SHARING AND CONSUMING WILD HARVESTED MEAT: PROVIDERS AND RECEIVERS OF VENISON By Amber Danielle Goguen A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Fisheries and Wildlife Œ Masters of Science 2015 ABSTRACT SHARING AND CONSUMING WI LD HARVESTED MEAT: PROVIDERS AND RECEIVERS OF VENISON By Amber Danielle Goguen Sharing and consuming wild harvested meat (WHM)Ša culturally significant interaction within nature worldwide ŒŒcreates links between human and natural systems. Little is known about the dynamics of WHM shari ng and consumption in modern soci ety, particularly in areas of the global north. My objective was to identify provisional and cultural ecosystem services provided by WHM in Michigan. I assessed how much venison is harvested, revealed sharing behaviors of hunters, and estimated the number and attributes of individuals providing and receiving venison. Questions about provider behaviors were included in the statewide 2013 Michigan Deer Harvest Study. In addition, telephone interviews with adult Michigan residents identified statewide WHM consumption patterns and receiver characteristics. I estimate 26-33 million pounds of wild harvested venison were procured during the 2013 Michigan deer hunting season. More than 85% of hunters who harvested a deer in 2013 shared their venison. Approximately 72% of Michigan residents have c onsumed venison at least once in their lifetime, nearly 50% of who reported consuming venison at least once in the past 12 months. Hunter providing behaviors magnify the potential number of people coupled to natural systems through hunting. In the absence of economic markets fo r WHM, the distribution of the provisional ecosystem service is extensive throughout the Michigan landscape. Nonetheless, the closed nature of sharing networks creates potential limits to the number and types of beneficiaries within this system. Policies or programs that encourage sharing of WHM can be expected to broaden the number and type of people c onnected to hunting and natural systems. ACKNOWLEDGMENTS This section of my thesis is by far the mo st difficult to write. A few paragraphs can neither begin to express my gratitude to all t hose who have helped me through this arduous yet highly rewarding process, nor the number of beings who have contributed in some way to its realization. First and foremost, I would like to express my deepest thanks my advisor, Dr. Shawn Riley, for his belief in my abilities, unwavering support, guidance through the research process, and technical expertise. If there was ever some one who embodied the word mentor, that would be Shawn. I would also like to thank the other members of my Graduate Committee, Dr. Jack Liu, Jordan Burroughs and Dr. John Organ for their suggestions and guidance throughout this project. I acknowledge the financial contributions of the following organizations in support of my graduate education and research: University Enrichment Fellows hip from The Graduate School at Michigan State University(MSU); National Science Foundation Graduate Research Fellowship Program; Michigan Department of Natural Resources; Joseph G. Schotthoefer Memorial Student Award from the Michig an Involvement Committee of Safari Club International; Vera M. Wallach Fellowship from the Department of Fisheries and Wildlife at MSU; Future Academic Scholars in Teachi ng (FAST) Fellowship from The Graduate School at MSU and the MSU Center for the Integration of Research Teaching and Learning (CIRTL) Steering Committee. I am grateful for the hard work and input of project collaborators, in particular the efforts of Brain Frawley and Brent Rudolph from the Mi chigan Department of Natural Resources and Graham Pierce from the Institute for Public Policy and Social Research (IPPSR) at MSU. I must also acknowledge the assistance of undergraduat e interns Drew Vandegrift and Molly Schools and the students of the Fall 2013 FW 434 Human Di mensions of Wildlife Management class at MSU who participated in focus groups to test survey questions. Special thanks to the members of the Riley Gore (and Burroughs) lab for their encouragement and feedback, and of course some good laughs. I thank my fellow graduate students and the professors and staff in the Department of Fisheries and Wildlife and across MSU for their contributions to my graduate career. I am also grateful to my friends and family around the globe, who have inspired, encouraged and sustained me, and perhaps most importantly, made me smile. I am especially thankful to my parents for introducing me to the wonders of the great outdoors and engraining a love for all things wild from my infancy. Not to mention their unconditio nal love as I find my own path in life. I must also thank my furriest of companions, my cat, Rufus, for his effortless comedic relief, keeping my keyboard warm on long winter nights, and his never-ending affection. My thanks flow to all of the Michigan deer hunters who responded to the 2013 DNR Deer Harvest Survey and the Michigan residents who participated in the 68 th State of the State Survey. I also must recognize Michigan hunters, and in particular deer hunters, for their generosity. Last, but certainly not least, I thank the deer: without them none of this research would be possible. TABLE OF CONTENTS LIST OF TABLES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v iii LIST OF FIGURES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi v ORGANIZATION OF THESIS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 CHAPTER 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Sharing and Consumption of Wild Harves ted Meat: Background and Significance to Society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Part 1: Significance of Meat in Society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 What is Wild Harvested Meat? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Risks and Benefits of Consuming Wild Harvested Meat. . . . . . . . . . . . . . 4 Access to Wild Harvested Meat in the Unite d States. . . . . . . . . . . . . . . . . 5 Part 2: The Importance of Sharing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Anthropological Theories and Studies on Food Sharing. . . . . . . . . . . . . . . 8 Commensality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Socialization Through Sharing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Socialization and Social Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Expanding Wild Harvested Meat™s Impact on Society. . . . . . . . . . . . . . . . 13 Part 3: Conceptual Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Coupled Human and Natural Systems (CHANS). . . . . . . . . . . . . . . . . . . . 14 Ecosystem Services Provided by Wild Harvested Meat. . . . . . . . . . . . . . . 15 Sharing and the Amplification of Ecosyste m Services. . . . . . . . . . . . . . . . 18 Part 4: Venison. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 CHAPTER 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 The Extent of Venison Sharing and Consumption: Hunters as Providers . . . . . . . . . . . . . 20 Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Study Area and Population. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Sampling Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Data Collection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Survey Instrument. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Variable Construction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Dependent variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Covariates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Calculating Edible Venison Harvest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Equations for edible venison yield. . . . . . . . . . . . . . . . . . . . . . . . . . 30 Additional measures for calcu lating edible venison yield for Michigan deer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Calculating edible venison yield for the 2013 deer season(s) . . . . 31 Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Weighting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Statistical tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Incorporating non-response bias into estimations. . . . . . . . . . . . . . 37 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Respondent Characteristics and Analysis Sa mple. . . . . . . . . . . . . . . . . . . . 37 Hunters as Venison Providers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Venison Receivers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Maximum Edible Venison Yield for 2013. . . . . . . . . . . . . . . . . . . . . . . . . 42 Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Hunters as Venison Providers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Venison Receivers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Maximum Edible Venison Yield for 2013. . . . . . . . . . . . . . . . . . . . . . . . . 49 CHAPTER 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 The Extent of Venison Sharing and Consumption: Recei vers. . . . . . . . . . . . . . . . . . . . . . 52 Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Study Area and Population. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Sampling Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Data Collection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Survey Instrument. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Variable Construction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Dependent variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Covariates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Coding open-ended questions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Weighting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Design-based analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Reporting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 7 Summary Statistics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Response rates and missing data. . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Respondent characteristics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 All respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Non-hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Frequent hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Wild harvested meat consumption. . . . . . . . . . . . . . . . . . . . . . . . . . 70 All respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Non-hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Frequent hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Venison Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 All respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Non-hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Frequent hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Modeling Wild Harvested Meat and Frequency of Venison Consumption. 78 Determinants of wild harvested meat consumption. . . . . . . . . . . . . 78 All respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Non-hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Determinants of frequency of venison consumption. . . . . . . . . . . . 81 All respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Non-hunters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Wild Harvested Meat Consumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Venison Consumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Determinants of Wild Harvested Meat and Frequency of Venison Consumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 CHAPTER 4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Management Implications and Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Management Implications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 APPENDICES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . 96 APPENDIX A: 2013 Michigan Deer Harvest St udy Questionnaire. . . . . . . . . . . . 97 APPENDIX B: 2013 Michigan Deer Harves t Study Questionnaire Cover Letters. 102 APPENDIX C: 2013 Michigan Deer Harvest Study Questionnaire Incentive. . . . 106 APPENDIX D: Additional 2013 Michigan Deer Harvest Study Data Tables. . . . 108 APPENDIX E: Study Specific Sections from the 68 TH SOSS Telephone Interview Transcript. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 APPENDIX F: Additional Tables from the 68 th SOSS for All Respondents. . . . . 126 APPENDIX G: Additional Tables from the 68 th SOSS for Non-Hunters. . . . . . . . 136 APPENDIX H: Additional Tables from the 68 th SOSS for Frequent Hunters. . . . 145 APPENDIX I: Notes on Coding-Ended Responses from the 68 th SOSS. . . . . . . . 154 APPENDIX J: Pre-Notification Letter for the 68 th SOSS. . . . . . . . . . . . . . . . . . . . 157 REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 LIST OF TABLES Table 2.1: Summary of studies conducted on the amount of edible venison produced from a white-tailed deer (WTD). Regr ession equations for edible venison yield from this table were used to ca lculate edible venison yield from the 2013 Michigan deer harvest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Table 2.2: Average live weights for Michigan white-tailed deer by age, sex and year round nutrition adapted from reporte d field dressed weights by Ozoga, et al. (1993, p. 43). Field dresse d weights were multiplied by the conversion factor 1.28 to obtain live weights (Case & McCullough, 1987; Harder, 1980). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Table 2.3: Composition of 2013 Michigan deer harvest by age and antlered/antlerless deer. Age structure determined from 2013 Michigan Department of Natural Resources de er checking station data (Mayhew, 2014). Antlered and antlerless division and total harvest numbers determined from the 2013 Michigan Deer Harvest Survey Report (Frawley, 2014). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Table 2.4: Edible venison yield for one deer based on age, sex and nutrition calculated using the average live weight (in pounds) for Michigan white-tailed deer from Table 2.2. The five different equations presented in Table 2.1 and the average of these equations were used to calculate edible venison yield. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Table 2.5: Hunting related characteristics and demographic profile of hunters who did and did not share their venison in the past 12 months from the 2013 Michigan Deer Harvest Study questionnaire. (2,719 observations were dropped from this analysis due to non-response). . . . . . . . . . . . . . . . . . . . 39 Table 2.6: To whom Michigan deer hunter s provided venison during the past 12 months from the 2013 Michigan Deer Harvest Study questionnaire. (4,758 observations dropped due to non-response.). . . . . . . . . . . . . . . . . . 43 Table 2.7: Total venison yield in pounds from the 2013 Michigan deer hunting season by age, sex and nutrition calculated using the values from Tables 2.3 and 2.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Table 3.1: Types of wild harvested meat consumed by all respondents (n=983), all non-hunters (n=510), and all frequent hunters (148) reported in weighted percentages out of the total population and those who reported consuming wild harvested meat for each group from the 68th SOSS. . . . . 73 Table 3.2: Reasons for not consuming wild harvested meat for all respondents (n=220) and non-hunters (n=189) who reported never consuming wild harvested meat reported in weighted percentages from the 68th SOSS. . . 74 Table 3.3: Comparison between wild harv ested meat consumers (n=763) and non- consumers (n=220) reported in we ighted percentages from the 68th SOSS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Table 3.4: Social network by wild harveste d meat consumption for all respondents, non-hunters and frequent hunters in weighted percentages from the 68th SOSS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Table 3.5: Frequency of venison consump tion by level of urbanization reported in weighted percentages for all respondents, non-hunters and frequent hunters from the 68th SOSS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Table 3.6: Frequency of venison consum ption by level of hunting experience: reported in weighted percentages out of total (n=950) from the 68th SOSS (FS-R Pearson=35.39 p<0.001). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Table 3.7: Design-based logist ic regression of wild harvested meat consumption for all respondents on level of hunting experience, social network, community type, sex, age, race, inco me and education level. Results reported in terms of odds ratios. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Table 3.8: Design-based logist ic regression of wild harvested meat consumption for non-hunters on social network, community type, sex, age, race, income and education level. Results reported in terms of odds ratios. . . . . . . . . . . 84 Table 3.9: Design-based linear regression of frequency of venison consumption for all respondents on level of hunting experience, social network, community type, sex, age, race, income and education level. . . . . . . . . . . 85 Table 3.10: Design-based linear regression of frequency of venison consumption for non-hunters on social network, community type, sex, age, race, income and education level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Table D.1: To whom Michigan deer hunt ers provided venison during the past 12 months from the 2013 Michigan Deer Harvest Study. (4,758 hunters did not respond to this question). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Table D.2: The number of people Michigan deer hunters shared their venison with over the past 12 months from the 2013 Mi chigan Deer Harvest Study. . . . 110 Table D.3: Hunting related characteristi cs of all respondents (n=19,981) and hunters who did and did not share their venison in the past 12 months (variable venison providers n=17,262) from the 2013 Michigan Deer Harvest 112 Study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table D.4: Demographic profiles of all respondents (n=19,981) and hunters who did and did not share their venison in the past 12 months (variable venison providers n=17,262) from the 2013 Michigan Deer Harvest Study. . . . . . 114 Table F.1: Wild harvested meat consumption for all respondents (n=997). . . . . . . . . 127 Table F.2: Reasons for not consuming wild harvested meat for all respondents who reported never consuming wild harvested meat (n=220). Open ended responses coded. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Table F.3: Types of wild harvested meat consumed by all respondents who reported consuming wild harvested meat (n=763). Open ended responses coded. . 127 Table F.4: Types of wild harvested meat consumed by all respondents who reported consuming wild harvested meat (n=763). Open ended responses coded and combined into categories of similar species. . . . . . . . . . . . . . . . . . . . . 129 Table F.5: Frequency of venison consum ption in the past 12 months for all respondents who reported consuming venison (n=735). . . . . . . . . . . . . . . 129 Table F.6: Origin of venison consumed over the past 12 months for all respondents who reported consuming venison in the pa st 12 months (n=491). . . . . . . . 130 Table F.7: Form of venison provided over the past 12 months for all respondents who reported consuming venison in the pa st 12 months (n=491). . . . . . . . 130 Table F.8: All respondents' relatio nships with hunters (n=997). . . . . . . . . . . . . . . . . . 131 Table F.9: Level of hunting experience for all re spondents (n=997). . . . . . . . . . . . . . 131 Table F.10: All respondents' sex (n=997). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Table F.11: All respondents' age re ported in categories (n=997). Note: in analysis age was used a continuous variable not in categories. . . . . . . . . . . . . . . . 132 Table F.12: All respondents' highest level of ed ucation completed (n=997). . . . . . . . . 133 Table F.13: All respondents' ethnicity (Hispa nic. Latino, or Spanish origin) (n=997). . 133 Table F.14: All respondents' race (n=997). Note: categories are not mutually exclusive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Table F.15: All respondents ra ce coded into mutually exclus ive categories (n=997). . 134 Table F.16: All respondents' annual household inco me in USD (n=997). . . . . . . . . . . . 134 Table F.17: All respondents' community type (n=997). . . . . . . . . . . . . . . . . . . . . . . . . 135 Table F.18: All respondents' residence by Michigan Department of Natural Resources (MDNR) Ecoregion (n=997). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have similar hunter participation rates and hunter densities compared to the Southern Lower Peninsula. . . . . . . . . . . 135 Table G.1: Wild harvested meat consumption for non-hunters (n=521). . . . . . . . . . . . 137 Table G.2: Reasons for not consuming wild harvested meat for non-hunters who reported never consuming wild harvested meat (n=189). Open ended responses coded. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Table G.3: Types of wild harvested meat consumed by non-hunters who reported consuming wild harvested meat (n=321). Open ended responses coded. . 138 Table G.4: Types of wild harvested meat consumed by non-hunters who reported consuming wild harvested meat (n=321). Open ended responses coded and combined into categories of similar species. . . . . . . . . . . . . . . . . . . . . 139 Table G.5: Frequency of venison consump tion in the past 12 months for non-hunters who reported consuming venison (n=307). . . . . . . . . . . . . . . . . . . . . . . . . 139 Table G.6: Origin of venison consumed over the past 12 months for non-hunters who reported consuming venison in the pa st 12 months (n=175). . . . . . . . 140 Table G.7: Form of venison provided over the past 12 months for non-hunters who reported consuming venison in the past 12 months (n=175). . . . . . . . . . . . 140 Table G.8: Non-hunters' relationships with hunters (n =512). . . . . . . . . . . . . . . . . . . . 141 Table G.9: Non-hunters' sex (n=521). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Table G.10: Non-hunters' age reported in categories (n=521). Note: in analysis age was used as a continuous variable not in categories. . . . . . . . . . . . . . . . . . 141 Table G.11: Non-hunters' highest level of edu cation completed (n=521). . . . . . . . . . . 142 Table G.12: Non-hunters' ethnic ity (Hispanic. Latino, or Spanish origin) (n=521). . . . 142 Table G.13: Non-hunters' race (n=521). Note: categories are not mutually exclusive . . 143 Table G.14: Non-hunter's race coded into three mutually exclusive categories (n=521). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Table G.15: Non-hunters' annual household income in USD (n=521). . . . . . . . . . . . . . 143 Table G.16: Non-hunters' community type (n=521). . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Table G.17: Non-hunters residence by Mich igan Department of Natural Resources (MDNR) Ecoregion (n=521). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have similar hunter participation rates and hunter densities compared to the Southern Lower Peninsula. . . . . . . . . . . . . . . . . . . . . . . . 144 Table H.1: Wild harvested meat consumption fo r frequent hunters (n=148). . . . . . . . 146 Table H.2: Types of wild harvested meat consumed by frequent hunters who reported consuming wild harvested meat (n=145). Open ended responses coded. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 Table H.3: Types of wild harvested meat consumed by frequent hunters who reported consuming wild harvested meat (n=145). Open ended responses coded and combined into categories of similar species. . . . . . . . . . . . . . . 147 Table H.4: Frequency of venison consumpti on in the past 12 months for frequent hunters who reported consuming venison (n=141). . . . . . . . . . . . . . . . . . . 148 Table H.5: Origin of venison consumed ove r the past 12 months for frequent hunters who reported consuming venison in the pa st 12 months (n=131). . . . . . . . 149 Table H.6: Form of venison provided over the past 12 months for frequent hunters who reported consuming venison in the pa st 12 months (n=131). . . . . . . . 149 Table H.7: Frequent hunters' relationships with other hunters (n=148). . . . . . . . . . . . 150 Table H.8: Frequent hunters' sex (n =148). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Table H.9: Frequent hunters' ag e reported in categories (n=148). Note: in analysis age was used as a continuous variable not in categories. . . . . . . . . . . . . . 150 Table H.10: Frequent hunters' highest level of education completed (n=148). . . . . . . . 151 Table H.11: Frequent hunters' ethnicity (His panic. Latino, or Spanish origin) (n=148). 151 Table H.12: Frequent hunters' race (n=148). Note: categories are not mutually exclusive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Table H.13: Frequent hunter's race coded in to three mutually ex clusive categories (n=148). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Table H.14: Frequent hunters' annual household income in USD (n=148). . . . . . . . . . . 152 Table H.15: Frequent hunters' community type (n=148) . . . . . . . . . . . . . . . . . . . . . . . . . 153 Table H.16: Frequent hunters™ residen ce by Michigan Department of Natural Resources (MDNR) Ecoregion (n=521). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have similar hunter participation rates and hunter densities compared to the Southern Lower Peninsula. . . . . . . . . . . 153 LIST OF FIGURES Figure 2.1: Distribution of the number of people hunters reported sharing their venison with over the past 12 months from the 2013 Michigan Deer Harvest Study (Mean=5.6, SD=4.52). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 ORGANIZATION OF THESIS This thesis is organized into four chapters; two as separate manuscripts, plus an introductory and concluding chapter. Throughout, this thesis follows the style of the Publication Manual of the American Psychological Association (6th Edition) required for submission to the journal Human Dimension of Wildlife. Chapter 1 consists of a literature review on a wide range of subjects relating to the consumption and shari ng of wild harvested meat. Chapter 2 presents results on edible venison yield and describes behaviors and characteristics of providers of wild harvested venison based on responses to a mail b ack questionnaire. Chapter 3 highlights findings from telephone interviews about receiving and c onsuming wild harvested m eat, with a particular focus on venison and non-hunters. Chapter 4 identifies potential implications from this thesis for wildlife management and policy and explores future directions for research on the topic of wild harvested meat sharing and consumption. Append ices contain data collection instruments, additional data tables, and detailed informa tion on open-ended response coding not included in the chapters. CHAPTER 1 Sharing and Consumption of Wild Harvested Meat: Background and Significance to Society Humans have been hunting and consuming m eat from wildlife (wild harvested meat (WHM) from the earliest of mome nts in human history. This su stained interaction with WHM has guided research on the topic from a variety of fields, most of which focus on the traditional relationship between communities and WHM in subs istence cultures. There are few studies that look at WHM outside of subsistence communities, and fewer still on WHM in urbanized societies of the global north. In this chapter, I attempt to compile and review literature from a wide reach of disciplines Œ sociology, an thropology, philosophy, ecology, biology, natural resource management, human ecology, public health, and social network analysis Œ to identify roles of WHM in society and its potential effects on humanity, with a particular focus on non-subsistence communities of the global north. U ndoubtedly, there are gaps in my inquiry as a consequence of the volume of related literat ure and the lens through which I view WHM. However, I hope this review creates a backdrop for my thesis, es tablishes the relevance of my research to wildlife conservation and management, and serves as a building block from which to develop theory about sharing and consumption of WHM. This chapter begins by providing a definition for WHM, discussing the significance of WHM in society from the development of humans to the modern locavore movement, the risks and benefits of WHM consumption and access to this valuable resour ce in the US. I continue my synthesis by discussing the roles of sharing in WHM consumption from multiple perspectives and identify the importance of WHM sharing in modern society. I apply the theoretical framework Coupled Human and Natural Systems (C HANS) (Liu et al., 2015; Liu et al., 2007) to the sharing and consumption of WHM, to clar ify the functional roles of WHM in society. Finally, I introduce wild harvested venison (deer meat) as the centerp iece of my thesis and argue why venison is an ideal WHM on which to focus my inquiry. Part 1: Significance of Meat in Society Meat--animal tissue or flesh derived from a mammal--fiis the most universally valued and sought after source of human nutritionfl (Bear dsworth & Bryman, 2004). The evolution of hunting and increased consumption of meat during the P liocene epoch is thought to have played a major role in the physiological and social de velopment of hominids (Larsen, 2003; O™Keefe & Cordain, 2004; Smil, 2002). The value of meat to society resulted in the industrialization and commoditization of meat (Bruckner, 2007; Magdoff, 2012), leading to an increased separation of source and consumer (Gouveia & Juska, 2002; He inz & Lee, 1998), decline in the quality of meat (Larsen, 2003; O™Keefe & Cordian, 2004), a nd concerns about the morality of meat consumption (Bruckner, 2007; Cahoone, 2009; M. N. Peterson, 2004; Smil, 2002). Local food movements seeking to disassociate with industrialized meat, have in fact pointed a spotlight at WHM in recent years, popularizing it thr ough publications such as Pollan™s (2006) The Omnivores Dilemma or Cerulli™s (2012) The Mindful Carnivore . The role of meat in human history and the status of meat in modern soci ety makes this research relevant and valuable. What is Wild Harvested Meat? Game meat is likely the most common term used to identify WHM. Broadly, game meat refers to the meat of game animals--wild anim als hunted for food and sport such as elk, deer, turkey, ducks, rabbits, raccoons, and squirrel. The Michigan Food Law of 2000 defines wild game as fianimals from their natural state and not cultivated, domesticated, or tamedfl (Michigan Department of Agriculture and Rural Developm ent, 2012, p. 6). Although strict definitions for game meat may exist, application and interpreta tion of the term has become increasingly difficult as the line between domestic and wild is blurre d with the advent of farming wild game, the creation of game sanctuaries for hunting, the feeding of wildlife as a management practice, and nomadic pastoral practices of herding wildlife populations (Geist, 1988). Ev en strictly wild populations are not immune to human interventi on, as most are managed in some fashion by state and federal agencies. This study examines and assesses the various functions of meat procured through hunting animals in their wild state (i.e., not fenced, farmed, fed or herded). Due to the myriad of uses of the te rm figame meatfl I use the more sp ecific term wild harvested meat (abbreviated WHM for ease of read ing) in lieu of game meat. Risks and Benefits of Consuming Wild Harvested Meat Meat has been part of the human diet for over 5 million years (Larsen, 2003). Modern domestic meat consumption in the US has been associated with obesity, hypertension, diabetes, and cardiovascular disease (O™Keefe & Cordain, 2004). WHM, however, can be a healthy source of lean protein, high in energy content and essential macronutrients (Larsen, 2003; O™Keefe & Cordain, 2004). WHM, such as venison, has 16-23% less fat and higher percentages of monounsaturated fats and omega 3 fatty acids co mpared to domestic beef, which is high in saturated fats associated with cardiovascular disease (O™Keefe & Cordain, 2004). The omega 3 fatty acids in WHM are partially responsible fo r its ‚gamey™ taste (O™K eefe & Cordain, 2004). In addition, WHM is free of antibiotics, hormone supplements, and other additives, and is not subject to engineered genetic modifications (GMO), although deer may still consume GMO crops. However, WHM handling and consumption can pose adverse health risks from zoonotic diseases (Karesh & Cook, 2005) and ingestion of bio-accumulated chemical contaminants such as pesticides, dioxins, polychlorinated biphenyls (PCB™s) and heavy metals (Burger, 2000). For example, the consumption of palm civets in Asia has been identified as the source of the SARS coronavirus outbreak (Bell, Roberton & Hunter, 2004). Of particular concern for hunters and their families is the mounting evidence that the use of lead shot contaminates meat with lead at levels that may be unsafe for consumption, especially by women who are pregnant or may become pregnant, and by children under 6 years of age (Danieli et al., 2012; Iqbal et al., 2009; Mateo, Rodriguez-De La Cruz, Vidal, Reglero & Camarero, 2007). Access to Wild Harvested Meat in the United States Meat from game animals raised on ranches or farms and processed according to U.S. Department of Agriculture (USDA) standards is available for purchase in US supermarkets or restaurants, and is frequently referred to as ‚g ame meat.