UNITED STATES
ENVIRONMENTAL PROTECTION
AGENCY
OFFICE OF RESEARCH AND
DEVELOPMENT
WASHINGTON. D.C. 20460
EPA/600/R-01/040
MAY 2001
AN ECOLOGICAL
AND HABITAT
VULNERABILITY
ASSESSMENT OF
THE WHITE
RIVER BASIN
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Mallard Duck Winter
Habitat Suitability Rank
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AN ECOLOGICAL AND HABITAT VULNERABILITY
ASSESSMENT OF THE WHITE RIVER BASIN
RESEARCH PLAN
Principal Investigators:
Ricardo D. Lopez
and
Daniel T. Heggem
U.S. Environmental Protection Agency
National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
//
Cover Images: A southern portion of the White River National Wildlife Refuge (Arkansas) and
vicinity: (left) a 1992 "false color" Landsat MultiSpectral Scanner image, highlighting vegetated
areas in shades of red; (right) a preliminary winter habitat suitability model (assuming current
landscape conditions) for mallard duck in the same region.
Notice: This research plan has undergone a peer review process, involving input from experts
within the U.S. Environmental Protection Agency (EPA) and from outside the EPA. Mention of
trade names or commercial products does not constitute endorsement or recommendation by
EPA for use.
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TABLE OF CONTENTS
BACKGROUND 1
RESEARCH RATIONALE AND NEED 2
STUDY AREA BOUNDARIES 5
RESEARCH OBJECTIVES 7
RESEARCH APPROACH 7
METHODOLOGY 11
SCHEDULE, MILESTONES 16
MAJOR PRODUCTS : 17
PROJECT BUDGET OVERVIEW 17
PROJECT MANAGEMENT 18
LITERATURE CITED 20
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BACKGROUND
The White River begins in northwest Arkansas, flows through south-central Missouri,
reenters Arkansas, and then flows southeast to its confluence with the Mississippi River (Figure
1). The White River Basin extends from the Ozark Mountains to the Mississippi Alluvial Plain,
and drains from a wide range of landscapes that contain farmland, upland forests, wetlands,
lakes, small streams, and urban development. Along the mainstem and tributaries of the White
River there are seven reservoirs, and within the White River Basin there are two National
Wildlife Refuges, a National Scenic River, and two National Forests. The lower White River,
75
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225 Kilometers
^B White River
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Major Water Body
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Figure 1. The White River (Arkansas and Missouri) and surrounding landscape.
which flows through the Mississippi Alluvial Plain, is one of the most important bottomland
hardwood wetlands in the world (Figure 2) and has been designated as a Ramsar Wetland of
International Importance (Ramsar 2000). The streams and wetlands in the lower White River
Basin are unique in that they support the largest winter concentration of mallard ducks in North
America and also provide critical habitat for plant species and animals, such as black bear and
migratory birds (Twedt et al. 1999). The river system also supports an important riverine
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fishery, including sturgeon and paddlefish. The aquatic plant communities within bottomland
hardwood swamps of this region are among the most biologically diverse and productive systems
in the world (summarized by Mitsch and Gosselink 1993). The White River Basin is an
especially valuable resource for the people of Arkansas because they directly depend upon it for
surface water, flood control, agricultural products, commercial transport, numerous forms of
outdoor recreation, commercial shelling industries, commercial fishing industries, tourism
industries, and for their enjoyment of its plants and wildlife.
»
Figure 2. A remnant bottomland hardwood swamp (Burnt Lake) with wetland-adapted cypress
trees and other wetland vegetation, within the boundaries of the White River National Wildlife
Refuge, Arkansas.
RESEARCH RATIONALE AND NEED
The Lower Mississippi River, its tributaries, and the landscapes within these watersheds
have undergone tremendous alteration in the past (Dahl 1990), which has resulted in the loss of
natural wetland vegetation and hydrologic characteristics of the landscape that are unique to
wetlands (Mitsch and Gosselink 1993). Since the 1970s the most extensive loss of wetlands has
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included those in Arkansas, Mississippi, and Louisiana (Dahl and Johnson 1991, Kress et al.
1996). These changes are likely to affect change in the biological diversity (Gosselink and
Turner 1978, Ewel 1990), the capacity of the land to attenuate flood events (Hopkinson and Day
1980a, Hopkinson and Day 1980b, Brown 1984), and downstream water quality (Kitchens et al.
1975, Day et al. 1977, Hupp and Morris 1990, Hupp and Bazemore 1993). This study is an
important first step toward a determination of how such landscape alterations are correlated with
changes in the hydrologic, chemical, and biological characteristics of the White River Basin and
how the influences of potential alterations may affect change in the future water quality and the
biological integrity of the ecosystem. Quantifying these relationships could improve the
decision-making processes for future land use planning in the White River and the Mississippi
River watershed.
