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PREFERENCES AND HARVEST INTENTIONS OF HUNTERS IN
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PREFERENCES AND HARVEST INTENTIONS OF HUNTERS IN MICHIGAN
AND THEIR EFFECTS ON WHITE-TAILED DEER HARVEST OUTCOMES

By

Elizabeth Lauren Ball

A THESIS

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

MASTER OF SCIENCE

Fisheries and Wildlife

2008

ABSTRACT

PREFERENCES AND HARVEST INTENTIONS OF HUNTERS IN MICHIGAN
AND THEIR EFFECTS ON WHITE-TAILED DEER HARVEST OUTCOMES

By

Elizabeth Lauren Ball

The selective harvesting of Michigan’s white-tailed deer (Odocoileus virginianus)
represents a potential concern for deer hunting constituents and the state’s management
agency. This study investigated hunters’ preferences for deer characteristics based on
three conceptualized buck categories (ideal, preferred and least preferred) and the
hunters’ intentions to be selective based on 2,628 responses to a mail survey. Hunters
surveyed preferred 7 to 10 antler points, 16 to 20” spread and 2 l/2-year-old antlered deer.
The majority (60%) of bucks that were harvested, however, were yearlings that did not
exhibit those characteristics. Furthermore, 32% of respondents indicated that they
intended to harvest any legal buck and not wait to harvest a buck of a specific category. I
further examined how these hunters’ preferences and intentions to be selective were
linked to the outcome of their hunt by measuring eight morphological characteristics of
751 harvested antlered deer during the 2006 firearm season. Six antler dimensions and
two body size measurements were collected to determine hunter selectiveness for them.
The majority (61%) of the 751 bucks collected were harvested on opening day. Although
hunters have harvest preferences, these preferences are seldom reflected in actual

outcomes thereby reducing the potential for hunter-induced selection to occur.

ACKNOWLEDGEMENTS

I would first like to thank my major advisor, Dr. Andrew G. McAdam who
throughout my master’s degree work has provided me with the encouragement,
mentorship and inspiration to not only work hard, but to think hard. Thanks Andrew!

Not enough words of thanks can be given to my friends and family, especially my
mother, father, sister and brother. Their support and encouragement throughout the last
couple of years has lead to the success of this project. Also, hunting and hanging out on
the bay provided me with opportunities to keep my sanity during my graduate career. To
those individuals, thanks for the memories!

I would like to thank my funding sources. The Michigan Department of Natural
Resources (MDNR) devoted their time and energy to making this project a success! Field
and survey data collections would not have been possible without their support. I am
deeply indebted to the Michigan Department of Natural Resources for their collaboration
and help with this project. Their excellent work with collecting measurements on
harvested bucks at MDNR check stations during the fall of 2006 made the project a huge
success! Thanks also to Safari Club International, The Novi Chapter in helping to
support the project through monetary fimds. Thank You!

Thanks to the supervisor of the Saginaw Bay Wildlife Management Unit, Tim
Reis, and the wildlife biologists and check station field staff including but not limited to:
Richard Shellenbarger, Bruce Barlow, Adam Bump, Barry Sova, Arnie Carr, Dick
Robertson, Don Bonnette, Jim Horwath and Barb Avers. Also several individuals were

instrumental in the development of this project and administration of the mail survey:

iii

Brent Rudolph, Sarah Mayhew, Brian Frawley, Christine Larson, Mark Miller, Rod Clute
and Marshall Strong. Without their coordination, planning and assistance I am assured
my mail questionnaires would not have made it to a single mail box!

Many thanks of appreciation also goes out to the Michigan State University
student volunteers who helped collect field data at the MDNR check stations during fall
2006 and assisted with data entry: Dezi Elzinga, Joplin Marshall, Jennifer Pellegrini,
Annie Dyczko, Catherine Pociask, Christy Thomas, Dan Wieferich, Kristy Peterson,
Stephen Burr, Morgan Notestine, Nick Barr, Kaysie Cox and Laurissa Gulich. I am also
thankful for my fellow lab members, Adam Goble and Ryan Taylor who helped with
field preparations and data collections.

Not enough words of appreciation and thanks could be given to colleagues and
friends who were more than willing to offer technical assistance and provide me with
thought provoking conversations throughout the duration of this project: Dr. Ben Peyton,
Dr. Jeff Conner, Dr. Sandra Herman, Dr. Brian Maurer, Dr. Joe Arvai, Dr. Meredith
Gore, Dr. Rebecca Christoffel, Dr. Tim Hiller, Andrea Jaeger, Peter Bull, Anne Axel, Dr.
Ty Wagner, Melissa Mata, Lauri Das and Ben Dantzer. Your technical assistance, advice

and mentorship were instrumental to the completion of this research project.

iv

TABLE OF CONTENTS

LIST OF TABLES ................................................................................... vii
LIST OF FIGURES ................................................................................. viii
ORGANIZATION OF THESIS .................................................................... 1

CHAPTER 1: General Introduction

General Introduction .................................................................................... 3
Tables and figures ................................................................................... 12
References ............................................................................................. 13

CHAPTER 2: Data Collection Methodology

Data Collection Methodology ....................................................................... 17
Tables and figures ................................................................................... 27
References ............................................................................................. 28

CHAPTER 3: Hunter preferences for antlered white-tailed deer attributes and their

harvest intentions
Introduction ........................................................................................... 30
Methods ................................................................................................. 33
Results ................................................................................................... 37
Discussion .............................................................................................. 40
Tables and figures ..................................................................................... 44
References ............................................................................................. 51

CHAPTER 4: Predicting the harvest success of Michigan firearm deer hunters and the
attributes of their harvested deer

Introduction ............................................................................................ 55
Methods ................................................................................................. 60
Results .................................................................................................. 64
Discussion .............................................................................................. 67
Tables and figures .................................................................................... 71
References .............................................................................................. 84

CHAPTER 5: General Discussion

General Discussion .................................................................................... 89
Tables and figures ................................................................................... 93
References ............................................................................................. 94

APPENDICES

APPENDIX A: Focus Group Meeting Scnpt94
APPENDIX B: Focus Group Postcard Invitation ...................................... 104
APPENDIX C: Focus Group Meeting Participant Consent Form .................. 107
APPENDIX D: Focus Group Meeting Survey ......................................... 110

APPENDIX B: “What Buck Would You Choose? A Survey of Deer Hunter
Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Instrument and Percent
Response ................................................................. 113

APPENDIX F: “What Buck Would You Choose? A Survey of Deer Hunter
Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Cover Letter 1 .......................... 135

APPENDIX G: “What Buck Would You Choose? A Survey of Deer Hunter
Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Reminder Postcard ..................... 137

APPENDIX H: “What Buck Would You Choose? A Survey of Deer Hunter
Preferences and Decisions in the Saginaw Bay Wildlife

Management Unit” Survey Cover Letter 2 .......................... 139
APPENDIX 1: Field Collections Postcard ............................................. 141
APPENDIX J: Research Approval Letters ............................................ 144

vi

LIST OF TABLES

Table 3.1. Responses to demographic questions on the mail questionnaire ................. 45

Table 3.2. Median trait preferences for antlered deer characteristics by buck

category .................................................................................. 46
Table 3.3. General linear model results for preferences for an ideal bucks’ total

number of antler points ................................................................ 47
Table 3.4. Reported differences among each of the selectivity intention groups ........... 48
Table 3.5. Selectivity intention group preferences for ideal buck attributes ................ 49
Table 4.1. Logistic model results for predicting the harvest success of hunters ............ 76
Table 4.2. The number of deer harvested per hunting day by age classes ................... 77

Table 4.3. Comparison of harvest age structure between MSU and MDNR samples. . . ...78

Table 4.4. Age-specific measurements of eight morphological characteristics of
harvested white-tailed deer (Odocoileus virginianus) ............................. 79

Table 4.5. Factor loadings for the first and second principle components analyses of eight
morphological antlered deer traits ................................................... 80

Table 4.6. General linear model results for the trait characteristics of harvested
antlered deer in terms of PCI ......................................................... 81

Table 4.7. General linear model results for the trait characteristics of harvested
antlered deer in terms of PC2 ......................................................... 82

Table 5.1. Percentage of harvested bucks meeting or exceeding the median preferences
for each buck attribute ................................................................. 92

vii

LIST OF FIGURES

Figure 1.1. A map of Michigan designating the opportunity for selection values .......... 12
Figure 2.1. Illustration of eight morphological trait measurements ........................... 27
Figure 3.1. Bar graph depicting the intentions to be selective for harvest ................... 44

Figure 4.]. Box plot illustrating the difference between the centrality of hunting to one’s
lifestyle and harvest success ......................................................... 70

Figure 4.2. Box plot illustrating the difference between intentions to be selective and
harvest success ......................................................................... 71

Figure 4.3. Box plot illustrating the difference between the type of land hunted and
harvest success ......................................................................... 72

Figure 4.4. Box plot illustrating the difference between when a hunter started hunting and
harvest success ........................................................................ 73

Figure 4.5. Box plot displaying the interaction between the intention to be selective and
the number of years of hunting experience as influencing principal
component one ......................................................................... 74

Figure 4.6. Box plot illustrating the difference between when a hunter started
hunting and the PC2 trait characteristics ........................................... 75

viii

ORGANIZATION OF THESIS

This thesis is organized into five chapters. The first chapter presents a general
introduction to my study including relevant background information and study objectives.
Chapter 2 provides an outline of the general methodological procedures employed for this
study. The third chapter summarizes the results obtained from a survey of firearm deer
hunters in the Saginaw Bay region of Michigan. It quantifies harvest preferences and
selectivity intentions and presents results from models explaining variation in hunter
preferences and intentions. Chapter 4 presents data collected on harvested antlered
white-tailed deer (Odocoileus virginianus) combined with survey data from each
respective hunter. The aim of Chapter 4 was to determine whether hunters with different
intentions to be selective in harvesting a buck have different harvest outcomes. The fifth
chapter presents a general discussion of my research findings and implications of such
research. Data collection instruments and research approval letters are provided as

appendices.

CHAPTER 1

General Introduction

General Introduction

1.1 The rise of human dimensions of wildlife management

A utilitarian philosophy defined the way society viewed wildlife in the early 19th
and 20th centuries in America (Petulla, 1987). The need for wildlife management and
conservation in the early 20th century was a theme consistent with an increased awareness
of wildlife by society. In 1933, Aldo Leopold published Game Management which
further strengthened the utilitarian view of human-wildlife relationships integrated with
an agricultural focus (Leopold, 1933). Despite being the keystone reference to scientific
inquiry of wildlife management for over 40 years it neglected to consider the human
aspect of wildlife management (Bath et al., 2001).

By 1960 little had changed. As pointed out by Mair in his critique of
presentations at the 25th North American Wildlife Conference,

“I am disturbed too at the apparent complete lack of research into the social and

cultural aspects of the wildlife conservation field. We are spending significant

sums of money on wildlife now and plan to spend much more in the future,

particularly with respect to the allied field of recreation. But there has been at this

conference no mention of research into the mores of people, their motivation and
their real needs (Mair, 1960)”.

It was not until the book Wildlife Management was published in 1978 by Robert Giles, Jr.
that wildlife management included a human element (Bath et al., 2001). The human
element, also referred to as the human dimension of wildlife management, has been
defined as,
. . .an area of investigation which attempts to describe, predict, understand, and
affect human thought and action toward natural environments and to acquire such

understanding for the primary purpose of improving stewardship of natural
resources (Zinn & Manfredo, 1992).

The importance of human dimensions stems from consumptive wildlife resource
users (e.g., hunters) playing an increasingly pivotal role in the management process.
Consumptive resource users can affect exploitable populations by reducing overall
numbers or reducing the number of certain types of animals (e.g., those meeting
minimum size requirements). Such harvesting practices are behavioral acts of hunters;
the human dimension aspect of wildlife management seeks to understand human behavior
and determine factors related to harvest outcomes.

1.2 Hunter-induced Selection

Harvest decisions can have important consequences for not only the size of game
populations, but also for the composition (i.e., sex ratio, abundance of specific trait
attributes) of populations (Fenberg & Roy, 2007). Previous concerns about harvest-
induced changes in herd composition have considered either skewed adult sex ratios
(Harris et al., 2002; Whitman et al., 2004) or skewed population age distributions
(Strickland et al., 2001). The effect of preferential harvesting of animals with specific
attributes, however, has not been as thoroughly explored except on certain species like
bighom sheep (Coltrnan, 2008).

Hunter-induced selection is the result of selective (i.e., non-random) harvesting of
prey with certain characteristics from within a population. In some cases selection is
focused on the size of one particular sex whereas, size-selective harvesting in other
systems is independent of sex (Fenberg & Roy, 2007). Recreational hunters, like natural
predators, have the ability to differentiate the individuals they harvest fi'om the
population (Kunkel, Ruth, Pletscher, & Homocker, 1999), but might select for very

different attributes in prey.

1.3 Natural Selection & Evolution

Ample empirical evidence exists supporting natural selection in the wild (Endler,
1986; Kingsolver et al., 2001). Natural selection often occurs as a distinct episode (e.g.,
drought, flood, winter storm) of selection where individuals possessing a specific
morphological trait(s) have a survival advantage over the rest of the population (Arnold
& Wade, 1984; Conner & Hart], 2004). Greater than 80% of estimates of natural
selection in the wild have resulted from measurements of morphological traits
(Kingsolver et al., 2001), including selection of overall body size and specific
morphological characteristics (Fox, 1975; Price et al., 1984).

Despite a growing body of work supporting the process of natural selection acting
on morphological traits in natural environments, there remains a gap in the literature
linking proposed anthropogenic influences to natural selection. Recreational hunters
might impose natural selection on their prey if only individuals with specific attributes in
the prey population are selectively harvested (i.e., hunter-induced selection). For
example, a study conducted on bighom sheep rams (Ovis canadensis) in Alberta, Canada
highlighted a system where hunters targeted specific individuals from the population
because of minimum harvest size regulations. The hunter-induced selection imposed on
the population fi'om 1971 to 2002 resulted in an evolutionary decline in the number of
‘trophy’ game animals available for harvest (Coltrnan et al., 2003). Hunters were found
to be selectively harvesting males with higher body weight and horn size, which caused a
decline in the trait means and reduced reproductive potential of rams. This particular
study provided rare evidence of direct evolutionary consequences resulting from harvest

outcomes mandated by minimum horn size harvest regulations.

Evolutionary effects resulting from harvest biases have also been documented in
marine fisheries experiencing excessive anthropogenic size-selective harvesting pressures
(for a review see Browman, 2000; Conover & Munch, 2002; Festa-Bianchet, 2003;
Stokes & Law, 2000). Documented size-selective harvesting has been shown to select
for traits that are economically desirable such as large size. Excessive harvest of
individuals with these traits can result in the evolution of less desirable traits such as
reduced size at maturity and reduced fecundity (Browman, 2000).

1.4 Social Psychology Aspect of Human Dimensions

1.4.] Understanding Hunting Behavior

In order to understand the potential effect of non-random harvest decisions on
wildlife populations we need to better understand how hunters make their harvest
decisions. The Theory of Planned Behavior (Ajzen & F ishbein, 1980) has been used in a
variety of contexts to gain a clearer understanding of wildlife resource users’ behavior. It
has been hypothesized that behavioral acts occur in a manner that is likely to confer a
preferred outcome, such that personal preferences can often serve as strong indicators of
behavioral intentions (Lichtenstein & Slovic, 2006). In a wildlife management context,
preferences for wildlife population sizes have been found to differ among stakeholder
groups (i.e., farmers, hunters and the general public; Curtis & Lynch, 2001). Also,
different user groups (e.g., Indian and colonist communities) have been investigated and
their harvesting preferences of specific game taxa (e.g., mammals, birds, reptiles)
quantified in terms of the species hunted and the number harvested (Redford & Robinson,
1987). The relationships between total numbers harvested and user groups (Redford &

Robinson, 1987; Vickers, 1984), animal body mass (Bodmer, 1995) and preferences for

alternative fishing management scenarios characterized by minimum and maximum total
length (Oh, Ditton, Gentner, & Riechers, 2005) have also been explored. None of the
aforementioned studies considered preferences for particular attributes other than body
mass or total length of the harvested individuals. Harvest preferences for specific
desirable attributes (e.g., body size, antler size or configuration) of a multi-attribute
individual such as an antlered white-tailed deer, is potentially important for determining
the influence of attributes on a hunters’ harvest outcome.

1.4.2 Behavioral Intentions

Given a behavior under volitional control, intentions are thought to be the direct
predecessors of behavior (Aj zen, 1991). The Theory of Planned Behavior provides one
theoretical framework that helps to understand and predict volitional behavior by
identifying determinants of a person’s intentions (Ajzen, 1991; Ajzen & Fishbein, 1980).
One determinant of intentions are attitudes (Homer & Kahle, 1988); empirical
relationships between attitudes and intentions, however, are inconsistent (Homer &
Kahle, 1988). Aspects of personality other than attitudes, such as motivation and
situational variables, might also affect the attitude-intention relationship (Ajzen &
Fishbein, 1974). Holsman & Petchenick (2006) found that attitudes about deer
population reduction goals did not affect the behavioral outcome of the number of deer
harvested. The degree to which attitudes accurately predict intentions and harvest
outcomes (i.e., behavior) is unclear.
1.5 White-Tailed Deer Harvesting in Michigan

In 2006 the annual harvest of white-tailed deer (Odocoileus virginianus) in the

southern lower peninsula of Michigan exceeded 450,000 (Clute, 2006), representing

roughly 53% of the estimated population for that area. As a result, selection pressures
from hunters could be strong enough to result in observable changes of deer attributes
towards less desirable forms. In order to determine this selection potential, I examined
hunter preferences for deer attributes and hunter harvest intentions. To establish a region
of Michigan that would have the highest likelihood for selection to occur, I quantified the
opportunity for hunter-induced selection on bucks for each deer management unit (DMU)
in the state of Michigan. The opportunity for selection (I) was calculated as the variance
in relative fitness of bucks based on existing population (2000-2005) and harvest
estimates (2000-2004) for each DMU in Michigan (see Figure 1.1; refer to the General
Methods section). In this case, I is based on the proportion of individuals harvested from
the total population and sets an upper limit to the strength of hunter-induced selection.
Typical harvest levels of antlered deer represent an extremely high opportunity for
selection during the firearm deer hunting season. Seventy-seven of ninety-six DMUs
typically experience an opportunity for selection on antlered deer that could fall within
the strongest 5% of previously recorded selection events in the wild (Kingsolver et al.,
2001). The majority of DMUs with the “strongest” (I = 5 to 11) opportunity for selection
were located in the Saginaw Bay Wildlife Management Unit (SBWMU) and all DMUs
located within SBWMU had “very strong” (I = 0.75 to 5) or “strongest” (1 = 5 to 11)
opportunity for selection values. Values for antlerless deer were also calculated but these
were generally very low indicating that too few antlerless deer are harvested for hunter-
induced selection on antlerless deer to be a problem.

The proportion of antlered white-tailed deer harvested in most DMUs in

Michigan, and in the SBWMU in particular, suggest that hunter-induced selection has the

potential to be very strong. As a first step toward quantifying hunter-induced selection,
this study investigated white-tailed deer hunters’ preferences, intentions and harvest
outcomes. White-tailed deer represent an optimal study subject due to their popularity as
a harvestable big game species, high annual harvest rates, and abundance within the state
of Michigan. In this system, prominent traits (i.e., large antlers) have the potential to
confer a fitness disadvantage during the hunting season because individuals with these
trait attributes might be disproportionately removed from the population via hunter
harvest. By understanding hunter preferences, intentions, and harvest outcome, it will be
possible to determine the potential targets of selection and the potential fitness
disadvantages incurred fiom selective harvesting of these individuals from the
population.
1.6 Study objectives

The overall goal of this research was to explore the potential evolutionary
consequences from non-random harvesting of antlered white-tailed deer by firearm deer
hunters in Michigan. As a first step towards quantifying hunter-induced selection, I set
out to measure the preferences and intentions of white-tailed deer firearm hunters and
their harvest outcomes. This goal was accomplished through the following objectives:

1. Quantify Michigan firearm deer hunters’ preferences for total number of

antler points, G2 tine length, antler spread and age of antlered deer.
2. Determine the intention of Michigan firearm deer hunters to be selective.
3. Examine the importance of context-independent factors (i.e., intention to be
persistent, expectations, importance of selectivity) and hunter attributes (i.e.

age, centrality to lifestyle) to their selectivity intentions.

