https://cpw.cvlcollections.org/files/original/820ae23d0f2f7ed0fcd8df8cfa9e480b.pdf 02134c43f699a97f3e8ee72b0518253f PDF Text Text The research in this publication was partially or fully funded by Colorado Parks and Wildlife. Dan Prenzlow, Director, Colorado Parks and Wildlife • Parks and Wildlife Commission: Marvin McDaniel, Chair • Carrie Besnette Hauser, Vice-Chair Marie Haskett, Secretary • Taishya Adams • Betsy Blecha • Charles Garcia • Dallas May • Duke Phillips, IV • Luke B. Schafer • James Jay Tutchton • Eden Vardy �Received: 27 March 2021 Revised: 10 July 2021 Accepted: 13 July 2021 DOI: 10.1111/csp2.505 CONTRIBUTED PAPER The future of wildlife conservation funding: What options do U.S. college students support? Lincoln R. Larson1 | Markus Nils Peterson2 | Richard Von Furstenberg1 Victoria R. Vayer1 | Kangjae Jerry Lee1 | Daniel Y. Choi2 | Kathryn Stevenson1 | Adam A. Ahlers3 Taniya Bethke5 | Jeremy T. Bruskotter6 | | Christine Anhalt-Depies4 | | Christopher J. Chizinski7 | | Kelly Heber Dunning10 | Brian Clark8 | Ashley A. Dayer9 11 12 13 | Larry Gigliotti | Alan Graefe | Kris Irwin14 Benjamin Ghasemi | Elizabeth Metcalf16 Samuel J. Keith14 | Matt Kelly15 | Gerard Kyle11 | Neelam C. Poudyal18 | Wayde Morse10 | Mark D. Needham17 | | | Michael Quartuch19 | Shari Rodriguez20 | Chelsie Romulo21 3 22 23 Ryan L. Sharp | William Siemer | Matthew T. Springer | Brett Stayton24 | Richard Stedman22 | Taylor Stein25 | Timothy R. Van Deelen26 | Jason Whiting27 | Richelle L. Winkler28 | Kyle Maurice Woosnam14 1 Department of Parks, Recreation & Tourism Management, North Carolina State University, Raleigh, North Carolina, USA 2 Department of Forestry & Environmental Resources, North Carolina State University, Raleigh, North Carolina, USA 3 Department of Horticulture and Natural Resources, Kansas State University, Manhattan, Kansas, USA 4 Wisconsin Department of Natural Resources, Madison, Wisconsin, USA 5 Council to Advance Hunting and the Shooting Sports, Washington, District of Columbia, USA 6 School of Environment and Natural Resources, The Ohio State University, Columbus, Ohio, USA 7 School of Natural Resources, University of Nebraska, Lincoln, Nebraska, USA 8 Kentucky Department of Fish & Wildlife Resources, Frankfort, Kentucky, USA 9 Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia, USA 10 School of Forestry & Wildlife Sciences, Auburn University, Auburn, Alabama, USA 11 Department of Rangeland, Wildlife & Fisheries Management, Texas A&M University, College Station, Texas, USA 12 Department of Natural Resource Management, South Dakota State University, Brookings, South Dakota, USA 13 Department of Recreation, Park & Tourism Management, The Pennsylvania State University, University Park, Pennsylvania, USA 14 Warnell School of Forestry & Natural Resources, University of Georgia, Athens, Georgia, USA 15 College of Forest Resources and Environmental Science, Michigan Tech University, Houghton, Michigan, USA 16 W. A. Franke College of Forestry & Conservation, University of Montana, Missoula, Montana, USA 17 Department of Forest Ecosystems & Society, Oregon State University, Corvallis, Oregon, USA 18 Department of Forestry, Wildlife & Fisheries, University of Tennessee, Knoxville, Tennessee, USA 19 Colorado Department of Natural Resources, Colorado Parks & Wildlife, Denver, Colorado, USA 20 Forestry & Environmental Conservation Department, Clemson University, Clemson, South Carolina, USA 21 Department of Geography, GIS, & Sustainability, University of Northern Colorado, Greeley, Colorado, USA This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Conservation Science and Practice published by Wiley Periodicals LLC. on behalf of Society for Conservation Biology Conservation Science and Practice. 2021;e505. https://doi.org/10.1111/csp2.505 wileyonlinelibrary.com/journal/csp2 1 of 12 �2 of 12 LARSON ET AL. 22 Department of Natural Resources, Cornell University, Ithaca, New York, USA 23 Department of Forestry & Natural Resources, University of Kentucky, Lexington, Kentucky, USA 24 RIFF Outdoors, Nashville, TN, USA 25 Department of Forest Resources and Conservation, Gainesville, Florida, USA 26 Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, Wisconsin, 53706, USA 27 Department of Recreation Administration, California State University, Fresno, California, USA 28 Department of Social Sciences, Michigan Technological University, Houghton, Michigan, USA Correspondence Lincoln R. Larson, Department of Parks, Recreation & Tourism Management, North Carolina State University, Raleigh, North Carolina, 27695, USA. Email: lrlarson@ncsu.edu Funding information U.S. Fish and Wildlife Service Multistate Conservation, Grant/Award Numbers: F19AP00094, F18AP00171 Abstract Insufficient funding is a major impediment to conservation efforts around the world. In the United States, a decline in hunting participation threatens sustainability of the “user-pay, public benefit” model that has supported wildlife conservation for nearly 100 years, forcing wildlife management agencies to contemplate alternative funding strategies. We investigated support for potential funding options among diverse college students, a rapidly expanding and politically active voting bloc with a potentially powerful influence on the future of conservation. From 2018 to 2020, we surveyed 17,203 undergraduate students at public universities across 22 states. Students preferred innovative approaches to conservation funding, with 72% supporting funding derived from industry sources (e.g., natural resource extraction companies), 63% supporting state sources (e.g., general sales tax), and 43% supporting conventional user-based sources such as license fees and excise taxes associated with outdoor recreation activities (e.g., hunting). Findings emphasize the need to broaden the base of support for conservation funding and highlight the importance of considering the preferences and perspectives of young adults and other diverse beneficiaries of wildlife conservation. KEYWORDS angling, college students, conservation policy, funding, hunting, public support, wildlife management 1 | INTRODUCTION Inadequate wildlife conservation funding is a threat to global biodiversity (Echols, Front, & Cummins, 2019; Waldron et al., 2013) exacerbated by modernization and socio-demographic changes that alter conservation priorities and challenge the efficacy of conventional funding mechanisms (Manfredo, Teel, Berl, Bruskotter, & Kitayama, 2020). Cultural shifts in conservation values are particularly conspicuous in the United States (Manfredo, Teel, Berl, Bruskotter, & Kitayama, 2020), where a unique “user-pay, public benefits” approach fueled by contributions from hunters and anglers has effectively supported conservation efforts for nearly 100 years (USDOI, 2020). Since the 1930s, excise taxes generated from hunting (Pittman-Robertson Act of 1937) and fishing equipment sales (Dingell-Johnson Act of 1950), combined with the Federal Duck Stamp and hunting and fishing license purchases, generate billions of dollars annually to support wildlife management and habitat conservation efforts. Overall, these funding sources comprise approximately 60–80% of revenue for state fish and wildlife agencies in the U.S. (AFWA & AZGFD, 2017; USDOI, 2020). These efforts have solidified hunting and fishing as pillars of the North American Model of conservation (Mahoney & Jackson, Mahoney & Jackson III, 2013). The sustainability of this funding model is threatened by the decline of hunting participation in the United States (Duda, Beppler, Austen, & Organ, 2021). Since the 1980s, the U.S. hunting population has dropped by approximately 2 million participants (USFWS, 2020), and the number of active hunters has declined by approximately 30% (USFWS, 2018). The decline is particularly �LARSON ET AL. sharp among young adults born after 1980 (Enck, Decker, & Brown, 2000; Winkler & Warnke, 2013). Waning participation has been attributed to factors including urbanization, structural shifts in demographics (e.g., aging, increasing racial/ethnic diversity), land ownership changes that impact hunting access, negative media coverage, and competing demands for time and money (Larson, Stedman, Decker, Siemer, & Baumer, 2014; Peterson, Hansen, Peterson, & Peterson, 2011; Poudyal, Cho, & Bowker, 2008). Financial impacts associated with the decline of hunting have been partially offset by a recent surge in shooting sports participation and associated excise tax revenue (Duda et al., 2021). In 2015, nearly 80% of all taxable firearm and ammunition sales in the U.S. were for nonhunting purposes (Southwick Associates, 2019). Some studies also suggest the disproportionate contributions of hunters and anglers to wildlife conservation may be overestimated when assessments consider financial contributions to environmental NGOs (nongovernmental organizations) and public tax dollars supporting federal land management (Peterson & Nelson, 2017; Smith & Molde, 2015). Nevertheless, most experts agree that, in the absence of viable funding alternatives, diminishing numbers of hunters will ultimately affect wildlife agencies' capacity to achieve management goals and engage in critical conservation activities (Duda et al., 2021; Larson