Recent detailed studies of the landscape in and around the remnant bottomland hardwood
wetlands of the Cache River (Figure 1) show that the relationships between landscape change
and wetland function in the region are complex and require a thorough understanding of impact
history (Kress et al. 1996), water quality (DeLaune et al. 1996, Dortch 1996, Kleiss 1996),
hydrology (Long and Nestler 1996, Walton et al. 1996a, Walton et al. 1996b, Wilber et al. 1996),
and habitat characteristics (Kilgor and Baker 1996, Smith 1996, Wakeley and Roberts 1996).
The White River, a major tributary to the Mississippi River, has not undergone a comprehensive
assessment of this kind. A fundamental assessment of the landscape history, resource rarity, and
ecological functions of the White River Basin is necessary to continue the efforts to better
understand how the remaining bottomland hardwood wetlands, and other inter-linked
ecosystems, of the Mississippi River Valley are impacted by future development. This need is
urgent because approximately 70% of Arkansas' wetlands have been converted to other land
cover types since the late nineteenth century (Dahl 1990), a loss of approximately 2.8 million
hectares (Figure 3), and over 400 thousand acres of this loss occurred in the mid-twentieth
century (Shaw and Fredine, 1956).
One of the land cover changes that predominates in this region of the United States is the
conversion of forest to agricultural areas (Heggem et al., 1999). Conversely, in recent years
some human-use areas (e.g., agricultural land) have been restored to their former 'natural' cover
types (e.g., forest) through the U.S. Department of Agriculture Wetland Reserve Program
(WRP). Information about the WRP can be found at the Internet web site: http://www.wl.fb-
net.org/. Both types of land cover change will be assessed in this study. The observed
relationships between land cover change and the status of ecosystems of the region will then be
used to determine how: (a) future change in vegetation cover may impact habitat suitability of
the basin; (b) future change in vegetation cover may impact water quality of rivers, lakes, and
wetlands; and (c) river and wetland hydrology and vegetation change are related. These
relationships will be used to predict potential habitat and water quality/quantity conditions of the
future. Thus, the potential future scenarios can be used to assess the vulnerability of the
ecosystems to future land cover change and land use change in the region.
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From 1883 Flood Data
From 1991 Satellite Data
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Figure 3. Wetland loss in the Mississippi Alluvial Valley (1883 - 1991). Most of the
remaining wetlands (black areas north of "New Orleans") are included in this study.
[adapted from Nature Conservancy 1992]. Arrows point to the approximate location of
the southern end of the White River National Wildlife Refuge in the late twentieth
century (right), and the same location in the late nineteenth century (left).
There are many projects currently under review for implementation in the White River
Basin, each of which has the potential to alter a substantial proportion of the remaining forested
areas of the landscape in the White River Basin. The planned projects include a navigation
project that requires river channel alterations and may affect the hydrology of riparian wetlands;
agricultural irrigation projects that involve increasing the removal of surface water from the
White River and modification of reservoir releases that may substantially change the hydrology
of the basin; roadway and bridge construction projects, thus fragmenting habitat. This project
will provide a method for determining how such projects may affect the water quality, quantity,
4
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and habitat characteristics of the basin. Future development has the potential to specifically alter
the delicate hydrology of palustrine and riverine wetlands, which may directly affect water
quality and the suitability of habitat for wetland organisms of the region. Thus, this project will
focus on the wetland areas of the White River Basin and the plant/animal communities of those
areas. Specifically, the current extent of roads and future road projects in the White River Basin
has great potential for causing forested wetland fragmentation, and may result in ecosystem
degradation. Fragmentation of forests and other land cover types is likely to have ecological
impacts on the region because White River watershed contains over 131,000 km of roads, of
which approximately 11,000 km are within 15 km of the White River/Cache River/Bald Knob
Wildlife Refuges, and 537 km of roads are inside the White River National Wildlife Refuge
boundary.
As a result of projected development pressures on the ecology of the lower Mississippi
River region, the Mississippi River Alluvial Plain and the White River Basin are currently the
focus of heightened U.S. EPA concern. Of particular concern is the ecological vulnerability of
the lower White River and the potential for loss of ecological function, given the plans for future
development. Thus, this study will specifically focus on habitat functions as part of an overall
assessment of ecological integrity of the White River ecosystem. In an effort to maintain an
effective balance between navigation, flood control, and resource protection along the
Mississippi River, EPA Regional Administrators have also committed to protect and restore the
environmental resources of its tributaries, such as those in the White River Basin. Additionally,
the loss of riparian vegetation in the White River Basin may be a contributing factor to the
overall load of nutrients in the Mississippi River and the Gulf of Mexico, and contribute to the
lack of habitat for plants, migratory birds, and other animals. Accordingly, they are committed
to a systems approach to improve and protect water and habitat quality within the Mississippi
River Basin, and those ecosystems in the Gulf of Mexico that are closely tied to the upstream
habitat and water quality (e.g., the U.S. EPA St. Louis Compact of 1998). This study will help to
fulfill this commitment by quantifying the potential impacts of nutrient loading and the loss of
habitat within the lower Mississippi River watershed. The St. Louis Compact may be viewed on
the U.S. EPA's Office of Wetlands, Oceans, and Watersheds Internet web site: http://www.epa.