4. Examine the morphological characteristics of antlered deer harvested during
the 2006 firearm season and determine the relationship between context-
independent factors (i.e., self-reported persistence, selectivity intentions),
hunter attributes (i.e., centrality to lifestyle, age, years of hunting experience)
and context-dependent factors (i.e., hunting pressure, land-type hunted, day of
season started hunting) and the characteristics of hunters’ harvested antlered
deer.

1. 7 Research implications

This project investigated the potential for selective harvesting to result in the
evolution of wild, free-ranging populations of antlered white-tailed deer in ten counties in
the east-central Lower Peninsula of Michigan. It serves as a first step toward
understanding the degree of selective harvesting in this area of Michigan by exploring

hunter preferences and selectivity intentions.

10

Figure 1.1 . Map of Michigan designating Deer Management Units and their respective
opportunity for selection values. The study area is outlined in yellow (Saginaw Bay

Wildlife Management Unit). This image is presented in color.

11

Figure

  

D Saginaw Bay mnagemant Unit

County boundaries
Average l Vdue by mu
Weak

Average
arong
Vbry Strong
aronged

12

REFERENCES

Aj zen, I. (1991). The theory of planned behavior. Organizational behavior and human
decision processes, 50, 179-211.

Ajzen, I., & F ishbein, M. (1974). Factors Influencing Intentions and the Intention-
Behavior Relation. Human Relations, 27(1), 1-15.

Aj zen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior.
New Jersey: Prentice-Hall, Inc.

Arnold, S. J ., & Wade, M. J. (1984). On the measurement of natural and sexual selection:
applications. Evolution, 38(4), 720-734.

Bath, A., Bissell, S. J ., Blanchard, K. A., Brown, T. L., Chase, L. C., Connelly, N. A., et
al. (2001). Human Dimensions of Wildlife Management in North America.
Bethesda, Maryland: The Wildlife Society.

Bodmer, R. E. (1995). Managing Amazonian wildlife: biological correlates of game
choice by detribalized hunters. Ecological Applications, 5(4), 872-877.

Browman, H. I. (2000). 'Evolution' of fisheries science. Marine Ecology Progress Series,
208, 299-313.

Clute, R. (2006). 2006 Michigan Deer hunting prospects: the statewide forecast. Lansing,
MI: Wildlife Division.

Coltman, D. W., O'Donoghue, P., Jorgenson, J. T., Hogg, J. T., Strobeck, C., & Festa-
Bianchet, M. (2003). Undesirable evolutionary consequences of trophy hunting.
Nature, 426.

Coltrnan, D.W. (2008). Molecular ecological approaches to studying the evolutionary
impact of selective harvesting in wildlife. Molecular Ecology, 1 7, 221-233.

Conner, J. K., & Hartl, D. L. (2004). A Primer of ecological Genetics. Sunderland, Mass:
Sinauer Associates, Inc.

Conover, D. 0., & Munch, S. B. (2002). Sustaining fisheries yields over evolutionary
time scales. Science, 297, 94-96.

Curtis, J ., & Lynch, L. (2001). Explaining deer population preferences: an analysis of
farmers, hunters and the general public. Agricultural and Resource Economics
Review, 30(1), 11.

Endler, J. A. (1986). Natural selection in the wild. Princeton, New Jersey: Princeton
University Press.

13

Fenberg, P. B., & Roy, K. (2007). Ecological and evolutionary consequences of size-
selective harvesting: how much do we know? Molecular Ecology.

F esta-Bianchet, M. (2003). Exploitative wildlife management as a selective pressure for
life-history evolution of large mammals. In M. Apollonio & M. Festa-Bianchet
(Eds), Animal Behavior and Wildlife Conservation (pp. 191-207). Washington,
DC: Island Press.

Fox, S. F. (1975). Natural selection on morphological phenotypes of the lizard Uta
stansburiana. Society of Evolution, 29, 95-107.

Harris, R. B., Wall, W. A., & Allendorf, F. W. (2002). Genetic consequences of hunting:
what do we know and what should we do? Wildlife Society Bulletin, 30(2), 634-
643.

Holsman, R.H., & Petchenick, J. (2006). Predicting deer hunting harvest behavior in
Wisconsin's Chronic Wasting Disease Eradication Zone. Human Dimensions of
Wildlife, 11, 177-189.

Homer, P. M., & Kahle, L. R. (1988). A structural equation test of the value-attitude-
behavior hierarchy. Journal of Personality and Social Psychology, 54, 63 8-646.

Kingsolver, J. G., Hoekstra, H. B., Hoekstra, J. M., Berrigan, D., Vignieri, S. N., Hill, C.
B., et al. (2001). The strength of phenotypic selection in natural populations. The
American Naturalist, 15 7(3), 245-261.

Kunkel, K. E., Ruth, T. K., Pletscher, D. H., & Homocker, M. G. (1999). Winter prey
selection by wolves and cougars in and near Glacier National Park, Montana.
Journal of Wildlife Management, 63(3), 901-910.

Leopold, A. (1933). Game Management. New York: C. Scribner's Sons.

Lichtenstein, S., & Slovic, P. (2006). The Construction of Preference: Cambridge
University Press.

Mair, W. W. (1960). Natural Resources and American Citizenship: a critique of the 25th
North American Wildlife and Natural Resources Conference. Transactions of the
North American Wildlife and Natural Resources Conference, 487-496.

Oh, C.-O., Ditton, R. B., Gentner, B., & Riechers, R. (2005). A stated preference choice
approach to understanding angler preferences for management options. Human
Dimensions of Wildlife, [0, 173-186.

Petulla, J. M. (1987). The evolution of wildlife values: a historical footnote. In D. J.

Decker & G. R. Goff (Eds.), Valuing wildlife: economic and social perspective
(pp. 335-344). Boulder, Colorado: Westview.

14

Price, T. D., Grant, P. R., Gibbs, H. L., & Boag, P. T. (1984). Recurrent patterns of
natural selection in a population of Darwin’s finches. Nature, 309, 787-789.

Redford, K. H., & Robinson, J. G. (1987). The game of choice: patterns of Indian and
colonist hunting in the neotropics. American Anthropologist, New Series, 89(3),
650-667.

Stokes, K., & Law, R. (2000). 'Evolution' of fisheries science; Fishing as an evolutionary
force. Marine Ecology Progress Series, 208, 299-313.

Strickland, B. K., Demarais, S., Castle, L. B., Lipe, J. W., Lunceford, W. H., Jacobson, H.
A., et a1. (2001). Effects of selective-harvest strategies on white-tailed deer antler
size. Wildlife Society Bulletin, 29(2), 509-520.

Vickers, W. (1984). The fauna] components of Lowland South American hunting kills.
Interciencia, 9, 10.

Whitman, K., Starfield, A. M., Quadling, H. S., & Packer, C. (2004). Sustainable trophy
hunting of African Lions. Nature, 428, 175-178.

Zinn, H. C., & Manfi'edo, M. J. (1992). Integrating human dimensions research and

natural resource management in the Rocky Mountain region. Paper presented at
the Human Dimensions Symposium.

15

CHAPTER 2

Data Collection Methodology

16

Data Collection Methodology
2.] Stuay area

2.1.1 Selection of study area

The study area for this project was chosen based on calculated values of the
opportunity for selection (denoted by I) (see General Introduction; see Figure 1.1). The
opportunity for hunter-induced selection was quantified based on existing population
(2000-2005) and annual harvest estimates (2000-2004) for each Deer Management Unit
(DMU) in Michigan taken fi'om Frawley (2007). Information from Michigan Department
of Natural Resources (MDNR) harvest surveys, deer check stations, deer pellet group
surveys, reports of deer-vehicle collisions and population modeling were used to estimate
deer population levels statewide (F rawley, 2007).

The Saginaw Bay Wildlife Management Unit (SBWMU) is located in a region of
Michigan that is dominated by agricultural and forested landscapes. Huron, Sanilac and
Tuscola counties are characterized by a long growing season (130 — 160 days), annual
precipitation of approximately 31 inches with below average winter temperatures (-28 ° F
to -24 ° F) and minimal snowfall during the winter months (Comer et al., 1995).
Saginaw, Bay, Midland, Gladwin, Arenac and the eastern areas of Clare and Isabella
counties are characterized by a long growing season (153 days), with minimum winter
temperatures of approximately 14 ° F (Comer et al., 1995).

2.2 Survey methods
2.2.1 Pre-survey focus groups
Two focus groups were utilized to facilitate the design of a mail questionnaire to

evaluate hunters’ attitude toward white-tailed deer harvest and to provide a qualitative

l7

description of resident firearm deer hunters in the SBWMU of Michigan. Both meetings
were conducted by following a scripted set of questions (Appendix A). Names of
potential focus group participants were elicited from a sampling fi'ame produced by the
MDNR in which individuals meeting the following criteria were included: 1) Michigan
residents, 2) 18 years of age or older as of January 1, 2006, and 3) had purchased a
license in 2006 to hunt white-tailed deer. All participants (11 = 29) indicated a willingness
to participate in a focus group discussion by returning a postcard indicating their
availability (Appendix B). Participants of each focus group meeting also provided their
consent to participate in the meetings (Appendix C) and completed a brief survey
(Appendix D). Focus group meetings were held with SBWMU firearm deer hunter
stakeholders in March of 2006 in Bay City, Michigan. These meetings were conducted to
achieve the following objectives:

1) Identify external variables that may impede a hunter’s ability to exercise
intended harvest actions.

2) Identify potential antlered deer traits that would allow later categorization of
these trait preferences among deer hunters.

3) Identify the perceptions of the stakeholders’ own harvest selectivity and
the reason(s) for their perceptions.

Focus group input helped to guide the development of hypotheses and the selection of
variables for modeling purposes.

2. 2. 2 Sampling criteria & sampling flame

The sampling frame for the mail questionnaire was determined by the following
criteria: 1) Michigan residents, 2) 18 years of age or older as of January 1, 2006, 3) had
purchased a license in 2006 to hunt white-tailed deer, and 4) had completed and returned

a 2003, 2004 or 2005 MDNR harvest questionnaire stating they had harvested a white-

18

tailed deer (antlered or antlerless) from within the research study area (SBWMU). Only
deer hunters possessing a combination license, an archery only license, and a firearm
only license qualified for this study. The sample group for the survey was derived from a
portion of the total number of firearm deer hunters who had previously hunted or hunt
within the SBWMU; it was not a statewide sample.

2.2.3 Mailing sequence dates & sample sizes

The self-adrninistered mail questionnaire (Appendix E) with repeat mailings was
conducted following methods described by Dillrnan (2000). A cover letter (Appendix F)
was included in each initial mailing to introduce the questionnaire and inform recipients
that filling out the survey indicated their voluntary participation. A total of 3,954 names
and addresses were used in the initial mailing of the questionnaire on January 12th, 2007
followed 15 days later with a reminder postcard (Appendix G). Non-respondents
received a second questionnaire 15 days later accompanied by a modified cover letter
(Appendix H). Non-respondents of the second questionnaire were sent a third and final
mailing of the questionnaire with the same modified cover letter 15 days after the second
mailing was delivered. All questionnaires were mailed from and returned to the MDNR
headquarters in Lansing, Michigan. A deadline of May 23", 2007 was established after
which time no returned mail questionnaires were included in the study. Questionnaire
responses were coded and transferred to a database using a MDNR program designed for
survey data entry purposes.

2. 2. 4 Study variables

The mail questionnaire was designed to assess hunter preferences for deer related

attributes (e. g. number of points, spread) and to determine the influence of non-deer

19

related factors (e.g., hunter persistence, landownership) on hunter preferences and
intentions for harvest outcomes. In addition, several other factors that potentially
affected harvest outcome were measured including selective harvest intentions, self-
reported persistence, experience (e. g., age, number of years hunting), centrality of
hunting to one’s lifestyle, hunting pressure, number of days hunted, the day hunting
began and land-type hunted (i.e., public vs. private). Although behavior was not
explicitly measured, the intentions for harvest and the actual harvest outcome were.
Some standard demographic questions typically asked on surveys (i.e., employment
status, education level and income) were not measured in this case.

Three categories of bucks that hunters would be willing to harvest as their first
buck of the firearm deer season were presented to respondents under the heading of:
ideal, preferred and least preferred. To reduce subjectivity and ambiguity among
responses, each category was described. Ideal bucks were defined as “Those that you
would not hesitate to take if the opportunity presented itself. You might be willing to
pass up shots at other bucks for part or all of the November firearm season to wait for this
buck”. A preferred buck was defined as “A buck that you would harvest when you
were not willing to wait any longer for your ideal buck. You might be willing to pass up
shots at other legal bucks for part or all of the November firearm season to wait for a
buck of at least this standard”. Finally, least preferred bucks were defined as “Those
you would harvest only after you gave up waiting for your ideal and preferred bucks.
You might decide to harvest your least preferred buck for venison or because you would
rather not risk ending your November firearm season without harvesting a buck at all”.

These three categories of bucks were further defined as deer that the respondent was

20

reasonably certain existed in their hunting area within the Saginaw Bay Wildlife
Management Unit.

Variables used in the data analysis stages were operationalized by the survey as
follows:

Selectivity intention: This was the hunter’s intention to be selective when
harvesting their first buck at the beginning of the 2006 November firearm deer season.
Intentions were measured using the options of: “I intended to shoot only a buck that met
my ideal buck standards, even if it meant not getting a buck during the 2006 November
firearm deer season”, “I intended to try and harvest my ideal buck for a while, but would
not have settled for anything less than my preferred buck standard, even if it meant not
getting a buck during the 2006 November firearm deer season”, “I intended to wait
awhile to harvest either an ideal or preferred buck, but intended to harvest a least
preferred buck, if necessary, to avoid going home without venison during the 2006
November firearm deer season”, and “I intended to take any legal buck that presented an
opportunity during the 2006 November firearm deer season.”

Preferences: Preferences for attributes of antlered deer were assessed by
qualitative descriptions of antler tine length, antler beam spread, total number of antler
points and age. For each buck category and for each trait attribute, a preference was
qualitatively described.

Harvest experience: Harvest experience was measured as whether a hunter
harvested one or two antlered deer during each of the past three November firearm deer

seasons (2004, 2005, and 2006).

21

Xe_ars of hunting experience: The years of firearm deer hunting experience was
measured by how many of the past three years (2003, 2004, and 2005) that a respondent
hunted in the SBWMU during the November firearm deer season.

Importance of selectivity: The importance of selectivity was measured as how
important select whitetail deer attributes were in helping hunters decide whether to
harvest a buck. Response options included “Extremely Important”, “Moderately
Important”, “Slightly Important”, “Not at all Important”, and “I am Unsure”. Responses
of “I am unsure” were treated as missing data as no direction of importance could be
gathered from such a response. “Extremely Important” was scored as the highest value
of importance whereas “Not at all Important” received the lowest value. Reported
responses were then averaged across the seven whitetail deer attributes for a final overall
importance of selectivity score for each hunter. Larger scores meant that the hunter
placed a high importance on these traits when making harvest decisions.

Expected harvest opportunity: Expected harvest opportunity (i.e., “Extremely
likely”, “Highly likely”, “Somewhat likely”, “Not at all likely”) was measured as the
respondents perceived likelihood of having the opportunity to harvest each category of
bucks.

Intention to be persistent: Two values for the intention to be persistent were
calculated. Responses from the survey enabled scores to be computed for the intention to
be persistent for an ideal buck category before switching to a preferred buck and the
intention to be persistent for an ideal or preferred buck before switching to a least
preferred buck. Respondents indicating that they intended to wait for at least part of their

season to try and harvest an ideal buck were asked when they would most likely stop

22

waiting for a particular category of buck and take another if the opportunity was
presented. The response options were when “75% of my opportunity to hunt remains”,
“50% of my opportunity to hunt remains”, “25% of my opportunity to hunt remains” or
“I wouldn’t shoot anything less than a buck of my ideal or preferred standards.”

Centrality of lifestyle: The centrality of deer hunting to one’s lifestyle was
assessed by the importance of deer hunting as a recreational activity compared to other
recreational activities. This question has been used extensively in the past (Hunt, Haider,
& Armstrong, 2002; Sutton, 2003) and serves as an indicator of the level of specialization
of a hunter. Possible responses to the question included: “My most important
recreational activity”, “One of my more important recreational activities”, “No more
important than any other recreational activity”, “Less important than most of my other
recreational activities”, and “Not at all important to me as a recreational activity”. Due to
the low number of responses to options “No more important than any other recreational
activity” (11 = 328), “Less important than most of my other recreational activities” (n =
46), and “Not at all important to me as a recreational activity” (11 = 26) these three
categories were combined into one category for analysis purposes.

Land-ups: The land ownership type that was primarily hunted on during the past
three November firearm deer seasons (2004, 2005, and 2006) was recorded as either
public or private.

Self-reported persistence: Self-reported persistence was calculated as the number
of days hunted before harvesting their first buck divided by the total number of days
available to hunt. A value of 1 indicated that the hunter harvested their first buck on their

last available hunting day.

23

H1unt'gg pressure: Hunting pressure was measured as the perceived hunting
pressure within a mile of the respondents’ primary hunting area, and was categorized as:
“Very light”, “Light”, “Moderate”, “Heavy”, and “Very Heavy.”

Start of the hunting season: Possible responses describing the start of the hunting
season included: “I began hunting on the first day the season opened (Wednesday, Nov.
15)”, “I began hunting on the second day of the season (Thursday, Nov. 16)”, “I began
hunting on the third day of the season (Friday, Nov. 17)”, “I began hunting during the
first weekend (Saturday and Sunday, Nov. 18 and 19)”, and “I began hunting during the
second week (Monday thru Friday, Nov. 20 to 25)”. Very few hunters began hunting on
days other than the first day of the season; therefore, these four categories were combined
into one category (i.e., “Any day after the first day”).

Harvest date: The date that an antlered deer was harvested. This date may have
been different from the date the deer was checked in at a check station.

To reduce the variability of situational factors contributing to harvest outcomes, a
sex-specific and site-specific approach was used throughout the survey. Specifically,
respondents were cautioned that although people hunt in more than one location and may
have different harvest intentions for those areas, the questions on the survey were to be
answered as they would apply to the respondents’ primary hunting area during the 2006
November firearm deer season in the Saginaw Bay Wildlife Management Unit. Drafts of
the questionnaire were reviewed by the researcher’s committee, fellow colleagues,
MDNR biologists and personnel, and firearm deer hunters. The questionnaire was then
piloted to hunters (N =10) and Michigan State University graduate and undergraduate

students (N =10). Necessary revisions were completed and a final version of the mail

24

questionnaire was approved by the University Committee Involving Research on Human
Subjects and the Institutional Review Board (IRB #05-1028, see Appendix J).
2.3 Data Collection on Harvested Deer

Measurements of harvested, antlered, white-tailed deer attributes were collected
from hunters during the 2006 firearm deer season, November 15-30’", 2006 in ten DMUs
that geographically comprise the SBWMU (See Figure 1.1) (ESRI, 1999).