et al., 2014). In addition to declines in hunting participation, social and cultural shifts such as rising urbanization and increasing education levels are reshaping American's wildlife value orientations and the broader conservation landscape (Manfredo, Teel, Berl, Bruskotter, & Kitayama, 2020; Manfredo, Teel, Don Carlos, et al., 2020). The American public is increasingly embracing mutualistic value orientations that view humans and wildlife as equals and emphasize harmonious coexistence (Manfredo, Teel, Don Carlos, et al., 2020). Mutualistic values may strengthen support for wildlife conservation, but they often conflict with utilitarian values that prioritize humans over wildlife and conservation funding systems that revolve around hunting and fishing (Manfredo, Teel, Don Carlos, et al., 2020; Serfass, Brooks, & Bruskotter, 2018). Due to declines in utilitarian values and activities (e.g., hunting) and concurrent increases in mutualistic values and activities (e.g., wildlife watching, USFWS, 2020), stakeholders and leaders are increasingly calling for wildlife agencies and other conservation organizations to identify and engage with broader and more diverse constituencies (AFWA & WMI, 2019; Echols et al., 2019; Martin et al., 2016). As social change progresses, wildlife agencies are asking an urgent question: from where will future conservation funding come? In 2016, the Association of Fish and Wildlife Agencies (AFWA) convened a Blue Ribbon Panel of government, nongovernmental, and industry 3 of 12 experts to investigate potential answers. The Panel's report highlighted one possible approach modeled after the Land and Water Conservation Fund (LWCF): funding conservation by utilizing existing revenue from the development of energy and mineral resources on federal lands (AFWA, 2016). Other conservation funding options include general sales taxes, transfer taxes, lottery funds, vehicle license plate sales, nonconsumptive recreation user fees, and outdoor equipment sales taxes (McKinney, Ris, Rorer, & Williams, 2005; Outdoor Industry Association, 2017). A recent national study found moderate to strong support for most of these potential funding options (Kellert et al., 2017). Some of these strategies have already been implemented successfully, yielding high levels of approval in certain U.S. states (Dalrymple et al., 2012). However, many state legislatures and wildlife agencies may be reluctant to explore or accept changes to conventional funding mechanisms, often due to political and cultural constraints (AFWA & WMI, 2019; Jacobson, Decker, & Carpenter, 2007). Although systemic change to conservation funding mechanisms has been slow, additional input from a diversifying constituent base could expedite this process (Echols et al., 2019). More than any other population segment, young adults are poised to challenge the conservation status quo. This age cohort, widely dubbed “postmillennials” or Gen Z, is more culturally diverse than previous generations (Fry & Parker, 2018), better educated (Taylor & The Pew Research Center, 2015), and more likely to embrace mutualistic wildlife value orientations (Manfredo, Teel, Berl, et al., 2020). Although young adults have historically voted at lower rates than other age groups (Leighley & Nagler, 2013), they are quickly becoming the largest generation in the U.S. electorate (surpassing Baby Boomers) and have emerged as an increasingly influential block of voters and future decision makers (Taylor & The Pew Research Center, 2015; Thomas, Gismondi, Gautam, & Brinkler, 2019). Gen Zers are politically active, environmentally conscious, and eager to catalyze social change (Rue, 2018; Su, Tsai, Chen, & Lv, 2019). These assets and attributes are even more pronounced among the 40% of young adults, or nearly 20 million students, who choose to attend college in the U.S. (NCES, 2019). Levels of civic engagement are particularly high among contemporary college students (Ballard, Ni, & Brocato, 2020). For instance, the voting rate of undergraduate students has more than doubled in the past decade (Thomas et al., 2019). When students engage with policy issues during their college years, it can lead to more habitual and sustained political participation later in life (Plutzer, 2002). In short, current college students represent a diverse demographic group who may ultimately chart the �4 of 12 course of conservation in the coming decades. Yet, despite their critical influence on the future of wildlife conservation, it is not yet clear what funding options college students would support or what sociodemographic factors might influence those preferences. Our study sought to answer these questions. 2 | METHODS 2.1 | Data collection From 2018 to 2020, we conducted a web-based survey of undergraduate students at 22 public universities across the U.S. (Figure S1 and Table S1). At each institution, we worked with administrators to send a questionnaire link via Qualtrics to a random sample of undergraduate students (typically 5000, but the sample frame ranged from 3000 to 16,000; Table S2). Only students who were randomly selected to receive the survey invitation were eligible to participate. In two cases where a university-wide random sample was not possible, we worked with colleges within the university to obtain a diverse sample of participants across a variety of majors. We included two email contacts at approximately weekly intervals, followed by a shorter survey of nonrespondents (featuring a subset of identical items) to check for nonresponse bias. The survey process involving human subjects was approved by the North Carolina State University Institutional Review Board (Protocol #12676). LARSON ET AL. We also investigated potential socio-demographic correlates of support for conservation funding, including gender identity, race and ethnicity, college major, and population size of the area where a participant grew up (rural to urban, Table 1). These factors help to shape social and cultural identities, which are typically strong correlates of beliefs and attitudes related to wildlife conservation (van Eeden et al., 2020). For example, education and urbanization have been linked to mutualistic wildlife value orientations (Manfredo, Teel, Don Carlos, et al., 2020), and particularly strong support for conservation funding has been reported by young adults and higher-income adults (Dalrymple et al., 2012; Kellert et al., 2017), as well as Hispanics and urban residents (Kellert et al., 2017). Because urban–rural conflicts in support for conservation often manifest as cultural and political differences across U.S. regions (Manfredo, Teel, Sullivan, & Dietsch, 2017), we also recorded the geographic location of each university: Northeast (NE), Southeast (SE), Midwest (MW), and West (W). Additionally, due to established links between recreation activities and pro-conservation behavior (Larson, Cooper, Stedman, Decker, & Gagnon, 2018), we measured respondents' participation in six outdoor recreation activities during the past 12 months (hunting, fishing, birding, camping, hiking, wildlife watching) with an index that summed scores and ranged from 0 (no participation) to 6 (high participation). 2.3 | Analysis 2.2 | Survey instrument Most items in our questionnaire focused on beliefs and behaviors related to hunting and fishing, but some also asked about attitudes toward conservation funding. For a full list of survey items used in this analysis, see supplemental Figure S2. To explore support for different funding options, we asked, “Would you oppose or support the following potential strategies to help fund wildlife conservation in the future?” We listed nine potential funding sources for rating on a scale from ( 2) strongly oppose to (+2) strongly support. Potential funding sources were drawn from a list of current and prospective conservation funding mechanisms utilized across the U.S. (McKinney et al., 2005; Outdoor Industry Association, 2017), including sources (e.g., charges on oil and gas development, public taxes, hunting and fishing license and equipment fees) that have been the focus of previous national surveys (Kellert et al., 2017; Manfredo et al., 2018). Prior to analysis, we removed responses from individuals who were not undergraduate students within the 18–34 year age range and individuals who skipped relevant questions. This resulted in removal of 13% of all questionnaires that were started. We used principal components analysis (PCA) with an orthogonal rotation to reduce multiple funding options into larger categories, and Cronbach's alpha to assess measurement reliability of these categories (Vaske, 2019). To adjust for potential sampling bias, we followed suggestions from Vaske (2019) to conduct poststratification weighting based on enrollment and student demographic data (NCES, 2019). Normalized multiplicative weights were developed for each case (respondent) based on school enrollment, gender identity, and race and ethnicity (Table S2). We examined weighted mean estimates and frequencies to describe response patterns. We then fit binary logistic regression models to investigate the relative influence of socio-demographic factors on support for conservation funding alternatives (scale