Spatial representation of bioaccumulation studies
2003
- 7Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Thesis / Dissertation Description
"Aquatic biological species form food webs in the LaBranche Wetlands, Louisiana. This wetland is characterized by a series of interconnected bayous forming a network. This project integrates an aquatic food web bioaccumulation model for hydrophic organic contaminants with an efficient spatial representation of the environment. This research integrates a food web model viewed with a spatial network of the underlying geography and environmental parameters to be used as a portable tool to study other networks of interconnected waterways given the necessary geographic, environmental, physicochemical and biological input data. In particular, it targets geographic study regions (bayous) that can be represented as linear features in a spatial network model using tools available in a geographic information system (GIS). Data stored as different events on the dynamically segmented linear feature, to be used in combination with rules, allow spatial representation of different species within their natural home range. These home ranges are modeled as segments in the network, based on dynamic segmentation methodology. Food web bioaccumulation models assume steady- state and transient conditions and use average environmental parameters. The model is used as a portable tool for another site. A contaminated riverine system, the Upper East Fork Poplar Creek, Oak Ridge, TN, was selected as a test site due to the availability of input parameters"--Abstract, page iii.
Bibliographic Details
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