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LSU Historical Dissertations and Theses Graduate School

Spring 3-30-1999 Diet Overlap of Native and Translocated Northern White-Tailed Deer in Southeastern Louisiana Brian Matthew Zielinski

Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Part of the Life Sciences Commons DIET OVERLAP OF NATIVE AND TRANSLOCATED NORTHERN WHITE-TAILED DEER IN SOUTHEASTERN LOUISIANA

A Thesis

Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science

in

The School of Forestry, Wildlife, and Fisheries

by Brian Matthew Zielinski B.A., State University of New York at Plattsburgh, 1996 May 1999 MANUSCRIPT THESES

Unpublished theses submitted for the Master’s and Doctor’s

Degrees and deposited in the Louisiana State University Libraries are available for inspection. Use of any thesis is limited by the rights of the author. Bibliographical references may be noted, but passages may not be copied unless the author has given permission.

Credit must be given in subsequent written or published work.

A library which borrows this thesis for use by its clientele

is expected to make sure that the borrower is aware of the above

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LOUISIANA STATE UNIVERSITY LIBRARIES ACKNOWLEDGEMENTS

I would like to genuinely thank my major professor, Dr. Mark K. Johnson.

Professor of Wildlife, School of Forestry, Wildlife, and Fisheries for his guidance and encouragement throughout this project, and for the many enjoyable memories during my tenure at LSU. For his trust in me, and my abilities as a graduate student, 1 am grateful.

I would also like to express my deep appreciation to the members of my graduate

committee: Dr. Robert. H. Chabreck, Professor of Wildlife, School of Forestry, Wildlife,

and Fisheries, and Dr. Alan Afton, Adjunct Professor of Wildlife, School of Forestry,

Wildlife and Fisheries for their assistance during my research and in preparation of this

manuscript.

Special thanks are extended to Mr. Arlen “Benny” Cenac and the Golden Ranch

Hunting Farm, for their assistance and contributions to this project. Particularly, 1 would

like to thank Mr. Randy Moertle, Lanny LeDay Sr., Lanny LeDay Jr., and Don Hohense

for their cooperation and incite during this study.

Much appreciation is extended to Darren Redfurn, Randy Walz, Linda Zeringue,

and Jamie Rogers of the Louisiana Agricultural Center, Southeastern Research Station,

for their time and effort in analyzing plant and fecal samples for my study.

A very special thanks goes to Mr. Jonathan W. Day for his unselfish assistance

during this project. For his field support and friendship, 1 am grateful. Thanks also go

to Stacey Robinson for developing my reference slide collection. Appreciation is also

extended to Dr. Lowell Urbatch, Associate Professor of Plant Biology, and Roland

Roberts, Ph. D candidate in Plant Biology, for their assistance with plant identification.

ii Finally I would like to thank my parents, Ronald W. Zielinski and Susan H.

Repsher, along with my father and mother in-law, Dennis and Judy Peterson, for

providing me encouragement and Financial support during my tenure at LSU, and

molding me into the man I am today. But above all, 1 would like to dedicate this work

to my lovely wife and best friend, Nikole L. Zielinski, who has given me her unfailing

love and support throughout my academic career. TABLE OF CONTENTS

ACKNOWLEDGEMENTS...... ii

LIST OF TABLES...... vi

LIST OF FIGURES...... vii

LIST OF PLATES...... viii

ABSTRACT...... ix

INTRODUCTION...... 1

LITERATURE REVIEW...... 5 DeerNutrition...... 5 Macro-Nutrient Requirements...... 6 Crude Protein (CP)...... 6 Forage Quality and Palatability...... 7 Diet Quality...... 8 Estimation of Diet Quality...... 10 Microhistological Analysis...... 11 Plant Fragment Identification...... 14 Differential Digestion and Fragment Discemability...... 15 Frequency Sampling...... 22

DESCRIPTION OF STUDY AREA...... 25 Location...... 25 Hydrology...... 25 Soils...... 28 Climate...... 29 Flora and Fauna...... 30 Deer Management Program...... 31 Spring-Summer...... 31 Fall-Winter...... 32

METHODOLOGY...... 33 Translocation of Northern Deer...... 33 Experimental Design...... 33 Fecal Sampling and Analysis...... 37 Reference Slide Preparation...... 39 Statistical Analysis...... 40

IV RESULTS...... 42 Diet Composition...... 42 Forage Diversity...... 52 Fecal Crude Protein...... 52

DISCUSSION...... 55 Native vs. Translocated Deer...... 55 Diet Composition...... 55 Forage Diversity...... 56 Fecal Crude Protein...... 56 Native and Translocated Deer...... 57 Diet Composition...... 57 Fecal Crude Protein...... 61

MANAGEMENT IMPLICATIONS...... 62

LITERATURE CITED...... 64

APPENDIX...... 78

VITA...... 82

v LIST OF TABLES

Estimated botanical compositions (% dry weight ± standard error) of fecal pellets from Native, Southern and Translocated, Northern white-tailed deer on Golden Ranch Hunting Farm, Gheens, Louisiana, during Spring, Summer, Fall, and Winter 1997, (n=30/population/season)...... 43

Chi-Square analyses using a = 0.05 w/ Bonferroni adjustment, for frequency of occurrence of shared plants identified in fecal pellets from Native, Southern and Translocated, Northern white-tailed deer during Spring (x2 = 10.32, a = 0.001, 1 df). Summer (x2 = 10.27, a = 0.001, 1 df), Fall (x2 = 9.89, a = 0.002, 1 df), and Winter (X2 = 8.94, a = 0.003, 1 df), on Golden Ranch Hunting Farm, Gheens, Louisiana, during 1997, (n=30/population/season)...... 48

Percentage diet similarity, average number of identified plants (± standard error) per fecal group, and probability associated with Student’s /-test by season and population of deer on Golden Ranch Hunting Farm, Gheens, Louisiana, (n=30/population/season)...... 51

Average crude protein content (% dry weight ± standard error) of deer fecal samples, and probability associated with Student’s /-test by season and population of deer on Golden Ranch Hunting Farm, Gheens, Louisiana, (n=30/population/season)...... 53

List of scientific and corresponding common names for plant taxa identified in fecal samples of Native, Southern and Translocated, Northern white-tailed deer during 1997, on Golden Ranch Hunting Farm, Gheens, Louisiana...... 79 LIST OF FIGURES

1. Golden Ranch Hunting Farm unit boundary...... 26

2. Location of fecal collection sites on Golden Ranch Hunting Farm...... 27 3

3. Location of Northern deer release sites from 1996 and 1997 on Golden Ranch Hunting Farm...... 34 LIST OF PLATES

1. Drawing that shows distinction between (A) segmented and (B) branched plant trichomes from (Johnson et al. 1983)...... 16

2. Drawing that shows pronounced difference in cell wall structure between (A) dicots and (B) monocots from (Johnson et al. 1983)...... 18

3. Drawing of distinct stellate trichome from Quercus spp., used for plant fragment identification from (Johnson et al. 1983)...... 20

4. Photograph of translocated northern deer showing 3x2 inch ear tags and 2 inch circular discs used for field identification...... 35

vm ABSTRACT

I used microhistological analysis of fecal pellets to estimate and compare seasonal diet compositions between free-ranging, southern and translocated, northern woodland white-tailed deer (Odocoileus virginianus) on Golden Ranch Hunting Farm,

Gheens, Louisiana, over four consecutive seasons, from January 1997 through January

1998. 1 analyzed pellet groups with Near Infrared Reflectance Spectroscopy (N1RS) and wet chemistry techniques to evaluate and compare crude protein levels between populations of deer and provide indices of diet quality.

On average, native and translocated deer diets were 87.65% similar during the entire study, and were significantly associated during all seasons (P < 0.00001),

suggesting that deer fed on similar plant species in like quantities throughout the year.

Few differences were found in plant selection frequencies per fecal sample, but

significant differences were detected (P < 0.001) among deer populations in the use of

Berchemia scandens and Vitis rotundifolia during spring. Northern deer also ingested

a greater diversity of plants (P < 0.05) during spring and winter; and fecal crude protein

levels were similar (P > 0.05) in all seasons except winter, when there was more

(P < 0.05) protein in southern deer diets. Overall, diet compositions, plant diversity,

and diet quality of southern and northern deer populations were similar, suggesting that

translocated deer select diets comparable to those of native animals. INTRODUCTION

Diets of grazing animals have received considerable study during the last thirty years. Dietary information for large, free-ranging herbivores has become an increasingly important tool in population management allowing assessments of nutrient intake and evaluation of forage competition among herbivores (Mclnnis et al. 1983). According to

Hodgman et al. (1996), monitoring the nutritional well being of free-ranging ungulates has become an essential part of big game management. Knowledge of wild herbivore food habits also is imperative for efficient range management. This information is required for: (1) optimal forage allocation to different species of herbivores, (2) selecting types of grazing animals compatible with the forage resource, (3) predicting the outcome of overgrazing by different animals, and (4) identifying new species on which to base management objectives (Holechek et al. 1982c). According to Smith and Shandruk

(1979), the effective management of wild ruminants and their habitats primarily depends

upon a working knowledge of both plants selected and the composition of diet during

each season. Hence, any method employed to estimate food habits of herbivores,

including microhistological analysis of fecal groups, should include a quantitative

measure of plant species eaten and the amount of each consumed.

The quantity of digestible dry matter (DDM) and energy available to white-tailed

deer varies by season. Many plants are browsed (or grazed) by deer to some degree, and

Atwood (1941) has identified 614 species on a national scale. In the Southeast, over 100

species of native plants are routinely consumed by deer (Harlow and Hooper 1971).

However, nutritional values and availability of different foods peak during different

1 seasons. For example, grasses and forbs in southern forests are of greatest nutritional quality during spring and early summer (Campbell et al. 1954). Conversely, winter rosettes of forbs and cool-season grasses provide less abundant, yet highly digestible forage during autumn and winter (Short 1975). To sustain deer populations when browse is of poor quality, wildlife managers often plant agronomic forages that are generally higher in nutrition than native plants (DeLany 1985, Keegan 1988, Steigler 1988).

Yet, variations in soil nutrients, plant maturation, and digestibility underscore the nutritional problems wild deer encounter throughout the year and form the basis for conditions that need to be improved through management (Short 1975).

To determine energy and nutritional value of ingested foods, it is essential to identify soluble and structural portions of plant material. Nutrients such as crude protein

(CP), phosphorous (P), and calcium (Ca) are essential for body maintenance and reproduction, and serve as major constituents of bones, antlers, and soft tissues. Does on poor nutritional regimes have lower fecundity, an uneven sex ratio in offspring, and

often can fail to achieve estrus as yearlings (Verme 1969). However, nutritionally

enhanced diets increase body weights, antler size, and productivity in deer (French et al.

1956, Magruder et al. 1957, Robinette et al. 1973). When microhistological studies of

fecal matter include an analysis of crude protein, it can provide an index of diet quality

that can be utilized to assess range condition and results of management.

Fecal studies of large ungulates have been conducted since the early 1900's to

determine diet composition. Herbivorous mammals masticate and degrade food items

so finely that microhistological techniques are necessary for plant species identification

2 (Zyznar and Urness 1969). The technique of microhistological analysis of fecal samples has received considerable use in previous research. The first technique was developed by

Baumgartner and Martin (1939) to analyze squirrel (Sciurus spp.) stomach contents. T his was accomplished by comparing the stomach contents with permanent reference slides of stained leaf and stem epidermis from known plants in the study area. Dusi (1949) later adapted this technique for fecal pellet analysis of cottontail rabbits (Sylvilagus spp.).