M > 1.0 = 1 or �LARSON ET AL. 5 of 12 T A B L E 1 Unweighted and weighted demographic attribute frequencies within college student sample across 22 U.S. states (n = 17,203) Variable Unweighted categoriesa Weighted categoriesb Gender 56.6% female 53.3% female or not listed 42.7% male 46.7% male 0.7% not listed Race/ethnicity Childhood location U.S. region College major 75.2% White 64.8% White 9.1% Hispanic/Latino 12.7% Hispanic/Latino 3.0% Black/African American 4.1% Black/African American 8.6% Asian 12.6% Asian 1.2% American Indian 1.7% American Indian 2.6% other/multiracial 3.6% other/multiracial 23.2% large city (250 k+) 24.8% large city (250 k+) 27.9% medium city (50–250 k) 28.5% medium city (50–250 k) 26.5% small city (10–50 k) 25.0% small city (10–50 k) 17.7% small town or rural area 16.9% small town or rural area 4.7% other 4.9% other 13.3% NE 16.1% NE 31.6% SE 33.6% SE 33.0% MW 26.9% MW 22.1% W 23.4% W 20.0% Ag & Natural Resources 20.0% Ag & Natural Resources 20.2% Science & Math 22.1% Science & Math 21.6% Engineering & Technology 22.1% Engineering & Technology 13.0% Business & Economics 13.2% Business & Economics 18.5% Social Science & Humanities 18.2% Social Science & Humanities 4.3% arts 4.5% arts/other 0.3% other Outdoor Rec scorec M = 2.85, SD = 1.74 M = 2.70, SD = 1.80 25.4% one activity or less 29.5% one activity or less 20.4% five activities or more 19.2% five activities or more a Unweighted categories display response options that appeared on the survey instrument. Weighted categories display demographic breakdown after applying normalized weights that account for gender, race, and university. In many cases, categorical variables were re-coded into larger categories to simplify analysis and interpretation. c Outdoor Rec score represents the sum of annual participation in six nature-based recreation activities (hunting, fishing, birding, camping, hiking, and wildlife watching). A score of six means a person participated in all six activities during past year. Zero means they participated in zero activities. Both means (M), standard deviation (SD), and binary groupings are presented for this variable. b support, M ≤ 1.0 = 0 or neutral or oppose) and ran three separate models for each funding category. We assessed model fit using χ2 goodness-of-fit tests and Nagelkerke pseudo-R2. We assessed the significance of specific demographic variables in the models using parameter coefficients and odds ratios (OR). To examine the sensitivity of our analysis, we tested both weighted and unweighted models and found no significant differences. We therefore reported unweighted results. 3 | RESULTS 3.1 | Sample description Our response rate was 14.2% (ranging from 6.1% to 31.5% among universities). Though low, this number is comparable to response rates recorded in other recent conservation social science research (Stedman, Connelly, Heberlein, Decker, & Allred, 2019). Overall, the survey �6 of 12 yielded a total sample size of 17,203 across all institutions (see Table S2). After weighting, the sample included 65% of respondents identifying themselves as white, 47% as male, 47% from rural hometowns or cities smaller than 50,000 residents, and 17% majoring in subjects related to agriculture or natural resources (Table 1). These ratios align relatively well with the national averages of students at public universities across the country (U.S. Census Bureau, 2018). To check nonresponse bias, we also collected 6,585 shorter questionnaires from students who did not respond to the initial invitations. We found only minor differences between the demographic attributes of full questionnaire respondents and nonrespondents; the latter group was slightly more likely to be male (+3.6%) and less likely to be natural resource majors ( 6.7%). However, all effect sizes were small (Cramer's V < 0.10), enabling us to conclude that response bias related to demographic attributes was minimal. LARSON ET AL. taxes/fees associated with outdoor recreation activities not linked to fishing and hunting (Figure 1). PCA demonstrated three key categories of funding options (Table S3): industry-supported sources that included natural resource extraction companies or outdoor recreation outfitters contributing revenue to conservation (72% support, M = 1.09); state funding sources that included general sales taxes, lottery proceeds, or state and local bonds (63% support, M = 0.96); and userbased sources such as licenses and excise taxes on hunting, fishing, and other outdoor recreation activities (43% support, M = 0.65; Figure 2). 3.2 | Support for future conservation funding strategies A majority of respondents strongly or very strongly supported eight of the nine potential future conservation funding options presented in the questionnaire (Figure 1). We observed the strongest support for resource extraction companies contributing revenue to conservation, followed by a staple of the current system: license fees from fishing and hunting. Students reported moderate support for state-based funding mechanisms such as lottery proceeds, dedicated sales tax, and state and local conservation bonds, and weakest support for F I G U R E 2 College students' support for three different categories of wildlife conservation funding across 22 U.S. states: industry funding sources (two items), state funding sources (three items), and user-based sources such as licenses and excise taxes (four items). Boxplot depicts weighted means for items in each funding category (adjusted n = 14,957) F I G U R E 1 Support for different wildlife conservation funding options among college students across 22 U.S. states (n = 17,203). * Note: Figure 1 should be used for the graphical table of contents �LARSON ET AL. 7 of 12 T A B L E 2 Parameter estimates (B) and odds ratios (OR) in logistic regression models showing demographic correlates of support for different categories of wildlife conservation funding strategies (industry funding sources, state funding sources, and user-based sources such as licenses and excise taxes) among college students across 22 U.S. states Unweighted ratio of population supporting funding option Gender (male) d Industry sourcesa 0.719 State sourcesb 0.624 B B OR User-based sourcesc 0.424 OR B OR 0.305 0.737*** 0.120 1.128** 0.296 0.744*** 0.112 1.119 0.087 1.091 0.024 0.976 d 0.012 0.988 0.284 0.753** 0.035 1.035 Race (Asian)d 0.311 0.733*** 0.199 0.819** 0.111 0.895 Race (Amer. Indian)d 0.115 1.121 0.031 1.031 0.001 0.999 0.226 0.798* 0.108 0.897 0.044 0.957 0.040 0.961 0.044 0.957 0.055 0.947 Race (Hispanic) Race (Black) Race (other) d Childhood (Mod. City) e e 0.001 0.999 0.028 0.973 0.091 0.913 0.037 1.038 0.033 0.968 0.240 0.787*** Childhood (other)e 0.160 0.852 0.135 0.874 0.011 0.989 f 0.133 1.142* 0.025 0.975 0.043 1.044 0.002 1.002 0.156 0.856** 0.055 1.056 0.205 0.815** 0.122 0.885* 0.189 0.827** 0.331 0.718*** 0.417 0.659*** 0.412 0.662*** 0.410 0.663*** 0.517 0.596*** 0.514 0.598*** 0.664 0.515*** 0.694 0.499*** 0.526 0.591*** 0.225 0.842 0.376 0.687*** 0.317 0.729*** 0.172 0.638*** 0.366 0.693*** 0.449 0.638*** 0.123 1.131*** 0.144 1.155*** 0.050 1.052*** Childhood (Small City) Childhood (rural)e Region (southeast) f Region (Midwest) Region (west) f Major (Science & Math) g Major (Engineer. & Tech) g Major (Business & Econ)g Major (social science) Major (other) g Outdoor rec score g Note: *, **, *** denote statistically significant Odds Ratio (OR) at α = 0.05, 0.01, and 0.001, respectively. a Industry sources include natural resource extraction and outdoor recreation product companies contributing revenue to conservation; Model Fit (Industry): χ2(19) = 456.74, p < .001; Nagelkerke R2 = 0.043 (n = 15,198). b State sources include sales taxes, lottery proceeds, and state and local bonds; Model Fit (State): χ2(19) = 450.55, p < .001; Nagelkerke R2 = 0.040 (n = 15,208). c User-based sources include license/fees and special excises taxes associated with hunting, fishing, or other types of outdoor recreation; Model Fit (Users): χ2(19) = 303.81, p < .001; Nagelkerke R2 = 0.027 (n = 15,209). d Reference category for race/ethnicity = White. e Reference category for childhood location = Large City. f Reference category for region = Northeast (NE). g Reference category for major = Agriculture & Natural Resources. The logistic regression modeling showed that demographic differences in funding support were minimal (Table 2). Although response frequencies varied, each demographic subgroup reported the same ranked prioritization of the three categories of funding sources (Table S4). Agriculture and natural resource majors and outdoor enthusiasts were most likely to support all funding options (Table 2). Male students were most likely to oppose industry- and user-based funding mechanisms, but were more likely to support state sources. Asian students were less likely to support industry and state sources, and Black students were less likely to support state sources (Table 2). Students from rural backgrounds were less likely to support user-based funding sources than students from urban backgrounds. Responses also varied to some degree across U.S. regions, with students at universities in the West most likely to oppose all conservation funding options (Table 