https://cpw.cvlcollections.org/files/original/6d2fe7e1883b398b9ef6b1dc0979f990.pdf bf82e1aaf8c170491fdb6739d87c32fc PDF Text Text The research in this publication was partially or fully funded by Colorado Parks and Wildlife. Heather Disney Dugan, Acting Director, Colorado Parks and Wildlife • Parks and Wildlife Commission: Carrie Besnette Hauser, Chair • Dallas May, ViceChair • Marie Haskett, Secretary • Taishya Adams • Karen Michelle Bailey • Betsy Blecha • Gabriel Otero • Duke Phillips, IV • Richard Reading • James Jay Tutchton • Eden Vardy �Version of Record: https://www.sciencedirect.com/science/article/pii/S0006320718316276 Manuscript_1b3648804f9d9cc7ffe98b71a99b4c17 Understanding and managing human tolerance for a large carnivore in a residential setting Type of paper: Research Paper Running head: Tolerance for large carnivores Keywords: black bears, social science, human-bear conflict, Colorado, bear-proofing, humanwildlife conflict Word count: 5848 Stacy A. Lischkaa,b, Tara L. Teelc, Heather E. Johnson d,1, and Kevin R. Crooksb a Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Ave., Fort Collins, CO, USA 80526 b Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA, 80523 c Department of Human Dimensions of Natural Resources, Colorado State University, Fort Collins, CO, USA 80523 d Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 415 Turner Dr., Durango, CO, USA 81301 1 Present address: U.S. Geological Survey, Alaska Science Center, 410 University Drive, Anchorage, AK, USA 99508 Corresponding Author: Stacy Lischka, Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA, 80523; E-mail: stacy.lischka@colostate.edu Role of the Funding Source This project was funded by Colorado Parks and Wildlife, USDA National Wildlife Research Center, Anheuser-Busch Environmental Fellowship, and Hill Memorial Fellowship. Researchers at Colorado Parks and Wildlife and USDA National Wildlife Research Center designed the study, conducted data collection and analysis, and interpreted data. Acknowledgements We thank residents of the City of Durango for completing surveys and S. Coons, C. Jager, L. Mengak, and R. Wilbur for field assistance. We thank G. Wittemyer, J. Ivan, and M. Quartuch for valuable feedback on earlier drafts of this paper. This project was funded by Colorado Parks and Wildlife, USDA National Wildlife Research Center, Anheuser-Busch Environmental Fellowship, and Hill Memorial Fellowship. The survey and administration procedures were approved for use with human subjects prior to implementation (CSU IRB protocol 005 -17H). Black bear care and handling procedures were approved for use with animals prior to implementation (Colorado Parks and Wildlife Animal Care and Use Protocol #01-2011). © 2019 published by Elsevier. This manuscript is made available under the Elsevier user license https://www.elsevier.com/open-access/userlicense/1.0/ �1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 Understanding and managing human tolerance for a large carnivore in a residential system ABSTRACT Human tolerance for interactions with large carnivores is an important determinant of their persistence on the landscape, yet the relative importance of factors affecting tolerance is not fully understood. Further, the impact of management efforts to alter tolerance has not been adequately assessed. We developed a model containing a comprehensive set of predictors drawn from prior studies and tested it through a longitudinal survey measuring tolerance for black bears (Ursus americanus) in the vicinity of Durango, Colorado, USA. Predictors included human-bear conflicts, outcomes of interactions with bears, perceptions of benefits and risks from bears, trust in managers, perceived similarity with the goals of managers, personal control over risks, value orientations towards wildlife, and demographic factors. In addition, we monitored changes in tolerance resulting from a bear-proofing experiment designed to reduced garbage-related conflicts in the community. Residents who perceived greater benefits associated with bears and more positive impacts from bear-related interactions had higher tolerance. Residents who perceived greater risks and more negative impacts and who had greater trust in managers, domination wildlife value orientations, and older age were less tolerant. Conflicts with bears were not an important predictor, supported by our finding that changes in conflicts resulting from our bear-proofing experiment did not affect tolerance. In contrast to conservation approaches that focus primarily on decreasing human-wildlife conflicts, our findings suggest that communication approaches aimed at increasing public tolerance for carnivores could be improved by emphasizing the benefits and positive impacts of living with these species. KEYWORDS Black bear, Ursus americanus, Colorado, social science, human-bear conflict, human-wildlife conflict 1. INTRODUCTION The conservation of mammalian carnivores is often challenging, particularly in systems dominated by humans (Chapron et al. 2014). Frequent and intense interactions between people and carnivores are the root cause of many of the challenges (Woodroffe et al. 2005). While some of these interactions can have positive outcomes for people, conflicts between humans and wildlife can lead to intolerance of species among people who face real and perceived impacts related to their health, safety, livelihoods, and property (Kansky and Knight 2014). Intolerance has the potential to affect the long-term sustainability of carnivore