Gross food items also have been recognized in deer feces. Adams (1957) found

bitterbush leaf and stem fragments in mule deer (Odocoileus hemionus) pellets.

Similarly, remains of various acorns and seeds also were identified from white-tailed deer

fecal matter in Texas (Lay 1965). Lay concluded that the epidermis survived digestion

by virtue of encasement of entire cell walls in cutin. Accuracy of the microhistological

technique has been demonstrated by Sparks and Malechek (1968), and Vavra and

Holechek (1980). Holechek et al. (1982a) also provided a comprehensive review of the

microhistological technique, while training of technicians was discussed by 1 lolechek and

Gross (1982a). They discovered that considerable variation may exist in accuracy among

technicians, even when properly trained. Vavra et al. (1978) and Mclnnis et al. (1983)

also have indicated that some differences in diet estimates were due to differential

digestion of epidermal material. Differential digestibility and fragmentation have been

implicated as primary factors that potentially bias estimates of herbivore diets when fecal

samples are used (Smith and Shandruk 1979). Despite these discrepancies, fecal analysis

is still advocated for estimating diets of free-ranging herbivores to avoid disadvantages

of other methods such as rumen analysis for which animals must be harvested.

3 The microhistological technique has been used to quantify food habits of white-tailed deer populations in many different habitats (Lay 1965, Chamrad and Box

1968, Coblentz 1970, Short 1971, Everitt and Drawe 1974, Arnold and Drawe 1979. Kie et al. 1980, Warren and Krysl 1983, DeLany 1985, McCullough 1985, Johnson et al.

1987, Keegan et al. 1989, Johnson and Dancak 1993). Previous literature also has evaluated dietary overlap between sympatric species such as: elk (Cervus elaphus) versus deer (Gogan and Barrett 1995, Kingery et al. 1996, Kirchhoff and Larsen 1998) and cattle

versus deer (Gallina 1993, Martinez et al. 1997). However, scientific literature currently

is lacking knowledge on the feeding habits and dietary overlap that may exist among

intraspecific species that occupy the same range after introduction of a translocated

population.

Therefore, my objectives were to quantify and compare 3 parameters including:

(1) seasonal diet composition, (2) diet diversity, and (3) diet quality, between native

free-ranging Avery Island white-tailed deer (O. v. mcilhennyi) (Miller 1928), and

translocated northern woodland white-tailed deer (O. v. borealis) from Wisconsin and

Kansas white-tailed deer (O. v. macrourus) from Missouri on the Golden Ranch Hunting

Farm, located in Gheens, Louisiana.

4 LITERATURE REVIEW

DEER NUTRITION

Forage contains organic and inorganic substances that supply energy and nutrients to herbivorous animals for life processes. Furthermore, nutritional quality of a food is determined by the nutrients contained within the food and the animal’s ability to digest or utilize these nutrients. Seasonal variations in species abundance, phenology, and nutrient quality of range plants causes variation in deer diets during different seasons creating nutritional stress for the animal (Short et al. 1969). Deer in the South and Southwest primarily are browsing animals except during late winter and early spring when there is an increase in utilization of grasses and forbs (Davis 1952, Goodrum and Reid 1954).

In south Texas, Davis (1952) reported that browse comprised the major portion of deer

diets, while total consumption and diets of deer on the King Ranch followed the annual

progression of plant growth on the range. Deer food consumption rates also vary

throughout the year, even when high quality food is freely available. Short et al. (1969)

reported that two-year old white-tailed deer in the South increased their food

consumption from lows during November and December to highs during spring.

Moreover, consumption generally decreased during hot, humid summers, but increased

slightly in August for bucks and gradually increased from July to October for does.

Intensified management of white-tailed deer involves estimation of carrying

capacities for which a knowledge of digestibility and nutritional requirements is essential

(Holter et al. 1979). According to Wheaton and Brown (1983), the seasonal variation in

the quality of deer diets and its effect on digestibility has been thoroughly demonstrated

5 (Kirkpatrick et al. 1969, Blair et al. 1977, Holter et al. 1979). Baker et al. (1979) found that digestibility of an experimental ration did not vary with the stresses of winter in mule deer fawns. Moreover, Cedarlund and Nystrom (1981) found no seasonal variation in the ability of moose (Alces alces) to digest browse, whereas roe deer (Capr coins capreolus) on the same range had an increased ability to digest fibrous material during winter.

In addition to the overall lack of sufficient food, specific deficiencies of energy, protein, calcium, phosphorous, cobalt and vitamin A produce symptoms of malnutrition

in domestic ruminants (French et al. 1956). Similarly, lack of essential nutrients may

create or contribute to subnormal growth, antler development, and reproduction of

white-tailed deer (French et al. 1956, Murphy and Coates 1966). Basic to the appropriate

management of deer forages is an understanding of deer nutrient requirements within

each season of the year. The most critical time in the development of a white-tailed deer

is the immediate post weaning period. Fawns may no longer depend upon mother's milk,

which during November is reported to contain approximately 34% crude protein on a dry

matter basis (Silver 1961). Yet, fawns must grow and accumulate sufficient energy

reserves to survive their first winter (Ullrey et al. 1973).

Macro-Nutrient Requirements

Crude Protein (CP)

Smith et al. (1975) reported that fawns require 3.05 g digestible nitrogen per

kilogram of metabolic weight0 75 per day for maximum growth. Ullrey et al. (1967),

found greater body weight gain in male fawns fed a complete pelleted diet with 22% CP

6 than when the diet contained 14% CP (dry matter basis). Ullrey et al. also concluded that male fawns have a higher dietary protein requirement than do female fawns for maximum weight gain during the immediate post-weaning period. According to Ullrey et al.

(1967), a dietary CP concentration of 12.7% did not appear adequate for males, but a CP level of 20.2% was sufficient with further studies needed to more closely define the amount. The work of French et al. (1955) and Magruder et al. (1957) suggests that a diet

(dry matter basis) for deer older than one year of age should contain about 7 to 8% CP for body weight maintenance and about 14 to 18% CP for optimum weight gain. Other studies have shown that deer grow poorly on diets with crude protein levels below 9%; they grow adequately when CP ranges from 10 to 13%, and they grow well if diets contain 14 to 20% CP (French et al. 1956, McEwen et al. 1957, Murphy and Coates 1966,

Ullrey et al. 1967). Holter et al. (1979) also concluded that digestibility of CP increased

with an increasing concentration of CP in the diet. Similarly, Smith et al. (1975) found

that digestibility of protein increased significantly with increasing dietary CP up to 20%.

However, protein in natural food is probably lower in digestibility than in formulated

diets due to a higher fiber content. This suggests that CP content in natural forages must

be higher than in prepared diets to achieve the same results (Holter et al. 1979).

Forage Quality and Palatabilitv

Many factors affect morphology and potential digestibility of woody and leafy

materials consumed by herbivores including growth stage, time of year, and chemical

constituents. The nutrient quality of twigs varies directly with growth stage, and

digestibility of the woody tissue is also affected by changing nutrient content

7 (Blair and Halls 1968). Dry matter content, cell wall content, and CP also change seasonally with varying growth stages. During spring, most woody plants experience a period of rapid growth in which they are succulent and low in fiber. However, when bud elongation essentially has ceased in late summer, early fall, the fibrous constituents reach

their highest levels making them less palatable to herbivores (Short el al. 1972).

Leaves develop as lateral protuberances on the bud apical mcristem and grow

rapidly through cell division and enlargement. Much of the leaf consists of mesophyll

cells that tend to be thin walled and loosely arranged. According to Short et al. (1972),

forage analyses applied to American beautyberry (Callicarpa americana) tissue indicate

that in comparison to twigs, leaves are more succulent and higher in CP, crude fat, ash,

nitrogen-free extract and cell contents, but lower in crude fiber, cell wall contents, acid

detergent fiber, lignin, and cellulose.

Anatomical features of plants, such as spines and thorns along with a variety of

chemical constituents including oils, also affect the palatability and digestibility of certain

shrub materials causing white-tailed deer to be selective browsers. Nagy and Tengerdy

(1968) hypothesized that absolute concentrations of volatile oils encountered in some

sagebrush populations could limit rumen microbial activity if these plants comprised the

entire diet of mule deer. Thus, shrubs with high amounts of oil compounds would only

provide low levels of metabolizable energy for utilization by deer (Short et al. 1972).

Diet Quality

Determination of diet quality for white-tailed deer can be both time-consuming

and expensive. Nutrient levels of selected forages have been used as indicators of dietary

8 quality (Cook 1964), but this generally is an unreliable method for determining diet quality of free-ranging ungulates (Theurer et al. 1976) due to their apparent ability to select the most nutritious forages available (Swift 1948, Klein 1970). Because esophageal fistulation usually is impractical and unsuitable to estimate diet quality due to

salivary phosphorus contamination (Holechek et al. 1985), determinations require both a

measure of diet (e.g., fecal analyses, rumen analyses, direct observation, etc.) and

simultaneous measures of nutritional attributes of each dietary component. An alternative

noninvasive approach is to measure a chemical characteristic of fecal material that bears a

relationship to the quality or quantity of ingested diets (Cordova et al. 1978.1 lolechek et

al. 1982ft) (Leslie and Starkey 1985).

Fecal nitrogen (FN) is a nutritional index that is positively associated with intake

(Arnold and Dudzinski 1963, Langlands et al. 1963, Stallcup et al. 1975), digestibility

(Lancaster 1949, Greenhalgh et al. 1960, Marten et al. 1963, Holloway et al. 1981),

level of protein (Raymond 1948, Greenhalgh and Corbett 1960, Hebert 1973, Arman et

al. 1975, Erasmus et al. 1978, Mould and Robbins 1981, Holechek et al. 1982t/), and

weight changes (Gates and Hudson 1981) in a variety of wild and domestic ruminants.

However, fecal indices that estimate diet quality have had limited application for wildlife

managers. Arman et al. (1975) contended that FN could be a valuable index if the

relationships of dietary nitrogen (DN) and FN could be established for a particular

ruminant in a given locality, but widespread use is limited because of variability in

species, forages, and seasons. Yet, Gates and Hudson (1981) found that FN reflected

changes in quality of forages used by Rocky Mountain elk (C. e. nelsoni)

9 (Leslie and Starkey 1985). Howery and Pfister (1990) also concluded that under controlled conditions, FN was useful for detecting large differences in DN. To date, researchers have used fecal nutrient levels to predict dietary nutrient levels in elk (Mould and Robbins 1981, Leslie and Starkey 1985), black-tailed deer (O h. columbianus)

(Leslie and Starkey 1985, Mubanga et al. 1985), white-tailed deer (Jenks et al. 1989,

Leslie et al. 1989), moose (Leslie et al. 1989), and domestic livestock (Belonje and Van

Den Berg 1980a,6, Holechek et al. 1982d, 1985) with good success. Because the advantages (Leslie and Starkey 1987) and disadvantages (Hobbs 1987) of FN as an indicator of DN in free-ranging deer have been documented, biologists may utilize FN as a management tool to evaluate diet quality of free-ranging herbivores, as long as they recognize potential biases.

Estimation of Diet Quality

Feeding trials and chemical analysis are the two most common methods employed

to estimate forage quality. However, feeding trials and laboratory methods used to

predict forage quality are labor intensive and costly. Currently, there are no rapid and

reliable methods for diet quality determination of free-ranging herbivores, but Holechek

et al. (1982e) and Stuth et al. (1989) suggest that application of infrared reflectance

techniques have potential in rangeland diet quality analyses.

