Research Participation Program
U.S. Environmental Protection Agency
Office of Research and Development
National Center for Environmental Assessment
Cincinnati, OH
Project #: EPA-ORD/NCEA-CIN-2014-01
Statistical Models/Indicator Datasets to Predict Aquatic
Condition on Stream Networks of Watersheds
Project Description:
A postdoctoral research training opportunity is currently available at the U.S. Environmental
Protection Agency (EPA), National Center for Environmental Assessment (NCEA). This
appointment will be served at the NCEA and the National Exposure Research Laboratory–
Ecological Exposure Research Division (NERL-EERD) facilities in Cincinnati, Ohio.
NCEA conducts high priority, science based assessments for EPA. Examples include a draft review
and synthesis of connectivity of streams and wetlands to downstream waters, the EPA’s
Mountaintop Mining Assessment, the First Triennial Biofuels Report to Congress, and the Bristol
Bay Assessment.
NERL-EERD focuses on understanding how ecosystems come into contact with pollutants or
stressors, and how ecosystems, and the plant and animal life within them, respond to these
exposures. This research informs decisions to support ecosystem protection and restoration by
providing a sound biological foundation for ecological exposure science. Research is conducted at a
variety of scales from molecular to ecosystem levels.
The National Aquatic Resource Surveys (NARS) were designed to determine and report on the
condition of the nation’s waters. NARS can answer questions about the extent of U.S. waters that
support healthy ecosystems, summarized by region. NARS data, by themselves, cannot be used to
determine the spatial distribution of aquatic condition within a region, e.g., where individual good
and poor condition streams and lakes are found. Such information is critical for resource managers
to prioritize management across watersheds. The objective of this research is to develop methods
and indicators that will contribute to national assessments of aquatic resource condition.
The research participant will use data from NARS and other surveys to develop statistical models
that relate condition of specific aquatic resources (e.g., streams or estuaries) to spatial indicators that
can be derived from nationally available datasets. Once these models are developed for a sampled
resource, condition could then be estimated for the entire population of that resource. In order to
develop these models, a number of statistical approaches will be examined, including geostatistical
analysis using spatial stream network modeling and functional process zones using cluster analysis.
This project consists of two research components: (1) to model spatially continuous stream
networks that incorporate autocorrelated errors at four watersheds in the U.S. based on a
generalized linear mixed model framework so that prediction (kriging) or block predictions (block
kriging) can be done on biotic and water chemistry data in those watershed; and (2) to conduct
geographic information system (GIS) and cluster analysis of geomorphological data for river
classification based on functional process zones (FPZ).
The participant may be involved in the following activities:
 Using geospatial datasets of river and stream networks, geomorphology and land cover GIS
data for specific watersheds to develop geodatabases of stream networks
 Developing spatial statistical models (e.g., spatial stream networks) relating spatial data to
independent variables (various indicators of stream condition) to predict condition at the
four watersheds
 Conducting rapid river classification using GIS-delineated functional process zones
 Applying river classification at regional and national scales
 Using GIS to develop new spatial indicators
 Developing similar modeling approach for other aquatic resources (i.e., lakes, estuaries, or
wetlands)
 Conducting geographic data mining, spatial hierarchical modeling, and spatial statistical
analysis.
The participant will learn about the use of spatial indicators and aquatic monitoring data, and will
learn to develop, test, and apply models that relate monitoring data to spatial indicators. S/he will
have access to a team of experts collaborating in and across disciplines on problems of crucial
importance. S/he will also be encouraged to communicate his/her research results through peerreviewed publications, presentations at meetings of professional societies, and seminars.
Qualifications:
Applicants must have received a doctoral degree in spatial ecology, geography, spatial statistics, or
aquatic ecology within five years of the desired starting, or completion of all requirements for the
degree should be expected prior to the starting date. Experience with ArcGIS, Python, and R and
the use of monitoring data are highly desirable.
The program is open to all qualified individuals without regard to race, sex, religion, color, age,
physical or mental disability, national origin, or status as a Vietnam era or disabled veteran. U.S.
citizenship or lawful permanent resident status is preferred (but can also hold an appropriate visa
status, however, an H1B visa is not appropriate).
The appointment is full-time for one year and may be renewed for up to two additional years upon
recommendation of NCEA and subject to availability of funds. The participant will receive a
monthly stipend. The participant must show proof of health and medical insurance. Funding may be
made available to reimburse a research participant's travel expenses to support field studies and to
present the results of his/her research at scientific conferences. No funding will be made available to
cover travel costs for pre-appointment visits, relocation costs, tuition and fees, or a participant's
health insurance. The participant does not become an EPA employee.
Technical Contact:
The contacts for this project are Michael McManus, NCEA (mcmanus.michael@epa.gov), and
Joseph Flotemersch, NERL (flotemersch@joseph.gov).
How to Apply:
An application can be found at http://orise.orau.gov/epa/applicants/application.htm. Please
reference Project #EPA-ORD/NCEA-CIN-2014-01 when calling or writing for information.