Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watson, Annetta Paule; Dolislager, Fredrick G

2007-05-01

This report evaluates whether new information and updated scientific models require that changes be made to previously published health-based environmental soil screening levels (HBESLs) and associated environmental fate/breakdown information for chemical warfare agents (USACHPPM 1999). Specifically, the present evaluation describes and compares changes that have been made since 1999 to U.S. Environmental Protection Agency (EPA) risk assessment models, EPA exposure assumptions, as well as to specific chemical warfare agent parameters (e.g., toxicity values). Comparison was made between screening value estimates recalculated with current assumptions and earlier health-based environmental screening levels presented in 1999. The chemical warfare agents evaluated include themore » G-series and VX nerve agents and the vesicants sulfur mustard (agent HD) and Lewisite (agent L). In addition, key degradation products of these agents were also evaluated. Study findings indicate that the combined effect of updates and/or changes to EPA risk models, EPA default exposure parameters, and certain chemical warfare agent toxicity criteria does not result in significant alteration to the USACHPPM (1999) health-based environmental screening level estimates for the G-series and VX nerve agents or the vesicant agents HD and L. Given that EPA's final position on separate Tier 1 screening levels for indoor and outdoor worker screening assessments has not yet been released as of May 2007, the study authors find that the 1999 screening level estimates (see Table ES.1) are still appropriate and protective for screening residential as well as nonresidential sites. As such, risk management decisions made on the basis of USACHPPM (1999) recommendations do not require reconsideration. While the 1999 HBESL values are appropriate for continued use as general screening criteria, the updated '2007' estimates (presented below) that follow the new EPA protocols currently under development are also protective. When EPA finalizes and documents a position on the matter of indoor and outdoor worker screening assessments, site-specific risk assessments should make use of modified models and criteria. Screening values such as those presented in this report may be used to assess soil or other porous media to determine whether chemical warfare agent contamination is present as part of initial site investigations (whether due to intentional or accidental releases) and to determine whether weather/decontamination has adequately mitigated the presence of agent residual to below levels of concern. However, despite the availability of scientifically supported health-based criteria, there are significant resources needs that should be considered during sample planning. In particular, few analytical laboratories are likely to be able to meet these screening levels. Analyses will take time and usually have limited confidence at these concentrations. Therefore, and particularly for the more volatile agents, soil/destructive samples of porous media should be limited and instead enhanced with headspace monitoring and presence-absence wipe sampling.« less

Symbolic Beliefs as Barriers to Responsible Environmental Behavior.

ERIC Educational Resources Information Center

Jurin, Richard R.; Fortner, Rosane W.

2002-01-01

Presents an exploratory study that investigates how environmental beliefs relate to self-reported environmental behaviors. Includes a student sample (N=110) which was administered a 208-item instrument. Reports that based on survey results, most of the sample perceived themselves as environmentally aware and differed only in strength of attitudes.…

[Effects of environmental factors on β diversity of zooplankton community in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay, Zhejiang, China].

PubMed

Zhu, Yi-feng; Dai, Mei-xia; Zhou, Xiao-hong; Lin, Xia; Mao, Shuo-qian; Yan, Xiao-jun

2015-08-01

Zooplankton samples were seasonally collected at 10 stations in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay. The abundance data from these samples were pooled and further combined with field environmental factors, then generalised dissimilarity modelling (GDM) was used to explore the effects of environmental factors on β diversity of zooplankton community. The results showed that altogether 95 species of zooplankton belonging to 14 taxa were found. In these taxa, small zooplankton with 62.6% of abundance was the main taxa, while copepods dominated in adult groups, which abundance accounted for 35.3%. According to Whittaker's definition and additive partition, a diversity accounted for 36.3% and β diversity 63.7%. Environmental factors explained 43.8% of β diversity, and geographical distance between sampling sites had no effect on β diversity. However, there were still 19.9% of β diversity remained to be explained. After GDM fitting, there were nine environmental variables affecting zooplankton β diversity and explaining 68.8% of β diversity. The variables contributing to β diversity from high to low were seasonal water temperature, dissolved oxygen, seawater temperature increment, conductivity, suspended particulate matter, salinity, transparency, water depth and redox potential, respectively. Seasonal water temperature, dissolved oxygen and seawater temperature increment were the most important factors for driving β diversity changes, and accounted for 23.9%, 13.7% and 9.7% of absolute contribution to the interpretable portion of the β diversity, respectively. When seasonal water temperature, dissolved oxygen and seawater temperature increment were below 25 °C, greater than 5 mg · L(-1) and over 1 °C, respectively, β diversity rapidly increased with the increasing variable gradients. Furthermore, other predictors had little effect on β diversity.

[Environmental geochemical baseline of heavy metals in soils of the Ili river basin and pollution evaluation].

PubMed

Zhao, Xin-Ru; Nasier, Telajin; Cheng, Yong-Yi; Zhan, Jiang-Yu; Yang, Jian-Hong

2014-06-01

Environmental geochemical baseline models of Cu, Zn, Pb, As, Hg were established by standardized method in the ehernozem, chestnut soil, sierozem and saline soil from the Ili river valley region. The theoretical baseline values were calculated. Baseline factor pollution index evaluation method, environmental background value evaluation method and heavy metal cleanliness evaluation method were used to compare soil pollution degrees. The baseline factor pollution index evaluation showed that As pollution was the most prominent among the four typical types of soils within the river basin, with 7.14%, 9.76%, 7.50% of sampling points in chernozem, chestnut soil and sierozem reached the heavy pollution, respectively. 7.32% of sampling points of chestnut soil reached the permitted heavy metal Pb pollution index in the chestnut soil. The variation extent of As and Pb was the largest, indicating large human disturbance. Environmental background value evaluation showed that As was the main pollution element, followed by Cu, Zn and Pb. Heavy metal cleanliness evaluation showed that Cu, Zn and Pb were better than cleanliness level 2 and Hg was the of cleanliness level 1 in all four types of soils. As showed moderate pollution in sierozem, and it was of cleanliness level 2 or better in chernozem, chestnut soil and saline-alkali soil. Comparing the three evaluation systems, the baseline factor pollution index evaluation more comprehensively reflected the geochemical migration characteristics of elements and the soil formation processes, and the pollution assessment could be specific to the sampling points. The environmental background value evaluation neglected the natural migration of heavy metals and the deposition process in the soil since it was established on the regional background values. The main purpose of the heavy metal cleanliness evaluation was to evaluate the safety degree of soil environment.

Landscape and meteorological factors affecting prevalence of three food-borne pathogens in fruit and vegetable farms.

PubMed

Strawn, Laura K; Fortes, Esther D; Bihn, Elizabeth A; Nightingale, Kendra K; Gröhn, Yrjö T; Worobo, Randy W; Wiedmann, Martin; Bergholz, Peter W

2013-01-01

Produce-related outbreaks have been traced back to the preharvest environment. A longitudinal study was conducted on five farms in New York State to characterize the prevalence, persistence, and diversity of food-borne pathogens in fresh produce fields and to determine landscape and meteorological factors that predict their presence. Produce fields were sampled four times per year for 2 years. A total of 588 samples were analyzed for Listeria monocytogenes, Salmonella, and Shiga toxin-producing Escherichia coli (STEC). The prevalence measures of L. monocytogenes, Salmonella, and STEC were 15.0, 4.6, and 2.7%, respectively. L. monocytogenes and Salmonella were detected more frequently in water samples, while STEC was detected with equal frequency across all sample types (soil, water, feces, and drag swabs). L. monocytogenes sigB gene allelic types 57, 58, and 61 and Salmonella enterica serovar Cerro were repeatedly isolated from water samples. Soil available water storage (AWS), temperature, and proximity to three land cover classes (water, roads and urban development, and pasture/hay grass) influenced the likelihood of detecting L. monocytogenes. Drainage class, AWS, and precipitation were identified as important factors in Salmonella detection. This information was used in a geographic information system framework to hypothesize locations of environmental reservoirs where the prevalence of food-borne pathogens may be elevated. The map indicated that not all croplands are equally likely to contain environmental reservoirs of L. monocytogenes. These findings advance recommendations to minimize the risk of preharvest contamination by enhancing models of the environmental constraints on the survival and persistence of food-borne pathogens in fields.

Landscape and Meteorological Factors Affecting Prevalence of Three Food-Borne Pathogens in Fruit and Vegetable Farms

PubMed Central

Strawn, Laura K.; Fortes, Esther D.; Bihn, Elizabeth A.; Nightingale, Kendra K.; Gröhn, Yrjö T.; Worobo, Randy W.; Wiedmann, Martin

2013-01-01

Produce-related outbreaks have been traced back to the preharvest environment. A longitudinal study was conducted on five farms in New York State to characterize the prevalence, persistence, and diversity of food-borne pathogens in fresh produce fields and to determine landscape and meteorological factors that predict their presence. Produce fields were sampled four times per year for 2 years. A total of 588 samples were analyzed for Listeria monocytogenes, Salmonella, and Shiga toxin-producing Escherichia coli (STEC). The prevalence measures of L. monocytogenes, Salmonella, and STEC were 15.0, 4.6, and 2.7%, respectively. L. monocytogenes and Salmonella were detected more frequently in water samples, while STEC was detected with equal frequency across all sample types (soil, water, feces, and drag swabs). L. monocytogenes sigB gene allelic types 57, 58, and 61 and Salmonella enterica serovar Cerro were repeatedly isolated from water samples. Soil available water storage (AWS), temperature, and proximity to three land cover classes (water, roads and urban development, and pasture/hay grass) influenced the likelihood of detecting L. monocytogenes. Drainage class, AWS, and precipitation were identified as important factors in Salmonella detection. This information was used in a geographic information system framework to hypothesize locations of environmental reservoirs where the prevalence of food-borne pathogens may be elevated. The map indicated that not all croplands are equally likely to contain environmental reservoirs of L. monocytogenes. These findings advance recommendations to minimize the risk of preharvest contamination by enhancing models of the environmental constraints on the survival and persistence of food-borne pathogens in fields. PMID:23144137

Development and Evaluation of a Quantitative PCR Assay Targeting Sandhill Crane (Grus canadensis) Fecal Pollution

PubMed Central

Ryu, Hodon; Lu, Jingrang; Vogel, Jason; Elk, Michael; Chávez-Ramírez, Felipe; Ashbolt, Nicholas

2012-01-01

While the microbial water quality in the Platte River is seasonally impacted by excreta from migrating cranes, there are no methods available to study crane fecal contamination. Here we characterized microbial populations in crane feces using phylogenetic analysis of 16S rRNA gene fecal clone libraries. Using these sequences, a novel crane quantitative PCR (Crane1) assay was developed, and its applicability as a microbial source tracking (MST) assay was evaluated by determining its host specificity and detection ability in environmental waters. Bacteria from crane excreta were dominated by bacilli and proteobacteria, with a notable paucity of sequences homologous to Bacteroidetes and Clostridia. The Crane1 marker targeted a dominant clade of unclassified Lactobacillales sequences closely related to Catellicoccus marimammalium. The host distribution of the Crane1 marker was relatively high, being positive for 69% (66/96) of the crane excreta samples tested. The assay also showed high host specificity, with 95% of the nontarget fecal samples (i.e., n = 553; 20 different free-range hosts) being negative. Of the presumed crane-impacted water samples (n = 16), 88% were positive for the Crane1 assay, whereas none of the water samples not impacted by cranes were positive (n = 165). Bayesian statistical models of the Crane1 MST marker demonstrated high confidence in detecting true-positive signals and a low probability of false-negative signals from environmental water samples. Altogether, these data suggest that the newly developed marker could be used in environmental monitoring studies to study crane fecal pollution dynamics. PMID:22492437

A Survey of Current Literature on Sampling, Sample Handling, and Long Term Storage for Environmental Materials.

ERIC Educational Resources Information Center

Maienthal, E. J.; Becker, D. A.

This report presents the results of an extensive literature survey undertaken to establish optimum sampling, sample handling and long-term storage techniques for a wide variety of environmental samples to retain sample integrity. The components of interest are trace elements, organics, pesticides, radionuclides and microbiologicals. A bibliography…

Genetic and Environmental Influences on Female Sexual Orientation, Childhood Gender Typicality and Adult Gender Identity

PubMed Central

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Background Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates – childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Methodology/Principal Findings Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. Conclusions/Significance This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation. PMID:21760939

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

DOE PAGES

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

2016-01-01

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

Genetic and environmental influences on adolescents' smoking involvement: a multi-informant twin study.

PubMed

Seglem, Karoline Brobakke; Waaktaar, Trine; Ask, Helga; Torgersen, Svenn

2015-03-01

Studying monozygotic and dizygotic adolescent twin pairs of both sexes reared together, the present study examined the extent to which the variance in smoking involvement is attributable to genetic and environmental effects, and to what extent there are sex differences in the etiology. Questionnaire data on how often the adolescent had ever smoked tobacco was collected from a population-based twin sample consisting of seven national birth cohorts (ages 12-18), their mothers, and their fathers (N = 1,394 families). The data was analyzed with multivariate genetic modeling, using a multi-informant design. The etiological structure of smoking involvement was best represented in an ACE common pathway model, with smoking defined as a latent factor loading onto all three informants' reports. Estimates could be set equal across sexes. Results showed that adolescent lifetime smoking involvement was moderately heritable (37 %). The largest influence was from the shared environment (56 %), while environmental effects unique to each twin had minimal influence (7 %).