Attribute measurements were taken at ten check stations that checked a high
proportion of antlered deer harvested within the study area and that were open throughout
the 16-day firearm deer season. The numbers of antlered deer processed for attribute
measurements at each check station were as follows: Bay City: 23, Cass City: 121 ,
Chipp-A-Waters: 66, Gladwin: 74, Maurer’s Meat: 68, Mr. Chips: 52, Sanford: 74, St.
Charles: 95, Standish: 92, Wilson State Park: 85, and one unknown. During the
collection of morphological attribute measurements of harvested deer, reminder postcards
(Appendix I) were handed out to successful hunters informing them that they would be
receiving a survey in the mail starting in January 2007. Hunting license or driver license
numbers were also collected to facilitate the mailing of a survey to each hunter.

Deer were measured if they were legally harvested by a Michigan resident within
any county of the 10-county SBWMU during the November firearm deer season and
were considered an antlered white-tailed deer by the MDNR (i.e., > 3” antler points).
Morphometric attribute data collection consisted of the measurements of six traits
including ear length, hindfoot length, G2 tine length and spread (see Figure 2.1). Two
further measurements (total number of antler points and antler beam diameter) were

obtained from the MDNR as part of their annual routine data collection procedures (see

25

Figure 2.1). Beam diameters were collected to the nearest tenth of one millimeter. All
other trait measurements were collected to the nearest tenth of one centimeter.
Measurements were collected using a cloth measurement tape following standardized
procedures:

Ear length: Measured from the base of the notch below the ear opening to the
most distant point on the margin of the pinna (external ear), excluding ear hair that
extends beyond this point (Lundrigan, 1996).

Hindfoot length: Measured from the calcaneum (heel or hock) to the base of the
hoof (Lundrigan, 1996).

G2 tine lengt_h: Measured fiom the baseline of the G2 tine (i.e. where the bottom
of the G2 tine intersects with the top edge of the main antler beam) to the tip of the tine,
following the centerline of the tine; both left and right antler G2 tines were measured.

Snfld: Measured as the widest distance between the left and right main antler
beams or points.

T_ot_al number of antler points: All points greater than 1” in length were
enumerated.

Beam diameter: Measured the main antler beam 1” from the antler burr; two
measurements were taken perpendicular to one another and then averaged for the final
main antler beam diameter. Both left and right sides of the main antler beam were

measured.

26

Figure

 

 

 

 

('2

Point must be 1”
long or greater

 

Figure 2.1. Illustration of the eight morphological measurements. (a) length of hind foot
and ear (mm), G2: length of second point (mm), H1: antler beam diameter (mm), A L/R:
total number antler points on left & right antler beams, C: greatest spread of antler beams

(mm). Antler illustrations are adapted from the Boone and Crockett Club ®.

27

REFERENCES

Comer, P. J., Albert, D. A., Wells, H. A., Hart, B. L., Raab, J. B., Price, D. L., et a1.
(1995). Michigan's native landscape: as interpreted fiom the General Land Ofiice
surveys 1816-1856: Michigan Natural Features Inventory.

Dillrnan, DA. (2000). Mail and internet surveys: the tailored design method (V 01. 2"d
Edition). New York: John Wiley and Sons, Inc.

ESRI. (1999). ArcView 3.2: Environmental Systems Research Institute, Inc. Redlands,
California, USA.

Frawley, B. (2007). Michigan Deer Harvest Survey Report 2006 Seasons (Wildlife
Report No. 3467). Lansing, Michigan: Division of Wildlife.

Hunt, L., Haider, W., & Armstrong, K. (2002). Understanding the fish harvesting
decisions by anglers. Human Dimensions of Wildlife, 7, 75-89.

Lundrigan, B. (1996). Standard methods for measuring mammals. In D. G. Kleiman, M.
E. Allen, K. V. Thompson & S. Lumpkin (Eds), Wild mammals in captivity:
principles and techniques. Chicago: The University of Chicago Press.

Sutton, S.G. (2003). Personal and situational determinants of catch-and-release choice of
freshwater anglers. Human Dimensions of Wildlife, 8, 109-126.

28

CHAPTER 3

Hunter preferences for antlered white-tailed deer attributes and their harvest intentions

29

INTRODUCTION

3.1. Introduction

Heavy harvest pressure on white-tailed deer (Gladfelter, 1984) over the past few
decades has made white-tailed deer management a prominent focus of many state wildlife
agencies (Brown et al., 2000) It is now widely recognized that successful management of
white-tailed deer depends on a simultaneous understanding of their biology and the
preferences of those who hunt them (Bath et al., 2001). White-tailed deer hunting
constituents have attitudes, values, and behaviors that are important to harvest outcomes
because of the influence they have on the decision-making process. Harvest decisions
have direct implications for management purposes because of the hunters’ potential to
harvest selectively. Trait preferences and selective harvest intentions therefore, are
thought to be two important factors influencing the outcome of a deer harvest and its
impact on wild deer populations.

3. 1.]. Preferences

Preferences provide a basis for harvest decisions and are thought to reflect
individually held values (Rokeach, 1973). Preferences for technique, style, harvest
determination, and social settings have been related to recreational specialization in
hunting and fishing, which is a measure of the intensity of involvement in a recreational
activity (Kuentzel & Heberlein, 1992; Bryan, 1979). In wildlife management scenarios,
only preferences for population sizes (Curtis & Lynch, 2001) and “types” of deer
(antlered vs. antlerless; Bhandari et al., 2006) have been investigated. No previous
research exists on preferences for specific white-tailed deer attributes as they relate to

harvest outcomes. Preferences for specific deer attributes could have important

30

implications for selective harvesting if hunters are able to harvest what they prefer.
Hunters might intend to harvest prey with non-preferred attributes because of harvest
expectations and motivations (F edler & Ditton, 1986) and commitment to the sport (Scott
& Shafer, 2001). For example, a hunter might prefer many antler points but not be
motivated enough to actively pursue bucks with those characteristics, and instead intend
to harvest a buck with fewer points.

3.1.2 Hunter Intentions

Behavioral intentions are defined as a determination to act in a certain way and
are frequently shown to be important predictors of behavior (Triandis, 1971; Wicker,
1969; Ajzen & Fishbein, 1974). The use of intentions to predict behavior has been
explored in a variety of contexts including the prediction of election outcomes (Turner &
Martin, 1984), wildland preservation (V aske & Donnelly, 1998), and schooling-work
behavior (Manski & Wise, 1983). These studies revealed that attitudes and normative
beliefs about a specific behavior were found to influence behavioral intentions. In
addition to attitudes, such behavioral influencing factors as social norms, personality
characteristics, and situational variables also must be accounted for (Ehrlich, 1969;
Warner & DeFleur, 1969). All of the aforementioned work investigating a variety of
behaviors has appeared in the social psychology literature, however, the intentions
regarding harvest outcomes for various prey of recreational hunters has not yet been
quantified. Little is known about whether intentions are related to preferences or other
factors that influence intentions in the context of recreational deer hunting. Whether

intentions are an accurate predictor of harvest outcome or how they affect harvest

31

outcomes has also not been determined. Currently, the relationship between what hunters
intend to harvest and the fulfillment of their intentions by a harvest outcome is unknown.

Understanding the relationships among preferences, intention, and harvest
outcome of white-tailed deer hunters is important to wildlife management because of the
potential for selective harvesting to affect herd demographics and composition. If
hunters consistently prefer certain attributes and intend to harvest deer with those
preferred attributes then these preferences could lead to selective (i.e., non-random)
harvesting. The continuous selective removal of preferred attributes from the population
could lead to the evolution of less desirable traits (e.g., Coltrnan et a1. 2003). If, however,
preferences are heterogeneous or if situational factors interrupt the connection between
preferences and intentions then the potential for hunter-induced selection would be
minimized.
3.2 Objectives

My first objective in this chapter was to quantify hunter preferences for specific
attributes of antlered white-tailed deer and whether they are consistent. Three
conceptualized buck categories (i.e., ideal, preferred and least preferred; see Chapter 2 for
details) were used to identify preferences for buck attributes. Furthermore, several
variables were used to quantify and help to explain variation in preferences for one buck
attribute (e.g., total number of antler points). A second objective of this chapter was to
understand how selective hunters intend to be and report the similarities and differences
among hunters with different selectivity intentions. The intentions to be selective of
Michigan firearm deer hunters were determined by asking hunters what category of buck

(i.e., ideal, preferred or least preferred) they intended to harvest for their first harvested

32

buck during the 2006 November firearm deer season. Findings related to these objectives

will be useful for managers to better understand their deer hunting constituents and the

influence that characteristics of these individuals have on hunter-induced selection.
MATERIALS & METHODS

3.3 Self-administered survey

Hunter preferences for buck traits and intentions to be selective were measured
using a self-administered mail questionnaire (N =3,954) with repeat mailings following
Dillrnan (2000). Data were collected from individuals that were 1) Michigan residents,
2) 18 years of age or older as of January 1, 2006, 3) and who had purchased a license in
2006 to hunt white-tailed deer, and 4) completed and returned a Michigan Department of
Natural Resources harvest questionnaire stating they had harvested a white-tailed deer
(antlered or antlerless during the 2003, 2004 or 2005 season) from within the study area
(see Chapter 2 for study area description). It was assumed that this was a representative
sample of individuals that have hunted the Michigan study area over the past three years.
All survey methodologies were approved by the University Committee Involving
Research on Human Subjects and the Institutional Review Board (IRB #05-1028;
Appendix J).

The mail questionnaire was designed to measure each hunter’s preferences for
antlered deer attributes (i.e., number of antler points, antler spread, G2 tine length & age),
their attitude towards the importance of harvest selectivity, and the importance of hunter
constructs (i.e., intention to be persistent, intention to be selective, expected opportunity
for harvesting bucks) and hunter attributes (i.e., age, centrality to lifestyle) to their

selectivity intentions. The importance of selectivity to a hunter was determined by the

33

importance a hunter placed on specific attributes of an antlered deer that might influence
harvest outcomes. Among hunter constructs and hunter attributes, context variables (i.e.,
hunting pressure, land-type hunted and day of season started hunting) were also
investigated for their relationship to hunters’ intentions to be selective.

Descriptive categories of bucks were developed to reduce subjectivity and
ambiguity among responses. Ideal, preferred and least preferred bucks were categorized
for the respondents (see Chapter 2 for details) and responses pertaining to only a hunters’
first harvested buck during the firearm deer season were considered. In addition, several
other factors including years of hunting experience, land-type hunted and centrality of
hunting to one’s lifestyle were measured (see Chapter 2 for details). Preferences for total
number of antler points were described for each buck category (i.e. ideal, preferred and
least preferred categories). It was assumed that total number of points would provide the
greatest distinction among categories of bucks because questions about preferences for
the total number of antler points had the fewest non-responses. Therefore, total number
of antler points for each category was used as a response variable in modeling
preferences.

3.3.1 Data Analysis

Hunter survey responses were summarized and models were developed to
determine the preferred total number of antler points. Relationships were also examined
between preferences and aspects of firearm deer hunting including land-type hunted, hunt
start date, and number of years of deer hunting experience that might help to explain
variation in hunter preferences for total number of antler points. Hunter intentions to be

selective were quantified by the descriptive category of buck that he or she intended to

34

harvest. Hunter preferences for attributes of antlered deer, the age of the respondent, the
number of years of firearm deer hunting experience, importance of selectivity, expected
harvest opportunity, the intention to be persistent, centrality of deer hunting to one’s
lifestyle, and land-type hunted were also used to develop the model exploring hunters
intention to be selective (see General Methods section for detailed descriptions of each
variable).

Chi-square tests were used to determine if the preferred total number of antler
points differed among the three descriptive categories of buck (i.e., ideal, preferred and
least preferred). All respondents providing data on buck category preference were used
for chi-square analyses. Comparisons among buck categories were made using median
descriptions of each buck attribute.

A series of general linear models (GLM) were assessed to investigate the relative
roles of several variables hypothesized to influence hunter preferences for total number of
antler points. An exploratory modeling approach was used to determine a minimal
adequate model to predict variation in the total number of antler points describing a
hunter’s ideal, preferred and least preferred bucks. A second model was generated for
each of the three buck categories with a response variable of preferred total number of
antler points. The response variable was originally categorized in the questionnaire but
was later converted to a continuous variable by replacing categorical values with the
mean value of each respective response category (e.g., responses from category “3 to 6
points” were replaced with a value of 4.5). Preference for total number of antler points
for a buck of each category were predicted using the expected opportunity to harvest an

ideal, preferred, or least preferred buck, the intention to be persistent, the respondents’

35

age, land-type hunted, the number of years of hunting experience, and the centrality of
hunting to one’s lifestyle.

Observations with missing data were deleted in statistical analyses. Eigenvalues
were calculated from a correlation matrix of the predictor variables to check for evidence
of multicollinearity among the predictor variables. The severity of the collinearity was
evaluated by calculating the condition index number of the correlation matrix and found
to be satisfactory.

The nature of the data set (i.e., amount and distribution of missing data)
prohibited the use of Akiake’s Information Criterion (AIC) for model comparisons.
Therefore, an improvised stepwise modeling approach was employed where models were
sequentially evaluated based on the overall model p-values, significance of parameters in
the model, residual sum of squares (RSS) and adjusted R-squared values. Numerous
models were fitted and non-significant parameters were removed (i.e., insignificant p-
values from AN OVA). For the reduced final fitted model, residual plots, Cook’s distance
plots and Q-Q plots were examined for heteroscedasticity, outliers, high leverage points
and influential points. Diagnostic plots of the minimal adequate models indicated that
residuals for total number of antler points were approximately normally distributed, and
there were no signs of heteroscedasticity or observations with undue influence on the
relationship. Variance inflation factors were also calculated for the final models and
found to be satisfactory (values < 10) for all main effects. All values for the general
linear models are presented as means :1: SE. All analyses were performed using R (R

Development Core Team, 2006).

36

RESULTS

Overall, a response rate of 66.5% for the mail questionnaire was achieved by
using a primary mailing and two follow-up reminder mailings. Nearly all (94 %) of the
2,628 respondents were male (Table 3.1). Respondents ranged in age from 18 to 90 years
old and the mean respondent age was 50 years old (SD = 14.3; Table 3.1). The majority
(90 %) of the respondents indicated that they had hunted the past three years (Table 3.1)
and that the most common license type that was purchased among respondents was the
combination license (63%; Table 3.1). Thirty-two percent of respondents indicated that
deer hunting was their most important recreational activity. A complete summary of
responses from the mail questionnaire are presented in Appendix E.

Hunters had clear preferences for antlered deer. Among the three buck categories,
there were significant differences in all of the attributes (number of antler points x2 =
2932.4, df = 8, p < 0.001; spread x2 = 2486.5, df= 8, p < 0.001; age x2 = 3204.4, df = 8, p
< 0.001; tine length x2 = 2560.9, df = 8, p < 0.001) described by hunters. Median
preferences for an ideal buck were 7 to 10 antler points, antler tine length greater than 10
inches, greater than a 21” antler spread, and 3.5 years of age or older (Table 3.2). These
descriptions of an ideal deer were very similar to the descriptions of a preferred buck, but
were very different fi'om how hunters described their least preferred buck. Median
preferences for a least preferred buck were 3” spike antlers with an antler spread of less
than 16 inches and only 1.5 years old (Table 3.2). These clear differences between an
ideal and least preferred buck indicate that hunters had clear preferences for several

attributes of bucks.

37

For all hunters that indicated the total number of antler points was important to
them (81.2% of total), a minimal model was developed to explain variation in preferences
for total number of antler points of an ideal buck (R2 = 0.25, F14,1963 = 46.18, P < 0.001;
Table 3.3). Hunters who felt that their hunting experience would result in an extremely
likely opportunity to harvest a least preferred buck preferred, on average, one more antler
point than hunters that felt they weren’t at all likely to harvest a least preferred buck (1.18
:l: 0.37, t = 3.18, df = 1968, P < 0.01). A similar trend was observed for hunters that felt
their hunting experience would result in an opportunity to harvest an ideal buck (F3,.963 =
9.88, P < 0.01). Hunters that felt their hunting would result in an extremely likely
opportunity to harvest an ideal buck reported that their ideal buck had on, average, 2.5
fewer antler points than hunters who reported that their hunting experience would result
in only a somewhat likely opportunity to harvest an ideal buck (see Table 3.3 for statistics
for each factor level). The age of the hunter negatively influenced his or her preferences
for the total number of antler points of an ideal buck such that older hunters defined their
ideal buck as having fewer total antler points than younger hunters (-0.03 d: 0.01, t = -
4.61, df = 1968, P < 0.01). If a hunter’s harvest intentions for 2007 were to harvest any
legal buck, they reported preferences for significantly fewer antler points than hunters
who intended to be selective for a specific buck category (-3.46 i 0.18, t = -19.22, df = 2,
P < 0.01). The importance of deer hunting in relation to other recreational activities also
significantly (F3,1968 = 9.88, P < 0.001; see Table 3.3) influenced hunter preferences for
total number of antler points. Compared to hunters who indicated that deer hunting was

their most important recreational activity, hunters who did not consider deer hunting to be

38

an important activity preferred significantly (-1.36 :l: 0.28, t = -4.89, df = 1968, P < 0.01;
see Table 3.3) fewer antler points on their ideal bucks.

Forty-one percent of hunters indicated that they intended to harvest any legal buck
whereas only 9 % indicated that they intended to wait and attempt to harvest only their
ideal buck (Figure 3.1). Twenty percent of respondents initially intended to harvest an
ideal buck but were willing to harvest a preferred buck. Thirty percent of hunters who
intended to wait to harvest either an ideal or preferred buck but were willing to harvest a
least preferred buck in order to avoid going home empty handed (Figure 3.1).

Differences among hunters based on their responses to how selective they
intended to be during the 2007 firearm deer hunting season were explored (Table 3.4).
Hunters with different selectivity intentions differed in age (F = 16.35, df = 3, P < 0.001).
Hunters intending to harvest only their ideal buck were significantly younger than those
hunters who intended to harvest any legal buck (-4.54 :t 0.79, t = -5.75, df = 3, P <
0.001), but hunters who intended to harvest only their ideal buck did not differ in age
from those who indicated that they would harvest any legal buck (-1.34 i 1.06, t = -1.27,
df = 3, P = 0.204). The proportion of hunters who hunted private land also differed
among these selectivity groups (x2 = 32.17, df = 3, P < 0.001). Hunters intending to
harvest their preferred buck had the highest proportion hunting on private land (82.6%),
followed by those who intended to only harvest their ideal (80.4%), least preferred
(79.8%), and any legal buck (74.3%). Years of hunting experience (i.e., less than 3 years

or greater than 3 years) did not vary (x2 = 1.61, df = 3, P = 0.65) among the selectivity

groups.

39

Preferences for the most extreme attributes of an ideal buck (i.e., > 11 points)
were also reported for each selectivity group (Table 3.5). Preferences among all the most
preferred ideal buck attributes were found to significantly differ among the selectivity
groups (e.g., ideal buck number of antler points: x2 = 1426.03, df = 12, P < 0.001; age: x2
= 1737.06, df= 12, P < 0.001; spread: x2 = 1171.59, df=12, P < 0.001; tine length x2 =
1235.55, df= 12, P < 0.001; see Table 3.5).

DISCUSSION

Harvesting represents the primary source of mortality for white-tailed deer
populations in Michigan (Clute, 2006) so it is important to understand the preferences
and selectivity intentions of hunters because of their potential to influence harvest
outcomes.

