Declining Deer Hunters

Declining Deer Hunters Wisconsin s gun deer hunter numbers are continuing to decline Applied Population Laboratory Richelle Winkler & Rozalynn Klaas February 2011 Summary The deer herd in the State of Wisconsin is largely kept in check by private hunters who purchase licenses and kill deer each fall. Not only is hun ng vital to wildlife management efforts, but it is also an important cultural ac vity through which people become intricately connected to the natural world. However, the number of deer hunters in the state has declined in recent years, causing concern about the future of the herd, the sport, and conserva on efforts. The number of gun deer hun ng licenses sold to Wisconsin residents declined from 644, 991 in 2000 to 602,791 in 2010. This is a decline of 6.5% in ten years, despite the fact that 10 and 11 year old hunters were added for the first me in 2009 and 2010. Declines have been most stark among males age 25-44, who have (in the recent past) hunted at high rates and killed a large number of deer. This report is the result of a study undertaken by the at the University of Wisconsin-Madison at the request of the Wisconsin Department of Natural Resources Wildlife Division. It is a collabora ve project between these two organiza ons with the goal of be er understanding how the popula on of the state s hunters is changing over me and to project future deer hunters. The study takes a demographic approach inves ga ng par cipa on in deer hun ng by age over me. Despite the fact that the number of female hunters is increasing and the ac vity is becoming more popular among younger females, the number of female hunters remains too small to make up for the decline in male hunters. In 2010, 91% of gun deer licenses sold were to males. For this reason, this report focuses on understanding declines in the male gun deer hunter popula on. Wisconsin Resident Gun Deer Hunters, 2000-2010 700,000 Females Other Males Males Age 25-44 600,000 500,000 400,000 300,000 200,000 100,000 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 We specifically examine the effects of me period, age, and genera onal differences on hunter par cipa on rates. Regarding me period, we find that par cipa on rates dropped markedly between 2001 and 2002 with the discovery of CWD. More importantly, rates con nued to drop between 2004 and 2009 across all ages and genera ons, except those over age 65 who are hun ng at higher rates than they have in the past. S ll, age plays an important role in people s likelihood to hunt, with par cipa on rates dropping off significantly a er about age 65. At the same me, genera onal differences help to determine hunter par cipa on rates. Males born during the Baby Boom (1946-1965) have been more likely to hunt than younger cohorts, regardless of age. Overall, recent declines in hunter numbers have occurred through two processes. First, rela vely few young men born since 1980 (the Millenial Genera on) have been recruited into hun ng. Second, reten on rates year to year among hunters age 30-55 have been rela vely low over the last decade. Projec ons of future hunters suggest that the male gun hunter popula on will decline more drama cally over the next ten to twenty years. We provide three future scenarios for male gun deer hunters using two different methodological approaches and making different assump ons about future par cipa on rates and how they will vary by age and cohort. Overall, the models suggest that in 2020, the number of male gun hunters will drop to about 480,000 (compared to 549,505 in 2010). If current pa erns con nue, the number could drop to 400,000 or fewer by 2030. Finally, a geographic analysis of the coun es in which hunters reside indicates that most hunters live in urban areas, but hunter par cipa on rates are highest in more rural areas of the state and par cularly high in northern Wisconsin. Deer hunter reten on rates among middle aged males have shown more decline in the eastern part of the state than in the west, with the most stark decline occurring in northeastern and southeastern Wisconsin. The propor on of 20-24 year olds who hunt (recruitment) declined in almost every county between 2000 (Genera on X) and 2009 (Millenials). This decline was greater in eastern Wisconsin than in the western part of the state. 1

Hunter Par cipa on Rates over Time In order to understand how hunter numbers are changing, it is important to consider changes in the propor on of all Wisconsin males who deer hunt (hunter par cipa on rates). We calculate par cipa on rates by single year of age over me to examine the propor on of all Wisconsin males of a certain age who purchased deer hun ng licenses in a par cular year. Isola ng these rates by age and examining them annually allows for a comparison of how par cipa on has changed over me. In the chart below lighter colors represent earlier years, and darker blues represent more recent years, except for 2002 which is shown in red because this was the year that Chronic Was ng Disease (CWD) was discovered in the Wisconsin herd. The chart can be read in two ways. One can follow the change in par cipa on over me by age by comparing up and down the ver cal axis at a specific age. For example, 33.5% of 40-year olds hunted in 2000, but only 25.5% of 40-year olds hunted in 2009. Alterna vely, one can follow a cohort of hunters over me by looking at a par cular age in one year in comparison to the par cipa on rate one