Appraisal of jump distributions in ensemble-based sampling algorithms

NASA Astrophysics Data System (ADS)

Dejanic, Sanda; Scheidegger, Andreas; Rieckermann, Jörg; Albert, Carlo

2017-04-01

Sampling Bayesian posteriors of model parameters is often required for making model-based probabilistic predictions. For complex environmental models, standard Monte Carlo Markov Chain (MCMC) methods are often infeasible because they require too many sequential model runs. Therefore, we focused on ensemble methods that use many Markov chains in parallel, since they can be run on modern cluster architectures. Little is known about how to choose the best performing sampler, for a given application. A poor choice can lead to an inappropriate representation of posterior knowledge. We assessed two different jump moves, the stretch and the differential evolution move, underlying, respectively, the software packages EMCEE and DREAM, which are popular in different scientific communities. For the assessment, we used analytical posteriors with features as they often occur in real posteriors, namely high dimensionality, strong non-linear correlations or multimodality. For posteriors with non-linear features, standard convergence diagnostics based on sample means can be insufficient. Therefore, we resorted to an entropy-based convergence measure. We assessed the samplers by means of their convergence speed, robustness and effective sample sizes. For posteriors with strongly non-linear features, we found that the stretch move outperforms the differential evolution move, w.r.t. all three aspects.

Variations in the offence actions of deliberate firesetters: a cross-national analysis.

PubMed

Fritzon, Katarina; Doley, Rebekah; Hollows, Kerrilee

2014-10-01

Since Canter and Fritzon first introduced their "4D" classification system for arson, many studies have replicated the model with samples of arsonists from around the world. However, scholars have reported differences in the offence actions of arsonists across samples. No study as yet has attempted to statically examine the relevance of these differences. Using multidimensional scaling procedures and two-way chi-square contingency analyses, this study examined whether cross-national differences in arson variables existed between Australian and British arsonists. The results indicated that differences did exist and, furthermore, that differences reflected the environmental characteristics of the country from which each sample was drawn. These findings have important theoretical and clinical implications, particularly for the utility of the "4D" model as an investigatory tool and for the wider arson profiling literature. © The Author(s) 2013.

Are polychlorinated biphenyl residues adequately describe by aroclor mixture equivalents. Isomer-specific principal components analysis of such residues in fish and turtles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwartz, T.R.; Stalling, D.L.; Rice, C.L.

1987-01-01

Polychlorinated biphenyl (PCB) residues from fish and turtles were analyzed with SIMCA (Soft Independent Modeling of Class Analogy), a principal components analysis technique. A series of technical Aroclors were also analyzed to provide a reference data set for pattern recognition. Environmental PCB residues are often expressed in terms of relative Aroclor composition. In this work, we assessed the similarity of Aroclors to class models derived for fish and turtles to ascertain if the PCB residues in the samples could be described by an Aroclor or Aroclor mixture. Using PCA, we found that these samples could not be described by anmore » Aroclor or Aroclor mixture and that it would be inappropriate to report these samples as such. 18 references, 3 figures, 3 tables.« less

Differential Susceptibility and the Early Development of Aggression: Interactive Effects of Respiratory Sinus Arrhythmia and Environmental Quality

PubMed Central

Eisenberg, Nancy; Sulik, Michael J.; Spinrad, Tracy L.; Edwards, Alison; Eggum, Natalie D.; Liew, Jeffrey; Sallquist, Julie; Popp, Tierney K.; Smith, Cynthia L.; Hart, Daniel

2012-01-01

The purpose of the current study was to predict the development of aggressive behavior from young children’s respiratory sinus arrhythmia (RSA) and environmental quality. In a longitudinal sample of 213 children, baseline RSA, RSA suppression in response to a film of crying babies, and a composite measure of environmental quality (incorporating socioeconomic status and marital adjustment) were measured, and parent-reported aggression was assessed from 18 to 54 months of age. Predictions based on biological sensitivity-to-context/differential susceptibility and diathesis-stress models, as well as potential moderation by child sex, were examined. The interaction of baseline RSA with environmental quality predicted the development (slope) and 54-month intercept of mothers’ reports of aggression. For girls only, the interaction between baseline RSA and environmental quality predicted the 18-month intercept of fathers’ reports. In general, significant negative relations between RSA and aggression were found primarily at high levels of environmental quality. In addition, we found a significant Sex × RSA interaction predicting the slope and 54-month intercept of fathers’ reports of aggression, such that RSA was negatively related to aggression for boys but not for girls. Contrary to predictions, no significant main effects or interactions were found for RSA suppression. The results provide mixed but not full support for differential susceptibility theory and provide little support for the diathesis-stress model. PMID:22182294

Monitoring bacterial indicators of water quality in a tidally influenced delta: A Sisyphean pursuit.

PubMed

Partyka, Melissa L; Bond, Ronald F; Chase, Jennifer A; Atwill, Edward R

2017-02-01

The Sacramento-San Joaquin Delta Estuary (Delta) is the confluence of two major watersheds draining the Western Sierra Nevada mountains into the Central Valley of California, ultimately terminating into San Francisco Bay. We sampled 88 sites once a month for two years (2006-2008) over 87 separate sampling events for a total of 1740 samples. Water samples were analyzed for fecal indicator bacteria (Escherichia coli, enterococci and fecal coliforms), and 53 other physiochemical, land use, and environmental characteristics. The purpose of the study was to create a baseline of microbial water quality in the Delta and to identify various factors (climatic, land use, tidal, etc.) that were associated with elevated concentrations of indicator bacteria. Fecal indicator bacteria generally had weak to modest relationships to environmental conditions; the strength and direction of which varied for each microbial indicator, drainage region, and across seasons. Measured and unmeasured, site-specific effects accounted for large portions of variance in model predictions (ρ=0.086 to 0.255), indicating that spatial autocorrelation was a major component of water quality outcomes. The effects of tidal cycling and lack of connectivity between waterways and surrounding landscapes likely contributed to the lack of association between local land uses and microbial outcomes, though weak associations may also be indicative of mismatched spatiotemporal scales. The complex nature of this system necessitates continued monitoring and regular updates to statistical models designed to predict microbial water quality. Copyright © 2016 Elsevier B.V. All rights reserved.

Archaeal β diversity patterns under the seafloor along geochemical gradients

NASA Astrophysics Data System (ADS)

Koyano, Hitoshi; Tsubouchi, Taishi; Kishino, Hirohisa; Akutsu, Tatsuya

2014-09-01

Recently, deep drilling into the seafloor has revealed that there are vast sedimentary ecosystems of diverse microorganisms, particularly archaea, in subsurface areas. We investigated the β diversity patterns of archaeal communities in sediment layers under the seafloor and their determinants. This study was accomplished by analyzing large environmental samples of 16S ribosomal RNA gene sequences and various geochemical data collected from a sediment core of 365.3 m, obtained by drilling into the seafloor off the east coast of the Shimokita Peninsula. To extract the maximum amount of information from these environmental samples, we first developed a method for measuring β diversity using sequence data by applying probability theory on a set of strings developed by two of the authors in a previous publication. We introduced an index of β diversity between sequence populations from which the sequence data were sampled. We then constructed an estimator of the β diversity index based on the sequence data and demonstrated that it converges to the β diversity index between sequence populations with probability of 1 as the number of sampled sequences increases. Next, we applied this new method to quantify β diversities between archaeal sequence populations under the seafloor and constructed a quantitative model of the estimated β diversity patterns. Nearly 90% of the variation in the archaeal β diversity was explained by a model that included as variables the differences in the abundances of chlorine, iodine, and carbon between the sediment layers.

Widespread covariation of early environmental exposures and trait-associated polygenic variation.

PubMed

Krapohl, E; Hannigan, L J; Pingault, J-B; Patel, H; Kadeva, N; Curtis, C; Breen, G; Newhouse, S J; Eley, T C; O'Reilly, P F; Plomin, R

2017-10-31

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample ( n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age ( R 2 = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding ( R 2 = 0.021; P = 7e-30), maternal smoking during pregnancy ( R 2 = 0.008; P = 5e-13), parental smacking ( R 2 = 0.01; P = 4e-15), household income ( R 2 = 0.032; P = 1e-22), watching television ( R 2 = 0.034; P = 5e-47), and maternal education ( R 2 = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.

Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model

DTIC Science & Technology

2014-09-01

Leaf-Off Tree Crowns in Small Footprint, High Sampling Density LIDAR Data from Eastern Deciduous Forests in North America.” Remote Sensing of...William A. 2003. “Crown-Diameter Prediction Models for 87 Species of Stand- Grown Trees in the Eastern United States.” Southern Journal of Applied...ER D C/ CE RL T R- 14 -1 8 Base Facilities Environmental Quality Remote Sensing Protocols for Parameterizing an Individual, Tree -Based

Oxygen decline in biotesting of environmental samples--is there a need for consideration in the acute zebrafish embryo assay?

PubMed

Küster, Eberhard; Altenburger, Rolf

2008-12-01

Environmental samples such as groundwater, sediment pore water, native or freeze dried sediments may be difficult to analyze for toxic effects with organismic aquatic bioassays. These samples might evoke low oxygen concentration or oxygen depletion during the test. The toxicity assessment could thus be confounded by low oxygen concentrations. The acute zebrafish embryo assay was used to analyze the influence of oxygen deficit on the embryonic development in the first 48 h post fertilization. Embryos were exposed to varying oxygen concentrations ranging from <30 to >80% oxygen saturation of water. A clear concentration dependent retardation of fish embryo development was observed. Because of a retarded development toxic thresholds of environmental samples which might include substances slowing down the development will be altered. For the purpose of identification of critical contaminants in complex environmental samples, it is proposed to actively aerate environmental samples which are likely to be oxygen depleted during the duration of the zebrafish embryo bioassay. 2008 Wiley Periodicals, Inc.

Assessing time-integrated dissolved concentrations and predicting toxicity of metals during diel cycling in streams

USGS Publications Warehouse

Balistrieri, Laurie S.; Nimick, David A.; Mebane, Christopher A.

2012-01-01

Evaluating water quality and the health of aquatic organisms is challenging in systems with systematic diel (24 hour) or less predictable runoff-induced changes in water composition. To advance our understanding of how to evaluate environmental health in these dynamic systems, field studies of diel cycling were conducted in two streams (Silver Bow Creek and High Ore Creek) affected by historical mining activities in southwestern Montana. A combination of sampling and modeling tools were used to assess the toxicity of metals in these systems. Diffusive Gradients in Thin Films (DGT) samplers were deployed at multiple time intervals during diel sampling to confirm that DGT integrates time-varying concentrations of dissolved metals. Thermodynamic speciation calculations using site specific water compositions, including time-integrated dissolved metal concentrations determined from DGT, and a competitive, multiple-metal biotic ligand model incorporated into the Windemere Humic Aqueous Model Version 6.0 (WHAM VI) were used to determine the chemical speciation of dissolved metals and biotic ligands. The model results were combined with previously collected toxicity data on cutthroat trout to derive a relationship that predicts the relative survivability of these fish at a given site. This integrative approach may prove useful for assessing water quality and toxicity of metals to aquatic organisms in dynamic systems and evaluating whether potential changes in environmental health of aquatic systems are due to anthropogenic activities or natural variability.

Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.

Mercury speciation and distribution in a glacierized mountain environment and their relevance to environmental risks in the inland Tibetan Plateau.

PubMed

Sun, Xuejun; Zhang, Qianggong; Kang, Shichang; Guo, Junming; Li, Xiaofei; Yu, Zhengliang; Zhang, Guoshuai; Qu, Dongmei; Huang, Jie; Cong, Zhiyuan; Wu, Guangjian

2018-08-01

Glacierized mountain environments can preserve and release mercury (Hg) and play an important role in regional Hg biogeochemical cycling. However, the behavior of Hg in glacierized mountain environments and its environmental risks remain poorly constrained. In this research, glacier meltwater, runoff and wetland water were sampled in Zhadang-Qugaqie basin (ZQB), a typical glacierized mountain environment in the inland Tibetan Plateau, to investigate Hg distribution and its relevance to environmental risks. The total mercury (THg) concentrations ranged from 0.82 to 6.98ng·L -1 , and non-parametric pairwise multiple comparisons of the THg concentrations among the three different water samples showed that the THg concentrations were comparable. The total methylmercury (TMeHg) concentrations ranged from 0.041 to 0.115ng·L -1 , and non-parametric pairwise multiple comparisons of the TMeHg concentrations showed a significant difference. Both the THg and MeHg concentrations of water samples from the ZQB were comparable to those of other remote areas, indicating that Hg concentrations in the ZQB watershed are equivalent to the global background level. Particulate Hg was the predominant form of Hg in all runoff samples, and was significantly correlated with the total suspended particle (TSP) and not correlated with the dissolved organic carbon (DOC) concentration. The distribution of mercury in the wetland water differed from that of the other water samples. THg exhibited a significant correlation with DOC as well as TMeHg, whereas neither THg nor TMeHg was associated with TSP. Based on the above findings and the results from previous work, we propose a conceptual model illustrating the four Hg distribution zones in glacierized environments. We highlight that wetlands may enhance the potential hazards of Hg released from melting glaciers, making them a vital zone for investigating the environmental effects of Hg in glacierized environments and beyond. Copyright © 2018 Elsevier B.V. All rights reserved.