populations, especially when manifest as illegal killing or support for large-scale efforts to reduce populations (Treves and Bruskotter 2014). As a result, management actions focused on increasing tolerance can help create landscapes with enhanced social support for conservation, and ultimately, carnivore persistence (Bruskotter and Wilson 2014). Tolerance is defined as an individual’s or group’s acceptance of negative effects and desire for positive effects arising from interactions with wildlife populations (Decker and Purdy 1 �46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 1988, Carpenter et al. 2000, Bruskotter et al. 2015, Streubig et al. 2018). Therefore, an individual who has a high tolerance for a species will state a preference for a larger population, whereas an individual with a lower tolerance will prefer a smaller population (Carpenter et al. 2000). Fundamentally, tolerance is a measure of attitudes toward wildlife. However, in practice, the term is sometimes used to describe both attitudes (e.g., favorable evaluations of species and the outcomes of conservation) and resulting behaviors (e.g., illegal killing, voluntary donations to support conservation; Bruskotter et al. 2015). Although tolerance as a concept can help wildlife managers quantify human preferences for wildlife populations in management decisions, there is little information about the relative importance of factors that affect tolerance and the influence of different management actions on it. As a result, managers have had limited success in applying management strategies that alter tolerance for specific species in the field (Gigliotti et al. 2000, Bruskotter et al. 2015). Researchers have attempted to measure and predict attitudes associated with tolerance for different species globally (e,g., Riley and Decker 2000, Lischka et al. 2008, Carter et al. 2012, Zajac et al. 2012, Inskip et al. 2016, Kansky et al. 2016, Struebig et al. 2018), assessing a variety of explanatory variables that draw from existing knowledge about the factors affecting attitudes more generally (Figure 1). Early efforts to understand the drivers of tolerance drew primarily from the experiences of wildlife managers. Based on input from stakeholders, managers typically assumed that the experience of negative interactions with wildlife was the most important determinant of an individual’s tolerance of a species (Conflict Model, Figure 1; Decker and Purdy 1988). While conflicts can include a wide range of interactions between people and wildlife (or between groups of people – i.e., human-human conflict over wildlife issues; Peterson et al. 2010, Hill et al. 2017), early studies of tolerance established a link between negative outcomes of interactions for people and reduced tolerance for species (Organ and Ellingwood 2000). A focus on conflicts gave managers a specific set of interactions to mitigate, yet it failed to recognize the influence of positive human-wildlife interactions on tolerance. To address this issue, Riley et al. (2002) proposed a broader measure of the outcomes of interactions with wildlife, termed impacts (Impacts Model, Figure 1). Impacts are defined as the important cognitive and emotional outcomes of both positive and negative human-wildlife interactions. For example, potential impacts resulting from seeing wildlife near one’s home might be feeling excitement or fear from the interaction, or confidence that management efforts are effective at maintaining the species. Impacts have been shown to be an important predictor of tolerance (Lischka et al. 2008), providing a mechanism to account for a wider array of outcomes of human-wildlife interactions. While these approaches (conflicts and impacts) largely stemmed from perceptions of wildlife managers, they are not strongly rooted in social science theory (Gigliotti et al. 2000). To address this need, researchers applied hazard acceptance theory to examine the influence of a suite of psychological variables (risks and benefits from wildlife species, trust in managers, perceived similarity with management agencies, and personal control over risks) on tolerance (Zajac et al. 2012, Bruskotter and Wilson 2014). This approach (Psychological Model, Figure 1) demonstrated that perceptions of the general risks and benefits associated with a species (e.g., the community is likely to experience more human-wildlife conflicts in the future, the species improves ecosystem health) were the primary proximate drivers of tolerance. Higher-order 2 �91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 influences, including trust in management agencies and perceived personal control over risks, affected tolerance indirectly through their influence on perceived risks and benefits. In contrast to measures of human-wildlife conflicts and impacts, which reflect the outcomes of direct interactions with wildlife, measures of perceived risks and benefits describe more general perceptions of the consequences of living with wildlife and the value gained from their existence (Kansky et al. 2016). Other factors drawn from social science theory have also proven useful in understanding tolerance. For example, wildlife value orientations (WVOs), defined as sets of basic beliefs about wildlife that provide contextual meaning to more general values, explain variation in a wide range of attitudes, including tolerance (Values Model, Figure 1; Zinn et al. 2000, Teel and Manfredo 2009). While WVOs have explained some patterns in tolerance, we expect that more specific