A General Test for Gene-Environment Interaction in Sib Pair-based Association Analysis of Quantitative Traits

Several association studies support the hypothesis that genetic variants can modify the influence of environmental factors on behavioral outcomes, i.e., G 9 E interaction. The case-control design used in these studies is powerful, but population stratification with respect to allele frequencies can give rise to false positive or false negative associations. Stratification with respect to the environmental factors can lead to false positives or false negatives with respect to environmental main effects and G 9 E interaction effects as well. Here we present a model based on Fulker et al. (1999) and Purcell (2002) for the study of G 9 E interaction in family-based association designs, in which the effects of stratification can be controlled. Simulations illustrate the power to detect genetic and environmental main effects, and G 9 E interaction effects for the sib pair design. The power to detect interaction was studied in eight different situations, both with and without the presence of population stratification, and for categorical and continuous environmental factors. Results show that the power to detect genetic and environmental main effects, and G 9 E interaction effects, depends on the allele frequencies and the distribution of the environmental moderator. Admixture effects of realistic effect size lead only to very small stratification effects in the G 9 E component, so impractically large numbers of sib pairs are required to detect such stratification

Cross-shelf and seasonal variation in larval fish assemblages on the southeast United States continental shelf off the coast of Georgia

Seasonal and cross-shelf patterns were investigated in larval fish assemblages on the continental shelf off the coast of Georgia. The influence of environmental factors on larval distributions also was examined, and larval transport processes on the shelf were considered. Ichthyoplankton and environmental data were collected approximately every other month from spring 2000 to winter 2002. Ten stations were repeatedly sampled along a 110-km cross-shelf transect, including four stations in the vicinity of Gray’s Reef National Marine Sanctuary. Correspondence analysis (CA) on untransformed community data identified two seasonal (warm weather [spring, summer, and fall] and winter) and three cross-shelf larval assemblages (inner-, mid-, and outer-shelf ). Five environmental factors (temperature, salinity, density, depth of the water column, and stratification) were related to larval cross-shelf distribution. Specifically, increased water column stratification was associated with the outer-shelf assemblage in spring, summer, and fall. The inner shelf assemblage was associated with generally lower temperatures and lower salinities in the spring and summer and higher salinities in the winter. The three cross-shelf regions indicated by the three assemblages coincided with the location of three primary water masses on the shelf. However, taxa occurring together within an assemblage were transported to different parts of the shelf; thus, transport across the continental shelf off the coast of Georgia cannot be explained solely by twodimensional physical factors

Integration of genetic and epigenetic markers for risk stratification: opportunities and challenges

Common genetic susceptibility variants could be used for risk stratification in risk-tailored cancer screening and prevention programmes. Combining genetic variants with environmental risk factors would improve risk stratification. Epigenetic changes are surrogate markers of environmental exposures during individual's lifetime. Integrating epigenetic markers, in lieu of environmental exposure data, with genetic markers would potentially improve risk stratification. Epigenetic changes are reversible and acquired gradually, providing potentials for prevention and early detection strategies. The epigenetic changes are tissue-specific and stage-of-development-specific, raising challenges in choice of sample and timing for evaluation of cancer-associated changes. The Horizon 2020 funded research programme, FORECEE, using empirical data, will investigate the value of integration of epigenomics with genomics for risk prediction and prevention of women-specific cancers

PANEL STRATIFICATION IN META-ANALYSIS OF ENVIRONMENTAL AND NATURAL RESOURCE ECONOMIC STUDIES

Meta-analyses of past research outcomes are becoming more popular, however, the issue of the panel nature of data has not been empirically investigated. We test various forms of data stratifications into panels for outdoor recreation economic studies but do not find any significant effects, possibly because of inherent data complexity.Environmental Economics and Policy, Resource /Energy Economics and Policy,

Making environmental assessments of biomass production systems comparable worldwide

Global demand for agricultural and forestry products fundamentally affects regional land-use change associated with environmental impacts (EIs) such as erosion. In contrast to aggregated global metrics such as greenhouse gas (GHG) balances, local/regional EIs of different agricultural and forestry production regions need methods which enable worldwide EI comparisons. The key aspect is to control environmental heterogeneity to reveal man-made differences of EIs between production regions. Environmental heterogeneity is the variation in biotic and abiotic environmental conditions. In the present study, we used three approaches to control environmental heterogeneity: (i) environmental stratification, (ii) potential natural vegetation (PNV), and (iii) regional environmental thresholds to compare EIs of solid biomass production. We compared production regions of managed forests and plantation forests in subtropical (Satilla watershed, Southeastern US), tropical (Rufiji basin, Tanzania), and temperate (Mulde watershed, Central Germany) climates. All approaches supported the comparison of the EIs of different land-use classes between and within production regions. They also standardized the different EIs for a comparison between the EI categories. The EIs for different land-use classes within a production region decreased with increasing degree of naturalness (forest, plantation forestry, and cropland). PNV was the most reliable approach, but lacked feasibility and relevance. The PNV approach explicitly included most of the factors that drive environmental heterogeneity in contrast to the stratification and threshold approaches. The stratification approach allows consistent global application due to available data. Regional environmental thresholds only included arbitrarily selected aspects of environmental heterogeneity;they are only available for few EIs. Especially, the PNV and stratification approaches are options to compare regional EIs of biomass or crop production such as erosion, biodiversity, or water quality impacts worldwide and thereby complement existing metrics assessing global EIs such as GHG emissions