Preferences for specific attributes of white-tailed deer and their relationship to
harvest outcome have not previously been explored. In this study, hunters were found to
clearly differentiate between what they considered to be their ideal versus least preferred
bucks. Older hunters preferred fewer antler points in comparison to their younger
counterparts. This relationship could be explained by a more recent popularization of
deer hunting as the pursuit of ‘trophies’ instead of a means for enjoyment and recreation.
Alternatively, preferences for buck attributes might change with age in much the same
way that hunters’ reasons for hunting change (Jackson, 1980). Of all hunters indicating
predetermined intentions for the 2007 season, those intending to harvest any legal buck
preferred fewer antler points than those hunters who intended to be selective. This
suggests that number of antler points is a less important attribute for a hunter who intends

to harvest any legal buck. This result has important implications because as the number

40

of individuals that prefer a greater number of antler points increases, the selective
pressure experienced by deer with the preferred antler point attributes increases. For
example, the preferences of a hunter who will only harvest their ideal buck matter for
natural selection as those hunters focus on specific attributes for harvest; whereas, the
preferences of a hunter who will harvest any legal buck is not as important as they are not
particular to any specific attribute.

Few Michigan firearm deer hunters have selectivity intentions that are strong
enough to limit their harvest to a specific buck category; many hunters (41%) intend to
harvest any legal buck. One explanation for why a hunter would not intend to be more
selective could be because of the challenges (e.g., hunting pressure) associated with being
more selective. Hunters might also learn from their prior hunting experiences and modify
their intentions appropriately. In a study of Colorado hunters, past experience
significantly predicted future participation intentions (Barro & Manfredo, 1986).

Litvaitis and Kane (1994) showed that hunter selectivity changed based on bear
abundance whereas Taber and Dasmann (1954) found that harvest intentions changed as
the perceived opportunity for harvesting larger deer diminished. The perceived
opportunity to successfully harvest a buck would play a significant role in influencing
antler point preferences. Hunters who reported a likely chance of harvesting either an
ideal or what they considered to be a least preferred buck, had preferences for more antler
points, suggesting that perceived abundance can directly influence hunter preferences.

No comparable studies have investigated the effects of perceived abundance on

preferences for attributes of white-tailed deer.

41

Different groups of hunters with different selectivity intentions were found. The
group with the most hunters were found to be in the harvest any legal buck group (N =
956; 40.7%). A difference in the number of years of hunting experience did not influence
how selective a hunter would be. As table 3.4 shows, the years of hunting experience
among selectivity intention groups was similar. Over 90% of hunters who would only
harvest their ideal buck had 3.5 or more years of hunting experience. Although hunting
experience levels were similar between all four selectivity groups, one group (any legal
buck) may be less persistent or less willing to hold out for an opportunity to be more
selective. The centrality of hunting to ones’ lifestyle, furthermore, was also found to
increase the selectivity of a hunter. As predicted fi'om the point preference model for
ideal bucks, hunters who considered hunting to be their most important recreational
activity preferred more points. But, as reported in Table 3.4, of all hunters willing to
harvest their ideal bucks, only 13.6% considered deer hunting to be their most important
recreational activity. However, 68.5% of hunters intending to harvest their least
preferred buck, considered deer hunting to be their most important recreational activity.
Hunters intending to harvest any legal buck that hunt private land (74.3 %) were thought
to have increased chances for success in comparison to those hunters who intended to
harvest an ideal buck only and hunt private land (80.4 %). However, regardless of land-
type hunted, the possible opportunity to harvest an ideal buck could be low and limit
one’s chances for success, therefore, encouraging hunters’ to be more lenient in their
harvest intentions and ultimately less selective.

Managing an exploited white-tailed deer population for an abundance of a few

specific, but desirable attributes for hunters’ with varied preferences is difficult.

42

Characteristics of hunters cannot be managed for, but management regulations can be
responsive to an ever-changing hunting population. Regulations focused on increasing a
specific attribute (i.e., number of antler points) could be implemented; however, based on
the results of this study, many hunters would not be satisfied with such regulations as
many hunters are satisfied with being able to harvest any legal buck.

Due to the heterogeneity of hunter preferences between ideal and least preferred
buck attributes and hunter differences among selectivity intention groups, it will remain
difficult to distinctly identify attributes receiving the greatest harvest pressure. Intensity
and timing of harvest, furthermore, should also be considered to avoid biased population
demographics and depleted gene pools (Coltrnan, 2008); however, when nearly half (41
%) of all hunters intend to harvest any legal buck, the intensity of selection for specific
attributes is hard to quantify because there are numerous different attributes that ‘any
legal buck’ could have (i.e., individuals with highly desirable vs. sub-optimal attributes).
To mitigate the adverse effects (e.g., altered demographic characteristics) of hunting, a
decreased emphasis on trophy scores and particular attributes of game animals should be
replaced by a greater emphasis on the enjoyment of hunting (Festa-Bianchet, 2003).
Particularly for hunters in the SBWMU, many just want to harvest a buck, and therefore,
a greater focus on the harvest of an antlerless deer should replace the desire to harvest a

buck.

43

Tables & Figures

 

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Any Legal Least Preferred Preferred Buck Ideal Buck
Buck Buck

Intentions to be selective

Figure 3.1. The percentages of Michigan white-tailed deer hunters out of a total of 2,425
respondents who indicated that they had specific intentions to be selective. Intentions to
be selective categories (i.e., harvest any legal buck, least preferred buck, preferred buck
or ideal buck) are shown on the x-axis whereas number of respondents is shown on the y-

axis. Hunter selectivity increases fi'om left to right along the x-axis.

Summary of Demographic Questions from the Survey

 

 

 

 

 

Variable Statistic Total
Sex % Male 94
% Female 6
(N) (2628)
Age Mean 50
Range 1 8-90
(N) (2623)
Years of hunting
experience % 0 years 2
% 1 year 2
% 2 years 6
% 3 years 90
(N)" @483)
License type % Combination license 63
% Firearm only license 32
% Both archery only & firearm 5
only licenses
on” (2546)

.Years of hunting experience during the past three years
"This total excludes 145 observations due to missingness.

.0.

This total excludes 87 observations due to missingness, non-sensical responses or the
no license purchase.

Table 3.1. Responses to demographic questions asked of Michigan resident firearm deer
hunters (n = 2,628) on the mail questionnaire conducted in 2007. Respondents were
asked to record the number of years they hunted as of the last three years, and the license

type they purchased.

45

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46

Point Preference Model for Ideal Bucks

 

 

Estimates B SE t P
Intercept 9.88 0.48 20.54 < 0.01
Age of the respondent -0.03 . 0.01 . -4.61 < 0.01
Odds ofharvestinganideal buck , , , __ 3,3,,” I ,_ _ 3 3_ ..
Somewhat likely -0.80 0.19 -4.13 < 0.01
Highly likely -1.37 0.43 -3.20 < 0.01
Extremely likely ‘ '2-57-. 0.61 _ - _-_4.20 < 0.01
Odds of harvesting a preferred buck _, ,_ .. , _ _ _ , _ ,
Somewhat likely 0.61 0.24 2.51 0.01
Highly likely 0.79 0.35 2.27 0.02
Extremely likely . 0.66 0.59 1.10 0.30
Odds of harvesting a least preferred ‘
buck . . .
Somewhat likely 0.71 0.36 1.98 0.05
Highly likely 1.09 0.38 2.89 < 0.01
Extremely likely 1.18 0.37 3.18 < 0.01
Centrality of hunting to one's *3
lifestyle
More important recreational
activity 0.07 0.17 0.38 0.70
No more important than other -1.36 0.28 -4.89 < 0.01
recreational activities
Harvest intentions for 2007 3 ,
Harvest any legal buck -3.46 0.18 -l9.22 < 0.01
Intentions are unknown for 2007 -1.37 0.28 -4.97 < 0.01

Table 3.3. A model explaining the variation in preferences for an ideal bucks’ total
number of antler points. The odds of harvesting a buck of a certain category are
represented by the expected opportunity of being able to harvest a buck. The level for the
odds of harvesting a category of buck represented by the intercept is “Not at all likely”.
The centrality to one’s lifestyle in the intercept is “Not at all important” and harvest

intentions are to harvest a specific buck category.

47

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REESE? :3: 33 ex. \o ex. Bygone? \e x3252 Qafiufiuh
REESE :63 fee.» +Sm =33

 

48

Summary of Selectivity Intention Group Preferences

Preferences for Ideal Buck Attributes

 

3.5+ > 10 inch

Selectivity Number of > I 1 antler years GZ antler > 20 inch

Intention respondents points old tine antler spread
Harvest any
legal buck 956 (40.7%) 16.9% 0.8% 24.5% 13.4%
Harvest least
preferred buck 712 (30.3%) 10.7% 14.7% 37.6% 4.7%
Harvest
preferred buck 466 (19.8%) 58.2% 36.9% 27.9% 72.1%
Harvest only
ideal buck 214 (9.1%) 14.2% 47.6% 9.9% 9.8%

 

Table 3. 5. Preference descriptions of hunter groups as identified by their intentions to be

selective. Hunter preferences for each ideal buck attribute are reported as the percentage

of hunters within each selectivity intention group.

49

REFERENCES

Ajzen, I., & Fishbein, M. (1974). Factors Influencing Intentions and the Intention-
Behavior Relation. Human Relations, 27(1), 1-15.

Ajzen, I., & M. Fishbein. (1980). Understanding attitudes and predicting social behavior.
Englewood Cliffs, NJ: Prentice Hall.

Bath, A., Bissell, S. J ., Blanchard, K. A., Brown, T. L., Chase, L. C., Connelly, N. A., et
al. (2001). Human Dimensions of Wildlife Management in North America.
Bethesda, Maryland: The Wildlife Society.

Barro, S.C., & Manfredo, MJ. (1996). Constraints, psychological involvement, and

hunting participation: Development and testing of a model. Human dimensions of
Wildlife, 1, 42-61.

Bhandari, P., Stedman, R. C., Lulofl‘, A. B., Finley, J. C., & Diefenbach, D. R. (2006).
Effort versus motivation: factors affecting antlered and antlerless deer harvest
success in Pennsylvania. Human Dimensions of Wildlife, 11, 423-436.

Brown, T. L., Decker, D. J., Riley, S. J., Enck, J. W., Lauber, T. B., Curtis, P. D., et al.
(2000). The future of hunting as a mechanism to control white-tailed deer
populations. Wildlife Society Bulletin, 28(4), 797-807.

Bryan, H. (1979). Recreational specialization applied. In U. 0. Alabama (Ed.), Conflict in
the great outdoors: toward understanding and managing for diverse sportsmen
preferences (V 01. 4). University: The Birmingham Publishing Company.

Clute, R. (2006). 2006 Michigan Deer hunting prospects: the statewide forecast. Lansing,
MI: Wildlife Division.

Coltman, D.W. (2008). Molecular ecological approaches to studying the evolutionary
impact of selective harvesting in wildlife. Molecular Ecology, I 7, 221-223.

Curtis, J ., & Lynch, L. (2001). Explaining deer population preferences: an analysis of
farmers, hunters and the general public. Agricultural and Resource Economics
Review, 30(1), 11.

Dillrnan, D. A. (2000). Mail and internet surveys: the tailored design method (V 01. 2nd
edition). New York: John Wiley and Sons, Inc.

Ehrlich, H.J. (1969). Attitudes, behavior, and the intervening variable. The American
Sociologist, 4(1), 29-34.

50

F edler, A.J. & Ditton, RB. (1986). A framework for understanding the consumptive
orientation of recreational fisherman. Environmental Management, 10(2), 221-
227.

F esta-Bianchet, M. (2003). Exploitative wildlife management as a selective pressure for
life-history evolution of large mammals. In M. Apollonio & M. F esta-Bianchet
(Eds.), Animal Behavior and Wildlife Conservation (pp. 191-207). Washington,
DC: Island Press.

Gladfelter, H. L. (1984). Midwest agricultural region. In L. K. Halls (Ed.), White-tailed
deer: ecology and management (pp. 427-440). Harrisburg: Stackpole books.

Jackson, R.M., & Norton. (1980). "Phases": The personal evolution of the sport hunter.
Wisconsin Sportsman, 9, 17-20.

Kuentzel, W. F., & Heberlein, T. A. (1992). Does specialization affect behavioral choices
and quality judgments among hunters? Leisure Sciences, 14, 211-226.

Litvaitis, J. A., & Kane, D. M. (1994). Relationship of hunting technique and hunter
selectivity to composition of black bear harvest. Wildlife Society Bulletin, 22, 604-
606.

Manski, C., & Wise, D. (1983). College choice in America, Cambridge, MA: Harvard
University Press.

R Program. (2006). R: A language and environment for statistical computing (Version
2.4.0). Vienna, Austria: R Core Development Team.

Rokeach, M. (1973). The Nature of Human Values. New York: Free Press.

Scott, D. & Shafer, C. S. (2001). Recreational specialization: a critical look at the
construct. Journal of Leisure Research, 33(3), 319-343.

Taber, R. D., & Dasmann, R. F. (1954). A sex difference in mortality in young
Columbian black-tailed deer. Journal of Wildlife Management, 18(3), 309-315.

Triandis, HQ (1971). Attitudes and attitude change. New York: Wiley.

Turner, C., & Martin, E. (eds.) (1984). Surveying subjective phenomena (V 01. 1), New
York: Russell Sage Foundation.

Vaske, J .J ., & Donnelly, M.P. (1999). A value-attitude-behavior model predicting

wildland preservation voting intentions. Society & Natural Resources, 12,
523-537.

51

Warner, L.G., & DeFleur, ML. (1969). Attitude as an interactional concept: social
constraint and social distance as intervening variables between attitude and action.
American Sociologist Review, 34, 153-169.

Wicker, A.W. (1969). Attitudes vs. Actions: the relationship of verbal and overt
behavioral responses to attitude objects. Journal of Social Issues, 25, 41-78.

52

CHAPTER 4

Predicting the harvest success of Michigan firearm deer hunters and the attributes of their
harvested deer

53

Introduction

4.1 Selective Harvesting

With the decline of natural predators, humans often become the primary source of
mortality for many game species (Van Deelen et al., 1997). This mortality not only
affects population numbers, but also has the potential to affect herd composition (e.g.,
age structure, sex ratio or average body size) if selective harvesting occurs (Harris et al.,
2002). Historically, hunting served as the means for acquiring meat for survival.
Animals with the highest yield of protein per unit effort were harvested (Gross, 1975),
providing early evidence of selective harvesting (Redford & Robinson, 1987). The shift
from subsistence hunting to recreational hunting (Bath et al., 2001) coincides with a
change in the focus of harvest outcomes from the greatest protein yield to the most
impressive secondary sexual characteristics (e.g., horns and antlers). These sex- and size-
selective harvesting practices originate from the value placed on products (i.e., skins and
leathers) of harvested species, hunter bias resulting from consumer preferences (Swain et
al., 2007) and hunter preferences for impressive secondary sexual traits (Tenhumberg et
al., 2004). Legal restrictions based on the secondary sexual characteristics of males mean
that harvests are also ofien restricted to males that have attained a certain status (Martinez
et al., 2005; Mysterud et al., 2006). As a result, selective harvesting has been associated
with disrupted mate choice processes (Loehr et al., 2006; Singer & Zeigenfuss, 2002),
localized genetic differentiation (Frait et al., 1998; Lee et al., 1989; Strandgaard &
Simonsen, 1993), altered ecology (Loehr et al., 2006; Singer & Zeigenfuss, 2002), and
population size fluctuations (Milner et al., 2006), but can also have important and adverse

evolutionary consequences (Coltman, 2008).

54

Evolutionary responses to natural selection were previously thought to occur over
long time scales, beyond the scope of wildlife conservation or management (Stockwell,
Hendry, & Kinnison, 2003), but recent documentation of rapid evolutionary changes in
unmanaged species (Kinnison & Hendry, 2001; Palumbi, 2001; Reznick & Ghalambor,
2001) indicate that observable evolutionary changes can occur over time scales relevant
to managers. Evolutionary changes resulting fiom selective harvesting were first noted in
commercial marine fishery populations (Browman, 2000; Conover & Munch, 2002;
Reznick & Ghalambor, 2001). In hunted populations, it was predicted that an emphasis
on male secondary sexual traits for harvest purposes could have similar important
evolutionary consequences (Milner, Nilsen, & Andreassen, 2006; Ratner & Lande, 2001)
but there have been few empirical tests of these predictions.

One important exception is the study by Coltman et al. (2003), that provided
empirical evidence for an evolutionary decline in the number of ‘trophy’ bighom sheep
rams (Ovis canadensis) as a result of harvest outcomes mandated by minimum horn size
regulations. Hunters were selectively harvesting males with larger body weight and horn
size. Selective removal of fifty-seven large rams between 1975 and 2002 caused the
populations’ mean horn length and body weight to decline by 0.023 and 0.026 standard
deviations per year, respectively. The resulting decline in body weight and horn length
led to reduced reproductive potential of rams. The selective harvesting of large rams also
led to an evolutionary change in the population, resulting in an increased frequency of

less desirable ‘non-trophy’ (i.e., lighter weight, smaller-homed) rams.

55

4.2 Social sciences

4.2.1 Intention-behavior relationship theories

To quantify the degree of selectivity in hunter behavior it is necessary to
understand how harvest decisions are made. The Theory of Planned Behavior suggests
that intentions are an immediate determinant of variable but explicit behavior (Aj zen &
Fishbein, 1991), and that they serve as a strong predictor of certain explicit behavioral
outcomes (Ajzen & F ishbein, 1974; Manski, 1990), such as harvest outcome. Harvest
decisions, therefore, may depend on many factors that ultimately influence the attributes
of a harvested buck.

Harvest decisions are likely influenced by both context-dependent and context-
independent factors (Ajzen & Fishbein, 1980; Miller & Vaske, 2003). Context-
dependent factors that could influence harvest success include the species hunted,
availability of game to harvest, location hunted and hunting pressure. Context-
independent factors describe attributes of the hunter and tend not to vary across hunting
contexts (Miller & Vaske, 2003). These could include a hunter’s degree of
specialization, persistence, and centrality of hunting to their lifestyle. Centrality to
lifestyle is described by Kim, Scott and Compton (1997) as the degree to which one’s
lifestyle and social networks are combined in the pursuit of the desired leisure activity.
The increased centrality of firearm deer hunting to one’s lifestyle is hypothesized to
increase the awareness a hunter has of the resource and the impacts he or she imposes on
it through harvesting (Sutton, 2003). Buchanan (1985) noted similar trends with respect
to fishing, with high levels of experience and centrality to lifestyle affecting anglers’

fiequency of engagement in fishing, and intensity of participation.

56

Empirical studies of the relationship between stated intentions, other behavior-
modifying factors, and harvest outcomes are generally lacking. One such investigation of
harvest decisions by bluefin tuna (Yhunnus thynnus) anglers found that factors such as the
level of previous experience and centrality of fishing to an angler’s lifestyle influenced
whether an angler practiced catch-and—release fishing (Sutton, 2001; Sutton & Ditton,
2001). Past social science research in wildlife management has primarily focused on
predicting harvest outcomes as influenced by beliefs and attitudes (Hrubes, Ajzen, &
Daigle, 2001), hunter effort (e.g., number of days in the field; Miller & Vaske, 2003; Van
Deelen & Etter, 2003), or motivation (Bhandari, Stedman, Luloff, Finley, & Diefenbach,
2006; Hunt et al., 2002). Past investigations of white-tailed deer hunting has looked at
the effects of beliefs, attitudes, effort and motivations on harvest success (Kennedy,

1974; Miller & Graefe, 2001; Heberlein & Kuentzel, 2002) but failed to investigate how
these context-dependent and independent factors relate to harvest outcomes in terms of
the attributes of the harvested animal.

In many places, white-tailed deer (Odocoileus virginianus) experience intensive
harvesting pressure (Waller & Alverson, 1997). This intensive harvesting could
potentially result in strong selection pressures for individuals with certain attributes. In
2006, the annual harvest of white-tailed deer in the southern lower peninsula of Michigan
exceeded 450,000 (Clute, 2006), representing roughly 53% of the estimated population
size for that area. Due to their abundant populations and their popularity as a big game
species, white-tailed deer serve as an excellent model organism to use in the investigation

of hunters’ selective harvest intentions and final harvest outcomes.