Surface Environmental Surveillance Project: Locations Manual Volume 1 – Air and Water Volume 2 – Farm Products, Soil & Vegetation, and Wildlife

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, Brad G.; Patton, Gregory W.; Stegen, Amanda

2009-01-01

This report describes all environmental monitoring locations associated with the Surface Environmental Surveillance Project. Environmental surveillance of the Hanford site and surrounding areas is conducted by the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy (DOE). Sampling is conducted to evaluate levels of radioactive and nonradioactive pollutants in the Hanford environs, as required in DOE Order 450.1, Environmental Protection Program, and DOE Order 5400.5, Radiation Protection of the Public and the Environment. The environmental surveillance sampling design is described in the Hanford Site Environmental Monitoring Plan, United States Department of Energy, Richland Operation Office (DOE/RL-91-50). This documentmore » contains the locations of sites used to collect samples for the Surface Environmental Surveillance Project (SESP). Each section includes directions, maps, and pictures of the locations. A general knowledge of roads and highways on and around the Hanford Site is necessary to successfully use this manual. Supplemental information (Maps, Gazetteer, etc.) may be necessary if user is unfamiliar with local routes. The SESP is a multimedia environmental surveillance effort to measure the concentrations of radionuclides and chemicals in environmental media to demonstrate compliance with applicable environmental quality standards and public exposure limits, and assessing environmental impacts. Project personnel annually collect selected samples of ambient air, surface water, agricultural products, fish, wildlife, and sediments. Soil and vegetation samples are collected approximately every 5 years. Analytical capabilities include the measurement of radionuclides at very low environmental concentrations and, in selected media, nonradiological chemicals including metals, anions, volatile organic compounds, and total organic carbon.« less

Fish biomarkers for environmental monitoring: An integrated model supporting enzyme activity and histopathological lesions

NASA Astrophysics Data System (ADS)

Neta, Raimunda Nonata Fortes Carvalho; Torres Junior, Audalio Rebelo

2014-10-01

We present a mathematical model describing the association between glutathione-S-transferase activity and brachial lesions in the catfish, Sciades herzbergii (Ariidae) from a polluted port. The catfish were sampled from a port known to be contaminated with heavy metals and organic compounds and from a natural reserve in São Marcos Bay, Brazil. Two biomarkers, hepatic glutathione S-transferase (GST) activity and histopathological lesions, in gills tissue were measured. The values for GST activity were modeled with the occurrence of branchial lesions by fitting a third order polynomial. Results from the mathematical model indicate that GST activity has a strong polynomial relationship with the occurrence of branchial lesions in both the wet and the dry seasons, but only at the polluted port site. The model developed in this study indicates that branchial and hepatic lesions are initiated when GST activity reaches 2.15 μmol min-1 mg protein-1. Beyond this limit, GST activity decreased to very low levels and irreversible histopathological lesions occurred. This mathematical model provides a realistic approach to analyze predictive biomarkers of environmental health status.

Caveats for correlative species distribution modeling

USGS Publications Warehouse

Jarnevich, Catherine S.; Stohlgren, Thomas J.; Kumar, Sunil; Morisette, Jeffrey T.; Holcombe, Tracy R.

2015-01-01

Correlative species distribution models are becoming commonplace in the scientific literature and public outreach products, displaying locations, abundance, or suitable environmental conditions for harmful invasive species, threatened and endangered species, or species of special concern. Accurate species distribution models are useful for efficient and adaptive management and conservation, research, and ecological forecasting. Yet, these models are often presented without fully examining or explaining the caveats for their proper use and interpretation and are often implemented without understanding the limitations and assumptions of the model being used. We describe common pitfalls, assumptions, and caveats of correlative species distribution models to help novice users and end users better interpret these models. Four primary caveats corresponding to different phases of the modeling process, each with supporting documentation and examples, include: (1) all sampling data are incomplete and potentially biased; (2) predictor variables must capture distribution constraints; (3) no single model works best for all species, in all areas, at all spatial scales, and over time; and (4) the results of species distribution models should be treated like a hypothesis to be tested and validated with additional sampling and modeling in an iterative process.

On estimating probability of presence from use-availability or presence-background data.

PubMed

Phillips, Steven J; Elith, Jane

2013-06-01

A fundamental ecological modeling task is to estimate the probability that a species is present in (or uses) a site, conditional on environmental variables. For many species, available data consist of "presence" data (locations where the species [or evidence of it] has been observed), together with "background" data, a random sample of available environmental conditions. Recently published papers disagree on whether probability of presence is identifiable from such presence-background data alone. This paper aims to resolve the disagreement, demonstrating that additional information is required. We defined seven simulated species representing various simple shapes of response to environmental variables (constant, linear, convex, unimodal, S-shaped) and ran five logistic model-fitting methods using 1000 presence samples and 10 000 background samples; the simulations were repeated 100 times. The experiment revealed a stark contrast between two groups of methods: those based on a strong assumption that species' true probability of presence exactly matches a given parametric form had highly variable predictions and much larger RMS error than methods that take population prevalence (the fraction of sites in which the species is present) as an additional parameter. For six species, the former group grossly under- or overestimated probability of presence. The cause was not model structure or choice of link function, because all methods were logistic with linear and, where necessary, quadratic terms. Rather, the experiment demonstrates that an estimate of prevalence is not just helpful, but is necessary (except in special cases) for identifying probability of presence. We therefore advise against use of methods that rely on the strong assumption, due to Lele and Keim (recently advocated by Royle et al.) and Lancaster and Imbens. The methods are fragile, and their strong assumption is unlikely to be true in practice. We emphasize, however, that we are not arguing against standard statistical methods such as logistic regression, generalized linear models, and so forth, none of which requires the strong assumption. If probability of presence is required for a given application, there is no panacea for lack of data. Presence-background data must be augmented with an additional datum, e.g., species' prevalence, to reliably estimate absolute (rather than relative) probability of presence.

Ocean Observing Public-Private Collaboration to Improve Tropical Storm and Hurricane Predictions in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Perry, R.; Leung, P.; McCall, W.; Martin, K. M.; Howden, S. D.; Vandermeulen, R. A.; Kim, H. S. S.; Kirkpatrick, B. A.; Watson, S.; Smith, W.

2016-02-01

In 2008, Shell partnered with NOAA to explore opportunities for improving storm predictions in the Gulf of Mexico. Since, the collaboration has grown to include partners from Shell, NOAA National Data Buoy Center and National Center for Environmental Information, National Center for Environmental Prediction, University of Southern Mississippi, and the Gulf of Mexico Coastal Ocean Observing System. The partnership leverages complementary strengths of each collaborator to build a comprehensive and sustainable monitoring and data program to expand observing capacity and protect offshore assets and Gulf communities from storms and hurricanes. The program combines in situ and autonomous platforms with remote sensing and numerical modeling. Here we focus on profiling gliders and the benefits of a public-private partnership model for expanding regional ocean observing capacity. Shallow and deep gliders measure ocean temperature to derive ocean heat content (OHC), along with salinity, dissolved oxygen, fluorescence, and CDOM, in the central and eastern Gulf shelf and offshore. Since 2012, gliders have collected 4500+ vertical profiles and surveyed 5000+ nautical miles. Adaptive sampling and mission coordination with NCEP modelers provides specific datasets to assimilate into EMC's coupled HYCOM-HWRF model and 'connect-the-dots' between well-established Eulerian metocean measurements by obtaining (and validating) data between fixed stations (e.g. platform and buoy ADCPs) . Adaptive sampling combined with remote sensing provides satellite-derived OHC validation and the ability to sample productive coastal waters advected offshore by the Loop Current. Tracking coastal waters with remote sensing provides another verification of estimate Loop Current and eddy boundaries, as well as quantifying productivity and analyzing water quality on the Gulf coast, shelf break and offshore. Incorporating gliders demonstrates their value as tools to better protect offshore oil and gas assets and the greater Gulf coast communities from storms and hurricanes. Data collected under the collaboration, along with deployment of gliders, will have long-term benefits in helping to understand the ecological and environmental health of the Gulf by monitoring real-time annual and seasonal physical variability.

Environmental DNA as a ‘Snapshot’ of Fish Distribution: A Case Study of Japanese Jack Mackerel in Maizuru Bay, Sea of Japan

PubMed Central

Takahashi, Kohji; Sawada, Hideki; Murakami, Hiroaki; Tsuji, Satsuki; Hashizume, Hiroki; Kubonaga, Shou; Horiuchi, Tomoya; Hongo, Masamichi; Nishida, Jo; Okugawa, Yuta; Fujiwara, Ayaka; Fukuda, Miho; Hidaka, Shunsuke; Suzuki, Keita W.; Miya, Masaki; Araki, Hitoshi; Yamanaka, Hiroki; Maruyama, Atsushi; Miyashita, Kazushi; Masuda, Reiji; Minamoto, Toshifumi; Kondoh, Michio

2016-01-01

Recent studies in streams and ponds have demonstrated that the distribution and biomass of aquatic organisms can be estimated by detection and quantification of environmental DNA (eDNA). In more open systems such as seas, it is not evident whether eDNA can represent the distribution and biomass of aquatic organisms because various environmental factors (e.g., water flow) are expected to affect eDNA distribution and concentration. To test the relationships between the distribution of fish and eDNA, we conducted a grid survey in Maizuru Bay, Sea of Japan, and sampled surface and bottom waters while monitoring biomass of the Japanese jack mackerel (Trachurus japonicus) using echo sounder technology. A linear model showed a high R2 value (0.665) without outlier data points, and the association between estimated eDNA concentrations from the surface water samples and echo intensity was significantly positive, suggesting that the estimated spatial variation in eDNA concentration can reflect the local biomass of the jack mackerel. We also found that a best-fit model included echo intensity obtained within 10–150 m from water sampling sites, indicating that the estimated eDNA concentration most likely reflects fish biomass within 150 m in the bay. Although eDNA from a wholesale fish market partially affected eDNA concentration, we conclude that eDNA generally provides a ‘snapshot’ of fish distribution and biomass in a large area. Further studies in which dynamics of eDNA under field conditions (e.g., patterns of release, degradation, and diffusion of eDNA) are taken into account will provide a better estimate of fish distribution and biomass based on eDNA. PMID:26933889

Assessing the effects of regional payment for watershed services program on water quality using an intervention analysis model.

PubMed

Lu, Yan; He, Tian

2014-09-15

Much attention has been recently paid to ex-post assessments of socioeconomic and environmental benefits of payment for ecosystem services (PES) programs on poverty reduction, water quality, and forest protection. To evaluate the effects of a regional PES program on water quality, we selected chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) as indicators of water quality. Statistical methods and an intervention analysis model were employed to assess whether the PES program produced substantial changes in water quality at 10 water-quality sampling stations in the Shaying River watershed, China during 2006-2011. Statistical results from paired-sample t-tests and box plots of COD and NH3-N concentrations at the 10 stations showed that the PES program has played a positive role in improving water quality and reducing trans-boundary water pollution in the Shaying River watershed. Using the intervention analysis model, we quantitatively evaluated the effects of the intervention policy, i.e., the watershed PES program, on water quality at the 10 stations. The results suggest that this method could be used to assess the environmental benefits of watershed or water-related PES programs, such as improvements in water quality, seasonal flow regulation, erosion and sedimentation, and aquatic habitat. Copyright © 2014 Elsevier B.V. All rights reserved.

Fluorescence-based proxies for lignin in freshwater dissolved organic matter

USGS Publications Warehouse

Hernes, Peter J.; Bergamaschi, Brian A.; Eckard, Robert S.; Spencer, Robert G.M.

2009-01-01

Lignin phenols have proven to be powerful biomarkers in environmental studies; however, the complexity of lignin analysis limits the number of samples and thus spatial and temporal resolution in any given study. In contrast, spectrophotometric characterization of dissolved organic matter (DOM) is rapid, noninvasive, relatively inexpensive, requires small sample volumes, and can even be measured in situ to capture fine-scale temporal and spatial detail of DOM cycling. Here we present a series of cross-validated Partial Least Squares models that use fluorescence properties of DOM to explain up to 91% of lignin compositional and concentration variability in samples collected seasonally over 2 years in the Sacramento River/San Joaquin River Delta in California, United States. These models were subsequently used to predict lignin composition and concentration from fluorescence measurements collected during a diurnal study in the San Joaquin River. While modeled lignin composition remained largely unchanged over the diurnal cycle, changes in modeled lignin concentrations were much greater than expected and indicate that the sensitivity of fluorescence-based proxies for lignin may prove invaluable as a tool for selecting the most informative samples for detailed lignin characterization. With adequate calibration, similar models could be used to significantly expand our ability to study sources and processing of DOM in complex surface water systems.

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Robust estimates of environmental effects on population vital rates: an integrated capture–recapture model of seasonal brook trout growth, survival and movement in a stream network

USGS Publications Warehouse

Letcher, Benjamin H.; Schueller, Paul; Bassar, Ronald D.; Nislow, Keith H.; Coombs, Jason A.; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B.; Whiteley, Andrew R.; O'Donnell, Matthew J.; Dubreuil, Todd L.

2015-01-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall.These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful.

Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network.

PubMed

Letcher, Benjamin H; Schueller, Paul; Bassar, Ronald D; Nislow, Keith H; Coombs, Jason A; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B; Whiteley, Andrew R; O'Donnell, Matthew J; Dubreuil, Todd L

2015-03-01

Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses. We developed an integrated capture-recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival. We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature. Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative) in the summer and fall. These observations, combined with our ability to estimate the occurrence, magnitude and direction of fish movement between these habitat types, indicated that heterogeneity in response may provide a mechanism providing potential resilience to environmental change. Given that the challenges we faced in our study are likely to be common to many intensive data sets, the integrated modelling approach could be generally applicable and useful. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Characterization of Sheep Wool as a Sustainable Material for Acoustic Applications

PubMed Central

Uris, Antonio; Candelas, Pilar

2017-01-01

In recent years, natural materials are becoming a valid alternative to traditional sound absorbers due to reduced production costs and environmental protection. This paper reports the acoustical characterization of sheep wool. Measurements on normal incidence and diffuse-incidence sound absorption coefficients of different samples are reported. The airflow resistance has also been measured. The results prove that sheep wool has a comparable sound absorption performance to that of mineral wool or recycled polyurethane foam. An empirical model is used to calculate the sound absorption of sheep wool samples. A reasonable agreement on the acoustic absorption of all sheep wool samples is obtained. PMID:29112133

Characterization of Sheep Wool as a Sustainable Material for Acoustic Applications.