and salient beliefs about species and interactions (impacts and risks/benefits) would have a stronger direct effect (Zinn et al. 2000). In addition, demographic characteristics such as gender and age are commonly explored in assessments of attitudes toward wildlife (Demographic Model, Figure 1; Kansky and Knight 2014). Demographics are likely to have less influence on tolerance, however, because they reflect latent influences, such as when gender represents differences in individuals’ power to employ risk-reducing behaviors rather than actual differences in attitudes toward carnivores (Carter et al. 2014). Although researchers have identified a variety of predictors of tolerance for different species and in different systems, these factors have not been simultaneously tested to identify their relative importance. To address this need, we developed a more comprehensive model containing a diverse suite of predictors drawn from prior research (Figure 1), and tested it through a longitudinal study of tolerance for black bears (Ursus americanus) in the vicinity of Durango, Colorado, USA. Using a survey of community residents, we explored the relative influence of human-bear conflicts, outcomes of human-bear interactions, perceptions of bearrelated benefits and risks, trust in managers, perceived similarity with the goals of managers, personal control over risks, wildlife value orientations, and demographics on tolerance for black bears. Further, we determined whether a bear-proofing experiment designed to reduce garbagerelated conflicts in the community was successful at increasing tolerance. Conflicts and interactions between people and black bears have been increasing across the U.S. (Hristienko and McDonald 2007), yet black bears are highly valued by urban and rural residents alike (Morzillo et al. 2010, Lowery et al. 2012), making them an excellent case study for understanding tolerance. By identifying important predictors of tolerance, as well as the effects of management actions on tolerance, our intention was to inform development of more holistic approaches to understanding tolerance that could be tested and applied in other contexts. Ultimately, this information is critical to designing efforts to increase support for maintaining carnivore populations in increasingly human-dominated landscapes. 2. METHODS 2.1 Study area 3 �136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 The city of Durango is located in southwest Colorado, along the Animas River, at an elevation of 1,988 m. The city is surrounded by mountainous public land and dominated by ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), pinyon pine (Pinus edulis), juniper (Juniperus spp.), aspen (Populus tremuloides), and mountain shrubs (i.e., Prunus virginiana, Peraphyllum ramosissimum, etc.) that provide diverse natural food sources for black bears. Long-term population trends of bears in the area are unknown, but between 2011 and 2014, a capture-mark-recapture study estimated that the female bear population in the vicinity of Durango declined from 176 to 82 bears (Laufenberg et al.2018). The decline was largely attributed to high rates of human-caused bear mortality when bears increased their use of human development during a natural food shortage. Durango, with a human population of approximately 18,500 individuals, has grown rapidly since 1970 (U.S. Census Bureau 2017), resulting in increases in anthropogenic foods available to bears. These food sources are concentrated around residential developments, leading to high rates of human-black bear interactions (Baruch-Mordo et al. 2008, Johnson et al. 2018). In response, the city of Durango implemented an ordinance in 2010 requiring residents to keep garbage in a locked wildlife-resistant container or a secured location such as a garage or shed. Despite the ordinance, high rates of reported human-bear conflicts motivated us to experimentally test the effectiveness of bear-resistant garbage containers for reducing garbagerelated human-bear conflicts (Johnson et al. 2018). Using a Before-After-Control-Impact (BACI) design (Williams et al. 2002), we collected pre-treatment data in 2011 and 2012. Then, in 2013, we distributed bear-resistant garbage containers, free-of-charge, to each household (1,145 residences) in 2 residential sections of the city (1 in the north and 1 in the south). In 2 paired control areas (1,123 residences), we did not distribute containers and residents could choose whether to use a regular garbage container or a bear-resistant container that they paid for themselves. To test the effectiveness of this experiment, we monitored rates of garbage-related human-bear conflicts throughout the treatment and control areas between 2011 and 2016, collecting data for 2 years before the deployment of the containers (2011-2012; pre-treatment) and for 4 years after deployment of the containers (2013-2016; post-treatment). 