57

This study, investigated the effect of context-dependent (e.g., game availability,
area hunted, and hunting pressure) and context-independent (e.g., specialization,
persistence, centrality of hunting to lifestyle) factors on the successful harvest of antlered
deer in one wildlife management unit in southern Michigan. I linked hunter responses on
their mail questionnaire with the attributes of their respective harvested bucks to test
predictions about factors influencing harvest outcomes. If hunters are harvesting
selectively, one would expect that intentions to be selective would be associated with
harvested deer possessing specific attributes. For example, if a hunter intends to be
selective for only their ideal buck, I would expect them to harvest a buck with attributes
associates with an ideal buck. Other factors, however, might mitigate these intentions
and their relationship with harvest outcome. One such factor might be hunters’ level of
previous experience, which affects the amount, type, and diversity of information
available to an individual when making harvest decisions (Schreyer, Lime, & Williams,
1984). Hunters with more years of hunting experience are hypothesized to be more
knowledgeable about their hunting situation and specific method of harvesting (i.e.,
specialization; see Chapter 3). I would, therefore, predict that hunters with greater
hunting experience would be less influenced by factors other than their intention to be
selective. I also hypothesized that context-independent factors (i.e., days available to
hunt and the day a hunter started hunting), self-reported persistence and degree of
specialization (i.e., centrality of hunting to one’s lifestyle) were important for
determining harvest outcome. By examining relationships between context-dependent
and independent factors associated with hunters and the attributes of their harvested deer,

I hoped to gain a more comprehensive understanding of what influences whether hunters

58

successfully harvest an antlered deer and the likelihood that harvest pressures could result
in undesirable attribute changes of antlered white-tailed deer.
MATERIALS & METHODS

4.3 Survey methods

4. 3. 1 Sampling criteria & sampling fi'ame generation

Hunters’ attitudes toward white-tailed deer harvests were assessed using a mail
questionnaire. Data were collected fiom a sample of hunters based on the following
criteria: 1) Michigan residents, 2)18 years of age or older as of January 1, 2006, 3) had
purchased a license in 2006 to hunt white-tailed deer, and 4) had completed and returned
a 2003, 2004 or 2005 Michigan Department of Natural Resources (MDNR) harvest
questionnaire stating they had harvested a white-tailed deer (antlered or antlerless) from
within the research study area (see Chapter 2 for study area descriptions). The hunter
sample for the survey (n = 3,954) was derived from a portion of the total number of
firearm deer hunters who have previously hunted or hunt within the Saginaw Bay
Wildlife Management Unit (SBWMU) in Michigan. It was assumed that the sample
represented a cross section of individuals who have hunted the SBWMU in the past three
years.

4.3.2 Mail questionnaire

The self-administered mail questionnaire with repeat mailings was conducted
following Dillrnan (2000) beginning in January 2007. The mail questionnaire was
designed to assess the relative roles of context-dependent and independent factors related
to hunting (e.g., hunter persistence, landownership) in determining their relevance for

predicting harvest outcomes. Several context-independent factors that could potentially

59

affect harvest outcome were measured including selective harvest intentions, self-
reported persistence, experience (i.e., hunter age, number of years hunting) and centrality
of hunting to one’s lifestyle. Context—dependent factors were measured including hunting
pressure, number of days hunted, the day hunting began, land-type hunted (public,
private) and harvest date (see Chapter 2 for detailed descriptions of variables). Survey
participants were also asked to report their harvest success from the 2006 November
firearm deer season. To reduce the variability of factors contributing to harvest
outcomes, this survey focused specifically on firearm white-tailed deer hunting in the
SBWMU. Respondents were reminded to only provide information pertinent to firearm
deer hunting within the study area during the 2006 firearm deer-hunting season. All
survey methodologies were approved by the University Committee Involving Research
on Human Subjects and the Institutional Review Board (IRB #05-1028; see Appendix J).

Responses to the mail questionnaire are reported in Appendix E. Throughout the
results, percentages may not always add to 100 due to rounding. In reporting
percentages, “< 1%” indicates that at least one respondent was included in a category and
“0%” means that no one was included in a category.
4.4 Field methods

4. 4.1 Check stations

In order to quantify the harvest outcome for individual hunters, data were
collected on harvested deer at MDNR deer check stations. Attributes from a total of 751
antlered deer were measured at ten deer check stations during the 2006 November
firearm deer season (see Chapter 2). Morphometric data collection consisted of the

measurements of six traits including car length, hindfoot length, 62 tine length (left and

60

right), spread, total number of antler points and antler beam diameter (left and right; see
Chapter 2). These traits were identified through focus group discussions with firearm
deer hunters as being important to harvest outcomes (see Chapter 2).
4. 5 Data analysis

A generalized linear model (GLiM) with a logit link function was used to
determine the significance of factors hypothesized to influence the probability of a hunter
successfully harvesting an antlered deer. The binary response variable was whether a
hunter harvested (1) or did not harvest a buck (0). Chi-square tests were used to
determine if the number of respondents differed significantly among the factor levels of
centrality to lifestyle, intention to be selective, land-type hunted and the day that a hunter
started hunting. Interpretation of the model was based on odds ratios. The odds ratio is
the odds of a hunter being successful at one level of an independent variable divided by
the odds of a hunter being successful at another (lower) level of the same independent
variable while all other independent variables are held constant. An odds ratio greater
than 1.0 indicates a positive function of the independent variable whereas an odds ratio
less than 1.0 indicates a negative function of the independent variable. It was assumed
that the independent variables were linear combinations of each other and that
observations were independent. All assumptions were adequately met. The dispersion
parameter (1.004) of the harvest success model (i.e., binary response) was assessed using
the family quasibinomial and found to be satisfactory. Variance inflation factors were
also calculated for the final model and found to be satisfactory (i.e., values < 10).

Principal component analysis (PCA) was conducted on the correlation matrix of

the eight morphometric variables of harvested deer. The total number of antler points

61

was log transformed prior to the PCA to achieve normality. The first and second
principal components fi'om this analysis were used as dependent variables in general
linear modeling procedures to assess relationships between hypothesized hunter variables
and the attributes of harvested deer. Attribute measurements of antlered white-tailed deer
harvested and checked from within the SBWMU are reported as means i SE unless
otherwise stated.

Appropriateness of predictor variables for each model was determined based on
an exploratory modeling approach. Included in these models were variables
hypothesized to be important predictors of harvest outcome including the hunter’s
intention to be selective, preferences for trait attributes and context-independent factors
including previous hunting experience, self-reported persistence, and centrality of
hunting to the hunter’s lifestyle. The amount and distribution of missing data in the
survey responses prevented the use of likelihood based information theoretic approaches
(e.g., Akiake’s Information Criterion [AlC]) for model comparisons. As a result, an
improvised stepwise modeling approach was employed where models with increasing
complexity were evaluated using overall model p-values and a significance level of or =
0.05. Non-significant variables were removed. All two and three-way interactions were
also tested for significance in the model.

For the final fitted model, residual plots, Cook’s distance plots and Q-Q plots
were examined for heteroscedasticity, outliers, high leverage points and influential
points. Diagnostic plots indicated that there were no signs of heteroscedasticity or
observations with undue influence on the relationship. All values for the linear model are

presented as means :t SE. Results include significant variable results (t-test of parameters

62

and their standard errors). All analyses were preformed using R (R Development Core
Team, 2006).
RESULTS

Forty-three percent of respondents harvested a buck during the 2006 November
firearm deer season (1,021 of 2,358 respondents). Centrality of deer hunting to one’s
lifestyle (7823012: 14.72, P < 0.001), intention to be selective (383,200, = 21.66, P < 0.001),
land-type hunted (3813003 = 32.70, P < 0.001) and the day that a hunter started hunting
(3613007 = 44.67, P < 0.001; Table 4.1) were significant factors when predicting harvest
success. If deer hunting was not important to a hunter, the probability of successfully
harvesting an antlered deer was reduced relative to hunters who deemed hunting a more
important recreational activity (see Figure 4.1). Furthermore, hunters that intended to
harvest an ideal or preferred buck but who were also willing to shoot a least preferred
buck were close to one and a half times more likely to successfully harvest a buck
compared to hunters who intended to harvest any legal buck (0.34 :t 0.11, z = 3.04, P <
0.01; Figure 4.2). The most selective class of hunters (i.e., those that intended to harvest
only their ideal buck), however, had a marginally lower predicted probability of
successfully harvesting an antlered deer compared to hunters that were willing to harvest
any legal buck (-0.33 i 0.18, z = -l .88, P < 0.06; see Figure 4.2). Hunters that hunted on
public land also had lower predicted harvest success relative to those who hunted on
private land (07] i 0.13, z = -5.29, P < 0.001; see Figure 4.3). Finally, if a hunter
started hunting on the first day of the season, they were three times more likely to harvest
an antlered deer (1.00 i 0.16, z = 6.35, P < 0.01; see Figure 4.4) compared to hunters

who started hunting after opening day.

63

Attributes of 751 harvested antlered white-tailed deer were measured at eight
MDNR deer check stations representing 21% of all antlered white-tailed deer checked at
these stations. Yearlings (1.5 year old bucks) were represented the most in the harvested
bucks checked (N = 310; 41.2 %). Also, the number of deer harvested per day
irrespective of age classes, decreased with time (see Table 4.2). Deer measured for this
study also did not differ in age structure from all 3,659 deer checked by the MDNR in
these areas (x2 = 2.7, df = 3, P = 0.43; Table 4.3). Antlered white-tailed deer harvested
and checked from within the SBWMU (N = 751; Table 4.4) had average beam diameters
of 21 .3 i 3.3 mm (lefi beam) and 21.5 i 3.4 mm (right beam). Harvested deer also had
average hindfoot and ear lengths of 40.6 i 2.1 and 16.0 i 1.3 cm, respectively. Left and
right G2 tine lengths were 9.2 i 3.0 and 9.1 :1: 3.0 cm, antler spread averaged 24.8 i 6.7
cm and number of antler points averaged 6.0 i 2.0. For the first principal component all
antler characteristics loaded positively so that large values indicated larger antlers overall
(Table 4.5). All antler characteristics except for the left and right G2 tine lengths loaded
negatively into the second principal component and both body size measurements (i.e.,
hindfoot length and ear length) loaded positively and were large values (Table 4.5). As a
result, first principal component scores were interpreted as overall antler size and second
principal component scores were interpreted as measures of body size relative to antler
size, where larger values represent larger body size relative to antler size. Sixty-four
percent of the variation in deer attributes was explained by the two principal component
axes (Table 4.5).

A general linear model (GLM) was used to explain the effects of years of hunting

experience, intention to be selective, preferences, and the interaction between the

64

intention to be selective and years of hunting experience on PCI . The overall model of
these effects explained 6% of the variation in PC] (i.e., antler size) of harvested white-
tailed deer (F 11,369 = 2.29, P = 0.01; Table 4.6). There was a marginally significant
negative interaction (1311369 = 2.29, -0.65 i O.37,t = -l .75, P = 0.080; Figure 4.5) between
the intention to be selective and three years of firearm deer hunting experience. For
experienced hunters, antler size of harvested deer increased whereas with increasing
selectivity there was no effect of selectivity on the antler size of deer harvested by
inexperienced hunters. Furthermore, minimum and maximum (legal 3” spike or > 11
points) point preference for preferred bucks had a significantly greater negative effect on
PCI traits of a harvested buck (legal 3” spike: -1.66 i 0.52, df = 4, t = -3.17, p < 0.01;
>11 points: -1.01 i 0.49, df = 4, t = -2.06, p < 0.05) as compared to point preference
being not at all important. Overall, the model explained only a small (6 %) amount of the
variation in the attributes of harvested bucks.

A general linear model (GLM) of PC2 explored the effects of several variables,
however, the final reduced model only included the day of the season that a hunter started
hunting, previous harvest experience, and preferences for the age of the least preferred
category of bucks. Several variable interactions were investigated but none of these were
significant and were, therefore, not included in the final model. The overall model
explained 4% of the variation in PC2 (i.e., body size relative to antler size) of harvested
white-tailed deer (F6362= 2.59, P = 0.018; Table 4.7). Previous successful harvest
experience was negatively related (t362 = -1.72 :1: 0.30, df = 1, P = 0.08) to PC2 as
compared to unsuccessful harvesting. Least preferred buck age preference of a 1.5-year-

old buck was the only significant factor level to influence PC2 traits (-0.35 i 0.13, df = 4,

65

t = -2.63, P < 0.05) in comparison to preferences not at all being important. Furthermore,
hunters that started hunting on opening day harvested deer with decreased body sizes
relative to antler size compared to hunters who began hunting after opening day (I362 = -
2.12, p = 0.04; see Figure 4.6).

DISCUSSION

Harvest-induced selection occurs only when there is consistent harvest pressure
that selects for specific traits (Coltman et al., 2003). If hunters who intend to be selective
in their harvest (i.e., harvest only their ideal buck or preferred buck), have homogenous
preferences for specific traits (e.g., total number of antler points), and are successful in
harvesting what they intend to harvest, then the preferential harvesting of bucks with 7-10
points, for example, would result in selective harvest pressures against bucks with those
attributes.

Unlike the bighom sheep hunters examined by Coltman et al. (2003), Michigan
deer hunters appear to be harvesting opportunistically. The likelihood that morphological
changes will occur in traits experiencing excessive harvest pressures is expected to be
minimal. Preferences for attributes are not consistent, and therefore, the selective
pressures against any one specific attribute are not consistent. Although hunters have
reported intentions to harvest specific bucks, harvest intentions could likely be influenced
by a hunters’ certainty that a buck of such a category exists where they hunt. Such
variability suggests that harvest opportunities and relative abundance of those bucks are
likely sources of stochasticity.

When harvest decisions are made selectively, the potential exists for these actions

to affect herd composition (Harris et al., 2002). Using the model predicting harvest

66

success, I found that the intention to be selective was a significant predictor of whether a
hunter harvested a buck, such that hunters that intended to harvest any legal buck were
less successful than those hunters who intended to harvest a specific buck category. This
result is contrary to what would be expected because hunters who are willing to harvest
any legal buck are less restrictive when harvesting specific attributes. However, hunters
who intend to harvest an ideal only buck are likely hunters who invest more time in
hunting, have greater motivation and commitment, and are more specialized (Kuentzel &
Heberlein, 1992) thereby improving their chances of harvest success.

The successful harvest of a buck during the 2006 November firearm deer season
was also predicted by how central deer hunting was to the respondent’s lifestyle in
comparison to other recreational activities. The positive effect of centrality of deer
hunting to one’s lifestyle on harvest success differs fiom work on anglers that suggested
that lifestyle did not affect catch-and-release behavior (Sutton, 2003). This result was
expected because as hunters become more involved with hunting, their specialization and
motivation to participate in the activity would increase. The land-type hunted was also
found to influence success such that hunters that hunted public land, had lower success.
This could be the result of more hunting pressure, or low game availability encountered
in public hunting areas. The day a hunter started hunting, influenced success as well.
Opening day proved to be the most successful as most hunters were not willing to wait
and harvest their buck and risk the chance of not being successful. Most deer were
harvested on the first day of the hunting season, suggesting that hunters where not
motivated enough to be selective or persistent in their intentions, to encounter

opportunities to be more selective. All of these findings indicate that harvest success is

67

highly variable among the hunting population. One common theme among each of these
findings is that motivation might be an important determinant in harvest success as well.

Research has suggested that motivations are important determinants of whether a
hunter harvests an antlered versus antlerless deer (Bhandari et al., 2006), but no
comparable research investigating if casual hunters have lower success rates exists. If
motivations were important to harvest success rates, two opposing patterns would have
emerged in my data. One would be that highly motivated hunters would be expected to
have a higher success rate than compared to hunters who are not highly motivated.
Secondly, hunters who are highly motivated but also highly selective could be as
unsuccessful as hunters who were not highly selective or motivated.

The interaction between the intention to be selective and years of hunting
experience (Figure 4.5) were investigated for their combined influence on harvest
outcome. Hunters who intended to be more selective did harvest bucks with larger
antlers if they were experienced hunters but not if they were inexperienced. These results
would cause one to expect that more selective hunters would harvest larger bucks.
According to the harvest data however, selective hunters didn’t always harvest bucks
with more points. This could be because of hunter motivation for pursing bucks with
specific attributes or hunter preferences for attributes. Harvest composition was
comprised of yearling-aged bucks harvested on opening day. Given that most bucks are
harvested the first day of the season suggests that hunters might intend to be selective but
are not waiting long enough to do so; or they remain less selective and harvest the first
opportunity presented to them. The two models that were developed to explain variation

in attributes of harvested bucks, explained very little (PCl model: 6%, PC2 model: 4%).

68

It is suggested that to more accurately predict the size of antlered deer harvested, spatio-
temporal factors (e.g., geography, land-use; McCullough, 1984) in conjunction with
hunter factors will need to be examined to provide a greater comprehensive assessment of
their relationship to harvest outcomes.

Preferences for both the total numberof antler points and the age of specific buck
categories were found to influence the attributes of harvested deer. This is an important
finding since the determinants of specific attributes of a harvested deer were previously
only speculative (F esta-Bianchet, 2003). Now though, it seems that hunter preferences
for two specific deer attributes have an important influence on the attributes of harvested
bucks. If these two attributes remain the primary deciding attribute of whether to harvest
a buck, management to limit the removal of bucks with these attributes from a population

need to be developed.

69

Tables & Figures

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Centrality to Lifestyle

Figure 4.1. Effects of centrality of deer hunting to one’s lifestyle on the probability of
successfully harvesting an antlered deer. The y-axis is a log-odds scale representing the
likelihood of a hunter successfirlly harvesting an antlered white-tailed deer. The mid-line
of each box represents the median probability of success for those respondents who
indicated the centrality of hunting to their lifestyle had greater importance. The box
indicates the boundary created by the lowest and highest 25% of the data. The whiskers
encompass the smallest and largest non-outlier observations while the open circles

represent outliers.

70

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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buck buck only

Figure 4.2. Probability of success given a hunter’s intention to be selective for a buck
category. Any legal buck refers to a buck with at least 3” antler tines. An ideal buck is
defined as those that you would not hesitate to take if the opportunity presented itself.
The y-axis is a log-odds scale representing the likelihood of a hunter successfully
harvesting a category specific buck. The mid-line of each box represents the median
probability of success. The box indicates the boundary created by the lowest and highest
25% of the data. The whiskers encompass the smallest and largest non-outlier

observations whereas the open circles represent outliers.

71

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Figure 4.3. Differences in the probability of predicted harvest success between hunters
on private and public land. The y-axis is the probability a hunter successfully harvesting
a buck. The mid-line of each box represents the median probability of success for those
respondents who indicated the land type they hunted. The box indicates the boundary
created by the lowest and highest 25% of the data. The whiskers encompass the smallest

and largest non-outlier observations whereas the open circles represent outliers.

72

 

 

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Day Started Hunting

Figure 4. 4. Differences between the day that a hunter started hunting and the probability
of harvest success. The y-axis is the probability a hunter successfully harvesting a buck.
The mid-line of each box represents the median probability of success for those
respondents who indicated the day of the season that they started hunting. The box
indicates the boundary created by the lowest and highest 25% of the data. The whiskers
encompass the smallest and largest non-outlier observations whereas the open circles

represent outliers.

73

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Intention to be Selective

Figure 4. 5. Box plot displaying the interaction between the intention to be selective and
the number of years of hunting experience as influencing principal component one. The
interaction is negative suggesting that the intention to be selective only matters for
experienced hunters (i.e., light grey) whereas for inexperienced hunters (i.e., dark grey)
the intention to be selective appears to have no modulating effect on harvest outcome in

terms of antler size.