PubMed

Del Rey, Romina; Uris, Antonio; Alba, Jesús; Candelas, Pilar

2017-11-07

In recent years, natural materials are becoming a valid alternative to traditional sound absorbers due to reduced production costs and environmental protection. This paper reports the acoustical characterization of sheep wool. Measurements on normal incidence and diffuse-incidence sound absorption coefficients of different samples are reported. The airflow resistance has also been measured. The results prove that sheep wool has a comparable sound absorption performance to that of mineral wool or recycled polyurethane foam. An empirical model is used to calculate the sound absorption of sheep wool samples. A reasonable agreement on the acoustic absorption of all sheep wool samples is obtained.

Ecosystems Biology Approaches To Determine Key Fitness Traits of Soil Microorganisms

NASA Astrophysics Data System (ADS)

Brodie, E.; Zhalnina, K.; Karaoz, U.; Cho, H.; Nuccio, E. E.; Shi, S.; Lipton, M. S.; Zhou, J.; Pett-Ridge, J.; Northen, T.; Firestone, M.

2014-12-01

The application of theoretical approaches such as trait-based modeling represent powerful tools to explain and perhaps predict complex patterns in microbial distribution and function across environmental gradients in space and time. These models are mostly deterministic and where available are built upon a detailed understanding of microbial physiology and response to environmental factors. However as most soil microorganisms have not been cultivated, for the majority our understanding is limited to insights from environmental 'omic information. Information gleaned from 'omic studies of complex systems should be regarded as providing hypotheses, and these hypotheses should be tested under controlled laboratory conditions if they are to be propagated into deterministic models. In a semi-arid Mediterranean grassland system we are attempting to dissect microbial communities into functional guilds with defined physiological traits and are using a range of 'omics approaches to characterize their metabolic potential and niche preference. Initially, two physiologically relevant time points (peak plant activity and prior to wet-up) were sampled and metagenomes sequenced deeply (600-900 Gbp). Following assembly, differential coverage and nucleotide frequency binning were carried out to yield draft genomes. In addition, using a range of cultivation media we have isolated a broad range of bacteria representing abundant bacterial genotypes and with genome sequences of almost 40 isolates are testing genomic predictions regarding growth rate, temperature and substrate utilization in vitro. This presentation will discuss the opportunities and challenges in parameterizing microbial functional guilds from environmental 'omic information for use in trait-based models.

Environmental Dysfunctions, Childhood Maltreatment and Women's Intimate Partner Violence Victimization.

PubMed

Cascio, Maria Lo; Guarnaccia, Cinzia; Infurna, Maria Rita; Mancuso, Laura; Parroco, Anna Maria; Giannone, Francesca

2017-06-01

Childhood maltreatment is considered a crucial explanatory variable for intimate partner violence (IPV) in adulthood. However, a developmental multifactorial model for the etiology of IPV is not shared by researchers yet. This study has investigated the role of a wide range of childhood maltreatments and family and social dysfunctions in predicting IPV; furthermore, it tests a model where childhood maltreatment mediates the relationship between environmental dysfunctions and IPV. The sample included 78 women: IPV (38) and non-IPV (40). The Italian version of the Childhood Experience of Care and Abuse (CECA) Interview was used to assess the presence of adverse childhood experiences. The Revised Conflict Tactics Scale (CTS-2) and the IPV History Interview were used to assess IPV in the last year and lifetime, respectively. The results of a multivariate logistic regression model have indicated that only sexual (odds ratio [OR] = 4.24) and psychological (OR = 3.45) abuse significantly predicted IPV; with regard to association between IPV and environmental dysfunctions, only poor social support (OR = 8.91) significantly predicted IPV. The results of a mediation model have shown that childhood psychological and sexual abuse, in association with each other, partially mediate the relationship between poor social support and IPV. The findings from this study pinpoint poor social support as an important predictor of IPV so far neglected in the literature on the developmental antecedents of IPV. They also support the theoretical assumption according to which dysfunctional environmental variables and types of childhood maltreatment interacting with each other may influence development outcomes.

Impact of hydrogeological data on measures of uncertainty, site characterization and environmental performance metrics

NASA Astrophysics Data System (ADS)

de Barros, Felipe P. J.; Ezzedine, Souheil; Rubin, Yoram

2012-02-01

The significance of conditioning predictions of environmental performance metrics (EPMs) on hydrogeological data in heterogeneous porous media is addressed. Conditioning EPMs on available data reduces uncertainty and increases the reliability of model predictions. We present a rational and concise approach to investigate the impact of conditioning EPMs on data as a function of the location of the environmentally sensitive target receptor, data types and spacing between measurements. We illustrate how the concept of comparative information yield curves introduced in de Barros et al. [de Barros FPJ, Rubin Y, Maxwell R. The concept of comparative information yield curves and its application to risk-based site characterization. Water Resour Res 2009;45:W06401. doi:10.1029/2008WR007324] could be used to assess site characterization needs as a function of flow and transport dimensionality and EPMs. For a given EPM, we show how alternative uncertainty reduction metrics yield distinct gains of information from a variety of sampling schemes. Our results show that uncertainty reduction is EPM dependent (e.g., travel times) and does not necessarily indicate uncertainty reduction in an alternative EPM (e.g., human health risk). The results show how the position of the environmental target, flow dimensionality and the choice of the uncertainty reduction metric can be used to assist in field sampling campaigns.

The Bottlenose Dolphin (Tursiops truncatus) as a Model to Understand Variation in Stress and Reproductive Hormone Measures in Relation to Sampling Matrix, Demographics, and Environmental Factors

DTIC Science & Technology

2011-09-30

energy metabolism, suppression of immune and inflammatory reactions and inhibition of bone and muscle growth. Studies of both captive and free- ranging...Anemia, hypothyroidism and immune suppression associated with polychlorinated biphenyl exposure in bottlenose dolphins (Tursiops truncatus). Proc R

Persistence among Non-Traditional Hispanic College Students: A Causal Model. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Nora, Amaury; Kraemer, Barbara; Itzen, Richard

This study examined environmental and institutional factors affecting persistence of Hispanic college students. The sample of 324 first- and second-year students surveyed in the spring of 1995 included students who were enrolled in programs at a private, Illinois, bilingual junior college which were established to educate students who were older,…

Beginning School Math Competence: Minority and Majority Comparisons. Report No. 34.

ERIC Educational Resources Information Center

Entwisle, Doris R.; Alexander, Karl L.

This paper uses a structural model with a large random sample of urban children to explain children's competence in math concepts and computation at the time they begin first grade. These two aspects of math ability respond differently to environmental resources, with math concepts much more responsive to family factors before formal schooling…

Scanning electron microscopy coupled with energy-dispersive X-ray spectrometry for quick detection of sulfur-oxidizing bacteria in environmental water samples

NASA Astrophysics Data System (ADS)

Sun, Chengjun; Jiang, Fenghua; Gao, Wei; Li, Xiaoyun; Yu, Yanzhen; Yin, Xiaofei; Wang, Yong; Ding, Haibing

2017-01-01

Detection of sulfur-oxidizing bacteria has largely been dependent on targeted gene sequencing technology or traditional cell cultivation, which usually takes from days to months to carry out. This clearly does not meet the requirements of analysis for time-sensitive samples and/or complicated environmental samples. Since energy-dispersive X-ray spectrometry (EDS) can be used to simultaneously detect multiple elements in a sample, including sulfur, with minimal sample treatment, this technology was applied to detect sulfur-oxidizing bacteria using their high sulfur content within the cell. This article describes the application of scanning electron microscopy imaging coupled with EDS mapping for quick detection of sulfur oxidizers in contaminated environmental water samples, with minimal sample handling. Scanning electron microscopy imaging revealed the existence of dense granules within the bacterial cells, while EDS identified large amounts of sulfur within them. EDS mapping localized the sulfur to these granules. Subsequent 16S rRNA gene sequencing showed that the bacteria detected in our samples belonged to the genus Chromatium, which are sulfur oxidizers. Thus, EDS mapping made it possible to identify sulfur oxidizers in environmental samples based on localized sulfur within their cells, within a short time (within 24 h of sampling). This technique has wide ranging applications for detection of sulfur bacteria in environmental water samples.

The relationship between species richness and ecosystem variability is shaped by the mechanism of coexistence.

PubMed

Tredennick, Andrew T; Adler, Peter B; Adler, Frederick R

2017-08-01

Theory relating species richness to ecosystem variability typically ignores the potential for environmental variability to promote species coexistence. Failure to account for fluctuation-dependent coexistence may explain deviations from the expected negative diversity-ecosystem variability relationship, and limits our ability to predict the consequences of increases in environmental variability. We use a consumer-resource model to explore how coexistence via the temporal storage effect and relative nonlinearity affects ecosystem variability. We show that a positive, rather than negative, diversity-ecosystem variability relationship is possible when ecosystem function is sampled across a natural gradient in environmental variability and diversity. We also show how fluctuation-dependent coexistence can buffer ecosystem functioning against increasing environmental variability by promoting species richness and portfolio effects. Our work provides a general explanation for variation in observed diversity-ecosystem variability relationships and highlights the importance of conserving regional species pools to help buffer ecosystems against predicted increases in environmental variability. © 2017 John Wiley & Sons Ltd/CNRS.

Mathematical Ability of 10-Year-Old Boys and Girls: Genetic and Environmental Etiology of Typical and Low Performance

PubMed Central

Kovas, Yulia; Haworth, Claire M. A.; Petrill, Stephen A.; Plomin, Robert

2009-01-01

The genetic and environmental etiologies of 3 aspects of low mathematical performance (math disability) and the full range of variability (math ability) were compared for boys and girls in a sample of 5,348 children age 10 years (members of 2,674 pairs of same-sex and opposite-sex twins) from the United Kingdom (UK). The measures, which we developed for Web-based testing, included problems from 3 domains of mathematics taught as part of the UK National Curriculum. Using quantitative genetic model-fitting analyses, similar results were found for math disabilities and abilities for all 3 measures: Moderate genetic influence and environmental influence were mainly due to nonshared environmental factors that were unique to the individual, with little influence from shared environment. No sex differences were found in the etiologies of math abilities and disabilities. We conclude that low mathematical performance is the quantitative extreme of the same genetic and environmental factors responsible for variation throughout the distribution. PMID:18064980

Air and surface contamination patterns of meticillin-resistant Staphylococcus aureus on eight acute hospital wards.

PubMed

Creamer, E; Shore, A C; Deasy, E C; Galvin, S; Dolan, A; Walley, N; McHugh, S; Fitzgerald-Hughes, D; Sullivan, D J; Cunney, R; Coleman, D C; Humphreys, H

2014-03-01

Meticillin-resistant Staphylococcus aureus (MRSA) can be recovered from hospital air and from environmental surfaces. This poses a potential risk of transmission to patients. To investigate associations between MRSA isolates recovered from air and environmental surfaces with those from patients when undertaking extensive patient and environmental sampling. This was a prospective observational study of patients and their environment in eight wards of a 700-bed tertiary care hospital during 2010 and 2011. Sampling of patients, air and surfaces was carried out on all ward bays, with more extended environmental sampling in ward high-dependency bays and at particular times of the day. The genetic relatedness of isolates was determined by DNA microarray profiling and spa typing. MRSA was recovered from 30/706 (4.3%) patients and from 19/132 (14.4%) air samples. On 9/132 (6.8%) occasions both patient and air samples yielded MRSA. In 32 high-dependency bays, MRSA was recovered from 12/161 (7.4%) patients, 8/32 (25%) air samples, and 21/644 (3.3%) environmental surface samples. On 10/132 (7.6%) occasions, MRSA was isolated from air in the absence of MRSA-positive patients. Patient demographic data combined with spa typing and DNA microarray profiling revealed four likely transmission clusters, where patient and environmental isolates were deemed to be very closely related. Air sampling yielded MRSA on frequent occasions, especially in high-dependency bays. Environmental and air sampling combined with patient demographic data, spa typing and DNA microarray profiling indicated the presence of clusters that were not otherwise apparent. Copyright © 2014 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

ENVIRONMENTAL SAMPLING AND ANALYSIS IN THE AFTERMATH OF HURRICANE KATRINA

EPA Science Inventory

This presentation describes the environmental sampling completed by EPA in southeastern Louisiana after Hurricane Katrina caused major catastrophic damage. Presentation also describes EPA's Environmental Unit activities in Baton Rouge and New Orleans, LA, and Dallas, TX.

Nuclear DNA contents of Echinchloa crus-galli and its Gaussian relationships with environments

NASA Astrophysics Data System (ADS)

Li, Dan-Dan; Lu, Yong-Liang; Guo, Shui-Liang; Yin, Li-Ping; Zhou, Ping; Lou, Yu-Xia

2017-02-01

Previous studies on plant nuclear DNA content variation and its relationships with environmental gradients produced conflicting results. We speculated that the relationships between nuclear DNA content of a widely-distributed species and its environmental gradients might be non-linear if it was sampled in a large geographical gradient. Echinochloa crus-galli (L.) P. Beauv. is a worldwide species, but without documents on its intraspecific variation of nuclear DNA content. Our objectives are: 1) to detect intraspecific variation scope of E. crus-galli in its nuclear DNA content, and 2) to testify whether nuclear DNA content of the species changes with environmental gradients following Gaussian models if its populations were sampled in a large geographical gradient. We collected seeds of 36 Chinese populations of E. crus-galli across a wide geographical gradient, and sowed them in a homogeneous field to get their offspring to determine their nuclear DNA content. We analyzed the relationships of nuclear DNA content of these populations with latitude, longitude, and nineteen bioclimatic variables by using Gaussian and linear models. (1) Nuclear DNA content varied from 2.113 to 2.410 pg among 36 Chinese populations of E. crus-galli, with a mean value of 2.256 pg. (2) Gaussian correlations of nuclear DNA content (y) with geographical gradients were detected, with latitude (x) following y = 2.2923*e -(x - 24.9360)2/2*63.79452 (r = 0.546, P < 0.001), and with longitude (x) following y = 2.2933*e -(x - 116.1801)2/2*44.74502 (r = 0.672, P < 0.001). (3) Among the nineteen bioclimatic variables, except temperature isothermality, precipitations of the wettest month, the wettest quarter and the warmest quarter, the others could be better fit with nuclear DNA content by using Gaussian models than by linear models. There exists intra-specific variation among 36 Chinese populations of E. crus-galli, Gaussian models could be applied to fit the correlations of its Nuclear DNA content with geographical and most bioclimatic gradients.

