United States

Department of

Agriculture

Forest Service

Southern

Research Station

General Technical

Report SRS–42

Bottomland Hardwoods of the

Mississippi Alluvial Valley:

Characteristics and Management

of Natural Function, Structure,

and Composition

Fayetteville, Arkansas

October 28, 1995
DISCLAIMER

The use of trade or firm names in this publication is for reader information and does not imply endorsement by the U.S.

Department of Agriculture of any product or service.

PESTICIDE PRECAUTIONARY STATEMENT

This publication reports research involving pesticides. It does not contain recommendations for their use, nor does it

imply that the uses discussed here have been registered. All uses of pesticides must be registered by appropriate

State and/or Federal agencies before they can be recommended.

CAUTION: Pesticides can be injurious to humans, domestic animals, desirable plants, and fish or other wildlife if they

are not handled or applied properly. Use all herbicides selectively and carefully. Follow recommended practices for the

disposal of surplus pesticides and their containers.

Papers published in these proceedings were submitted by authors in electronic media. Editing was done to ensure a

consistent format. Authors are responsible for content and accuracy of their individual papers.

July 2001

Southern Research Station

P.O. Box 2680

Asheville, NC 28802

Cover: Canopy and other forest vegetation in the Red Gum Research Natural Area (RNA) on the Delta

National Forest, Sharkey County, MS. Red gum, so called by early loggers in the deep South for the red

heartwood in old growth of this species, is one common name for sweetgum (Liquidambar styraciflua L.).

This RNA contains remnant old-growth bottomland hardwood forest that still is dominated by sweetgum.

Photo by Lynda Wyant.
i

Bottomland Hardwoods of the

Mississippi Alluvial Valley:

Characteristics and Management of

Natural Function, Structure, and

Composition

Proceedings of a Symposium

Held during

The Natural Areas Conference

Fayetteville, Arkansas

October 28, 1995

Paul B. Hamel and Thomas L. Foti, Technical Editors
ii

Preface

In October 1995 the symposium “Bottomland hardwoods of the Mississippi Alluvial Valley:

characteristics and management of natural function, structure, and composition,” was held

as part of the Natural Areas Conference in Fayetteville, AR. Dr. Scott Yaich, who now works

for the Arkansas Game and Fish Commission, organized the symposium to provide

managers with information necessary to restore composition, structure, and function to the

forested ecosystem of the Mississippi Alluvial Valley. Symposium participants included

managers of private, State, and Federal lands, as well as land management planners

across a range of public and private jurisdictions.

Symposium presenters were invited to submit manuscripts; and only one manuscript

previously had been submitted for journal publication (Kleiss, B.A. 1996. Sediment retention in a bottomland haradwood wetland in eastern Arkansas. Wetlands. 16(3): 321–333.).

Subsequent to the symposium, Dr. Yaich asked us to compile and complete this volume. We

acknowledge assistance provided by the many individuals who reviewed the submitted

manuscripts.

All but one of the papers presented here were peer-reviewed by individuals unknown to

the authors. That manuscript, the contribution of Dr. James T. Tanner who was then a

professor of Zoology at the University of Tennessee, is included because it reflects the

thinking of a biologist who studied the last extensive old-growth stand of bottomland

hardwoods in the Mississippi Alluvial Valley. Dr. Tanner died shortly after completing the

paper included in this volume.

Publication of these proceedings was underwritten by a grant made by the U.S. Fish and

Wildlife Service to the Arkansas Natural Heritage Commission and by the USDA Forest

Service, Southern Research Station.

—the editors

PEER REVIEW PROCESS

Each manuscript was reviewed by at least one and as many as three scientists selected by

the editors for their subject-matter expertise. When the compiling editors decided to accept

a submitted manuscript, they returned it and the peer reviews to the senior author, who

then revised and resubmitted it in a form suitable for printing. Although each paper has

been edited to reflect a uniform format and type style, responsibility for content and

accuracy remains with the individual authors.
iii

Table of Contents

Northern Arkansas Spring Precipitation Reconstructed from Tree Rings, 1023–1992 A.D.

Malcolm K. Cleaveland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Presettlement Forests of the Black Swamp Area, Cache River, Woodruff County, Arkansas

from Notes of the First Land Survey

Thomas L. Foti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Application of General Land Office Survey Notes to Bottomland Hardwood Ecosystem

Management and Restoration in the Lower Mississippi Valley—An Example from

Desha County, Arkansas

John L. Tingle, Charles V. Klimas, and Thomas L. Foti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Composition, Potential Old Growth, Fragmentation, and Ownership of Mississippi

Alluvial Valley Bottomland Hardwoods: A Regional Assessment of Historic Change

Victor A. Rudis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

The Effect of Herbivory by White-Tailed Deer and Additionally Swamp Rabbits

in an Old-Growth Bottomland Hardwood Forest

Margaret S. Devall, Bernard R. Parresol, and Winston P. Smith . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

A Comparison of Breeding Bird Communities and Habitat Features Between

Old-Growth and Second-Growth Bottomland Hardwood Forest

Winston P. Smith, Howard E. Hunt, and W. Kent Townley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Seasonal Habitat Distribution of Swamp Rabbits, White-Tailed Deer, and

Small Mammals in Old Growth and Managed Bottomland Hardwood Forests

Winston P. Smith and Patrick A. Zollner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Chainsaws, Canebrakes, and Cotton Fields: Sober Thoughts on Silviculture for

Songbirds in Bottomland Forests

Paul B. Hamel, James S. Meadows, Emile S. Gardiner, and John A. Stanturf . . . . . . . . . . . . . . . . . . . . 99

A Long-Term View of Old-Growth Deciduous Forests

James T. Tanner and Paul B. Hamel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

List of Corresponding Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
iv
1

NORTHERN ARKANSAS SPRING PRECIPITATION RECONSTRUCTED

FROM TREE RINGS, 1023-1992 A.D.

Malcolm K. Cleaveland1

Abstract—Three baldcypress (Taxodium distichum (L.) Rich.) tree-ring chronologies in northeastern Arkansas and

southeastern Missouri respond strongly to April-June (spring) rainfall in northern Arkansas. I used regression to

reconstruct an average of spring rainfall in the three climatic divisions of northern Arkansas since 1023 A.D. The

reconstruction was validated by comparing it to independent observed data. The reconstruction shows highly variable

hydroclimatic conditions in the past, with considerable long-term low frequency variation. Managers who wish to know the

“natural” state of ecosystems must consider ecosystem response to climate and the long-term changes in climatic

averages and variability that have shaped the adaptability of the ecosystems. This adaptability may translate into

resilience in the face of anthropogenic climate change.

1

 Tree-Ring Laboratory, Department of Geosciences, Division of Geography, University of Arkansas-Fayetteville, Fayetteville, AR 72701.

INTRODUCTION

Climate varies considerably, not only at high frequencies,

e.g., year-to-year, but at much lower frequencies, over

decades and centuries (Bradley 1999, Crowley and North

1991). The observed (instrumental) data, rarely much longer

than 100 years in the United States, give little insight into the

nature of such low frequency climate variability, such as the

occurrence of long duration extreme drought (e.g., Stahle

and others 2000). Annual rings from climate-sensitive trees

serve as proxies to investigate past climate (Cook and

others 1999, Fritts 1976, Stockton and others 1985). The

reconstruction presented here forms part of a network of

long spring precipitation reconstructions (Stahle and

Cleaveland 1992, 1996). Eventually these reconstructions

will cover most of the Southeastern United States and the

lower Mississippi Valley.

DATA

Tree-Ring Data

The tree-ring data come from baldcypress (a long-lived,

deciduous conifer) at three sites (fig. 1, table 1). The

samples were extracted with increment borers from many

trees at each site above the basal swelling, a nondestructive

sampling technique. Some cross-sections were cut from

down trees to extend chronologies into the past. Core

samples were glued into wooden mounts and the transverse

surfaces of all samples sanded until polished.

Trees may not grow a ring everywhere when stressed,

leaving a ring missing from the chronological sequence. On

the other hand, many trees will occasionally form false rings,

i.e., intra-annual features that look like real rings but create

an error if included in the chronological sequence (Fritts

1976, Stokes and Smiley 1996, Swetnam and others1985).

All samples were crossdated to detect false and missing

rings. Crossdating involves pattern matching between many

ring sequences at a site and nearby sites to ensure correct

dating of each ring (Stokes and Smiley 1996). The dated

series were then measured to 0.01 mm.

Tree-ring series contain nonclimatic growth trends that must

be removed to make them statistically stationary (Fritts

1976). I used program ARSTAN (Cook 1985, Cook and

others 1990) to fit an exponential curve declining to a

constant or a regression line to each series, then divided

each ring width by its corresponding curve value. The

dimensionless indices derived by this process have a mean

of 1.0 (eliminating differences in mean growth rates of the

series) and relatively stable variance. Because the negative

exponential curves and regression lines do an imperfect job

of detrending in many cases, I further detrended the indices

with a “stiff” cubic smoothing spline (Cook and Peters 1981,

Peters and Cook 1981). The flexibility of the smoothing

spline is controlled by setting a parameter equal to the

wavelength of a sine wave which will have 50 percent of its

variance removed by indexing (Cook 1985, Cook and Peters

1981, Peters and Cook 1981). For example, a 10-year spline

Figure 1—Locations of the tree-ring chronologies (table 1) used

to reconstruct total spring (April–June) precipitation averaged

from the three northern Arkansas climatic divisions.
2

would fit the variation in a time series much more closely

than a 100-year spline, the minimum stiffness used in

detrending indices.

Tree-ring series usually contain persistence caused by

physiology (Fritts 1976). Autoregressive (AR) modeling and

removal of the persistence (“whitening”) make the climatic

signal in tree rings clearer (Cook 1987, Meko 1981). The

individual detrended series were AR modeled with the

pooled multivariate AR model and the resulting whitened

series were then averaged with an algorithm that weights

values that fall near the mean higher than outliers (Cook

1985, Cook and others 1990). If significant AR persistence

remained in the average, the chronology was rewhitened.

The result was the “residual” chronology (Cook 1985). I

averaged the three residual chronologies together to form a

whitened regional tree-ring composite.

Climate Data

The precipitation data came from the National Climatic Data

Center (NCDC) Historical Climatology series (Karl and

others1983), a CD-ROM (NCDC n.d.) and updates to the

CD-ROM. Exploratory correlations with the 12 months from

the northern and central Arkansas and southern Missouri

climate divisions showed that April-June rainfall in the three

northern Arkansas climate divisions (Northwest, North

Central and Northeast; fig. 1) correlated best with growth of

the three tree-ring chronologies. Although the tree climate

divisions reconstructed contain none of the tree-ring

chronologies, they are nonetheless well correlated with the

averaged tree growth because the trees respond to broad

patterns of regional climate over hundreds of kilometers

(Cook and others 1996). Monthly precipitation from the three

northern Arkansas climatic divisions (fig. 1; NCDC n.d.) were

averaged 1895-1992. The average of the three divisions was

an AR-0 process, i.e., it contained no significant persistence

(SAS Institute Inc. 1993).

CALIBRATION, RECONSTRUCTION AND

VALIDATION

Calibration

Although the chronology average goes to 1992, I terminated

the calibration period in 1985 because only one of the three

chronologies extends further (table 1). I regressed (Draper

and Smith 1981, SAS Institute Inc. 1989b) the regional treering average against the northern Arkansas spring climate

average for 1895-1985 and for two subperiods, 1895-1939

and 1940-1985 (fig.2, table 2). The 1895-1985 calibration

equation used for reconstruction was:

 Yt = 113.7 + 241.7Xt

 (1)

where Yt

 is the total April-June rainfall for year t (average of

the three climate divisions) and Xt is the average of the three

residual chronologies. The results were excellent,

accounting for more than 64 percent of the climatic variance

1895–1985. The Durbin-Watson test (Draper and Smith

1981) showed the residuals from regression 1895-1985 to

be significantly serially correlated (r = 0.18), as were the

residuals 1940-1985 (r = 0.29). Nevertheless, inspection of

scatterplots of the residuals (not shown) appear to contain

no marked departures from linearity.

Reconstruction and Validation

The regression coefficients (eqn. 1) were applied to the

entire tree-ring series to produce estimates of spring rainfall

(fig. 3) from averaged annual growth. The other calibrations

Table 1—Characteristics of tree-ring chronologies used to reconstruct spring

(April-June) precipitation in northern Arkansas

Latitude/ Standard Radii/

Site/code name Datesa longitude deviation trees

All Lake, MO 1188–1992 360

,34’N 0.38 63/

 (ALL) 900

,29’W 32

Black Swamp, AR 1023–1980 350,09’N 0.39 61/

 (BSW) 910

,18’W 31

Bayou DeView, AR 1137–1985 340

,57’N 0.42 60/

 (DEV) 910,13’W 28

a Residual (whitened) chronology (Cook 1985, 1987).

Figure 2—Observed (dashed line) and reconstructed (solid line)

total spring (April-June) precipitation averaged from the three

northern Arkansas climatic divisions, 1895–1992 (Karl and others

1983, NCDC n.d.).
3

Table 2—Calibration and validation statistics for reconstruction of spring (April-June)

precipitation (mm) in northern Arkansas. B0

 and B1 are the intercept and slope of the

regression line, respectively. There is no significant difference (P > 0.05) between the

parameters in the two subperiods, 1895-1939 and 1940-1985

Calibration Residual

period R2adja B0 B1 autocorrelationb

1895-1985 0.644 113.7 241.7 0.18*

1895-1939 .673 107.2 250.4 .06NS

1940-1985 .604 120.2 233.5 .29*

Validation t-test diff. Sign test Reduction

period Correlationc of meansd +/-e of errorf

1940-1985 .783*** .02NS 36/9*** .62

1895-1939 .825*** .00NS 36/9*** .68

* = P < 0.05; *** = P < 0.001; NS = P > 0.05, not significant

a Multiple correlation coefficient adjusted for loss of degrees of freedom (Draper and Smith 1981).

b Autocorrelation of residual tested with the Durbin-Watson statistic (Draper and Smith 1981, Neter and

Wasserman 1974).

c Pearson product-moment correlation coefficient (Steel and Torrie 1980).

d Two-tailed paired observation test of difference between observed and reconstructed precipitation means

(Steel and Torrie 1980); failure to find a significant difference is a good result.

e One-tailed test on the agreement between signs of departures from the means of the observed and

reconstructed series (Conover 1980); positive shows agreement on the direction of the departures.

f

The reduction of error statistic varies between negative infinity and positive 1.0; any positive number

indicates skill at recovering paleoclimatic information (Fritts 1976).

Figure 3—Reconstructed total spring (April-June) precipitation averaged from the three northern Arkansas climatic divisions,

1023–1992.
4

permitted validation of the series, because the observed

data not used in the short calibrations could be tested for

accuracy (Snee 1977). All tests of model estimates versus

independent data indicate that the models have been

validated (table 2). In addition, tests of the regression

coefficients verify their essential equality in the two

subperiods (Neter and Wasserman 1974, SAS Institute Inc.

1989a). The reconstruction variance appears quite high in

the earliest three and a half centuries (fig. 3). This is

probably an artifact of lower sample size in the early part of

the time series, not a real phenomenon.

CLIMATIC VARIATION

It has been shown that average drought indices may vary

over periods of several decades (Stahle and Cleaveland

1992, Stahle and others1988, 2000). Climate variability may

also change considerably over decades (e.g., Cleaveland

and others 1992, Cleaveland and Stahle 1996). One way of

visualizing changes of climate is through cubic spline

smoothing curves like those used to detrend tree-ring growth

series. Figure 4 shows 10- and 30-year cubic spline curves

for observed and reconstructed spring precipitation 1895-

1992. The low frequency curves agree in their main features,

although the last 30 years of the 30-year splines appear to

be at least partially out of phase.

The spline curves offer insight into past variation (fig. 5). The

addition of a very stiff 100-year spline derived from the long

reconstruction shows quite clearly that there are centurylong average-to-dry periods (e.g., 1100-1250 and 1370-

1500; fig. 5) that might be expected during the Medieval

Warm Period usually set from the ninth to the fourteenth or

mid-fifteenth centuries (Hughes and Diaz 1994). On the

other hand, in some places the Medieval Warm Period may

have been both warmer and wetter than present, e.g., the

Colorado Plateau in the southwestern United States

(Petersen 1994). Petersen (1994) also characterizes the

Little Ice Age (ca. 1500-1850) as colder and drier than

present conditions in that region. This appears to have been

a period of low variability in northern Arkansas, but the

period 1645-1715, usually thought of as the heart of the

Little Ice Age (Frenzel and others 1994) does not appear to

have been anomalously dry (fig. 5). Stahle and others (2000)

postulate a very long, extremely severe “megadrought” in the

last half of the sixteenth century that appears to have

affected northern Mexico and much of the United States. A

very bad drought occurs in northern Arkansas during this

period (fig. 5).

Changes in variability and occurrence of extremes occur

throughout the reconstruction. Two conspicuous periods of

few extremes and low variability shown by the 10- and 30-

year splines are ca. 1480-1550 and 1670-1810 (fig. 5). The

twentieth century appears to have been a period of average

to above average rainfall in northern Arkansas.

Another way to investigate the variability of climate is to look

at the distribution of extremes. In table 3 the 100 wettest and

100 driest years (20.6 percent of the 970 reconstructed

years) were classified by which century they fell into. The

twentieth, eleventh and fourteenth centuries had more

extremes than the other centuries. The balance was very

different, however. The twentieth century had many more dry

extemes than wet (18/9), while the eleventh century had 11

dry and 16 wet extemes. It is interesting to note that

although most of the twentieth century 100-year spline curve

is above average (fig. 5), this century has twice as many dry

extemes as wet. The directions of anomalies in the

smoothed curves do not necessarily govern the directions of

anomalies in extreme values.

SUMMARY AND CONCLUSIONS

I used an average of three long tree-ring chronologies to

reconstruct spring (April-June) total precipitation averaged

from the three northern Arkansas climatic divisions. Treering growth accounted for more than 64 percent of the

climatic variance 1895-1985 and the regression model

validated well against independent data.

Past spring precipitation varied considerably through time,

with averages of long periods above and below the modern

mean values. Several prolonged periods of drought

exceeding anything in the twentieth century appear to have

occurred in the past. The occurrence of extreme wet and dry

years was unevenly distributed through time. Variability

Table 3—The reconstructed wettest and driest springs

(April-June) in northern Arkansas, 1023–1992

Century Wet Dry Total

11th (1023–1100) 16 11 27

12th (1101–1200) 10 12 22

13th (1201–1300) 6 6 12

14th (1301–1400) 14 11 25

15th (1401–1500) 7 6 13

16th (1501–1600) 9 6 15

17th (1601–1700) 12 5 17

18th (1701–1800) 6 14 20

19th (1801–1900) 11 11 22

20th (1901–1992) 9 18 27

Figure 4—Smoothing spline curves showing variation from the

long-term mean of observed and reconstructed total spring (April–

June) precipitation averaged from the three northern Arkansas

climatic divisions, 1895–1992.
5

occurs on all scales, from year-to-year to centuries.

Managers of natural areas can add another source of

disturbance to their list of influences in the ecosystems they

work with: Natural Climatic Change. However, ecosystems

that have not been degraded may show a surprising degree

of adaptability to anthropogenic change in climate (e.g.,

Houghton and others 1996), because those ecosystems

have evolved with the highly variable climatic states seen in

the reconstruction. This adaptation to climatic change is

apparently a major source of biological diversity in

ecosystems and ecosystems depend on biodiversity for their

adaptive responses (McCann and others 1998, Polis 1998).

ACKNOWLEDGMENTS

I am grateful to the agencies that funded this research and

have supported the University of Arkansas-Fayetteville TreeRing Laboratory: The National Science Foundation Climate

Dynamics Program (grants ATM-8914561 and ATM9222506) and the National Park Service Global Change

Program (which has since been transferred to the U.S.

Geological Survey) (cooperative agreement CA6000-1-

8013). The Department of Interior Fish and Wildlife Service

sponsored my attendance at the 22nd Natural Areas

Conference and invited me to present this paper in the

Symposium on Bottomland Hardwoods of the Mississippi

Alluvial Valley. I also thank the reviewers who suggested

improvements to the paper.

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America. Eos, Transactions American Geophysical Union. 81:

121,125.

Steel, R.G.D.; Torrie, J.H. 1980. Principles and procedures of

statistics, 2d ed. New York: McGraw-Hill. 633 p.

Stockton, C.W.; Boggess, W.R.; Meko, D.M. 1985. Climate and

tree rings. In: Hecht, A.D., ed. Paleoclimatic analysis and

modeling. New York: John Wiley & Sons: 71–161.

Stokes, M.A.; Smiley, T.L. 1996. An introduction to tree-ring dating.

Tucson, AZ: University of Arizona Press. 73 p.

Swetnam, T.W.; Thompson, M.A.; Sutherland, E.K. 1985. Using

dendrochronology to measure radial growth of defoliated trees.

Agric. Handb. 639. Washington, DC: U.S. Department of

Agriculture Forest Service, Cooperative State Research Service.

39 p.
7

PRESETTLEMENT FORESTS OF THE BLACK SWAMP AREA,

CACHE RIVER, WOODRUFF COUNTY, ARKANSAS, FROM NOTES

OF THE FIRST LAND SURVEY

Thomas L. Foti1

Abstract—Relationships between forest vegetation and soil were reconstructed from field notes of the 1846 Public Land

Survey (PLS) along a portion of the Cache River including Black Swamp. Locations of corners were digitized along with

species, diameter, and distance from section or quarter-section corners. Trees were grouped for analysis according to

occurrence on groups of ecologically meaningful soil units (similar texture, flood frequency and saturation) using a

digitized county soil map. Trees occurring at corners were treated as point-quarter samples to calculate density and

dominance; these and relative abundance were used to calculate importance value (IV). Five bottomland and two upland

types were defined, based on ecological distinctions in site characteristics. Based on ordination by Detrended

Correspondence Analysis, these were shown to occupy a moisture gradient from frequently flooded bottomlands, through

less flooded and better-drained bottomlands to well-drained uplands and dry uplands. These types are analyzed to allow

restoration biologists maximum flexibility in using them in setting or analyzing restoration goals. One bottomland type

occurred on sites where hydrologic regime has been altered by flood control levees to the extent that restoration to the

presettlement forest is no longer possible. One of the upland types has not been previously documented and may have

been primary habitat for a now-rare plant species, Cyperus grayoides Mohlenbrock.

1

 Chief of Research, Arkansas Natural Heritage Commission, Little Rock, AR.

INTRODUCTION

Clearing, drainage and other forms of ecosystem alteration

have been and continue to be extensive in the Mississippi

Alluvial Plain. Currently, national and international attention

is being given to restoration and management needs within

this region, such as the North American Waterfowl

Management Plan (Arkansas Game and Fish Commission

1988). A number of programs exist that encourage

reforestation within the region, perhaps most significantly the

USDA Wetland Reserve Program and Conservation Reserve

Program. In the Arkansas portion of the region (“the

Arkansas Delta”) State and Federal agencies as well as

private organizations are actively acquiring land, most

extensively for addition to the Cache River National Wildlife

Refuge and White River National Wildlife Refuge.

On these newly acquired public lands, reforestation is

occurring as needed. On Federal lands, ecosystem

management is emphasized, that attempts to “. . . restore

and sustain ecosystem integrity (composition, structure and

function) and produce ecologically acceptable levels of

sustainable multiple uses (U.S. Fish & Wildlife Service 1994).

Such a management strategy implicitly requires knowledge

of baseline ecological conditions against which to compare

management alternatives.

Surveyors’ notes compiled during the Public Land Survey

(PLS) conducted by the General Land Office (GLO) in the

19th Century provide the only systematic survey of the

vegetation of the mid-continent during that time, prior to

massive timber cutting and settlement. When correlated with

physical site characteristics, 19th century vegetation data can

be used to develop understanding of and models of plant

community composition and structure, as well as distribution

on the landscape (Bourdo 1956).

A model of early vegetation of an area does not define a

restoration or management goal; it is necessarily incomplete

and uncertain. Conditions controlling vegetation may have

changed or current needs may preclude restoration to this

vegetation. However, even under these circumstances the

model is useful in providing one baseline to be used in

evaluating the feasibility of and progress toward such a goal.

The primary purpose of this study was to use existing

surveyor’s notes to develop a model of early vegetation of

Black Swamp. A secondary objective was to undertake an

initial assessment of the utility of the model to assist in

development of reasonable goals for ecosystem restoration

in the Lower Mississippi Alluvial Valley in eastern Arkansas.

METHODS

Study Area

The study area selected was Township 6 North, Range 3

West (T6NR3W or The Township) along the Cache River

(fig. 1). Acquisition is actively underway in this area for the

Cache River National Wildlife Refuge. The study area

includes a portion of the Arkansas Game and Fish

Commission Black Swamp/Rex Hancock Wildlife

Management Area, designated under the Ramsar

Convention as Wetlands of International Importance. The

Arkansas Natural Heritage Commission (ANHC) holds a

conservation easement on a part of the Wildlife

Management Area. The study area includes naturally

forested wetlands as well as cleared and farmed

bottomlands and uplands. This area was chosen partly

because of the availability of Geographic Information System

(GIS) data layers and other digital data that facilitate the

spatial analysis of GLO data.
8

The Cache River is the longest tributary of the White River

that lies entirely within the Mississippi Alluvial Plain. In the

study area, it and its floodplain are usually distinctively

incised below the level of the surrounding uplands, but

natural levees and terraces within and above the floodplain

create variations in flood depth, duration and frequency.

Soils and geological substrate of the uplands vary from

poorly drained clay flats to productive loamy and sandy

upland soils to excessively drained sandy hills. A variety of

upland and bottomland vegetation types occur in

relationship to flood regime, soil characteristics and other

physical features. On lowest, semi-permanently flooded sites

is black swamp itself, dominated by water tupelo (Nyssa

aquatica L.), with baldcypress (Taxodium distichum (L.)

Rich.) common along watercourses. Buttonbush

(Cephalanthus occidentalis L.) is a common shrub species.

On higher bottoms are areas dominated by overcup oak

(Quercus lyrata Walt.), Nuttall oak (Q. texana Buckl.), willow

oak (Q. phellos L.) and others. Upland forests have generally

been cleared for row-crop agriculture, principally soybeans

and rice.

VEGETATION SAMPLING

I obtained survey notes on T6NR3W from the office of the

Arkansas State Land Commissioner. David Garretson

surveyed The Township in 1846.

Surveyors of the PLS traversed the western and northern

sides of each section of 1 mile (1.6 km) square, which were

organized into townships of 6 by 6 sections. They

monumented corners of each section and gave the distance

and direction to a tree in each quadrant of the compass (four

trees). Species and sizes of these witness or bearing trees

were noted. At the halfway point of each side of each section

the surveyor marked the “quarter corner” and noted distance

and direction to a witness tree of stated species and size

north and south of the monument (two trees). The surveyor

also noted two additional “line trees” along each side and

recorded species and size. Crossing points of major

features, such as rivers, canebrakes, etc. were located. At

the end of the traverse of each side (1 mi or 1.6 km) the

quality of the land, the kind of “timber” and the “undergrowth”

characteristic of the mile were noted.

Plant identification by the surveyors was in some cases

problematical. The identity of “cucumber” is unknown.

Although cucumber magnolia (Magnolia acuminata L.)

occurs in Arkansas, it does not occur on sites similar to

those in the study area. The identity of “black oak” in the

survey notes is an important question of identification. This

name is recorded in most of the communities identified here,

in both bottomlands and uplands. Black oak (Quercus

velutina Lam.) does occur on upland sites in the vicinity of

the study area, but not in bottomlands. It is likely that in

bottomlands the term black oak in the notes refers to Nuttall

oak (Q. texana Buckl.), which was not described for more

than 85 years after this survey; to cherrybark oak (Q. pagoda

Ell.), or possibly even to water oak (Q. nigra L.). In the

Figure 1—Location of the study area.

Study area

Little Rock

Memphis
9

uplands the term may apply either to black oak or to

southern red oak (Q. falcata Michx.); in 19th-century

contemporary surveys the latter was usually referred to as

“Spanish Oak.” I take “white oak” to mean Q. alba L., but the

name occurs in the notes not only in upland forests, but also

on bottomland forests, where Q. alba should not occur. This

is particularly problematic to interpret; both swamp white oak

(Q. michauxii Nutt., not Q. bicolor Willd., which does not

occur in Arkansas) and overcup oak (Q. lyrata Walt.) are

recognized by the surveyor. However, the name “swamp

white oak” occurred only one time (in MCCROR, one of the

wettest community types). Therefore, my assumption is that

the term “white oak” means Q. michauxii Nutt. in the bottoms

and Q. alba L. in the uplands. “Pin oak” in the lists may refer

to Q. palustris, or perhaps to another of the red oaks, such

as Nuttall oak. Although willow oak (Q. phellos L.) is often

called pin oak locally, willow oak was recognized separately

by the surveyor. These uncertainties will be discussed

further in community descriptions. Spelling of common

names in the descriptions that follow will be that of the

surveyor, rather than an assumed accepted common name

or scientific name.

Further difficulties occur in interpreting the importance of

cypress and tupelo. Instructions to surveyors were unclear

as to where the diameter of trees was to be measured, but

there is a mention of diameter at the base (White 1983).

Even if diameter were measured at breast height, the

diameter and consequently basal area and IV of species

with buttressed or swollen bases, such as cypress and

tupelo, would have been exaggerated.

ANALYSIS PROCEDURES

Universal Transverse Mercatur (UTM) positions of 49 section

corners were determined from USGS topographic maps. The

UTM coordinates of the quarter-corners, line trees and

distinctive features were calculated from the surveyor’s

noted direction and distance from each section corner.

Locations of 455 trees were digitized. For one location, a

cypress knee was used as a line marker, but since it was not

a “tree” and no diameter or distance was noted, it was not

included in the data set for analysis. The locations were

read into a sites file in GRASS geographic information

system.

Recorded distances and directions from points to trees of

recorded species and size allowed use of the point-quarter

sample method (Cottam and Curtis 1956) to estimate

species composition, density and basal area.

In this study area a digitized map of soil series (map units)

produced by the University of Arkansas in cooperation with

the USDA Natural Resources Conservation Service served

as the primary physical basis for sorting trees into potentially

distinguishable communities. A digital map of the floodplains

of the 1-, 3- and 100-year frequency floods developed by the

U.S. Army Corps of Engineers provided an additional

physical basis for grouping GLO trees. To simplify analysis, I

aggregated the 39 soil map units into a smaller set of

ecologically meaningful and distinct groups. The bottomland

groups were distinguished based on duration of inundation

or saturation of the soil series, based on descriptions in the

county soil survey. Upland soil groups included a group of

sandy loam soils along with soils of well drained natural

levees and soils with sodium or magnesium salts (termed in

the analyses “natric” soils), all of which have dry-mesic

character. A separate upland group consisted of soil of

loamy fine sand (one soil only—Bulltown) that is xeric.

I sorted trees into groups based on physical features (soil

series or groups of series) important in plant community

distribution. I used all trees from each data source (corner,

quarter-corner and line) to calculate relative abundance and

relative basal area (relative dominance). In the case of

section corners and quarter corners where distance data

were recorded, I calculated additional quantitative measures

of forest structure, including absolute and relative density,

absolute and relative basal area and geometric mean

diameter, the diameter at which mean basal area occurs. I

calculated importance value for each species within each

group as the averaged sum of relative abundance and

relative basal area calculated from all trees, and relative

density based only on corner trees (IV = [RA + RBA

+ RD]/3).

I used relationships among the groups analyzed by

multivariate statistical analysis: Detrended Correspondence

Analysis (DCA or DECORANA; Hill and Gauch 1980) placed

the communities along a continuum based on species

composition.

In the discussions that follow, density and diameter are

sometimes given. These are not included in the tables that

follow, but are available from the author.

RESULTS

The Township includes 12,597 ha (31,131 ac), of which 15

percent lies within the 1-year floodplain, 28 percent within

the 3-year floodplain and 70 percent within the 100-year

floodplain of the Cache River and tributaries.

Forest Over the Entire Study Area

The surveyor recorded 31 genera or species in The

Township (table 1 includes scientific names). Most of these

are common taxa in the area today, but a few are uncertain.

Over the whole study area (table 2), cypress was the most

important species with an IV of 16.6 percent, followed by

white oak at 12.6 and tupelo gum at 11.2, the only other

species with IV > 10. Sweet gum, ash, black oak, elm and

hickory had IV’s between 5 and 10. White oak was the most

numerous species with 64 individuals recorded, followed by

ash, sweet gum, tupelo gum, black oak, elm, cypress, and

hickory. On corners with measured distances to witness

trees, ash and white oak had the greatest density of 12.7 per

ha (5.1 per ac) each, followed by sweet gum and tupelo

gum; average density computed from all corner and quarter

corner trees was 114/ha (45.6 per ac). Cypress had the

largest mean diameter at 75 cm (30"), followed by white oak,

sweet gum, black walnut (one tree only) and tupelo gum.

While only white oak compares in importance with cypress

and tupelo, and only these three have IV > 10, it is important

to note that the combined IV of all oaks is virtually identical

to that of cypress and tupelo combined. Thus, the forest of

The Township may be described as cypress-tupelo-oak on

wetter sites and oak-mixed hardwoods on drier sites.
10

DEFINITION OF SOIL GROUPS FOR

VEGETATION ANALYSIS

Thirty-nine soil map units (plus water) occur in the township

and GLO survey trees occurred on 27 of these. These 27

soil map units were aggregated into 7 soil groups (see table

3 for the codes by which the groups are referred to

elsewhere). No GLO trees occurred on 12 soil series (table

4). These are not included in the analysis, but have been

aggregated in mapping. In aggregate they cover about 7

percent of the study area.

Analysis of Soil/Vegetation Groups

The distribution in the study area of the following soil/

vegetation types, even in generalized form, is a complex one

(fig. 2). Tree species listed as “most important” below are the

ones with IV > 10 percent.

TUCKER Forest (Tupelo-Cypress)—Tuckerman silty clay

loam occurs in the lowest bottoms, immediately adjacent to

the Cache River within the floodplain (fig. 2). The group

includes a few trees on small watercourses outside the

floodplain of the Cache River. A total of 91 trees of 16

species were recorded on this soil. The most important trees

were tupelo gum and cypress (table 2). Tupelo gum was the

most numerous species followed by cypress and overcup

oak. Total density was 120 per ha (48 per ac), with tupelo

gum having the highest density followed by persimmon and

overcup oak. Cypress had largest mean diameter, followed

by tupelo gum and white oak (2 trees only).

KOBFRQ Forest (Cypress-Oak-Tupelo-Maple)—This

group is primarily comprised of Kobel frequently flooded

soils that occur primarily below Black Swamp in the

floodplain of the Cache River (fig. 2). A total of 21 trees of 13

species were recorded. The most important trees were

cypress followed by white oak (presumed Q. michauxii

Nutt.), tupelo gum and maple. No species were particularly

abundant, with all species having from one to three

occurrences in the data set. White oak, tupelo gum and

maple had higher density than other species, and the total

density was 175 per ha (70 per ac), the second-highest of

the site types. Cypress had the greatest mean diameter,

followed by swamp white oak (one tree only) and tupelo

gum.

MCCROR Forest (Cypress-Sweetgum-Ash-Oak)—

McCrory fine sandy loam soil occurs primarily east of and

within the floodplain of the Cache River (fig. 2), on terraces

slightly elevated above the adjacent Tuckerman soil. A total

of 59 trees of 13 species were recorded on this site type.

The most important were cypress, followed by sweet gum,

ash, white oak (presumed Q. michauxii Nutt.) and overcup

oak. Cypress was the most abundant species, followed by

sweet gum, white oak, overcup oak and ash. Ash and sweet

gum had the highest density, and the total density of 122 per

ha (49 per ac) was moderate in comparison to other types.

Cypress had the greatest mean diameter, followed by white

oak and sweet gum.

KOBLEV Forest (Oak-Sweetgum-Ash-Cypress)—The

principal soil of this group is Kobel silty clay loam, ponded. It

occurs primarily west of the Cache River. The several other

soil mapping units that are found on poorly drained natural

levees are distributed primarily as linear bands within larger

areas of Kobel frequently flooded soil and Kobel ponded soil.

They occur elsewhere in the Cache floodplain and in the

uplands along watercourses as well. A total of 117 trees

occurred on these sites. The most important tree species

was white oak (presumed Q. michauxii Nutt.), followed by

sweetgum, ash and cypress. The most abundant species

was white oak, followed by ash, sweet gum and elm. Ash

had the highest density followed by white oak and

sweetgum. Cypress had the greatest mean diameter,

followed by sweet gum and tupelo gum. “Black oak” in this

type was probably Q. pagoda Ell. or Q. texana Buckl.

ASKEW Forest (Sweetgum-Ash-Elm-Hackberry)—Askew

fine silt loam is found on small, elevated areas within the

floodplain of the Cache River, generally surrounded by Kobel

or McCrory soil (fig. 2). A total of only 9 trees of 7 species

were recorded on these sites (table 2), but they were

analyzed separately because of the distinctive differences in

site characteristics. The most important tree species was

sweet gum, followed by ash, elm, and hackberry. Ash and

Table 1—Common names of tree species as recorded by

surveyor with scientific names of presumed actual taxa

Common name (scientific names)

Ash (Fraxinus L. sp. - F. pennsylvanica Marsh, F.

americana L.)

Black gum (Nyssa sylvatica Marsh)

Black oak (Quercus velutina Lam., Q. falcata Michx.,

Q. texana Buckley, Q. pagoda Ell.; see text)

Black walnut (Juglans nigra L.)

Box elder (Acer negundo L.)

Cherry (Prunus serotina Ehrh.)

Cucumber (identification uncertain, see text)

Cypress (Taxodium distichum (L.) Rich.)

Dogwood (Cornus florida L.)

Elm (Ulmus L.sp. - U. americana L.)

Hackberry (Celtis laevigata Willd.)

Hickory (Carya Nuttall sp.)

Horn beam (Carpinus caroliniana Walt.)

Locust (Gleditsia L. sp. or Robinia L. sp.)

Maple (Acer L. sp. - A. rubrum L., A. saccharinum L.)

Mulberry (Morus rubra L.)

Overcup oak (Quercus lyrata Walt.)

Pawpaw (Asimina triloba (L.) Dunal)

Pecan (Carya illinoensis (Wang) K. Koch)

Persimmon (Diospyros virginiana L.)

Pin oak (Quercus palustris Muench, Q. texana Buckley)

Post oak (Quercus stellata Wang.)

Red bud (Cercis canadensis L.)

Sassafras (Sassafras albidum (Nutt.) Nees)

Slippery elm (Ulmus rubra Muhl.)

Swamp elm (Planera aquatica (Walt.) Gmelin)

Swamp white oak (Quercus michauxii? Nutt.)

Sweet gum (Liquidambar styraciflua L.)

Tupelo gum (Nyssa aquatica L.)

White oak (Quercus alba L., Q. michauxii Nutt., see text)

Willow oak (Quercus phellos L.)
11

sweet gum were the only species to have 2 individuals in the

data set. The total density was the highest of any of the site

types at 407 per ha (163 per ac), but this is based on only 3

corners. Sweet gum had the largest mean diameter among

the species.

UPLAND Forest (White Oak-Black Oak-HickorySweetgum)—This group, including well-drained natural

levees, upland loamy and natric soils (table 3), occurs

outside the floodplain on both sides of the Cache (fig. 2). It

contains areas that are poorly drained bottomlands and the

following excessively well-drained xeric type. Soils in this

group are typically well drained. For this analysis it was not

possible to eliminate all the poorly drained areas. A total of

137 trees of 17 species occurred on these sites (table 2).

The most important species were white oak (probably Q.

alba L.) and black oak (probably Q. velutina Lam. on these

dry sites, or Q. falcata Michx.), followed by hickory and

sweetgum. Most abundant trees were white oak and black

oak, followed by hickory, elm, sweetgum, and dogwood.

Black oak, white oak and elm had the highest density; the

total density of 116 per ha (47 per ac) was moderate. Black

walnut, post oak and willow oak had greatest mean

diameter.

UPSAND Forest (Black Oak-White Oak-Post Oak-Hickory

Woodland)—This type was comprised of one soil only -

Bulltown loamy fine sand. These sites are generally

excessively well drained, leading to droughty conditions. A

total of 21 trees of 6 species occurred on these sites (table

2). Overall density of the forest (34 per ha or 14 per ac),

characterizes it as a woodland or savanna. The most

Table 2—Importance values of trees of the soil/vegetation groupsa b

 Soil type / forest group

Species TUCKER KOBFRQ MCCROR KOBLEV ASKEW UPLAND UPSAND ALL

Tupelo gum 35.9 11.3 4.6 11.2

Cypress 25.0 25.0 31.3 10.1 16.7

Overcup oak 8.1 4.5 10.6 4.3 0.8 4.6

Persimmon 8.0 2.3 2.9 2.6

Ash 5.8 12.1 12.9 20.3 5.4 7.9

Pecan 2.7 6.5 2.3 1.0 1.4

Elm 2.7 4.5 6.7 6.4 10.6 9.0 5.8

Maple 2.4 10.0 4.0 2.0

White oak 1.9 11.8 11.9 17.4 4.2 21.0 21.3 12.6

Swamp elm 1.8 3.0 .7 .9

Willow oak 1.3 2.1 .8 1.7 .1

Locust 1.0 .7 1.4 .7

Pin oak .9 2.3 .7 .4

Hackberry.9 4.1 1.5 1.8 10.0 1.2

Black gum .9 2.2 5.1 1.9

Sweet gum .6 4.9 15.4 13.9 44.5 10.6 8.4 9.4

Swamp white oak 6.6 .3

Hickory6.1 4.5 6.2 11.9 14.8 5.3

Cucumber 1.6 .4

Black oak 6.3 18.9 26.4 7.4

Sassafras 1.5 .6 .6

Red bud .7 .2

Horn beam .6 4.1 .2

Pawpaw .7 .9 .2

Box elder .6 2.3 .7

Dogwood 6.1 9.3 2.2

Mulberry 1.7 .5

Black walnut .9 .2

Post oak .9 19.7 1.0

Cherry .6 .2

Slippery elm 1.4 .4

 Total trees 91 21 59 117 9 137 21 455

 Corner trees 68 14 38 90 6 90 18 324

a

 Detailed data on which the IV's are based are available from the author.

b In calculations of IV, relative abundance was based on all trees in the database, while relative basal area and relative density were

based on corner trees only.
12

Table 3—Soil groups used in analysis, with descriptions of constituent soils

Code – Name

 Texture, slope, hydrology, location, landform Hydric? Ac Ha

 TUCKER – Tuckerman

Tuckerman SiClLm, 0–1 percent, frqfld, fldpln Yes 3,753 1519

Tuckerman FnSaLm, 0–1 percent, frqfld, sm drains Yes 870 352

Tichnor SiLm, 0–1 percent, frqfld, fldpln Yes 74 30

KOBFRQ – Kobel silty clay loam

Kobel SiClLm, 0–1 percent, frqfld, Cache backswamp Yes 2,621 1061

MCCROR – McCrory fine sandy loam

McCrory FnSaLm, 0–1 percent Cache terraces Yes 3,663 1482

KOBLEV – Kobel and poorly drained natural levees

Kobel SiClLm, 0–1 percent, ponded, Cache backswamp Yes 1,910 773

Arrington SiLm, 0–3 percent, rarely fld No 198 80

Yankopin (Commerce) SiClLm, <3 percent, rarely fld No 845 342

Yankopin (Commerce) SiClLm, 0–3 percent, frqfld No 1,275 516

Dundee SiLm, 0–1 percent No 271 110

Amagon SiLm, 0–1 percent, terraces Yes 326 132

Forestdale SiClLm, –1 percent, frqfld, fldpln Yes 332 134

ASKEW – Askew fine sandy loam

Askew FnSaLm, 1–3 percent, knolls in bottoms No 930 376

UPLAND – Various

Well-drained natural levee

Dubbs SiLm, 0–1 percent No 153 62

Bosket FnSaLm, 0–1 percent No 345 140

Bosket FnSaLm, 1–3 percent No 1,024 414

Bosket FnSaLm, 3–8 percent No 412 167

Natric – sodium or magnesium Salt

Lafe SiLm, 0–1 percent No 16 6

Hillemann SiLm, 0-1 percent No 46 19

Foley-Bonn complex, 0–1 percent No 419 169

Grubbs SiLm,1–3 percent No 790 320

Grubbs SiLm, 3–8 percent, eroded No 464 188

Grenada SiLm, 1–3 percent No 540 218

 Upland sandy loam

Wiville FnSaLm, 0–1 percent, near Bulltown No 2,493 1009

Wiville FnSaLm, 1–3 percent, on edge of bottoms No 1,902 770

Wiville FnSaLm, 3–8 percent, on edge of bottoms No 373 151

UPSAND – loamy fine sand

Bulltown LmFnSa, 1–8 percent, on dunes No 2,067 836

Cl = clay(ey); fld = flood(ed); Fn = fine; frq = frequently; Lm = loam(y); pln = plain; Sa = sand(y); Si = silt(y);

sm = small.
13

Table 4—Soils on which no witness trees occurred and the group with which

they were combined for mapping purposes

Name, texture, slope, hydrology Group Ac Ha

Kobel SiClLm, 0–1 percent KOBLEV 56 23

Calhoun SiLm, 0–1 percent KOBLEV 395 160

Calloway SiLm, 0–1 percent UPLAND 396 160

Calloway SiLm, 1–3 percent UPLAND 49 20

Overcup SiLm, 0–1 percent KOBLEV 664 269

Jackport SiClLm, 0–1 percent KOBLEV 10 4

Patterson FnSaLm, 0–2 percent KOBLEV 161 65

Dubbs SiLm, 1–3 percent UPLAND 152 61

Oaklimeter SiLm, 0–2 percent, occasionally flooded KOBLEV 1 0

Arrington SiLm, 0–3 percent, freq. flooded KOBLEV 30 12

Hillemann SiLm, 1–3 percent (natric) UPLAND 210 85

Grenada SiLm, 3–8 percent (natric) UPLAND 540 218

Water 355 144

Figure 2—Generalized map of soil groups with General Land Office corners and line trees, approximate

section lines and major features shown. Arkansas Highway 33 runs N-S through the western part of the

study area but is not shown because it lies on section lines and would obscure witness tree locations.

