Grantee Research Project Results
2003 Progress Report: Data Management and Analysis
EPA Grant Number: R829458C004Subproject: this is subproject number 004 , established and managed by the Center Director under grant R829458
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for Air, Climate, and Energy Solutions
Center Director: Robinson, Allen
Title: Data Management and Analysis
Investigators: Noble, Peter
Institution: University of Southern Mississippi
Current Institution: University of Washington , University of Southern Mississippi
EPA Project Officer: Packard, Benjamin H
Project Period: December 1, 2001 through November 30, 2005 (Extended to May 20, 2007)
Project Period Covered by this Report: December 1, 2002 through November 30, 2003
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Aquatic Ecosystems
Objective:
The main objectives of this research project are to: (1) develop a Web-driven database for the deposition of metadata and the Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico (CEER-GOM) investigators' data; and (2) conduct statistical analysis of ecological data. The database will be constructed using MySQL, which allows project participants to execute Web-based interactions, including submit, annotate, sort, filter, and find specific data within a given experiment, and extract data from multiple experiments. The database will integrate data from all aspects of the study and include collection water quality, biogeochemistry, species/taxonomy, Terminal Restriction Length Polymorphism patterns, DNA sequences, sequence annotation, and DNA macroarray data, as well as other types of data deemed relevant. To meet the second objective of the project, Dr. Noble will determine relevant linkages that change with scale and with the dynamics of the system by using artificial neural networks (NNs), with crossvalidation through conventional multivariate statistics. These combined statistical approaches should yield similar but not identical results because NNs are better at dealing with the nonlinear nature of biological data than conventional statistics.
Progress Summary:
Software Development
The following new analysis tools have been added to Dr. Noble's Web site (http://noble.ce.washington.edu Exit ): Hurst calculator, Correlation Dimension (CD) calculator, and Fractal Dimension (FD) calculator. These calculators will be used to examine the long-term data sets obtained from the project collaborators. New calculators dealing with disorder and connectedness will be added to this Web site in the near future.
The Hurst calculator determines if a time series has memory—meaning, if we know the value of an environmental variable at time x, can we say anything about the value at time y? How much time does it take for this dependency to approach randomness? Obviously, if there is some dependency on previous events, we can estimate the value of y given x. Alternatively, if there is no dependency, we cannot estimate values of the environmental variables based on previous events. The Hurst calculator tells us if there is a dependency on previous events. The CD calculator is used to estimate the degrees of freedom of a time series. The CD calculator tells us how many factors are contributing to the dynamics of a time series. This calculator might provide us with important clues to the variability of environmental factors. The FD calculator provides information on the roughness of digital images. This software was developed to aid the biofilm group, though no one yet has had time to utilize the software.
The connectedness software (being developed) determines connection among variables by looking at short-term correlations. For example, if the concentration of chlorophyll A at time x is 10 mg/L, what variables (e.g., N and P) were correlated to concentration before time x? One assumes that the correlations indicate connectivity, though this might not be true in all cases. The connectedness of an aquatic ecosystem is determined by summing all the variables that were previously correlated (at some cutoff, e.g., ± 0.80) to chlorophyll A. The disorder software (being developed) determines the amount of entropy associated with individual variables as well as the entire system. The software is rooted in Information Theory. The basic premise here is that disorder in a time series is the probability that an event will occur over the probability of all possible event states times the log of this probability. Preliminary data analysis shows that disorder and connectedness change with time in pristine ecosystems such as the North Inlet estuary. The investigator believes that in eutrophic systems disorder and connectedness is low—the system is more ordered and less connected. Hence, this approach might provide an important tool for indicating eutrophication in estuarine ecosystems.
Manuscripts
The investigator has prepared a number of manuscripts reporting this research. A manuscript dealing with eutrophication of salt marsh estuaries based on phytoplankton community pigment analysis has been published. Two manuscripts dealing with the application of DNA microarrays and neural network analysis have been published in Applied and Environmental Microbiology and a third is being prepared for publication. Two additional manuscripts dealing with new neural network software have been written (one manuscript has been submitted for review and the other is being prepared for submission to the journal Science). Dr. Noble is collaborating with three groups at CEER-Atlantic Coast Environmental Indicators Consortium (J. Morris, University of South Carolina; L. Valdes and H. Pearl, University of North Carolina; Jay Pinckney (Texas A&M University). Dr. Noble has developed new software programs to analyze the connectedness and disorder associated with ecological variables. He believes that there is a relationship between connectedness and disorder of estuarine ecosystems and that these measures can be used as an indicator of eutrophication.
Collaborations With Atlantic Coast Environmental Indicators Consortium Projects
A Beta version of the neural network software is being tested by Drs. Jim Morris (University of South Carolina) and Chet Racocinski (CEER-GOM). The software is entitled "Neuronet" and runs on any PC or Macintosh computer. In addition to releasing the software for free distribution with publication of the Tribou, et al. (2004) paper, we intend on providing a Web-based tutorial on my Web site so that researchers can easily learn how to use the software for their EPA research.
