v>EPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington, D.C. 20460
ERA/600/R-99/016
February 1999
An Ecological
Assessment
of the Louisiana
Tensas River Basin
Classified Image -
Vegetation Change
1970s to 1990s.
Land Cover
Forest
Forest Loss
Forest Gain
Human Use
Water
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Printed with Soy/Canola ink on paper that contains at least 50% recycled fiber and is recyclable.
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An Ecological Assessment of the
Louisiana Tensas River Basin
Daniel T. Heggem1, Anne C. Neale1,
Curtis M. Edmonds1, Lee A. Bice2,
Rick D. Van Remortel2, and K. Bruce Jones1
1 Environmental Sciences Division, U.S. Environmental Protection Agency,
Las Vegas, Nevada
2 Lockheed Martin Environmental Services, Las Vegas, Nevada
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Table of Contents
Executive Summary
Chapter 1. Taking a Broader View
Purpose and Organization of This Atlas
Landscape Ecology and the Analysis of Broad-Scale Environmental Condition
What are Landscape Indicators and How Do They Help to Understand Environmental Conditions?
How Were the Landscape Indicators Selected?
How Were the Landscape Indicators Measured?
How Were the Landscape Indicators Summarized?
Chapter 2. The National Context
Data Sources
How to Read the Maps and Charts in this Report
Human Use Patterns
Forest Patterns
Patterns Affecting Water Quality
National Context Summary
Chapter 3. The Tensas River Basin Landscape Assessment
Biophysical Setting
Land Cover
Humans in the Landscape
Population Density and Change
Human Use Index
Roads
Roads Along Streams
Forests in the Landscapes
Percentage of Forest Cover
Forest Fragmentation
Percent of the Watershed in the Largest Forest Patch
Detailed Forest Analysis of the Tensas River Basin, 1970s to 1990s
Vegetation Change
Vegetation Change by Subwatershed
Forest and Crop Land Along Streams
Water and the Landscape
Watershed Indicators
Riparian Analysis
Vegetation Change Along the Tensas River Reach
Backswamp Area Analysis
Soil Erodibility Analysis
Wetland Restoration Analysis
Chapter 4. Water Quality
Nitrogen and Phosphorus Export to Streams
Chapter 5. Comments and Recommendations
1
2
3
4
6
10
12
13
13
16
17
19
22
24
25
25
27
28
28
28
29
30
30
30
33
33
34
36
37
38
40
41
42
43
43
45
46
55
62
63
Appendix
66
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EXECUTIVE SUMMARY
TENSAS RIVER BASIN - A LANDSCAPE APPROACH TO COMMUNITY-
BASED ENVIRONMENTAL PROTECTION
Tensas River Basin 1970s
False Color Image
Tensas River Basin 1990s
False Color Image
These images illustrate the 12% decrease in total forested landcover between the early 1970s and the
early 1990s.
Tensas River Basin
The purpose of this document is to give the results
of an ecological assessment using landscape ecology and
water quality methods in the Tensas River Basin, Louisiana.
This assessment can be used as a tool to estimate the
impact of human land use practices that are being currently
implemented to improve environmental quality. It can be
also used for ecosystem targeting and help people make
good decisions on the best location for restoration sites.
The U.S. EPA's Office of Research and Development,
Landscape Ecology Branch did this work under the
guidance of U.S. EPARegion 6, the Louisiana Department
of Environmental Quality and the U .S. EPA Gulf of Mexico
Program by way of the Regional Applied Research Program
(RARE).
The Tensas River Basin encompasses approxi-
mately 930,000 acres of Mississippi River alluvial flood plain
in Northeast Louisiana. Historically, most of the Basin was
covered with bottomland hardwood forested wetlands. The
bottomland hardwood wetlands of the Tensas River Basin
have been described as some of the richest ecosystems in
the country in terms of diversity and productivity of plant and
animal species. At the same time, these cleared lands are
recognized as some of the Nation's most productive
farmland for grain and fiber. The result is a conflict of land
use between traditional row crop agricultural interests and a
concern fora healthy, diverse, and stable ecosystem.
The Tensas River Basin is a target watershed of
several U.S. Environmental Protection Agency environmen-
tal studies including the Nonpoint Source Management
Program, U.S. EPA Region 6, and the Gulf of Mexico
Program. The Nonpoint Source Management Program has
identified watersheds in Louisiana which have been
impaired by nonpoint pollution and where land use prac-
tices contribute to these pollutant problems. This program
identified specifically what types of best management
practices need to be implemented to improve environmen-
tal conditions. Using the existing data and with the
cooperation of landowners, the Tensas River Basin offered
aunique opportunity toimplement best management
practicesthat could help reduce the concentration of
sediment, excess nutrients, or pesticides leavingthe
Basin. The nutrients leaving the Tensas River Basin,
combined with other Mississippi Valley watersheds, are of
concern to the Gulf of Mexico Program because research
has shown that excess nutrients cause hypoxia (<2 mg/l
oxygen) in the bottom waters of the Gulf of Mexico. This
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condition represents a threat to the coastal marine ecosystem
and fisheries in this region of the Gulf. Landscape Ecology
methods provide a tool to assess the impact of human landuse
practices thatare being implemented to improve environmental
quality.
In years past, the freshwater marshes, stream bank
areas, and bottomland swamps of theTensas River Basin were
understrong development pressures. Large portions of forest
near streams and in backwaterswamp areas were converted to
agriculture. This toss of forested areas decreased filtering
capacity that normally removes pollution and nutrients before
they enter streams, lakes, and estuaries. Wetland forests also
dissipate energy and nutrients associated with extreme
precipitation events and therefore reduce damage to down-
stream farms and cities resulting from floods. The Tensas River
Basin is unique in that natural levees along the riparian vegeta-
tion lie on the highest ground in the Basin. This causes
drainage waterto run parallel to streams for many miles before
actually entering the stream and river water channels. Wet-
lands and backswamps then become the vegetation filtering
areas for pollutants and nutrients. Preserving or restoring
wetland forests have other economic benefits including wetland-
based recreation, including hunting and harvesting wetland
plants. The people who live within the Tensas River Basin
realize that the vegetation along a stream and in backswamp
areas can influence the condition of both the stream bank and
tie water In the stream. Restoration efforts began in the early
1990s.
The strip of vegetation along streams is known as
the riparian vegetation zone. It is commonly described by the
types of vegetation it contains and by the presence of water.
In an ideal situation, many pollutants and fertilizers will be
Intercepted or absorbed by the riparian vegetation and if s root
system. This helps to keep the streams dean. Bank erosion
fe also mitigated by intact riparian vegetation. The conditions
of the riparian ecosystem overa whole watershed can be
studied in order to learn where, for example, a restoration
project would most improve water quality. Similarly, a charac-
terization of riparian conditions over the entire Tensas River
Basin can help to identify which areas of the Basin are most
likely to see improved water quality as a result of riparian
vegetation improvements.
Land cover is the product of past land uses on the
backdrop of the biophysical setting. A map of landcover is
essentially a picture of the dominant vegetative, water, or
urban cover in an area. The images of land cover in the
Tensas River Basin for 1972 and 1991 (see above) are based
primarily on images taken by the Landsat Multispectral
Scanner satellite since the early 1970s. The land cover map
was based on the North American Landscape Character-
ization (NALC) data, a Federal effortto create similar date for
theen6recouniry. The resolution of the land coverdatais60
meters, so each pixel (picture element) represents an area
aboutthe size of afootballfield. Although individual
pixels are fartoo small to be rendered accurately here,
the visual impression of broadscale regional patterns is
readily apparent. Forest vegetation shows up on the
image as red in color, agriculture shows up as light red,
grey, light blue and white and almost always shows a
pattern with rows or right angles typical of farm fields.
These images were then classified for landuse.
The classifications were forest, human use (urban and
agriculture) and water. Through the use of computerized
Landscape analyses, the 1972 image was compared to
the 1991 image and changes in forest areas and human
use areas were calculated. As the images show, there
was a tremendous forest loss over that time period. In
1972 the land covertypes forest and agriculture covered
an area of about 34% and 65% of the area, respectively.
In 1991 the land covertypes forest and agriculture
covered an area of about 22% and 77% of the area,
respectively. Where forests have been removed, agricul-
ture and urban land covers become more dominant, this
can be seen by comparing the images to observe the
forest loss over 20 years.
The images also show how the forest, agricul-
ture and urban landcover vary across the landscape of the
Tensas River Basin. Understanding the variation of
landcoverwith respect to landscape features, such as
cities, roads, lakes and streams, is the foundation of the
landscape ecological assessment. Other landscape
indicators include: population density and change, human
use index, roads, roads along streams, percentage of
forest cover, forestfragmentetion, percent of the water-
shed in the largest forest patch, forest analysis of the
Tensas River Basin, vegetation change, vegetation
change by subwatershed, forest and crop land along
streams, watershed indicators, riparian analysis,
vegetation change along the Tensas River Reach,
backswamp area analysis, soil erodibility analysis, and
wetland restoration analysis.
The Tensas River Basin is one of 2,099 individual
watersheds located across the United States. Many
people throughout the United States are restoring riparian
vegetation areas and are in need of CIS and landscape
methods to help them make good decisions on the best
locations for restoration sites.
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Chapter 1: Taking a Broader View
The Gulf of Mexico Program is working with its partners
including U.S. EPA Regions 4,5,6, and 7 to identify ap-
proaches to reduce nutrients in the surface waters of the
Mississippi River System. The problem is being ad-
dressed at the scale of the larger watershed (Mississippi
River System). This report reflects the Landscape
Ecology research done to characterize changing land-
scape patterns as they relate to potential changes in
nutrient loading for one river basin. This approach can be
refined and applied to other watersheds within the Missis-
sippi River System.
Environmental quality is important to everyone. It affects
our health, our quality of life, the sustainability of our
economies, and the futures of our children. Yet pres-
sures from an increasing population, coupled with the
need for economic development and an improved
standard of living often result in multiple impacts on our
natural resources. And, just as a person with a less-
than-healthy life style is more prone to infection, a
weakened ecosystem is less able to withstand additional
stress. Unfortunately, it is often difficult to see these
changes in environmental quality because they occur
slowly or at scales we do not normally consider.
There is growing public, legal, and scientific awareness
that broader-scale views are important when assessing
regional environmental quality. In the past, media
attention has focused on dramatic events, focusing our
environmental awareness on local or isolated phenom-
ena such as cleaning up Superfund sites, stopping
pollution from a drainage pipe, saving individual endan-
gered species, or choosing a site for a parish landfill. In
an era of environmental legislation, monitors of environ-
mental quality responded to legal standards, like those
for drinking water or air quality, and as a result they
reported very narrow views of the environment. Given
this view of the world, scientists studied fine-scale model
systems and considered humans to be external factors.
Today, our perceptions are changing. We realize that
humans and our actions are an integral part of the
global ecosystem, and that the environment is compli-
cated and interconnected with human activities across
local and regional scales. We have begun to take a
broader view of the world and of our place in natural
systems.
Technology has advanced in ways that make it easier to
obtain new views of overall environmental quality.
Larger patterns and processes can be studied by using
computers and satellites. These technologies, com-
bined with a better understanding of how the pieces fit
together, help to understand where we are now with
regard to environmental quality, where we hope to be in
the future, and what steps need to be taken to get there.
This atlas takes advantage of some of these technolo-
gies in assessing environmental conditions over the
Tensas River Basin of Louisiana.
Just as we now watch broad-scale weather patterns to
get an idea of whether it will rain in the next few days, we
can develop a better assessment of current environmen-
tal conditions by combining regional and local-scale
information. Broad-scale weather patterns are important
because they affect and constrain what happens locally
on any given day. By taking a broader view of the environ-
ment, or widening our perspective about how the environ-
ment is put together, it becomes easier to see where
changes occur and to anticipate future problems before
they materialize.
Bottom-land Hardwood forest of the Tensas River Basin.
Environmental issues, such as nutrient runoff are identified by the Tensas
Technical Steering Committee.
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'-';!ii(T(f<:fjt f\$R(KStn&\t o: vie Louisiana /erisas hiver tiasin una/3tei 1 ,
Purpose and Organization of this Atlas
This atlas presents an environmental assessment of
the Tensas River Basin of Louisiana (Figure 1.1).
The assessment was conducted by using measure-
ments derived from satellite imagery and spatial
data bases and summarized by subwatersheds.
The information presented in this atlas is intended to
help visualize and understand the changing condi-
tions across the watershed and how this pattern of
conditions can be used as a context for understand-
ing community-level situations within the region.
The atlas is divided into five chapters with one appendix.
This chapter introduces the reasons for doing a broad-
scale regional analysis of environmental condition.
Chapter 2 places the Tensas River Basin into the context
of the lower 48 states. Chapter 3 presents an analysis of
landscape conditions in the Tensas River Basin and
briefly explains the landscape analysis methodology.
Chapter 4 discusses water quality issues in the Tensas
River Basin. Chapter 5 presents some recommendations
for future efforts. The Appendix provides additional data
that could not be included in Chapters 3 and 4.
Ftguw 1.1
Tensas River Basin
LEGEND
• OBss
— Intestate
US and State Highways
/\/Tensas River
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Landscape Ecology and the Analysis of
Broad-Scale Environmental Condition
To most people, the term "landscape" suggests either a
scenic vista or a backyard improvement project. To
ecologists and other environmental scientists, a land-
scape is a conceptual unit for the study of spatial
patterns in the physical environment and the influence of
these patterns on important environmental resources.
Landscape ecology is different from traditional ecology in
several ways. First, it takes into account the spatial
arrangements of the components or elements that make
up the environment. Second, it recognizes that the
relationships between ecological patterns and processes
change with the scale of observation. Finally, landscape
ecology includes both humans and their activities as an
integral part of the environment.
There are many applications for landscape ecology and
broad-scale information in regional assessments. For
example, we can identify the areas that are most heavily
impacted today by combining information on population
density, roads, land cover, and air quality. In the Tensas
River Basin, we already have good information (from the
U.S. Census Bureau) about which areas are most urban-
ized. But which areas have only a small proportion of
stream length bordered by adjacent forest cover? Which
areas are characterized by a
high degree of forest fragmen-
tation? What percentage of
forest loss occurred on wet
soils? What about informa-
tion for watersheds instead of
areas? Broad-scale mea-
surements can be taken in
order to make relative com-
parisons of these indicators
over the entire region.
Another use of this approach
is to identify the most vulner-
able areas within the water-
shed. Vulnerable areas are
not yet heavily impacted, but
because of their circum-
stances they are in danger of
becoming so.
One example might be an area that has a relatively high
percent of forest cover, but that is also experiencing rapid
gains in human use of the land. Such an area might be
more vulnerable to forest fragmentation than a similar
area with less human use or less forest area.
A third application of this approach is to place localities
into a watershed and/or regional context. Some indi-
vidual towns and rural areas in the Tensas River Basin
may seem isolated, perhaps within a large forested area.
However, all are connected by physical features and by
ecological processes. Water flows from one place to
another, roads provide a connecting infrastructure, and
land cover patterns of forest and agriculture form a
connected backdrop for all of our activities. While land
management decisions are made and implemented at a
local scale, a watershed perspective can guide our
decisions and make us better stewards of our environ-
ment. By placing our homes, farms, neighborhoods, and
government organizations into a watershed landscape
picture, we can begin to make informed decisions that
consider not only our goals and actions, but our
neighbor's as well.
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What are Landscape Indicators and How
Dp They Help to Understand Environmental Con-
ditions?
Figure 1.2 illustrates how a single community is linked to
the landscape at several different scales and across
different mapping units (watersheds and parishes in this
example). Tallulah is highlighted in the middle of the
figure. At this scale we concentrate on individual land
parcels and roads, and our decisions are based on a
local perspective. Broader-scale perspectives emerge as
we follow the lines up either side of the figure. We see
that the community is part of both a subwatershed (left)
and a parish (right), which, in turn, are components of
groups of watersheds and parishes. These larger groups
are components of the entire region. This is an important
concept because local environmental issues can have
regional impacts.
An indicator is a number that is calculated by summariz-
ing data. The indicator calculations may also consider
related data or use a model to improve reliability. Well
known economic indicators include the seasonally-
adjusted unemployment percentage and number of
housing starts, both of which indicate overall economic
condition. In these indicators, seasonal adjustment is
made with a model, and most economists look at sev-
eral indicators together instead of just one at a time.
Similarly, landscape indicators can be measurements of
ecosystem components (such as the amount of forest)
or processes (such as net primary productivity), and
models can be used to help interpret the measurements
in order to understand overall ecological conditions.
Flgura 1.2
This figtifo may help to understand how
a dy (bottom csnt&i) fits Into a larger
context ofalthw watersheds (left
branch) or parishes (right branch).
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Figure 1.3 shows an example of measuring spatial pat-
terns as an indicator of stream conditions. The distribution.
of streamside land cover has been mapped for the same
subwatershed that is shown in Figure 1.2. Stream seg-
ments that are green have adjacent forest; orange indi-
cates that streams are next to agriculture or urban land
covers. The pattern of streams in relation to land cover is
an indicator of conditions within the stream. Forests often
filter pollutants, preventing them from reaching the water,
whereas agricultural and urban landuse often contribute
pollutants to streams. They also dissipate energy associ-
ated with major precipitation events; this reduces nutrient
loading and the severity of flooding. A simple summary
indicator might be the percentage of stream length in the
parish that is adjacent to forest land cover. To refine this
indicator, a model might help to account for "natural"
conditions, for example whether or not forest was the
natural land cover for the parish.
Figure 1.3
Spatial patterns of land cover in
relation to streams for a
subwatershed in the Tensas River
region. Stream segments are colored
green or orange, depending on
whether the segments are adjacent to
forest or agriculture/urban land cover.
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iiflfl CSOWB^ lliCSIslESap.iiiOEEassilE^iMirifc: ^^!*GijjMfcSi«ii!!!!!!ffi!!!!!!!!
How Were the Landscape Indicators Selected?
The starting point for selecting indicators was what
people in the area said they cared about. These concerns
were then matched to our ability to make meaningful
measurements, recognizing that some things just can't be
measured very well given the available data or models.
As a result of workshops and advice from people who live
in the Tensas River Basin, three general environmental
themes were identified-human use, forest and water.
These three themes and the indicators measured within
each theme are discussed in detail in Chapter 3.
Figure 1.4 shows an example of a landscape indicator. In
this example you can see that if forest patches are not
connected, the forest is more vulnerable to the distur-
bance. Figures 1.5 and 1.6 are pictorial representations of
key landscape attributes that affect the sustainability of
environmental condition across broad scales.
Figure 1.5 shows some key landscape components that
sustain a high quality environment, and Figure 1.6 shows
some human modifications of the landscape that can
reduce the sustainability of natural resources. These
figures, although not of the Tensas River Basin, illustrate
some of the important landscape indicators analyzed in
this atlas.
Landscapes are very complicated, and the generality of
the conceptual models is an accurate reflection of the
level of scientific understanding of landscape dynamics.
Scientists who study landscape ecology are trying to
improve our ability to interpret landscape indicators
relative to environmental values. The improvements will
help to interpret the information that is contained in this
atlas, and will also suggest new landscape indicators or
new ways to measure the ones that are included here.
In the meantime, it is worth exploring how much is known
about regional conditions, and what can be said by using
state-of-the-art landscape indicators.