2). However, fit statistics for all models (Nagelkerke R2 < 0.043) suggested none of the demographic characteristics we tested were powerful predictors of support for conservation funding, and overall levels of support were similar across categories (Table S4). Regardless of demographic backgrounds, a majority of college students supported multiple conservation funding options, particularly those that rely on industry- and state-based sources of revenue. �8 of 12 4 | DISCUSSION Results suggest that contemporary college students, the civic and political leaders of the future, are willing to support a diverse portfolio of conservation funding strategies. Results also reify concerns regarding the sustainability of conservation funding approaches that rely heavily on hunters and anglers and exclude other groups (AFWA, 2016; AFWA & WMI, 2019; Duda et al., 2021; Serfass et al., 2018). Our findings could help practitioners and policy makers develop an innovative and broader suite of conservation funding options that are likely to appeal to current and future generations. According to college students, the most acceptable funding option was requiring natural resource (e.g., oil, coal, natural gas) extraction companies to contribute revenue toward conservation. This strategy, a key recommendation of the Blue Ribbon Panel (AFWA, 2016) and a potential funding source specified in the original version of the Recovering America's Wildlife Act (2019), appears to be one that most young adults in college would strongly support. National surveys of older adults reveal similar approval of funding based on fines for environmental polluting or charges levied on oil and gas production (Kellert et al., 2017). Although these approaches have been criticized because they might establish links between natural resource degradation and conservation, the longstanding effectiveness of programs such as LWCF demonstrate their potential value (Echols et al., 2019). If an industry-based funding model were extended to include revenue generated from other companies, such as nonconsumptive outdoor recreation outfitters, it appears that college students would also support it. Dedicated state funding for conservation was also acceptable to a majority of college students. Examples of these innovative strategies, which range from state sales taxes to lottery proceeds, already exist in multiple U.S. states (McKinney et al., 2005; Outdoor Industry Association, 2017) and often earn public support (Dalrymple et al., 2012; Kellert et al., 2017). However, support for state sales taxes, in particular, is more uncertain for older adult populations (Dalrymple et al., 2012; Kellert et al., 2017). Often due to political and structural constraints, state legislatures and wildlife agencies have been slow to alter the status quo and embrace new strategies (Jacobson et al., 2007). Our results suggest the strong preferences of young adults could help to catalyze cultural shifts that open novel avenues for state-based conservation funding sources. We observed weaker support for more conventional, user-based conservation funding models—the same approaches that form the foundation of the current funding model in the U.S. Although many students LARSON ET AL. approved of funding derived from hunting and fishing license sales, they were less likely to embrace excise taxes and expressed stronger resistance to licenses and taxes levied on alternative outdoor recreation activities. Opposition to a “backpack tax” has permeated the outdoor recreation industry since the demise of the Teaming with Wildlife Act (2008), which sought to extend excise taxes to nonconsumptive recreation products (Outdoor Industry Association, 2017). Like previous research (Naderi & Van Steenburg, 2018), our study suggests that although many college students want more funding for conservation, they may be less inclined to support pro-environmental causes when they perceive tangible financial costs to themselves or their lifestyles. College students' relative lack of support for user-pay approaches contrasts with previous studies of older adults who often favor user-pay models (Dalrymple et al., 2012). Roots of this difference are unclear and may stem from generational wealth gaps or differences in how equitable access to environmental amenities is valued. Irrespective of the mechanisms involved, these differences underscore the need to develop innovative conservation funding strategies that young adults would support. Without the backing of Gen Zers, the precarious plight of conservation funding may be in further jeopardy (Duda et al., 2021). Socio-demographic differences in funding support were minor, suggesting that prominent polarization dividing American society (Wilson, Parker, & Feinberg, 2020) and influencing support for environmental protection (McCright, Xiao, & Dunlap, 2014) may be less intense when it comes to wildlife conservation. For example, we found comparable levels of funding support across the rural to urban gradient, partially assuaging concerns that an “extinction of experience” linked to urbanization might negatively impact environmental concern and pro-environmental behavior (Gaston & Soga, 2020). We also discovered strong links between outdoor recreation and funding support, showing that regular exposure to nature and natural landscapes fosters positive conservation outcomes among both rural and urban students (Larson et al., 2018). Differences in support based on race and ethnicity were minimal, reinforcing research showing that environmentalism is not an inherently white phenomenon (Lazri & Konisky, 2019). Findings ultimately suggest that consensus about conservation funding exists across diverse populations of young adults, offering common ground for productive engagement that has been observed in other conservation contexts (Sandbrook, Fisher, Holmes, Luque-Lora, & Keane, 2019). Despite substantial support for conservation funding throughout our comprehensive sample of U.S. college students, a few notable demographic differences �LARSON ET AL. emerged. For instance, certain subgroups of students, such as males from rural backgrounds, were particularly averse to user-based funding sources such as excise taxes. This could stem from sociocultural and political forces that were not measured directly here (Manfredo, Teel, Don Carlos, et al., 2020). For example, Manfredo et al. (2017) describe how efforts to adopt more inclusive conservation governance models have fueled intense backlash and distrust among traditional stakeholder groups (e.g., hunters). Cultural differences might also explain regional disparities we observed in support for conservation, emphasizing the need to account for local context when developing socially acceptable conservation funding strategies. Future research could address several limitations of this study. Our sample did not represent students at all types of institutions (e.g., private schools, smaller public schools) or young adults not attending college, though our sample demographics mirror those of U.S. college students and younger subsets of the American electorate in many ways (U.S. Census Bureau, 2018). Moreover, studies could incorporate a wider variety of conservation funding options, including strategies that affect wildlife conservation outcomes beyond the state level and explicitly consider both game and nongame species (Dalrymple et al., 2012). Future research could also explore young adults' support for innovative conservation funding options at a global scale, helping to assist other countries facing destabilized funding models to protect critical habitat and limit biodiversity declines around the world (Waldron et al., 2013). Current college students constitute a demographically diverse and politically influential segment of the public that will help to lead future conservation policy in the U.S. and abroad (Plutzer, 2002; Taylor & The Pew Research Group, 2015). Expanding antiquated approaches to conservation funding and decision-making requires engagement with younger audiences (Anderson & Loomis, 2006; Martin et al., 2016). Documenting and responding to the perspectives and preferences of diverse college students, all of whom represent beneficiaries in wildlife management (Decker et al., 2019), is a key step in that process. 5 | C ON C L U S I ON Findings suggest that most college students across the U.S. are in support of changes to conventional wildlife conservation funding mechanisms. Although hunting and fishing-related revenue will surely remain a major source of conservation funding in the U.S., this study highlights the importance of diversifying the base of support for conservation to enhance financial sustainability (Jacobson, Organ, Decker, Batcheller, & Carpenter, 2010). 