year older and one year later. For instance, the cohort of hunters who were age 39 in 2000 (born in 1961, later Baby Boomers) were the most likely people to hunt in 2000 with a 34% par cipa on rate. In 2001, these same people were age 40 and 33% hunted. In 2009, the same cohort was 48 years old and 28% hunted. Despite this cohort s declining par cipa on, they were s ll the most likely group to hunt in 2009. Comparing by age, par cipa on rates declined steadily at almost every age between 2000 and 2009. Hunters over age 65 were the excep on, experiencing increasing rates. Males age 25-44 experienced the most stark declines in par cipa on. In 2000, 31% of Wisconsin males age 25-44 purchased gun deer hun ng licenses in comparison to only 23% in 2009. At the same me the propor on of Wisconsin males who are recruited into hun ng at a young age has been declining-- 29% of 15 year old males gun hunted in 2000 compared to only 24% in 2009. In summary, this chart demonstrates that: Par cipa on rates vary by age, dropping off markedly a er age 65. Par cipa on rates are declining over me at all ages under 65, and increasing moderately at age 65 and over. Following cohorts over me, a er age 20 par cipa on rates tend to decline very slightly each year over me. Male Gun Hunter Participation Rates, 2000-2009 0.350 0.325 0.300 0.275 0.250 0.225 0.200 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0.175 0.150 0.125 0.100 0.075 0.050 12 15 18 21 24 27 30 33 36 39 42 45 Age 48 51 54 57 60 63 66 69 72 75 78 2

Aging Hunters The chart on the previous page shows that for males, par cipa on tends to peak at middle ages, then to drop off steadily a er about age 65. When people are more likely to hunt at certain ages in comparison to others, hunter numbers could shi drama cally as the composi on of the total popula on of Wisconsin shi s in age. For example, in 2009, 40% of Wisconsin resident hunters were between ages 43 and 63 (the Baby Boom genera on). What will happen to the number of Wisconsin hunters as these hunters get older and reach the ages where par cipa on rates tend to drop off? The combina on of a large number of poten al hunters (people overall) in the Baby Boom genera on and rela vely high rates of par cipa on for Baby Boomers has contributed to large numbers of hunters over the last several years. Can we expect this to con nue? Age 80 76 72 68 64 60 56 52 48 44 40 36 32 28 24 20 16 12 Age Structure: Wisconsin Deer Hunters (2009) 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 Number of Wisconsin Resident Male Gun Deer Hunters The chart at le shows the age structure of Wisconsin resident male gun deer hunters in 2009. The bulge in hunters age 43-55 (late Baby Boomers) is drama c. There are about 154,000 hunters in this twelve year age range, whereas there are only 105,400 hunters following them at ages 24-36. This is a difference of over 48,000 hunters. What kind of effect will this age bulge have on the number of future hunters as the Baby Boomers grow older? One of the reasons for projected declines in the hunter popula on over the next ten to twenty years, is the aging of hunters. S ll, the effect of aging may be moderated if the Baby Boom genera on remains more likely to hunt as they reach older ages than the genera ons who came before them. The Baby Boomers are different than their predecessors in many ways, including that they are more wealthy, more healthy, and par cipate more in outdoor recrea on. Of greater concern than the aging of the Baby Boomers are the considerably smaller cohorts of younger hunters and weak recruitment into hun ng at younger ages. These factors are already having significant impacts on the hunter popula on and should be expected to have more drama c effects in the coming years. Age effects are only part of the story. Par cipa on rates have declined steadily since 2000, controlling for changes in age. The chart at right shows the difference between the number of actual hunters in 2005 and in 2009 and the number of hunters there would have been if par cipa on rates by age had remained constant since 2000. This what might have been type of scenario shows the number of hunters that have been lost due to declining par cipa on rates over me and by cohort, or those lost that are not due to changes in the age structure. If age-specific par cipa on rates had not declined, then there would have been about 52,000 more male hunters in 2009 than there were in 2000. Instead, there were 54,000 less, for a total difference of over 105,000 hunters lost due to change over me and weak recruitment. All of this suggests that although age effects are important, they do not adequately explain recent hunter decline. Subsequently, popula on projec ons based on constant rate share methods (such as the constant rate model shown later in this report) should be interpreted skep cally. Difference between Number of Actual Hunters and Expected Hunters based on 2000 Participation Rates by Age -100,000 One of the reasons for projected declines in the hunter population is the aging of hunters, especially the large cohorts of the Baby Boom generation. Yet age is only part of the story. Participation rates have declined steadily since 2000, controlling for changes in age. 20,000 0-20,000-40,000-60,000-80,000 Hunter Population Controlling for Age Effects, 2000-2009 2005 2009-120,000 3