* t
Large-scale
disturbance
(human use)
Population]
persists
Recovery
G
Large-scale
disturbance
(human use)
\
o
Population |
does not
persist
Time
FJguw 1.4
Fonst fragmentation can result In the loss of a species due to natural distur-
barm. In tills exampte larger, more connected forest sustains the species over
firm*, vWisraas smaltor, more Isolated habitat loses the species over time.
(hi Ms example, tan Is non-forest, red Is occupied forest, and white is unoccu-
pM forost)
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Forest connectivity
is crucial for the
persistence of
forest species,
especially in areas
with moderate
amounts of
agriculture
Riparian zones
filter sediments
and pollutants,
especially in
agricultural
areas, in
addition to
providing
important
wildlife habitats
Large blocks of
interior forest
habitat are
important for
many forest
species
Figure 1.5
A pictorial representation of some
landscape components that sustain
a high-quality environment.
The number of
forest scales
surrounding a
point in the
landscape
determines the
variety of
forest species
found there
Forest edge
habitat is
important for
many species
that require more
than one habitat
type to survive
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Agriculture on sfeej
slopes increases
loss and sediment
loading to streams I
Dams alter the natural
habitats and hydrology
of streams
Agriculture areas near
streams Increase stream
sediment loads and
chemical inputs
Flgun 1,6
A pictorial representation of some human
of tha landscape that reduce the
of natural resources
The amount and
location ofagricultur
in a watershed
influences
landscape pattern
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Humans reduce riparian
cover along streams,
which decreases
filtering capacity
,-,.
Forest harvest
practices influence
forest connectivity
and patch sizes
Air pollution spreads
across the landscape,
affecting regional
air quality
Roads near streams
increase sediment and
pollution loads by
increasing surface
runoff
Population growth
results in loss of forest
and changes in overall
watershed landscape
pattern
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How Were the Landscape Indicators Measured?
Many kinds of data were used to prepare the indicators
shown In this atlas. Federal agencies were the primary
source for data, including maps of elevation, watershed
boundaries, road and river locations, population, soils,
and land cover. Sources included the U.S. Geological
Survey (USGS), the U.S. Environmental Protection
Agency (EPA), the U.S. Department of Agriculture
(USDA), the U.S. Census Bureau, the U.S. Fish and
Wildlife Service, the Louisiana Department of Environ-
mental Quality, The Mississippi Alluvial Plain Project of
The Nature Conservancy, and the North American
Landscape Characterization (NALC) Program.
Data collected by satellites were used to map land
cover and Its change over time. The sensors carried
on satellites measure the light reflected from the
Earth's surface. Because different surfaces reflect
different amounts of light at various wavelengths, it is
possible to identify land cover from satellite measure-
ments of reflected light. Figure 1.7 illustrates the
differential reflectance properties of water, sediments
suspended in water, and land surfaces for a typical satel-
lite image. Examples of land cover maps derived from
satellite images appear later in this atlas.
In a typical digital map, data are stored as a series of
numbers for each theme. These maps can be thought of
as checkerboards, where each grid square (or pixel, which
is an abbreviation of "picture element') represents a data
value for a particular landscape attribute (for example soils,
topography, or land cover type) at a specific location.
figuro U
Hfusfm'tion of differential light
nttecianca properties for
wafer, sediments suspended
In water, and land surfaces
ovora portion of Vancouver,
British Columbia -These
Images can be manipulated In
various ways to extract
information about the Earth's
surface,
Sourcs; North American
Landscape
Characterization
Pmgram
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Figure 1.8 illustrates one method of measuring a land-
scape indicator. This method ("overlaying") simply
overlays maps of different themes in order to extract
information about spatial relationships among the
themes. These relationships are then stored as a new
map which combines the information from the original set
of maps.
Figure 1.8
Land cover (with agriculture in red) is combined with topography to indicate
agriculture on steep slopes. The combined map shows agriculture on slopes
greater than 3%.
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How Were the Landscape Indicators
Summarized?
Usually, a watershed is defined as a catchment area
that is drained by a single stream or river (i.e., the
Mississippi watershed consists of all the area drained by
the Mississippi river system, including ail tributaries).
The dividing lines between watersheds are formed by
ridges. Water on one side flows into one stream, water
on the other side flows into a different steam. Thus,
watersheds are a natural unit defined by the landscape.
Watersheds can be defined at several different scales.
The USGS has divided the contiguous U.S. into 2,099
watershed units known as 8-digit hydrologic accounting
units (HUCs). The Tensas River Basin is defined as one
of these 8-digit HUCs and serves as the boundary of our
study area.
The Tensas River Basin 8-digit HUC was further divided
into 11-digit HUCs or subwatersheds (defined by the
USDA) as a basis for analyzing and summarizing the
landscape data (Figure 1.9). In many ecological studies,
especially those which assess water-related concerns,
subwatersheds are an appropriate unit for summarizing
data.
Fig 1.9
Tbnsas Rivof Basin divided Into subwatersheds.
Each stibwattjfslmd was given a unique number
(2*9) for this report.
The next chapter will look at the landscape from a na-
tional perspective. As you read about the national land-
scape, see how the Tensas River Basin compares to
other watersheds in the United States.
Subwatershed Hectares
5625
45532
92534
62012
11136
7353
79748
72365
Total
372000 (Hectares)
930000 (Acres)
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13
I
Chapter 2: The National Context
Before looking in detail at the Tensas River Basin, it is
helpful to place the Basin within a national perspective.
This chapter paints a picture of the lower 48 United States,
showing differences and patterns among watersheds at a
continental scale. A national context helps us interpret the
overall condition of the Tensas River Basin, relative to the
rest of the country. It also helps to determine if conditions
like those found in the Tensas River Basin are likely to
exist elsewhere.
While it would be desirable to look in great detail over the
entire nation, in practice only a few aspects of environmen-
tal condition can be described in a consistent fashion
nationwide. The coarse-scale maps in this chapter show
watershed rankings based on a variety of landscape
indicators. The rankings portray relative conditions across
the nation but do not show the absolute values of indicators
for each watershed. Indicator values are summarized in
the companion bar charts.
Data Sources
Four main data sources were used here. The most
important was a national map of land cover (Figure 2.1)
which describes the types of vegetation covering an area,
whether it is forest, crops or pasture, or covered with water
or urban areas. Although the resolution (spatial and land
cover) is fairly coarse (1 square kilometer and 9 of the
original 160 land cover classes), the familiar national
pattern is apparent-forests in the East, grasslands and
crops in the Midwest, and shrublands, deserts, and moun-
tain forests in the West. The Tensas River Basin is typical
of the alluvial valley of the lower Mississippi River, riverside
urban areas, agricultural valleys and plains, and forested
wetlands. The variety of the land cover types in the Tensas
River Basin, relative to other regions in the United States,
can make spatial pattern an important ingredient for
making environmental decisions in this region.
Some additional information was used to calculate the
indicators of environmental quality nationwide. Figure 2.2
shows the maps of roads, streams, and watersheds.
Clearly, not all the roads and streams are included. These
maps may be appropriate for a nationwide overview, but
much more detailed maps are needed for regional assess-
ments such as the Tensas River Basin analysis described
later. The watershed boundaries (Figure 2.2) identify 2,099
individual watershed units across the United States.
gure 2.1
lational land cover map. The U.S. Geological
'urvey produced this map of "Seasonal Land Cover
Regions of the Conterminous United States." The map was
erived from March-October (1990) 1-km Advanced Very High
Resolution Radiometer (AVHRR) imagery, digital elevation,
coregions, and climate data. The original 160 classes of land cover
ave been grouped into the 9 broad categories shown here.
Western Forest
Eastern Forest
Croplands
Shrublands
Grasslands
Wetlands
Water
Barren
Urban
-------
•10
For each watershed, the nine indicators (Table 2.1) included
Jr> this chapter were calculated from land cover and from the
spatial relationships among roads, streams, and land cover.
9 mXn ut& AfCUSA OtSaioU-
Table 2.1 List of landscape indicators used for the national context.
U-lndex (proportion of watershed area with anthropogenic land cover)
Agriculture Index (proportion of watershed area with agriculture land cover)
Number of natural land cover types per unit area
Proportion of watershed that has forest land cover
Average forest patch size as a percentage of watershed area
Index of forest connectivity
Proportion of total stream length with forest land cover
Proportion of total stream length with anthropogenic land cover
Number of roads crossing streams per unit stream length
-------
-------
An Cc<^3'~ "•'^j-''~5&""^"£^'tteLous&naTensss River Basin: Chapter?
How to Read the Maps and Charts in this Report
Rgure 2.3 illustrates the types of maps and charts that
appear In Chapter 2.
jjjjj tnip of mld-AtJantlc_watersheds ..... i_s£olor-cpded
"" "
-
relapvely
rabia" and "more durable" conditions
•ft,.
pile Data Range
shows the
(indicator values
for watersheds
Contained, jn each
tpfntile.
QoWte
Data Range (Percent)
1 • <70.600
2 & 70.600-76.869
3 3 76.870-84.579
4 • 84.580-89.889
5 • >89.890
X axis tsji^eugger limit of a datej
"
70 80 90 100
Woody landcover along streams was calculated as the percent
of streamlength with forest landcover types. By intersecting a
buffer zone around each stream with the landcover, a data set is
created which records all landcover types within a specified
distance to stream center.
Sources: USGS 1:100,000 River Reach 3 stream data, and
MRLC 30 meter Landsat land-cover data.
Indicator Value
Figure 2,3
How to road the maps and charts In this report.
-------
Human Use Patterns
One of the simplest and most informative indicators of
environmental impact is the extent to which humans
have changed the natural vegetation to crops or urban
land cover. These indicators are easy to interpret be-
cause profound land cover changes influence almost
every aspect of the environment from wildlife habitat to
soil erosion.
The national maps of human use intensity (Figure 2.4)
show watershed rankings for both total human use-
agriculture plus urban (Figure 2.4a) and only agriculture
(Figure 2.4b). Urban areas are relatively minor in terms of
total area, and farming areas are more extensive, so the
two maps are very similar. Most of the human appropria-
tion of land has occurred in the central United States and
along the eastern seaboard. Higher elevations and the dry
southwest appear to have been less impacted by conver-
sion to agricultural or urban land cover. Like most of the
south, Louisiana has a complicated pattern of land use that
deserves more detailed attention.
The chart gives some details about the distribution of
human use intensity among watersheds. You can see that
about 40% (800) of the watersheds have had only minor
Agriculture or Urban Land Cover
National Rank
Quintile Data Range
1 • < 3
3 - 12
12 -34
34 -72
>72
10 20 30 40 K) 60 70 80 90 100
Indicator \felue
Figure 2.4
Proportion of watershed area with: (a) agriculture or urban land cover, (b)
agriculture land cover.
-------
conversions to agriculture. These watersheds are prima-
rily located in arid and mountainous areas, where grazing,
although an important agricultural activity, does not change
the grassland cover type at this scale. About 10% (200) of
the Nation's watersheds have been almost completely
converted to agricultural land; these are located mostly in
the fertile central United States.
The Tensas River Basin (Figure 2.4b) is shown in red
putting ft in the 5th quintile and giving it a data range of
greater than 69. This means that there is a very high
agricultural land use practice in this watershed.
The complicated spatial patterns in the southern United
States are evident in the map of land cover diversity
(Figure 2.5). The map shows the watershed ranking for
the number of different natural land cover types (anything
except urban and agriculture) per unit area. These
rankings are based on the original 160-class version of
land cover and not the 9-class version shown in Figure 2.1.
The greatest diversity of natural land cover is found in
the western United States, where large changes in
elevation produce different vegetation types at the top
and bottom of the same watershed. But there are also
diverse watersheds in coastal areas, including parts of
the Mississippi Gulf region.
Agriculture Land Cover
National Rank
Quintile Data Range
1 • < 3
2 • 3-11
3 a 11-31
4 • 31-69
5 • >69
-------
Forest Patterns
Forest patterns are particularly relevant in the southern
United States because forests are the dominant natural
vegetation cover. In contrast, natural land cover in the
western United States also includes grasslands and
shrublands, so forest patterns alone do not describe
departures from potential natural vegetation types. We
used three different indices of forest pattern in the water-
sheds: amount of forest, average forest patch size, and
forest connectivity. The resulting national rankings of
watersheds for these forest indices are shown in Figure
2.6.
The first map (Figure 2.6a) shows the watershed rankings
of forest area, expressed as the percentage of total water-
shed area. The chart indicates that about 20% (400) of the
nation's watersheds are almost completely forested, and
that about 30% have little forest cover. About 100 water-
sheds have no forests at all when measured at this scale.
Forest cover is the most common vegetation type in nearly
all of the watersheds east of the Ohio River. Many western
watersheds are only forested at higher elevations.
The two other maps are different ways of looking at
whether the forests that do occur in a watershed are
continuous or fragmented into smaller patches. Figure
2.6b shows watershed rankings of average forest patch
area or size, expressed as a percentage of total water-
shed area. Figure 2.6c shows watershed rankings of
forest connectivity, defined as the probability that a ran-
domly selected forested spot on the map is adjacent to
another forested spot.
Natural Land Cover Types
0.1 02 0.3 0.4 OS 0.6 0.7 0.8 0.9 1 More
Indicator \felue
National Rank
Quintile Data Range
1 • < 0.19
2 fi 0.19-0.28
3 £3 0.29-0.42
4 | 0.43-0.76
5 • > 0.77
Figure 2.5
Number of natural land-cover types per 100 square kilometers of
watershed area.
-------
|UmiMaM*M«Mmro6J
All three maps have a similar pattern. Forest cover is
usually continuous where most of the watershed is for-
ested. In other cases, such as some watersheds in the
southwest, forest cover is a minor component overall, and
yet Is still continuous where it does occur. Compared to
potential natural cover conditions, forest loss and fragmen-
tation of the remainder is significant in the northeast United
States, along the east coast, and in the Mississippi River
valley. The patterns in Louisiana are typical of those found
in other places in the southern part of the country.
Although the three maps have a similar pattern, the charts
illustrate different views obtained by using different indica-
tors. The distribution of watersheds is more or less
uniform for the indicator based on percentage of forested
area. The charts for the other two indicators suggest that
in most watersheds, the average forest patch is a small
percentage of total area, but that forest cover tends to be
connected in whatever amount actually exists.
Percentage of Watershed that is Forested
National Rank
Quintile Data Range
< 2.0
2.0 - 22.0 I
22.0 - 60.0
60.0 - 89.0 |
>89.0
Indtator Value
Ffgurv 2,6
T/WW forest pattern Indicators: (a) percentage of watershed that is forested, (b) average forest patch size as a
porcontago of total watershed area, and (c) index of forest connectivity.
-------
Average Forest Patch Size
©
National Rank
Quintile Data Range
1 • < 0.1
2 H 0.1 - 0.5
3 Q 0.5- 1.9
4 • 1.9 -11.6
5 • >11.6
102030405060708090100
Indicator Value
Index of Forest Connectivity
©
National Rank
Quintile Data Range
1 • < 0.31
2 H 0.31 -0.58
3 3 0.59 -0.78
4 • 0.79 -0.92
5 • > 0.92
102030405060708090100
Indicator Value
-------
Patterns Affecting Water Quality
Water quality and aquatic life are intimately related to land
cover near streams. The vegetation near streams is
referred to as riparian vegetation. It forms an important
buffer zone protecting water quality. Natural vegetation
absorbs agricultural nutrients, slows the rate of water
movement, and is a settling zone for soil particles sus-
pended in runoff. Riparian conditions are often evaluated
within a few meters of a stream, but the larger landscape
context is also important.
One way to measure environmental conditions is to look at
whether streams flow through predominantly forested or
developed landscapes within a watershed. If there are no
large urban areas or agricultural zones anywhere near
streams, then it is less likely that water quality is being
affected by these land uses. If forest cover dominates in
the vicinity of streams, then there is greater opportunity
for forests to buffer the conditions within streams.
Watershed rankings of the proportions of stream length
dominated by different land cover types are shown in
Figure 2.7. These proportions are based on forest cover
(Figure 2.7a) or urban and agriculture cover (Figure 2.7b)
within about one-half kilometer of streams in each water-
shed. Along the Mississippi River, the rankings for
forested riparian zones show a sharp contrast between
the area near the river and the forested areas to the east
and west. The Tensas River Basin is one of the areas
near the Mississippi River.
"*: liLJ'ilhuf::l • ilXti A:S , : iS'ii! !.n., >i i, ,";;. 'Hit if f ii ft' !88.7
fndfctibfVWue
Ftgura 2.7
Proportion of total streamlength that is: (a) forested, or
(b) agriculture and urban.
-------
The rankings based on the proportion of agriculture or
urban land cover in riparian zones show similar patterns in
the southern United States. The differences are more
complicated in the western United States because
nonforested vegetation may also be shrublands or grass-
lands.
Nationwide, the charts indicate that about 40% of the
watersheds have riparian landscapes that are at least 70%
forested, but an equal number of watersheds have very
little forest cover in riparian landscapes. About 10% (200)
of the watersheds have riparian landscapes that are nearly
all agriculture or urban, and about the same number are
almost completely undeveloped.
Water quality is also related to larger patterns of land use
over entire watersheds. For example, roads near streams
affect water quality not only as direct pollution sources, but
also because they represent paths for rapid runoff. The
frequencies of roads crossing rivers were expressed here
as the number of road crossings per unit river length in
each watershed. This expression helps to adjust for
differences in the total length of rivers between water-
sheds.
The map of watershed rankings for this indicator (Figure
2.8) is complicated, and it does not closely resemble the
national patterns found earlier when looking at land cover.
The Tensas River Basin, like most of the Southeast and
Midwest United States, has extensive road networks. Low
lying areas are built-up to make roads thus changing the
way water flows in the watershed.
Total Stream Length - Agriculture and Urban
National Rank
Quintile Data Range
• < 3.4
102030405060708090100
Indicator Value
-------
wXcnioftfaLJU&anaTetisas River Basin: Chapter2*.
National Context Summary
Several important features of the Tensas River Basin can
be identified by placing the region into a national context.
The Tensas River Basin certainly has complicated
spatial patterns of land cover, and the finer-scale analy-
ses shown later in this Atlas seem warranted. In fact, the
Tensas River Basin should be an excellent case study
area because of the variety of conditions that it contains.
Some patterns in the Tensas River Basin are typical of
other areas along the southern agricultural belt. This
means that what is learned in the Tensas may be appli-
cable in other regions in the lower Mississippi Valley.
Because the Tensas is also a transition zone between
regions of more or less impact to the east and west,
further studies here may also be relevant to environmen-
tal monitoring in these other areas.
The Tensas River is not the most highly impacted water-
shed in the south, but it is different from the less im-
pacted areas that are found at slightly higher elevations in
the east and west. The patterns in the watershed
creates an opportunity to consider a full range of environ-
mental strategies from restoration of the more developed
areas to protection aimed at forests and wetlands. This
brief look at the Tensas River Basin in a national context
has confirmed that many aspects of the broad-scale
view of environmental quality can be usefully explored
here.
Road - Stream Crossings
National Rank
Quintile Data Range
1 • <1.4
2 • 1.4 - 2.2
3 D 2.2 - 3.0
4 H 3.0 - 4.2
5 • >4.2
Flguro 2.8
Number of road-stream crossings per 100 kilometers of streams.
-------
f~""$3^if"*tZ'%"^°*~ 7^""*
^t'S5-* , * ~ *
Chapter 3: The Tensas River Basin
Landscape Assessment
This chapter illustrates the landscape indicators used to
assess watershed conditions in the Tensas River Basin.
