United States Environmental Protection Agency

About: United States Environmental Protection Agency is a government organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Population & Environmental exposure. The organization has 13873 authors who have published 26902 publications receiving 1191729 citations. The organization is also known as: EPA & Environmental Protection Agency.

Incorporating concentration dependence in stable isotope mixing models

Abstract: Stable isotopes are often used as natural labels to quantify the contributions of multiple sources to a mixture. For example, C and N isotopic signatures can be used to determine the fraction of three food sources in a consumer's diet. The standard dual isotope, three source linear mixing model assumes that the proportional contribution of a source to a mixture is the same for both elements (e.g., C, N). This may be a reasonable assumption if the concentrations are similar among all sources. However, one source is often particularly rich or poor in one element (e.g., N), which logically leads to a proportionate increase or decrease in the contribution of that source to the mixture for that element relative to the other element (e.g., C). We have developed a concentration-weighted linear mixing model, which assumes that for each element, a source's contribution is proportional to the contributed mass times the elemental concentration in that source. The model is outlined for two elements and three sources, but can be generalized to n elements and n+1 sources. Sensitivity analyses for C and N in three sources indicated that varying the N concentration of just one source had large and differing effects on the estimated source contributions of mass, C, and N. The same was true for a case study of bears feeding on salmon, moose, and N-poor plants. In this example, the estimated biomass contribution of salmon from the concentration-weighted model was markedly less than the standard model estimate. Application of the model to a captive feeding study of captive mink fed on salmon, lean beef, and C-rich, N-poor beef fat reproduced very closely the known dietary proportions, whereas the standard model failed to yield a set of positive source proportions. Use of this concentration-weighted model is recommended whenever the elemental concentrations vary substantially among the sources, which may occur in a variety of ecological and geochemical applications of stable isotope analysis. Possible examples besides dietary and food web studies include stable isotope analysis of water sources in soils, plants, or water bodies; geological sources for soils or marine systems; decomposition and soil organic matter dynamics, and tracing animal migration patterns. A spreadsheet for performing the calculations for this model is available at http://www.epa.gov/wed/pages/models.htm.

The Development of a Standardized Neighborhood Deprivation Index

Abstract: Census data are widely used for assessing neighborhood socioeconomic context. Research using census data has been inconsistent in variable choice and usually limited to single geographic areas. This paper seeks to a) outline a process for developing a neighborhood deprivation index using principal components analysis and b) demonstrate an example of its utility for identifying contextual variables that are associated with perinatal health outcomes across diverse geographic areas. Year 2000 U.S. Census and vital records birth data (1998–2001) were merged at the census tract level for 19 cities (located in three states) and five suburban counties (located in three states), which were used to create eight study areas within four states. Census variables representing five socio-demographic domains previously associated with health outcomes, including income/poverty, education, employment, housing, and occupation, were empirically summarized using principal components analysis. The resulting first principal component, hereafter referred to as neighborhood deprivation, accounted for 51 to 73% of the total variability across eight study areas. Component loadings were consistent both within and across study areas (0.2–0.4), suggesting that each variable contributes approximately equally to “deprivation” across diverse geographies. The deprivation index was associated with the unadjusted prevalence of preterm birth and low birth weight for white non-Hispanic and to a lesser extent for black non-Hispanic women across the eight sites. The high correlations between census variables, the inherent multidimensionality of constructs like neighborhood deprivation, and the observed associations with birth outcomes suggest the utility of using a deprivation, index for research into neighborhood effects on adverse birth outcomes.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

The BioPAX community standard for pathway data sharing

Abstract: Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.