Grantee Research Project Results
2006 Progress Report: A Statistical Modeling Methodology for the Detection, Quantification, and Prediction of Ecological Thresholds
EPA Grant Number: R832447Title: A Statistical Modeling Methodology for the Detection, Quantification, and Prediction of Ecological Thresholds
Investigators: Richardson, Curtis J. , Qian, Song S.
Institution: Duke University
EPA Project Officer: Packard, Benjamin H
Project Period: February 1, 2005 through June 30, 2007 (Extended to August 31, 2008)
Project Period Covered by this Report: February 1, 2005 through June 30, 2006
Project Amount: $278,876
RFA: Exploratory Research: Understanding Ecological Thresholds In Aquatic Systems Through Retrospective Analysis (2004) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Water
Objective:
The primary objective of this research project is to develop a statistical modeling approach for the detection and quantification of ecological thresholds that can be used in aquatic ecosystems worldwide. Specifically, we will use a Bayesian hierarchical modeling approach to integrate the single-species changepoint analysis method developed by Qian, et al. (2003) to study the interactions among fast and slow responding species or ecological metrics indicating alternative stable states. Under this structural approach, the resulting species/metric thresholds will be integrated to form an ecosystem-level threshold distribution. A risk-based criteria approach will be developed to assess ecological resilience and predict the threshold for alternative state changes.
Progress Summary:
In the past year, we focused our work in two areas: (1) organized our database inventory, selected key indicator species, and (2) developed and are now testing a new integrated statistical method for threshold analysis.
Database mining and analysis are ongoing. We are going through all data files related to the threshold studies that were done in the Everglades and are checking quality assurancy/quality control (QA/QC) records. This is a time-consuming step, and we expect to complete the task before the end of the summer. We have thoroughly reviewed our existing methods, summarized in Qian, et al. (2003). The review concluded that the traditional confidence interval is not a suitable tool for summarizing uncertainty in ecological threshold. Our Bayesian approach resulted in a more relevant way for summarizing uncertainty and linking the estimated ecological threshold to environmental standards. In a separate study, we investigated the possible applications of a multilevel analysis of variance (ANOVA) method. The multilevel ANOVA model is a potentially valuable tool for ecological threshold study.
Future Activities:
In the second year of the project, we expect to: (1) complete database inventory and QA/QC verification; (2) complete the development of our multilevel threshold model, which will have the features of the univariate changepoint model as presented in Qian, et al. (2003) and the multilevel structure as described by Gelman (2005) (the objective of this approach is to identify the correlations structure between multiple ecological indices); and (3) test the multilevel changepoint model using the Everglades experimental data.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
Other project views: | All 8 publications | 2 publications in selected types | All 2 journal articles |
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Type | Citation | ||
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Qian SS, Shen Z. Ecological applications of multilevel analysis of variance. Ecology 2007;88(10):2489-2495. |
R832447 (2006) R832447 (2007) R832447 (Final) |
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Richardson CJ, King RS, Qian SS, Vaithiyanathan P, Qualls RG, Stow CA. Estimating ecological thresholds for phosphorus in the Everglades. Environmental Science & Technology 2007;41(23):8084-8091. |
R832447 (2006) R832447 (2007) R832447 (Final) |
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Supplemental Keywords:
total phosphorus; soluble reactive phosphorus; ecological thresholds, Bayesian changepoint analysis, credible interval,, RFA, Scientific Discipline, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, Aquatic Ecosystem, Environmental Monitoring, Ecology and Ecosystems, species interaction, ecosystem monitoring, statistical modeling, aquatic ecosystems, ecological classification, aquatic indicatorsRelevant Websites:
http://www.env.duke.edu/wetland Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.