Making environmental assessments of biomass production systems comparable worldwide

Global demand for agricultural and forestry products fundamentally affects regional land-use change associated with environmental impacts (EIs) such as erosion. In contrast to aggregated global metrics such as greenhouse gas (GHG) balances, local/regional EIs of different agricultural and forestry production regions need methods which enable worldwide EI comparisons. The key aspect is to control environmental heterogeneity to reveal man-made differences of EIs between production regions. Environmental heterogeneity is the variation in biotic and abiotic environmental conditions. In the present study, we used three approaches to control environmental heterogeneity: (i) environmental stratification, (ii) potential natural vegetation (PNV), and (iii) regional environmental thresholds to compare EIs of solid biomass production. We compared production regions of managed forests and plantation forests in subtropical (Satilla watershed, Southeastern US), tropical (Rufiji basin, Tanzania), and temperate (Mulde watershed, Central Germany) climates. All approaches supported the comparison of the EIs of different land-use classes between and within production regions. They also standardized the different EIs for a comparison between the EI categories. The EIs for different land-use classes within a production region decreased with increasing degree of naturalness (forest, plantation forestry, and cropland). PNV was the most reliable approach, but lacked feasibility and relevance. The PNV approach explicitly included most of the factors that drive environmental heterogeneity in contrast to the stratification and threshold approaches. The stratification approach allows consistent global application due to available data. Regional environmental thresholds only included arbitrarily selected aspects of environmental heterogeneity;they are only available for few EIs. Especially, the PNV and stratification approaches are options to compare regional EIs of biomass or crop production such as erosion, biodiversity, or water quality impacts worldwide and thereby complement existing metrics assessing global EIs such as GHG emissions

Modeling Demand for Outdoor Recreation Settings with Choice Based Data Accounting for Exogenous and Endogenous Stratification

Estimating regional demand models by pooling different samples without correcting for such differences causes model misspecification as each sample belongs to a different population. Weighted regression using Pseudolikelihood to account for differences in sample population with adjustment for heteroskedasticity improves efficiency but the estimates are biased. We estimate regional demand for National Forest settings types in the southeastern states of U.S using weighted and unweighted regression. Using estimation of demand for National Forests as a case study, we resolve problems relating to inference about the data generating process when different samples are pooled together. We show that though efficiency of weighted estimates improves after correcting for heteroskedasticity, they still remain biased as the weights interact with covariates to explain part of model misspecification. In this paper, we show that it is best to use unweighted regression including interactions with weights as covariates.exogenous stratification, endogenous stratification, choice based data, outdoor recreation, Environmental Economics and Policy, Q000, Q500,

Stratification requirements for seed dormancy alleviation in a wetland weed.

Echinochloaoryzicola(syn.E. phyllopogon) is an exotic weed of California rice paddies that has evolved resistance to multiple herbicides. Elimination of seedlingsthroughcertain weed control methods can limit the spread of this weed, but is contingent on accurate predictions of germination and emergence timing, which are influenced by seed dormancy levels.In summer annuals, dormancy can often be relieved through stratification, a period of prolonged exposure to cold and moist conditions.We used population-based threshold models to quantify the effects of stratification on seed germination of four E. Oryzicola populations at a range of water potential (Ψ) and oxygen levels. We also determined how stratification temperatures, moisture levels and durations contributed to dormancy release. Stratification released dormancy by decreasing base Ψ and hydrotimerequired for germination and by eliminating any germination sensitivity to oxygen. Stratification also increased average germination rates (GR), which were used as a proxy for relative dormancy levels. Alternating temperatures nearly doubled GR in all populations, indicating that seeds could be partially dormant despite achieving high final germination percentages. Stratification at Ψ = 0 MPa increased GR compared to stratification at lower water potentials, demonstrating that Ψ contributed to regulating dormancy release. Maximum GR occurred after 2-4 weeks of stratification at 0 MPa; GR were often more rapid for herbicide-resistant than for herbicide-susceptible seeds, implying greater dormancy in the latter. Manipulation of field conditions to promote dormancy alleviation of E. oryzicola seeds might improve the rate and uniformity of germination for seed bank depletion through seedling weed control. Our results suggest field soil saturation in winter would contribute towards E. oryzicola dormancy release and decrease the time to seedling emergence

Environmental aspects of tensile membrane enclosed spaces

Buildings enclosed by fabric membranes are very sensitive to changes in environmental conditions as a result of their low mass and low thermal insulation values. Development in material technology and the understanding of the structural behaviour of tensile membrane structures along with the vast progress in computer formfinding software, has made it possible for structural design of tensile membrane structures to be approached with almost total confidence. On the contrary, understanding of the environmental behaviour in the spaces enclosed by fabric membrane and their thermal performance is still in its infancy, which to some extent has hindered their wide acceptance by the building industry. The environmental behaviour of tensile membrane structures is outlined and the possible use of the fabric’s topology and geometry particularly to enhance ventilation rates and airflow velocities within the enclosed space is discussed. A need for further research in this area is identified in order to fully realise the potential benefits offered by these structures