Microbial communities in sediment from Zostera marina patches, but not the Z. marina leaf or root microbiomes, vary in relation to distance from patch edge

PubMed Central

Ettinger, Cassandra L.; Voerman, Sofie E.; Lang, Jenna M.; Stachowicz, John J.

2017-01-01

Background Zostera marina (also known as eelgrass) is a foundation species in coastal and marine ecosystems worldwide and is a model for studies of seagrasses (a paraphyletic group in the order Alismatales) that include all the known fully submerged marine angiosperms. In recent years, there has been a growing appreciation of the potential importance of the microbial communities (i.e., microbiomes) associated with various plant species. Here we report a study of variation in Z. marina microbiomes from a field site in Bodega Bay, CA. Methods We characterized and then compared the microbial communities of root, leaf and sediment samples (using 16S ribosomal RNA gene PCR and sequencing) and associated environmental parameters from the inside, edge and outside of a single subtidal Z. marina patch. Multiple comparative approaches were used to examine associations between microbiome features (e.g., diversity, taxonomic composition) and environmental parameters and to compare sample types and sites. Results Microbial communities differed significantly between sample types (root, leaf and sediment) and in sediments from different sites (inside, edge, outside). Carbon:Nitrogen ratio and eelgrass density were both significantly correlated to sediment community composition. Enrichment of certain taxonomic groups in each sample type was detected and analyzed in regard to possible functional implications (especially regarding sulfur metabolism). Discussion Our results are mostly consistent with prior work on seagrass associated microbiomes with a few differences and additional findings. From a functional point of view, the most significant finding is that many of the taxa that differ significantly between sample types and sites are closely related to ones commonly associated with various aspects of sulfur and nitrogen metabolism. Though not a traditional model organism, we believe that Z. marina can become a model for studies of marine plant-microbiome interactions. PMID:28462046

GIS-based niche modeling for mapping species' habitats

USGS Publications Warehouse

Rotenberry, J.T.; Preston, K.L.; Knick, S.

2006-01-01

Ecological a??niche modelinga?? using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

Social and Environmental Factors Related to Smoking Cessation among Mothers: Findings from the Geographic Research on Welling (Grow) Study

PubMed Central

Castro, Yessenia; Heck, Katherine; Forster, Jean L.; Widome, Rachel; Cubbin, Catherine

2015-01-01

Objectives The current study examined associations between race/ethnicity and psychosocial/environmental factors with current smoking status, and whether psychosocial/environmental factors accounted for racial differences in smoking status in a population-based sample of mothers in California. Methods Cross-sectional data from 542 women with a history of smoking were used. Analyses adjusted for age, partner status, and educational attainment. Results In models adjusted for sociodemographics, black women had significantly lower odds, and Latina immigrants had significantly higher odds of being a former smoker compared to white women. Persons smoking in the home, having a majority of friends who smoke, having perceptions of their neighborhood as being somewhat or very unsafe, and experiencing food insecurity were associated with decreased odds of being a former smoker. When these variables were entered into a single model, only being a Latina immigrant and having a majority of friends who smoke were significantly associated with smoking status. Conclusions Black women demonstrated a notable disparity compared with white women in smoking status, accounted for by psychosocial/environmental factors. Immigrant Latinas demonstrated notable success in ever quitting smoking. Social networks may be important barriers to smoking cessation among women. PMID:26450549

Evaluation of triclosan in Minnesota lakes and rivers: Part I - ecological risk assessment.

PubMed

Lyndall, Jennifer; Barber, Timothy; Mahaney, Wendy; Bock, Michael; Capdevielle, Marie

2017-08-01

Triclosan, an antimicrobial compound found in consumer products, may be introduced into the aquatic environment via residual concentrations in municipal wastewater treatment effluent. We conducted an aquatic risk assessment that incorporated the available measured triclosan data from Minnesota lakes and rivers. Although only data reported from Minnesota were considered in the risk assessment, the developed toxicity benchmarks can be applied to other environments. The data were evaluated using a series of environmental fate models to ensure the data were internally consistent and to fill any data gaps. Triclosan was not detected in over 75% of the 567 surface water and sediment samples. Measured environmental data were used to model the predicted environmental exposures to triclosan in surface water, surface sediment, and biota tissues. Toxicity benchmarks based on fatty acid synthesis inhibition and narcosis were determined for aquatic organisms based, in part, on a species sensitivity distribution of chronic toxicity thresholds from the available literature. Predicted and measured environmental concentrations for surface water, sediment, and tissue were below the effects benchmarks, indicating that exposure to triclosan in Minnesota lakes and rivers would not pose an unacceptable risk to aquatic organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Are environmental scanning units effective?

PubMed

Stubbart, C

1982-06-01

Many authorities have urged companies to set up environmental scanning to assist corporate planning. Some advocates have recommended a unit at corporate level. This would give breadth of view and penetration into the future. It would arm decision makers with accurate forecasts. The information would be broad in scope and future directed. It could provide also assumptions for long-range planning. The Fahey and King study produced a model of corporate scanning types. The data showed that environmental information was built into the plan. Though the political environment was important, scanning was inadequate. The best location for scanning was not at corporate level and most firms used irregular methods. The Thomas study concluded that effective environmental scanning was permanent and multi level and that 'best practice' was continuous scanning. In 1978 the sample organizations were revisited. Five of the twelve have not changed their practice. The factors which encouraged a continuous model were the attitudes of academics and business media, demonstrated success of the units, the right kind of personnel. Contrary influences were changes in top management, decentralization moves, resource cuts, defining the environment and its significance, the availability of scanning competent personnel, surprise itself, and the availability of alternatives e.g. external forecasts.

Estimating the Spatial Distribution of Groundwater Age Using Synoptic Surveys of Environmental Tracers in Streams

NASA Astrophysics Data System (ADS)

Gardner, W. P.

2017-12-01

A model which simulates tracer concentration in surface water as a function the age distribution of groundwater discharge is used to characterize groundwater flow systems at a variety of spatial scales. We develop the theory behind the model and demonstrate its application in several groundwater systems of local to regional scale. A 1-D stream transport model, which includes: advection, dispersion, gas exchange, first-order decay and groundwater inflow is coupled a lumped parameter model that calculates the concentration of environmental tracers in discharging groundwater as a function of the groundwater residence time distribution. The lumped parameters, which describe the residence time distribution, are allowed to vary spatially, and multiple environmental tracers can be simulated. This model allows us to calculate the longitudinal profile of tracer concentration in streams as a function of the spatially variable groundwater age distribution. By fitting model results to observations of stream chemistry and discharge, we can then estimate the spatial distribution of groundwater age. The volume of groundwater discharge to streams can be estimated using a subset of environmental tracers, applied tracers, synoptic stream gauging or other methods, and the age of groundwater then estimated using the previously calculated groundwater discharge and observed environmental tracer concentrations. Synoptic surveys of SF6, CFC's, 3H and 222Rn, along with measured stream discharge are used to estimate the groundwater inflow distribution and mean age for regional scale surveys of the Berland River in west-central Alberta. We find that groundwater entering the Berland has observable age, and that the age estimated using our stream survey is of similar order to limited samples from groundwater wells in the region. Our results show that the stream can be used as an easily accessible location to constrain the regional scale spatial distribution of groundwater age.

Fit-for-purpose: species distribution model performance depends on evaluation criteria - Dutch Hoverflies as a case study.

PubMed

Aguirre-Gutiérrez, Jesús; Carvalheiro, Luísa G; Polce, Chiara; van Loon, E Emiel; Raes, Niels; Reemer, Menno; Biesmeijer, Jacobus C

2013-01-01

Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data characteristics (i.e. sample size, spatial distribution).

Temporal trends of Dechlorane Plus in air and precipitation around the North American Great Lakes.

PubMed

Olukunle, Olubiyi I; Lehman, Daniel C; Salamova, Amina; Venier, Marta; Hites, Ronald A

2018-06-13

Dechlorane Plus (DP) is a chlorinated flame retardant manufactured only in Niagara Falls, New York and in Huai'an, China. To determine if the environmental levels of this compound were changing significantly, we measured the long-term temporal trends of its concentrations near the Great Lakes between 2005 and 2015 using air (vapor + particle phase) samples (N = 1047) and precipitation samples (N = 449). We used a multiple linear regression model of DP concentrations to isolate the variabilities due to sampling date and population near the sampling site. The results show that the total DP concentrations in precipitation varied seasonally, maximizing on January 18, but the concentrations in the vapor + particle phase did not show seasonal variations. Vapor + particle phase DP levels were relatively high in Cleveland, and precipitation DP levels were relatively high at Point Petre. DP's concentrations in neither phase were changing as a function of sampling date, indicating that the input of this compound into the environment is continuing, presumably because its use and production are not regulated. Based on the ratio of the anti conformer relative to the total of the two conformer concentrations, we suggest that the syn conformer is somewhat more environmentally stable than the anti conformer. Copyright © 2018 Elsevier B.V. All rights reserved.

First results of a simultaneous measurement of tritium and 14C in an ultra-low-background proportional counter for environmental sources of methane

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mace, Emily K.; Aalseth, Craig E.; Day, Anthony R.

Abstract Simultaneous measurement of tritium and 14C would provide an added tool for tracing organic compounds through environmental systems and is possible via beta energy spectroscopy of sample-derived methane in internal-source gas proportional counters. Since the mid-1960’s atmospheric tritium and 14C have fallen dramatically as the isotopic injections from above-ground nuclear testing have been diluted into the ocean and biosphere. In this work, the feasibility of simultaneous tritium and 14C measurements via proportional counters is revisited in light of significant changes in both the atmospheric and biosphere isotopics and the development of new ultra-low-background gas proportional counting capabilities for smallmore » samples (roughly 50 cc methane). A Geant4 Monte Carlo model of a Pacific Northwest National Laboratory (PNNL) proportional counter response to tritium and 14C is used to analyze small samples of two different methane sources to illustrate the range of applicability of contemporary simultaneous measurements and their limitations. Because the two methane sources examined were not sample size limited, we could compare the small-sample measurements performed at PNNL with analysis of larger samples performed at a commercial laboratory. The dual-isotope simultaneous measurement is well matched for methane samples that are atmospheric or have an elevated source of tritium (i.e. landfill gas). For samples with low/modern tritium isotopics (rainwater), commercial separation and counting is a better fit.« less

Youth appraisals of inter-parental conflict and genetic and environmental contributions to attention-deficit hyperactivity disorder: examination of GxE effects in a twin sample.

PubMed

Nikolas, Molly; Klump, Kelly L; Burt, S Alexandra

2012-05-01

Identification of gene x environment interactions (GxE) for attention-deficit hyperactivity disorder (ADHD) is a crucial component to understanding the mechanisms underpinning the disorder, as prior work indicates large genetic influences and numerous environmental risk factors. Building on prior research, children's appraisals of self-blame were examined as a psychosocial moderator of latent etiological influences on ADHD via biometric twin models, which provide an omnibus test of GxE while managing the potential confound of gene-environment correlation. Participants were 246 twin pairs (total n = 492) ages 6-16 years. ADHD behaviors were assessed via mother report on the Child Behavior Checklist. To assess level of self-blame, each twin completed the Children's Perception of Inter-parental Conflict scale. Two biometric GxE models were fit to the data. The first model revealed a significant decrease in genetic effects and a significant increase in unique environmental influences on ADHD with increasing levels of self-blame. These results generally persisted even after controlling for confounding effects due to gene-environment correlation in the second model. Results suggest that appraisals of self-blame in relation to inter-parental conflict may act as a key moderator of etiological contributions to ADHD.

Youth Appraisals of Inter-parental Conflict and Genetic and Environmental Contributions to Attention-Deficit Hyperactivity Disorder: Examination of G×E Effects in a Twin Sample

PubMed Central

Klump, Kelly L.; Burt, S. Alexandra

2012-01-01

Identification of gene × environment interactions (GxE) for attention-deficit hyperactivity disorder (ADHD) is a crucial component to understanding the mechanisms underpinning the disorder, as prior work indicates large genetic influences and numerous environmental risk factors. Building on prior research, children's appraisals of self-blame were examined as a psychosocial moderator of latent etiological influences on ADHD via biometric twin models, which provide an omnibus test of GxE while managing the potential confound of gene-environment correlation. Participants were 246 twin pairs (total n=492) ages 6–16 years. ADHD behaviors were assessed via mother report on the Child Behavior Checklist. To assess level of self-blame, each twin completed the Children's Perception of Inter-parental Conflict scale. Two biometric GxE models were fit to the data. The first model revealed a significant decrease in genetic effects and a significant increase in unique environmental influences on ADHD with increasing levels of self-blame. These results generally persisted even after controlling for confounding effects due to gene-environment correlation in the second model. Results suggest that appraisals of self-blame in relation to inter-parental conflict may act as a key moderator of etiological contributions to ADHD. PMID:22006350

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Comparison of DOT-ELISA and Standard-ELISA for Detection of the Vibrio cholerae Toxin in Culture Supernatants of Bacteria Isolated from Human and Environmental Samples.