9 of 12 New legislation that aims to expand conservation funding options (e.g., RAWA, 2020) could help to accomplish this goal and will likely appeal to young adults. The imminent conservation funding crisis may be daunting (Duda et al., 2021; Echols et al., 2019), but our research illuminates unique opportunities to adapt traditional tactics and create contemporary, inclusive solutions rooted in multi-stakeholder engagement (involving different types of recreationists) and inter-sector collaborations (involving industry, government, NGOs, and the public). Younger generations across the U.S. appear poised and eager to support innovative funding alternatives for wildlife conservation if state agencies and policy makers choose to pursue these strategies. ACKNOWLEDGMENTS This research was funded by the U.S. Fish and Wildlife Service's Multistate Conservation Grant Program (grant #F18AP00171 and #F19AP00094), which is jointly managed by the Association of Fish and Wildlife Agencies and the Service's Widlife and Sport Fish Restoration Program. The authors would like to thank all of the collaborators at universities and state agencies around the United States who assisted with questionnaire design, implementation, data management, and analysis (see Table S1 for full list of collaborators), as well as all of the students who took the time to participate in our survey. CONFLICT OF INTEREST The authors declare no conflicts of interest. AUTHOR CONTRIBUTIONS Lincoln R. Larson, M. Nils Peterson, and Kangjae Jerry Lee, were the principal investigators of the study and oversaw conceptualization of the study, funding acquisition, and research design. All authors worked to collect data within their respective institutions/states. Richard von Furstenberg, Victoria R. Vayer, and Daniel Y. Choi assisted the principal investigators with data integration and analysis, including development of tables and figures. Lincoln R. Larson led the writing of the original draft, with contributions from many other research team members. All authors reviewed and edited the article and approved the submitted version. ET HI CS S TA TE MEN T Our study protocol was approved by the North Carolina State University Institutional Review Board (Protocol #12676) prior to data collection. DA TA AVAI LA BI LI TY S T ATE ME NT Data used in this study are publicly available at https:// doi.org/10.5061/dryad.dz08kprx8. �10 of 12 ORCID Lincoln R. Larson https://orcid.org/0000-0001-95911269 Adam A. Ahlers https://orcid.org/0000-0002-5699-0897 Jeremy T. Bruskotter https://orcid.org/0000-0002-17827835 Ashley A. Dayer https://orcid.org/0000-0002-8105-0776 Kelly Heber Dunning https://orcid.org/0000-0002-99014730 Benjamin Ghasemi https://orcid.org/0000-0002-16068953 Gerard Kyle https://orcid.org/0000-0002-6944-9020 Mark D. Needham https://orcid.org/0000-0001-62653371 Chelsie Romulo https://orcid.org/0000-0003-1612-1969 R EF E RE N C E S Anderson, L. E., & Loomis, D. K. (2006). Balancing stakeholders with an imbalanced budget: How continued inequities in wildlife funding maintains old management styles. Human Dimensions of Wildlife, 11(6), 455–458. https://doi.org/10.1080/ 10871200600984513 Association of Fish & Wildlife Agencies (AFWA). (2016). The future of America's fish and wildlife: A 21st century vision for investing in and connecting people to nature. Washington, DC: Association of Fish & Wildlife Agencies. Retrieved from https://www. fishwildlife.org/application/files/8215/1382/2408/Blue_ Ribbon_Panel_Report2.pdf Association of Fish & Wildlife Agencies (AFWA) & Arizona Game and Fish Department (AZGFD). (2017). The state conservation machine. Phoenix, AZ: Association of Fish & Wildlife Agencies. Retrieved from https://www.fishwildlife.org/application/files/ 3615/1853/8699/The_State_Conservation_Machine-FINAL.pdf Association of Fish & Wildlife Agencies (AFWA) & The Wildlife Management Institute. (2019). Fish and Wildlife Relevancy Roadmap: enhanced conservation through broader engagement (v1.0) (128 pp.). M. Dunfee, A. Forstchen, E. Haubold, M. Humpert, J. Newmark, J. Sumners, & C. Smith (Eds.). Washington, DC: Association of Fish & Wildlife Agencies. Retrieved from https://www.fishwildlife.org/application/files/ 2515/7547/9977/Fish_Wildlife_Relevancy_Roadmap__Final_ 12-04-19-lowres.pdf Ballard, P. J., Ni, X., & Brocato, N. (2020). Political engagement and wellbeing among college students. Journal of Applied Developmental Psychology, 71, 101209. https://doi.org/10.1016/j.appdev. 2020.101209 Dalrymple, C. J., Peterson, M. N., Cobb, D. T., Sills, E. O., Bondell, H. D., & Dalrymple, D. J. (2012). Estimating public willingness to fund nongame conservation through state tax initiatives. Wildlife Society Bulletin, 36(3), 483–491. https://doi. org/10.1002/wsb.164 Decker, D. J., Forstchen, A. B., Siemer, W. F., Smith, C. A., Frohlich, R. K., Schiavone, M. V., … Pomeranz, E. F. (2019). Moving the paradigm from stakeholders to beneficiaries in wildlife management. The Journal of Wildlife Management, 83 (3), 513–518. LARSON ET AL. Duda, M. D., Beppler, T., Austen, D. J., & Organ, J. F. (2021). The precarious position of wildlife conservation funding in the United States. Human Dimensions of Wildlife. https://doi. org/10.1080/10871209.2021.1904307 Echols, A., Front, A., & Cummins, J. (2019). Broadening conservation funding. Wildlife Society Bulletin, 43(3), 372–381. https:// doi.org/10.1002/wsb.1003 Enck, J. W., Decker, D. J., & Brown, T. L. (2000). Status of hunter recruitment and retention in the United States. The Wildlife Society Bulletin, 28(4), 817–824. Fry, R., & Parker, K. (2018). Early benchmarks show “post-millenials” on track to be most diverse, best-educated generation. Washington, DC: Pew Research Center. Retrieved from http:// www.pewsocialtrends.org/2018/11/15/early-benchmarks-showpost-millennials-on-track-to-be-most-diverse-best-educatedgeneration-yet/. Gaston, K. J., & Soga, M. (2020). Extinction of experience: The need to be more specific. People and Nature, 2(3), 575–581. https:// doi.org/10.1002/pan3.10118 Jacobson, C. A., Decker, D. J., & Carpenter, L. (2007). Securing alternative funding for wildlife management: Insights from agency leaders. The Journal of Wildlife Management, 71(6), 2106–2113. https://doi.org/10.2193/2006-442 Jacobson, C. A., Organ, J. F., Decker, D. J., Batcheller, G. R., & Carpenter, L. (2010). A conservation institution for the 21st century: Implications for state wildlife agencies. Journal of Wildlife Management, 74(2), 203–209. https://doi.org/10.2193/ 2008-485 Kellert, S. R., Case, D. J., Escher, D., Witter, D. J., MikelsCarrasco, J., & Seng, P. T. (2017). The nature of Americans: Disconnection and recommendations for reconnection. Mishawaka, IN: D.J. Case & Associates. Retrieved from https:// natureofamericans.org/ Larson, L. R., Cooper, C. B., Stedman, R. C., Decker, D. J., & Gagnon, R. J. (2018). Place-based pathways to proenvironmental behavior: Empirical evidence for a conservation–recreation model. Society & Natural Resources, 31 (8), 871–891. https://doi.org/10.1080/08941920.2018.1447714 Larson, L. R., Stedman, R. C., Decker, D. J., Siemer, 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. https://doi.org/10.1080/10871209.2014.850126 Lazri, A. M., & Konisky, D. M. (2019). Environmental attitudes across race and ethnicity. Social Science Quarterly, 100(4), 1039–1055. https://doi.org/10.1111/ssqu.12626 Leighley, J. E., & Nagler, J. (2013). Who votes now? Demographics issues, inequality, and turnout in the United States. Princeton, NJ: Princeton University Press. Mahoney, S. P., & Jackson, J. J., III. (2013). Enshrining hunting as a foundation for conservation: The North American model. International Journal of Environmental Studies, 70(3), 448–459. https://doi.org/10.1080/00207233.2013.801178 Manfredo, M. J., Sullivan, L, Don Carlos, A. W., Dietsch, A. M., Teel, T. L., Bright, A. D., & Bruskotter, J. T. (2018). America's wildlife values: The social context of wildlife management in the U.S. national report from the research project entitled “America's wildlife values”. Fort Collins, Co: Colorado State University, Department of Human Dimensions of Natural Resources. �LARSON ET AL. Retrieved from https://www.fishwildlife.org/application/files/ 9915/4049/1625/AWV_-_National_Final_Report.pdf Manfredo, M. J., Teel, T. L., Berl, R. E., Bruskotter, J. T., & Kitayama, S. (2020). Social value shift in favour of biodiversity conservation in the United States. Nature Sustainability, 4, 323– 330. https://doi.org/10.1038/s41893-020-00655-6 Manfredo, M. J., Teel, T. L., Don Carlos, A. W., Sullivan, L., Bright, A. D., Dietsch, A. M., … Fulton, D. (2020). The changing sociocultural context of wildlife conservation. Conservation Biology, 34(6), 1549–1559. https://doi.org/10.1111/cobi.13493 Manfredo, M. J., Teel, T. L., Sullivan, L., & Dietsch, A. M. (2017). Values, trust, and cultural backlash in conservation governance: The case of wildlife management in the United States. Biological Conservation, 214, 303–311. https://doi.org/10.1016/j. biocon.2017.07.032 Martin, A., Coolsaet, B., Corbera, E., Dawson, N. M., Fraser, J. A., Lehmann, I., & Rodriguez, I. (2016). Justice and conservation: The need to incorporate recognition. Biological Conservation, 197, 254–261. https://doi.org/10.1016/j.biocon.2016.03.021 McCright, A. M., Xiao, C., & Dunlap, R. E. (2014). Political polarization on support for government spending on environmental protection in the USA, 1974–2012. Social Science Research, 48, 251–260. https://doi.org/10.1016/j.ssresearch.2014.06.008 McKinney, D., Ris, L., Rorer, H., & Williams, S. (2005). Investing in wildlife: State wildlife funding campaigns. Ann Arbor, MI: The International Association of Fish and Wildlife Agencies & the Ecosystem Management Initiative, University of Michigan School of Natural Resources and Environment. Retrieved from https://www.fishwildlife.org/application/files/5415/1856/1677/ Investing_in_Wildlife_Summary.pdf Naderi, I., & Van Steenburg, E. (2018). Me first, then the environment: Young millennials as green consumers. Young Consumers, 19(3), 280–295. National Center for Education Statistics (NCES). (2019). Digest of Education Statistics: 2019 Tables and Figures. Retrieved from https://nces.ed.gov/programs/digest/d19/tables/dt19_303. 