™ Often, this farm raised meat from wildlife species is simply referred to as game meat, or even wild meat, without direct reference to its husbandry, making it difficult for the aver age consumer to differentiate between wild harvested and farm raised sources. Additionally, the average consumer may be unaware that the meat available for purchase in US stores and rest aurants does not come from hunters. In fact, the sale and trade of WHM is illegal within the US . A few exceptions exist in the form of legal markets for other wildlife parts such as antler s and pelts and alligator meat (Abhat & Unger, 2010). The absence of markets in WHM is a key tenet of US wildlife conservation: Unregulated and unsustainable market driven hunting for food and fashion were identified as key threats to wildlife at the turn of the 19 th century and a catalyst to the su bsequent development of wildlife conservation in the US (Organ, Mahoney & Geist, 2010). The current system of wildlife management in the US, often referred to as the North American Model of Wildlife Conservation, or simply the North American Model, is unique in this fact compared to many of its European counterparts, where some form of regulated market in WHM exists. The only way to legally access WHM in the US is through a hunter or someone who knows a hunter. Hence, sharing and social networks play a large role in how WHM is distributed throughout the country. This is evidenced by the number of people who have consumed WHM in comparison to the number of hunters- who make up approximately 6% of the population (U.S. Fish and Wildlife Service [USFWS], 2012). A 1996 study in New York reported that 61.6% of non-hunters had eaten WHM (Stedman & Decker, 1996). A 2011 national survey by Responsive Management (RM) and the National Shooting S ports Foundation (NSSF) revealed that 42% of Americans had consumed WHM over the past 12 m onths. (Note: Both of these studies used the term game meat in their data collection and analysis.) Other methods of obtaining WHM are beginning to develop in the US, for example the Nebraska Deer Exchange (NDE). The NDE is a website created in 2008 and hosted by the Nebraska Game and Parks Commission where deer North American Model of Wildlife Conservation is the re sult of wildlife management in the US over past two centuries and is the basis for modern wildlife conservation in the U.S (Organ et al, 2010). The model is made of seven pillars: (1) Wildlife as a public trust resource; (2 ) Elimination of markets for wildlife; (3) Allocation of wildlife by law; (4) Wildlife can only be killed for a legitima te purpose; (5) Wildlife is considered an international resource; (6) Science is the proper tool for discharge of wildlife policy; (7) Democracy of hunting (Organ et al., 2012). hunters and those who want wild harvested venison can make connections to share the harvest (Hildreth, Hygnstrom, Hams &VerCa uteren, 2011). The website specifically states that venison cannot be sold, but recipients can pay hunters for other services such as the processing of the meat (Hildreth et al., 2011). In some states, effort s are being made to lega lize the sale of WHM. For instance, lawmakers in New Jersey recently put forth a bill to allow the commercial harvest and sale of venison (New Jersey Assembly Bill No. 3039, 2014). Generally, the decision to allow the sale of WHM rests in the states™ legislature who are entrusted to manage the states wildlife for the benefit of current and future generations (Batcheller et al., 2010). Thus, variation exists from state to state regarding specific regulations for wildli fe and enforcement of those regulations. Part 2: The Importance of Sharing Although WHM is not available in US stores or restaurants, hunters and non-hunters still consume WHM (Burger, 2000 & 2002; RM & NSSF, 2011; Stedman & Decker, 1996; Titus, Haynes & Paragi, 2009). Because only 6% of th e US population hunts, interactions between hunters and non-hunters are essential for the transfer of WHM to 94% of the US population (USFWS, 2012). The word I am using to describe this interaction, or exchange, is sharing. Sharing is defined as fito give [or have] a portion (of something) with an other or othersfl (The Oxford American College Dictionary, 2002, p.1258). The act of sharing WHM involves a provider (most often a hunter) and a receiver, who can either be a hunter or a non-hunter. WHM can be given directly from a provider to a recei ver, such as a raw piece of meat, or can be enjoyed together such as sitting down for a meal , where the act of sharing is no so direct. Most often WHM (in both raw and cooked forms) is shared through informal networks between hunters, their families, relatives, fr iends, neighbors, coworkers and the landowners whose property they hunt. More formalized sharing exists in the common practice of hosting community wild game dinners and through charitab le meat donation programs, such as Hunters for the Hungry. In Michigan, churches are known for their large wild game dinners, sometimes hosting 200-400 guests. In 2009 and 2010 the Hunters for the Hungry program provided 2.6 million pounds of WHM 2, equaling an estimated 10.5 billi on meals, to America™s hungry (National Rifle Association [NRA], 2010). Sharing, in particular the sharing of m eat, has been a topic of keen interest for many re searchers in the social sciences. Anthropological Theories and Studies on Food Sharing Anthropologists interested in the evolution of human societies often study food sharing in hunter-gather communities. Analysis of food tran sfer in various hunter-gather societies has produced four distinct evolutionary theories about sharing: kin selection, reciprocal altruism, tolerated scrounging, and costly signaling (Gurven, 2004a; Kaplan & Gurven, 2005; Koster, 2011; Nolin, 2010). The theory of kin selection posits that sharing food evolved as a way to aid others who carry the same alleles, increas ing the likelihood one™s own genes are passed on (Kaplan & Gurven, 2005). Reciprocal altruism refers to food sharing as a way to garner future support in a time of need (Kaplan & Gurven, 2005) . Tolerated scrounging describes when food is shared because the cost of defending it outweighs the cost of sharing (Kaplan & Gurven, 2005). Costly signaling indicates when food is shared to signal unobservable traits about the donor, such has his hunting skills or cooperative nature (Kaplan & Gurven, 2005). It has been WHM totals are only from the following species: Deer, Elk, Antelope, Moos e, Pheasant, and Waterfowl (NRA, 2010). suggested that these theories are not mutually exclusive, and likely are components of a complex system (Koster, 2011; Moore, 2004) Studies of hunter-gather communities have show n that WHM is treated differently than other natural resources (Kameda, Takezawa & Ha stie, 2005). Meat is shared more extensively than non-animal based food products or gathered resources (Kaplan et al., 1985). Some studies of hunter-gather communities site inability to store large quantities of meat for long periods of time as the main reason behind the high incidence of WHM sharing (Kaplan et al., 1985). Kaplan et al. (1985) also found that resource availability impacted sharing behaviors, concluding that sharing is more prominent in societies wher e meat is available year round. For example, migrating herds of caribou offer access to meat during short periods each year, requiring that meat be saved to last the entire season possi bly limiting sharing behavi ors (Kaplan et al., 1985). Other studies counter these arguments, noting th at food preservation techniques allow food to last for longer periods of time (Gurven, 2004b). However, storage also has a down side, because stores must be guarded and decr ease mobility (Kaplan et al., 1985) . Kaplan et al. (1985) also found that meat sharing, compared to the sharing of other resources, had the greatest impact on nutritional status. Gurven (2004b) found that sharing large, more difficult to acquire food items with high variability in acquisition (such as large game) is mo re common than the sharing of small easily acquired food items. Bliege Bird and Bird (1997) report that hunters seek both consumptive and social benefits from sharing of meat. Alvard (2004 ) argues that the cost of not sharing is higher than the cost of sharing, due to the network of relations built by the act of sharing meat. Using social network theory, Koster (2011) and Nolin (2010) found that kinship, interhousehold distance, and reciprocity were strong predictors of sharing behavior. Koster ( 2011) found that resources tend to move based on lines of kinship associated with need and not reciprocity, and also found differences between lineal and collateral kin. Koster™s study contradicts findings by Allen-Arave, Gurven and Hill (2008) where reciprocity was re ported to be the main motivator of sharing among kin. Bliege Bird et al. ( 2001) propose costly signaling as an offset to discrepancies in motivation for reciprocal altruism, claiming th at signaling is a benefit derived from giving without immediate returns. These studies dem onstrate that sharing WHM can be motivated by many factors and that it can positive im pacts on providers and receivers. Commensality Food sharing has been studied outside of hunter gather communities focusing on a wide range of topics: fostering a sense of community in academic and organizational environments (Roderick, Carr & Zundel, 2009; Watland, Hallenbeck & Kresse, 2008) as a form of aid and support in at risk communities (Quandt, Arour y, Bell, McDonald & Vitolins, 2001); connecting diverse groups of people (Wise, 2011); relationships between culture and health (Fischler, 2011; Pachucki, Jacques & Christakis, 2011); intimacy (Miller, Rozin & Fiske, 1998); and the broader cultural context of food (Mintz & DuBois, 2002). For Kass (1994), the common saying fiyou are what you eatfl appears true. He states, fieating comprises the appropriation, incorporation, and de-formation of a complex other, and its homogenization into simples, in preparation for their transformation into complex samefl (Kass, 1994, p. 26). In essence, ingesting the flesh of another animal connects us to that being. For many people, the act of eating may not be so prof ound, but it is a pleasurable and social act, that connects us to those with whom we share our meal (Miller et al., 1998; Rozin, 1999). Simmel (1997) states, fiOf all the things that people have in common, the mo st common is that they must eat and drinkfl (p. 130). He goes on to explain that one of the mo st significant things about our common need to consume, is that anyone can sit dow n together at a meal; it is a universal act and opportunity to bring diverse groups together (Simmel, 1997). Comm ensality, or the act of eating together, promotes and improves the flow of communication, nurtures relationships, and fosters sense of community in families, organizations , and communities (Fischle r, 2011; Watland et al., 2008). These effects are observed across cultural, ethnic, and religious boundaries (Patton, 2005; Wise, 2011;). Throughout European history there is evidence that providing venison to others was a way to build social capital and strengthen social connections (Fletcher, 2011). In the Canadian artic, the Inuit credit WHM with maintaining th e Inuit ethnic identity of subsistence hunters, maintaining social relationships, and enforci ng connections to nature and wildlife (Omura, 2013). For Inuit, the key tenets of hunting are that the wildlife must be respected and their meat must be used and shared (Omura, 2013). In summar y, food sharing is a social activity that helps build and maintain social bonds and a vehi cle through which these bonds are expressed (Jimenez, Monton-Subias & Romero, 2011). Socialization Through Sharing Socialization is the process through which attitudes, behaviors and values are learned (Stedman, 2012). Primary socialization occurs thr ough parents (or their social equivalent), while secondary socialization occurs through broader sources of influence such as peers and community (Stedman 2012). Socialization is an im portant component of hunting culture, as it is often the primary mechanism fo r the recruitment of new hunters (Ryan & Shaw, 2011; Stedman & Heberlein, 2001). Heberlein (1991) proposed that participation in social activities where WHM is shared might develop acceptance of the activity among non-hunters by strengthening or developing shared beliefs. Stedman and Decker ( 1996) found that sharing game meat at meals or in other ways may be one readily available a nd effective means of enhancing positive social interaction among hunters, or of socializing non-hunters to hunters via food and stories about hunting. As discussed in the previous section, sh aring provides occasions for diverse groups to gather over the universal act of eating and is the basis for building and maintaining social bonds in many societies (Jimenez et al., 2011; Simm el, 1997; Wise, 2011). Anthropological theories speculate sociality may be responsible for the em ergence of the modern day human race, and that hunting and subsequent meat sharin g may be responsible for at leas t some of this instrumental development (Kawai, 2013; Stanford & Bunn, 2011). Programs such as the Orion Institute™s Windsor Dinners or Michigan™s Gourmet Gone Wild ®, use socialization theory to provide opportunities for hunters and non-hunters to interact over a shared meal of WHM. Socialization and Social Networks In their 2014 publication Larson, Stedman, Decker, Siemer & Baumer proposed a social structure (or habitat) for hunting recruitment in the US based on social-ecological theories about individual behavior. Starting wi th the individual, the social st ructure expands outward to the micro level (family), meso level (community s upport networks such as peers and extended family), and the macro level (society) (Larson et al., 2014). Essentially, this theory models a hunters ego network and their level of influence. Increasing social distance reflects weaker connections between the individual and their relations, however, it also means a broader audience. In part, the hunter recruitment stru cture based on primary socialization suffers from homophily Œ the social network concept that e xplains the phrase fibirds of a feather flock togetherfl (McPherson, Smith-Lovin & Cook, 2001). Hunters have close social relationships with other hunters, forming a more ‚closed™ network. In relation to sharing, this supports anthropological theories about the role of kin selection in resource distribution. Granovetter™s (1973) theory on the strength of weak ties posits that connections outside ones inner circle provide the opportunity for the flow of new information. Through using weaker ties, one is able to converse with the communit y, rather than preach to the choir. Focusing on secondary forms of socializati on accesses the meso and macro levels of a hunter™s social network. Sharing WHM can be both a primary a nd secondary form of socialization to hunting and presents its self as a way for hunters to communicate at the community level and extend their social reach. Ljung, Riley, Heberlein & Ericsson (2012) conducted research to test the potential societal implications of soci alization to hunting through the act of sharing WHM. In Sweden they found that WHM consumption positively influe nced attitudes toward hunting (Ljung et al., 2012). Further evidence from Sweden suggests the effects of WHM sharing are similar in rural and urban settings, although availability Œ and th us frequency of consumption- are markedly different in these two environments (Ljung, Riley & Ericsson, 2014). Expanding Wild Harvested Meat™s Impact on Society Sharing WHM doesn™t simply put protein on the table. WHM provi des opportunities for sharing the culture of hunting, and also to extend the benefits provided by hunting. As Heffelfinger (2014) put it fivenison has to be earnedfl (p. 43). There is an entire process that goes into putting venison on the table and what it takes to be ‚earned™ is part of what makes it special. Hunting is a valuable part of US culture and tradition that enriches quality of life by connecting people to nature, one another, and their food (Bruckner, 2007; Knezevic, 2009; M. N. Peterson, Hansen, M. J. Peterson, & T. Peterson, 2010; M.N. Peterson, 2004). Hunting can build connections to nature through the act of self-sufficiency, by functioning to remind hunters of their ‚traditional relationship™ with nature, by increasing ecological knowledge, and through firender[ing] the materiality of food producti on explicitfl (M. N. Peterson et al., 2010, p. 127) (Cahoone, 2009; Franklin, 1998; Organ et al., 2010; M. N. Peterson, 2004). WHM serves as a vehicle for sharing these experiences and embodies their social and ecological significance (M. N. Peterson et al., 2010). Fletcher (2011) claims that venison™s fiintangible symbolic worthfl was often greater than it™s economic value in Europe an history, placing a weighty meaning on the gift of venison (p. 210). The Inuit of the Canadian artic use the phrase fireal foodfl to describe meat that is obtained by hunting (Omura , 2013). This simple translation emphasizes the importance of WHM to Inuit culture. Linking back to the meso level of a hunter™s social network and the importance of secondary socialization, sharing expands the potential impact WHM can have on society. Part 3: Conceptual Framework Coupled Human and Natural Systems (CHANS) The CHANS framework proposed by Liu et al. ( 2007) identifies reciprocal interactions and feedback loops between human and natural systems that occur through time and space. For this reason the CHANS framework is useful in identifying couplers: factors that link human and natural systems. In essence, couplers are the threads that stitch human and natural systems together. Having connections within and across systems provides resi stance, resilience, adaptability, stability, and sustainability (Levin & Lubchenco, 2008; Liu et al., 2007). Fundamentally, the more connecti ons that exist, the stronger a system becomes. Sharing and consuming WHM has been identifie d as a potentially significant coupler (Freese, 1997; M. N. Peterson et al., 2010). Essential elements linking human and natural systems are the ecosystem services provided by the environment to humans and the impact they have on human well-being and society. I propose that WHM couples human and natural systems through the provisional and cultural ecosystem services it provides. A pplying the CHANS framework to the sharing and consumption of WHM integrates research c onducted on WHM across many disciplines, which was discussed in Parts 1 & 2 of this chapter. Ecosystem Services Provided by Wild Harvested Meat In the CHANS framework, natural systems provi de ecosystem services to humans, such as the air we breathe or the feeling we get af ter taking a walk in the woods (Liu et al., 2007; Millennium Ecosystem Assessment [MEA], 2005). WHM can be associated with two types of ecosystem services: provisional and cultural. Provisional ecosystem services are the tangible benefits people receive (Liu et al., 2007; MEA, 2005), such as the nutritional value (fresh lean local healthy protein that is antibiotic and chemical free) of WHM. Food security in many developing countries is unavoidably linked to WHM consumption, creating confounding conservati on issues trying to balance local livelihoods and biodiversity (Richardson, 2010). Bushmeat (a term often used to describe WHM in the tropics) is an important source of protein for many remote communities, but has largely been driven to unsustainable levels of harvest due to urban demand and income generated from the market sale of bushmeat, another provisional ecosystem service provi ded by WHM (VanVliet & Mbazza, 2011; Wilkie & Carpenter, 1999). In some areas of the tropics, the bushmeat trade has become an essential part of local economics (Bowen-Jones, Brown & Robinson, 2003; VanVliet & Mbazza, 2011). Reliance on WHM extends to many cultures beyo nd the tropics. For example, indigenous subsistence communities, such as the Inuit of Alaska and Canada, rely on protein harvested from the wild for survival (Titus et al., 2009). There is also speculation that WHM may play an important role in the diets of r ecreational hunters in the US and their families and those in need (Burger, 2000 & 2002; K. Tidball, M. Tidball & Curtis 2013). Burger (2002) posits that recreational hunters and their families may be over looked in terms of their dietary dependence on WHM. Burger (2002) estimated that the mean ra te of venison consumption by attendees at a sportsmen event was one 4oz meal every four days and that 5% of venison consumers ate 8oz of venison a day. Additionally, Burger (2000) reported that some non-hunter s eat WHMs (including fish) year round thanks to the generosity of friends and family. Burger (2000) also noted that gifted venison made up at leas t 50% of some non-hunters diets, emphasizing the importance of sharing in distributing provisional ecosystem services. Although many of the previous examples describe dietary dependence, to be considered a provisional ecosystem service, WH M does not need to be consumed at the subsistence level, e.g. comprising a major part of an individual™s di et. No matter the frequency of consumption the nutritional benefits provided by a serving of WHM are the same. WHM may be consumed to offset the cost of purchasing meat , or simply on its own merit. Cultural ecosystem services are more difficu lt to quantify and measure: These are the non-tangible benefits people derive from natura l systems (Lui et al., 2007; MEA, 2005). Culture and nature are inevitably linked; many aspects of human society are in fluenced and shaped by the natural system in which that society is lo cated (MEA, 2005). Cultural ecosystem services can be categorized as spiritual and religious, recreational, aesthetic, inspirational, social interactions, sense of place, cultural heritage, and educational (Hernandez-Morcillo, Plieninger & Bieling, 2013; MEA, 2005). WHM does not have to be an essential part of someone™s diet to maintain its importance. For many people, WHM is not a part of everyday life, but saved for special occasions. Almost every culture in the world has customs and tr aditions surrounding the sharing and consumption of WHM. In China, particularly in urban areas, the consumption of wildlif e meat is considered a rare delicacy and a status symbol of a fa shionable lifestyle (Zhang, Hua & Sun, 2008). For indigenous Alaskans the sharing and consumption of WHM pr ovides not only an essential protein source, but plays an important role in cultural activities (e.g. ceremonies) and personal relationships, and is central to their sense of identity (Dombrowski, 2007; Titus et al., 2009). Urban consumers of bushmeat believe that bushm eat possesses cultural, spiritual and nutritional values (Milner & Bennett, 2003; Van Vilet & Mbazza, 2011). Researchers have struggled to define and measure cultural ecosystem services, often resulting in oversight of their importan ce in decision-making and conservation policy (Hernandez-Morcillo et al., 2013; MEA, 2005). When cultural ecosystem services are lost or devalued, ties between human and natural syst ems are weakened, creating environmental and societal disruptions (MEA, 2005). Conversely, environmental and social disruptions may also result in the devaluation or loss of ecosystem services. Re gardless of the mechanism, once cultural ecosystem services are lost, they are di fficult to be reestablishe d or replaced, increasing the gap between human and natural systems and decreasing the systems resiliency (Hernandez- Morcillo et al., 2013). Sharing and the Amplification of Ecosystem Services Sharing WHM is not only an important elemen t of many cultures, but it also functions to extend the provisional and cultural ecosystem services WHM provides to a larger portion of society. Hunters are not the only ones who receive ecosystem services provided by WHM; recipients of the hunter™s harvest are additional beneficiaries, expanding the potential number of people engaged in this system. Societal impact s created by WHM are manifested from perceived benefits or costs an individual identifies when interacting with WHM. If an individual has no interaction with WHM, they canno t directly perceive benefits or costs, and the impact of WHM goes unrecognized. Creating opportunities to share WHM may he lp society recognize these impacts and the important role WHM plays in coupling human and natural systems. Part 4: Venison Cervidae are present in ecosystems throughout the world (Geist, 1998). Roth and Merz (1996) claim that the deer family may be the mo st economically important wildlife taxa. Deer are the most common species pursued by hunters in the US Œ 80% of all US hunters hunt deer (Aiken & Harris, 2011). White-tailed deer ( Odocoileus virginianus) are one of the most widely distributed mammals in the Western Hemis phere (Demarais, Miller & Jacobson, 2000). VerCauteren et al. (2011) identify white-tailed deer as the world™s most popular big-game species. Additionally, white-tailed deer are one of the most abundant species in the US and are of increasing concern to wildlife managers (C ampa et al., 2011; Doughe rty, Fulton & Anderson, 2003; VerCauteren et al., 2011). In 2010 the estimate d population of white-tailed deer in the US was 30 million (VerCauteren et al., 2011). Burger (2000) reported that venison is the most commonly consumed wild-harvested protein. When harvested, deer provide large quantities of lean protein, which may increase the prevalence of meat sharing (Gurven, 2004b). Wild harvested venison in the US embodies many of th e benefits accredited to WHM Œ it is a fresh lean local free-range healthy protein that is antibiotic and chemical free. Deer hunting in the US is steeped in trad ition - some communities are known for their deer hunting culture and actually cancel school and close businesses on the first day of deer season. In parts of the country where deer hunting is popular, deer may be considered a cultural keystone species (Brent Rudolph, personal comm unication, April 2, 2015; Garibaldi & Turner, 2004). The concept of cultural keystone species, a parallel to the concept of ecological keystone species, identifies species that play an important role in local culture, ar e harvested and managed intensely, and are often used as symbols (Garibaldi & Turner, 2004). Because deer are wildly distributed, used a nd valued by humans, focusing on the sharing of venison increases the generali zability of this study. The popularity of deer and availability of venison, ensure a wide range of experiences with venison and the ability to conduct research across large populations. CHAPTER 2 The Extent of Venison Sharing and Consumption: Hunters as Providers The consumptive use of natural resources has long played an important role in the cultures of many societies and in connecting humans to nature. As traditional natural resources users decline in number and urba n populations with protectionist wildlife value orientations grow, questions arise about the role of u tilitarian activities, such as hunting, in 21 st century American society (Heberlein & Ericsson, 2005; Manfredo, Teel & Bright, 2003; Manfredo, Teel & Henry, 2009; USFWS, 2011; Whittaker, Vask e & Manfredo, 2006; Zinn, Manfredo & Barro, 2002). Hunting has long been the focus of studies in the biological and social sciences, however, little research in the US has been conducted on the meat produced through hunting, or wild harvested meat (WHM). Increased importance on the roles of WHM, or iginating from public trust resources (Organ & Batcheller, 2009), warrants systematic inquiry into the use of WHM and the ecosystem services it provides in presen t day society. Identifying the extent of WHM sharing and consumption can have implications for wildlife manageme nt, conservation policy, public health and the preservation of traditional natural re source use cultures. The framework of Coupled Human and Natura l Systems (CHANS) proposed by Liu et al. (2007) identifies the ecosystem services natural systems provide to humans, and more broadly society, as important components connecting humans and nature. Sharing and consuming WHM has been identified as a potentially significant coupler of human and natural systems (Freese, 1997; M. N. Peterson et al., 2010), however little research has been conducted to support this theory in the global north. WHM is associated wi th two types of ecosystem services: provisional and cultural. Provisional ecosystem services are the tangible benefits people receive, for example, WHM (Liu et al., 2007; MEA, 2005) . Identifying the amount of WHM produced by hunters establishes the potential provisional ecosystem services WHM can provide to society. Cultural ecosystem services are more difficu lt to quantify and measure: These are the non-tangible benefits people derive from natura l systems (Lui et al., 2007; MEA, 2005). Cultural ecosystem services are often categorized as sp iritual and religious, recreational, aesthetic, inspirational, social relations, sense of place, cultural heritage, and educational (Hernandez- Morcillo et al., 2013; MEA, 2005). The cultural ecosystem services produced by WHM are mainly derived from the act of sharing, either providing WHM to others or receiving WHM from others. Food sharing is a social activity that helps build and maintain social bonds and is a vehicle through which these bonds are expressed (Jiménez et al. 2011). Identifying sharing behaviors of hunters may be an innovative way to measure the cultura l ecosystem services provided by WHM. Sharing WHM is not only an important elemen t of the hunting process, but sharing also functions to extend the provisional and cultural ecosystem servi ces WHM provides to a larger portion of society. Because the sale of WHM is illegal within US borders, the only way to legally access WHM in the US is from a hunter. Thus, hunters are the main providers of WHM and hunter social networks likely play a key role in how WHM is distributed throughout the country. Sharing increases the number of beneficiaries of hunting, may socialize non-hunters to hunting (Heberlein, 1991; Stedman & Decker, 1996), and has been credited with positively influencing attitudes toward hunting (Ljung et al., 2012; Ljung et al., 2014). In recent years, multiple stakeholders have increased their attention on WHM, such as locavores seeking local healthy