PubMed

Meza-Lucas, Antonio; Pérez-Villagómez, María-Fernanda; Martínez-López, José-Patricio; García-Rodea, Ricardo; Martínez-Castelán, María-Guadalupe; Escobar-Gutiérrez, Alejandro; de-la-Rosa-Arana, Jorge-Luis; Villanueva-Zamudio, Altagracia

2016-09-01

A comparison of DOT-ELISA and Standard-ELISA was made for detection of Vibrio cholerae toxin in culture supernatants of bacteria isolated from human and environmental samples. A total of 293 supernatants were tested in a double blind assay. A correlation of 100 % was obtained between both techniques. The cholera toxin was found in 20 Inaba and 3 Ogawa strains. Positive samples were from seafood (17 samples), potable water (1 sample) and sewage (5 samples). The DOT-ELISA was useful as the standard-ELISA to confirm the presence of cholera toxin in the environmental samples.

Bayesian model selection: Evidence estimation based on DREAM simulation and bridge sampling

NASA Astrophysics Data System (ADS)

Volpi, Elena; Schoups, Gerrit; Firmani, Giovanni; Vrugt, Jasper A.

2017-04-01

Bayesian inference has found widespread application in Earth and Environmental Systems Modeling, providing an effective tool for prediction, data assimilation, parameter estimation, uncertainty analysis and hypothesis testing. Under multiple competing hypotheses, the Bayesian approach also provides an attractive alternative to traditional information criteria (e.g. AIC, BIC) for model selection. The key variable for Bayesian model selection is the evidence (or marginal likelihood) that is the normalizing constant in the denominator of Bayes theorem; while it is fundamental for model selection, the evidence is not required for Bayesian inference. It is computed for each hypothesis (model) by averaging the likelihood function over the prior parameter distribution, rather than maximizing it as by information criteria; the larger a model evidence the more support it receives among a collection of hypothesis as the simulated values assign relatively high probability density to the observed data. Hence, the evidence naturally acts as an Occam's razor, preferring simpler and more constrained models against the selection of over-fitted ones by information criteria that incorporate only the likelihood maximum. Since it is not particularly easy to estimate the evidence in practice, Bayesian model selection via the marginal likelihood has not yet found mainstream use. We illustrate here the properties of a new estimator of the Bayesian model evidence, which provides robust and unbiased estimates of the marginal likelihood; the method is coined Gaussian Mixture Importance Sampling (GMIS). GMIS uses multidimensional numerical integration of the posterior parameter distribution via bridge sampling (a generalization of importance sampling) of a mixture distribution fitted to samples of the posterior distribution derived from the DREAM algorithm (Vrugt et al., 2008; 2009). Some illustrative examples are presented to show the robustness and superiority of the GMIS estimator with respect to other commonly used approaches in the literature.

The procedures manual of the Environmental Measurements Laboratory. Volume 2, 28. edition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chieco, N.A.

1997-02-01

This report contains environmental sampling and analytical chemistry procedures that are performed by the Environmental Measurements Laboratory. The purpose of environmental sampling and analysis is to obtain data that describe a particular site at a specific point in time from which an evaluation can be made as a basis for possible action.

The Effect of Environmental Science Projects on Students' Environmental Knowledge and Science Attitudes

ERIC Educational Resources Information Center

Al-Balushi, Sulaiman M.; Al-Aamri, Shamsa S.

2014-01-01

The current study explores the effectiveness of involving students in environmental science projects for their environmental knowledge and attitudes towards science. The study design is a quasi-experimental pre-post control group design. The sample was 62 11th-grade female students studying at a public school in Oman. The sample was divided into…

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

PubMed

Xie, Gisselle Yang; Olson, Deanna H; Blaustein, Andrew R

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats.

Infrastructure features outperform environmental variables explaining rabbit abundance around motorways.

PubMed

Planillo, Aimara; Malo, Juan E

2018-01-01

Human disturbance is widespread across landscapes in the form of roads that alter wildlife populations. Knowing which road features are responsible for the species response and their relevance in comparison with environmental variables will provide useful information for effective conservation measures. We sampled relative abundance of European rabbits, a very widespread species, in motorway verges at regional scale, in an area with large variability in environmental and infrastructure conditions. Environmental variables included vegetation structure, plant productivity, distance to water sources, and altitude. Infrastructure characteristics were the type of vegetation in verges, verge width, traffic volume, and the presence of embankments. We performed a variance partitioning analysis to determine the relative importance of two sets of variables on rabbit abundance. Additionally, we identified the most important variables and their effects model averaging after model selection by AICc on hypothesis-based models. As a group, infrastructure features explained four times more variability in rabbit abundance than environmental variables, being the effects of the former critical in motorway stretches located in altered landscapes with no available habitat for rabbits, such as agricultural fields. Model selection and Akaike weights showed that verge width and traffic volume are the most important variables explaining rabbit abundance index, with positive and negative effects, respectively. In the light of these results, the response of species to the infrastructure can be modulated through the modification of motorway features, being some of them manageable in the design phase. The identification of such features leads to suggestions for improvement through low-cost corrective measures and conservation plans. As a general indication, keeping motorway verges less than 10 m wide will prevent high densities of rabbits and avoid the unwanted effects that rabbit populations can generate in some areas.

Variables Associated With Tic Exacerbation in Children With Chronic Tic Disorders

PubMed Central

Himle, Michael B.; Capriotti, Matthew R.; Hayes, Loran P.; Ramanujam, Krishnapriya; Scahill, Lawrence; Sukhodolsky, Denis G.; Wilhelm, Sabine; Deckersbach, Thilo; Peterson, Alan L.; Specht, Matt W.; Walkup, John T.; Chang, Susanna; Piacentini, John

2014-01-01

Research has shown that motor and vocal tics fluctuate in frequency, intensity, and form in response to environmental and contextual cues. Behavioral models have proposed that some of the variation in tics may reflect context-dependent interactive learning processes such that once tics are performed, they are influenced by environmental contingencies. The current study describes the results of a function-based assessment of tics (FBAT) from a recently completed study comparing Comprehensive Behavioral Intervention for Tics (CBIT) with supportive psychotherapy. The current study describes the frequency with which antecedent and consequence variables were reported to exacerbate tics and the relationships between these functional variables and sample baseline characteristics, comorbidities, and measures of tic severity. Results showed that tic-exacerbating antecedents and consequences were nearly ubiquitous in a sample of children with chronic tic disorder. In addition, functional variables were related to baseline measures of comorbid internalizing symptoms and specific measures of tic severity. PMID:24778433

Environmental literacy of Hispanic, urban, middle school students in Houston, Texas

NASA Astrophysics Data System (ADS)

Meuth, Amber M.

With the global crises facing the planet that bring major implications, (Hart & Nolan, 1999; Hungerford & Simmons, 2003) it is imperative that there be an environmentally literate citizenry who can identify, solve, and prevent environmental issues. Since middle school students are evolving into participating citizens and are developing the ability to think in abstract terms, they are a critical group to study regarding levels of environmental literacy. Additionally, with the increased resource needs and decreased air and water quality in highly populated urban areas, focusing on the environmental literacy of students living and attending school in urban areas is essential. The purpose of this study was to describe the levels of environmental literacy of a group of Hispanic, urban, middle school students in Houston, Texas. Sixth, seventh, and eighth grade students who attend a charter school in Houston, Texas were given, the Middle School Environmental Literacy Survey (MSELS). This survey has been developed to measure components of environmental literacy as related to domains identified critical to environmental literacy (McBeth et al., 2008). The four domains include ecological knowledge, environmental affect, cognitive skills, and behavior. Data collected from the survey was used to determine levels of environmental literacy in the following variables: ecological knowledge, verbal commitment, actual commitment, environmental sensitivity, general environmental feelings, and environmental issue and action skills. Descriptive statistics were calculated and analyzed for each grade level and as an entire sample for each variable in order to generate a profile of the group. Composite scores were calculated in the four domains (ecological knowledge, environmental affect, cognitive skills, and behavior) and were compared to high, moderate, and low levels of environmental literacy set forth by top environmental education researchers (McBeth et al., 2008). Additionally, two secondary analyses were conducted. First, mean scores for each grade level were compared by gender to see if gender plays a role in environmental literacy variables. Second, mean scores in each environmental literacy variable were compared by grade level to investigate if significant differences occur between grade levels. The results indicate that the participants in this sample have high levels of ecological knowledge but convey only moderate feelings towards the environment. The students report that they are willing to engage in more pro-environmental behaviors than they actually report doing. They also display modest abilities to indentify and analyze environmental issues as well as select appropriate action plans. Regarding the domains critical to environmental literacy, the mean scores for this sample fell within the high range for ecological knowledge; scores for affect, cognitive skills, and behavior all fell within the moderate range. For each grade level, the overall environmental literacy composite scores also fell within the moderate range. When compared to students in a national study, generally, in the performance based sections of the MSELS, the 6 th and 8th grade students in this sample scored at or above the students in the national sample while on the self-report sections, the 6th and 8th grade students in this sample generally scored below the students in the national sample. That being said, however, when comparing composite scores for the Affect, Cognitive Skills, and Behavior domains, both sets of students scored within the moderate range. In the Knowledge domain, the students in this sample scored in the high range while the students in the national sample scored in the moderate range. Gender did not appear to play a part in the levels of the environmental literacy variables, while grade level may make a difference for certain variables such as verbal commitment, actual commitment, and environmental sensitivity.

Human Life History Strategies.

PubMed

Chua, Kristine J; Lukaszewski, Aaron W; Grant, DeMond M; Sng, Oliver

2017-01-01

Human life history (LH) strategies are theoretically regulated by developmental exposure to environmental cues that ancestrally predicted LH-relevant world states (e.g., risk of morbidity-mortality). Recent modeling work has raised the question of whether the association of childhood family factors with adult LH variation arises via (i) direct sampling of external environmental cues during development and/or (ii) calibration of LH strategies to internal somatic condition (i.e., health), which itself reflects exposure to variably favorable environments. The present research tested between these possibilities through three online surveys involving a total of over 26,000 participants. Participants completed questionnaires assessing components of self-reported environmental harshness (i.e., socioeconomic status, family neglect, and neighborhood crime), health status, and various LH-related psychological and behavioral phenotypes (e.g., mating strategies, paranoia, and anxiety), modeled as a unidimensional latent variable. Structural equation models suggested that exposure to harsh ecologies had direct effects on latent LH strategy as well as indirect effects on latent LH strategy mediated via health status. These findings suggest that human LH strategies may be calibrated to both external and internal cues and that such calibrational effects manifest in a wide range of psychological and behavioral phenotypes.

What makes people leave their food? The interaction of personal and situational factors leading to plate leftovers in canteens.

PubMed

Lorenz, Bettina Anne-Sophie; Hartmann, Monika; Langen, Nina

2017-09-01

In order to provide a basis for the reduction of food losses, our study analyzes individual food choice, eating and leftover behavior in a university canteen by consideration of personal, social and environmental determinants. Based on an extended literature review, a structural equation model is derived and empirically tested for a sample of 343 students. The empirical estimates support the derived model with a good overall model fit and sufficient R 2 values for dependent variables. Hence, our results provide evidence for a general significant impact of behavioral intention and related personal and social determinants as well as for the relevance of environmental/situational determinants such as portion sizes and palatability of food for plate leftovers. Moreover, we find that environmental and personal determinants are interrelated and that the impact of different determinants is relative to perceived time constraints during a visit of the university canteen. Accordingly, we conclude that simple measures to decrease avoidable food waste may take effects via complex and interrelated behavioral structures and that future research should focus on these effects to understand and change food leftover behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

An analytical framework for estimating aquatic species density from environmental DNA

USGS Publications Warehouse

Chambert, Thierry; Pilliod, David S.; Goldberg, Caren S.; Doi, Hideyuki; Takahara, Teruhiko

2018-01-01

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Testing mixing models of old and young groundwater in a tropical lowland rain forest with environmental tracers

USGS Publications Warehouse

Solomon, D. Kip; Genereux, David P.; Plummer, Niel; Busenberg, Eurybiades

2010-01-01

We tested three models of mixing between old interbasin groundwater flow (IGF) and young, locally derived groundwater in a lowland rain forest in Costa Rica using a large suite of environmental tracers. We focus on the young fraction of water using the transient tracers CFC‐11, CFC‐12, CFC‐113, SF6, 3H, and bomb 14C. We measured 3He, but 3H/3He dating is generally problematic due to the presence of mantle 3He. Because of their unique concentration histories in the atmosphere, combinations of transient tracers are sensitive not only to subsurface travel times but also to mixing between waters having different travel times. Samples fall into three distinct categories: (1) young waters that plot along a piston flow line, (2) old samples that have near‐zero concentrations of the transient tracers, and (3) mixtures of 1 and 2. We have modeled the concentrations of the transient tracers using (1) a binary mixing model (BMM) of old and young water with the young fraction transported via piston flow, (2) an exponential mixing model (EMM) with a distribution of groundwater travel times characterized by a mean value, and (3) an exponential mixing model for the young fraction followed by binary mixing with an old fraction (EMM/BMM). In spite of the mathematical differences in the mixing models, they all lead to a similar conceptual model of young (0 to 10 year) groundwater that is locally derived mixing with old (>1000 years) groundwater that is recharged beyond the surface water boundary of the system.

Development and Psychometric Examination of the Inclusive Teaching Strategies in Nursing Education Instrument.

PubMed

Levey, Janet A

2017-08-01

Nurse educators might be unknowingly excluding learners secondary to teaching practices. Universal design for instruction (UDI) prepares and delivers accessible content and learning environments for diverse learners; however, it is not well known in nursing education. The aim of the study was to examine the psychometric properties of the Inclusive Teaching Strategies in Nursing Education (ITSinNE) 55-item instrument. Confirmatory factor analysis was performed on a sample of 311 educators in prelicensure programs. The ITSinNE scales had good to adequate estimates of reliability. The exogenous model fit the sample and model-implied covariance matrix; however, the endogenous model was not a good fit. Further instrument development is required. Measuring factors influencing nurse educators' willingness to adopt UDI will enable intervention research to enhance professional development fostering content and environmental access for all learners.

Sex moderates associations between perceptions of the physical and social environments and physical activity in youth.