Section lines do not match at Cache River because surveys were conducted separately on each side of

the river. The surveyor measured (approximately) and noted the discrepancies. Locations of General Land

Office trees are indicated with a –. Soil groups are abbreviated: AS = ASKEW, KF = KOBFRQ, KL =

KOBLEV, MC = MCCROR, TU = TUCKER, UP = UPLAND, US = UPSAND.

Cl = clay(ey); fld = flood(ed); Fn = fine; frq = frequently; Lm = loam(y); pln = plain; Sa =

sand(y); Si = silt(y); sm = small.
14

important species was black oak (probably Q. velutina

Lam.), followed by white oak (probably Q. alba L.), post oak

and hickory. The most abundant species in the sample was

black oak, followed by post oak and hickory. Black oak had

the highest density, followed by post oak and hickory. Sweet

gum (1 individual) had the highest diameter followed by

white oak.

Relationships Among Soil/forest Groups—Detrended

Correspondence Analysis placed the soil/vegetation groups

along a continuum that apparently represents a moisture

gradient, as judged by species composition. From wettest to

driest, the order was TUCKER, MCCROR, KOBFRQ,

KOBLEV, ASKEW, UPLAND and UPSAND (fig. 3). Scores of

the species at positive and negative extremes of Axis 2

indicate that Axis 2 primarily separates the KOBLEV soil/

vegetation group from the ASKEW type. While these are

adjacent and in close proximity on Axis 1, they are clearly

separated on Axis 2. On this axis, horn beam, hackberry and

sweetgum occupy one extreme. They are all high or present

in ASKEW and low or absent in KOBLEV. At the other

extreme, sassafras, pawpaw and red bud are all present in

KOBLEV and absent from ASKEW. These differences

separate the vegetation on KOBLEV poorly drained natural

levees from that of similar ASKEW high mounds within the

floodplain.

DISCUSSION

The seven soil/forest groups categorized here represent

adaptations to a moisture gradient, ranging from extremely

wet bottomlands through well-drained bottomlands and

moist uplands to dry uplands. Because these communities

are related to particular soils they should provide useful

guidance to restoration efforts within and near the study

area. Most of the types are similar to those found on littledisturbed sites of the same soil today, so inspection of the

extant sites can provide details on overstory, midstory and

understory composition of the communities, propagules for

restoration, and the ability to do functional assessments of

the types. In such cases, the 1846 community model serves

only to provide the perspective that the existing forest is not

simply an artifact of human management or

mismanagement in the past 150 years, but is in fact a variant

of the “natural” forest of the region. However, at least two of

the types provide interesting and perhaps unexpected

insights:

1. KOBFRQ (Kobel silty clay loam, frequently flooded)

occurs in the second most hydric position on the moisture

continuum, and consequently in a more hydric location than

the related soil group KOBLEV (Kobel silty clay loam,

ponded and poorly drained natural levees). Yet today

KOBFRQ is virtually all cleared and in agriculture, while

large areas of KOBLEV are still forested. This is because

most areas of KOBLEV are within the floodplain of Cache

River, which at this point is not channelized or leveed. In

contrast, most areas of KOBFRQ lie outside the Cache

floodplain along Cache Bayou, which was a distributary of

the White River at the time of the GLO survey. Flood control

levees along the White have since disconnected the source

and dramatically reduced flooding in this area, allowing rowcrop agriculture. From a restoration standpoint, this is a clear

demonstration that the early forest may not be the

appropriate goal for current restoration efforts. In the case

where hydrologic regime has been dramatically and

Figure 3—Soil/vegetation groups plotted on Axis 1 vs. Axis 2 of Detrended Correspondence Analysis.
15

unalterably changed from the “natural”, forest species suited

to the new conditions will have to be propagated.

2. True upland forest (white oak-black oak-hickory) occurred

in this area, with dogwood as a diagnostic species, limited to

the uplands, as it is today. To many, the LMV was

synonymous with bottomland hardwood forest. Nevertheless,

large areas were covered with upland hardwood forest, pine

forest or prairie, depending on site conditions. Many of these

less appreciated vegetation types have been decimated even

more than the bottomland hardwoods. A perhaps very rare

and dramatically impacted community in this study area is

represented by UPSAND, the community occurring on

Bulltown loamy fine sand. This community, previously

undocumented, was dominated by widely spaced trees. This

community is typically referred to as savanna, barrens or

woodland (a community with 25-60 percent canopy cover of

trees). Searches by the ANHC have failed to locate any

extant sites occupied by this type, even in degraded form.

The presence of enough fine material in this soil, along with

ease of removing the few trees, probably led to early clearing

of the sites. At this point, little is known about the overall

composition and structure of this community, but its

importance may be illustrated by the occurrence in Missouri

of the sedge Cyperus grayoides Mohlenbrock on similar

lowland sandy sites. After failing to find suitable habitat in the

vicinity of this study site, ANHC botanist John Logan

discovered the species in Arkansas by looking in sandhill

woodlands in the West Gulf Coastal Plain 300 km to the

south (Personal communication. 1996. Logan, J. Arkansas

Natural Heritage Commission, Suite 1500, Tower Building,

323 Center St., Little Rock, AR 72201). Restoration of the

community on appropriate sites should be a high priority.

ACKNOWLEDGMENT

This paper was improved by the important suggestions of an

anonymous reviewer.

REFERENCES

Arkansas Game and Fish Commission. 1988. A proposal for the

Cache/Lower White Rivers Joint Venture Project, a component of

the North American Waterfowl Management Plan’s Lower

Mississippi Valley Joint Venture. Little Rock, AR: Arkansas Game

and Fish Commission, in cooperation with U.S. Fish and Wildlife

Service and other supporting agencies.

Bourdo, E.A., Jr. 1956. A review of the General Land Office Survey

and of its use in quantitative studies of former forests. Ecology.

37: 754-768.

Cottam, G.; Curtis, J.T. 1956. The use of distance measures in

phytosociological sampling. Ecology. 37: 451-460.

Hill, M.O.; Gauch, H.C. 1980. Detrended correspondence analysis:

an improved ordination technique. Vegetatio. 42: 47-50.

U.S. Fish & Wildlife Service. 1994. Comprehensive management

plan for the Cache River and White River National Wildlife

Refuges within the Cache/Lower White Rivers Ecosystem.

Unpublished master plan. St. Charles, AR: U.S. Fish and Wildlife

Service.

White, C.A. 1983. A history of the rectangular survey system.

Washington, DC: Government Printing Office.
16

APPLICATION OF GENERAL LAND OFFICE SURVEY NOTES TO

BOTTOMLAND HARDWOOD ECOSYSTEM MANAGEMENT AND

RESTORATION IN THE LOWER MISSISSIPPI VALLEY—AN EXAMPLE

FROM DESHA COUNTY, ARKANSAS

John L. Tingle, Charles V. Klimas, and Thomas L. Foti1

Abstract—The lower Mississippi River floodplain supported about 9 million ha of hardwood forests, and now less than

2 million. Reforestation is a priority of resource agencies, but efforts are hampered by uncertainties about species

composition and site relations of plant communities. We compared the first land survey notes for an area along the

Mississippi River in the 1800’s to modern forest. The results suggest that (1) geomorphic surfaces generally provide a

good basis for discriminating general patterns of plant community structure and composition, (2) modern forests differ

from the forests of the early settlement era in importance of dominant species, suggesting that modern forests may not

be appropriate restoration models, and (3) future distribution of plant communities will be altered because the lower

Mississippi River has been stabilized, affecting future environments of deposition. Importantly, oak species, the primary

material for restoration efforts, have never been particularly dominant on these sites.

1 Tingle, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS; Klimas, Charles Klimas and Associates, Seattle, WA; and Foti,

Arkansas Natural Heritage Commission, Little Rock, AR.

INTRODUCTION

Bottomland hardwood forests blanketed most of the alluvial

valley of the lower Mississippi River at the time of European/

American settlement. These forests were highly diverse,

supporting many species of resident, migratory, and

wintering wildlife, including several that have since become

extinct or regionally extirpated (Fredrickson 1978).

Agricultural development has since reduced the original

forest from about 10 million ha to less than 2 million ha

(Forsythe 1985). Much of the remaining forest is located

adjacent to the Mississippi River, inside the mainstem levee

system, where flooding conditions and forest composition

limit the overall quality and diversity of wildlife habitat

available (Klimas 1991). Most remaining forests on the

former floodplain are small fragments unconnected to major

forest blocks.

In recent years a variety of programs have been initiated to

encourage reforestation of floodplains (Allen 1990). These

include the Conservation Reserve Program and Wetland

Reserve Program, administered by the U.S. Department of

Agriculture. Federal and state wildlife agencies are acquiring

agricultural land for restoration to meet wildlife objectives.

Planning a reforestation project involves selection of

species, planting techniques, and maintenance

requirements. Traditional forest re-establishment for wildlife

or other purposes tends to focus on a few species selected

to meet project needs. However, where ecosystem

restoration for wildlife habitat is the principal concern, the

objective is often to establish a forest community with a

species composition and structure reflecting natural

conditions for the site (U.S. Fish and Wildlife Service 1994),

although usually species that produce hard mast for desired

wildlife are emphasized, particularly oak species.

Ecosystem management has recently received emphasis as

a direction for management of public lands, including

National Forests and National Wildlife Refuges. Ecosystem

management is here defined as management “...to restore

and sustain ecosystem integrity (composition, structure and

function) and produce ecologically acceptable levels of

sustainable multiple uses” (USFWS 1994). In the context of

ecosystem restoration, this objective requires that fairly

specific compositional and structural models be available to

guide the restoration design. Modern forests, even those

regarded as “old growth” based on structural criteria, may

not be appropriate models for restoration projects because

of the likelihood that they have been substantially altered by

human activity, particularly with respect to the relative

abundance of non-dominant trees or of major understory

species. Information from early observers and surveyors can

provide insights into the character of the pre-settlement

ecosystem, but development of fairly specific community

characterizations to guide restoration requires a mechanism

to relate historic data to specific site conditions in the

modern landscape.

The objectives of this study are to

1. Characterize the vegetation documented by the first land

survey of the study area in 1837, both over the entire study

area and stratified according to ecologically meaningful

landforms.

2. For those portions of the study area where the existing

vegetation has been characterized, compare existing

vegetation as described by Klimas (1991) with that

documented by the first land survey.

3. Qualitatively describe the understory vegetation on the

selected landforms using the mile notes of the surveyors.

METHODS

Overview

The study area is a portion of Desha County, Arkansas,

southwest of the confluence of the Arkansas and Mississippi

Rivers (fig. 1). It was selected because of the variety of
17

Figure 1—Vicinity map showing the location of the study area relative to the confluence of the Arkansas and Mississippi Rivers.
18

pertinent information available, and because it is typical of a

fairly large segment of the lower Mississippi River alluvial

valley with regard to the distribution of major landforms, the

distribution and composition of modern forests, and land use

history. The resources used included:

1. General Land Office (GLO) notes from the Desha County

surveys of 1824 and 1837 (hereafter referred to as the 1837

survey) provided information on land and forest conditions

as well as witness tree data suitable for use in deriving

quantitative information on forest structure and composition.

In this instance, “structure” refers to basal area and density

of trees per unit area, by species. The notes recorded the

work of two separate surveyors, Nicholas Rightor and Daniel

Miller, both of whom recorded witness tree data in consistent

and comparable terms. A testament to the difficulty of the

working conditions is that Mr. Rightor had six men desert his

employ during his first week of work. Data recorded included

diameter and species of each tree used to witness section

and quarter-section corners, as well as the distance and

direction from the corner to the tree. Also, diameter and

species of two “line” trees per mile were usually noted

(Bourdo 1956, White 1983).

2. The principal source of information on modern forest and

site conditions was the Lower Mississippi River

Environmental Program (LMREP), which is an inventory and

research program initiated and administered by the

Mississippi River Commission, U.S. Army Corps of

Engineers (Kolb and others 1968). The modern forest data

were compiled by Klimas (1988), who sampled 1,100 sites

within the confined (leveed) floodplain of the lower

Mississippi River in 1984 and 1985 as part of the LMREP.

He collected detailed information on overstory and

understory composition and structure within one-tenth acre

plots, and used multivariate analyses to isolate discrete

community types. He then tested those types for their fidelity

to specific site conditions reflecting flooding regimes, soil

conditions, and similar variables. He found that most of the

identified communities are associated with particular

combinations of alluvial deposition (as reflected in the

CERDS layer Environments of Deposition) and substrate

age (as reflected in the meander history mapping described

below); this finding is the basis for designating the four major

Site Types described below and in table 1.

3. One additional resource employed in this study, and also

used to construct the vegetation models described in Klimas

(1988) is a set of maps of the lower river showing channel

meander history since 1765 (Mississippi River Commission

1881-97, 1938, 1941). These allowed us to eliminate from

consideration all 1837 witness trees occupying sites that had

since been reworked by lateral river migration (and for

which, consequently, no ca. 1837 physical site data exist).

Thus the mapped geomorphic features could be assumed to

be the same basic landforms extant at the time of the survey.

Klimas (1988) identified 4 major site types: Point Bars (welldrained sandy deposits); Point Bars with natural levee

deposits (better drained than the previous and with newer

soils); Swales, Abandoned Channels and Backswamps

(poorly drained sites); and Backswamps and Abandoned

Channels with natural levee deposits (poorly drained sites

but with better internal drainage than the previous) (table 1).

Figure 2 shows the geomorphic map and distribution of GLO

survey points used in this study.

4. The various resources described above were employed

here to investigate the possibility that the modern forest may

offer an incomplete model to guide restoration efforts. In

particular, we wished to determine if modern communities

provide good models of the species composition and

dominance patterns appropriate for the sites they occupy,

and whether any particular community types are underrepresented in the modern forest relative to conditions prior

to major modifications due to clearing, differential harvest,

and river regulation.

In order to meet the objectives of the study, the following

analyses were conducted:

Characterize the vegetation documented by the first land

survey of the study area in 1837, both over the entire study

area and stratified according to ecologically meaningful

landforms.

The witness trees were grouped according to their

occurrence on each of the four major landforms or site types

(table 1). Initial analysis concentrated on the relative

abundance of all trees in the samples, including both corner

trees and line trees. Then the data from corner trees only

were summarized in terms of tree composition, density, and

basal area. . This analysis was limited to corners that had

not been reworked by rivers since 1837, as determined by

Mississippi River Commission maps of the lower river

showing channel meander history since 1765 (MRC 1881-

97, 1938, 1941), as reported by Klimas (1988). These

corners were eliminated because the site type of reworked

corners would not necessarily be the same as that occurring

at that corner in 1837, and therefore comparisons of 1837 to

present would be meaningless. The analyses are based on

treating the trees at each section and quarter-section corner

as point-centered quarter samples used to calculate

absolute and relative density and basal area for each

species after the method of Cottam and Curtis (1956).

Programs were checked against examples in MuellerDombois and Ellenberg (1974). Relative density and relative

Table 1—Site type classification

{Private} site Geomorphic General

type code description interpretation

A Point bars Basic alluvial site type

B Point bars with Better drained, often

natural levee deposits with newer soils

C Large swales within Poorly drained

point bars; abandoned

channels; backswamps

D Backswamps with Poorly drained sites

natural levee deposits; with better drained

abandoned channels surface soils

with natural levee

deposits
19

basal area were averaged to obtain species’ importance

values (IV). Relative frequency was not used in calculations

of IV because in corners where only two trees were

sampled, frequency could only take one of three values.

Other measures which were calculated included geometric

mean diameter (the diameter at which the mean basal area

occurs) and absolute density.

Two-way Indicator Species Analysis (TWINSPAN; Hill 1979b)

as implemented in PC-ORD Version 4 (MJM Software,

Gleneden Beach, OR) was used to investigate the

relationships among vegetation types.

For those portions of the study area where the existing

vegetation has been characterized, compare existing

vegetation as described by Klimas (1988) with that

documented by the first land survey.

Those trees located on sites inside the modern levee system

were summarized by site type. This allowed comparison of

the modern forest, which is restricted almost entirely to sites

on the river side of levees, to the 1837 forest on the same

sites. It also ensured compatibility with data produced by

Klimas (1988), who only studied forest on the river side of

the levees.

Klimas (1988) described 51 separate plant community types

in the lower Mississippi valley. Twenty-seven of these were

Figure 2—Geomorphology map of the study area displaying the locations of survey corners.

considered compositionally and structurally consistent with

modern forest conditions within the Desha County study

area under consideration here. Those 27 communities were

described based on 567 plots, which in this study were

distributed among the four major geomorphic Site Types in

proportion to the area occupied by each Site Type. Thus the

modern forest data used in the analysis were not

necessarily measured within the study area, but were a

synthesis of data taken from those site types across the

Lower Mississippi Valley.

For each Site Type, the modern forest data were

summarized for all trees greater than 14 cm d.b.h., which is

approximately the minimum size of trees selected by the

GLO surveyors as witness trees. The data were summarized

by combining relative density and relative dominance data,

then dividing by two to yield an Importance Value equivalent

to the IV calculated for the GLO data.

Two methods were used to compare GLO vegetation/site

types to modern forests.

The first comparison involved only those GLO corners that

were on the river side of the levees (inside the levees),

presently naturally vegetated, and consequently mapped in

CERDS. Each tree in the GLO database was associated with

the current CERDS cover type for the site. GLO trees having
20

a common current CERDS classification were grouped to

investigate correlation between GLO and current vegetation.

The IV of each species within each CERDS type was

computed. GLO data were also summarized for each Site

Type (geomorphic classification) to assess the uniqueness

of the associated vegetation communities.

For the second method of comparison, the GLO data were

summarized for each Site Type on sites both inside and

outside the levee, except those sites that had been reworked

by the river subsequent to the survey. This provided

additional data points for quantitative comparisons of

overstory composition and structure, as well as the

understory analysis described below.

Qualitatively describe the understory vegetation on the

selected landforms using the mile notes of the surveyors.

The surveyor’s observations concerning understory

conditions were summarized by landform/vegetation types.

The GLO surveyor’s comments on suitability of the land for

cultivation, apparent flooding depths, general timber type,

and understory composition were reasonably consistent

within geomorphic site types. The major source of potential

confusion was the characterization of these attributes over

long distances, often an entire section line (one mile). In

some instances he would differentiate segments of the line,

for example:

“Land the first 15.49 Chs 1st rate cane bottom The ballance

Swamp. Timber Oak gum Cypress Ash &c (“&c” is the GLO

surveyor’s abbreviation for “etc.”) undergrowth green briers

privy vines &c” (sic.)

“Land South half tolerable good bottom cane vines &c North

half Swamp 10 feet overflow Timber Cypress Oak Ash &c

undergrowth vines briers &c” (sic.)

Unless the site was within a zone of river meander activity

during the intervening years, such descriptions invariably

corresponded well with variations in site type on the modern

landscape, when compared to the geomorphic map. In other

cases the observation point was within a large area of fairly

uniform terrain, and the comments could be assumed to

apply to the basic site type dominant in the area. Generally,

all comments that could be associated with particular site

types were reasonably consistent in describing flood depths

and understory. Timber types were more variable, possibly

because small stands were included in the overall

description. Thus cypress frequently is mentioned in

association with almost all site types, suggesting that its

occurrence in small swales and channels was sufficient to

catch the surveyor’s attention. In any case, canopy tree

descriptions may be more biased than witness tree data,

which are preferable.

However, in the case of the understory the surveyor’s

observations are the only source of information. As noted

above, these observations seem quite consistent, as these

examples indicate:

POINT BAR

“...Undergrowth Cane Vines &c”

“...undergrowth vines &c”

POINT BAR WITH NATURAL LEVEES

“...Undergrowth cane & Vines”

“... undergrowth heavy cane vines &c”

ABANDONED CHANNELS, SWALES

“...undergrowth vines brier &c”

“...Undergrowth Cane & Green briers”

BACKSWAMP

“...undergrowth privy vines green briers &c”

“...Undergrowth Switch cane palmetto &c”

BACKSWAMP WITH NATURAL LEVEE

“...undergrowth heavy cane”

“... very heavy cane...”

RESULTS

Table 1 shows the general site types related to vegetation

that were designated as the basis for subdividing the data

set. Table 2 shows the number of sample trees in each of the

designated site types, as well as the distribution of sites in

relation to the modern levee system.

Twenty-five species were named in the GLO notes (table 3)

along with the likely scientific name to which they refer.

Uncertainty as to correct nomenclature exists and is

reflected in the table.

Distinctiveness of Site/Vegetation Types

Table 4 shows the composition of each of 4 vegetation/site

types based on all trees in the database, both corner trees

and line trees. Quantities include number of trees in the

database and relative abundance, by species. A total of 229

trees were included in this analysis. Hackberry, sweetgum

and ash occurred on all 4 site types and were the most

abundant species, averaging from 15 percent to 17 percent

of total trees. Persimmon and white oak also occurred on all

4 types, but in much lower abundance, making up just over 5

percent and just under 4 percent of total trees, respectively.

Cypress occurred in three site types, and made up over 28

percent of the trees on swales, channels and backswamps

(site type C). Pecan occurred on three site types as well, and

made up 15 percent of the trees on point bars (site type A).

The summary IV data based only on corner trees are shown

in table 5. Detailed data on absolute and relative density and

dominance, along with geometric mean diameter by species

are available from the third author. As measured by IV, which

includes both density and size of trees, sweetgum and ash

scored highest, improving on their abundance scores, while

hackberry declined somewhat, falling below the IV of

cypress, which, because of its large size scored much

higher in IV than in abundance. The buttressing of cypress

trees may well cause an overestimate of its basal area and

IV, relative to density. Persimmon and white oak also score

lower in IV than abundance. Considering average IV values

over all site types, ash was the most important species,

followed by sweetgum, cypress and hackberry. The

importance of all oaks combined did not equal the

importance of any one of these species.

TWINSPAN analysis (table 6) shows differences in species

IV among the site types. Cypress is important only in the
21

poorly drained types (C and D). Hackberry, while important

in all types, achieved highest importance in the poorly

drained types. Cottonwood and pecan only achieved high

importance on the best-drained type (B).

GLO Site/Vegetation Types and Modern

Vegetation—Overstory Comparisons

Initial analysis sorted GLO trees according to the CERDS

Land Cover type that today occupies the site types where

they were located. All trees (corner and line) located on sites

that are inside the modern levee were included in the initial

analysis, and percentage of total in the CERDS type sites

was calculated (table 7).

Ten or more GLO trees occurred in three CERDS vegetation

types. Therefore compositional analysis (relative abundance)

was limited to GLO trees of Cottonwood (17 trees),

Hackberry/American Elm/Green Ash (64 trees, including two

that were mapped as pure Hackberry) and Sycamore/

Sweetgum/American Elm (59 trees) sites. CERDS

vegetation types with fewer than 10 GLO trees include Black

Willow, Cypress/Tupelo, Overcup Oak/Bitter Pecan, Pecan,

Scrub, Sweetgum and Sweetgum/Oak.

Sites presently mapped as Cottonwood type were

dominated by cottonwood (23 percent) in 1837 as well,

followed by sycamore, sweetgum and hackberry. Present

Hackberry/American Elm/Green Ash cover type sites were

dominated in 1837 by ash (25 percent) and sweetgum (23

percent), followed by hackberry and cypress. Today’s

Sycamore/Sweetgum/American Elm areas were dominated

by ash (22 percent), followed by hackberry, sweetgum and

cottonwood.

The compositional comparisons between the 1837 forests

and modern stands on the same sites are of interest, but

composition alone is a limited attribute to compare

communities of sites in 1837 to those of today. It is

necessary to establish a relationship between identifiable

GLO communities, based on both abundance and size, and

modern landscape features, such as our site types. Table 8

summarizes importance values and species composition of

the four site types within the levees. As measured by

importance values, ash, sweetgum and hackberry

dominated, in that order. Cottonwood was important only in

the relatively well-drained site type A at almost 16 percent.

Cypress was only important (34 percent) in swales,

backswamps and other poorly drained sites (type C). Pecan

was most important on point bars (type A, 9 percent), and

honey locust (probably actually water locust) was only

important on swales, channels and other poorly drained

sites (type C, 9 percent).

These analyses demonstrate that geomorphic Site Types are

effective discriminators of GLO overstory vegetation

described in terms of both composition and structure.

Therefore the summaries of all of the GLO data (except for

sites reworked by the river after the survey) were then

compared to modern forest data summarized by Klimas

(1988) for the same site types to further illustrate differences

and similarities between the 1837 forests and those sampled

in 1985.

Table 3—Tree species listed in the 1837 GLO surveyor’s

notes, with probable modern equivalent and scientific

name. Unidentified indicates illegibility of the surveyor’s

notes. “Maple” was not used in the analysis since it

occurred only in excluded sites

Surveyor name Scientific name

Ash Fraxinus sp.

Black oak Quercus nigra, falcata,

 texana?

Boxelder Acer negundo

Cottonwood Populus deltoides

Cypress Taxodium distichum

Dogwood Cornus florida

Elm Ulmus sp.

Hackberry Celtis laevigata

Honey locust Gleditsia triacanthos, G.

 aquatica?

Hickory Carya sp.

Maple Acer sp.

Mulberry Morus rubra

Oak Quercus sp.

Overcup oak Quercus lyrata

Pecan Carya illinoensis

Persimmon Diospyros virginiana

Pin oak [willow oak?] Quercus palustris,

 phellos

Redbud Cercis canadensis

Red oak [cherrybark oak?] Quercus pagoda?

Red priv(e)y [swamp privet] Forestiera acuminata

Sassafras Sassafras albidum

Sycamore Platanus occidentalis

Sweetgum Liquidambar styraciflua

White oak [cow oak?] Quercus alba [Quercus

 michauxii]?

Willow Salix nigra

Cane Arundinaria gigantea

Palmetto Sabal minor

Green briers (or briers) Smilax spp.

Privey (or red privey) Probably Forestiera spp.

Table 2—Distribution of corner trees with respect to

levees (total trees per site type in parentheses)

{Private} site No. trees No. trees Total number

type code inside levee outside levee of trees

A 43 (51) 0 (1) 43 (52)

B 32 (44) 8 (11) 40 (55)

C 22 (33) 12 (19) 34 (52)

D 13 (15) 41 (55) 54 (70)

 Total 110 (143) 61 (86) 171 (229)
22

Table 9 contrasts the importance values of dominant species

(all species with an IV of 10 or greater) of the GLO forests

on each major site type (inside and outside the modern

levee system) with the modern forests inside the levee

system. The modern forest descriptions are summarized

from sample data taken along the river between Memphis,

TN and Baton Rouge, LA. Although this sample area

extends well beyond the study area, Klimas (1988)

determined that forest communities within this reach are

consistent in terms of composition and structure. Although

species compositions in 1985 were similar to those in 1837 it

is clear that some species have decreased in dominance

(sweetgum, cypress, ash) while others have increased

(hackberry and boxelder).

GLO Site/Vegetation Types and Modern

Vegetation—Understory Comparisons

To summarize numerous observations stated in the mile

notes, cane was noted on all site types, but was rare on the

heaviest soils (backswamp and abandoned channels – site

type C), and reached its greatest importance on natural

levee soils wherever they occurred. Palmetto was mentioned

occasionally, usually on backswamp sites. Green briers or

briers and privey or red privey also were largely restricted to

backswamps or abandoned channels, and was not noted on

point bars or on natural levee deposits. These latter sites

were almost invariably occupied by unspecified vines, unless

completely covered by dense canebrake.

A variety of other observations turned up in the notes. The

presence of large “windfalls” and references to “prairie cane”

suggest that large openings within the canopy were common

at the time of the survey. No references to fire were noted,

but on at least one occasion the surveyor noted that cypress

logs had been downed and prepared to be rafted out of the

forest during high water. Occasional mention of farm

buildings and roads as reference points make it clear that

this was not wilderness. On the other hand, comments about

provisioning campsites and difficulties traversing large areas

make it equally clear that much of the area had not been

substantially altered by the white settlers.

Understory conditions in the modern forest are far more

diverse than the GLO notes indicate, but this is certainly a

reflection of the surveyor’s disinterest in understory plants

unless they impeded his progress. Klimas (1988) recorded

hundreds of plant species in the forests flanking the lower

Mississippi River, including more than two dozen vine

species. The species the surveyors noted with regularity are

present in the modern forest on the same sites and with the

Table 4—Composition of four GLO vegetation/site types based on relative abundance of all trees in the

database—corner and line

Vegetation/site type

Species A B C D Total trees

No. Percent No. Percent No. Percent No. Percent No. Percent

Ash 11 21.15 9 16.36 9 17.31 11 15.71 40 17.47

Black oak 2 3.85 — — — — — — 2 .87

Boxelder 1 1.92 3 5.45 — — 1 1.43 5 2.18

Cottonwood 4 7.69 3 5.45 — — 1 1.43 8 3.49

Cypress 2 3.85 — — 15 28.85 5 7.14 22 9.61

Dogwood 1 1.92 — — — — — — 1 .44

Elm 1 1.92 3 5.45 1 1.92 6 8.57 11 4.80

Hackberry 6 11.54 10 18.18 7 13.46 15 21.43 38 16.59

Hickory — — 2 3.64 — — — — 2 .87

Honey locust — — — — 3 5.77 1 1.43 4 1.75

Mulberry — — 3 5.45 — — — — 3 1.31

Oak — — — — — — 1 1.43 1 .44

Overcup oak — — — — 1 1.92 — — 1 .44

Pecan 8 15.38 2 3.64 — — 1 1.43 11 4.80

Persimmon 1 1.92 5 9.09 4 7.69 2 2.86 12 5.24

Pin oak — — — — 2 3.85 1 1.43 3 1.31

Red bud — — — — — — 2 2.86 2 .87

Red oak — — — — 1 1.92 3 4.29 4 1.75

Red privey — — — — 1 1.92 1 1.43 2 .87

Sassafras 1 1.92 1 1.82 — — 1 1.43 3 1.31

Sweetgum 12 23.08 9 16.36 4 7.69 10 14.29 35 15.29

Sycamore — — 2 3.64 — — 3 4.29 5 2.18

Unidentified — — — — — — 1 1.43 1 .44

White oak 2 3.85 2 3.64 1 1.92 4 5.71 9 3.93

Willow — — 1 1.82 3 5.77 — — 4 1.75

 Total 52 100.00 55 100.00 52 100.00 70 100.00 229 100.00
23

Table 5—Summary Importance Value (IV) data on all site/vegetation types used in analysis of distinctiveness of

site/vegetation types

Site/vegetation types

Average

Species A B C D Frequency IV

Ash 19.77 17.88 21.05 17.91 4 19.153

Black oak 4.83 — — — 1 1.208

Boxelder 1.30 5.63 — 1.18 3 2.028

Cottonwood 15.60 2.36 — 1.00 3 4.740

Cypress 1.78 .3 7.10 12.85 3 12.933

Dogwood 1.21 — — — 1 .303

Elm 1.40 1.60 — 6.21 2 2.303

Hackberry 7.70 15.01 10.96 15.69 4 12.340

Pecan 10.82 1.95 — 1.48 3 3.562

Persimmon 1.49 6.74 7.06 2.70 4 4.498

Sassafras 1.40 4.45 — 1.18 3 1.758

Sweetgum 28.53 24.91 2.94 15.18 4 17.890

White oak 4.17 5.29 1.84 3.37 4 4.498

Hickory — 3.34 — — 1 .835

Mulberry — 4.93 — — 1 1.233

Sycamore — 4.31 — 11.19 2 3.875

Willow — 1.60 6.25 — 2 1.963

Honey locust — — 6.03 1.26 2 1.823

Pin oak — — 5.08 — 1 1.270

Red privey — — 1.69 1.18 2 .718

Oak — — — .93 1 .233

Red oak — — — 3.29 1 .823

Red bud — — — 2.29 1 .573

Unidentified — — — 1.11 1 .278

 Total IV 100.00 100.00 100.00 100.00 100.00

Total species 13 14 10 18

same general patterns of abundance, with the exception of

cane. In the modern forest cane tends to follow a similar

pattern with respect to general site affinities, with its most

extensive and consistent occurrence on natural levee

deposits. However, the large, dense canebrakes and cane

prairies described by the surveyors are no longer a common

feature, and most stands of cane are localized or sparsely

distributed in comparison to the conditions described in the

early 1800s.

DISCUSSION

The overall objective of this study was to determine if

information from the GLO survey could be used to help

guide ecosystem restoration activities in the lower

Mississippi Valley. Ecosystem restoration implies many

possible considerations relating to the ability to recover a

broad suite of ecosystem functions, but a basic tenet of most

restoration plans is that restored plant communities should

eventually have compositional and structural characteristics

that reflect undisturbed conditions as closely as possible. In

the lower Mississippi Valley, the principal remaining

examples of extensive bottomland forests are located along

the Mississippi River within the confines of the mainstem

levee system. These forests do not meet the “undisturbed”

criterion because of a long history of cutting and hydrologic

modification, and therefore other sources of information

must be employed to develop models to guide restoration.

Klimas (1988) has demonstrated that distinct modern forest

types within the levee system are associated with particular

geomorphic surfaces (as mapped in CERDS), which

suggests a convenient basis for designing forest restorations

on cleared lands. However, Klimas (1991) expressed

skepticism that modern forest remnants within the levee

system provide accurate models of “appropriate” community

characteristics for those sites because the existing forests

have been subjected to multiple and chronic stresses that

may tend to favor certain opportunistic tree species and

reduce representation of less resilient species. Stresses in

the modern confined floodplain include altered hydrology,

altered sediment distribution patterns, arrested channel

movement, and a long history of differential harvest of

valuable timber species. Much of the modern forest also

occupies sites that were farmed in the past. These

considerations cast doubt on the use of modern forests to

serve as models for restoration, and there is little basis for

determining which characteristics of the modern forest are

“appropriate” and which are artifacts of human disturbance.
24

Table 6—TWINSPAN analysis of IV all corner trees, both

inside and outside of modern levees. (Value is

generalized measure of IV)

3124

Cypress 4 1 – 3 000

Hickory – – 2 – 00100

Mulberry – – 2 – 00100

Willow 3 – 1 – 001010

Pin oak 3 – – – 001011

Black oak – 2 – – 001100

Dogwood – 1 – – 001100

Cottonwood – 4 1 1 001101

Persimmon 3 1 3 1 00111

Honey locust 3 – – 1 0100

Pecan – 3 1 1 0101

Ash 4 4 4 4 01100

Hackberry 3 3 4 4 01100

Sweetgum 1 4 4 4 01101

White oak 1 2 3 2 01101

Sassafras – 1 2 1 01110

Boxelder – 1 3 1 01111

Red privey 1 – – 1 10

Sycamore – – 2 3 1100

Elm – 1 1 3 1101

Oak – – – 1 111

Red oak – – – 2 111

Red bud – – – 1 111

Unidentified – – – 1 111

0001

001

0 1

Table 7—GLO trees of sites occupied today by three CERDS land cover types

Species Cottonwood Hackberry/elm/ash Sycamore/swtg/elm Total

No. Percent No. Percent No. Percent No. Percent

Ash 1 5.88 16 25.00 13 22.03 30 21.44

Black oak 1 5.88 1 1.56 1 1.69 3 2.14

Boxelder 1 5.88 1 1.56 3 5.08 5 3.57

Cottonwood 4 23.53 1 1.56 6 10.17 11 7.86

Cypress — — 7 10.94 1 1.69 8 5.71

Dogwood 1 5.88 1 1.56 — — 2 1.43

Elm — — — — 4 6.78 4 2.86

Hackberry 2 11.76 11 17.19 7 11.86 20 14.29

Honey locust — — — — 1 1.69 1 .71

Mulberry — — 1 1.56 2 3.39 3 2.14

Overcup oak — — 1 1.56 — — 1 .71

Pecan 1 5.88 6 9.38 4 6.78 11 7.87

Persimmon — — — — 5 8.47 5 3.57

Sassafras — — — — 1 1.69 1 .71

Sweetgum 2 11.76 15 23.44 7 11.86 24 17.14

Sycamore 3 17.65 — — 2 3.39 4 3.57

White oak 1 5.88 2 3.13 2 3.39 5 3.57

Willow 1 1.56 — — 1 .71 — —

 Total 17 100.00 64 100.00 59 100.00 140 100.00

The observations of the GLO surveyors represent a potential

opportunity to resolve this uncertainty. The forests they

described had certainly been influenced by Native

Americans and early European settlers, but they had not

been subjected to the fundamental and extensive

disruptions imposed over the past century of exploitation

and river engineering. However, the unique, site-specific

insights contained in the GLO notes cannot be applied to

restoration planning without a mechanism to translate the

information into community descriptions that can be

associated with identifiable features of the modern

agricultural landscape.

The analyses described in this paper demonstrate that the

information contained in the GLO notes can be usefully

translated to the modern landscape on the basis of

geomorphic setting. GLO witness tree data describe unique

communities when summarized within the same major

geomorphic settings used by Klimas (1988) to discriminate

among modern forests. This requires consideration of

structural data, as simple composition (species presence/

absence) does not always differentiate among communities.

Comparisons of GLO data to modern stand data within

geomorphic site types indicate that significant shifts in

dominance have taken place, and that modern forests may

provide misleading models for restoration projects. Shifts

may have resulted from biases in harvest or changes in

hydrology or other reasons. If the changes noted here are

due to biases in removal, then restoration to “original”

composition is warranted. If changes are due to hydrologic

modifications, then restoration to new communities is

needed. Sweetgum and/or ash were the leading dominants

on Site Types A and B in the early 1800s, but neither
25

species is particularly important on those sites today. They

have been replaced by boxelder and/or hackberry as the

leading dominants. In 1837 hackberry was second or third to

these species on Site Types A and B and was the leading

dominant on site type D. Boxelder had low IV in the 1837

data, but may have been selected against by the surveyors

as a short-lived tree. Secondary species (pecan,

cottonwood, and sycamore) continue to be present at levels

comparable to those noted at the time of the GLO survey on

these Site Types. On Site Type C, baldcypress was by far the

most important species at the time of the GLO survey, but it

now ranks fourth in importance on those sites, having been

largely replaced by hackberry, black willow, and boxelder.

This change may be real, or may indicate a preference for

cypress as a witness tree by the surveyors, or an

overestimate of importance because of its buttressed base.

The modern forest inside the mainstem levee system has

become dominated by opportunistic species (hackberry and

box elder, in particular), largely at the expense of sweetgum

and ash on drier sites, and baldcypress on poorly drained

sites. Secondary species that were noted in the GLO survey

are present in the modern forest, and presumably most

understory species continue to occupy their characteristic

sites. Thus, overall plant community composition has not

been significantly altered, but dominance patterns and

community structure have changed dramatically.

GLO surveyor’s observations regarding understory

conditions are anecdotal and limited to a few common

species for the most part. They do not suggest any major

changes over time, with one exception. The formerly

abundant cane has clearly declined dramatically. This fact

has been well-recognized as a region-wide phenomenon,

and suggested mechanisms contributing to the decline have

included cattle grazing, conversion of cane sites to

agriculture, fire suppression, and a reproductive cycle that

tends to delay recovery following disturbance (Remsen

1986). The potential significance of such changes is

illustrated by the changes that have occurred in abundance

over the past 150 years. Even though this species is still

common, it no longer dominates community character on

many sites, which has implications for a variety of

ecosystem elements. For example, the loss of extensive

canebrakes has been proposed as a likely cause of

extinction for at least one wildlife species, Bachman’s

Warbler (Remsen 1986) and likely declines in another

species, Swainson’s Warbler. The wholesale shifts in

overstory dominance patterns are likely to have had similarly

significant impacts on ecosystem functions, and restoration

Table 8—Summary of inside-the-levees importance values

Vegetation types

Species A B C D Total Mean

No. IV No. IV No. IV No. IV Number Number IV

Ash 9 19.77 6 21.28 5 28.10 4 35.02 24 6.00 26.04

Black oak 2 4.83 — — — — — — 2 .50 1.21

Boxelder 1 1.30 2 4.48 — — 1 4.92 4 1.00 2.68

Cottonwood 4 15.60 — — — — — — 4 1.00 3.90

Cypress 1 1.78 — — 5 34.09 — — 6 1.50 8.97

Dogwood 1 1.21 — — — — — — 1 .25 .30

Elm 1 1.40 1 1.96 — — — — 2 .50 .84

Hackberry 5 7.70 6 14.01 3 8.99 3 17.06 17 4.25 11.94

Hickory — — 2 4.08 — — — — 2 .50 1.02

Honey locust — — — — 3 9.09 — — 3 .75 2.27

Mulberry 3 6.05 — — — — 3 .75 6 1.51 2.08

Oak — — — — — — 1 3.85 1 .25 .96

Pecan 5 10.82 1 2.36 — — — — 6 1.50 3.30

Persimmon 1 1.49 3 6.13 — — — — 4 1.00 1.91

Pin oak — — — — 1 3.20 — — 1 .25 .80

Red oak — — — — — — 1 4.61 1 .25 1.15

Sassafras 1 1.40 1 5.24 — — — — 2 .50 1.66

Sweetgum 10 28.53 5 29.22 1 4.34 1 5.84 17 4.25 16.98

Sycamore — — 2 5.20 — — 1 23.32 3 .75 7.13

White oak 2 4.17 — — 1 2.79 1 5.38 4 1.00 3.09

Willow — — — — 3 9.40 — — 3 .75 2.35

 Total trees 43 100.00 32 100.00 22 100.00 13 100.00 110 27.50 N/A

Total species 13 11 8 8
26

Table 9—Comparison between 1837 (GLO) and 1985

(Klimas 1988) dominant vegetation on each of four

geomorphic site types

Site type A

Point bars

1837 Forests 1985 Forests

Leading dominants IV Leading dominants IV

Sweetgum 28 Hackberry 20

Ash 20 Boxelder 17

Cottonwood 16 Pecan 13

Pecan 11 Cottonwood 12

All other species 25 All other species 38

Site type B

Point bars with natural levee deposits

1837 Forests 1985 Forests

Leading dominants IV Leading dominants IV

Sweetgum 25 Boxelder 18

Ash 18 Hackberry 18

Hackberry 15 Pecan 12

All other species 44 All other species 40

Site type C

Abandoned channels, backswamps, and

large swales

1837 Forests 1985 Forests

Leading dominants IV Leading dominants IV

Baldcypress 37 Hackberry 32

Ash 21 Black willow 14

Hackberry 11 Boxelder 12

All other species 31 All other species 22

Site type D

Abandoned channels, backswamps, and large

swales with natural levee deposits

1837 Forests 1985 Forests

Leading Dominants IV Leading Dominants IV

Ash 18 Boxelder 28

Hackberry 16 Black willow 20

Sweetgum 15 Sycamore 10

Baldcypress 13

Sycamore 11

All other species 27 All other species 42

planning should attempt to recover the original dominance

patterns.