gov/OWOW/watershed/compact.html. The successful completion of this project will help to
develop a protocol capable of determining the potential ecological and habitat vulnerability of
the White River and the Mississippi Alluvial Valley, and may be useful as a protocol for larger
regions of the United States, such as the entire Mississippi River watershed.
STUDY AREA BOUNDARIES
The ecological vulnerability of water bodies to land cover change will be assessed and
reported for the lower White River, bounded by the USGS Hydrologic Unit Code (HUC) 0802
(Figure 4). The same attributes will be assessed and reported for the upper White River region
(HUC 1101) because this watershed is hydrologically connected to the lower White River. The
ecological vulnerability of habitat to land cover change will be assessed and reported for the
region defined as the Mississippi Alluvial Valley Ecoregion (Omernik 1987), which includes the
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lower White River hydrologic boundary (HUC 0802). The habitat in the Mississippi Alluvial
Valley Ecoregion (Figure 4) is important to include because it is connected to the existing habitat
of the lower White River (e.g., the White River National Wildlife Refuge and the Cache River
National Wildlife Refuge). A "fine-scale" sub-region (Figure 5) of the White River Basin has
been selected to test the habitat vulnerability methodologies, which will be applied to the
Mississippi Alluvial Valley Ecoregion study area. The fine-scale study area includes the White
River National Wildlife Refuge, Cache River National Wildlife Refuge, and Bald Knob National
Wildlife Refuge. An intended benefit of this project is that the results (e.g., from the fine-scale
study area) will be directly applicable to the management practices of the wildlife refuge
professionals of the region.
Figure 4. Study area utilized for habitat analyses is the (green-shaded) Mississippi Alluvial
Valley Ecoregion (Omernik 1987). Study areas utilized for water quality analyses are the USGS
Hydrologic Unit Code (HUC) regions 0802 (blue boundary) and 1101 (red boundary).
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RESEARCH OBJECTIVES
A) Within the fine-scale and ecoregion study areas, five fundamental landscape ecology
hypotheses (state here as questions) will be addressed by this study:
1. What are the ranges (i.e., what are the gradients) of conditions in the landscape?
2. How are the landscape gradients related to the habitat suitability for plant and animal
species?
3. What changes in current habitat suitability are predicted, given hypothetical changes in
the future landscape?
4. What will be the consequences of predicted changes on plants and animals of the region?
5. How do the gradients of landscape change, thus the predicted habitat suitability, change
at different spatial scales?
B) Within the USGS hydrologic units, five fundamental landscape ecology hypotheses (state
here as questions) will be addressed by this study:
1. What are the ranges (i.e., what are the gradients) of conditions in the landscape?
2. How are the landscape gradients related to surface water quality/quantity?
3. What changes in surface water quality/quantity are predicted, given hypothetical changes
in the future landscape?
4. What will be the consequences of predicted changes on water quality/quantity?
5. How do the gradients of landscape change, thus the predicted water quality/quantity,
change at different spatial scales?
This project is a component of the 10-year research strategy for the Landscape Sciences
Program (Jones et al. 2000a). The three primary areas of the research strategy to be addressed by
this study are: (a) change detection by comparing thematic data sets in a geographic information
system (GIS) environment; (b) investigation and development of landscape indicators; and (c)
assessment and quantification of landscape change. An overall objective of this study is to
improve the understanding of ecological relationships between potential landscape stressors,
habitat suitability/vulnerability, and water quality/quantity of the study areas. Our results may
parallel efforts and techniques of the ORD Regional Vulnerability Assessment (REVA) and the
U.S. EPA Region 6 Cumulative Risk Index of Analysis (CRIA), and may result in collaborative
use of data layers and information for the ecological models. The research efforts of the White
River Basin project will therefore be coordinated with the REV A and CRIA projects to best
accomplish the above-mentioned research goals.
