Committee (see section on Management Structure). Research tasks will be prioritized considering the
following criteria:

1) Direct linkages to ReVA’s objectives or deliverables;

2) linkages to other ReVA tasks;

3) adherence to quality assurance and metadata standards;

4) timeline and needed outyear support;

5) plans for evaluating research results;

6) applicability to other regions;

7) planned technology transfer; and

8) client interest (see Appendix A for proposed task description format).

ReVA will not develop an overall research plan, but will periodically update this strategy as the program
and issues evolve.

4.1 Mapping Exposures
4.1.1 Step One

The first step in ReVA will be the development of spatial data sets for the Mid-Atlantic assessment area
(Figure 3). This will involve all relevant data that are available for the entire region and can be
represented spatially, i.e., a value for each point on the regional map. Spatially explicit data are required
to compare risk across the entire region (Hunsaker et al. 1992). The data will include infrastructure (e.g.,
roads), stressors (e.g., atmospheric deposition, Chang et al. 1987, and chemical inputs, USDA 1996),
landscape characterization data (e.g., Jones et al. 1996), sensitive resources (e.g., wetlands) and ecological
endpoints (¢.g., avian biodiversity, Flather et al. 1992). Spatial data will be retained at the finest
resolution available. This will keep options open for reporting assessments at a variety of spatial units
(O'Neill et al. 1997). Developing the spatial databases involves addressing three important issues:

1) Which data to include;
2) reaggregation of data into consistent reporting units; and

3) how to estimate and retain the uncertainties in the data.

Recent research reported in the Landscape Atlas (Jones et al. 1997), the ReVA Stressor Atlas (Lunetta et
al. 1999), and the Index of Watershed Indicators (IWI) (http://www.epa.gov/iwi/) indicate that
comprehensive regional databases exist for a surprising number of environmental stressors and ecological
resources. The emphasis in ReVA will be on utilizing the wealth of available data. Collection of new
data will not be emphasized, particularly for the Phase One assessment.

Where critical gaps exist, ReVA will conduct indicator research. For example, none of the current
landscape indicators address distance between patches. Since interpatch distance is known to be critical
to the impact of habitat fragmentation on wildlife, the new indicator fills a critical gap (Keitt et al. 1997,
Barabasi and Reka 1999, Sutherland et al. 2000). This research will be conducted as a joint project of
ReVA and the Landscape Sciences Program (NERL, Environmental Sciences Division, ESD).

Some indicators will be direct measures of stress, such as projected land development or pesticide
concentrations in streams. Other indicators will be the output of models, such as sulfur dioxide

Page 13 of 43


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Page 34 of 43


7.3, ReVA Information Management and Data Policies

Adherence to management principles and establishment of a management plan are vital to the success of
any program. While these involve a significant level of up-front effort, the aim is to alleviate future
problems. Nowhere is this more important than in the case of information and data management. By
establishing a common understanding of what data are available, where they are stored, how they are
maintained, and how they can be accessed, ReVA intends to ease the individual researcher’s burden for
information management. These information management practices and data policies will be further
elaborated in a separate document that is currently under development. General policies for information
management include:

1) Adherence to Federal Geographic Data Committee (FGDC) metadata standards for all spatial data
sets. Additional metadata documentation will likely be suggested for derived databases to document
uncertainties and errors associated with sequential steps in developing regional scale models. FGDC
metadata standards can be found at: http://www.fgdc.gov/metadata/csdgm/.

2) Use of a central metadata server to facilitate use of available data among all ReVA PIs and to ensure
use of the same versions of these data. ORD’s Environmental Information Management System
(EIMS) is an Oracle-based relational database system used to store and retrieve metadata information
regarding EPA products. While the actual locations of the information objects may be distributed,
having a common source from which to search for available information will provide researchers with
a powerful tool. It should be noted that EIMS is equipped with security features that allow differential
access control to all its documents, by originator, group, EPA or the public. EIMS can be accessed at:
http://www.epa.gov/eims or through ReVA’s website: http://www.epa.gov/reva.

3) Use of Terrasoar as ReVA’s spatial data warehouse. While the metadata for spatial products will be
available through EIMS, a system called Terrasoar, because of its unique search, browse, and ordering
capability, will serve as the data warehouse for ReVA spatial data. Terrasoar can be access at:
http://epawww.epa.gov/j02remsn/download.html. (Note: Terrasoar is currently only available for
internal EPA use, however links between Terrasoar and EIMS are envisioned in the future.)

4) Establishment and support for the following goal regarding an exclusivity period: “Research products
developed with support from the ReVA program will be deemed limited access for a period of one (1)
year, during which researchers will perform all the necessary tasks required for publication. The term
limited is intended to convey access by the ReVA core team and other ReVA principal investigators
while disallowing overall public access. Providing limited access during the first year allows ReVA
to continue progress in integrating the various and disparate areas of research into a cohesive
assessment while not compromising the intellectual investments made by individual researchers.
After one year, data will be made available to the public.” While our goal is to make data available as
soon as possible, ReVA will adhere to ORD and/or agency policies regarding data exclusivity.

Page 30 of 43


7 J0 6€ eed

Phase

Report Research Category
Principal Contribution Exposure Communicating
Task Title Investigator | Division/Org | to Objective | 1 | 2* Stressors Receptors | Assessment Results
Decision-Support tool for Joe Williams NRMRL 1,4 v | pesticides Groundwater | exposure
Assessing Groundwater model
Vulnerability to Pesticides
Decision-Support tool for Joe Williams NRMRL 5 v water quality; risk management
Prioritizing Areas for habitat
Restoration
Assessment of Joe Williams, NRMRL, 1,4 v | increased Groundwater | exposure
Groundwater Vulnerability | Bob Shedlock | USGS-WRD development model
Regional Risk Assessment | Jim Andreasen | NCEA 1,5 v | NIS- native exposure
of Non-Indigenous Species terrestrial species model
Vulnerability of Forests to | Kurt Riitters USFS 1,2,4 v NIS; air health; native | exposure
NIS and Other Stressors deposition species model
Identifying Stopover Roger TVA 1,3,4 v increased native exposure
Locations for Neotropical Tankersley development | species model
Migratory Birds
Strategy to Incorporate Lisa Wainger UMD 4 v integration cost/benefit of
Socio-Economics into the alt. policies
Regional Vulnerability
Assessment
Advancing Economic and | Lisa Wainger UMD 4 v integration cost/benefit of
Ecologic Indicators for alt. policies
Regional Risk Assessment
Development of Urban George Hess NCSU 4 v increased
Sprawl Index development
Predicting Probability of Rex Schaberg | Duke 1,3 v resource
Impacts from Chip Mills extraction
and OSB Mills
Development of Species Larry Master Association 4 v native
Distribution Database for species
Biodiversity
Information



the results of all tasks will allow an evaluation of the most promising available technologies and will
guide the development of new monitoring and assessment techniques that are better suited to addressing
emerging environmental issues.

2.5 ReVA as the Second Phase in an Integrated Ecological Assessment

ReVA is designed to develop and evaluate methods to synthesize available information on the distribution
of stressors and sensitive ecological resources. It contributes to linking assessment endpoints identified
by regional stakeholders with regional stressors. Monitoring networks are established to determine status
and trends in these endpoints. Within the MAIA, broad assessment endpoints have been established by
“resource groups” (i.e., landscapes, forests, streams, estuaries) and initial condition reports have been
completed or are underway (Jones et al. 1997, U.S. EPA 1998a, U.S. EPA 2000, USDA Forest Service in
press). Approaches to evaluating risk management alternatives for these assessment endpoints will be
demonstrated by ReVA (Figure 2).

Four major drivers of change and their associated stressors have emerged from an evaluation of regional
monitoring and assessment activities (e.g., EMAP and state monitoring programs) conducted in the Mid-
Atlantic region over the past 5 years. These drivers of change are:

1. Land-use change and population growth;
2. resource extraction (including over-fishing of both fin and shellfish, timber harvest, and mining);

3. pollution (including urban non-point source pollution, agricultural runoff, atmospheric deposition);
and

4, non-indigenous species (this includes not only pests and pathogens, but also introduced species that
are desired and managed for society such as rainbow or brown trout).

A fifth category of cumulative effects has also been implicated in the degradation of some ecosystems
(USDA Forest Service in press). ReVA will contribute to addressing questions related to these five large-
scale environmental changes by focusing research to map, model, assess, and compare exposures at the
regional scale. These stressor categories are consistent with those identified by the NSTC (1999a) as
priority areas for research.

Page 7 of 43


recreation, scenic values, etc. The ReVA indicators could be integrated into a overall estimate of the
extent to which the economic attractiveness of an area might be degraded by environmental impacts.
Such an overview would be invaluable to decision-makers in setting planning and restoration priorities
and developing landuse plans for zoning and other available planning tools.

4.3 Developing Alternative Future Scenarios

The development of alternative future scenarios is an important component of ReVA. Future scenarios
will include increases in human population (e.g., Campbell 1997) with its associated increases in
pressures on the environment (e.g. air deposition, hydrologic modification), continued urban development
(Knox 1993), and climate change (Watson et al. 1996). Future scenarios for the Phase One assessment
will focus primarily on extrapolating changes in land use but will also estimate potential changes in
spatial distribution of pollution, non-indigenous species (NIS), and resource extraction to examine
potential impacts to water quality, human health, etc. Future scenarios for Phase Two will incorporate
projected land use changes as well as anticipated changes in other stresses (e.g., air emissions, spread of
NIS, projected resource extraction) and changes in regional weather patterns and will be developed by
predicting likely changes in socio-economic drivers over the next 20-25 years.

A particular problem is posed by extrapolating land use changes. For example, population growth can
result in conversion of land to residential and agricultural uses (Wheeler et al. 1998). Distributing these
changes spatially will be critical to projecting changes in stresses such as aquatic non-point source
pollution (e.g., percent impervious surface or agriculture on steep slopes) and forest productivity. Land
use changes can also directly alter estimates of resources (e.g., wildlife habitat, Browder et al. 1989).

The development of land use change models is an important research area. ReVA has already sponsored
development of several models and techniques for projecting land-use change at the regional scale. These
range from simply documenting plans for highway construction and new employment centers across the
Mid-Atlantic region, to estimating land demand from state census projections, to customizing applications
of a traditional resource economics model (Hardie and Parks 1997) and a state-of-the-art cellular model of
urban growth (Clarke et al. 1997). The intent is to compare projections resulting from different modeling
paradigms to determine, through weight of evidence, the most likely regional growth centers.