In addition to providing general guidance regarding the

composition and structure of relatively undisturbed forests,

this study illuminates some fundamental difficulties in

achieving forested wetland restoration within the lower

Mississippi Valley.

In particular, the relationship between forest characteristics

and geomorphic surfaces highlights the potential

significance of the relative lack of geomorphic dynamics in

the modern floodplain. Certain species tend to regenerate

on substrates that are made available by channel migration,

such as cottonwoods on point bars and baldcypress in

recently cutoff oxbows. With the stabilization of the river,

these habitats are no longer being created to any great

extent. Simple analysis of cover type distributions shows that

these species remain as common dominants in the region,

but more detailed evaluations (Klimas 1988) show that the

majority of their occurrences are as relicts of older stands, or

on sites recently disturbed by human activity rather than

river movement. Much of the remaining baldcypress in the

study area, for example, is associated with the perimeter of

old, stabilized oxbows or it exists as scattered large trees in

stands with other, drier-site species in the understory.

Similarly, extensive cottonwood is found most commonly in

abandoned agricultural fields, plantations, or on disturbed

soils adjacent to levees or borrow pits. There are some

extensive cottonwood stands on river islands and similar

habitats subjected to regular extreme scour and deposition,

but there are relatively few cottonwood sites that correspond

to the classic succession patterns on accretion topography

such as newly-formed point bars. Whatever unique

characteristics such stands had may not be well represented

in the modern forest. In the case of baldcypress, the

implications are even more problematic, in that the majority

of existing stands appear to be remnants of former stands

that will not regenerate, and the sites that are typically

invaded by cottonwood (old fields, disturbed soils) are not

likely to be appropriate baldcypress habitat. The lack of

suitable habitat for baldcypress regeneration will cause the

gradual loss of this unique component of the Mississippi

Valley ecosystem unless special restoration approaches are

devised to ensure its persistence.

In general, plant communities are dependent on riverine

processes and features and unless we restore the

processes we cannot expect the same communities to

return.

SUMMARY

GLO information interpreted in the context of geomorphic

surfaces appears to provide a good basis for establishing

goals regarding restoration of forest composition and

structure within the study area. The established relationship

between modern forests and geomorphology suggest that

this approach is likely to be appropriate throughout the

Mississippi Alluvial Valley, if the quality of the surveyor’s

notes is comparable to those we used. The required

geomorphic mapping is available for the entire region (see

Saucier and Snead 1989 for basic references).

This study demonstrated that modern forests inside the

mainstem levee system do not provide good models for

overstory restoration. Chronic severe disturbance has

altered their composition and structure substantially. They

remain the best available source of information on potential

understory conditions, except that the characteristics of the

modern cane populations have been shown to be

substantially different from pre-settlement conditions.
27

The application of GLO/geomorphic models to restoration

must be approached thoughtfully. For example, changes in

flooding patterns would affect the applicability of GLO data,

although the consistent site affinities of secondary and

understory species tend to offset this concern. A more

fundamental consideration has to do with the curtailment of

river meander behavior. Although existing forests do not yet

fully reflect this change, it is inevitable that communities

which are directly associated with river migration, such as

many black willow, cottonwood, and baldcypress forests, will

eventually be greatly reduced as elements of the overall

forest matrix. Restoration planners should strive not only to

reestablish appropriate patterns of community composition

and structure, but also find ways to offset the chronic

disturbance and loss of ecosystem dynamics that have

resulted from wholesale stabilization and confinement of the

river.

We thank E.C. Burkhardt for providing the GLO survey notes

used in this study.

REFERENCES

Allen, James A. 1990. Establishment of bottomland oak plantations

on the Yazoo National Wildlife Refuge complex. Southern Journal

of Applied Forestry. 14: 206-210.

Bourdo, E.A., Jr. 1956. A review of the General Land Office Survey

and of its use in quantitative studies of former forests. Ecology

37: 754-768.

Cottam, Grant; Curtis, John T. 1956. The use of distance measures in phytosociological sampling. Ecology. 37: 451-460.

Forsythe, Stephen W. 1985. The protection of bottomland hardwood wetlands in the Lower Mississippi Valley. Trans. of the North

American Wildlife and Natural Resources Conference. 50: 566-

572.

Fredrickson, Leigh H. 1978. Lowland hardwood wetlands: current

status and habitat values for wildlife. In: Greeson, P.E.; Clark,

V.R.; Clark, J.E. eds. Wetland functions and values: the state of

our understanding. Minneapolis, MN: American Water Resources

Association: 296-306.

Hill, Mark O. 1979. TWINSPAN – a FORTRAN program for

arranging multivariate data in an ordered two-way table by

classification of the individuals and attributes. Ithaca, NY: Cornell

University, Ecology and Systematics.

Klimas, Charles V. 1988. Forest vegetation of the leveed floodplain

of the Lower Mississippi River. Lower Mississippi River Environmental Program Report 11. Vicksburg, MS: Mississippi River

Commission. 89 p.

Klimas, Charles V. 1991. Limitations on ecosystem function in the

forested corridor along the lower Mississippi River. In: Proceedings, International symposium on wetlands and river corridor

management. Berne, NY: Assoc. State Wetland Managers. 61-66

Kolb, Charles R.; W.B. Steinried Jr.; E.L. Krinitzky [and others].

1968. Geological investigation of the Yazoo Basin, Lower

Mississippi Valley. Revised 1982. Technical Report No. 3-480,

Vicksburg, MS: U.S. Army Engineer Waterways Experiment

Station.

Mississippi River Commission. 1938. Lower Mississippi River

early stream channels, at approximate half-century intervals, in

12 sheets. Vicksburg, MS, USA.

Mississippi River Commission. 1941. Lower Mississippi River

stream channels, 1930-1932, and 1940-1941, 12 sheets.

Vicksburg, MS, USA.

Mueller-Dombois, Dieter; Ellenberg, Heinz. 1974. Aims and

methods of vegetation ecology. New York: Wiley.

Remsen, J. Van, Jr. 1986. Was Bachman’s warbler a bamboo

specialist? Auk 103: 216-219.

Saucier, Roger T.; Sneed, John L. 1989. Quaternary geology of the

Lower Mississippi Valley. [Map]. Boulder, CO: Geological Society

of America.

U.S. Fish and Wildlife Service. 1994. Comprehensive management plan for the Cache River and White River National Wildlife

Refuges within the Cache/Lower White Rivers Ecosystem.

Unpublished master plan. Charles, AR: U.S. Fish and Wildlife

Service.

White, C. Albert. 1983. A History of the rectangular survey system.

Washington, DC: United States Government Printing Office.
28

COMPOSITION, POTENTIAL OLD GROWTH, FRAGMENTATION, AND

OWNERSHIP OF MISSISSIPPI ALLUVIAL VALLEY BOTTOMLAND

HARDWOODS: A REGIONAL ASSESSMENT OF HISTORIC CHANGE

Victor A. Rudis1

Abstract—Recent Mississippi River Alluvial Valley (MAV) bottomland hardwood forest surveys revealed a larger

proportion of intermittent flood zone (inundated 1 to 2 months), early successional (primarily hackberry-elm-ash), and

permanent flood zone (inundated > 6 months annually, primarily baldcypress-water tupelo) community types than in the

1930s. For the same time period, these same surveys showed a smaller proportion of nonpermanent (inundated < 6

months), late-successional community types (overcup oak-water hickory and mixed bottomland hardwood) than in the

1930s. Sporadic flood zone (inundated < 1 month), shade-tolerant community types were less common in the MAV than

elsewhere in the South-Central United States (Alabama, Arkansas, Louisiana, Mississippi, east Oklahoma, Tennessee,

and east Texas). Most forests with old-growth conditions (site productivity-based minimum basal area, net growth near

zero, and no recent commercial harvest activity) were in private ownership and characteristic of select community types.

Findings were based on a reexamination of systematic sample-based forest surveys of the region. Annual change in

bottomland hardwood area was diminishing (-1.1 percent, 1970s to 1980s; +0.3 percent, 1980s to 1990s), but the

frequency of large (> 2,023 ha) forest fragments continued to decline (-2.4 percent, 1970s to 1980s; -4.0 percent, 1980s

to 1990s). To reconstruct the historic mix of bottomland hardwood community types, renew forest cover, and retain or

enhance associated resource values, this assessment suggests a primary focus on conserving large fragments, shifting

nonpermanent flood zone, early successional community types toward late-successional types, and restoring occasional

flooding regimes and forest cover adjacent to small remnant bottomland hardwood fragments.

1 Research Forester, USDA Forest Service, Southern Research Station, Starkville, MS.

INTRODUCTION

Nonforest cover represents the majority land use in the

formerly extensive bottomland hardwood region known as

the Mississippi Alluvial Valley (MAV). At present MAV forest

communities contain no designated wilderness and few

forest plantations. Yet the region’s forest cover is

comparatively roadless and more closely tied to hunting

activities than other regions of the South-Central United

States (Alabama, Arkansas, Louisiana, Mississippi, east

Oklahoma, Tennessee, and east Texas) (Rudis 1998).

Potential wood productivity of MAV forests is greatest among

all regions of the South (Rudis 1998). Reforestation goals

include timber production with economically valued species,

but also the maintenance of threatened black bear and other

forest-dependent wildlife populations and primitive

recreation opportunities. Other goals include sequestering

elemental carbon within species native to the region,

conserving forested habitats and flooding regimes for

indigenous plant and animal species, and improving water

quality and other economically valued forest recreation like

ecotourism. Attaching priority to these multiple goals

requires an understanding of the region’s historic bottomland

hardwood communities and anthropogenic threats to current

communities.

In the MAV, historic bottomland hardwood composition and

old-growth (mature, stable forests unmodified by postEuropean settlement) forest conditions are not well

documented. Bottomland hardwood forests in the MAV were

almost certainly extensive, contiguous, undisturbed by

modern anthropogenic uses, and a different mix of

community types than found today.

The earliest systematic observations on record were from

the 1800s Land Office, i.e., land surveyors’ field notes of

bearing, or witness, trees. Though not necessarily

representative of all conditions, surveyors’ accounts provide

clues to former MAV forest composition. From one such

account dated 1821 for West Feliciana, LA, Delcourt (1975)

noted that surveyors referenced comparatively few witness

trees in swampland. Nevertheless, in ravines and tributary

stream bottoms, dominant witness trees were (southern)

magnolia, (American) beech and (American) holly, with

baldcypress and (water) tupelo in alluvial swamps. In 1975,

the surveyed study area had only a few large (American)

beech trees (Delcourt 1975). By the 1980s, modern-day

surveys (McWilliams and Rosson 1990) reported none but

baldcypress and water tupelo among the 14 species with > 3

percent importance by volume for the MAV region.

Recent systematic, extensive area surveys noted that more

than one-half of the 1930s MAV bottomland hardwood forest

area has disappeared (McWilliams and Rosson 1990, Rudis

and Birdsey 1986), and the majority area converted to

agricultural uses (MacDonald and others 1979). A Yazoo

River basin report (Anonymous 1944) noted in the 1940s

that better drained floodplain forests were cleared first,

followed by land clearing of poorly drained areas—a pattern

likely repeated through the rest of the MAV. Following land

clearing, subsequent agricultural improvements included

drainage structure installation, nearby stream

channelization, and changes to the regional flooding regime

(Turner and others 1981). These changes fragmented

bottomland hardwood forests with agricultural fields and

roads and indirectly caused soil deposition and reforestation

along new stream channels.
29

Forests that are no longer contiguous may not sustain a

region’s existing mix of species and resources, nor improve

selected desired resources, such as black bear habitat

(Rudis and Tansey 1995) or primitive recreation

opportunities (Rudis 1987). Sample-based inventories of

forest fragments, i.e., contiguous forests > 0.4 ha and

unbroken by nonforest cover >37 m wide, noted significant

associations by tree species (Rudis 1993), empirical

community type and resource indicators for existing

bottomland hardwood communities across the south-central

region. These studies showed that the smaller the forest

fragment, the more likely the forest was an early

successional community characteristic of nonpermanent

flood zones (inundated <6 months). The smaller the

fragment, the more frequently it had anthropogenic

intrusions, e.g., fences, evidence of livestock use, and

rubbish, and the closer it was, on average, to developed

roads and agricultural and urban land. The larger the

fragment, the more likely the forest had evidence of hunting,

and the more likely the sampled tree community was

characteristic of a permanently wet community type

(inundated >6 months). Fragment size was also directly

associated with timber volume. The largest fragments were

less likely to have evidence of harvest since the prior survey.

These findings suggested that the potential for vegetation

disturbance by land-use activities was inversely associated

with fragment size. If old-growth conditions were typical of

undisturbed conditions, then the probability of finding such

conditions was greatest in the largest fragments.

OBJECTIVES AND METHODS

To test the hypothesis that nonpermanent flood zone,

bottomland hardwood community types in the MAV were

removed or otherwise altered, I summarized published

community-type surveys since the 1930s and compiled

associated data on forest fragment size and community

types since the 1970s, and old growth by owner class for the

most recent survey period.

Because community types before European settlement were

poorly documented, I compared the current distribution of

MAV bottomland hardwood community types with a

surrogate for what might have existed from recent surveys

for the entire South-Central United States. I also selected

old-growth criteria compatible with available forest survey

data to suggest the likely distribution of area in remnant oldgrowth condition by community type and ownership class.

Surveys from the Forest Inventory and Analysis Research

Work Unit (FIA) of the U.S. Department of Agriculture Forest

Service were the primary data sources. Detailed FIA

bottomland hardwood community types for 1932–35

(Eldredge 1938; Stover 1942; Winters 1939a, 1939b; Winters

and others 1938) were for a region roughly comparable to

the MAV, including west Kentucky, southeast Missouri, and

west Tennessee, but excluding southern Illinois. County

boundaries in the delta survey units of Arkansas, Louisiana,

and Mississippi (fig. 1) were the boundaries in subsequent

survey reports (McWilliams and Rosson 1990, Rudis and

Birdsey 1986, Sternitzke and Putnam 1956).

The early forest surveys reported summary findings with

limited documentation compared to today. Nevertheless,

such accounts embody the only detailed extensive area

estimates by foresters of the time. Surveys from the 1930s

through the 1960s used community-type estimates from

systematic field observations and temporary plots (Frayer

and Beltz 1985, Sternitzke and Putnam 1956). The FIA

community types before the 1970s likely came from ocular

estimation of dominant tree species. Between the 1970s and

1990s, FIA calculated community types from sampled tree

species equidistant at 20-m intervals, > 10 m inside forest

edges at 10 points within a 0.4-ha plot area (5 points and a

0.2-ha area for Louisiana’s 1984 survey). Observations were

from permanent plots spaced 4.8 km apart that FIA classed

as forested (land with > 10 percent tree crown cover and

land temporarily < 10 percent tree crown cover not

developed for other uses, >0.4 ha in size and >37 m wide).

Because the history of sampled areas is often unknown and

forests have often been periodically disturbed, many

sampled plots are classed as mixed-age class. A surrogate

for age class is stand-diameter class, often referenced in

timber resource reports as stand-size class, which is a

classification of the height and size of trees. Stand-diameter

classes are: sawtimber (> 50-percent stocked with live trees

Figure 1—Counties in the Arkansas, Louisiana, and Mississippi

Delta survey unit, Mississippi Alluvial Valley.
30

>12.7 cm d.b.h. and >50-percent stocked with live trees >

22.9 cm softwood, and >27.9 cm hardwoods; poletimber (>

50-percent stocked with live trees >12.7 cm, and < 50-

percent stocked with sawtimber trees); and smaller (<50-

percent stocked with live trees < 12.7 cm).

This study examined only sampled plots characterized as

bottomland-community type (<25 percent pine stocking,

judged by field crews to be in a wetland physiographic class,

or having > 50 percent overstory in bottomland species).

Tree sampling recorded live tree stems > 12.7 cm (1.4 m)

d.b.h., on variable radius (8.6-m2 factor) prism plots and live

tree stems 2.5 to 12.6 cm on fixed (2.2-m radius) plots

around three points. Additional details are provided

elsewhere (Faulkner and others 1995, Rosson 1995, Rudis

1995).2 Definitions for these and other common FIA terms

are in the appendix.

Numerical FIA estimates are typically most reliable for a

large proportion of the sampled population and least reliable

for a smaller one. Louisiana’s 1991 survey (Rosson 1995),

for example, noted 67-percent confidence that a 502 000-ha

estimate was within 5000 ha (1 percent of 502 000 ha) of the

actual amount; and 67-percent confidence that an 810-ha

estimate was within 200 ha (25 percent of 810 ha) of the

actual amount. Because technology, field procedures, and

forest-type estimation may change between surveys, care is

advised in interpreting results. Shifts in forest-type area may

be a result of procedural changes before 1974. Readers

should refer to the original survey reports for further

documentation. Because one cannot avoid procedural

differences, caution is advised in concluding that forest-type

classification, areal adjustments, and sample area

expansion procedures are comparable to those used today.

Composition

I estimated the likelihood of finding forest land within a range

of flood zones, shade tolerances, and empirical community

types. This forest occurrence probability used forest-plot

information on flood zone and shade tolerance selected at

random for an approximately equal number of nonforest

plots.

For forest plots, flood zone, shade tolerance, and community

type were the dominant species by importance (average

occurrence frequency, basal area, and number of stems per

plot) value derived from trees tallied on sampled plots. Flood

zone values were averaged by plot, with ordinal values

assigned by species typical of flood zones inundated (1)

permanently, (2) periodically, (3) intermittently, (4)

sporadically, and (5) inundated only in wet years, after

Wharton and others (1982). Shade tolerance values were

averaged by plot, with ordinal values assigned by species

as: (1) very tolerant, (2) tolerant, (3) intermediate, (4)

intolerant, and (5) very intolerant, after Burns and Honkala

(1990).

I cross-referenced these results with an earlier study of plots

classed by ordinal flood zone and shade tolerance values for

the South-Central United States. The earlier study (Rudis

1995) established 32 empirical community types for that

region’s 2,666 bottomland hardwood plots with distinctive

and internally similar tree species importance. [The process

employed hierarchical clustering to minimize the residual

(error) sum of squares using FASTCLUS and Ward’s method

(SAS Institute Inc. 1990).]

For the MAV region, I used flood zone and shade tolerance

estimates from the forest plots that occurred in the MAV

(Rudis 1995). Because half of the region’s bottomland

hardwood forests had been cleared since the 1930s, I

conservatively assumed that there was at least an equal

area (represented by about an equal number of plots) of

nonforest land today that was formerly in bottomland

hardwood forests. I combined the sample of flood zone and

shade-tolerance values from forested plots with the random

array of values from nonforest plots to calculate occurrence

probabilities. I also applied identical procedures to calculate

occurrence probabilities for bottomland hardwood forests of

the South-Central United States.

Occurrence probability was 1.00 (100 percent) at a flood

zone and shade-tolerance location represented by a

forested sample and 0.00 (0 percent) otherwise. G3GRID

(SAS Institute Inc. 1991) generated grid patterns that

afforded visual comparisons of forest occurrence probability

distributions calculated from both regions. Grid patterns

were interpolated linearly, between 0.00 and 1.00 in 0.02-

percent increments, between flood zone 2, shade value 1

(permanently flooded, very shade tolerant) and flood zone 6,

shade value 5 (inundated only in wet years, very shade

intolerant). Occurrence probability was set to 0.00 for values

outside that range.

Potential Old Growth

To date, no systematic survey of old-growth conditions has

been attempted for the entire MAV. I estimated area of

potential old growth from an a posteriori analysis of an

existing database, namely sample-based FIA surveys. There

is no one, widely agreed definition of old growth that one can

generally accept from an a posteriori analysis. Unlike

Frelich’s (1995) reexamination of North-Central United

States from FIA data, FIA surveys in the South-Central

United States classed age as mixed if >2 strata with a > 10-

year age difference existed. Other criteria used in old-growth

assessments, i.e., a standing dead tree tally, live-to-dead

tree ratio, and other disturbances (Devall and Rudis 1991),

were not available for all plots.

I selected two types of old-growth criteria: one based on

size, the second based on biological maturity. The first used

the ratio of basal area of trees >50 cm diameter at 1.4 m

(d.b.h.) divided by basal area of trees >12.7 cm d.b.h. to

provide estimates of forest land with large trees. The second

used three progressively restrictive biological maturity

criteria designed to estimate forests: (1) likely to be old or

mature, (2) having net growth approximately zero, and (3)

having no recent harvest evidence. The first biologically

mature criteria selected samples with basal area equal to or

greater than that averaged for 45- to 65-year-old bottomland

2

 U.S. Department of Agriculture, Forest Service, Forest Inventory

and Analysis Research Work Unit. 1993. Forest survey inventory

work plan, Mississippi 1993-1994. 128 p. On file with USDA, Forest

Service, Southern Research Station, P.O. Box 928, Starkville, MS

39760–0928.
31

hardwood forests. (Age and basal-area data came from the

east Texas’ 1986 forest survey. I used this region to

characterize bottomland hardwood stand age, as that region

used precise estimates from a special survey of dominant

tree age.3

 Other States and years used 10-year and mixed

age classes.) The second criterion selected samples with

net growth (current minus past volume from the prior survey

a decade earlier) close to zero. The third selected samples

with no commercial harvest or cutting activity since the

previous survey.

Fragmentation

Between 1974 and 1995, FIA surveys defined the areal

extent, i.e., forest fragment size, associated with each 0.4-ha

forested plot in south-central States as contiguous, >0.4 ha,

unbroken by nonforest cover >37 m wide. Each forest

fragment was inventoried by size class: 0.4 to 4; 5 to 20; 21

to 40; 41 to 202; 203 to 1012; 1013 to 2023; and >2023 ha.

The FIA field crews estimated forest fragment area from

aerial photography and field observations. Image and scale

of aerial photographs varied from black and white, 1:20,000

or 40,000 in the 1970s and early 1980s, to color infrared,

1:58,000 after 1986.

RESULTS AND DISCUSSION

Forest Surveys

Conducted in the 1930s, the first extensive forest surveys of

the MAV recorded 9 percent of the 5 190 500 ha of forests as

old growth, and an additional 18 percent as having been cut

but with some old-growth conditions (table 1). Forests near

New Orleans and other development centers had already

experienced extensive cutting for wood products by the mid1930s. Remnant uncut old growth at the time was chiefly on

poorly drained and clay-dominated soils. Many species

became commercially important only after World War I, e.g.,

trees in sweetgum-water oak communities, or had no

commercial value, trees in overcup oak-water hickory

community type (table 1).

3 U.S. Department of Agriculture, Forest Service, Southern

Research Station, Forest Inventory and Analysis Research Work

Unit. 1985. Forest survey inventory work plan, 1985. 56 p.

Administrative report. On file with: U.S. Department of Agriculture,

Forest Service, Southern Research Station, Starkville, MS 39762–

6124.

Table 1—Bottomland forest area by type and condition, Mississippi 

Alluvial Valley, 1932–35 

 

All Second 

 Old growthb

Forest type conditions growtha

 Partialc Uncutd

 

- - - - - - - - - - - - - 1000 ha - - - - - - - - - - - - % 

 

Baldcypress-water tupelo 684.9 521.4 131.4 32.1 5 

Overcup oak-water hickory 857.0 331.6 285.4 239.9 28 

Cottonwood and willowe 558.0 558.0 — — — 

Mixed bottomland hardwood 

Sweetgum-mixed 1,017.3 794.0 129.3 93.9 9 

Hackberry-elm-ash 814.0 571.8 199.6 42.6 5 

Water oaksf 422.6 320.6 88.7 13.3 3 

Other mixtures 836.7 729.0 86.1 21.6 3 

 

Total 5,190.5 3,826.5 920.6 443.4 9 

a Vegetative growth habits typical of abandoned clearings, recent catastrophic 

disturbances, or new riverbank soil deposits (Winters and others 1938). 

b Stands composed of sawtimber trees with the characteristics of the original mature trees 

of the region (Eldredge 1937). 

c = 10 percent volume removed but characterized by residual trees from the old-growth 

forest (Eldredge 1937). 

d < 10 percent volume removed (Eldredge 1937). 

e Early successional types defined in the 1930s as transitional, having no maturity potential 

(Winters and others 1938). 

f

Water, Nuttall, and willow oak. 

Sources: Eldredge 1938; Stover 1942; Winters 1939a, 1939b; Winters and others 1938.
32

Apart from the steep declines since the 1930s, communitytype comparisons reveal a greater proportion of hackberryelm-ash and baldcypress-water tupelo and a lesser

proportion of overcup oak-water hickory and mixed

bottomland hardwood types represented today (fig. 2).

Changes between the 1930s and 1990s show that the loss

of bottomland hardwood area slowed only in the past

These early surveys recorded a paucity of old growth in

southeastern Arkansas and points north (table 2) and east

in Mississippi (table 3). The MAV maps of the period also

indicated extensive land described as formerly forested but

cleared for agricultural crops for the area north of the

Arkansas River. Most uncut old growth, primarily overcup

oak-water hickory was in Louisiana (table 4).

Table 2—Mississippi Alluvial Valley bottomland forest area by type and 

condition, east Arkansas, west Kentucky, southeast Missouri, and west 

Tennessee, 1935 

Old growthb

Survey region and 

forest type 

All 

conditions 

Second 

growtha Partialc Uncutd

 

 - - - - - - - - - - - 1000 ha - - - - - - - - - - - % 

Southeast Arkansas 

 Baldcypress-water tupelo 36.6 24.8 9.3 2.6 7 

 Overcup oak-water hickory 136.8 72.2 42.7 21.9 16 

 Cottonwood and willowe

 81.9 81.9 — — — 

 Mixed bottomland hardwood 

 Sweetgum-water oaksf

 184.3 150.0 24.1 10.3 9 

 Hackberry-elm-ash 169.2 116.6 44.0 8.7 5 

 Water oaksf

 129.1 104.1 21.5 3.5 3 

 Other mixtures 351.0 297.0 42.4 11.6 3 

 

 Total 1,089.1 846.6 184.0 58.5 5 

Northeast Arkansas, west Kentucky, 

 southeast Missouri, and west 

 Tennessee 

 Baldcypress-water tupelo 109.5 91.7 15.6 2.2 2 

 Overcup oak-water hickory 67.0 52.0 11.2 3.8 6 

 Cottonwood and willowe

 106.3 106.3 — — — 

 Mixed bottomland hardwood 

 Sweetgum-water oaksf

 177.1 153.2 10.5 13.4 8 

 Hackberry-elm-ash 191.2 164.7 20.4 6.1 3 

 Water oaksf

 107.9 101.5 5.7 0.6 1 

 Other mixtures 209.7 195.7 12.5 1.6 1 

 

 Total 968.8 865.1 76.0 27.8 3 

a

Vegetative growth habits typical of abandoned clearings, recent catastrophic disturbances, 

or new riverbank soil deposits (Winters and others 1938). 

b

 Stands composed of sawtimber trees with the characteristics of the original mature trees of 

the region (Eldredge 1937). 

c = 10 percent volume removed but characterized by residual trees from the old-growth forest 

(Eldredge 1937). 

d <10 percent volume removed (Eldredge 1937). 

e Early successional types defined in the 1930s as transitional, having no maturity potential 

(Winters and others 1938). 

f

Water, Nuttall, and willow oak. 

Sources: Eldredge 1938, Winters 1939a.
33

Table 3—Mississippi Alluvial Valley bottomland forest area by type 

and condition, Mississippi, 1932 

 

Old growthb 

Forest type 

All 

conditions 

Second 

growtha Partialc

 Uncutd

 

- - - - - - - - - - 1000 ha - - - - - - - - - - % 

 

Baldcypress-water tupelo 58.3 31.2 25.6 1.5 3 

Overcup oak-water hickory 182.4 82.7 83.0 16.7 9 

Cottonwood and willowe 87.9 87.9 — — — 

Mixed bottomland hardwood 

 Hackberry-elm-ash 126.5 93.5 31.2 1.9 1 

 Water oaksf 50.0 36.7 11.1 2.1 4 

 Other mixtures 54.6 49.7 4.9 — — 

 

 Total 705.7 495.3 179.6 30.9 4 

 

a Vegetative growth habits typical of abandoned clearings, recent catastrophic 

disturbances, or new riverbank soil deposits (Winters and others 1938). 

b

 Stands composed of sawtimber trees with the characteristics of the original 

mature trees of the region (Eldredge 1937). 

c = 10 percent volume removed but characterized by residual trees from the oldgrowth forest (Eldredge 1937). 

d < 10 percent volume removed (Eldredge 1937). 

e Early successional types defined in the 1930s as transitional, having no maturity 

potential (Winters and others 1938). 

f Water, Nuttall, and willow oak. 

Source: Stover 1942.

Figure 2—Percent bottomland-hardwood forest area by forest type and total forest area of Arkansas,

Louisiana, and Mississippi Delta survey units, 1932–35 and 1991–95.

Cypress-tupelo

Hackberry-elm-ash

Mixed (water oak, other)

Overcup oak-water hickory

Cottonwood, willow

Sweetgum-mixed

Forest types

1932–35

4.3 million ha

1991–95

2.1 million ha
34

decade (table 5). Since the 1970s, only baldcypress-water

tupelo and willow community types have increased.

The 1967 delta survey unit in Mississippi documented that

two-thirds of its forest land, about 170 000 ha, were soybean

fields cleared since the 1957 survey (Beltz and Christopher

1967). Forests cleared for agriculture between 1957 and

1967 were about 28 percent overcup oak-water hickory, 37

percent sweetgum-mixed oaks, 13 percent hackberry-elmash, and 22 percent other community types (Beltz and

Christopher 1967). Overcup oak-water hickory—characteristic of poorly drained clay flats—was preferentially

removed, i.e., the proportion of area removed was larger by

8 percent than what existed in the Mississippi 1946–48

survey (Sternitzke and Putnam 1956).

Though Sternitzke and Putnam (1956) attributed much of

the change in the MAV’s forest composition to clearing of

forests in areas suitable for agricultural production, they also

noted heavy cutting during World War II for selected species.

Overcup oak and the then undifferentiated tupelo, i.e.,

today’s blackgum, swamp tupelo, or water tupelo, sawtimber

Table 4—Mississippi Alluvial Valley bottomland forest area by type and 

condition, Louisiana, 1934–1935 

 

Old growthb

Survey region and 

forest type 

All 

conditions 

Second 

growtha Partialc

 Uncutd

 

 

- - - - - - - - - - 1000 ha - - - - - - - - - - - - - % 

Northeast Louisiana, 1934 

 Baldcypress-water tupelo 38.5 24.0 8.5 6.0 16 

 Overcup oak-water hickory 328.7 71.4 107.8 149.5 45 

 Cottonwood and willowe 88.6 88.6 — — — 

 Mixed bottomland hardwood 

 Sweetgum-water oaksf 276.0 186.2 42.4 47.5 17 

 Hackberry-elm-ash 163.5 64.9 75.4 23.2 8 

 Water oaksf 78.9 42.3 30.0 6.6 17 

 Other mixtures 99.9 76.7 22.1 1.0 1 

 

 Total 1,074.1 554.1 286.2 233.8 22 

South Louisiana Delta, 1935 

 Baldcypress-water tupelo 442.0 349.7 72.4 19.8 14 

 Overcup oak-water hickory 142.0 53.3 40.6 48.0 22 

 Cottonwood and willowe 193.2 193.2 — — — 

 Mixed bottomland hardwood 

 Sweetgum-water oaksf 233.9 191.1 28.6 14.1 6 

 Hackberry-elm-ash 163.6 132.1 28.6 2.8 2 

 Water oaksf 44.2 36.0 7.8 0.4 1 

 Other mixtures 133.9 109.9 16.6 7.4 6 

 

 Total 1,352.8 1,065.3 194.6 92.6 7 

aVegetative growth habits typical of abandoned clearings, recent catastrophic 

disturbances, or new riverbank soil deposits (Winters and others 1938). 

b

 Stands composed of sawtimber trees with the characteristics of the original mature trees 

of the region (Eldredge 1937). 

c = 10 percent volume removed but characterized by residual trees from the old-growth 

forest (Eldredge 1937). 

d < 10 percent volume removed (Eldredge 1937). 

e Early successional types defined in the 1930s as transitional, having no maturity potential 

(Winters and others 1938). 

f Water, Nuttall, and willow oak. 

Sources: Winters 1939b, Winters and others 1938. 
35

Table 5—Bottomland forest area by type and survey period, Arkansas, Louisiana, and Mississippi 

Delta survey units, 1930s to 1990s 

Survey period 

Forest type 

Change 

since 

the 

1930s 

1991– 

1995 

1984– 

1988 

1974– 

1978 

1964– 

1969 

1947– 

1954 

1932– 

1935a

Percent - - - - - - - - - - - - - - - - - - - - - 1000 ha - - - - - - - - - - - - - - - - - 

Baldcypress-water tupelo -34 380.4 412.9 363.4 NA 439.8 573.5 

Overcup oak-water hickory -71 210.4 217.7 286.8 NA 549.6 717.6 

Cottonwood-willow -59b 327.8 467.2 

 Willow 146.3 135.4 127.7 NA NA NA 

 Cottonwood 43.9 42.7 57.1 NA NA NA 

Mixed bottomland hardwood 2,239.0c

 Sweetgum-mixed -53 402.1 399.3 494.7 NA NA 851.8 

 Hackberry-elm-ash -9 565.4 545.1 590.2 NA NA 618.6 

 Other mixtures -69 287.4 366.0 NA NA 1,054.4 

 

 Total -52 2,080.1 2,040.5 2,285.9 2,702.2 3,556.2 4,346.1 

NA - not available. 

a 1932–35 adjusted to this three-State region by multiplying Mississippi Alluvial area estimates in table 1 by 0.84 (4,364.1 

divided by 5,190.5). 

b Cottonwood and willow. 

c

 Sweetgum-mixed, hackberry-elm-ash, and other mixtures; no details available.

volume declined 27 percent between the 1930s and 1947–

54 survey period (Sternitzke and Putnam 1956), which is

limited evidence suggesting that the 1930s remnant oldgrowth forests dominated by these species were

extensively logged. During the same period, baldcypress

sawtimber volume increased by 33 percent—limited

evidence suggesting the 1930s remnant old-growth forests

dominated by baldcypress were not extensively logged.

By the 1947–54 surveys, poletimber and smaller diameter

class area represented 45 percent of bottomland hardwood

communities, and almost one-half were in the mixed types.

Sternitzke and Putnam (1956) ascribed the predominance

of younger age conditions to extensive cutting and some to

reversion to forest after farm abandonment during the

Depression and World War II.

Area in poletimber and smaller diameter class was greater

for the 1947–54 survey period than subsequent years (fig.

3). Baldcypress-water tupelo area in sawtimber diameter

class increased between the 1947–54 period and 1990s.

With this exception, area in sawtimber diameter class was

also greater for the 1947–54 period than in subsequent

years. Later surveys showed declines in nearly all bottomland hardwood community types classed as poletimber and

smaller diameter class, and a slower, smaller increase in

the sawtimber diameter class (fig. 3).

Comparisons of Bottomland Hardwood

Community Type in the South-Central

United States

Based on an ocular comparison of a forest occurrence

probability grid by flood zones and shade tolerance,

community types today appear to occupy more of the grid in

South-Central United States’ bottomland hardwoods (fig. 4A)

than in the MAV (fig. 4B). To gain a better understanding of

the community types depicted in the above grids, I crossreferenced Rudis’s (1995) empirically defined community

types with FIA community types. Lines in figure 5 join

empirical community types containing at least 50 percent of

each FIA community type. For the most part, FIA community

types represented a narrow range of flood zones. Exceptions

were sweetbay-swamp tupelo-red maple type which

occupied a broad range of flood zones, and swamp chestnut

oak-cherrybark oak type, which was in the sporadic flood

zone but had no majority affiliation with any empirical

community type.

Closer inspection of the forest occurrence probability grids

for the South-Central United States (fig. 4A) and MAV (fig.

4B) show a gap around flood code 5, shade code 2.5, which

corresponds to blackgum (NY) and American holly (IO)

empirical community types, and swamp chestnut oakcherrybark oak FIA community type in figure 5. A second,

smaller gap in the MAV grid occurs around flood code 3,

shade code 3.5, which corresponds to the swamp tupelo

=

- - -

=

2,239.0C

-59b
36

(NB) empirical community type, or the FIA swamp tupelosweetbay community type (fig. 5).

Quantitative species-based comparisons corroborate these

qualitative comparisons. Species representing > 3 percent

dry weight importance in the east or west south-central Gulf

Coastal Plain, but not the MAV, include: blackgum,

cherrybark oak, hickory, laurel oak, loblolly pine, sweetbay,

swamp tupelo, and yellow-poplar (McWilliams and Rosson

1990).

Old-Growth Potential

By selecting only sampled forests with >0.05 percent basal

area from trees >50 cm d.b.h. (table 6), one obtains

estimates from forests visually perceived as older stands.

Community distribution along the flood zone-shade

Figure 3—Forest area by diameter class for Arkansas, Louisiana, and Mississippi Delta survey units,

1947–95. For 1947–54 surveys, no data within mixed hardwood (MH) types. Sawtimber diameter class,

1947–54: forests with hardwood trees ≥ 27.9 cm, softwoods ≥ 22.9 cm, and net volume > 1,500 board

feet (sic, no metric equivalent); 1974 and later: ≥ 50-percent stocked with trees ≥ 12.7 cm diameter,

and ≥ 50-percent stocked with trees > 27.9 cm (hardwoods), > 22.9 cm (softwoods). Poletimber and

smaller-diameter class: forests with trees not meeting sawtimber-diameter class criteria.

Table 6—Bottomland hardwood forest area by forest type and proportion of large tree 

basal area in the Arkansas, Louisiana, and Mississippi Delta survey units, 1991–1995 

Percent large tree basal areaa

Forest type 

All 

areas None > 0.1 0.1–20 21–40 > 40 

 

- - - - - - - - - - - - - - - - - 1000 ha - - - - - - - - - - - - - - - 

Baldcypress-water tupelo 380.4 39.0 341.4 188.9 111.9 40.7 

Overcup oak-water hickory 210.4 14.9 195.5 60.0 76.5 59.1 

Willow 146.3 60.3 90.0 30.9 14.8 40.3 

Cottonwood 43.9 8.0 35.9 7.6 5.2 23.1 

Sweetgum-Nuttall oak-willow oak 402.1 19.0 383.1 120.7 135.5 126.9 

Hackberry-elm-ash 565.4 58.1 507.4 127.1 224.3 156.0 

Sweetbay-swamp tupelo-red maple 47.7 11.8 36.0 17.2 14.8 3.9 

Sycamore-pecan-elm 60.0 16.2 43.8 16.9 15.5 11.4 

Other mixed 221.0 38.8 185.2 74.6 63.2 47.4 

 

 Total 2,080.1 266.0 1,814.2 643.8 661.6 508.7 

 

aBasal area of live trees = 50 cm diameter at 1.4 m (d.b.h.) divided by basal area of live trees = 12.7 

cm d.b.h. 

≥ ≥
37

Figure 4—Predicted bottomland-hardwood occurrence by average flood zone and shade tolerance: (A)

South-Central United States bottomland hardwoods, 1986–91. (Sample size: 5,366, i.e., 2,666 estimates

from forest area samples based on tree importance values and 2,700 randomly assigned estimates

representing nonforested, former bottomland hardwood forests; (B) Arkansas, Louisiana, and Mississippi

Delta survey units, 1987–91. (Sample size: 1,724, i.e., 824 estimates from forest area samples based on

tree importance values and 900 randomly assigned estimates representing nonforested, former

bottomland hardwood forests).

(B)

(A)
38

tolerance grid shows a very limited occurrence in flood zone

codes 4 through 6 and shade tolerance codes 2 and 3 (fig.

6).

A more conservative distribution of potential old-growth

types emerges with the biological maturity criteria (table 7).

Most communities in flood zone codes 5 disappear. These

correspond to FIA community types like swamp chestnut

oak-cherrybark oak and sycamore-pecan-elm. Primarily it is

flood codes 2 through 4, i.e., baldcypress-water tupelo,

overcup oak-water hickory, cottonwood, and willow, that

have basal area equal to or greater than the range

associated with mature forests (fig. 6B). Basal area from

mature, i.e., 45- to 65-year-old southern bottomland

hardwood, forests range from 20.9 to 29.6 m2 per hectare

(table 7). This range compares favorably with one 1990 27.4-

m2

-per-hectare estimate from three southern floodplain

research natural areas known to contain old-growth trees

(Devall and Ramp 1992) and Martin’s (1992) 25-m2

-perhectare minimum for mixed mesophytic, old-growth forests.

Additional criteria [net growth 0+1.4 m3

 per hectare per year

(fig. 7A) and no harvest since the previous survey (fig. 7B)],

reveal that the greatest old-growth potential occurs in the

wettest community types. Combining the three biological

maturity criteria with the size criterion shows that estimates

even smaller (table 8).

Ownership is largely in private hands, even when estimating

area with old-growth potential (table 9). By forest type,

corporate owners—frequently banks, insurance firms,

agricultural businesses, and, in Louisiana, companies with

oil production interests—control a large percentage of

baldcypress-water tupelo area, even when based on the

most restrictive old-growth criteria (table 10).

Fragmentation and Changes 1970s to 1990s

If small in area, a forest fragment is more likely than a large

forest fragment to show evidence of livestock use and

selected human intrusions (beverage, food, and other

containers; trash; buildings; foundations; and fences); to be

closer to agricultural and urban areas, roads and fences;

and to contain less timber growing stock (Rudis 1995). If

large, a forest fragment is more likely to have Spanish moss

(Tillandsia usneoides L.) and signs restricting hunting

activities (Rudis 1995). Larger forest fragments are from the

permanent flood zone types; smaller fragments are from

sporadic, intermittent, and periodic flood zone, early

successional community types (Rudis 1995). These indices

suggest change in the uses and resource values of remnant

Figure 5—Forest Inventory and Analysis (FIA) community types and empirical-community types by average

flood zone and shade tolerance value, South-Central United States bottomland hardwoods. Linked are

empirical types that also categorize ≥ 50 percent of the FIA community type. Empirical community type codes

by dominant species (additionally coded by percent importance if characteristic of more than one type): A34-

red maple, A47-red maple, AN-boxelder, C65-hackberry, C35-hackberry, CC-blue-beech, CL-pecan, CQwater hickory, CR-hawthorne, CX-other hickories, F58-green ash, F29-green ash, IO-American holly, L80-

sweetgum, L46-sweetgum, L25-sweetgum, MV-sweetbay, MX-mixed, importance < 5 percent for any one

species, NB-swamp tupelo, NQ-water tupelo, NY-blackgum, OO-no trees, > 2.5 cm at 1.4 m, PD-cottonwood,

QL-overcup oak, QN-water oak, QP-willow oak, T44-baldcypress, T88-baldcypress, UA-winged elm, UCcedar elm, UM-American elm (after Rudis 1995). Sample size = 2,666 plots.