RESEARCH APPROACH
The models to be developed in this study could be constructed for other areas or by
measuring other parameters, given the availability of sufficient ecological data. The specific
plants and animals used in the habitat models of this study will be based upon a combination of
selection criteria, in the order listed: (a) availability of habitat suitability information in the
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literature for a species and geographic coverage of these data; (b) plants or animals that are
indicators of ecological conditions; (c) plants or animals that have undergone a decline in the
region; (d) species that are listed as endangered or threatened at the state or national level; and
(e) species of special interest, as expressed by the local or regional stakeholders. The selected
ecological parameters should also provide guidance for subsequent researchers that perform
similar studies and may have data of improved quality in the future.
The research approach is to:
A) Examine the relationships between landscape condition and habitat suitability:
1) Determine habitat requirements for plant and animal species or guilds (see criteria,
above), using habitat suitability indexes and other natural history information available
in the literature.
2) Use the habitat requirements of species or guilds, in combination with habitat
characteristics (e.g., wetland type) from the 1980s and 1990s, entered into a GIS, to
produce a habitat suitability model for the study areas under current landscape
conditions.
3) Utilize historical trends in combination with prior ecological research results to
hypothesize potential landscape stressor gradients that may be relevant to changes in
habitat suitability (e.g., conversion of forest to agricultural land). The selection of
potential stressor gradients will be based on current knowledge of the habitat
requirements for particular species or guilds and may be based on a combination of
habitat parameters (e.g., vegetation cover requirement and home range requirements).
An initial analysis of general habitat requirements may help to focus efforts on other
more detailed habitat-stressor relationships, for example the loss of core forest areas as
a stressor for plants and animals.
B) Examine the relationships between landscape condition and water quality/quantity:
1) Obtain water chemistry and hydrologic data (e.g., National Water Quality Assessment
data, staff gauge measurements, and stream flow measurements) for the hydrologic
study areas (HUC's 0802,1101). Because prior research has demonstrated that
landscape characterization results are scale dependent (Jones et. al 1997) the
hydrologic study area will be analyzed at several different spatial scales: (i) as a
complete river ecosystem (HUG 0802 and 1101, combined); (ii) as a mixture of lotic
and lentic ecosystems containing major impoundments and steep terrain (HUC 1101);
(iii) as a predominantly lotic ecosystem, flowing through the alluvial flood plain (HUC
0802); and (iv) at finer scales (e.g., 8-digit HUC sub-basins), where appropriate.
2) Determine and delineate land cover types (e.g., forest) and determine spatial gradients
of land cover in the 1990s for the hydrologic study areas (e.g., using land cover
derived for the Arkansas GAP, see Methodology and Figure 6).
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c
B
Figure 5. Approximate fine-scale study area (A), used to test some of the habitat
suitability/vulnerability methodologies. The fine-scale study area includes the White River
National Wildlife Refuge (B), Cache River Wildlife Refuge (C), and the Bald Knob National
Wildlife Refuge (D). The hydrologic study area boundary (E) is included for reference (see
Figure 4 for detail).
3) Utilize the land cover change gradient in the White River hydrologic study areas to
hypothesize potential land cover stressor gradients, that are relevant to surface water
quality (e.g., surface water concentration of nitrate+nitrite or phosphorus). The
potential stressor gradients will also be based on prior research results that indicate a
relationship between landscape condition and water quality or hydrology. Many of the
mechanisms of the relationships between land cover and surface water chemistry are
known. For example, prior studies in agricultural areas have demonstrated an inverse
relationship between the presence of riparian vegetation and nutrient loading to nearby
streams, because of nutrient uptake by the plants in the riparian zone (Peterjohn and
Correll 1984). Other research suggests that, in general, there is a strong positive
correlation between the improvement of water quality and the presence of wetland soil
conditions and vegetation (Hey et al. 1989, Poiani et al. 1996, Fennessy and Cronk
1997, Giese et al. 2000). Thus, the loss of riparian vegetation (e.g., narrowing of
riparian vegetation width) will be tested as a potential water quality stressor in the
White River hydrologic study areas.
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C) Model future landscape change scenarios and predict the ecological/habitat vulnerability:
Using the gradient trends and relationships (determined in step A and B, above) or specific
development plans for the future (e.g., road construction plans), develop several future
landscape change scenarios. For example, a future scenario for a study area may be a result of
a hypothetical 10% decrease in wooded riverine wetland along a segment of the White River,
given specific information of similar change from a development plan or historical trends.
Future impacts on plant and animal habitat, and future impacts on water quality/quantity will
be estimated by implementing similar hypothetical changes in the land cover of those models.
The future scenario models for habitat and water quality/quantity could be used to estimate
the vulnerability of these resources to impacts, and to minimize the potential negative impacts
of development.