Work is also proceeding in-house to integrate attributes of the resource economics model and projected
highway construction into a new cellular growth model that incorporates the drivers and data from
multiple approaches. ReVA has initiated a thorough inventory and evaluation of the leading land-use
change models currently in use or under development (U.S. EPA 2000). This report examines 22 models
and permits ReVA to identify appropriate models for projecting future scenarios at various resolutions,
and to target new research where gaps exist in modeling scales, land-use types, and conceptual
approaches.

For the Phase Two assessment, changes in stressor amounts and distributions will be estimated by:

1) Surveying EPA’s program offices to evaluate the current thinking on what are estimated future trends
in pollution loadings and pollution prevention;

2) surveying regional stakeholders for future issues associated with increasing population and
development pressures; and

3) sponsoring workshops of experts to develop alternative future scenarios based on a combination of
estimated changes in population numbers, demographics, behavior and resource utilization.

Page 17 of 43


Appendix A
Summary of Tasks

ReVA Proposed Task Description Format

Date of Update:

Task Title:

Abstract: One paragraph, written for lay reader as this will go on the ReVA website if funded.
Objective(s) of Task: Bullets

How Task Relates to ReVA Research Objectives: List specific ReVA research objectives that will be
addressed by this research and briefly explain how the research will help ReVA achieve these objectives
and goals.

Linkages to Other ReVA Tasks: ¢.g., If this research improves ability to estimate distributions of
stressors or sensitive resources, which models can be used to estimate current and future vulnerabilities;
if this research will result in a new effects or risk model, are there other ReVA tasks that will provide the
basis for looking at relative risk for a ReVA endpoint over a region?

Approach: Short description of how task objectives will be accomplished.

Data Sets Used: Source, scale, extent, FGDC metadata-compliant?

New Data Collected: List data sets that will be assembled.

Quality Assurance: Should include plans for documentation of error/uncertainty in data used or
collected, and how error and uncertainty (including error propagation for derived datasets) will be

documented for results.

Activities by Fiscal Year: Should show clearly the progression of the research and if there are
opportunities to use interim results.

Progress and Products to Date: Peer reviewed publications, presentations, data or models that can be
used in the ReVA Phase I assessment.

Deliverables: Specific GIS coverages along with units represented (e.g surface maps, by 8-digit HUC,
ecoregion), predictive models, etc.

Page 35 of 43


Figure

InN Wh IB Be We

IN

rm

we

List of Figures

Page
Steps in the integrated assessment process: Approaches developed by ORD research
PLORTAMS. 26. eee nee een ene E nee 2

Current and planned ReVA research ..

The Mid-Atlantic Integrated Assessment (MAIA) study area ......... 0... ce ees e ee ees 10
Steps in the Phase One Assessment 1.0... 6... cee cece eee teen eee een eee eens 12
Overlay approach to estimate exposure and vulnerabilities 15
ReVA organizational structure ..... 2.6.66. cece cece cence teen e nen enes 28
ReVA program Structure... 6.6 eee eee eeteeee eee e nen ete e eet e eens 29
List of Tables
Page
Phased Approach Strategy ........ 0. cece eee e eee e ee renee ene t eect nee ene eee 11
APM Titles 2.0.0... cece ccc eee eee eee ee tee eee eee eee 21
Potential Interprogram and Interagency Interactions with ReEVA .............e eee eens 25


ep 40 gz oBeq

STAR

‘ORD Planning Staff
JERL, NHEERL,NRMRL,
NCEA.NCER, MAIA)

Coordination, planning and
integration staff

Figure 6. ReVA organizational structure.

[— Region 3-ESD
MAIA Team,
stakeholders

‘Urban sprawl index.



concentrations or nutrient loadings calculated from watershed properties (Hunsaker et al. 1992). Still
other indicators will be extrapolations from finer-scaled mechanistic studies (Rastetter et al. 1991).
Surrogate indicators of exposure (e.g., fragmentation indices, agriculture on steep slopes) and other
metrics (e.g., human use index) from the landscape sciences will supplement the existing information on
stressors and allow a more comprehensive view of regional vulnerability.

All measurements have associated uncertainty or measurement error. There are at least two sources of
error. First, the value assigned to the spatial unit has an associated uncertainty. Second, even if the
indicator value were known with certainty, there is uncertainty associated with the impact actually
occurring within that spatial unit (Wickham et al. 1997).

In addition, individual indicators are not necessarily independent. Agriculture on steep slopes, for
example, is correlated with nutrient concentrations in freshwaters or with sediment loading to estuarine
ecosystems. Spatial and auto-correlation will also be considered. For example, roads and particularly
intersections of interstate highways are correlated with economic development activity, habitat
fragmentation, and increased runoff from impervious surfaces. There does not appear to be any way to
reduce the dataset to a subset of orthogonal indicators since, for example, the spatial network of roads is
also needed as an indicator of routes for exotic species invasion and as barriers to dispersal between
fragmented habitat patches.

Because risk assessment considers uncertainty, all sources of uncertainty must be retained. Measurement
errors and correlations with other indicators are retained as a variance-covariance matrix. Coverages from
statistical models have an associated goodness-of-fit estimate. Standard error analysis techniques will be
used to estimate the uncertainty associated with coverages generated by process models. Research on
combining uncertainty estimates for integrated rankings will be a high priority.

4.1.2 Step Two

The second step will be the development of additional coverages derived from the primary spatial data.
ReVA will employ three approaches.

The first approach follows the ecological risk assessment paradigm (U.S. EPA 1998b). Spatial
distributions of stressors, resources, and exposure indicators are overlapped to represent exposure

(Figure 5). The second approach builds on the work of NERL’s Landscape Sciences Program (ESD) in
developing and demonstrating the use of landscape indicators to assess ecological condition (Jones et al.
1997). The approach uses statistical models to estimate impacts on valued resources such as water quality
and wildlife habitat. For example, this approach allows us to move from available spatial data on nutrient
deposition, roads crossing streams, intact riparian zones, and agriculture on steep slopes to an estimate of
tisk of increased nutrient loading for every watershed across the region.

The third approach uses spatial process models to extrapolate from point monitoring data to the spatial
distribution of stressors. Examples include the estimation of atmospheric deposition (nitrogen, ozone,
sulfate, and some toxics) using monitoring data from systems such as the Clean Air Status and Trends
Network (CASTNet, see: http://www.epa.gov/ardpublc/acidrain/castnet/) combined with deposition
models (e.g., Models3/CMAQ (Community Multiscale Air Quality), see: http://www.epa.gov/asmdner/
models3), and known occurrences of aquatic non-indigenous species combined with geographic path
analysis techniques to identify risk to native species. Survey and monitoring network data also will be
used to formulate and test structured equation models using path analysis techniques.

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Page 20 of 43


Perhaps the most easily understood integration method is the weighted-sum approach (e.g., Wade et al.
1995). Condition is the sum of the component indicators, weighted by their importance. Relative
importance, however, involves subjective judgment. The National Park Service may have a very different
view of watershed vulnerability than the state planner responsible for economic development. The
weighted sums algorithm has the flexibility to allow the decision-maker to vary the “importance” weights
associated with individual indicators and develop individualized overviews of vulnerability.

Another evaluation approach might consider the risk of crossing thresholds established by federal law.
This approach would use a suite of indicators to estimate the risk that a particular assessment unit was in
violation of the endangered species act, the Clean Water legislation, etc. Areas in potential violation of
statutes or regulations could then be identified for further study.

A third assessment approach might be to represent each indicator value as a point in a multivariate state
space (Johnson 1988). The measure of vulnerability is then calculated as the Euclidean distance to the
closest region of “unacceptable impact.” This approach would also be valuable in identifying the
magnitude of change in specific indicators that would produce the greatest reduction in risk. A measure
of current environmental condition could also be calculated as the distance between the present state and
an optimal point defined as the ideal or desired environmental condition.

The state space approach has the advantage of easily accounting for errors in both site and reference
measurements. The approach uses a measure of distance derived from Fuzzy Set Theory (Zimmerman
1987, Tran and Duckstein, 2002). This theory was developed by Zadeh (1965) to deal with problems
resulting from “fuzzy” or uncertain data. Each measured value is described by an interval, for example,
the mean plus and minus a standard deviation. The site measurements and the reference site are
represented by a “fuzzy” circle or polygon in the multidimensional state space. In essence, the distance
measure integrates all the distances, from the nearest to the furthest, between the site and the desired state.

The state space approach can also account for codependencies among the indicators. In the usual
representation of a Cartesian space, the axes meet at right angles and assumes that the variables are
independent of each other, i.e., a correlation coefficient of 0.0. If the coefficient is 1.0, the two axes
overlay each other since two metric values would represent different measurements of exactly the same
thing. It follows that covariances can be represented by the angles between the axes. For example, a
correlation coefficient of 0.5 would be represented by an angle of 45 degrees. Once the original Cartesian
state space is modified, using the calculated covariance, the “fuzzy” distances can be calculated for this
transformed space.

A similar approach can be taken using multivariate statistics. The statistical calculations are based on the
variance-covariance matrix and therefore directly account for measurement errors and codependencies.
This method estimates the probability that a site has departed significantly from the “natural” reference
site and/or that the site is no longer significantly different from the “degraded” reference site.

ReVA will also explore methods such as multiple objective decision theory (Hipel 1992), artificial
intelligence (Rauscher and Hacker 1989), and spatial information integrating technology (Osleeb and
Kahn 1999).

Risks also can be estimated for economic objectives. This approach would directly consider the
viewpoint of a decision-maker responsible for economic development in the region. In general, the
attractiveness of a specific geographic location to development and investment is determined by
socioeconomic factors such as available labor, power, transportation, etc. But decisions are also based on
the environmental condition of the location, involving factors such as clean air and water, available

Page 16 of 43.


SCIENCE REGION 3/
COMMUNITY STAKEHOLDERS

Coordination

Program Manager
MAIA Team Leader
ResearchTeam Leader
Applications Team Leader
Post-Doctoral fellow

x Menegenvent

pophentions.

‘Team Leader
GIS Support
Communications

‘Small research teams organized by Principal Investigators

Figure 7. ReVA program structure.