23456

Flood zone (annual inundation)

1

2

3

4

5

Very

tolerant

<1 month

Very

intolerant

T88

NQ

SX PD

NB

T44

A34

CQ

QL

A47 F58

F29

CC

IO

NY

MX

L25

UA

CL QN

CX

UM

L46

MV AN

OO

UC

L80 C65

C35

QP

Baldcypresswater tupelo

Willow Cottonwood

Overcup oakwater hickory

Hackberryelmash

SweetgumNuttall oakwillow oak SycamoreSweetbay- pecan-elm

swamp tupelored maple

CR

Swamp chestnut oakcherrybark oak

3-6 months 1-2 months only in

 wet years

>6 months
39

Table 7—Maturity criteria, bottomland forest area, and sample size by potential 

site productivity and maturity class, Arkansas, Louisiana, and Mississippi 

Delta survey units, 1991–1995 

 

Maturity criteriaa Arkansas, Louisiana, and Mississipppi 

Delta survey units 

Potential site 

productivity class Basal 

area 

Sample 

size All areas =Maturity criteria 

 

 m3/ha/yr m2/ha Number 1000 ha Number 1000 ha Number 

 

15.8 or more 29.6 3 92.0 39 23.1 10 

11.6 to 15.7 25.6 10 223.8 94 83.8 35 

8.4 to 11.5 23.7 15 381.0 154 179.9 74 

6.0 to 8.3 22.6 19 681.0 279 356.6 145 

3.5 to 5.9 21.8 17 623.9 253 361.3 146 

1.4 to 3.4 20.9 6 78.4 34 37.8 16 

 

 Total 2,080.1 853 1,042.5 426 

 

a Average stand basal area and sample size for 45- to 65-year-old bottomland forest stands. 

Stand age represents the mean of five dominant trees spaced = 20 m within a 0.4-ha area. 

Source: East Texas 1986 surveys.

≥

≥

≥

Table 8—Bottomland forest area by forest type and growth criteria for the Arkansas, 

Louisiana, and Mississippi Delta survey units, 1991–1995 

Growth criteriaa A, B, C, and percent 

large tree basal areab 

Forest type 

All 

areas A A, B A, B, C 1–100 1–20 21–40 >40 

 

 - - - - - - - - - - - - - - - - - - - - - - 1000 ha - - - - - - - - - - - - - - - - - - - - - 

 

Baldcypress-water tupelo 380.4 290.1 75.9 37.5 34.7 14.7 10.2 9.8 

Overcup oak-water hickory 210.4 110.6 20.2 13.1 13.1 4.2 2.3 6.6 

Willow 146.3 54.3 14.7 4.6 4.6 2.7 1.9 

Cottonwood 43.9 12.6 — — — — — — 

Sweetgum-Nuttall oak- 

 willow oak 402.1 204.5 38.5 15.9 15.9 4.6 5.1 6.2 

Hackberry-elm-ash 565.4 264.9 80.0 18.3 18.3 7.3 6.8 4.3 

 

47.7 25.2 — — — — — — 

Sweetbay-swamp tupelo-

 red maple 

Sycamore-pecan-elm 60.0 15.4 2.6 2.6 2.6 — 2.6 — 

Other mixed 221.0 65.0 19.1 14.5 9.3 2.4 6.9 — 

 

 Total 2,080.1 1,042.5 209.1 106.5 98.5 33.3 29.5 35.7 

 

a

 A is average basal area of 45- to 65-year-old bottomland hardwood stands (table 7); B is net growth on live 

trees = 0 ± 1.4 m3

 per hectare per year; C is no evidence of commercial harvest since prior surveys (about 7 

years earlier). 

b b Basal area of live trees Basal area of live trees = 50 cm diameter at 1.4 m (d.b.h.) divided by basal area of live trees = > 50 cm diameter at 1.4 m (d.b.h.) divided by basal area of live trees 12.7 d.b.h. > 12.7 d.b.h.
40

Figure 6—Predicted bottomland-hardwood occurrence, Arkansas, Louisiana, and Mississippi Delta

survey units by average flood zone and shade tolerance for forests with: (A) large trees (> 0.1 percent

basal 3 50 cm diameter at 1.4 m (d.b.h.) divided by basal area of live trees > 12.7 cm d.b.h.; (B) basal

area 3 average for 45- to 65-year-old southern bottomland-hardwood communities by potential site

productivity class (20.9 to 29.6 square meters per hectare, productivity classes 1.4 to 3 15.8 cubic

meters per hectare per year [see table 7]).

>

> >

(A)

(B)
41

Figure 7—Predicted bottomland-hardwood occurrence, Arkansas, Louisiana, and Mississippi Delta survey

units by average flood zone and shade tolerance for (A) forests with basal area >= potential site-productivity

averages for 45- to 65-year-old southern bottomland-hardwood communities and net growth = 0 + or - 1.4

cubic meters per hectare per year; (B) forests with conditions listed in (A) and no evidence of commercial

harvest activity.

(A)

(B)
42

or regenerated forests. On average, fragmented forest cover

is less likely to retain or recover the resource values

associated with the region’s once large, contiguous forests.

Between the 1970s and 1990s, total forest area in the MAV

changed only slightly, from 2.3 to 2.1 million ha, but there

was a shift to fragment size classes < 2000 ha (fig. 8), and to

baldcypress-water tupelo community types (table 11). For

the largest (> 2023 ha) fragment size class, the decline was

primarily in mixed hardwoods and hackberry-elm-ash (table

11). Declines in the largest fragment class were 9 percent in

baldcypress-water tupelo, and above 30 percent in all other

community types examined.

SUMMARY AND IMPLICATIONS

Comparisons with historical MAV data showed that the

sporadic flood zone, late-successional community types,

especially mixed bottomland hardwoods, were the most

Figure 8—Bottomland-hardwood forest area by fragment size class and survey year, Arkansas, Louisiana, and

Mississippi Delta survey units, 1974–78, 1984–88, and 1991–95.

1974–78

2285.9

1984–88

2044.3

1991–95

2080.1

All classes (1000 hectares)

0.4–4 5–20 21–40 41–202 203–1012 1013–2023 > 2023

1000 hectares

Fragment size class (hectares)

Table 9–Bottomland forest area by forest type and growth criteria in the 

Arkansas, Louisiana, and Mississippi Delta survey units, 1991–1995 

Growth criteriaa

 

Forest type All areas A A, B A, B, C 

 

1000 

ha % 

1000 

ha % 

1000 

ha % 

1000 

ha % 

Public 300.6 14 148.4 14 11.9 6 7.7 7 

Other corporateb

 526.9 25 308.9 30 67.1 32 29.9 28 

Forest industry 272.3 13 123.5 12 23.4 11 14.4 14 

Farmer 405.2 19 171.8 16 46.2 22 25.3 24 

Other privatec

 575.1 28 289.9 28 60.6 29 28.6 27 

 

 Total 2,080.1 100 1,024.5 100 209.1 100 106.5 100 

a

 A is = average basal area of 45- to 65-year old bottomland hardwood stands (table 7); B is 

net growth on live trees = ± 1.4 m3 per hectare per year; C is no evidence of commercial 

harvest since prior surveys (about 7 years earlier). 

b Other than forest industries. 

c

 Other than farmers and corporate owners.

Table 9–Bottomland forest area by forest type and growth criteria in the 

Arkansas, Louisiana, and Mississippi Delta survey units, 1991–1995 

Growth criteriaa

 

Forest type All areas A A, B A, B, C 

A is >average basal area of
43

 

Growth criteriaa

Forest type and 

owner class All areas A A, B A, B, C 

 

 

1000 ha % 1000 ha % 1000 ha % 1000 ha % 

Baldcypress-water tupelo 

 Public 15.0 4 12.7 4 1.4 2 — — 

 Other corporateb 166.5 44 133.4 46 35.3 47 15.5 41 

 Forest industry 39.9 10 34.2 12 7.7 10 7.7 21 

 Farmer 57.2 15 19.8 7 5.1 7 5.1 14 

 Other privatec 101.8 27 90.0 31 26.3 35 9.2 25 

 

 Total 380.3 100 290.1 100 75.9 100 37.5 100 

Overcup oak-water 

 hickory, cottonwood, 

 and willow 

 Public 98.1 26 47.1 27 3.9 11 3.9 22 

 Other corporateb 92.0 22 39.5 22 12.5 36 7.3 41 

 Forest industry 51.8 13 22.7 13 5.1 15 — — 

 Farmer 64.2 17 29.4 17 6.9 20 4.2 24 

 Other privatec 94.5 22 38.7 22 6.6 19 2.2 13 

 

 Total 400.6 100 177.4 100 35.0 100 17.6 100 

Sweetgum-Nuttall oak- 

 willow oak 

 Public 60.8 15 33.2 16 — — — — 

 Other corporateb 64.1 16 30.1 15 7.9 21 — — 

 Forest industry 42.3 11 20.0 10 6.3 16 4.3 27 

 Farmer 101.6 25 52.9 26 14.6 38 6.5 41 

 Other privatec 133.3 33 68.3 33 9.7 25 5.1 32 

 

 Total 402.1 100 204.5 100 38.5 100 15.9 100 

Hackberry-elm-ash 

 Public 84.3 15 34.9 13 — — — — 

 Other corporateb 144.2 26 79.7 30 6.1 16 2.0 11 

 Forest industry 104.7 19 40.2 15 2.0 5 — — 

 Farmer 86.9 15 40.0 15 17.2 45 9.5 52 

 Other privatec 145.4 26 70.0 26 12.8 34 6.9 37 

 

 Total 565.4 100 264.9 100 38.0 100 18.3 100 

Mixed hardwoods 

 (sycamore-pecan-elm, 

 sweetbay-swamp 

 tupelo-red maple, and 

 other mixed) 

 Public 42.4 15 20.5 26 6.5 30 3.9 22 

 Other corporateb 38.4 14 14.3 18 5.3 24 7.3 41 

 Forest industry 31.7 11 4.4 5 2.4 11 — — 

 Farmer 88.4 31 25.0 31 2.4 11 4.2 24 

 Other privatec 82.9 22 16.2 20 5.2 24 2.3 13 

 

 Total 283.9 100 80.4 100 21.7 100 17.6 100 

Table 10—Bottomland forest area by forest type, owner, and growth criteria in the

Arkansas, Louisiana, and Mississippi Delta survey units, 1991–1995

a

 A is ≥ average basal area of 45- to 65-year old bottomland hardwood stands (table 7), B is net growth on

live trees = ± 1.4 m3 per hectare per year, C is no evidence of commercial harvest since prior surveys (about

7 years earlier).

b

 Other than forest industries.

c

 Other than farmers and corporate owners.

 

Growth criteriaa

Forest type and 

owner class All areas A A, B A, B, C 

 
44

Table 11—Bottomland forest area by forest type, survey period, change since the 

1970s, and forest fragment size class in Arkansas, Louisiana, and Mississippi Delta 

survey units 

 

 Forest fragment size class (hectares) 

 

All size 0.4 to 41 to 203 to 1,013 to 

Forest type and survey period classes 40 202 1,012 2,023 >2,023 

 

 - - - - - - - - - - - - - - - -1000 ha - - - - - - - - - - - - - - - - - 

 

Baldcypress-water tupelo 

363.4 23.9 19.9 63.7 78.3 177.6 

412.9 23.0 48.7 78.0 72.2 190.8 

380.4 28.6 58.0 62.6 69.8 161.4 

 17.0 4.7 38.1 -1.1 -8.5 -16.2 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent 5 20 2 -2 -11 -9 

 

Overcup oak-water hickory, 

 cottonwood, and willow 

 

471.6 54.3 71.0 130.1 83.9 132.4 

395.8 44.9 62.6 118.5 53.3 118.4 

400.6 55.3 82.9 88.1 82.4 92.0 

-71.0 1.0 11.9 -42.0 -1.5 -40.4 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent -15 2 17 -32 -2 -31 

 

Sweetgum-Nuttall oak-willow oak 

494.7 106.4 90.0 128.7 86.9 82.6 

399.3 78.9 95.0 91.7 70.0 64.2 

402.1 80.2 87.1 121.4 71.3 42.0 

-92.6 -26.2 -2.9 -7.3 -15.6 -33.7 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent -19 -25 -3 -6 -18 -41 

 

Hackberry-elm-ash 

590.2 50.7 69.3 150.7 83.8 235.8 

545.1 70.4 73.7 147.2 121.4 132.7 

565.4 74.4 101.8 167.8 129.1 92.4 

-24.8 23.7 32.5 17.1 45.3 -143.4 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent -4 47 47 11 54 -61 

 

Mixed hardwoods (sycamore- 

 pecan-elm, sweetbay-swamp- 

 tupelo-red maple, and other 

 mixed) 

366.0 49.8 62.2 72.4 42.4 139.2 

287.4 58.6 65.0 66.8 48.8 49.4 

331.6 74.0 81.0 112.1 29.1 35.3 

-34.4 24.2 18.8 39.7 -13.3 -103.9 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent -9 49 30 55 -31 -75 

 

All forest types 

2,285.9 285.1 312.5 545.5 375.2 767.6 

2,044.3 275.8 344.9 502.3 365.8 555.6 

2,080.1 312.6 410.8 552.0 381.7 423.0 

-205.8 27.5 98.3 6.5 6.5 -344.6 

 1974–1978 

 1984–1988 

 1991–1995 

 Change 

 Percent -9 9 31 1 2 -45 

- - - - - - - - - - - - - - - - 1000 ha - - - - - - - - - - - - - - - - -
45

vulnerable to anthropogenic intrusions. The permanent flood

zone community types typified by baldcypress-water tupelo,

and the intermediate flood zone, early successional

community types typified by hackberry-elm-ash were the

least vulnerable. Since the 1970s, the largest (> 2023 ha)

forests have continued to decline, with the nonpermanent

flood zone types most affected. Based on old-growth criteria

(potential site productivity-based minimum basal area, net

growth near zero, and absence of harvest activity),

permanent flood zone bottomland community types were

associated with the most old-growth potential and large

forest fragments and were primarily in private ownership.

Nonpermanent flood zone types were associated with small

forest fragments and the least old-growth potential. Clewell

and Lea (1989) and Zedler and Weller (1989) describe

associated forested wetland creation, maintenance,

restoration, and research needed.

National reforestation programs to restore forested

communities, such as the 1970s Forestry Incentive Program

and the 1980s Conservation Reserve Program, have not

traditionally focused on regional shifts in species or

community types or forest fragmentation. If restoration of

historic community types is also a desired future goal, these

programs require approaches sensitive to regional changes.

Declines in large forest fragments suggest losses in their

associated values, e.g., optimal habitat for black bear (Rudis

and Tansey 1995) and primitive recreational opportunities

(Rudis 1987, 1995). Hoover and Shannon (1995) suggest

social and political institutions and processes to maintain

regional conservation land corridors and mitigate

fragmentation, e.g., formal regional planning, informal

adjacent landowner cooperation, and more stakeholder

participation in the planning process.

If restoration of the 1930s proportion of MAV bottomland

hardwood community types is desired, these programs will

require focused efforts that (1) shift area of hackberry-elmash toward late-successional types, (2) establish species

typical of likely missing bottomland hardwood types, e.g.,

swamp chestnut oak-cherrybark oak, (3) conserve remaining

late-successional, nonpermanent flood zone types, and (4)

foster occasional flooding characteristic of sporadic,

intermittent, and periodic flood zones. Localized

reforestation along rivers and streams and reconnection

among existing small bottomland hardwood remnants also

improve chances for recovery of landscape and regional

scale values, e.g., water quality and habitats for selected

wildlife species characteristic of floodplain forests (Hamel

2001).

ACKNOWLEDGMENTS

This manuscript benefited from informal and formal

discussions at the conference held in Fayetteville, AR,

October 1995. Tom Foti, Jim Rosson, and John Vissage

offered additional suggestions. I especially thank an

anonymous reviewer for a thorough review and very helpful

suggestions.

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47

APPENDIX A

Common and scientific names as listed in the text (Little 1979):

Common name Scientific name

Ash Fraxinus spp.

Green ash F. pennsylvanica Marsh.

White ash F. americana L.

Baldcypress Taxodium disticum (l.) Rich. var. distichum

American beech Fagus grandifolia Ehrh.

River birch Betula nigra L.

Blackgum Nyssa sylvatica var. biflora (Walt.) Sarg.

Blue-beech Carpinus caroliniana Walt.

Boxelder Acer negundo L.

Cottonwood Populus tremuloides Michx.

Elm Ulmus spp.

American elm U. americana L.

Cedar elm U. crassifolia Nutt.

Winged elm U. alata Michx.

Hackberry Celtis laevigata Willd.

C. occidentalis L.

Hawthorn Crataegus spp.

Hickory Carya spp.

C. illinoensis (Wangenh.) K. Koch

Water hickory C. aquatica (Michx f.) Nutt.

American holly Ilex opaca Ait

Southern magnolia Magnolia grandiflora L.

Red maple Acer rubrum L.

Oak Quercus spp.

Cherrybark oak Q. falcata var. pagodifolia Ell.

Delta post oak Q. stellata var. paludosa Sarg.

Laurel oak Q. laurifolia Michx.

Nuttall oak Q. nuttallii Palmer

Overcup oak Q. lyrata Walt.

Shumard oak Q. shumardii Buckl.

Swamp chestnut oak Q. michauxii Nutt.

Water oak Q. nigra L.

White oak Q. alba L.

Willow oak Q. phellos L.

Pecan Carya illinoensis (Wangenh.) K. Koch

Persimmon Diospyros virginiana L.

Loblolly pine Pinus taeda L.

Slash pine P. elliottii Engelm.

Sweetbay Magnolia virginiana L.

Sweetgum Liquidambar styraciflua L.

Sycamore Platanus occidentalis L.

Swamp tupelo Nyssa sylvatica var. biflora (Walt.) Sarg.

Water tupelo N. aquatica L.

WIllow Salix spp.

Yellow-poplar Liriodendron tulipifera L.
48

Flood zones—Sporadic, intermittent, nonpermanent,

permanent zones.

Forest types—Community types recognized by Forest

Inventory and Analysis and named by the species that

comprise the majority of the stocking. These include:

baldcypress-water tupelo associates include green ash, red

maple, and sweetgum. This type occurs chiefly on very wet

sites where surface water is present throughout the growing

season in years of normal rainfall. Cottonwood associates

include willow, white ash, green ash, and sycamore. Sites are

along stream banks where bare moist soil is available, e.g.,

along river and stream margins. Hackberry-elm-ash

associates include water oak, willow oak, laurel oak,

sweetgum, water hickory, and boxelder. Sites are typical of

river margins and moist bottoms. Overcup oak-water hickory

associates include green ash, hackberry, American elm, red

maple, and persimmon. Sites are in low-lying, poorly drained

flats with clay or silty-clay soils. Sycamore-pecan-elm

associates include boxelder, green ash, hackberry,

cottonwood, willow, sweetgum, and river birch. Sites are on

alluvial flood plains. Swamp chestnut oak-cherrybark oak

associates include white oak, Delta post oak, Shumard oak,

white ash, and hickories. Sites are on terraces or ridges in

first bottoms. Sweetbay-swamp tupelo-red maple associates

include slash pine, and moist site hardwood species. Sites

normally have saturated soils throughout the growing

season, such as along branch heads, drains, bays, and

swamp borders. Sweetgum-Nuttall oak-willow oak

associates include cottonwood, green ash, sycamore,

pecan, American elm, red maple, and boxelder. This type

occurs chiefly on sites with exposed moist soil such as

stream banks and pond margins.

Saplings—Live trees with stems 2.5 to < 12.7 cm in d.b.h.

Seedlings—Live trees with stems <2.5 cm in d.b.h. and >

3.0 cm tall for hardwoods, >1.5 cm tall for softwoods.

Stand diameter class—A classification of the height and

size of trees in a stand. Sawtimber diameter class stands are

>50 percent stocked with live trees >12.7 cm d.b.h. and >50

percent stocked with sawtimber (>22.9 cm softwood and >

27.9 cm hardwood) trees. Poletimber stands are >50

percent stocked with live trees > 12.7 cm and <50 percent

stocked with sawtimber trees. Smaller diameter class stands,

typically composed of saplings and seedlings, are < 50

percent stocked with live trees < 12.7 cm.

Stocking—Degree of occupancy of land by live trees. It is

measured by basal area or number of trees by size and

spacing, or both, as a percent of a specified standard, which

is the basal area or number of trees, or both, required to

utilize the tree growth potential of the land.

APPENDIX B

Definition of Terms
49

THE EFFECT OF HERBIVORY BY WHITE-TAILED DEER AND

ADDITIONALLY SWAMP RABBITS IN AN OLD-GROWTH

BOTTOMLAND HARDWOOD FOREST

Margaret S. Devall, Bernard R. Parresol, and Winston P. Smith1

Abstract—Forest openings create internal patchiness and offer different habitat qualities that attract wildlife, especially

herbivores, that flourish along forest edges. But intense herbivory in these openings can reduce or eliminate herbaceous

and woody species and thus influence local species composition and structure of the forest. This study in an old-growth

bottomland hardwood forest in southeastern Arkansas compares plant colonization among experimental plots, which

excluded white-tailed deer (Odocoileus virginianus), deer and swamp rabbits (Sylvilagus aquaticus), and control plots.

After the third year, plant species composition and abundance were significantly affected by herbivores.

1 Research Ecologist, USDA Forest Service, Southern Research Station, Stoneville, MS; Mathematical Statistician, USDA Forest Service,

Southern Research Station, Asheville, NC; and Research Wildlife Biologist, USDA Forest Service, Pacific Northwest Forest and Range

Experiment Station, Juneau, AK, respectively.

INTRODUCTION

Old-growth forests of various types, which had developed

with only low-intensity human disturbance, occupied much of

the presettlement landscape of Arkansas (Holder 1970).

European exploration and settlement of Arkansas began in

the 16th century. Although the forests provided a valuable

source of wood to European settlers, they were an

impediment to farming. Wetland forests were especially

threatened because at the time of European colonization

wetlands were considered useful only after they were

drained. The Swamp Land Acts of 1849–1850 granted

swamplands in Federal ownership to the States to be

reclaimed and disposed of; thereafter, widespread

destruction of forested wetlands proceeded at a rapid rate

(Turner and Craig 1980). Since colonial times almost half of

the wetlands in the United States have been destroyed, and

until recently thousands of acres were lost each year

(MacDonald and others 1979). As a result, while old-growth

forests are becoming less common throughout the United

States, old-growth forested wetlands are even scarcer.

Although much is unknown about old-growth forests, it is

obvious that many of their characteristics are different from

those of younger forests (Juday 1988, Runkle 1991). While

numerous definitions of old-growth forests have been

suggested, two features occur in many of these definitions:

(1) trees die singly or in small groups, creating openings or

gaps in which regeneration of seedlings can occur; and (2)

large logs and snags account for many of the values of the

forests (Runkle 1982, 1991). For example, they provide food,

shelter, or germination sites for various plant and animal

species (Harmon and others 1986). Conversely, in many

younger eastern forests large-scale disturbances occur often

enough to be the dominant influence on their structure and

composition (Runkle 1982, 1991).

Increased densities of deer (Odocoileus virginianus) and

other herbivores that thrive in fragmented forests can alter

plant species composition and structure (Alverson and

others 1988). Swamp rabbits (Sylvilagus aquaticus) can be

serious deterrents to the establishment of tree seedlings in

wetlands. They clip seedlings at various heights above the

ground and eat the tender parts (Blair and Langlinais 1960).

Although there have been numerous studies of the effects of

white-tailed deer on forests (Anderson and Loucks 1979,

Alverson and others 1988, Griffin 1976, Richards and

Farnsworth 1971, Ross and others 1970, Stewart and

Burrows 1989), deer habitat and behavior vary considerably

from one part of the country to another, and their effects on

different plant species vary. Therefore, local studies are

indispensable in answering questions about the effects of

deer on a particular forest type (Strole and Anderson 1992).

Moreover, the consequences of disturbance regimes and

herbivory on old-growth bottomland hardwood forests are

not well known because there have been few studies on the

remaining old-growth wetland forests. The purpose of this

study is to determine the effects of white-tailed deer and

swamp rabbits on plant species diversity. Specific objectives

include testing the hypotheses that species composition of

tree regeneration is independent of white-tailed deer or

combined white-tailed deer and swamp rabbit use of gap

openings; and that plant species richness, abundance, and

diversity within gaps are independent of white-tailed deer or

white-tailed deer and swamp rabbit use.

The study area (Moro Bottoms) is a 40-ha old-growth

bottomland hardwood forest located in Cleveland County,

AR. It is part of a larger area owned by the Arkansas Natural

Heritage Commission and the Arkansas Nature

Conservancy. Dominant tree species at Moro Bottoms are

oaks (Quercus falcata var. pagodifolia Ell., Q. nigra L., Q.

lyrata Walt., Q. alba L., Q. phellos L., Q. michauxii Nutt., Q.

velutina Lam.), sweetgum (Liquidambar styraciflua L.), and

baldcypress [Taxodium distichum (L.) Rich.], with several

hickory species [Carya tomentosa (Poir.) Nutt., C. ovata

(Mill.) K. Koch and C. cordiformis (Wangenh.) K. Koch]. The

small tree and shrub layer includes ironwood (Carpinus

caroliniana Walt.), Carolina ash (Fraxinus caroliniana Mill.),
50

and hollies (Ilex opaca Ait., I. decidua Walt.).2

 Moro Bottoms

is an excellent example of a late transition bottomland

hardwood forest becoming old growth through gap

regeneration. Trees, especially sweetgum and cherrybark

oak, are quite large (up to 149 cm)3 with exceptionally good

form. Moro Bottoms provided an ideal opportunity to study

the effects of large mammalian herbivores on biodiversity in

wetland forest gaps. A severe windstorm during the late

summer of 1989 caused windthrows, which created gaps in

the overstory ranging from 0.1 to 0.5 ha. A cursory survey

before the study suggested moderate use of the area by

deer in late fall and greater use by swamp rabbits.4 Johnson

and others (1995) noted that older forests generally provide

the best foraging conditions for deer in fall and winter.

MATERIALS AND METHODS

Thirty paired plots consisting of herbivore exclosures and

adjacent unmanipulated controls were installed within

windthrow gaps. Each of the paired plots was randomly

placed on one side of a north-south line located

approximately through the center of each windthrow gap.

Exclosures were approximately 2.5 by 4 m and were

constructed of 5- by 10- cm welded wire fencing and 2.4-m

metal posts. The fence was elevated 15 cm from the ground

to allow entry of swamp rabbits. Within each exclosure ten

0.5- by 1.0-m quadrats were randomly located. These were

fenced with 2.5- by 5-cm welded wire 0.6 m high to

additionally exclude swamp rabbits. The remaining ten 0.5-

by 1.0-m plots were available to swamp rabbits, but were

protected from deer use. Adjacent to each exclosure was a

control plot with three fence posts along one side. The

control plot was divided into 10 contiguous 0.5- by 1-m

quadrats. The exclosures were constructed in 1990 during

winter prior to the growing season. While it would have been

ideal to set up a separate set of fencing to exclude only

swamp rabbits, and not to nest the rabbit exclosures inside

the deer exclosures, operationally it would have been

extremely difficult to accomplish. The logistics were such

that the only practical course was to nest the treatments.

Data were collected during spring, summer, and fall of 1990,

1991, and 1992. Percent cover for herbaceous species (0 to

5, 6 to 15, 16 to 25, 26 to 35 . . . 95 to 100) and total percent

cover were recorded in deer exclosures, deer-and-rabbit

exclosures, and control plots. During 1990 and 1991 total

cover of grasses and sedges were recorded in place of each

separate species, except for cane [Arundinaria gigantea

(Walter) Muhl.], because of the difficulty of identifying these

species when they were not fruiting or flowering; Smilax and

Vitis totals also were recorded. During 1992 all herbaceous

species were recorded separately. Duplicates of plant

species in the plots were collected from areas nearby and

identified; species not present in the exclosures were also

collected.

During each visit the number and species of shrub and tree

seedlings in each plot were recorded. All oak seedlings were

recorded as Quercus spp. during 1990 and 1991, but the

oaks were recorded by species during 1992. Oak seedling

leaves can be quite variable so a few hard-to-determine

seedlings were counted as red oak group. We were not able

to distinguish separate hickory or blueberry (Vaccinium spp.)

seedlings because of the difficulty of classifying seedlings

and small nonfruiting specimens of these species, so these

were recorded as Carya or Vaccinium spp. Plants were

collected and identified, using Radford and others (1968),

Little (1978), Steyermark (1963), Allen (1980), and Chabreck

and Condrey (1979). “An Atlas and Annotated List of the

Vascular Plants of Arkansas” (Smith 1988) was consulted to

verify that the species identified occurred in Arkansas.

During the summer of 1991, exclosure and control plots 16

and 20 were destroyed by tree falls; exclosures 31 and 32

with controls were subsequently constructed to replace

them. During the summer of 1992, falling trees destroyed

plots 9 and 30.

We assumed a priori there would be seasonal differences

and reasonably expected to have yearly differences, so we

dispensed testing for these effects. The most expedient

analyses for comparing treatments at each measuring

period were, therefore, simple paired t-tests. Hence, paired ttests were used to analyze the percent-cover data with the

following comparisons: deer exclusion versus control and

deer and rabbit exclusion versus control. Due to the nested

nature of rabbit exclosures with deer exclosures, no

statistically independent test could be constructed for

comparing the effects of rabbit exclosures versus deer

exclosures. Nonparametric analysis of variance (KruskalWallis test) was employed to evaluate the seedling data. A

probability of < 0.05 was accepted as statistical justification

for rejecting a null hypothesis.

RESULTS

One hundred and fifty-six vascular plant species were

present in the plots. Thirty-eight of these were tree or shrub

species. Twelve grass (Graminae spp.) species, 10 sedge

(Cyperaceae spp.) species, and 73 other herbaceous

species were recorded in the plots. Also, there were 13

woody vines (Vitaceae spp.), 8 nonwoody vines, and 2 ferns.

The number of plant species encountered varied

considerably among treatments. There was no clear pattern

of treatment effects across sampling periods on plant

diversity as reflected by species richness (mean number of

species per unit area), cumulative species (total number of

species across all plots in a treatment category), or number

of unique species (species that occurred in only one

treatment category) (fig. 1A–C).

2

 Peacock, Lance. 1983. Moro Bottoms site (preserve) summary.

Little Rock, AR: Arkansas Nature Conservancy. 7 p. Unpublished

report. On file with: The Nature Conservancy, Arkansas Field Office,

601 N. University Avenue, Little Rock, AR 72205.

3

 Devall, Margaret S. 1998. Dendroecological study of Moro Bottoms

Natural Area. 10 p. Unpublished data. On file with: U.S. Department

of Agriculture, Forest Service, Southern Research Station, Center

for Bottomland Hardwoods Research, P.O. Box 227, Stoneville, MS

38776.

4 Smith, Winston P.; Toliver, John R.; Devall, Margaret S.; Parresol,

Bernard R. 1990. Windthrow gaps in an old-growth bottomland

hardwood forest: wildlife use and consequent influence on forest

composition. 16 p. Study plan. On file with: U.S. Department of

Agriculture, Forest Service, Southern Research Station, Center for

Bottomland Hardwoods Research, P.O. Box 227, Stoneville, MS

38776.
51

 SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Sampling period

ControlDeerDeer and rabbit

Number of plant species

(A)

Figure 1A—Mean number of species per plot recorded seasonally in 5-m2 plots (species richnness). Moro Bottoms Natural Area (SP = spring, SU = summer,

AU = autumn).
52

Figure 1B—Number of species across all plots within a treatment category for each period (cumulative species). Moro Bottoms Natural Area (SP = spring,SU = summer, AU = autumn).

Number of plant species

ControlDeerDeer and rabbit

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Sampling period

(B)
53

ControlDeerDeer and rabbit

Number of plant species

 SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Sampling period

(C)

Figure 1C—Number of species found only in one treatment category for each period (unique species). Moro Bottoms Natural Area (SP = spring, SU = summer,AU = autumn).
54

Eighty plant species were present in the deer and in the

deer-and-swamp-rabbit exclosures in 1992, and 82 in the

controls. The number of species occurring in a plot ranged

from 9 to 25 in the deer exclosures, 9 to 31 in the deer-andswamp-rabbit exclosures, and 9 to 23 in the controls.

Percent cover of herbaceous vegetation recorded among

treatment and control plots during 1990–92 is summarized

in figure 2. Percent cover in the controls ranged from 15 to

100 with standard deviations ranging from 16 to 25; in the

deer exclusion plots, cover ranged from 5 to 100 with

standard deviations of 16 to 26; cover in the deer-and-rabbit

plots varied from 5 to 100 with standard deviations of 18 to

28. Percent cover of vegetation in the deer and in the deerand-rabbit exclosures was significantly less than that in the

control plots in the spring of 1990 (table 1). The control

versus deer comparison also was significant in the summer

of 1990. Significant differences did not occur again until the

summer of 1992, and in the fall of 1992 control versus deer

exclusion and control versus deer-and-rabbit exclusion were

both highly significant.

Means of percent cover of grasses, sedges, and other

herbaceous vegetation are presented in figure 3 A–C. In

general, percent cover of grasses and sedges was higher in

control plots than in deer or in deer-and-rabbit plots, while

coverage of other herbaceous species was higher in deer

and in deer-and-rabbit plots. Paired comparisons (t statistic)

of percent cover of grasses, sedges, and other herbaceous

vegetation between control and treatment plots

demonstrated that the observed pattern often reflected

significant variation among treatments (table 2).

The sum of woody seedlings of all species ranged from a

low of 138 in the deer exclosures in spring 1991 to a high of

761 in the deer-and-swamp-rabbit exclosures in 1992 (table

3). The total numbers of woody seedlings were similar (P>

0.05) among treatments during the 3 years of the study

(table 4). Although not significant, 1992 results showed

smaller probability values than the 1990 and 1991 data.

Significant differences among deer and deer-and-swamprabbit exclosures and controls were not demonstrated during

spring, summer, or fall of any year for selected species that

were thought to be favorite deer foods: sweetgum,

greenbriars, red maple (Acer rubrum L.), and oak species,

and for ironwood, which is eaten by deer, but is low choice

(Halls 1977).

Diversity of the stands was investigated using the Shannon

diversity index. Values of the Shannon index ranged from a

low of 3.15 to a high of 3.70 (fig. 4).

DISCUSSION

We studied the vegetation occurring in forest gaps, but did

not collect quantitative data beyond the gaps. Nevertheless,

some comparisons to other older bottomland hardwood

forests can be made. Moro Bottoms is in the west gulf

Coastal Plain. Other sites located in the Mississippi River

alluvial floodplain have different soils, stand origin, and

possible disturbance history. Robertson and others (1978)

studied woody species in two stands on Horseshoe Lake

Island in Alexander County, IL, one relatively undisturbed

and one recovering from disturbance in the late 1800’s or

early l900’s. Trees with the highest importance value in the

35-ha old-growth stand were sweetgum, red maple, and

green ash (F. pennsylvanica Marsh.). Sugar maple (A.

saccharum Marsh.), sweetgum, tupelo gum (Nyssa aquatica

L.), bitternut hickory, American elm (Ulmus americana L.),

northern red oak (Q. rubra L.), and sassafras [Sassafras

albidum (Nutt.) Nees] were dominants in the secondary

stand. In the old-growth shrub-sapling stratum, 22 woody

species were encountered, with pawpaw [Asimina triloba (L.)

Dunal], red buckeye (Aesculus pavia L.), buttonbush

(Cephalanthus occidentalis L.), grapes (Vitis spp.), and silver

maple (A. saccharinum L.) the dominant species. There were

20 species in the secondary forest. In the seedling stratum,

46 and 45 species of trees, shrubs, and vines occurred in

the old growth and secondary areas, respectively, compared

to 51 at Moro Bottoms. Pawpaw, red buckeye, green ash,

tupelo gum, and bitternut hickory dominated seedlings in the

secondary forest. The forests seem similar to that at Moro

Bottoms, except that the secondary forest at Horseshoe

Lake Island contained more fast-growing, short-lived

species.

Table 1—Paired comparisons of percent cover of

herbaceous vegetation in the Moro Bottoms exclosures

Standard Prob

Date Variable Mean error T > |T|

Spring 1990 C vs. D .08 .03 2.64 .01a

C vs. DR .11 .03 3.17 0 a

Summer 1990 C vs. D .08 .03 2.53 .02b

C vs. DR .04 .03 1.61 .12

Fall 1990 C vs. D .05 .03 1.61 .12

C vs. DR .02 .02 1.02 .32

Spring 1991 C vs. D .01 .03 .29 .78

C vs. DR -0 .02 -.15 .88

Summer 1991 C vs. D -0 .02 -.15 .88

C vs. DR .01 .03 .38 .70

Fall 1991 C vs. D .04 .02 1.83 .08

C vs. DR .02 .02 .82 .42

Spring 1992 C vs. D .04 .02 1.69 .10

C vs. DR .04 .02 1.73 .09

Summer 1992 C vs. D .06 .02 3.04 .01a

C vs. DR .08 .02 3.47 0 a

Fall 1992 C vs. D .11 .22 4.67 0 a

C vs. DR .08 .02 3.47 0 a

Vs. = versus; mean and standard error = standard error of

differences in percent cover; T = student’s t statistic; Prob >|T| =

associated probability from paired t-test; C vs. D = control versus

deer; C vs. DR = control versus deer-and-swamp rabbit.

a P = 0.01.

b P = 0.05
55

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Season and year

Mean percent

ControlDeerDeer and rabbit

Figure 2—Mean of percent ground cover of herbaceous vegetation within control, deer exclusion, and deer-and-rabbit exclusion plots, Moro Bottoms Natural Area.

(SP = spring, SU = summer, AU = autumn).
56

SP 1990 SU 1990 F 1990 SP 1991 SU 1991 F 1991 SP 1992 SU 1992 F 1992

Season and Year

(A)

Figure 3A—Mean of percent ground cover of grasses and sedges at Moro Bottoms Natural area. (SP = spring, SU = summer, AU = autumn).

ControlDeerDeer and rabbit

Percent cover

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Season and year
57

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Season and year

(B)

Figure 3B—Mean of percent ground cover of grasses and other herbaceous vegetation at Moro Bottoms Natural Area. (SP = spring, SU = summer, AU = autumn).

ControlDeerDeer and rabbit

Percent cover

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Season and year
58

(C)

Figure 3C—Mean of percent ground cover of grasses within control, deer exclusion, and deer-and-rabbit exclusion plots at Moro Bottoms Natural Area. (SP = spring,SU = summer, AU = autumn).

 SP 1990 SU 1990 F 1990 SP 1991 SU 1991 F 1991 SP 1992 SU 1992 F 1992

Season and Year

ControlDeerDeer and rabbit

Percent cover

DeerDeer and rabbit

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 AU 1992

Season and year
59

Table 2—Mean and standard error of differences in percent cover of grasses, sedges, and 

other herbaceous vegetation between control and deer exclusion and between control and 

deer-and-rabbit exclusion, Moro Bottoms Natural Area 

 Plant Sample Standard 

Date group size Variable Mean error T Prob > |t| 

Spring 1990 Grasses 30 C vs. D 2.33 2.44 .96 .35 

 C vs. DR 2.83 2.42 1.17 .25 

 Sedges 30 C vs. D 7.17 2.68 2.68 .01a

 30 C vs. DR 4.67 1.74 2.68 .01a

 Other 30 C vs. D -1.38 3.15 -.44 .66 

 30 C vs. DR 1.55 3.20 .49 .63 

Summer 1990 Grasses 30 C vs. D 4.83 2.80 1.72 .09 

 30 C vs. DR 4.16 2.65 1.57 .13 

 Sedges 30 C vs. D 7.33 2.09 3.52 0a

 30 C vs. DR 8.33 1.92 4.33 0a

 Other 30 C vs. D -3.50 2.67 -1.31 .20 

 30 C vs. DR -7.50 3.28 -2.29 .03b

Fall 1990 Grasses 30 C vs. D -.83 1.78 -.47 .64 

 30 C vs. DR -.66 1.85 -.36 .72 

 Sedges 30 C vs. D 7.33 2.21 3.32 0a

 

 30 C vs. DR 6.17 1.31 4.72 0a

 

 Other 30 C vs. D -2.17 2.42 -.90 .38 

 30 C vs. DR -4.31 2.48 -1.74 .09 

Spring 1991 Grasses 30 C vs. D -1.50 1.68 -.89 .38 

 30 C vs. DR -2.50 1.90 -1.32 .20 

 Sedges 30 C vs. D 6.67 3.16 2.11 .04b

 30 C vs. DR 9.00 2.63 3.42 0a

 Other 30 C vs. D -4.50 2.94 -1.53 .14 

 30 C vs. DR -6.67 2.63 -2.94 .01a

Summer 1991 Grasses 28 C vs. D 7.68 3.38 2.27 .03b

 28 C vs. DR 7.86 3.21 2.45 .02b

 Sedges 28 C vs. D 7.14 2.46 2.90 .01a

 28 C vs. DR 8.21 2.52 3.26 0a

 Other 28 C vs. D -15.18 4.55 -3.34 0a

 28 C vs. DR -15.18 4.38 -3.47 0a

Fall 1991 Grasses 28 C vs. D 5.00 2.04 2.45 .02b

 

 28 C vs. DR 5.18 2.42 2.14 .04b

 Sedges 28 C vs. D 5.18 2.25 2.30 .03b

 28 C vs. DR 6.07 2.48 2.44 .02b

 Other 28 C vs. D -6.25 2.72 -2.30 .03b

 28 C vs. DR -9.46 3.68 -2.57 .02b

Spring 1992 Grasses 29 C vs. D 3.28 1.89 1.73 .09 

 29 C vs. DR 4.31 1.93 2.23 .03b

 Sedges 29 C vs. D 7.59 3.40 2.23 .03b

 29 C vs. DR 11.38 3.24 3.51 0a

 Other 29 C vs. D -7.07 3.36 -2.10 .04b

 29 C vs. DR -11.90 3.80 -3.13 0a

Summer 1992 Grasses 27 C vs. D 4.44 1.65 2.69 .01a

 27 C vs. DR 5.37 2.05 2.62 .01a

 Sedges 27 C vs. D 3.52 1.92 1.83 .08 

 27 C vs. DR 4.44 2.02 2.20 .04b

 Other 27 C vs. D -2.04 2.79 -.73 .47 

 27 C vs. DR -5.74 3.23 -1.78 .09 

Fall 1992 Grasses 28 C vs. D 5.18 1.95 2.66 .01a

 28 C vs. DR 5.18 2.28 2.27 .03b

 Sedges 28 C vs. D 2.68 1.77 1.51 .14 

 28 C vs. DR 3.39 1.76 1.92 .07 

 Other 28 C vs. D 2.86 2.32 1.23 .23 

 28 C vs. DR -.71 2.89 -.25 .80 

SE = standard error; T = student's t statistic; Prob > |t| = associated probability from paired t-test of means; 

C vs. D = control versus deer exclusion; C vs. DR = control versus deer-and-rabbit exclusion. 

a

P = 0.01. 

b P = 0.05.

P

P

size
60

Devall (1982) studied the Beauvais tract (42 ha) at Cat

Island, a bottomland swamp in West Feliciana Parish, LA,

where timber has been selectively cut, but old trees are also

present (oldest 450 years), and there is some gap

regeneration. Twenty-two tree species occurred in this forest.

Sugarberry (Celtis laevigata Willd.) had the highest

importance value, followed by cypress and green ash. Many

of the trees and woody vines occurring at Moro Bottoms

were also present at Cat Island. The midstories were

dissimilar, with sugarberry, green ash, and American elm

common at Cat Island. Fifty-one species (herbs and woody

seedlings) occurred in 1-m quadrats (not located in gaps),

18 of which were present at Moro Bottoms, and 75 species

were collected outside of quadrats, 13 of these at Moro

Bottoms. Grass and sedge species were much more

important at Moro Bottoms, and herbaceous diversity was

greater.