Each indicator is discussed separately; maps illustrate
the relative rankings of subwatersheds and charts show
the distributions of indicator values.
We begin with a brief look at the biophysical setting of
the Tensas River Basin including maps of the data used to
calculate indicator values. Included are regional pictures
of topography, rivers, watershed boundaries, and land
cover. An important criterion when choosing digital data
was consistency across the watershed. Consistency is
essential because the goal is a sub-watershed
comparative assessment.
The landscape indicators are grouped according to three
themes: human use, forests, and water. The following
discussions introduce each theme and a number of
analyses pertinent to the Tensas River Basin are applied
to each theme. The interpretation of indicators are not
exhaustive. In addition, these groups are subjective since
any given indicator could be relevant to more than one
theme and each affect water quality, the subject of Chapter
4. For example, a discussion of an indicator of forest
change along streams or riparian corridors appears in both
the analysis of forest change and the analysis of water.
The concluding section in this chapter describes a
current program that focuses on restoring wetlands.
Based on analyses presented in this chapter, a GIS
illustration of areas of potential restoration gives land
managers an example of a powerful decision tool.
;"-7g
Figure 3.1
Shaded relief map of the Tensas River Basin. Source: U.S. Geological
Survey, Digital Elevation Model, 3 arc—second.
Biophysical Setting
The Tensas River Basin encompasses approximately
375,834 hectares (930,000 acres) of Mississippi River
alluvial flood plain in Northeast Louisiana. The Tensas
River is now hydrologically connected to the Atchafalaya
River which is a major distributary of the Mississippi River.
Historically, most of the Basin was covered with bottom-
land hardwood forested wetlands. The bottomland
hardwoods of the Tensas River Basin have been de-
scribed as some of the richest ecosystems in the country
in terms of diversity and productivity of plant and animal
species. At the same time, these lands are recognized as
some of the nation's most productive farmland for grain
and fiber. The result is a conflict of land use between
traditional row crop agricultural interests and concern for a
healthy, diverse, and stable ecosystem.
The alluvial flood plain of the region forms the backdrop
for all of the physical and biological processes that shape
the watershed. Generally when you look at a map of a
watershed, whether it is a physical map, a vegetation
map, or even a socio-political map, the most striking
features of the landscape are created by topographic
features. In the Tensas River Basin (Figure 3.1) a lack of
topographic variety encourages a variety of different
landforms including point-bars, abandoned river courses,
abandoned channels, natural levees, and backswamps.
The Tensas River Basin is unique in that natural levees
along the riparian vegetation lie on the highest ground in
the Basin. This causes drainage water to run parallel to
streams for many miles before actually entering the
stream and river water channels. Wetlands and
-------
backswamps then become the vegetation filtering areas
for pollutants and nutrients. These landforms create a
diverse physical and ecological region. Bayous, channels,
streams, and rivers direct the flow of water across the
landscape and are dominant features in the Tensas River
Basin (Figure 3.2). In the previous chapter we looked at
the Tensas River Basin in the context of a watershed
within the lower 48 contiguous states. In this chapter, we
further divide the watershed into topographically relevant
subwatersheds or zones and examine landscape indica-
tors based on these subwatersheds. These
subwatersheds, known as 11-digit hydrological accounting
zones, were defined by combining the USGS 8-digit HUG
boundary with the NRCS 11-digit boundaries and are
shown in Rgure 3.3.
Note that Zones 2, 7, and 9 were not defined as 11-digit
hydrologic accounting units by NRCS but do fall within the
boundary of the 8-digit USGS HUC boundary.
Subwatersheds 2 and 7 may be parts of other
subwatersheds or contain most likely, bayous in which
water could flow in many directions.
Therefore, these areas are included in the combined 11-
digit boundary but may not actually be totally hydrologi-
cally linked to the Basin. Subwatershed 9 appears to be
linked to the Basin through a major tributary. The indica-
tor values calculated for zones 2 and 7 are probably not
as reliable as the values for those zones in which an
entire subwatershed was in the assessment area.
USGSS-Dlglt
Accounting Units
NRCS11-Dlglt
Accounting Units
Figure 3.2
1991/92 NALC Image
60-meter False Color Composite
Combined 8 and 11 Digit
Accounting Unit Zones
Figure 3.3
Combination of USGS 8-digit HUC boundaries with
NRCS 11-digit boundaries. Zones 2,7, and 9 are shown in red.
-------
Land Cover
Land cover is the product of past land uses on the
backdrop of the biophysical setting. A map of land
cover is essentially a picture of the dominant vegeta-
tive, water, and urban cover in an area. Figure 3.4
illustrates the land cover of the Tensas River Basin.
This land cover map was jointly prepared by the
USFWS, the USGS Biological Research Division
(formerly known as the National Biological Service)
and the University of Arkansas at Fayetteville. They
used Landsat Thematic Mapper 30-meter satellite
imagery to derive the 17 classes displayed in the map
Although individual pixels are far too small to be
rendered accurately here, the visual impression of
broad-scale watershed patterns is readily apparent.
This Land Cover map can be used for many types of
landscape analyses and assessments. For our
assessment of the land cover we started with only
three classes: forest, human use, and water. Later on
in this chapter we explain in much more detail
how these were derived.
The two most dominant land cover types in the
Tensas River Basin are forest and human use, which
presently cover about 22% and 77% of the area,
respectively. Some of the subwatersheds are prima-
rily forested and approach 60% forest cover. Some
subwatersheds have less than 5% forest cover.
Where forests have been removed, agriculture and
urban land covers become more dominant. The
median amount of urban land cover per watershed is
about 2%. Agriculture is an extremely important land
use in the region; four subwatersheds have more than
60% of agriculture land cover.
Landcover
LJ Cypress/Willow
|O Wet Hardwoods
Hardwoods
Edge Forest
Other Forest
Scrub/Shrub
Conservation Reserve
Grass
Lakes
Urban
Rice
m Soybean
Cotton
Milo
g]| Sugar Cane
]f Com
Bother Crops
Figure 3.4
Land Cover in the Tensas River Basin. Source: USFWS, 3RD, and the
University of Arkansas at Fayetteville. Landsat TM 30 -meter satellite imagery,
June 1992.
-------
Humans in the Landscape
Humans structure the landscape for their purposes, and
landscapes structure human activities. For example,
humans may decide the shapes and sizes of individual
agricultural fields, but watershed-scale patterns of topog-
raphy, soils, and geology determine whether or not there
can be fields at all. Because human-dominated land-
scapes are used for different purposes which impose
different patterns, land use history is always important for
understanding local landscapes. The interplay between
humans and landscapes has created a tapestry of-multi-
scale patterns in the Tensas River Basin, and combina-
tions of these two factors influence the sustainability of
ecological processes.
Population Density and Change
According to the U.S. Census Bureau, the population of
the Tensas River Basin in 1990 was about 29,300
people, which represents about 0.0001 of the total
population of the United States. With a population of
29,300 covering an area of 3,763 square kilometers, the
average population density of the Tensas Basin is about
7.8 people per square kilometer.
Between 1970 and 1990, the total population in the
Tensas Basin (East Carroll, Madison, and Tensas par-
ishes) decreased from 37,680 to 29,300. Thus, the
average population density decreased from about 10
people per square kilometer to 7.8 people per square
kilometer. Figure 3.5 shows the population of the
Tensas River Basin by parishes and the populations of
three cities in the Basin.
Human Use Index
The proportion of an area that is used for agriculture or
urban land use is a measure of human use known as the
U-index. We often assume that humans tend to simplify
their environment. At landscape scales, however, the map |
of human land use displays complicated patterns (Figure
3.4, Land Cover). The scale at the transition from simple
to complicated patterns might be a measure of the scale to
which humans have structured a landscape or, conversely,
the scale at which geophysical processes constrain
human activity. By looking at watershed patterns of the U- j
index, it is possible to identify those areas which have
experienced the greatest land cover conversion from the
natural cover of vegetation.
3.5
(1990) of Louisiana Parishes within the
ft/was Rlwr Basin,
-------
f "~" *y^""S£Mfe'insi:i|
29 I
;t--, ^jlv-Vrf-fJI'-.v---...^.-^-.--^^-.-.,..-^*
The watershed pattern of human use in 1991/92 is re-
flected in the subwatershed rankings over the region
(Figure 3.6). The highest U-index value for a
subwatershed is about 96.7%, which means that 96.7% of
that watershed has agricultural or urban land cover. The
lowest value is 38.9%, and the average value is 77.3%.
Compared to the national human use maps in Chapter 2,
this is a very high human use index.
Zone U - Index
82.3%
96.7%
87.6%
66.0%
38.9%
39.0%
69.6%
78.9%
77.3%
Roads
Roads and other transportation corridors are designed to
connect the human-dominated elements of a landscape.
The network of roads in the Tensas River Basin permits
access, commerce, and communication throughout the
region. Roads are also important for connectivity among
ecological communities. Sometimes roads restrict eco-
logical communities, as in the case of animals that are
unable to cross roads. Sometimes roads enhance
ecological communities, such as for plant species that
spread along disturbed roadsides. In some cases, areas
remote from roads may better accommodate wildlife, e.g.,
Louisiana black bears. The influence of a given road
extends for some distance, depending on such things as
road size and surface type, traffic volume, and type of
use. There are few places in the Tensas River Basin that
are entirely free of their influence.
According to the road maps used for this atlas, there are
about 3,666 kilometers of roads in the Tensas River
Basin. This data set (U.S. Census TIGER) includes all
types of roads-interstates, U.S. and State highways,
county roads, and city streets. This works out to an
average of 125 meters of road per person in the region.
It is no wonder that roads are one of the most important
human features in the Tensas River Basin landscape
today.
Figure 3.7 illustrates the road network within the Tensas
River Basin. It is immediately apparent, with the excep-
tion of road concentration in the urban areas of Lake
Providence, Tallulah, and Saint Joseph, that roads are
uniformly distributed throughout the Basin. Figure 3.7
also breaks out kilometers of roads by zone.
Figure 3.6.
Human Use (U) Index, Tensas River Basin.
-------
SBI!^^
Zone
2
3
4
S
6
7
8
9
ToW
Kilometers
83.5
485.0
349.9
49t.4
46,7
63,6
778.4
767.1
3,666.0
Ha
5,601
45,387
92,471
61.742
11,126
7,345
79,713
72,212
375,807
Ratio of Km/Ha
1.49
1.07
1.03
0.80
0.42
0.87
0.98
1.06
0.98 (Avg)
Roads Along Streams
Roads affect stream water in many ways and roads in
close proximity to streams have the most potential for
adverse effects on stream water quality. Figure 3.8
shows road intersections with streams by sub-watershed
in the Tensas River Basin. Since roads have an impervi-
ous surface, and ditches are built to channel water off
roads and into streams, the rate of water runoff is higher
where there are more roads. Although large spills of
polluting materials are rare and often quickly contained,
small spills of petroleum products, antifreeze, and other
vehicle-related chemicals happen every day on every
mile of road in the region. These small spills eventually
go somewhere, usually into streams. Road construction
near streams is a temporary stress on water quality, but
after construction, the roads remain, and routine mainte-
nance can contribute to poorer water quality. For these
and other reasons it is important to consider how the
proximity of roads to streams might influence regional
water quality.
Forests in the Landscapes
Forests are important elements of both natural and
human-dominated landscapes. Forests provide many
benefits including wood fiber, outdoor recreation, wildlife
habitat, and regulation of some watershed hydrologic
functions. Historic patterns of land use and development
have created the present distribution of forests from what
once was essentially all forest. There have also been
changes in the plant and animal species which live in
forested environments. In this section, the pattern of the
existing forest cover is described as it affects various
environmental values, particularly wildlife habitat.
Percentage of Forest Cover
At one time, nearly all parts of the Tensas River Basin
were forested. Today, the amount of remaining forests
helps to indicate the probable condition of streams within
each watershed. The proportion of watershed covered
by forest is indicative, but not conclusive, of stream
conditions because the specific types of non-forest land
cover (such as urban or crop) are also important.
Figuro 3.7
Roads In the Tensas River Basin. Source: US Census TIGER.
-------
Figure 3.8
Roads Crossing Streams.
Streams
Roads
Ha
5,601
45,387
92,471
61,742
11,126
7,346
79,713
72,212
Xings/Ha
0.32
0.35
0.31
0.19
0.07
0.27
0.28
0.33
375,807 0.28
The forest cover map of the Tensas River Basin (Figure
3.9) is based on the North America Landscape Charac-
terization (NALC) satellite imagery data. NALC satellite
data, available since the early 1970s, is a Federal effort to
create similar data sets for the entire country. The resolu-
tion of the NALC data is 60 meters; thus, each pixel
(picture element) represents an area about the size of a
football field. Compare the land cover map shown in
Figure 3.4 (30-meter pixels) to the NALC data (Figure
3.9).
Although individual pixels are far too small to be rendered
accurately here, the visual impression of broad-scale
regional patterns is readily apparent. Forest vegetation
shows up on the NALC image as red in color, agriculture
shows up as light red, grey, light blue and white. When the
NALC Image is enlarged the agriculture almost always
shows a pattern of rows or right angles typical of farm
fields.
-------
1972 NALC Image
False Color
Composite
1972 NALC Image
with Land Cover,
Classification
Figure 3.9a.
Difference between
the 1972 NALC
Image and the
1991/1992 NALC
Image results in
a Forest Loss
and Gain Image
1391/1992
NALC Image
Falsa Color
Composite
1991/1992 NALC
Image with Land
Cover Classification
Figure 3.9b.
Figure 3.9e.
LEGEND
I I Tensas Study Area
Land Cover
••Forest
^H Forest Loss
|n| Forest Gain
Human Use
Figure 3.9d.
Flgura 3.9
Forest Cover In tha Tensas River Basin.
-------
The NALC images (Figure 3.9a and 3.9b) were classi-
fied to show landuse (Figures 3.9c and 3.9d). The
classifications were forest, human use (urban and
agriculture), and water. The 1972 image was compared
to the 1991/92 image and changes in forest areas and
human use areas were calculated. The forest cover
changes are shown in Figure 3.9e. As the figure shows,
there was significant forest loss during that time period.
Subwatersheds, 4, 5, 8, and 9 have had substantial
forested loss. The northern subwatershed, 2 and 3, have
had little forest loss because they had been converted to
agriculture long before 1970. Where forests have been
removed over the last 20 years, agriculture land cover has
become more dominant, as can be seen by comparing
Figures 3.9c with 3.9d.
Forest Fragmentation
As in other regions of the United States, forest fragmen-
tation is an important issue in the Tensas River Basin.
Although the word has several meanings, the general
concept is that what was once a large continuous forest
has been broken up into smaller pieces. In the eastern
United States, forest loss is generally associated with
agriculture and urban uses which remove some forest
and leave the remaining stands in smaller, isolated
blocks. The pattern of forest loss can be important as the
amount lost. For example, a checkerboard pattern
exhibits more fragmentation than a clumped pattern of
the same amount of forest.
Forest fragmentation was assessed by using the forest
and non-forest data classification shown in Figures 3.9c
and 3.9d. The fragmentation statistic measures the
probability that a randomly selected forested spot is
adjacent to another forested spot. High values indicate
low fragmentation. This statistic was calculated for 1972
as 88% and 1991/92 as 84%. These are relatively high
values which indicate that much of the forest area in the
Tensas River Basin is interconnected. Forest fragmenta-
tion will be discussed in more detail later in this chapter.
Percent of the Watershed in the Largest Forest
Patch
About 30 years ago, A.W. Kuchler made maps of poten-
tial natural vegetation, that is, the vegetation that would
occur if vegetation was only influenced by natural pro-
cesses such as weather and fire. In the Tensas River
Basin, Kuchler's maps show that the potential natural
vegetation is almost exclusively forest.
Previous discussion introduced the concepts of forest
loss (Figure 3.9) and forest fragmentation. Consider a
watershed with some given amount of forest cover. If the
forest is in one continuous stand, then the largest forest
stand equals the total forest cover. If the largest-stand is
smaller than this expected value, then fragmentation has
occurred and the remaining forest cover is discontinuous.
The largest forest patch in the Tensas River Basin in 1972
was 54,939.2 hectares compared to the largest forest
patch in 1991/92 of 37,997.3 hectares. This is a loss of
16,941.9 hectares from the largest patch. The average
forest patch in 1972 was 38.9 hectares and in 1991/92
was 23.1 This is a loss in average forest patch size of
15.8 hectares throughout the Tensas River Basin.
These forest patch size statistics may be used to deter-
mine where local reforestation would best improve forest
connectivity regionally. A significant increase in the size
of the largest forest patch could be made by joining the
two largest patches. More information on Wetland Forest
restoration is given later in this chapter.
-------
Detailed Forest Analysis of the Tensas River
Basin, 1970s to 1990s.
The landscape analysis began with taking the 1972
classified data and running computer programs which
calculate the various landscape statistics. The landscape
statistics for the 1972 and 1991/92 data are given in
Tables 3.1 and 3.2 (all tables are found at the end of
Chapter 3). Figures 3.10 and 3.11 show the classified
images of the Tensas River Basin for 1972 and 1991/92
respectively. The Tensas River Basin was classified into
three categories: forest, human use (urban and agricul-
ture), and water. The water statistics are not presented
In the tables.
In 1972 the data show the amount of forest area in the
Tensas River Basin as 126,298 hectares and the human
use as 244,522 hectares. These represent 33.6% and
65.1% of the total Tensas River Basin area. In 1991/92 the
amount of forest area is 80'J807 hectares and human use
is 290,336 hectares. These represent 21.5% and 77.3% of
the total Tensas River Basin. The net forest loss for this
period is 45,491 hectares (112,463 acres) or 12.3% of the
land area. These data indicate a substantial decrease in
forest and an increase in human use over the years. The
totals and percents are given for each subwatershed
(Tables 3A and 3.2). The landscape analysis for percent
forest change which includes the entire Tensas River
Basin is shown in Table 3.3. The classified data which
show the forest vegetation change is given in Figure 3.12.
These data were also analyzed by subwatershed and
presented in Table 3.3.
Forest patch statistics are also given in Tables 3.1 and
3,2. A high same-type forest edge percentage indicates
low forest fragmentation. In 1991/92, subwatershed
number 6 has a same-type edge percentage of 94.9.
This is a very high value showing that the forest in
subwatershed number 6 is highly connected. The Tensas
River National Wildlife Refuge is located in subwatershed
number 6 which accounts for the high value as connected
forest patches are needed for wildlife management. The
largest forest patch size and the average patch size are
also given in these tables.
Land Cover
Forest
Human Use
Water
Figure 3.10
1970s Classified Image, Land Cover.
-------
Land Cover
BH Forest
|O Human Use
•I Water
Land Cover
Forest
Forest Loss
Forest Gain
Human Use
Water
Figure 3.11
1990s Classified Image, Land Cover.
Figure 3.12
Classified Image, Vegetation Change 1970s to 1990s.
-------
Vegetation Change
In the previous sections, we discussed landscape
change based on NALC images that had been classi-
fied. Another method is to calculate indices directly
from the satellite imagery. It is interesting to compare
the results of the preceding landscape change analy-
sis with those presented in the following discussion.
A common perception is that patterns of forest and
agriculture and urban areas remain constant over time.
In this section we present patterns of vegetation
change measured by comparing satellite images from
1972 and a composite of 1991 and 1992. The change
fs determined by using a vegetation index called Nor-
malized Difference Vegetation Index (NDVI) which was
calculated for each pixel on each of the two dates.