An Applications/Information Management team has been established to facilitate data sharing among all
the remote sites and with non-EPA partners and to provide general GIS support in the development of
integrated research products. Based on past experience, it has been recognized that an applications team
can improve overall efficiency through serving as a clearing-house for interim products and requests for
information from clients. This will lessen disruption of progress by allowing the principal investigators to
focus on their research while the applications team is responsible for maintaining on-going service to, and
communications/feedback with our clients. IM representatives from all the remote sites will work with
the RTP Applications team in the development of an information management plan and data policies.
Databases used in all ReVA projects will be stored and made available through ORD’s Environmental
Information Management System (EIMS). (See section on Information Management below).

In addition to the Applications team, the central ReVA program will establish a Core Research Team.
The Core Research Team will have responsibility for program goals in indicator development, integrated
assessment, future scenarios and technology transfer. In some cases, the Core Research Team will
undertake independent research in an effort to fill gaps needed to fulfill program goals. In the majority of
cases, the Core Research Team will operate as collaborators and co-investigators in projects with other
ORD programs, such as EMAP or the Global Change Program, in projects with the laboratories
participating in ReVA, and in projects with other federal agencies. The Core Research Team plays a
critical role in the ReVA structure since this small central group will have hands-on experience with all
facets of the dispersed research program.

Page 29 of 43



Section 4

General Approach

One of the ReVA strategies is to use a phased approach (Table 1). To demonstrate a proof-of-concept
within a reasonable time frame, Phase One efforts will focus primarily on existing data and models or
those that are already under development. Research priorities for the Phase One assessment are to
develop techniques needed to use existing data in assessing regional vulnerability (e.g., interpolating
point data, combining disparate data) and integrating the information to compare risk among individual
stressors (e.g., developing statistical techniques to integrate spatial data and to quantify error and
uncertainty associated with multiple stressor impacts on multiple ecological resources). Future
projections of land use change and associated effects will also be considered in Phase One.

Table 1. Phased Approach Strategy

Type of
Phase | Assessment Endpoints | Stressors Future Scenarios Research Priorities
1 Comparative Forests Pollution Land use change Using available data
(high number of | Streams (atmospheric and models
stressors = high deposition, non- | Atmospheric deposition
probability of point source, under proposed policy | Exposure models
cumulative agricultural) changes, e.g., “Clear
effects, etc.) Skies” Initiative Integrating
Land use information
change
Resource
extraction
Non-indigenous
species
2 Relative Risk Forests Same as above, | Land use change Integrating data and
(estimates of Streams but more detail models
probability of Estuaries Spread of NIS
crossing Agriculture Identifying thresholds
threshold) Groundwater Changes n emissions
Human Communicating
Health Changes in results
Economics demographics/
consumption/resource | Determining
extraction applicability of
models to other
Changes in agricultural | regions

practices

Page 11 of 43


1.3 Integrated Science for Ecosystem Challenges

In 1999, the National Science and Technology Council (NSTC), Committee for the Environment and
Natural Resources, Subcommittee on Ecological Systems (CENR/SES) proposed a strategy to address
major ecosystem challenges: Stresses that affect the integrity of ecosystem structure and function, and the
ability of natural and managed systems to provide goods, services, and other benefits to society (NSTC
1999a). These stresses, which often act in concert to produce cumulative effects which are poorly
understood, include: 1) Changes in land and resource use; 2) introductions of invasive species; 3) inputs
of pollutants and excessive nutrients; 4) extreme natural events; and 5) changes in atmospheric and
climate conditions. The proposed strategy called for interagency efforts in the area of Integrated Science
for Ecosystem Challenges (ISEC) to “develop, coordinate and maintain a national research infrastructure
to provide the scientific information needed for effective stewardship of the nation’s natural resources.”

Three strategic priorities were established:

1. Synthesize existing information and develop new knowledge about the structure, function, and
resiliency of habitats and ecosystems;

2. improve understanding of the effects of multiple stresses on habitat and the delivery of ecosystem
goods and services; and

3. provide advanced models and information technologies to improve assessments and forecasts of
habitat and ecosystem conditions under alternative policy and management options.

Following the proposal, the CENR/SES developed an implementation plan (NSTC 1999b) that was
supported by the Administration and put forward as a new budget initiative. The implementation plan
called for $96 million in new funds to enhance ongoing agency and interagency activities in 4 critical
areas:

1. Invasive species, biodiversity, and species decline;

2. harmful algal blooms, hypoxia, and eutrophication;

3. habitat conservation and ecosystem productivity; and
4,

information management, monitoring, and integrated assessments.

ORD’s ReVA program is supported primarily with funds under the third critical area, habitat conservation
and ecosystem productivity. Research under this critical area is designed to include: Integrated research
on landscape and watershed processes; ecosystem structure and function at the land-water interface;
criteria and indicator development; sustainability science; modeling and forecasting responses to multiple
stresses; and aquatic habitat assessment.

1.4 Regional Vulnerability

A region is defined as a large, multi-state geographic area such as the Mid-Atlantic, Northeast, Southeast,
or Pacific Northwest. An EPA Region is a useful representation of a geographic region, because it
reflects the size of the geographic area being considered in the ReVA Program and because strategic
planning and management decisions are made at this scale.

Vulnerability has multiple elements in its definition but is most simply represented by the probability that
future condition will change in a negative direction. We see the ecosystem as a relatively stable
configuration of a number of species with the ability to resist and/or recover from the normal array of
disturbances such as fire, flood, and drought that it has experienced over its evolutionary history. We

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Page 26 of 43


Section 6
Relationships to Other Programs

ReVA is an integral part of the programs being conducted in EPA Region 3, including the Mid-Atlantic
Integrated Assessment (MAIA) geographic initiative (Figure 3). As part of the U.S. EPA Region 3
MAIA initiative, a set of assessment questions have been developed through interactions with various
stakeholder groups. These questions represent the problem formulation stage of the risk assessment
process. These questions also reflect environmental issues and problems raised as part of the EPA Region
3 strategic planning process. Although ReVA is only a part of the entire assessment process, it will
contribute to answering the following regional assessment questions:

1, What abiotic and biotic factors are associated with environmental effects (condition) in the Region?
. What are the relative rankings of regional stressors?

Where are the "hotspots" of poor condition in the Region?

. What are the differences between areas with good versus poor condition?

. What are the socioeconomic factors contributing to stressors and condition?

aA wn

. What are socioeconomic and environmental costs and benefits associated with alternative management
programs?

7. What are the trade offs associated with alternative management programs?

8. Which environmental problems are putting the Region at greatest risk?

Within MAIA, the EMAP Program provides information on the condition and trends in ecological
resources, including monitoring information. ReVA builds on this and other monitoring data (USDA
Forest Health Monitoring (FHM) Program, USGS National Water Quality Assessment (NAWQA)
program, USFWS National Wetlands Inventory, and NOAA Status and Trends Network, Multi-
Resolution Landscape Characterization (MRLC)), and integrates it with spatially explicit models of
stressor distributions, and surrogate indicators of exposure (developed from monitoring data) to map
multiple exposures affecting regional resources and the sustainability of ecological goods, services, and
other benefits. Using this information, ReVA will develop the tools and approaches to assess the current
and future ecological vulnerability of systems within the region (Figures 3 and 4).

As stated under the General Approach Section, ReVA will also consider alternative futures that might
occur with land use changes and associated stresses such as non-point source pollution and atmospheric
deposition and how the ecological vulnerability of systems might change with different patterns of land
use. These current and future estimates are critical for the Mid-Atlantic Regional Assessment (MARA) of
Global Climate Change being conducted by The Pennsylvania State University researchers and
collaborators under the U.S. Global Climate Change Program. Changes will occur in the Mid-Atlantic
region regardless of whether global climate change occurs. Having information on projected changes

Page 23 of 43


ReVA’s approach is to focus analyses at the regional scale. This effort will complement other ORD
research programs that are examining ecological processes at the watershed or community level (e.g., the
National Exposure Research Laboratory’s (NERL) Multi-media Integrated Modeling System (MIMS) and
Basin-scale Assessment for Sustainability of Ecosystems (BASE)). Research over the past 30 years has
examined the issue of scale and clearly indicates that ecological processes operate differently at different
scales. Further, processes that occur at a higher-level (broader) scale tend to constrain processes at lower-
level (finer) scales. For example, the site-specific impacts of non-point source pollution depend on land
use and sedimentation occurring upstream as well as regional patterns of geology, topography, and
weather. Efforts that attempt to remediate problems at the local scale may thus be ineffective if the
influence of these regional scale processes is not recognized. ReVA’s research will explore how stressor
and exposure patterns influence regional processes and will include: 1) land use change and the influence
of socio-economics on urban and rural development as well as regional resource exploitation; 2) the
spread of non-indigenous species as it relates to regional development and landscape characteristics; 3)
changes in habitat distribution and availability and the implications for population viability and regional
biodiversity; 4) cumulative impacts of climate change, NIS, increased development and air pollution; and
5) subregional (i.e., watershed, ecoregion) differences in sensitivity that effect differences in response and
thus vulnerability.

While vulnerability analyses will be conducted at the regional scale, we recognize that effective
environmental decision-making often occurs at scales below the regional, i.e., local, community, and
watershed. To demonstrate how the regional perspective can improve this level of decision-making,
ReVA will partner with clients at the state and local scale to develop, demonstrate, and communicate
finer-scale applications of the regional assessment information. Specific examples of how the regional
context will contribute to these applications include: 1) an increased ability to anticipate timing and
distribution of future environmental problems that progress across the landscape (e.g., spread of NIS and
increased development pressure); 2) identification of specific areas that are regionally significant because
of the presence of rare species, limited habitat (e.g., areas of unfragmented forest), or that provide critical
points of connectivity for migratory species (¢.g., stopover locations for neotropical migratory birds); 3)
an improved understanding of how landscape characteristics can help predict impacts from changes in
watershed management (e.g., classification of watersheds to determine total maximum daily loads
(TMDLs)); and 4) improved strategic planning for future development through identification of areas that
are less sensitive to change (e.g., siting of industrial parks, extraction of mineral and timber resources).