There are few exotic species present in Moro Bottoms. In

addition to Mariana maiden fern [Thelypteris torresiana

(Gaud.) Alston] reported by Orzell and Bridges,5 Japanese

Table 4—Kruskal-Wallis test of number of woody

seedlings present in the Moro Bottoms deer, deer-andswamp rabbit, and control exclosures

Prob. >

Chi-Degrees of chiDate square freedom square

Spring 1990 2.85 2 0.24

Summer 1990 1.34 2 .51

Fall 1990 1.38 2 .50

Spring 1991 1.20 2 .55

Summer 1991 .83 2 .66

Fall 1991 .92 2 .63

Spring 1992 4.36 2 .11

Summer 1992 1.56 2 .46

Fall 1992 4.92 2 .09

5

 Orzell, Steve; Bridges, Edwin. 1990. Moro Creek Bottoms,

Arkansas. 4 p. Unpublished report. On file with: Arkansas Natural

Heritage Commission, 1500 Tower Building, 323 Center Street, Little

Rock, AR 72201.

Table 3—Density values of woody seedlings occurring in the plots at Moro

Bottoms

1990 1991 1992

Plot

Species type SP SU F SP SU F SP SU F

- - - - - - - - - - - - - - - - Number of seedlings - - - - - - - - - - - - - - -

All

species D 281 485 356 138 287 307 548 500 540

DR 358 392 431 197 369 370 720 683 761

C 309 526 473 159 400 360 493 609 697

Oaksa D 178 240 232 48 160 173 336 295 333

DR 220 288 253 73 202 225 417 402 443

C 197 318 312 27 222 211 320 393 484

Red

maple D 26 19 3 5 5 2 25 12 14

DR 14 27 10 5 1 4 92 35 35

C 7 11 10 2 3 2 24 25 18

Sweetgum D 11 18 11 12 12 12 10 18 15

DR 13 21 23 10 19 18 18 25 24

C 12 20 15 11 18 14 15 19 16

Ironwood D 36 56 52 16 31 32 82 76 90

DR 60 67 69 59 42 25 106 101 134

C 40 78 68 59 55 29 63 86 78

SP = spring; SU = summer; F = fall; D = deer exclusion plots, DR = deer-and-swamp rabbit plots;

C = control.

a Oaks = water oak, overcup oak, white oak, willow oak, black oak, cherrybark oak.

a

species

maple

a
61

Figure 4—Values of the Shannon diversity index for herbaceous vegetation within control, deer exclusion, and deer-and-rabbit exclusion plots at MoNatural Area. (SP = spring, SU = summer, AU = autumn).

— - — - Control

Deer

- - - - - - Deer an

SP 1990 SU 1990 AU 1990 SP 1991 SU 1991 AU 1991 SP 1992 SU 1992 

Season and year

Shannon index

3.73.83.53.43.33.23.1

3

2.9
62

honeysuckle (Lonicera japonica Thunb.) was noted in and

near plot 21. Although Orzell and Bridges (see footnote 5)

mentioned damage by feral pigs, we did not note evidence of

feral pigs during the study.

It was somewhat surprising that species richness, total

cumulative species, and number of unique species were

apparently not affected by herbivory of white-tailed deer or

swamp rabbits (fig. 1A–C). Deer density varied considerably

in different seasons, from < 1 deer per square kilometer in

spring to 21.8 deer per square kilometer in autumn.6

Alverson and others (1988) reported that herbivory

prevented regeneration of common woody species such as

Canada yew (Taxus Canadensis Marsh.), eastern hemlock

[Tsuga Canadensis (L.) Carr.], and white cedar (Thuja

occidentalis L.) even at deer densities as low as four deer

per square kilometer, reduced reproductive success, or

caused local extirpation of several herbaceous species

indigenous to northern hemlock-hardwood forests. Tilghman

(1989) reported analogous results for comparable deer

densities in Pennsylvania. In other cases, comparable deer

populations have caused severe damage to the understory

(Hough 1965). Similar to our results, Balgooyen and Waller

(1995) found that percent cover of several herbaceous

species declined significantly in areas with higher historic

and recent deer densities. In spite of these effects, deer

densities did not seem to be directly related to the overall

number of herbaceous species, the Shannon-Weaver index

of diversity, or vegetative cover.

Perhaps the initial shock of exclusion accounted for the

differences in percent cover of herbaceous vegetation in

1990, because all evidence of treatment effects disappeared

by autumn 1990. It seems that the intensity of browsing

pressure was not sufficient to cause apparent impacts until

the end of the third year of exclusion of deer and rabbits. At

that time we began to detect differences in the percent cover

of total vegetation in the control versus deer exclosures, and

by the fall of 1992 there were differences between the

control versus deer and control versus deer and swamp

rabbits, although not in the direction one might expect. The

control plots had greater percent cover of vegetation than

the exclosure plots. Perhaps deer and swamp rabbits kept

the vegetation trimmed, so some species did not grow large

and shade others, or grazing stimulated growth.

We observed that the percent cover of grasses and sedges

was consistently greater and the percent cover of other

herbaceous vegetation regularly less in control plots than in

exclusion plots. Although there was some variation, sedges

were clearly more abundant in control plots than in deerexclusion plots, and the effect was even more pronounced in

the deer-and-rabbit plots. Deer rarely eat sedges and

grasses (Harlow and Hooper 1972, Murphy and Noble 1973,

Newsom 1984); deer in bottomland forests prefer herbs such

as Aster spp. (Murphy and Noble 1973). Little published

information exists regarding the food preferences of swamp

rabbits, but such features as digestability that are attractive

to ungulates are also important to rabbits (Hjaltén 1991).

Thus, the pattern of cover that we observed was probably a

consequence of deer and/or rabbits avoiding grasses and

sedges and selectively browsing other herbs.

Deer browsing has been shown to reduce plant biodiversity

(Dzieciolowski 1980, Strole and Anderson 1992) and can

bring about inconspicuous changes in species composition,

even when deer are not very abundant (Anderson and

Loucks 1979, Stewart and Burrows 1989, Strole and

Anderson 1992). Treatment effects may occur slowly;

recovery, if deer are excluded, can require several growing

seasons (Ross and others 1970). Neither deer nor swamp

rabbits appeared to be very numerous at Moro Bottoms, but

by the third year of deer and swamp rabbit exclusion

(summer 1992), the effects of herbivory became apparent.

Many of the previous studies mentioned recount vegetation

responses after five or more growing seasons; the effects of

herbivory at Moro Bottoms may become more pronounced

with time. The long-term consequences of herbivory on the

biological diversity of this old-growth bottomland hardwood

forest can only be determined through further study.

Few cypress, hickory, or holly seedlings occurred in the

plots. Although acorns are a favorite deer food (Halls 1977),

oak seedlings were not scarce (fig. 3). Ironwood and red

maple seedlings were also numerous (fig. 3). It was apparent

from the larger number of seedlings present in spring and

fall that many seedlings did not survive the summer

(evidently new seedlings germinated after rains). We did not

monitor survival of particular seedlings, but few of the oaks,

ironwood, red maple, cypress, and hickory appeared to be

more than 1 year old until 1992, when more older oak

seedlings were present, especially willow oak (Q. phellos L.)

and water oak. Sweetgum seedlings were not as numerous

as the oak species, but appeared to survive the summers

better (dead willow oak and water oak seedlings were

present in the fall, although new oak seedlings had

germinated).

Balgooyen and Waller (1995) noted differences in the effects

of deer grazing on herbaceous and woody plants. The gaps

at Moro Bottoms were created by a windstorm in late

summer of 1989, thus most of the vegetation we measured

germinated no earlier than the spring of 1990, when the

study began. Delayed oak germination can occur in the fall,

as well. Perhaps herbaceous species are affected sooner by

grazing than woody species, and the effects of herbivory by

deer and rabbits on woody species will become apparent

later.

The gaps are at different elevations, but all are covered with

1 m or more of water most years for varying periods during

spring, and they may be flooded briefly after hard rains at

other times of the year. While inundation no doubt had an

effect on the vegetation at Moro Bottoms, periodic flooding

occurred during the time that herbs and woody species

growing at Moro Bottoms became adapted to conditions

there, thus they should have adapted to withstand

submersion (Noble and Murphy 1975).

6

 Smith, Winston P.; Devall, Margaret S.; Parresol, Bernard R. 1995.

Windthrow gaps, mammalian herbivores, and diversity of old-growth

bottomland hardwood forests. 122 p. Completion report. On file with:

U.S. Department of Agriculture, Forest Service, Southern Research

Station, Center for Bottomland Hardwoods Research, P.O. Box 227,

Stoneville, MS 38776.
63

Except as noted above, seedlings occurring in the

exclosures reflected the composition of the overstory,

suggesting that gap processes could have been operating

when the existing canopy developed (Runkle 1991). This

also suggests that without outside influence, the forest will

remain stable in the near future and will not change in

composition. Succession to a different forest type does not

appear to be occurring. During the time the study was

conducted, occasional trees fell, creating new gaps or

increasing the size of existing ones; Runkle (1991) states

that repeated death of canopy trees in eastern old-growth

forests is common. In older forests, crown sizes are large

enough to provide opportunities for seedling and sapling

growth.

ACKNOWLEDGMENTS

We thank the Arkansas Natural Heritage Commission and

the Arkansas Field Office of The Nature Conservancy for

allowing us to carry out the study on their preserve. A USDA

Forest Service Research Cost-Share Grant

(Dendroecological history of old-growth bottomland

hardwood forest in southern Arkansas; Agreement SRS–33–

CC–98–458 dated January 01, 1998) with cost-share

support provided by Arkansas Forestry Commission,

Arkansas Game and Fish Commission, Arkansas Game and

Fish Foundation, and Arkansas Natural Heritage

Commission funded the study. We appreciate the help with

plant identifications by Eric Sundell, Seth Barnes, Michael

Lelong, Danny Skojac, and Allen Moore.

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an introduction. Natural Areas Journal. 8(1): 3–6.

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and naturalized). Agric. Handb. 541. Washington, DC: U.S.

Department of Agriculture, Forest Service. 375 p.

MacDonald, P.O.; Frayer, W.E.; Clauser, J.K. 1979.

Documentation, chronology, and future projections of bottomland

hardwood habitat loss in the lower Mississippi Alluvial Plain. State

College, PA: HRB Singer, Inc. 133 p. Vol. 1.

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and use of browse plants by deer on a bottomland hardwood area

in Tensas Parish, Louisiana. In: Proceedings of the annual

conference of the Southeastern Association of Game and Fish

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White-tailed deer. Ecology and management. Harrisburg, PA:

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prolonged flooding on understory vegetation. Castanea. 40: 228–

238.

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of the vascular flora of the Carolinas. Chapel Hill, NC: The

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1978. Vegetation and tree species patterns near the northern

terminus of the southern floodplain forest. Ecological

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64

Ross, B.A.; Bray, J.R.; Marshall, W.H. 1970. Effects of long-term

deer exclusion on a Pinus resinosa forest in north-central

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48–55.
65

A COMPARISON OF BREEDING BIRD COMMUNITIES AND HABITAT

FEATURES BETWEEN OLD-GROWTH AND SECOND-GROWTH

BOTTOMLAND HARDWOOD FOREST

Winston P. Smith, Howard E. Hunt, and W. Kent Townley1

Abstract—To characterize bird species composition, relative abundance, and habitat affinities, spot-mapping and stripcount censuses were conducted in an old-growth stand and adjacent second-growth tracts in Moro Bottoms Natural

Area, Arkansas, during 1991 and 1992. More species were recorded on the old-growth site (S = 35) as compared to the

second-growth grid (S = 32). Similarly, the old-growth grid had a larger Shannon-Weaver diversity index than the secondgrowth site. Territories of several species coincided with specific habitat features: white-eyed vireo (Vireo griseus),

Carolina wren (Thryothorus ludovicianus), Kentucky warbler (Oporornis formusus), and prothonotary warbler

(Protonotaria citrea) were associated with treefall canopy gaps; Acadian flycatcher (Empidonax virescens) and

prothonotary warbler were affiliated with standing water; and the American redstart (Setophoga ruticilla) showed a strong

affinity for swamp chestnut oak (Quercus michauxii). Small forest openings (< 0.26 ha) comprising < 22 percent of the

total area of old growth bottomland forest do not appear to adversely affect and may enhance breeding bird diversity.

1

 Research Wildlife Biologist, Pacific Northwest Research Station, 2770 Sherwood Lane, Suite 2A, Juneau, AK 99801-8545; Hunt and Townley,

Department of Biological Sciences, Box 3179, Louisiana Tech University, Ruston, LA 71272-3179.

INTRODUCTION

Southern bottomland hardwood forests are critical as

breeding, wintering, and en-route habitat during migration,

contributing significantly to continental avifaunal diversity of

Eastern North America (Smith and others 1993a). Alarming

is the rate of loss of this unique resource, especially during

the recent half-century, with a conversion of 80 percent of

the Mississippi River Valley (Creasman and others 1992,

Turner and others 1981) and 52 percent of all southern

bottomland forests (Smith and others 1993a) to agriculture

or cleared for development (MacDonald and others 1978,

Rudis and Birdsey 1986). Moreover, remaining forests occur

as fragments (Rudis and Birdsey 1986) and have undergone

a variety of timber harvests. Indeed, all but an estimated

0.01 percent of presettlement old-growth bottomland forests

has experienced significant anthropogenic disturbance

(Smith and others 1993a). Furthermore, future management

imposed on remaining bottomland forests will necessarily

intensify to meet increasing demands on hardwood products

(Barton 1986, Murphy 1975), especially with the recent

surge in markets for hardwood pulp.

Arkansas was no exception to the pattern that occurred

across Eastern North America, especially in southern forests

(Sharitz and others 1992). Before European arrival,

Arkansas landscapes were largely vast acreages of

continuous, upland and bottomland deciduous forests; early

settlement and agriculture, and more recently silviculture,

dramatically modified forest habitats (James and Neal

1986).

Conversion and alteration of remaining bottomland

hardwood forests have been so extensive that its continued

existence as a functioning ecological system is uncertain

(Creasman and others 1992, Ernst and Brown 1989).

Because songbirds (Passeriformes) and other forest

landbirds occupy a broad spectrum of habitats

encompassing the full vertical forest profile, i.e., forest floor

to canopy, and use a diverse array of resources as food

(e.g., plant material, soil and plant invertebrates) and as

other necessary components of their life history, this

vertebrate group represents an excellent barometer of forest

ecosystem integrity and function.

Thus, a comparison of avifaunal species composition and

abundance between undisturbed and second-growth forest

should provide some insights regarding how well managed

forests function as habitat for their indigenous biota;

quantifying features associated with use of forest habitat by

individual species would presumably identify essential

stand-level components (or ecological correlates) necessary

for successful reproduction. Moreover, the relationships

between vegetative characteristics and avian distribution

and abundance in southern bottomland hardwood forests

are poorly documented. The purpose of this paper is to

compare the bird community of a second-growth bottomland

hardwood forest to a “paired” old-growth stand. Specific

objectives were to: 1) determine whether breeding bird

abundance and diversity were similar between old-growth

and second-growth forests; 2) identify and quantify habitat

features that were associated with distribution of bird

species in old-growth and second-growth bottomland

hardwood forests; and 3) determine whether these habitat

attributes differed between old-growth and second-growth

forests.

STUDY SITES

The study area was located approximately 8 km east of

Fordyce, AR, along Moro Creek on the Moro Bottoms

Natural Area (fig. 1). The Natural Area is a 70-ha tract of

primarily old growth under the joint stewardship of the

Arkansas Nature Conservancy and the Arkansas Natural

Heritage Commission. The area is located in the upper West

Gulf Coastal Plain (Hoiberg 1957 as cited in James and

Neal 1986). The climate is hot and humid during the

breeding season with a mean summer temperature of 27 oC.

Mean annual rainfall is 123.4 cm, with much of the rain

occurring in the spring.
66

Portions of the study area adjacent to the creek are

inundated periodically during the early part of the breeding

season, but water usually does not persist for more than a

week at a time. Several sloughs and creeks join the main

channel of the stream such that water is abundant

throughout the study area. The elevation of the site ranges

48 to 51 m above mean sea level.

The census areas consisted of two adjacent tracts of oakgum-cypress (Quercus spp.-Liquidambar styracifluaTaxodium distichum) bottomland hardwood forests located

along Moro Creek. The first study site was a 12-ha tract of

old growth east of Moro Creek in Cleveland County (fig. 1).

Overstory on the old-growth site was dominated by

sweetgum, black gum (Nyssa sylvatica), overcup oak

(Quercus lyrata), and bald cypress. The understory was

composed primarily of eastern hornbeam (Carpinus

caroliniana) and American hop hornbeam (Ostrya

virginiana). The herbaceous layer was poorly developed in

areas of closed canopy. Dewberry (Rubus spp.) is common

in areas of canopy gaps.

The second study site was a 12-ha second-growth stand of

bottomland located to the west of Moro Creek in Calhoun

County (fig. 1). This site experienced a high-grade harvest

about 30 years before the study. Overstory dominants were

similar to the old-growth site. The understory was composed

primarily of saplings of overstory trees and eastern

hornbeam. The herbaceous layer was denser than in the

old-growth study area and was comprised mostly of

dewberry and grasses (Gramineae).

During August 1989, Moro Bottoms experienced a severe

windstorm. Numerous windthrows occurred creating gaps in

the overstory ranging in size from a single stem to about 0.3

ha). Because of these natural disturbances within the old

growth and the proximity to managed second-growth forests,

the Natural Area presented an excellent setting to examine

the effects of recent natural and anthropogenic disturbances

on habitat for forest landbirds.

PROCEDURES

Detailed maps of the old-growth and second-growth study

sites were made that included major habitat features like

Moro Creek and branching sloughs as well as all downed

trees. All treefall canopy gaps were delineated by drawing

lines connecting the trunks of mature trees at the gap edge.

Maps of streams and canopy gaps were digitized into a

Geographic Information System (GIS).

Habitat Sampling

A stratified, random-sampling procedure was used to locate

an equal number of random points in the old-growth and

second-growth study sites. The point-center quarter method

(Cottam and Curtis 1956) was used to sample the overstory;

tree height was included with tree species and d.b.h.

measurements. Distance to the nearest snag, water, and

gap also were measured. Together these data served as a

null model of habitat features “available” within study sites

for comparisons with measurements recorded where birds

were seen and between study grids.

For singing male birds detected visually during spot-map

censuses, several habitat variables were measured. Each

bird’s height from the ground was recorded using a

clinometer; also its position in the vegetation (e.g., trunk,

interior canopy, exterior canopy) was noted. In addition, tree

species and height, diameter at breast height (d.b.h.),

distance to the nearest snag, and distance to the nearest

water were measured. A snag was defined as a dead tree

>1.8 m tall with a d.b.h. of >10.2 cm (Thomas 1979).

Diameter at breast height was measured only in 1992. On

the old-growth site, distance from each singing male to the

nearest gap was recorded. Canopy closure was quantified

using a spherical densiometer (Lemmon 1956).

To quantify vegetation regrowth in canopy gaps, visual

obstruction was measured using a density board (Nudds

1977). The board was 4 m high and marked off in 10-cm

increments. The board was placed in the center of the

longest axis of the gap. Readings were made at 5-m

intervals from the board along the axis and along an axis

perpendicular to it.

Avifaunal Sampling

The spot-map technique (International Bird Census

Committee 1970) was employed to map the territories of

breeding males in a 12-ha grid (600 m x 200 m) within both

the old-growth and second-growth sites during the breeding

season in 1991 and 1992. Grid boundaries were located at

Figure 1—The study area, including Moro Bottoms Natural Area

(large irregular shaped polygon) and adjacent private lands,

Cleveland and Calhoun counties, AR, 1991 and 1992. (Hatched

rectangles represent old-growth and second-growth spot-mapping

grids.)
67

least 50 m from any external edge. Numbered stakes were

placed at 25-m intervals throughout the grid to facilitate

locating each singing male’s position on the grid. Weekly

censuses were conducted on each grid. Locations of all

male birds seen or heard were plotted on a map. Maps from

each season were compiled by species and entered into the

ARC/INFO GIS. Territories were derived as the minimum

convex polygon that included all of the locations of a singing

male (Mohr 1947). The area of each territory and the area

covered by water and by gaps (old-growth site only) were

calculated.

Strip count censuses were conducted weekly during the

breeding season in 1991 and 1992. Strip count transects 50

m wide and 600 m long were established through the center

of the old-growth and second-growth spot-map grids. All

male birds seen or heard within the 50-m wide strip were

recorded to provide an estimate of avian abundance for

each study site. The time of each census was alternated

weekly between morning and evening.

Statistical Analysis

All statistical analyses were performed using SAS 6.03 on

an IBM personal computer. We used the Shapiro-Wilk test

for normality (Shapiro and Wilk 1965) to examine the

distribution of variables. When distributions departed from

normality, or when variances were unstable or

heterogeneous, we used nonparametric counterparts to test

our ecological hypotheses. Statistical analyses almost

invariably addressed common null hypotheses that were

examined through multiple comparisons. Therefore, we

followed the recommendations of Chandler (1995) and used

sequential Bonferroni adjustments of P-values (Wright

1992). For a “family” (Chandler 1995:525) of multiple

statistical tests, we selected an experiment-wise error rate of

10 percent; that is, the probability of a type I error for all

individual comparisons collectively was < 0.1. We selected

10 percent, rather than the conventional 5 percent error rate,

to mitigate a reduction in statistical power so that individual

comparisons were not too conservative (Chandler 1995).

Thus, corresponding individual, comparison-wise error rates

varied according to the number of individual tests conducted

and followed the general procedures for Bonferroni

adjustments outlined by Wright (1992).

For example, multiple comparisons of habitat use were

conducted in each habitat type to test the general

hypothesis that distribution of birds was nonrandom. The

general hypothesis was rejected with a 10 percent error rate

if any of the underlying specific hypotheses was rejected.

Individual comparisons were used to test underlying specific

hypotheses, i.e., determine whether distribution in old

growth or second growth was associated with any of a set of

specific habitat features (e.g., snags). In this example, we

made 13 comparisons of use against the same underlying

availability distribution. In the most conservative scenario

(i.e., where the adjusted comparison-wise P-value equals

the experiment-wise error divided by the number of

individual comparisons, Chandler 1995), the comparisonwise error rate of individual tests was 0.10/13, or 0.0077.

That is, each comparison of use of a specific habitat feature

in old growth or second growth to its corresponding

availability occurred with an error rate of 0.77 percent. In

some circumstances, we reduced the total number of

individual tests and increased statistical power by

conducting comparisons sequentially according to P-values

(Wright 1992:1009).

We used nonparametric test statistics for all univariate

comparisons of habitat features between bird use (visual

observations) and availability (random points). Distance to

the nearest water, snag, and treefall canopy gap were tested

for correlation using the Pearson correlation statistic

(Kleinbaum and others 1988). No significant correlation

occurred among any of the variables, so all variables were

treated as independent variables in subsequent analyses.

Because no significant difference existed in habitat

distribution between years, 1991 and 1992 data from each

habitat were combined to increase sample size and

statistical power. Only birds with at least five visual records

in each habitat type were included in analyses. Habitat use

patterns of American redstart were analyzed although they

were recorded only in second-growth habitat.

Tree species used by each bird species and corresponding

height and d.b.h. values were compared to trees available

(as estimated from a random sample of points) with a

Kolmogorov-Smirnov Goodness-of-Fit (one-sample) test for

continuous data (Zar 1984:55). Canopy closure and

distance to nearest water, snag, and treefall canopy gap

were compared to the same measures from random sites

using a Wilcoxon signed rank test (Zar 1984).

Species composition and structure of avian communities

were characterized with the Shannon-Weaver diversity index

(Shannon and Weaver 1949). A Student’s t test (Zar 1984)

was used to test for significant differences between oldgrowth and second-growth habitats with spot-mapping and

strip census results.

RESULTS

Bird Species Distribution, Density, and Diversity

Twelve spot-mapping censuses were conducted between

May 26 and August 13, 1991, and 15 spot-mapping

censuses were conducted between May 12 and August 15,

1992, on the old-growth and second-growth sites. In 1991

and 1992, there were 486 and 651 individuals and 543 and

591 individuals recorded in the old-growth and secondgrowth, respectively. Twelve and 15 strip-count censuses

also were conducted in the old-growth and second-growth

sites during the same time periods in 1991 and 1992,

respectively.

A total of 38 species was detected in old growth, whereas 34

species were detected in second-growth habitat (table 1).

The ten most common species recorded each in old-growth

and second-growth habitats (according to weighted

estimates of density from 1991 and 1992) are presented in

table 2. For comparison, we include ranks of bird species

recorded in four previous studies of bottomland hardwood

forests. In our study, 12 warbler species (Parulinae) were

detected in old growth, whereas nine warblers were

detected in second-growth habitat. The white-eyed vireo

(Vireo griseus) was the most common bird in both habitats in

1991 and in second-growth habitat in 1992 along with the

Carolina wren (Thryothorus ludovicianus). The red-eyed
68

Table 1—Breeding bird density (pairs per 100 ha) derived

from spot-mapping censuses by habitat and year on Moro

Bottoms Natural Area, Arkansas, 1991 and 1992.

______________________________________________________________________________

 Old growth Second growth

Species 1991 1992 1991 1992

______________________________________________________________________________

Northern parula 30 51 40 31

 (Parula americana)

Black-and-white warbler * 10 * *

 (Mniotilta varia)

Yellow-throated warbler 10 10 10 10

 (Dendroica dominica)

Pine Warbler 10 10

 (Dendroica pinus)

American redstart * 40 40

 (Setophoga ruticilla)

Prothonotary warbler 40 51 30 30

 (Protonotaria citrea)

Swainson’s warbler * 10 10

 (Limnothlypis swainsonii)

Louisiana waterthrush * 10

 (Seiurus motacilla)

Kentucky warbler 20 40 20 40

 (Oporornis formusus)

Common yellowthroat 10 20

 (Geothlypis trichas)

Hooded warbler * 10 30 10

 (Wilsonia citrina)

Worm-eating warbler *

 (Helmitheros vermivorus)

Summer tanager 20 20 10 10

 (Piranga rubra)

Northern cardinal 40 30 51 40

 (Cardinalis cardinalis)

Indigo bunting 10

 (Passerina cyanea)

 Total density 451 584 522 542

______________________________________________________________________________

Table 1—Breeding bird density (pairs per 100 ha) derived

from spot-mapping censuses by habitat and year on Moro

Bottoms Natural Area, Arkansas, 1991 and 1992.

______________________________________________________________________________

Old growth Second growth

Species 1991 1992 1991 1992

______________________________________________________________________________

Great blue heron * *

 (Ardea herodias)

Yellow-crowned night-heron * * * *

 (Nycticorax violaceus)

Wood duck * * * *

 (Aix sponsa)

Red-shouldered hawk * * * *

 (Buteo lineatus)

Wild turkey * * * *

 (Meleagris gallopavo)

Yellow-billed cuckoo * *

 (Coccyzus americanus)

Barred owl * * * *

 (Strix varia)

Chimney swift * * * *

 (Chaetura pelagica)

Ruby-throated hummingbird * * * *

 (Archilochus colubris)

Red-bellied woodpecker 20 20 10 20

 (Melanerpes carolinus)

Downy woodpecker 20 20 10 10

 (Picoides pubescens)

Northern flicker *

 (Colaptes auratus)

Pileated woodpecker * 10 *

 (Dryocopus pileatus)

Eastern wood-peewee 10

 (Contopus virens)

Acadian flycatcher 30 40 30 30

 (Empidonax virescens)

Great crested flycatcher 20 20 10 10

 (Myiarchus crinitus)

American crow * * * *

 (Corvus brachyrhynchos)

Carolina chickadee 20 20 30 30

 (Parus carolinensis)

Tufted titmouse 30 30 30 30

 (Parus bicolor)

White-breasted nuthatch 10 10 10 10

 (Sitta carolinensis)

Carolina wren 30 40 40 61

 (Thryothorus ludovicianus)

Blue-gray gnatcatcher * * 10 10

 (Polioptila caerulea)

White-eyed vireo 51 51 71 61

 (Vireo griseus)

Yellow-throated vireo 10 10 * *

 (Vireo flavifrons)

Red-eyed vireo 30 60 40 30

 (Vireo olivaceus)

 * = species with too few sightings to delineate a breeding territory,

or the species was too mobile to map accurately.
69

Table 2—Rank of 10 most abundant bird species in old-growth (OG) and secondgrowth (SG) habitats from Moro Bottoms Natural Area, Arkansas and from previous

avifaunal studies in bottomland hardwood forest

______________________________________________________________________________

Moro Bottoms

Species OG SG Hoiberga Dicksonb Fordc Hameld

______________________________________________________________________________

White-eyed vireo 1 1 8 1 + 6

 (Vireo griseus)

Red-eyed vireo 2 3 1 7 + 5

 (Vireo olivaceus)

Prothonotary warbler 3 5 10 10 5 +

 (Protonotaria citrea)

Northern parula 4 4 – + + 1

 (Parula americana)

Carolina wren 5 2 2 2 + 9

 (Thryothorus ludovicianus)

Acadian flycatcher 5 7 5 6 3 2

 (Empidonax virescens)

Northern cardinal 7 6 4 5 2 4

 (Cardinalis cardinalis)

Kentucky warbler 8 8 6 + + +

 (Oporornis formosus)

Tufted titmouse 9 9 3 3 7 3

 (Parus bicolor)

Red-bellied woodpecker 10 + + 8 + 10

 (Melanerpes carolinus)

Downy woodpecker 10 + + + 8 +

 (Picoides pubescens)

Carolina chickadee 10 10 + + 4 7

 (Parus carolinensis)

American redstart + + 9 – – +

 (Setophaga ruticilla)

Hooded warbler – + 7 + – +

 (Wilsonia citrina)

Yellow-billed cuckoo + + – 4 + +

 (Coccyzus americanus)

Swainson’s warbler + + – 9 – +

 (Limnothlypsis swainsonii)

Blue-gray gnatcatcher + + + – 1 8

 (Polioptila caerulea)

Indigo bunting + + – – 6 +

 (Passerina cyanea)

Ruby-throated hummingbird – + – – 9 +

 (Archilochus colubris)

Common grackle – + – + 10 +

 (Quiscalus quiscula)

______________________________________________________________________________

+ = species was recorded; – = species was not reported.

aAdapted from Hoiberg 1957, cited in James and Neal (1986).

bAdapted from Dickson (1978b).

cAdapted from Ford (1990).

dAdapted from birds recorded in old-growth bottomland hardwoods (Hamel 1989).
70

vireo (Vireo olivaceus) was the most common bird in old

growth in 1992. The American redstart (Setophaga ruticilla)

was a common bird in second-growth habitat, yet was only

recorded once in old growth. The greatest density of

breeding birds occurred in 1992 in old growth, whereas the

lowest density was in old growth in 1991 (table 1).

Shannon-Weaver diversity indices derived from spotmapping and strip-count censuses of old-growth forest were

consistently greater, but not significantly different, than

indices computed for second-growth habitat (table 3).

Species richness also was not statistically different between

habitats, but trends (table 3) were similar to diversity with a

larger number of species recorded in old growth (29) as

compared to second growth (27). Within a habitat type, no

significant differences were detected either within years or

between years for either sampling technique (e.g., spotmapping in old growth between 1991 and 1992). We

consistently recorded more species with the spot-mapping

method, but spot-mapping and strip-count censuses

produced similar species richness and diversity estimates.

The old-growth spot-mapping grid contained 24 gaps that

ranged in size from 127.5 to 2685.5 m2

. Number of species

and total number of birds recorded in gaps ranged 0 to

12 and 0 to 45, respectively. According to Spearman rank

correlation analysis, species richness was positively

correlated with area of treefall canopy gaps in 1991

(rs = 0.83, P < 0.001) and 1992 (rs = 0.73 P < 0.001). Total

registrations also was positively correlated with gap area in

1991 (r

s

 = 0.83, P < 0.001) and 1992 (r

s

 = 0.80, P < 0.001).

The highest values for species richness and total birds

occurred in the largest gap.

Habitat Availability and Use

Habitat features—Comparison of distances measured from

random points to various habitat features revealed

significant differences between habitats. Average distance

from random points to nearest snags and to surface water

was significantly greater in old-growth than in second-growth

habitat (table 4). Mean distance to the nearest tree was

significantly greater in second-growth habitat than in old

growth. No significant difference in d.b.h. distribution or tree

height distribution existed between habitats.

Tree species composition (fig. 2) was similar in old-growth

and second growth forests. Eastern hornbeam was the most

common tree in both habitats, comprising 49 percent of stem

density in old-growth and 23 percent in second-growth

habitat. Oaks had a relative density of 20 percent in secondgrowth study habitat compared to 8 percent in old growth.

Species habitat distribution—Perch heights varied among

species and were significantly different between habitat

types for the downy woodpecker (table 5). Acadian

flycatchers occurred closer to water than expected, i.e., as

compared to random points, in both old growth and second

growth; this was true of prothonotary warblers in old growth

(table 6). Acadian flycatchers were sighted directly over

water in 68.0 percent of the observations. In second growth,

Carolina wrens, tufted titmice, and white-eyed vireos all

occurred farther from water than expected. Carolina wrens

and Kentucky warblers also occurred farther from water than

expected in old growth.

Snags were abundant across both study sites, occurring

primarily in canopy openings. Carolina wrens in both

habitats, and Kentucky warblers in old growth, were

recorded closer to snags than were random sites (table 7).

Carolina wrens and Kentucky warblers used snags as

singing perches in 50 percent of our observations.

Table 3—Shannon-Weaver diversity indices (H’) and

species richness (S) for spot-mapping and strip-count

censuses among three forest habitats, Moro Bottoms

Natural Area, Arkansas, 1991 and 1992

______________________________________________________________________________

Spot-mapping Strip-count

technique technique

Habitat H’ S H’ S

______________________________________________________________________________

Old growth

 1991 3.106 35 3.014 28

 1992 3.099 33 3.095 30

Second growth

 1991 2.961 32 2.947 26

 1992 3.021 32 3.037 28

______________________________________________________________________________

Table 4—Means (x) and standard errors (SE) for all

variables measured in random plots across old-growth

and second-growth habitat, Moro Bottoms Natural Area,

Arkansas, 1991 and 1992 (comparison-wise P-value: P

<0.0167)

______________________________________________________________________

Old growth Second growth

Variable x SE x SE

______________________________________________________________________________

Distance to water (m) 41.8 4.1 20.5 1.3a

Distance to snag (m) 14.0 0.7 11.1 0.7b

Distance to gap (m) 23.4 1.4 — —

Canopy openness (percent) 24.1 1.1 27.3 1.3

Distance to tree (m) 3.5 .1 4.4 .2c

D.b.h. (cm) 17.8 1.5 17.1 1.2

Tree height (m) 11.3 .7 11.0 .6

Basal area (m2

/ha) 20.4 11.9

Stem density (trees/ha) 816.3 516.5

______________________________________________________________________________

a Significant difference between old-growth and second-growth study

sites, P < 0.0001. b Significant difference between old-growth and second-growth study

areas, P < 0.003. c Significant difference between old-growth and second-growth study

areas, P < 0.001.
71

Figure 2—Relative frequency distribution (percent) of tree species in the old-growth and second growth study sites, Moro Bottoms Natural

Area, Cleveland and Calhoun Counties, AR, 1991 and 1992.

Table 5—Sample size (N), mean perch height (x) and standard error (SE) of

perch sites in meters for bird species in old-growth and second-growth

habitat Moro Bottoms Natural Area, Arkansas, 1991 and 1992 (comparisonwise P-value: P <0.01)

______________________________________________________________________________

Old growth Second growth

Species Nx SE Nx SE

______________________________________________________________________________

Acadian flycatcher 25 5.5 0.5 15 4.1 0.3

American redstart — — — 29 15.4 1.3

Carolina chickadee 6 9.3 1.9 9 8.4 .9

Carolina wren 14 2.6 .4 26 3.0 .4

Downy woodpecker 5 7.2 .9 5 14.8 2.4a

Kentucky warbler 10 1.8 .4 12 1.5 .2

Northern cardinal 13 11.3 2.0 17 10.2 1.6

Prothonotary warbler 34 5.4 .5 19 5.2 .6

Red-bellied woodpecker 11 16.5 1.3 7 19.3 1.9

Tufted titmouse 11 10.8 1.3 9 9.9 1.8

White-eyed vireo 28 5.5 .3 30 5.9 .5

______________________________________________________________________________

a Significant difference (P < 0.01) in mean perch height between old-growth and secondgrowth study areas.

Tree Species

Relative frequency (%)

Ironwood

Sweetgum

Black gum

Overcup oak

Carolina ash

American holly

Hop hornbeam

Bald cypress

Persimmon

Water oak

Water elm

Swamp chestnut oak

Red maple

Other

0

10

20

30

40

50

60

Old growth

Second growth
72

Table 6—Sample size (N), mean (x), standard error (SE), Wilcoxon test

statistic (Z), and significance level (Prob >|Z|) for each species for

distance to the nearest surface water (m) for each habitat, Moro

Bottoms Natural Area, Arkansas, 1991 and 1992 (comparison-wise

P-value: P <0.0077)

______________________________________________________________________________

Species/

random variable Nx SE Za b Prob>|Z|

______________________________________________________________________________

 Old growth

Acadian flycatcher 25 5.2 3.0 -6.485 0.0001

Carolina chickadee 6 45.2 13.1 1.331 .1833

Carolina wren 14 81.8 14.2 3.766 .0002

Downy woodpecker 5 33.0 15.1 -0.298 .7652

Kentucky warbler 10 88.1 24.1 2.708 .0068

Northern cardinal 13 28.5 5.0 .510 .6098

Prothonotary warbler 34 27.6 7.8 -3.240 .0012

Red-bellied woodpecker 11 60.0 14.3 1.799 .0716

Tufted titmouse 11 54.7 16.1 .662 .5079

White-eyed vireo 28 58.1 12.4 1.474 .1404

Distance to water (m) 93 41.8 4.1

Second growth

Acadian flycatcher 15 3.3 1.1 -4.871 .0001

American redstart 29 36.1 7.6 .511 .6013

Carolina chickadee 9 44.3 18.8 .792 .4282

Carolina wren 26 52.8 13.0 2.153 .0313

Downy woodpecker 52 3.0 3.3 .783 .4335

Kentucky warbler 12 40.0 17.9 .671 .5023

Northern cardinal 17 48.7 13.6 2.349 .0188

Prothonotary warbler 19 20.6 7.5 -1.496 .1345

Red-bellied woodpecker 7 27.3 10.4 .435 .6638

Tufted titmouse 9 87.3 27.9 3.039 .0024

White-eyed vireo 30 42.9 8.2 2.688 .0072

Distance to water (m) 96 20.5 1.3

______________________________________________________________________________

a Calculated from use sites and 93 random sites in the old-growth study site using

the Wilcoxon signed rank test.

b Calculated from use sites and 96 random sites in the second-growth study site

using the Wilcoxon signed rank test.

Carolina wrens, Kentucky warblers, prothonotary warblers,

and white-eyed vireos were sighted closer to treefall canopy

gaps than random points (table 8). Moreover, perch sites of

the Carolina wren, Kentucky warbler, and white-eyed vireo

had a greater mean percentage of canopy openness (table

9). The white-eyed vireo appeared to locate its territory

around single canopy gaps >500 m2

. Although gaps

composed only 22.0 percent of the old-growth study area,

38.0 percent and 35.4 percent of spot-mapping records

occurred within treefall canopy gaps in 1991 and 1992,

respectively. The reason for this positive association with

canopy gaps is unclear, but occupied gaps had greater

understory density (53.2 percent + 5.56) from forest floor to

a height of four meters than gaps where birds had not been

recorded (31.1 percent + 3.96). Only the Acadian flycatcher

appeared to avoid canopy gaps. In second-growth habitat

they used areas with greater closed canopy (table 9), and in

old-growth forest, Acadian flycatchers were sighted at

greater distances than expected from canopy gaps (table 8).

Red-bellied woodpeckers in old-growth and American

redstarts in second-growth habitat used trees that had

greater d.b.h. than was generally available (table 10). These

species and the Carolina chickadee preferred trees of

greater height in both habitats than was generally available

(table 11). Carolina wrens in old growth and Kentucky

warblers in both habitats, used shorter trees than expected.

Unfortunately, because d.b.h. was only measured in 1992,

some species were omitted from the analysis due to

insufficient sample size.
73

Table 7—Sample size (N), mean (x), standard error (SE), Wilcoxon

test statistic (Z), and significance level (Prob >|Z|) of distance to the

nearest snag (m) for each bird species in old-growth and secondgrowth habitat, Moro Bottoms Natural Area, Arkansas, 1991 and 1992

(comparison-wise P-value: P <0.0077)

______________________________________________________________________________

Species/

random variable Nx SE Za b Prob>|Z|

______________________________________________________________________________

 Old growth

Acadian flycatcher 25 15.6 2.2 0.681 0.4957

Carolina chickadee 6 22.3 6.2 1.817 .0708

Carolina wren 14 7.0 1.8 -3.591 .0003

Downy woodpecker 5 8.8 4.1 -1.171 .2414

Kentucky warbler 10 5.3 1.8 -3.210 .0013

Northern cardinal 13 13.8 2.0 .410 .6818

Prothonotary warbler 34 10.5 1.3 -1.923 .0544

Red-bellied woodpecker 11 15.5 3.5 .346 .7293

Tufted titmouse 11 13.4 2.8 - .410 .6815

White-eyed vireo 28 10.6 1.3 -1.826 .0680

Distance to snag (m) 93 14.0 0.7

Second growth

Acadian flycatcher 15 13.7 2.1 1.892 .0585

American redstart 29 13.4 1.8 1.186 .1871

Carolina chickadee 9 10.0 2.1 .285 .7757

Carolina wren 26 4.0 1.1 -4.771 .0001

Downy woodpecker 5 5.4 2.0 -1.401 .1612

Kentucky warbler 12 8.1 1.2 - .303 .7619

Northern cardinal 17 12.3 2.8 .046 .9632

Prothonotary warbler 19 10.8 1.5 .682 .4948

Red-bellied woodpecker 7 12.6 2.4 .937 .3487

Tufted titmouse 9 8.9 1.7 - .129 .8972

White-eyed vireo 30 11.2 1.6 .827 .3973

Distance to snag (m) 96 11.1 .7

______________________________________________________________________________

a Calculated from use sites and 93 random sites in the old-growth study site using

the Wilcoxon signed rank test.

b Calculated from use sites and 96 random sites in the second-growth study site

using the Wilcoxon signed rank test.

Finally, we compared use of tree species by birds to

corresponding estimates of availability with a KolmogorovSmirnov (KS) goodness-of-fit test (Appendix 1). We

discourage drawing inferences about tree species

preferences, however, because of the small sample of

observations obtained for each bird species, and because

the KS goodness-of-fit test was not developed for use with

nominal data. Still, the relative frequency distributions and

computed statistics suggest nonrandom use of trees by

most bird species. The American redstart showed the largest

bias toward use of a single species with 65 percent of its

use occurring in swamp chestnut oak (Quercus michauxii).

Perch sites selected by other bird species were more evenly

distributed across a variety of tree species (Appendix 1).

DISCUSSION

Assumptions and Implications

Moro Bottoms Natural Area was an excellent natural

laboratory for examining birds of old-growth and secondgrowth habitats. Because this was not a replicated

experiment, however, we caution generalizing results of our

study to other southern bottomland hardwood forests.

Moreover, there were several assumptions inherent in

procedures used in this study, some of which bear

significant implications on results and conclusions. For

example, we assumed that our sample of species

distributions across habitats reflected the variability that

existed in each of the habitats. Most of the visual

observations of birds were distributed among species that
74

typically frequent the midstory or understory strata. Dense

foliage and low light conditions in bottomland hardwood

forests made it difficult to observe birds in the upper canopy.