Near infrared reflectance spectroscopy (N1RS) is a method for rapidly and

reproducibly measuring the chemical composition of fecal samples. The analysis is based

on the fact that each major chemical component of a sample has a unique near infrared

absorption property, allowing researchers to differentiate one component from another

10 (i.e., crude protein from phosphorous) (Marten et al. 1989). The summation of these absorption properties, combined with the radiation-scattering properties of the sample, determines the diffuse reflectance of a given sample. For any chemical constituent of

interest, reflectance properties are measured at the maximum and minimum absorption

point. The ratio of these two values measured on different samples is then correlated to

the concentration of the constituent in those samples (Marten et al. 1989). By performing

this correlation, an equation can be developed to predict the concentration of specific

constituents in fecal samples based on their reflectance properties.

The NIRS method of analysis has several main advantages including: speed of

analyses, simplicity of sample preparation, multiplicity of analyses with one operation,

and non-consumption of the sample. Conversely, the chief disadvantages are

instrumentation requirements, dependence on calibration procedures, and lack of

sensitivity for minor chemical constituents (Marten et al. 1989). Despite these

drawbacks, the use of near-infrared reflectance spectroscopy on fecal pellets to predict

forage quality of free-ranging herbivores has potential as a management and research tool

(Brooks et al. 1984, Coleman et al. 1989, Stuth et al. 1989, Lyons and Stuth 1992).

MICROHISTOLOGICAL ANALYSIS

Microhistological analysis of fecal samples has been utilized to determine food

habits of many cervids besides white-tailed deer including mule deer (Gill et al. 1983,

Kucera 1997), black-tailed deer (O’Bryan 1983, Kirchhoff and Larsen 1998), and elk

(Gogan and Barrett 1995, Kingery et al. 1996, Kirchhoff and Larsen 1998). Preparation

of material for microscopic identification also has varied considerably. Crocker (1959)

11 simply diluted fecal pellets with water and spread the material between two microscope slides. Storr (1961) boiled, dried, and ground samples in a mixture of nitric and chromic acids; samples then were washed with water, stained with violet medium, and finally centrifuged and mounted on slides. Holechek (1982) determined the influence of sample preparation procedures on the ratio of identifiable to non-identifiable fragments and concluded that sample preparation for microhistological analysis can improve the number of identifiable fragments by either soaking in 0.05 m sodium hydroxide or bleach in conjunction with the use of Hertwig’s clearing solution.

Sparks and Malechek (1968) adapted the frequency sampling method reported by

Fracker and Brischle (1944) to quantify botanical compositions using microscopic

techniques. One of the basic assumptions of the microhistological method outlined by

Sparks and Malechek (1968) is that a 1:1 relationship exists between relative particle

density (ie., the number of fragments per microscope field) and percent dry weight of

identifiable fragments ground to a uniform size through a 1 mm screen. The

mathematical rationale for converting frequency to density is discussed by Johnson

(1982). Other studies conducted by Vavra and Holechek (1980), Johnson and Pearson

(1981), Holechek and Gross (19826), and Holechek et al. (1982J) confirmed that the

relationship between relative particle density and dry weight reported by Sparks and

Malechek (1968) is generally true. After analyzing limitations of other techniques,

Holechek et al. (1982c) stated that fecal analysis is the method of choice for evaluating

wild ruminant diets. However, fecal analysis methodology assumes that: (1) fragments of

nearly every ingested plant species and all plant parts within species are recoverable and

12 identifiable in fecal samples (Storr 1961), (2) recovery or identification rates of plant fragments are consistently proportional to ingestion rates of plant species and plant parts or that digestion correction factors can be developed to account for differential digestion biases (Dearden et al. 1975), (3) results are repeatable among technicians with similar training (Sparks and Malechek 1968), and (4) there is a predictable relationship between frequency of occurrence of dietary items in the sample and the weight of or density of those fragments (Sparks and Malechek 1968, Havstad and Donart 1978, Marshall and

Squires 1979) (Gill et al. 1983).

The results of fecal analysis generally reveal that: (1) diets of grazers are

estimated with acceptable accuracy (Stewart 1967, Free et al. 1970, Sanders et al. 1980,

Johnson and Pearson 1981), and (2) accuracy of fecal analysis to estimate diets of “mixed

feeders” is controversial because evidence is contradictory (Zyznar and Urness 1969,

Todd and Hansen 1973, Vavra et al. 1978, Smith and Shandruk 1979). There have been

several reasons postulated for the disparity in results including: (1) different digestion

rates of plant species and plant parts at different phenological stages (Slater and Jones

1971, Dearden et al. 1975, Vavra and Holechek 1980, Johnson and Wofford 1983),

(2) differential detection and recognition of plant species during microscopic evaluation

(Hoover 1971, Westboy et al. 1976, Havstad and Donart 1978, Kie et al. 1980, Sanders et

al. 1980), (3) differential particle size reduction and recognition induced during sample

preparation (Westboy et al. 1976, Holechek 1982), (4) differences in experience and

training among analysts (Holechek and Gross 1982a, Holechek et al. 1982a), and

(5) analytical biases (Anthony and Smith 1974, Holechek and Vavra 1981, Holechek and

13 Gross 1982a, Johnson 1982) (Gill et al. 1983). Additional disadvantages of fecal analysis

include large labor inputs and the need for an extensive reference slide collection.

Fecal analysis also has several distinct advantages when estimating diets of free-

ranging herbivores. According to Smith and Shandruk (1979), major advantages of fecal

sampling include: (1) unlimited numbers of fecal samples can be obtained without

intensive animal observations, (2) topography or dense vegetation does not hinder

collection, (3) animals need not be harvested or their feeding habits disrupted, (4) 15

fecal samples gives the same level of dietary precision as 50 deer rumen samples

(Anthony and Smith 1974), and (5) animal movements are unaffected. For these

reasons, fecal analysis still remains one of the most popular biological tools to evaluate

free-ranging herbivore diets.

Plant Fragment Identification

Monocot and dicot plant fragments found in fecal samples are identified by direct

comparisons with drawings and reference slides made from native forages found on

study sites. Drawings can be made either by hand or with the aid of a microscopic

drawing tube, which allows the novice to draw and outline the micro-anatomy of a plant

fragment accurately (Johnson et al. 1983). Micro-anatomy of monocots and dicots

provide the basis for histological comparison through the identification of structures such

as: venation, cell wall contour, stomatal arrangement, trichomes, silica cells, glands,

cuticle, crystals, and epidermal cells (Johnson et al. 1983). Within these major types of

plant features there also can be a large amount of variation. For example, trichomes can

be either segmented or branched (Plate 1). This complex breakdown of primary plant

14

- structures allows for the accurate identification of plant fragments in fecal matter.

Distinguishing monocots from dicots tends to be a simple task because of the pronounced difference in cell wall structure (Plate 2). However, the ability to distinguish between various dicots requires consistent recognition of cell patterns and anatomical features

(Johnson et al. 1983). Often the presence of a distinctive trichome such as that found in

Quercus spp. (Plate 3) provides key evidence for identifying a plant fragment. But trichomes also may separate from a plant fragment, in which case other diagnostic

structures must be documented for accurate identification. In most cases, 1 to 3

micro-anatomical features are needed for the accurate determination of monocot and

dicot plant species (Johnson et al. 1983).

Differential Digestion and Fragment Discernahilitv

Because all plant fragments cannot be identified, there have been attempts to

account for differences among species as to proportions of fragments that can be

identified and to account for affects of differential digestion of fragments (Johnson et al.

1983). Differential digestibility has been widely discussed as one of the primary causes

for error when using fecal samples to estimate herbivore diet. Holechek et al. (1982c)

concluded that fecal analysis tends to underestimate forbs in the diet in a variety of

ruminants, although some studies have reported this not to be the case (Todd and 1 lansen

1973, Anthony and Smith 1974, Kie et al. 1980). Moreover, some researchers have gone

to great lengths to account for the effects of differential digestion (Voth and Black 1973)

even without significant documentation that digestion introduces sampling bias.

According to Frey-Wyssling and Muhlentahler (1959), there arc no known

15 Plate 1

Drawing that shows distinction between (A) segmented and (B) branched plant trichomes from (Johnson et al. 1983).

16 1

(A) (B)

17 Plate 2

Drawing that shows pronounced difference in cell wall structure between (A) dicots and (B) monocots from (Johnson et al. 1983).

18 (A) (B)

19 Plate 3

Drawing of distinct stellate trichome from Quercus spp., used for plant fragment identification from (Johnson et al. 1983).

20 21 microorganisms that possess cutin degrading enzymes. Subsequently, histological analysis is solely based on the micro-anatomical features of the indigestible cutin and cells underlying the cutin that avoid the digestion process (Johnson et al. 1983). Thus, identification is made only from the cutin which retains the impression of epidermal tissues. Johnson et al. (1983) recorded the number of fragments and proportions identified for a variety of undigested and digested plants and found that for 47 plant species tested, digestion increased discernability for 3 while decreasing it for 9, with the other 35 plant species showing little effect. But regardless of the plant species, digestion

had little influence on the ability to estimate botanical composition of herbivore diets.

Frequency Sampling

Sparks and Malechek (1968) demonstrated that frequency sampling was an

accurate alternative to counting each plant fragment when quantifying botanical

composition on microscopic slides. As a result, many researchers have used this

“frequency conversion” technique to estimate herbivore diets (Todd and Hansen 1973,

Dearden et al. 1975, Johnson 1979, Gill et al. 1983, Johnson et al. 1983, McCullough

1985, Johnson et al. 1987). After the fecal sample is ground to a uniform size, a

predetermined number of fields are systematically examined and the presence of each

species is recorded per microscopic field (Sparks and Malechek 1968). As long as the

amount of ground fecal matter on each slide averages 1 to 3 fragments per field, average

relative frequency of occurrence represents average relative abundance of the different

species in the mixture (Johnson et al. 1983). In turn, the measure of relative abundance

provides an estimate of relative dry weight for each food item quantified in the

22 herbivore’s diet (Johnson 1982). The relationship between frequency of occurrence and

particle density is based on a finite amount of plant fragments distributed at random

across the microscope slide. Percent frequency may then be converted to relative density

of particles per location by using a table developed by Fracker and Brischle (1944).

A detailed description of this mathematical theory is available in Johnson (1982), but

the standard form of the relationship between frequency and density is expressed in the

formula:

F = 100 (1-e d),

where F is relative frequency, e is the natural logarithm and d is the mean particle density

determined by the number of fragments (n) and the number of microscope fields

examined (k) so that:

d = n / k.

If fragments from m different plant species are randomly distributed in the microscope

field, the particle density of each is independent from the others. Thus, the density (d)

of fragments per field may be converted to relative density (RD).

density of discerned fragments for a species RD = ------X 100. £ of densities of discerned fragments for all species

The relationship between RD and dry weight for most plant species is highly associated

as long as each microscopic field can be treated as an individual sampling unit. For this

to occur, the following assumptions must be made; (1) microfragments of plants are

randomly distributed on the microscope slide, (2) microfragments from different plant

taxa are the same average size, and (3) dry weight bulk densities of different plant taxa

23 are the same (Fracker and Brischle 1944). These assumptions are valid because the distribution, size, and average number of fragments per microscopic field are controlled in the slide making process and there are no significant differences in dry weight bulk densities among leaf tissues of different plants (Johnson 1982).