2.2 Data collection From January to April 2012, 2014, and 2016, we sent self-administered mail surveys to all households within Durango city limits (n = 5,852), as well as a random sample of 1,500 residents of near-town areas. Included in our overall sample were all residents of the experimental area (control and treatment areas). The 2014 survey was designed to measure tolerance for bears, as well as the relative importance of all predictors (Figure 1, Appendix C). The 2012 and 2016 surveys also measured tolerance and were used to evaluate changes in this variable only among residents of the bear-proofing experimental area. We identified names and addresses for mailings from the La Plata County Assessor’s spatially referenced plat maps and tax roll information. We administered the surveys using a modified version of the Tailored Design Method (Dillman et al. 2014) with 5 total mailings including 1 invitation letter, 2 mailings of the printed survey, and 2 postcard reminders. Respondents were also offered the option to reply via an online survey in each mailing. Non4 �181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 response bias was assessed with a postcard mailed to individuals who did not return the full survey. The postcard contained a subset of 5 questions to allow for comparison to the full survey and known characteristics of the Durango population from the U.S. Census. All survey materials and procedures met the approval of XXX’s Institutional Review Board (Protocol #XXX-XXX). 2.3 Measurement and analysis Tolerance, our response variable, has been examined using a variety of approaches, including attitudinal (e.g., desired future population size) and behavioral (e.g., illegal killing, voting, contributing to conservation organizations) measures (Riley and Decker 2000, NaughtonTreves et al. 2003, Treves and Martin 2014, Bruskotter et al. 2015, Struebig et al. 2018). We chose to employ a commonly used attitudinal measure – desired future population size for bears – which offers a standardized approach to quantifying tolerance through the use of a single survey question (e.g., Riley and Decker 2000, Bruskotter et al. 2015, Struebig et al. 2018). Based on the findings of Bruskotter et al. (2015), which found a high correlation between attitudinal and behavioral measures of tolerance, we assumed that this attitudinal measure would also accurately predict behaviors resulting from tolerance. Specifically, we asked respondents to report their preferences for a change in the size of the bear population near their home over a 2year period, on a 5-point scale from 1 = decrease greatly to 5 = increase greatly, with a midpoint of 3 = stay the same (Riley and Decker 2000, Bruskotter et al. 2015, Struebig et al. 2018; Appendix C). We expected respondents with a lower tolerance for bears would prefer a decrease in the current bear population, while those with a higher tolerance would prefer an increase (Carpenter et al. 2000). For predictors within the Conflict Model, we measured prior experience with human-bear conflict by asking survey respondents to report the number of times over the past 2 years they experienced a suite of 11 interactions with bears in the area where they live, on a 4-point scale (“How often have you experienced the following interactions with black bears in the area where you live?” Response options: 0 = 0 times, 1 = 1-2 times, 2 = 3-4 times and 3 = ≥5 times; Figure 2, Appendix C). Conflicts included interactions likely to result in nuisances for the household (e.g., bear got into my garbage or damaged fruit trees; Nuisance conflicts) as well as interactions likely to threaten human or domestic animal safety (e.g., bear attacked or harassed pets or livestock; Safety conflicts). For Nuisance conflicts, we summed the frequency values for all nuisance-causing conflicts. Because few people reported experiencing Safety conflicts, we recoded these into a binary variable (1 = experienced ≥ 1 safety conflict, 0 = did not experience a safety conflict; Wilbur et al. 2018). We followed the methods of Lischka et al. (2008) to quantify predictors in the Impacts Model. We asked respondents to report whether they had experienced a suite of 33 (12 positive, 28 negative) affective (emotion-based) outcomes of interactions with bears over the past 2 years (e.g., feeling fear or excitement when they saw a bear) and across 3 different settings (i.e., around home, in town, and in natural areas outside of town), where 1 = experienced the outcome and 0 = did not experience the outcome (Appendix A.1, Appendix C). We also asked respondents to report the importance of each outcome on a 3-point scale from 1 = not at all important to 3 = very important. Because impacts are defined as outcomes of interactions that are 5 �226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 both recognized and important, we retained only impacts that respondents reported having experienced and felt were important. We weighted the retained impacts by responses to a third question rating the respondent’s desired change in the frequency at which they experienced the outcome (ranging from 0 = no change to 2 = large change). We summed the resulting values across all positive and negative impacts separately, resulting in a score for positive impacts (Positive impacts) and negative impacts (Negative impacts). We measured predictors in the Psychological Model following methods of Zajac et al. (2012). We created scales from multi-item questions measuring respondents’ perceived benefits (e.g., The presence of black bears improves the quality of life in Durango; Benefit) and risks (e.g., I fear having an encounter with black bears; Risk) associated with bears, trust in the management agency (e.g., I am confident Colorado Parks and Wildlife [CPW] can effectively manage black bears; Social trust), perceptions of the degree to which the agency shares their goals (e.g., I believe CPW shares values similar to mine; Social value similarity), and personal control over risks related to bears (e.g., I have the ability to protect my property from wildlife; Personal control; Appendix A.2). Individual items were