The research tasks needed to achieve ReVA’s goal include: 1) improving techniques to interpolate point
monitoring data (estimate values between points) and extrapolate the results of finer-scaled effects
research (e.g., dose-response studies); 2) developing spatially distributed models of exposure to estimate
tisk where monitoring data on stressors or resources are lacking; 3) developing new indicators that utilize
available data to identify changes in regional scale vulnerability; 4) developing statistical techniques to
quantify the probability and uncertainty associated with future shifts in environmental condition resulting
from multiple stressors; and 5) exploring techniques to communicate the economic and social costs and
benefits of alternative risk reduction activities.

viii


Executive Summary

The goal of ORD’s Regional Vulnerability Assessment (ReVA) Program is to develop approaches to
quantifying regional ecological vulnerabilities so that risk management activities can be targeted and
prioritized. ReVA’s focus is to develop a set of methods that are applicable to the range of data available
in regions (e.g., physiography, land use/cover change, change in climate, air pollution, non-indigenous
species (NIS), the distribution and condition of resources, and others) and provide information to
facilitate decision-making at the regional, watershed, and local scale. Information will be integrated to
allow an assessment of the cumulative risks associated with multiple stressors on multiple resources, to
identify the specific geographic areas of concern, and to evaluate the particular stressors that offer the
greatest sources of vulnerability. The application of the tools developed by ReVA should allow decision-
makers to put environmental issues in perspective and will provide the spatial context necessary to
improve decision making at the watershed and community level. ReVA’s pilot study is focusing on the
Mid-Atlantic region as part of the Mid-Atlantic Integrated Assessment (MAIA) (a federal, state and local
partnership led by U.S. EPA, Region 3). In future years, ReVA will move to other regions of the U.S.

As we have learned through ORD’s ten-year involvement with the MAIA, a comprehensive integrated
regional assessment involves many steps and incorporates data and research that focus on understanding
ecosystem processes at a variety of scales. As MAIA has evolved, five distinct, iterative steps to
improving environmental decision-making have emerged: 1) monitoring to establish status and trends, 2)
association analyses to suggest probable cause where degradation is observed, 3) prioritization of the role
of individual stressors as they affect cumulative impacts and risk of future environmental degradation,

4) analysis of the trade-offs associated with future policy decisions, and 5) development of strategies to
restore areas and reduce risk. The Environmental Monitoring and Assessment Program (EMAP) is
developing approaches to address steps one and two; ReVA is developing approaches to address steps
three and four. Approaches to address step 5 will be developed in a new research program that is under
development.

Based on EMAP and other monitoring data, MAIA has identified 5 groups of stressors that are implicated
in the decline of ecological condition across the region: 1) land use change and population growth, 2)
resource extraction, 3) pollution and pollutants, 4) non-indigenous invasive species, and 5) cumulative
impacts from combinations of multiple stressors. Assessment of the risk associated with these stressors
requires a regional approach that incorporates forecasts of anticipated distributions of these stressors.
Similarly, evaluation of the potential impacts to regional resources requires analysis of the sustainability
of goods, services, and other benefits they provide. ReVA will develop exposure models that estimate
current and future distributions of the 4 drivers of change and their associated stressors as they relate to
endpoints such as native biodiversity, resource productivity, and clean drinking water. Risk of
cumulative impacts will be identified in areas where multiple changes are projected. ReVA will assess
risk associated with these individual stressors as well as their potential cumulative effects. ReVA will
quantify effects associated with anticipated changes (e.g., population growth, air deposition under Clean
Air Act amendments) and illustrate trade-offs associated with alternative policy decisions (e.g., limits to
growth around major metropolitan centers) through future scenarios analysis.

vii


Phase Two research priorities will focus on expanding the range of resources (endpoints) assessed (e.g.,
human health, economic systems), identifying thresholds associated with various exposures, refining the
integration techniques to better quantify relative risks, and addressing research gaps identified in the
Phase One assessment. Future scenarios developed for the Phase Two assessment will include land use
change projections as well as changes in emissions and other chemical loadings, projected spread of non-
indigenous species, and projected changes in regional weather patterns. The Phase Two assessment will
be completed in 2006 if funding for ReVA continues at the same level.

ReVA is designed to improve environmental decision-making by putting regional scale issues (see
stressor categories, Figure 2) in perspective. Vulnerability, as discussed earlier, depends on the co-
occurrence of stressors, along with their sequence and magnitude, and variation in the sensitivity of
resources. ReVA’s approach to assessing vulnerability will proceed by first mapping stressors, sensitive
resources, and surrogate indicators of exposure (e.g., landscape indicators such as fragmentation,
agriculture on steep slopes, etc.), then
integrating this information to map
vulnerabilities, and finally, assessing the risk
of impacts to valued resources (Figure 4).
Through the development of alternative future
scenarios, ReVA will ideally illustrate how
policy decisions and the associated changes in }

Acquire/Develop
Spatial Coverages

vulnerability, affect our quality of life. This
illustration will help decision-makers evaluate the Map Exposures
trade-offs associated with alternative
policy choices. Mi
Develop and Apply
This research strategy is intended to Integration Techniques
provide the reader with a better T
understanding of the concepts and
strategic approaches underlying ReVA Assess Current Vulnerabilities
and to highlight research priorities. The Identify
general elements or steps involved in , <——— Anticipated
implementing the ReVA approach are Changes in
discussed below. Specific research plans Develop Aitemative Socio-Economic
and projects will be formulated to T Drivers
accomplish the various activities
described in Figure 2.’ Additional detail, specific Integrate
research proposed, schedule, deliverables,
and quality assurance will be provided in t
the individual research plans. Individual ‘Assess Future Vulnerabilities
research plans must be peer
reviewed and approved by iy y
the Associate Director for
Ecology for each EPA Communicate Results Transfer Technology

lab/center, other appropriate
agency manager or

university official. Relevancy of the

individual research projects will be Demonstrate Applications

determined by the ReVA Steering

Committee and the ReVA Planning Figure 4. Steps in the Phase One Assessment.

Page 12 of 43


do complete regional assessments and assumes that assessment endpoints have already been identified
and that monitoring data that represent these endpoints are available. As EPA ORD has learned through
our ten-year involvement with the Mid-Atlantic Integrated Assessment (MAIA - a federal, state and local
partnership led by EPA Region 3), a comprehensive integrated regional assessment involves many steps
and incorporates data and research that focus on understanding ecosystem processes at a variety of scales.
As MAIA has evolved, five distinct, iterative steps to improving environmental decision-making have
emerged: 1) monitoring to establish status and trends; 2) association analyses to suggest probable cause
where degradation is observed; 3) prioritization of the role of individual stressors as they affect
cumulative impacts and risk of future environmental degradation; 4) analysis of the trade-offs associated
with future policy decisions; and 5) development of strategies to restore areas and reduce risk. The
Environmental Monitoring and Assessment Program (EMAP) is developing approaches to steps one and
two; ReVA is developing approaches to address steps three and four; and approaches to address step five
will be developed by a new research program that is under development (Figure 1). ReVA will
demonstrate application of these approaches and will provide guidance for this phase of the assessment
process, but the full assessment of regional vulnerabilities is primarily the responsibility of regional
decision-makers. ReVA is designed to improve the methods and tools available to these decision-makers.

Monitoring to establish
status and trends

est new monitoring data used to
develop exposure models

" EMAP

Association analyses to
‘suggest probable cause
where degradation

is observed

Prioritization of the role of
individual stressors as they
nagetements to affect cumulative impacts
‘monitoring design and risk of future degradation

reiterate

ReVA

Analysis of trade offs vortuniis for
associated with ‘opportunities .
future policy decisions regional ak “oe
and development plans local restoration

' Evaluate success in improving decision-making

Development of strategies to
restore areas and reduce risk

Restoration/
Risk Mgmt

Figure 1. Steps in the integrated assessment process: Approaches developed by ORD research
programs.

Page 2 of 43


ReVA is sponsoring research under the National Center for Environmental Research’s (NCER) Science to
Achieve Results (STAR) program to identify anticipated changes in socio-economic drivers and likely
changes in human pressures on the environment (see Request for Applications (RFA) at:
www:epa.gov/ncerga). ReVA will work closely with NERL’s Environmental Sciences Division and
EPA’s Office of Environmental Information (OEI) in the development of a joint EPA/U.S. Geological
Survey effort to develop a “Driving Forces of Land Use Change University Consortium.” Stakeholders in
communities will also be queried as to likely responses to projected land use change so that a variety of
alternative scenarios can be developed that will reflect management options to achieve a range of
potential management goals and alternatives.

As future scenarios are developed, the challenge is to translate the projected scenario into spatial changes
in stressors and resources. In most cases, the changes can be extrapolated using the same models used in
the assessment of current conditions. For example, population growth and urbanization will result in
increased SO, that can be distributed spatially by the same air diffusion models. The most difficult task
involves translating socioeconomic drivers into land use change. One approach will combine models
from economic geography and statistical analysis to determine the probability of a pixel changing to
agricultural or residential land use. The underlying geographic theory states that the probability of
change will be determined by the access to roads (i.e., cost to transport products) as well as distance and
size of accessible urban markets (Wickham et al.2000).

Another approach is based on an analysis of landscape sensitivity to fragmentation (Riitters et al. in
review). Some landscapes are more sensitive (to the loss of resource area) than others, owing to
differences in the spatial arrangement of their component resources. Models predict the likelihood of
fragmentation as a result of different degrees of land-cover change in different spatial patterns of driving
forces (e.g., roadbuilding versus urban sprawl). Continental maps of current fragmentation sensitivity (in
progress) measure the relative risks already taken by historical patterns of land use. Sensitivity can be re-
evaluated for any future scenario and map of land-cover change, including local remediation, to estimate
the likely regional impacts on fragmentation-sensitive resources. The models have been developed by
using the Multi-Resolution Land Characteristics (MRLC) land-cover maps but the general procedure can
be tuned for other data sources and scales.

Once the scenario is translated into spatial changes in stressors and response variables, the regional
assessment can proceed with the same approach used in assessing current vulnerability. The result will be
an overview of the impact of the proposed changes on environmental condition of the Region. This will
make possible a comparison of pre- and post-scenario overviews including the identification of areas that
are at greatest risk of degradation under alternative scenarios. These areas, therefore, might be the most
vulnerable and targeted for risk management activities.