Hunter Recruitment and Reten on Male hunters in Wisconsin generally start hun ng between age 10 and 14 (recruitment). A er age 14, the number of hunters depends on the extent to which the already ini ated con nue to hunt (reten on). People s experiences, their likelihood to be recruited into hun ng and to con nue to hunt over me vary by genera on. We examine such genera onal influences by analyzing hunters by the year they reached hun ng age and following each group (cohort) over me. Are people who came of age in some years more likely to hunt than people who reached hun ng ages at other mes? Genera onal (or cohort) effects stem from influences of the past that have affected certain cohorts differently than others. For instance, the social, economic, and environmental condi ons of the post- World War II period in the United States influenced the developmental years of the Baby Boom genera on, which in turn might influence the likelihood of that genera on to hunt. Percent of People who Hunted d by Age Group and Year 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 1980 1985 Recruitment of New Hunters: 1980 2006 1980 1985 1991 1996 2001 1991 1996 Later Cohorts Baby Boom Cohorts 2001 2006 Differences between cohorts begin with hunter recruitment at younger ages. The chart at le shows the percent of the Wisconsin popula on who hunted between 1980 and 2006. The Baby Boom cohorts (highlighted in red) were much more likely to hunt at younger ages than subsequent genera ons that have followed. Since 1980, in comparison to younger genera ons, Baby Boomers have been more likely to hunt across their life me so far, regardless of age. In other words, evidence suggests that Baby Boomers were the last highly recruited cohort of hunters. 0.0% 18 24 Age Groups Data are from National Survey of Fishing, Hunting, and Wildlife related Recreation conducted by US Census Bureau for US Fish and Wildlife Service; State of Wisconsin ; 1980, 1985, 1991, 1996, 2001, and 2006. In addi on to recruitment, we must examine the reten on of hunters as they age forward in me. Do they con nue to hunt or drop out? Do new people start hun ng? One way to understand hunter reten on is to compare the number of people in a hun ng cohort who purchased licenses in 2000 to the number who purchased licenses nine years later in 2009. The chart at right shows the propor on of hunters who con nue to hunt. For the younger cohorts, only 76% of those who hunted in 2000 con nued to hunt in 2009. Once in their 20s, closer to 90% con nued. Par cipa on dropped off more for the cohorts in their 30s, 40s, and 50s, and most drama cally for cohorts entering their 60s, 70s and 80s. 25 34 % 2000 Hunters Remaining in 2009 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Hunter Retention by Cohort (2000-2009) 12-15 16-19 20-24 25-29 30-34 35-39 40-45 45-49 50-54 55-59 60-64 65-69 70plus Age in 2000 (Hunters are 9 years Older at end of Period in 2009) Another way to analyze hunter reten on by cohort is to examine what demographers refer to as survival ra os. These ra os compare the number of hunters at a certain age in one year to the number of hunters one year older the next year. If that ra o comparison is greater than 100%, then that cohort added new hunters over the year. If the ra o is less than 100%, then that cohort lost hunters in the course of the year. We Average Annual Hunter Retention by Age, 2004-2009 135% average annual ra os experienced between 2004 and 2009 for each set of ages in order to examine the average survival 130% of hunters from one year to the next between specific ages. 125% This logic fuels the cohort survival projec on model shown 120% later in this report. 115% 110% 105% 100% 95% 90% 85% 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 Age in Prior Year i i Between age 15 and 23, a significant number of the boys who tried hun ng decide it is not for them. Between age 25 and 35 about 99.5% con nue each year. However, a er age 35 hunter reten on gradually declines. About 2% drop out each year age 35-63. A er age 63, 5-10% or more drop out each year. S ll, its important to consider that these survival ra os may vary across cohorts. In par cular, evidence suggests that Baby Boomers will be more likely to con nue to hunt as they grow older than the older cohorts shown here because they already hunt more, are healthier, and are wealthier than any cohort that has come before. 4

Age, Period, Cohort Analysis Examining pa erns of hunter par cipa on by me period, age, and cohort reveals several factors poin ng to the fact that the hunter popula on is declining. These declines are somewhat related to the changing age structure of the Wisconsin popula on, yet par cipa on rates for male gun hunters have declined at almost every age, sugges ng that the me period is a more important factor in hunter decline. In addi on, cohort groups of hunters tend to lose par cipa on over me, as a propor on of hunters drop out each year. Evidence suggests that genera onal differences are an important explana on for changing numbers of hunters as well. In sum, hunter numbers have been declining due to a combina on of me period, age, and cohort effects that work in conjunc on with one another. Age effects are rela vely straigh orward and related to life course events that tend to occur at par cular ages (like going away to college, having children, or re ring) and physiological changes that occur as our bodies mature. Time period effects could represent specific events that occur at a certain moment in me, like the discovery of CWD in the Wisconsin