ethically raised meat and wildlif e managers looking to recruit new hunters based on interests in local foods (Larson et al., 2014; Ryan & Shaw, 2011; K. Tidball et al., 2013). Some have even go so far as to propose changes to laws pertaining directly to WHM by allowing for the commercial harvest and sale of WHM in areas of abundant deer populations in New Jersey (Adams, 2015; NJ Assembly Bill No. 3039; Thogmartin, 2006; VerCauteren et al., 2011). Better knowledge and insight into the extent of WHM sharing and consumption, and the provisional and cultural ecosy stem services WHM provides to society, will contribute to current deliberations about the role of hunting in American culture and wildlife policy decision-making. This can be accomplished, in part, by investigating the amount of WHM produced by hunters, and by exploring hunter WHM sharing behvaiors such as how many hunters share, to whom, and any defining characteristics of hunters who share. Methods Study Area and Population Michigan, noted for its upper and lower peninsulas, is located in the north central US with a land area of 56,539 mi 2 (U.S. Census, 2010). Human dens ity and intensity of land use decrease south to north across the state (Michigan Department of Environmental Quality [MDEQ], 2014; Michigan Department of Technology, Management and Budget [MDTMB] Center for Shared Solutions [CSS], 2011) Approximately 75% of Michigan™s population lives in urban areas and 25% in rural areas (U.S. Census, 2010). In 2010, Michigan™s population was estimated to be 9,883,706, comprised of 77% white non-Hispanic or non-Latino, 49% male, with an overall median age of 39 years (U.S. Census, 2010). Deer are one of the most economically im portant and sought after big game species throughout the world (Geist, 1998; Roth & Me rz, 1996). In the US, white-tailed deer (Odocoileus virginianus) are the most abundant and popular bi g game species. Nearly 80% of all hunters in the US hunt deer, of which white-tailed deer are most wide-spread and abundant (Aiken & Harris, 2011; VerCauteren et al., 2011). La rge quantities of lean protein produced from wild harvested deer may increase the prevalen ce of meat sharing (Gur ven, 2004b). Furthermore, deer hunting has a long history and heritage in many communities where deer are found (Stransky, 1984). Because deer are wildly distri buted, used and valued by humans, focusing on the sharing of venison increases th e generalizability of this study. Michigan™s population has the greatest proportion of deer hunters in the US and ranks third in the total number of resident deer hunt ers 16 years and older (Aiken & Harris, 2011). Approximately 90% of all Michig an hunters hunt white-tailed deer, the most abundant deer species present in Michigan (Frawley, 2006). In 2013, 712,404 people purchased a deer hunting license in Michigan, 661,788 of whom were estimated to have hunted (Frawley, 2014). An estimated 9.2 million days were spent afield by deer hunters in 2013, culminating in a harvest of approximately 385,000 deer (Frawley, 2014). In 2 013, the mean age of Michigan deer hunting license buyers was 42 years, 89% of whom we re male (Frawley, 2014). Besides contributing substantially to the Michigan Department of Natural Resources (MDNR) budget, hunting has an estimated $1.16 billion annual impact on the st ate™s overall economy a nd is considered an important cultural heritage among the states residents (Langenau, 1994; MDNR, 2010; Rudolph, 2005). Sampling Design Questions were included on the MDNRs 2013 Michigan Deer Harvest Study, a well-established annual survey with standardized protocols (Frawley, 2014). The 2013 Michigan Deer Harvest Study used a mixed methods approach to collect data from hunter s (Greene, Caracelli & Graham, 1989). Hunters either vol untarily reported their harvest online or they were randomly selected through a stratified random sample of deer license buye rs to respond to a mail back questionnaire. The online survey was promoted in the 2013 Deer Hunters Digest, on the MDNR website, and in an email to all 2013 deer license purchasers for whom MDNR had an email address (N=. Hunters who voluntarily reported their harvest online (n=3,774) were removed from the total possible population prio r to drawing a sample for the mail back questionnaire creating an effective population size of N=708,632. The remaining population of hunters was divide d into four mutually exclusive strata based on the type of deer hunting license purchased (firearm, archery, antlerless, mentored youth, or combination) and the season in which it was valid. In 2013, Michigan had seven deer hunting seasons: Early antlerless firearm (Sept 21-22); Liberty H unt (Sept 21-22); Archery (Oct 1-Nov14, Dec 1-Jan 1); Independence Hunt (Oct 17-20); Regular firearm (Nov 15-30); Muzzle loading (Dec 6-22); Late antlerless firearm (Dec 23-Jan1) (MDNR, 2013). Youth (16 and under) and disabled hunters were eligible for the Liberty Hunt, while the Independence Hunt was only for disabled hunters (MDNR, 2013). The first st ratum included hunters eligible only for the archery, firearm and muzzleloader seasons (N=439,173). The second stratum included hunters eligible only for the early and late antlerless seas ons in addition to the seasons in the first stratum (N=208,866). The third stratum included hunters e ligible for the Liberty season (N=56,931) and the fourth stratum included only disabled hunter s (N=3,662). Strata were sampled separately to ensure all types of hunters had sample sizes large enough for statisti cal tests. The final stratified random sample contained 57,432 hunters: 28,591 from the first stratum, 13,469 from the second stratum, 11,714 from the third stratum and 3,658 from the fourth stratum. However, 1,895 hunters selected for the sample did not have ad dresses. Thus, the final sample of hunters who were mailed questionnaires, totaled 55,537 hunter s: 27,438 from the first stratum, 13,106 from the second stratum, 11,517 from the third stratum and 3,476 from the fourth stratum. The sample size and sampling scheme of the 2013 Michigan Deer Harvest Study was designed to minimize coverage and sampling errors (Dil lman, Smyth & Christian, 2009). Data Collection The 2013 Michigan Deer Harvest Study used a modified Dillman Total Design method with three mailings (Dillman, Smyth & Christian, 2009). The first mailing was sent on January 22, 2014, the second mailing was sent on March 14, 2014, and the third mailing was sent on April 26, 2014. Also included in the mailing was a le tter of consent describing the study from the chief of the MDNR Wildlife Division (Appendix B) and an offer from Safari Club International to be entered in a drawing to win a firearm or bow if the questionnaire wa s returned by February 20, 2014 (Appendix C). Data on age, sex and residence of respondents was extracted from the MDNR deer hunting license database along with questionnaire responses. Permission to access this data was given my MDNR and approved by the MSU Hu man Research Protection Program (HRPP) Social Science / Behavioral / Education Instit utional Review Board (SIRB) to ensure the protection of human subjects (IRB #x13-721e ). Basic demographic information is collected by the MDNR with all hunting license purchases. Hunters™ community type was identified as belonging to one of three categories based on the lo cation of the zip code used in survey mailing in relation to census defined urbanized areas. The 2010 U.S. Census identified urban areas as densely populated census tracks and/or blocks that have at least 2,5000 residents, 1,500 of whom must reside outside intuitional group quarters (U.S. Census, 2011). An urbanized area is an urban area with 50,000 people or more (U.S. Census, 2011). Michigan zip codes and U.S. Census urban areas where mapped using ArcGIS 10.1 (Environmental Systems Research Institute [ESRI], 2012). Michigan zip codes ( and urban area ( data files were downloaded from the U.S. Census TIGER/line Shapefiles website (www.census.gov/geo/maps-data/ data/tiger.html). Michigan zip codes were selected by location in relation to the urbanized area source layer. Zip codes completely within the urbanized area layer were iden tified as urban. Zip codes that intersected the urbanized area, but were not completely within the urbanized area , were identified as the urban buffer. Zip codes not touching the urbanized areas layer were identifie d as not urban. Survey Instrument The 2013 Michigan Deer Harvest Study is a f our-page questionnaire that asks questions about hunter harvest, activities and satisfaction, and statewide deer management issues. Hunters who harvested deer with a Damage Management Assistance (DMA) permits were asked not to report DMA harvest on the questionnaire because it is mandatory to report DMA harvest directly to the MDNR. I included additional questions asking hunters if they shared any of the venison they harvested in the past 12 months, with wh om did they share veni son (immediate household members, relative not within household, frie nds, neighbors or coworkers, landowner who™s property they hunted, community group game dinne r, food bank or other donation program, or other open ended response) and the estimated total number of people they directly shared venison with in the past 12 months (See Appendix A for a complete version of the questionnaire). Categories for possible relations a hunter shared their venison with were derived from pilot interviews with hunters, discussions with MDNR researchers, and previous surveys asking non-hunters about their relationships with hunters (Ljung et al., 2012; Ljung et al., 2014; Stedman & Decker, 1996). Sharing was defined as offering raw (meat) or prepared (cooked) venison to another person. All questions about venison sharing behaviors were limited to a reference period of 12 months to assist respondent recall (Dillman et al., 2009; Vaske, 2008). An open-ended estimate for the total number of people with whom hunters directly shared their venison was used to elicit a full list of possible answers and avoid influencing potential answers with response options (Tourangeau, Rips, & Rasinski, 2000; Vaske, 2008). Additionally, researchers had little information from which to formulate appropriate response options. I purposely asked hunters to estimate the total number of people they directly shared their venison with after prompting them to identify with w hom they shared their venison, assuming that responding to the first question would assist them with their estimate for the second. Variable Construction Dependent variables. Type of venison receivers was created from responses to question nine in the 2013 Michigan Deer Harvest Study questionnaire. It is comprised of seven binary variables describing all the possible relations with whom a hunter shared their venison; immediate household members, relative not with in household, friends, neighbors or coworkers, landowner who™s property they hunted, community group game dinner, food bank or other donation program, or other not specified. Respon dents who checked off the fiotherfl category and provided an explanation were coded into the previously defined categories based on the type of relationship they described. For example, hunting buddies was coded as friends and church potluck as community event. Respondents, who checked off the fiotherfl category and expressed that they had no deer/venison to share were coded as fidid not sharefl. Respondents who provided responses such as fithe wolvesfl or fimy dogfl were removed from the fiotherfl category and coded as fidid not sharefl unless they also provided a response to one of the established sharing categories. Number of venison receivers was a continuous count variable created from responses to question ten on the 2013 Michigan Deer Harvest Study questionnaire. It details the estimated number of people with whom a hunter directly provided venison. Venison Providers was a binary variable identifying whether or not a hunter shared their venison with at least one other person. This fivenison providersfl variable was created from the combined responses to questions nine and ten on the 2013 Michigan Deer Harvest Study questionnaire. If a hunter responded having shared or not shared their venison to at last one of the two possible questions they were identified as sharing or not sharing, respectively. These two questions were combined to maximize the num ber of respondents to questions on sharing behaviors due to issues of non-response. Covariates. Harvested in 2013 was a binary variable identifying if a hunter harvested at least one deer in the 2013 deer hunting season(s). Harvested antlered deer in 2013 was a binary variable identifying if a hunter harvested at least one antlered deer in the 2013 deer hunting season(s). In 2013 hunters were allowed to harvest a maximum of 2 antlered deer. Harvested antlerless deer in 2013 was a binary variable identifying if a hunter harvested at least one antlerless deer in the 2013 deer hunting season(s). This does not include antlerless deer harvested using a DMA permit. Total Harvest was a continuous count variable identifying the total number of deer a hunter harvested during the 2013 deer hunting season(s). Participated in Early and/or Late Antlerless Season(s) was a binary variable describing whether or not a hunter participated in at least one of the early or late antlerless firearm seasons. Participated in Muzzleloader Season was a bi nary variable describing whether or not a hunter participated in the muzzleloader season. Participated in Archery Season was a binary variable describing whether or not a hunter participated in the archery season. Participated in Regular Firearm Season was a binary variable describing whether or not a hunter participated in the regular firearm season. Equipment Used was a categorical variable describing the type of equipment a hunter used during the 2013 deer hunting season(s) where: 0= just a bow (include recurved, compound and cross bows); 2=just a firearm (includes all firearms eligible to be used during any of the deer hunting seasons); 3=both bow and firearm; 4=just participated in di sabled hunts. If a hunter just participated in the disabled hunts it is impossible to figure out what type of equipment they used. If a hunter participated in the disabled hunts and another season they are classified as using the equipment required for the other season, however, they may have used a different type of equipment during the disabled season. Sex was a binary variable where 0=male and 1=female. Age was continuous variable describing the respondent™s age in years at the time of the study. Ecoregion was a categorical va riable that identifies what MDNR Ecoregion the hunter lives in as described by Frawley (2014) where: 0= Upper Peninsula; 1=Northern Lower Peninsula; and 2=Southern Lower Peninsula. Community type was a categorical variable describing the level of urbanization of a respondent™s community where 0=not urban; 2=urban buffer; and 3=urban. Calculating Edible Venison Harvest Equations for edible venison yield. Although many estimates exist, relatively few formal inquiries using actual specimens have been conducted to determine the total amount of edible venison that can be obtained from a white-t ailed deer. I was only able to find five studies, the most recent of which was conducted in 1983, that used wild white-tailed deer, provided some information about methodologies, and reported either raw data, regression equations or both to determine edible venison yield. Table 2.1 provi des a short summary of each study including author(s), year, data source description and final edible venison yield equations. Taking into account the composition of the Michigan deer harv est and ranges in deer size based on age, sex and nutrition, the average of these equations was used to estimate the maximum edible venison yield from the 2013 Michigan deer harvest. Table 2.1: Summary of studies conducted on the am ount of edible venison produced from a white-tailed deer (WTD). Regression equations fo r edible venison yield from this table were used to calculate edible venison yield from the 2013 Michigan deer harvest. Author(s) Year Data Source Equations/Averages Sample Description Location Hamilton 1947 9 WTD 5 Western NY abandoned farmland; 2 Adirondack region NY; 2 Ontario EV=0.6791*LW-16.57 EV=0.859*HDW-16.078 EV=0.573*LW Severinghaus 1949 109 WTD: 22 Bucks, 78 Does; Aged 5 months Œ 11 years; plus Hamilton™s data. Majority Catskills and Western NY; few Adirondack region NY plus Hamilton™s data EV=0.655*LW-13.64 Hamerstrom & Camburn 1950 24 WTD: 5 Fawns (2 doe, 3 buck); 6 yearlings (2 doe, 4 buck); 13 adults (4 doe, 9 buck) Edwin S. George Reserve, Livingston County, Michigan EV=0.538*LW-1.48 Cowan, Hartsook, Whelan, Watkins, Lindzey, Wetzel & Liscinsky 1968 13 WTD aged 12-39 months Not specified, likely Pennsylvania. EV=0.4354*LW+1.5163 EV=0.4945*FDW+5.3977 EV=0.5092*HDW+6.6179 Marchello, Berg, Slanger & Harrold 1983 15 WTD North Dakota EV = 0.49*LW EV=0.59*FDW EV=0.72*SDW Abbreviations Definitions from Cowan et al. (1968). EV Edible Venison Weight of edible red meat (muscular tissue). This does not include the heart or other organs that may be used for consumption. LW Live Weight Total weight of the deer before it is harvested (before bleeding). FDW Field Dressed Weight Weight of deer with its entrails (not including heart, liver, lungs) removed but its™ hide still intact. HDW Hog Dressed Weight Weight of deer with its entrails (including heart, liver, lungs) removed but its™ hide still intact. Often FDW and HDW are used interchangeably, however, the technical difference is defined here. SDW Skinned and Dressed Weight Weight of a carcass that has been hog dressed and then skinned. Additional measures for calculating ed ible venison yield for Michigan deer . Information on the average size of Michigan white-tailed deer and composition of the 2013 harvest were also used to calculate the maximum edible veni son yield for the 2013 Michigan deer hunting season. Average live weights for Michigan white-tailed deer by age (0.5, 1.5, 2.5, 3.5, 4.5, and 5.5+), sex (doe or buck) and year round nutrition (poor or good) can be found in Table 2.2. This table is adapted from reported field dressed weights by Ozoga, Doepker & Sargent (1993; Table 3, p. 43). Field dressed we ights were multiplied by the conversion factor 1.28 to obtain live weights (Case & McCullough, 1987; Harder, 1980). The average weights from poor and good nutrition, respectively, were used as the low and high ends of the range for the maximum edible venison yield estimate. The age structure and total antlered and antlerless harvest from the 2013 Michigan deer hunting season(s) was determined from 2013 MDNR deer checking station data (Mayhew, 2014) and from the 2013 Michigan Deer Harvest Survey Report (Frawley, 2014), respectively (Table 2.3). Calculating edible venison yield for the 2013 deer season(s). Equations from each of the five individual studies reported in Table 2.1 were used independently to calculate edible venison yield, and then outputs were averaged together for final maximum venison yield estimates. First, the edible venison yield for one deer based on age, sex and nutrition was calculated using the average live weight (in pounds) for Michigan white-tailed deer from Table 2.2 (Table 2.4). These values were then multiplie d by the total number of deer harvested per sex and age class (Table 2.3) to determine the total venison yiel d from the 2013 Michigan deer hunting season by age, sex and nutrition. These estimat es were averaged by equation and then in total, to determine the maximum edible veni son yield from the 2013 Michigan deer hunting season(s). Table 2.2: Average live weights for Michigan white-tailed deer by age, sex and year round nutrition adapted from reported fi eld dressed weights by Ozoga et al (1993, p. 43). Field dressed weights were multiplied by the conversion f actor 1.28 to obtain live weights (Case & McCullough, 1987; Harder, 1980). Deer Age (in years) and Sex (M=male; F=female) by antler status Live weight by year round nutrition Poor Nutrition Good Nutrition Average Antlered Deer M 1.5 125163144 M 2.5 164202183 M 3.5 178229204 M 4.5 186239212 M 5.5+ 192251221 Average 169217193 Antlerless Deer M 0.5 659077 F 0.5 597768 F 1.5 115136125 F 2.5 131152141 F 3.5 143161152 F 4.5 151163157 F 5.5+ 154166160 Average 117135126 Antlered and Antlerless Average 143176159 Table 2.3: Composition of 2013 Michigan deer harvest by age and antlered/antlerless deer. Age structure determined from 2013 Michigan Depa rtment of Natural Resources deer checking station data (Mayhew, 2014). Antlered and antlerless division and total harvest numbers determined from the 2013 Michigan Deer Harvest Survey Report (Frawley, 2014). Deer Age (in years) and Sex (M=male; F=female) by antler status Estimated Number of Deer in 2013 Harvest Estimated Percentage of 2013 Harvest Antlered Deer M 1.5 98,59925.6% M 2.5 62,58416.2% M 3.5 34,1128.9% M 4.5 6,6201.7% M 5.5+ 1,1390.3% Total 203,05452.7% Antlerless Deer M 0.5 27,5787.2% F 0.5 27,8157.2% F 1.5 38,61410.0% F 2.5 32,5658.5% F 3.5 26,9647.0% F 4.5 12,8793.3% F 5.5+ 15,8334.1% Total 182,24847.3% Antlered and Antlerless Total 385,302100.0% Table 2.4: Edible venison yield for one deer based on age, sex and nutrition calculated using the average live weight (in pounds) for Michigan white-tailed deer from Table 2.2. The five different equations presented in Table 2.1 and the average of these equations were used to calculate edible venison yield. Deer Age (in years) and Sex (M=male; F=female) by antler status Edible venison yield (in pounds) from one deer by equation and nutrition status Hamilton, 1947 Severinghaus, 1949 Hamerstrom & Camburn, 1950 Cowan et al., 1968 Marchello et al., 1983 Average of five equations Poor Good Avg. Poor Good Avg. Poor Good Avg. Poor Good Avg. Poor Good Avg. Poor Good Avg. Antlered Deer M 1.5 69 94 81 69938166867656 7264618071648575 M 2.5 95 121 108 94119106871079773 90818099908610796 M 3.5 104 139 122 1031361209412210879 101908711210094122108 M 4.5 109 146 128 1081431269812711382 106949111710498128113 M 5.5+ 114 154 134 11215113110213311885 1119894123109101134118 Average 98 131 114 971281138911510275 9686831069588115102 Antlerless Deer M 0.5 28 44 36 29453734474030 4135324438304437 F 0.5 23 36 30 25373130403527 3531293833273732 F 1.5 62 76 69 62756961726652 6156566661587064 F 2.5 72 87 79 72867969807558 6863647569677973 F 3.5 81 93 87 80928676858064 7268707975748479 F 4.5 86 94 90 85938980868367 7270748077788582 F 5.5+ 88 96 92 87959181888568 7471758278808783 Average 63 75 69 63756961716652 6056576662596964 Antlered and Antlerless Average 78 98 88 77978773898162 7568688375718980 Analysis Weighting. The results reported in this thesis are those of the analysis of the aggregate unweighted data. Because of the stratified sa mpling design of the 2013 Michigan Deer Harvest Study the probability of selection in the samp le differed across strata. Vaske (2008) suggests weighting the sample by population proportions to obtain results that can be generalized to the target population. Since the entire population of hunters in each stratum was known prior to sampling, design weights were calculated using the formula population percentage divided by sample percentage (Vaske, 2008). When compared with weighted data, results from unweighted data did not differ statistically (Appendix D). Statistical tests. All analysis was conducted using Stata Version 13 (StataCorp, 2013a). Pearson™s Chi squared ( 2) was used to test whether or not a hunter shared their venison in the past 12 months (venison providers) differed across the binary and categori cal covariates. The phi () coefficient and Cramér™s V were used to measure of the stre ngth of association (effect size) between venison providers and the binary and categorical covariates, respectively. These coefficients range from 0-1, where 0 is no rela tionship and 1 is a perfect relationship. Two-sample t-tests were used to test whether or not a hunter shared their venison in the past 12 months (venison providers) differed across the continuous covariates. Point biserial correlations (rpb) were used to measure the strength of associ ation between venison providers and continuous covariates. Point biserial correlations are a speci al case of the Pearsons r that reports values ranging from -1 to 1 and can be interpreted the same where 0 means no linear relationship and absolute value of the coefficient is the streng th of the relationship. In addition to tests of statistical significance and effect size, all predictors were used in a binary logistic regression to predict a hunter™s sharing behaviors. Ninety-five percent confidence intervals for the proportion of the sample observed w ith trait of interest (p ) were calculated using the formula for confidence intervals with a known population from Zar (1996). Incorporating non-response bias into estimations. Hunters who did not harvest a deer in 2013 were more likely to skip questions abou t venison sharing than hunters who harvested a deer. To minimize potential biases associated with those non-respondents, I report sharing behaviors in the combined venison provider variab le (described above) and use a lower estimate that takes into consideration the fact that non-respondents were less likely to have harvested a deer and thus less likely to have shared venison. Instead of eliminating non-respondents from the results, which would likely inflate sharing estimates, this estimate applies the reported sharing percentages for respondents based on if a hunter harvested a deer or not in 2013 (harvested in 2013 variable) to non-respondents based on their 2013 deer harvest. Results Respondent Characteristics and Analysis Sample An initial 55,537 surveys were mailed, however, 1,260 questionnaires were non- deliverable, resulting in an effective sample size of 54,277. Out of the 54,277 delivered questionnaires, 27,834 questionnaires were retuned by hunters (net response rate ~ 51%). Respondents were 89% male and had a mean age of 44, which closely resembles population parameters for all deer hunting license buyers: 89 % male and an average age of 42 years. Minors (under the age of 18, n=5,856), hunters who reported they did not participate in the 2013 season (n=1,775), and non-Michigan resident hunters (n=1,041) were dropped from the sample for analysis, resulting in a final sample size of 19,981. Hunters as Venison Providers Approximately 51.6% of adult hunters who pa rticipated in the 2013 deer-hunting season reported sharing their venison in the past 12 mont hs. This percentage increased to an estimated 85.1% if a hunter reported harvesting a deer in 2013. Twenty-five percent of hunters who did not harvest a deer in 2013 still reported sharing veni son in the 12 months prior to receiving the questionnaire. Extrapolating to all Michigan hunters who participated in the 2013 deer hunting season; approximately 341,483 ± 4,500 Michigan deer hunters are estimated to have shared their venison. Although many variables were considered statistically different between hunters who did and did not share, only variables related to harvest (harvested in 2013, harvested antlered deer in 2013, harvested antlerless deer in 2013, and total harvest) resulted in a large enough effect size to be considered for any sort of functional relationship when taking into account sample size (Table 2.5). Further analyses were conducted looking for predictors of sharing behaviors in hunters including comparisons between all Michigan coun ties, hunters who shared with many or few people, hunters who shared only within the household, only outside the household or both, and age as a categorical variable. None yielded any statistically significant results with effect sizes large enough to warrant reporting. Some predictors were significant in the binary logistic regression to predict a hunter™s sharing behaviors, however their effect size was also small and the overall model was neither statistically significant nor correctly specified. Table 2.5: Hunting related characteristics and demogr aphic profile of hunters who did and did not share their venison in the past 12 months from the 2013 Michigan Deer Harvest Study questionnaire. (2,719 observations were dropped from this analysis due to non-response). Variable All respondents who provided information on sharing behaviors (n=17,262)* Shared venison in past 12 months (n=9,475) Did not share venison in past 12 months (n=7,787) Statistical test for significant difference between variables on sharing behaviors Strength of the relationship between variables and sharing behaviors N % n % n % Harvested in 2013 Yes 8,53749%7,26377%1,274 16% x2= 6200 p<0.001 phi=0.600 No 8,72551%2,21223%6,513 84% Harvested Antlered Deer in 2013 Yes 5,67533%4,86151%814 10% x2= 3200 p<0.001 phi= 0.433 No 11,58767%4,61449%6,973 90% Harvested Antlerless Deer in 2013 Yes 4,50726%3,89841%609 8% x2=2500 p<0.001 phi= 0.378 No 12,75574%5,57759%7,178 92% Total number of Deer Harvested 0 8,72551%2,21223%6,513 84% t=-81.567 p<0.001 rpb=0.509 t=77.603 p<0.001 1 5,81734%4,83451%983 13% 2 1,99412%1,74718%247 3% 3 5353%5075%28 0% 4 1331%1191%14 0% 5 360%340%2 0% Table 2.5 (cont™d): 6 180%180%0 0% 7 40%40%0 0% Mean 0.710.0071.1220.0090.209 0.006 Participated in Early and/or Late Antlerless Firearm Season Yes 2,06612%1,38515%681 9% x2=140.13 p<0.001 phi=0.090 No 15,18188%8,08085%7,101 91% Participated in Archery Season Yes 9,13753%5,66460%3,473 45% x2=395.24 p<0.001 phi=0.151 No 8,12547%3,81140%4,314 55% Participated in Muzzleloader Season Yes 4,90828%3,08733%1,821 23% x2=177.61 p<0.001 phi=0.101 No 12,35472%6,38867%5,966 77% Participated in Regular Firearm Season Yes 15,39089%8,45189%6,939 89% x2=0.030 p=0.862 phi= 0.001 No 1,87211%1,02411%848 11% Type of Equipment Used Just Bow 1,2327%6737%559 7% x2=423.58 p<0.001 Cramer's V = 0.158 Just Gun 7,78245%3,64138%4,141 53% Bow and Gun 7,90046%4,98853%2,912 37% Age 18-29 1,98812%1,12012%868 11% t= 9.041 Pr (T>t) = 0.000 rpb=-0.069 t=-9.041 p<0.001 30-39 2,17313%1,27313%900 12% 40-49 3,35219%1,96521%1,387 18% Table 2.5 (cont™d): 50-59 4,40526%2,53727%1,868 24% 60-69 3,85122%1,90220%1,949 25% 70-79 1,2557%5766%679 9% 80-89 2301%971%133 2% 90+ 80%50%3 0% mean 51.450.11550.510.15152.59 0.175 Sex Male 15,94092%8,75492%7,186 92% x2=0.0711 p=0.790 phi=-0.002 Female 1,3228%7218%601 8% Ecoregion Upper Peninsula 1,4689%7528%716 9% x2=9.016 p=0.011 Cramer's V=0.023 Northern Lower Peninsula 3,52320%1,93120%1,592 20% Southern Lower Peninsula 12,27171%6,79272%5,479 70% Community Type Not Urban 9,83857%5,44358%4,395 57% x2=1.830 p=0.400 Cramer's V=0.010 Urban Buffer 5,94435%3,22434%2,720 35% Urban 1,4338%7828%651 8% * For community type variable n= 17,215 for all respondents who provided information on sharing behaviors. Venison Receivers Michigan deer hunters who shared their venison, shared with a mean of 5.6 people (SD = 4.52, Figure 2.1). Considering the estimated number of hunters who share, an estimated 1,912,305 people ± 67,209 people, or 19.35% ± 0.68% of the total Michigan population, received venison from hunters during the 12 months prior to survey administration. Of hunters who reported sharing venison, approximately 68.8% shared with members of their household, 52.0% with relatives, and 50.4% shared with friends, neighbors, or coworkers (Table 2.6). Only 2.4% of hunters who shared reported donating venison to a food bank or other donation program. This proportion, however, equates to an estimated 15,882 ±1,390 hunters statewide during the 2013 deer hunting seasons. Maximum Edible Venison Yield for 2013 A maximum estimated 26-33 million pounds of edible venison were harvested during the 2013 deer hunting seasons: 10-12 million pounds from antlerless deer and 16-20 million pounds from antlered deer (Table 2.7). Discussion Hunters as Venison Providers In the absence of legal markets in WHM, Mi chigan hunters share frequently and widely with a variety of people in their social network. This highlights