When the NDVI values are essentially the same at both
dates, then there has been no change. When the
value is greater in 1972 than 1991/92, we interpret this
as vegetation loss. When the value in 1972 is less than
1991^32, we interpret this as vegetation gain. Total
vegetation change is taken to be the sum of loss and
gain on an area basis.
The NDVI can be derived from satellite images because
the near infrared band produces a large reflectance
compared to the visible red band when looking at vegeta-
tion. The formula for NDVI is:
NDVI = Infrared Band - Visible Red Band
Infrared Band + Visible Red Band
The NDVI also has the advantage of compensating for
changing illumination conditions like surface slope,
aspect, and other factors. Indexes derived by NDVI
range from -1.0 to 1.0, where negative index values
represent clouds, water, and snow. Index values near
zero represent barren soil and rock, and positive index
values are indicators of the variation in vegetation.
Comparison of temporal changes in reflectance mea-
sures from satellites, such as NDVI, can be useful for
gaining insight into land cover changes when land cover
maps from two different dates are not available. Inter-
preting the measurements relative to land cover change
Is not straightforward though because some changes in
reflectance are not changes in land cover. Crop rotation
is a good example. Change in NDVI measurements
may be the result of seeing a field in production on one
date and fallow on the other. Interpretation of these
measurements for actual land cover change requires a
lot of additional work beyond calculating their difference
over time.
Despite the complications, the amount and spatial pat-
tern of NDVI change is important. For example, many of
the decreases in NDVI turn out to be associated with
road improvements, new residential developments,
urbanization projects, and construction of reservoirs.
Gains in NDVI may be the result of crop rotation or matur-l
ing vegetation in residential developments. Gains in NDVII
appear to be associated with both natural and anthropo-
genic processes, whereas non-crop rotation NDVI losses
appear to be more consistently associated with anthropo-
genic activities.
These examples show that, after calibration, NDVI
changes over time can help answer several ecologically
important questions such as: (1) how much change has
occurred? (2) is vegetation change evenly distributed
over all the watersheds in the region, and (3) is vegeta-
tion change concentrated in the headwater regions of
streams? Figure 3.13 shows the vegetation change from
1972 through 1991/92.
Tensas River Basin Agriculture Field.
-------
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4^
Vegetation Change by Subwatershed
Figure 3.14 shows the percentage of total NDVI change
for all subwatersheds in the Tensas River Basin. All of
the changes observed represent losses in vegetation.
Vegetation loss shows a general pattern with the highest
rate of change in subwatershed 8. Vegetation changes in
subwatersheds 2, 3, and 4 are most likely due to farming
practices of rotating crops. Lower vegetation changes
can be noted in subwatersheds 6 and 7 due to the
relative stability of the forests in those areas. The high
loss in vegetation in subwatershed 8 is most likely due to
forest loss in that area since 1972. Table 3.4 contains
the numerical data of gains and loss by pixels and the
percentage for each subwatershed. Similar patterns of
vegetation changes were observed in Figure 3.9 which
showed forest losses and gains based on classified
NALC images.
Tensas River Basin, Bottomland Hardwoods.
Figure 3.13
NDVI Change between 1972 and 1991/92 in the Tensas River Basin.
Red = Loss and Green = Gain.
-------
Figure 3.14
Net percentage of change /n the NDVI for the Tensas River Basin from 1972
to 1991/92 by subwatershed. All changes represent net losses.
Forest and Crop Land Along Streams
The strip of vegetation along streams is known as the
riparian vegetation zone. It is commonly described by the
types of vegetation it contains. In an ideal situation, many
pollutants and fertilizers will be intercepted or absorbed by j
the riparian vegetation, and this process helps to keep the
streams clean. Bank erosion is also mitigated by intact
riparian vegetation. The Tensas River Basin is unique in
the natural levees along with the riparian vegetation lie on
the highest ground in the Basin. This causes drainage
water to run parallel to streams for many miles before
actually entering the streams and river water channels.
Wetlands and backswamps then become the vegetation
filtering areas for pollutants and nutrients.
Forested riparian zones are a natural part of the healthiest |
stream ecosystems in the southern United States. They
provide an effective barrier to runoff of water, pollutants,
and excess fertilizer and support a variety of valuable plantl
and wildlife species. Conversely, when riparian forests
are replace by agriculture, the riparian zone not only loses
its natural buffering capacity but now becomes a potential
source of pollution and excess fertilizer. Agricultural
practices usually employ fertilizers, pesticides, and other
chemicals that are essential to crop growth and yield.
These chemicals can more readily be moved into
streams which flow through agricultural fields, in compari-
son to streams which flow through forests. The maps on
these pages illustrate differences among watersheds in
the length of stream that has either forest or crop cover in
the riparian zone.
Figure 3.15 shows the relative amount of forests and
human use land cover within a 360-meter buffer riparian
zone along the Tensas River and its major tributaries.
Figure 3.16 shows the amount of forests and human use
land cover within a 120-meter buffer zone on either side of
all the stream reaches of the Tensas River Basin.
Subwatersheds 2 and 3 have the least percentage of
forest in riparian zones. Subwatersheds to the south have
the greatest amount of forested riparian cover. All of the
sub-watersheds have stream length with some cropland
cover. The watersheds with the highest potential for
negative impacts are in Subwatersheds 2, 3, and 4.
Whereas the distribution of riparian forests is an indica-
tor of natural buffering capacity, the distribution of crop
land cover in riparian zones is an indicator of potential
problems. Figure 3.17 zooms in on stream length
between Subwatersheds § and 8 and shows cropland
cover (human use) and forested areas in the riparian
zone. All of the areas shown in red were historically
forested and are now cropland cover.
-------
Figure 3.17{
Next Page
Forest 91/92
Forest Loss
Forest Gain
Human Use
Water
Forest 91/92
Forest Loss
Forest Gain
Human Use
Water
Figure 3.15
Riparian Zone of Tensas River and its Major Tributaries (360-meter buffer).
Figure 3.16
Riparian Zone of all Stream Reaches (120-meter buffer).
-------
A^?ss~^-l of !l;e Ljii&ans Tsnsas River Baslri Chapter 3 •
y
Forest
Forest Loss
Forest Gain
Human Use
Water
Water and the Landscape
I . i •,
Everyone knows the importance of water. But many
people do not realize how much its quality depends on
the surrounding landscape. Water quality, like landscape
condition, is the cumulative impact of environmental
stress and land management practices at broad scales.
Changes in the distribution and pattern of ecological
resources and human activities can alter fundamental
water processes including flow and balance, nutrient and
sediment loading, and chemistry. These changes can, in
turn, influence the water quality and quantity that are
valued by society. Figures 3.16 and 3.18 illustrate the
stream network within the Tensas River Basin.
This section presents landscape indicators that are
related to water quality in the streams of the Tensas
River Basin. "Riparian" indicators describe landscape
conditions near streams and "watershed" indicators
describe conditions over entire watersheds. The riparian
indicators include measures of human activities (agricul-
ture and roads) near streams and the amount of wetland
area. The size and amount of riparian buffers along
streambanks is an important determinant of soil loss and
sediment movement, which in turn affect water quality.
The group of watershed indicators presented here
primarily measure the potential for soil and nutrient
losses from surrounding landscapes which would ulti-
mately be deposited in streams. Put simply, watersheds
covered by natural forests are more likely to be in good
condition than watershed? with high percentages of
intensive human land uses. Because intact riparian
areas buffer streams from the potentially adverse effects
of watershed-scale events like erosion, both types of
indicators need to be evaluated when considering overall
landscape influences on stream condition and water
quality.
Flgura 3,17
Enlargement of Riparian Zone with 1992 NALC Image.
-------
Watershed Indicators
While streamside conditions are important, it is also
important to have indicators of potential impacts on water
quality from sources throughout the watershed. It was
mentioned earlier that the watershed indicators pre-
sented here are primarily concerned with soil erosion and
runoff processes. These indicators are relatively easy to
determine from existing databases. In any case, erosion
processes are extremely important. The results of in-
creased erosion may include reduced agricultural produc-
tivity, increased water treatment costs, introduction of
pesticides and fertilizers in the water supply, loss of
habitat for fish and other species, and reduced recreation
potential.
In years past the freshwater marshes, stream bank
areas, and bottomland swamps of the Tensas River
Basin were under strong development pressures. Large
portions of forest near streams and in backwater swamp
areas were converted to agriculture. This loss of for-
ested areas interfered with the soil and water interactions
in forested wetlands that removes pollution (excess
nutrients) before it enters streams, lakes, and estuaries.
Wetland forests also dissipate peak flows during floods
and release the waters slowly, reducing damage to down-
stream farms and cities. Preserving or restoring wetland
forests has other economic benefits including wetland-
based recreation such as hunting and harvesting wetland
plants. Residents of the Tensas River Basin realize that
the vegetation along a stream and in backswamp areas
can influence the condition of both the stream bank and
the water in the stream. They began restoration efforts in
the early 1990s.
Figure 3.18
Stream network in the Tensas River Basin. Source: EPA RF3.
-------
Riparian Analysis
The conditions of the riparian ecosystem over a whole
watershed can be studied in order to learn where, for
example, a restoration project would most improve water
quality. Similarly, a characterization of riparian conditions
over the entire Tensas River Basin can help to identify
which areas of the Basin are most likely to see improved
water quality as a result of riparian vegetation improve-
ments.
The forest change data for the riparian areas of the Tensas
River Basin are given in Table 3.6. This analysis was done
by taking the forest change data and applying it to all the
streams in the watershed in areas 120 meters on either
side of the stream. This is shown in Figure 3.11. Each
subwatershed was also analyzed so a comparison can be
made between the different subwatersheds.
1972 NALC (mage
with Forest Change
NALC Image with
360 motor Buffer
Forest Loss and Gain
within 360 meters of
Tensas River and
Major Tributaries
Land Cover
B Forest
Forest Loss
Forest Gain
mi Human Use
•H Water
Ftguro 3.19
Changs within 360 meters of Tensas River and Major Tributaries.
-------
Backswamp Area Analysis
This comparison can be seen in Table 3.6. Riparian areas
have undergone changes in the Basin. In most cases, the
forest change tends to be higher near streams. The
highest forest change in the riparian areas was in
subwatershed 8 where there was a 23.7 percent loss in
forest vegetation. This data shows us where land use
practices can be changed to help improve water quality.
Improvements could be made in subwatershed 8 if the
land owners are willing to convert the riparian strip of land
back to forest vegetation.
Vegetation Change along the Tensas River Reach
The vegetation along a stream affects the condition of
the stream and the water in the stream. This analysis
includes the area 360 meters on either side of the main
channel of the Tensas River and the same distance on
either side of the major tributaries of the Tensas River.
The results are shown in Table 3.5 and illustrated in
Figure 3.19.
Compared to the overall Tensas River Basin which had a
21.3% overall loss in forest vegetation the data show that
loss in the immediate area of the river and its tributaries
was only 7.5%. Although the loss of forest vegetation
was 7.5%, it shows that more vegetation was left within
360-meters of the main portion of the Tensas River and
should help prevent stream bank erosion and excess
nutrient loading to the river.
The backswamp areas of the Tensas River Basin play a
very important role in the ecology of this water system.
The land is very flat which means that water can move into
stream channels and it can also collect in low-lying areas.
These areas, which can hold water for months at a time
after big rain events, make up lakes, swamps, and wetland
forests. Figure 3.20 shows the location of Tensas River
Basin backswamp areas. Information about changes to
and locations of the backswamp areas will be an indicator
of water quality in this watershed.
The backswamp areas in the Tensas River Basin are
very important in terms of using the excess nutrients
found in the water and holding water during heavy rain
events. The combination of these flood areas with the
forest change landscape indicators is shown in Table 3.7
and Figure 3.21. Forest change in backswamp areas is
somewhat different that in other areas. A higher per-
centage of backswamp area was lost in subwatershed 4
(around the town of Tallulah) than in the entire Tensas
watershed. A complete comparison between the Tensas
subwatersheds is given in Table 3.7.
Backswamps in the Tensas River Basin.
-------
I Backswamp Areas
Land cover
mi Forest
•• Forest Loss
H=| Human Use
Forest Gain
••Water
FJgun 3.20,
Backswamps In tho Tfensas Rrver Basin.
Figure 3.21
Forest Change in Backswamp Areas.
Source? The Nature Conservancy and the
Biological Resources Division of the USGS
-------
Soil Erodibility Analysis
Soil erosion is important because it reduces productivity
of agricultural lands and because eroded soil can be
transported to a stream where it becomes sediment.
Topsoil is expensive to replace and natural soil-forming
processes would require thousands of years to replenish
soil already lost from the Nation's farmland. One of the
tools developed by agricultural scientists to estimate soil
loss from farm lands is the Universal Soil Loss Equation,
or USLE. The USLE is intended to demonstrate how
agricultural practices contribute to or reduce soil erosion.
The USLE is not generally applied to nonfarm land cover
types.
Figure 3.22 shows the watershed classes for the different
USLE K-factor erodibility values assigned to the surface
soil horizons. The K-factor estimates the relative erodibil-
ity of a soil with respect to all possible textures (range 0.0
to 0.64). Surface soils in the Tensas River Basin exhibit
K-factors ranging from 0.18 to 0.48. As shown in the
figure, the most erodible soils seem to occur most com-
monly in old oxbows and meander channels and are
spread evenly throughout the Basin. The least erodible
soils occur in backswamp areas adjacent to active
stream channels.
Q0.32
0.33
0.35
0.38
0.39
0.4
0.41
El 0.45
^0.48-
Figure 3.22
Relative Soil Erodibility Map for Tensas River Basin.
Source: NRCS STATSGO.
-------
Wetland Restoration Analysis
Restoration of wetlands and associated processes is a
primary objective of many of the stakeholders in the
Tensas River Basin. As a result, the Tensas River Basin
has been the focus of many environmental studies which
provide many types of data to continue our analysis. Many
GIS coverages are readily available from groups involved in
previous and ongoing studies. These resources provided
the opportunity to use this data along with the forest
change data to evaluate potential wetland restoration. One
of the GIS databases available covers all the areas which
are a part of the Louisiana Private Lands Restoration -
Wetland Reserve Program. These are areas where land
owners have changed land use from agriculture back to
forests. Rgure 3.23a shows restoration efforts that have
been taking place over the past 5 years around the Tensas |
River Basin. This image shows that the areas previously
selected for forest restoration were suitable in terms of
restoring forests along riparian areas and connecting
existing forests. Figure 3.23b is a view of the forest
change, wetland restoration sites and streams to better
show how the forest restoration sites are suitable in terms
of restoring forest along riparian areas and connecting
existing forests.
Displaying GIS databases and remote sensing data
together can visually give land managers more information
about soils, flood potential, and other types of features to
help make the best choices for restoration.
/\/ T*nsai River Study Areas
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Wnttand Rasatv® Program (WRP).
Romota Sensing Image
-------
Using the landscape analysis indicator of percent forest,
Table 3.8, we recalculate the landscape statistics to
include the Wetland Restoration data. The results of this
analysis are shown in Table 3.8. Table 3.8 provides a
statistical view of the Tensas Basin in 20 years or when the
trees have grown enough to establish a forested area. It is
interesting to note that most of the restoration efforts have
gone into the subwatersheds 4 and 7. Using the data from
this analysis future decisions in selecting restoration sites
land managers may want to focus more attention to
subwatersheds 8 and 9.
Figure 3.236
Proposed Wetland Restoration
A
_ Restored Forest Sites
I I Watershed Boundaries
Proposed Sites
Forest
Forest Loss
Forest Gain
Water
4
8 Miles
-------
Through landscape analysis we can also locate sites for
potential forest wetland restoration. Figure 3.24 shows a
combination of a hydric soils map with a flood map and
the forest change map along a 360-meter buffer of the
main channel of the Tensas River Basin and its major
tributaries. Using these maps land managers can make
decisions on locating potential restoration sites by factor-
ing In fertile and non-fertile soil types, land which has the
potential to flood, and areas which were forest and could
easily be forested again in the future. Based on the
combinations of these indicators, the best candidates for
potential restoration sites are shown in green on the right
Image of Rgure 3.24. Figure 3.24 shows an enlarged
map for ease in identifying restoration locations. Figure
SotteMip
Forest Loss/Gain -
Within 360 mater Buffer
of the Tensas River and
Major Tributaries
Roofed AM
3.25 illustrates this technique applied over the entire Basin.
We have also determined the percent of forest change
including restoration efforts over the Tensas River Basin
and its subwatersheds. Figure 3.26 shows the percent of
forest change, the forest change for the whole basin, and
the net forest restoration effort to date. Zones 4 and 7
show the most impact from the restoration efforts and
Zones 6,8, and 9 show little change in restoration. Zone 8
shows the most forest loss of all the Zones with a 21.2
percent loss over the 20-year time period. The combina-
tion of GIS analysis and these kinds of landscape analysis
can give land managers powerful decision tools for improv-
ing environmental quality.
Figure 3.24
Potential Forest Wetland Restoration.
Areas of Potential Resoratton -
Combination of Forest Loss and Flooded
Areas Displayed on Hydric Soils.
Land cover
•I Forest
B Forest Loss
Forest Gain
Human Usa
••Water
BUI Potential Restoration
/v Tensas River
Soils - Percent Hydric
33-51%
152-82%
83-99%
-------
I I Restored Forest Sites
I I Proposed Sites
/\/ Roads
/\/ Streams
I I Watershed Boundaries
10 Miles
Figure 3.25 Potential Forest Wetland Restoration for the
Entire Tensas River Basin
-------
251
15
8
i i
1 L
51
Percent Forest Gain
Percent Forest Loss
Net Forest Change
Projected Gain from Restoration
Projected Net Forest Change with Restoration
Ofi
JLJLjL
w
w
o
10]
4i-J
15
25
1
8
Tensas River Basin Zones
Figure 3.26
9 Total
Area
-------
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-------
Chapter 4: Water Quality
Perceived problems with water quality have been an
issue in the Tensas River Basin. The approach taken
here to examining water quality was to first gather all the
stream water quality data available and then to analyze it
both temporally and spatially. Initially the hope was to
gather enough data to be able to associate water quality
with some of the landscape metrics discussed previously.
The major source of the data was STORET, the EPA
water quality data base. Not only is the EPA data stored
in this data base but so is data from the USGS and
various states including Louisiana. All of the existing
water quality data for the Tensas River Basin was re-
quested. It was then verified with Louisiana Department
of Environmental Quality (LDEQ) and USGS that all
existing water quality data for the basin were contained in
the storet data base.
The water quality data search yielded a data set that
included stream water quality data from 17 stations.
However many of these stations included only data from
a one-time sampling effort often dating back to the 1970s
or the station ceased to operate in the 1970s or early
1980s. The criterion for using a station's water quality data
required that it have data from the 1990s or it be located
close to a station that had data from the 1990s. This
criteria was selected as these would be the most relevant
data to current conditions in the Tensas River Basin. This
criteria limited the data available for analysis to three sites;
Tendal, Winnsboro, and Clayton. The locations of these
stations are shown in Figure 4.1. Both Louisiana state
and the USGS collect samples from Tendal and Clayton.
Unfortunately, with a sample number of only three water
quality monitoring stations, it is impossible to make valid
associations between the water quality data and any of the
landscape metrics that was previously presented. In
addition to the three stream monitoring stations, water
quality data from Lake Providence were also retrieved.