herd, or more gradually occuring biological, social, economic, poli cal, and cultural changes that have transpired over the last few years (i.e., programs promo ng youth hun ng, habitat change, or economic recession). Cohort effects refer to experiences of different genera ons and reflect social and cultural transforma ons that occured in the past or that have occurred very gradually over a long period of me and have impacted different age groups in different ways (such as urbaniza on and improved medical care that extends healthy life). Thinking about changes in the deer hunter popula on in these ways offers a first look into how and why the popula on is changing and how it might con nue to change over the next several years. Age Effects 0.3 0.2 0.1 0.0 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80-0.1-0.2-0.3-0.4-0.5-0.6-0.7 Period Effects 0.3 The complicated thing about an age-period-cohort analysis is that these factors work simultaneously making it difficult to separate effects caused by each individual component. In other words, it is difficult to tell whether it is a group s age at the moment, something about the me period, and/ or a cohort issue that is affec ng par cipa on rates. The previous charts and discussion have a empted to dis nguish these effects; yet, the three con nue to confound one another. In order to isolate the effects of age, period, and cohort and to individually examine each, we implement an Age- Period-Cohort (APC) sta s cal analysis aimed at understanding how each of these factors works independently of the others to impact the Wisconsin deer hun ng popula on. Using data from 2000 to 2009 on the number of licenses sold by single year of age (12 to 80+), we es mate the independent effects of age, period, and cohort on changes in the Wisconsin male gun deer hunter popula on. 0.2 0.1 0.0-0.1-0.2-0.3-0.4-0.5-0.6-0.7 0.3 0.2 0.1 0.0-0.1-0.2-0.3-0.4-0.5-0.6-0.7 1932 1934 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Cohort Effects 1936 1938 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Baby Boomers The charts at le show the results of this analysis by likelihood to purchase a hun ng license. Values below the zero axis represent decreased likelihood of hun ng at that age, cohort, or me period. Values above the zero axis represent increased likelihood to hunt. The ver cal scale for each chart is the same to facilitate comparing age, period, and cohort effects to one another. These results by age, period, and cohort inform the APC projec on model shown later in this report. Period effects demonstrate a consistent decline in the likelihood to hunt across all age and cohort groups over me. Age and cohort effects are stronger than period effects (farther from zero). Focusing on age, males are most likely to hunt as teens. A er age 65, the likelihood of men to hunt decreases steadily. Cohorts who started to hunt 1952 to 1986 are most likely to hunt, and par cularly those who came of age 1970-1977 (the later cohorts of the Baby Boom genera on who were born 1958-1965). Genera ons following the Baby Boomers have been less likely to hunt. In par cular, recruitment of cohorts coming of age since 1990 has been weak. These are the Millenial genera on. Note, however, that the effect of cohort on genera ons born prior to 1940 is difficult to interpret because we do not have observa ons of these cohorts before they were age 60 and already at older ages. They may have already been less likely to hunt due to old age, rather than cohort. 5

Future Deer Hunter Projec ons: Data and Methods The two sources of data used in genera ng projec ons are (1) counts of Wisconsin resident gun deer hun ng license purchases by single year of age and sex provided by the Wisconsin Department of Natural Resources Wildlife Management for the years 2000 to 2009, and (2) es mates and forecasts of the total popula on of the State of Wisconsin by single year of age and sex provided by Emeritus Professor Paul Voss at the. These forecasts were created using a cohortcomponent method of forecas ng in May 2007. We include three different projec on models (scenarios) to project the number of future Wisconsin resident male gun deer hunters. Two of these models (Constant Rate and APC) follow a share projec on methodology, wherby a subset of the popula on (in this case, deer hunters) is expressed as a propor on of the total popula on (here, the State of Wisconsin). Hun ng rates are calculated by dividing the number of male hunters of a certain age by the Wisconsin male popula on of the same age. For instance, 28% of all 48 year old males in Wisconsin in 2009 were gun deer hunters. This approach offers insight into how changes in Wisconsin s popula on composi on may affect future numbers of hunters in the coming years. The Constant Rate model assumes that age-specific par cipa on rates from 2009 will remain constant each year into the future. These 2009 rates are then applied to a forecast of the total Wisconsin male popula on by age to generate a projec on of the future number of male gun deer hunters. This model assumes that any change in the number of future hunters will be a ributable to changes in the age structure of the base popula on (the total male Wisconsin popula on). The approach is well-suited for situa ons in which it is believed that par cipa on rates by age will remain stable over me, but would produce an unrealis c projec on of future hunters if par cipa on rates change over me. In