the ubiquit y of sharing behaviors among hunters, but also the limitations in the ex tent of venison consumption under a non-market system. However, these results al so suggest that that many peopl e, beyond just hunters, benefit Figure 2.1: Distribution of the number of people hunter s reported sharing their venison with over the past 12 months from the 2013 Michigan Deer Harvest Study (Mean=5.6, SD=4.52). Table 2.6: To whom Michigan deer hunters provided venison during the past 12 months from the 2013 Michigan Deer Harvest Study questionn aire. (4,758 observations dropped due to non-response.) Receivers n % Out of those who shared (n= 9,063) % Out of all respondents to the question (n= 15,223) I did not share any of my venison 6,160 40% Members of my household 6,243 69% 41% Relatives not in my household 4,713 52% 31% Friends, neighbors or coworkers 4,568 50% 30% Landowner whose property I hunted 1,165 13% 8% Community Group game dinner 243 3% 2% Food bank or other donation program 219 2% 1% Other Not Specified 75 1% 0% 0200 400 600 800 1000 1200 1400 1600 246810121416182022242629313540 Number of providers Number of recievers Table 2.7: Total venison yield in pounds from the 2013 Michigan deer hu nting season by age, sex and nutrition calculated using the values from Tables 2.3 and 2.4. Deer Age (in years) and Sex (M=male; F=female) by antler status Edible venison yield (in pounds) by equation and nutri tion status for the 2013 Michigan deer hunting season(s) Hamilton, 1947 Severinghaus, 1949 Hamerstrom & Camburn, 1950 Poor Good Avg. Poor Good Avg. Poor Good Avg. Antlered Deer M 1.5 6,765,506 9,251,0118,008,2596,756,3269,153,6257,954,9766,508,2038,477,2837,492,743 M 2.5 5,926,276 7,558,2966,742,2865,862,5327,436,6346,649,5835,423,8666,716,7936,070,329 M 3.5 3,556,321 4,742,3784,149,3493,510,0024,653,9684,081,9853,214,7104,154,3343,684,522 M 4.5 724,740 966,440845,590714,525947,648831,087651,266842,747747,007 M 5.5+ 129,690 175,251152,471127,756171,701149,728116,015152,110134,063 Total 17,102,533 22,693,37719,897,95516,971,14122,363,57719,667,35915,914,06020,343,26718,128,664 Antlerless Deer M 0.5 765,617 1,221,091993,354803,0341,242,3441,022,689927,7491,288,5871,108,168 F 0.5 651,289 989,777820,533693,3161,019,792856,554839,9281,108,087974,007 F 1.5 2,381,043 2,918,0892,649,5662,386,9782,904,9642,645,9712,336,0692,761,5292,548,799 F 2.5 2,347,683 2,828,8962,588,2902,340,6332,804,7692,572,7012,239,1782,620,4072,429,792 F 3.5 2,178,291 2,506,4262,342,3592,164,1362,480,6262,322,3812,039,7492,299,7052,169,727 F 4.5 1,107,635 1,208,3931,158,0141,098,4901,195,6721,147,0811,027,5031,107,3261,067,415 F 5.5+ 1,389,206 1,526,8361,458,0211,376,9861,509,7321,443,3591,284,9761,394,0101,339,493 Total 10,820,764 13,199,50812,010,13610,863,57313,157,89912,010,73610,695,15112,579,65211,637,401 Antlered and Antlerless Total 27,923,297 35,892,88531,908,09127,834,71435,521,47631,678,09526,609,21132,922,91829,766,065 Table 2.7 (cont™d): Deer Age (in years) and Sex (M=male; F=female) by antler status Edible venison yield (in pounds) by equation and nutri tion status for the 2013 Michigan deer hunting season(s) Cowan et al., 1968 Marchello et al., 1983 Average of five equations Poor Good Poor Poor Poor Avg. Poor Good Poor Antlered Deer M 1.5 5,534,651 7,128,2156,331,4336,060,4537,853,8536,957,1536,325,0288,372,7977,348,913 M 2.5 4,559,355 5,605,7135,082,5345,024,3126,201,8855,613,0985,359,2686,703,8646,031,566 M 3.5 2,694,225 3,454,6573,074,4412,973,8763,829,6683,401,7723,189,8274,167,0013,678,414 M 4.5 545,034 699,998622,516602,085776,482689,283647,530846,663747,097 M 5.5+ 96,983 126,194111,588107,200140,075123,637115,529153,066134,297 Total 13,430,248 17,014,77715,222,51314,767,92618,801,96216,784,94415,637,18220,243,39217,940,287 Antlerless Deer M 0.5 825,670 1,117,694971,682882,1501,210,7941,046,472840,8441,216,1021,028,473 F 0.5 755,238 972,258863,748802,4831,046,717924,600748,4511,027,326887,888 F 1.5 1,995,367 2,339,6892,167,5282,179,6962,567,1982,373,4472,255,8302,698,2942,477,062 F 2.5 1,900,534 2,209,0602,054,7972,083,2952,430,5112,256,9032,182,2652,578,7292,380,497 F 3.5 1,723,937 1,934,3181,829,1281,894,1102,130,8732,012,4912,000,0442,270,3902,135,217 F 4.5 866,507 931,107898,807953,1911,025,892989,5421,010,6651,093,6781,052,172 F 5.5+ 1,082,895 1,171,1361,127,0161,191,6741,290,9801,241,3271,265,1481,378,5391,321,843 Total 9,150,149 10,675,2639,912,7069,986,59911,702,96510,844,78210,303,24712,263,05711,283,152 Antlered and Antlerless Total 22,580,397 27,690,04125,135,21924,754,52530,504,92827,629,72725,940,42932,506,45029,223,439 from WHM in a non-market system and that changes to this system could have impacts on how WHM is distributed and used. Other research suggests sharing of WHM provides cultural ecosystem services to hunters and the recipients of their harvest. Although co nclusions about the importance of sharing to Michigan deer hunters cannot be made directly fro m this study, the vast number of hunters who share their harvest provides evidence of the cultural ecosystem services WHM sharing and consumption produce in Michigan. Re search that identifies and assesses the specific nature and effect of cultural ecosystem services provide d by sharing WHM would inform deliberations about social relevance of hunting (Larsen et al., 2014). It is not surprising that hunter-sharing behaviors were highly correlated with having a deer; you cannot share what you do not have. Besi des harvesting a deer, there were no other variables that explained whether or not a hunter shared their venison. Either, there are no differences between hunters who do and do not share, the variables measured in this study (besides harvest) are not sufficient to define characteristics of venison providers, or measurement error exists in assessing sharing behaviors. Anthropological theories on food sharing credit the social environment surrounding a hunter as a driver for their sharing behaviors (Kaplan & Gurven, 2005; Koster, 2011; Nolin, 2010). This study did not measure these factors, such as number of household members or interhousehold distance between the hunter and their relatives and friends. Other potential factors that may be responsible for shar ing behaviors that were not meas ured are how a hunter uses their venison and individual personality traits. There are two main sources of measuremen t error for questions relating to hunter™s sharing behaviors. It is possible that there may be social desira bility bias in reporting sharing behaviors, thus more hunters ma y have reported sharing than actually do share. There is no way to assess the influence of social desirability bias on hunter response to these questions. Previous research, however, suggests that when hunters report sharing behaviors, they are honest but forgetful (Nolin, 2010). If Nolin™s (2010) findings are accurate, sharing behaviors in my study may be under-reported rather than over-reported. Furthermore, because sharing behaviors are partially dependent on harvesting a deer, just because a hunter did not share this year does not mean that have not shared in previous year s or will not share in the future. A one-year measurement of sharing behaviors may underest imate the total number of hunters who share venison because the availability of venison varies year-to-year. A better way to measure variability in sharing behaviors would be to identify sharing behaviors over a longer period of time or to categorize hunters base d upon the frequency of their sharing behaviors when they have venison (e.g., never, sometimes, always). Venison Receivers Michigan deer hunters who shared, provided venison to an average of approximately 6 people over a 12 month period of time. This find ing illustrates the role of sharing in the amplification of ecosystem serv ices provided by hunting to a larger portion of the population. However, as discussed previously, this estimate might be low. For deer hunters, the act of sharing venison is relatively habitual, and thus they are less likely to remember each occurrence (Nolin, 2010; Tourangeau et al., 2000). Another factor that may influence the number of people a hunter reported sharing with, or if they reported sharing at all, is their own definition of sharing. Although study questions provided a definition of sharing and response categories, some hunters may not define providing venis on to the household as sharing. Also, in question piloting and through antidotal conversations, hunters often use sharing to refer to giving away packages of raw meat, not having friends over for dinner. Th us, although sharing was defined as including raw and cooked venison meals, it is possible that some hunters referred only to providing packages of raw meat in their estimates. A dditionally, the estimate a hunter provided for the number of people they shared their venison with did not include people they shared with at large events. It is likely the average number of people a hunter shares with is higher than reported in this study. Hunters who provided information on their sh aring behaviors most often shared within their household. This is expected based on evolutionary theories of kin selection which predict increased food sharing with kin because it increases chances of offspring survival (Kaplan & Gurven, 2005). Relatives were the second most common relation hunters sh ared venison with, closely followed by friends. Relatives not within the household received venison less frequently than household members, supporting Koster™s (2011) theory that sharing is more common between lineal than collateral kin. What is unexpected is that hunters shared venison with friends almost as frequently as with relatives. A small percentage of hunters reported sharing venison at a community game dinner or providing venis on to donation programs, yet these events can generate more recipients than pr oviding venison at the individual level. My results suggest that frequency of hunter sharing behaviors decreases with increased social distance from the hunter. Social proximity appears to be a key factor influencing sharing behaviors among hunters. The frequency with which hunters share outside of their household suggests that socialization to hunting through WHM venison may occur. The nu mber of non-hunters with whom hunters shared, however, cannot be estimated from my results. Maximum Edible Venison Yield for 2013 Often the value of WHM is measured in economic terms, or the price per pound of a roughly equivalent product (Wilcox, 1976). Prices for farm-raised venison avai lable in stores and online vary considerably and lack market resear ch. For example prices at Elk USA range from $9.95 per pound for ground venison up to $39.95 per pound for tenderloin, while ground venison from Michigan Venison has a similar pri ce but tenderloin costs only $24.00 per pound. However, ground venison in Lansing, Michigan grocery stores from Butcher Boy Food Products costs approximately $13.00 per pound. Extensive mark et research is conducted on national beef prices by the USDA Economic Research Service (E RS). Thus, although venison is superior to beef in many ways, using the price of high qualit y lean beef is the best option for an economic assessment of the value of wild harvested ve nison. From June 2013-June 2015 the average price per pound for USDA choice boneless sirloin steak was $7.61 (Hahn, 2015). Based on this information the economic value of the venison harvested by Michigan deer hunters in 2013 was between $197 and $247 million US dollars. It is likely that this estimate is low because farm raised venison prices seem to be much highe r. Besides being healthy, the venison hunters™ harvest represents a large economic value, providing hunters with a return for their investment in hunting and potentially savings on their grocery bill. The economic value of wild harvested venison is another example of the provisional ecosystem services WHM can provide. The amount of venison produced each year by Michigan deer hunters provides an average of approximately 3 pounds of venison - or twelve 4-ounce servings - for every person in Michigan. The U.S. Department of Agriculture (USDA) and U.S. Department of Health and Human Services (HHS) recommend 26 oz per week of meat, poultry, or eggs for a healthy diet (USDA & HHS, 2010). The venison harvested by Michigan deer hunters in 2013 represents the yearly meat protein requirement for 307-385 th ousand adults, or 3-4% of the Michigan population. Although venison harvested cannot be used as the sole meat protein source for a vast majority of people, enough venison is harveste d each year that some families may rely on venison as a substantial source of protein. In addition to protein, venison has 16-23% less fat and higher percentages of monounsaturated fats and omega 3 fatty acids co mpared to domestic meat (O™Keefe & Cordain, 2004). WHM is free of most antibiotics, hormone supplements, and other additives. Substituting domestic meat with venison can have positive he alth effects (Larsen, 2003). The sheer amount of venison harvested by hunters in Michigan each year clearly demonstrates the provisional ecosystem services that WHM can provide in te rms of protein and access to nutrition, and these benefits are valuable and sought after regardless of the frequency of consumption. It is important to interpret the estimates produced here as a maximum possible yield of edible venison because researchers reporting meat yield did so from animals mostly taken under controlled conditions. For instance, Hamerstrom & Camburn (1950) state that their results are likely not representative of the edible venison yield from recreational hunting due to the scientific nature of the harvest (e.g. neck shots to maximize meat yield) and processing. All of the studies used in the formula tion of my calculations for edible venison yield per deer, used either professional or highly trained butchers to conduct their processing. Furthermore, hunters may be choosier with what meat they keep fo r consumption. Accuracy of the shot, care and speed in dressing and bleeding, butchering ability, and differences in deer size and weight all influence the amount of edible venison a deer yields (Cowan et al., 1968; Hamerstrom & Camburn, 1950; Hamilton, 1947; Marchello et al., 1983; Severinghaus, 1949). Also, the type of hunting equipment used and the deer™s physical condition at time of kill influence how much edible venison is produced (Jenkins & Bartlett, 1959). Additional studies that more accurately estimate the range of edible venison yields fr om wild harvested deer would provide a more accurate estimate of edible venison yield from recreational deer hunting. Although no standardized method has been establ ished to calculate the amount of edible venison produced from a deer, most estimates are based upon the average size of the deer harvested (Cowan et al., 1968; Hamerstrom & Camburn, 1950; Hamilton, 1947; Marchello et al., 1983; Severinghaus, 1949). To use these equations, assumptions were made about the average size of a deer harvested in Michigan. Weights of white-tailed deer vary based on subspecies, region, season, age and habitat quality (Sauer, 1984). Michigan hunters typically harvest deer younger than five years, which likely increases variability in live weights of harvested Michigan deer (Ozoga et al., 1993). Although this study™s calculations attempted to control for these variations, some error is unavoida ble when estimating edible venis on yield using the average size of a live deer. Furthermore, as th e amount of deer harvested varies from year to year, the amount of edible venison produced from one hunting season to the next may be quite variable The equations used to estimate edible venis on yield also varied considerably, likely due differences in methodologies and for the reasons described above. However, these equations provide the best available method for estimati ng maximum edible venison yield from the 2013 Michigan deer harvest. Further information on venison consum ption rates and sharing amounts could help identify how the resource is being used and the specifics of the provisional ecosystem services it provides. CHAPTER 3 The Extent of Venison Shari ng and Consumption: Receivers Major societal transformations are changing the way humans interact with and think about nature and wildlife (Heberlein & Ericsson, 2005; Manfredo et al., 2009; Manfredo et al., 2003; Robinson & Ridenour, 2012; Whittaker et al., 2006; Zinn et al., 2002). In 1820, 5% of the U.S. population lived in cities (Organ et al., 2010); in 2010, 80% of the U.S. population inhabited urbanized environments (U.S. Ce nsus, 2010). Living in a man-made urban environment decreases the frequency of direct ex perience with wildlife, an d more broadly nature, increasing the geographical and social distan ce between human and natural systems (Dizard, 2003; Heberlein & Ericsson, 2005; Manfredo et al., 2009; Manfredo & Zinn, 1996; Robinson & Ridenour, 2012). Furthermore, fewe r ties to rural environments and utilitarian values expressed by people who live in urbanized environments may mean decreasing support for traditional natural resource users, such as hunters (Heberlein & Ericsson, 2005; Manfredo et al., 2009). Weakening links between human and natural system s are identified as a threat to environmental conservation and human well-being (MEA, 2005). Identification and understanding of current links between human and natural systems, how thes e links are being used and can continue to be used in order to maintain and reinforce conn ections between human and natural systems can have implications for wildlife management , conservation policy, public health and the preservation of traditional natural resource use cultures. Hunting, and the sharing and consumption of the wild harvested meat (WHM) it produces, are important sociocultural, economic , ecological and nutritional activities around the world (Fischer et al., 2013). WHM, the meat of wildlife Œ animal s that maintain their wild state and survive with minimal human intervention Œ procured through hunting is an important and valuable natural resource. Sharing and consuming WHM has been identified as a potentially significant coupler of human and natural systems (Freeze, 1997; M. N. Peterson et al., 2010). The framework of Coupled Human and Natural Systems (CHANS) proposed by Liu et al. (2007) aids in understanding the impor tance of WHM to society by identifying the provisional and cultural ecosystem services associated with WHM sharing and consumption. Provisional ecosystem services are the tangible benefits people receive from nature (Liu et al., 2007; MEA, 2005), such as the nutritional value of WHM. WH M is local free-range lean protein, high in energy content and essential macronutrients that is also antibiotic, hormone, and additive free, and is not subject to engineered genetic modi fications (Larsen, 2003; O™Keefe & Cordain, 2004). Cultural ecosystem services are the non-tangible benefits people derive from natural systems (Liu et al., 2007; MEA, 2005). Culture and nature are inevitably linked, providing humans with cultural ecosystem services such as spiritual and religious associations with nature, recreational opportunities, aesthetic or inspirational enjoyment, creating a sense of place and cultural heritage, enforcing social relations, and offing educational opportunities (Hernandez-Morcillo et al., 2013; MEA, 2005). Potential cultural ecosystem services provided by the sharing and consumption of WHM include: establishing and maintaining social relations, social recognition of a successful hunter, a remi nder of the hunting experience, and a direct connection to nature and the source of our food (Fletcher, 2011; Heffelfinger, 2014; Jiménez et al, 2011; Omura, 2013; M. N. Peterson et al., 2010). Sharing WHM is not only an important el ement of the hunting experience, but also amplifies provisional and cultural ecosystem se rvices WHM provides to a larger portion of society. In the US, where the sale of WHM is illegal in almost all in stances, sharing through social networks is the only way WHM is move d through society. Heberlein (1991) proposed that participation in social activiti es where WHM is shared may deve lop acceptance of the activity among non-hunters by strengthening or developing shar ed beliefs. Sharing WHM at meals, or in other ways, is thought to be one readily availa ble and effective means of enhancing positive social interaction among non-hunters and hunters or of socializing non-hunters to hunting via food and stories about hunting (Stedman and Decker, 1996). In Sweden Ljung et al., (2012) reported that WHM consumption positively influe nced attitudes toward hunting. Effects of sharing WHM were found to be similar in ru ral and urban settings in Sweden, although availability Œ and thus frequency of consumptionŒ are markedly different in these two environments (Ljung et al., 2014). The societ al impacts WHM provides are created by an individuals perceived benefits or costs when interacting with WHM. Creating opportunities to share WHM may help society recognize these im pacts and the important role WHM plays in coupling human and natural systems. To analyze the role of WHM as a coupler of human and natural systems, it is necessary to first explore the extent of WHM sharing a nd consumption and the mechanisms for WMH transfer. Sharing involves two different actions, providing and receiving, each with their own motivations and effects. Chapter 2 focused on the providers (hunters) of WHM. This chapter focuses on receivers of WHM Œ people who were provided (or received) WHM, either from another individual or from their own harvest. I measured the extent and mechanism of WHM movement through society by identifying: 1) the social and physical pathways by which WHM is transferred to a receiver; 2) opportunities a nd barriers to WHM reception; 3) number and attributes of receivers; 4) and frequency of WHM consumption by receivers. Results from this study will help identify potential ecosystem serv ices provided by WHM, the beneficiaries these ecosystem services, and populations who may not receive these benefits. Methods Study Area and Population Michigan (56,539 mi 2) is located in the northcentral US, bounded by Lake Superior to the north, Lake Michigan and Wisconsin to the west, Indiana and Ohio to the south and Lakes Huron and Erie and the Canadian province of Ontario to the east. Traveling south to north along Michigan™s landscape human density and intensit y of land use typically decrease (MDEQ, 2014; MDTMB CSS, 2011). Approximately 75% of Mi chigan™s population lives in urban areas (U.S. Census, 2010). In 2010, Michigan™s population was estimated to be 9,883,706, comprised of 76.6% white non-Hispanic or non-Latino, 49.1% male , with a median age of 38.9 years (U.S. Census, 2010). From 2003-2005 an average of 790,000 people purchased a Michigan hunting license each year with an averag e age of 41 years, 92% of who were male (Frawley, 2006). Deer hunting (90%), small game (37%), and turkey (14%) were the three most popular licenses purchased during this time frame (Frawley, 2006). Deer hunting has maintained its popularity in the state. During the 2013 hunting season 712,404 people purchased a deer hunting license a majo rity of whom were male (89%) with an average age of 42 years. While-tailed deer hunting has a long history and heritage in Michigan (Langenau, 1994; Rudolph, 2005). Because deer are widely distri buted (Geist, 1998) and readily used and valued by humans (Roth & Merz, 1996), focusing on the sharing of venison increases the generalizability of this study. The popularity of deer and deer hunting in the US (Aiken & Harris, 2011; USFWS, 2011) and the large amount of venison produced by a single deer likely increase the frequency of sharing behaviors (Gurven, 2004b; Stransky, 1984), ensuring a wide range of experiences with venison and the ability to conduct research across large populations. Sampling Design Questions were included in the Michigan St ate University (MSU) Institute for Public Policy and Social Research™s (IPPSR) Office for Survey Research (OSR) 68th State of the State Survey (SOSS); a longstanding quarterly telephone survey with standardized protocol. A full report on methodologies including questions and raw data can be found on the IPPSR website (http://ippsr.msu.edu/soss/). SO SS methods were reviewed and approved by the MSU Human Research Protection Program (HRPP) Social Sc ience / Behavioral / Education Institutional Review Board (SIRB) to ensure the protection of huma n subjects (IRB #x95-499e). The target population for this study was Michigan residents > 18. However, as data were collected via telephone interviews, the study population was further limited to English-speaking individuals that either lived in a household with a landline or possessed a cellphone and could effectively communicate over the phone. The sampling frame was divided into thr ee separate segments: re-contacted, new landline, and new cell phone. The re-contacted segment was comprised of all respondents who completed the interview two rounds earlier (66 th SOSS) and who agreed to be recontacted. Respondents can only be recontacted for one additional survey, ensuring that these individuals only responded to the 66th and 68th SOSS. According to the IPPSR OSR, with adjustments for non-response, this recontact sample still represents a representative random sample of the target population. IPPSR OSR contracted Survey Sampling, INC. (SSI) to provide samples of landlines and cellphone numbers within the state of Michigan for the new landline and cellphone segments. The new landline sample was created using a list-assisted random-digit-dial (RDD) sampling procedure (Casady & Lepkowski, 1993) . SSI selected known working Michigan area code and phone number exchanges from a contin uously updated countrywide database of all known working area code and phone number exchange combinati ons. The sample was stratified by county and the total number of possible 10 digit phone numbers per county was calculated. Phone numbers within each county were randomly selected and allocated proportionally based upon a county™s contribution to the total number of possible phone numbers for the state. Additionally, Disproportionate Stratified Samp ling (DDS) was used to improve efficiency (Center for Disease Control, 2013). The sample wa s divided into two strata Œ listed and unlisted numbers Œ and was sampled in a ratio of 1.5: 1 listed to unlisted. SSI also removed known numbers associated with busine sses and institutions and screened the sample for disconnected numbers. The new cellphone segment was also derived us ing RDD. SSI created a database of all known number exchanges allotted to wireless numbers derived from the monthly updated Telcordia Terminating Point Master Data File. SSI compared this database to its list-assisted RDD database and removed listed numbers to avoi d dual sampling frames. SSI also screened the final sample and divided it into categories ba sed on level of billing activity; IPPSR OSR only contacts cellphone numbers with recent billing activity. Potential respondents within each of these three segments we re contacted differently. All numbers within the re-contact segment were used. Numbers from the new landline and cellphone segments were selected randomly in bl ocks of 50 from their respective SSI samples. Once pulled from the SSI sample all numbers were contacted, regardless of if the total number of respondents was reached. Subsamples were pulled in this manner so that an accurate response rate could be calculated from all attempted numbers. IPPSR OSR attempted to contact an equal number of landline and cellphone users, however more cellphones numbers were pulled from the SSI sample because the working number rate and co mpletion rate for cellphone is less than that of landlines. Data Collection The 68th SOSS telephone interviews were conducted April 11 to June 24, 2014 during all times of the day and week. Numbers selected to be contacted, and for which an address was available, were sent a notification approximate ly one week in advance of being contacted (Appendix J). A minimum of nine call attempts were made per number, after which the call schedule for that phone number was reviewed by a SOSS supe rvisor to determine if more contact attempts should be made at different time s or on different days. Supervisors reviewed the time of day and days of the week the nine calls were made to ensure equal representation. If contact was established, but no interview conducted, 12 attempts to conduct the interview were made or until the individual refused the interview. Respondents within each of the three segmen ts (recontact, landline, and cellphone) were selected differently. Interviews conducted within the recontact segment were done with the individual who originally responded to 66 th SOSS survey questions. When contacting a new landline number the interviewer established that the phone line was associated with a residence, and that the person who answered the phone was over the age of 18. The Troldahl-Carter technique then was used to select a respondent using probability sampling. The Troldahl-Carter technique asks the respondent how many adults over the age of 18 live in the household including themselves and how ma ny of those adults are male (Troldahl & Carter, 1964). Four matrices are used to randomly select a re spondent based on the number of adults in the household, their sex and age (Troldahl & Carter, 1964). Cell phone numbers were assumed to belong to one individual and no selection process was used, however, cell phone respondents had to be the owner of cell phone, 18 years or older and a resident of Michigan to be eligible for the study. Interviewers were trained by SOSS supervis ors and provided the rigorously developed OSR telephone interviewing training package, in addition to specific instructions on the 68th SOSS instrument and question objectives. Interv iews were conducted using Computer Assisted Telephone Interviewing (CATI) implemented with the Computer Assisted Survey Extension System software (CASES version 5.5). This prog ram presents the interviewer with the scripted interview in sequential order as programed by the IPPSR OSR and assists the interviewer in recording responses to closed-ended and open-ended questions. By guiding the interviewer through the interview script the CASES program improves data quality by minimizing human error in questionnaire administra tion and data collection, reduces variability across interviewers through standardized protocols and monitoring, and results in a more streamlined interview process increasing the efficiency of questionnai re administration and data collection (Shanks, 1983; Tourangeau et al., 2000). Survey Instrument ISSPR OSR uses well-established basic demographic questions on the SOSS. These demographic questions were used to determin e a respondent™s sex, age, education level, ethnicity, race, religious affiliation, political party identity, political ideology, household income, community type and Michigan county of residence. Study specific questions were piloted th rough focus groups with upper level MSU Department of Fisheries and Wildlife undergradu ates, an Amazon Mechanical Turk survey, two rounds of phone interviews conducted with non-hunters and hunters by a undergraduate intern, and pilot interviews conducted by ISSPR OSR- trained interviewers. Open-ended and closed-ended questions were used to determine personal hunting experience, relationships with hunters, overall WHM consumption activities and venison sp ecific behaviors. (Note: Interview questions used the term ‚game meat™ -see Appendix E fo r full question wording). WHM was defined as derived from hunting in Michigan and that it did not include meat that was bought at a store or farm, or was eaten in a restaurant. Additionally, the phrase ‚whether you were the hunter or were given the meat by a hunter™ was used to establish that the individual did not