4.4 Technology Transfer and Communication

In most cases, the results of an assessment are finalized as a report or journal article that is of limited use
to the individual decision-maker. ReVA will expand its focus to include products that have broader
application and will work directly with clients to develop tools that will support environmental decision-
making. The nature of a more broadly applicable output can be illustrated with an example of the
Weighted Sums approach to assessment. The final step in this algorithm involves the user choosing a
weight for each of the indicators, i.e., how important each individual stressor or impact is to overall
environmental condition. In a formal report, these weights might be chosen based on the best available
scientific opinion on relative impacts.

Page 18 of 43


600R01008

a United States
7 Environmental Protection
ww Agen

The U.S. EPA’s Regional
Vulnerability Assessment
Program

A Research Strategy for 2001-2006


Appendix B

Current Members of ReVA’s Program
Office Review Committee

Denice Shaw Office of Environmental Information (OEI)

Donald Rodier Office of Prevention, Pesticides and Toxic Substances (OPPTS)
Laura Gabanski Office of Water (OW)

Marty Reiley Office of Water (OW)

Melissa McCullough Office of Air Quality Planning and Standards (OAQPS)

Pasky Pascual Office of Science Policy (OSP)

Richard Haeuber Office of Air and Radiation (OAR)

Vicki Sandiford Office of Air Quality Planning and Standards (OAQPS)

Page 41 of 43


Section 2
Regional Vulnerability Assessment (ReVA) Program

2.1 What is ReVA?

ReVA is a research program to develop and demonstrate approaches and tools for quantifying, assessing
and communicating ecological vulnerabilities at regional scales so that risk management activities at all
scales can be prioritized and targeted. Building on available monitoring data (e.g., EMAP, state
monitoring data, regional spatial data provided by other agencies, newly available remotely sensed data),
ReVA will explore and evaluate techniques to predict and compare the spatial patterns of multiple
stressor exposures and will thus contribute to regional ecological risk assessments conducted through the
EPA National Center for Environmental Assessments (NCEA), Regional and Program Offices, and other
agencies. ReVA will develop approaches to integrate spatially explicit information on resource
sensitivity and condition, and current and future stressor distributions, with associated social values to
inform environmental decision-making.

2.2 Goal and Objectives

The goal of ReVA is to develop and demonstrate approaches to comprehensive, regional-scale assessment
that effectively inform decision-makers of the severity, extent, distribution, and uncertainty of current and
projected environmental risks.

ReVA’s objectives represent the sequential steps needed to achieve this goal:

1. Provide regional-scale, spatially explicit information on the extent and distribution of both stressors
and sensitive ecological resources;

2. develop and evaluate techniques to integrate information on exposure and effects so that ecological
tisk due to multiple environmental changes can be assessed and compared, and management actions
prioritized;

3. project consequences of potential environmental changes and risk management strategies under
alternative future scenarios;

4. effectively communicate economic and quality of life trade-offs associated with alternative
environmental policies;

5. develop techniques to prioritize areas for ecological risk reduction; and

6. identify information gaps and recommend actions to improve monitoring and focus research.

Page 5 of 43


assume stability, resiliency, adaptability, and resistance when we extract resources from the system,
depend on it to purify wastes, or impose recreational impacts. However, these assumptions are no longer
valid when the stresses we impose are outside the range that the organisms have evolved to resist and
move that ecological system outside the normal range of variability. Thus, the vulnerability of an
ecological system increases as the number, intensity, and frequency of stressors increases.

Vulnerability also must consider the interaction of multiple changes on a system. There is a long and
well-documented history of synergistic effects in which one stressor lowers the resistance of the
organisms to other stresses (Foran and Ferenc 1999). An example is provided by the high elevation
Spruce-Fir forest in the Southern Appalachians. It has been suggested that acid precipitation has lowered
the resistance of the trees, permitting an epidemic outbreak of a non-indigenous pest, the balsam woolly
adelgid, and the Fraser fir forests are being destroyed (Hain and Arthur 1985). Even though each stressor
could be resisted independently, superimposed stressors can cause unexpected unstable reactions. In most
cases, we don't have sufficient research information to identify all of the potential synergistic effects, but
we can at least point out that the vulnerability of an ecosystem increases as the number of different
changes increases. The more different stressors there are, even at sublethal levels, the greater the risk that
synergistic effects will occur and cause serious damage. Improved risk assessment of synergistic effects
will be a ReVA research focus in outyears (beyond 2006).

Ecosystems are particularly vulnerable to human land use/cover changes - both urban and agricultural. In
addition to altering the native ecosystem, land use conversion causes an array of side-effects such as
habitat fragmentation, non-point source pollution, and changes in water movement and water quality.
Land use conversion both encourages and is influenced by road building - with its own array of
environmental impacts (Forman and Alexander 1998). Land use change can also drive changes in air
quality with additional vehicular traffic and particulate matter associated with disturbance. Therefore,
vulnerability must also consider the socioeconomic drivers that determine the probability that natural
ecosystems will be converted to human uses.

In addition to the stressors on regional systems, vulnerability must also consider the sensitivity and
adaptability of natural systems being stressed. Some systems may be particularly sensitive to a stressor or
to cumulative effects from several stressors. Some of the sensitive resources can be identified from
research results, e.g., some plant species are particularly sensitive to ozone, some fish species to chemical
stressors, small stream systems to removing riparian vegetation. Other sensitive resources can be deduced
- plant species at the northern or southern edge of their distribution are already under climatic stress and
may be sensitive to any additional stress.

Vulnerability also must consider the sensitivity or probability of extinction for rare species and rare
habitat. Such species and habitats are vulnerable in the sense that the damage is irreparable. There are
also unique habitats like wetlands, mountain tops, and caves that support a unique flora and fauna, which
must also be considered vulnerable and irreplaceable.

Finally there are ecological resources that are considered vulnerable which provide society with valued
goods, services and other benefits. This may involve resource extraction (e.g., forests and fisheries),
recreation (e.g., forests and lakes), waste treatment, and nutrient recycling. Vulnerable ecological
resources in this category are critical because damage to them can have an immediate impact on society.

Regional vulnerability is many things. It is rarity, synergy, sensitivity, and spatial context. No single
question or approach will suffice. Regional vulnerability analysis will draw on many sources of data, will
explore many different assessment methods, and will enable decision-makers to ask many different
questions.

Page 4 of 43


£30 Le abe

Phase

Report Research Category
Principal Contribution Exposure Communicating
Task Title Investigator Division/Org | to Objective | 1 | 2* Stressors Receptors | Assessment Results
Regional Scale Betsy Smith ESD all ov
Comparative Risk
Assessment
Information Management Vasu Kilaru ESD all v
Land Use Change Ron Matheny ESD 3 v risk of
Modeling development
Geostatistical Modeling of | David Holland | ESD 1,3 v air deposition
Sulfur and Nitrogen
Deposition
Development of Bruce Jones ESD 2 v increased water quality; | exposure
Landscape Indicators for development | forest & model
Use in Regional Ecological streams
Risk Assessment habitat
Consequences of Bruce Jones ESD 2,3 v increased water quality; | exposure
Landscape Change in the development | native model
Mid-Atlantic species
Quantification of Bruce Jones ESD 23 v increased water quality | exposure
Landscape development model
Indicators/Water Quality
Relationships in MAIA
Riparian Habitat Indicator | Bruce Jones ESD 1,2 v increased native exposure
Development development | species model
Applications of Fuzzy Logic | Bruce Jones ESD 25 v exposure quantifying risk
in Estimating Landscape model
Indicator Values development/
integration
Landscape Indicator Ann Pitchford | ESD 23,5 v pesticides water quality; | exposure
Development for native model
Watershed Risk species;
Assessment for Pesticides designated
and Toxic Substances use



Table 3. Potential Interprogram and Interagency Interactions with ReVA.

Program/Organization

Opportunity

EPA - NHEERL - EMAP

Additional indicators for Western Pilot important for ReVA’s national
implementation; suggestions for improved monitoring based on hierarchical
stratification reflecting sensitivity to stress.

EPA - NCEA Enhancements to Ecological Risk Assessment Guidelines.
EPA - NRMRL Decision-support tools, prioritization of areas for risk management/reduction
EPA -NCER Relevance of RFA, grants and cooperative efforts to ReVA (See NCER Web

Site).

EPA - Office of Water

Spatially-based biological criteria with management implications. Water and
vulnerability indicators added to “Surf Your Watershed”. Identification of
sensitive watersheds.

EPA - Office of Air and
Radiation

Impact of future emissions; identification of sensitive watersheds/ecoregions.

EPA - Office of Prevention,
Pesticides, and Toxic
substances

Spread of NIS and implications for pesticide use; impacts of agricultural inputs
on water quality.

MAIA

Improved assessment technologies. Future scenarios to illustrate alternative
choices. Partnerships with stakeholders for application development.

Region 4 Ecological
Assessment Program
(REAP)

Evaluation and refinement of methods developed in R 3.

Global Change Program

MARA and SE assessments.

Committee on the
Environment and Natural
Resources

Approach used in National Report Card. Interagency collaboration and
demonstration of ISEC and ecological forecasting.

USGS Water Resources Scaling issue studies, spatial and temporal data access. Improved
Division assessment methods.
USGS Biological Spread of NIS, identification of vulnerable resources for conservation

Resources Division

planning.

FWS, USGS-BRD, NRCS

Wetland studies, metrics, and spatial data access.

BLM, USDA-FHM

Range land characterization and spatial coverages. Future risk to forest
health.

NPS, FWS Reserves

UV-B and amphibian monitoring data; threats to T&E species.

TVA

Application development, communication to stakeholders, future ming
impacts.

The Nature Conservancy

Regional implications of TNC conservation/ preservation spatial areas;
information on existing biodiversity.

Center for Transportation
and Environment

Transportation corridor planning-spatial coverage.

National Association of
Professional Planners

Planning workshops-stakeholder input and proposed areas of development.

Page 25 of 43


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Page 42 of 43


then provides the base for assessing additional changes that might occur because of climate. Similarly,
ReVA will use projections of changes in regional weather patterns developed under MARA.

Both scientific and management program interactions will be fostered by ReVA. Within EPA, for
example, ReVA has been interacting with the EMAP Program for information on status and extent of
ecological resource condition at large spatial scales, indicator development and testing, and association
analyses. The NERL Landscape Sciences Program is conducting research on landscape indicators, their
association with ecological resource condition, and remote sensing of these indicators. ReVA will build
on this information foundation in developing and evaluating assessment techniques and tools for
conducting assessments at large spatial scales. In addition, ReVA is closely interacting with NCEA to
identify gaps in existing assessment tools and areas of needed research, and to evaluate and test local
scale assessment procedures that appear to be applicable at broader scales. ReVA also is working with,
and has funded, scientists in universities and other agencies to conduct research on issues ranging from
NEXRAD radar tracking of migratory birds to determine areas for protection along the migratory routes
to assessing the vulnerability of regional aquatic ecosystems to non-indigenous species introductions.