This lake in the Tensas Bayou serves as the headwaters
of the Tensas River.
This analysis focused on two variables: total phosphorus
and total nitrogen as nitrjte and nitrate. In the analysis of
the data, significant differences between the three stations
were examined as well as seasonal differences and trends
over many years.
Figure 4.2 shows the seasonal distribution of the
nitrogen and phosphorus data from 1990 through 1996
for all three LDEQ water quality monitoring stations. This
type of display is known as a box and whisker plot. The
top and bottom edges of the blue box represent the 25th
and 75th percentiles of the distribution of the data (i.e.,
50% of the data values fall within this range). The vertical
lines extend from the blue box down to the 10th and up
to the 90th percentile (i.e., 80% of the data values fall
within this range).
Tendal
7369500 (USGS)
58010066 (LADEQ)
Lake Providence
58010132 (LADEQ)
Winnsboro
58010331 (LADEQ)
LEGEND
•$• Water Quality Monitoring States
/V Intestates
/V US and State Highways
A/Tanas Rlvsr
El Study Area
Clayton
07370190 (USGS)
58010159 (LADEQ)
Figure 4.1
Location of Tensas River Basin Water Quality Monitoring Stations.
-------
The small horizontal line drawn within the blue box
indicates the median value. Any value outside of the
10th and 90th percentiles is displayed on the graph as a
light blue dot. This type of display was chosen rather
than a simple mean ± standard deviation plot because a
normality test indicated that many of the data distribu-
tions for a given station or season were not normally
distributed. In part due to the low sample numbers,
which are indicated above the box and whisker illustra-
tion, a mean value would be heavily influenced by outlier
values. One extreme outlier nitrogen value of 5.9 mg/L
was omitfed from Figure 4.2 for the summer season from
the Tendal station. This outlier, omitted for display pur-
poses only, was included in the calculations in the sum-
mary statistics given in the Appendix.
Figure 4.2 shows seasonal differences exist for both
nitrogen and phosphorus concentrations for all three
stations with the exception of phosphorus concentra-
tions from the Tendal station. In general, nutrient
concentrations decline from the spring through the fall
arid then start increasing again in the winter. It is
Interesting that the Tendal station does not seem to
fluctuate seasonally nearly as much as do the other two
stations. Perhaps, this phenomenon is due to the
proximity of agricultural fields to the water quality moni-
toring station. Statistical summaries of the water quality
data from the LDEQ stations can be found in the Appen-
dix.
To determine whether there were significant differences
between the three stations, a Wilcoxon rank-sum (also
known as Mann-Whitney U) test was performed. Again,
a nonparametric statistic was used because the data
are not normally distributed and the sample numbers
are low. There were no significant differences between
ail three stations for total nitrogen. This was true for all
seasons combined and for individual seasons. For total
phosphorus there were statistically significant differ-
ences between Tendal and Clayton and between
Tendal and Winnsboro when ail seasons were
combined. When this analysis was performed on
Individual seasons, there were statistically significant
differences between Tendal and Clayton for the summer
and the fall and there were significant differences be-
tween Teodal and WinnsbQro for the fall. All other
comparisons of station and season yielded nonsignifi-
cant differences. A summary of this analysis is included
In the Appendix.
Figures 4.3 through 4.5 show the historical total nitrogen
concentrations for all three locations on separate graphs.
Figures 4.6 through 4.8 show the historical total phos-
phorus concentrations. When there is a LDEQ station
collocated with a USGS station, the points are plotted
with different color symbols. It would appear that both
nitrogen and phosphorus concentrations have increased
slightly for the Clayton station when comparing data from
the 1970s to the 1990s. It should be noted however that
the data from the 1970s were exclusively collected by the
USGS while the data from the 1990s were exclusively
collected by LDEQ. It may not be appropriate to compare |
these data directly as there may have been differences in
methodology.
It is also interesting to compare the water quality from the
three stream monitoring stations to the water quality in
Lake Providence (Figures 4.9 and 4.10). Lake Provi-
dence serves as the headwaters of the Tensas River and
clearly the nitrogen and phosphorus levels are lower than
they are at Tendal, Winnsboro, or Clayton.
When evaluating the quality of the water in the Tensas
River, one should look at how the data compare with any
established criteria. To limit eutrophication potential to
downstream waters, the EPA Quality Criteria for Water
(1986) advises that total phosphorus levels should not
exceed 0.1 mg/ L. This is also the criteria used by the
EPA's Surf Your Watershed program. Clearly many of the
values from the Tensas River samples exceed that level.
We were unable to find a total nitrogen criteria for surface
water.
In summary the following can be said about nutrient
levels in the Tensas River: They are higher in the stream
water than they are in the headwaters, they are generally
seasonal in nature, phosphorus levels are at a level
where they could contribute to eutrophication, and there
are some significant differences in phosphorus levels
between Tendal and the other two monitoring stations.
To perform a more thorough investigation of the water
quality in the Tensas River Basin, a comprehensive water
quality study that would characterize the water quality of
all the subwatersheds within the basin should be de-
signed and conducted.
-------
=3
3.0 '
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2.0
1.8 •
1.6 -
1.4-
1.2 -
1.0 -
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0.6 -
0.4 -
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Spring Summer Fall Winter Spring Summer Fall Winter Spring Summer Fall Winter
Tendal
Winnsboro
Clayton
Rgure 4.2 Total nitrogen and phosphorus concentrations for three Louisiana state water quality monitoring stations in
the Tensas River Basin. Data displayed are from those samples collected 199O - 1996. The top and bottom edges
of the light blue box represent the 25th and 75th percentiles of the distribution of the data (i.e., 5O% of the data values
fall within this range). The horizontal line drawn within the blue box represents the median value. The vertical
lines extend to the 10th and 90th percentile. Any value outside of this range is displayed on the graph as a light
blue dot. The number of data points included in the analysis is printed above each box.
-------
3.0
2.5
2'0
i: 1.0
z
"5"
jo 0.5 1
0.0
«. * •
09/09/73 06/05/76 03/02/79 11/26/81 08/22/84 05/19/87 02/12/90 11/08/92 08/05/95 05/01/^8
Sample Collection Date
STATION • • • 07369500 • • • 58010066
Figure 4.3 Total nitrogen concentrations for two water quality monitoring stations in Tendal, La.
3.0 •
2.5'
2.0
I 1.0
0.5
0.0
02/12/90 11/08/92 08/05/95
Sample Collection Date
STATION • • » 58010331
Figure 4.4, Total nitrogen concentrations for Wmnsboro, La.
05/01/98
-------
3.0 -
2.5
2.0-
1.5-
i: 1.0
to
o 0.5 '
0.0
i—i—i—i—i—i—i—i—i—i—r
09/09/73 OS/05/76 03/02/79 11/26/31 08/22/84 05/19/87 02/12/90 11/08/92 08/05/95 05/01/98
Sample Collection Date
STATION • • • 07370190 • * • 58010159
Figure 4.5 Total nitrogen concentrations for two water quality monitoring stations in Clayton, LA
2.0-
1.8 -
1.6
1.4 '
1.2
1.0 •
0.8 -
0.4
0.2
0.0
*•-
* «
09/09/73 06/05/76 03/02/79 11/26/81 08/22/84- 05/19/87 02/12/90 11/08/92 08/05/95 05/01/98
Sample Collection Date
STATION « * » 07369500 * • • 58010066
Rgure 4.6 Total phosphorus concentrations for two water quality monitoring stations inTendal, LA
-------
isiiiw
2.0
1.8
1.6
I1'41
g 1.2
•i. 1.0
£ 0.8
I 0.6
0.4 -I
0.2
0.0
02/12/90 11/08/92 08/05/95
Sample Collection Date
STATION • • * 58010331
Figure 4.7 Total phosphorus concentrations for Winnsboro, LA
05/01/98
2.0
1.8
1.6
rf"1^
I 1.41
g 1.2
§1.01
£ 0.8
0.4
0.2
0.0
09/09/73 06/O5/76 03/02/79 11/26/81 08/22/84 05/19/87 02/12/90 11/08/92 08/05/95 05/01/98
Sample Collection Date
STATION • * • 07370190 * • • 58010159
Rgure 4.8 Toted phosphorus concentrations for two water quality monitoring stations in Clayton, LA
-------
3.0
2.5
2.01
1.0
1 1 1 1 1 * ' ' 1 '
11/26/81 08/22/84 05/19/87 02/12/90
Sample Collection Date
STATION • * * 58010132
Rgure 4.9. Total nitrogen concentrations for Lake Providence at Tensas Bayou
11/08/92
2.0 •
1.8-
1.6
*-•**
|,4;
w 1.2 -
b«
o
£ 1.0
£ 0.8
'ro
o °-6 "
I—
0.4
0.2 -
0.0
11/26/81
08/22/84
05/19^7
Sample Collection Date
STATION * » • 58010132
Rgure 4.10. Total phosphorus concentrations for Lake Providence at Tensas
02/12/90
Bayou
11/08/92
-------
Nitrogen and Phosphorus Export to Streams
Despite the many benefits, there is a potential negative
impact of fertilizer application on agricultural fields. The
problem was first identified decades ago as part of the
study of lake eutrophication. Lake eutrophication is a
process by which excess nutrients in lake water make it
easier for undesirable plants to thrive, which in turn
Consume other resources and adversely affect lake water
quality for other purposes. The potential effects of the
export of nitrogen and phosphorus from farmlands to
streams have been intensively studied for several de-
cades, it i§ now possible to survey the scientific literature
to determine how much nitrogen and phosphorus export
can be expected for different types of land uses in
different areas,
A literature survey of North American nutrient export
studies (Young and others, 1996, in the Journal of
Environmental Management) provided coefficients for
estimated export (kg/ha/yr) for nitrogen and phosphorus
under different types of land uses. To estimate total
nutrient export potential on the Tensas River Basin, the
reported median coefficients for comparable agricultural
use? were multiplied by the amount of land cover in the
agriculture land cover classes. The coefficient-times-land
use model was developed in 1980 for the United States
Environmental Protection Agency by Rechow and others
(US EPA 440/5-80-011, Washington, DC). The coeffi-
cients reported for nitrogen varied from 2.6 to 6.2 kg/ha/
yr, with a median value of 3.9 kg/ha/yr. The values
reported for phosphorus ranged from 0.3 to 1.5 kg/ha/yr,
with a median value of 0.7 kg/ha/yr.
The scientific literature provides a simple predictive
model based only on nitrogen and phosphorus loadings
to streams. Of course, this model does not reflect actual
fertilizer application rates which determine local export
amounts. However, over an area such as the Tensas
River Basin, the models are valuable as a screening tool
to rank subjvatersheds Based on potential impacts,
assuming that average fertilizer rates are used through-
out the region. In a nutshell, if there are no agricultural
lands in a watershed, then fertilizer application is near
zero, Such a watershed has less risk of impacts than a
Watershed for which 30 percent of the area is used for
agriculture. One major drawback of this simple model is
that It ignores fertilizer applications in urban areas, where
areas such as lawns, gardens, and golf courses can
receive heavy fertilizer doses several times a year.
When this model was applied to the Tensas River Basin
the potential nitrogen loading was 4.96 kg/ha/yr and the
potential phosphorus loading was 1.34 kg/ha/yr. These
are very high values when compared to values found
elsewhere in the U.S. These values were calculated
from the agricultural landuse data shown in the landcover
data in Chapter 3 (Figure 3.4). These data show
225,708 hectares of land used for intensive agriculture,
which does not include grasslands for grazing, orchards,
and vegetation in towns. This is 60% of the total land
area which is consistent with the human use index
shown in Chapter 3 (Figure 3.6). Again, this model only
shows the amount of nitrogen and phosphorus that may
be available for transport into the water system.
-------
Chapter 5: Comments and
Recommendations
There are many fine features which make up the
Tensas River Basin. Fertile farmlands, deep forests
and abundant wildlife form the basis of the good life
provided by the land near the Tensas River. The
continued good health of the Tensas River Basin
depends on how the land is used. The health of the
basin should be of concern to everyone living there
because their livelihood depends on what the land
can provide. Efforts to practice Best Farming Prac-
tices and the steps taken to restore forested wet-
lands in the Tensas River Basin are a big step in the
direction of keeping the Tensas healthy. A healthy
Tensas River providing clean water and sound prod-
ucts will also benefit those living down stream and
can improve the quality of the Gulf of Mexico.
This chapter draws comments and recommenda-
tions from what was learned from the landscape
analysis of the Tensas River Basin. Two of the main
concerns of land management and environmental
monitoring and protection are determining whether
environmental features are changing (for better or
worse) and determining whether management and
protection practices are working effectively. These
are complex issues. While the landscape analysis
performed in this atlas begins to address these
questions, it is only a beginning and is only part of the
scientific work needed to answer complex ecological
questions.
Comments
The forest loss over the time period studied was
remarkable. Forest loss of this magnitude is bound
to have an effect on environmental quality. Much of
the lost forest was converted to agriculture making
human use of the land very high in most of the
subwatersheds. High intensity agriculture makes
use of fertilizer. The landscape model showing the
potential for nutrient (nitrogen and phosphorus)
loading is high when compared to other watersheds
throughout the United States. Although most of the
fertilizer applied is effectively used to grow a good
crop, it is virtually unavoidable that some of the
fertilizer will run off the land. The fertilizer which
does run off can be intercepted by natural vegetation
but when this vegetation is gone, excess fertilizer
can run directly into the water and be carried down
stream.
The land of the Tensas River Basin is flat. Water
moves slowly compared to a river located in the
mountains. Water flow is driven by events such as
rain storms and hurricanes. Water and nutrients can
be held in swamp areas only to be flushed out during
high precipitation events. The natural vegetation
located in the backswamp areas can be as or more
important in holding excess nutrients than the vegeta-
tion located near the stream.
The landscape analyses demonstrated that since
1972 the forest was lost around the forest edges and
generally not separated into small patches. Forest
patch size was maintained so that in the event of
stress to the forest (fire or flood) the forest and forest
wildlife should be able to reestablish itself in a robust
manner. Looking at the forest restoration efforts
indicated that very wise decisions were made in the
locations of forests reestablishment. Areas chosen
included riparian areas, backswamp areas and areas
which connected forest patches. Hopefully this land-
scape assessment can verify that the correct deci-
sions were made, reveal how the forest changes will
look when the trees have matured, and identify addi-
tional areas to restore. It also showed that little or no
restoration efforts are underway in the southern part of
the watershed. Using Best Farming Practices to
reduce fertilizer runoff combined with forest restora-
tion should make a positive impact on the quality of
water and the quality of the land.
Figure 5.1 The Tensas River Winter 1997-1998
-------
^ £<^*:>S>K^'^sassirient of the Louisiana Tensas River Bas'n Chapter 5
lensas River Basin
Landscape Indicator Analysis
Forest
Change
•with
Restoration
Tobla 5.1 gives a summary of all the landscape indicators given in this report. The colors along with the values represent the Tensas River Basin §
Red tor concern, yellow for caution, and green for sound. I ~
As discussed in Chapter 3 in the Wetland Restoration
section, the data layers included in this data set can
be used to help identify sites for potential wetland
forest restoration. The data can be queried based on
a set of "rules" defined by local land managers,
farmers, and environmental quality specialists. For
example, one could identify (as we did in Chapter 3)
all patches of land within 360 meters of the Tensas
River that are currently agriculture but were histori-
cally forested, have hydric soils, and have a high
potential to flood. Perhaps current agricultural use
would be a factor. Maybe it would be more economi-
cally feasible to convert land from one type of agricul-
tural use that it would from another (e.g., more
economical to convert from soybean than from rice).
Recommendations
There are many more types of landscape analyses
Which could be done to provide information to land
managers* farmers and environmental quality special-
ists. The Jandcover map shown in Chapter 3 (Figure
3.4) could be used to perform much more detailed
analysis investigating different types of agricultural
use. These data could be analyzed to further identify
locations of landuse and landcover in relation to
features on the landscape. If wildlife species-spe-
cific questions arise, these data can be used to
f)riQ^el habitat, requirements. For example, if a given
spe"cies requires a certain size forest patch and has a
distance to water requirement, the data can be que-
ried to identify land parcels that meet those require-
ments.
-------
Using the forest change data, all of the landscape
indicator data and the landuse/landcover data, more
analyses could be done on comparing the
subwatersheds to each other. Indicators such as U-
index, roads crossing streams, forest loss and nutri-
ent loading could be used to rank the subwatersheds.
This would be used to target landuse practice
changes to areas most in need.
The North American Landscape Characterization
image database provides 20 years of change detec-
tion data. These data could be classified and used
effectively to identify status and trends of landuse
elsewhere in the Mississippi River Basin. The NDVI
analysis was an informative, cost effective, and quick
method for assessing ecological change detection for
the Tensas River Basin. This method could also be
developed and used to characterize ecological
changes for the entire Mississippi River Basin or to
target areas that need further analysis using tradi-
tional land classification methods.
subwatershed have an affect on water quality. With
an in-depth water quality study, not only would re-
searchers be able to answer questions such as those
posed above but the data would provide a baseline
data base of water quality that could be used later to
determine whether restoration and protections efforts
made today have the desired effect in the future.
Without this type of information, it will be difficult to
determine how successful these efforts have been.
"A system of conservation based solely on economic
self-interest is hopelessly lopsided. It tends to ignore,
and thus eventually to eliminate, many elements in the
land community that lack commercial value, but that
are (as far as we know) essential to its healthy func-
tioning."
-Aldo Leopold (father, farmer, and ecologist)
Water quality continues to be an issue in the Tensas
River Basin yet there is very little data available to
adequately characterize water quality for the basin.
This is particularly true when trying to link water
quality with any of the landscape metrics discussed in
this report. The water quality data presented in
Chapter 4 is easy to use in terms of characterizing
individual water quality monitoring stations but diffi-
cult to use in terms of characterizing a subbasin or
the entire Watershed. The present sampling loca-
tions can detect the presence and quantity of nutri-
ents but can't tell you if one subbasin or area is
contributing more or less than another. We feel that a
well-designed water quality study would add a wealth
of information to the data available for the Tensas
River Basin. This study should be designed and
implemented to characterize each subwatershed
along with the entire Tensas River Basin using ran-
domized sampling techniques stratified within the
subwatersheds. With this type of information, there
are many questions that could be answered such as:
do certain types of agriculture affect the Tensas River
nutrient loads more that others; does landuse (forest
cover or agricultural) in backswamps or riparian areas
have an effect on the flow of nutrients; does landuse
in the
Figure 5.2 Airphoto of the Tensas River near Westwood, LA
-------
Appendix: Additional Information About
theTensas River Basin
Tensas River Basin- Forest Change Analysis for the 1970 Classification
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Phcal Analyser
3 types found.
1043984 pixels (non-missing).
2256364 pixels coded as missing.
Data Code
2
1
3
Pixel
Count
679228
350828
13928
Pixel Percent
0.65061
0.33605
0.01334
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
1393704
742606
34785
Same-type percentage
0.939641
0.886800
0.591778
Patch Statistics
Data code
2
1
3
Number
patches
1066
3248
878
Largest
patch
621658
152609
2969
Overall values, not area-weighted:
5192 621658
N patches
<5 cells
779
2159
673
Avg patch Proportion
size 5
637.174 0.9982
108.014 0.9897
15.863 0.9219
201.076 0.9943
LEGEND
1: Forest;
! T3L TCL701.wpd -078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Change Analysis 1970 Class Subwatershed 2
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
3 types found.