74

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Figure 4.6. Differences between the day that a hunter started hunting (0 = opening day of
November 15‘”, 2006 or any day afier opening day) in the second principal component
score of their harvested deer. Large values of PC2 are interpreted as small antler size
relative to large body size. In contrast, small values of PC2 represent larger antler size

relative to body size.

75

Harvest Success Model

 

 

Estimates B SE 2 Odds ratio P
Intercept p-0.86 0.17 -4.84 . 0.42 < 0.01
Centrality of hunting to
lifestyle . .
More Important -0.13 0.10 -1.32 0.87 0.19
Not Important .. -0.63 0.16 -4.01 0.53 < 0.01
Selectivity intentions ..
Ideal to Preferred to
Least Preferred 0.34 0.1 1 3.04 1.40 < 0.01
[deal to Preferred -0.20 0.13 -1.60 0.81 0.1 1
Ideal Only -0.33 0.18 -1.89 0.72 0.06
Land ownership ., . .
Public -0.71 0.13 -5.29 7 0.49 < 0.01
Day began hunting
First day of the season 1.00 0.16 6.35 2.73 < 0.01

Table 4.1. The final model parameter estimates for predicting the harvest success of a

hunter. Odds ratio values > 1 indicate a positive relationship between the variable and

predicting harvest success. An odds ratio value < 1 indicates a negative association.

Selectivity intentions are relative to a hunters’ intention to harvest any legal buck. Land

ownership is relative to hunting on private land, and the day began hunting is relative to a

hunter who started hunting any day after opening day. The centrality of deer hunting to

one’s lifestyle is relative to deer hunting being considered a hunters’ most important

recreational activity.

76

Day of Harvest

 

 

Age Class 1 st 2nd 3rd 6th 9th 10th
1.5 310 66 55 6 6 4
2.5 78 16 1 9 3 3 1
3.5 26 1 1 7 0 0 0
4.5 4 0 2 0 0 0
8.5 1 0 0 0 0 2

 

Table 4.2. The number of deer harvested per hunting day by age classes.

77

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78

PCl represents antler size while PC2 is body size
relative to antler size

 

 

Age Classes

Phenotypic Traits 1.5 2.5 3.5 4.5

(N) (495) (137) (51) (6)
Left G2 Tine Length (cm) 9.21fl.97 123614.29 14.212t4.00 12.301556
Right GZ Tine Length (cm) 9.07:2.97 12.26i4.35 14.02i4.24 13.24i4.84
Lefi Beam Diameter (mm) 21 .27i3.33 25.84i4.63 28.57i4.21 27.001210
Right Beam Diameter(mm) 21 .46:3 .42 25.68i4.97 28.67i4.42 28.33i3.08
Hindfoot Length (cm) 40.64zt2.07 40.941216 40.99i2.23 40.75i3.67
Ear Length (cm) 15.97i1.28 16.14i0.88 16.20i1 .04 16.77i0.88
Beam antler spread (cm) 24.82i6.66 34.581276 39.56i7.07 38.242t7.38
Total number of points 5.25:1.94 7.18:2.03 7.98i1.67 7.33:1: 1.63

 

Table 4.4. Eight morphological characters of four age classes of harvested white-tailed

deer (Odocoileus virginianus) from the Saginaw Bay Wildlife Management Unit in

Michigan during the November firearm deer season of 2006. Sample sizes (N) within

each age class are shown in parentheses.

79

Items PC 1 PC 2

Total number of points 0.76 -0.24
Left G2 Tine Length 0.70 0.13
Right G2 Tine Length 0.73 0.13
Left Beam Diameter 0.92 -0.09
Right Beam Diameter 0.90 -0.08
Outside antler spread 0.84 -0.16
Ear Length 0.26 0.51
Hindfoot Length 0.19 0.81
Eigenvalue 2.02 l .02
% explained variance 50.94 13.08

Table 4. 5. Factor loadings of the first and second principal components from principal

component analyses of eight morphological antlered deer traits.

80

PCl Model

 

 

Estimates B SE df t P
Intercept -0.74 0.74 - -l .07 0.31
Intention to be selective 0.66 0.35 1 1.85 0.06
Preferred buck point
preference 7 g 7 . _ .
Legal 3 ” spike -1.66 0.52 4 -3.17 < 0.01
3 — 6 points -0.50 0.35 4 -1.42 0.16
7 — 10 points -0.62 0.36 4 -1.73 0.08
Greater than 11 points -_1.01 0.49 4 -2.06 0.04
Years of hunting I
expenence , g . __ , . _ . _
3 years g 093.. 0.73 1 1.27 0.21
Least preferred buck age
preference _ , V
Fawn -0.20 0.36 4 -0.55 0.58
I ’/2 years old 0.44 0.29 4 1.51 0.13
2 ’/2 years old 0.13 0.41 4 0.33 0.74
3 ’/2 years old -.-_1-77 0.69 4 2.54 _ V 0.01
Intention to be selective x
Years ofhunting ;_ . __ _ _ . ,, . . -.
3 years -0.65 0.37 1 -l.75 0.08

Table 4. 6. The final model parameter estimates for predicting the morphological

characteristics of a harvested antlered deer in terms of the first principal component (i.e.

size of antler traits). Preferences for points and age are relative to preferences not at all

being important to a hunter.

81

PC2 Model

 

 

Estimates B SE df t P
Intercept 1.23 4_ 0.4 - 3.05 . < 0.01
Day when started hunting

First Day (Opening Day) -0.61 0.29 g 1 -2.12 0.04

Harvest Experience . .. ,_ _ . g ‘
Successful -0.5 1 0.3 1 -1 .72 0.09
Least preferred buck age
preference _. __ _
Fawn -0.33 0.18 4 -1.89 0.06
I ’/2 years old -0.35 0.13 4 -2.63 0.01
2 ’/2 years old -O.20 0.20 4 -1.05 0.30
3 ’/2 years old -0.06 0.35 4 -0.16 0.87

Table 4. 7. The final model parameter estimates for predicting the morphological
characteristics of a harvested antlered deer in terms of the second principal component

(i.e. size of body traits relative to antler size).

82

REFERENCES

Ajzen, I. (1991). The theory of plannedBehavior Relation. Human Relations, 27(1), 1-15.

Ajzen, 1., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior.
New Jersey: Prentice-Hall, Inc.

Bath, A., Bissell, S. J., Blanchard, K. A., Brown, T. L., Chase, L. C., Connelly, N. A., et
al. (2001). Human Dimensions of Wildlife Management in North America.
Bethesda, Maryland: The Wildlife Society.

Bhandari, P., Stedman, R. C., Luloff, A. E., Finley, J. C., & Diefenbach, D. R. (2006).
Effort versus motivation: factors affecting antlered and antlerless deer harvest
success in Pennsylvania. Human Dimensions of Wildlife, 11, 423-436.

Browman, H. I. (2000). 'Evolution' of fisheries science. Marine Ecology Progress Series,
208, 299-313.

Buchanan, T. (1985). Commitment and leisure behavior: A theoretical perspective.
Leisure Sciences, 7, 401-420.

Clute, R. (2006). 2006 Michigan Deer hunting prospects: the statewide forecast. Lansing,
MI: Wildlife Division.

Coltman, D. W., O'Donoghue, P., Jorgenson, J. T., Hogg, J. T., Strobeck, C., & Festa-
Bianchet, M. (2003). Undesirable evolutionary consequences of trophy hunting.
Nature, 426, 655-658.

Coltman, D.W. (2008). Molecular ecological approaches to studying the evolutionary
impact of selective harvesting in wildlife. Molecular Ecology, 17, 221-233.

Conover, D. 0., & Munch, S. B. (2002). Sustaining fisheries yields over evolutionary
time scales. Science, 297, 94-96.

Dillrnan, D. A. (2000). Mail and internet surveys: the tailored design method (V 01. 2nd
edition). New York: John Wiley and Sons, Inc.

Frait, F ., Hartl, G.B., Lovari, S., Delibes, M., & Markov, G. (1998). Quaternary radiation
and genetic structure of the red fox Vulpes vulpes in the Mediterranean Basin, as
revealed by allozymes and mitochondrial DNA. Journal of Zoology, 245, 43-51.

Festa-Bianchet, M. (2003). Exploitative wildlife management as a selective pressure
for life-history evolution of large mammals. In M. Apollonio & M. F esta-
Bianchet (Eds.), Animal Behavior and Wildlife Conservation (pp. 191-207).
Washington, DC: Island Press.

83

Gross, D. (1975). Protein Capture and Cultural Development in the Amazon Basin.
American Anthropologist, 77, 526-549.

Harris, R.B., Wall, W.A., & Allendorf, F .W. (2002). Genetic consequences of hunting:
what do we know and what should we do? Wildlife Society Bulletin, 30(2), 634-
643.

Heberlein, T.A., & Kuentzel, W.F. (2002). Too many hunters or not enough deer?
Human and biological determinants of hunter satisfaction and quality. Human
Dimensions of Wildlife, 7, 229-250.

Hrubes, D., Ajzen, 1., & Daigle, J. (2001). Predicting hunting intentions and behavior: an
application of the theory of planned behavior. Leisure Sciences, 23, 165-178.

Kennedy, J .J . (1974). Attitudes and behavior of deer hunters in a Maryland forest. Journal
of Wildlife Management, 38(1), 1-8.

Kim, S., Scott, D., & Crompton, J .L. (1997). An exploration of the relationships among
social psychological involvement, behavioral involvement, commitment, and
future intentions in the context of birdwatching. Journal of Leisure Research, 29,
320-341.

Kinnison, M. T., & Hendry, A. P. (2001). The pace of modern life 11: from rates of
contemporary microevolution to pattern and process. Genetica, 112-113, 145-164.

Kuentzel, W. F., & Heberlein, T. A. (1992). Does specialization affect behavioral choices
and quality judgments among hunters? Leisure Sciences, 14, 211-226.

Lee, T.E.J., Derr, J .N., Bickham, J .W., & Clark, TL. (1989). Genetic variation in
pronghom from west Texas. Journal of Wildlife Management, 53, 890-896.

Loehr, J ., Carey, J ., Hoefs, M., & Suhonen, J. (2006). Hom growth rate and longevity:
implications for natural and artificial selection in thinhom sheep (Ovis dalli).
Journal of Evolutionary Biology, 20(2), 818-828.

Manski, C. F. (1990). The use of intentions data to predict behavior: a best-case analysis.
Journal of the American Statistical Association, 85(412), 934-940.

Martinez, M., Rodriguez-Vigal, C., Jones, O.R., Coulson, T., & Miguel, AS. (2005).
Different hunting strategies select for different weights in red deer. Biology
Letters of The Royal Society, 1(3), 353-356.

Milner, J. M., Nilsen, E. B., & Andreassen, H. P. (2006). Demographic side effects of

selective hunting in ungulates and carnivores. Conservation Biology, 21(1), 36-
47.

84

Miller, CA. & Graefe, AR. (2001). Effect of harvest success on hunter attitudes toward

white-tailed deer management in Pennsylvania. Human Dimensions of Wildlife,
189-203.

Miller, CA. & Vaske, J .J . (2003). Individual and situational influences on declining
hunter effort in Illinois. Human Dimensions of Wildlife, 8, 263-276.

Mysterud, A., Tryjanowski, P., & Panek, M. (2006). Selectivity of harvesting differs
between local and foreign roe deer hunters: trophy stalkers have the first shot at
the right place. Biology Letters of The Royal Society, 2(4), 632-635.

Palumbi, S. R. (2001). Humans as the world's greatest evolutionary force. Science, 293.

R Program. (2006). R: A language and environment for statistical computing (Version
2.4.0). Vienna, Austria: R Core Development Team.

Ratner, S., & Lande, R. (2001). Demographic and evolutionary responses to selective
harvesting in populations with discrete generations. Ecology, 82(11), 3093-3104.

Redford, K. H., & Robinson, J. G. (1987). The game of choice: patterns of Indian and
colonist hunting in the neotropics. American Anthropologist, New Series, 89(3),
650-667.

Reznick, D. N., & Ghalambor, C. K. (2001). The population ecology of contemporary
adaptations: what empirical studies reveal about the conditions that promote
adaptive evolution. Genetica, 112-113, 183-198.

Singer, F .J ., & Zeigenfuss, LC. (2002). Influence of trophy hunting on horn size on
mating behavior and survivorship of mountain sheep. Journal of Mammalogy,
83(3), 682-698.

Sutton, S. G. (2001). Understanding catch-and-release behavior of recreational anglers.
Unpublished Dissertation, Texas A&M University, College Station, Texas.

Sutton, S. G. (2003). Personal and Situational Determinants of Catch-and-Release choice
of freshwater anglers. Human Dimensions of Wildlife, 8, 109-126.

Sutton, S. G., & Ditton, R. B. (2001). Understanding catch-and-release behavior among
US. Atlantic bluefin tuna anglers. Human Dimensions of Wildlife, 6, 49-66.

Swain, D.P., Sinclair, A.F., & Hanson, J .M. (2007). Evolutionary response to size-

selective mortality in an exploited fish population. Proceedings of the Royal
Society B: Biological Sciences, 274(1613), 1015-1022.

85

Tenhumberg, B., Tyre, A.J., Pople, A.R., & Possingham, H.P. (2004). Do harvest
refiJges buffer Kangaroos against evolutionary responses to selective harvesting?
Ecology, 85(7), 2003-2017.

Van Deelen, T.R., & Etter, DR. (2003). Effort and the fimctional response of deer
hunters. Human Dimensions of Wildlife, 8, 97-108.

Waller, D. M., & Alverson, W. S. (1997). The white-tailed deer: a keystone herbivore.
Wildlife Society Bulletin, 25(2), 217-226.

86

CHAPTER 5

General Discussion

87

General Discussion

Harvest-induced selection occurs only when there is consistent harvest pressure
that selects for specific traits (Coltman et al., 2003). If hunters I) consistently prefer
extreme traits, 2) intend to be selective in their harvest (i.e., harvest only a preferred
buck) and 3) are successful in harvesting what they intend to harvest, then there will be
hunter-induced selection against bucks with preferred attributes. In this study, I found
support for the first premise that hunters prefer bucks with extreme traits, but there were
many hunters that intended to not be selective at all and harvest outcome was only
slightly affected by hunter selectivity indicating that hunter-induced selection on white-
tailed deer is likely weak.

5.1 Hunters prefer rare attributes

Hunters preferred attributes of bucks that represented a small proportion of white-
tailed deer in the SBWMU. The average harvested buck, however, did not reflect
hunters’ preferences for their ideal or preferred antlered deer attributes but instead the
regulation nrinirnum of at least a 3” spike antlered buck. If hunters harvested what they
preferred prior to the start of the firearm season, attribute preferences of hunters would be
reflected by their harvested buck as has been shown to be the case with recreational and
subsistence hunters (Mysterud et al., 2006; Ginsberg & Milner-Gulland, 1994).
However, as illustrated in Chapter 4, this is not the case with Michigan firearm deer
hunters that hunt in the SBWMU. This contradicts research findings that suggest
recreational and subsistence hunters do exhibit a harvest preference (Ginsberg & Milner-

Gulland, 1994).

88

Due to the limited availability of bucks with desirable attributes that are in high
demand by hunters, the chances that these bucks survive a hunting season would be low.
Therefore, highly preferable traits are likely being removed from populations each season
and these bucks do not have the opportunity to influence antler attributes of future
populations. This leads to sustained selection for smaller antler attributes because each
successive hunting season removes individuals with larger antler attributes. These hunter
preferences however, will only result in hunter-induced selection if hunters intend to be
selective for these attributes and are successful in harvesting what they intend to harvest.
5. 2 Many hunters do not intend to be selective

Many hunters instead intend to harvest any legal buck (i.e., opportunistic),
thereby maximizing their chances to harvest a buck during the firearm deer season.
Many reasons can be offered as to why hunter intentions often do not match their
preferences. For example, a motivating factor for such hunters’ harvest intentions would
not concern select attributes of bucks but instead potentially focus on social or economic
reasons for harvesting bucks. From a social standpoint, many hunters engage in hunting
because it’s a family tradition and something they can share with others. Hunters of this
mindset would be considered to place less emphasis on specific deer attributes and more
on the enjoyment of being able to hunt. For many though, deer hunting and harvesting is
a means of subsistence. Therefore, hunters might concern themselves with attributes
other than antlers, to justify their harvesting decisions.

Hunter satisfaction, if realized by the successful harvest of any legal buck, would
be met; however, it would be lacking if measured by preferences and selectivity

intentions being realized by hunters’ harvest outcomes. Some hunters intend to be

89

selective but lack access to the opportunities where the availability of deer that match
their selectivity intentions are abundant; therefore, instead of having the option to choose
among bucks they might settle for a buck they don’t prefer or have their selectivity
intentions realized by going home without having harvested a buck at all.

5. 3 Harvest outcome is largely stochastic

Despite the plurality of hunters who intend to harvest any legal buck, there was a
smaller subset of hunters who intended to be selective and only harvest a buck that met a
certain minimum standard. Hunters who intended to be more selective did harvest bucks
with larger antlers if they were experienced hunters but not if they were inexperienced.
Two hunters might have the same harvest intentions but only one is successful based on
their previous experience suggesting that no matter how selective an inexperienced
hunter intends to be, their experience levels limit them from successfully being more
selective.

F rom the large range of buck attributes that were harvested, it is apparent that no
one segment of the buck population is being harvested exclusively. Two-thirds of the
bucks collected for this study were harvested on the opening day of the season and two-
thirds of the harvest was yearling-aged bucks, which had attributes consistent with
hunters’ least preferred bucks (Table 5.1). The relationship between hunter intentions to
harvest any legal buck and harvest outcome highlights the breakdown between hunter
preferences and their intentions to be selective. Hunters do have preferences, but remain
unwilling to risk not at all getting a buck in order to get a buck that they prefer.

To determine the potential for hunter-induced selection it is necessary to predict

and assess the impacts of hunter harvests using empirical data (Coltman et al., 2003).

90

This research provided valuable information to the MDNR about their deer hunting
constituents’ preferences and intentions for the harvest of antlered white-tailed deer.

This research provided a starting point to determine if hunters have the capability through
harvesting practices in the SBWMU to cause observable changes in the antler
characteristics of white-tailed deer. It remains an important objective in future research
to determine the intensity and direction of harvest-induced selection that might lead to the

evolution of less desirable attributes in harvested animals.

91

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REFERENCES

Coltman, D. W., O'Donoghue, P., Jorgenson, J. T., Hogg, J. T., Strobeck, C., & Festa-
Bianchet, M. (2003). Undesirable evolutionary consequences of trophy hunting.
Nature, 426, 655-658.

Ginsberg, J. R., & Milner-Gulland, E. J. (1994). Sex-biased harvesting and population
dynamics in ungulates: implications for conservation and sustainable use.
Conservation Biology, 8(1), 157-166.

Mysterud, A., Tryjanowski, P., & Panek, M. (2006). Selectivity of harvesting differs
between local and foreign roe deer hunters: trophy stalkers have the first shot at
the right place. Biologr Letters of771e Royal Society (FirstCite Early Online
Publishing).

93

APPENDIX A

Focus Group Meeting Script

94

WHITE-TAILED DEER FOCUS GROUP SCRIPT

1. Introductions:

Facilitator:

Thank you for coming here this evening. My name is Elizabeth Ball and I am a
research assistant at Michigan State University working with Dr. Andrew G. McAdam.
The purpose of tonight’s meeting is to gain insight into how hunters select the deer they
want to harvest and whether those preferences might effect the genetics of deer over time.
We want to design a survey that will be mailed out to a large sample of deer hunters, but
to do that we need to get a better understanding of what questions to ask and how best to
ask them. That is why we are here this evening. I’d like you to help me explore this idea
of selecting the deer to harvest and then I will use that information to design our survey.
We’ll also be taking some preliminary physical measurements of deer at check stations
based on what we learn here tonight to further explore whether any patterns emerge. For
this discussion we are going to focus on firearm hunting in the Saginaw Bay management
unit.