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Figure 6. 'Arkansas GAP' land cover in the 1990s, derived from Landsat TM imagery (USGS
1998)
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METHODOLOGY
Conceptual framework for modeling ecological/habitat vulnerability:
1. Develop habitat suitability models (i.e., based on current condition) for plant and animal
species using the habitat requirements of each species (or guild) and available land cover data
(see Table 1 and Data section, below)
2. Develop a water quality/quantity model for the current conditions in the White River
hydrologic study areas using available water quality/quantity data and available land cover
data (see Data section, below)
3. Estimate the trends in the historical land cover change for the study areas using gradient
analyses, landscape indicators (Table 2), and a GIS.
4. Apply potential future landscape change scenarios to models in framework steps 1 and 2,
based upon: (a) extending the trends observed in framework step 3 into the future; (b)
expected ecosystem responses to environmental stress (Odum, 1985), for example the loss of
facultative wetland vegetation in the riparian zone given hypothetical alterations in the
hydrology of the study areas; and (c) application of known projects or development plans to
the "current condition" landscape (established in framework steps 1 and 2), for example
hypothesizing an increase in forest land cover at specific WRP restoration sites.
Landscape indicators
An ecological indicator is a measurement of change in ecological resources (Bromberg
1990, Hunsaker and Carpenter 1990, Hunsaker et al. 1990). When measured at the landscape-
scale (Forman 1995) ecological indicators are called "landscape indicators", and are defined as
measurable characteristics of the environment, both abiotic and biotic, that can provide
quantitative information about ecological resources (Jones et al. 1997). Because it is currently
impossible to measure all of these characteristics, in this study we selected landscape indicators
(Table 2) that have demonstrated a correlation between landscape conditions and ecosystem
integrity (Lopez 1999, Jones et al. 2000b, and Jones et al. 2000c). The use of GIS mapping
techniques to determine correlations between indicators and response enables the determination
of change in ecological resources because it allows for more rapid analyses of correlations
between hypothesized landscape indicators and response parameters (Scott et al. 1993, Jones et
al. 1997).
Gradient and statistical analyses
A fundamental component of a landscape-ecological study design is the selection of a
sufficient number of study sites to account for the full range of disturbance conditions (Green
1979, Karr and Chu 1997). To examine gradients of landscape change in the study areas
(ranging from least-impacted to impaired) complete available data coverage of the study areas
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and a stratified random sampling design within each study area will be used. Prior knowledge of
local experts, a preliminary review of the history, and a review of the current land cover of the
study areas indicate that there is sufficient variability within each study area to successfully^
perform gradient analyses. Table 1 lists the minimum modified-Anderson (1976) "Level 1"
land-cover classes to be used for the analysis of the land-cover gradients.
The relationships between land cover parameters, water quality/quantity, and habitat
characteristics will be tested using multi-variate statistical techniques (e.g., multiple regression or
multiple analyses of variance) to determine ecologically relevant and statistically significant
correlations. Because one or both of the assumptions of parametric statistics tests (normality and
equality of variance) may be violated in the data, a non-parametric analogue may be used (e.g.,
Spearman Rank Correlation, Kruskal Wallis test), a = 0.05 [Zar 1984]. All analyses will be
completed with Statview statistical software (SAS Institute, v.5.0.1).
Table 1.
Non-exclusive list of land cover classes that will be used to examine potential
changes in habitat suitability and water quality (i.e., habitat and ecological
vulnerability) in the White River Basin study areas (after Anderson et al. 1976)
Land cover class name(s) Regional example(s)
Urban or Built-Up Land Shopping center, parking areas, sub-urban area
Grassland Grassy 'old field'
Forest Land Forest
Water Pond, lake, stream
Agricultural Land Rice, soybean, cotton row crop
Barren Land Gravel pit, beach
Wetland Oxbow, hardwood swamp, emergent marsh
Watershed determination
A set of watersheds, corresponding to pour point water sampling locations, will be
determined using a GIS and the National Elevation Dataset (NED). Watershed sizes will range
from approximately 10 km2 to 400 km2 and may differ from the USGS hydrologic units
described in the site description section, above. Watershed boundaries will be produced within
Arc/Info Grid using water sample (point) locations and elevation model produced from the NED.
Hydrologic sinks in the digital elevation model will be filled to ensure that a continuous drainage
network, flow accumulations, and flow direction grids are created. Subsequently, drainage
channels will be generated using cells with flow accumulations with greater than approximately
1000 grid cells (i.e., cells into which at least 10 hectares of watershed area are drained). If water
sample (point) coordinates are inaccurate, sample points will be manually moved using location
descriptions.
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Table 2.