Dr. Noble also is collaborating with Drs. Lexia Valdes and Hans Pearl (University North Carolina) and Jay Pinckney (Texas A&M University). He is analyzing the long-term data sets of the Neuse River, Galveston Bay, and North Inlet estuaries, and looking at the connectedness and disorder of environmental variables and phytoplankton communities.
Future Activities:
Dr. Noble will continue to add analysis tools to his Web site (http://noble.ce.washington.edu Exit ), and will use these calculators to examine the long-term data sets obtained from the collaborators. In addition, he will continue to conduct statistical analysis of the ecological data that are collected.
Journal Articles on this Report : 5 Displayed | Download in RIS Format
| Other subproject views: | All 18 publications | 10 publications in selected types | All 10 journal articles |
|---|---|---|---|
| Other center views: | All 175 publications | 58 publications in selected types | All 52 journal articles |
| Type | Citation | ||
|---|---|---|---|
|
|
El Fantroussi S, Urakawa H, Bernhard AE, Kelly JJ, Noble PA, Smidt H, Yershov GM, Stahl DA. Direct profiling of environmental microbial populations by thermal dissociation analysis of native rRNAs hybridized to oligonucleotide microarrays. Applied and Environmental Microbiology 2003;69(4):2377-2382. |
R829458C004 (2003) |
Exit Exit |
|
|
Gough HL, Dahl AL, Tribou E, Noble PA, Gaillard J-F, Stahl DA. Elevated sulfate reduction in metal-contaminated freshwater lake sediments. Journal of Geophysical Research: Biogeosciences 2008;113(G4):G04037, doi:10.1029/2008JG000738. |
R829458C004 (2003) R829458C004 (2004) |
Exit |
|
|
Morris JT, Porter D, Neet M, Noble PA, Schmidt L, Lapine LA, Jensen JR. Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization. International Journal of Remote Sensing 2005;26(23):5221-5234. |
R829458C004 (2003) R829458C004 (2005) R828677C003 (2004) R828677C003 (Final) |
Exit Exit |
|
|
Noble PA, Tymowski RG, Fletcher M, Morris JT, Lewitus AJ. Contrasting patterns of phytoplankton community pigment composition in two salt marsh estuaries in southeastern United States. Applied and Environmental Microbiology 2003;69(7):4129-4143. |
R829458C004 (2003) R829458C004 (2005) R826944 (2000) R826944 (Final) R828677C003 (2003) |
Exit Exit Exit |
|
|
Urakawa H, El Fantroussi S, Smidt H, Smoot JC, Tribou EH, Kelly JJ, Noble PA, Stahl DA. Optimization of single-base-pair mismatch discrimination in oligonucleotide microarrays. Applied and Environmental Microbiology 2003;69(5):2848-2856. |
R829458C004 (2003) R829458C004 (2005) |
Exit Exit Exit |
Supplemental Keywords:
population, community, ecosystem, watersheds, estuary, estuaries, Gulf of Mexico, nutrients, hypoxia, innovative technology, biomarkers, water quality, remote sensing, geographic information system, GIS, integrated assessment, risk assessment, fisheries, conservation, restoration, monitoring/modeling, Apalachicola Bay, Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico, CEER-GOM, CEER-ACE, Environmental Monitoring and Assessment Program, EMAP, Galveston Bay, Mobile Bay, benthic indicators, ecoindicator, ecological exposure, ecosystem monitoring, environmental indicators, environmental stress, estuarine ecoindicator, estuarine integrity., RFA, Scientific Discipline, ECOSYSTEMS, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, Ecology, Aquatic Ecosystems & Estuarine Research, Ecosystem/Assessment/Indicators, Ecosystem Protection, Aquatic Ecosystem, Ecological Effects - Environmental Exposure & Risk, Aquatic Ecosystems, Environmental Monitoring, Ecological Monitoring, Ecology and Ecosystems, Biology, Gulf of Mexico, Ecological Indicators, monitoring, ecoindicator, ecological exposure, neural network software, estuaries, estuarine integrity, data management, CEER-GOM, estuarine ecoindicator, environmental indicators, environmental stress, water qualityRelevant Websites:
http://noble.ce.washington.edu Exit
Progress and Final Reports:
Original AbstractMain Center Abstract and Reports:
R829458 Center for Air, Climate, and Energy Solutions Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R829458C001 Remote Sensing of Water Quality
R829458C002 Microbial Biofilms as Indicators of Estuarine Ecosystem Condition
R829458C003 Individual Level Indicators: Molecular Indicators of Dissolved Oxygen Stress in Crustaceans
R829458C004 Data Management and Analysis
R829458C005 Individual Level Indicators: Reproductive Function in Estuarine Fishes
R829458C006 Collaborative Efforts Between CEER-GOM and U.S. Environmental Protection Agency (EPA)-Gulf Ecology Division (GED)
R829458C007 GIS and Terrestrial Remote Sensing
R829458C008 Macrobenthic Process Indicators of Estuarine Condition for the Northern Gulf of Mexico
R829458C009 Modeling and Integration
The 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.
Project Research Results
10 journal articles for this subproject
Main Center: R829458
175 publications for this center
52 journal articles for this center