24 DESCRIPTION OF STUDY AREA

LOCATION

My study was conducted on Golden Ranch Hunting Farm in LaFourche Parish,

Gheens, Louisiana, which is situated within the Inactive Delta Marsh Zone of the Deltaic

Plane (Chabreck 1970). Golden Ranch is bounded by Company Canal to the north. Lake

Salvador on the east, the Gulf Intercoastal Water Way (GIWW) to the southeast, and the

Golden Ranch plantation property line on the west (Figure 1). Golden Ranch consisted of

20,250 ha, and was dominated by agricultural fields, forested corridors, and fresh water

marsh with spoil banks making up the many interdistributary ridges found throughout the

property. Because a majority of the plantation was fresh water marsh, the study area was

limited to 2,025 upland ha that routinely are pumped off for production of agronomic

crops and supplemental forages (Figure 2). The upland area was bounded by Company

Canal to the north. Bayou Matheme ridge to the east, the Texaco pipeline to the south,

and the Golden Ranch property line to the west.

HYDROLOGY

My study area was located in the upper coastal regions of Barataria Basin, defined

by Bayou LaFourche to the west and the Mississippi River to the cast. Major water

bodies in the immediate area were Bayou Des Allemands, Company Canal, and Bayou

Vacherie, which provided the greatest amount of hydrologic influence to the study site.

Water levels also were manipulated seasonally through the use of two water control

structures approximately 1.5 m wide, to produce conditions conducive to native tlora

and fauna (Millet 1997). Golden Ranch was characterized by the presence of man-made

25 Data Source: Louisiana Dept. Natural Resources Golden Ranch Hunting Coastal Restoration Division Database Analysis Section Farm Property Boundar 1991 Satellite Imagery Date: August 27,1998 Map ID: 98-5-098

Figure 1. Golden Ranch Hunting Farm unit boundary.

26 Data Source: Louisiana Louisiana Dept. Natural Resources Coastal Restoration Division Northern deer collection sites Database Analysis Section Southern deer collection sites 1994 Satellite Imagery Date: August 27/ 1998 Study Site Boundary Map ID: 98-5-099

2 Miles 3 Kilometers

Figure 2. Location of fecal collection sites on Golden Ranch Hunting Farm.

27 canals and ditches, created for the purposes of navigation, petroleum exploration, irrigation, and pipelines. Upland swamps also were abundant due to drainage from interdistributary ridges that cut across the property. Most of the large canals that crossed the property also were bordered by spoil banks to prevent flooding of agricultural fields.

SOILS

There were 6 different soil series present within the study area, constituting 3

distinct habitat types; agricultural land, forested wetlands, and fresh water marsh

(Matthews 1984). Soil types found within Golden Ranch Hunting Farm included:

Commerce silt loam (Cm) and Commerce silty clay loam (Co) (fine-silty, mixed,

nonacid, thermic, Aerie Fluvaquent), Sharkey clay (Sk) and Sharkey clay, occasionally

flooded association (Sr) (very-fine, smeetitic, nonacid, thermic, Aerie Epiaquert),

Fausse-Sharkey association (FA) (very-fine, montmorillonitic, nonacid, thermic, Typic

Fluvaquent), Rita muck (Ra) (very-fine, montmorillonitic, nonacid, thermic, cracked,

Typic Fluvaquent), Barbary-Faussee association (BB) (very-fine, montmorillonitic,

nonacid, thermic, Typic Hydraquent), and Allemands muck (AE) (clayey,

montmorillonitic, euic, thermic, Terric Medisaprist). The Commerce and Sharkey clay

series consisted of poorly drained, moderately permeable, firm, mineral soils that

typically were found on the natural levees along Bayou LaFourche and its distributaries,

making them suitable for agricultural production and growth of upland forests. The

Fausse-Sharkey association, Sharkey clay-occasionally flooded, and Rita muck series

comprised the forested wetland areas and are poorly drained, slowly permeable, firm,

mineral soils that formed in or over clayey alluvium. The third habitat type, fresh water

28 marsh, was composed of the Barbary-Faussee association and the Allemands muck scries,

which are very poorly drained, organic and mineral soils formed in or over clayey

alluvium, and range in elevation from -6 to 3 ft above sea level.

CLIMATE

The climate of southern Louisiana primarily is determined by its subtropical

latitude, the continental land mass to the north, and the Gulf of Mexico to the south

(Calhoun 1997). Summer months are dominated by semi-tropical weather, with frequent

afternoon precipitation brought on by moist air from the Gulf (Chabreck 1972). Winter is

characterized by alternating cold spells, with continental winds blowing from the north,

and warm tropical winds arising from the south.

During the study period, January 1997 to January 1998, average monthly

temperatures ranged from 28.49 °C to 11.88 °C (Louisiana Monthly Climate Review,

National Oceanic and Atmospheric Administration, Houma, Louisiana). Spring months

(March-May) had an average temperature of 20.34 °C, with a mean low of 17.89 °C

occurring in April. The summer season (June-August) averaged 27.68 °C, with a

maximum mean temperature of 28.49 °C being recorded in July. Fall months

(September-November) averaged 21.32 °C, but climbed as high as 27.05 °C during

September, while the winter season (December-February) averaged 13.05 °C, with a

mean low temperature of 11.88 °C being recorded in December.

The mean monthly precipitation for Houma, Louisiana, the closest weather station

to my study site, was 14.81 cm from January 1997 to January 1998 (Louisiana Monthly

Climate Review, National Oceanic and Atmospheric Administration, Houma, Louisiana).

29

1 Winter was the wettest season averaging 20.53 cm of rainfall, over a mean of 12 rain days per month, with a maximum daily record of 12.95 cm of rain falling during January of

1998. Fall months were the driest during the study period, with an average of 9.08 cm of precipitation in 8 days of rain per month, with a daily maximum of 5.56 cm of rain occurring in September. Similarly, spring and summer averaged 12.21 cm and 15.46 cm of rainfall, during an average of 8 and 11 rain days per month, respectively.

FLORA AND FAUNA

Golden Ranch contained a vast array of native plant species. Forested corridors that bordered pasture or paralleled interdistributary ridges were abundant with live oak

('Quercus virginiana), water oak (Quercus nigra), Drummond red maple (Acer rubrum var. drnmmondii), box elder (Acer negundo), sweetgum (Liqnidambar styraciflua),

southern hackberry (Celtis laevigata), and black willow (Salix nigra). Beneath the

canopy, plant species such as waxmytrle (Myrica cerifera), muscadine (Vitis

rotundifolia), persimmon (Diospyros virginiana), buttonbush (Cephalanthus

occidental), deciduous holly (lllex decidua), saltbush (Baccharis halimifolia), and

elderberry (Sambucus canadensis) dominated the midstory and shrub areas. The

remaining understory was primarily composed of blackberry (Rubus spp.), greenbriar

(Smilax spp.), boneset (Eupatorium spp.), rattan vine (Berchemia scandens), goldenrod

(Solidago spp), blazing star (Liatris spp.), waterprimrose (Ludwigia spp.), teaweed (Sida

rhombifolia), brazilian vervain (Verbena brasiliensis), snoutbean (Rhynchosia spp.), and

pepper vine (Ampelopsis spp.).

30 Dominant wetland vegetation in marsh habitats was maidencane (Panicum hemitomon), bull-tongue (Sagittaria lancifolia), wapato (Sagittaria latifolia), sedges

(Carex spp.), and white waterlily (Nymphea odorata), along with beggar ticks (Bidens spp.) occurring beside the canals (Millet 1997).

Golden Ranch also was home to an abundance of wildlife including furbearers, waterfowl, alligators (Alligator mississipiensis), and birds of prey. Nutria (Myocastor coypus) and muskrat (Ondatra zibethicus) were common furbearers, whereas common

waterfowl species included mallard (Anas platyrhynchos), gadwall (Anas strepera), and

blue-winged teal (Anas discors). Alligators were common in canals, ditches, and ponds

throughout the plantation. Birds of prey such as the golden eagle (Aquila chrysaetos)

and immature bald eagle (Haliaeetus leucocephalus) also were present but in limited

numbers.

DEER MANAGEMENT PROGRAM

During the 1997-1998 deer season. Golden Ranch Hunting Farm began its 12th

year of intensive deer management. The deer management program included: (1)

recording harvest data, (2) recording observation data, (3) harvest restrictions (bucks and

does), (4) planting food plots, (5) constructing additional hectares of food plots, and (6)

supplemental feeding with battery operated broadcast feeders to satisfy management

goals of increasing both the quantity and quality of the deer herd.

Spring-Summer

In April 1996, 70 ha of sugarcane fallow land were planted in a group IV soybean

(Glycine max) called Hyperformer 498. The deer utilized several different areas of the

31 soybean fields, but completely destroyed 16 ha of soybeans near the end of Couteau du

Cypre road because of their concentrated use. In 1995, 81 ha of American jointvetch

(Aeschynomene americana) were also planted. All of the fields reached heights of four to

six feet, flowered, and produced seed. It was hoped that this excellent seed base would

regenerate a substantial crop in 1996. However, this did not occur and only nominal

growth was detected in several of the food plots. For 1996, only 61 ha of jointvetch were

planted, also producing minimal growth. During the summer 1997, Golden Ranch

continued its soybean program and again began planting American jointvetch in small

quantities. Southern cross clover (Trifolium spp.) also was planted to compensate for the

lack of nutrition in native forages during summer months.

Fall-Winter

During 1996, 84 food plots totaling 39 ha were planted on the study site with fall

and winter season forages for deer. Three feed types planted were wheat (Triticum

aestivum), ryegrass (Loliutn multiflorurri), and tripoli clover (Trifolium spp.). Food plots

were prepared and planted from September 15 to October 15, 1996, with a wheat,

ryegrass, and tripoli clover mix at the rate of 5 bushels of wheat, 125 pounds of ryegrass,

and 25 pounds of tripoli clover per hectare. Due to good success in 1996/97, the

fall/winter deer management program for 1997/98 was identical, with the exception of

reducing the total number of food plots across the study area. All food plots grew well

during winter and early spring.

32 METHODOLOGY

TRANSLOCATION OF NORTHERN DEER

Golden Ranch Hunting Farm in agreement with the Louisiana Department of

Wildlife and Fisheries, translocated 69 northern deer from Wisconsin (O. v. borealis) and

34 deer from Missouri {O. v. macrourus) over a 2 year period onto 5 different sites, with

separate release sites only being used to release deer on both sides of the property

(Figure 3) (Day 1998). Wisconsin deer came from a large enclosure in Southeastern

Wisconsin (Mark Schobel, R Zoo, Neshkoro, Wisconsin) where they resembled a wild

herd except for being enclosed. Conversely, Missouri deer were bom and tit-raised

within the LSU captive deer herd, located at Idlewild Research Station in Clinton,

Louisiana (Day 1998). While immobilized, deer were fitted with colored 3x2 inch car

tags or 2 inch circular discs, allowing for field identification (Plate 4).

EXPERIMENTAL DESIGN

I used 1:40,000 scale color infrared (C1R) aerial photography provided by the

National Aerial Photography Program (NAPP) to outline the study area based on

surrounding roads and landmarks. A total of 10 study plots were selected (6 for southern

deer, 4 for northern deer) from within the upland 2,025 ha region of Golden Ranch,

ranging from open pasture to forested ridges (Figure 2). All ten sites were utilized until

the end of August 1997, with only six sites remaining thereafter due to loss of permission

to access parts of study area. After initial site selection, seasonal observations resulted in

modification or expansion of these sites to ensure that sampling criteria would be met

during each season.