this case, the current structure of the hunter popula on with small cohorts of younger hunters and our age, period, and cohort analysis all suggest that par cipa on rates will con nue to decline. For these reasons, the share model is not likely a realis c projec on of future hunters. Instead, this model might best be used as a gauge against which to compare other projec on models. The Age-Period-Cohort (APC) model also follows a share approach, but rather than assuming 2009 rates will remain constant, it applies sta s cal es mates of the likelihood of hun ng by age, period, and cohort (as shown in the charts on page 5) to construct future par cipa on rates. Like the Constant Rate share model, it then mul plies these rates mes the projected future Wisconsin male popula on by single year of age, cohort group, and me period. First, the effect of every age (12 to 80+), period (2000 to 2009), and cohort (1932 to 2009) is es mated using Yang et al. s (2008) i intrinsic es mator sta sical approach in Stata so ware. We then transform the likelihood es mates and combine them to generate expected future par cipa on rates by age, period, and cohort. The age effect is assumed to remain stable into the future, the period effect is assumed to con nue to decline at the same average pace that it has over the last five years, and the effect of cohorts entering hun ng star ng in 2008 is assumed to be the average of the 1992 to 1997 cohorts. The APC model assumes that future par cipa on rates will be affected by age, period, and cohort effects and it considers the changing age structure of the total Wisconsin male popula on. Note: this is a new method that has not been well tested, but theore cally it should provide a realis c projec on of future hunters. In addi on to the share models, we also provide a Cohort Survival projec on model. This model follows a different logic. Rather than using the total Wisconsin male popula on as a base, this approach uses that current (2009) hun ng popula on as a base. We start with 2009 hunters and age them forward over me. Each year, we assume that a certain propor on of hunters will survive to hunt again the next year, following the average survival ra os by age that were observed 2004-2009. Survival ra os depict changes in the hunter popula on, year to year and age to age. They measure the effects of people recruited into and dropping out of hun ng. The ra os are calculated for several pairs of years and then an average of reten on ra os between 2004 and 2009 is calculated for each age. For example, the average ra o for 13 to 14 year old male gun hunters is 1.054. This means that the number of 14 year old hunters is on average 5.4% larger each year than the number of 13 year old hunters the previous year. These ra os are shown in the Average Annual Reten on by Age chart on page 4. Only the survival ra os for the youngest ages (12 to 13 and 13 to 14) show increases; all other ra os show decreases in the number of hunters as cohorts age over me. The survival ra o model captures the effects of age, recent period changes, and to a lesser extent genera onal (or cohort) trends because it follows cohorts of hunters over me. This model assumes that the average rates of transfer into and out-of hun ng by cohorts at par cular ages in recent years will con nue into the future. The most significant point of error following this approach is in projec ng the number of new 12-year old hunters who will be recruited into hun ng each year. To make this projec on, we assume that the percent of all 12-year olds who hunt in 2010 will be the average of this propor on 2004-2009 and that this propor on will steadily decline over me at a similar to pace to what it has over the last several years. This method should provide a realis c projec on of future hunters. i Yang, Y., W. J. Fu, S. Schulhofer-Wohl, and K.C. Land. 2008. The intrinsic es mator for age-period-cohort analysis: What it is and how to use it. American Journal of Sociology 113 (6): 1697-1736. 6

The Future of Deer Hunters in Wisconsin: Projec ons Projec ons suggest that the number of male gun deer hunters will decline considerably over the next several years. Although they follow very different methodological approaches, both the Cohort Survival and APC models offer remarkably similar results. Both suggest that hunter numbers should be expected to decline so that in 2020, the number of male gun hunters would drop to about 480,000 (compared to 549,505 in 2010). By 2030, these models predict that the number could drop to 400,000 or fewer. If hunters con nue to drop out of hun ng and new young hunters enter hun ng at rates similar to what they have in the recent past, then the Cohort Survival model should reasonably predict the number of future male gun hunters. The APC model assumes that par cipa on rates of the Baby Boom genera on will remain rela vely high as this group ages un l at least age 70, but that declining period effects and lower par cipa on rates of younger cohorts will lead to declining par cipa on rates across all ages over me. The Constant Rate model assumes that par cipa on rates will not con nue to decline as they have since 1980, but rather that par cipa on rates will remain stable in the future at the same rates experienced in 2009. This model should be considered as a point of comparison with the other models, rather than a realis c scenario of future hunter popula on, unless there is a drama c recruitment of young and middle age hunters within the next five years. 