I’d like to acknowledge the fact that meetings recently regarding Deer Population
Goals have been held throughout the state. I’d like to inform you that this isn’t about any
of that. However, I feel this meeting and what we will be discussing is equally important.
If you do not feel it is important or you do not find interest in what we will be discussing
here tonight, then you are free to leave. If you happen to choice this option, I thank you
for coming regardless of your decision to not participate.

We won’t be asking any personal questions, but I want to assure you up front that
everything that is said here tonight is confidential. At no time will any of your responses
be associated with your name. We will only use first names in our discussion, and your
names will not be included in the report of this study.

2. What our task is here tonight:

a. The purpose of this study is to find out Whether or not hunters represent a
SELECTIVE FORCE that could act on the genetic makeup and biology of
deer over time. We are restricting ourselves in this first exploration to
THE SAGINAW BAY MANAGEMENT UNIT and the buck harvest
choices made by hunters during the FIREARM deer season, although we
may also have time to ask about antlerless decisions.

b. If you permit me, I would like to tape our discussions. This is only so I can
correctly record what is said here tonight and concentrate on the
discussion rather than take detailed notes. Once I have made my notes
from the tape it will be erased. Your identity will be confidential. Again,
we will only use first names in our discussion, and your names will not be
included in the report of this study. May I proceed with taping this

95

meeting?

To get the most out of our discussions tonight, there are a few simple
ground rules for us to follow.

vi.

vii.

It is important that each of you share what is on your mind. We
will often be following a “round robin” format. This means that I
will go around the room and ask each individual in turn to provide
their point of view. If you have more than one idea, give the most
important one first and then we’ll move on to the next person.
We’ll keep going around the table until all the ideas are collected.
Part of my job as moderator is to ensure that everyone has a chance
to share their views. Sometimes we will use this round robin
approach and sometimes we can just have an open discussion.

Please don’t be swayed by other opinions if you have a different
point of view. I expect that there will be differences of opinions in
this group and it is important to know what the group disagrees on
as well as agree. We are not here to persuade each other of
anything, but rather to share our opinions.

I am not looking for any particular responses to the questions I
have for you. There is no right or wrong answers. I would like you
to share your views and respect the views of others although you
may disagree.

Any time that a question is unclear, please ask for clarification

As facilitator, I may ask you to be brief and I may need to interrupt
you or redirect the conversation. Please know up front that I do not
mean to be rude or discourteous but we have a carefully designed
set of research questions and I am just trying to keep to our
schedule and achieve our goals.

Please speak one at a time and loud enough so that everyone here
can hear your comments.

Finally, we only have two hours to discuss several things which are
central to this study. So, let’s try to stay on track. Personal
experiences are interesting, but we need to stick to topics that will
help me understand what deer characteristics you use when you
decide to harvest or to pass. We have scheduled the meeting for
two hours, but we have much to discuss. Should the need arise,
would you be willing to stay until 9:30?

96

viii. My task is to keep everyone on the topic and your task is to
provide your experience and input. Does anyone have any
questions on the ground rules?

ix. Is everyone OK with the ground rules?

x. All of you should have been given one of the surveys when you
came in. Please do not forget to leave that with me. This provides
me with a better profile for the group and covers some items so we
don’t have to take time from our discussions. Please don’t put
your name on it.

xi. Any questions about any thing related to our meeting this evening?
Say where the restrooms are located.

(I. I would like to start the meeting by going around the table and having you
introduce yourself — first names only, please — and telling me where you
live within the Saginaw Bay Management Unit.

FOCUS OF THE MEETING

1. a. We might have a mix of hunters here that range from definite trophy hunters to folks
who are interested only in the hunt experience and putting venison in the freezer. But
every deer hunter goes to the field with some set of expectations or hopes and some
notion about the type of deer they will shoot.

b. Just to get us started, think about 3 categories of bucks when you hunt in the 10
county Saginaw Wildlife Management unit. The ideal buck you’d like to harvest, the
preferred buck to take if the ideal doesn’t show, and the last resort buck that you’d take
if you had to.

c. We’re going to talk about what physical characteristics make that an ideal buck, a
preferred buck or a last resort buck. Then we are going to talk about what conditions or
factors cause you to shift your decision from one to the other. Let’s take factors like

safety, legal shooting time, clean shot, and ethical shot out of the picture. We can assume
we are talking about a buck harvest opportunity that already meets those criteria.

HARVESTABLE DEER LEVEL #1
2. Let’s consider what characteristics would make a buck your ideal buck.

a. Let’s go around the table and each of you give me the one most important
characteristic of a buck that you feel would make it your ideal buck.

97

b. Just give me one and we will move on to the next person and keep going
around until the ideas are all out. 1 will write them on the easel so we can
keep track of them. If someone has already mentioned your most important
attribute, tell me that and I’ll add a check for everyone who says that is
most important.
c. Jon Doe, let’s start with you. What is the most important characteristic of a
buck that qualifies it as an ideal buck for you?
These are the most important things you look for in an ideal buck, any other
characteristics that may not be so important, but they do count? [I’d open this up to the
group and list them on the easel as they come up with things]

3. Now that we have a composite list of characteristics that make a buck ideal I need
a better sense of how important these are to the group. [clean up the list if it
needs it; collapse any; make sure you understand what each item means and ask if
any are unclear to you; might also ask the group if the list is clear to them]

A. Take a minute to consider the list and decide what is the most important

B. I’ll give you 3 votes, so you can hold up your hand and vote for the three things on the

list most important to you

C. So, how many would put this one in the top 3 to 5 most important characteristics of an

ideal deer in the Saginaw Bay Wildlife Management Area?

4. Now, I need to be sure I understand how you judge a buck’s physical
characteristics. Some are obvious, but let’s take this one [e.g., body size]. If there isn’t
another deer to compare it against, what features of the deer tell you that it has an ideal

[body size]?

PROBE: How do you judge a characteristic you listed (quantifiable)?

NOTE: this section will be repeated in order to guantm traits for each deer level.
BODY SIZE

-Total length?

-Shou1der height?

-Size of brisket?

-Relative proportion of body size to leg length?

-Ground shrinkage?
AGE

-Behavior?

-Social interactions with other deer?
ANTLER SIZE

-Ear length?

-Diarneter of antler beams?

-Number of points?

-Spread of antlers?

-Configuration: typical vs. non-typical?

- Antlers wider than ears?

98

MISCELLANEOUS
-Tail length?
-Hind foot length?
-Behavior?
-Color of tarsus glands?

HARVESTABLE DEER LEVEL #2

5. Let’s consider what characteristics would make a buck your preferred buck if the
ideal buck isn’t available.

a. Let’s go around the table and each of you give me the one most important
characteristic of that buck that you feel would make it your preferred buck and
that helps you to decide whether to harvest it or not.
b. Just give me one and we will move on to the next person and keep going
around until the ideas are all out. I will write them on the easel so we can
keep track of them. If someone has already mentioned your most important
attribute, tell me that and I’ll add a check for everyone who says that is
most important.
c. Jon Doe, let’s start with you. What is the most important characteristic of that
buck which would make it your preferred buck?

6. Now that we have a composite list of characteristics that make a buck ideal I need a
better sense of how important these are to the group.

A. Take a minute to consider the list and decide what is the most important

B. Let’s use a show of hands, by voting any number of times until the list is ranked to
show which are the most important characteristics of an ideal deer in the Saginaw Bay
Widlife Management Area as far as you are concerned.

C. So, how many would put this one in the top 3 to 5 most important characteristics?

7. [IF THERE ARE NEW FEATURES ON THE LIST, OTHERWISE THIS
WOULD NOT BE NECESSARY TO REPEAT WOULD IT?]Now, I need to be sure
I understand how you judge a buck’s physical characteristics. Some are obvious, but let’s
take this one [e.g., body size]. If there isn’t another deer to compare it against, what
features of the deer tell you that it has an ideal [body size]?

PROBE: How do you judge a characteristic you listed ]guantifiablc]?

NOTE: this section will be repeated in order to guantfiy’ traits for each deer level.
BODY SIZE

-Total length?

-Shoulder height?

-Size of brisket?

-Relative proportion of body size to leg length?
-Ground shrinkage?

99

AGE

-Behavior?

-Social interactions with other deer?
ANTLER SIZE

-Ear length?

-Diameter of antler beams?

-Number of points?

-Spread of antlers?

-Configuration: typical vs. non-typical?

- Antlers wider than ears?
MISCELLANEOUS

-Tail length?

-Hind foot length?

-Behavior?

-Color of tarsus glands?

HARVESTABLE DEER LEVEL #3

8. If neither an ideal buck nor a preferred buck show up, what are their
characteristics that even your last resort buck must have?

a. Let’s go around the table and each of you give me the one most important
characteristic of that buck that you feel would make it your last resort buck and
that helps you to decide whether to harvest it or not.
b. Just give me one and we will move on to the next person and keep going
around until the ideas are all out. I will write them on the easel so we can
keep track of them. If someone has already mentioned your most important
attribute, tell me that and I ’11 add a check for everyone who says that is
most important.
c. Jon Doe, let’s start with you. What is the most important characteristic of that
buck which would make it your last resort buck?

9.Now that we have a composite list of characteristics that make a buck a last resort I
need a better sense of how important these are to the group.

A. Take a minute to consider the list and decide what is the most important

B. Let’s use a show of hands, and you can vote any number of times until the list is
ranked to show which are the most important characteristics of an ideal deer in the
Saginaw Management Area as far as you are concerned.

C. So, how many would put this one in the top 3 to 5 most important characteristics?

10. Now, I need to be sure I understand how you judge a buck’s physical
characteristics. Some are obvious, but let’s take this one [e.g., body size]. If there isn’t
another deer to compare it against, what features of the deer tell you that it has an ideal

[body size]?

100

PROBE: How do you judge a characteristic you listed jguantifiable]?

NOTE: this section will be repeated in order to guanp’fy traits for each deer level.
BODY SIZE

-Total length?

-Shoulder height?

-Size of brisket?

-Relative proportion of body size to leg length?

- Ground shrinkage?
AGE

-Behavior?

-Social interactions with other deer?
ANTLER SIZE

-Ear length?

-Diameter of antler beams?

-Number of points?

-Spread of antlers?

-Configuration: typical vs. non-typical?

- Antlers wider than ears?
MISCELLANEOUS

-Tail length?

-Hind foot length?

-Behavior?

-Color of tarsus glands?

ROUND ROBIN: I need a sense of how often you are able to harvest an ideal buck,
a preferred buck and a last resort buck.

a. In the last 5 years of hunting in this part of M1 (the SBWMU), how many of
those years have you harvested the ideal buck with a FIREARM as your first buck of
the season?

PROBE: how many years out of the past 5 have you harvested an
ideal buck during ARCHERY season instead of firearm season?

PROBE: how many years out of the past 5 have you harvested an
ideal buck during FIREARM season as your SECOND buck of the year?

b. In the last 5 years of hunting in this part of MI (the SBWMU), how many of
those years have you harvested the preferred buck with a FIREARM as your first
buck of the season?

c. Now how many years of the past 5 in this part of MI (the SBWMU) have you
harvested what you would consider your preferred buck instead of an ideal buck
as your first FIREARM buck of the season?

101

d. Now how many years of the past 5 in this part of MI (the SBWMU) have you
harvested what you would consider your last resort buck instead of an ideal buck
as your first FIREARM buck of the season?

e. How many of you can remember the attributes of the bucks you have harvested
within the last five years?

ROUND ROBIN: I need a sense of how good you think you are at judging
the characteristics of a buck that you feel are most important?

f. How often are you correct in your judgment of a deer (i.e. it matches your
expectations and doesn’t suffer from ground shrinkage or turn out to be bigger
than you thought?).

i. When does this happen?

COMPROMISES FOR ALL LEVELS

Okay, the group has told me how often you are successful at harvesting your
ideal/preferred/last resort buck (i.e. the deer that either meets those standards that we’ve
just discussed or doesn’t). Now, I’d like you to think about what factors would cause you
to decide it was time to shift fi'om the “ideal” to the preferred buck quality. When and
why do you decide?

a. TO TAKE Your preferred instead of ideal buck;
b. TO TAKE Your last resort instead of preferred buck

PROBE: Do you go to the hunt with the intention to shoot the first preferred
buck unless an ideal buck comes through first?

PROBE: what causes the risk of not harvesting your ideal buck to become
greater than the intentions to harvest your preferred or last resort buck with all the
important characteristics?

1. When the season is running short (temporal constraints)
i. the longer I wait, the greater my chances are for not harvesting any legal buck
let alone my ideal buck
2. Availability of deer
i. as the season progresses, there are less deer available for harvest
3. Land type I am hunting
i. public lands
a. fewer deer
b. greater hunting pressure
ii. private lands
a. own: I am my own deer manager

102

b. rent / lease: I must manager deer for the land owner

BASED ON WHAT YOU’VE HEARD HERE TONIGHT, WHAT PROBLEMS ARE
WE GOING TO HAVE DESIGNING A SURVEY THAT WILL GIVE A VALID
MEASURE OF HOW MUCH SELECTIVITY IS GOING ON IN A GIVEN
MANAGEMENT UNIT?

EONCLU SION: This ends the formal part of our discussions. Are there any other

comments you would like to make concerning selective deer hunting or this evenings
discussions? I would like to thank you for assisting me in this study. If you have any
further questions or concerns, please feel free to contact me at the number on the letter I
provided when you came in. Once again thank you.

103

APPENDIX B

Focus Group Postcard Invitation

104

(originally printed on 4x6” notecard)

Dear Sir or Madam:

If you hunt white-tailed deer within the Saginaw Bay Management Unit, I’d like
to invite you to participate in a focus group discussing how hunters select the deer
they harvest. The Department of Fisheries and Wildlife at Michigan State
University will be holding these focus groups for research purposes in March.
Focus groups involve 8 to 12 people in a relaxed two-hour discussion led by a
trained facilitator. If you would be interested in discussing how harvest is affected
by hunter selectivity at such a meeting, please complete and return the attached
postage paid card. If you have any questions please contact me.

Sincerely,

Elizabeth Ball/ Project Coordinator
Michigan State University
Ph. 517-353-3030

Elizabeth Ball/Research Assistant
Department of Fisheries and Wildlife
Rm. 13 Natural Resources Building
Michigan State University
East Lansing, MI, 48824-1222

105

Elizabeth Ball

13 Natural Resources Bld.
Dept. Fisheries and Wildlife
Michigan State University
East-Lansing, MI 48824

RECIPIENT NAME
RECIPIENT ADDRESS

 

1) Please circle the counties in the Saginaw
Bay Management Unit where you hunt deer.

 

 

 

 

 

2) Which of the following seasons do you
hunt? (Check all that apply)

__ Archery

__ Firearm

3) How many of the following did you harvest last deer season? (If none write 0)
_antlered deer antlerless deer

If you are willing to participate in a focus group, please provide your name and
phone number below so we may contact you to arrange a time, date, and location
for the meeting.

Name:

 

(Area Code :) /

 

106

APPENDIX C

Focus Group Meeting Participant Consent Form

107

Focus Group Meeting for the Development of Michigan’s Firearm Deer Hunter
Selectivity Survey. Conducted by the Department of Fisheries and Wildlife,
Michigan State University

Dear Focus Group Participant,

Thank you for taking the time to participate in this two hour meeting. Focus groups are
an important way that the researcher’s gathers citizen’s views on issues like hunter
selectivity. The researchers will take tonight’s comments into consideration when
developing Michigan’s Firearm Deer Hunter Selectivity Survey.

Comments provided at this meeting should provide a wide range of views on deer
hunting selectivity. Meeting discussions will be used in developing a mail survey to be
sent to firearm deer hunters within the Saginaw Bay Management Unit.

Your participation at tonight’s meeting is voluntary. You may refuse to answer certain
questions or exclude yourself from parts of the discussion. You can be assured that all
data gathered will remain confidential and your privacy will be protected to the
maximum extent allowable by law. If you have questions about the study, contact Dr.
Andrew McAdam, 13 Natural Resources Building, Michigan State University, East
Lansing, MI 48824 or by phone at (517) 432-0396 or email at mcad)am_a@msu.edu. In
case you have questions or concerns about your rights as a research participant, please
feel free to contact Peter Vasilenko, Ph.D., Michigan State University's Chair of
University Committee on Research Involving Human Subjects by phone: (517) 355-
2180, fax: (517) 432-4503, email: <irb@msu.edu>, or regular mail: 202 Olds Hall,
Michigan State University, East Lansing, MI 48824-1047.

 

By printing and signing your name on the reverse side of this letter, you consent to your
voluntary participation in this meeting. To ensure an accurate documentation of tonight’s
comments, I am requesting that you permit me to audiotape the meeting. This is only so I
can correctly record what is said here tonight and concentrate on the discussion rather
than take detailed notes. Once I have made my notes from the tape it will be erased. By
printing and signing your name in the appropriate section on the back of this

letter, you consent to being audio taped tonight. For your reference/files, I am providing
you a copy of this letter to take home.

Sincerely,

Elizabeth Ball

Additional Investigator

Michigan State University
Department of Fisheries and Wildlife

108

I consent to my voluntary participation in this focus group:

(PRINTED NAME)

 

(SIGNATURE)

 

I consent to being audio taped during this focus group:

(SIGNATURE)

 

109

APPENDIX D

Focus Group Meeting Survey

110

SBMU FIREARM DEER HUNTER Focus GROUP MEETING
MARCH 20“, 2006
BAY COUNTY COMMUNITY CENTER
SAGINAW, MICHIGAN

1. Please check all of the seasons you typically hunt deer in the Saginaw Bay
Wildlife Management Unit counties.

Early Archery Firearm Late Archery Muzzleloader

3. What type of land do you deer hunt in the 10 county area of the SBWMU?

    
     
    
 

 
 

   
   
 

Public I e Arenac
— Clare ,Gledwinp.
Private Saginaw ay who".
IsabellaEMldlamIFf’f 3
Both E i 795“" Sanilac

 

Saginaw 3

    

4. Do you own land that you use for deer hunting in the SBWMU counties?

Yes No

 

 

UI

. Name up to 3 counties that you have hunted in the Saginaw Bay Wildlife
Management Unit in the past 5 years.

 

 

6. How many total antlered and antlerless deer have you harvested in the past 5
years in any of the Saginaw Bay Wildlife Management Unit counties?

Antlered Antlerless

Please turn over

:>

111

7. Please indicate how many of your harvested deer you have on display in your
home, business or elsewhere.

Number of head or shoulder mounts?

Number of full body mounts?

Number of European mounts (with skull and antlers)?

Number of antler-only mounts?

8. Do you hunt on land managed by a collaboration of private land owners in
this Saginaw Bay WMU where hunters are encouraged to shoot:

Only certain sized bucks Yes No

 

A certain number of does Yes No

 

 

9. On the land you hunt in this SBWMU, are there any restrictions imposed by
yourself, your hunting friends or the landowner regarding the deer that can
be harvested (other than the legal restrictions set by the MIDNR)? Please

explain.

112

APPENDIX E
“What Buck Would You Choose? A Survey of Deer Hunter

Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Instrument and Percent Response

113

What buck would you choose?
A survey of deer hunter preferences and
decisions in the Saginaw Bay Wildlife

Management Unit

RECIPIENT NAME
RECIPIENT ADDRESS

 

—'

Clare :Gladwin .

...Saginau 1

  
  

 

Huron

............
. _._‘_"_....- """

 

Isabella

 

 

 

   

0
~
~

....... =---i Tuscola Sanilac

Saginaw

114

 

PLEASE NOTE!
THIS IS A SURVEY OF HUNTER HARVEST CHOICES FOR BUCKS IN THE SAGINAw BAY
UNIT. SOME PEOPLE HUNT IN MORE THAN ONE LOCATION AND MAY HAVE DIFFERENT
HARVEST INTENTIONS FOR THOSE AREAS. PLEASE ANSWER ALL OF THE QUESTIONS IN
THIS SURVEY AS THEY APPLY To THE AREA YOU HUNT THE MOST FOR BUCKS DURING
THE NOVEMBER FIREARM SEASON IN THE SAGINAW BAY UNIT (SEE MAP ON THE
SURVEY COVER). THANK YOU.