measured on a 5-point scale from 1 = strongly disagree to 5 = strongly agree (Appendix C). Because these measures were derived from previously validated scales, we conducted a factor analysis (Principal Axis Factoring) for each scale (5 total) to reduce dimensionality and calculate values for each respondent (Johnson 1998). We assessed scree plots and eigenvalues to determine the appropriate number of factors to retain (Appendix A.2; Johnson 1998) as well as factor loadings to denote practical significance (> 0.40; Devellis 2012), and conducted reliability analysis (Cronbach’s α) to test the internal consistency of each scale (Cortina 1993). To improve scale reliability, we removed several items from the Risk and Personal control scales (Appendix A.2). With these modifications, all scales exhibited acceptable internal consistency (α > 0.6, Vaske 2008). For the Values Model, we measured WVOs following the methods of Teel and Manfredo (2009), modified to a reduced 14-item set (Chase et al. 2016; Appendix A.3, Appendix C). Respondents rated these items, representing basic beliefs about wildlife and wildlife management, on a 7-point scale from 1 = strongly disagree to 7 = strongly agree. We computed scores on two value orientation scales, domination (view of wildlife that prioritizes human wellbeing over wildlife and treats wildlife in utilitarian terms; Domination) and mutualism (view that places greater emphasis on equality, caring, and compassion for wildlife; Mutualism), by averaging responses to corresponding belief items. For the Demographic Model, we asked respondents to report the year of their birth (to calculate Age by subtracting from 2014), gender (Gender; Reference class = male), and highest level of education completed (Education; 1 = some post-secondary education, 2 = Bachelor’s degree or higher, Reference class = high school diploma or less; Table 1, Appendix C). To assess the relative influence of predictors of Tolerance, we conducted linear regression modeling using responses to the 2014 survey. We compared the ability of each of the 5 a priori models (Conflict, Impacts, Psychological, Values, Demographic) and a global model (including all predictor variables; Figure 1) to explain Tolerance (Appendix B.1). We compared models using Akaike’s Information Criteria (AIC), where models with the lowest AIC values 6 �271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 reflect more empirical support from the data (Burnham and Anderson 2010). We identified important explanatory variables in the global model by determining where 95% confidence intervals (CIs) around standardized regression coefficients excluded zero. We only retained survey responses that included data for all predictor variables. Prior to modeling, we assessed multicollinearity by inspecting bivariate correlations (Pearson’s r) among predictor variables (Appendix B.2). Where r > 0.50, we inspected Variance Inflation Factor (VIF) values. If VIF values were > 5, we removed the variable with the weaker correlation with Tolerance (Zar 1999). We also used linear regression to investigate whether Tolerance changed in response to the bear-proofing experiment, using responses from the 2012 and 2016 surveys. We chose to use 2012 and 2016 survey responses to maximize the potential to detect an impact of the experiment and avoid multiple responses from the same residences. We analyzed Tolerance using a BACI, where we tested for a significant interaction between Time (pre-treatment [2012] vs. posttreatment [2016]; Reference class = pre-treatment) and Treatment (treatment vs. control area; Reference class = control). Because we suspected that differences between north and south neighborhoods may influence Tolerance (Johnson et al. 2018), we also included site as a binary variable (Reference class = north). We ran a single linear regression model that included Time, Treatment, Site, and Time × Treatment as fixed effects. We identified important explanatory variables by determining where 95% CIs around standardized regression coefficients excluded zero, and evaluated the impact of the experiment by assessing the Time × Treatment interaction. All analyses were conducted in SPSS (version 24.0, Chicago, Illinois). 3. RESULTS 3.1 Survey response After removing undeliverable addresses (n2012 = 524, n2014 = 698, n2016 = 1,117), our adjusted response rates were 55% in 2012 (n = 2,944), 45% in 2014 (n = 2,316), and 51% in 2016 (n = 2,432). When we assessed potential non-response bias, we found that homeowners were represented in our sample at a rate higher (85% in 2012, 85% in 2014, 83% in 2016) than homeownership rates in Durango (49%; U.S. Census Bureau 2017). Further, Tolerance of homeowners was significantly lower than that of renters ( x own = 2.63, SE own = 0.03, x rent = 2.99, SE rent = 0.02, t2326 = -9.64, p < 0.001, Cohen’s d = 0.37). We found no other statistically significant differences between respondents and non-respondents (p > 0.05). As a result, we chose to weight survey data by homeownership to allow for more accurate generalization of study findings to the population (Groves 2006). Within the 2014 respondent data (n = 2,316), 50% of respondents were male and 50% were female. A plurality (41%) earned a bachelor’s degree as their highest level of education, another 30% earned a graduate degree, and 15% attended at least some college. The mean age of respondents was 50.1 years old (SE = 0.36, range: 16-101 years). 