ReVA is also interacting closely with MAIA, Region 3 Divisions, and Program Offices to identify large-
scale issues which existing technology and tools are not adequately addressing. ReVA is represented on
the ORD MAIA Steering Committee. In addition, ReVA is working with the USDA Forest Service on
forest fragmentation and other management issues that affect the sustainability of forest productivity and
health.

Some of the other collaborative interactions that have, or will, occur with other offices, agencies, and
organizations are listed in Table 2. Many of the tools, approaches, and demonstration assessments being
developed by ReVA will provide perspective for many other activities including selection of high priority
areas for protection and restoration within the region, evaluation of spatially-based biological criteria,
development and refinement of regional comparative ecological risk assessment, and smart-growth
initiatives such as potential siting for transportation corridors.

ReVA has developed and will sustain outreach activities to ensure that new opportunities for

collaboration will be identified and new applications for its tools and approaches can be tested through
MAIA and in other regions in the future.

Page 24 of 43


Section 1
Introduction

1.1 Purpose

This document presents the research strategy for the U.S. Environmental Protection Agency (U.S. EPA)
Regional Vulnerability Assessment (ReVA) Program. This strategic document provides the context for
prioritizing research necessary to conduct and implement the ReVA Program. Individual research plans
for the projects comprising the different elements of ReVA have been, or will be developed. These
research plans are required to pass peer review before receiving support from the program. This strategy
will be updated periodically as needed.

1.2 Background

Until recently, ecological studies and management practices were conducted and implemented at local
scales. During the past two decades, however, it has become clear that evaluations of environmental
problems and management practices cannot be considered only at local scales. Increasingly, acidic
deposition, global climate change, atmospheric contaminant transport, transformation and fate, forest
fragmentation, biodiversity loss, and land use changes have been recognized as problems that have to be
addressed at broader scales (EPA Science Advisory Board, SAB). Local scale assessments continue to
provide valuable information, but expanded knowledge about broader scale problems and their
contribution to local scale problems, as well as the cumulative effects of local scale issues, is needed.
Unfortunately, many traditional approaches and tools are not applicable at broader scales. Approaches
for collecting, analyzing, and interpreting information have to be modified or developed if efficacious
management practices are to be implemented to ameliorate local, regional, and global scale problems.
Drawing inferences requires more than just aggregating existing local site data (O’Neill et al. 1986).

Multiple stressors and associated stressors affect multiple resources at these broader scales and identifying
and partitioning the individual and cumulative effects of stressors across all resources represents a major
research challenge (U.S. EPA 1988, National Science and Technology Council 1999a). In addition to
addressing this research challenge, a regional approach is also needed to effectively target risk
management activities and gain insight into the most cost-effective or socially acceptable ways to address
the complex issues associated with multiple stressor - multiple resource interactions (Graham et al. 1991).
These research needs were highlighted by the U.S. EPA SAB (1995, 1998b) and were incorporated in the
U.S. EPA Office of Research and Development (ORD) Ecological Research Strategy (1998b) as a high
priority research area. Regional scale insight is critical if finer scale problems are to be put into
perspective and management practices are to be effective.

ReVA is designed to develop approaches that address the latter phases of an integrated ecological
assessment, following development of specific assessment questions (problem formulation) and building
on available monitoring data, with a focus on integrating and synthesizing information on the spatial
patterns of multiple exposures to allow a comparison and prioritization of risks. ReVA is not designed to

Page 1 of 43


Surrogate Indicators
of Exposure

Spatial Distribution of
Sensitive Ecological
Resources

Spatial Distribution of
Stressors

Ecological
Response Analysis

_ Risk Management
Y y a Alternatives
Reduce Stress Redistribute Adapt to Stress
Stress

Figure 5. Overlay approach to estimate exposure and vulnerabilities.

Research will involve the development of models to link stressors to impacts on specific ecological
resources. For example, metapopulation theory relates properties such as stability to the spatial
configuration of a habitat. The theory can be used to relate changes in the spatial pattern of habitat to
wildlife and endangered species. Development of such specific models would allow ReVA to translate
fragmentation indicators into indicators of potential impact on specific species. All models used or
developed by ReVA will be evaluated through sensitivity and error analyses. Where multiple models
representing the same process or relationship are available, results will be compared as to where they
agree or disagree and an assessment of these differences will be made and documented.

4.2 Integration and Evaluation

Information must be integrated across response variables and stressor distributions to assess overall
environmental condition (Wickham et al. 1999). This synthesis is a complex process with many
challenges and developing the appropriate methodologies is a high-priority research task in ReVA. The
integration methods developed and employed by ReVA will be evaluated as to sensitivities to different
data issues (e.g., continuous or noncontinuous data, skewed distributions) and to small changes in
variables, and to the ease of use and understanding by the user.

Page 15 of 43



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Jones, K.B., J. Walker, K.H. Riitters, J.D. Wickham, and C. Nicoll. 1996. Indicators of landscape
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Hill, K.B. Jones, D, Luecken, and R. Zepp. 1999. Mid-Atlantic Stressor Profile Atlas. Online:
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O’Neill, R.V., D.L. DeAngelis, J.B. Waide, and T.F.H. Allen. 1986. A Hierarchical Concept of
Ecosystems. Princeton University Press, Princeton, NJ.

O'Neill, R.V., C.T. Hunsaker, K.B. Jones, K.H. Riitters, J.D. Wickham, P.M. Schwartz, I.A. Goodman,
B.L. Jackson, and W.S. Baillargeon. 1997. Monitoring environmental quality at the landscape scale.
BioScience 47:513-519.

Osleeb, J.P. and S. Kahn. 1999. Integration of geographic information. pp. 161-189. In V.H. Dale and
M.R. English (Ed.), Tools to Aid Environmental Decision Making. Springer-Verlag, New York, NY.

Rastetter, E.B., A.W. King, B.J. Cosby, G.M. Hornberger, R.V. O'Neill, and J.E. Hobbie. 1991.
Aggregating fine-scale ecological knowledge to model coarser-scale attributes of ecosystems.
Ecological Applications 2:55-70.

Rauscher, H.M. and R. Hacker. 1989. Overview of artificial intelligence applications in natural resource
management. J. Knowledge Engineering 2:30-42.

Riitters, K.H. et al. In review. Patch characteristics as a basis for vulnerability to fragmentation.

Page 32 of 43


Sutherland, G.D., A.S. Harestad, K. Price, and K.P. Lertzman. 2000. Scaling of natal dispersal distances
in terrestrial bird and mammals. Conservation Ecology [online] 4:16.

Tran, L. and L. Duckstein. 2002. Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy
Sets and Systems, 130(3):331-341.

USDA, Forest Service. In press. State of the Forests in the Mid-Atlantic Region.

U.S. EPA. 1988. Future Risk: Research Strategies for the 1990s. U.S. EPA Science Advisory Board.
Washington, DC.

U.S. EPA. 1995. SAB Report: Futures Methods and Issues. U.S. EPA Science Advisory Board,
Environmental Futures Committee. EPA-SAB-EC-95-007A. Washington, DC, 86 p.

U.S. EPA. 1998a. Condition of the Mid-Atlantic Estuaries. EPA/600/R/98/147. U.S. EPA, Office of
Research and Development, Washington, DC, 50 p.

U.S. EPA. 1998b. Guidelines for Ecological Risk Assessment. Office of Research and Development,
Washington, DC, EPA/630/R-95/002F.

Wade, T.G., J.D. Wickham, and W.G. Kepner. 1995. Using GIS and a graphical user interface to model
land degradation. Geo Info Systems 5:38-42.

Watson, R.T., M.C. Zinyowera, R.H. Moss, and D.J. Dokken. 1996. Climate Change 1995. Cambridge
University Press, Cambridge, United Kingdom.

Wheeler, J.O., P.O. Muller, G.I. Thrall, and T.J. Fik. 1998. Economic Geography. John Wiley and Sons,
New York, NY.

Wickham, J.D., R.V. O’Neill, K.H. Riitters, T.G. Wade, and K.B. Jones. 1997. Sensitivity of selected
landscape pattern metrics to land-cover misclassification and differences in land-cover composition.
Photogrammetric Engineering and Remote Sensing 63:397-402.

Wickham, J.D., K.B. Jones, K.H. Riitters, R.V. O’Neill, R.D. Tankersley, E.R. Smith, A.C. Neale, and
D.J. Chaloud. 1999. An integrated environmental assessment of the Mid-Atlantic Region.
Environmental Management 24:553-560.

Wickham, J.D., R.V. O’Neill, and K.B. Jones. 2000. A geography of ecosystem vulnerability.
Landscape Ecology, 15(6):495-504.

Zadeh, L.A. 1965. Fuzzy sets. Information and Control 8:338-353.

Zimmerman, H.J. 1987. Fuzzy Sets, Decision Making, and Expert Systems. Kluwer Academic
Publishers, Boston, MA.

Page 33 of 43


Section 5
Schedule and Products

5.1 Annual Performance Measures

ReVA has identified the following (Table 2) Annual Performance Measures (APMs) in accordance with
the Government Performance and Results Act (GPRA) of 1993.

Table 2. APM Titles

FY

APM Title

2003

Complete an assessment estimating the comparative vulnerability of forests and small streams in
the Mid-Atlantic region of the United States to multiple stressors, including land use change,
atmospheric deposition, resource extraction, agricultural runoff, and invasive, non-indigenous
species.

2004

Decision-support tool for Mid-Atlantic that enables assessment of impacts associated with
alternative land use, air deposition, and resource extraction scenarios as determined by client.

2006

Complete an assessment of the regional sustainability/vulnerability of ecosystems in the Mid-
Atlantic region of the United States; provide decision support tools for risk reduction activities.

2008

Complete an assessment of the regional sustainability/vulnerability of ecosystems to local, regional,
and national stressors, now and in the future; demonstrate cost-effective adaptation and mitigation
technologies for watershed and regional systems in the Mid-Atlantic region of the United States and
in one additional region.