Canopy species commonly sighted tended to be those that

were more active (e.g., American redstart) or more vocal

(e.g., red-bellied woodpecker). Consequently, our results

were probably biased toward species or individuals of a

species that were more easily detected and observed. Also,

spherical densiometers yield biased estimates of forest

canopy cover (Cook and others 1995). Cover may be

overestimated and spherical densiometers may be

insensitive to variation in forest cover, especially in the midrange of canopy closure.

In addition, microhabitat features important for successful

reproduction among forest landbirds are numerous and

include food, foraging substrate, water, singing perches, and

nest sites. Because we only obtained direct observations of

singing perches, limited conclusions can be drawn about

bird habitat needs and microhabitat segregation among

species.

Finally, there were numerous comparisons of habitat

features between habitats and between used and available

sites within each habitat. In one such comparison, we used

the KS one-sample test to compare tree species

distributions (i.e., use versus available) when our data did

not strictly meet an important assumption of this analysis,

namely that observations are continuous data from a ratio,

interval, or ordinal scale of measurement (Zar 1984:55).

Also, because we did not apply a Bonferroni correction to

each set of analyses (e.g., Neu and others 1974), there was

an average of one chance in 20 (for P < 0.05) that a

statistical analysis could yield a spurious significant

conclusion.

Forest Composition

Vegetation at Moro Bottoms appeared typical of bottomland

hardwood forests of minor stream floodplains across the

Southern United States. Clairain and Kleiss (1988) reported

a similar assemblage of tree species for the Cache River

Basin in eastern Arkansas. At Cache River and Moro

Bottoms, forest types and corresponding overstory

dominants were distributed according to a moisture gradient

with cypress-tupelo inhabiting more hydric sites and overcup

oak (Quercus lyrata) and swamp chestnut oak occurring on

somewhat drier, mesic sites. Understory diversity was

limited under closed canopy at both sites, a feature probably

related to frequent and periodic prolonged inundation, as

well as limited sunlight across the forest floor (Smith and

others 1995).

Bird Species Distribution and Diversity

Moist bottomland hardwood forests of the Southern United

States often support an abundant and diverse breeding bird

community (Smith and others 1993a). James and Wamer

(1982) reported that mature deciduous forests supported the

highest avian diversity and density of all North American

forest types. Similar results were reported for Arkansas

where mature, moist forests had the highest breeding

species diversities (Shannon-Weaver index = 2.91) of any

habitat in the State (Shugart and James 1973). In our study,

diversity indices computed from spot-mapping censuses of

old growth averaged 3.10 (table 2).

It is generally recognized that there is a correlation between

foliage height diversity and bird species diversity in several

Table 8—Sample size (N), mean (x), standard error (SE), Wilcoxon

test statistic (Z), and significance level (Prob >|Z|) of recorded

distances to the nearest canopy gap (m) for each bird species in old

growth, Moro Bottoms Natural Area, Arkansas, 1991 and 1992

(comparison-wise P-value: P <0.01)

______________________________________________________________________________

Species/

random variable Nx SE Za Prob>|Z|

______________________________________________________________________________

Acadian flycatcher 25 37.7 5.4 2.734 0.0063

Carolina chickadee 6 21.5 4.4 .107 .9150

Carolina wren 14 6.4 2.9 -4.688 .0001

Downy woodpecker 5 15.2 5.6 - .865 .3873

Kentucky warbler 10 5.4 2.5 -3.555 .0004

Northern cardinal 13 17.5 3.0 - .864 .3874

Prothonotary warbler 34 10.9 1.6 -4.688 .0001

Red-bellied woodpecker 11 19.5 3.0 - .250 .8030

Tufted titmouse 11 39.9 12.1 .934 .3505

White-eyed vireo 28 5.2 1.1 -5.914 .0001

Distance to gap (m) 93 23.4 1.4

______________________________________________________________________________

a Calculated from use sites and 93 random sites using the Wilcoxon signed rank

test.
75

forests in the Eastern United States (MacArthur and

MacArthur 1961). At Moro Bottoms, breeding bird diversity

and richness increased with successional stage. In old

growth, or mature forests in general, Dickson (1991)

attributed high avian diversity to an increased number of

canopy layers and tree age categories. As habitat

complexity and heterogeneity increase, habitat requirements

for a greater number of species can be met (Martin 1992).

Similar results were reported for the Atchafalaya Basin by

Kennedy (1977): bird species richness and diversity varied

with foliage density, which increased from the earliest seral

stage to the oldest seral stage.

In our study, old growth had a closed canopy interrupted by

treefall canopy gaps, which provided several layers of

herbaceous and woody vegetation. The understory was

sparse except in canopy gaps where midstory and

understory layers proliferated. This diverse canopy structure

was not present in second-growth habitat where trees were

generally spaced farther apart and where development of a

dense low understory under a more open canopy was

presumably facilitated.

Avian abundance also varies with forest habitat structure

and complexity, which presumably facilitates partitioning of

resources among conspecifics (Kennedy 1977), as well as

Table 9—Sample size (N), mean (x), standard error (SE), Wilcoxon test

statistic (Z), and significance level (Prob >|Z|) of canopy openness

(percent) for each bird species in old growth and second-growth

habitat, Moro Bottoms Natural Area, Arkansas, 1991 and 1992

(comparison-wise P-value: P <0.0077)

______________________________________________________________________________

Species/

random variable Nx SE Zab Prob>|Z|

______________________________________________________________________________

 Old growth

Acadian flycatcher 25 18.4 1.5 -1.554 0.1200

Carolina chickadee 6 15.7 3.4 -1.662 .0966

Carolina wren 14 57.5 2.8 6.077 .0001

Downy woodpecker 5 36.6 11.6 .751 .4527

Kentucky warbler 10 52.8 4.9 4.257 .0001

Northern cardinal 13 23.3 2.7 .687 .4920

Prothonotary warbler 34 31.6 3.0 2.554 .0107

Red-bellied woodpecker 11 22.3 1.6 1.518 .1291

Tufted titmouse 11 24.6 1.6 1.518 .1291

White-eyed vireo 28 36.1 2.1 5.231 .0001

Canopy openness (%) 93 24.1 1.1

Second growth

Acadian flycatcher 15 14.7 1.8 -2.823 .0048

American redstart 29 17.7 1.6 1.891 .0494

Carolina chickadee 9 30.8 3.4 1.440 .1499

Carolina wren 26 42.8 2.6 4.580 .0001

Downy woodpecker 5 25.2 4.4 .234 .8146

Kentucky warbler 12 53.5 4.9 4.137 .0001

Northern cardinal 17 26.6 3.1 .636 .5246

Prothonotary warbler 19 21.6 1.8 - .477 .6335

Red-bellied woodpecker 7 21.9 3.3 - .297 .7687

Tufted titmouse 9 30.8 3.4 .111 .9113

White-eyed vireo 30 31.0 1.5 2.663 .0077

Canopy openness (%) 96 27.3 1.3

______________________________________________________________________________

a Calculated from use sites and 93 random sites in the old-growth study site using

the Wilcoxon signed rank test.

b Calculated from use sites and 96 random sites in the second-growth study site

using the Wilcoxon signed rank test.
76

among species (Mannan and others 1984). That is, the

number of conspecifics occupying a habitat is not

necessarily reduced as habitat complexity and species

diversity increases. In the Atchafalaya Basin, Kennedy

(1977) reported that the greatest avian abundance occurred

in bottomland hardwood forest, the latest seral stage among

an array of successional seres examined, and the habitat

with the greatest foliage complexity. In the Congaree Swamp

and Santee Swamp, Hamel (1989:624) reported

considerable overlap in bird communities (similarity index =

0.9) between old-growth and selectively cut stands and

between selectively cut and clearcut stands. Similarity

between old growth and second growth was intermediate

(0.7); the lowest similarity in bird communities (0.6) existed

between old-growth and clearcut stands (Hamel 1989:624).

In this study, breeding bird density varied inconsistently

between years and habitats with total old-growth densities

exceeding those in second-growth habitat in 1992, but not in

1991 (table 3). Unfortunately, we did not estimate foliage

complexity in either habitat (only understory density in gaps)

and only measured five features related to forest structure.

Of these only two differed between habitats (table 4).

Second-growth habitat had greater snag density and

showed greater spacing among stems >10 cm d.b.h., the

latter of which may have reduced canopy cover in second

growth habitat.

Avian density at Moro Bottoms was greater than that

reported for a moist forest in the Ozark region of Arkansas

(Shugart and James 1973). Average breeding bird density

was 525 breeding pairs per 100 ha in Moro Bottoms,

whereas 150 breeding pairs per 100 ha were observed in

the Ozarks. However, total avian density at Moro Bottoms

was appreciably lower than that reported for bottomland

forests of western Tennessee (830 breeding pairs per 100

Table 10—Sample size (N), mean (x), standard error (SE), KolmogrovSmirnov test statistic (D), and significance level (Prob > KS) of perch

site d.b.h. (cm) for each bird species in old-growth and secondgrowth habitat, Moro Bottoms Natural Area, Arkansas, 1991 and 1992

(comparison-wise P-value: P <0.0077)

______________________________________________________________________________

Species/

random variable Nx SE Da b Prob>KS

______________________________________________________________________________

 Old growth

Acadian flycatcher 14 12.2 2.2 0.1935 0.7521

Carolina wren 12 7.8 2.0 .2769 .3891

Kentucky warbler 6 1.7 1.0 .5269 .0875

Northern cardinal 8 20.4 5.8 .2311 .8260

Prothonotary warbler 18 12.5 2.1 .1505 .8840

Red-bellied woodpecker 6 46.8 2.4 .8065 .0013

Tufted titmouse 6 41.6 12.1 .4731 .1603

White-eyed vireo 16 11.4 2.1 .1505 .9165

D.b.h. (cm) 93 17.8 1.5

 Second growth

Acadian flycatcher 11 16.1 2.7 .2794 .4244

American redstart 18 46.1 3.5 .7601 .0001

Carolina wren 16 9.4 2.0 .2038 .5911

Kentucky warbler 7 1.3 0.6 .4479 .1459

Northern cardinal 10 24.0 5.3 .3604 .1900

Prothonotary warbler 12 12.0 2.2 .2083 .7435

Tufted titmouse 6 40.5 5.8 .6250 .0243

White-eyed vireo 19 13.6 2.3 .2889 .1415

D.b.h. (cm) 96 17.1 1.2

______________________________________________________________________________

a Calculated from use sites and 93 random sites in the old-growth study site and

using the Kolmogrov-Smirnov test.

b Calculated from use sites and 96 random sites in the second-growth study site

using the Kolmogrov-Smirnov test.
77

ha; Ford 1990) or breeding bird densities reported among all

habitats of the Congaree Swamp (range 818 to 1572 pairs

per 100 ha; Hamel 1989). In contrast, pine forests of the

west Gulf Coastal Plain had 2 to 4 times lower densities than

mature bottomland hardwood forests (Dickson 1978a).

Species common to Moro Bottoms were similar to

communities reported for bottomland hardwood forests

elsewhere (table 2). Regrettably, there are few remaining

examples of bird communities of old-growth bottomland

forests (Dickson 1978a, Hamel 1989). Except for Hamel

(1989), previous studies of southern bottomland bird

communities mostly come from sites where logging or other

land uses have influenced extent and composition of

remaining forests (Dickson 1978b, Ford 1990). Fortunately,

there was an earlier study from southern Arkansas (Hoiberg

1957, cited in James and Neal 1986) that could be included

in our comparisons (table 2). The 10 most abundant species

recorded in Moro Bottoms (pooled between habitats) almost

completely overlapped (one exception from each study) the

10 most common species reported by Hoiberg (James and

Neal 1986). Northern parula, the sixth most frequently

observed species in our study, was the only species not

ranked among Hoiberg’s 10 most common species. In

contrast, the hooded warbler (Wilsonia citrina) was the

seventh most common species in the Hoiberg study, but was

Table 11—Sample size (N), mean (x), standard error (SE), KolmogrovSmirnov test statistic (D), and significance level (Prob > KS) of perch

site tree height (m) for each bird species in old-growth and secondgrowth habitat, Moro Bottoms Natural Area, Arkansas, 1991 and 1992

(comparison-wise P-value: P <0.0077)

______________________________________________________________________________

Species/

random variable Nx SE Da b Prob>KS

______________________________________________________________________________

 Old growth

Acadian flycatcher 25 11.4 1.2 0.2433 0.1048

Carolina chickadee 6 16.8 2.7 .6984 .0069

Carolina wren 14 3.3 .4 .4770 .0008

Downy woodpecker 5 12.8 3.8 .2984 .7785

Kentucky warbler 10 2.1 .4 .6349 .0009

Northern cardinal 13 15.4 2.6 .2882 .2647

Prothonotary warbler 34 8.7 .8 .2011 .1945

Red-bellied woodpecker 11 26.5 2.2 .6984 .0001

Tufted titmouse 11 20.7 2.6 .6657 .0002

White-eyed vireo 28 8.8 .9 .1865 .3664

Tree height (m) 93 11.3 .7

Second growth

Acadian flycatcher 15 13.9 1.7 .3895 .0293

American redstart 29 24.4 1.2 .6563 .0001

Carolina chickadee 9 21.8 2.5 .6337 .0020

Carolina wren 26 5.7 1.0 .2247 .1976

Downy woodpecker 5 20.8 2.1 .6563 .0301

Kentucky warbler 12 2.3 .4 .6093 .0005

Northern cardinal 17 16.1 2.3 .3621 .0333

Prothonotary warbler 19 8.5 1.0 .1801 .6291

Red-bellied woodpecker 7 27.6 1.1 .8281 .0002

Tufted titmouse 9 23.7 2.2 .6562 .0012

White-eyed vireo 30 9.1 1.0 .1573 .5422

Tree height (m) 96 11.0 .6

______________________________________________________________________________

a Calculated from use sites and 93 random sites in the old-growth study site using

the Kolmogrov-Smirnov test.

b Calculated from use sites and 96 random sites in the second-growth study site

using the Kolmogrov-Smirnov test.
78

not among the 10 most common species at Moro Bottoms.

There also was substantial overlap between Moro Bottoms

and the Atchafalaya Basin (Dickson 1978b) and between

Moro Bottoms and the old-growth habitat of the Congaree

Swamp (Hamel 1989) with eight and nine species,

respectively, common to those communities (table 2). In

west Tennessee bottomlands (Ford 1990), however, only six

of the top ten species made the Moro Bottoms list.

At least some of the variation among studies can be

explained as sampling error. For example, the 12-ha oldgrowth grid encompassed about 30 percent of the entire

stand, but it did not include the complete range of elevation

or microtopographic variation that existed throughout the

stand (Zollner 1993). Alternatively, differences in species

composition (or density) of >1 species across bottomland

sites may reflect some habitat differences, albeit subtle, or

even ephemeral. Hamel (1989) noted several species

whose occurrence was limited to only one of the six forest

habitats sampled in South Carolina. In our study, we noted

variation across Moro Bottoms Natural Area in specific

habitat features such as the presence of canebrakes.

Canebrakes and other dense undergrowth are a favorite

nesting habitat for Swainson’s warblers.

Also, wood thrush may have been absent from our grids

because those sites often were still flooded during spring

when breeding males arrived. Indeed, it was not uncommon

to have the Natural Area almost completed flooded for a few

days in late June (Zollner 1993). Because of their

dependence on soil invertebrates as a food base, wood

thrush establishment of territories on our study grids may

have been precluded by the extent and duration of flooding.

Ford (1990:35) noted that the wood thrush had the lowest

density (5 pairs per 100 ha) of widespread species in west

Tennessee bottomlands where almost all of what remains is

the lower elevation habitat, which was presumably too wet

for clearing and conversion to agriculture.

Finally, some of the variation was almost certainly related to

species-specific breeding ranges or because of the areasensitive nature of some species (Robbins and others

1989). The American redstart, for example, was probably

absent from south-central Louisiana (Dickson 1978b)

because rarely (if ever) does this species breed that far

south in Louisiana. Moro Bottoms Natural Area is part of a

narrow, frequently interrupted, riparian system largely

surrounded by pine plantations. The hairy woodpecker

(Picoides villosus) may be precluded from occurring within

small bottomland fragments; the cerulean warbler

(Dendroica cerulea) was probably absent because of either

of the aforementioned reasons.

Habitat Use

Water—Water is a dominant feature of bottomland

hardwood forests (Smith 1977). Ford (1990) reported that

the highest densities of birds in west Tennessee occurred in

bottomland forests along an unchannelized river. Swift and

others (1984) found the highest bird densities in Connecticut

were associated with plots that included streams. They also

reported a positive correlation between surface water

coverage and species richness and density in both the

foliage gleaning and ground foraging avian guilds.

Shugart and James (1973) classified the Acadian flycatcher,

northern parula, Kentucky warbler, and American redstart as

moist forest specialists in Arkansas. However, Shugart and

James (1973) did not specifically examine the effects of

surface water on singing perch site selection. All four of

these moist forest specialists were abundant at Moro

Bottoms; only the Acadian flycatcher, however, was closely

associated with surface water. Somewhat surprising, the

prothonotary warbler was not listed as a moist forest

specialist (Shugart and James 1973), but also showed a

strong affinity for water at Moro Bottoms. The importance of

water to these two species also was reflected by the large

proportion of Acadian flycatcher and prothonotary warbler

territories that were comprised of water (Smith and others

1993b).

The Kentucky warbler, another moist forest specialist

(Shugart and James 1973), surprisingly occurred farther

from water than expected in Moro Bottoms (table 6). Thus,

surface water alone may not be critical to some moist forest

species; rather, it may be an ecological correlate of the

moisture regime, such as invertebrate abundance. For

Acadian flycatchers and prothonotary warblers, standing

water may provide direct and indirect benefits as both

species were often seen perching over or adjacent to

streams. They seemed to use these areas as flyways along

which they foraged. Conversely, the Kentucky warbler was

not observed using these flyways and probably prefers the

moist forest because of increased food associated with

these habitats. Indeed, Smith (1977) noted the high

abundance of insects and soil invertebrates in moist forests

as compared to an upland post oak forest (Quercus stellata)

in Arkansas.

The Carolina wren and the Kentucky warbler were the only

species that occurred in drier sites of both old-growth and

second-growth habitats. This may be related to the flood

regimes in Moro Bottoms. These two species both feed on

or near the ground and nest on the ground or in cavities

(Carolina wren only) or low shrubs (Ehrlich and others

1988). In our study, foraging substrate within territories that

were too close to streams would frequently have been

unavailable because of flooding, which occurred several

times throughout the 1991 and 1992 breeding seasons.

Snags—Snags were very abundant in both habitats. In

second-growth habitat, this was to some extent a result of

“habitat improvement” by a local hunting club; in old growth,

stubs created by wind (i.e., snapped tops) and mortality from

windthrow damage of adjacent trees probably contributed to

snag abundance. Flooding and associated stress-induced

mortality was probably common in both habitats. Thus,

snags at Moro Bottoms were probably not a limiting

resource as reported elsewhere (e.g., Dickson and others

1983). Most cavity nesters at Moro Bottoms showed no

significant affinity for snags (table 7). Only the Carolina

wren, which occasionally nests in cavities, and the Kentucky

warbler showed an affinity for snags, especially snags

created by treefalls. These snags were generally located in

the center of canopy gaps where Carolina wrens and

Kentucky warblers were frequently observed foraging and

singing. In many circumstances, snags were the only

elevated singing and display perches in the interior of gaps.
79

Gap Size—Internal patchiness in the form of treefall canopy

gaps attracted a large number of bird species and

individuals in Moro Bottoms. Openings created by treefalls

lead to a high degree of habitat structural diversity (Urban

and Smith 1989). This diversity is similar to that at the forest

edge, but might be considered internal edge that operates at

a finer scale (Noss 1988). Noss (1988) reported that the

proportion of gaps in a forest was the best predictor of bird

density in Florida. At Moro Bottoms, gaps represented 22

percent of the old-growth habitat, which was greater than the

3.4 percent reported by Noss (1988).

Birds concentrated in gaps presumably because of

increased food resources (Noss 1988) and abundant

favorable nest sites (Morse 1985). The dense shrub layer

that develops in gaps offers concealment for nests, as well

as an increased fruit and seed production over nongap

areas of the forest. Blake and Hoppes (1986), in a mist net

study of gaps in Illinois, reported more migratory frugivores,

granivore-omnivores, and foliage gleaning insectivores in

gap areas than in nongap areas.

Of the 10 species intensively studied in old growth at Moro

Bottoms, four species showed a significant association with

gaps (table 8): Carolina wren, Kentucky warbler,

prothonotary warbler, and white-eyed vireo. As expected,

these same species preferred areas with a more open

canopy (table 9). Freemark and Collins (1992) included

tufted titmouse and northern cardinal in a list of interior edge

species, but excluded the Kentucky warbler. Noss (1991)

also listed Carolina chickadee and red-bellied woodpecker

as edge attracted species in Florida. Variation in affinities

shown by species (Freemark and Collins 1992, Noss 1991)

may be a result of differences in habitat across studies.

Abundance and availability of gaps at Moro Bottoms may

have made it difficult to discern the importance of internal

patchiness by simply measuring distances to the nearest

gap. Only those birds that spent most of the time in the gap

interior showed statistically significant use. For the Kentucky

warbler, included among forest interior species by Freemark

and Collins (1992), the difference may be only in semantics.

Kroodsma (1984) reported that the Kentucky warbler

avoided edge, but there was no apparent reference as to

whether canopy gaps were considered edge.

The white-eyed vireo was the only species that clearly

selected individual gaps based on the amount of vegetative

cover in the understory and midstory. Emlen and others

(1986) listed the absence of dense low shrubs as the main

environmental constraint on white-eyed vireos. Ford (1990)

reported that white-eyed vireo density in Tennessee

increased with increasing height of the herbaceous layer

and increasing stem density. Outline drawings of the “nichegestalt” for this species (James 1971) seemed to show that

they preferred areas of open canopy with a dense low shrub

cover. The white-eyed vireo was the only species whose

territory contained a significantly greater proportion of

canopy gaps (65 percent) than expected in Moro Bottoms

(22 percent) (Smith and others 1993b). In contrast, the

Acadian flycatcher appeared to avoid gaps by using areas

with a closed canopy. Ford (1990) found Acadian flycatchers

to be negatively correlated with shrub cover. Noss (1988)

and Kroodsma (1984) also listed this species as avoiding

edge.

Tree species, d.b.h., and height—The frequency

distribution of tree species used by birds was significantly

different from the available distribution for all avian species

(table 12). This difference may be related to height of

various tree species; for example, the white-eyed vireo

perched most often in eastern hornbeam which rarely (if

ever) reaches a height of 15 m. Acadian flycatchers seemed

to prefer Carolina ash (Fraxinus caroliniana) and water elm

(Planera aquatica). This preference may be site specific,

associated with perching over water, which is where these

tree species grow, rather than because of the attributes of

the trees. One probable example of a strict preference for

tree species in our study was the frequent use of swamp

chestnut oak by the American redstart. Sweetgum and black

gum were much more abundant in second-growth habitat

(fig. 2), yet the American redstart was nearly always seen in

swamp chestnut oak. Large leaves and dense foliage, which

are typical of the swamp chestnut oak, presumably provide

abundant foraging substrate, an attractive feature for

insectivorous leaf-gleaning specialists such as the American

redstart.

Ecological and Management Implications

The high avian diversity associated with undisturbed mature

deciduous hardwood forests may be related to small,

naturally occurring canopy openings, <2 ha, created by

windstorms and fire. These canopy gaps are responsible for

much of the foliage and structural variation within these

forests (Urban and Smith 1989). Large logs and snags

remaining after disturbance provide foraging and nesting

substrate for numerous bird species of old-growth forests

(Juday 1988, Thomas and others 1988). Approximately 14

species of Arkansas’ birds are associated with edge habitat

created by canopy gaps (Shugart and James 1973).

In contrast, anthropogenic disturbances, such as timber

management, typically occur more frequently, create larger

forest canopy openings, and result in more extensive

cumulative disturbance across landscapes than natural

disturbance regimes (Runkle 1982, 1991). Larger gaps (i.e.,

>2 ha) created by most regeneration and some thinning

operations may reduce species diversity by displacing

canopy or area-sensitive species and allowing invasion of

common early succession and edge species (Urban and

Smith 1989). Clearcutting, the harvest method generally

practiced in Arkansas, creates larger canopy openings with

harder, external edges (Noss 1988) than natural disturbance

processes. Consequently, breeding forest interior species

that depend on larger expanses of continuous mature

forests have declined in many portions of their historical

range (Freemark and Collins 1992, Hamel and others 1998).

The potential exists to modify timber harvest practices to

promote avian diversity (Thompson and others 1992).

Uneven-aged stands resembling presettlement forests could

perhaps be achieved with silviculture prescriptions such as

single tree or small group selection, which produce relatively

small canopy gaps. However, additional research is needed

on the effects of gap size and interspersion across

landscapes on bird habitat use, especially as it relates to
80

reproductive success. Only then can prescriptions be

developed to minimize negative impacts of forest

management on indigenous avifauna.

ACKNOWLEDGMENT

This study was supported by Arkansas Forestry

Commission, Arkansas Game and Fish Commission,

Arkansas Game and Fish Foundation, Arkansas Natural

Heritage Commission through USDA Forest Service

Challenge Grant No. 19-90-045, with cooperation from the

Arkansas Nature Conservancy. J. Wakeman and J. Spalding

were very helpful during all phases of this research project.

K. Willis and P. Dusang provided computer and

programming assistance. We extend a special thanks to J.H.

McGuiness for coordination of projects under the auspices

of this cooperative agreement. Also, M.S. Woodrey and P.B.

Hamel reviewed an early draft of this manuscript and

provided valuable comments that ultimately improved the

quality of this paper.

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163 p. M.S. thesis.
83

SEASONAL HABITAT DISTRIBUTION OF SWAMP RABBITS,

WHITE-TAILED DEER, AND SMALL MAMMALS IN OLD GROWTH

AND MANAGED BOTTOMLAND HARDWOOD FORESTS

Winston P. Smith and Patrick A. Zollner1

Abstract—We studied swamp rabbits, white-tailed deer, and small mammals in an old-growth and adjacent secondgrowth and young-growth bottomland hardwood forest stands in southern Arkansas, August 1991–February 1993. Based

on average home range size and degree of overlap, minimum and maximum density estimates of swamp rabbits were 31

per km2 (no overlap) and 52 per km2 (overlap), respectively. Pellet group estimates of white-tailed deer suggested that

density varied from virtually zero in spring to 22 per km2 during autumn. With 29,436 trap nights of total effort during

winter, spring, and summer seasons, we captured 939 small mammals that were distributed among 14 species. There

were more individuals (n = 445) of more species (S = 11) in old-growth forest than other habitats; more new animals were

captured during spring (n = 378). Peromyscus gossypinus was clearly the most abundant species in all habitats during

all seasons; but it was always more abundant in old growth than other habitats. Ochrotomys nuttalli was the only species

that was notably more abundant in habitat other than old growth.

1

 Research Wildlife Biologist, Pacific Northwest Research Station, 2770 Sherwood Lane, Suite 2A, Juneau, AK 99801-8545; Department of

Wildlife and Fisheries, Mississippi State University, Mississippi State, MS 39762-9690 (Present address: USDA Forest Service, North Central

Research Station, Forestry Sciences Laboratory, 5985 Highway K, Rhinelander, WI 54501), respectively.

INTRODUCTION

European settlement and associated development during

the last three centuries were responsible for dramatic

alteration of forested landscapes. Some of the greatest

losses occurred in forested wetlands, presumably because

of an early dependence on waterways and the readily

available rich and productive soils of associated floodplains.

Within the Mississippi River floodplain alone, 80 percent of

the historical forested acreage (8.5 million ha, Creasman

and others 1992) was converted to agriculture or cleared for

urban development (MacDonald and others 1979, Rudis and

Birdsey 1986). So extensive has been the transformation

that southern bottomland forests are viewed as an

“endangered ecosystem” (Ernst and Brown 1989).

Remaining forests occur as fragments (Rudis 1993) that

have experienced a variety of timber harvests. Thus, all but

an estimated 0.1 percent of presettlement old-growth

bottomland hardwood forests have experienced significant

anthropogenic disturbance (Smith and others 1993).

There are attributes of old-growth forests (Thomas and

others 1988) largely absent from second-growth forests

(Runkle 1981, 1991). In bottomland forests, appreciable

differences are apparent between old-growth stands and old

(ca. 100 year-old) second-growth forests (Robertson and

others 1978). These include substantial differences in forest

structure such as the presence of large, decadent trees,

stem density and volume, canopy height and cover,

understory herb and shrub cover, and coarse woody debris

(Bailey 1993). These and other differences are important to

the relative success of different plant species (Runkle 1991)

and ultimately the diversity of habitats available within a

hardwood forest community (Sherman 1978). Continued

disturbance of old-growth deciduous forests alters species

composition and structure and generally reduces species

richness and habitat diversity (Sherman 1978).

Biological investigations of floodplain forests of North

America have been limited to game species such as whitetailed deer (Odocoileus virginianus; see Halls 1984), swamp

rabbit (Sylvilagus aquaticus; see Whitaker and Abrell 1986;

Zollner and others 1996), or waterfowl (see Reinecke and

others 1989). Nongame wildlife received little attention from

researchers or land managers until recently (Burdick and

others 1989, Wigley and Roberts 1994). Invertebrates,

plants, and other indigenous biota contribute significantly to

local and regional biological diversity, yet have been virtually

ignored (Harris 1989, Sharitz and others 1992).

To adequately assess and credibly project future, additional

(and probable cumulative) adverse impacts of land

management on the biological diversity of this unique

resource, baseline information on species distribution,

relative abundance, life history characteristics, and habitat

requirements is essential. Moreover, these baseline studies

should include previously unmanaged and relatively

undisturbed environments to ensure that “the entire

ecological arena within which our biota evolved” (Smith and

Hamel 1991:4) is represented, even though all that remains

are fragments of old-growth southern bottomland hardwood

forests.

This paper presents a community profile of mammals in

southern bottomland hardwood forests. Specifically, we

describe seasonal habitat distribution and relative

abundance of several mammal species along an age

gradient of old growth, intermediate second growth, and

young growth (i.e., recent high-grade harvest) from two

successive years of intensive sampling. Although this study

was an unreplicated retrospective study, it effectively

represents a substantial portion of the quantitative

information available on the mammal fauna of southern

bottomland hardwood forests.
84

STUDY AREA

The study area was Moro Bottoms Natural Area,

approximately 8 km east of Fordyce, AR (fig. 1). Moro

Bottoms Natural Area is in the upper West Gulf Coastal Plain

(James and Neal 1986) and contains a 40-ha old-growth

bottomland hardwood forest along Moro Creek, in Section

10, T11S, R12W, Cleveland County, AR. The old-growth

stand was part of a larger tract (ca. 70 ha) in Cleveland and

Calhoun counties, under the joint stewardship of the

Arkansas Natural Heritage Commission and the Arkansas

Nature Conservancy.

The climate is typical of the Coastal Plain with hot and

humid summers and a mean summer temperature of 27 oC.

Mean annual rainfall is 123.4 cm with much of the rain

occurring during spring. Portions of the study area adjacent

to the creek are inundated periodically during spring and

early summer, but water usually does not persist for more

than a week at a time. Several sloughs and creeks join the

main channel of the stream such that water is abundant

throughout the study area. Elevation of the site ranges

48–51 m above mean sea level.

The Moro Bottoms site is an excellent example of an oldgrowth bottomland hardwood forest. Trees, especially

sweetgum (Liquidambar styraciflua) and cherrybark oak

(Quercus falcata var. pagodifolia), are quite large with

exceptionally good form. Average density for overstory trees

was 31 stems per ha, and average basal area was 35.0 m2

per ha (153 ft2 per acre; Smith and others 1995, Zollner

1993). Sweetgum, cherrybark oak, and willow oak (Q.

phellos) are the three most common overstory species

(Smith and others 1995, Zollner 1993).

Moro Bottoms provided an ideal opportunity to study

mammals of unmanaged bottomland hardwood forest. Also,

during August 1989 Moro Bottoms experienced a severe

windstorm. Numerous windthrows occurred creating gaps in

the overstory ranging in size from a single stem (0.01 ha) to

about 0.3 ha. Because of these natural disturbances within

old growth and the proximity to managed second-growth

forests, the Natural Area presented an excellent setting to

examine the effects of recent natural and anthropogenic

disturbances on mammalian species habitat distribution and

relative abundance.

Figure 1—Distribution and orientation of deer pellet group transects, Moro Bottoms

Natural Area, Cleveland County, AR.

Natural area

White-tailed

deer

pellet group

N
85

METHODS

Swamp Rabbits

Capture and handling—Beginning on 12 January 1991,

and continuing through 2 June 1991, from 60 to 145 traps

were maintained and checked daily. These included 20 wiremesh traps covered in shade cloth and 125 wooden box

traps (20 X 20 X 60 cm). Eight drift fences were constructed

and installed near clusters of box traps to enhance trapping

success (Smith and others 1993, Zollner 1993).

Following capture, rabbits were weighed, identified to age

(i.e., juvenile or adult) and sex, fitted with a 350-g radiocollar, and released. Each rabbit was allowed 1 week to

adjust to its collar and recover from the stress of capture.

Thus, observations of movements and habitat use began

during the second week post-capture (Smith and others

1993, Zollner 1993).

Animal movements—It is important to monitor movements

during all activity periods to accurately reflect habitat

selection. However, it is difficult to determine the particular

time when activity begins during different times of the year.

Using the results of a detailed behavioral study as our basis

(Marsden and Holler 1964), we selected 1830 as a

conservative estimate of when evening activity should

commence during any month of the year. Likewise, 0630

was selected as a time when rabbits continued to be active

during all times of the year. Accordingly, the period between

0800 and 1700 was designated as the period during which

rabbits would most likely be resting during all times of the

year (Smith and others 1993, Zollner 1993).

Each rabbit was monitored daily between 0630 and 1830.

Because the initial response of swamp rabbits to perceived

threat is to remain motionless (Hamilton, 1955), we were

often able to approach within a few meters of individuals and

locate specific brush piles or thickets where the animal was

resting. This procedure facilitated our locating rabbits

consistently within an area defined by a 5–m radius. The

difficulty of moving through the study area in the dark limited

our ability to monitor rabbits at night. Twice each week,

rabbits were located between 1830 and 0630.

Microhabitat use—During June and October of 1991, 36

quadrats in each of three study grids (fig. 2) were randomly

selected and searched for signs of swamp rabbit browse.

This sample size was calculated based upon variance (Stein

1945) in the density of browseable stems found during a

pilot study (Zollner 1993). Quadrats were searched for

browse by dividing them into quarters that correspond to the

corners of the quadrat. Inside each quarter 15 0.5 X 0.5-m

plots were placed systematically at 2-m intervals along three

rows, 5 m apart. Inside each plot, number of browseable

(available) stems and browsed (used) stems of each plant

species were recorded. Browseable stems were defined as

Figure 2—Location of old growth, second growth, and recently harvested (cut-over) bottomland

hardwood small mammal trapping grids, Moro Bottoms Natural Area, Cleveland County, AR.

N
86

all vegetation less than 0.8 m above the ground and <1 cm

in diameter. Stems were considered browsed by rabbits if

they were cut off cleanly and not torn as is typical of whitetailed deer (Strole and Anderson 1990). All quarter sections

where browse was observed in any plot were considered

browsed for that survey and their locations were noted.

During July and November of 1991, microhabitat

characteristics were measured in each quadrat quarter

where evidence of browsing was observed. Six

characteristics were measured at each site where swamp

rabbit browsing was observed and at randomly selected

points in each habitat type. A 10-m north-south line transect

intercepted the center of each habitat point, and was used to

estimate the percent composition of herbaceous vegetation,

shrub coverage, down treetops, and fallen logs at each site.

The average value of spherical densiometer measurements

(Vora 1988) at the center of each plot and 5 m from the

center of each plot at 0, 90, 180, 270 degrees was used to

estimate percent canopy closure at each site. A point-centerquarter method of habitat evaluation was used to

approximate overstory basal area (Gysel and Lyon 1980).

Trees >5 cm diameter at breast height (d.b.h.) with no

branches from other trees over their crowns were

considered in the overstory.

Density—Because of the small number of new captures and

recaptures, we were not able to use a ratio-estimator to

estimate population size and density. Instead, we present

minimum population estimates that were derived from the

average core area (i.e., maximum area where observed

utilization distribution exceeds a uniform utilization

distribution, Dixon and Chapman 1980) occupied by each

adult female, adult male, and juvenile. In addition, we

estimated density under the following assumptions: an

average home range overlap of 25 percent among females

and 50 percent between females and juveniles; and the

entire study area was suitable swamp rabbit habitat.

White-Tailed Deer

Habitat use—We estimated seasonal use of gaps and

forested habitats by white-tailed deer from counts of fecal

pellet groups (Eberhardt and Van Etten 1956). This

technique requires that observers remove or mark (e.g.,

spray paint) all pellets encountered along a predefined

transect. The observer then returns to the transect after a

predetermined period of time has elapsed and records the

number of pellet groups that are encountered. Typically, the

sequence of transects traversed during the marking or

clearing phase is maintained during the enumeration phase

so that the “elapsed time,” i.e., time period between clearing

and counting, is approximately the same for all transects

(Neff 1968). Total number of pellet groups recorded among

all transects provides an estimate of deer density according

to the premise that white-tailed deer on the average

defecate at a predictable rate. We used the summer (24

groups per day) and autumn-winter (31 groups per day)

estimates for southern white-tailed deer (Sawyer and others

1990).

In this study, we conducted bimonthly censuses; months

were alternated between years so that a 2–year period

provided seasonal estimates that included every month.

Also, transects were established in such a fashion as to

incorporate forested habitats and gaps in proportion to their

occurrence across the study area. We initially (December

1990) established 17 transects: four transects were 4 m X

0.25 km; the remaining transects were 4 m X 0.5 km (fig. 1).

In July 1992, we added one 4 m X 325 m transect and eight

4 m X 350 m transects. Figure 1 illustrates the spatial

distribution and orientation of transects across the study

area. Chi-square was used to test the null hypothesis that

occurrence of deer within habitats was according to

availability (i.e., proportion of study area) of gaps and

forested habitats (Byers and others 1984). We used an

experiment-wide error rate of 0.05; comparison-wide error

rate varied according to the number of comparisons and

followed the procedures of Bonferroni adjustments (Byers

and others 1984).

Small Mammals

Habitat distribution—We estimated seasonal species

distribution and abundance across three bottomland

hardwood habitats by live trapping for 2 years during spring,

summer, and winter. Trapping began August 1991 and

continued through February 1993. We established three 300

m X 300 m (9 ha) trapping grids, one each in old-growth,

second-growth, and recently logged (cutover) bottomland

hardwood forest habitats (fig. 2). A 15 X 15 array (i.e., 20–m

spacing between traps) of Sherman (H.B. Sherman Traps

Inc., P.O. Box 20267, Tallahassee, FL 32316) live traps (7.6

X 8.9 X 22.9 cm) was established on the forest floor of each

grid. Superimposed on the existing grid in each habitat, we

established a 3 X 3 array (100–m spacing) of elevated

platforms (1.8 m) and a 5 X 5 array (60–m spacing) of

wooden box traps on the forest floor. On each elevated

platform, we placed a Sherman live trap and a wooden box

trap (20 X 20 X 60 cm). All wooden box traps were equipped

with a predator guard (Zollner, 1993)

Also, four “triad” arrays of 10 pitfall traps were installed, one

midway on each of three sides (north, south, east), and one

in the approximate center of each grid. Each triad array

included a center pitfall trap and three drift fence “arms”

radiating at about 120° angles from the center. Each triad

arm was comprised of a center pitfall trap and a trap on

each end, between which were two 10–m X 60–cm

aluminum drift fences. Each pitfall trap was made of two No.

10 aluminum cans taped end-to-end; concrete “anchors”

were bolted to the bottom of each pitfall trap to prevent

water table pressure from expelling the cans.

Thus, each habitat grid contained 408 traps: 234 Sherman

live traps, 34 wooden box traps, and 40 pitfall traps. General

sampling protocol included the operation of all grids

simultaneously during each season. On each grid, traps

were checked once in the morning; Sherman and box live

traps were baited with a mixture of rolled oats and vanilla

extract. Each trapping session began during the

approximate middle of each calendar season and continued

continuously until we approached 100 percent recapture, or

for a period not exceeding 10 days. Individuals were

identified to species and sex, weighed, measured, uniquely

marked, and released at the trap site. Small mammals (e.g.

Peromyscus sp.) were toe-clipped using a standard

procedure (Blair 1941); larger mammals (e.g., Didelphis

virginiana) were marked with a numbered, self-piercing ear
87

tag (National Band and Tag Company, Newport, KY) in both

ears.

Species abundance was estimated seasonally as the

number of individuals of each species captured on a habitat

grid. Although total area contained within each grid was

similar, number of captures was not an estimate of density

because of movements of individuals from and to the grid

during the sampling period (Van Horne 1982). For the

purpose of estimating relative abundance, however, we

assumed that the effective sampling area, i.e., total area

supporting animals captured on a grid, did not vary across

habitats.

RESULTS

An initial survey of the study area revealed that at the

beginning of the study, about 25 percent of the old-growth

tract was in windthrow gaps. Canopy openings ranged in

size from 500 m2

 to 5000 m2 with most of the gaps being

less than 1500 m2; about a third of the gaps were larger than

2500 m2

 (Smith and others 1995).

Swamp Rabbits

Density—From 12 January through 26 June 1991, 13,520

trap nights of effort were used to capture 13 swamp rabbits.

Seven individuals, four adult females, one adult male, and

two juveniles were large enough to carry a radio-transmitter

for monitoring. A total of 107 nocturnal, 809 diurnal, and 308

crepuscular locations were recorded; 862 locations were

recorded during spring-summer (summer) and 362 locations

were recorded during fall-winter (winter).

Mean home range for adult females during the growing

season (spring-summer) was 11.9 ha (29.3 acres), whereas

the adult male had a summer home range of 19.9 ha (49.2

acres) and a juvenile home range was 5.6 ha (13.8 acres).

Assuming no home range overlap among females or among

males, nor between juveniles and males or females, with

complete overlap of male and female home ranges, our

minimum density estimate during the growing season was

8.4 adult females per km2 (21.8 per mi2), 5.0 adult males per

km2 (13 per mi2), and 17.9 juveniles per km2 (46.4 per mi2).

With 25 percent overlap, the average exclusive area

occupied by females becomes 8.9 ha (22.0 acres); for

juveniles averaging 50 percent overlap, their exclusive core

area is 2.8 ha (6.9 acres). Corresponding density estimates

become 11.2 adult females per km2 (29.1 per mi2

) and 35.7

juveniles per km2 (92.8 per mi2); adult male density

estimates remain unchanged. Thus, minimum population

size on the study area (40 ha) during the growing season

was 13 swamp rabbits with perhaps as many as 21, if our

estimates of home range overlap were reasonable.

Habitat use and microhabitat characteristics—The initial

survey of the study area classified 27 percent of the

quadrats as gaps with the remaining portion categorized as

closed-canopy forest. All but five of 1,117 diurnal and

crepuscular locations occurred in gaps. When compared to

that expected according to the relative abundance of gaps

(i.e., 27 percent of 1,117, or 302 locations) with a goodnessof-fit test (Zar 1984), we found that the probability of this

occurring by random chance was very small (χ2

 = 2,978,

P < 0.0001). In some circumstances, mostly during

crepuscular time periods, rabbits were first encountered in

open, grassy areas; the vast majority of diurnal and

crepuscular locations, however, were within resting/hiding

places such as in large brushpiles or woody debris from

windthrown trees, or inside a cavity in the bole of a down

tree. Unfortunately, we were unable to classify nocturnal

locations because of having to use triangulation rather than

direct observations.