33 Data Source: Louisiana Dept. Natural Resources Jan. 13, 19% - Wisconsin CoaBtal Restoration Division Database Analysis Section Feb. 1,19% - Wisconsin 1994 Satellite Imagery Jan. 25,1997 - Wisconsin Date: August 27,1998 Map ID: 98-5-100 Feb. 13,1997 - Missouri Feb. 17-18,1997 - Missouri

Study Site Boundary

Figure 3. Location of Northern deer release sites from 1996 and 1997 on Golden Ranch Hunting Farm.

34 Plate 4

Photograph of translocated northern deer showing 3x2 inch ear tags and 2 inch circular discs used for field identification.

35 36 FECAL SAMPLING AND ANALYSIS

Based on previous research, a total of 30 fecal pellet groups were collected from both southern and northern deer during each season, from January 1997 through January

1998 (i.e., spring (March-May), summer (June-August), fall (September-November), winter (December-February) (Anthony and Smith 1974). When possible, pellet groups

for northern and southern deer were collected from designated study plots, but if deer

patterns shifted during the sampling period, observations were adjusted accordingly.

Fecal groups for both populations were only collected when a deer could be visibly

classified as either a native or translocated animal, and after direct physical observation of

defecation to ensure pure samples from southern and northern deer. Fecal groups then

were placed in separate paper bags and labeled, before being put on ice to prevent

possible microbial action during transport to the laboratory. For the purpose of my study,

a fecal group had to be composed of at least 10 pellets to be considered a viable sample.

I took extreme care to prevent contamination of the samples with soil or other plant

material. Once in the lab, fecal samples were oven-dried at 60 °C for 48 to 72 hours, and

ground through a Wiley mill fitted with a 40 mm mesh screen to create uniform fragment

size among all fecal groups. At least 2 g of fecal material from each sample was then

taken to the Southeastern Research Station, Louisiana State University Agricultural

Center in Franklinton, Louisiana, and analyzed for crude protein using Near Infrared

Reflectance Spectroscopy (NIRS) and wet chemistry techniques as per forage nutrient

analysis methods to estimate diet quality (AOAC 1990).

37 For seasonal diet determination, approximately 0.25 g of ground fecal matter from each sample was placed in a 50/50 bleach and water solution for approximately 5-10 minutes to remove pigments from the ground fecal fragments. The material then was put in a microwave for 15 to 20 seconds and left standing for another 5 minutes with occasional agitation. Fecal fragments were flushed thoroughly with water using a 100

mm mesh sieve. The bleached fecal matter then was placed on a sequence of 5 slides.

Enough sample material was placed on each slide to provide for an average of 1 to 3

identifiable plant fragments per microscopic field (Litvaitis et al. 1996), while a total of at

least 20 frequency (field) observations were done per slide to insure high repeatability

between slides (Flolechek and Vavra 1981), and so an average of 100 fields were

examined for each fecal group. I analyzed 24,000 microscopic fields under a Leitz

compound binocular microscope at 100 X, with 200 X being used when the diagnostic

characteristics were unclear (Holechek and Valdez 1985).

1 determined botanical composition of fecal matter using microhistological

analysis. Histological features such as size and shape of epidermal hairs, presence or

absence of hairs, cell shapes, stomatal arrangement and crystals included in epidermal

cells provided diagnostic characteristics for the identification of plant species (Sparks

and Malechek 1968). To reduce mis-identifications, small particles that lacked distinct

histological features were excluded (Holechek and Gross 1982a). A discernablc fragment

was defined as having at least 1 to 3 anatomical characteristics, such as silica bodies,

trichomes, crystals or distinct stomatal arrangement (Johnson and Wofford 1983).

Identified particles were then placed in 4 categories for data analysis: (1) grass and

38 grass-like species, (2) forbs, and (3) woody browse/fruit with those remaining being grouped into an unidentifieds category (4).

REFERENCE SLIDE PREPARATION

Reference slides of native plant species found during each season on the study site were made to provide a collection of potential forage species. Visual evidence of consumption by white-tailed deer were the criterion for identifying a plant as a potential forage species. A total of 10 g of each plant specimen observed to be consumed by deer was removed, but only parts representing the most succulent portions of the plant, such as leaves, stems and buds, in order to simulate actual feeding by deer. Each clipped forage species was then taxonomically classified and placed in a separate paper bag. If a plant species could not be keyed out in the field, classification was completed with the aid of

Dr. Lowell Urbatch, Associate Professor of plant biology, LSU; Roland Roberts. Ph. D

candidate in plant biology, LSU; and Dr. Robert Chabreck. Professor of Wildlife. LSU.

Once in the laboratory, plant specimens were dried at 60 °C for 48 to 72 hours and ground

in a Wiley mill (40 mm mesh screen). Three slides were then prepared for each forage

species collected on the study site in the following manner. Selected plant material was

placed in a 50/50 bleach and water solution for approximately 5-10 minutes to remove

pigments from the ground plant and leafy fragments. The material then was put in a

microwave for 15 to 20 seconds and left standing for another 5 minutes with occasional

agitation. Plant fragments were flushed thoroughly with water using a 100-mesh sieve,

placed in a 1 dram vile and passed through the following series in 20 minute time

intervals before mounting;

39 Step 1. 50% water / 50% alcohol,

Step 2. 100% alcohol,

Step 3. 50% alcohol / 50% xylene,

Step 4. 100% xylene.

During this process, plant fragments were dehydrated in alcohol to facilitate the uptake of xylene. Additionally, xylene is miscible with Permount mounting media to provide for a long lasting, clear specimen mount. My training for quantifying herbivore diets from fragmented range plants was completed in 3 phases according to the procedures described by Holechek and Gross (1982a). Complete descriptions and drawings of plant fragment characteristics were prepared to aid in identification. A taxonomic style key based on each plant species anatomical characteristics also was developed to further assist in the accurate identification of fragments through diagnostic features.

STATISTICAL ANALYSIS

I estimated botanical diet compositions for deer from each pellet group collected,

based upon plant fragment frequency, subsequent conversion to relative density, and final

expression as percent dry weight of the total sample (Fracker and Brischle 1944, Sparks

and Malechek 1968). The percent dry weight of each plant species from individual pellet

groups then was averaged (±SE) across all fecal samples for northern and southern deer

within a given season to provide estimates of forage consumption and diet composition.

Diet similarity between populations of deer was determined using Kulczynski's

Similarity Index (SI) (Oosting 1956). Spearman’s rank-order correlation coefficient

(Siegel and Castellan 1988) also was used to detect where the degree of diet similarity

40 among shared plant species was significantly associated among native and translocated deer. Plants were ranked in ascending order based on the total percent dry weight each comprised in the diet, with the most consumed forage species being assigned a rank of 1.

Ties in data also were taken into account to ensure equal importance of plant species having identical percent dry weight values in the diet. Knowing apriori that a deer’s diet changes over all seasons, I used Chi-Square goodness of fit tests with a Bonferroni adjustment to compare the frequency of occurrence of identified forages selected per fecal sample by native and translocated deer within each season. However, to ensure that the distribution of the test statistic was approximately x 2, plant species had to occur a

minimum of 6 times among all 60 fecal samples for a given season (Freund and Wilson

1997).

I performed paired /-tests (Steel and Torrie 1980:102) using SAS (SAS Institute

Inc. 1990) to determine whether plant diversity per fecal group during a given season

varied significantly between southern and northern white-tailed deer. In addition, 1

analyzed fecal crude protein data using paired /-tests to determine if diet quality differed

significantly between native and translocated deer within each season. Statistical

significance was accepted at the 0.05 level of probability of a Type I error, unless

otherwise noted.

41 RESULTS

DIET COMPOSITION

Botanical compositions of diets indicated that native and translocated deer fed on a seasonal high of 49 and 46 plants during spring and a seasonal low of 20 and 19 plants during winter, respectively (Table 1). A decrease in consumption of shared forages also was evident as the year progressed, with an average of 42, 38, 31, and 19 plant species being ingested by both populations during spring, summer, fall, and winter seasons, respectively. On average, 85.47% of the diet was identified for southern deer, with dry weights of plants ranging from 0.06 to 36.99%, whereas 86.57% of all plant fragments were identified for northern deer, with dry weights fluctuating from 0.06 to 38.86% of the average diet during the entire year. Both populations of deer primarily were grazers

during the spring and summer seasons, with forbs accounting for 57.44 and 69.93% of

native deer diets and 61.12 and 77.02% of northern deer diets, respectively. Conversely,

deer primarily were browsers during the fall months, with woody browse/fruit comprising

50.22 and 47.81% of respective diets. Winter provided for the only deviation in foraging

behavior among deer populations, with native deer being primarily grazers, while

northern deer slightly favored browsing over grazing, albeit only by 1.09% on a dry

weight basis. On average, diets of native deer consisted of more grass and grass-like

species, whereas translocated deer ingested a greater percentage of forbs and woody

browse/fruit during the study period. Similarity in forage selection was also evident

among deer, with Rubus spp., Glycine max, Quercus spp., and Lolium multiflorum

42 Table 1. Estimated botanical compositions (% dry weight ± standard error) of fecal pellets from Native, Southern and Translocated, Northern white-tailed deer on Golden Ranch Hunting Farm, Gheens, Louisiana, during Spring, Summer, Fall, and Winter 1997, (n-30/population/season). Spring Summer Fall Winter

Southern Northern Southern Northern Southern Northern Southern Northern

Plant taxa % SE % SE % SE % SE % SE % SE % SE % SE

Grass and Grass-likes:

Arundinaria spp. 0.36 0.25 — — 0.14 0.14 — — — — — — — — — —

Bromus uniolodes 0.43 0.32 0.27 0.20 — — — — — — 0.13 0.13 — — — —

Echinocloa spp. 0.62 0.22 1.05 0.31 0.62 0.30 — — — — — — — — — —

Lolium multiflorum — — — — — — — — 0.73 0.24 0.25 0.15 36.99 1.47 33.32 1.60

Lolium perenne 1.37 0.43 0.79 0.26 0.18 0.10 — — — — — — — — — —

Panicum spp. 10.56 1.27 9.75 1.01 9.31 1.16 4.48 0.72 4.07 0.65 3.51 0.57 0.41 0.22 0.62 0.21

Paspalum spp. 0.84 0.37 0.19 0.14 0.22 0.16 0.29 0.20 0.69 0.34 0.65 0.40 — — — —

Pennisetum spp. 0.17 0.12 0.28 0.14 0.33 0.23 0.39 0.18 — — — — — — — —

Triticum aestivum — — — — — — — — — — — — 1.88 0.45 1.54 0.37

Total Grass and Grass-likes: 14J5 12J3 10.80 5.16 5.49 4.54 39.28 35.48

Forbs:

— — Acmella spp. 1.23 0.42 0.45 023 — — — — — — — — — —

Altemathera philoxeroides — — 0.27 0.14 — — — — 0.13 0.09 0.06 0.06 0.12 008 0.06 004

Ambrosia spp 1.08 0.36 2.60 0.48 1.15 0.26 0.92 030 — — 0.51 0.23 — — — —

Ampelopsis spp 1.14 035 1.01 0.25 0.09 0.09 0.10 0.10 — — — — — — — —

Aster spp 0.49 0.21 2.03 045 0.93 0.30 0.58 0.24 1.53 0 51 2.99 061 — — — — Table 1. cont’d.