5.2 Milestones for the Phase One Assessment

Task Date

ReVA Strategy Peer Review February 2001
Final ReVA Strategy January 2003
Phase 1 Spatial Data Compilation Complete March 2002
Evaluation of Integration Methods March 2003
Future Scenarios Developed May 2003
Draft Report NERL Review August 2003
APM Mid-Atlantic Forest and Streams Vulnerability Assessment September 2003

Page 21 of 43.


Section 7 Management Structure
7.1 Cross-ORD Structure ....
72 ReVA Program Structure .. .
723 ReVA Information Management and Data Policies ...

Section 8 References ............ cece cece eee eee eee eee eet ete e eens 31
Appendix A Summary of Tasks .......... 6.0.6. c ccc c eee e cece een ene tenn e teen ee 35

Appendix B Current Members of ReVA’s Program Office Review Committee .
Appendix C Current Members of ReVA’s ORD Planning Committee ....................65 43


£4 40 Op eBeq

Phase
Report Research Category
Principal Contribution Exposure Communicating
Task Title Investigator Division/Org | to Objective | 1 | 2* Stressors Receptors | Assessment Results
Strategy for ? NCEA 4 communicating
Communicating Ecological risk

Risk to Lay Audiences

*Phase 2 Report will include Report 1 items



£30 ge obedg

Phase
Report Research Category
Principal Contribution Exposure Communicating
Task Title Investigator Division/Org | to Objective | 1 | 2* Stressors Receptors | Assessment Results
Atmospheric Ecosystem Joe Sickles ESD 1,3 v air deposition
Stressor Pattern and Trend
Analysis
Landscape Jim Wickham ESD 1 v risk of water quality | N+P loading;
Characterization: MRLC. development exposure
Coordination model
Use of Fuzzy Logic to Liem Tran Penn State 24 v integration quantifying risk
Integrate Disparate Data
Projected Land Use and Sandy Bird ERD 3 v probability of | water quality; | exposure
Land Cover Change for the change native model
Mid-Atlantic Integrated species
Assessment
Regional Vulnerability Susan Cormier | EERD 45 vo water quality;
Assessment of Streams habitat
Landuse Change Under Laura Jackson | NHEERL 3 v risk of all exposure
Alternative Future development model
Scenarios
Predicting Freshwater IBI | Tony Olsen NHEERL 2,3 ov risk of native exposure
development | species; assessment
water quality
Natural and Anthropogenic | Denis White NHEERL 2 v native
Factors Affecting species
Freshwater Fish species.
Diversity
Prioritization Analyses for | Denis White NHEERL. 1 v native
Conservation of Fish species
Species
Vulnerability of Aquifers to. | Bart Faulkner | NRMRL 2 v toxics Groundwater | exposure
Trace Metals in the Mid- model
Atlantic Region



€p 40 @ abe

Drivers of Change and

Associated Stressors
‘Pollution
dep - N,S,O,, toxics
rien

pesticides
‘Land Use Change
sedimentation

ing
timber harvest
sNon-indigenous Species
‘terrestrial - flora, pests and
pathogens

‘aquatic - flora and fauna

Exposure Assessment

Exposure Models
integrative Statistics
«Fuzzy Logic

Resource Categories

(response variables)
Forests

producthty

hoatth

sustainabity of native species
‘Steams

designated use

water quality

‘sustainability of native species
Groundwater
sWetands
Human Health
Economics
‘Estuaries
Agriculture

Mapping Vulnerabilities
sHigh Number of Stressors,

(high probability of cumulative/synergistic effects)

‘High Number of Resources
(high value to society)

«Probability of Increasing Risk

s2Vulnerability Indices

saShift in Multivariate State-Space

|

{Consumer Reports
sCost/Benefit Analysis
‘Alternative Futures
szsLocal-scale Applications

Communicating Results

sResearch underway, expected completion for Phase 1
2Research underway, expected completion for Phase 2
sResearch needed, desired for Phase 2

Figure 2. Current and planned ReVA research.


these approaches can add to the process of evaluating and synthesizing environmental data towards
improved environmental decision-making).

ft

Figure 3. The Mid-Atlantic Integrated Assessment (MAIA) study area.

Page 10 of 43



Table of Contents

Executive Summary ........ 2.6.06 cee cece cence eer e nnn ene n een e eens vii

Section 1 Introduction

LIL Purpose ...
12. Background
13. Integrated Science for Ecosystem Challenges .

14 Regional Vulnerability

wwe

eVA) Program ...

Section 2 Regional Vulnerability Assessment
1 Whatis ReVA? ....
Goal and Objectives .. .
ReVA’s Research Hypotheses . .
ReVA and EPA’s Ecological Research Strategy ..............6055

.5 ReVA as the Second Phase in an Integrated Ecological Assessment . .

2
22
23

nN
ms

IN
ADAUUAY

Section 3 ReVA Strategies 0.2.0.0... 6 cece ccc eee eee een teen e ene n eee 9

Section 4 General Approach
4.1 Mapping Exposures ...
4.1.1 Step One...

Step Two...

4.2 Integration and Evaluation
4.3 Developing Alternative Future Scenarios .17
4.4 Technology Transfer and Communication . 18
4.5 Demonstration of Finer-Scale Applications . 2.0.0.2... 0c. c cece cece eee ee ees 19
Section 5 Schedule and Products . 2)
Annual Performance Measures . . 21

SL
5

Milestones for the Phase One Assessment
Products ..........
Measures of Success ..
5 Customer Perspective .
Science Perspective ..
5.4.3 Management and Operations Perspective . .

5.4

Section 6 Relationships to Other Programs .............. 0.0 cece eee eee ee eee ences 23



Section 8
References

Barabasi, A. and A. Reka. 1999. Emergence of scaling in random networks. Science 286:509-512.

Browder, J.A., L.N. May, A. Rosenthal, J.G. Gosselink, and R.H. Baumann. 1989. Modeling future
trends in wetland loss and brown shrimp production in Louisiana using Thematic Mapper imagery.
Remote Sensing of Environment 28:45-59.

Campbell, P.R. 1997. Population Projections: States, 1995 to 2025. pp. 25-113. U.S. Bureau of the
Census, Population Division, Washington, DC.

Chang, J.S., R.A. Brost, I.S. Isaksen, S$. Mandonich, P. Middleton, W.R. Stockwell, and C.J. Walcek.
1987. A three-dimensional Eulerian acid deposition model. J. Geophysical Research 92:681-700.

Clarke, K.C., L. Gaydos, and S. Hoppen. 1997. A Self-Modifying Cellular Automaton Model of
Historical Urbanization in the San Francisco Bay Area. Environment and Planning B: Planning and
Design 24:247-261.

Flather, C.H., S.J. Brady, and D.B. Inkley. 1992. Regional habitat appraisals of wildlife communities: A
landscape-level evaluation of a resource planning model using avian distribution data. Landscape
Ecology 7:137-147.

Foran, J. and S. Ferenc (Ed.). 1999. Multiple Stressors in Ecological Risk and Impact Assessment.
Society of Environmental Toxicology and Analytical Chemistry. SETAC. Pensacola, FL.

Forman, R.T.T. and L.E. Alexander. 1998. Roads and their major ecological impacts. Annual Review of
Ecology and Systematics 29:207-231.

Graham, R.L., C.T. Hunsaker, R.V. O’Neill, and B.L. Jackson. 1991. Ecological risk assessment at the
regional scale. Ecological Applications 1:196-206.

Hain, F.P. and F.H. Arthur. 1985. The role of atmospheric deposition in the latitudinal variation of
Fraser fir mortality caused by the Balsam Woolly Adelgid (Adelges picea (Ratz.) (Hemipt.,
Adelgidae)): A hypothesis. Zeitschrift fur Angewandte Entomologie 99:145-152.

Hardie, I.W. and P.J. Parks. 1997. Land use in a region with heterogeneous land quality: An application
of an area base model. American Journal of Agricultural Economics 79:299-310.

Hipel, K.W. (Ed.). 1992. Multiple objective decision making in water resources. American Water
Resources Association, Monograph 18, Herndon, VA.

Page 31 of 43


Clearly, opinions on the relative weights will vary with the end-user. A state planning agency might be
most concerned with indicators that might diminish the potential for economic development. A.
conservation agency might be most concerned with indicators that might degrade an area set aside for
preservation. A regulatory agency might be most concerned with indicators that reflect potential
violations of legal limits. So there is no one set of weights that maximizes the utility of the regional
assessment database and the assessment algorithm. Therefore, the weighted sums model might be loaded
on a CD that can be placed in an envelope inside the back cover of the final report. The CD would
contain the instructions and software to access the ReVA database, manipulate the weights placed on
different indicators, and provide output that is tailored to the user's application. ReVA will also make the
data sets and algorithms available on the internet so that individual decision-makers can tailor the
assessment to specific planning needs.

Communicating results in terms of how they affect people’s quality of life is an important task for ReVA.
The application of resource valuation and quantification and communication of both the social and
economic costs and benefits of alternative decisions will allow better environmental accounting and will
illustrate the ecological implications of society’s actions. These efforts will be accomplished in Phase
Two.

ReVA will also support the development of guidelines for the different aspects of assessing regional
vulnerability. Guidelines will likely be developed for:

1) Information management;

2) data quality assessment, diagnostics, and transformation for statistical integration;
3) use of different integration methods;

4) future scenario development;

5) multi-criteria decision-making;

6) identifying priorities for risk management and possibly others.

4.5 Demonstration of Finer-Scale Applications

Recognizing that most environmental decision-making occurs at scales that are less than regional, ReVA
will partner with stakeholder groups to develop and demonstrate applications of local scale decision-
making. These demonstrations will occur concurrently with the regional scale assessment as they can
provide useful feedback that will improve the overall assessment product. Stakeholder groups may
include non-governmental groups (e.g., the Canaan Valley Institute), county planning organizations (e.g.,
Baltimore County), or private institutions (e.g., the Water Environment Research Foundation) that are
interested in developing decision-support tools that enhance local planning or restoration efforts. An
example is the development of a restoration tool that uses decision-tree analysis to identify and prioritize
areas for riparian reforestation based on attributes associated with erodability and reducing sediment
loads, habitat enhancement and regional connectivity for migratory species, aesthetics and wetland
protection. ReVA will provide data and technical assistance in the use of regional scale information for
these demonstrations. It is expected that the tools developed will use a combination of regional scale
information along with finer-scale models that provide additional detail. An evaluation of how these data
and models work together may provide insights into the issue of scale and identifying the limits of how
far fine-scale information can be extrapolated and how far regional scale information can be drilled down
to answer local management questions.