PubMed

Moore, Justin B; Beets, Michael W; Kaczynski, Andrew T; Besenyi, Gina M; Morris, Sara F; Kolbe, Mary Bea

2014-01-01

To determine if the sex of the child moderates the relationships between perceptions of the physical/social environments and moderate to vigorous physical activity (MVPA) in youth. Cross-sectional. North Carolina. A final sample of 711 children, 8 to 17 years of age, was available for analysis. Self-reported presence of environmental factors previously identified to be associated with physical activity in youth was collected via survey. Daily MVPA was assessed via accelerometry for a minimum of 4 days. Multilevel linear regression models were employed, adjusted for clustering at the county and individual level. MVPA was first regressed onto sex and environmental perception items while controlling for grade and race. The interaction term between sex and environmental perception was then added to the model. A significant positive association was observed in the first models between MVPA and two items related to parent permission to (1) walk and (2) ride a bike in the neighborhood. These effects were fully moderated by sex, with males indicating "yes" on these items exhibiting 6.87 and 5.21 more minutes of MVPA (respectively) than males indicating "no." Environmental perceptions appear to be related to MVPA, but this relationship is present only in males. Future research should be conducted to identify modifiable social and physical characteristics that are associated with MVPA in females.

An environmental stress model correctly predicts unimodal trends in overall species richness and diversity along intertidal elevation gradients

NASA Astrophysics Data System (ADS)

Zwerschke, Nadescha; Bollen, Merle; Molis, Markus; Scrosati, Ricardo A.

2013-12-01

Environmental stress is a major factor structuring communities. An environmental stress model (ESM) predicts that overall species richness and diversity should follow a unimodal trend along the full stress gradient along which assemblages from a regional biota can occur (not to be confused with the intermediate disturbance hypothesis, which makes predictions only for basal species along an intermediate-to-high stress range). Past studies could only provide partial support for ESM predictions because of the limited stress range surveyed or a low sampling resolution. In this study, we measured overall species richness and diversity (considering all seaweeds and invertebrates) along the intertidal elevation gradient on two wave-sheltered rocky shores from Helgoland Island, on the NE Atlantic coast. In intertidal habitats, tides cause a pronounced gradient of increasing stress from low to high elevations. We surveyed up to nine contiguous elevation zones between the lowest intertidal elevation (low stress) and the high intertidal boundary (high stress). Nonlinear regression analyses revealed that overall species richness and diversity followed unimodal trends across elevations on the two studied shores. Therefore, our study suggests that the ESM might constitute a useful tool to predict local richness and diversity as a function of environmental stress. Performing tests on other systems (marine as well as terrestrial) should help to refine the model.

Environmental impact of geopressure - geothermal cogeneration facility on wetland resources and socioeconomic characteristics in Louisiana Gulf Coast region. Final report, October 10, 1983-September 31, 1984

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smalley, A.M.; Saleh, F.M.S.; Fontenot, M.

1984-08-01

Baseline data relevant to air quality are presented. The following are also included: geology and resource assessment, design well prospects in southwestern Louisiana, water quality monitoring, chemical analysis subsidence, microseismicity, geopressure-geothermal subsidence modeling, models of compaction and subsidence, sampling handling and preparation, brine chemistry, wetland resources, socioeconomic characteristics, impacts on wetlands, salinity, toxic metals, non-metal toxicants, temperature, subsidence, and socioeconomic impacts. (MHR)

The search for loci under selection: trends, biases and progress.

PubMed

Ahrens, Collin W; Rymer, Paul D; Stow, Adam; Bragg, Jason; Dillon, Shannon; Umbers, Kate D L; Dudaniec, Rachael Y

2018-03-01

Detecting genetic variants under selection using F ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics. © 2018 John Wiley & Sons Ltd.

Genovo: De Novo Assembly for Metagenomes

NASA Astrophysics Data System (ADS)

Laserson, Jonathan; Jojic, Vladimir; Koller, Daphne

Next-generation sequencing technologies produce a large number of noisy reads from the DNA in a sample. Metagenomics and population sequencing aim to recover the genomic sequences of the species in the sample, which could be of high diversity. Methods geared towards single sequence reconstruction are not sensitive enough when applied in this setting. We introduce a generative probabilistic model of read generation from environmental samples and present Genovo, a novel de novo sequence assembler that discovers likely sequence reconstructions under the model. A Chinese restaurant process prior accounts for the unknown number of genomes in the sample. Inference is made by applying a series of hill-climbing steps iteratively until convergence. We compare the performance of Genovo to three other short read assembly programs across one synthetic dataset and eight metagenomic datasets created using the 454 platform, the largest of which has 311k reads. Genovo's reconstructions cover more bases and recover more genes than the other methods, and yield a higher assembly score.

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

PubMed

Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

2018-03-01

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

GENETIC AND ENVIRONMENTAL RISK FOR MAJOR DEPRESSION IN AFRICAN-AMERICAN AND EUROPEAN-AMERICAN WOMEN

PubMed Central

Duncan, Alexis E.; Munn-Chernoff, Melissa A.; Hudson, Darrell L.; Eschenbacher, Michaela A.; Agrawal, Arpana; Grant, Julia D.; Nelson, Elliot C.; Waldron, Mary; Glowinski, Anne L.; Sartor, Carolyn E.; Bucholz, Kathleen K.; Madden, Pamela A.F.; Heath, Andrew C.

2014-01-01

It is unknown whether there are racial differences in the heritability of major depressive disorder (MDD) because most psychiatric genetic studies have been conducted in samples comprised largely of white non-Hispanics. To examine potential differences between African-American (AA) and European-American (EA) young adult women in (1) DSM-IV MDD prevalence, symptomatology and risk factors and (2) genetic and/or environmental liability to MDD, we analyzed data from a large, population representative sample of twins ascertained from birth records (n= 550 AA and n=3226 EA female twins) aged 18–28 years at the time of MDD assessment by semi-structured psychiatric interview. AA women were more likely to have MDD risk factors; however, there were no significant differences in lifetime MDD prevalence between AA and EA women after adjusting for covariates (Odds Ratio = 0.88, 95% confidence interval: 0.67–1.15 ). Most MDD risk factors identified among AAs were also associated with MDD at similar magnitudes among EAs. Although the MDD heritability point estimate was higher among AA than EA women in a model with paths estimated separately by race (56%, 95% CI: 29%–78% vs. 41%, 95% CI: 29%–52%), the best-fitting model was one in which additive genetic and nonshared environmental paths for AA and EA women were constrained to be equal (A = 43%, 33%–53% and E = 57%, 47%–67%). Despite a marked elevation in the prevalence of environmental risk exposures related to MDD among AA women, there were no significant differences in lifetime prevalence or heritability of MDD between AA and EA young women. PMID:24910290

Genetic and environmental risk for major depression in African-American and European-American women.

PubMed

Duncan, Alexis E; Munn-Chernoff, Melissa A; Hudson, Darrell L; Eschenbacher, Michaela A; Agrawal, Arpana; Grant, Julia D; Nelson, Elliot C; Waldron, Mary; Glowinski, Anne L; Sartor, Carolyn E; Bucholz, Kathleen K; Madden, Pamela A F; Heath, Andrew C

2014-08-01

It is unknown whether there are racial differences in the heritability of major depressive disorder (MDD) because most psychiatric genetic studies have been conducted in samples comprised largely of white non-Hispanics. To examine potential differences between African-American (AA) and European-American (EA) young adult women in (1) Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) MDD prevalence, symptomatology, and risk factors, and (2) genetic and/or environmental liability to MDD, we analyzed data from a large population-representative sample of twins ascertained from birth records (n = 550 AA and n = 3226 EA female twins) aged 18-28 years at the time of MDD assessment by semi-structured psychiatric interview. AA women were more likely to have MDD risk factors; however, there were no significant differences in lifetime MDD prevalence between AA and EA women after adjusting for covariates (odds ratio = 0.88, 95% confidence interval [CI]: 0.67-1.15). Most MDD risk factors identified among AA women were also associated with MDD at similar magnitudes among EA women. Although the MDD heritability point estimate was higher among AA women than EA women in a model with paths estimated separately by race (56%, 95% CI: 29-78% vs. 41%, 95% CI: 29-52%), the best fitting model was one in which additive genetic and non-shared environmental paths for AA and EA women were constrained to be equal (A = 43%, 33-53% and E = 57%, 47-67%). In spite of a marked elevation in the prevalence of environmental risk exposures related to MDD among AA women, there were no significant differences in lifetime prevalence or heritability of MDD between AA and EA young women.

BUMPER v1.0: a Bayesian user-friendly model for palaeo-environmental reconstruction

NASA Astrophysics Data System (ADS)

Holden, Philip B.; Birks, H. John B.; Brooks, Stephen J.; Bush, Mark B.; Hwang, Grace M.; Matthews-Bird, Frazer; Valencia, Bryan G.; van Woesik, Robert

2017-02-01

We describe the Bayesian user-friendly model for palaeo-environmental reconstruction (BUMPER), a Bayesian transfer function for inferring past climate and other environmental variables from microfossil assemblages. BUMPER is fully self-calibrating, straightforward to apply, and computationally fast, requiring ˜ 2 s to build a 100-taxon model from a 100-site training set on a standard personal computer. We apply the model's probabilistic framework to generate thousands of artificial training sets under ideal assumptions. We then use these to demonstrate the sensitivity of reconstructions to the characteristics of the training set, considering assemblage richness, taxon tolerances, and the number of training sites. We find that a useful guideline for the size of a training set is to provide, on average, at least 10 samples of each taxon. We demonstrate general applicability to real data, considering three different organism types (chironomids, diatoms, pollen) and different reconstructed variables. An identically configured model is used in each application, the only change being the input files that provide the training-set environment and taxon-count data. The performance of BUMPER is shown to be comparable with weighted average partial least squares (WAPLS) in each case. Additional artificial datasets are constructed with similar characteristics to the real data, and these are used to explore the reasons for the differing performances of the different training sets.

Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions.

PubMed

Shareef, Hussain; Mutlag, Ammar Hussein; Mohamed, Azah

2017-01-01

Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland-Altman test, with more than 95 percent acceptability.

Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions

PubMed Central

Shareef, Hussain; Mohamed, Azah

2017-01-01

Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland–Altman test, with more than 95 percent acceptability. PMID:28702051

X-231B technology demonstration for in situ treatment of contaminated soil: Contaminant characterization and three dimensional spatial modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

West, O.R.; Siegrist, R.L.; Mitchell, T.J.

1993-11-01

Fine-textured soils and sediments contaminated by trichloroethylene (TCE) and other chlorinated organics present a serious environmental restoration challenge at US Department of Energy (DOE) sites. DOE and Martin Marietta Energy Systems, Inc. initiated a research and demonstration project at Oak Ridge National Laboratory. The goal of the project was to demonstrate a process for closure and environmental restoration of the X-231B Solid Waste Management Unit at the DOE Portsmouth Gaseous Diffusion Plant. The X-231B Unit was used from 1976 to 1983 as a land disposal site for waste oils and solvents. Silt and clay deposits beneath the unit were contaminatedmore » with volatile organic compounds and low levels of radioactive substances. The shallow groundwater was also contaminated, and some contaminants were at levels well above drinking water standards. This document begins with a summary of the subsurface physical and contaminant characteristics obtained from investigative studies conducted at the X-231B Unit prior to January 1992 (Sect. 2). This is then followed by a description of the sample collection and analysis methods used during the baseline sampling conducted in January 1992 (Sect. 3). The results of this sampling event were used to develop spatial models for VOC contaminant distribution within the X-231B Unit.« less

Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.

PubMed

Fourcade, Yoan; Engler, Jan O; Rödder, Dennis; Secondi, Jean

2014-01-01

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one "virtual" derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

PubMed Central

Fourcade, Yoan; Engler, Jan O.; Rödder, Dennis; Secondi, Jean

2014-01-01

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one “virtual” derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases. PMID:24818607

The Unique and Shared Genetic and Environmental Contributions to Fear, Anger, and Sadness in Childhood

PubMed Central

Clifford, Sierra; Lemery-Chalfant, Kathryn; Goldsmith, H. Hill

2015-01-01

This study examined the extent to which subordinate dimensions of negative emotionality were genetically and environmentally distinct in a sample of 1316 twins (51% female, 85.8% Caucasian, primarily middle class, mean age = 7.87 years, SD = .93), recruited from Wisconsin hospital birth records between 1989 and 2004. Cholesky, independent pathway, and common pathway models were fitted for mother-report, father-report, and in-home observation of temperament. Although findings support the use of negative emotionality, there were heritable aspects of anger and fear not explained by a common genetic factor, and shared environmental influences common to anger and sadness but not fear. Observed fear was independent from observed anger and sadness. Distinctions support specificity in measurement when considering implications for child development. PMID:26182850

Groundwater environmental tracer data collected from the Chicot, Evangeline, and Jasper aquifers in Montgomery County and adjacent counties, Texas, 2008

USGS Publications Warehouse

Oden, Timothy D.

2011-01-01

The Gulf Coast aquifer system is the primary water supply for Montgomery County in southeastern Texas, including part of the Houston metropolitan area and the cities of Magnolia, Conroe, and The Woodlands Township, Texas. The U.S. Geological Survey, in cooperation with the Lone Star Groundwater Conservation District, collected environmental tracer data in the Gulf Coast aquifer system, primarily in Montgomery County. Forty existing groundwater wells screened in the Gulf Coast aquifer system were selected for sampling in Montgomery County (38 wells), Waller County (1 well), and Walker County (1 well). Groundwater-quality samples, physicochemical properties, and water-level data were collected once from each of the 40 wells during March-September 2008. Groundwater-quality samples were analyzed for dissolved gases and the environmental tracers sulfur hexafluoride, chlorofluorocarbons, tritium, helium-4, and helium-3/tritium. Water samples were collected and processed onsite using methods designed to minimize changes to the water-sample chemistry or contamination from the atmosphere. Replicate samples for quality assurance and quality control were collected with each environmental sample. Well-construction information and environmental tracer data for March-September 2008 are presented.