Spring Summer Fall Winter

Southern Northern Southern Northern Southern Northern Southern Northern

Plant taxa % SE % SE % SE % SE % SE % SE % SE % SE

Berchemia scandens 0.38 0.18 1.37 0.27 0.25 0.13 0.16 0.11 1.49 0.38 0.50 0.16 0.90 0.20 1.27 0.23

Brunnichia spp. 0.09 0.07 — — — — — — — — — — — — — —

Campis radicans 0.50 0.20 0.19 0.13 0.12 0.09 0.20 0.11 — — — — — — — —

Chamaecrista fasciculata 1.65 0.32 0.38 0.17 2.06 0.37 1.10 0.28 3.17 0.52 3.10 0.48 1.27 0.38 1.35 0.35

Desmodium spp. 0.09 0.07 — — — — — — — — 0.10 0.10 — — — —

Eupatorium spp. 2.97 0.50 2.11 0.53 2.53 0.49 2.99 0.73 2.90 0.57 2.72 0.50 — — — —

Glycine max — — — — 33.93 3.12 38.86 3.71 — — — — — — — —

Hibiscus lasiocarpos 1.33 0.37 1.06 0.31 2.45 0.54 1.71 0.38 1.49 0.34 1 68 046 — — — —

Hypericum spp. 3.34 0.46 3.45 0.49 1.71 0.33 2.31 0.47 1.52 041 2.55 0.42 — — — —

Ipomea spp. 0.30 0.16 — — — — — — — — — — — — — —

Iva annua — — — — — — 0.72 0.28 0.50 0.27 0.28 0.20 — — — —

Liatris spp. 2.18 0.44 2.72 0.44 2.20 0.46 2.78 0.64 3.24 0.46 3.27 0.48 1.17 0.37 1.14 0.53

Ludwigia spp. 1.27 0.30 0.55 0.24 0.97 0.29 1.66 0.41 3.45 0.45 4.59 0.55 0.34 0.15 0.50 0.23

Medicago lupulina — — — — — — 0.15 0.10 — — — — — — — —

Nymphea odorata 0.29 0.17 0.37 0.13 — — — — — — — — — — — —

Oenothera spp. 0.09 0.09 — — — — — — — — — — — — — —

Oxalis stricta 0.71 0.24 0.63 0.25 1.22 0.35 0.99 0.36 — — — — — — — —

Passiflora spp. 0.90 0.24 1.03 0.32 0.08 0.08 — — — — — — — — — —

Phytolacca americana — — 0.06 0.06 — — — — — — — — — — — — Table 1. cont’d.

Spring Summer Fall Winter

Southern Northern Southern Northern Southern Northern Southern Northern

Plant taxa % SE % SE % SE % SE % SE % SE % SE % SE

Pluchea spp. 0.50 0.21 1.35 0.35 0.63 0.24 0.60 0.29 — — — — — — — —

Rhynchosia spp 0.88 0.36 1.52 0.38 0.24 0.15 0.43 0.26 — — — — — — — —

Rubus spp. 19.79 1.30 20.09 1.13 0.90 0.35 1.00 0.40 — — — — — — — —

Rudbeckia hirta 0.27 0.16 — — — — — — — — — — — — — —

Smilax spp. 0.18 0.15 0.12 0.07 0.45 0.22 0.21 0.10 0.96 0.26 0.81 0.23 5.18 1.06 5.41 0.73

Sohdago spp. 2.76 0.58 2.92 0.45 2 92 0.44 2.23 0.52 1.20 0.32 2.46 0.55 — — — —

Toxicodendron radicans 0.09 0.07 0.15 0.11 0.31 0.12 0.39 0.17 0.20 0.15 0.35 0.18 — — — —

Trifolium spp. 6.61 0.93 8.07 0.68 8.16 0.65 7.89 0.69 — — — — 4.34 0.47 4.77 0.68

Verbena brasiliensis 0.81 0.36 0.86 0.31 2.91 0.53 4.12 0.70 3.30 0.66 3.00 0.74 — — — —

Verbesina virginica — — — — 0.22 0.14 0.40 0.15 0.65 0.22 0.95 0.27 — — — —

liburnum spp 006 0.06 0.37 0.18 0.43 0.18 0.23 0.12 0.87 0.27 0.56 0.25 0.79 028 0.27 0.16

Vigna lute olo 4.52 0.54 5.33 0.56 2.90 062 3.84 058 4.71 0.52 4.79 0.56 — — — —

Vitis rotundifoha 094 026 006 006 0 17 0.10 0.45 0 19 — — 0.28 0.17 — — — —

Total Forbs: 57.44 61.12 69.93 77.02 3 IJ 1 35.55 14.11 14.77

Woody Browse/Fruit:

Acer spp — — 052 025 0 15 0 12 — — — — 009 009 — — — —

Bacchant haltmtfoha 030 0 13 0 12 007 0 36 0 16 023 O il 4 07 0 53 635 0 65 4.25 049 5.92 078

Celt a laevigata 087 026 0 58 024 037 0 17 063 0.20 0.67 022 1 30 039 0.35 0 18 1 09 038 Table 1. cont’d.

Spring Summer Fall Winter

Southern Northern Southern Northern Southern Northern Southern Northern

Plant taxa % SE % SE % SE % SE % SE % SE % SE % SE

Cephalanthus occidentalis 0.49 0.30 0.51 0.22 0.46 0.20 0.45 0.20 — —

Cornus spp. 1.39 0.52 0.70 0.32 0.20 0.12 0.39 0.17 0.15 0.11 0.63 0.29 0.03 0.03

Diospyros virginiana 0.40 0.17 0.26 0.15

Illex spp. 0.59 0.24 0.49 0.18 1.67 0.35 1.01 0.23 10.30 0.73 7.07 0.73 8.69 0.59 10.80 0.81

Liquidambar styraciflua 0.74 0.24 0.59 0.21 0.31 0.18 0.20 0.11 0.19 0.13 0.16 0.11

Myrica cerifera 0.54 0.17 0.30 0.13 0.84 0.23 0.42 0.13 8.65 0.66 4.83 0.62 13.03 0.80 11.93 0.62

Nyssa sylvatica 0.85 0.27 1.27 0.38 ov Quercus spp. 23.93 2.30 24.12 1.76 2.49 0.64 1.86 0.46

Salix nigra 0.15 0.11 0.40 0.18 0.47 0.18 0.38 0.15 0.43 0.18 0.38 0.17 2.45 0.43 2.46 0.32

Sambucus canadensis 0.06 0.06 — — 0.29 0.16 — —

Sida rhombifolia 1.57 0.51 2.50 0.63 2.76 0.59 3.88 0.83 1.09 0.33 2.24 0.71 1.25 0.50 1.05 0.37

Ulmas alata — — 0.15 0.11 0.06 0.06 0.22 0.17 0.34 0.14 0.38 0.20 0.92 0.40 1.46 0.40

Total Woody Browse/Fruit: 7.55 8.13 7.94 7.81 50.22 47.81 33.46 36.57

Total Unidentifieds: 20.67 18.38 1132 10.03 12.97 12.12 13.15 13.18

Grand Total: 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 being ingested in the greatest quantities by both populations of deer during spring, summer, fall, and winter, respectively.

Diets of native versus northern deer were significantly associated during spring

(rs = 0.71, P < 0.00001), summer (rs = 0.90, P < 0.00001), fall (rs = 0.88. P < 0.00001),

and winter (rs = 0.96, P < 0.00001), indicating that both populations of deer selected

similar forages in like proportions. Moreover, native and translocated deer consumed a

total of 4, 11,3, and 5 plant species in like frequencies during the spring, summer, fall,

and winter, respectively (Table 2). However, of 23 forages selected similarly among

deer, only Rubus spp. during spring, and Lolium multiflorum, Illex spp., and Myrica

cerifera during winter, were identified in 100% of all fecal samples. Few significant

differences were found in the frequency of occurrence of plants selected by southern

versus northern deer. But, a marginal difference was detected (P < 0.001) in the use of

Berchemia scandens (P = 0.001) and Vitis rotundifolia (P = 0.001) during the spring

season. However, rattan vine and muscadine only made up 0.38±0.18 and 0.94±0.26% of

southern deer diets, and 1,37±0.27 and 0.06±0.06% of the average northern deer diet.

Moreover, Berchemia scandens and Vitis rotundifolia were only found in 37 and 20% of

all fecal samples during spring, respectively. Diet similarity averaged 87.65% among

populations of deer over the entire study period, and ranged from a low of 85.1% during

spring, to a high of 92.4% during the winter months, indicating that the two populations

of deer generally fed on similar forages during all seasons (Table 3).

47 Table 2. Chi-Square analyses using a = 0.05 w/ Bonferroni adjustment, for frequency of occurrence of shared plants identified in fecal pellets from Native, Southern and Translocated, Northern white-tailed deer during Spring (x2 = 10.32, a = 0.001, 1 df), Summer (jf = 10.27, a = 0.001, 1 df), Fall (x2 = 9.89, a = 0.002, 1 df), and Winter (jf = 8.94, a = 0.003, 1 df), on Golden

Spring Summer Fall Winter

Frequency Frequency Frequency- Frequency-

Plant Species (Taxa) Southern Northern x2 Southern Northern x2 Southern Northern x2 Southern Northern X2

Grass and Grass-likes:

Echinocloa spp. 7 10 0.74 6 0 6.67 — — — — — —

Lolium multiflorum — — — — — — 8 3 2.78 30 30 0.00

Lolium perenne 10 8 0.32 — — — — — — — — —

Panicum spp. 25 28 1.46 27 23 1.92 23 19 1.27 4 8 1.67

Paspalum spp. 5 2 1.46 — — — 4 4 0.00 — — —

Pennisetum spp. 2 4 0.74 2 5 1.46 — — — — — —

Triticum aestivum — — — — — — — — — 12 15 0.61

Forbs:

Acmella spp. 8 4 1.67 — — — — — — — — —

Ambrosia spp. 8 18 6.79 14 10 1.11 0 6 6.67 — — —

— — Ampelopsis spp 10 13 0.63 — — — — — — —

Aster spp. 5 14 6.24 9 6 0.80 8 16 4.44 — — —

Berchemia scandens 5 17 1034 4 2 0.74 14 9 1.76 15 17 0.27

— Campis radicans 6 2 231 2 4 0.74 — — — — —

Chamaecrista fasciculata 17 6 833 18 13 1.67 22 20 032 11 13 0.28 Table 2. cont’d.

Spring Summer Fall Winter

Frequency Frequency Frequency Frequency

Plant Species (Taxa) Southern Northern X2 Southern Northern x2 Southern Northern X1 Southern Northern

Eupatorium spp. 21 14 3.36 17 14 0.60 20 18 0.29 — — —

Glycine max — — — 30 28 2.07 — — — — — —

Hibiscus lasiocarpos 11 11 0.00 15 15 0.00 14 11 0.62 — — —

Hypericum spp. 24 22 0.37 16 16 0.00 11 19 4.27 — — —

Iva annua — — — 0 6 6.67 4 2 0.74 — — —

Liatris spp. 19 20 0.07 16 14 0.27 22 20 0.32 11 8 0.69

Ludwigia spp. 16 6 7.18 12 16 1.07 23 25 0.42 6 6 0.00

Nymphea odorata 3 7 1.92 — — — — — — — — —

Oxalis stricta 8 7 0.09 10 7 0.74 — — — — — —

Passiflora spp. 11 10 0.07 — — — — — — — — —

Pluchea spp. 6 12 2.86 6 4 0.48 — — — — — —

Rhynchosia spp. 6 14 4.80 3 3 0.00 — — — — — —

Rubus spp. 30 30 0.00 7 6 0.10 — — — — — —

Smilax spp — — — 5 5 0.00 10 10 0.00 20 24 1.36

Solidago spp. 18 21 0.66 22 15 3.45 11 14 0.62 — — —

Toxicodendron radicans — — — 6 5 0.11 2 4 0.74 — — —

Trifolium spp. 22 27 2.78 30 29 1.02 — — — 25 25 0.00 — Verbena brasiliensis 5 7 0.42 18 20 0.29 17 14 0.60 — — l erbesina virginica — — — 3 6 1.18 8 10 0.32 — — — Table 2. cont’d.