15569 pixels (non-missing).
13339 pixels coded as missing.
Data Code
2
1
3
Pixel Count
13267
712
1590
Pixel Percent
0.85214
0.04573
0.10213
Number of edges and percent of same-type edges
Data
code
2
1
3
Number edges
26724
1973
3413
Same-type percentage
0.952253
0.439432
0.846469
Patch Statistics
Data code
2
1
3
Number
patches
24
93
8
Largest
patch
13159
101
1564
Overall values, not area-weighted:
125 13159
N patches
<5 cells
15
67
3
Avg patch Proportion
size 5
552.792 0.9978
7.656 0.8666
198.750 0.9975
124.552 0.9918
T3L TCL702.wpd - 078Leb98
LEGEND
1: Forest;
2: Human Use;
3: Water
-------
Tensas River Basin- Forest Change Analysis 1970 Class Subwatershed3
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
126078 pixels (non-missing).
1 15728 pixels coded as missing.
Data
Code
2
1
3
Pixel Count
120252
5403
423
Pixel Percent
0.95379
0.04285
0.00336
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
242246
14325
1169
Same-type percentage
0.969626
0.484328
0.426005
Patch Statistics
Data code
2
1
3
Number
patches
37
746
78
Largest
patch
120166
864
155
Overall values, not area-weighted:
861 120166
N patches
<5 cells
31
597
67
Avg patch Proportion
size 5
3250.054 0.9997
7.243 0.8286
5.423 0.7754
146.432 0.9916
LEGEND
1: Forest;
T3L TCL703.wpd -078Leb98
2: Human Use; 3: Water
:, '! „'. :„ 1 »'!':*
-------
Tensas River Basin- Forest Change Analysis 1970 Class Subwatershed4
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
3 types found.
256891 pixels (non-missing).
235912 pixels coded as missing.
Data Code
2
1
3
Pixel Count
193968
61666
1257
Pixel Percent
0.75506
0.24005
0.00489
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
395488
131605
3259
Same-type percentage
0.954090
0.862444
0.505370
Patch Statistics
Data code
2
1
3
Number
patches
191
788
165
Largest
patch
190513
36436
297
Overall values, not area-weighted:
1144 190513
N patches
<5 cells
142
529
137
Avg patch Proportion
size 5
1015.539 0.9987
78.256 0.9854
7.618 0.8282
224.555 0.9947
T3L TCL704.wpd -078Leb98
LEGEND
1: Forest;
2: Human Use;
3: Water
-------
iite s^^
'sf
Tensas River Basin- Forest Change Analysis 1970 Class Subwatershed 5
LANDSTAT: Landscape Statistics Program, v. 7-94
., . " !
Results of Pixel Analyzer
3 types found.
171594 pixels (non-missing).
409844 pixels coded as missing.
Data
Code
1
2
3
Pixel Count
84382
85707
1505
Pixel Percent
0.49175
0.49948
0.00877
:i
Number of edges and percent of same-type edges
Data code
1
2
3
Number edges
173218
174895
3482
Same-type percentage
0.930307
0.932977
0.430213
Patch Statistics
Data code
1
2
3
Number
patches
449
226
235
Largest
patch
49643
39931
95
Overall values, not area-weighted:
910 49643
N patches
<5 cells
279
168
155
Avg patch Proportion
size 5
187.933 0.9940
379.235 0.9968
6.404 0.8246
188.565 0.9939
LEGEND
1: Forest;
T3L TCL705.wpd -078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Change Analysis 1970 Class Subwatershed 6
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
3 types found.
30910 pixels (non-missing).
35042 pixels coded as missing.
Data
Code
1
2
3
Pixel Count
21398
9300
212
Pixel Percent
0.69227
0.30087
0.00686
Number of edges and percent of same-type edges
Data code
1
2
3
Number edges
42860
19261
509
Same-type percentage
0.952077
0.910025
0.235756
Patch Statistics
Data code
1
2
3
Number
patches
132
68
99
Largest
patch
19442
6530
30
Overall values, not area-weighted:
299 19442
N patches
<5 cells
107
59
93
Avg patch Proportion
size 5
162.106 0.9920
136.765 0.9909
2.141 0.3679
103.378 0.9874
LEGEND
1: Forest;
T3L TCL706.wpd -078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin- Forest Analysis 1970 Class Subwatershed 7
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
3 types found.
20411 pixels (non-missing).
30425 pixels coded as missing.
Data Code
3
1
2
Pixel Count
246
12354
7811
Pixel Percent
0.01205
0.60526
0.38269
Number of edges and percent of same-type edges
Data code
3
1
2
Number edges
720
26329
16763
Same-type percentage
0.298611
0.872498
0.799081
Patch Statistics
Data code
3
1
2
Number
patches
75
124
84
Largest
patch
38
11878
7163
Overall values, not area-weighted:
283 11878
N patches
<5 cells
67
100
63
Avg patch Proportion
size 5
3.280 0.5650
99.629 0.9870
92.988 0.9853
72.124 0.9812
LEGEND
1: Forest;
T3L TCL707.wpd -078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Change Analysis 1970 Class Subwatershed 8
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Phfe! Analyser
3 types found.
221441 pixels (non-missing).
224103 pixels coded as missing.
Data
Code
1
3
2
Pixel Count
108326
5713
107402
Pixel Percent
0.48919
0.02580
0.48501
Number of edges and percent of same-type edges
Data
code
1
3
2
Number edges
226751
13033
224181
Same-type percentage
0.903630
0.692550
0,905822
Patch Statistics
Data code
1
3
2
Number
patches
974
322
559
Largest
patch
53393
2952
98811
Overall values, not area-weighted:
1855 98811
N patches
<5 cells
754
260
462
Avg patch Proportion
size 5
111.218 0.9892
17.742 0.9249
192.132 0.9935
119.375 0.9896
LEGEND
1: Forest;
T3L TCL708.wpd -078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin- Forest Change Analysis 1970 Class Subwaterstied9
LANDSTAT: Landscape Statistics Program, y. 7-94
'ill
Results of Pixel AnalyTBr
3 types found.
200615 pixels (non-missing).
505923 pixels coded as missing.
Data
Code
2
1
3
Pixel Count
140272
57279
3064
Pixel Percent
0.69921
0.28552
0.01527
Number of edges and percent of same-type edges
Data
code
2
1
3
Number edges
290790
125715
8241
Same-type percentage
0.914664
0.809879
0.475549
Patch Statistics
Data code
2
1
3
Number
patches
286
919
157
Largest
patch
113329
8394
643
Overall values, not area-weighted:
1362 113329
N patches
<5 cells
199
600
111
Avg patch Proportion
size 5
490.462 0.9979
62.328 0.9825
19.516 0.9445
147.294 0.9927
LEGEND
PL TCL709.wpd -078Leb98
1: Forest;
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Change Analysis for the 1990 Classification
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
1043948 pixels (non-missing).
2256400 pixels coded as missing.
Data
Code
2
1
3
Pkel Count
806490
224465
12993
Pkel Percent
0.77254
0.21502
0.01245
Number of edgss and percent of same-type edges
Data
code
2
1
3
Number edges
1643483
484982
31735
Same-type percentage
0.954937
0.845994
0.621932
Patch Statistics
Data code
2
1
3
Number
patches
753
3488
691
Largest
patch
750008
105548
3036
Overall values, not area-weighted:
4932 750008
N patches
<5 cells
561
2364
465
Avg patch Proportion
size 5
1071.036 0.9989
64.353 0.9825
18.803 0.9423
211.668 0.9947
LEGEND
1: Forest;
T3LTCL901.wpd- 078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Changs Analysis 1990 Class Subwatershed2
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
15558 pixels (non-missing).
13 350 pixels coded as missing.
Data Code
2
1
3
Pkel Count
12809
1056
1693
PkelPercent
0.82331
0.06788
0.10882
Number of edgss and percent of same-type edgss
Data code
2
1
3
Number edges
25848
2728
3521
Same-type percentage
0.953536
0.538123
0.867367
Patch Statistics
Data code
2
1
3
Number
patches
26
75
5
Largest
patch
12695
242
1582
Overall values, not area-weighted:
106 12695
N patches
<5 cells
18
48
3
Avg patch Proportion
size 5
492.654 0.9977
14.080 0.9375
338.600 0.9965
146.774 0.9935
LEGEND
1: Forest;
, T3LTCL902.wpd-078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Changs Analysis 1990 Class Subwatershed 3
LANDSTAT: Landscape Statistics Prog-am, v. 7-94
Results of Pixel Analyzer
3 types found.
126080 pixels (non-missing).
1 15726 pixels coded as missing.
Data Code
2
1
3
Pkel Count
121907
3872
301
Pkel Percent
0.96690
0.03071
0.00239
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
244617
10325
929
Same-type percentage
0.976800
0.483196
0.290635
Patch Statistics
Data code
2
1
3
Number
patches
83
496
82
Largest
patch
121748
368
34
Overall values, not area-weighted:
661 121748
N patches
<5 cells
76
388
68
Avg patch Proportion
size 5
1468.759 0.9992
7.806 0.8355
3.671 0.6379
190.741 0.9933
LEGEND
1: Forest;
T3LTCL903.wpd- 078Leb98
2: Human Use;
3: Water
-------
Tensas River Basin - Forest Changs Analysis 1990 Class Subwatershed 4
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pkel Analyzer
3 types found.
256905 pixels (non-missing).
235 898 pixels coded as missing.
Data Code
2
1
3
Pkel Count
225015
31199
691
Pkel Percent
0.87587
0.12144
0.00269
Number of edgss and percent of same-type edges
Data code
2
1
3
Number edges
456804
69663
2009
Same-type percentage
0.963801
0.766648
0.367845
Patch Statistics
Data code
2
1
3
Number
patches
123
793
110
Largest
patch
220608
11614
51
Overall values, not area-weighted:
1026 220608
N patches
,<5 cells
91
507
71
Avg patch Proportion
size 5
1829.390 0.9994
39.343 0.9715
6.282 0.8336
250.395 0.9955
LEGEND
1: Forest; 2: Human Use; 3: Water
T3LTqL904.wpd- 078Leb98
-------
Tensas River Basin - Forest Change Analysis 1990 Ckss Subwatershed 5
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
171571 pixels (non-missing).
409 867 pixels coded as missing.
Data Code
2
1
3
Pkel Count
113185
57244
1142
PixelPercent
0.65970
0.33365
0.00666
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
228851
117397
2657
Same-type percentage
0.958877
0.918022
0.458412
Patch Statistics
Data code
2
1
3
Number
patches
125
535
162
Largest
patch
109734
24872
153
Overall values, not area-weighted:
822 109734
N patches
<5 cells
97
367
116
Avg patch Proportion
size 5
905.480 0.9987
106.998 0.9889
7.049 0.8196
208.724 0.9943
LEGEND
1: Forest; 2: Human Use; 3: Water
T3LTCL905wpd- 078Leb98
-------
Tensas River Basin - Forest Change Analysis 1990 Class Subwatershed 6
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
30923 pixels (non-missing).
35029 pixels coded as missing.
Data Code
2
1
3
Pkel Count
12025
18864
34
Pkel Percent
0.38887
0.61003
0.00110
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
24805
37566
107
Same-type percentage
0.925257
0.949742
0.271028
Patch Statistics
Data code
2
1
3
Number
patches
48
138
9
Largest
patch
8770
13133
13
Overafl values, not area-weighted:
195 13133
N patches
<5 cells
34
107
7
Avg patch Proportion
size 5
250.521 0.9959
136.696 0.9907
3.778 0.7353
158.579 0.9925
LEGEND
1: Forest; 2: Human Use; 3: Water
T3LTCL906.ivpd- 078Leb98
-------
Tensas River Basin - Forest Changs Analysis 1990 Class Subwatershed 7
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
3 types found.
20413 pixels (non-missing).
30423 pixels coded as missing.
Data Code
1
2
3
Pixel Count
12266
7962
185
PkelPercent
0.60089
0.39005
0.00906
Number of edges and percent of same-type edges
Data
cods
1
2
3
Number edges
25914
17072
495
Same-type percentage
0.881223
0.816483
0.298990
Patch Statistics
Data code
1
2
3
Number
patches
175
72
50
Largest
patch
11186
6181
37
Overall values, not area-weighted:
297 11186
N patches
<5 cells
144
52
39
Avg patch. Proportion
size 5
70.091 0.9825
110.583 0.9882
3.700 0.7081
68.731 0.9822
LEGEND
1: Forest; 2: Human Use; 3: Water
T3LTCL907.wpd- 078Leb98
-------
Tensas River Basin - Forest Change Analysis 1990 Ckss Subwatershed 8
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pkel Analyzer
3 types found.
221446 pixels (non-missing).
224098 pixels coded as missing.
Data Code
1
2
3
Pkel Count
61431
154211
5804
Pkel Percent
0.27741
0.69638
0.02621
Number of edges and percent of same-type edges
Data code
1
2
3
Number edges
131713
316410
12986
Same-type percentage
0.853325
0.941313
0.742030
Patch Statistics
Data code
1
2
3
Number
patches
1123
368
268
Largest
patch
28713
145233
3014
Overall values, not area-weighted:
1759 145233
Npatches
<5 cells
874
309
219
Avg patch Proportion
size 5
54.703 0.9774
419.052 0.9969
21.657 0.9388
125.893 0.9900
LEGEND
1: Forest;
! T3LTCL908.wpd-078Leb98
2: Human Use; 3: Water
-------
Tensas River Basin - Forest Change Analysis 1990 Class Subwatershed 9
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pkel Analyzer
3 types found.
200602 pixels (non-missing).
505 936 pixels coded as missing.
Data Code
2
1
3
Pkel Count
158225
39231
3146
Pkel Percent
0.78875
0.19557
0.01568
Number of edges and percent of same-type edges
Data code
2
1
3
Number edges
325007
88907
8482
Same-type percentage
0.933106
0.750256
0.475949
Patch Statistics
Data code
2
1
3
Number
patches
245
1047
193
Largest
patch
130614
6618
1065
Overall values, not area-weighted:
1485 130614
N patches
<5 cells
179
705
115
Avg patch Proportion
size 5
645.816 0.9981
37.470 0.9699
16.301 0.9406
135.086 0.9917
LEGEND
1: Forest;
T3LTCLS09.-wpd- 078Leb98
2: Human Use;
3: Water
-------
13k
Tensas River Basin - Riparian Analysis 120 meter Buffer
IANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
5 types found.
691533 pixels (non-missing).
2608815 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
406345
112527
147034
13105
12522
Pixel Percent
0.58760
0.16272
0.21262
0.01895
0.01811
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
819978
246478
312040
39447
30836
Same-type percentage
0.922619
0.800923
0.852474
0.266433
0.610455
Patch Statistics
Data code Number
patches
5 1752
2 3758
1 2673
4 4459
9 808
Largest
patch
216825
21183
74997
196
2998
N patches
<5 cells
1203
3002
1930
3868
624
Avg patch
size
231.932
29.943
55.007
2.939
15.498
Proportion
5
0.9954
0.9595
0.9789
0.5519
0.9206
Overall values, not area-weighted:
13450 216825 ' 51.415 0.9763
LEGEND
1: Forest;
• T2Ll?0.wpd - 078Leb98
2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin- Riparian Analysis Zone 2 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
5 types found.
6071 pixels (non-missing).
22837 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
4117
65
138
171
1580
Pixel Percent
0.67814
0.01071
0.02273
0.02817
0.26025
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
7312
197
382
431
3351
Same-type
percentage
0.920268
0.192893
0.306283
0.361949
0.862728
Patch Statistics
Data code Number
patches
5 59
2 , 31
1 44
4 43
9 3
Largest
patch
3508
7
29
31
1574
N patches
<5 cells
35
26
39
35
1
Avg patch
size
69.780
2.097
3.136
3.977
526.667
Overall values, not area- weighted:
180 3508 33.728
Proportion
5
0.9840
0.4769
0.6014
0.6374
0.9994
0.9641
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
5: Human Use;
T2L120z2.wpd -078Leb98
9: Water
-------
Tensas River Basin - Riparian Analysis Zone 3 120 meter Buffer
LANDSJAT: Landscape Statistics Program, v". 7-94
Results of Pixel Analyser
5 types found.
67779 pixels (non-missing).
174027 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
63736
1675
1282
992
94
Pixel Percent
0.94035
0.02471
0.01891
0.01464
0.00139
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
124010
4978
3352
2991
223
Same-type
percentage
0.958269
0.281237
0.465394
0.265129
0.358744
Patch Statistics
Data code Number
patches
5 131
2 557
„„ ,, ,.
1 198
4 356
9 25
,.„.. .....,_
Largest
patch
44560
77
229
195
27
N patches
<5 cells
92
494
152
322
19
Avg patch
size
486.534
3.007
6.475
2.787
3.760
Overall values, not area-weighted:
1267 44560 53.496
Proportion
5
0.9977
0.5648
0.7956
0.5161
0.6702
0.9757
T2L120z3.wpd -078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
! : ''!,; • "'I1'1 ' ' '" I ', ' f
-------
Tensas River Basin - Riparian Analysis Zone 4 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
5 types found.
178889 pixels (non-missing).
313914 pixels coded as missing.
Data Code
2
5
4
1
9
Pixel Count
30382
123765
2677
21443
622
Pixel Percent
0.16984
0.69185
0.01496
0.11987
0.00348
Number of edges and percent of same-type edges
Data code
2
5
4
1
9
Number edges
66396
247653
8046
46917
1703
Same-type percentage
0.811871
0.941265
0.237882
0.781593
0.369348
Patch Statistics
Data code Number
patches
2 931
5 310
4 979
1 568
9 127
Largest
patch
18102
102728
38
11243
113
N patches
<5 cells
757
210
831
389
104
Avg patch Proportion
size 5
32.634 0.9609
399.242 0.9972
2.734 0.5159
37.752 0.9686
4.898 0.7379
Overall values, not area-weighted:
2915 102728 61.368 0.9795
T2L120z4.wpd -078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
;Tt
-f—
Tensas River Basin - Riparian Analysis Zone 5 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
I
1
Results nf Pixel Analyser
5 types found.
56051 pixels (non-missing).
525387 pixels coded as missing.
Data Code
2
5
1
4
9
Pixel Count
10188
18202
25536
1072
1053
Pixel Percent
0.18176
0.32474
0.45559
0.01913
0.01879
Number of edges and percent of same-type edges
Data code
2
5
1
4
9
Number edges
20235
33670
49159
2833
2362
Same-type
percentage
0.831085
0.885061
0.919038
0.289799
0.455546
Patch Statistics
Data code Number
patches
2 294
5 247
1 251
4 365
9 174
Largest
patch
1722
2394
12462
73
95
N patches
<5 cells
202
132
150
320
126
Avg patch
size
34.653
73.692
101.737
2.937
6.052
Overall values, not area-weighted:
1331 12462 42.112
Proportion
5
0.9664
0.9886
0.9898
0.5075
0.7854
0.9721
!•• T2L120z5.wpd-078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
,:l
-------
Tensas River Basin - Riparian Analysis Zone 6 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Piye,] Analyser
5 types found.
30904 pixels (non-missing).
35048 pixels coded as missing.