have to be a hunter to have eaten WHM. Venison was defined as deer meat to ensure respondent understanding. Respondents were first asked if they had ever eaten WHM. Respondents who identified as having eaten WHM were asked a open-ended question about what types of WHM from hunting in Michigan they had consumed. Respondents who identified as having not eaten WHM were asked an open-ended question to determin e if there was any particular reason why not. Open-ended questions were used here to elic it a full list of possi ble answers and avoid influencing potential answers with response options (Tourangeau et al., 2000; Vaske, 2008). Additionally, researchers had very little information from which to formulate appropriate response options. If a respondent answered as having eaten venison they were asked specific questions about frequency of venison consumption over the past 12 months (not at all, once or twice, 3 to 10 times, more than 10 times), from whom it was provided (self, member of household, family not within household, friends , neighbors or coworker, community game dinner or event, other open ended), and in what form the venison was provided (uncooked or raw, cooked or prepared, and other open ended). All questions about venison were limited to reference period of 12 months to assist respondent recall about specific behaviors (Dillman et al., 2009; Vaske, 2008). All respondents were asked about their relationships with hunters (member of household, family not within household, frie nds, neighbors or coworker, and other open ended) and their level of hunting experience. Partially close-ended response options were used to ensure all possible response opti ons were recorded. (A complete interview transcript can be found in Appendix E). Variable Construction Dependent variables. Wild harvest meat consumption was a binary variable reporting whether or not an individual has ever consumed WHM. Frequency of venison consumption was a mutua lly exclusive ordinal categorical variable that is treated as a continuous variable in analysis. It meas ures a respondents frequency of venison consumption from 0-4 where: 0 = never consumed venison; 1 = consumed venison at least once during their lifetime; 2 = consumed venison 1-2 times in the past 12 months; 3 = consumed venison between 3 and 10 times in the past 12 months; and 4 = consumed venison more than 10 times in the past 12 months. If a respondent had reported consuming WHM, but not venison they were excluded from this variab le, rather than coded as never having consumed venison. Covariates. Hunter in household was a binary variable reporting whether or not the respondent lived with a hunter at the time of the interview. Relative(s) hunt(s) was a binary variable reporting whether or not the respondent has family that does not live w ithin their household that hunt. Friend(s) hunt(s) was a binary variable reporting whether or not the respondent has friends, neighbors or coworkers who hunt. Knew hunter growing up was a binary variable reporting whether or not anyone close to the respondent hunted while they were growing up. Social Network was a mutually exclusive ordinal categor ical variable that is treated as a continuous variable in analysis. It measures the number and strength of relationships a respondent has with hunters. It is created out of the four binary variables hunter in household, relative(s) hunt(s). friend(s) hunt(s) and knew hunter growing up. The variable is coded as follows: 0= knows zero hunters; 1=only knew a hunter growing up; 2=only has friends that are hunters; 3= Knew a hunter growing up and has friends that are hunters; 4= Has relatives that are hunters, or has relatives and friends that are hunters, or has relatives that are hunters and knew a hunter growing up; 5= Has relatives and friends that are hunters and knew a hunter growing up; and 6= Has a hunter in their household and may have other relationships with hunters. Most respondents in category 6 not only had a hunter in their household, but also had relatives and friends who hunt and knew a hunter growing up. Community type was a categorical variable describing the level of urbanization of a respondent™s community where 1=rural; 2=between rural and urban; and 3=urban. Sex was a binary variable where 0=male and 1=female. Age was continuous variable describing the respondent™s age in years at the time of the interview. Race was a binary variable where 0=white and 1=not white. Income was a mutually exclusive ordinal catego rical variable that is treated as a continuous variable in analysis. It measures a respondent™s a nnual household income from 1-11 where: 1= Less than 10,000; 2=10,0 00-19,999; 3=20,000-29,999; 4=30,000-39,999; 5=40,000-49,999; 6=50,000-59,999; 7=60,000-69,999; 8= 70,000-89,999; 9=90,000-99,999; 10=100,000-150,000 and 11=More than 150,000. Education level was a mutually exclusive ordinal categor ical variable that is treated as a continuous variable in analysis. It measures th e high level of education a respond has achieved at the time of the interview where: 0-11 = 0-11 th grades respectively; 12=high school graduate or GED holder; 13 = 1st year of college; 14= 2nd year of college; 15=technical/junior college graduate; 16=3rd year college; 17= 4 year college gra duate; 18=some post graduate; 19=graduate degree. Coding open-ended questions. All open-ended responses were field coded by the interviewer to assist in coding of open-ended responses. The researchers provided the interviewer with a list of likely response s to open-ended question (see Appendix E for a complete list of field coding optio ns per question). The interviewer was instructed to only code responses that exactly matched the response options; otherwise they transcribed the respondent™s complete answer to be coded later by the researcher based on thematic similarities (Babbie, 1990). A complete description of how all opened questions were coded can be found in Appendix I. Analysis Weighting. The IPPSR OSR uses a complex weigh ting scheme for SOSS called design weighting and iterative proporti onal fitting (also called raking weighting) (CDC, 2013). Design weighting takes into account a respondent™s probabilities of selection and iterative proportional fitting adjusts the data to match demographic characteristics of the target population. For a complete detailed description of how the weigh ting factor was created see pages 7-9 in the 68th SOSS Methodological Report (http://ippsr.msu.edu/soss/). The landline and cellphone segments of the data were weighted to correct for unequal probabilities of selection. The recontact segmen t was combined into either the landline or cellphone segment accordingly. IPPSR OSR assume s that because the recontact segment was originally selected using the same methodologies, they do not differ from the new sample in terms of selection probability. The landline segm ent was adjusted to re present the number of unlisted versus listed numbers. Listed numbers we re adjusted to represent only 65% of all data records in accordance with National Center for Health Statistic estimates for the time the sample was taken (Piekarski, 2013). The landline segment was then weighted by the reciprocal of the number of separate phone lines the household had and by the inverse of the number of adults in the household and then adjusted so that the total number of cases matched the actual number of completed interviews for the landline segment. The cellpho ne segment respondents were weighted by the reciprocal of the combined total number of separate landlines and cellphone numbers the respondent had and then adjusted so that the total number of cases matched the actual number of comple ted interviews for the cellphone segment. The landline and cellphone segments were then merged and adjusted so that the proportion of respondents who only owned a cellphone matched the estimated proportion of Michigan residents in 2012 that only owned a cellphone according to the most recent National Health Interview Survey estimates. Adjustments for non-response were made using the 2008-2012 American Community Survey (ACS) to match statewide proportions for race (white, black, other racial group) and sex (male or female) by age group in years (18-29, 30-29, 40-49, 50-59, 60-69, 70-79, and 80 or older). The weighted data were then adjusted to ensure that the number of cases for each region was the same as the actual number of interviews completed. Respondents from the Detroit area were deflated to proportionally represent Detroit within the southeast region of Michigan. The data were then weighted so that the propor tion of cases from each region matched the 2008-2012 ACS for total adult population per region. The final weighted data set was compared against the 2008-2012 ACS distributions for race, sex, age and region. A final weighting was done to bring all distributions within 1.10% of the actual va lues according to the ACS. The final weighting factor was defined as STATEWT2. Design-based analysis. All analysis was conducted using Stata version 13 (StataCorp, 2013a). The complex sampling design of the SOSS violates the assumption that observations are independently and identically distributed and thus requires a design-based analysis using sample weights. When analyzing data derived from a co mplex survey, design-based analysis results in increased accuracy in the calculation of point estimates and standard error (StataCorp, 2013b). Using the svy command Stata reports the F-statistic in the form of an adjusted Wald test statistic (Fw) (Aneshensel, 2012). The design-based equivalent to the Pearson chi-square test statistic is a second order design-adjusted Rao-Scott F-test statistic (F S-R Pearson) (Heeringa, West & Berglund, 2010). A design-based logistic regression model was used to identify the determinants of the binary variable WHM consumption. This de sign-based approach uses pseudo maximum likelihood estimation to calculate odds ratios (Archer & Lemeshow, 2006; Heerengia et al., 2010). Sample variance is computed using the Taylor series linearization (TSL) method (Heeringa et al., 2010). While data derived from complex survey designs can lead to inferential errors due to larger standard errors, the TSL method adjusts the st andard error to the complexities of the survey design ( Aneshensel, 2012). In nonsurvey data TSL is often referred to as a robust variance estimator (StataCorp, 2013b). Model fit was assessed using the Archer ŒLemeshow F-adjusted mean residual goodness-of-f it test, which is interpreted the same as a Hosmer-Lemeshow goodness-of-fit test, where a p- value >0.05 suggests the model is correctly specified (Archer & Lemeshow, 2006, Heerengia et al., 2010). A design-based linear regression was used to identify the dete rminants of the continuous variable frequency of venison consumption. (Note: A design-based ordinal logistic regression was also used for this model and reported identical results. The simpler linear regression model was used here for ease of reporting and interpretation.) This fiaggregatedfl design based approach uses weighted least squares estimation to calcu late regression coefficients (Heerengia et al., 2010). As in design-based logistic regression, sample variance is computed using TSL. Additionally, the R 2 value is weighted ( R2weighted) by applying the observations sample weights to the squared differences used to calculate the sum of squares (Aneshensel, 2012). Heeringa et al. (2010) suggested this R2weighted should be interpreted as fithe fraction of explained variance in y attributable to the regression on xfl (p. 194). Reporting. All summary statistics (except for the response rates and missing data section) are reported as weighted percentages. Total number of respondents per response and un- weighted percentages for all questions for all respondents and the subgroups non-hunters and frequent hunters can be found in Appendix F, Appendix G & Appendix H, respectively. For purposes of some analyses non-hunters and freque nt hunters were separated from the sample. Non-hunters were defined as individuals who had never gone hunting. Frequent hunters were defined as respondents who reported hunting near ly every year. Results are reported for all respondents, non-hunters and frequent hunters sepa rately, and each section is specifically identified. Additionally, to identify the determinants of WHM consumption and frequency of venison consumption for non-hunters an additiona l design-based logistic regression model and design-based linear regression were created for this subpopulation. Results Summary Statistics Response rates and missing data. A total of 997 telephone interviews were completed: 289 recontact interviews (53% landline, 47% cellphone) and 708 new interviews (48% landline, 52% cellphone). Fourteen observations were dropped from analys is because a response was not given to the initial question about ever consumi ng WHM. My resulting e ffective sample size was thus 983 respondents. For all analyses involving the dependent variable fifrequency of venison consumptionfl an additional five observati ons were dropped due to non-response and 28 observations were dropped because they repor ted consuming WHM but not venison. For all analyses involving the demographic variables, 22 observations were dropped due to non-response for race. Age (23 missing), education (s even missing) and income (96 missing) were imputed using regression with all demographic variables. The variable ficommunity typefl had 7 missing values, which were imputed using the respondent™s reported zip code compared to information on urban areas and clusters from the U.S. Census, satellite imagery, and road density. Average interview length was 20.4 minutes ( =5.0) and the mean number of calls required to complete an interview was 4.38. The overall margin of sampling error was ± 3.9%. The final disposition of cases and response, cooperation, refusal and contact rates were calculated using American Association for P ublic Opinion Research (AAPOR) standard definitions and formulas for complex sampli ng designs (AAPOR, 2011). The adjusted response rate 4 (RR4) was 22.3%. The adjusted cooperation rate 4 (COOP4) was 60.3%. The adjusted refusal rate 2 (REF2) was 14.7%. The adju sted contact rate 3 (CON3) was 76.5%. Respondent characteristics. All respondents. Respondents were 52% male, 74% white and the mean age was 55 years. Twenty percent of respondents had gradua ted high school or held a GED, an additional 22% graduated from a four-year college, and 15% acquired a graduate degree. Approximately 42% of respondents indicated their annual household income was > $50,000.00, and another 29% indicated their annual household income was $50,000- $99,999. Twenty-f ive percent of all respondents lived in a rural community 33% in a community between urban and rural and 42% in an urban community. Respondents had a variety of relationships with hunters: 77% knew a friend, neighbor, or coworker who hunted; 68% knew a hunter when they were growing up; 60% had a family member who didn™t live within their household who hunted, and 24% lived with a hunter. A majority of respondents had never gone hunting (57%). Fourteen percent of respondents went hunting nearly every year, 6% had gone hunting in the last five years, and 23% had gone hunting at least once but not within the last 5 years. Only 10% of all respondents did not know a hunter as a member of their household, relative, fr iend, neighbor, coworker or growing up. Non-hunters. Non-hunters, individuals who had never gone hunting, comprised 57% of the sample. Non-hunters were 68% female, 65% wh ite and the mean age was 48 years. Nineteen percent of non-hunters had graduated high school or held a GED, an additional 24% had graduated from a four year college, and 16 % had acquired a graduate degree. Approximately 44% of non-hunters indicated their annual household income was less than $50,000.00, and another 25% indicated their annual household income wa s $50,000- $99,999. Seventeen percent of non-hunters lived in a rural community 35% in a community betwee n urban and rural and 48% in an urban community. Non-hunters also had a variety of relationships with hunters: 67% knew a friend, neighbor, or coworker who hunted; 50% knew a hunter when they were growing up; 45% had a family member who didn™t live within their household who hunted, and 15% lived with a hunter. Approximately 18% of non-hunters did not know a hunter as a member of their household, relative, friend, neighbor, coworker or growing up. In comparison to all respondents, a greater proportion of non-hunters were female and nonwhite. Non-hunters were younger, slightly better educated and had slightly a lower annual household income compared to a ll respondents. Fewer non-hunters had identifiable relationships with hunters compared to all respondents. Frequent hunters. Frequent hunters, individuals who reported going hunting nearly every year, comprised 14% of the sample. Freq uent hunters were 79% male, 82% white and the mean age was 46 years. Twenty-seven percent of frequent hunters had graduated high school or held a GED, an additional 17% had graduated from a four year college, and 11% had acquired a graduate degree. Approximately 45% of fre quent hunters indicated their annual household income was less than $50,000.00, a nd another 35% indicated their annual household income was between $50,000.00 and $99,999.00. Forty-one percent of frequent hunters stated they lived in a rural community, 32% in a community between urban and rural, and 26% in an urban community. The social network of frequent hunters included many relationships with hunters: 98% knew a friend, neighbor, or coworker who hunted; 95% knew a hunter when they were growing up; 88% had a family member who didn™t live within their household who hunted, and 57% lived with another hunter. In comparison to all respondents and the non- hunter subgroup, a greater proportion of frequent hunters were male and white. Freque nt hunters were younger, slightly less educated and had a slightly lower annual household income compared to all respondents and the non- hunter subgroup. As anticipated, frequent hunters had more relations hips with other hunters than all respondents and the non-hunter subgroup. Wild harvest meat consumption. All respondents. A majority of respondents (75%) reported having consumed WHM derived from hunting in Michigan. When asked what types of WHM they had consumed, venison was the most common response: 96% of individuals who reported consuming WHM had consumed venison (Table 3.1). Fish (29%), rabb it/hare (28%), pheasant (20%), turkey (20%), squirrel (18%), duck (13%) and bear (12%) were also popular species to eat. In total all respondents identified 32 different wildlife species that had been used for consumption, 29 of which were species than can be hunted in Michigan. Only 3% of respondents reported consuming non-Michigan game species. Approximately 25% of respondents reporte d having never eaten WHM derived from hunting in Michigan (Table 3.2). The most comm on reason why an individual had not consumed WHM was finever having the opportunityfl (21%), fo llowed by fidiet/lifestylefl (16%), fitaste and smellfl (15%), fidon™t know any huntersfl (12 %), fidon™t knowfl (11%) and fidon™t huntfl (10%). Compared with all respondents who had consum ed WHM, those who reported having never eaten WHM indicated they had less hunting ex perience and knew fewer hunters (Table 3.3). Respondents who had never consumed WHM were more likely to be female, non-white, and live in an urban area. The number and strength of a respondent™s relationships with hunters was correlated with WHM consumption ( FS-R Pearson =34.41; p<0.001) (Table 3.4). Non-hunters. A majority of non-hunters (59%) repor ted having consumed WHM derived from hunting in Michigan. When asked what t ypes of WHM they had consumed, venison was the most common response: 96% of non-hunters who reported consuming WHM had consumed venison. Fish (21%), rabbit/hare (16%), turkey ( 13%), pheasant (12%) were also popular species to eat among non-hunters. In tota l, non-hunters identified 21 different wildlife species that had been consumed, 19 of which were species than can be hunted in Michigan. Only 1% of non-hunters reported consuming non-Michigan game species. Approximately 41% of non-hunters reported having never eaten WHM derived from hunting in Michigan. The most common reasons why a non-hunter had not consumed WHM was finever having the opportunityfl (22%), followed in frequency by fidiet/lifestylefl (16%), fitaste and smellfl (14%), fidon™t know any huntersfl (1 3%), fidon™t huntfl (11%), fidon™t knowfl (10%) (Table 3.1). The number and stre ngth of non-hunters relationships with hunters was correlated with WHM consumption ( FS-R Pearson =14.29; p<0.001). Frequent hunters. Ninety-nine percent of frequent hunters reported having consumed WHM derived from hunting in Michigan. When as ked what types of WHM they had consumed, venison was the most common response: 97% of frequent hunters who reported consuming WHM had consumed venison. Rabbit/hare (48%), fi sh and turkey (39%), squirrel (38%), bear (28%), pheasant (25%), duck (19%), goose and grouse (17%) and elk (16%) were also popular species to eat among frequent hunters. In total frequent hunters identified 31 different wildlife species that had been used for consumption, 29 of which were species than can be hunted in Michigan. Only 3% of non-hunters reported consuming non-Michigan game species. Venison consumption. All respondents. Seventy-two percent of all respondents (n=983) reported consuming venison. Of all respondents who reported consuming venison (n=735), 31% had not consumed venison in the past 12 months, 28% had consumed venison once or twice in the past 12 months, 21% had consumed venison between 3-10 times in the past 12 months, and 20% reported consuming venison more than 10 times in the pa st 12 months (Table 3.5). Of respondents who reported consuming venison in the past 12 months (48%), 56% reported receiving venison from family members who did not liv e within their household, followed in frequency by friends, neighbors or coworkers (54%), and members of their household (26%). Approximately 19% of respondents reported providing venison for themselves and only 7% received it from a community event or game dinner. Venison was pr ovided to an equal percentage of respondents in uncooked and cooked forms (approximately 65% each). The frequency of venison Table 3.1: Types of wild harvested meat consum ed by all respondents (n=983), all non-hunters (n=510), and all frequent hunters (148) reported in weighted percentages out of the total population and those who reported consuming wild harvested meat for each group from the 68th SOSS. Responses All Respondents Non-Hunters Frequent Hunters All (n=983) Reported consuming WHM (n=763) All (n=510) Reported consuming WHM (n=321) All (n=148) Reported consuming WHM (n=145) Venison/deer 72% 96% 57% 96% 94% 97% Rabbit/hare 21% 28% 9% 16% 47% 48% Fish 22% 29% 13% 21% 37% 39% Pheasant 15% 20% 7% 12% 24% 25% Squirrel 13% 18% 5% 8% 37% 38% Turkey 15% 20% 7% 13% 38% 39% Duck 9% 13% 5% 8% 19% 19% Bear 9% 12% 3% 5% 28% 28% Grouse 4% 6% 1% 1% 17% 17% Goose 5% 7% 2% 4% 17% 17% Elk 5% 6% 1% 2% 15% 16% Raccoon 2% 3% 1% 1% 9% 9% Turtle 3% 4% 1% 2% 7% 16% Quail 2% 2% 0% 1% 7% 7% Woodcock 1% 2% 0% 0% 8% 8% Beaver 1% 1% 0% 0% 4% 4% Feral Swine 2% 2% 2% 3% 4% 4% Muskrat 1% 2% 1% 0% 4% 4% Other- Species not specified 1% 1% 0% 0% 3% 3% Moose 1% 1% 0% 1% 2% 2% Bison 1% 1% 0% 0% 1% 1% Woodchuck 1% 1% 0% 0% 3% 3% Farmed Species 1% 1% 1% 2% 1% 1% Do not know 1% 0% 2% 0% 0% 0% Opossum 0% 1% 0% 0% 3% 3% Frog 0% 1% 0% 0% 3% 3% Porcupine 0% 0% 0% 0% 0% 0% Table 3.1 (cont™d): Dove 0% 0% 0% 0% 1% 2% Snake 0% 0% 0% 0% 1% 2% Alligator/ Crocodile 0% 0% 0% 0% 0% 0% Fox 0% 0% 0% 0% 2% 2% Pigeon 0% 0% 0% 0% 1% 1% Skunk 0% 0% 0% 0% 1% 1% Crawfish 0% 0% 0% 0% 0% 0% Sparrow 0% 0% 0% 0% 0% 0% Table 3.2: Reasons for not consuming wild harveste d meat for all respondents (n=220) and non- hunters (n=189) who reported never consuming wild harvested meat reported in weighted percentages from the 68th SOSS. Responses All Respondents (n=220) Non-Hunters (n=189) Weighted % Weighted % Never had opportunity 21% 22% Taste and smell 15% 14% Diet/lifestyle 16% 16% Don't know any hunters 12% 13% Don't hunt 10% 11% Don't like 8% 9% Do not know 11% 10% No reason 9% 8% Against hunting 5% 5% Moral or ethical concerns 2% 0% Don't know where to get 2% 3% Don't trust source 1% 1% Table 3.3: Comparison between wild harvested m eat consumers (n=763) and non-consumers (n=220) reported in weighted percentages from the 68th SOSS. Variables Consumers (n=763) Non consumers (n=220) Level of Hunting Experience Never Hunted 45% 91% Hunted at least once but not in the past 5 yrs28% 9% Hunted in the past five years 27% 1% Social Network Hunter in household 30% 7% Relative(s) hunt(s) 72% 26% Friend(s) hunt(s) 87% 50% Knew hunter growing up 80% 33% Knows zero hunters 2% 33% Community Type Rural 29% 12% Between Rural and Urban 32% 37% Urban 39% 51% Sex Male 52% 36% Female 48% 65% Age (mean) 50% 48% Race White 82% 53% Not White 16% 44% Income (mean) 50,000 - 59,999 50,000 - 59,999 Education (mean) Technical/Junior College Graduate Technical/Junior College Graduate Table 3.4: Social network by wild harvested meat consumption for a ll respondents, non-hunters and frequent hunters in weighted percentages from the 68th SOSS. Social Network (increasing in number and strength of relationships) WHM consumption All Respondents (n=983) Non-hunters (n=510) Frequent Hunters (n=147) Never consumed WHM Consumed WHM at least once Total Never consumed WHM Consumed WHM at least once Total Never consumed WHM Consumed WHM at least once Total None 8% 2% 10% 14% 3% 17% 0% 0% 0% Only knew a hunter growing up 2% 2% 5% 3% 3% 6% 0% 0% 0% Only has a friend that is a hunter 5% 6% 11% 8% 8% 16% 0% 0% 0% Knew a hunter growing up and has friends that are hunters 3% 8% 11% 4% 7% 11% 0% 6% 6% Has relatives that are hunters, or has relatives and friends that are hunters, or relatives that are hunters and knew a hunter growing up 4% 8% 11% 6% 7% 13% 0% 3% 3% Has relatives and friends that are hunters and knew a hunter growing up 2% 26% 28% 3% 18% 20% 0% 35% 35% Has a hunter in their household plus other relationships with hunters 2% 23% 24% 3% 13% 16% 0% 55% 56% Total 25% 75% 100% 41% 59% 100% 1% 99% 100% FS-R Pearson =34.4107 p<0.001 FS-R Pearson =14.2927 p<0.001 FS-R Pearson =0.7490 p=0.5480 consumption was correlated with the level of urbanization of all respondents community type (FS-R Pearson =7.51; p<0.001). About 67% of all respondents who lived in a rural community had consumed venison in the past 12 months co mpared to 37% living in an urban area. Non-hunters. Fifty-seven percent of all non-hunters (n=510) reported consuming venison. Of the non-hunters who reported consuming venison (n=307), 40% had not consumed venison in the past 12 months, 33% had consumed venison once or twice in the past 12 months, 19% had consumed venison between 3-10 times in the past 12 months, and 8% reported consuming venison more than 10 times in the pa st 12 months. Ninety-two percent of respondents who had never consumed venison were non-hunter s, whereas only 20% of respondents who had consumed venison >10 times in the past 12 mo nths were non-hunters (Table 3.6). Non-hunters who reported consuming venison in the past 12 m onths (34% of all non-hunters) received their venison most often from friends, neighbors or coworkers (61%), followed by family members who did not live within their household (59%), and members of their household (20%). Approximately 5% of non-hunters reported receivi ng venison from a community event or game dinner. Venison was more often provided to non- hunters in a cooked (71%) than uncooked form (54%). Frequency of venison consumption was weakly correlated with the level of urbanization in a non-hunters community type ( FS-R Pearson =3.64; p<0.001). Approximately 54% of non- hunters who lived in a rural community had consum ed venison in the past 12 months compared to 26% living in an urban area. Frequent hunters. Ninety-four percent of all frequent hunters (n=148) reported consuming venison. Of the fre quent hunters who reported consuming venison (n=141), 7% had not consumed venison in the past 12 months, 9% ha d consumed venison once or twice in the past 12 months, 27% had consumed venison between 3-10 times in the past 12 months, and 57% reported consuming venison > 10 times in the pa st 12 months. Frequent hunters who reported consuming venison in the past 12 months (93% of all frequent hunters) received their venison most often from themselves (71%), followed in frequency by friends, neighbors or coworkers (49%), family members who did not live within their household (43%), and members of their household (37%). Approximately 9% of freque nt hunters reported receiving venison from a community event or game dinner. This percentage is a greater percentage than that of all respondents (7%) and the subgroup non-hunters (5%). Venison was more often provided to frequent hunters in an uncooked form (70%) compared to a cooked form (66%). Modeling Wild Harvested Meat and Frequency of Venison Consumption The variables age, education, and income were not statistically associated with either dependent variable, WHM consumption or freq uency of venison consumption. Removing these demographic variables from the model did not a ffect overall model significance. However, it did influence coefficients for other variables, particularly race. Age, education and income were included in the final model as control variables. Determinants of wild harvest meat consumption. All respondents. Level of hunting experience, social network and race were the only significant predictors of WHM consumption (Table 3.7). Level of hunting experience and social network were both positive predictors of WHM consumption (p<0.001). Being of a race other than white was inversely related to WHM consumption (p<0.01). The odds of consuming WHM for someone who hunted at least once but not in the past five years is 3.57 times the odds of someone has never gone hunting consuming WHM, adjusting for the other covariates. This Table 3.5: Frequency of venison consumption by le vel of urbanization reported in weighted percentages for all respondents, non-hunters and frequent hunters from the 68th SOSS. Frequency of Venison Consumption Level of Urbanization All respondents (n=950) Non-hunters (n=510) Frequent hunters (n=143) Rural Between Rural and Urban Urban Total Rural Between Rural and Urban Urban Total Rural Between Rural and Urban UrbanTotal Never 3% 10% 14% 27% 4% 16% 21% 42% 0% 0% 0% 1% Consumed, but not within the past 12 months 5% 7% 11% 23% 4% 7% 12% 24% 2% 3% 2% 7% 1-2 Times in the past 12 months 6% 6% 8% 20% 4% 6% 9% 19% 7% 1% 2% 9% 3-10 times in the past 12 months 4% 6% 6% 16% 3% 5% 3% 11% 6% 10% 11% 27% 10+ times in the past 12 months 7% 5% 2% 14% 2% 1% 1% 5% 28% 20% 9% 56% Total 25% 34% 41% 100% 18% 35% 47% 100% 42% 34% 24% 100% FS-R Pearson = 7.51 p<0.001 FS-R Pearson =3.6365 p<0.001 FS-R Pearson =2.0198 p=0.0238 Table 3.6: Frequency of venison consumption by le vel of hunting experience: reported in weighted percentages out of total (n=950) from the 68t h SOSS (FS-R Pearson=35.39 p<0.001). Frequency of Venison Consumption Level of Hunting Experience Never Hunted Has hunted at least once but not within the past 5 years Hunted within last 5 years Total Never 24% 2% 0% 26% Consumed, but not within the past 12 months 13% 8% 2% 23% 1-2 Times in the past 12 months 11% 7% 3% 21% 3-10 times in the past 12 months 6% 4% 5% 15% 10+ times in the past 12 months 3% 3% 9% 15% Total 57% 23% 20% 100% effect is even greater for someone who has hunted in the past five years. The linearized standard error and confidence interval for hunted in the la st five years are high because in the weighted data set only 1.4 observations had hunted in the past five years but never consumed WHM. However, the confidence