10.asp Outdoor Industry Association. (2017). State funding mechanisms for outdoor recreation. Boulder, CO: Outdoor Industry Association. Retrieved from https://headwaterseconomics.org/wp-content/ uploads/state-rec-fullreport.pdf Peterson, M. N., Hansen, H. P., Peterson, M. J., & Peterson, T. R. (2011). How hunting strengthens social awareness of coupled human-natural systems. Wildlife Biology in Practice, 6(2), 127– 143. https://doi.org/10.2461/wbp.2010.6.10 Peterson, M. N., & Nelson, M. P. (2017). Why the North American model of wildlife conservation is problematic for modern wildlife management. Human Dimensions of Wildlife, 22(1), 43–54. https://doi.org/10.1080/10871209.2016.1234009 Plutzer, E. (2002). Becoming a habitual voter: Inertia, resources, and growth in young adulthood. The American Political Science Review, 96(1), 41–56. Poudyal, N., Cho, S. H., & Bowker, J. M. (2008). Demand for resident hunting in the southeastern United States. Human Dimensions of Wildlife, 13, 158–174. https://doi.org/10.1080/ 10871200801922965 Recovering America's Wildlife Act 2019, H.R. 3742 (116th Congress). (2019–2020). Retrieved from https://www.congress.gov/ bill/116th-congress/house-bill/3742 11 of 12 Rue, P. (2018). Make way, millennials, here comes Gen Z. About Campus, 23(3), 5–12. https://doi.org/10.1177/1086482218804251 Sandbrook, C., Fisher, J. A., Holmes, G., Luque-Lora, R., & Keane, A. (2019). The global conservation movement is diverse but not divided. Nature Sustainability, 2(4), 316–323. https:// doi.org/10.1038/s41893-019-0267-5 Serfass, T. L., Brooks, R. P., & Bruskotter, J. T. (2018). North American model of wildlife conservation: Empowerment and exclusivity hinder advances in wildlife conservation. Canadian Wildlife Biology and Management, 7(2), 101–118. Smith, M. E., & Molde, D. A. (2015). Wildlife conservation and management funding in the U.S. Reno, NV: Nevadans for Responsible Wildlife Management. Retrieved from http://www.nrwm. org/wp-content/uploads/2015/06/Smith-Molde-WildlifeFunding-spreadsheet-Rev-F2-19Jun15.pdf Southwick Associates. (2019). Breaking down excise taxes on firearms and ammunition. Fernandina Beach, FL: Southwick Associates. Retrieved from https://www.southwickassociates.com/ breaking-down-excise-taxes-on-firearms-and-ammunition/ Stedman, R. C., Connelly, N. A., Heberlein, T. A., Decker, D. J., & Allred, S. B. (2019). The end of the (research) world as we know it? Understanding and coping with declining response rates to mail surveys. Society & Natural Resources, 32(10), 1139–1154. Su, C. H. J., Tsai, C. H. K., Chen, M. H., & Lv, W. Q. (2019). U.S. sustainable food market generation Z consumer segments. Sustainability, 11(13), 3607. https://doi.org/10.3390/su11133607 Taylor, P., & The Pew Research Center. (2015). The next America: Boomers, millennials, and the looming generational showdown. New York: Public Affairs. Teaming with Wildlife Act, 2008. S. 2670 (110th Congress). (2007– 2008). Retrieved from https://www.congress.gov/bill/110thcongress/senate-bill/2670 Thomas, N., Gismondi, A., Gautam, P., & Brinkler, D. (2019). Democracy counts 2018: Increased student and institutional engagement. Boston, MA: Tufts University, Institute for Democracy & Higher Education. Retrieved from https://idhe.tufts. edu/sites/default/files/DemocracyCounts2018.pdf United States Census Bureau. (2018). School enrollment in the United States: 2017. Retrieved from https://www.census.gov/ data/tables/2017/demo/school-enrollment/2017-cps.html United States Department of the Interior (USDOI). (2020). Sportsmen and sportswomen generate nearly $1 billion in conservation funding. Washington, DC: U.S. Department of the Interior. Retrieved from https://www.doi.gov/pressreleases/sportsmen-and-sportswomengenerate-nearly-1-billion-conservation-funding United States Fish & Wildlife Service (USFWS). (2018). 2016 National Survey on fishing, hunting, and wildlife-associated recreation (FHW/16-NAT). Washington, DC: U.S., Department of the Interior, U.S. Fish & Wildlife Service, and U.S. Department of Commerce. Retrieved from https://www.fws.gov/ wsfrprograms/subpages/nationalsurvey/nat_survey2016.pdf United States Fish & Wildlife Service (USFWS). (2020). Wildlife and Sportfish Restoration: Historical hunting license data. Retrieved from https://www.fws.gov/wsfrprograms/subpages/licenseinfo/ hunting.htm van Eeden, L. M., Slagle, K., Newsome, T. M., Crowther, M. S., Dickman, C. R., & Bruskotter, J. T. (2020). Exploring nationality and social identity to explain attitudes toward conservation �12 of 12 actions in the United States and Australia. Conservation Biology, 34(5), 1165–1175. https://doi.org/10.1111/cobi.13488 Vaske, J. J. (2019). Survey research and analysis (2nd ed.). Champaign, IL: Sagamore Venture Publishing. Waldron, A., Mooers, A. O., Miller, D. C., Nibbelink, N., Redding, D., Kuhn, T. S., … Gittleman, J. L. (2013). Targeting global conservation funding to limit immediate biodiversity declines. Proceedings of the National Academy of Sciences, 110(29), 12144–12148. https://doi.org/10.1073/ pnas.1221370110 Wilson, A. E., Parker, V., & Feinberg, M. (2020). Polarization in the contemporary political and media landscape. Current Opinion in Behavioral Sciences, 34, 223–228. https://doi.org/10.1016/j. cobeha.2020.07.005 Winkler, R., & Warnke, K. (2013). The future of hunting: An ageperiod-cohort analysis of deer hunter decline. Population and Environment, 34, 460–480. https://doi.org/10.1007/s11111-0120172-6 LARSON ET AL. SU PP O R TI N G I N F O RMA TI O N Additional supporting information may be found online in the Supporting Information section at the end of this article. How to cite this article: Larson, L. R., Peterson, M. N., Furstenberg, R. V., Vayer, V. R., Lee, K. J., Choi, D. Y., Stevenson, K., Ahlers, A. A., AnhaltDepies, C., Bethke, T., T. Bruskotter, J., Chizinski, C. J., Clark, B., Dayer, A. A., Dunning, K. H., Ghasemi, B., Gigliotti, L., Graefe, A., Irwin, K., … Woosnam, K. M. (2021). The future of wildlife conservation funding: What options do U.S. college students support? Conservation Science and Practice, e505. https://doi.org/10.1111/csp2.505 � https://cpw.cvlcollections.org/files/original/d6d4b70bcd141e80fd4743aff3aaa630.pdf a8399f50451b6ed1a737a1e29e3dae2c PDF Text Text Figure S1. U.S. states (in red) containing the 22 large public universities who participated in the student survey effort from 2018-2020. See Table S2 for more details about each institution, sample size, and response rates. �Table S1. Full list of project collaborators at (a) universities and (b) state wildlife agencies by USFWS region and state a) Region SEAFWA WAFWA WAFWA SEAFWA SEAFWA SEAFWA SEAFWA MAFWA WAFWA WAFWA SEAFWA MAFWA MAFWA WAFWA SEAFWA SEAFWA SEAFWA SEAFWA SEAFWA SEAFWA MAFWA NEAFWA NEAFWA MAFWA WAFWA NEAFWA SEAFWA MAFWA SEAFWA SEAFWA WAFWA WAFWA WAFWA NEAFWA MAFWA MAFWA State AL CA CO FL GA GA GA IN KS KS KY MI MI MT NC NC NC NC NC NC NE NY NY OH OR PA SC SD TN TN TX TX TX VA WI WI Role University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University University Organization Auburn University California State University, Fresno University of Northern Colorado University of Florida University of Georgia University of Georgia University of Georgia Indiana University Kansas State University Kansas State University University of Kentucky Michigan Tech University Michigan Tech University University of Montana North Carolina State University North Carolina State University North Carolina State University North Carolina State University North Carolina State University North Carolina State University University of Nebraska, Lincoln Cornell University Cornell University Ohio State University Oregon State University Pennsylvania State University Clemson University South Dakota State University University of Tennessee University of Tennessee Texas A&M University Texas A&M University Texas A&M University Virginia Tech University University of Wisconsin University of Wisconsin Name Wayde Morse Jason Whiting Chelsie Romulo Taylor Stein Kris Irwin Kyle Woosnam Sam Keith James Farmer Adam Ahlers Ryan Sharp Matt Springer Matt Kelly Richelle Winkler Elizabeth Metcalf Lincoln Larson Jerry Lee Nils Peterson Daniel Choi Torey Vayer Rich von Furstenberg Chris Chizinski William Siemer Rich Stedman Jeremy Bruskotter Mark Needham Alan Graefe Shari Rodriguez Larry Gigliotti Neelam Poudyal Kiley Davan Larry Hysmith Gerard Kyle Ben Ghasemi Ashley Dayer Tim Van Deelen Christine Anhalt-Depies �b) Region SEAFWA SEAFWA WAFWA WAFWA WAFWA WAFWA WAFWA SEAFWA SEAFWA SEAFWA MAFWA WAFWA SEAFWA SEAFWA MAFWA WAFWA SEAFWA SEAFWA MAFWA MAFWA NEAFWA NEAFWA MAFWA MAFWA