Microhabitat features of browsing sites used by rabbits

during summer and winter are summarized in table 1 along

with features measured at random sites. During the summer,

stand density of the overstory at sites used by rabbits for

browsing (42.0 stems per ha) was greater (χ2 = 7.51, d.f. =

1, P < 0.01) than at random sites (23.0 stems per ha).

Understory basal area at browse sites (0.13 m2 per ha) was

less (χ2 = 6.21, d.f. = 1, P < 0.025) than that available across

the study area (0.22 m2 per ha). Also, midstory basal area at

browse sites (2.35 m2 per ha) was less (χ2 = 4.28, d.f. = 1,

P < 0.05) than that recorded at random sites (2.78 m2 per

ha).

White-Tailed Deer

During the period December 1990—April 1992, 17 transects

were sampled in the old-growth stand (48.4 ha) bimonthly;

14 transects were sampled in adjacent second-growth

stands (26.4 ha). Beginning July 1992 and continuing

through November, an additional nine transects were

surveyed in the old-growth stand. The elapsed time (i.e.,

period between cleaning a transect and enumerating pellet

groups) varied from 3 to 8 days across bimonthly sampling

periods according to number of investigators and amount of

flooding, but was similar among transects within a sampling

period (fig. 3).

Density of white-tailed deer across the old-growth and

second-growth stands varied considerably among bimonthly

sampling periods (fig. 3). Throughout the study period, the

study area (i.e., old-growth stand) received much more use

during autumn-winter (x = 13.5 deer per km2 [35.0 deer per

mi2]) than during spring-summer (x = 1.1 deer per km2 [2.8

deer per mi2

]). Unfortunately, estimates were not available

from March or April 1991 because >90 percent of the

transects were flooded. Deer densities in the adjacent

second-growth stand (fig. 2) showed the same seasonal

patterns as that recorded in the old-growth stand (fig. 3).

Deer densities recorded during March and April in the

second-growth stand (of which <25 percent was inundated)

were typical of spring-summer values in the old-growth

habitat (fig. 3).

Frequency of occurrence of white-tailed deer in gaps or

closed-canopy forest in the old-growth stand or in an

adjacent second-growth stand is summarized in table 2. In

table 3, frequency of occurrence of white-tailed deer in

canopy gaps or closed-canopy forest across old-growth and

adjacent second-growth stands is presented. The latter

provides insight into how deer used the old-growth stand

relative to surrounding available forest habitat.
88

Generally, white-tailed deer used gaps and closed-canopy

forest in proportion to availability (χ2

 < 3.84, d.f. = 1 P >

0.05) across the old-growth study area and in an adjacent

second-growth stand Notable exceptions occurred in the

old-growth stand during April 1992 (χ2

 = 6.4, P < 0.025) and

June 1992 (χ2

 = 4.3, P < 0.05) when deer used gaps more

frequently and closed-canopy forest habitat less frequently

than expected from availability. Also, percent use of canopygaps in the second-growth stand during February 1992 was

greater (χ2 = 6.9, P < 0.01) than expected. Although a similar

pattern occurred in the old-growth stand, it was not quite

significant (χ2 = 2.9, 0.05 < P < 0.10), probably because of

the effect that inundation had on area sampled (table 2) and

the sample size of pellet groups.

When examined from the perspective of bimonthly

distributions in habitats across both stands, deer appeared

to depart (i.e., χ2 > 7.82 P < 0.05) more from the expected

Table 1—Mean (×) and standard error (×s

) of microhabitat features of random

sites and sites where rabbits were observed browsing, Moro Bottoms Natural

Area, AR, February 1991–March 1992 (χ2 statistic is from a non-parametric

analysis of variance.)

Random Browse

Variable site site

× ×s × ×s χ2 P > χ2

Summer

(n = 46) (n = 30)

 Percent cover dead

 Wood <5 cm 3.13 1.21 8.37 2.55 2.13 0.250

 Wood >5 cm 3.01 1.793.36 1.88 0.09 .750

 Shrub cover % 9.83 2.91 8.19 1.68 .01 .900

 Bare ground % 68.23 5.74 73.85 3.13 .01 .900

 Herbaceous cover % 28.77 5.2926.11 3.13 .23 .750

Basal area (m2 per ha)

 Overstory 34.66 2.36 37.16 2.17 .36 .750

 Midstory 2.78 0.45 2.35 0.31 4.28 .050

 Understory 0.22 .40 0.13 .03 6.21 .025

Density (stems per ha)

 Overstory 23.0 2.03 42.0 5.74 7.51 .010

 Midstory 137.0 38.65 118.0 13.31 .26 .750

 Understory 397.0 67.21 483.0 131.07 .61 .750

Canopy closure 75.92.63 80.8 1.94 3.45 .100

Herbaceous density

 (stems per m2 9.2 1.36 10.9 1.09 .87 .750

Winter

(n = 53) (n = 48)

Percent cover dead

 Wood <5 cm 5.31 1.75 3.78 2.06 .41 .500

 Wood >5 cm 1.77 .62 1.59.66 .03 .750

Shrub cover % 4.86 1.65 9.50 4.63 .09 .750

Bare ground % 80.96 3.83 79.73 5.24 1.19 .250

Herbaceous cover % 11.83 2.14 13.82 3.48 .06 .750

Basal area (m2 per ha)

 Overstory 35.34 1.82 36.00 2.58 .11 .500

 Midstory 1.86 .23 1.40 .22 .74 .250

 Understory .09.02 .10 .03 .04 .750

Density (stems per ha)

 Overstory 31.0 6.70 23.0 3.23 .03 .750

 Midstory 234.0 49.22 147.0 20.32 .73 .250

 Understory 418.0 143.03 240.0 42.59.71 .250

Canopy closure 28.5 1.84 32.7 3.72 1.08 .250

Herbaceous density

 (stems per m2) 5.3 .77 8.3 1.78 1.36 .750
89

Table 2—Relative abundance (percent occurrence) of white-tailed deer in closed-canopy forest and

canopy openings (gaps) in bottomland forest, Moro Bottoms Natural Area, AR, December 1990–

November 1992 (percentages computed for within habitat totals; Chi-square statistic [χ2] computed for

goodness-of-fit test, d.f. = 1)

Old growth Second growth

Availability Use Availability Use

Month per year Gaps Forest Gaps Forest Gaps Forest Gaps Forest

December 1990 8.5 91.5 12.0 88.0 0.2 10.3 89.7 0.0 100.0 0.4

March 1991 — — — — — 10.3 89.7 23.0 77.0 .2

April 1991 — — — — — 10.3 89.7 .0 100.0 .6

July 1991 18.8 81.2 0.0 100.0 .1 10.3 89.7 .0 100.0 .6

October 1991 18.8 81.2 17.3 82.7 .2 10.3 89.7 11.5 88.5 .3

February 1992 18.8 81.2 32.0 68.0 2.9 10.3 89.7 22.2 77.8 6.9

April 1992 18.8 81.2 50.0 50.0 6.4 10.3 89.7 .0 100.0 .1

June 1992 18.8 81.2 100.0 0.0 4.3 10.3 89.7 .0 0.0 .0

September 1992 18.8 81.2 50.0 50.0 1.3 10.3 89.7 33.3 66.7 1.7

October 1992 18.8 81.2 16.7 83.3 .1 10.3 89.7 7.1 92.9 .3

November 1992 18.8 81.2 12.0 88.0 .8 10.3 89.7 3.6 96.4 1.3

Figure 3—White-tailed deer density estimates from bimonthly pellet group counts in bottomland hardwood forest, Moro Bottom Natural

Area, AR, December 1990—November 1992.

Dec. 90 Mar. 91 Apr. 91 Jul. 91 Oct. 91 Feb. 92 Apr. 92 Jun. 92 Sep. 92 Oct. 92 Nov. 92

Old growth Second growth

25

20

15

10

5

0

Deer/km2 Figure 3—White-tailed deer density from bimonthly pellet group counts in bottomland hardwood forest, Moro Bottom Natural Area, AR,

December 1990–November 1992.

χ2 χ2
90

null model (table 2). In particular, deer used closed-canopy,

old-growth forest more often (χ2

 = 14.5, d.f. = 1, P < 0.001)

and closed-canopy, second-growth forest less often (χ2 =

16.0, d.f. = 1, P < 0.001) than expected in December 1990.

This pattern occurred again during early autumn (October)

1991 (old-growth: χ2 = 15.1, d.f. = 1, P < 0.001; secondgrowth: χ2 = 26.4, d.f. - 1, P < 0.001). Conversely, deer used

closed-canopy second-growth forest more often during

autumn (November) of 1992 (χ2 = 5.8, d.f. = 1, P < 0.01)

while showing proportional use among other habitats.

During February 1992, deer mostly occurred in the secondgrowth stand with greater than expected use of both gaps

(χ2 = 21.2, d.f. = 1, P < 0.001) and closed-canopy forests

(χ2 = 6.8, d.f. = 1, P < 0.01). This pattern was reversed in the

following spring (April) when deer occurred almost

exclusively within the old-growth stand (table 4), with a

significant preference for canopy gaps (χ2 = 10.2, d.f. = 1,

P < 0.01).

Small Mammals

During the study, 29,436 trap nights of effort were equally

distributed across habitats as follows: summer—2,396 trap

nights; winter—8,520 trap nights, and spring—8,520 trap

nights. We captured a total of 871 terrestrial small mammals

distributed among 9 species (table 4); we also captured 2

southern flying squirrels (Glaucomys volans), 6 gray

squirrels (Sciurus carolinensis), 1 fox squirrel (S. niger), 51

opossum (Didelphis virginiana), and 8 raccoons (Procyon

lotor). More animals were captured during spring (n = 378)

than either winter (n = 330) or summer (n = 231). Old growth

produced the largest number of new captures (n = 445) and

species (S = 11), whereas second growth produced the

fewest new captures (n = 183).

Mammal species composition of habitats varied across

seasons and years. The cotton mouse (Peromyscus

Table 3—Relative abundance (percent occurrence) of white-tailed deer in closed-canopy forest and canopy

openings (gaps) in bottomland forest, Moro Bottoms Natural Area, AR, December 1990–November 1992

(percentages computed for across habitat totals; Chi-square statistic [χ2

] computed for goodness-of-fit test,

d.f. = 3)

Old growth Second growth

Availability Use Availability Use

Gaps Forest Gaps Forest Gaps Forest Gaps Forest

December 1990 4.6 49.4 6.0 78.6 1.4 44.7 0.0 15.4 32.0

March 1991 — — — — 10.3 89.7 23.0 77.0 4.3

April 1991 — — — — 10.3 89.7 .0 100.0 .6

July 1991 12.0 52.0 0 20.0 3.7 32.3 .0 80.0 4.5

October 1991 12.0 52.0 15.1 71.9 3.7 32.3 1.5 11.5 45.6

February 1992 12.0 52.0 11.4 24.3 3.7 32.3 14.3 50.0 38.4

April 1992 12.0 52.0 45.5 45.5 3.7 32.3 .0 9.0 12.6

June 1992 12.0 52.0 100.0 0.0 3.7 32.3 .0 0 7.3

September 1992 12.0 52.0 20.0 20.0 3.7 32.3 20.0 40.0 6.9

October 1992 12.0 52.0 10.0 2.9 3.7 32.3 50.0 37.1 1.0

November 1992 12.0 52.0 5.7 41.5 3.7 32.3 1.9 50.9 9.2

gossypinus) was clearly the predominant species during all

seasons and across all habitats (table 4); it was more

abundant in old-growth habitat during all seasons. The only

other small mammals that were consistently captured across

habitats and seasons were hispid cotton rat (Sigmodon

hispidus) and golden mouse (Ochrotomys nuttalli). The

golden mouse was the only small mammal species that was

notably less common in old growth as compared to the other

habitats (table 4).

There were limited data, but some interesting variation in

platform captures of terrestrial small mammals was

apparent. During spring 1992, relatively heavy rainfall

occurred at the end of the trapping session. During the initial

4 days of trapping, when there was no measurable

precipitation, we captured 11 Peromyscus gossypinus in

elevated platform traps; no other species were recorded.

Results from one night of trapping following and during

rainfall yielded 19 P. gossypinus and 2 Ochrotomys nuttalli.

Nine P. gossypinus were recaptures of individuals previously

caught in forest floor traps; the other 10 platform captures

were unmarked P. gossypinus. When we examined data

from the 9 nearest forest floor traps (i.e., surrounding 3 X 3

array), in only one instance did we find >1 trap occupied. In

that one instance, there were four occupied traps.

Another interesting anecdote was a dramatic increase in the

number of gray squirrels captured during April—May 1991.

While trapping swamp rabbits with wooden box traps on the

forest floor, we captured squirrels at a rate that was an order

of magnitude greater than previously observed during this

study. Typically, efforts to capture swamp rabbits during this

study averaged 1 to 2 gray squirrels per week. After 2 to 3

weeks of catching notably more gray squirrels, comparable

trapping efforts again yielded about 1 to 2 gray squirrels per

week. A relatively large proportion of the gray squirrels was

represented by juveniles, suggesting perhaps that the

χ2
91

P. leucopus, which are extremely difficult to differentiate in

the field (Lowery 1974, St. Romain 1976). Adult P.

gossypinus were relatively easy to recognize in this study

because their weights clearly exceeded the maximum

reported for P. leucopus (36 g; Sealander and Heidt 1990).

The primary difficulty was determining whether smaller

(<35 g) individuals were juvenile P. gossypinus or adult P.

leucopus. Pelage of juvenile and adult Peromyscus typically

differ, but variation exists and opportunities for confusion are

not uncommon (St. Romain 1976, Lowery 1974).

Consequently, we likely misclassified some individual

Peromyscus.

Swamp Rabbit

Density—The swamp rabbit is confined to southern

bottomland forests of the Southeastern United States

(Chapman and others 1982). Historically, its range extended

from east Texas to extreme northeast South Carolina, and

from southern Illinois and extreme southwestern Indiana, to

the coast of the Gulf of Mexico. The lower Mississippi

Alluvial Valley (MAV) likely was a center of abundance for

Table 4—Seasonal abundance of small mammals in old-growth (OG), second-growth (SG), and younggrowth (YG) bottomland hardwood forest, Moro Bottoms Natural Area, AR, during the period August

1991–February 1993

Summer Winter Spring

Species OG SG YG OG SG YG OG SG YG

1991–92

Peromyscus gossypinus 42 21 24 56 24 28 48 23 25

 cotton mouse

Peromyscus leucopus 00 1 000 32 0

 white-footed mouse

Sigmodon hispidus 30 2 000 20 3

 hispid cotton rat

Ochrotomys nuttalli 0 8 0 0 2 2 0 10 0

 golden mouse

Reithrodontomys fulvescens 11 3 014 00 0

 fulvous harvest mouse

Microtus pinetorum 00 1 000 00 0

 woodland vole

Cryptotis parva 10 0 000 00 0

 least shrew

Blarina carolinensis 21 0 000 00 0

 southern short-tailed shrew

Sciurus carolinensis 00 0 000 00 0

 gray squirrel

Sciurus niger 00 0 000 00 0

 fox squirrel

Glaucomys volans 00 0 000 02 0

 southern flying squirrel

Didelphis virginiana 491 110 21 0

 opossum

Procyon lotor 10 0 000 00 0

 raccoon

Rattus rattus 10 0 000 00 0

 black rat

 Totals 55 40 31 57 28 34 55 38 28

continued

sudden increase in number of captures was related to

dispersal.

DISCUSSION

Assumptions and Limitations

The Moro Bottoms Natural Area and adjacent private lands

represented a natural laboratory and unique opportunity to

examine small mammal communities across a variation of

unmanaged and managed bottomland hardwood forests.

Unfortunately, this was not a replicated experiment and thus

one should be cautious about drawing general inferences

beyond our study.

Sources of error in this study included escape of captured

individuals before confirming whether they were new

captures. Unconfirmed small mammal captures occurred

infrequently (<1 per grid per season). We recorded them as

new animals and thus may have over-estimated relative

abundance of some species. Another potential source of

error was misidentification of Peromyscus gossypinus and
92

this species; indeed, the MAV historically included 65

percent of all southern bottomland forests (Smith and others

1993) and perhaps as much as 80 percent of the bottomland

forests in the range of Sylvilagus aquaticus.

In recent years, the distribution of the swamp rabbit has

diminished southward (Chapman and others 1982) and

population levels have decreased (Korte and Fredrickson

1977), presumably because of habitat loss and

fragmentation. In Missouri, Korte and Fredrickson (1977)

reported a decrease in distribution and abundance of this

species that coincided with the reduction of potential habitat

from 850,000 ha in 1870 to fewer than 40,000 ha in 1973.

Conversion of bottomland forests to row crops and

urbanization continued on into the mid–1980’s (Rudis and

Birdsey 1986); recall, 80 percent of the bottomland forests in

the lower MAV has been lost since European settlement.

Comparable loss of potential habitat was reported for other

portions of the range of this species (Whitaker and Abrell

1986). Consequently, the swamp rabbit is listed as a species

of special concern in Illinois, Indiana, Kentucky, and

Missouri.

In Indiana, Whitaker and Abrell (1986) attributed the decline

of swamp rabbits to four factors: (1) loss of available habitat,

(2) hunting pressure, (3) flooding, and (4) predator pressure.

Also, landscape context was listed as an important factor

determining long-term viability of swamp rabbit populations.

Apparently, populations occupying prime habitat nearby are

important as sources for marginal, less suitable habitat,

which may support swamp rabbits in good years.

Little information exists regarding historical or current

densities of swamp rabbit populations across its

geographical range. Terrel (1972) reported an autumn

density of 0.4 per ha (40 per km2

) in Indiana, with individuals

typically requiring a home range of 4.4 ha. More recently,

Whitaker and Abrell (1986) reported that an estimated 80

rabbits were distributed across 10 sites totaling 700 acres

(283.4 ha), which represents an average density of 0.28

Table 4—Seasonal abundance of small mammals in old-growth (OG), second-growth (SG), and younggrowth (YG) bottomland hardwood forest, Moro Bottoms Natural Area, AR, during the period August

1991–February 1993 (continued)

Summer Winter Spring

Species OG SG YG OG SG YG OG SG YG

1992–93

Peromyscus gossypinus 33 17 16 74 15 71 118 14 79

 cotton mouse

Peromyscus leucopus 10 0 000 60 3

 white-footed mouse

Sigmodon hispidus 4 0 7 8 4 6 10 0 10

 hispid cotton rat

Ochrotomys nuttalli 10 0 26904 2

 golden mouse

Reithrodontomys fulvescens 00 2 000 00 1

 fulvous harvest mouse

Microtus pinetorum 00 0 010 00 0

 woodland vole

Cryptotis parva 00 0 000 00 0

 least shrew

Blarina carolinensis 20 0 000 00 0

 southern short-tailed shrew

Sciurus carolinensis 12 0 000 12 0

 grey squirrel

Sciurus niger 00 0 000 10 0

 fox squirrel

Glaucomys volans 00 0 000 00 0

 southern flying squirrel

Didelphis virginiana 36 5 742 31 1

 opossum

Procyon lotor 21 2 100 00 1

 raccoon

Rattus rattus 00 0 000 00 0

 black rat

 Totals 47 26 32 92 30 89 139 21 97
93

rabbits per ha (28.2 per km2

). In this study, the minimum

density estimate during the growing season was 31.3 per

km2

 (0.31 per ha); average home range (100 percent) during

this period was 19.8 ha (Smith and others 1993, Zollner

1993). Our less conservative estimate (i.e., assuming 25

percent overlap in home range among females and 50

percent overlap between females and juveniles) of swamp

rabbit density approached 52 rabbits per km2 (0.52 per ha).

Given the observed overlap in home ranges among females,

and between females and juveniles (Smith and others 1993,

Zollner 1993), we suspect that swamp rabbit density during

our study was greater than the minimum 0.31 per ha; and

perhaps was not very different from that reported for Indiana

(Terrel 1972).

Nevertheless, it is difficult to ascertain whether densities

observed in this study (or reported in the literature)

represented low, intermediate, or high population levels. If

frequency of encountering pellet groups or incidental direct

observations are indicative of population levels, Moro

Bottoms Natural Area supported a conspicuously lower

density of swamp rabbits than Delta Experimental Forest, an

essentially contiguous 1050–ha tract of secondary

bottomland forests within the Mississippi River floodplain,

near Stoneville, Washington County, MS (W.P. Smith,

personal observation). Behavioral experiments and other

observations conducted during this study support the

hypothesis that swamp rabbit latrines (i.e., pellet groups)

represent territorial markers (Zollner and others, in press)

and thus, are probably a fair indication of relative

abundance.

Habitat use—One of the earliest investigations of this

species (Harrison and Hickie 1931) concluded that S.

aquaticus was associated with canebrakes, hence the

common name “cane cutter.” Whitaker and Abrell (1986)

later reported that good swamp rabbit habitat included cane

(Arundinaria gigantea), or elderberry (Sambucus

canadensis) on elevated areas with sufficient cover and

protected from most flooding. They noted that several tree

species were common among these sites: sugarberry (Celtis

laevigata), hackberry (C. occidentalis), silver maple (Acer

saccharinum), hickories and pecan (Carya laciniosa, C.

cordiformis, C. pecan [illinoensis]) elms (Ulmus spp.), ashes,

(Fraxinus spp.), sweetgum, cottonwood (Populus deltoides),

sycamore (Platanus occidentalis), oaks, and boxelder (Acer

negundo).

Although it varied considerably, giant cane was common in

portions of Moro Bottoms, especially where the canopy

previously had been interrupted. Generally, swamp rabbits

were observed more often where cane occurred than

expected; but it is unclear as to whether this was a causal

relationship, or if the co-occurrence of swamp rabbits and

cane are ecological correlates of some other phenomenon,

i.e., response to an interruption of the forest canopy. Clearly,

swamp rabbits occurred in canopy gaps much more

frequently than would be predicted from availability; but

many gaps did not have cane. The close association of

swamp rabbits with cane in Indiana (Harrison and Hickie

1931, Whitaker and Abrell 1986) was also likely a

circumstance where two bottomland hardwood endemics

with similar ecological requirements occupied the same

habitat rather than an obligate, or even facultative,

relationship.

Similar to Whitaker and Abrell (1986), we observed greater

than expected occurrence of certain tree species at sites

used by swamp rabbits, especially at browsing sites (Zollner

1993). Many of the species were similar to those reported by

Whitaker and Abrell (1986), notably elms, hickories, and

oaks. Since swamp rabbits typically do not use soft or hard

fruit, nor do they have any known needs affiliated with

certain tree species, we suspect that these associations are

reflecting common favorable environmental circumstances

rather than any life history need. One notable exception is

the predisposition that certain tree species have for forming

bole or buttress cavities, which may offer ideal refuge

against predation or inclement weather. Red maple was

identified in lowland sites as a cavity-prone species (W.P.

Smith, unpublished data).

Some tree species were observed less often at browse sites

than random sites, notably black gum, Carolina ash,

shellbark hickory, and Nuttall oak (Zollner 1993). But again,

this is probably a coincidence related to specific habitat

needs. Microsite distribution of many bottomland tree

species is often influenced greatly by smal1 (10–20 cm)

variations in elevation (Castleberry and others 1996, Pauley

and others 1996, Putnam and others 1960). Many of the tree

species that occurred less frequently at sites where rabbits

were observed foraging (as compared to random sites)

typically occur at lower elevations (e.g., Nuttall oak vs. water

oak, Zollner 1993) where flooding occurs more frequently

and for longer periods. Conversely, loblolly pine was three

times more likely to occur at sites used by rabbits for

foraging as compared to random sites. Loblolly pine typically

occurs on the highest sites within a floodplain, usually on a

small, elevated knoll.

Thus, it may be that the seasonal schedule of inundation to

a large extent dictates habitat use by swamp rabbits by

limiting the availability of the more hydric habitat types,

especially during winter and early spring. Strole and

Anderson (1992) clearly demonstrated that use of browse

resources by a mammalian herbivore is directly related to

the availability of those resources. That flooding in Moro

Bottoms Natural Area restricted access to portions of

individual home ranges, or availability of resources, was

supported by the behavioral response of swamp rabbits to

inundation (Zollner 1993). During periods of prolonged

flooding, swamp rabbits with home ranges near the

adjacent, upland pine per hardwood forest moved into the

uplands until the water receded. Individuals on the western

portion of the study area restricted their movements,

remaining on patches of small, elevated ridges.

If inundation frequently imposes restrictions on the use of

resources within a floodplain, such as often happened in

Moro Bottoms Natural Area, then the quality of swamp rabbit

habitat may be as much dependent on the nature of

adjacent upland sites as the species composition and

structure of the more hydric forest associations. Moreover,

when these ecological bottlenecks occur during periods of

resource impoverishment, such as in winter and early

spring, short-term carrying capacity and long-term
94

population viability are directly linked to frequency and

duration of perennial flooding and the quality of adjacent

elevated habitat, respectively. Whitaker and Abrell (1986)

reported that elevated areas that were protected from most

flooding represented an important feature of good swamp

rabbit habitat. It appears that the landscape context of

bottomland forests may be an equally important feature of

swamp rabbit habitat, especially where minor bottoms (i.e.,

bottomland forests of relatively narrow streams and

floodplains) occur in an agriculture-dominated landscape or

matrix of upland, even-aged pine forests.

White-Tailed Deer

Natural history—The white-tailed deer has an almost

ubiquitous distribution in the coterminous United States with

a geographic range that extends into southern Canada and

south to northern South America (Smith 1991). Among forest

biomes, the density of white-tailed deer generally is directly

related to the number of forest openings. In the Southeast,

bottomland hardwood forests of the Coastal Plain produce

some of the highest quality food for white-tailed deer, which

attain densities of 25 deer per km2

. Bottomland forests

adjacent to agricultural row crops, such as soybean, can

support substantially higher densities of white-tailed deer.

Where agricultural crops add significant amounts of

nutrients to their diet, deer are much larger and local

populations can be more than twice the density of

comparable areas without row crops nearby (Smith 1991).

Although early regeneration stands offer much variety and

biomass of herbaceous and woody forage, the lowest quality

foods in the Southeast occur in homogeneous loblolly pine

and slash pine (Pinus elliottii) forests (Newsom 1984).

White-tailed deer allocate more time to feeding than any

other activity. Significant seasonal shifts in center of activity

often occur in response to local changes in food availability.

Generally, grasses and forbs dominate the diet during spring

and early summer; as herbs mature, deer switch to

succulent, new-growth leaves and twigs. During autumn,

soft and hard fruit (e.g., berries and acorns, respectively)

predominate in the diet, including fruits of beech, Smilax

spp., Crataegus spp., Vaccinium spp. Rhus spp., Vitis spp.,

Rubus spp., and Pyrus spp. Winter diets are determined

largely by availability. Dried leaves of deciduous trees,

sedges, grasses, mushrooms and other fungi, and woody

browse comprise a large proportion of the diet (Smith 1991).

Habitat distribution and density—In this study, use of oldgrowth bottomland hardwoods by deer varied seasonally

with the greatest use occurring during autumn (table 2).

Even then, densities were about one-half the average

reported for southern bottomland forests (Smith 1991).

Although it is uncertain why deer density in the old-growth

stand was less than expected, we suspect it was at least in

part related to the landscape context of Moro Bottoms

Natural Area (Castleberry and others, in press). Moro

Bottoms is a segment of a relatively narrow, riparian corridor

that dissects a landscape of intensively managed

timberland, mostly even-aged stands of loblolly pine. This

habitat represents one of the poorest quality environments

for white-tailed deer, typically supporting from one-third to

one-fifth the density of deer that can be sustained in

bottomland forests (Newsom 1984).

The pattern of seasonal use observed in our study (table 2)

is probably typical of deer inhabiting minor bottoms

(Castleberry and others, in press). White-tailed deer of the

Coastal Plain will often make short-distant movements (as

opposed to migrations elsewhere) in response to changes in

the abundance of local food resources. Because of the

importance of acorns as a high-energy food item during

autumn, deer in this study were probably attracted to the

bottoms during October 1991 to exploit a va1uable but

ephemeral resource. That deer did not concentrate in the

bottoms in November 1992 (table 2) may have been related

to early, prolonged periods of inundation. When prolonged

flooding occurs in early autumn, acorns that otherwise would

be easily accessible are either submerged or washed away.

Alternatively, acorns may not have been readily available

because 1992 was a poor year for acorn production.

Few deer used the old-growth or second-growth bottomland

hardwood stands during spring or summer (table 2). Again,

this was probably related to food availability. Although evenaged loblolly pine stands offer little in the way of palatable

forage, nearby (<1 km) young regeneration stands probably

provided a greater abundance of better quality forage than

was available in the bottomland forests. Indeed, deer use of

the bottoms was in early succession habitat of forest gaps

where one would expect to find more palatable herbaceous

and woody new-growth during this period.

Small Mammals

Species habitat distribution and abundance—According

to season, Peromyscus gossypinus comprised 50–98

percent of new captures across habitat grids (fig. 2). In 12 of

18 samples (3 habitats X 3 seasons X 2 years), >70 percent

of new captures were P. gossypinus. Its prevalence was

most apparent in old-growth habitat, especially during winter

and spring (table 4). Its abundance in second-growth habitat

was less than in old growth with new captures often less

than 50 percent of that recorded on the old-growth grid. The

cut-over site supported comparable (1991–1992) or greater

numbers (winter and spring 1992–1993) of P. gossypinus

than did second-growth habitat (Table 4).

Peromyscus gossypinus is primarily an inhabitant of moist

forest habitats, especially common within dense underbrush

along streams and throughout bottomland hardwood forest

(Sealander and Heidt 1990). Where P. gossypinus and P.

leucopus are sympatric, P. gossypinus typically diminishes in

abundance along a mesic-xeric gradient (St. Romain 1976);

it is absent from drier upland forest types (Sealander and

Heidt 1990). Peromyscus gossypinus nests in hollow

stumps, tree cavities, or beneath logs.

Old-growth forests possess many characteristics that are

absent in second-growth forest (Runkle 1991). In bottomland

forests, even older (ca. 100 year-old) second-growth stands

lack many of the features typical of their old-growth

counterparts (Robertson and others 1978). Abundant snags,

dead or dying tree limbs, and coarse woody debris, typical

of old-growth forest (Harmon and others 1986, Thomas and

others 1988), contribute critical nesting microhabitat

components and provide an array of substrates within which

a plethora of invertebrates proliferate (Bailey 1993, Savely

1939). Moreover, natural disturbances and regeneration
95

typical of old-growth gap dynamics (Runkle 1991) contribute

significantly to habitat diversity (Sherman 1978).

Variation between old-growth and second growth bottomland

hardwood forest in abundance of P. gossypinus can

probably be explained by many of the habitat differences

outlined above. However, the second-growth grid also

included some drier, upland forest habitat components.

Elevational differences between adjacent lowland habitats

were probably important during periods of inundation as the

second-growth grid rarely became flooded. Although P.

gossypinus is arboreal and apparently can move vertically in

response to heavy rainfall, many individuals may be forced

to move to higher sites during periods of prolonged flooding

(Andrzejewski 1963). Temporary immigrants may be more

susceptible to live capture as they are presumably pressed

to search for food. The lowest capture rates in second

growth occurred during spring 1993 when lower elevation

habitat was not flooded and old growth experienced its

highest number of new captures of P. gossypinus (table 4).

Conversely, water was common across lowland sites during

spring 1992, and we captured more new Peromyscus spp.

and more new Ochrotomys nuttalli than in spring 1993. But,

there was not a clear inverse relationship between new

captures on old-growth and second-growth grids during the

entire study.

In addition to differences in elevation and moisture, there

were apparent differences between old-growth and secondgrowth habitat in soil and vegetation; loblolly pine, for

example, was a significant component of the overstory

(Zollner 1993). Some of the variation we observed in P.

gossypinus habitat distribution was likely attributable to

upland habitat features that were common across the

second-growth grid. Afterall, P. gossypinus is reported to be

less abundant or absent in drier, upland woodlands where P.

leucopus is apparently more abundant (Sealander and Heidt

1990).

The recently harvested (cut-over) site was high graded

during 1989–1990 and had some habitat features that were

similar to old growth. In particular, the remaining slash was

an abundant source of coarse woody debris. Also, many

portions of the cutover were not different in habitat structure

to windthrow gaps that occurred across the old-growth site.

An obvious difference was the absence of large, old trees

and associated canopy cover and standing basal area.

Whether these similarities in habitat contributed to P.

gossypinus abundance more closely resembling old-growth

habitat than second-growth habitat is unclear. Indeed, it is

uncertain whether variation in P. gossypinus abundance

between second-growth and recently harvested sites (table

4) reflected real differences associated with habitat quality,

or as with old-growth habitat, represented an influence of

seasonal flooding.

Features of the second-growth grid probably contributed to

variation in habitat distribution of other species. In particular,

Ochrotomys nuttalli was captured more frequently than

predicted from random chance; 65 percent (30 per 46) of its

captures occurred in second-growth habitat (table 4).

Ochrotomys nuttalli, like P. gossypinus, is common in moist,

lowland forests with dense underbrush and is arboreal, often

building nests in vine thickets as high as 5 m above the

forest floor (Sealander and Heidt 1990). Both O. nuttalli and

P. gossypinus readily move vertically in bottomland forest; in

our study, they were the only species that were regularly

captured in elevated platform traps. Food items of O. nuttalli

are apparently similar, but contain less animal matter than P.

gossypinus (Sealander and Heidt 1990).

Given its reputed preference for bottomland forests, it is

unclear why we caught so few O. nuttalli. Overall, P.

gossypinus was nearly 16 times more abundant than O.

nuttalli; in old-growth habitat, the disparity in abundance

between the two species was much greater (table 4).

Perhaps the variation we recorded reflected differences in

habitat preference. Although both species occur in moist,

lowland forests, O. nuttalli also occurs in drier, upland

forests of pine and cedar (Sealander and Heidt 1990). Thus,

although both habitats may be generally suitable, each

species may find microhabitat features common to one

habitat more attractive; or, each may be behaviorally or

physiologically predisposed to successfully responding to

peculiar ecological scales.

Regular and frequent inundation, typical of the old-growth

grid, may have had a greater influence on the distribution

and abundance of O. nuttalli as compared to P. gossypinus.

Some small mammals, notably shrews (Soricidae), are not

predisposed to moving vertically in forested habitats. In

circumstances where lowland forests become flooded for

prolonged periods, terrestrial small mammals presumably

must seek higher elevation, suitable habitat as refugia.

Voles (Clethrionomys spp.) of European bottomland forests

typically moved from lowland forest into surrounding habitat

during flooding episodes (Andrzejewski 1963).

Alternatively, interspecific interactions may have contributed

to the variation in distribution of O. nuttalli. Peromyscus

gossypinus is very aggressive, whereas O. nuttalli is notably

docile (Sealander and Heidt 1990). Perhaps the abundance

and aggressive nature of P. gossypinus influenced the

occurrence of O. nuttalli on the old-growth grid. It is not

uncommon for competitive interactions to influence the

structure of rodent communities (Brown 1975, Grant 1972).

Moreover, interspecific aggression is a common mechanism

mediating competitive exclusion, indeed, “the machinery of

competition” (MacArthur 1972). This conclusion also is

supported by the more frequent occurrence of O. nuttalli

in second-growth habitat where abundance of P. gossypinus

was 30 percent of that in old growth, and less than 4 times

more abundant than O. nuttalli on the second-growth grid

(table 4).

The remaining species were captured in too few numbers to

detect response to habitat variation. There were many

species, shrews in particular, whose scarcity or absence in

our samples remains confusing. Shrews are difficult to

capture and typically are under-represented with Sherman

live traps (Kirkland 1977), but we totaled over 1,300 trap

nights of effort with pitfall traps. Further study of bottomland

forest is necessary to determine whether shrews are an

insignificant component of the mammal fauna, or whether

more innovative or intensive measures of sampling are

needed to adequately include this guild.
96

Didelphis virginiana appeared to be more abundant on the

second-growth grid with 22 of 51 captures (table 4), but we

suspect that this result could have just as easily occurred

because of unrelated factors. Didelphis virginiana prefers

riparian woodlands and typically to a lesser extent, occurs in

drier upland forest (Sealander and Heidt 1990). In this study,

the second-growth grid had elements of both lowland

deciduous woodlands and upland mixed forests. If its more

frequent capture was a response to habitat condition,

occurrence on the second-growth grid may have been a

reflection of habitat heterogeneity rather than specific

microhabitat features.

Managed Versus Unmanaged Forest

The effect of forest management on indigenous vertebrate

populations has gained prominence in recent years and is

probably one of the most pressing questions of applied

ecologists (Smith, in press). There are notable limitations

(e.g., unreplicated study design) to what general

conclusions can be drawn from direct comparisons of the

three habitats studied in our experiment. Still, examining the

results of this study in the context of a disturbance and

forest stand age gradient may provide some useful insights

regarding the impacts of logging on the mammal fauna of

bottomland forest.

In a retrospective study of managed and unmanaged

stands, McComb and Noble (1980) reported that densities of

some small mammals typical of bottomland hardwood

forests (e.g., Peromyscus leucopus) can decline following

intensive timber harvesting. However, they reported more

captures for most species in harvested stands than in

unmanaged stands. In our study, there was no consistent

disparity in abundance between the old-growth and cutover

grids. However, we did not sample the cutover site until two

growing seasons following harvest.

Studies of upland hardwood forests in the Eastern United

States have produced somewhat ambiguous and

inconclusive results. Healy and Brooks (1988) reported no

differences in small mammal community composition across

seedling, sapling, sawtimber, and mature hardwood forest

habitats. These were somewhat surprising results as

clearcutting Appalachian hardwood forests is usually

followed by a dramatic increase in small mammal

abundance (Kirkland 1977).

In northern hardwoods, Degraaf and others (1991) reported

striking differences in the abundance of some mammals

between poletimber and sawtimber stands. Overall, shrews

occurred in somewhat higher numbers in poletimber stands,

but primarily because of the response of a single species.

The remaining three shrew species had comparable

captures in both habitats. Other species, such as the

woodland jumping mouse (Napeozapus insignis), showed a

similar preference for poletimber stands. In contrast,

Peromyscus maniculatus was nearly twice as abundant in

sawtimber than poletimber stands.

According to Kirkland (1977), small mammal communities

increase in abundance following harvest, but decrease in

abundance and diversity to below preharvest levels by the

time a stand reaches the pole stage. Subsequently, both

abundance and diversity of small mammal communities tend

to increase as northern Appalachian hardwood forests

mature. This same pattern was generally observed in our

study with the fewest number of individuals and species

recorded in the second-growth stand (table 4). The oldgrowth grid typically had the greatest species richness and

abundance of mammals, whereas the recently harvested

stand was intermediate between old-growth and secondgrowth habitats (table 4).

The general pattern of small mammal distribution observed

in this study and reported by Kirkland (1977) parallels

changes that occur in understory vegetation structure in

response to disturbance. Old-growth forests show

considerable spatial heterogeneity because of the

interspersion of canopy gaps. Where the canopy has been

interrupted because of windthrow, a dense herbaceous and

woody understory develops and existing regeneration

surges into the midstory. Anthropogenic disturbance, such

as diameter-limit logging, also creates considerable spatial

heterogeneity within a forest with uniform canopy. In recent

cutovers, understory vegetation increases dramatically and

young-growth stands in many ways resemble canopy gaps

found within old-growth forests. Conversely, poletimber and

young sawtimber second-growth stands can have relatively

homogeneous horizontal and vertical structure as compared

to old-growth forests or young-growth stands, particularly

cutovers with some sort of legacy. This is especially true of

second-growth stands that have not undergone intermediate

stand management and the canopy closes in, becomes fairly

dense, and very little sunlight reaches the forest floor.

Maintaining spatial heterogeneity, especially vertical and

horizontal structure, may be the single most important

feature of habitat management of bottomland forests for

indigenous small mammal communities. Considerations of

scale of disturbance, both temporal and spatial, also may be

important (Hayward and others 1999) to sustain populations

of forest habitat specialists. This is especially true of

species, such as Peromyscus gossypinus, that apparently

require moist forest habitat. Single tree or group selection

harvests of late seral forests will likely create the understory

and midstory structure typical of gap-phase old growth

without overly exposing these stands to drying and other

detrimental consequences that arise when the entire forest

canopy is removed through clearcutting (Hayward and

others 1999).

ACKNOWLEDGMENT

This study was supported by Arkansas Forestry

Commission, Arkansas Game and Fish Commission,

Arkansas Game and Fish Foundation, Arkansas Natural

Heritage Commission through USDA Forest Service

Challenge Grant No. 19–90–045, with cooperation from the

Arkansas Nature Conservancy. K. Willis provided field

assistance and arranged logistic support. W.K. Townley

assisted with small mammal trapping. We extend a special

thanks to T. McCarthey for supervising and conducting small

mammal trapping and to J.H. McGuiness for field

coordination of all projects under the auspices of this

cooperative agreement. J. Michelle Cawthorn reviewed an

early draft of this paper and offered valuable comments.
97

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99

CHAINSAWS, CANEBRAKES, AND COTTON FIELDS: SOBER THOUGHTS

ON SILVICULTURE FOR SONGBIRDS IN BOTTOMLAND FORESTS

Paul B. Hamel, James S. Meadows, Emile S. Gardiner, and John A. Stanturf1

Abstract—Forested wetlands of the Mississippi Alluvial Valley (MAV) are the most productive of birds, including

neotropical migratory birds, of all land uses there. Forest land uses are difficult to maintain in economic competition with

annual crops. We compare perspectives of a bird biologist, a wildlife manager, a production forester, and an economic

pragmatist to the issue: How can we manage bottomland forests for products, like birds, in addition to economically

viable commodities? Our thesis assumes: (a) private lands are the major land ownership category, (b) economically

successful timber production generally is prerequisite to existence of forest on private lands, and (c) traditional

silvicultural tools can produce bird habitats. Principles for production of specific bird communities in bottomland

hardwoods remain to be articulated. We assert that the future of neotropical migratory birds in bottomlands depends

upon communication between avian biologists and silviculturists and the innovative capacity of land managers.

1 Research Wildlife Biologist, Research Forester, and Research Forester, USDA Forest Service, Southern Research Station, Stoneville, MS; and

Project Leader, USDA Forest Service, Southern Research Station, Athens, GA, respectively.

INTRODUCTION

The forested wetlands and seasonally inundated bottomland

hardwood forests of the Lower Mississippi Alluvial Valley

(MAV), growing as they do on soils deposited as erosional

products of the major portion of the North American

continent, are very productive as bird habitats. The soils

here are also productive for a number of warm-season

agricultural crops, from cotton to catfish, and forest products

including short-rotation fiber and long-rotation high-quality

wood products. Land use in the region is a competitive result

of potential for cash production, constrained by hydrological

uncertainties. For a century, public policy at the Federal,

State, and local level has emphasized control of water flow

(Barry 1997) which has produced outstanding opportunities

for agriculture, seriously reduced forestry activities, and

eliminated many wildlife species, including some song and

other birds. Still, however, MAV forests are the primary

contributors of certain birds to the nation’s avifaunal estate

(Hunter and others 1993).

In this paper, we address the question: How can we afford to

manage bottomland forests for products, like birds, in

addition to economically viable commodities? To explore this

question, we review current knowledge and practice of

silviculture for forest birds in MAV forests, we illustrate the

intensity of potential conflicts over land use with several

different management viewpoints, and we provide case

histories of consequences of past and of potential land

management actions. Our role is to highlight the difficulties

involved in attempting to produce commodities, like

neotropical migratory birds (NTMB), that have low direct

economic return, in an environment where the burgeoning

population of the nation has created a very great demand

for food and fiber. We conclude by pointing out the

importance of cooperation among people with differing

interests in land use to the future persistence of the current

avifauna. We contend that only by collaboration among the

variety of viewpoints represented among land owners, land

managers, and interested citizens can this rich environment

succeed in producing the desired economic, ecological, and

aesthetic commodities of which it is capable.