650,000 Gun Deer Hunter Projection: 2000-2030 Includes Males only Age 12 and over Year Observed Constant Survival APC 2000 597,025 2005 554,223 2009 543,479 2010 541,360 538,457 538,190 2015 548,291 511,241 514,784 2020 552,208 479,254 482,886 2025 552,965 443,594 441,347 2030 550,829 405,605 394,334 600,000 550,000 500,000 450,000 400,000 350,000 Constant Rates Projection APC Projection Cohort Survival Projection Observed Hunters 300,000 12,000 10,000 8,000 Age Structure of Gun Deer Hunters, 2030 Includes Males only Age 12 and over Constant Rates Projection APC Projection Cohort Survival Projection The chart at le shows the projected number of hunters in 2030 by age for each of the different models. The Cohort Survival and APC models produce very similar results, while the Constant Rate model produces a much younger hunter age structure. 6,000 4,000 2,000 0 The chart reveals that the most realis c projec ons will generate a scenario in which the hunter popula on is considerably older than it is today. By 2030, the APC and Cohort Survival models project that 28-30% of male gun deer hunters will be age 60 and over. This is important because it suggests the need for more accessible hun ng opportuni es for an aging popula on. 7

This sec on examines where Wisconsin resident deer hunters live in order to be er understand the changing male gun deer hun ng popula on. The map on the le shows a dot for every thirty hunters, taken from WDNR license data that includes hunter addresses in 2009. Hunters are clustered in the major urban centers of the state. In fact, 56% of all male gun deer hunters lived in metropolitan coun es in 2009, with 21% living in Dane (25,739 hunters), Waukesha (24,945), Milwaukee (21,278), Brown (20,617), and Marathon (20,394) coun es alone. At the same me, deer hun ng is a more popular ac vity in the more rural parts of state and especially in the north. The map on the right shows hun ng par cipa on rates for males age 15 and over by county in 2009. The total number of male gun deer hunters residing in each county is divided by an es mate of the total male Wisconsin popula on at these ages living in each county. So, while a large number of people in the most urban areas hunt, it is s ll a small percentage of the total popula on-- only 5.7% of Milwaukee county males deer hunted in 2009. The reverse is true for more rural areas where 50% or more of males deer hunt. The culture of hun ng is s ll alive in more rural areas of the state. Par cipa on rates are higher in western Wisconin than in the eastern part of the state. We might expect par cipa on to be stronger in the southwest than the southeast because it is considerably more rural. However, par cipa on rates also tend to be higher in the nortwest than the northeast, despite the fact that the northeast is at least as rural as the northwest. Notes: Because these data are based on DNR license sales, American Indian hunters (especially prevalent in Menominee, Sawyer, Vilas, Forest, and Ashland coun es) are not included in the numerators of these figures. Also, all of the maps showing county-level par cipa on rates rely on US Census Es mates for county popula on by age and sex (vintage 2009) for the denominators. These data are the best currently available by age and sex; however, they may be somewhat imprecise, especially in coun es experiencing recent changes in age-specific migra on. Finally, the census es mates include the popula on living in prisons. This ar ficially reduces the 20-24 year old par cipa on rates in Waushara, Jackson, Columbia, Sheboygan, Monroe, and Winnebago Coun es and affects the change in recruitment rate in Waushara County. For these reasons, par cipa on rates by county (par cularly at ages 20-24) should be interpreted with some cau on. 8 Where do Deer Hunters Live? A Geographical Analysis Lake Michigan Minnesota Illinois Michigan Lake Superior Price Clark Rusk Forest Taylor Barron Burnet Buffal o Washburn Crawford Trempealeau Pepin Wisconsin Resident Male Gun Hunters 2009 1 Dot = 30 Hunters Applied Population Lab Lake Michigan Minnesota Illinois Michigan Lake Superior Price Clark Dane Polk Vilas Grant Iron Rusk Bayfield Sawyer Sauk Oneida Forest Douglas Taylor Dunn Marathon Rock Marinette Dodge Oconto Wood Barron Jackson Lincoln Ashland Burnett Juneau Monroe Vernon Portage Chippewa Adams Shawano Buffalo Langlade Pierce St. Croix Columbia Washburn Waupaca Brown Lafayette Richland Eau Claire Crawford Jefferson Fond du Lac Waushara Outagamie Walworth Florence Waukesha Manitowoc La Crosse Winnebago Calumet Sheboygan Marquette Trempealeau Door Racine Pepin Washington Lake Kewaunee Kenosha Ozaukee Milwaukee 51% 36.6% 46.9% 39.5% 40.3% 30.9% 53.9% 12.2% 37.7% 49% 53% 31.7% 44.1% 44.3% 34.3% 46.9% 42.2% 58.9% 40.3% 45.9% 55.8% 42.3% 39.5% 27.9% 43.4% 45.8% 41.9% 36.7% 31.8% 42% 31.5% 43.6% 35.7% 36.2% 42.7% 33.4% 34.5% 28.9% 41.4% 50.9% 31.7% 18.8% 54.6% 34.2% 26.7% 24.7% 36.7% 33.4% 26.3% 34.6% 38.9% 25.8% 24.7% 15.5% 21.9% 13.9% 19.8% 19.3% 40.3% 23.4% 44.4% 24.9% 30.4% 42.5% 36.2% 9.8% 12.7% 5.7% 49.8% 14.7% 28.8% Applied Population Lab Male Gun Deer Hunter Participation Rate (2009) 5.7% to 14.9% 15.0% to 24.9% 25.0% to 34.9% 35.0% to 44.9% 45.0% to 58.9% Age 15 and Over Male Gun Hunter Participation Rates