WAFWA WAFWA NEAFWA SEAFWA MAFWA SEAFWA SEAFWA WAFWA NEAFWA MAFWA State AL AL CA CA CO CO CO FL GA GA IN KS KY KY MI MT NC NC NE NE NY NY OH OH OR OR PA SC SD TN TN TX VA WI Role Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Agency Organization Alabma Dept. of Conservation & Natural Resources Alabma Dept. of Conservation & Natural Resources California Dept. of Fish & Wildlife California Dept. of Fish & Wildlife Colorado Parks & Wildlife (CPW) Colorado Parks & Wildlife (CPW) Colorado Parks & Wildlife (CPW) Florida Fish & Wildlife Conservation Commission Georgia Wildlife Federation (GWF) Georgia Dept. of Natural Resources (GADNR) Indiana Dept. of Natural Resources Kansas Dept. of Wildlife, Parks & Tourism Kentucky Dept. of Fish & Wildlife Kentucky Dept. of Fish & Wildlife Michigan Dept. of Natural Resources Montana Fish, Wildlife & Parks North Carolina Wildlife Resources Commission (NCWRC) North Carolina Wildlife Resources Commission (NCWRC) Nebraska Game & Parks Commission Nebraska Game & Parks Commission New York Dept. of Environmental Conservation (NYDEC) New York Dept. of Environmental Conservation (NYDEC) Ohio Dept. of Natural Resources Ohio Dept. of Natural Resources (and NWTF) Oregon Dept. of Fish & Wildlife Oregon Dept. of Fish & Wildlife Pennsylvania Game Commission South Carolina Dept. of Natural Resources (SCDNR) South Dakota Game, Fish & Parks Tennessee Wildife Resources Agency Tennessee Wildife Resources Agency Texas Parks & Wildlife Dept. Virginia Dept. of Game & Inland Fisheries Wisconsin Dept. of Natural Resources Name Marisa Futral Amy Silvano Robert Pelzman Clark Blanchard Mike Quartuch Bryan Posthumus Travis Long Tyler Allen Charles Evans Walter Lane Jack Basiger Aaron Austin Becky Wallen Brian Clark Steve Beyer Greg Lemon Deet James Chet Clark Micaela Rahe Jeff Rawlinson Mike Schiavone Kelly Stang Eric Postell Johanna Dart Allen Molina Brandon Dyches Coren Jagnow Billy Downer Taniya Bethke Randy Huskey Michael May Steve Hall Brian Moyer Keith Warnke �Table S2. (a) Response rate data, (b) enrollment data, and (c) weighting calculations by university campus for surveys of university students in the United States, 2018–2020. The total normalized weight applied to each individual response was multiplicative: school × gender × race or ethnicity. Excel files available upon request. a) School Auburn University California State University, Fresno University of Northern Colorado University of Florida University of Georgia Ball State University Kansas State University University of Kentucky Michigan Tech University University of Montana NC State University University of Nebraska Cornell University Ohio State University Oregon State University Penn State University Clemson University South Dakota State University University of Tennessee Texas A&M University Virginia Tech University of Wisconsin Totals and averages State AL CA CO FL GA IN KS KY MI MT NC NE NY OH OR PA SC SD TN TX VA WI Implementation 2020: Mar-April 2019: Feb-March 2018: Aug-Sept 2019: Sept-Oct 2019: March-April 2018: March-Oct 2018: Feb-March 2018: Nov-Dec 2018: Nov-Dec 2018: Apr-May 2018: Feb-March 2019: Sept-Oct 2018: April 2018: April-May 2019: Nov 2019: Feb-March 2018: Nov-Dec 2019: April 2019: Sept 2019: Sept-Oct 2019: Oct 2018: April-May Sample Completed surveys 5,000 645 5,000 918 3,000 482 10,000 594 7,500 1,111 7,000 423 5,000 845 1,758 370 3,000 946 3,000 478 5,000 893 5,000 1,089 3,701 745 5,000 738 5,000 796 5,000 530 5,000 740 8,552 928 5,000 1,088 16,000 1,122 5,000 1,017 5,000 705 123,511 17,203 Response rate 12.90% 18.36% 16.07% 5.94% 14.81% 6.04% 16.90% 21.05% 31.53% 15.93% 17.86% 21.78% 20.13% 14.76% 15.92% 10.60% 14.80% 10.85% 21.76% 7.01% 20.34% 14.10% 13.93% �b) School Auburn University California State University, Fresno University of Northern Colorado University of Florida University of Georgia Ball State University Kansas State University University of Kentucky Michigan Tech University University of Montana NC State University University of Nebraska Cornell University Ohio State University Oregon State University Penn State University Clemson University South Dakota State University University of Tennessee Texas A&M University Virginia Tech University of Wisconsin Totals and averages State AL CA CO FL GA IN KS KY MI MT NC NE NY OH OR PA SC SD TN TX VA WI Implementation 2020: Mar-April 2019: Feb-March 2018: Aug-Sept 2019: Sept-Oct 2019: March-April 2018: March-Oct 2018: Feb-March 2018: Nov-Dec 2018: Nov-Dec 2018: Apr-May 2018: Feb-March 2019: Sept-Oct 2018: April 2018: April-May 2019: Nov 2019: Feb-March 2018: Nov-Dec 2019: April 2019: Sept 2019: Sept-Oct 2019: Oct 2018: April-May Enrollment Ratio of total enrollment Female proportion Female students White ratio White students 24,628 0.046 0.484 11,920 0.792 19,505 22,125 0.042 0.588 13,010 0.178 3,938 10,232 0.019 0.650 6,651 0.579 5,924 35,491 0.067 0.563 19,981 0.530 18,810 29,611 0.056 0.568 16,819 0.689 20,402 16,160 0.030 0.596 9,631 0.783 12,653 17,869 0.034 0.471 8,416 0.777 13,884 22,136 0.042 0.555 12,285 0.753 16,668 5,797 0.011 0.275 1,594 0.880 5,101 8,306 0.016 0.554 4,602 0.762 6,329 25,199 0.047 0.466 11,743 0.671 16,909 20,830 0.039 0.472 9,832 0.745 15,518 15,182 0.028 0.530 8,046 0.364 5,526 46,820 0.088 0.487 22,801 0.666 31,182 25,699 0.048 0.465 11,950 0.627 16,113 40,363 0.076 0.468 18,890 0.655 26,438 19,669 0.037 0.490 9,638 0.814 16,011 10,544 0.020 0.532 5,609 0.864 9,110 22,815 0.043 0.508 11,590 0.782 17,841 53,743 0.101 0.473 25,420 0.603 32,407 27,811 0.052 0.430 11,959 0.652 18,133 31,705 0.060 0.513 16,265 0.699 22,162 532,735 1.000 0.504 268,653 0.658 350,566 �c) School Auburn University California State University, Fresno University of Northern Colorado University of Florida University of Georgia Ball State University Kansas State University University of Kentucky Michigan Tech University University of Montana NC State University University of Nebraska Cornell University Ohio State University Oregon State University Penn State University Clemson University South Dakota State University University of Tennessee Texas A&M University Virginia Tech University of Wisconsin Totals and averages State AL CA CO FL GA IN KS KY MI MT NC NE NY OH OR PA SC SD TN TX VA WI Ratio of total respondents Prop. female responses No. female responses Prop. white responses No. white responses 0.037 0.502 324 0.866 559 0.053 0.673 618 0.255 234 0.028 0.747 360 0.702 338 0.035 0.649 386 0.617 366 0.065 0.656 729 0.732 813 0.025 0.665 281 0.871 368 0.049 0.567 479 0.864 730 0.022 0.698 258 0.753 279 0.055 0.330 312 0.855 809 0.028 0.567 271 0.882 422 0.052 0.533 476 0.773 690 0.063 0.540 588 0.812 884 0.043 0.649 484 0.527 393 0.043 0.616 455 0.775 572 0.046 0.566 451 0.724 576 0.031 0.523 277 0.781 414 0.043 0.572 423 0.882 653 0.054 0.509 472 0.958 889 0.063 0.553 602 0.816 888 0.065 0.568 637 0.652 732 0.059 0.410 417 0.721 733 0.041 0.600 423 0.810 571 1.000 0.565 9,722 0.751 12,913 Other Weights: Female Male Gender AVERAGE White Non-white Race AVERAGE School weight Normalized weight 1.233 1.149 0.778 0.725 0.685 0.639 1.929 1.797 0.861 0.802 1.234 1.149 0.683 0.636 1.932 1.800 0.198 0.184 0.561 0.523 0.911 0.849 0.618 0.575 0.658 0.613 2.049 1.908 1.043 0.971 2.459 2.291 0.858 0.800 0.367 0.342 0.677 0.631 1.547 1.441 0.883 0.823 1.452 1.353 1.073 1.000 Actual Normalized 0.892 0.878 1.140 1.122 1.016 1.000 0.877 0.780 1.371 1.220 1.124 1.000 �Figure S2. Survey items used to measure college students beliefs about conservation funding and socio-demographic attributes Section 5: Your Thoughts about Funding Conservation 5.2. Would you oppose or support the following potential strategies to help fund wildlife conservation in the future? (Circle ONE response for each item.) Potential strategy to help fund Strongly Oppose Neutral Support Oppose wildlife conservation efforts: Portion of state sales tax dedicated to 1 2 3 4 conservation Portion of state lottery proceeds dedicated to 1 2 3 4 conservation State and local bonds that support conservation 1 2 3 4 Licenses and fees associated with hunting and fishing Licenses and fees associated with other types of outdoor recreation activities (not just hunting and fishing) Excise or special sales tax on hunting and fishing equipment purchases (guns, ammunition, rods and reels, tackle, etc.) Excise or special sales tax on other types of outdoor recreation equipment purchases (hiking gear, tents, kayaks, bikes, binoculars, etc.) Outdoor recreation outfitters (Cabela’s, Bass Pros Shops, REI, etc.) contribute a portion of their annual revenue to conservation Companies that profit from natural resource extraction (oil/gas, timber, etc.) contribute a portion of their annual revenue to conservation 5 5 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Section 6: Background Information 6.1. In what year were you born? Year: ____________ 6.2. With what gender do you identify? Strongly Support □ Female □ Male □ Not listed (specify): �6.3. Which of the following best describes your racial/ethnic background? (Check ALL that apply.) □ White □ Hispanic/Latino □ Black or African American □ Asian □ American Indian or □ Native Hawaiian or Pacific □ Middle Eastern or North ___________________________ Alaska Native Islander □ Other (specify): African 6.4. Which of the following BEST describes your college major or field of study (or likely major, if you are currently undecided)? (Check ONE response.) □ Agriculture & Natural Resources (Agriculture, Ecology, Conservation Biology, Environmental Science, Crop & Soil Science, Animal Science, Natural Resource Management, Parks and Recreation, etc.) □ Science & Math (Biology, Physics, Chemistry, Math, Statistics, Public Health, etc.) □ Engineering & Technology (Engineering, Materials Science, Computer Science, etc.) □ Business & Economics (Accounting, Economics, Finance, Management, etc.) □ Social Science & Humanities (Psychology, Sociology, Anthropology, Political Science, History, English, Religion, Language & Linguistics, Education, etc.) □ Arts (Architecture, Design, Performance Arts, etc.) □ Other (please specify) _____________________________________________________ 6.5. How would you best describe the area where you grew up? (Check ONE response.) □ A large city or urban area (more than 250,000 people) □ A medium-sized city (50,000-250,000 people) □ A small city (10,000 to 50,000 people) □ A small town or rural area (10,000 people or less) □ Other (describe): _____________________________________ �Table S3. Principal Components Analysis (PCA) with orthogonal rotation depicting three-factor structure of itemsa measuring college students’ support for different conservation funding options (n = 15,159) Factor (with Items) Mean SD 1 2 3 1. State funding sources 0.96 0.77 (3 items, Cronbach’s α = 0.826) Portion of state sales tax dedicated to 0.88 0.93 0.191 0.219 0.714 conservation Portion of state lottery proceeds 1.06 0.90 0.108 0.211 0.736 dedicated to conservation State and local bonds that support 0.93 0.84 0.180 0.189 0.735 conservation 2. License fee & excise taxes 0.65 0.83 (4 items, Cronbach’s α = 0.776) Licenses and fees associated with 1.24 0.86 0.346 0.259 0.376 hunting and fishing Licenses and fees associated with other 0.69 1.06 0.286 0.115 0.559 types of outdoor recreation activities (not just fishing and hunting) Excise or special sales tax on hunting and 0.60 1.18 0.122 0.291 0.657 fishing equipment purchases (guns, ammunition, rods and reels, tackle, etc.) Excise or special sales tax on other types 0.04 1.20 0.073 0.123 0.844 of outdoor recreation equipment purchases (hiking gear, tents, kayaks, bikes, binoculars, etc.) 3. Industry funding sources 1.09 0.91 (2 items, Cronbach’s α = 0.748) Outdoor recreation outfitters (Cabela’s, 0.93 1.03 0.255 0.327 0.572 Bass Pro Shops, REI, etc.) contribute a portion of their annual revenue to conservation Companies that profit from natural 1.24 0.98 0.310 0.183 0.805 resource extraction (oil/gas, timber, mining, etc.) contribute a portion of their annual revenue to conservation Items rated on scale ranging from -2 = “strongly oppose” to =2 = “strongly support” Only factor loadings based on Varimax (orthogonal) rotation Note: PAF indicated an optimal three-factor solution that accounted for 69.67% of the variance, with 3 factors containing Eigenvalues > 0.80 and explaining > 10% of the variance; Rotations converged in five iterations; KMO = 0.797, p < 0.001. a b �Table S4. Weighted proportion of college students (with SE) in different demographic groups supportinga different conservation funding options across 22 U.S. states Conservation Funding Categoriesb Industry State User-based Demographic Group n Sources Sources Sources Gender Male 7043 0.68 (0.006) 0.63 (0.006) 0.38 (0.006) Female or not listed 7843 0.75 (0.005) 0.63 (0.005) 0.47 (0.006) Race/ethnicity White 9639 0.73 (0.005) 0.65 (0.005) 0.43 (0.005) Hispanic/Latino 1890 0.74 (0.010) 0.62 (0.011) 0.45 (0.011) Black/African American 602 0.70 (0.019) 0.51 (0.020) 0.44 (0.020) Asian 1870 0.64 (0.011) 0.58 (0.011) 0.40 (0.011) American Indian 246 0.76 (0.027) 0.68 (0.030) 0.42 (0.032) Other/multiracial 614 0.68 (0.019) 0.61 (0.020) 0.42 (0.020) Childhood Location Large city (250k+) 3716 0.70 (0.008) 0.61 (0.008) 0.43 (0.008) Medium city (50-250k) 4321 0.71 (0.007) 0.63 (0.007) 0.44 (0.008) Small city (10-50k) 3618 0.73 (0.007) 0.64 (0.008) 0.43 (0.008) Small town or rural area (<10k) 2638 0.75 (0.008) 0.66 (0.009) 0.40 (0.010) Other 626 0.66 (0.019) 0.57 (0.020) 0.41 (0.020) U.S. Region Northeast (NE) 2413 0.71 (0.009) 0.64 (0.010) 0.43 (0.010) Southeast (SE) 4436 0.74 (0.007) 0.64 (0.007) 0.44 (0.007) Midwest (MW) 4255 0.73 (0.007) 0.63 (0.007) 0.44 (0.008) West (W) 3853 0.68 (0.008) 0.62 (0.008) 0.39 (0.008) College Major Ag & Natural Resources 2534 0.79 (0.008) 0.75 (0.009) 0.53 (0.010) Science & Math 3400 0.72 (0.008) 0.62 (0.008) 0.42 (0.008) Engineering & Technology 3454 0.68 (0.008) 0.60 (0.008) 0.37 (0.008) Business & Economics 2038 0.64 (0.011) 0.56 (0.011) 0.38 (0.011) Social Sciences & Humanities 2805 0.75 (0.008) 0.63 (0.009) 0.45 (0.009) Arts/Other 700 0.75 (0.017) 0.64 (0.019) 0.41 (0.019) Support for funding option defined as mean rating of > 1.0 on scale from -2 (strongly oppose) to +2 (strongly support). b Industry sources include natural resource extraction and outdoor recreation product companies contributing revenue to conservation. State sources include sales taxes, lottery proceeds, and state and local bonds. User-based sources include license/fees and special excises taxes associated with hunting, fishing, or other types of outdoor recreation. a � https://cpw.cvlcollections.org/files/original/0fba63bbfe5913eaf9d88b0bc42d3178.zip 770ede14741d2cc9b378060258955641 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal Articles Description An account of the resource CPW peer-reviewed journal publications Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The future of wildlife conservation funding: What options do U.S. college students support? Description An account of the resource <span>Insufficient funding is a major impediment to conservation efforts around the world. In the United States, a decline in hunting participation threatens sustainability of the “user-pay, public benefit” model that has supported wildlife conservation for nearly 100 years, forcing wildlife management agencies to contemplate alternative funding strategies. We investigated support for potential funding options among diverse college students, a rapidly expanding and politically active voting bloc with a potentially powerful influence on the future of conservation. From 2018 to 2020, we surveyed 17,203 undergraduate students at public universities across 22 states. Students preferred innovative approaches to conservation funding, with 72% supporting funding derived from industry sources (e.g., natural resource extraction companies), 63% supporting state sources (e.g., general sales tax), and 43% supporting conventional user-based sources such as license fees and excise taxes associated with outdoor recreation activities (e.g., hunting). Findings emphasize the need to broaden the base of support for conservation funding and highlight the importance of considering the preferences and perspectives of young adults and other diverse beneficiaries of wildlife conservation.</span> Bibliographic Citation A bibliographic reference for the resource. Recommended practice is to include sufficient bibliographic detail to identify the resource as unambiguously as possible. Larson, L. R., Peterson, M. N., Furstenberg, R. V., Vayer, V. R., Lee, K. J., Choi, D. Y., ... &amp; Woosnam, K. M. (2021). The future of wildlife conservation funding: What options do US college students support?. Conservation Science and Practice, e505. <a href="https://doi.org/10.1111/csp2.505" target="_blank" rel="noreferrer noopener">https://doi.org/10.1111/csp2.505</a> Creator An entity primarily responsible for making the resource Larson, Lincoln R. Peterson, Markus Nils Von Furstenberg, Richard Vayer, Victoria R. Lee, Kangjae Jerry Choi, Daniel Y. Stevenson, Kathryn Ahlers, Adam A. Anhalt-Depies, Christine Bethke, Taniya Bruskotter, Jeremy T. Chizinski, Christopher J. Clark, Brian Dayer, Ashley A. Dunning, Kelly Heber Ghasemi, Benjamin Gigliotti, Larry Graefe, Alan Irwin, Kris Keith, Samuel J. Kelly, Matt Kyle, Gerard Metcalf, Elizabeth Morse, Wayde Needham, Mark D. Poudyal, Neelam C. Quartuch, Michael R. Rodriguez, Shari Romulo, Chelsie Sharp, Ryan L. Siemer, William Springer, Matthew T. Stayton, Brett Stedman, Richard Stein, Taylor Van Deelen, Timothy R. Whiting, Jason Winkler, Richelle L. Woosnam, Kyle Maurice Subject The topic of the resource Angling College students Conservation policy Funding Hunting Public support Wildlife management Extent The size or duration of the resource. 12 pages Date Created Date of creation of the resource. 2021-07-26 Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/InC-NC/1.0/" target="_blank" rel="noreferrer noopener">In Copyright - Non-Commercial Use Permitted</a> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noreferrer noopener">Attribution 4.0 International (CC BY 4.0)</a> Format The file format, physical medium, or dimensions of the resource application/pdf Language A language of the resource English Is Part Of A related resource in which the described resource is physically or logically included. Conservation Science and Practice Type The nature or genre of the resource Article