Method for ultra-trace cesium isotope ratio measurements from environmental samples using thermal ionization mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snow, Mathew S.; Snyder, Darin C.; Mann, Nick R.

2015-05-01

135Cs/ 137Cs isotope ratios can provide the age, origin and history of environmental Cs contamination. Relatively high precision 135Cs/ 137Cs isotope ratio measurements from samples containing femtogram quantities of 137Cs are needed to accurately track contamination resuspension and redistribution following environmental 137Cs releases; however, mass spectrometric analyses of environmental samples are limited by the large quantities of ionization inhibitors and isobaric interferences which are present at relatively high concentrations in the environment. We report a new approach for Cs purification from environmental samples. An initial ammonium molybdophosphate-polyacrylonitrile (AMP-PAN) column provides a robust method for extracting Cs under a wide varietymore » of sample matrices and mass loads. Cation exchange separations using a second AMP-PAN column result in more than two orders of magnitude greater Cs/Rb separation factors than commercially available strong cation exchangers. Coupling an AMP-PAN cation exchanging step to a microcation column (AG50W resin) enables consistent 2-4% (2σ) measurement errors for samples containing 3-6,000 fg 137Cs, representing the highest precision 135Cs/ 137Cs ratio measurements currently reported for soil samples at the femtogram level.« less

Use of immunomagnetic separation for the detection of Desulfovibrio vulgaris from environmental samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, R.; Hazen, T.C.; Joyner, D.C.

2011-04-15

Immunomagnetic separation (IMS) has proved highly efficient for recovering microorganisms from heterogeneous samples. Current investigation targeted the separation of viable cells of the sulfate-reducing bacterium, Desulfovibrio vulgaris. Streptavidin-coupled paramagnetic beads and biotin labeled antibodies raised against surface antigens of this microorganism were used to capture D. vulgaris cells in both bioreactor grown laboratory samples and from extremely low-biomass environmental soil and subsurface drilling samples. Initial studies on detection, recovery efficiency and viability for IMS were performed with laboratory grown D. vulgaris cells using various cell densities. Efficiency of cell isolation and recovery (i.e., release of the microbial cells from themore » beads following separation) was followed by microscopic imaging and acridine orange direct counts (AODC). Excellent recovery efficiency encouraged the use of IMS to capture Desulfovibrio spp. cells from low-biomass environmental samples. The environmental samples were obtained from a radionuclide-contaminated site in Germany and the chromium (VI)-contaminated Hanford site, an ongoing bioremediation project of the U.S. Department of Energy. Field deployable IMS technology may greatly facilitate environmental sampling and bioremediation process monitoring and enable transcriptomics and proteomics/metabolomics-based studies directly on cells collected from the field.« less

21 CFR 118.7 - Sampling methodology for Salmonella Enteritidis (SE).

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 2 2013-04-01 2013-04-01 false Sampling methodology for Salmonella Enteritidis (SE). 118.7 Section 118.7 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN....7 Sampling methodology for Salmonella Enteritidis (SE). (a) Environmental sampling. An environmental...

21 CFR 118.7 - Sampling methodology for Salmonella Enteritidis (SE).

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 2 2014-04-01 2014-04-01 false Sampling methodology for Salmonella Enteritidis (SE). 118.7 Section 118.7 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN....7 Sampling methodology for Salmonella Enteritidis (SE). (a) Environmental sampling. An environmental...

21 CFR 118.7 - Sampling methodology for Salmonella Enteritidis (SE).

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 2 2012-04-01 2012-04-01 false Sampling methodology for Salmonella Enteritidis (SE). 118.7 Section 118.7 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN....7 Sampling methodology for Salmonella Enteritidis (SE). (a) Environmental sampling. An environmental...

21 CFR 118.7 - Sampling methodology for Salmonella Enteritidis (SE).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Sampling methodology for Salmonella Enteritidis (SE). 118.7 Section 118.7 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN....7 Sampling methodology for Salmonella Enteritidis (SE). (a) Environmental sampling. An environmental...

21 CFR 118.7 - Sampling methodology for Salmonella Enteritidis (SE).

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Sampling methodology for Salmonella Enteritidis (SE). 118.7 Section 118.7 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN....7 Sampling methodology for Salmonella Enteritidis (SE). (a) Environmental sampling. An environmental...

Mathematical modeling of wastewater-derived biodegradable dissolved organic nitrogen.

PubMed

Simsek, Halis

2016-11-01

Wastewater-derived dissolved organic nitrogen (DON) typically constitutes the majority of total dissolved nitrogen (TDN) discharged to surface waters from advanced wastewater treatment plants (WWTPs). When considering the stringent regulations on nitrogen discharge limits in sensitive receiving waters, DON becomes problematic and needs to be reduced. Biodegradable DON (BDON) is a portion of DON that is biologically degradable by bacteria when the optimum environmental conditions are met. BDON in a two-stage trickling filter WWTP was estimated using artificial intelligence techniques, such as adaptive neuro-fuzzy inference systems, multilayer perceptron, radial basis neural networks (RBNN), and generalized regression neural networks. Nitrite, nitrate, ammonium, TDN, and DON data were used as input neurons. Wastewater samples were collected from four different locations in the plant. Model performances were evaluated using root mean square error, mean absolute error, mean bias error, and coefficient of determination statistics. Modeling results showed that the R(2) values were higher than 0.85 in all four models for all wastewater samples, except only R(2) in the final effluent sample for RBNN modeling was low (0.52). Overall, it was found that all four computing techniques could be employed successfully to predict BDON.

Investigation of cloud point extraction for the analysis of metallic nanoparticles in a soil matrix

PubMed Central

Hadri, Hind El; Hackley, Vincent A.

2017-01-01

The characterization of manufactured nanoparticles (MNPs) in environmental samples is necessary to assess their behavior, fate and potential toxicity. Several techniques are available, but the limit of detection (LOD) is often too high for environmentally relevant concentrations. Therefore, pre-concentration of MNPs is an important component in the sample preparation step, in order to apply analytical tools with a LOD higher than the ng kg−1 level. The objective of this study was to explore cloud point extraction (CPE) as a viable method to pre-concentrate gold nanoparticles (AuNPs), as a model MNP, spiked into a soil extract matrix. To that end, different extraction conditions and surface coatings were evaluated in a simple matrix. The CPE method was then applied to soil extract samples spiked with AuNPs. Total gold, determined by inductively coupled plasma mass spectrometry (ICP-MS) following acid digestion, yielded a recovery greater than 90 %. The first known application of single particle ICP-MS and asymmetric flow field-flow fractionation to evaluate the preservation of the AuNP physical state following CPE extraction is demonstrated. PMID:28507763

Sampling and monitoring for the mine life cycle

USGS Publications Warehouse

McLemore, Virginia T.; Smith, Kathleen S.; Russell, Carol C.

2014-01-01

Sampling and Monitoring for the Mine Life Cycle provides an overview of sampling for environmental purposes and monitoring of environmentally relevant variables at mining sites. It focuses on environmental sampling and monitoring of surface water, and also considers groundwater, process water streams, rock, soil, and other media including air and biological organisms. The handbook includes an appendix of technical summaries written by subject-matter experts that describe field measurements, collection methods, and analytical techniques and procedures relevant to environmental sampling and monitoring.The sixth of a series of handbooks on technologies for management of metal mine and metallurgical process drainage, this handbook supplements and enhances current literature and provides an awareness of the critical components and complexities involved in environmental sampling and monitoring at the mine site. It differs from most information sources by providing an approach to address all types of mining influenced water and other sampling media throughout the mine life cycle.Sampling and Monitoring for the Mine Life Cycle is organized into a main text and six appendices that are an integral part of the handbook. Sidebars and illustrations are included to provide additional detail about important concepts, to present examples and brief case studies, and to suggest resources for further information. Extensive references are included.

Genetic and environmental contributions to the inverse association between specific autistic traits and experience seeking in adults.

PubMed

Romero-Martínez, Ángel; Moya-Albiol, Luís; Vinkhuyzen, Anna A E; Polderman, Tinca J C

2016-12-01

Autistic traits are characterized by social and communication problems, restricted, repetitive and stereotyped patterns of behavior, interests and activities. The relation between autistic traits and personality characteristics is largely unknown. This study focused on the relation between five specific autistic traits measured with the abridged version of the Autism Spectrum Quotient ("social problems," "preference for routine," "attentional switching difficulties," "imagination impairments," "fascination for numbers and patterns") and Experience Seeking (ES) in a general population sample of adults, and subsequently investigated the genetic and environmental etiology between these traits. Self-reported data on autistic traits and ES were collected in a population sample (n = 559) of unrelated individuals, and in a population based family sample of twins and siblings (n = 560). Phenotypic, genetic and environmental associations between traits were examined in a bivariate model, accounting for sex and age differences. Phenotypically, ES correlated significantly with "preference for routine" and "imagination impairments" in both samples but was unrelated to the other autistic traits. Genetic analyses in the family sample revealed that the association between ES and "preference for routine" and "imagination impairments" could largely be explained by a shared genetic factor (89% and 70%, respectively). Our analyses demonstrated at a phenotypic and genetic level an inverse relationship between ES and specific autistic traits in adults. ES is associated with risk taking behavior such as substance abuse, antisocial behavior and financial problems. Future research could investigate whether autistic traits, in particular strong routine preference and impaired imagination skills, serve as protective factors for such risky behaviors. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

PubMed

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Spectral multivariate calibration without laboratory prepared or determined reference analyte values.

PubMed

Ottaway, Josh; Farrell, Jeremy A; Kalivas, John H

2013-02-05

An essential part to calibration is establishing the analyte calibration reference samples. These samples must characterize the sample matrix and measurement conditions (chemical, physical, instrumental, and environmental) of any sample to be predicted. Calibration usually requires measuring spectra for numerous reference samples in addition to determining the corresponding analyte reference values. Both tasks are typically time-consuming and costly. This paper reports on a method named pure component Tikhonov regularization (PCTR) that does not require laboratory prepared or determined reference values. Instead, an analyte pure component spectrum is used in conjunction with nonanalyte spectra for calibration. Nonanalyte spectra can be from different sources including pure component interference samples, blanks, and constant analyte samples. The approach is also applicable to calibration maintenance when the analyte pure component spectrum is measured in one set of conditions and nonanalyte spectra are measured in new conditions. The PCTR method balances the trade-offs between calibration model shrinkage and the degree of orthogonality to the nonanalyte content (model direction) in order to obtain accurate predictions. Using visible and near-infrared (NIR) spectral data sets, the PCTR results are comparable to those obtained using ridge regression (RR) with reference calibration sets. The flexibility of PCTR also allows including reference samples if such samples are available.

Environmental investigation for property transfer, Fort Holabird Crime Records Center. Environmental investigation and alternatives assessment. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finger, F.J.; Todd, Q.R.

An Environmental Investigation and Alternatives Assessment was conducted for the Crime Records Center at Fort Holabird in Baltimore, Maryland. Groundwater sampling, underground storage tank tightness testing, radon sampling, asbestos sampling, soil observations, and a review of previously collected data were used to develop remedial alternatives and recommendations. Removal and record keeping were recommended for asbestos. The recommendation for groundwater was no action.

The Sampling and Analysis Plan, Galena Airport and Kalakaket Creek Radio Relay Station, Alaska. Addendum

DTIC Science & Technology

1994-09-08

information deactivated during 1993. Currently, approximately 30 required in a QAPP per the U.S. Environmental caretakers are present at the facility...the total analytical cost. A subset of those Galena Airport-The current environmental samples collected and screened will be sent to an investigative...sampling report United States Environmental Protection Agency (US preparation. EPA), USAF, state, and local requirements. Ms. Sandy Smith is

Environmental Filtering Process Has More Important Roles than Dispersal Limitation in Shaping Large-Scale Prokaryotic Beta Diversity Patterns of Grassland Soils.

PubMed

Cao, Peng; Wang, Jun-Tao; Hu, Hang-Wei; Zheng, Yuan-Ming; Ge, Yuan; Shen, Ju-Pei; He, Ji-Zheng

2016-07-01

Despite the utmost importance of microorganisms in maintaining ecosystem functioning and their ubiquitous distribution, our knowledge of the large-scale pattern of microbial diversity is limited, particularly in grassland soils. In this study, the microbial communities of 99 soil samples spanning over 3000 km across grassland ecosystems in northern China were investigated using high-throughput sequencing to analyze the beta diversity pattern and the underlying ecological processes. The microbial communities were dominated by Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, and Planctomycetes across all the soil samples. Spearman's correlation analysis indicated that climatic factors and soil pH were significantly correlated with the dominant microbial taxa, while soil microbial richness was positively linked to annual precipitation. The environmental divergence-dissimilarity relationship was significantly positive, suggesting the importance of environmental filtering processes in shaping soil microbial communities. Structural equation modeling found that the deterministic process played a more important role than the stochastic process on the pattern of soil microbial beta diversity, which supported the predictions of niche theory. Partial mantel test analysis have showed that the contribution of independent environmental variables has a significant effect on beta diversity, while independent spatial distance has no such relationship, confirming that the deterministic process was dominant in structuring soil microbial communities. Overall, environmental filtering process has more important roles than dispersal limitation in shaping microbial beta diversity patterns in the grassland soils.

COMPARISON OF USEPA FIELD SAMPLING METHODS FOR BENTHIC MACROINVERTEBRATE STUDIES

EPA Science Inventory

Two U.S. Environmental Protection Agency (USEPA) macroinvertebrate sampling protocols were compared in the Mid-Atlantic Highlands region. The Environmental Monitoring and Assessment Program (EMAP) wadeable streams protocol results in a single composite sample from nine transects...