interval does not include zero, indicating that although there is high error in this prediction, hunting within the past five years is a significant predictor of WHM consumption. Nonetheless, the preci se size of this effect is unknown. For every one unit increase in the social network variable, the odds ratio of consuming WHM increases by 63%, adjusting for other covariates. As level of hunting experience and number a nd strength of relationships with hunters increase, the likelihood of consuming WHM also increa ses. The opposite is true for the race variable. Someone being of a race other th an white is 52% less likely to have consumed WHM than a white person, adjusting for other covariates. Non-hunters. A non-hunter™s social network was a positive predictor of frequency of venison consumption (p<0.001 level; Table 3.8). For every one-unit increase in a non-hunters social network the odds ratio of consumi ng WHM increases by 57%, adjusting for other covariates. A non-hunter of a race other than white was a negative predictor of WHM consumption (p<0.05). A non-hunter of a race othe r than white is 46% less likely to have consumed WHM than a white person, adjusting for other covariates. Determinants of frequency of venison consumption. All respondents. Level of hunting experience, social network, and living in an urban community were the only reliable predictors of frequency of venison consumption for this model (Table 3.9). Level of hunting experience and so cial network were both positive predictors (p<0.001). Living in an urban community was a negative predictor of frequency of venison consumption (p<0.01). The predicted frequency of venison consumption is 0.422 times greater for someone who hunted at least once but not in the past five years compared to someone who never hunted, holding all other predictors constant. The predicted frequency of venison consumption is 1.31 times greater for someone who has gone hunting in the past five years compared to someone who has never gone hun ting, holding all other predictors constant. Frequency of venison consumption increased by 0.268 for every one-unit increase in social network, holding all other predictors constant. There was no observed difference in frequency of venison consumption between respondents living in a community between rural and urban and living in a rural community. The predicted freq uency of venison consumption for someone from an urban community is -0.342 less than someone from a rural community, holding all other predictors constant. Non-hunters. A non-hunter™s social network was a positive predictor of frequency of venison consumption (p<0.001 level; Table 3.10). Living in an urban community and living in a community between rural and urban were negative predictors of a non-hunter™s frequency of venison consumption (p<0.01 and p<0.05, respectiv ely). Frequency of venison consumption increased by 0.252 times for every one-unit increase in a non-hunter™s social network, holding all other predictors constant. The predicted frequency of venison consumption for a non-hunter from community between rural and urban is -0.361 less than a non-hunter from a rural community, holding all other predictors constant. The predicted frequency of venison consumption for a non- hunter from an urban community is -0.490 less than a non-hunter from a rural community, holding all other predictors constant. Table 3.7: Design-based logistic regression of wild harvested meat consumption for al l respondents on level of hunting experience, social network, community type, sex, age, race, income and education level. Results reported in terms of odds ratios. Predictor Estimated odds ratio Linearized SE t-Statistic p-Value 95% CI DEFF Level of Hunting Experience Never Hunted* Hunted at least once but not in the past 5 years 3.570 0.978 4.64 0.000 2.085 6.111 1.126 Hunted in the past five years 24.151 19.062 4.03 0.000 5.132 113.666 0.811 Social Network 1.631 0.103 7.75 0.000 1.441 1.846 1.470 Community Type Rural* Between Rural and Urban 0.689 0.225 -1.14 0.254 0.363 1.307 1.410 Urban 0.728 0.241 -0.96 0.336 0.380 1.392 1.417 Sex 0.677 0.166 -1.59 0.113 0.418 1.097 1.361 Age 0.997 0.007 -0.38 0.705 0.985 1.011 1.470 Race (not white) 0.484 0.134 -2.63 0.009 0.282 0.833 1.596 Income 1.067 0.049 1.40 0.160 0.975 1.167 1.385 Education 0.950 0.040 -1.20 0.230 0.874 1.033 1.501 Intercept 0.411 0.332 -1.10 0.271 0.084 2.005 1.330 n=961 Fw (10 , 951) = 16.54, p< 0.0000 FA-L(9 , 952) = 0.598, p= 0.799 * Denotes reference category Table 3.8: Design-based logistic regression of wild harvested meat consumption fo r non-hunters on social network, community type, sex, age, race, income and education level. Results reported in terms of odds ratios. Predictor Estimated odds ratio Linearized SE t-Statistic p-Value 95% CI DEFF Social Network 1.566 0.102 6.91 0.000 1.379 1.779 1.370 Community Type Rural* Between Rural and Urban 0.606 0.227 -1.34 0.181 0.291 1.263 1.339 Urban 0.656 0.250 -1.11 0.269 0.310 1.387 1.353 Sex 0.624 0.171 -1.72 0.086 0.364 1.069 1.290 Age 1.003 0.007 0.44 0.657 0.989 1.017 1.363 Race (not white) 0.536 0.161 -2.08 0.038 0.298 0.966 1.499 Income 1.084 0.056 1.57 0.117 0.980 1.199 1.341 Education 0.945 0.045 -1.19 0.236 0.860 1.038 1.460 Intercept 0.320 0.283 -1.29 0.198 0.057 1.815 1.263 n=497 Fw(8 , 489) = 7.79 , p< 0.0000 FA-L(9 , 488) = 1.168, p= 0.313 * Denotes reference category Table 3.9: Design-based linear regression of frequency of venison consumption for all respondents on level of hunting experience, social network, community type, sex, age, race, income and education level. Predictor Parameter Estimate Linearized SE t-Statistic p-Value 95% CI DEFF Level of Hunting Experience Never Hunted* Hunted at least once but not in the past 5 years 0.422 0.114 3.71 0.000 0.199 0.645 1.363 Hunted in the past five years 1.308 0.136 9.60 0.000 1.041 1.576 1.390 Social Network 0.268 0.025 10.92 0.000 0.220 0.316 1.465 Community Type Rural* Between Rural and Urban -0.197 0.113 -1.74 0.082 -0.418 0.025 1.357 Urban -0.342 0.114 -3.00 0.003 -0.565 -0.119 1.394 Sex 0.036 0.087 0.42 0.678 -0.134 0.206 1.343 Age -0.003 0.003 -1.35 0.178 -0.008 0.002 1.487 Race (not white) -0.161 0.109 -1.48 0.140 -0.375 0.053 1.637 Income 0.006 0.016 0.40 0.690 -0.025 0.038 1.320 Education -0.004 0.015 -0.25 0.806 -0.032 0.025 1.369 Intercept 0.596 0.302 1.97 0.049 0.004 1.188 1.321 n=928 R2weighted = 0.4542 Fw(10 , 918) = 75.03 , p< 0.0000 * Denotes reference category Table 3.10: Design-based linear regression of frequency of venison consumption for non-hunters on social network, community type, sex, age, race, income and education level. Predictor Parameter Estimate Linearized SE t-Statistic p-Value 95% CI DEFF Social Network 0.252 0.027 9.33 0.000 0.199 0.306 1.306 Community Type Rural* Between Rural and Urban -0.361 0.183 -1.97 0.050 -0.721 0.000 1.336 Urban -0.490 0.175 -2.8 0.005 -0.834 -0.146 1.346 Sex -0.106 0.107 -0.99 0.324 -0.317 0.105 1.184 Age 0.002 0.003 0.53 0.596 -0.005 0.008 1.399 Race (not white) -0.171 0.130 -1.31 0.191 -0.426 0.085 1.476 Income 0.028 0.023 1.23 0.219 -0.017 0.073 1.267 Education 0.005 0.020 0.24 0.812 -0.034 0.043 1.290 Intercept 0.250 0.406 0.62 0.538 -0.548 1.048 1.155 n=482 R2weighted = 0.2714 Fw(8 , 474) = 17.52, p< 0.0000 * Denotes reference category Discussion Wild Harvested Meat Consumption A large majority of all respondents (three-f ourths) and nearly two-thirds of all non-hunters reported consuming WHM at least once in their lifetime. Alt hough there are no studies on which to compare results for all respondents, Stedman & Decker (1996) estimated that 61.6% of non-hunters in their New York sample had cons umed WHM. The term game meat was used in questions about consumption for their 1996 study, similar to the present study, however the term was not specifically defined in in the study™s questionnaire. It is thought provoking that these two studies conducted 18 years apart in different locations produced similar numbers. It seems that the number of non-hunters reporting consuming WHM at least once in their lifetime appears to converge around two thirds. Generalizing to the entire state of Michigan, th is means that a vast majority of the state™s residents, including non-hunters, have interacted with hunting/hunters through the consumption of WHM at some point in their life. The extent of WHM consumption derived from hunting in Michigan is vast, and this wide distribution of the state™s wildlife resources offers evidence that WHM provides provisional and cultural ecosystem services to society (Ljung et al. 2012). Although game species were the most popular, results suggest that there are other types of WHM that may be desired by individuals in the popul ation. Identifying populations interested in non- traditional game species and monitoring their consumption may be important for wildlife management; however, increasing access to thes e sources of WHM may also increase the number of people who perceive eco system services from WHM. The variety of wildlife species named by res pondents in this study has implications for the definition of WHM or figame meatfl and future studies on the topic. First, many non-game species were identified in this study. Using the term figamefl may underreport what wildlife species are being consumed. The term fiwild-har vestedfl in lieu of fig amefl may be a simple solution to this variability in definition. Most formal definitions of the word meat define it as coming from a mammal eliminating fish, birds, re ptiles, amphibians, crustaceans etc. as meat. Many respondents in this study did not use such a strict definition, alt hough it is impossible to know how many did. It was particularly unexpected that fish were often identified as a WHM, even though the term hunting was used in the defi nition. To ensure continuity in the definition of WHM and accuracy in reporting, my results indicate that not only is it important to define the source of the meat (e.g. wildlife from hunting), but also to establish wither or not non-mammalian species are included in this definition (e.g. wild harvested meat, fowl or fish; wild harvested meat and fowl, not including fish). However, in this particular study, every individual who identified fish as a WHM also reported consuming a traditional game species: either fowl, meat or both. Non-hunters comprised a majority of peopl e who reported they had never consumed WHM. Increasing opportunities for non-hunters to consume WHM may be a simple way to engage, or perhaps socialize, non-hunters to hunting. Furthermore, the taste and smell or a general dislike of WHM were also cited as reasons for not consuming WHM. Considering that these respondents reported not having ever tried WHM, another mechanism to involve non- hunters with hunting may be to dispel myths a bout WHM tasting gamey or unpleasant. Programs such as Michigan™s Gourmet Gone Wild ® take this approach by providing participants with WHM dishes prepared by a professional chef. Cookbooks, clinics and other easily accessible media that describe proper handling of WHM as well as creative recipes may be helpful in lessening perceived barriers to consumption. Venison Consumption Venison was unanimously the most popular form of WHM consumed in this study. Nearly all individuals who reported consuming WHM reporte d consuming venison. This identifies venison as an ideal proxy for studyi ng WHM consumption in Michigan, and perhaps other areas where deer are prevalent and deer hunting a popular form of recreation. Being able to focus on one type of WHM encourages more deta iled questioning, reduces concerns about varied definitions of ‚game meat™ and more broadly meat, and improves respondent recall. However, although using the frequency of venison consumption as a proxy for WHM likely decreases measurement error, this method may under esti mate overall frequency of WHM consumption. Forty-eight percent of all respondents and 34% of non-hunters reported consuming venison in the past 12 months. A national survey of the United States repo rted that 42% of the population had consumed WHM in the past 12 m onths (RM & NSSF, 2011). In a study of Swedish residents, Ljung et al. (2012) found that 65% of non-hunters reported consuming WHM at least once per year. In a follow up study of Swedish WHM consumption, it was revealed that 62% of non-hunters from urban Stockholm consumed WHM at least once per year, whereas 81% of non-hunters in rural Northern Sweden reported consuming WHM at least once per year (Ljung et al. 2014). Again, the Swedish equivalent for th e term game meat was used in questions about consumption for these studies, but the term was not specifically defined in in the study™s questionnaire. The differences in terminology and language may be partially responsible for differences in reported consumption rates. In Sweden, WHM may be more readably available to non-hunters because meat can be sold directly by hunters and in stores and restaurants, likely increasing the overall WHM consumption rate in Sweden compared to the US. Results indicate that in the United States, the total number of pe ople who consume WHM is much higher than the percent of the population that actually hunts, which is about six percent (USFWS, 2011). This supplies direct evidence th at sharing WHM greatly increases the number of beneficiaries of provisional and cultural ecosystem services WHM provides to society. These estimates are much greater than reported in Chapter 2. Hunters reported sharing venison with approximately 19% of the population. For receiv ers of venison the event may be unique, and distinctive events are easier to recall than repeated ones (Tourangeau et al., 2000). To estimate the extent of venison sharing, responses from r eceivers are likely more accurate than those of hunters, because hunters are honest but forgetful when it comes to sharing their harvest (Nolin, 2010). Frequent hunters were by far the most freque nt consumers of venison. A large majority of frequent hunters reported consuming venison, many of whom re ported consuming venison more than 10 times in the past 12 months. Hunters not only provided themselves venison, but also received it from many other sources. This hi gher rate of WHM consumption by frequent hunters identifies the provisional ecosystem services WHM may provide to hunters and their families, but also raises concerns about frequent hunters level of exposure to contaminants in WHM. When questioning hunters about their consumption pa tterns it is important to keep in mind that they are both providers and receivers of WHM and a different scale with higher frequency of consumption options is likely needed to assess just how often hunters are consuming WHM. Determinants of Wild Harvested Meat a nd Frequency of Venison Consumption A non- hunter™s social relationships with hunters increasing in strength and frequency was a positive predictor of WHM consumption, wh ereas living in an urban community and race (being not white) were negative predictors of WHM consumption. Research from Sweden also reported living in a rural residence and knowi ng hunters were positive predictors of non-hunter WHM consumption (Ljung et al., 2012 & Ljung et al., 2014). The role of knowing hunters for WHM consumption in the US emphasizes the importa nce of social networks in the extent of the distribution of WHM, especially to non-hunters, and underscores the potential cultural ecosystem services sharing WHM may provide. Furtherm ore, hunter densities are lower in urban environments, thus someone living in an urban community is less likely to know a hunter as a function of their community type. Limited consumption of WHM by races other th an white is likely a result of multiple factors. A majority of hunters in Michigan (85%) and the United States (94%) are white (USFWS, 2011), and any racial division proba bly extends to hunters™ social networks. Additionally, the black population of Michigan ma inly lives in urban communities, and results indicate that living in an urban community re duces access to WHM (Rastogi, Johnson, Hoeffel, & Drewery, 2011). Furthermore, Burger (2000) reported significant differences in WHM (including fish) consumption patterns for different races. Blacks reported eating more WHM, but very little venison (Burger, 2000). In this study there was no statistically significance difference in consumption patterns for veni son based on race. However, cultural variations in consumption patterns should still be considered when ma king estimates of WHM consumption, even when using venison as a proxy. My small sample size of respondents from a race other than white made comparisons of race acro ss different types of WHM statis tically invalid. Additionally, grouping all races other than white into one cate gory likely eliminates any effect of cultural differences on WHM consumption. Contrary to Burger™s (2002) findings, females were just as likely as males to have consumed WHM when controlling for level of hunting experience. Results from Sweden support this finding. Ljung et al. (2014) found that sex did not predict non-hunter WHM consumption. Thus, although females may not be active hunters, they are equally engaged in hunting when it comes to WHM consumption. Hunters who share WHM beyond their normal so cial networks, particularly to groups who are less associated with hunting, can increase the extent of WHM consumption and potentially the number of people connected to hu nting. Sharing WHM may be a relatively easy way to introduce and include underrepresented groups in the number and type of ecosystem services produced by hunting. CHAPTER 4 Management Implications and Future Directions Management Implications In the previous chapters, I established that wild harvested meat (WHM) provides provisional and cultural ecosystem services to a considerable proportion of Michigan society. Recognition of these services and their amplif ication beyond hunters increases the number of people benefiting from and connected to the hunti ng wildlife management system. Consideration of these services and their beneficiaries coul d be an important element for making informed decisions in conservation policy and wildlife mana gement in Michigan. The social relevance of hunting will likely only become more important if current declines in hunter numbers continue. The provisional and cultural ecosystem services provided by hunters may be a key component of maintaining the relevancy and impor tance of these traditional natu ral resource uses to Michigan society. I identified access to WHM as the primary factor limiting the extent of WHM consumption into society. Thus, fostering oppor tunities for sharing and consuming WHM may be a practical and effective strategy to increase participation in hunting and garner acceptance and support for hunters and hunting among Michigan residents, particularly with groups underrepresented in hunting, such as urbanites and racial minoritie s. Sharing opportunities could be increased through formalized programs like Windsor Dinners, Gourmet Gone Wild ®, or the Nebraska Deer Exchange. Less structured approa ches that encourage hunters to expand their WHM sharing network also may be an effective a nd a low cost way of increasing benefits from hunting. Encouraging hunters to share their m eat in social settings where non-hunters are present may be the most readily implemented method to maintain the social relevancy of hunting, encourage positive attitudes toward hunting, and potentially recruit new hunters. Additionally, dispelling myths regarding taste of WHM may incr ease the inclination of non-hunters to try WHM. Additionally, public support for hunting is strong when hunting is characterized as a method of obtaining food. Identifying how hunters use their WHM, regardless of motivation, and disseminating this informati on, may be another simple way to positively change attitudes about hunting. Commercial harvest and sale of WHM are currently under consideration in US wildlife management as a mechanism to control abundant populations of white-tailed deer ( Odocoileus virginanus). A structured inquiry into the extent of sharing and consumption of WHM under current practices would help inform the developmen t of such policies. I ha ve found that the lack of a legal market in WHM does not impede the sharing of WHM. A system of sharing and consumption governed by informal in stitutions appears to have evolved, or perhaps, remained. It is not clear that a regulated market in WHM w ould increase the number of beneficiaries of the current wildlife management system, and, in f act, could have the opposite effect. Imposing an economic value on WHM in this system could cha nge who benefits and how, and the number of beneficiaries of this system, for better or worse. I have also identified a considerable so cial network in which WHM is shared and consumed and my results provide an initial estima te of the extent of this network. This network of sharing and consumption also identifies numer ous pathways for exposure to zoonotic disease and chemical contaminants from WHM. Shoul d the need arise to provide public health information to WHM consumers, it is important to recognize that WHM is consumed by many more people than just hunters and their household members. Educational campaigns geared towards hunters and their families may not reach all consumers. Future Directions This thesis has provided basic knowledge on a relatively unstudied system Œ the sharing and consumption of WHM Œ but it has also generated more questions about this same system. The extent of WHM sharing and consumption was measured, but little is known about how much WHM is transferred through sharing networks and how it is used as a provisional ecosystem service. Understanding the sociocultural value of this system and the importance of the act of sharing WHM to providers and receivers would fu rther identify the cultural ecosystem services WHM provides. The CHANS model identifies co nnections between human and natural systems and the feedback loops and reciprocal interactions between the two. My study only looked at one relationship in this system, the ecosystem services WHM (the natural system) provide to humans. More information and analysis of the othe r interactions that complete this system, such as the effect of WHM sharing and consumption has on attitudes towards and relevancy of hunting, would further our knowledge of WHM as a coupler of human and natural systems. The next step in this inquiry is to further specify the provisional and cultural ecosystem services that WHM sharing and consumption provide through an in-depth inquiry, and to quantify the influence of these services on human well-be ing, attitudes toward hunting and nature, and conservation policy. APPENDICES APPENDIX A 2013 Michigan Deer Harvest Study Questionnaire APPENDIX B 2013 Michigan Deer Harvest Survey Questionnaire Cover Letters APPENDIX C 2013 Michigan Deer Harvest Study Questionnaire Incentive APPENDIX D Additional 2013 Michigan Deer Harvest Study Data TablesTable D.1: To whom Michigan deer hunters provided venison during the past 12 months from the 2013 Michigan Deer Harvest Study. (4,758 hunters did not respond to this question). Receivers n Out of those who shared (n= 9,063) Out of all respondents to the question (n= 15,223) % Weighted % % Weighted % I did not share any of my venison 6,160 40% 40% Members of my household 6,243 69% 69% 41% 41% Relatives not in my household 4,713 52% 52% 31% 31% Friends, neighbors or coworkers 4,568 50% 51% 30% 30% Landowner whose property I hunted 1,165 13% 13% 8% 8% Community Group game dinner 243 3% 3% 2% 2% Food bank or other donation program 219 2% 2% 1% 1% Other Not Specified 75 1% 1% 0% 0% Table D.2: The number of people Michigan deer hunters shared their venison with over the past 12 months from the 2013 Michigan Deer Harvest Study. Mean: 5.6 SEM: 0.047 Number of people shared with n Out of those who shared (n= 9,051) Out of all respondents to the question (n= 15,952) % Weighted % % Weighted % 0 6,901 43%43% 1 594 7% 7% 4% 4% 2 1,380 15%15% 9% 9% 3 1,258 14%14% 8% 8% 4 1,502 17%17% 9% 9% 5 954 11%11% 6% 6% 6 990 11%11% 6% 6% 7 354 4% 4% 2% 2% 8 531 6% 6% 3% 3% 9 120 1% 1% 1% 1% 10 596 7% 7% 4% 4% 11 47 1% 0% 0% 0% 12 241 3% 3% 2% 2% 13 25 0% 0% 0% 0% 14 46 1% 1% 0% 0% 15 156 2% 2% 1% 1% 16 23 0% 0% 0% 0% 17 12 0% 0% 0% 0% 18 16 0% 0% 0% 0% 19 3 0% 0% 0% 0% 20 106 1% 1% 1% 1% 21 5 0% 0% 0% 0% 22 7 0% 0% 0% 0% 23 2 0% 0% 0% 0% 24 4 0% 0% 0% 0% 25 19 0% 0% 0% 0% 26 4 0% 0% 0% 0% 28 1 0% 0% 0% 0% 29 1 0% 0% 0% 0% 30 33 0% 0% 0% 0% 31 1 0% 0% 0% 0% 32 1 0% 0% 0% 0% Table D2 (cont™d): 35 3 0% 0% 0% 0% 37 2 0% 0% 0% 0% 40 5 0% 0% 0% 0% 41 1 0% 0% 0% 0% 42 1 0% 0% 0% 0% 45 2 0% 0% 0% 0% 50 3 0% 0% 0% 0% 55 1 0% 0% 0% 0% 80 1 0% 0% 0% 0% Missing 4,029 Total 19,981 Table D.3: Hunting related characteristics of all respondents (n=19,981) and hunters who did and did not share their venison in the past 12 months (variable venison providers n=17, 262) from the 2013 Michigan Deer Harvest Study. Variable All respondents (n=19,981) Venison Providers (n=17,262) Shared venison in past 12 months Did not share venison in past 12 months n % Weighted % n % Weighted % n % Weighted % Venison Providers 9,47555% 55% 7,78745% 45% Harvested in 2013 Yes 8,782 44% 44% 7,26342% 42% 1,2747% 7% No 11,199 56% 56% 2,21213% 13% 6,51338% 38% Harvested Antlerless Deer in 2013 Yes 4,611 23% 23% 3,89823% 22% 609 4% 3% No 15,370 77% 77% 5,57732% 33% 7,17842% 41% Harvested Antlered Deer in 2013 Yes 5,854 29% 29% 4,86128% 28% 814 5% 5% No 14,127 71% 71% 4,61427% 27% 6,97340% 40% Total number of Deer Harvested 0 11,199 56% 56% 2,21213% 13% 6,51338% 38% 1 5,997 30% 30% 4,83428% 28% 983 6% 6% 2 2,044 10% 10% 1,74710% 10% 247 1% 1% 3 545 3% 3% 507 3% 3% 28 0% 0% 4 136 1% 1% 119 1% 1% 14 0% 0% 5 37 0% 0% 34 0% 0% 2 0% 0% 6 19 0% 0% 18 0% 0% 0 0% 0% 7 4 0% 0% 4 0% 0% 0 0% 0% Table D3 (cont™d): Participated in Early and/or Late Antlerless Firearm Season Yes 2,258 11% 11% 1,3858% 8% 681 4% 4% No 17,705 89% 89% 8,08047% 47% 7,10141% 41% Participated in Archery Season Yes 10,195 51% 51% 5,66433% 33% 3,47320% 20% No 9,786 49% 49% 3,81122% 22% 4,31425% 25% Participated in Muzzleloader Season Yes 5,451 27% 27% 3,08718% 18% 1,82111% 11% No 14,530 73% 73% 6,38837% 37% 5,96635% 37% Participated in Regular Firearm Season Yes 17,771 89% 89% 8,45149% 49% 6,93940% 40% No 2,210 11% 11% 1,0246% 6% 848 5% 5% Type of Equipment Used Just Bow 1,418 7% 7% 673 4% 4% 559 3% 3% Just Gun 9,332 48% 48% 3,64121% 22% 4,14124% 24% Bow and Gun 8,772 45% 45% 4,98829% 30% 2,91217% 17% Table D.4: Demographic profiles of all respondents (n=19,981) and hunters who did and did not share their venison in the past 12 months (variable venison providers n=17,262) from the 2013 Michigan Deer Harvest Study. Variable All respondents (n = 19,981)* Venison Providers (n=17,262)** Shared venison in past 12 months Did not share venison in past 12 months n % Weighted % n % Weighted % n % Weighted % Venison Providers 9,475 55% 55% 7,78745% 45% Age 18-29 2,202 11% 12% 1,120 6% 7% 868 5% 5% 30-39 2,433 12% 13% 1,273 7% 8% 900 5% 6% 40-49 3,806 19% 20% 1,965 11% 12% 1,3878% 8% 50-59 5,109 26% 27% 2,537 15% 15% 1,86811% 11% 60-69 4,538 23% 19% 1,902 11% 9% 1,94911% 10% 70-79 1,583 8% 8% 576 3% 3% 679 4% 4% 80-89 298 1% 1% 97 1% 1% 133 1% 1% 90+ 12 0% 0% 5 0% 0% 3 0% 0% Sex Male 18,47692% 92% 8,754 51% 51% 7,18642% 41% Female 1,505 8% 8% 721 4% 4% 601 3% 4% Ecoregion Upper Peninsula 1,753 9% 8% 752 4% 4% 716 4% 4% Northern Lower Peninsula 4,045 20% 20% 1,931 11% 11% 1,5929% 9% Southern Lower Peninsula 14,18371% 72% 6,792 39% 40% 5,47932% 32% Level of Urbanization Not Urban 11,27757% 56% 5,443 32% 31% 4,39526% 25% Urban Buffer 6,960 35% 36% 3,224 19% 19% 2,72016% 16% Urban 1,692 8% 9% 782 5% 5% 651 4% 4% * n= 19,929 for variable level of urbanization ** n= 17,215 for variable level of urbanization APPENDIX E Study Specific Sections from the 68 th SOSS Telephone Interview Transcript Study Specific Sections from the 68 th SOSS Telephone Interview Transcript This modified version of the interview transcri pt shows only questions created specifically for this study and demographic questions. A full set of all survey questions and question order is available at http://ippsr.msu.edu/soss/ . In the actual interview dem ographic questions were asked prior to the study specific questions. For the purposes of this thesis I have provided study specific questions first. Notes for reading the interview transcript: R refers to respondent Interview questions are in bold. Other interview text that was read to the respondent is in quotation marks. Notes to the interviewer about specific questions are provided below the question in italics. Question response options were not provided to the respondent unless read as part of the question. The response options were provided to the interviewer to field code responses during the interview. Beginning of Interview Transcript CONCENT fiBefore we begin, let me tell you that this interview is completely voluntary. You may choose not to participate and you may end your participation at any time without penalty. Should we come to any question that makes you feel too uncomfortable or you do not want to answer, just let me know and we can go on to the next question. Information collected for this study will be kept confidential to the extent allowed by local, state and federal law, and no reference will be made in any oral or written report that would link you individually to this study. This call may be recorded for quality assurance.fl If respondent wanted contact information for the project manager, the principal investigator, or the IRB that information was provided upon request. STUDY SPECIFC QUESTIONS AB OUT WILD HARVESTED MEAT fiTo better inform conservation po licy, we are interested in how people use and value natural resources in Michigan. One of those resources is the meat obtai ned through hunting, also called game meat. The following questions are about the eating and sharing of game meat from Michigan.fl Meat1: Have you ever eaten game meat that came from hunting in Michigan, whether you were the hunter or were given the meat by a hunter? Do NOT include meat that was bought at a store or farm, or was eaten at a restaurant . 1. YES [go to meat2a ] 2. NO [go to meat1a] 8. DO NOT KNOW [go to meat13] 9. REFUSED THIS QUESTION [ go to meat13] Meat1a: Is there any particular reason why you have not eaten game meat? Field code response. This means do not read the responses but choose the response that best fits the respondents answer. If a response does not fit, use the other specify to enter the text. Check all that apply. A. DIET (DON'T EAT MEAT/RED MEAT) B. TASTE C. DON'T HUNT D. NEVER HAD OPPORTUNITY E. DON'T KNOW ANY HUNTERS F. DON'T KNOW WHER E TO GET GAME MEAT G. AGAINST HUNTING/UNCOM FORTABLE WITH HUNTING X. OTHER Y. DO NOT KNOW Once meat 1a is answered go to meat 13. Meat2a: What types of game meat that came from hunting in Michigan have you had? Field code responses (do not read choices to R). Only select an option if R uses the exact term, otherwise use specify. Check all that apply. A. VENISON/DEER B. TURKEY C. ELK D. RABBIT OR HARE E. PHEASANT F. GOOSE G. GROUSE H. SQUIRREL I. DUCK J. FISH (ANY/ALL TYPES) X. OTHER Y. DO NOT KNOW Meat2b: What other types of game meat from hunting in Michigan have you had? Field code responses (do not read choices to R). Only select an option if R uses the exact term, otherwise use other specify. Check all that apply. W. NOTHING ADDITIONAL A. VENISON/DEER B. TURKEY C. ELK D. RABBIT OR HARE E. PHEASANT F. GOOSE G. GROUSE H. SQUIRREL I. DUCK J. FISH (ANY/ALL TYPES) X. OTHER Y. DO NOT KNOW If respondent answered as having eaten venison (deer meat) they were asked the following question (Meat3). If they had not ea ten venison they were asked question Meat 13. Meat3: In the past 12 months, approximately how many times have you eaten deer meat (also called venison) that came from huntin g in Michigan, whether you were the hunter or were given the meat by a hunter? Not at all, on ce or twice, three to ten times, or more than ten times. 