Page 19 of 43


EPA/600/R-01/008
2002

The U.S. EPA’s Regional
Vulnerability Assessment Program

A Research Strategy for 2001-2006

Elizabeth R. Smith’
Robert V. O'Neill?
James D. Wickham’
K. Bruce Jones*
Laura Jackson®
J. Vasu Kilaru*
Ronald Reuter’

1 United States Environmental Protection Agency
Office of Research and Development
National Exposure Research Laboratory
Environmental Sciences Division

2 TN and Associates
Oak Ridge, Tennessee

3 United States Environmental Protection Agency
Office of Research and Development
National Health and Environmental Effects Research Laboratory

The suggested citation for this document is: Smith, E.R., R. V. O’Neill, J.D. Wickham,
K.B. Jones, L. Jackson, J.V. Kilaru, and R. Reuter. 2000. The U.S. EPA's Regional
Vulnerability Assessment Program: A Research Strategy for 2001 - 2006. U.S.
Environmental Protection Agency, Office of Research and Development, Research
Triangle Park, NC.


Appendix C

Current Members of ReVA’s

ORD Planning Committee

Rochelle Araujo
Patricia Bradley
Jeff Frithsen
Steve Hedtke
Barbara Levinson
Joe Williams

NERL
MAIA Team
NCEA
NHEERL
NCER
NRMRL

Page 43 of 43


Section 7
Management Structure

7.1 Cross-ORD Structure

ReVA’s management structure is designed to enhance coordination across ORD and to ensure that the
needs of clients (who include EPA Program Office and Regional decision-makers) are addressed, as well
as to take advantage of available information and expertise (Figure 6). The National Exposure Research
Laboratory (NERL) has the administrative responsibility for the development and management of ReVA.
As ReVA represents a significant contribution to the ORD Ecological Research Strategy, oversight for the
development and management of ReVA will be done by a Steering Committee composed of ORD’s four
Associate Directors for Ecology, representing NERL, the National Health and Environmental Effects
Research Laboratory (NHEERL), the National Risk Management Research Laboratory (NRMRL), and
the National Center for Environmental Assessment (NCEA).

A Program Office Review Committee has been established to provide an opportunity for EPA Program
Offices to review ReVA’s progress and to provide feedback. This committee consists of one or two
representatives from each EPA Program Office and it is anticipated that the committee will meet once a
year with the ReVA Program Director to review plans and products. The ReVA program director also is
responsible for keeping this committee updated as to developments and changes in program direction.

An ORD Planning Committee has been established for ReVA to help prioritize needed research, to
identify opportunities for cross-laboratory collaboration, and to review budget decisions. This committee
consists of representatives from NHEERL, NRMRL, NCEA, NERL, and NCER and a representative from
Region 3.

7.2 ReVA Program Structure

Experience with large-scale assessments in the past has helped guide the management structure of the
ReVA program (Figure 7). The ReVA central team will be headquartered in NERL at facilities in
Research Triangle Park, NC. All planning and management activities for ReVA will be the responsibility
of the central team. This central team will consist of the program director, a Post-Doctoral fellow
assigned to the program director, the lead for the Applications team and the lead for the Research team.
There will be one primary ReVA contact person at each remote laboratory site.

Page 27 of 43


Evaluation of Results: Using peer review process, weight of evidence, other?

How Outcomes Can be Extended to Other Regions: Are results directly applicable, or can the
approach be adapted for other regions if data are available?

How Outcomes Can be Made Available to Clients: Can outcome be applied directly by clients or does
it require development of guidelines or other tech transfer/training? What mechanism is suggested for
making available to clients (e.g. internet, incorporation into a decision-support tool)?

List of Clients: Should be clear what is level of decision-making (regional, community, research
community).

Major Collaborators: EPA ORD researchers, universities, other agencies.

Budget Request By FY: Through the end of the project. Should be able to link with yearly activities
and deliverables.

Page 36 of 43


5.3 Products

* Decision-support systems that use remote sensing, GIS, and predictive modeling for prioritizing issues
and management actions

* New indicators for measuring cumulative effects, ecosystem vulnerability, and changes in quality of
life

* Techniques for incorporating ecosystem assessments and valuation in policy decisions

* Improved models that forecast changes in ecosystem resiliency and the capability to support living
resources

* Identification of gaps in information and knowledge to refine monitoring and prioritize research

* Methods to integrate ecosystem, social, and economic data to illustrate trade offs associated with
alternative policy choices

5.4 Measures of Success

ReVA is committed to establishing specific measures of success for the program, and to continuously

gauge the program against those measures and refine it as needed. Though work is needed to define the

measures, the following outline highlights key elements.

5.4.1 Customer Perspective

* Use of ReVA-generated information in accomplishing the customer’s mission

* Satisfying customer needs and expectations

+ Building a broad-based constituency for the program

+ ReVA approach incorporated in the customers programs

5.4.2 Science Perspective

* High quality science as reflected by frequent and critical peer reviews and publications in professional
journals

* Continued incremental improvement in accomplishing scientific and technical program objectives

5.4.3: Management and Operations Perspective
* Research deliverables accomplished within cost and on schedule
* Managers and technical staff desire to participate in the program and see it as a career opportunity

+ Program enhances inter-organization cooperation in key areas such as risk assessments, risk reduction,
regional planning and ecosystem management

Page 22 of 43


2.3 ReVA’s Research Hypotheses
ReVA’s working hypotheses or assumptions are:

* Spatial connections (upstream-downstream, transportation network, shortest air distance) are
important in determining the total ramifications of local human activities. Therefore, cumulative
ecological condition over large regions is related to large scale patterns as well as small scale
decisions.

* Spatial variability reduces the efficiency of bottom up approaches (and increases the efficiency of top
down approaches) when assessing ecological condition over large regions.

* Sustainability can only be achieved by maintaining regional variability. Some areas must be reserved
to maintain regional biodiversity. Some areas are vulnerable to human disturbance.
Additional hypotheses that are being tested in ReVA include:

+ Regional environmental and socio-economic data are available at various spatial scales that can help
decision makers prioritize risk reduction activities.

* Modern methods of organizing, presenting and analyzing these data can make them more useful and
more valuable for purposes of making risk management decisions.

+ Efficient data management and retrieval systems and analytical and presentation software can make
regional environmental and socio-economic data available to many decision-makers at an acceptable
level of spatial disaggregation and at an acceptable cost.

+ Because the types of data and decision-support software needed are relatively uniform from region to
region, there are significant economies of scale in developing regional ecosystem vulnerability
indicators that make the long-term payoff from investing in up-front data/software development
worthwhile.

2.4 ReVA and EPA’s Ecological Research Strategy

There are six questions, described in the EPA ORD Ecological Research Strategy (U.S. EPA 1998b), that
guide the ReVA research:

1. What are the most effective ways to identify and describe the current distributions of stressors (both
natural and anthropogenic) and ecological resources in a region?

2. What are the most appropriate models to quantify the relationships between exposure and effects at
regional scales?

3. How can available data on stressor and ecological resource distributions be used to quantitatively
estimate exposures at regional scales?

4. How should regional risk assessments deal with cascading exposure and effect phenomena?

5. How can self-consistent, alternative future regional exposure scenarios be constructed, taking into
account likely linkages among social and economic drivers in a region?

6. How can ecological outcomes best be linked to human uses and values in integrated feedback loops,
rather than simply as unidirectional effects of human activity?

The first three questions will be addressed in the first phase of ReVA research. The last three questions
will be addressed in outyears and provide future research directions beyond this strategy. Specific
research tasks (listed in Appendix 1) will address various aspects of these six questions. The synthesis of

Page 6 of 43,


Section 3
ReVA Strategies

The ReVA strategies support the goal and objectives, and address the research questions and regional
themes. The ReVA strategies are:

1. Use a phased approach for implementing ReVA, with Phase One focusing on integrating available
information to demonstrate the proof of concept and to identify needed research to assess ecological
vulnerability at regional scales.

2. In Phase Two, expand the scope of research to include additional stressors and response variables and
refine the integration techniques through application to this broader array of information.

3. Initiate the pilot in the Mid-Atlantic region because it complements, and builds on, the EMAP
Program, the MAIA geographic initiative (Figure 3), previous landscape analyses and results, and can
contribute to EPA Region 3 strategic planning efforts and management decisions. Continued ORD
participation in MAIA also provides the opportunity to refine the Ecological Risk Assessment
Guidelines (U.S, EPA 1998) for application to regional scale priority-setting assessments.

4. Develop the ReVA approaches and tools and demonstrate their application at the regional, watershed,
and local scale in partnerships with clients. Utilize client partnerships to facilitate technology transfer.

5. Initiate studies in other regions to test the applicability of the methods and approaches in other areas
and repeat the process.

ReVA’s unique focus is the spatially explicit, regional-scale viewpoint that builds on the pioneering work
of EPA’s Landscape Sciences Program in developing new assessment techniques (Jones et al. 1997).
ReVA is a cross-ORD program that also partners with other federal and state agencies to bring together
the best available data and research capabilities to determine how to do regional scale comparative risk
assessments. ReVA is intended to develop and demonstrate approaches for regional-scale assessments
that can be implemented across the country using methods developed in our pilot study region (the Mid-
Atlantic). Therefore, the methods need to have the flexibility to be used in other regions. This means that
analyses must use data that are available in each region (i.e., be flexible in input), and models and
information must be at the appropriate scale. As such, ReVA will identify gaps in our ability to conduct
comprehensive regional scale assessments and will thus guide improvements in monitoring and help
identify future research needs.

Work within a second region is expected to begin in FY03-04. This will allow a test of the approaches
developed in the mid-Atlantic region, and further refinement of the vulnerability assessment technology.
Selection of the second region will be based on the following criteria: 1) Data availability (regional-scale,
spatially explicit) - ReVA will work with EPA’s Office of Environmental Information (OED) to identify
data-rich regions; 2) availability of a team within the region to work with ReVA scientists (to provide
feedback and to facilitate technology transfer); 3) different environmental issues (a test of the
applicability of the approach); and 4) client interest (ideally, decision-makers who are interested in what

Page 9 of 43