3.2 Tolerance modeling 7 �316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 From the full respondent pool in 2014, 745 respondents returned surveys with complete data for all predictor variables. For our measure of Tolerance, more than half (53%) of respondents reported wanting the bear population near their home to stay the same over the next 2 years, while 29% wanted a decrease and 18% wanted an increase. Respondents most frequently reported the conflicts of having had a bear break into their garbage, heard about someone being harassed by a bear, and had a bear damage fruit trees or other property (Figure 2). Reported rates of nuisance- and safety-related conflicts did not change between the pre-treatment and treatment periods (p > 0.05 for all tests). Respondents experienced an average of 3.2 Positive impacts (SE = 0.16, range: 0-24) and 6.7 Negative impacts (SE = 0.31, range: 0-44) resulting from their interactions with bears (Appendix A.1). The most common impacts were feeling that the area was good wildlife habitat when seeing bears in natural areas (59%) or in town (51%), feeling connected to nature when seeing bears in natural areas (56%), and feeling excited when seeing bears in natural areas (54%) or near home (54%). Mean scores on the Domination scale were moderate ( = 4.17, SE = 0.04, range: 1-7), representing the degree to which respondents held utilitarian value orientations. Mean scores for the Mutualism scale were also moderate ( = 4.79, SE = 0.05, range: 1-7), reflecting the degree to which respondents placed more of an emphasis on caring and compassion for wildlife. Among the 5 a priori models we compared, the Psychological model provided the best fit to our Tolerance data (Table 1), with an r2 value of 0.43. The Impacts model (r2 = 0.19), Values model (r2 = 0.15), Conflict model (r2 = 0.08), and Demographic model (r2 = 0.06) had decreasing ability to explain Tolerance. The global model had an AIC value 30 units less than the Psychological Model, indicating that additional variables significantly improved model fit, but yielded only slight gains in explanatory power (r2 increased from 0.43 to 0.46; Table 1). In the global model, Positive impacts, Negative impacts, Benefit, Risk, Social trust, Domination, and Age had 95% CIs that excluded zero (Table 2). Positive impacts and Benefit had a positive relationship with Tolerance, indicating that people who perceived more positive outcomes of their interactions with bears and assigned greater benefits to them were more tolerant. In contrast, Risk and Negative impacts had a negative relationship, where individuals who assigned a greater level of risk to bears and who perceived more negative outcomes of interactions had lower tolerance. Social trust also had a negative relationship, indicating that residents who reported higher trust in the agency to address interactions with bears were less tolerant. Older respondents and those with Domination value orientations were also less tolerant of bears. Of these 7 factors, the magnitude of effect of Benefit and Risk was largest (Figure 3). After the deployment of bear-resistant containers, observed rates of garbage-related conflicts in the treatment areas slightly declined, while conflicts in control areas significantly increased (Johnson et al. 2018). Although the management experiment assumed that a reduction in human-bear conflicts in the treatment area relative to the control area would increase tolerance for bears, the Time × Treatment effect was not meaningful in modeling (Table 3). Tolerance before (2012) and after (2016) the deployment of the bear-resistant containers was not significantly different (Table 3; Figure 4), as mean values before and after the distribution of bear-resistant containers were similar in treatment ( ̅ 2012 = 2.78 [SE = 0.045]; ̅ 2016 = 2.82 [SE = 0.05]) and control ( ̅ 2012 = 2.95 [SE = 0.04]; ̅ 2016 = 2.92 [SE = 0.05]) areas. Tolerance values 8 �360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 were slightly higher in control areas and in the south neighborhood during all years, a pattern that did not change in response to shifting patterns of conflicts. 4. DISCUSSION For tolerance to become a useful tool in the practice of wildlife conservation, it is critical to understand the factors driving it and how they are affected by conservation actions. By testing the relative importance of a suite of predictors posited in prior studies, we provide guidance on the combination of drivers likely to influence tolerance. In contrast to many of the assumptions that underlie management of negative interactions with black bears, our models indicated that residents’ reported experiences with safety- and nuisance-related conflicts with bears did not strongly affect their tolerance for the species. In fact, the benefits attributed to bears played the most important role in determining a person’s tolerance for bears. Notably, we were able to ground-truth our model predictions by testing if tolerance for bears changed as a result of a largescale bear-proofing experiment designed to reduce human-bear conflicts (Johnson et al. 2018). Although treatment areas experienced small declines in observed conflicts with the distribution of garbage containers, control areas experienced a significant increase in conflicts. Despite these changes, tolerance for bears was consistent between 2012 and 2016 in both the treatment and control areas. In addition, a sizeable (57%) reduction in the female bear population in the vicinity of Durango (Laufenberg et al. 2018) did not appear to affect tolerance for bears in 