2003 Progress Report: Combining Environmental Data SetsEPA Grant Number: R829095C001
Subproject: this is subproject number 001 , established and managed by the Center Director under grant R829095
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP)
Center Director: Urquhart, N. Scott
Title: Combining Environmental Data Sets
Investigators: Hoeting, Jennifer A. , Breidt, F. Jay , Davis, Richard A. , Gitelman, Alix I. , Reich, Robin M. , Stevens, Don L. , Weisberg, Steven B.
Current Investigators: Hoeting, Jennifer A. , Breidt, F. Jay , Davis, Richard A. , Gitelman, Alix I. , Johnson, Devin S. , Ritter, Kerry J. , Stevens, Don L.
Institution: Colorado State University , Oregon State University , Southern California Coastal Water Research Project Authority , University of Alaska - Fairbanks
EPA Project Officer: Packard, Benjamin H
Project Period: October 1, 2001 through September 30, 2006
Project Period Covered by this Report: October 1, 2002 through September 30, 2003
RFA: Research Program on Statistical Survey Design and Analysis for Aquatic Resources (2001) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration , Water and Watersheds , Water , Ecosystems
The objective of this research project is to develop approaches for spatio-temporal design and modeling to further understanding of aquatic resources.
Models for Compositional Data (D.S. Johnson, Colorado State University [CSU], Ph.D. student and J.A. Hoeting, CSU)
The development of new models and methodology for the analysis of compositional data continues. These models will be used to develop a better understanding of species traits of benthic invertebrates and may be useful in the development of indicators of stream fitness. Johnson successfully defended his Ph.D. dissertation in August 1, 2003. His thesis is entitled “Bayesian Analysis of state-space models for discrete compositions.” Devin is now Assistant Professor in the Department of Mathematics Sciences, University of Alaska–Fairbanks. In October 2003, Hoeting nominated Johnson’s thesis for the Savage Award for the top thesis in Bayesian statistics. This is joint research with CSU researchers funded by other STAR projects (L. Poff and B. Bledsoe). We also received assistance from Alan Herlihy (Oregon State University [OSU], U.S. Environmental Protection Agency [EPA]). Johnson and Hoeting gave several talks, published one paper, and are working on several other papers on this topic.
Modeling of Mid-Atlantic Highlands Streams Assessment (MAHA) Data (B. Kellum, CSU; J.A. Hoeting, CSU; N.S. Urquhart, CSU)
The goal of this regression modeling was to predict acid neutralizing capacity at unobserved locations based on the MAHA data. We demonstrated directional spatial correlation in the MAHA data. Brett Kellum successfully defended his M.S. thesis on this work in Fall 2002. A technical report resulting from this work is available on the Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP) Web Site. A poster was presented at the 2003 joint STARMAP/Programon Designs and Models for Aquatic Resource Surveys (DAMARS) meeting. Project completed.
Design and Analysis Methods for Geo-referenced Binary Data (M. Leecaster, Idaho National Engineering and Environmental Laboratory; K.J. Ritter and S. B. Weisberg, Southern California Coastal Water Research Project)
Our goals are to determine appropriate grid size for producing maps using Markov random field models and to compare to geostatisical modeling approaches. We modified software for estimation of parameters of autologistic model to allow for hexagon grid. We performed initial simulations to determine appropriate enhancement of Environmental Monitoring and Assessment Program (EMAP) grid for estimation of variogram and mapping. Leecaster gave a presentation at the 2003 joint STARMAP/DAMARS meeting.
New Project: Statistical Computing Book (J. Hoeting, CSU)
Topics for the book are: Optimization, Numerical integration, EM algorithm, Simulation, Basic and Advanced MCMC methods, Bootstraping, Density estimation, Smoothing. The intended audience is graduate students and researchers in statistics, as well as scientists in other fields. This book will be co-authored with G. Givens (CSU). We have a contract with Wiley for an anticipated publication date in late 2004/early 2005.
New Project: Spatial Modeling of Binary Aquatic Data (A. Merton, CSU and J. Hoeting, CSU)
The goal of this project is to advance statistical methods for modeling stream network data. This project is in its early stages, but it is anticipated that this work will lead to Merton’s Ph.D. thesis.
New Project: Hierarchical Models for Analyzing Radio Telemetry Habitat Association Data (M. Dailey, CSU, A. Gitelman, OSU, and F. Ramsey, OSU)
Our goal is to develop a hierarchical Bayesian model to model radio telemetry data on habitat selection by fish in Oregon streams.
We anticipate submission of two to three manuscripts to statistical and or ecological peer-reviewed journals by December 31, 2004. Hoeting and Johnson are to give an invited talk at the Joint Statistical Meeting, August 2004. Dailey plans to present work at the Joint Statistical Meeting (contributed talk) and 2004 Joint STARMAP/DAMARS meeting. Hoeting and Davis will participate in the National Science Foundation (NSF)-sponsored workshop “Statistics in Ecology” in Jackson Hole, Wyoming, in December 2004. A peer-reviewed journal article may be submitted related to this conference. Hoeting is the organizer for the American Statistical Association Section on Statistics and the Environment (ENVR) 2004 Computational Environmetrics workshop to be held in Chicago in the fall of 2004.
Leecaster and Ritter will complete simulation study and determine recommendations for enhancement of EMAP grid. This will be submitted to a peer-reviewed journal. If funds permit, they also will develop a methodology to determine optimal sample locations to enhance EMAP with the goal of minimizing the variance of the variogram estimate.
Merton will settle on a Ph.D. topic. Possible submission of a paper on Bayesian model averaging for spatial models. Merton will give a presentation at the Joint STARMAP/DAMARS conference in the fall of 2004.
Hoeting is working on a possible collaboration with Uli Sneider of the National Center for Atmospheric Research on perfect sampling methods for binary spatial models. If successful, this work should lead to submission of a manuscript to a peer-reviewed journal.
Integration of STARMAP activities with our NSF Integrative Graduate Education and Research Training Program for Interdisciplinary Mathematics, Ecology and Statistics (PRIMES) continues. PRIMES visitors like J. Berger (Duke) and A. Gelfand (Duke) enrich the STARMAP activities.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
|Other subproject views:||All 78 publications||10 publications in selected types||All 8 journal articles|
|Other center views:||All 302 publications||54 publications in selected types||All 42 journal articles|
||Johnson DS, Hoeting JA. Autoregressive models for capture-recapture data:a Bayesian approach. Biometrics 2003;59(2):341-350.||
Supplemental Keywords:latent processes, Matern covariance function, model selection, remote sensing, sampling design, path analysis, kernel regression, thin plate splines, small area estimation, geographic information system, GIS, tessellation stratified sampling, water quality, land cover, land use, accuracy, precision, outreach, distance learning, web-based learning, needs-based instruction, accommodating cultural differences, management, efficiency,, RFA, Scientific Discipline, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, Aquatic Ecosystem, Environmental Monitoring, EMAP, ecosystem monitoring, statistical survey design, spatial and temporal modeling, aquatic ecosystems, water quality, Environmental Monitoring and Assessment Program, modeling ecosystems
Progress and Final Reports:Original Abstract
Main Center Abstract and Reports:R829095 Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP)
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R829095C001 Combining Environmental Data Sets
R829095C002 Local Inferences from Aquatic Studies
R829095C003 Development and Evaluation of Aquatic Indicators
R829095C004 Extension of Expertise on Design and Analysis to States and Tribes
R829095C005 Integration and Coordination for STARMAP