Non-exclusive list of landscape indicators that will be used to examine potential changes
in habitat suitability and water quality (i.e., habitat and ecological vulnerability) in the
White River Basin study areas (after Lopez 1999, Jones et al., 2000b, and Jones et al. 2000c)
Name of Indicator Explanation of Indicator Hypothesized Response Parameters
Forest land cover Percent of support area that Habitat suitability and water quality/quantity
has forest land cover
Agricultural land Percent of support area that Habitat suitability and water quality/quantity
cover has agricultural land cover
Urban land cover Percent of support area with Habitat suitability and water quality/quantity
urban land cover
Wetland land cover Percent of support area with Habitat suitability and water quality/quantity
wetland land cover
Inter-wetland Mean distance between Habitat suitability and water quality/quantity
distance wetlands in support area
Wetland density Number of wetland patches Habitat suitability and water quality/quantity
within a support area
Riparian agriculture Percent of support area with Habitat suitability and water quality/quantity
agricultural land cover
adjacent to stream edge
Riparian forest Percent of support area with Habitat suitability and water quality/quantity
forest land cover adjacent to
stream edge
Forest fragmentation Percent of forested areas that Habitat suitability and water quality/quantity
join a forested area to a non-
forested area
Road density Mean number of kilometers Habitat suitability and water quality/quantity
of roads per km2 of support
area
Roads near streams Proportion of total stream Habitat suitability and water quality/quantity
length having roads within
30 meters .
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Non-exclusive list of data used in this study:
Aerial Photographs: These data will vary by region and by availability. Color infrared
photographs as stereo-pairs will be the ideal selection criteria but final selection will depend
upon availability. These data are available from a variety of sources and will be searched at the
EROS Data Center in Sioux Falls, SD. The ideal range of scales is from approximately 1:6000
to 1:24,000, however scales up to 1:40,000 may be used if finer scales are unavailable. These
data will be used to validate land cover, such as forest or agriculture, for the purpose of
determining the habitat suitability for plants and animals, and the impact on water
quality/quantity.
Landsat Thematic Mapper (TM) Data: These data are available from the EROS Data Center,
Sioux Falls, SD, and are acquired from earth orbit. Digital image data are available in three
visible bands (Red, Green, and Blue), one near-infrared band, and two mid-infrared bands with a
spatial resolution of 30 meters. These data will be used to estimate area of land cover,
specifically sandy shore habitat, urban areas, herbaceous vegetation, and woody vegetation, for
the purpose of determining the habitat suitability for plants and animals, and the impact on water
quality/quantity.
Landsat MultiSpectral Scanner (MSS) Data: These data are available from the joint EROS Data
Center and the North American Landscape Characterization (NALC) database that is located at
the U.S. EPA Landscape Ecology Branch (LEB) facility in Las Vegas, Nevada (see Program
Management). These data are acquired from earth orbit and are processed to facilitate land cover
change analyses (i.e., minimal cloud cover, co-registered decadal images). Digital image data
are available in two visible bands (Red and Green), and two near-infrared bands, and have a
nominal spatial resolution of approximately 80 meters, resampled to 60 meter resolution. These
data will be used to estimate area of land cover, specifically sandy shore habitat, urban areas,
herbaceous vegetation, and woody vegetation, for the purpose of determining the habitat
suitability for plants and animals, and the impact on water quality/quantity.
National Wetland Inventory (NWI) Maps: (photo-interpretation mark-up of 7.5 minute USGS
quadrangles): Where available in digital format, these maps will be ordered from the USFWS. If
large-scale hard-copy maps will suffice, these data will be ordered in paper or Mylar format from
the USFWS. These data will be used to estimate area of land cover, specifically wetland classes,
for the purpose of determining the habitat suitability for plants and animals, and the impact on
water quality/quantity.
Gap Analysis Program (GAP) Data: These data are available from USGS and estimate the
current land cover of the study areas (1990s data). The purpose of the program is to provide
regional assessments of the conservation status of native vertebrate species and natural land
cover types, and to facilitate the application of this information to land management activities.
These data will be used to estimate area of land cover, specifically plant species, vegetation type,
and agriculture, for the purpose of determining the habitat suitability for plants and animals and
14
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the impact on water quality/quantity. The habitat models in the GAP dataset will also be used
for comparison to the habitat suitability models developed in this study.
USFWS - NBS Land Cover Data: These data are available from the U.S. Fish and Wildlife
Service and National Biological Service. These land cover data were classified from two-season
(spring/fall) 1992 TM data at 30m resolution. Forest and some agricultural lands were classified
using supervised classification. Remaining agricultural lands classifications are from
independent classification of 1992 TM data by USDA and University of Arkansas Center for
Advanced Spatial Technologies. These data will be used to estimate area of land cover,
specifically agriculture crop type, for the purpose of determining the habitat suitability for
animals, and the impact on water quality/quantity.
1950s Forest Cover Data: These data were made available by The Nature Conservancy. These
data include a digital file depicting forest cover in the late 1950s, as determined by aerial
photograph interpretation. These data will be used to estimate area of forest cover in the 1950s,
for the purpose of estimating the presence of mature forest stands in the study areas.