2014. During late summer 2012, there was a major shortage of natural foods for bears around Durango, causing bears to increase their use of anthropogenic foods and resulting in an increase in humaninduced mortality (e.g., vehicle collisions, lethal removals; Laufenberg et al. 2018). Although trends in bear population sizes are not necessarily indicative of trends in human-bear interactions (Towns et al. 2009), our results suggest that experiences with human-bear conflicts in and of themselves do not strongly shape tolerance for bears; however, the cognitive and emotional outcomes of these experiences can. While it is possible that there may be a time lag between changes in conflicts and changes in tolerance, we feel that measuring tolerance 3 years after distribution of the garbage containers reflected a timeframe in which most managers would expect results. Yet, in our experiment, we found that conflict management efforts did not alter tolerance for bears over this time period. In our modeling, perceived risks and benefits associated with bears were most important in explaining variation in tolerance. Similarly, we found that both the positive and negative outcomes of interactions with bears (i.e., impacts) were important drivers. Further, the contribution of perceived benefits was greater than that of perceived risks and negative impacts, a pattern that may contradict the perceptions of many practitioners. This finding suggests that efforts to modify tolerance for bears and other carnivores may be more successful if designed to focus on benefits provided by the species in conjunction with risks, rather than focusing on risks alone. Consistent with our conclusions, Slagle et al. (2013) found that exposure of Ohio residents to communication messages describing benefits of bears to people and ecosystems yielded an increase in tolerance, whereas messages focused solely on risks did not. Therefore, we suggest that existing strategies to change attitudes and behaviors toward bears could also be modified to improve results. For example, standard “BearAware” materials used across the U.S. to encourage strategies for coexistence with bears focus messaging almost exclusively on minimizing risks to 9 �405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 bears (Gore et al. 2008; Baruch-Mordo et al. 2011). Messages such as “garbage kills bears” commonly comprise the core of such messaging. While the intent of these efforts may be to encourage human behaviors to reduce conflicts and increase tolerance for bears, our results suggest that tailoring content to highlight the benefits to people of living with bears could be more effective at increasing tolerance. Specifically, communication highlighting the role bears play in a healthy ecosystem as well as recreational and other quality of life benefits that might accrue from their presence may promote more positive perceptions and thereby increase tolerance. We found that individuals who expressed higher trust in the wildlife agency to effectively manage black bears were less tolerant of the species. We hypothesize that this relationship between tolerance and social trust, an indicator of perceived capacity of the agency to effectively manage human-bear conflicts, may be mediated by other factors, including whether individuals support the specific actions used by managers to address those conflicts. While agencies often employ a variety of approaches to minimize human-bear conflict, the approaches most notable to the public are frequently those that involve lethal removal of conflict-involved bears. Support for lethal responses to human-wildlife conflict tends to be lowest among people who are most tolerant of the species (Inskip et al. 2014). Although we did not directly explore the relationship between agency trust and specific management actions here, items on our survey provide some insight. Specifically, we found that residents who desired the largest reduction in the number of bears killed in response to conflict reported lower trust scores ( = -0.10 [SE = 0.07]) than residents who felt the number of bears killed was acceptable (Social trust: = 0.07 [SE = 0.06]). We expect that individuals who are more accepting of lethal control are also less tolerant of bears. In light of this finding, the influence of broader factors, such as value orientations toward wildlife, becomes an important consideration. Given previous research demonstrating the effect of wildlife value orientations on attitudes toward a host of wildlife-related issues, including trust in wildlife management agencies (Manfredo et al. 2017) and support for management actions such as lethal control (e.g., Manfredo et al. 2016), it is reasonable to assume that these orientations could have an indirect influence on tolerance. However, our model also identified a direct effect on tolerance; people with an orientation prioritizing the needs of humans over wildlife (i.e., domination) were less tolerant of bears. While it may be nearly impossible to alter people’s values toward wildlife (Manfredo et al. 2016), understanding how those values influence tolerance may help identify situations where the success of conservation actions will be impacted by social support. For instance, in areas with a high prevalence of domination value orientations there may be less support for efforts to reintroduce and recover carnivores. In such situations, practitioners might face substantial social conflict over conservation interventions, requiring more intensive and targeted efforts to build support (Bruskotter 2013). Social science information can help anticipate where that social conflict might occur over species protection. In these situations, information about value orientations and other psychological concepts can be useful to help frame communication messages that are more likely to resonate with target audiences (Teel and Manfredo 2009). 