1. NOT AT ALL [go to meat13] 2. ONCE OR TWICE 3. 3 TO 10 TIMES 4. MORE THAN 10 TIMES 7. ATE IN LAST 12 MONTHS, BUT UNSURE HOW MANY TIMES 8. DO NOT KNOW WHETHER ATE ANY IN LAST 12 MONTHS [ go to meat13] 9. REFUSED THIS QUESTION [ go to meat13] If the respondent identified that they had eaten venison in the last 12 months they were asked the following series of questions (Meat4-12). If they had not eaten venison in the last 12 months they were asked question Meat13. fiThe following questions are about where the venison came from that you ate over the past 12 months.fl Meat4: Did you hunt any of the venison yourself? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat5: Did you get any from members of your household? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat6: Did you get any from family that doesn't live with you? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat7: Did you get any from friends, neighbors, or coworkers? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat8: Did you get any from a community game dinner or event? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat9: Did you get any venison from another source? 1. YES[specify] 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat10: Thinking about the venison you got from those sources over the past 12 months, was any of it provided to you in an uncooked or raw form? Include frozen meat only if it was uncooked or raw 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat11: Was any of it provided in a cooked or prepared form? Include frozen meat only if it was already cooked or prepared. 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat12: Was any of it provided in another form? 1. YES[specify] 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION fiThe following questions are about hunting in general, not just deer hunting, and are not restricted to hunting in Michiganfl Meat13: Not including you, do any of the members of your household hunt? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat14: Do any other family members that don't live with you hunt? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat15: Do any of your friends, coworkers, or neighbors hunt? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat16: When you were growing up, did an yone you were close to hunt? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat17: Have you ever gone hunting? 1. YES 2. NO [go to next section] 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat18: Do you go hunting nearly every year? 1. YES 2. NO [go to next section] 8. DO NOT KNOW 9. REFUSED THIS QUESTION Meat19: Have you gone hunting in the last 5 years? 1. YES 2. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION DEMOGRAPHIC QUESTIONS fiNow, I have some background questions for you.fl Sex: I need to verify that I am spea king with a (male/female) adult? 1. MALE 2. FEMALE Age: In what year were you born? 19 __ __ Education: What is the highest level of education you have completed? 0. DID NOT GO TO SCHOOL 1. 1st GRADE 2. 2nd GRADE 3. 3rd GRADE 4. 4th GRADE 5. 5th GRADE 6. 6th GRADE 7. 7th GRADE 8. 8th GRADE 9. 9th GRADE 10. 10th GRADE 11. 11th GRADE 12. HIGH SCHOOL GRADUATE OR GED HOLDER 13. 1st YEAR COLLEGE 14. 2nd YEAR COLLEGE 20. TECHNICAL/JUNIOR COLLEGE GRADUATE 15. 3rd YEAR COLLEGE 16. COLLEGE GRADUATE (FOUR YEARS) 17. SOME POST GRADUATE 18. GRADUATE DEGREE 98. DO NOT KNOW 99. REFUSED THIS QUESTION Ethnicity: Are you of Hispanic, Latino, or Spanish origin? 1. YES-HISPANIC/LATI NO/SPANISH ORIGIN 5. NO-NOT HISPANIC/LATI NO/SPANISH ORIGIN 8. DO NOT KNOW 9. REFUSED THIS QUESTION Race: What is your race? Would you say white or Caucasian, African American or black, Hawaiian or other Pacific Islander, Asian, or American Indian or Alaska Native? Check all that apply. A. WHITE OR CAUCASIAN B. AFRICAN AMERICAN OR BLACK C. HAWAIIAN OR OTHER PACIFIC ISLANDER D. ASIAN E. AMERICAN INDIAN OR ALASKA NATIVE F. OTHER G. REFUSED Income: fiTo get a picture of people's financial si tuations, we'd like to know the general range of incomes of all households we interview. This is for statistical analysis purposes and your answers will be kept strictly confidential.fl Inca: Now, thinking about your household's total annual income from all sources (including your job), did your household receive $40,000 or more in 2013? 1. YES [go to incd ] 5. NO [go o incb] 8. DO NOT KNOW 9. REFUSED THIS QUESTION incb: Was it less than $20,000? 1. YES [go to incc] 5. NO [go to incca] 8. DO NOT KNOW 9. REFUSED THIS QUESTION incca: What is less than $30,000? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION incc: Was it less than $10,000? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION incd: Was it $60,000 or more? 1. YES [go to incg] 5. NO [go to incf] 8. DO NOT KNOW 9. REFUSED THIS QUESTION incf: Was it $50,000 or more? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION incg: Was it more than $100,000? 1. YES [go to inci] 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION inch: Was it more than $70,000? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION incha: Was it more than $90,000? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION inci: Was it more than $150,000? 1. YES 5. NO 8. DO NOT KNOW 9. REFUSED THIS QUESTION Community Type: Would you say you live in a rural community, a small city or town, a suburb, or an urban community? 1. RURAL COMMUNITY 2. SMALL CITY OR TOWN, VILLAGE 3. A SUBURB 4. URBAN COMMUNITY 0. SPECIFY:OTHER 8. DO NOT KNOW 9. REFUSED THIS QUESTION County: What county do you live in? 1. Alcona 2. Alger 3. Allegan 4. Alpena 5. Antrim 6. Arenac 7. Baraga 8. Barry 9. Bay 10. Benzie 11. Berrien 12. Branch 13. Calhoun 14. Cass 15. Charlevoix 16. Cheboygan 17. Chippewa 18. Clare 19. Clinton 20. Crawford 21. Delta 22. Dickinson 23. Eaton 24. Emmet 25. Genesee 26. Gladwin 27. Gogebic 28. Grand Traverse 29. Gratiot 30. Hillsdale 31. Houghton 32. Huron 33. Ingham 34. Ionia 35. Iosco 36. Iron 37. Isabella 38. Jackson 39. Kalamazoo 40. Kalkaska 41. Kent 42. Keweenaw 43. Lake 44. Lapeer 45. Leelanau 46. Lenawee 47. Livingston 48. Luce 49. Mackinac 50. Macomb 51. Manistee 52. Marquette 53. Mason 54. Mecosta 55. Menominee 56. Midland 57. Missaukee 58. Monroe 59. Montcalm 60. Montmorency 61. Muskegon 62. Newaygo 63. Oakland 64. Oceana 65. Ogemaw 66. Ontonagon 67. Osceola 68. Oscoda 69. Otsego 70. Ottawa 71. Presque Isle 72. Roscommon 73. Saginaw 74. St. Clair 75. St. Joseph 76. Sanilac 77. Schoolcraft 78. Shiawassee 79. Tuscola 80. Van Buren 81. Washtenaw 82. Wayne 83. Wexford At the end of the interview respondents were thanked for their participation and asked if they could be recontacted in a couple of moths for another interview. APPENDIX F Additional Tables from the 68 th SOSS for All RespondentsTable F.1: Wild harvested meat consumption for all respondents (n=997). Responses n % Weighted % Yes 763 77% 73% No 220 22% 25% Do not know 11 1% 1% Refused this question 3 0% 0% Total 997 100% 100% Table F.2: Reasons for not consuming wild harveste d meat for all respondents who reported never consuming wild harvested meat (n=220). Open ended responses coded. Responses n Out of total sample (n=983) Out of those asked (n=220) % Weighted % % Weighted % Never had opportunity 42 4% 5% 19% 21% Taste and smell 34 3% 4% 15% 15% Diet/lifestyle 33 3% 4% 15% 16% Don't know any hunters 25 3% 3% 11% 12% Don't hunt 24 2% 3% 11% 10% Don't like 21 2% 2% 10% 8% Do not know 20 2% 3% 9% 11% No Reason 17 2% 2% 8% 9% Against hunting 14 1% 1% 6% 5% Moral or ethical concerns 6 1% 1% 3% 2% Don't know where to get 4 0% 1% 2% 2% Don't trust source 4 0% 0% 2% 1% Table F.3: Types of wild harvested meat consumed by all respondents who reported consuming wild harvested meat (n=763). Open ended responses coded. Responses n Out of total sample (n=983) Out of those asked (n=763) % Weighted % % Weighted % Venison/deer 735 74% 71% 96% 96% Rabbit/hare 239 24% 21% 31% 28% Fish 227 23% 22% 30% 29% Pheasant 169 17% 14% 22% 20% Squirrel 147 15% 13% 19% 18% Turkey 143 14% 14% 19% 20% Table F.3 (cont™d): Duck 102 10% 9% 13% 13% Bear 93 9% 8% 13% 12% Grouse 68 7% 4% 9% 6% Goose 57 6% 5% 7% 7% Elk 44 4% 4% 6% 6% Raccoon 27 3% 2% 4% 3% Turtle 25 3% 3% 3% 4% Quail 18 2% 2% 2% 2% Woodcock 16 2% 0% 2% 2% Beaver 15 2% 1% 2% 1% Feral Swine 14 1% 2% 2% 2% Muskrat 13 1% 1% 2% 2% Other- Species not specified 13 1% 1% 2% 1% Moose 11 1% 1% 1% 1% Do not know 8 1% 1% 1% 2% Bison 7 1% 1% 1% 1% Woodchuck 7 1% 1% 1% 1% Farmed Species 6 1% 1% 1% 1% Opossum 5 1% 0% 1% 1% Frog 5 1% 0% 1% 1% Porcupine 4 0% 0% 1% 0% Dove 2 0% 0% 0% 0% Snake 2 0% 0% 0% 0% Alligator/ Crocodile 2 0% 0% 0% 0% Fox 2 0% 0% 0% 0% Don™t Know 2 0% 0% 0% 0% Pigeon 1 0% 0% 0% 0% Skunk 1 0% 0% 0% 0% Crawfish 1 0% 0% 0% 0% Sparrow 1 0% 0% 0% 0% Table F.4: Types of wild harvested meat consumed by all respondents who reported consuming wild harvested meat (n=763). Open ended responses coded and combined into categories of similar species . Response Categories n Out of total sample (n=983) Out of those asked (n=763) % Weighted % % Weighted % Big game 739 74% 71% 97% 97% Upland game birds 306 31% 27% 40% 36% Small game with season 271 27% 24% 36% 33% Fish 227 23% 22% 30% 29% Waterfowl 124 12% 11% 16% 16% Furbearers 46 5% 4% 6% 6% No limit small game 36 4% 4% 5% 5% Reptiles and amphibians 30 3% 3% 4% 3% Non-Michigan game 19 2% 2% 2% 3% Don™t Know 2 0% 0% 0% 0% Table F.5: Frequency of venison consumption in th e past 12 months for all respondents who reported consuming venison (n=735). Mean =2.26 SD=1.11 Min= 1 Max= 4 Response Options n Out of total sample (n=983) Out of those asked (n=735) % Weighted % % Weighted % 1. Not at all 239 24% 22% 33% 31% 2. Once or twice 203 20% 20% 28% 28% 3. 3-10 times 150 15% 15% 20% 21% 4. More than 10 times 138 14% 14% 19% 20% Do not know whether ate any in the last 12 months 2 0% 0% 0% 0% Refused this question 3 0% 0% 0% 1% Total 735 74% 71% 100% 100% Table F.6: Origin of venison consumed over the past 12 months for all respondents who reported consuming venison in the past 12 months (n=491). Response Categories Yes Out of total sample (n=983) Out of those asked (n=491) No Don™t know Refused %Yes Weighted % Yes %Yes Weighted % Yes Self 97 10% 9% 20% 19% 393 1 0 Members of household 120 12% 13% 24% 26% 371 0 0 Family not within household (Relatives) 275 28% 27% 56% 56% 216 0 0 Friends, neighbors or coworkers 261 27% 26% 53% 54% 230 0 0 Community game dinner or event 39 4% 3% 7% 7% 452 0 0 Other 9 1% 1% 2% 2% 481 1 0 Road kill 3 0% 0% 1% 1% na na na Donation 3 0% 0% 1% 1% na na na Restaurant or Store 3 0% 0% 1% 1% na na na Table F.7: Form of venison provided over the past 12 months for a ll respondents who reported consuming venison in the past 12 months (n=491). Response Categories Yes Out of total sample (n=983) Out of those asked (n=491) No Don™t know Refused %Yes Weighted % Yes %Yes Weighted % Yes Uncooked/Raw 306 31% 31% 62% 64% 182 1 2 Cooked/Prepared 314 31% 31% 64% 66% 173 1 3 Other 55 6% 5% 11% 11% 425 8 3 Table F.8: All respondents' relationshi ps with hunters (n=997). Response Categories Yes % Yes Weighted % Yes No Don't know Refused Members of household hunt 224 22% 24% 766 4 3 Family members not within household hunt 602 60% 60% 383 11 1 Friends, coworkers, or neighbors hunt 785 79% 77% 170 41 1 Knew hunter growing up 710 71% 68% 277 10 0 Table F.9: Level of hunting experience for all respondents (n=997). Mean =0.84 SD=1.1 Min= 0 Max= 3 Response options n % Weighted % 0. Never gone hunting 521 52% 57% 1. Gone hunting at least once but not in the past 5 years 267 27% 23% 2. Gone hunting in the last 5 years but not every year 61 6% 6% 3. Goes hunting nearly every year 148 15% 14% Total 997 100% 100% Table F.10: All respondents' sex (n=997). Sex n % Weighted % Male 516 52% 47% Female 481 48% 53% Total 977 100% 100% Table F.11: All respondents' age report ed in categories (n=997). Note: in analysis age was used a continuous variable not in categories. Mean = 54.91 SD= 17.16 Min= 18 Max=95 Age n % Weighted % 18-29 100 10% 17% 30-39 103 10% 17% 40-49 127 13% 15% 50-59 227 23% 20% 60-69 217 22% 14% 70-79 134 13% 8% 80+ 66 7% 7% Refused 23 2% 3% Total 997 100% 100% Table F.12: All respondents' highest level of education completed (n=997). Mean =15.04 SD=2.70 Min= 7 Max=19 Education Level n % Weighted % 0. Did not go to school 0 0% 0% 1. 1st Grade 0 0% 0% 2. 2nd Grade 0 0% 0% 3. 3rd Grade 0 0% 0% 4. 4th Grade 0 0% 0% 5. 5th Grade 0 0% 0% 6. 6th Grade 0 0% 0% 7. 7th Grade 2 0% 0% 8. 8th Grade 7 1% 1% 9. 9th grade 3 0% 0% 10. 10th Grade 5 1% 0% 11. 11th Grade 17 2% 2% 12. High School Graduate or GED Holder 219 22% 20% 13. 1st Year College 92 9% 10% 14. 2nd Year College 151 15% 15% 15. Technical/Junior College Graduate 41 4% 5% 16. 3rd Year College 40 4% 5% 17. College Graduate (Four Years) 219 22% 22% 18. Some Post Graduate 37 4% 3% 19. Graduate Degree 157 16% 15% Do Not Know 2 0% 0% Refused This Question 5 1% 1% Total 997 100% 100% Table F.13: All respondents' ethnicity (Hispanic. Latino, or Spanish origin) (n=997). Responses n % Weighted % No 969 97% 97% Yes 17 2% 2% Do Not Know 1 0% 0% Refused This Question 10 1% 1% Total 997 100% 100% Table F.14: All respondents' race (n=997). Note: categories are not mutually exclusive . Race n % Weighted % White or Caucasian 838 84% 77% African American or Black 96 10% 14% Hawaiian or Other Pacific Islander 2 0% 1% Asian 11 1% 3% American Indian or Alaskan Native 15 2% 3% Other 34 3% 3% Refused 20 2% 2% Table F.15: All respondents race coded into mu tually exclusive categories (n=997). Race n % Weighted % White Only 819 82% 74% Black Only 90 9% 13% Other Including Multi Race 66 7% 11% Missing 22 2% 2% Total 997 100% 100% Table F.16: All respondents' annual household income in USD (n=997). Income n % Weighted % 1. Less than 10,000 44 4% 6% 2. 10,000-19,999 101 10% 11% 3. 20,000-29,999 84 8% 8% 4. 30,000-39,999 61 6% 6% 5. 40,000-49,999 110 11% 11% 6. 50,000-59,999 81 8% 7% 7. 60,000-69,999 81 8% 8% 8. 70,000-89,999 116 12% 12% 9. 90,000-99,999 30 3% 3% 10. 100,000-150,000 126 13% 12% 11.More than 150,000 67 7% 6% Do Not Know 31 3% 4% Refused 65 7% 6% Total 997 100% 100% Table F.17: All respondents' community type (n=997). Response Options n % Weighted % Rural Community 279 28% 25% Small City or Town, Village 337 34% 33% A Suburb 271 27% 29% Urban Community 110 11% 13% Missing 0 0% 0% Total 997 100% 100% Table F.18: All respondents' residence by Michigan Department of Natural Resources (MDNR) Ecoregion (n=997). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have similar hunter participation rates and hunter densities compared to the Southern Lower Peninsula. MDNR Ecoregion n % Weighted % Upper Peninsula Ecoregion 59 6% 4% Northern Lower Peninsula Ecoregion 108 11% 10% Southern Lower Peninsula Ecoregion 830 83% 87% Total 997 100% 100% APPENDIX G Additional Tables from the 68 th SOSS for Non-HuntersTable G.1: Wild harvested meat cons umption for non-hunters (n=521). Responses n % Weighted % Yes 321 62% 58% No 189 36% 40% Do not know 9 2% 2% Refused this question 2 0% 1% Total 521 100% 100% Table G.2: Reasons for not consuming wild harveste d meat for non-hunters who reported never consuming wild harvested meat (n=189). Open ended responses coded. Responses n Out of total sample (n=521) Out of those asked (n=189) % Weighted % % Weighted % Never had opportunity 37 7% 9% 20% 22% Diet/lifestyle 29 6% 6% 15% 16% Taste and smell 27 5% 5% 14% 14% Don't know any hunters 23 4% 5% 12% 13% Don't hunt 21 4% 4% 11% 11% Don't like/no desire to try 20 4% 3% 11% 9% Against hunting/ uncomfortable with hunting 14 3% 2% 7% 5% No Reason 14 3% 3% 7% 8% Do not know 14 3% 4% 7% 10% Moral or ethical concer ns 5 1% 1% 3% 2% Don't know where to get game meat 4 1% 1% 2% 3% Don't trust source 3 0% 1% 2% 1% Table G.3: Types of wild harvested meat cons umed by non-hunters who reported consuming wild harvested meat (n=321). Open ended responses coded. Responses n Total sample (n=521) Those asked (n=321) % Weighted % % Weighted % Venison/deer 307 59% 55% 96% 96% Fish 65 12% 12% 20% 21% Rabbit/hare 55 11% 9% 17% 16% Turkey 40 8% 7% 12% 13% Pheasant 39 7% 7% 12% 12% Duck 26 5% 5% 8% 8% Squirrel 24 4% 5% 7% 8% Bear 14 3% 3% 4% 5% Goose 10 2% 2% 3% 4% Grouse 8 2% 1% 2% 1% Turtle 6 1% 1% 2% 2% Elk 5 1% 1% 2% 1% Raccoon 5 1% 1% 2% 1% Feral Swine 5 1% 2% 2% 3% Farmed Species 4 1% 1% 1% 2% Beaver 2 0% 0% 1% 0% Muskrat 2 0% 1% 1% 1% Moose 2 0% 0% 1% 1% Woodchuck 1 0% 0% 0% 0% Quail 1 0% 0% 0% 1% Alligator/ Crocodile 1 0% 0% 0% 0% Sparrow 1 0% 0% 0% 0% Other- Species not specified 1 0% 0% 0% 0% Do not know 1 0% 0% 0% 0% Bison 0 0% 0% 0% 0% Woodcock 0 0% 0% 0% 0% Porcupine 0 0% 0% 0% 0% Opossum 0 0% 0% 0% 0% Frog 0 0% 0% 0% 0% Pigeon 0 0% 0% 0% 0% Dove 0 0% 0% 0% 0% Snake 0 0% 0% 0% 0% Skunk 0 0% 0% 0% 0% Fox 0 0% 0% 0% 0% Crawfish 0 0% 0% 0% 0% Table G.4: Types of wild harvested meat cons umed by non-hunters who reported consuming wild harvested meat (n=321). Open ended responses coded and combined into categories of similar species . Response Categories n Out of total sample (n=521) Out of those asked (n=321) % Weighted % % Weighted % Big game 307 59% 55% 96% 95% Upland game birds 71 14% 12% 22% 20% Fish 65 12% 12% 20% 21% Small game with season 62 12% 11% 19% 19% Waterfowl 31 6% 6% 10% 10% Furbearers 9 2% 2% 3% 3% No limit small game 8 2% 2% 2% 4% Reptiles and amphibians 6 1% 1% 2% 2% Non-Michigan game 2 0% 0% 1% 1% Table G.5: Frequency of venison consumption in the past 12 months for non-hunters who reported consuming venison (n=307). Mean =1.94 SD=0.95 Min= 1 Max= 4 Response Options n Out of total sample (n=521) Out of those asked (n=307) % Weighted % % Weighted % 1. Not at all 131 25% 22% 43% 40% 2. Once or twice 99 19% 18% 32% 33% 3. 3-10 times 50 10% 10% 16% 19% 4. More than 10 times 26 5% 4% 8% 8% Do not know whether ate any in the last 12 months 1 0% 0% 0% 0% Refused this question 0 0% 0% 0% 0% Total 307 59% 55% 100% 100% Table G.6: Origin of venison consumed over the past 12 months fo r non-hunters who reported consuming venison in the past 12 months (n=175). Response Categories Yes Out of total sample (n= 521) Out of those asked (n=175) No Don't know Refused %Yes Weighted % Yes %Yes Weighted % Yes Self 1 0% 0% 1% 0% 173 1 0 Members of household 35 7% 7% 20% 20% 140 0 0 Family not within household 104 20% 19% 59% 59% 71 0 0 Friends, neighbors or coworkers 102 20% 20% 58% 61% 73 0 0 Community game dinner or event 9 2% 2% 5% 5% 166 0 0 Other 4 1% 1% 2% 3% 171 0 0 Road kill 0 0% 0% 0% 0% na na na Donation 1 0% 0% 1% 0% na na na Restaurant or Store 3 1% 1% 2% 2% na na na Table G.7: Form of venison provided over the past 12 months for non-hunt ers who reported consuming veni son in the past 12 months (n=175). Response Categories Yes Out of total sample (n=521) Out of those asked (n=175) No Don't know Refused %Yes Weighted % Yes % Yes Weighted % Yes Uncooked/raw 93 18% 18% 53% 54% 80 1 1 Cooked/Prepared 122 23% 23% 70% 71% 51 1 1 Other 23 4% 4% 12% 13% 146 1 1 Table: G.8: Non-hunters' relationships with hunters (n=512). Response Categories Yes % Yes Weighted % Yes No Don't know Refused Members of household hunt 75 14% 15% 445 3 1 Family members not within household hunt 238 46% 45% 272 10 1 Friends, coworkers, or neighbors hunt 365 68% 67% 136 28 1 Close relationship with hunter growing up 277 53% 50% 236 8 0 Table G.9: Non-hunters' sex (n=521). Sex n % Weighted % Male 168 32% 32% Female 353 68% 68% Total 521 100% 100% Table G.10: Non-hunters' age reported in categories (n=521). Note: in analysis age was used as a continuous variable not in categories. Mean =47.65 SD= 18.42 Min= 18 Max=95 Age n % Weighted % 18-29 70 13% 21% 30-39 55 11% 17% 40-49 65 12% 14% 50-59 97 19% 17% 60-69 110 21% 12% 70-79 66 13% 8% 80+ 40 8% 7% Missing 18 3% 4% Total 521 100% 100% Table G.11: Non-hunters' highest level of education completed (n=521). Mean =15.26 SD=2.69 Min= 7 Max=19 Education Level n % Weighted % 0. Did not go to school 0 0% 0% 1. 1st Grade 0 0% 0% 2. 2nd Grade 0 0% 0% 3. 3rd Grade 0 0% 0% 4. 4th Grade 0 0% 0% 5. 5th Grade 0 0% 0% 6. 6th Grade 0 0% 0% 7. 7th Grade 1 0% 0% 8. 8th Grade 0 0% 0% 9. 9th grade 3 1% 0% 10. 10th Grade 4 1% 1% 11. 11th Grade 8 2% 2% 12. High School Graduate or GED Holder 110 21% 19% 13. 1st Year College 43 8% 8% 14. 2nd Year College 70 13% 15% 15. Technical/Junior College Graduate 21 4% 5% 16. 3rd Year College Graduate 25 5% 6% 17. College Graduate (Four Years) 122 23% 24% 18. Some Post Graduate 19 4% 4% 19. Graduate Degree 91 17% 16% Do Not Know 2 0% 0% Refused This Question 2 0% 0% Total 521 100% 100% Table G.12: Non-hunters' ethnicity (Hispanic. Latino, or Spanish origin) (n=521). Responses n % Weighted % Yes 14 3% 3% No 501 96% 95% Do Not Know 1 0% 0% Refused This Question 5 1% 1% Total 521 100% 100% Table G.13: Non-hunters' race (n=521). Note: categories are not mutually exclusive. Race n % Weighted % White or Caucasian 403 77% 68% African American or Black 77 15% 20% Hawaiian or Other Pacific Islander 2 0% 2% Asian 9 2% 4% American Indian or Alaskan Native 7 1% 2% Other 21 4% 5% Missing 13 3% 3% Table G.14: Non-hunter's race coded into three mu tually exclusive categories (n=521). Race n % Weighted % White Only 393 75% 65% Black Only 75 14% 19% Other Including Multi Race 40 8% 14% Missing 13 3% 3% Total 521 100% 100% Table G.15: Non-hunters' annual household income in USD (n=521). Mean =5.85 SD=3.09 Min= 1 Max= 11 Income n % Weighted % 1. Less than 10,000 28 5% 6% 2. 10,000-19,999 56 11% 12% 3. 20,000-29,999 41 8% 8% 4. 30,000-39,999 30 6% 7% 5. 40,000-49,999 58 11% 12% 6. 50,000-59,999 41 8% 6% 7. 60,000-69,999 39 7% 6% 8. 70,000-89,999 55 11% 10% 9. 90,000-99,999 17 3% 3% 10. 100,000-150,000 62 12% 13% 11. More than 150,000 33 6% 5% Don't know 21 4% 5% Refused 40 8% 7% Total 521 100% 100% Table G.16: Non-hunters' community type (n=521). Response Options n % Weighted % Rural Community 102 20% 17% Small City or Town, Village 181 35% 35% A Suburb 174 33% 33% Urban Community 64 12% 15% Missing 0 0% 0% Total 521 100% 100% Table G.17: Non-hunters™ residence by Michigan Department of Natural Resources (MDNR) Ecoregion (n=521). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have similar hunter participation rates and hunter densities compared to the Southern Lower Peninsula. MDNR Ecoregion n % Weighted % Upper Peninsula Ecoregion 21 4% 2% Northern Lower Peninsula Ecoregion 29 6% 5% Southern Lower Peninsula Ecoregion 471 90% 93% Total 521 100% 100% APPENDIX H Additional Tables from the 68 th SOSS for Frequent Hunters Table H.1: Wild harvested meat consumpti on for frequent hunters (n=148). Responses n % Weighted % Yes 145 99% 99% No 3 1% 1% Do not know 0 0% 0% Refused this question 0 0% 0% Total 148 100 100% Table H.2: Types of wild harvested meat cons umed by frequent hunters who reported consuming wild harvested meat (n=145). Open ended responses coded. Responses n Out of total sample (n=148) Out of those asked (n=145) % Weighted % % Weighted % Venison/deer 141 95% 94% 97% 97% Fish 55 37% 37% 38% 39% Rabbit/hare 72 49% 47% 50% 48% Turkey 52 35% 38% 36% 39% Pheasant 43 29% 24% 30% 25% Duck 30 20% 19% 20% 19% Squirrel 58 39% 37% 40% 38% Bear 42 28% 28% 29% 28% Goose 28 19% 17% 19% 17% Grouse 34 23% 17% 23% 17% Turtle 7 5% 7% 5% 7% Elk 19 13% 15% 14% 16% Raccoon 13 9% 9% 9% 9% Feral Swine 5 3% 4% 3% 4% Farmed Species 1 1% 1% 1% 1% Beaver 9 6% 4% 6% 4% Muskrat 5 3% 4% 3% 4% Moose 2 1% 2% 1% 2% Woodchuck 4 3% 3% 3% 3% Quail 9 6% 7% 6% 7% Alligator/ Crocodile 0 0% 0% 0% 0% Sparrow 0 0% 0% 0% 0% Other- Species not specified 6 4% 3% 4% 3% Do not know 1 1% 0% 1% 0% Table H.2 (cont™d): Bison 1 1% 1% 1% 1% Woodcock 12 8% 8% 8% 8% Porcupine 1 1% 0% 1% 0% Opossum 3 2% 3% 2% 3% Frog 5 3% 3% 3% 3% Pigeon 1 2% 1% 1% 1% Dove 2 1% 1% 1% 2% Snake 2 1% 2% 1% 2% Skunk 1 1% 1% 1% 1% Fox 2 1% 2% 1% 2% Crawfish 1 1% 0% 1% 0% Table H.3: Types of wild harvested meat cons umed by frequent hunters who reported consuming wild harvested meat (n=145). Open ended responses coded and combined into categories of similar species . Response Categories n Out of total sample (n=148) Out of those asked (n=145) % Weighted % % Weighted % Big game 144 97% 95% 99% 98% Upland game birds 94 64% 60% 65% 62% Fish 55 37% 37% 38% 39% Small game with season 83 56% 54% 57% 56% Waterfowl 39 26% 25% 27% 25% Furbearers 20 14% 14% 14% 14% No limit small game 14 9% 11% 10% 11% Reptiles and amphibians 11 7% 11% 8% 11% Non-Michigan game 3 2% 3% 2% 3% Table H.4: Frequency of venison consumption in the past 12 months for frequent hunters who reported consuming venison (n=141). Mean=3.35 SD=0.90 Min=1 Max=4 Response Options n Out of total sample (n=148) Out of those asked (n=141) % Weighted % % Weighted % 1. Not at all 10 7% 6% 7% 7% 2. Once or twice 17 11% 9% 12% 9% 3. 3-10 times 43 29% 26% 31% 27% 4. More than 10 times 71 48% 54% 50% 57% Do not know whether ate any in the last 12 months 0 0% 0% 0% 0% Refused this question 0 0% 0% 0% 0% Total 141 100% 100% 100% 100% Table H.5: Origin of venison consumed over the past 12 months for fr equent hunters who reported consuming venison in the past 12 months (n=131). Response Categories Yes Out of total sample (n= 148) Out of those asked (n=131) No Don't know Refused %Yes Weighted % Yes %Yes Weighted % Yes Self 93 63% 62% 71% 71% 55 0 0 Members of household 42 28% 33% 32% 37% 89 0 0 Family not within household 54 36% 38% 41% 43% 77 0 0 Friends, neighbors or coworkers 61 41% 43% 47% 49% 70 0 0 Community game dinner or event 13 9% 8% 10% 9% 118 0 0 Other 3 2% 2% 2% 3% 127 1 0 Road kill 2 1% 1% 2% 2% na na na Donation 1 1% 1% 1% 1% na na na Restaurant or Store 0 0% 0% 0% 0% na na na Table H.6: Form of venison provided over the past 12 months for fre quent hunters who reported consuming venison in the past 12 months (n=131). Response Categories Yes Out of total sample (n=148) Out of those asked (n=131) No Don't know Refused %Yes Weighted % Yes % Yes Weighted % Yes Uncooked/raw 88 59% 62% 67% 70% 43 0 0 Cooked/Prepared 83 56% 58% 63% 66% 48 0 0 Other 14 9% 9% 11% 11% 114 3 0 Table: H.7: Frequent hunters' relationshi ps with other hunters (n=148). Response Categories Yes % Yes Weighted % Yes No Don't know Refused Members of household hunt 79 53% 57% 69 0 0 Family members not within household hunt 128 86% 88% 20 0 0 Friends, coworkers, or neighbors hunt 144 97% 98% 3 1 0 Close relationship with hunter growing up 139 94% 95% 9 0 0 Table H.8: Frequent hunters' sex (n=148). Sex n % Weighted % Male 126 85% 79% Female 22 15% 21% Total 148 100% 100% Table H.9: Frequent hunters' age re ported in categories (n=148). Note: in analysis age was used as a continuous variable not in categories. Mean=46.03 SD=15.90 Min=18 Max=95 Age n % Weighted % 18-29 11 7% 14% 30-39 23 16% 24% 40-49 30 20% 22% 50-59 39 27% 19% 60-69 26 18% 11% 70-79 14 9% 7% 80+ 4 3% 2% Missing 1 0% 1% Total 148 101% 100% Table H.10: Frequent hunters' highest level of education completed (n=148). Mean =14.50 SD=2.58 Min=8 Max=19 Education Level n % Weighted % 0. Did not go to school 0 0% 0% 1. 1st Grade 0 0% 0% 2. 2nd Grade 0 0% 0% 3. 3rd Grade 0 0% 0% 4. 4th Grade 0 0% 0% 5. 5th Grade 0 0% 0% 6. 6th Grade 0 0% 0% 7. 7th Grade 0 0% 0% 8. 8th Grade 2 1% 1% 9. 9th grade 0 0% 0% 10. 10th Grade 0 0% 0% 11. 11th Grade 1 1% 1% 12. High School Graduate or GED Holder 41 28% 27% 13. 1st Year College 20 14% 18% 14. 2nd Year College 21 14% 13% 15. Technical/Junior College Graduate 3 2% 1% 16. 3rd Year College Graduate 7 5% 7% 17. College Graduate (Four Years) 29 20% 17% 18. Some Post Graduate 5 3% 2% 19. Graduate Degree 18 12% 11% Do Not Know 0 0% 0% Refused This Question 1 1% 1% Total 148 101% 100% Table H.11: Frequent hunters' ethnicity (Hispani c. Latino, or Spanish origin) (n=148). Responses n % Weighted % Yes 0 0% 0% No 147 99% 100% Do Not Know 0 0% 0% Refused This Question 1 1% 0% Total 148 100% 100% Table H.12: Frequent hunters' race (n=148). Note: categories are not mutually exclusive. Race n % Weighted % White or Caucasian 131 86% 84% African American or Black 6 4% 8% Hawaiian or Other Pacific Islander 0 0% 0% Asian 2 1% 4% American Indian or Alaskan Native 3 2% 4% Other 3 2% 1% Missing 3 2% 2% Table H.13: Frequent hunter's race coded into thr ee mutually exclusive categories (n=148). Race n % Weighted % White Only 129 87 79% Black Only 5 3 6% Other Including Multi Race 9 6 10% Missing 5 3 4% Total 148 99% 99% Table H.14: Frequent hunters' annual household income in USD (n=148). Income n % Weighted % 1. Less than 10,000 3 2% 5% 2. 10,000-19,999 12 8% 11% 3. 20,000-29,999 16 11% 13% 4. 30,000-39,999 13 9% 7% 5. 40,000-49,999 15 10% 9% 6. 50,000-59,999 16 11% 10% 7. 60,000-69,999 13 9% 9% 8. 70,000-89,999 16 11% 13% 9. 90,000-99,999 3 2% 3% 10. 