Digital Raster Graphics (DRG): These data are available from the USGS and are scanned
images of USGS topographic maps. The image inside the map neatline is georeferenced to the
surface of the earth and fit to the Universal Transverse Mercator projection. These data
(scale= 1:24,000) will be used as supplementary information for estimating the area of land
cover, specifically human activity (roads and urban areas), for the purpose of determining the
habitat suitability for plants and animals, and the impact on water quality/quantity.
National Land Cover Data (NLCD): These data are sponsored by the Multi-Resolution Land
Characteristics (MRLC) Consortium and are a product that contains land-cover data for the
conterminous United States. NLCD land cover was mapped using general land cover classes
(see http://www.epa.gov/mrlc/classes.html). These data will be used to estimate area of land
cover, specifically wetland, upland, water, residential, commercial, and industrial, for the
purpose of determining the habitat suitability for plants and animals, and the impact on water
quality/quantity.
National Elevation Dataset (NED): These data have been developed by merging the highest-
resolution, best-quality elevation data available across the United States into a seamless raster
format, and are available from the USGS. NED is the result of the maturation of the USGS
effort to provide 1:24,000-scale Digital Elevation Model (DEM) data for the conterminous
United States and l:63,360-scale DEM data for Alaska. These data will be used to develop a
DEM and a watershed model of the study areas.
National Water-Quality Assessment (NAWQA) Data: These data are available from the USGS
and are designed to describe the status and trends in the quality of the Nation's ground- and
surface-water resources. As part of the NAWQA program, investigations will be conducted in
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59 areas, called study units, two of which correspond with the White River Basin hydrologic
study areas (the Mississippi Embayment NAWQA study unit and the Ozark Plateau NAWQA
study unit). These data will be used to estimate current water quality/quantity in the White River
Basin, for the purpose of determining the relationships between land cover gradients and water
quality/quantity.
Storage and Retrieval (StoRet) System Data: These data are available from the U.S. EPA Office
of Water. The system is a repository for water quality, biological, and physical data. These data
will be used as a supplement to the NAWQA data to estimate current and historical water
quality/quantity in the White River Basin, for the purpose of determining the relationships
between land cover gradients and water quality/quantity.
Breeding Bird Survey (BBS) Data: The BBS is a large-scale survey of North American birds. It
is a roadside survey, primarily covering the continental United States and southern Canada,
although survey routes have recently been initiated in Alaska and northern Mexico. The BBS
was started in 1966, and the over 3,500 routes are surveyed in June by experienced birders.
Some of these routes are within the White River study areas. These data will be used to spot-
check the results of the bird models, although there are insufficient BBS data at the scale of this
study to perform statistical analyses.
Habitat Suitability Index (HSI) and Natural History Information: These indexes and information
will be used for selected plant and animal species to construct a GIS-based model of habitat
suitability. These suitability models (based upon current conditions) will then be re-run under a
variety of future landscape change scenarios for the purpose of estimating ecological and habitat
vulnerability.
SCHEDULE, MILESTONES
2000 Mar. - Apr. RARE funding awarded. Determined MSS data coverage for general study area,
ordered new satellite data (including "leaf-off scenes).
2000 May LEB completion of contract work assignment. Initial LEB team member
meetings to develop study boundaries, potential indicators
2000 June RARE funding received and committed. Contractor completion of Technical
Work Assignment, preliminary meetings with contractor regarding study
boundaries and data coverage, completion of Draft Research Plan, preliminary
meeting with U.S. EPA Region 6 regarding indicator parameter selection, GIS
data coverage collection
2000 July U.S. EPA Region 6 and stakeholder meeting in Little Rock, Arkansas to discuss
parameter selection and other issues, study area reconnaissance
2000 Oct. Completion of quarterly report on study progress to Region 6
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2000 Nov.- Mar. Peer review of U.S. EPA research plan, completion of quarterly report on study
progress to Region 6, preliminary habitat suitability model for the fine scale
study area completed
2001 Apr. Completion of quarterly report on study progress to Region 6
2001 July Completion of all habitat suitability models, collection of remote sensing and
GIS data, model development for water quality analyses, completion of quarterly
report on study progress to Region 6
2001 Oct. Completion of habitat vulnerability - future scenario analyses, completion of
quarterly report on study progress to Region 6
2002 Jan. Preliminary water quality models for hydrologic study area, completion of
quarterly report on study progress to Region 6