CURRENT ENVIRONMENT

For illustrative purposes, we use the lands of the MAV. The

2193 400 ha (5,417,700 ac) of the Delta, as it is called, were

formerly primarily covered by forest (Hamel and Buckner

1998, MacDonald and others 1979), on which grew truly vast

volumes of high-quality timber of a number of species. These

forests and their history have been described thoroughly

(Foti 2001, Rudis 2001, Tingle and others 2001). At the

present time, < 30 percent of the landscape is forested

(Faulkner and others 1995). The great majority of the

remaining land in the Delta is devoted to cash crop

production, primarily of cotton, soybeans, rice, corn, catfish,

wheat, and other crops. The entire Delta is separated from

the floodwaters of the Mississippi River by an extensive

levee system, which extends from near Memphis, TN, in the

north to the mouth of the Yazoo River near Vicksburg, MS,

nearly 320 airline kilometers south.

Much of the forest land is located in the batture, the area

between the levees and the Mississippi River. In this area,

flooding usually occurs on at least an annual basis. Major

remaining patches of forest on the protected side of levees

in the Delta include the Delta National Forest in Sharkey and

Issaquena Counties; Mahannah Wildlife Management Area

in Issaquena County; as well as Yazoo, Panther Swamp, and

Dahomey National Wildlife Refuges in Washington, Sharkey,

Issaquena, and Bolivar Counties. The remaining forests

primarily are confined to relatively low-lying sites, sites

formerly flooded for extensive periods each growing season.

Because of this, the full range of bottomland forest types

currently is not represented in proportion to its past

occurrence. Extent of flooding creates limits for forest

production on sites; additionally, the use of revetments and

dikes for water control limits the creation of new land and

hence the sites for some species like eastern cottonwood

(Populus deltoides). A reasonable correspondence exists
100

between the bottomland hardwood zones of Wharton and

others (1982) and the agricultural crop potential of sites

(table 1). Drainage and flood protection make possible the

cultivation of crops on relatively lower sites. Much of the

remaining forest land is too low to support tree species

typical of sites flooded only briefly each year, such as

cherrybark oak (Quercus falcata var. pagodaefolia). Thus,

the forest of the remaining landscape lies on a highly

skewed subset of the original presettlement situation, as well

as a relatively skewed subset of the forested lands before

the most recent episode of land clearing during the soybean

era subsequent to 1968. This lack of high sites restricts

opportunities for silviculture, both for timber and for

songbirds.

THE PEOPLE

Land use conflicts can be intense because individuals with a

stake in decisions about land have separate, valid,

seemingly non-overlapping views of the most appropriate

uses of the land. The different perspectives lead to different

sets of objectives in management. Until the advocates of

different perspectives understand (Covey 1989) and respect

the objectives of others, achievement of objectives of several

different perspectives is not likely.

We here offer thoughts on four separate perspectives on the

use of MAV lands—perspectives that represent a wide

range, albeit not the full range, of potential views. We

present them to stimulate the reader to identify not only with

their particular favorite but also to appreciate the

consistency of the others. We invite readers to see this

situation as one in which a greater success will be achieved

when proponents of different perspectives draw circles to

include additional ideas rather than draw lines in the sand to

separate themselves from their supposed opponents.

The perspectives we identify are those of a bird biologist,

intended to reflect a strong protectionist position; a wildlife

manager, intended to reflect an intense interest in

successful hunting of game; a production forester, intended

to reflect a focused attention on maximizing fiber production;

and an economic pragmatist, intended to reflect a sincere

concern with the bottom line of profit. To the bird biologist,

any forest land use is preferable to agricultural cropland;

those land management activities are gauged as profitable

which increase the extent of bird habitat for species

otherwise in limited supply. Often, the older the forest the

better it is perceived to be. To the wildlife manager, any land

use or practice that improves the quality of the hunting

experience is useful; substantial manipulations are often

necessary. The wildlife manager is interested in producing

habitat that supports high populations of certain desirable

species. To the production forester, maintenance of sufficient

land in forest to assure a steady supply of top-quality wood

of desired species is paramount. Foresters appreciate the

change that occurs with time in any forest stand, and are

prepared to groom the forest as it changes. To the economic

pragmatist, any land use or practice is reasonable, as long

as no other is available to produce a higher profit; this

usually implies an agricultural or development land use. In

this perspective lands that do not pay for themselves are of

questionable use.

Each of these perspectives, as a sole determinant of

objectives, leads to single-minded attachment to a particular

set of objectives that may exclude the others, i.e., produces

Table 1—Correspondence between capacity of sites to support forest and agricultural crops 

Hydrologic situation Wharton zone Forest type Agricultural crop 

Permanently inundated I: Open water None None 

 

Seasonal flooding 

 >6 months per year II Baldcypress- Catfish, rice 

 water tupelo 

 3 to 6 months/year III Overcup oak- Rice, soybeans (marginally) 

 water hickory, 

 Nuttall oak 

 1 to 2 months/year IV Mixed hardwoods: Soybeans, corn, cotton 

 water oak, 

 sweetgum, 

 green ash 

 <1 month/year V Mixed hardwoods: Cotton primarily 

 cherrybark oak, 

 sweet pecan, 

 swamp chestnut oak 

 Wet years only VI Mixed hardwoods: Cotton primarily 

 including upland 

 species 
101

conflict with them. Such conflict is unavoidable. The

important issue is how the conflict is resolved, and whether

resolution represents a loss of opportunity to achieve

objectives of other perspectives in the aggregate. Relative

costs and benefits of seeking to achieve different

combinations of objectives have not frequently been

evaluated on the broad scale of such varying perspectives.

Unless such a broad approach can be pursued, however,

the prognosis for the future of NTMBs in the MAV is grim.

These birds are representative of the apparently most

dispensable elements in the ecological and or economic

puzzle. The cost of dispensing with them is unknown.

Two useful examples of approaches to bringing different

perspectives into discussion with each other are the Black

Bear Conservation Committee (BBCC) and the Southeast

Management Working Group Partners in Flight. The

experience of these two groups that began as ad hoc

partnerships suggests that successful achievement of

objectives to maintain populations of species like bears and

migratory birds need not interfere with objectives to maintain

productive forest management in the landscape. These two

partnerships have constructively drawn a circle to include

the views of the perspectives above. The BBCC, in

particular, has usefully engaged all four of them in dialogue.

CURRENT SILVICULTURAL PRACTICE

Silviculture, the theory and practice of controlling forest

establishment, composition, structure, and growth (Spurr

1979) provides forest managers with practical methods

designed to manipulate current stand conditions in order to

achieve desirable future stand conditions. Similarly, forest

management is the process of making and executing

decisions that direct the long-term development of forests on

any particular tract of land. Ideally, both silviculture and

management can be used to manipulate the forest to

provide a particular vegetative structure at a specified time

in the future. The following principles may be obvious but are

nonetheless worthy of recognition:

1.“It ain’t management unless you do it on purpose.”

Management requires the statement of objectives,

indicated as desired future conditions or outputs.

2.Manipulation of survivorship of trees is the primary

silvicultural activity currently used, i.e., the chainsaw is

the primary management tool of silviculture; corollary to

this is that cutting trees is a necessary part of managing

forest lands.

 3.Hydrological manipulations have profoundly affected the

remaining patches of forest, such that site

characteristics today may reflect the hydrological

manipulations as much as or more than the historical

development of the site.

 4.Management options are limited by the site

characteristics, which reflect history of hydroperiod and

land use.

 5.Management must be cost effective, or alternative land

uses will take precedence.

 6.Within the context created by the previous five

principles, we can learn from old-growth stands about

the productive capacities of sites.

In a useful, nontechnical review of silvicultural systems for

ornithologists, Thompson and others (1995) identify the four

regeneration methods commonly used in North America as

selection, shelterwood, seed tree, and clearcutting. They

compare the use of these methods in terms of the age-class

distribution they produce in even-aged (shelterwood, seed

tree, clearcutting) or uneven-aged silvicultural systems

(selection). They identify silvicultural practices as

regeneration practices or intermediate treatments.

Regeneration practices include the method of establishing

the new stand (natural or artificial) and the site preparation

activities that may be employed to do so. Intermediate

treatments include release cuttings of saplings, thinnings of

older stands, and salvage and sanitation cuttings to remove

dead or dying trees. Additional aspects of forest

management operations, such as road building and

maintenance, fire control and management, and use of

pesticides and herbicides, as well as fuel wood harvest can

have effects on stand structure and composition, and hence

on the bird community that inhabits the stands. A more

technical review of silvicultural systems for bottomland

hardwoods is presented by Meadows and Stanturf (1997).

In MAV habitats where extensive conversion of forest to

croplands has occurred, reforestation involving natural or

artificial establishment of stands of trees on former

agricultural lands is an important forest management

technique. Often, stand establishment is difficult.

Intercropping cottonwoods and oaks is a possible

silvicultural manipulation to address the situation in which

land use changes have reduced the rate of development of

sites necessary for natural regeneration of cottonwood

(Schweitzer and others 1997, Twedt and Portwood 1997).

GENERAL PRINCIPLES FOR MANAGEMENT

OF NEOTROPICAL MIGRATORY BIRDS

The bird communities of the bottomland hardwood forests

are quite diverse (Smith and others 1996), and include

numerous species in both the spring and summer breeding

season and in the winter nonbreeding season (Hamel 1992).

Many of these birds are NTMB species whose declining

populations make them of particular concern at the present

time (Hunter and others 1993, Smith and others 1996).

Our thesis is that profitable silviculture is the primary hope

for NTMB in the MAV. We believe this because most of the

birds of interest in the MAV are forest birds, for which

maintenance of forest cover in the landscape is critical.

Competition among land uses, i.e., agriculture and forestry,

is intense, and extensive set-asides of forest land, either

through purchase or regulation, are unlikely to provide

sufficient tracts to assure the persistence of all bird species.

Furthermore, manipulation of forests will be necessary to

assure the persistence of early successional habitats and

the birds that require them.

Our thesis depends upon three premises:

1.private lands are the major land ownership category in

the MAV,

2.economically successful timber production is generally

a prerequisite for the existence of forest on private

lands, and
102

3.traditional tools of silviculture can effectively be used to

produce habitats for NTMB.

From these premises, we argue that the future of NTMB in

bottomlands depends upon:

1.improved inventory of bird communities,

2.communication between avian biologists and

silviculturists, and

 3.the innovative capacity of land managers.

All of the management activities aimed at producing suitable

habitat for birds assume that:

1.satisfactory bird habitat can be described in primarily

structural terms;

2.production of woody vegetation cover is not only

necessary but sufficient for production of insect foods

as well as fruits of forest trees, and that this cover is

sufficient to accord appropriate cover for roosting and

breeding purposes of the birds;

3.corollary to the first two, if woody cover is produced,

insect populations will follow, and they will in turn

support bird populations, i.e. secondary consumers;

4.bird occurrence is synonymous with successful bird

reproduction and survival.

These assumptions appear reasonable. However, they are

not validated, particularly in bottomland systems (Wigley

and Roberts 1994, 1997). They also oversimplify a complex

reality, e.g., Hamel 1992, Sherry and Holmes 1995,

Thompson and others 1995. They do form a starting place

for adaptive management, in which as actions are taken,

managers are enabled to learn from the consequences of

their actions and improve the desirability of the

consequences as time goes on. The work of Twedt and

others (1999), Mueller and others (1999), and Loesch and

others (1999) is illustrative of the process by which

assumptions such as those above serve to structure

management decision-making and lead to useful

improvements. The process is similar to that advocated by

Starfield (1997).

Our major theory of habitat utilization assumes that

vegetation structure, rather than its species composition, is

the driving force behind bird species occurrence. We

assume that where appropriate structure occurs, the birds

will be present. Especially do we see this as a question of

choice on the part of the birds, where by some mechanism

dispersing individuals locate and choose to settle in habitats

of appropriate structure. We focus on structure because

extensive theory exists that relates bird occurrence to

vegetation structure, based upon the work of James (1971),

Shugart (1984), DeGraaf (1987), and well illustrated by the

works of Verner and others (1986), and Morrison and others

(1992). Additional extensive theory assumes that the

conditions of land use surrounding a particular patch, that is,

the landscape position of the tract of appropriate vegetation,

is a key feature limiting the occurrence of birds (Robbins and

others 1989). A major, little-tested assumption embedded in

the focus on structure is its linkage to appropriate foods and

to appropriate sites for nesting, roosting, and escape cover.

Because we are not sure of the specific responses of

individual bird species to particular manipulations,

management activities have inherent risks of failure.

Individual managers, as reasonable humans, exhibit a range

of tolerance toward risk-taking in their management

decisionmaking. Pukkala and Kangas (1996) note that

measuring attitude toward risk is probably more difficult than

measuring risk itself. They state, “In a situation involving risk,

the optimum plan may be different for a risk-avoiding, a riskneutral, and a risk-seeking decision-maker.” Uncertainties of

outcomes in land management thus may be caused by

deficiencies in the information base on which decisions are

taken as well as on the decision style of the manager.

Specific considerations for the management of individual

bird species are not likely to be developed soon (Martin and

Finch 1995). Earlier workers (Dickson and others 1995,

Hamel 1992, Pashley and Barrow 1993, Wigley and Roberts

1994,) have provided information on the occurrence of

species in stands of different ages. We lack a long-term data

set indicating how individual species respond to particular

treatments applied to bottomland hardwood stands and

followed over time. Wigley and Roberts (1997) and Hamel

(1992) provide hypotheses of landscape-scale interactions

of songbirds and forest management, but these too have not

been subjected to sufficient experimental testing.

Several principles seem appropriate as guidelines for

management of NTMBs in bottomland hardwood forests,

however, they need to be tested (Dickson and others 1995,

Wigley and Roberts 1997).

1.Bigger patches of forest are always better for forest

birds than smaller ones. Pashley and Barrow (1993)

recommend the optimal condition at the local scale to

be a very large, forested tract managed under a natural

disturbance regime. Large patches of forest buffer the

effects of increased brood parasitism, predation, and

other demographic consequences attendant on small

populations inhabiting small tracts. The data of Robbins

and others (1989) provide a strong rationale for

maintenance of large tracts.

2.Reforestation will be a most important part of the future

potential for birds in bottomland hardwoods. Particularly

in the MAV where only a modest proportion of the

landscape is forested, primarily in small, scattered

patches, only specific reforestation activities will provide

for the establishment of forests on lands far from seed

sources (Mueller and others 1999).

3.We can learn from old-growth stands about the future

composition and structure of stands left without

intervention. The works by Devall and others (2001) and

Smith and others (2001) as well as Hamel (1989)

provide information on the use of old-growth stands as

controls for comparison with second-growth bottomland

forests.

 4.Fragmentation of habitats has profound effects that local

managers may be helpless to control, mitigate, or

otherwise affect. Robinson and others (1995) provide a
103

chilling review of the effects of forces operating at the

landscape scale on bird community dynamics within

stands at the local scale. Readers uncertain of the

consequences to local populations of such landscapescale factors would do well to read that work.

Several recent papers provide some guidance to land

managers concerning silviculture for songbirds in

bottomland hardwoods (Dickson and others 1995; Hamel

1992; Pashley and Barrow 1993; Wigley and Roberts 1994,

1997). Hamel (1992) related individual species to particular

layers of vegetation in the forest, assuming that

manipulations which eliminate or favor particular layers of

forest will similarly destroy or improve habitats for the

species that use those layers. Pashley and Barrow (1993)

provide a set of recommendations that involves local level

management as well as regional scale management. Wigley

and Roberts (1994) review results of 17 studies that indicate

associations or dissociations between individual bird species

and particular management treatments. Most of these

studies involve descriptions of bird communities in stands of

different ages, although some reflect experimental work. Few

of the studies were long-term examinations of community

changes in response to application of treatments. Dickson

and others (1995) identify species that have been shown to

increase or to decrease in response to particular treatments

in bottomland hardwood forests. They note that little specific

information on such effects has been developed in

bottomland hardwood ecosystems. They recommend

maintaining current forests and preventing further

conversion to other uses, as well as reclamation of some

previously converted land to forest. They suggest protection

of existing old growth, existing corridors between existing

stands, and the development of more old-growth stands.

Wigley and Roberts (1997) review the modest literature on

landscape correlates of species occurrence and abundance

in bottomlands, noting that much of the theory is intuitively

sound, but that it lacks empirical and experimental testing.

Among issues for which scant information currently exists

are the role of fire and long-term annual variation in

population levels of species. Unlike other southern

ecosystems, very little is known about the utility of fire in

wetlands as a management or ecological tool. Likewise, few

long-term data sets are available to evaluate the variability of

bird use of particular stands.

Management for NTMBs in bottomland hardwood forests is

only part of the management picture, even of birds, for more

than many other forests. Southern forests, particularly

bottomland hardwood forests, are winter destinations for

migrants from the north as well as summer destinations for

migrants from the south, and stopover habitat for migrants in

transit both spring and fall. Concentration on management of

breeding habitats only will overlook the importance of these

habitats in other seasons.

CASE STUDIES: SILVICULTURE FOR

SEVERAL RARE BIRDS IN THE MAV

Two bird species, one a resident and the other a NTMB,

have been effectively lost from the MAV fauna. One of them

is probably extinct, the other possibly so; each was a regular,

if not common, member of the MAV fauna. They provide an

opportunity to review the possible silvicultural treatments

that might have been employed to keep them from becoming

so rare. A third species provides an example of an

unintended benefit of silviculture designed strictly to produce

fiber.

Ivory-billed woodpecker—In bottomland hardwoods, ivorybilled woodpeckers (Campephilus principalis) utilized stands

of big, old trees. The apparent habitat requirements were for

extensive stands with dying or senescent trees. An approach

to producing this habitat silviculturally is the use of thinnings

on moderate-to-good sites to accelerate the production of

large trees with substantial crowns, eventually creating the

conditions in which dead and dying limbs can supply the

insect foods for the birds. Such senescent trees are not

usually retained in stands managed for economic objectives.

Unfortunately, needed information on the possible density of

birds and their energetic requirements is unavailable,

hindering the process of modeling how to do produces their

habitat. Our point, nevertheless, is that active management

possibly could produce the desired conditions faster than

could passive.

Bachman’s warbler—The Bachman’s warbler (Vermivora

bachmanii) was a species of openings in the canopy and

areas with dense shrub cover interspersed with larger trees.

They have long been associated with canebrakes

(Arundinaria gigantea), and may have been obligate users of

them (Remsen 1986). In the MAV, canebrakes likely

occurred most prominently on relatively high ground, land

now devoted to production of cotton. Serious gaps exist in

our knowledge of the ecophysiology of cane: Does the

species require full sunlight, partial sunlight, or full shade?

Can canebrakes be developed on relatively wetter sites?

Assuming that cane requires relatively open conditions,

thinning a stand heavily would probably produce the light

conditions in which woody understory vegetation, such as

cane, could thrive in a forested environment, thereby

producing habitat for the species (Platt and Brantley 1997).

Such manipulative intervention may be a more direct method

for creating habitat for the birds than passively waiting for a

natural disturbance such as an ice storm, tornado, or

hurricane. Unfortunately, the extreme rarity of the birds has

prevented the implementation of such an experiment.

Warbling vireo—A third case involves another species rare

in the MAV, the warbling vireo (Vireo gilvus). Its habitat is

relatively long, narrow tracts of willows or other early

successional trees growing along a watercourse or a slough.

In such conditions, the species is exposed to potentially

severe pressure from brown-headed cowbirds (Molothrus

ater), birds that lay their eggs in other birds’ nests.

Reforestation treatments involving cottonwood plantations,

with and without intercropping with other species, have

produced habitats in which warbling vireos do very well.2

RESEARCH AND MANAGEMENT NEEDS

Virtually all authors commenting on land management for

birds in bottomland hardwood forests note that information

2

 Personal observation. 1997. Paul Hamel, Research Wildlife

Biologist, USDA Forest Service, Southern Research Station, P.O.

Box 227, Stoneville, MS 38776.
104

on the basic biology and silviculture for birds is scanty, that

landscape effects may be as or more profoundly influential

on populations as stand-level vegetation structure, and that

currently existing monitoring data, comprised mostly of

relative abundance information, do not give as detailed a

picture as will data on survivorship and reproductive

success. These latter data are, however, expensive to

gather; they may be virtually impossible to gather outside

the research context for some forest canopy dwelling

species like the cerulean warbler (Dendroica cerulea)

(Hamel 2000, Mueller and others 1999).

CONCLUSIONS

Conflicts between different interests in the use of the land

can and perhaps may produce serious potential problems in

the future. We believe that such conflicts can best be

avoided by active dialogue between perspectives. When the

debate relates to objectives of management, rather than to a

decision to manage or not to manage, each of the outlined

perspectives will be able to contribute to a vision of a

landscape containing a rich mix of chainsaws, canebrakes,

and cotton fields. Where bird biologists and wildlife

managers do not attempt to incorporate their objectives into

production forestry, many opportunities will be missed. When

production foresters fail to incorporate bird management

objectives and wildlife habitat goals into their silvicultural

practice, opportunities for improved silviculture will be

foregone. In such cases, all dependents on the bottomland

forest landscape may become losers, especially the NTMBs

and other species that depend on forest habitats.

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Thompson, F.R., III; Probst, J.R.; Raphael, M.G. 1995. Impacts of

silviculture: overview and management recommendations. In:

Martin, T.E.; Finch, D.M., eds. Ecology and management of

neotropical migratory birds: a synthesis and review of critical

issues. New York: Oxford University Press: 201–219.

Tingle, J.L.; Klimas, C.V.; Foti, T.L. 2001. Application of General

Land Office survey notes to bottomland hardwood ecosystem

management and restoration in the lower Mississippi Valley—an

example from Desha County, Arkansas. In: Hamel, Paul; Foti,

Thomas, eds. Bottomland hardwoods of the Mississippi Alluvial

Valley: characteristics and management of natural function,

structure, and composition; 1995 October 28; Fayetteville, AR.

Gen. Tech. Rep. SRS–42. Asheville, NC: U.S. Department of

Agriculture, Forest Service, Southern Research Station: 16–27.

Twedt, D.J.; Hamel, P.B.; Cooper, R.J.; Woodrey, M.S. 1999. An

evaluation strategy for conservation goals of the Mississippi

Alluvial Valley migratory bird initiative. In: Bonney, R.; Pashley,

D.N.; Cooper, R.; Niles, L., eds. Strategies for bird conservation:

the partners in flight planning process. Proceedings of the

partners in flight international workshop; 1995 October 1–5; Cape

May, NJ. Ithaca, NY: Cornell Laboratory of Ornithology. [Available

on the Web: http://www.ornith.cornell.edu/pifcapemay/twedt.htm].

Twedt, D.J.; Portwood, J. 1997. Bottomland reforestation for

neotropical migratory birds: are we missing the forest for the

trees? Wildlife Society Bulletin. 25(3): 647–652.

Verner, J.; Morrison, M.L.; Ralph, C.J., eds. 1986. Wildlife 2000:

modeling habitat relationships of terrestrial vertebrates. Madison,

WI: University of Wisconsin Press. 470 p.

Wharton, C.H.; Kitchens, W.M.; Pendleton, E.C.; Sipe, T.W. 1982.

The ecology of bottomland hardwood swamps of the Southeast: a

community profile. FWS/OBS–81/37. Washington, DC: U.S. Fish

and Wildlife Service, Biological Services Program. 133 p.

Wigley, T.B.; Roberts, T.H. 1994. A review of wildlife changes in

southern bottomland hardwoods due to forest management

practices. Wetlands. 14(1): 41–48.

Wigley, T.B.; Roberts, T.H. 1997. Landscape-level effects of forest

management on faunal diversity in bottomland hardwoods. Forest

Ecology and Management. 90: 141–154.
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A LONG-TERM VIEW OF OLD-GROWTH DECIDUOUS FORESTS

James T. Tanner and Paul B. Hamel1 2

Abstract—Lowland old-growth forests in the Southeastern United States and Eastern Europe (Poland)

survived because of accidents of history, topography, and ownership until they came under governmental

protection. Such old-growth stands are the similar the world over; they have trees of many ages, patchy

distribution of habitats, and a variety of microhabitats, all of which result from the death and fall of trees.

Species diversity is high for both plants and animals. Old-growth forests constitute important habitat for

many carnivores and for some endangered species; they are places for ecological research and for recreation and enjoyment. Science has shown that management, as well as protection, is necessary and can

improve conditions.

1

 Tanner, now deceased, Department of Zoology, University of Tennessee, Knoxville, TN. Please address correspondence to Paul B. Hamel,

USDA Forest Service, Southern Research Station, Center for Bottomland Hardwoods Research, P. O. Box 227, Stoneville, MS 38776. (Email:

phamel@fs.fed.us).

2

 Editors note: This contribution originally was prepared for a 1989 Natural Areas Conference symposium on old-growth deciduous forests.

Dr. Tanner’s untimely death in early 1991 prevented publication of the manuscript with others in that symposium (Natural Areas Journal in

volume 11, 1991, and volume 12, 1992). It is presented here in abridged form as a tribute to Dr. Tanner whose work on old-growth bottomland

hardwoods in the Mississippi Alluvial Valley stands as a tribute to the persistence of the man and the value of biodiversity in the Mississippi

Alluvial Valley.

INTRODUCTION

These remarks primarily concern old-growth deciduous

forests in the lowlands of two areas: the Southeastern

United States and Poland. My own experience in old growth

has been in bottomland forests of the Southeastern States

(Tanner 1942, 1986).

LOCATIONS OF OLD-GROWTH FORESTS

Where are old-growth deciduous forests today, particularly in

the Southeastern United States, and why are they there?

The answer lies partly in the history of the logging industry,

the events of which did not occur uniformly over all areas.

For example, logging interests grew faster in Georgia than in

South Carolina. In the former, no old-growth bottomland

forests survived, but in the latter two areas are now

preserved, largely as a result of the action of conservationists: one in the Congaree Swamp National Monument, of

Richland County, and the other in Four Holes Swamp, of

Berkeley and Dorchester Counties. Four Holes Swamp is

now the Francis Beidler Forest. In the Mississippi Delta,

logging began in Missouri and progressed southward. Later,

it started in southern Louisiana and moved northward. The

two movements met in northern Louisiana at the Singer

Tract, Madison Parish, then the largest tract of remaining

bottomland forest (Tanner 1942). This occurred unfortunately

at the beginning of World War II, when hardwood timber was

in high demand and funds for conservation were reduced.

The Singer Tract was logged, but some similar old-growth

bottomland forest was preserved several kilometers to the

east in the Delta National Forest in Mississippi; Devall and

Ramp (1992) describe three Research Natural Areas there.

Old-growth forests persisted in other areas because of stand

inaccessibility and the difficulties of logging. For example,

old-growth forest remains in the remote Great Smoky

Mountains. In both the Okefenokee Swamp and the

Everglades, hardwood or cypress stand as islands in vast

expanses of marshland that have kept loggers at bay. These

two areas now are preserved as a National Wildlife Refuge

and a National Park, respectively. Noss (1991) described a

somewhat similar situation where a hardwood forest in a

Florida hammock persisted because it was isolated in a pine

forest. In the Southeast larger old-growth forests remain

because of accidents of history and topography that delayed

and eventually prevented logging. Many small stands, albeit

not forests, have survived because family-owned farms have

brought protection, notably in the upper Mississippi valley

(Parker 1989).

In Poland, however, as Tomia ojc (1991) describes, an oldgrowth forest survives today because it once was a hunting

preserve for royalty. The same is true of Denmark’s forests;

and in Japan I visited old forests that remained only because

they were Shinto shrines.

CHARACTERISTICS OF OLD-GROWTH

Old-growth forests have survived in two ways. One is by

history of not having been changed by human action nor

destroyed by natural accident. This implies that an oldgrowth forest is the terminal stage of a plant succession

(Barnes 1989). Because almost no forest has been

unaffected by human activity (Tomialojc 1991), we need a

definition based on observable forest characteristics of the

forest.

Participants at the 1989 symposium, “Characteristics,

management, and restoration of old-growth temperate

deciduous forests in the Southern United States,” 16th

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Natural Areas Conference, 18 October 1989, Knoxville, TN,

and the authors of notable publications (Barnes 1989,

Parker 1989) generally agree on the characteristics of oldgrowth forests. They contain trees of all ages, from saplings

to large individuals. These trees form at least a two-layered

canopy. Tree distribution is patchy; and there are openings

where trees have fallen. Standing-dead and dead-topped

trees are present, and on the ground are large and small

logs and exposed root masses. Details of these

characteristics as observed in the Polish Bia owieza Forest

are described by Tomia ojc (1991).

Old-growth forest characteristics result from the death of

individual trees and from small-scale disturbance. Tree death

produces the standing dead trees, fallen logs, upturned root

masses, and small canopy gaps. Small-scale disturbance

events (a very relative term) include windfalls or blow-downs,

mortality from insects and disease, flooding, and fire

(Dickson 1991, Runkle 1991). All such natural processes

produce patchiness and the microhabitats so important to

species inhabiting old-growth forests.

A general characteristic of old-growth forests (Dickson 1991,

Tomia ojc 1991) is that they contain a high diversity of

species, both plant and animal, but often with a low number

of individuals of each species. Much more has been written

about the diversity of animals than of plants. Important to

animals is the typical horizontal patchiness resulting from a

mixture of habitats, each with a relatively small area. Noss

(1991) discusses in detail the relation between patchiness

and the well-known “edge effect,” where adjacent habitats

may provide different animal necessities. Noss (1991) also

points out that patchiness can produce a variety of

microclimates within a small area.

Several kinds of microhabitats are more abundant in oldgrowth than in young forests, e.g., hollow, standing snags

and prostrate logs, broken and tangled limbs of fallen trees,

and upturned roots of fallen trees. Animal groups that use

such microhabitats are woodpeckers, other hole-nesting

birds, flying squirrels (Glaucomys Thomas sp.), bats, and

carnivores that need dens for sleeping or reproduction.

Especially important to woodpeckers are dead and dying

trees that provide habitat for wood-boring insects. These are

all examples of how tree death is such a significant process

in old-growth. Details of these relations are reinforced by

Dickson (1991), Hamel and Ford,3

 Pelton (personal

communication. 1989. M.R. Pelton. Professor Emeritus. Dept.

of Forestry, Wildlife & Fisheries, University of Tennessee,

P.O. Box 1071, Knoxville, TN 37901–1071), and Tomialojc

(1991); other examples are given by Carey (1989).

Authors who remark on the abundance of carnivores in oldgrowth forests are Dickson (1991), Hamel and Ford 1989

(see footnote 3), and Tomia ojc (1991). Higher abundance

probably results from a combination of the microhabitats that

provide dens and the greater diversity of animal species that

may constitute prey.

Old-growth forests have a greater supply of some foods than

young forests. In deciduous forests large oaks (Quercus L.

sp.), hickories (Carya Nuttall sp.), and other mast-producing

trees are heavier producers than younger trees; and in an

evergreen forests the old conifers produce more seed than

younger ones (Carey 1989).

Some outstanding exceptions exist to the proposition that

old-growth forests are characterized by a diversity of species

and patchiness. For example, pine forests (Pinus L. sp.) of

the Southeastern United States (Dickson 1991) and the pine

and other coniferous forests of the Rocky Mountain region

(Moir and Dieterich 1988) present an almost monotonous

scene because of the few tree species, and the often

unbroken extent of forest. Animal diversity also is low. In

some respects, however, such forests of old trees are the

best producers of seed, which is food for several animal

species. Their dying and dead trees provide food for

woodpeckers and nesting or denning places for several

kinds of birds and mammals. Indeed, in longleaf pine (Pinus

palustris Miller)-wiregrass (Aristida stricta Michaux)

communities regularly disturbed by fire, the diversity of

herbaceous plants and of fauna dependent on burrows of

gopher tortoises [Gopherus polyphemus (Daudin)] is

especially high (Wharton 1978).

In both the Southeastern and Rocky Mountain coniferous

forests, fire has been vital in establishing and maintaining

evergreen forests. This raises an interesting question: Are

these coniferous stands true “old-growth,” or are they

patches created by disturbance within a larger forest? Any

answer will depend on definitions and interpretations of

scale, but I [Dr. Tanner] believe that such forests should be

considered old-growth because they provide important

habitat for some animal and plant species.

PRESERVATION OF OLD-GROWTH

A compelling reason for preserving old-growth forests is to

prevent the extinction of endangered species. In North

America, examples of rare species that lived in mature

forests are the ivory-billed woodpecker [Campephilus

principalis (Linnaeus), which now may be extinct], redcockaded woodpecker [Picoides borealis (Vieillot); Dickson

1991], red wolf (Canis niger Bartram; now extinct in its

original range), Florida cougar (Felis concolor Linnaeus),

and northern spotted owl [Strix occidentalis (Xantus)]. Rare

species surviving in the primeval Bia owieza forest of Poland

are listed by Tomia ojc (1991). However, there is danger in

discussing forest preservation only in terms of endangered

species and not the entire habitat. Our objective should be

to preserve the whole forest, which in its diversity is the

habitat of many species, including some that may be rare.

Some old-growth stands are now being preserved in the

Research Natural Areas (RNA’s) program of the USDA

Forest Service, described by Devall and Ramp (1992), who

explain the objectives of the program and describe three

established areas in Mississippi. Greene (1988) describes

this program as it operates in Washington and Oregon.

Within RNA’s, old-growth forests are the focus for ecological

research. We know that woodland species evolved in mature

forests long before humans entered their habitat. We need 3

 Hamel, P.B.; Ford, Robert P. 1989. Unpublished report on file with:

Research Wildlife Biologist. USDA Forest Service, P.O. Box 227,

Stoneville, MS 38776.

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examples of the original habitat if we are to understand the

evolution and ecology of the native species.

Tomia ojc (1991) lists a number of research projects

conducted in the Bia owieza Forest. In one such study,

Walankiewicz (1991) found that the conclusions about

nesting in highly modified forest habitats, including the

addition of nesting boxes, are not supported by results of

studies in the old-growth forest of Poland. There are

differences between the two habitats other than the nature

and number of nesting cavities.

Moore and Swank (personal communication. 1989. Wayne T.

Swank. Scientist Emeritus. Coweeta Hydrologic Laboratory,

3160 Coweeta Lab Rd., Otto, NC 28763) report on the

movement of plant nutrients through precipitation, soil,

biomass, and streams in old-growth forests of the Great

Smoky Mountains. Their work is highly relevant to our

understanding old-growth hardwood forest ecology. The

insight from their work may have its greatest application in

understanding differences between the nutrient dynamics of

temperate forests and those of less-studied tropical rain

forests such as are found in the Amazon Basin. We do not

know enough to understand the ecology of rain forests and

not nearly enough to plan intelligently for the tremendous

human changes occurring in tropical regions.

Although one definition of old growth is “climax forest,” which

implies a steady state, Tomia ojc (1991) has observed

changes in the Bia owieza Forest and Barnes (1989) in

mature forests of the Great Lakes region of the United

States. Possible and widely different causes of such

changes are (1) a protracted plant succession, (2) effects of

browsing mammals or of insects, (3) climatic change, and

(4) air pollution (including acid rain). Each possible cause is

both a very interesting ecological problem and a process

significant to humankind. We submit that old-growth forests

are needed as places for studying vital problems.

A final reason for preservation of old-growth forests, and to

some the most important, is their aesthetic beauty. The

inherent worth of them is difficult to put into words, but its

reality is proven by the number of visitors to the Bia owieza

Forest (Tomia ojc 1991), to trails of the Great Smoky

Mountains, and to the Congaree Swamp in South Carolina

and Mahogany Hammock in the Everglades National Park.

MANAGEMENT OF OLD-GROWTH FORESTS

The two most often discussed subjects concerning oldgrowth forests are their characteristics and their

management. Management goals and practices are

discussed by Devall and Ramp (1992), Noss (1991), Runkle

(1991), Tomia ojc (1991), and Wellbaum and Doyle

(personal communication. 1989. Wellbaum, E.M. Forester.

Tennessee Valley Authority. Land Between the Lakes,

Golden Pond, KY 42211-9001). Earlier discussions were

published by Thomas and others (1988), Barnes (1989), and

Parker (1989). At one extreme is the hands-off policy,

holding that old-growth forests should be preserved and not

managed. This approach has proven to be impractical;

experience has shown that such forests benefit from

procedures such as selective cutting, control of non-native

species, and the re-introduction of extirpated species. To

accomplish the goal that old-growth forests should be used

for research and education requires management, as

described for the Polish forest by Tomia ojc (1991). For

years the U.S. Department of Interior’s National Park

Service (NPS) has been charged with conflicting

responsibilities: to preserve and protect natural areas while,

at the same time, making them open to the public. Almost

every management decision the NPS makes is a

compromise.

A most troubling problem concerning conservation of oldgrowth has to do with size. Old-growth forests constitute a

variety of habitats resulting from random storms, floods, and

other disturbances. To realize the ecological benefits of such

incidental events, large areas are needed. Large areas

reduce the effects on habitat wrought by boundaries with

cut-over or cultivated lands, mitigating the encroachment of

invasive plant species. Also, some animals, especially

carnivores, need large home ranges or territories.

Unfortunately, many, if not most, old-growth forests in the

United States and similarly developed regions are only

remnants, too small to foster successful conservation. This

has led several ecologists to apply principles of island

biogeography (MacArthur and Wilson 1967) to the planning

and management of forest preserves (Frankel and Soulé

1981, Harris 1984).

Finally, another question remains: Can management

produce the many characteristics by which we recognize an

old-growth forest, thereby effectively reconstructing an oldgrowth ecosystem? During the planning process we must

know what we are trying to restore. Preservation of existing

old-growth stands will be necessary to provide the model.

Papers (from the 1989 Symposium; Smith and Hamel 1991)

that address the question of reconstruction include that by

Runkle (1991) and the unpublished remarks of Wellbaum

and Doyle (personal communication. 1989. Wellbaum, E.M.

Forester. Tennessee Valley Authority. Land Between the

Lakes, Golden Pond, KY 42211-9001). On the Tensas River

National Wildlife Refuge, which is the old Singer Tract in

Louisiana, managers have begun to restore some areas to

at least resemble an old stand of bottomland timber.

Whether such efforts succeed remains to be seen.

ACKNOWLEDGMENTS

Dr. Tanner’s final words are prophetic; they presage the

current work by a dozen years, and the current symposium

by 6 years. His contributions to our understanding of the

ecology of old-growth stands, particularly in bottomland

hardwoods, will not diminish with time. His junior author

thanks Margaret Devall and Wayne Swank for their

thoughtful reviews.

LITERATURE CITED

Barnes, B.V. 1989. Old-growth forests of the northern Lake States:

a landscape ecosystem perspective. Natural Areas Journal.

9: 45–57.

Carey, A.B. 1989. Wildlife associated with old-growth forests in the

Pacific Northwest. Natural Areas Journal. 9: 151–162.

Devall, M.S.; Ramp, P.F. 1992. Forest Service Research Natural

Areas and protection of old growth in the South. Natural Areas

Journal. 12(2): 75–85.

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Dickson, J.G. 1991. Birds and mammals of pre-colonial southern

old-growth forests. Natural Areas Journal. 11(1): 26–33.

Frankel, O.H.; Soulé, M.E. 1981. Conservation and evolution.

Cambridge: Cambridge University Press. 327 p.

Greene, S. 1988. Research natural areas and protecting old-growth

forests on federal lands in Western Oregon and Washington.

Natural Areas Journal. 8: 25–30.

Harris, L.D. 1984. The fragmented forest: island biogeography and

the preservation of biotic diversity. Chicago: University of Chicago

Press. 211 p.

MacArthur, R.H.; Wilson, E.O. 1967. The theory of island

biogeography. Princeton, NJ: Princeton University Press.

Moir, W.H.; Dieterich, J.H. 1988. Old-growth ponderosa pine from

succession in pine-bunchgrass forests in Arizona and New

Mexico. Natural Areas Journal. 8: 17–24.

Noss, R.F. 1991. Effects of edge and internal patchiness on avian

habitat use in an old-growth Florida hammock. Natural Areas

Journal. 11(1): 34–47.

Parker, G.R. 1989. Old-growth forests of the central hardwood

region. Natural Areas Journal. 9: 5–11.

Runkle, J.R. 1991. Gap dynamics of old-growth eastern forests:

Management implications. Natural Areas Journal. 11(1): 19–25.

Smith, W.P.; Hamel, P.B. 1991. Old-growth temperate deciduous

forests: Legacy or legend. Natural Areas Journal. 11(1): 4–6.

Tanner, J.T. 1942. The Ivory-billed Woodpecker. Research Rep. 1.

New York: National Audubon Society. 123 p.

Tanner, J.T. 1986. Distribution of tree species in Louisiana

bottomland forests. Castanea. 51: 168–174.

Thomas, J.W.; Ruggiero, L.F.; Mannan, R.W. [and others]. 1988.

Management and conservation of old-growth forests in the United

States. Wildlife Society Bull. 16: 252–262.

Tomia ojc, L. 1991. Characteristics of old growth in the Bia owieza

Forest, Poland. Natural Areas Journal. 11(1): 7–18.

Walankiewicz, W. 1991. Do secondary cavity-nesting birds suffer

more from competition for cavities or from predation in a primeval

deciduous forest? Natural Areas Journal. 11(4): 203–210.

Wharton, C. H. 1978. The natural environments of Georgia. Atlanta:

Georgia Dept. of Natural Resources. 227 p.

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Malcolm K. Cleaveland

Tree-Ring Laboratory

Department of Geosciences

Division of Geography

University of Arkansas-Fayetteville

Fayetteville, AR 72701

Margaret S. Devall

USDA Forest Service

Southern Hardwoods Laboratory

P. O. Box 227

Stoneville, MS 38776

Tom Foti

Arkansas Natural Heritage Commission

Suite 1500, Tower Building

323 Center St.

Little Rock, AR 72201

Paul B. Hamel

USDA Forest Service

Center for Bottomland Hardwoods Research

P. O. Box 227, 432 Stoneville Rd.

Stoneville, MS 38776 USA

Victor A. Rudis

USDA Forest Service

Forestry Sciences Laboratory

P. O. Box 928

Starkville, MS 39760-0928

Winston P. Smith

Pacific Northwest Research Station

Forestry Sciences Laboratory

2770 Sherwood Lane, Suite 2A

Juneau, AK 99801-8545

List of Corresponding Authors
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Hamel, Paul B.; Foti, Thomas L., tech. eds. 2001. Bottomland hardwoods of the Mississippi

Alluvial Valley: Characteristics and management of natural function, structure, and

composition. 1995 October 28. Fayetteville, AR. Gen. Tech. Rep. SRS–42. Asheville, NC:

U.S. Department of Agriculture, Forest Service, Southern Research Station. 109 p.

A symposium entitled “Bottomland hardwoods of the Mississippi Alluvial Valley: characteristics

and management of natural function, structure, and composition” convened on October 28,

1995, as part of the Natural Areas Conference, October 25–28, 1995, in Fayetteville, AR. The

symposium’s goal was to provide information that managers need to begin restoring the

composition, structure, and function of forest ecosystems in the Mississippi Alluvial Valley.

Included in the proceedings from that symposium are 8 of 13 presentations. These peerreviewed contributions address historical conditions of forests in the Mississippi Alluvial Valley

(two papers), historical changes that are reflected in today’s forests (one paper), the effect of

historic and prehistoric rainfall patterns (one paper), forest fauna in the region (two papers),

the effect of herbivory on forest vegetation (one paper), and management of bottomland

hardwood forests for multiple outputs (one paper). A ninth paper, concerning characteristics of

old-growth forests, is a posthumous submission authored by Dr. James T. Tanner; and the tenth

paper was published in another venue. The intended audience of these proceedings includes

managers of private, State, and Federal lands, as well as land management planners from a

range of jurisdictions.

Keywords: Bottomland hardwoods, forest history, mammals, Mississippi Alluvial Valley, old

growth, songbirds, wetland restoration.
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directed by Congress—to provide increasingly greater service

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