100,000-150,000 20 14% 9% 11. More than 150,000 9 6% 5% Don't know 1 1% 1% Refused 11 7% 5% Total 148 101% 100% Table H.15: Frequent hunters' community type (n=148). Response Options n % Weighted % Rural Community 65 44% 41% Small City or Town, Village 49 33% 32% A Suburb 18 12% 13% Urban Community 16 11% 13% Missing 0 0% 0% Total 148 100% 99% Table H.16: Frequent hunters™ residence by Michigan Department of Natural Resources (MDNR) Ecoregion (n=521). Note: In statistical analysis the Upper Peninsula and Northern Lower Peninsula Ecoregions were combined because they have simila r hunter participation rates and hunter densities compared to the Southern Lower Peninsula. MDNR Ecoregion n % Weighted % Upper Peninsula Ecoregion 17 11% 8% Northern Lower Peninsula Ecoregion 28 19% 19% Southern Lower Peninsula Ecoregion 103 70% 73% Total 148 100% 100% APPENDIX I Notes on Coding Open-Ended Responses from the 68 th SOSS Notes on Coding Open-Ended Responses from the 68th SOSS Meat1a: fiIs there any particular reason why you have not eaten game meat?fl If the respondent answered that they had not eaten game m eat from hunting in Michigan they were asked fiIs there any particular reason why you have not eaten game meat?fl This question had an open-ended response that was field coded by the interviewer into 9 possible categories. Multiple categories could apply per respondent. The potential response options were (a) diet (don™t eat mea t/red meat); (b) taste; (c) I don™t hunt ; (d) never had opportunity; (e) don™t know any hunters; (f) don™t know where to get game meat; (g) against hunting/uncomfortable with hunting; (x) other; and (y) do not know. Some of the responses recorded in other could easily be coded into the previously specified categories (a-g). Four additional response options emerged from answers to this question: (h) no reason; (i) dislike game meat; (j) don™t trust source; and (k) expressed moral or ethical reasons. The variable no reason was created to describe respondents who felt there was no particular reason why that had not consumed game meat. The variable dislike game meat was created to express a respondent™s general dislike of game meat or a disinterest in trying game meat due to their di slike. The variable don™t trust source was created to express a respondent™s concerns about the source of the meat and it™s processing. The variable expressed moral or ethical concerns was created to express a respondents moral or ethical issues with killing or eating wildlife. Categories were not exclusive, except no reason. Only one respondent answered no reason and dislike. They were coded as having the response dislike and removed from the response category no reason. MEAT 2: fiWhat types of game meat from hunting in Michigan have you had? fi This question had an open-ended response that was live coded by the interviewer into 12 possible categories. Multiple categories could apply per respondent. The potential response options were: (a) venison; (b) turkey); (c) elk; (d) rabbit or hare; (e) pheasant; (f) goose); (g) grouse; (h) squirrel; (i) duck; (j) fish; (x) other; and (y) do not know. The other category was later coded into 24 additional response options: (k) bear; (l) partridge; (m) turtle; (n) bison; (o) raccoon; (p) woodcock; (q) beaver; (r) muskrat; (s) feral swine; (t) woodchuck; (u) quail; (v) moose; (w) porcupine; (aa) opossum; (ab) frog; (ac) pigeon; (ad) dove; (ae) snake; (af) skunk; (ag) alligator/crocodile; (ah) fox; (ai) crawfish; (aj) sparrow; (ak) other species not specified; (al) farmed species. Some individuals used different words to describe the same species. Partridge is another term for grouse in Michigan, thus the coded response option partridge (l) was combined with the response option grouse (g). Wild pig, boar, and wild boa r were all defined as feral swine. Ground hog and woodchuck were defied as woodchuck. All of these potential responses where then reduced to 9 categories of similar themed species. Deer, black bear and elk were combined into the category big game. According to the MDNR turkey is considered big game in Mich igan, however, technically turkey is an upland game bird. Turkey, quail, woodcock, pheasant and grouse were combined to create the category upland game birds. Duck and goose were combin ed to create the category waterfowl. Raccoon, beaver, muskrat and fox were combined into th e category furbearers. Rabbit/hare and squirrel were combined to create the category small game with season. Technically red squirrels are part of the non-limit season, however the larger squirr el species (grey and fox), which have seasons, are hunted more often and contain more meat. Thus the response squirrel was included in the small game with season category, although we ca nnot be sure which squirrel species the respondent was referring to. Opossum, porcupine, woodchuck, feral swine, feral pigeons and house sparrows can be hunted year round with a valid Michigan hunting license and were combined to create the category no-limit small ga me. Turtle, snake, and frog were combined into the category Reptiles and Amphibians. Bison, moose, dove and alligator were combined into the category non-Michigan game. On e respondent answered crayfish, which was combined into the fish category. Meat 9: fiDid you get any venison from another source?fl Some of the responses to this question could easily be coded into the previously specified source categories (self, member s of household, relatives, friends, neighbors or coworkers and community dinner or event). Three additional re sponse options emerged from answers to this question: road kill, donation, and restaurant or store. Road kill referred to venison that had been harvested form the side of the road. Donati on referred venison that was provided to the individual in the form of a dona tion, either from another person or at a food bank or other food donation program. Restaurant or store referred to individuals who had purchased their venison from a restaurant or store. This response is co ntrary to the definition of game meat provided during the survey, however, individuals who resp onded this way had also received venison from previously specified sources and were not removed from the study. Meat 12: fiWas any of it provided in another form?fl Some of the responses to this question could easily be coded into the previously specified source categories (raw/uncooked and cooked/prepared). Responses such as sausage, jerky, canned, smoked, sticks, salami, and salted were all added to the cooked/prepared response category. Responses that did not indicate a uncooked or cooked form, such as frozen or packaged, remained coded as other. Community Type: fiWould you say you live in a rural community, a small city or town, a suburb, or an urban community?fl If a respondent answered with another category that was not specified, this was recorded as other with their specific response transcribed. The open-ended responses were then coded to best match the original four response opti ons. The responses the country, the boonies, and farming community was coded as rural. The response township was coded as part of a small city or town. The responses between the country and the city and lower middle class suburb were coded as suburban. The responses larger city and Battle Creek were identified as urban . Furthermore, seven additional respondents did not provide an answer to this question; however, these respondents did provide their zip code in response to another question. Using the respondent™s zip code compared to informati on on urban areas and clusters from the U.S. Census, satellite imagery, and road density these additional respondents were assigned a community type based upon the original four response options. APPENDIX J Pre-Notification Letter for the 68 th SOSS Institute for Public Policy and Social Research State of the State Survey College of Social Science Nisbet Building Michigan State University 1407 S. Harrison Road Room 343 East Lansing, MI 48824 517-884-0364 Fax: 517-884-7557 ippsr.msu.edu/soss {Date} {Name} {Address} {City}, {State} {Zip} Dear {Name}, I am writing to ask for your household™s assistance with the State of the State Survey , a research project conducted by the Institute for Public Policy and Social Research at Michigan State University. We would like an adult member of your household to participate in a one-time telephone interview . The State of the State Survey asks Michigan residents for their opinions on current public policy issues, and results are used to inform elected officials, the media, and the general public. It has been conducted by the Institute for Public Policy and Social Research in collaboration with the Office for Survey Research at Michigan State University since 1994; to date, over 65,000 people have participated in the survey. In the next few days, your household will receive a phone call from an interviewer at Michigan State University. You will only be asked for information; we will not try to sell you anything or ask for money. If your household is called at an inconvenient time, the interviewer will work with you to find a date and time for the interview that fits your schedule. Your time and participation are highly valued and appreciated. The interviewer will first ask a few questions to determine which adult in your household we need to interview, and the interview itself will take approximately 20 minutes. Your participation in this research is completely voluntary and confidential. Your answers will never be linked to your household, and we will never share your name or phone number with any other organization. If you have any questions about this study, please contact me at glpierce@msu.edu or 517-884-0364. You can learn more about the MSU State of the State Survey at http://ippsr.msu.edu/soss/ On behalf of Michigan State University and the Institute for Public Policy and Social Research, I want to thank you for your assistance in this research effort. Sincerely, Graham L. Pierce Project Manager, State of the State Survey Institute for Public Policy and Social Resarch Michigan State University REFERENCESREFERENCES Abhat, D., & Unger, K. (2010) Managing wildlife in shades of gray: Threats to the pillars of the North American Model. The Wildlife Professional , Fall 2010. Adams, K. (2015). Wild venison for sale? Quality Deer Management Association™s Whitetail Report 2015, 30-31. Aiken, R., & Harris, A. (2011). Deer hunting in the United States: Demographics and trends. Addendum to the 2006 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. U.S. Fish and Wildlife Service (USFWS) Report 2006-10. Allen-Arave, W., Gurven, M., & Hill, K. (2008). R eciprocal altruism, rath er than kin selection, maintains nepotistic food transf ers on an Ache reservation. Evolution and Human Behavior, 29(5), 305-318. Alvard, M. (2004). Good hunters keep smaller shares of larger pies. Open peer commentary on Gurven, M., To give and to give not: the behavioral ecology of human food transfers. Behavioral and Brain Sciences, 27(4), 543-583. American Association for Public Opinion Res earch (AAPOR). 2011. Standard definitions: Final dispositions of case codes and outcome rates for surveys. 7 th edition. Aneshensel, C. S. (2012). Theory-based data analysis for the social sciences. Thousand Oaks, CA: Sage. Archer, K.J., & Lemeshow, S. ( 2006). Goodness-of-fit test for a logistic regression model fitted using survey sample data. The Stata Journal, 6(1), 97-105. Babbie, E. R. (1990). Survey research methods . Belmont, CA: Wadsworth Publication Company. Batcheller, G. R., Bambery, M. C., Bies, L., Decker, T., Dyke, S., Guynn, D., McEnroe, M., O™Brien, M., Organ, J. F., Riley, S. J., & Roehm, G. (2010). The public trust doctrine: implications for wildlife management and c onservation in the Unite d States and Canada. Technical Review 10-01. The Wildlife Society, Bethesda, Maryland, USA. Beardsworth, A., & Bryman, A. (2004). Meat consumption and meat avoidance among young people: An 11-year longitudinal study. British Food Journal , 106, 313-327. Bell, D., Roberton, S., & Hunter, P. R. (2004). Animal origins of SARS coronavirus: possible links with the international trade in small carnivores. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences , 359(1447), 1107-1114. Bliege Bird, R. L., & Bird, D. W. (1997). Delaye d reciprocity and tolerated theft: The behavioral ecology of food-sharing strategies. Current Anthropology, 38(1), 49-78. Bliege Bird, R., Smith, E., & Bird, D. W. ( 2001). The hunting handicap: costly signaling in human foraging strategies. Behavioral Ecology and Sociobiology, 50(1), 9-19. Bowen-Jones, E., Brown, D., & Robinson, E. J. Z. (2003). Economic commodity or environmental crisis? An interdisciplinary a pproach to analyzing the bushmeat trade in central and west Africa. Area, 35(4), 390-402. Bruckner, D. W. (2007). Considerations on the morality of meat consumption: Hunted-game versus farm-raised animals. Journal of Social Philosophy, 38(2), 311-330. Burger, J. (2000). Gender differences in meal patter ns: Role of self-caught fish and wild game in meat and fish diets. Environmental Research Section A , 83, 140-149. Burger, J. (2002). Daily consumption of w ild fish and game: exposures of high end recreationalists. International journal of Environmental Health Research, 12, 343-354. Cahoone, L. (2009). Hunting as a moral good. Environmental Values , 18, 67-89. Campa III, H., Riley, S. J., Winterstein, S. R., H iller, T. L., Lischka, S. A., & Burroughs, J. P. (2011). Chaning landscapes for White-T ailed Deer Management n the 21st Century: Parcelization of Land Ownership and Evolving Stakeholder Values in Michigan. Wildlife Society Bulletin, 35(5): 168-176. Carpenter, L. H. (2000). Harvest Management Goals. In Demarais, S., & Krausman, P. R. (Eds.), Ecology and Management of Large Mammals in North America (192-213). Upper Saddle River, NY: Prentice Hall. Casady, R. J., & Lepkowski, J. M. (1993). Stratified telephone survey designs. Survey Methodology, 19(1), 103-113. Case, D. J., & McCullough, D. R. (1987). The white-tailed deer of North Manitou Island. California Agricultural Experiment Stati on, Division of Agriculture and Natural Resources, University of California. 55(9). Centers for Disease Control and Prevention (CDC). (2013) The BFRSS data user guide . Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. Cerulli, T. (2012). The mindful carnivore: A vegetarian's hunt for sustenance. New York, NY: Pegasus Books. Cowan, R.L., Hartsook, E.W., Whel an, J.B., Watkins, J.L., Lindzey, J.S., Wetzel, R.W., & Liscinsky, S.A. (1968). Weight your deer with a string. Penn. Game News , 39(11), 17-19. Danieli, P. P., Serrani, F., Primi, R., Ponzetta, M. P., Ronchi, B., & Amici, A. (2012). Cadmium, Lead, and Chromium in Large Game: A Lo cal-Scale Exposure Assessment for Hunters Consuming Meat and Liver of Wild Boar. Archives of environmental contamination and toxicology , 63(4), 612-627. Demarais, S., Miller, K. V., & Jacobson, H. A. (2000). White-tailed deer. In Demarais, S., & Krausman, P. R. (Eds.), Ecology and Management of Large Mammals in North America (192-213). Upper Saddle River, NY: Prentice Hall. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, phone, mail, and mixed-mode surveys: the tailored design method . Hoboken, NJ: John Wiley & Sons. Dizard, J. E. (2003). Mortal stakes: Hunters and hunting in contemporary America. Amherst, MA: University of Massachusetts Press. Dombrowski, K. (2007). Subsiste nce livelihood, native identity and internal differentiation in Southeast Alaska. Anthropologica, 211-229. Dougherty, E. M., Fulton, D. C., & Anderson, D. H., (2003). The Influence of gender on the relationship between wildlife value orientations , beliefs, and the acceptability of lethal deer control in Cuyahoga Valley National Park. Society & Natural Resources , 16(7), 603-623. Environmental Systems Research Institute (E SRI). (2012). ArcGIS Desktop: Release 10.1 [computer software}. Redlands, CA: Environmental Systems Research Institute. Fischler, C. 2011. Commensa lity, society and culture. Social Science Information 50, 528-548. Fischer, A., Sandström, C., Delibes-Mateos, M ., Arroyo, B., Tadie, D., Randall, D., ... & Maji, A. (2013). On the multifunctionality of huntingŒa n institutional analysis of eight cases from Europe and Africa. Journal of Environmental Planning and Management , 56(4), 531-552. Fletcher, J. (2011). Gardens of Earthly Delight: The history of deer parks . Oxford, UK: Windgather Press. Franklin, A. (1998). Naturalizing sports: Hunting and angling in modern environments. International Review for the Sociology of Sport, 33(4), 355-366. Frawley, B. J. (2014). Michigan deer harvest survey report 2013 seasons. Michigan Department of Natural Resources. Wildlife Report No. 3585. Frawley, B. J. (2006). Demographics, recruitm ent, and retention of michigan hunters: 2005 update. Michigan Department of Natural Resources. Wildlife Division Report No. 3462. Freese, C. H. (Ed.). (1997). Harvesting wild species: implications for biodiversity conservation . Baltimore, MD: Johns Hopkins University Press. Garibaldi, A., & Turner, N. (2004). Cultural keystone species: impli cations for ecological conservation and restoration. Ecology and Society, 9(3), 1. Geist, V. (1988). How markets in wildlife meat and parts, and the sale of hunting privileges, jeopardize wildlife conservation. Conservation Biology , 2(1), 15-26. Geist, V. (1998). Deer of the world: their evolution, behaviour, and ecology. Mechanicsburg, PA: Stackpole books. Gouveia, L., & Juska, A. (2002). Taming nature , taming workers: Constructing the separation between meat consumption and meat production in the US. Sociologia Ruralis , 42(4), 370-390. Gurven, M. (2004a). To give and to give not: the behavioral ecology of human food transfers. Behavioral and Brain Sciences, 27(4), 543-583. Gurven, M. (2004b). Reciprocal altruism and food sharing decisions among Hiwi and Ache hunter-gathers. Behavioral Ecology and Sociobiology, 56, 366-380. Granovetter, M. S. (1973). The strength of weak ties. American journal of sociology, 1360-1380. Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational evaluation and policy analysis , 11(3), 255-274. Hahn, W. (2015). Meat price spreads [Data file and documentation]. Retrieved from http://www.ers.usda.gov/data-products/meat-price-spreads.aspx Hamerstrom, F. N., & Camburn, F. L. (1950). Wei ght relationships in the George Reserve deer herd. Journal of Mammalogy, 5-17. Hamilton, W. J. (1947). Dressed we ights of some game mammals. The Journal of Wildlife Management, 349-350. Harder, J. D. (1980). Reproduction of white-tailed deer in the north central United States. In White-tailed deer population management in the north central states, Hine, R.L. & Nehls, S. (eds.). Symposium Proceedings 1979 Nort h Central Section. The Wildlife Society. Heberlein, T. A. 1991. Changing attitudes and funding for wildlife-preserving the sport hunter. Wildlife Society Bulletin , 19, 528-534. Heberlein, T. A., & Ericsson, G. (2005). Ties to the countryside: accounting for urbanites attitudes toward hunting, wolves, and wildlife. Human Dimensions of Wildlife, 10, 213-227. Heeringa, S. G., West, B. T., & Berglund, P. A. (2010). Applied survey data analysis. Boca Raton, FL: CRC Press. Heffelfinger, J. (2014), The Gift of Venison. Tracks, Nov/Dec: 42-46. Heinz, B., & Lee, R. (1998). Getting down to the meat: The symbolic construction of meat consumption. Communication Studies , 49(1), 86-99. Hernández-Morcillo, M., Plieninger, T., & Bieling, C. (2013). An empirical review of cultural ecosystem service indicators. Ecological Indicators , 29, 434-444. Hildreth, A. M., Hygnstrom, S. E., Hams, K. M., & VerCauteren, K. C. (2011). The Nebraska deer exchange: a novel program for donating harvested deer. Wildlife Society Bulletin, 35(3), 195-200. Iqbal, S., Blumenthai, W., Kennedy, C., Yip, F. Y ., Pickard, S., Flanders, W. D., – Brown, M. J. (2009). Hunting with lead: Association between blood lead levels and wild game consumption. Environmental Research , 109, 952-959. Jenkins, D.H., & Bartlett, I. H. (1959). Michigan whitetails. Michigan Department of Conservation, Game Division. Lansing, MI. Jiménez, G. A., Montón-Subías, S., & Romero, M. S. (2011). Guess who's coming to dinner: feasting rituals in the prehistoric societies of Europe and the near east. Oakville, CT: Oxbow books. Kameda, T., Takezawa, M., & Hastie, R. (2005) . Where Do Social Norms Come From?: The Example of Communal Sharing. Psychological Science, 14(6), 331-334. Kaplan, H., & Gurven, M. (2005) The natural hist ory of human food sharing and cooperation: A review and a new multi-individual approach to the negation of norms. In Gintis, H., Bowles, S., Boyd, R, & Fehr, E. (Eds.), Moral Sentiments and Material Interests: The Foundations of Cooperation in Economic Life. (75-114). Cambridge, MA: The MIT Press. Kaplan, H., Hill, K., Cadeliña, R. V., Hayden, B ., Hyndman, D. C., Preston, R. J., –Yesner, D. R. (1985). Food sharing among ache foragers : Tests of explanatory hypotheses [and comments and reply]. Current Anthropology, 223-246. Karesh, W. B., & Cook, R. A. (2005). The human-animal link. Foreign Affairs, 84(4), 38-50. Kass, L. R. (1994). The hungry soul: Eating and the perfecting of our nature. New York, NY: The Free Press. Kawai, K. (Ed.). (2013). Groups: the evolution of human sociality. Kyoto, Japan: Kyoto University Press & Trans Pacific Press. Knezevic, I. (2009). Hunting and environm entalism: Conflict or misperceptions. Human Dimensions of Wildlife, 14(1), 12-20. Koster, J. (2011). Interhousehold meat sharing among Mayangna and Miskito horticulturalists in Nicaragua. Human Nature , 22, 394-415. Langenau, E. (1994). 100 years of deer manageme nt in Michigan. Michigan Department of Natural Resources. Wildlife Division Report Number 3213. Larsen, C. S. (2003). Animal source f oods and human health during evolution. The Journal of nutrition, 133(11), 3893S-3897S. Larson, L. R., Stedman, R. C., Decker, D. J., Si emer, W. F., & Baumer, M. S. (2014). Exploring the social habitat for hunting: Toward a comprehensive framework for understanding hunter recruitment and retention. Human Dimensions of Wildlife, 19(2), 105-122. Levin, S. A., & Lubchenco, J. (2008). Resilience, robustness, and marine ecosystem-based management. Bioscience , 58(1), 27-32. Liu, J., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., ... & Taylor, W. W. (2007). Complexity of coupled hu man and natural systems. Science, 317(5844), 1513-1516. Liu, J., Mooney, H., Hull, V., Davis, S. J., Gaskell, J., Hertel, T., ... & Li, S. (2015). Systems integration for global sustainability. Science, 347(6225), 1258832. Ljung, P. E., S. J. Riley, Heberlein, T. A., & Ericsson, G. (2012). Eat prey and love: game meat consumption and attitudes towards hunting. The Wildlife Society Bulletin, 36, 669-675. Ljung, P. E., Riley, S. J., & Ericsson, G. (2014). Game meat consumption feeds urban support of traditional use of natural resources. Society & Natural Resources , 28(6), 657-669. Magdoff, F. (2012). Food as a commodity. Monthly Review , 63(8),15-22. Manfredo, M. J., Teel, T. L., & Bright. A. D. (2003). Why are public values toward wildlife changing? Human Dimensions of Wildlife , 8(4), 287Œ306. Manfredo, M. J., Teel, T. L., & Henry, K. L. (2009). Linking society and environment: A multilevel model of shifting wildlife value orie ntations in the western United States. Social Science Quarterly, 90(2), 4007-427. Manfredo, M. J., & Zinn, H. C. (1996). Population change and its implications for wildlife management in the new west: A case study of Colorado. Human Dimensions of Wildlife, 1(3), 62-74 Marchello, M. J., Berg, P. T., Slanger, W. D ., & Harrold, R. L. (1985). Cutability and nutrient content of white-tailed deer. Journal of Food Quality, 7(4), 267-275. Mateo, R., Rodriguez-De La Cruz, M., Vidal, D., Reglero, M., & Camarero, P. (2007). Transfer of lead from shot pellets to game meat during cooking. Science of the Total Environment, 372(2), 480-485. Mayhew, S. L. (2014). Deer checking station data Œ 2013 seasons: Summary Tables. Michigan Department of Natural Resources Wildlife Division Report. McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001) . Birds of a feather: Homophily in social networks. Annual review of sociology , 415-444. Michigan Department of Agriculture and Rura l Development: Food and Dairy Division. (2012). Enrolled House Bill No. 5196. Act 92 of 2000, FOOD LAW OF 2000, (289.1101- 289.8111). Michigan Department of Environmental Qual ity (MDEQ); generated by Amber Goguen; using DEQ Environmental Mapper land use layer; https://web1.mcgi.state.mi.us/ environmentalmapper/ (03 March 2014). Michigan Department of Natural Resources (M DNR). (2010). Michigan deer management plan. Wildlife Division Report No. 3512. Michigan Department of Natural Resources (MDNR) Wildlife Division. (2013), Michigan Hunting and Trapping Digest. Lansing, MI. Michigan Department of Technology, Manageme nt and Budget (DTMB) Center for Shared Solution (CSS). 2011. Population Density in Michigan: 2010. Retrieved from http://www.michigan.gov/documents/cgi /cgi_census_map_popdens_tract_10_347989_7. pdf Millennium Ecosystem Assessment (MEA). (2005) Ecosystems and human well-being: Current state and trends (Vol.1). Washington, D.C.: Island Press. Miller, L., Rozin, P., & Fiske, A. P. (1998). Food sharing and feeding another person suggest intimacy; two studies of American college students. European Journal of Social Psychology, 28(3), 423-436. Milner-Gulland, E. J., & Bennett, E. L. (2003). Wild meat: the bigger picture. Trends in Ecology & Evolution, 18(7), 351-357. Mintz, S. W., & Du Bois, C. M. (2002). The anthropology of food and eating. Annual review of anthropology, 99-119. Moore, J. (2004). The history of human food transfers: Tinbergen™s other question. Open peer commentary on Gurven, M., To give and to give not: the behavioral ecology of human food transfers. Behavioral and Brain Sciences, 27(4), 543-583. National Rifle Association (NRA) Hunter Servic es Department. (2010). Hunters for the Hungry nationwide resources: 2009-2010 Season, . Nolin, D. A. (2010). Food-sharing networks in Lamalera, Indonesia: Reciprocity, kinship, distance. Human Nature, 21, 234-268. O™Keefe, J. H., & Cordain, L. (2004). Cardiovascular disease resulting from a diet and lifestyle at odds with our paleolithic genome: How to become a 21 st century hunter-gather. May Clinic Proceedings, 79, 101-108. Omura, K. (2013) The ontology of sociality: Shari ng: and subsistence mechanisms. In Kawai, K. (Ed.). Groups: the evolution of human sociality. Kyoto, Japan: Kyoto University Press & Trans Pacific Press. Organ, J. F., & Batcheller, G. R. (2009). Reviving the public trust doctrine as a foundation for wildlife management in North America. In Manfredo, M.J., Vaske, J.J., Brown P.J., Decker, D.J., & Duke, E.A. (eds). Wildlife and society: the science of human dimensions. Washington, D.C.: Island Press. Organ, J.F., Geist, V., Mahoney, S.P., Williams, S., Krausman, P.R., Batcheller, G.R., – D.J. Decker. (2012). The North American Mode l of Wildlife Conservation. The Wildlife Society Technical Review 12-04. The Wild life Society, Bethesda, Maryland, USA. Organ, J., Mahoney, S. & Geist, V. (2010). Born in the hands of hunters: The North American Model of Wildlife Conservation. The Wildlife Professional, Fall 2010. Oxford American College Dictionary. (2002). New York, NY: Oxford University Press. Ozoga, J.J., Doepker, R.V., Sargent, M.S. (1993). Ecology & management of white-tailed deer in Michigan. Wildlife Division Report Number 3209. Pachucki, M. A., Jacques, P. F., & Christakis, N. A. (2011). Social network concordance in food choice among spouses, friends, and siblings. American Journal of Public Health , 101(11), 2170. Patton, J. Q. (2005). Meat sharing for coalitional support. Evolution and Human Behavior , 26(2), 137-157. Peterson, M. N. (2004). An approach for demo nstrating the social legitimacy of hunting. Wildlife Society Bulletin, 32(2), 310-321. Peterson, M. N., Hansen, H. P., Peterson, M. J., & Peterson, T. R. (2010). How hunting strengthens social awareness of coupled human-natural systems. Discussion Form: Wildlife Biology Practicum , 6(2), 127-143. Piekarski, L.B. (2013). Random digit telephon e sampling methodology North America [White Paper]. Survey Sampling Internati onal. Retrieved March 24, 2015 from http://www.surveysampling.com/ssi-med ia/Corporate/White%20Paper%202012/SSI- Random-Digit-Sampling-in-NA.image. Pollan, M. (2006). The omnivore's dilemma: a natural history of four meals. New York, NY: Penguin Books. Quandt, S. A., Arcury, T. A., Bell, R. A., McDonald, J., & Vitolins, M. Z. (2001). The social and nutritional meaning of food shar ing among older rural adults. Journal of Aging Studies, 15(2), 145-162. Rastogi, S., Johnson, T. D., Hoeffel, E. M., & Drewery, M. P. (2011). The black population: 2010. 2010 U.S. Census Briefs. C2020BR-06. Responsive Management & The National Shootin g Sports Foundation (RM & NSSF). (2011). American attitudes toward hunting, fishing, and target shooting 2011. National Shooting Sports Foundation, Inc. Newton, CT. Richardson, R. B. (2010). Ecosystem services and food security: Economic perspectives on environmental sustainability. Sustainability , 2(11), 3520-3548. Robison, K. K., & Ridenour, D. (2012). Whither the love of hunting? Explaining the decline of a major form of rural recreation as a consequence of the rise of virtual entertainment and urbanism. Human Dimensions of Wildlife , 17(6), 418-436. Roderick, C., Carr, M., & Zundel, P. (2009). Br eaking bread together: A tradition to foster learning and community. Teaching Showcase Proceedings. Roth, H. H., & Merz, G. (Eds.). (1996). Wildlife resources: a global account of economic use. New York, NY: Springer. Rozin, P. (1999). Food is fundamental , fun, frightening, and far-reaching. Social Research, 9-30. Rudolph, B.A. (2005). Population biology, abundance, and management history of Michigan white-tailed deer. Paper presented at the Michigan Society of American Foresters fiForests and Whitetails-Striving for Bala nce.fl St. Ignace, Michigan, 9-10 June. Ryan, E., & Shaw, B. (2011). Improving hunter recruitment and retention. Human Dimensions of Wildlife, 16(5), 311-317. Sauer, P. R. (1984). Physical characteristics. In Halls, L. K. (ed). White-Tailed Deer: Ecology and Management. Harrisburg, PA: Stackpole Books. Severinghaus, C.A. (1949). The liveweight-dressed weight and liveweight-edible meat relationships (in deer). New York State Conservationist , 4(2): 26. Shanks, J. M. (1983). The current status of computer-assisted telephone interviewing: Recent progress and future prospects. Sociological Methods & Research , 12(2), 119-142. Simmel, G. (1997). Simmel on culture: selected writings (Vol. 903). David Frisby, & Mike Featherstone (Eds.). Thousand Oaks, CA: Sage. Smil, V. (2002). Eating meat: Evolu tion, patterns, and consequences. Population and Development Review , 28(4), 599-639. Stanford, C. B., & Bunn, H. T. (Eds.). (2001). Meat-eating & human evolution New York, NY: Oxford University Press. StataCorp. (2013a). Stata Statistical Software: Re lease 13 [computer software] . College Station, TX: StataCorp LP. StataCorp. (2013b). Stata survey data reference manual: release 13. College Station, TX: StataCorp LP. State Of New Jersey 216th Legislator, Assembly Bill No. 3039, Introduced Marched 24, 2014, Sponsored by Caroline Casagrande. Stedman, R. (2012) Sociology of wildlife management . In Decker, D. J., Riley, S. J., & Siemer, W. F. (Eds.). Human dimensions of wildlife management (2nd ed). Baltimore, MD: John Hopkins University Press. Stedman, R. C., & Decker, D. J. (1996). Illu minating an overlooked hunting stakeholder group: nonhunters and their interest in hunting. Human Dimensions of Wildlife, 1(3), 29-41. Stedman, R.C., & Heberlein, T.A. (2001) . Hunting and rural socialization. Rural Sociology 66(4), 599-617. Stransky, J.J. (1984). Hunting the whitetail. In Halls, L. K. (ed). White-Tailed Deer: Ecology and Management. Harrisburg, PA: Stackpole Books. Thogmartin, W. (2006). Why not consider the commercialization of deer harvests? BioScience, 56(12), 957. Tidball, K. G., Tidball, M. M., & Curtis, P. (2013). Extending the locavore movement to wild fish and game: questions and implications. Natural Sciences Education, 42(1), 185-189. Titus, K., Haynes, T. L., & Paragi, T. F. (2009). The importance of moose, caribou, deer, and small game in the diet of Alaskans. In Ingestion of Lead from Spent Ammunition: Implications for Wildlife and Humans. Boise, ID: The Peregrine Fund. Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response . New York, NY: Cambridge University Press. Troldahl, V. C., & Carter Jr, R. E. (1964). Random selection of respondents within households in phone surveys. Journal of Marketing Research, 71-76. U.S. Census Bureau. (2010). State & county Quickfacts: Michigan, USA. Retrieve March 15, 2015, from http://quickfacts.census.gov. U.S. Census Bureau. (2011). Urban area criteria for the 2010 Census. Federal Register 76(164) [Docket Number 110714393Œ1393Œ01]. U.S. Department of Agriculture (USDA) a nd U.S. Department of Health and Human Services (HHS). (2010). Dietary Guidelines for Americans (7th ed). Washington, DC: U.S. Government Printing Office. U.S. Fish and Wildlife Service (USFWS). (2012) . 2011 national survey of fishing, hunting, and wildlife-associated recreation: National overview . Preliminary Findings from the 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. . Vaske, J. J. (2008). Survey research and analysis: Applications in parks, recreation and human dimensions. State College, PA: Venture Publishing. VerCauteren, K. C., Anderson, C. W., Van Deelen, T. R., Drake, D., Walte r, W. D., Vantassel, S. M. & Hygnstrom, S. E. (2011). Regul ated commercial harvest to manage overabundant white-tailed deer: An idea to consider? Wildlife Society Bulletin , 35, 185Œ194. Van Vliet, N., & Mbazza, P. (2011). Rec ognizing the multiple reasons for bushmeat consumption in urban areas: a necessary step toward the sustainable use of wildlife for food in central Africa. Human Dimensions of Wildlife , 16(1), 45-54. Watland, K. H., Hallenbeck, S. M., & Kresse, W. J. (2008). Breaki ng bread and breaking boundaries: A case study on increasing organizational learning opportunities and fostering communities of practice through sharing meals in an academic program. Performance Improvement Quarterly, 20(34), 167-184. Whittaker, D., Vaske, J. J., & Manfredo, M. J., (2006). Specificity and the cognitive hierarchy: Value orientations and the acceptability of urban wildlife management actions. Society & Natural Resources , 19(6), 515-530. Wilcox, S. W. (1976). Deer production in th e United States 1969-1973. Tempe, AZ: Arizona State University. Wilkie, D. S., & Carpenter, J. F. (1999). Bush meat hunting in the Congo Basin: an assessment of impacts and options for mitigation. Biodiversity & Conservation , 8(7), 927-955. Wise, A. (2011). Moving food: gustatory commensality and disjuncture In everyday multiculturalism. New Formations 74, 82-107. Zar, J. H. (1996). Biological statistics. Upper Saddle River, NJ: Prentice Hall. Zhang, L., Hua, N., & Sun, S. (2008). Wildlife tr ade, consumption and conservation awareness in southwest China. Biodiversity and Conservation, 17(6), 1493-1516. Zinn, H. C., Manfredo, M. J., & Barro, S. C. (2002). Patterns of wildlife value orientations in hunters families. Human Dimensions of Wildlife, 7(3), 147-162.