 

 

 

1. Which license or combination of licenses did you purchase in 2006 to hunt
antlered deer? (Please Circle only ONE response.) Non-response rate: 2%

1. I did not purchase a deer hunting license: 1%

2. Combination license (firearm and archery): 61%
3. Firearm only license: 31%

4. Both archery only and firearm only licenses: 5%

2. Which of the following 2006 deer seasons did you hunt in the Saginaw Bay
Unit? (Please circle all that apply.)

1. Early archery (Oct. 1 - Nov. 14): Hunted: 49% Not hunted: 51%

2. Late archery (Dec. 1 —Jan. 1): Hunted: 19% Not hunted: 81%

3. November firearm (Nov. 15 - 30): Hunted: 91% Not hunted: 9%

4. Muzzleloader (Dec. 8 — 17 for zone 2) & (Dec. 1 — 17 for zone 3): Hunted:
39% Not hunted: 61%

5. Late firearm (Dec. 18 — Jan. 1): Hunted: 9% Not hunted: 91%

6. I hunted none of the 2006 deer seasons in the Saginaw Bay Unit: Hunted:
96% Not hunted: 4%

115

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118

8. How many days did you have available to hunt during the 2006 November
firearm deer season in the Saginaw Bay Unit? (Please count a partial day as
one day and write the number.) Average: 9.65 days

I had days available to hunt the 2006 November firearm deer
season.

9. How many total days did you hunt during the 2006 November firearm deer
season in the Saginaw Bay Unit? (Please count a partial day as one day and
write the number below.) Average: 7.27 days

I hunted days in the Saginaw Bay Unit during the 2006 November
firearm season.

10. On what day did you begin hunting in the Saginaw Bay Unit for a 2006
November firearm buck after the season opened on November 15‘“? (Please
circle only ONE response.) Non-response rate: 8%

1. I began hunting on the first day the season opened (Wednesday, Nov. 15):
80%

2. I began hunting on the second day of the season (Thursday, Nov. 16): 2%

3. I began hunting on the third day of the season (Friday, Nov. 17): 3%

4. I began hunting during the first weekend (Saturday 8. Sunday, Nov. 18 - 19):
7%

5. I began hunting during the second week (Monday - Friday, Nov. 20 — 25): 9%
6. I am unsure

11. How many days did you hunt during the 2006 November firearm deer
season in the Saginaw Bay Unit before harvesting your first buck for the year?
(Please count a partial day as one day and write the number below.) 1 day: 19%,
2 days: 5%, 3 days: 3%, Other: 8%; Non-response rate: 22%

I hunted days before harvesting my first 2006 buck during the
November firearm deer season.

 

g El l harvested my first 2006 buck during the early archery season.
1 0%

g El I harvested my first 2006 buck after the November firearm season
or I did not harvest a buck at all. 33%

119

12. After getting your first buck during the 2006 November firearm deer

season, how many days did you continue to hunt before harvesting your second
firearm buck?

(For example: If you harvested your fi_rst buck on November 15'" and your second
buck on November 20‘” you would answer 5 days. If you got two bucks on the
same day, write “0”.)

0 days: 3%, 1 day: 1%, 2 days: 1%, 5 days: 1%, Other: 3%; Non-response rate:
40%

I hunted days between my first and second buck harvest.

g [I l harvested my second 2006 buck after the November firearm
season or I did not harvest a second buck at all. 52%

120

 

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121

We are interested in what you consider to be your “ideal,” “preferred,” and “least
preferred” buck that you would harvest during the November firearm deer
season. Below we present three categories of bucks a hunter might have in
mind. You might not go out to hunt thinking in terms of these three categories,
but please read through the three categories of bucks below and refer to them
when you answer the questions that follow.

1. WHAT IS AN IDEAL BUCK?

AN IDEAL BUCK IS ONE YOU WOULD NOT HESITATE TO TAKE IF THE
OPPORTUNITY PRESENTED ITSELF.

YOU MIGHT BE WILLING TO PASS UP SHOTS AT OTHER BUCKS FOR PART OR
ALL OF THE NOVEMBER FIREARM SEASON TO WAIT FOR THIS BUCK.

YOU ARE REASONABLY CERTAIN A BUCK OF THIS CATEGORY EXISTS IN THE
AREA THAT YOU HUNT THE MOST WITHIN THE SAGINAW BAY UNIT.

2. WHAT IS A PREFERRED BUCK?

YOU WOULD TAKE A BUCK LIKE THIS WHEN YOU WERE NOT WILLING TO
WAIT ANY LONGER FOR YOUR IDEAL BUCK.

YOU MIGHT BE WILLING TO PASS UP SHOTS AT OTHER LEGAL BUCKS FOR
PART OR ALL OF THE NOVEMBER FIREARM SEASON TO WAIT FOR A BUCK
OF AT LEAST THIS STANDARD.

YOU ARE REASONABLY CERTAIN A BUCK OF THIS CATEGORY EXISTS IN THE
AREA THAT YOU HUNT THE MOST WITHIN THE SAGINAW BAY UNIT.

3. WHAT IS A LEAST PREFERRED BUCK?

YOU WOULD TAKE A LEAST PREFERRED BUCK ONLY AFTER YOU GAVE UP
WAITING FOR YOUR IDEAL AND PREFERRED BUCKS.

YOU MIGHT DECIDE TO HARVEST YOUR LEAST PREFERRED BUCK FOR
VENISON OR BECAUSE YOU WOULD RATHER NOT RISK ENDING YOUR
NOVEMBER FIREARM SEASON WITHOUT HARVESTING A BUCK AT ALL.

YOU ARE REASONABLY CERTAIN A BUCK OF THIS CATEGORY OR BETTER
EXISTS IN THE AREA THAT YOU HUNT THE MOST WITHIN THE SAGINAW BAY
UNIT.

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134

APPENDIX F
“What Buck Would You Choose? A Survey of Deer Hunter

Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Cover Letter 1

135

Michigan Deer Hunter:

This survey is designed to explore what physical characteristics of bucks hunters look for
when deciding whether or not to harvest a buck. As hunters, we venture afield each fall
with some idea of the buck we’d like to harvest. Some of us have a very specific buck in
mind. Some of us want venison in the freezer and are less concerned about the
characteristics of the buck we harvest. Many of us are somewhere in between.

In the first phase of this study, we are focusing on the Saginaw Bay Wildlife
Management Unit (hereafter referred to as the Saginaw Bay Unit). We would
appreciate your assistance in this study of deer hunter preferences and decisions in the
field. Please complete this questionnaire, seal it in the postage paid envelope provided
and put it in the mail.

Your responses will remain confidential and your privacy will be protected to the
maximum extent allowable by law. Records from this survey will be stored in databases
at Michigan State University during the duration of this project. Only project researchers
will have exclusive access to the data.

If you checked your buck into a MDNR deer check station and received a postcard and
additional measurements were collected from your buck, your responses to this survey
will be linked to the data collected from your buck. If no additional measurements were
collected from your buck at a MDNR check station, your responses will remain
anonymous.

Taking a few minutes to fill out this questionnaire is completely voluntary and indicates
your voluntary agreement to participate in this study. If you have any questions or
concerns regarding your rights as a study participant you may contact — anonymously, if
you wish — Peter Vasilenko, Ph.D., Director of Human Research Protections, (517) 355-
2180, fax (517) 432-4503, email irb@msu.edu, or mail 202 Olds Hall, Michigan State
University, East Lansing, MI 48824-1047.

If you have any questions regarding this survey, please contact me at the address below,
toll-free at 1-800-557-2148, or email at: balleli2@m_su.edu.

Thank you for your assistance!
\_,dLv7)W;3a-u’

Elizabeth Ball, Research Assistant
Michigan Department of Natural Resources, Wildlife Division
P.O. Box 30030, Lansing, MI 48909-9965

136

APPENDIX G
“What Buck Would You Choose? A Survey of Deer Hunter

Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Reminder Postcard

137

(originally printed on 4x6” notecard)

Dear Michigan Deer Hunter:

Two weeks ago, you received a survey regarding the harvest of bucks in the Saginaw Bay
Wildlife Management Unit.

If you already completed and returned the survey, please accept my sincere thanks! If you
have not, taking the time to fill out and return the survey will benefit the management of

Michigan’s white-tailed deer. It is vital that we receive your input!

If by some chance you did not receive the questionnaire, or it got misplaced, please call me
toll free at 1-800-557-2148 to receive another copy.

Sincerely,

K 114/3W JCDGJ‘LL

 

 

 

 

 

 

 

' Michigan Department of Natural Resources PRESORTED
Wildlife Population Studies FIRST CLASS
Box 30030 US. Postage
Lansing, MI 48909-7530 PAID

Lansing,
Michigan
RECIPIENT NAME
RECIPIENT ADDRESS

138

APPENDIX H
“What Buck Would You Choose? A Survey of Deer Hunter

Preferences and Decisions in the Saginaw Bay Wildlife
Management Unit” Survey Cover Letter 2

139

Dear Michigan Deer Hunter:

A survey regarding your preferences and decisions while hunting in the Saginaw Bay
Wildlife Management Unit was recently sent to you. This survey is designed to explore
what physical characteristics hunters look for when deciding whether or not to harvest a
particular buck.

I would like to reminder you that your responses are important. As a Michigan deer
hunter you were randomly selected to represent fellow sportsan and woman. Your
responses supply valuable information to the Michigan Department of Natural Resources
and researchers at Michigan State University.

The time it will take you to complete this questionnaire will only help to better serve the
needs of Michigan deer hunters. Again your assistance in this study of deer hunter
preferences and decisions in the field is greatly appreciated. Please complete this
questionnaire, seal it in the postage paid envelope provided and put it in the mail.

Your responses will remain confidential and your privacy will be protected to the
maximum extent allowable by law. Records from this survey will be stored in databases
at Michigan State University during the duration of this project. Only project researchers
will have exclusive access to the data.

Taking a few minutes to fill out this questionnaire is completely voluntary and indicates
your voluntary agreement to participate in this study. If you have any questions or
concerns regarding your rights as a study participant you may contact - anonymously, if
you wish — Peter Vasilenko, Ph.D., Director of Human Research Protections, (517) 355-
2180, fax (517) 432-4503, email irb@msu.edu. or mail 202 Olds Hall, Michigan State
University, East Lansing, MI 48824-1047.

If you have any questions regarding this survey, please contact me at the address below,
toll-free at 1-800-557-2148, or email at: balleli2@msu.edu.

Your cooperation is greatly appreciated!
.,¢u3aaauj’éaw

Elizabeth Ball, Research Assistant

Michigan Department of Natural Resources, Wildlife Division
PO. Box 30030

Lansing, MI 48909-9965

140

APPENDIX I

Field Collections Postcard

141

(originally printed on 4x6” notecard)

Dear Michigan Deer Hunter:

We are taking additional measurements of your 2006 firearm buck as part of some
exciting research by Michigan State University. This research project is designed to
investigate Michigan deer hunters’ preferences, attitudes, and selectivity regarding their
buck harvests. This study will help MDNR deer managers to investigate the possible
changes in future buck characteristics resulting from selective harvest. As a hunter that
checked-in a buck harvested within the Saginaw Bay Wildlife Management Unit, you
will receive a mail questionnaire early next year. Another 3,500 randomly selected
individuals who hunted this unit will also receive the questionnaire. Please watch your
mailboxes afier January 1", 2007. Your responses to the survey will be
. -« especially important. We want to know what you want and how you
made decisions in the field about which buck to harvest. When our
data are analyzed in 2007, we will put a report on the website of the
Department of Fisheries and Wildlife, Michigan State University
(http://www.i‘wmsuedul). Thank You.

 

Sincerely,

Elizabeth Ball/ Graduate Student
Michigan State University
Ph. 1-800-557-2148

142

Measurements taken from your antlered white-tailed buck harvested in the Saginaw
Bay Wildlife Management Unit

   
 

Age will also be
collected

,2
ll'

Hindfoot length

Length of longest T b f tl . t
- otalnum ero an er oms
antler tme p Greatest outside antler spread

./

 

 

 

 

143

APPENDIX J

Research Approval Letters

144

MICHIGAN STATE
UNIVERSITY”,

RE
i:

 

 

 

race or
lLATORY

AFFAIRS '

tesearch
’rograms

a HEALTH
u. REVIEW
\RD (eras)

ESEARCH
L REVIEW
0 (CRiRB)

SCIENCE!
)UCATION
I. REVIEW
RD (ans)

2 Olds Hall
. Michigan
3824-1046
{555-2180
4324503

Imsuedu

gmsuedu
)msuedu

p-crctian
..I"...ll~-

RevisiOn
Application
' Approval

October'27, 2006

To: Andrew McAdam
Department of Fisheries and Wildlife
Michigan State University
East Lansing, MI 48824

Category: EXPEDITED 2L7 .
October 27, 2006
October 26, 2007

Re: IRB ii 05-1028
Revision Approval Date:
Project Expiration Date:
Title: QUANTIFYlNG HUNTER-lNDUCED SELECTION ON WHITE-muse DEER.

The Institutional Review Board has completed their review of your project I am pleased to advise you that the
revision has been approved.

Revision to Include changes to the the postcard and research methodology.

' The review by the committee has found that your revision is consistent with the continued protection of the

rights and welfare of human subjects, and meets the requirements of MSUs Federal Wide Assurance and the
Federal Guidelines (45 CF R 46 and 21 CF R Part 50). The protection of human subjects in research is a
partnership between the iRB and the investigators. We look fonlvard to working with you as we both fulfill our
responsibilities.

' Renewals: iRB approval is valid until the expiration date listed above. If you are continuing your project. you

must submit an Application for Renewal application at least one month before expiration. If the project is

, completed. please submit an Application for Permanent Closure.

Revisions: The iRB most review any changes in the project. prior to initiation of the change. Please submit an
Application for Revision to have your changes reviewed. it changes are made at the time of renewal please
include an Application for Revision with the renewal application.

Problems: if issues should arise during the conduct of the research. such as unanticipated problems. adverse
events. or any problem that may increase the risk to the human subjects. notify the IRB office promptly. Forms
are available to report these Issues.

Please use the iRB number listed above on any forms submitted which relate to this project. or on any

correspondence with the IRB office.

Good luck in your research. If we can be of further assistance. please contact us at 517—355-0180 or via email
at W. Thank you for your cooperation.

Sincerely,
flab/£0

Peter Vasilenko, Ph.D.
SIRB Chair

145

-.1

ESSE-
:IIIIIZIE]
Elli]

OFFICE OF
EGULATORY
AFFAIRS

an Research
on Programs

ICAL & HEALTH
'iONAL REVIEW
BOARD (BIRB)

[TY RESEARCH
IONAL REVIEW
BOARD (CRIRB)

>CIAL SCENCEI
.L I enucanou
‘iONAL REVIEW

BOARD (SIRE)

202 Olds Hail
arising. Michigan
48824-1046
517-355-2180

Ir: 5174324503

searchmsuedu
iRB@msu.edu
crirb@msu.edu

 

MICHIGAN STATE

UNIVERSITY REVISION

Application
Approval

December 6. 2006

T03 Andrew McAdam
Department of Fisheries and Wildlife
Michigan State University
East Lansing. Mi 48824

Category. EXPEDITED 2-7
December 6. 2006
January 16. 2007

Re: iRB ll 05-1028

Revision Approval Date:
Project Expiration Date:
Title: OUANTIFYING HUNTER-INDUCED SELECTION ON WHITE-TAILED DEER.
The Institutional Review Board has completed their review of your project. i am pleased to advise you that the
revision has been approved.

Approved revision to reflect a change in the subject cover letter.

The review by the committee has found that your revision is consistent with the continued protection of the
rights and welfare of human subjects. and 'meets the requirements of MSUs Federal Wide Assurance and the
Federal Guidelines (45 CFR 46 and 21 CFR Part 50). The protection ofhuman subjectsln research is a
partnership between the IRS and the Investigators. We look forward to working with you as we both fulfill our

responsibilities. '

Renewals: IRB approval ls valid until the expiration date listed above. Iiyou are continuing your project. you
must submit an Application for Renewal application at least one month before expiration. If the project ls

. completed. please submit an Application for Permanent Closure.

Revisions: The iRB must review any changes in the project. prior to initiation of the change. Please submit an
Application for Revision to have your changes reviewed It changes are made at the time of renewal. please
include an Application for Revision with the renewal application.

Problems: If issues should arise during the conduct of the research. such as unanticipated problems. adverse
events. or any problem that may increase the risk to the human subjects. notify the IRB office promptly. Forms

are available to report these issues.

Please use the iRB number listed above on any forms submitted which relate to this project. or on any
correspondence with the IRB office

Good luck in your research. If we can be of further assistance. please contact us at 517-355-2180 or via email
at lRB@msu.fiu. Thank you for your cooperation.

Sincerely.
Mg”

Peter Vasilenko, Ph.D.
SIRB Chair

146

EDI
BEIGE!
EDI

OFFICE OF

EGULATORY .

AFFAIRS
an Research
)i'i- Programs

ICAL 81 HEALTH
'lONAL REVIEW
BOARD (BIRD)

ITY RESEARCH
10NAL REVIEW
BOARD (CRIRB)

)CIAL SCIENCE!
\L i EDUCATION
i'iOMAL REVIEW

BOARD (SIRB)

202 Olds Hail
arising, Michigan
48824-1046
517-355-2180

ax: 517-432-4503

ese'archmsuedu
i: lRB@msu.edu
crirb@rnsu.edu

 

firmalr've-acrion
unirv instinctic '2.

MICHIGAN STATE

UNIVERSITY Revision

Application
Approval

December 18. 2006

To: Andrew McAdam
Department of Fisheries and Wildlife
Michigan State University
East Lansing. Mi 48824

Category: EXPEDITED 2-7
December 18. 2006
December 17, 2007

Re: iRB s 05-1028 '
Revision Approval Date:
Project Expiration Date:

Title: QUANTIFYING HUNTER-INDUCED SELECTION ON WHITE-TAILED DEER.

The Institutional Review Board has completed their review of your project. I am pleased to advise you that the
revision has been approved.

Approved revision to include a change in non-response letter and the reminder post card being sent out
as follow up to the respected participants.

The review by the committee has found that your revision is consistent with the continued protection of the
rights and welfare of human subjects. and meets the requirements of MSU's Federal Wide Assurance and the
Federal Guidelines (45 CFR 46 and 21 CFR Part 50). The protection of human subjects in research is a
partnership between the IRB and the Investigators. We look forward to working with you as we both fulfill our

responsibilities.

Renewals: iRB approval is valid until the expiration date‘iisted above. if you are continuing your project. you
must submit an Application for Renewal application at least one month before expiration. If the project Is

« completed. please submit an Application for Permanent Closure.

Revisions: The IRB must review any changes in the project. prior to initiation of the change. Please submit an
Application for Revision to have your changes reviewed. if changes are made at the time of renewal. please

include an Application for Revision with the renewal application.

Problems: If issues should arise during the conduct of the research. such as unanticipated problems. adverse
events. or any problem that may increase the risk to the human subjects. notify the iRB Office promptly. Forms

are available to report these Issues.

Please use the IRB number listed above on any forms submitted which relate to this project. or on any
correspondence with the iRB Office.

Good luck in your research. if we can be of further assistance. please contact us at 517-355-2180 or via email
at jRB@msu.edu. Thank you for your cooperation.

Sincerely.

War/~2—

Peter Vasilenko, Ph.D.
SIRB Chair

147

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