Data Code
2
5
1
9
4
Pixel Count
3294
8736
18088
208
578
Pixel Percent
0.10659
0.28268
0.58530
0.00673
0.01870
Number of edges and percent of same-type edges
Data code
2
5
1
9
4
Number edges
7270
18187
36335
510
1680
Same-type percentage
0.794360
0.909441
0.941764
0.233333
0.252976
Patch Statistics
Data code Number
patches
2 134
5 38
1 148
9 99
4 220
Largest
patch
2233
6204
12910
30
54
N patches
<5 cells
113
30
124
93
201
Avg patch
size
24.582
229.895
122.216
2.101
2.627
Proportion
5
0.9502
0.9958
0.9896
0.3462
0.5000
Overall values, not area-weighted:
639 12910 48.363 0.9736
T2L120z6.wpd -078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
I "
' l>
Tensas River Basin - Riparian Analysis Zone 7 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
i i
Results nf Pixel Afialyyer
5 types found.
4164 pixels (non-missing).
46672 pixels coded as missing.
Data Code
1
5
9
2
4
Pixel Count
832
2232
88
356
656
Pixel Percent
0.19981
0.53602
0.02113
0.08549
0.15754
Number of edges and percent of same-type edges
Data code
1
5
9
2
4
Number edges
1589
4113
232
858
1505
Same-type percentage
0.643172
0.743010
0.206897
0.403263
0.390033
Patch Statistics
Data code
1
5
9
2
4
Number
patches
89
80
40
88
144
Largest
patch
220
1527
10
60
59
N patches
<5 cells
65
55
35
78
115
Avg patch
size
9.348
27.900
2.200
4.045
4.556
Proportion
5
0.8798
0.9601
0.3864
0.6826
0.7332
Overall values, not area-weighted:
441 1527 9.442 0.8725
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
5: Human Use;
T2L120z7.wpd -078teb98
9: Water
Kilt
-------
Tensas River Basin - Riparian Analysis Zone 8 120 meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
5 types found.
199037 pixels (non-missing).
246507 pixels coded as missing.
Data Code
1
2
5
4
9
Pixel Count
55256
50401
84262
3229
5889
Pixel Percent
0.27762
0.25322
0.42335
0.01622
0.02959
Number of edges and percent of same-type edges
Data code
1
2
5
4
9
Number edges
117407
109954
175871
10432
13355
Same-type
percentage
0.870348
0.827846
0.891574
0200920
0.704231
Patch Statistics
Data code Number
patches
1 809
2 1260
5 602
4 1382
9 338
Largest
patch
27137
20356
63889
51
2956
N patches
<5 cells
650
1080
475
1251
281
Avg patch
size
68.302
40.001
139.970
2.336
17.423
Overall values, not area-weighted:
4391 63889 45.328
Proportion
5
0.9805
0.9687
0.9916
0.4230
0.9221
0.9714
T2L120z8.wpd -078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
•if mini in in
Tensas River Basin - Riparian Analysis Zone 9 120 meter Buffer
III
LANDSTAT: Landscape St
atistics Program, v. 7-94
Results nf Pixel Analyzer
5 types found.
148346 pixels (non-missing).
558192 pixels coded as missing.
Data
Code
5
2
4
1
9
Pixel Count
99881
16982
4564
24001
2918
Pixel Percent
0.67330
0.11448
0.03077
0.16179
0.01967
Number of edges and percent of same-type edges
Data
code
5
2
4
1
9
Number edges
205285
39785
13792
53387
7863
Same-type percentage
0.899340
0.670806
0.264139
0.752861
0.467125
Patch Statistics
Data code
5
2
4
1
9
Number
patches
565
1152
1574
936
209
Largest
patch
54525
2744
109
6286
729
Overall values, not area-weighted:
4436 54525
N patches
<5 cells
384
896
1366
687
152
Avg patch Proportion
size 5
176.781 0.9942
14.741 0.9195
2.900 0.5537
25.642 0.9560
13.962 0.9147
i
33.441 0.9643
.!:% " 'I
M'J '<;';
'II
IteGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
T2L120z9.wpd-078Leb98
5: Human Use; 9: Water
-------
Tensas River Reach and Major Tributaries
Riparian. Analysis 360 Meter Buffer
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyzer
5 types found.
76659 pixels (non-missing).
1720848 pixels coded as missing.
Data Code
5
1
9
2
4
Pixel Count
39356
20793
4527
8883
3100
Pixel Percent
0.51339
0.27124
0.05905
0.11588
0.04044
Number of edges and percent of same-type edges
Data code
5
1
9
2
4
Number edges
78676
44387
12243
19844
9503
Same-type
percentage
0.841362
0.757406
0.470228
0.657327
0.260549
Patch Statistics
Data code Number
patches
5 367
1 647
9 307
2 665
4 990
Largest
patch
5116
4686
1343
763
131
N patches
<5 cells
239
475
238
505
836
Avg patch
size
107.237
32.138
14.746
13.358
3.131
Overall values, not area-weighted:
2976 5116 25.759
Proportion
5
0.9911
0.9621
0.9123
0.9097
0.5842
0.9527
TBLM360j2.wpd - 078Leb98
LEGEND: 1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin - Backswamp Analysis
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyger
5 types found.
125436 pixels (non-missing).
3162902 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
52834
22824
4506
35286
9986
Pixel Percent
0.42120
0.18196
0.03592
0.28131
0.07961
Number of edges and percent of same-type edges
Data code
5
2
4
1
9
Number edges
77195
33574
9158
50619
19588
Same-type percentage
0.860405
0.760410
0.304761
0.801754
0.740147
Patch Statistics
Data code
5
2
4
1
9
Number
patches
5688
3569
1951
4574
732
Largest
patch
2281
1944
178
2681
2656
N patches
<5 cells
4370
2930
1760
3524
560
Avg patch Proportion
size 5
9.289 0.8549
6.395 0.7833
2.310 0.4257
7.714 0.8255
13.642 0.9116
Overall values, not area-weighted:
16514 2681 7.596 0.8227
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
:: |!' T2LXxffllwpd-078Leb98
5: Human Use; 9: Water
-------
Tensas River Basin - Backswamp Analysis Zone 2
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyzer
5 types found.
2616 pixels (non-missing).
26094 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
950
26
124
115
1401
Pixel Percent
0.36315
0.00994
0.04740
0.04396
0.53555
Number of edges and percent of same-type edges
Data code
5
2
4
1
9
Number edges
1197
37
264
214
2696
Same-type percentage
0.729323
0.027027
0.291667
0.392523
0.918769
Patch Statistics
Data code Number
patches
5 184
2 23
4 51
1 33
9 12
Largest
patch
133
2
20
26
1371
N patches
<5 cells
145
23
47
27
9
Avg patch Proportion
size 5
5.163 0.7305
1.130 0.0000
2.431 0.4113
3.485 0.6696
116.750 0.9893
Overall values, not area-weighted:
303 1371 8.634 0.8440
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
T2LXxffll2.\vpd - 078Leb98
5: Human Use; 9: Water
-------
f<^^ ^cofoytcoi Assassment of ths Loulsfsn3 Tensas RJver Basin: Appendix
• Ill
Tensas River Basin - Backswamp Analysis Zone 3
LANDSTAT: Landscape Statistics Program, V. 7-94
Results nf Pixel Analyser
5 types found.
7005 pixels (non-missing).
233235 pixels coded as missing.
Data Code
5
1
2
9
4
Pixel Count
5480
522
478
225
300
Pixel Percent
0.78230
0.07452
0.06824
0.03212
0.04283
ii
Number of edges and percent of same-type edges
Data code
5
1
2
9
4
Number edges
7390
1020
1030
503
667
Same-type percentage
0.905683
0.503922
0.416505
0.493042
0.560720
Patch Statistics
Data code
5
1
2
9
4
Number
patches
685
104
122
29
60
Largest
patch
1296
91
43
100
189
N patches
<5 cells
531
83
100
20
54
Avg patch
size
8.000
5.019
3.918
7.759
5.000
Proportion
5
0.8279
0.7414
0.7176
0.8756
0.7700
Overall values, not area-weighted:
1000 1296 7.005 0.8130
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
" j.;i i T2LXxffll3,wpd - 078Leb98
5: Human Use; 9: Water
-------
Tensas River Basin - Backswamp Analysis Zone 4
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyser
5 types found.
33623 pixels (non-missing).
452883 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
19018
6909
879
6551
266
Pixel Percent
0.56562
0.20548
0.02614
0.19484
0.00791
Number of edges and percent of same-type edges
Data code
5
2
4
1
9
Number edges
26988
10140
1868
10236
479
Same-type percentage
0.913739
0.781262
0.328694
0.777354
0.455115
Patch Statistics
Data code Number
patches
5 1558
2 911
4 320
1 652
9 84
Largest
patch
2279
1173
46
333
35
N patches
<5 cells
1104
703
271
469
69
Avg patch
size
12.207
7.584
2.747
10.048
3.167
Proportion
5
0.8935
0.8136
0.5290
0.8773
0.6165
Overall values, not area-weighted:
3525 2279 9.538 0.8622
LEGEND
1: Forest;
2: Forest Loss;
T2LXxffll4.wpd - 078Leb98
4: Forest Gain; 5: Human Use; 9: Water
-------
i til V.
Tensas River Basin - Backswamp Analysis Zone 5
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyyar
5 types found.
23173 pixels (non-missing).
540827 pixels coded as missing.
Data Code
5
..!.. A
1
4
9
Pixel Count
6798
3704
11259
551
861
Pixel Percent
0.29336
0.15984
0.48587
0.02378
0.03716
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
9827
4550
15566
997
1349
Same-type
percentage
0.905973
0.827692
0.926057
0.368104
0.607858
Patch Statistics
Data code Number
patches
5 694
2 633
1 1119
4 201
9 159
Largest
patch
2010
300
2688
24
89
N patches
<5 cells
526
506
874
168
120
Avg patch
size
9.795
5.852
10.062
2.741
5.415
Overall values, not area-weighted:
2806 2688 8.258
Proportion
5
0.8601
0.7643
0.8595
0.4791
0.7573
0.8316
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
I T2LXxffll5.wpd - 078Leb98
5: Human Use; 9: Water
-------
Tensas River Basin - Backswamp Analysis Zone 6
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Piyel Analyser
5 types found.
2259 pixels (non-missing).
62721 pixels coded as missing.
Data Code
5
4
1
9
2
Pixel Count
214
71
1717
97
160
Pixel Percent
0.09473
0.03143
0.76007
0.04294
0.07083
Number of edges and percent of same-type edges
Data code
5
4
1
9
2
Number edges
162
79
1758
127
220
Same-type percentage
0.746914
0.265823
0.883959
0.299213
0.572727
Patch Statistics
Data code Number
patches
5 65
4 49
1 330
9 59
2 43
Largest
patch
19
6
139
11
22
N patches
<5 cells
54
48
258
56
34
Avg patch
size
3.292
1.449
5.203
1.644
3.721
Proportion
5
0.5140
0.0845
0.7490
0.2474
0.6875
Overall values, not area-weighted:
546 136 4.137 0.6799
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
5: Human Use;
T2LXxffll6.wpd - 078Leb98
9: Water
-------
I
Tensas River Basin - Backswamp Analysis Zone 7
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
5 types found.
3266 pixels (non-missing).
43902 pixels coded as missing.
Data Code
5
4
1
2
9
Pixel Count
646
188
1992
367
73
Pixel Percent
0.19780
0.05756
0.60992
0.11237
0.02235
Number of edges and percent of same-type edges
Data code
5
4
1
2
9
Number edges
781
278
2378
520
146
Same-type
percentage
0.706786
0.370504
0.890664
0.650000
0.534247
Patch Statistics
Data code Number
patches
5 130
4 72
1 265
2 81
9 12
Largest
patch
44
23
498
76
23
N patches
<5 cells
95
63
204
66
8
Avg patch
size
4.969
2.611
7.517
4.531
6.083
Overall values, not area-weighted:
560 498 5.832
Proportion
5
0.7152
0.4734
0.8183
0.6948
0.7534
0.7627
T2LXxffll7.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin - Backswamp Analysis Zone 8
LANDSTAT: Landscape Statistics Program, v, 7-94
Results of Pixel Analyzer
5 types found.
20543 pixels (non-missing).
421657 pixels coded as missing.
Data Code
2
1
5
4
9
Pixel Count
4544
5872
4679
760
4688
Pixel Percent
0.22119
0.28584
0.22777
0.03700
0.22820
Number of edges and percent of same-type edges
Data code
2
1
5
4
9
Number edges
6077
8188
6824
1620
9057
Same-type percentage
0.726181
0.693942
0.709115
0.211728
0.814066
Patch Statistics
Data code Number
patches
2 988
1 1135
5 848
4 397
9 281
Largest
patch
938
860
305
22
2551
N patches
<5 cells
861
904
728
377
236
Avg patch
size
4.599
5.174
5.518
1.914
16.683
Proportion
5
0.6912
0.7301
0.7459
0.2421
0.9185
Overall values, not area-weighted:
3649 2551 5.630 0.7500
T2LXxffll8.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Art'. JKS
n nil i in 11 n
Tensas River Basin - Backswamp Analysis Zone 9
LANDSTAT: Landscape Statistics Program, v. 7-94
1
'Results nfPfxel AnalyTgr
5 types found.
32976 pixels (non-missing).
670510 pixels coded as missing.
Data Code
2
1
5
9
4
Pixel Count
6840
7172
14994
2217
1753
Pixel Percent
0.20742
0.21749
0.45469
0.06723
0.05316
Number of edges and percent of same-type edges
Data code
2
1
5
9
4
Number edges
11575
11057
23820
4481
3726
Same-type percentage
0.748855
0.700009
0.809908
0.561928
0.273484
Patch Statistics
Data code Number
patches
2 844
1 1146
5 1608
9 227
4 775
Largest
patch
1944
435
1974
464
40
N patches
<5 cells
711
907
1272
156
691
Avg patch
size
8.104
6.258
9.325
9.767
2.262
Proportion
5
0.8266
0.7896
0.8533
0.8836
0.4278
Overall values, not area-weighted:
4600 1974 7.169 0.8133
LEGEND
1: Forest;
;
; T2LXxffll9.wpd - 078Leb98
2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
I
-------
Tensas River Basin - Forest Change Analysis
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyzer
5 types found.
1043907 pixels (non-missing).
2256441 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
660978
147836
19409
202203
13481
Pixel Percent
0.63318
0.14162
0.01859
0.19370
0.01291
Number of edges and percent of same-type edges *
Data code
5
2
4
1
9
Number edges
1362552
330052
60144
435798
33600
Same-type percentage
0.931209
0.789288
0.272363
0.852767
0.595476
Patch Statistics
Data code Number
patches
5 1387
2 5047
4 6209
1 3220
9 943
Largest
patch
595999
21183
196
99871
3006
N patches
<5 cells
1086
4064
5326
2324
731
Avg patch
size
476.552
29.292
3.126
62.796
14.296
Proportion
5
0.9975
0.9582
0.5763
0.9819
0.9140
Overall values, not area-weighted:
16806 595999 62.115 0.9800
LEGEND
1: Forest;
2: Forest Loss; 4: Forest Gain; 5: Human Use;
T2LFor.wpd -078Leb98
9: Water
-------
Tensas River Basin - Forest Change Analysis Zone 2
1,
i "
F
1!'"
t
|l
l
HI
/;!,:,: ;;::: • • ' t i £•'•,.' II : , i ' : .
Results of Pixel Analy/er
5 types found.
15559 pixels (non-missing).
13349 pixels coded as missing.
Data Code
5
4
2
1
9
Pixel Count
12776
473
209
503
1598
Pixel Percent
0.82113
0.03040
0.01343
0.03233
0.10271
Number of edges and percent of same-type edges
Data code
5
4
2
1
9
Number edges
25877
1397
683
1397
3413
Same-type
percentage
0.941415
0.342162
0.218155
0.437366
0.850864
Patch Statistics
Data code Number
patches
5 36
4 102
2 81
1 71
9 9
Largest
patch
12554
56
14
88
1574
N patches
<5 cells
21
80
64
54
5
Avg patch
size
354.889
4.637
2.580
7.085
177.556
Overall values, not area-weighted:
299 12554 52.037
Proportion
5
0.9970
0.7230
0.5742
0.8410
0.9956
0.9778
:: T2LForZ2.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin - Forest Change Analysis Zone 3
LANDSTAT: Landscape Statistics Program, v. 7-94
"Results of Pixel Analy/ar
5 types found.
126076 pixels (non-missing).
115730 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
118966
3140
2210
1419
341
Pixel Percent
0.94361
0.02491
0.01753
0.01126
0.00270
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
240508
9303
5979
4581
936
Same-type percentage
0.962758
0.321187
0.465295
0.220912
0.444444
/
Patch Statistics
Data code Number
patches
5 99
2 896
1 317
4 584
9 50
Largest
patch
118759
199
229
195
121
N patches
<5 cells
89
783
253
537
40
Avg patch
size
1201.677
3.504
6.972
2.430
6.820
Proportion
5
0.9990
0.6325
0.8154
0.4355
0.8358
Overall values, not area-weighted:
1946 118759 64.787 0.9799
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
T2LForZ3.wpd - 078Leb98
5: Human Use; 9: Water
-------
;! -,*!
jit.'
I
Tensas River Basin - Forest Change Analysis Zone 4
S'il ' : .
.;i' : , "iJj
„ ,1' i , !! Hi '
±im^u& JLf>i • J-xuius^-ajjc
'ii; . . ••' ' ' ',''>.
juiusu^a r lugicuii, v. i-yt
: ; " ,'i
Results of Pixel Analyser
5 types found.
256864 pixels (non-missing).
235939 pixels coded as missing.
Data
Code
5
2
1
4
9
Pixel Count
190676
34739
26983
3765
701
Pixel Percent
0.74232
0.13524
0.10505
0.01466
0.00273
1!
Number of edges and percent of same-type edges
Data
code
5
2
1
4
9
Number edges
390435
77568
60100
11769
1943
Same-type
percentage
0.946759
0.786497
0.776123
0.242671
0.387545
Patch Statistics
Data code
5
2
1
4
9
Number
patches
216
1204
645
1292
139
Largest
patch
187267
18102
11243
38
113
Overall values, not area-weighted:
3496 187267
N patches
<5 cells
163
986
440
1080
117
Avg patch
size
882.759
28.853
41.834
2.914
5.043
73.474
Proportion
5
0.9986
0.9553
0.9719
0.5461
0.7432
0.9826
I :• ! '|:: ' !! T2LForZ4.wpd - 078Leb98
LEGEND .;' ' . , ,' "
1: Forest; 2: Forest Loss; 4: Forest Grain; 5: Human Use; 9: Water
-------
Tensas River Basin - Forest Chiange Analysis Zone 5
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
5 types found.
171505 pixels (non-missing).
409933 pixels coded as missing.
Data Code
2
5
1
4
9
Pixel Count
30141
83380
54148
2487
1349
Pixel Percent
0.17574
0.48617
0.31572
0.01450
0.00787
Number of edges and percent of same-type edges
Data code
2
5
1
4
9
Number edges
64889
170793
111406
7090
3076
Same-type percentage
0.850545
0.928662
0.920202
0.301410
0.443108
Patch Statistics /
Data code Number
patches
2 576
5 165
1 350
4 756
9 221
Largest
patch
8090
38714
16950
180
120
N patches
<5 cells
431
124
227
644
156
/
Avg patch
size
52.328
505.333
154.709
3.290
6.104
Proportion
5
0.9756
0.9977
0.9928
0.5746
0.8013
Overall values, not area-weighted:
2068 38714 82.933 0.9846
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
T2LForZ5.wpd - 078Leb98
5: Human Use; 9: Water
-------
!* *,:«!