Spring Summer Fall Winter

Frequency Frequency Frequency Frequency

Plant Species (Taxa) Southern Northern x2 Southern Northern z2 Southern Northern X2 Southern Northern X2

Viburnum spp. .... — — 6 4 0.48 9 6 0.80 8 3 2.78

Vigna luteola 26 27 0.16 15 20 1.71 25 24 0.11 — — —

Vitis rotundifolia 11 1 10.42 3 6 1.18 — — — — — —

Woody browse/fruit:

Baccharis halimifolia 6 3 1.18 5 5 0.00 23 27 1.92 25 23 0.42

Celtis laevigata 10 7 0.74 5 10 2.22 8 11 0.69 4 8 1.67

Cephalanthus occidentalis 3 6 1.18 5 5 0.00 — — — — — —

Cornus spp. 10 5 2.22 3 6 1.18 2 7 3.27 — — —

Diospyros virginiana — — — — — — 6 3 1.18 — — —

lllex spp. 7 7 0.00 15 15 0.00 29 26 1.96 30 30 0.00

Liquidambar styraciflua 8 8 0.00 3 3 0.00 — — — — — —

Myrica cerifera 9 5 1.49 12 9 0.66 29 24 4.04 30 30 0.00

Nyssa sylvatica 8 11 0.69 — — — — — — — — —

Quercus spp. — — — — — — 29 30 1.02 15 12 0.61

Salix nigra 2 5 1.46 6 6 0.00 5 5 0.00 18 22 1.20

Sida rhombfolia 10 13 0.63 15 15 0.00 9 13 1.15 9 8 0.08

Ulmas alata — — — — — — 6 4 0.48 6 12 2.86 Table 3. Percentage diet similarity, average number of identified plants (± standard error) per fecal group, and probability associated with Student’s /-test by season and population of deer on Golden Ranch Hunting Farm, Gheens, Louisiana, (n=30/population/scason).

Southern Deer Northern Deer

Season % Diet Similarity Avg. tt of Plants SE Avg. # of Plants SE Pr > t

Spring 85.1 18.80 0.29 19.73 0.24 0016

Summer 86.6 16.63 0.36 15.90 0.44 0.205

Fall 86.5 16.56 0.35 16.90 0.25 0.443

Winter 92.4 12.10 0.28 13.03 0.20 0.008

51 '

FORAGE DIVERSITY

On average, the number of forages identified per fecal sample ranged from a high

of 18.80±0.29 and 19.73±0.24 in spring to a low of 12.10±0.28 and 13.03±0.20 during

winter, for native and translocated deer, respectively (Table 3). The greatest diversity

in plant consumption occurred during summer, in which fecal pellets of native and

translocated deer contained 12 to 21 and 10 to 21 species per sample, respectively.

Conversely, the least variety in fecal samples occurred during winter, when fecal pellets

of both deer populations contained 10 to 15 plants per sample. Fecal samples from

southern and northern deer also contained the same diversity during spring and winter,

ranging from 16 to 22 and 10 to 15 species, respectively. Similarly, fecal pellets

contained the same variety of plant species per sample during fall, which ranged from 13

to 20 for southern deer and 14 to 21 for northern deer. Although the average number of

plants identified per fecal sample was similar during summer and fall among deer

populations, a significant difference was detected during spring (P = 0.016) and winter

(P = 0.008) because northern deer pellet groups contained 0.93 more plants on average

during each season.

FECAL CRUDE PROTEIN

Fecal crude protein levels for both populations of deer never fell below 16.5%

for any season during the study period, and were only significantly different during the

winter (P = 0.003) months (Table 4). Crude protein levels ranged from a high in the

spring of 18.99±0.33 and 19.16±0.28% to a low of 16.58±0.33 and 16.54±0.33% during

the fall, for native and translocated deer, respectively. Moreover, fecal pellets of southern

52 Table 4. Average crude protein content (% dry weight ± standard error) of deer fecal samples, and probability associated with Student’s ?-test by season and population of deer on Golden Ranch Hunting Farm, Gheens, Louisiana, (n=30/population/season). Southern Deer Northern Deer

Season Avg. % CP SE Avg. % CP si: I’r > I

Spring 18.99 0.33 19.16 0.28 0.704

Summer 17.25 0.32 17.33 0.39 0.876

Fall 16.58 0.33 16.54 0.33 0.941

Winter 18.01 0.28 16.63 0.35 0.003

53 deer contained more crude protein on average during fall and winter seasons, whereas northern deer had higher levels during the spring and summer months. Southern deer fecal groups also ranged from a maximum crude protein level of 22.49% during fall, to a low of 12.46% during spring, whereas translocated deer ranged from a high of 23.0% crude protein during spring, to a low of 12.44% during winter.

54 DISCUSSION

NATIVE VS. TRANSLOCATED DEER

Diet Composition

I identified few differences in plant selection among deer populations at Golden

Ranch Hunting Farm. In fact, significant differences in the frequency of occurrence of

plants within fecal pellets were marginal, and only detected for Berchemia scandens and

Vitis rotundifolia during the spring season. However, it is important to note that these

species represented less than 2% of the overall diet for both populations of deer,

suggesting they were of little biological importance. To date, O'Bryan (1983) has

conducted the only other study which has documented food habits of intraspecific species

after translocation of one population. Similar to results from this study, O'Bryan

demonstrated that proportions of browse, grass, and forbs found in the diets of

translocated black-tailed deer were similar to those reported for the resident population

(Longhurst et al. 1979). Additionally, O’Bryan conducted observations of deer while

feeding, which strengthened this inference that the diet of relocated deer was similar to

that of native animals. Results from O’Bryan and my study suggest that translocated

populations of deer may have a predisposition to select diets similar to those of native

animals, even when relocated and confronted with entirely new foraging habitat. It has

been suggested that learning may play a vital role in influencing diet choice by

herbivores, and that animals deprived of physical interaction, or opportunities to learn

food selection habits may exhibit significantly different foraging behaviors (Provenza

and Balph 1987, Mirza and Provena 1990,1994). It is not known how long it takes for

55 translocated deer to learn to select the best diets on foreign range. However, Spalingcr et al. (1997) suggest that foraging behavior in white-tailed deer is largely an innate behavior.

Forage Diversity

I found that plant diversity (ie., the number of plants identified per fecal sample)

differed between populations of deer during spring and winter. However, this difference

only averaged 0.93 plants during both seasons. Although statistically significant, these

results are likely not biologically important because differences were attributed to less

than a single plant species per season. It is possible that this variation in plant diversity

among deer during spring and winter resulted from technician bias, but any existing bias

should have been similarly distributed among native and translocated deer diets. Thus,

a more acceptable hypothesis is that the average differences in the number of forages

identified per fecal sample simply resulted from variations in plant species availability

within home ranges of the deer sampled.

Fecal Crude Protein

The last significant finding among southern and northern deer occurred in fecal

crude protein levels during winter. However, this difference was only 1.38% and was

likely attributed to variation in the amount of ryegrass consumed by each population

of deer. During winter, southern deer consumed an average of 3.8% more Lolium

multiflorum on a dry weight basis than northern deer. Moreover, Johnson et al. (1987)

reported mean CP levels of ryegrass to be 20±2.0% for an upland forested site in

southeastern Louisiana. Although geographically different from my study site, this

56 reported CP level of ryegrass can be used as an estimate, and suggests that the greater

proportion of ryegrass ingested by southern deer probably caused the minor difference in

fecal crude protein levels.

NATIVE AND TRANSLOCATED DEER

Diet Composition

1 identified 61 forage species during the study, which is most consistent with

Arnold and Drawe (1979) and Keegan et al. (1989), who identified a total of 69 and 51

plant taxa in the diets of white-tailed deer, respectively. Conversely, my results differed

from Healy (1971) and Martinez et al. (1997) in which deer ingested fewer taxa. totaling

36 and 46, respectively. 1 found that southern and northern deer consumed a total of 37

forbs, 15 browse species, and 9 graminoids over all seasons. This pattern of forage class

consumption is similar to Martinez et al. (1997), who reported that deer in Mexico

consumed a total of 20 forbs, 19 shrubs/browse species, and 9 grasses. Likewise, total

forage class consumption by deer in south Texas was comparable, with diets being

comprised of 34 forbs, 32 browse species, and 1 grass (Arnold and Drawe 1979).

Although native and translocated deer foraged similarly when compared to other deer

herds, differences in habitat type, plant associations, land use, and density of deer

certainly account for much of the variation when reporting total number of forage species

selected by deer (Korschgen 1962).

On average, I identified 85.47 and 86.57% of diets for southern and northern deer

respectively, which is similar to reports from Arnold and Drawe (1979). They estimated

the food habits of white-tailed deer in south Texas, and found that 88.8% of the diet was

57

L recognizable with 11.3% being comprised of unidentified material. Analogous to past research, southern and northern deer also consumed the greatest number of plant species during the spring (Everitt and Drawe 1974, Arnold and Drawe 1979, Everitt and

Gonzalez 1981), presumably because forages are succulent, highly digestible, and have higher nutritive values than during any other season (Church 1975, Varner et al. 1977,

Vangilder et al. 1982, Meyer et al. 1984). As expected, there was a decrease in numbers

of plants utilized after spring, which continued through winter for both populations of

deer, most likely due to changes in forage availability, subsequent phenological stages,

and decreased nutritive values of remaining plants (Gallina 1993).

Deer on Golden Ranch Hunting Farm relied most heavily on forbs (43.20 and

47.12% annually), and less heavily on browse (24.79 and 25.08%), while graminoids

made up the smallest forage class consumed (17.48 and 14.38%) for southern and

northern deer, respectively. However, this trend of consumption is different from several

previous studies, in which deer diets were comprised of mostly browse, less forbs, and

least of grasses (Arnold and Drawe 1979, Martinez et al. 1997). Moreover, although deer

at Golden Ranch ingested forbs in the greatest quantities during the year, Coblentz (1970)

found that browse was the major forage class consumed by George Reserve deer in

Michigan. Likewise, Davis (1952) reported that browse comprised the major portion of

the deer’s diet in south Texas. However, total browse consumption by native and

translocated deer was similar to Short (1971), who reported 19% browse use by deer in

east Texas. Moreover, Martinez et al. (1997) reported grass consumption by deer in

Mexico to be 12% of the average diet, only slightly less than that ingested by deer on

58 Golden Ranch. Variation in available range plants and annual progression of plant growth most likely are causative factors for differences in relative importance and total

amount of each forage class consumed between my study and that of others (Davis 1952).

Previous literature on foraging behavior (ie., grazing vs. browsing) of deer during

different seasons is abundant, but has reported mixed results. Davis (1952) and Goodrum

and Reid (1954) reported that deer in the South and Southwest primarily are browsing

animals except during late winter and early spring when there is an increase in the

utilization of forbs and grasses. Likewise, Coblentz (1970) reported that deer on the

George Reserve primarily were browsers and Lay (1969) stated that field observations

of deer range revealed more sign of browse use by deer than any other forage class.