Applied Population Lab Applied Population Lab Applied Population Lab Reten on and Recruitment Struggles are more Serious in Eastern Wisconsin We ve demonstrated that the number of deer hunters in Wisconsin is declining due to lower reten on of middle aged hunters and also because of rela vely low recruitment rates of young male hunters, par cularly those in the Millenial genera on. Here, we examine the geographic distribu on of these factors mapping them by county. The map on the previous page shows that male gun deer hunter par cipa on rates are generally lower in the eastern part of the state than the west. The analysis on this page shows that reten on of middle aged hunters and recruitment of young males into hun ng have also been lower in eastern Wisconsin over the last decade. Reten on of Middle Aged Hunters The map at right shows county-level declines in hunter par cipa on rates among the cohort of male gun deer hunters who were age 30-49 in 2004 (and then age 35 to 54 in 2009). This group includes the la er half of the Baby Boom genear on who have the highest deer hun ng par pa on rates of any cohort of Wisconsin hunters. Darker grays depict more decline. For instance, in Forest County in 2004, 61.2% of this cohort of men hunted. Five years later in 2009, only 49.6% of the men in this cohort hunted (decline of 11.6%). Par cipa on declined most in northeastern Wisconsin, and in coun es with significant re rement migra on and lakefront development. Numerically, eastern coun es generally lost more hunters, while western Wisconsin generally retained its hun ng base. Hunter Recruitment Turning to recruitment of young hunters. The map below le shows par cipa on rates in 2009 at ages 20-24, represen ng current recruitment levels. We examine ages 20-24 because by this age, a hunter iden ty is usually estabished and hunters generally con nue to hunt for years to come. This map shows that par cipa on is highest in the more rural and western areas of the state. In several coun es, about half of young men hunt. The map below right shows change in par cipa on rates for 20-24 year olds between 2000 and 2009. This effec vely compares recruitment of the Millenial genera on (age 20-24 in 2009) to prior recruitment of Genera on X hunters (age 20-24 in 2000). Almost everywhere recruitment has declined, but a few coun es (shown in green) have increased young adult par cipa on. Reading these maps together, we can Recruiting Young Hunters Age 20-24 Recruiting Young Hunters Age 20-24 see that in St. Croix County, for Minnesota Minnesota instance, the par cipa on rate Lake Superior Lake Superior among 20-24 year olds in 2009 Bayfield Bayfield was 28%. This represents a Douglas 37.6% Douglas -7.9% 22% 1.4% Michigan Michigan Ashland Iron Ashland Iron decline of 14% from 2000, 27.7% 40% -1.8% 7.4% Vilas Vilas 20.3% -20.5% when par cipa on was 42% Washburn Burnett Sawyer Washburn Sawyer 38.9% Burnett 40% 35.3% Florence -28.9% -2.3% Florence -10% 28.7% -22.5% Price Oneida Price Oneida (28%+14%= 42%). Polk Barron Rusk 40.5% 39.7% 48.5% St. Croix 28% Pierce 16.8% Pepin Dunn 12.9% 42.9% Buffalo 51.2% Chippewa Eau Claire 10.4% Trempealeau 51% Male Gun Deer Hunter Participation Rate (2009) Age 20-24 3.3% to 14.9% 15.0% to 24.9% 25.0% to 34.9% 35.0% to 44.9% 45.0% to 57.0% 34.6% La Crosse 10.3% Grant 14.3% Clark Jackson 25% Vernon 49.2% Crawford 30.1% Taylor 57% 52.1% Monroe 34.7% 46.5% 28.1% Richland 36.3% Wood 30% Juneau 25.7% 38.2% Lafayette 35.4% Marathon 29% Sauk 27.6% Lincoln 36.1% Adams 24.2% Portage 11.5% 27.5% Waushara Columbia 25.5% Dane 5.3% Langlade 41.2% 29.1% Forest Shawano 37.1% Waupaca 39.6% Marquette 43.6% Lake 44.6% 32.8% Rock Walworth 15.3% 6.8% Illinois Dodge Marinette 28% Lake Michigan Oconto 40.6% Outagamie Winnebago 14.2% Fond du Lac 23% 22.5% 19.9% Brown 13.5% Manitowoc Calumet 23.6% 31.1% Washington 21.4% Sheboygan 13.8% Ozaukee 11.4% Jefferson Waukesha 19.1% 12.7% Milwaukee 3.3% Racine 8.9% Kenosha 6.5% Door 25.4% Kewaunee 34% Polk -11.4% St. Croix -13.7% Pierce -2.1% Pepin Barron -7% Dunn -3.8% -2.4% Buffalo -4.4% Rusk 10.3% Chippewa -19.4% Eau Claire -5.2% Trempealeau -7.7% Change in Male Gun Deer Hunter Participation Rates (2000-2009) Age 20-24 -30.0% to -15.1% -15.0% to -10.1% -10.0% to -5.1% -5.0% to -0.1% 0.0% - 11.0% La Crosse Grant Clark 0.9% Jackson -6.5% Vernon 3.2% Crawford -6.8% Taylor 3.4% Monroe -7.6% -5.8% Wood -8.4% Juneau -20.9% Richland Sauk 2.8% -10.9% -9.6% Lafayette -5.6% Lincoln -8% Marathon -9.7% Adams -1.2% -18.3% Portage -5.6% -5.7% Waushara Dane -2.9% Langlade -12.2% Columbia -10% -3.6% Rock Forest Shawano Waupaca -7.5% Marquette 1% Lake 1.2% -9.3% -5.4% Illinois Dodge -4% Jefferson Minnesota Burnett -2.9% Douglas -2.6% Bayfield -0.4% Sawyer -5% Polk Barron Rusk -3.8% -4.9% -2.8% St. Croix -3.1% Pierce -2% Pepin Washburn -6.3% Dunn -2.5% -0.5% Buffalo -3.1% Chippewa -4% Eau Claire -1.3% Trempealeau -2.9% La Crosse -0.9% Ashland -4.7% Grant -1.4% Clark Jackson -2.6% Vernon -3.7% Crawford Change in Number of Male -4.7% Gun Deer Hunters (2004-2009) Cohort Aged 30-49 in 2004 Marinette -8.2% Oconto -15% Outagamie Winnebago -1.2% -2% -5.7% Fond du Lac -0.9% Walworth -3.2% Waukesha Brown -3.6% Manitowoc Calumet -1.7% -7.1% Washington -5.6% -2.4% Sheboygan -3.2% Ozaukee -4.3% Milwaukee -1.5% Racine -2.9% Kenosha -0.4% -12% to -5.1% -5.0% to -3.1% -3.0% to -2.1% -2.0% to 0% Door -6.2% Kewaunee -6.8% Lake Michigan -2.8% Taylor -4.8% Monroe Iron Price -7.4% Richland -3.8% Lake Superior Wood -3.4% Juneau -7.4% -3.6% Lafayette -2.3% Sauk -3.4% Retention of Middle Aged Hunters 2004-2009 Lincoln -6.4% Vilas Oneida Marathon -3.9% Adams -3.4% -8.8% -6.7% Portage -3.2% -3.2% Waushara Columbia -2% Dane -0.9% Langlade -5.9% Rock -2.7% Shawano -5.1% Waupaca -4.5% Marquette -4.2% Lake -3% Illinois Michigan Florence -7% Forest -11.6% Marinette -6.1% Dodge Jefferson Oconto Outagamie Winnebago -2.4% Fond du Lac -2.9% Walworth -2.3% Brown -2.7% Manitowoc Calumet -4.1% -4.2% Washington Sheboygan -1.8% Ozaukee -2.4% Waukesha -2.1% Milwaukee -0.4% Racine -1.9% Kenosha -1.2% Lake Michigan Declines have been most stark in coun es (like St. Croix) where a metropolitan popula on has been expanding into more rural territory and in areas that have been experiencing re rement migra on and lakefront development. Both of these are cases of growing popula on pressure and land development. In addi on, they may limit hun ng access and change local culture. -1.4% -3.2% -3.1% -6.6% Door -3.7% Kewaunee -4.2% 9

Key Points The number of gun deer hun ng licenses sold to Wisconsin residents declined from 644, 991 in 2000 to 602,791 in 2010. This is a decline of 6.5% in ten years. Declines have been most stark among males age 25-44, who have (in the recent past) hunted at high rates and killed a large number of deer. Hunter par cipa on rates vary by age. Men are most likely to deer hunt as teens, but between age 15 and 23 a significant number of those who try hun ng decide that it is not for them and do not con nue. A er age 60-65, hunter par cipa on rates dropping off considerably as hunters reach older ages. Examining the popula on of male gun deer hunters in 2009 by age shows a large bulge in the Baby Boom genera on (age 43-63) and a rela ve dearth of young hunters following them. As Boomer hunters age into years when health may keep them from hun ng, hunter numbers are likely to decline. S ll, Baby Boomers will likely hunt at rela vely high rates later into life than their predecessors as they are more likely to stay healthier longer, to hunt, and to be wealthy enough to afford access and gear. As of 2010, the aging of the Baby Boom genera on is not responsible for current hunter decline, but this will increasingly become an important factor over the next ten to twenty years. Hunter par cipa on rates at all age and cohort groups have steadily declined each year since 2000. If Wisconsin males had con nued to hunt at the same rate as they did in 2000 (by age), there would have been 105,000 more hunters than the number of licenses actually sold in 2009. Projec ons suggest that the number of male gun deer hunters will decline considerably over the next several years. Between 2010 and 2020, projec ons suggest hunters will decline from 549,505 licenses sold to about 480,000. By 2030, the number of male gun deer hunters is projected to decline to 400,000 or fewer. The popula on of hunters is also projected to age considerably in coming years. By 2030, approximately 30% of male gun deer hunters will be over age 60. This suggests a need for more accessible hun ng opportuni es for an aging popula on. Most Wisconsin hunters (56%) live in metropolitan coun es. However, the rate at which people hunt is significantly higher in more rural areas and par cularly in northern Wisconsin. In several coun es, 50% or more of men age 15 and over hunt. Interes ngly, par cipa on rates are somewhat higher in western Wisconsin than in the eastern part of the state. The recent decline in male gun deer hunter numbers can be a ributed to rela vely weak reten on of hunters age 35-45 over the last decade and to rela vely weak recruitment of young men into hun ng who were born since 1980. The table at right shows annual hunter reten on over the last decade by age group. Reten on of male gun hunters drops off a er age 35. While 99.5% of hunters age 20-35 con nue hun ng each year, a er age 35 increasing numbers of hunters drop out. County-level analysis shows that reten on of middle-aged hunters has been declining more rapidly in eastern Wisconsin than west with large declines in the southeast, the Fox Valley, and the northeast. Furthermore, rela vely few males born since 1980 have been recruited into hun ng at young ages, making the cohorts of hunters age 20-30 in 2010 small. This shi coincides with what is o en referred to as the Millennial Genera on (see Howe and Strauss 2000). Research suggests that Millennials are less likely to par cipate in all types of outdoor recrea on than preceding genera ons and that they are less likely to agree that it is important to be outside as much as possible (Leisure Trends Group 2008, Howe 2009). Geographically, young hunter (age 20-24) par cipa on rates are stronger (and declining less) in the west than in the east. Overall, the Millennial genera on is being recruited into hun ng at lower rates than the prior Genera on X in almost every county. This has par cularly been the case in areas where a metropolitan popula on has been expanding into more rural territory (like St. Croix and Polk Coun es) and in areas that have been experiencing re rement migra on and lakefront development (e.g. Vilas, Oneida, Washburn, and Juneau Counites). These are cases of growing popula on pressure and land development. In addi on, they may limit hun ng access and change local culture. Average Male Gun Hunter Retention (Year to Year) Age Drop Out Rate 25-35 0.5% 35-45 1.5% 45-55 1.9% 55-65 2.7% 65-75 6.1% 75-79 10.6% For more informa on contact: Richelle Winkler, PhD Dept of Community & Environmental Sociology rwinkler@ssc.wisc.edu or (608) 262-1216 www.apl.wisc.edu