2002 Mar. Completion of water quality - future scenario analyses
2002 Apr. Completion of quarterly report on study progress to Region 6
2002 Sept. Publication of U.S. EPA report, preparation of manuscripts for refcreed journal
articles #1 - #3 (see Major Project Deliverables)
MAJOR PRODUCTS
A) Project report: An Ecological and Habitat Vulnerability Assessment of the White River Basin
(hard-copy text and digital format)
B) Refereed journal articles:
#1 Utilizing landscape-ecological relationships of the past to model ecological scenarios of
the future: a remote-sensing and GIS approach
#2 The landscape-ecological relationships between land-cover change and habitat
suitability in the Mississippi Alluvial Valley
#3 The landscape-ecological relationships between land-cover change and water quality in
the White River Basin
C) Images/data from study areas
D) Land cover maps
E) Ecological models
PROJECT BUDGET OVERVIEW
U.S. EPA Region 6 RARE funding - Land cover maps, consistency assessment, and
implementation of habitat models
In-kind support from the Landscape Ecology Branch - Processing and interpretation of satellite
data and derived products; technical expertise in remote sensing and image processing; analyses
using geographic information systems; multi-variate statistical analyses; ecological model
development; map production; presentation of results; data set management and archiving, final
report and ref creed journal article production
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PROJECT MANAGEMENT
The Landscape Ecology Branch
U.S EPA's Landscape Ecology Branch (LEB) is located on the campus of the University
of Nevada, Las Vegas and is under the U.S. EPA's Office of Research and Development,
Environmental Sciences Division. The LEB employs 33 professionals, including biologists,
research ecologists, engineers, statisticians, GIS specialists, remote sensing specialists, photo-
interpreters, data management specialists, graphic artists, technical writers, and procurement
specialists. The LEB has robust hardware and software capabilities (e.g., ESRI-Arc/Info, ESRI-
ArcView, ERDAS-Imagine, RSI-ENVI) that enable the efficient processing and analysis of data.
The Branch employs 6 full-time Ph.D. researchers and possesses a modern laboratory, supported
by the resources and facilities of the Environmental Sciences Division and the U.S. EPA
Environmental Photographic Interpretation Center in Reston, Virginia.
The LEB conducts research in the field of landscape ecology and related disciplines,
develops landscape assessment and characterization applications, and develops tools and
methods for solving regional environmental problems. Many of these projects involve the
analysis of ecosystem and watershed vulnerability to human-induced stresses. The primary goal
of the LEB is to develop tools for: (1) understanding and forecasting ecosystem trends; (2)
assessing the ability of an ecological resource to provide desired benefits; (3) anticipating
emergency environmental problems; and (4) monitoring and documenting progress in
maintaining and restoring ecosystems. LEB research includes developing ecologically-
meaningful indicators of landscape condition and trends related to endpoints of importance to the
EPA; developing, applying, and transferring tools for measurement, assessment, and prediction
of the sustainability and vulnerability of landscapes at multiple spatial and temporal scales; and
maintaining pace with rapidly developing science and technology of remote sensing. Current
LEB projects include applied research in Arizona, Arkansas, California, Colorado, Delaware,
Georgia, Idaho, Illinois, Indiana, Kentucky, Louisiana, Maryland, Michigan, Minnesota,
Mississippi, Missouri, Nevada, New Jersey, New Mexico, New York, North Carolina, North
Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Vermont,
Virginia, Washington, West Virginia, and Wisconsin.
U.S. EPA Team Members and Contact Information
Donald Ebert
Ecologist
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2158
Fax: (702) 798-2692
ebert.donald @ epa.gov
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Curt Edmonds
Electronics Engineer
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2264
Fax: (702) 798-2692
edmonds.curtis @ epa.gov
Daniel Heggem (Co-Principal Investigator)
Research Environmental Scientist
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2278
Fax: (702) 798-2692
heggem.daniel @ epa.gov
K. Bruce Jones, Ph.D.
Chief, Landscape Ecology Branch
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2671
Fax: (702) 798-2692
jones.bruce@epa.gov
Ricardo D. Lopez, Ph.D. (Co-Principal Investigator)
Physical Scientist
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2394
Fax: (702) 798-2692
lopez.ricardo@epa.gov
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John G. Lyon, Ph.D.
Director, Environmental Sciences Division
U.S. EPA National Exposure Research Laboratory
Environmental Sciences Division/ORD
P.O. Box 93478
Las Vegas, NV 89193-3478
Tel: (702) 798-2525
Fax: (702) 798-2692
lyon.j ohng @ epa. go v
Gerald Carney, Ph.D.
(CRIA Coordinator, U.S. EPA Region 6)
Norman E. Dyer, Ph.D.
(Scientist, Special Assistant for Technology Transfer, U.S. EPA Region 6)
Barbara Keeler
(Regional Project Coordinator, U.S. EPA Region 6)
Sharon Osowski, Ph.D.
(CRIA Coordinator, U.S. EPA Region 6)
Ken Teague
(Ecologist, U.S. EPA Region 6)
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