Conversely, deer from the Welder Refuge in Texas were reported to be primarily grazers

rather than browsers during all seasons (Chamrad and Box 1968. Drawe 1968). Forage

consumption patterns of deer on Golden Ranch seemed to be just as variable as those

previously reported, with deer being primarily grazers during the spring and summer

(Davis 1951, Meyer et al. 1984), browsers during fall (Warren and Krysl 1983), and both

grazers and browsers during winter. However, some similarities in foraging behavior

were evident among deer populations. Southern and northern deer consumed mostly

grass during winter and spring (Chamrad and Box 1968, Kie et al. 1980), with the highest

values recorded during winter (Drawe and Box 1968). Moreover, forb consumption

dropped to its lowest point during fall and winter seasons for both populations of deer, as

it did for whitetails in south Texas (Arnold and Drawe 1979). The difference in forage

class consumption by deer during winter is attributed to the fact that southern deer

59 consumed greater amounts of supplemental forage, Lolium multiflorum. In fact, had this cool-season grass not been available to deer, and the diets of deer had proportionately increased based on estimated values, browse would have dominated both diets during winter, with Myrica cerifera and Illex spp. being ingested in the greatest quantities.

When available, deer utilize agronomic and supplemental forage species to a high degree (Korschgen 1962, Flyger and Thoerig 1965, Nixon et al. 1970, Hartman 1972,

DeLany 1985, Dancak 1990), and foraging behavior by native and translocated deer on

Golden Ranch did not deviate from this premise. Soybeans and ryegrass represented

36.40 and 35.16% of average deer diets during the summer and winter, and were found in

97 and 100% of all fecal groups, respectively. In related research, Keegan et al. (1989),

reported that American jointvetch comprised 32% of summer-fall diets for deer, while

being identified in an average of 90.7% of all fecal samples. Similarly, Johnson et al.

(1987) found that food plot forages comprised about 19.47% of deer diets, and occurred

in 90 tol00% of fecal samples during consecutive winters for free-ranging deer in

southeastern Louisiana. Moreover, Sowell et al. (1985) demonstrated that mule deer in

the Texas Panhandle used substantial amounts of wheat and ryegrass when available,

comprising 27% of winter diets. Although results are similar, percent dry weight totals

for agronomic and supplemental forages are consistently higher than reported elsewhere.

This high utilization of soybeans and ryegrass by both populations of deer is likely due to

several factors including high deer densities, and low native forage availability and poor

nutrition during these seasons. Based on a Forward-Looking Infrared (FLIR) census

in 1997, deer densities on the study area were estimated to be 0.28 (±0.05) deer/ha

60 (Day 1998), and still increasing because of over conservative doe harvests. Moreover, because of this high deer density, a distinct 4 to 5 ft browse line had developed through much of the forested habitat, thus forcing deer to concentrate on agronomic forages due to decreases in native forage availability. These introduced forages also are highly palatable and nutritious for deer, whereas most native forages available during summer and winter are mature forbs, grasses, or woody twigs that are high in fiber content and low in

nutrient concentrations, creating nutritional stress for the animals (Short 1975). However,

when compared, summer may be the most nutritionally stressful period in the South,

because of heat, low forage quality, and reduced forage intake (Goodrum and Reid 1962.

Ockenfels and Bissonette 1982, Blair et al. 1984).

Fecal Crude Protein

Several factors have been implicated for causing difficulties when using fecal

nitrogen as an index to dietary quality including seasonal changes in digestibility of

forages (Greenhalgh et al. 1960, Minson and Kemp 1961, Holloway et al. 1981) and

protein-complexing properties of phenolics and other secondary metabolites in plants

(McLeod 1974) that may elevate FN irrespective of DN (Mould and Robbins 1981).

Yet, many researchers have still reported a close relationship to exist between dietary

nitrogen and fecal nitrogen (Raymond 1948, Hinnant 1979, Leslie and Starkey 1985,

Mubanga et al. 1985). Based on this established association of FN to DN, fecal crude

protein levels suggest that southern and northern deer diets were of similar quality during

all seasons of the year.

61 MANAGEMENT IMPLICATIONS

The most striking result of my study is the marked similarity between southern and northern deer in diet compositions, diet diversity, and apparent diet quality during all seasons of the year. My results suggest that translocated deer, even when placed in a new environment, have the predisposition to select similar diets to that of native deer populations (O’Bryan 1983). My results also are consistent with prior evidence that

suggests foraging behavior by deer is largely an innate behavior (Spalinger et al. 1997).

These similarities in diet are even more surprising when you consider the fact that during

the entire study period there were no observed interactions between native and

translocated deer at any time and distinct social groups seemed prominent, even though

deer were sympatric with one another (Day 1998). Thus, contradictory to previous

reports (Provenza and Balph 1987, Mirza and Provena 1990, 1994), physical interaction

may play only a small role in influencing diet selection by herbivores (Olson-Rutz and

Umess 1987, Spalinger et al. 1997).

Currently, many landowners are translocating northern deer into native

populations in hopes of enhancing genetics for antler growth (McCall et al. 1988).

However, landowners must fully understand the potential consequences of such an act on

range condition and biological parameters of residential populations. Results from my

study suggest that a high degree of intraspecific competition for food resources may

occur because diets among native and translocated deer were highly similar. Therefore,

serious thought must be given when translocating animals into a residential deer

population because this intraspecific competition will affect overall forage availability

62 and nutrition, and possibly prevent northern deer from attaining the nutrition needed to express their genetic potential in terms of growth. Thus, landowners must prioritize their management objectives, and realize that eagerness for superior deer may in fact produce deer of lower quality due to higher deer densities and intraspecific competition for food resources. Although results from my study are promising in that northern deer showed high similarities in dietary habits to that of their southern counterpart, long-term survival

and performance of translocated northern deer in southern habitat has yet to be

determined.

63 LITERATURE CITED

Adams, L. 1957. A way to analyze herbivore food habits by fecal examination. Trans. N. Amer. Wildl. Conf. 22:152-159.

Anthony, R. G., and N. S. Smith. 1974. Comparison of rumen and fecal analysis to describe deer diets. J. Wildl. Manage. 38:535-540.

Arman, P., D. Hopcraft, and I. McDonald. 1975. Nutritional studies on East African herbivores. 2. Losses of nitrogen in the faeces. Br. J. Nutr. 33:265-276.

Arnold, G. W., and M. L. Dudzinski. 1963. The use of faecal nitrogen as an index for estimating the consumption of herbage by grazing animals. J. Agric. Sci. 61: 33-43.

Arnold, L. A. Jr., and D. L. Drawe. 1979. Seasonal food habits of white-tailed deer in the South Texas Plains. J. Range Manage. 32:175-178.

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Atwood, E. L. 1941. White-tailed deer foods of the United States. J. Wildl. Manage. 5:314-332.

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Belonje, P. C., and A. Van Den Berg. 1980a. The use of fecal analysis to estimate the phosphorus intake by grazing sheep. I. The use of pool instead of individual samples. Onderstepoort J. Vet. Res. 47:163-167.

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Blair, R. M., and L. K. Halls. 1968. Growth and forage quality of four southern browse species. Proc. Ann. Conf. Southeast. Assoc. Game and Fish Comm. 21:57-62.

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77 APPENDIX

78 Table 5. List of scientific and corresponding common names for plant taxa identified in fecal samples of Native, Southern and Translocated, Northern white-tailed deer during 1997, on Golden Ranch Hunting Farm, Gheens, Louisiana.______Plant Species (Taxa)

Scientific Name' Common Name

Grass and Grass-likes:

Arundinaria spp. Cane

Bromus uniolodes Rescuegrass

Echinocloa spp. Bamyardgrass

Lolium multiflorum Ryegrass

Lolium perenne Perennial Ryegrass

Panicum spp. Panic Grass

Paspalum spp. Paspalum

Pennisetum spp. Millet

Triticum aestivum Wheat

Forbs:

Acmella spp. Spotflower

Alternathera philoxeroides Alligatorweed

Ambrosia spp. Ragweed

Ampelopsis spp. Pepper Vine

Aster spp. Aster

Berchemia scandens Rattan Vine

Brunnichia spp. Eardrop Vine

Campis radicans Trumpet Creeper

Chamaecrista fasciculata Sleepingplant

Desmodium spp. Ticktrefoil

Eupatorium spp. Boneset

Glycine max Soybeans

Hibiscus lasiocarpos Rosemallow

79 Table 5. cont’d.

Plant Species (Taxa)

Scientific Name' Common Name

Hypericum spp. St. Johns Wort

Ipomea spp. Morning Glory

Iva annua Sumpweed

Liatris spp. Blazing Star

Ludwigia spp. Waterprimrose

Medicago lupulina Black Medic

Nymphea odorata White Waterlily

Oenothera spp. Eveningprimrose

Oxalis stricta Yellow Lady sorrel

Passiflora spp. Passionflower

Phytolacca americana Pokeweek

Pluchea spp. Fleabane

Rhynchosia spp. Snoutbean

Rubus spp. Blackberry

Rudbeckia hirta Black-eyed Susan

Smilax spp.2 Greenbriar

Solidago spp. Goldenrod

Toxicodendron radicans Poisen Ivy

Trifolium spp. Clover

Verbena brasiliensis Brazilian Vervain

Verbesina virginica White Crown-beard

Viburnum spp. Arrow-Wood

Vigna luteola Marsh Cowpea

Vitis rotundifolia Muscadine

80 Table 5. cont’d.

Plant Species (Taxa)

Scientific Name1 2 Common Name

Woody Browse/Fruit:

Acer spp. Maple, Box Elder

Baccharis halimifolia Saltbush

Celtis laevigata Southern Hackbcrry

Cephalanthus occidentalis Buttonbush

Cornus spp. Dogwood

Diospyros virginiana Persimmon

Illex spp. Deciduous Holly. Yaupon

Liquidambar styraciflua Sweetgum

Myrica cerifera Waxmyrtlc

Nyssa sylvatica Blackgum

Quercus spp. Oak

Salix nigra Black Willow

Sambucus canadensis Elderberry

Sida rhombifolia Teaweed

Ulmas alata Winged Elm 1 Scientific and common names follow Thomas and Allen (1993. 1996. 1998) unless otherwise noted. 2 Scientific and common names follow Radford et al. (1968).

81 VITA

Brian Matthew Zielinski was bom on December 30, 1973. in Rhinebeck. New

York, to Ronald W. and Susan H. Zielinski. He attended Highland Elementary School, and eventually graduated from Highland High School, Highland. New York, in 1992.

In August of 1992, he began his collegiate career at the State University of New

York at Plattsburgh. Four short years later in May of 1996, he graduated cum U/iuJc with a bachelor of arts degree in Environmental Science and decided to pursue a master' s program in Wildlife Science.

In August of 1996, he married his wife Nikole L. Zielinski, and together they ventured to Graduate School at Louisiana State University and Agricultural and

Mechanical College in Baton Rouge, Louisiana. While working on his thesis, he was employed as a GIS assistant for the CADG1S Lab, Louisiana State University, and in

January of 1998, he began working for the Louisiana Department of Natural Resources in

Baton Rouge, as a Natural Resource Specialist. He is presently a candidate for the degree of Master of Science in wildlife.

82 MASTER'S EXAMINATION AND THESIS REPORT

Candidate: Brian Matthew Zielinski

Major Field: Wildlife

^itle of Thesis: Diet Overlap of Native and Translocated Northern White-tailed Deer in Southeastern Louisiana

Approved:

Date of Examination:

3-30-99