,!!< I!.,1!:!!!1:!.
Tensas River Basin - Wetland Restoration Analysis Zone 6
: Landscape Statistics Program, v. 7-94
I1 ;
t
t
I''"' •
if
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l . ,
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K
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if •:
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r;.
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Resnlts of Pixel Analyser
5 types found.
30904 pixels (non-missing).
35048 pixels coded as missing.
Data Code
2
5
1
9
4
Pixel Count
3294
8736
18088
208
578
Pixel Percent
0.10659
0.28268
0.58530
0.00673
0.01870
Number of edges and percent of same-type edges
Data code
2
5
1
9
4
Number edges
7270
18187
36335
510
1680
Same-type percentage
0.794360
0.909441
0.941764
0.233333
0.252976
Patch Statistics
Data code Number
patches
2 134
5 38
1 148
9 99
4 220
Largest
patch
2233
6204
12910
30
54
N patches
<5 cells
113
30
124
93
201
Avg patch
size
24.582
229.895
122.216
2.101
2.627
Proportion
5
0.9502
0.9958
0.9896
0.3462
0.5000
Overall values, not area-weighted:
639 12910 48.363 0.9736
LfiGEND
1: Forest;
- 078Leb98
2: Forest Loss;
4: Forest Gain;
5: Human Use;
9: Water
-------
Tensas River Basin - Wetland Restoration Analysis Zone 7
LANDSTAT: Landscape Statistics Program, v. 7-94
'Results of Pixel Analy/er
5 types found.
20405 pixels (non-missing).
30431 pixels coded as missing.
Data Code
1
5
9
2
4
Pixel Count
10572
6337
234
1731
1531
Pixel Percent
0.51811
0.31056
0.01147
0.08483
0.07503
Number of edges and percent of same-type edges
Data code
1
5
9
2
4
Number edges
22433
13925
693
4528
4457
Same-type
percentage
0.881246
0.756266
0.285714
0.523410
0.329370
Patch Statistics
Data code Number
patches
1 138
5 90
9 77
2 205
4 345
Largest
patch
9851
3781
33
631
70
N patches
<5 cells
110 ,
60
66
182
278
Avg patch
size
76.609
70.411
3.039
8.444
4.438
Overall values, not area-weighted:
855 9851 23.865
Proportion
5
0.9834
0.9858
0.5812
0.8458
0.7054
0.9470
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
T2LForZ7.wpd - 078Leb98
5: Human Use; 9: Water
-------
tJsX
f' | 11 '"" • ''' ; :, ' ' • ' -. ', ' i'' i ' 'l '
1 ; 1 ':, ,
LEGEND
1: Forest;
2: Forest Loss;
4: Forest Gain;
5: Human Use;
T2LForZ8.wpd - 078Leb98
9: Water
-------
Tensas River Basin - Forest Change Analysis Zone 9
LANDSTAT: Landscape Statistics Program, v. 7-94
Rflgiilts nf Pixel Analyzer
5 types found.
200588 pixels (non-missing).
505950 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
134423
24496
6039
32586
3044
Pixel Percent
0.67014
0.12212
0.03011
0.16245
0.01518
Number of edges and percent of same-type edges
Data code
5
2
4
1
9
Number edges
280756
57829
18850
73665
8265
Same-type percentage
0.900811
0.683602
0265517
0.756302
0.462795
Patch Statistics
Data code
5
2
4
1 '
9
Number
patches
413
1415
1964
993
228
Largest
patch
106774
3731
109
6286
729
N patches
<5 cells
312
1110
1679
715
168
Avg patch
size
325.479
17.312
3.075
32.816
13.351
Proportion
. 5
0.9964
0.9315
0.5753
0.9672
0.9067
Overall values, not area-weighted:
5013 106774 40.014 0.9697
T2LForZ9.wpd - 078Leb9S
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Ill
ifi I
|H
111
.
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li'i
tt
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Tensas River Basin - Wetland Restoration Analysis
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyser
5 types found.
1043906 pixels (non-missing).
2256442 pixels coded as missing.
Data Code
' 5
I. 2
4
i.
(. 1
;" 9
Pixel Count
652100
146646
30335
201389
13436
Pixel Percent
0.62467
0.14048
0.02906
0.19292
0.01287
Number of edges and percent of same-type edges
Data code
'
V 2
"•
:, 4
i
••
i
—
9
Number edges
1344920
327272
83052
433866
33469
Same-type percentage
0.930219
0.789948
0.446022
0.853519
0.596343
Patch Statistics
Data code Number
patches
5 1420
2 5034
4 6100
1 3207
9 932
Largest
patch
587999
21183
1574
99710
3006
N patches
<5 cells
1108
4058
5227
2320
722
Avg patch Proportion
size 5
459.225 0.9974
29.131 0.9577
4.973 0.7337
62.797 0.9818
14.416 0.9146
Overall values, not area-weighted:
16693 587999 62.536 0.9801
T2LWipFlwpd - 078Leb98
^LEGEND ;''"" "i;"1 "" ! ' ' ' '" ''" _ ;
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin - Wetland Restoration Analysis Zone 2
LANDSTAT: Landscape Statistics Program, v. 7-94
Results nf Pixel Analyser
5 types found.
15559 pixels (non-missing).
13349 pixels coded as missing.
Data Code
5
4
2
1
9
Pixel Count
12776
473
209
503
1598
Pixel Percent
0.82113
0.03040
0.01343
0.03233
0.10271
Number of edges and percent of same-type edges
Data code
5
4
2
1
9
Number edges
25877
1397
683
1397
3413
Same-type percentage
0.941415
0.342162
0.218155
0.437366
0.850864
Patch Statistics
Data code Number
patches
5 36
4 102
2 81
1 71
9 9
Largest
patch
12554
56
14
88
1574
N patches
<5 cells
21
80
64
54
5
Avg patch
size
354.889
4.637
2.580
7.085
177.556
Proportion
5
0.9970
0.7230
0.5742
0.8410
0.9956
Overall values, not area-weighted:
299 12554 52.037 0.9778
T2LW22.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
'T1
*;
!":"!'
IHK
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Tensas River Basin - Wetland Restoration Analysis Zone 3
LANDSTAT: Landscape Statistics Program, v. 7-94
Rp.gnlts nf Phrel Analyser
5 types found.
126076 pixels (non-missing).
1 15730 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
118781
3140
2210
1604
341
Pixel Percent
0.94214
0.02491
0.01753
0.01272
0.00270
i
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
240195
9303
5979
5008
936
Same-type
percentage
0.962235
0.321187
0.465295
0.264577
0.444444
Patch Statistics
Data code Number
patches
5 99
2 896
1 317
4 588
9 50
Largest
patch
118574
199
229
195
121
N patches
<5 cells
89
783
253
537
40
Avg patch
size
1199.808
3.504
6.972
2.728
6.820
Overall values, not area-weighted:
1950 118574 64.654
Proportion
5
0.9990
0.6325
0.8154
0.5006
0.8358
0.9799
LEGEND
1: Forest;
i i, .i *
T2LWz3.wpd - 078Leb98
2: Forest Loss;
4: Forest Gain;
5: Human Use; 9: Water
-------
Tensas River Basin - Wetland Restoration Analysis Zone 4
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Preal Analyser
5 types found.
256865 pixels (non-missing).
235938 pixels coded as missing.
Data Code
5
2
1
4
9
Pixel Count
184146
33844
26341
11848
686
Pixel Percent
0.71690
0.13176
0.10255
0.04613
0.00267
Number of edges and percent of same-type edges
Data code
5
2
1
4
9
Number edges
377554
75536
58623
28668
1901
Same-type
percentage
0.944336
0.787929
0.777971
0.629168
0.391899
Patch Statistics
Data code Number
patches
5 242
2 • 1188
1 641
4 1227
9 130
Largest
patch
180859
17264
11112
1502
113
N patches
<5 cells
181
976
435
1015
108
Avg patch
size
760.934
28.488
41.094
9.656
5.277
Overall values, not area-weighted:
3428 180859 74.931
Proportion
5
0.9984
0.9543
0.9715
0.8634
0.7522
0.9830
T2LWz4.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
An Ecotogicai Assessment of the Loiiisfana Tensas River Basin: Appendix
i ill
1 1*1
,i I i
•mi
lit!, J
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IT" • .1
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Tensas Rjyer Basin - Wetland Restoration Analysis Zone 5
LANIDSfAT: Landscape Statistics Program, v. T94
• "l"l'l!| ''„' , i1 " i", ' '. ' ',.' ' '!'' , . • ',i'»l'4l .. 1 ' ill, li,1 ,
'I'iii'ii': ..':
Results nf Pixel AnalyTer
5 types found.
171511 pixels (non-missing).
409927 pixels coded as missing.
Data Code
2
5
1
4
9
Pixel Count
30119
82039
54134
3869
1350
Pixel Percent
0.17561
0.47833
0.31563
0.02256
0.00787
Number of edges and percent of same-type edges
Data code
2
5
1
4
9
Number edges
64831
168118
111379
9945
3079
Same-type percentage
0.851013
0.927456
0.920227
0.481750
0.442676
Patch Statistics
Data code Number
patches
2 568
5 171
1 349
4 751
9 222
Largest
patch
8090
34533
16937
1587
120
N patches
<5 cells
424
128
226
643
157
Avg patch
size
53.026
479.760
155.112
5.152
6.081
Proportion
5
0.9759
0.9976
0.9929
0.7268
0.8007
Overall values, not area-weighted:
2061 34533 83.217 0.9846
1 il ',J.'i"'i" I,1
it;t! IE''
LEGEND
!!ll"'i ' 1:Forest;"
2: Forest Loss;
4: Forest Gain;
T2LWzS.wpd - 078Leb98
5: Human Use; 9: Water
-------
Tensas River Basin - Wetland Restoration Analysis Zone 6
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
5 types found.
30904 pixels (non-missing).
35048 pixels coded as missing.
Data Code
2
5
1
9
4
Pixel Count
3294
8736
18088
208
578
Pixel Percent
0.10659
0.28268
0.58530
0.00673
0.01870
Number of edges and percent of same-type edges
Data code
2
5
1
9
4
Number edges
7270
18187
36335
510
1680
Same-type percentage
0.794360
0.909441
0.941764
0.233333
0.252976
Patch Statistics
Data code Number
patches
2 134
5 38
1 148
9 99
4 220
Largest
patch
2233
6204
12910
30
54
N patches
<5 cells
113
30
124
93
201
Avg patch
size
24.582
229.895
122.216
2.101
2.627
Proportion
5
0.9502
0.9958
0.9896
0.3462
0.5000
Overall values, not area-weighted:
639 12910 48.363 0.9736
T2LWz6.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
; ,:;:: ",
Tensas River Basin - Wetland Restoration Analysis Zone 7
LANDSTAT: Landscape Statistics Program, v. 7-94
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Results of Pixel AnalyTer
5 types found.
20405 pixels (non-missing).
30431 pixels coded as missing.
Data
Code
1
5
9
2
4
Pixel Count
10416
5570
207
1448
2764
Pixel Percent
0.51046
0.27297
0.01014
0.07096
0.13546
Number of edges and percent of same-type edges
Data
code
1
5
9
2
4
Data code
1
5
9
2
4
Number edges
22018
12252
618
3833
7007
Same-type percentage
0.888364
0.745674
0.266990
0.504305
0.549451
Patch Statistics
Number
patches
120
91
74
210
307
Largest
patch
9786
3780
33
620
1315
Overall values, not area-weighted:
802 9786
N patches
<5 cells
100
58
65
188
251
Avg patch Proportion
size 5
86.800 0.9847
61.209 0.9847
2.797 0.5314
6.895 0.8004
9.003 0.8538
25.443 0.9493
1 i T.I. i
, ; T2LWz7,wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
Tensas River Basin - Wetland Restoration Analysis Zone 8
LANDSTAT: Landscape Statistics Program, v. 7-94
Results of Pixel Analyser
5 types found.
221426 pixels (non-missing).
2241 18 pixels coded as missing.
Data Code
1
2
5
4
9
Pixel Count
56488
51239
103493
4261
5945
Pixel Percent
0.25511
0.23140
0.46739
0.01924
0.02685
Number of edges and percent of same-type edges
Data
code
1
2
5
4
9
Data code
1
2
5
4
9
Number edges
120778
112422
216924
13786
13549
Same-type
percentage
0.860927
0.819075
0.898218
0.222690
0.698280
Patch Statistics
Number
patches
898
1400
546
1634
355
Largest
patch
27145
20356
88833
101
2965
N patches
<5 cells
706
1198
451
1469
298
Avg patch
size
62.904
36.599
189.548
2.608
16.746
Overall values, not area-weighted:
4833 88833 45.815
Proportion
5
0.9794
0.9659
0.9936
0.4799
0,9196
0.9717
T2LWz8.wpd - 078Leb98
LEGEND
1: Forest; 2: Forest Loss; 4: Forest Gain; 5: Human Use; 9: Water
-------
•'-^ £iXrk/fc>cdt Assessment of ths Louisiana Tensas River Basin: Appendix
lilt* , I Ill Ill Ill
,1 ',' . _
•it.,'
Tensas River Basin - Wetland Restoration Analysis Zone9
tANDSTAT: Landscape Statistics Progran£ v. 7-94
Results nf Pixel Analyzer
5 types found.
200588 pixels (non-missing).
505950 pixels coded as missing.
Data Code
5
2
4
1
9
Pixel Count
134408
24496
6054
32586
3044
Pixel Percent
0.67007
0.12212
0.03018
0.16245
0.01518
Number of edges and percent of same-type edges
Data code
5
2
4
1
9
Number edges
280727
57829
18883
73665
8265
Same-type percentage
0.900793
0.683602
0.266483
0.756302
0.462795
Patch Statistics
Data code
5
2
4
1
9
Number
patches
415
1415
1962
993
228
Largest
patch
106754
3731
109
6286
729
N patches
<5 cells
314
1110
1676
715
168
Avg patch
size
323.875
17.312
3.086
32.816
13.351
Proportion
5
0.9964
0.9315
0.5771
0.9672
0.9067
Overall values, not area-weighted:
5013 106754 40.014 0.9697
i, 1 ;,
a1!'
LEGEND
1: Forest;
"
2: Forest Loss;
4: Forest Gain;
: .ft- , .' .' || ' T2LWz9.wpd - 078Leb98
5: Human Use; 9: Water
Bill" ,"
if i?
-------
Summary Statistics for water quality parameters from three water quality monitoring stations
in the Tensas River Basin.
Station
Clayton
Clayton
Clayton
Clayton
Clayton
Clayton
Clayton
Clayton
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Season
Fall
Fall
Spring
Spring
Summer
Summer
Winter
Winter
Fall
Fall
Spring
Spring
Summer
Summer
Winter
Winter
Fall
Fall
Spring
Spring
Summer
Summer
Winter
Winter
Parameter
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
Nitrogen
Phosphorus
N
7
7
9
9
13
13
12
12
7
7
9
9
14
14
12
12
4
4
6
6
11
11
9
9
Mean Standard
Deviation
0.05
0.12
0.89
0.46
0.73
0.24
0.53
0.44
0.43
0.55
0.88
0.53
0.98
0.43
0.56
0.49
0.22
0.16
0.83
0.45
1.00
0.33
0.43
0.42
0.059
0.053
0.523
0.225
0.802
0.106
0.456
0.331
0.938
0.216
0.775
0.261
1.547
0.276
0.586
0.290
0.400
0.102
0.615
0.230
0.857
0.210
0.209
0.313
Maximum
0.18
0.23
1.98
0.89
2.53
0.44
1.86
1.26
2.55
0.96
2.50
1.07
5.90
1.04
2.25
1.10
0.82
0.31
1.63
0.72
2.54
0.85
0.66
1.13
Median
0.02
0.11
0.85
0.39
0.26
0.23
0.34
0.38
0.02
0.54
0.57
0.44
0.38
0.29
0.45
0.45
0.02
0.12
0.72
0.42
0.61
0.28
0.52
0.33
Minimum
0.02
0.08
0.25
0.24
0.02
0.03
0.22
0.09
0.02
0.22
0.02
0.24
0.02
0.18
0.01
0.00
0.02
0.09
0.21
0.10
0.01
0.06
0.08
0.13
-------
lilKiliilSS
Results ofWUcoxon Rank SumTest for Determining differences between water quality monitoring stations
Lit
i1: 1
LI!:
i'l :
W'ii1
ii III1.
i si1::
Compare Station to Station
Tendal
Tendal
Tendal
Tendal
Clayton
Clayton
Clayton
Clayton
Clayton
Clayton
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Clayton
Clayton
Clayton
Clayton
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Tendal
Clayton
Clayton
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Clayton
Clayton
Clayton
Clayton
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Winnsboro
Clayton
Clayton
Clayton
Clayton
Winnsboro
Winnsboro
Winnsboro
Parameter
Total Nitrogen
Total Phosphorus
Total Nitrogen
Total Phosphorus
Total Nitrogen
Total Phosphorus
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Nitrogen
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Total Phosphorus
Season
All Combined
All Combined
All Combined
All Combined
All Combined
All Combined
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Significantly Different
No
Yes
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
No
No
No
Yes
-------
Acknowledgements
The authors wish to express their thanks to the
authors of the U.S. EPA Report, "An Ecological
Assessment of the United States Mid-Atlantic Re-
gion: A Landscape Atlas," for the extensive use of
Chapters 1 and 2 from that document. The citation
for the above report is as follows:
Jones, K.B., K.H. Riitters, J.D. Wickham, R.D
Tankersley, Jr., R.V. O'Neill, D.J.
Chaloud, E.R. Smith, and A.C. Neale,
1997. An Ecological Assessment of
the United States Mid-Atlantic Region:
A Landscape Atlas U.S. EPA/ ORD,
EPA/600/R-97/130
The authors also would like to acknowledge the
following people and their contributions to this docu-
ment: Dr. Eugene Meier, Larinda Tervent, James E.
Seals, and the U.S. EPA Gulf of Mexico Program,
Kenneth Teague, U.S. EPA Region 6, Mike Adcock,
Tensas River Basin Coordinator, Mark Swan, The
Louisiana Nature Conservancy, Robert F. Carsel,
U.S. EPA, NERL, Athens, GA, Jan R. Boydsten,
Louisiana Dept. of Environmental Quality, Donna
Sutton, Lockheed/Martin Corp., Dan Sahagun, ATA
Corp., Deborah J. Chaloud, Don Ebert, Katie
Feldman and Tyrone Roach, U.S. EPA, NERL, Las
Vegas, NV. A special thanks goes to Pat Deliman
for use of several of his photographs of the Tensas
River Basin.
Notice
The purpose of this atlas is to show examples of how
the principles of landscape ecology can be applied in
a watershed-scale ecological assessment. The
examples do not constitute a definitive assessment
of ecological conditions in the Tensas River Basin.
The EPA, through its Office of Research and
Development (ORD), partially funded the research
described here under U.S. EPA contract #68-C5-
0065 to Lockheed/Martin Corporation. It has been
peer reviewed by the EPA and approval for publica-
tion. Mentions of trade names does not constitute
endorsement or recommendation for use.
-------
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-------
-------
1970s Classified Image,
Land Cover
1990s Classified Image,
Land Cover
Land Cover
BBJ Forest
Human Use
•• Water
------- |