5. CONCLUSION 10 �450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 Local and regional governments, management authorities, and conservation organizations globally are attempting to promote efforts to conserve carnivore species that can be involved in conflicts with people (Woodroffe et al. 2005). Ultimately, the long-term success of these efforts hinges on people’s tolerance for the species, particularly in places where conflicts occur frequently. This study, which was conducted in an area with a high frequency and intensity of interactions between residents and black bears, offers insights that may be applicable to understanding tolerance in other systems and for other carnivore species. By drawing from psychological theory and conservation practice, we were able to identify the important role of the outcomes of both positive and negative interactions between people and wildlife in determining tolerance. Indeed, consistent with prior research on other carnivore species (e.g., Inskip et al. 2016), residents commonly experienced both positive and negative consequences of living in an area shared by black bears. In fact, a majority (72%) of respondents to our survey reported experiencing at least some nuisance-related conflicts with bears in the previous 2 years, yet 46% also reported at least one positive impact from their interactions with bears. The occurrence of human-bear interactions in this study system is not likely to decrease in the future, especially given projected changes in land use and climate (Johnson et al. 2015, 2017). While the relative importance of specific drivers of tolerance may vary across locations and social contexts, our findings could have particular relevance for areas where interactions between humans and large carnivores are common and increasing. Further, our model integrated tolerance-related concepts from prior studies conducted across various contexts and species, thereby offering a more comprehensive approach that not only proved valuable in our bear case, but also warrants testing for use in other systems. We suggest that efforts to increase tolerance for bears and other carnivores can be improved by more adequately accounting for the underlying psychological influences that play a role in shaping human-wildlife interactions more broadly. This would include communication aimed at highlighting the positive aspects, or benefits, residents receive from living with carnivores, as well as methods to reduce the negative outcomes of the same. 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 While our study advances understanding of tolerance and contributes, alongside other recent investigations (e.g., Carter et al. 2012, Streubig et al. 2018), to a more standardized approach to concept measurement, we acknowledge needs that could be addressed through future research. First, we recommend further testing of our model to examine patterns of tolerance across varying social and cultural contexts and species, using both attitudinal and behavioral metrics. As an illustration of the latter, a useful line of inquiry would be to determine the relationship between desired population levels for bears (an attitudinal indicator) and behavioral measures of tolerance, such as individuals’ willingness to take action to reduce conflict (e.g., use of bear-resistant garbage containers). This could be replicated in other systems, including additional locations and for other species and conflict scenarios, to develop a generalized understanding of attitudinal and behavioral measures of tolerance. Second, while our global model, consisting of all predictors, explained 46% of the variation in tolerance, our understanding may be improved by evaluating additional influences to account for unexplained variation. Using interdisciplinary approaches that incorporate a diversity of social science disciplines and mixed-methods techniques could help broaden the suite of factors that are considered, including socio-cultural, political, and economic influences. For example, the psychological factors we explored are nested within a variety of other layers of social influence such as institutional actions and broader group-level factors (e.g., norms), which can affect 11 �495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 attitudes toward wildlife (Manfredo et al. 2014, Lischka et al. 2018). We suggest that multi-level systems approaches that include these broader considerations could provide further insights into the tolerance concept and its application (Lischka et al. 2018). Finally, we suggest that conservation interventions aimed at increasing tolerance for carnivore species, such as communication efforts designed to build greater support for species protection or policies that dictate the application of lethal removal, be evaluated to identify the most effective mechanisms for achieving this goal. Developing and testing intervention strategies with a more solid understanding of tolerance and its drivers is a critical next step in the application of the concept to facilitate carnivore conservation in human-dominated landscapes (Treves and Bruskotter 2014). REFERENCES Baruch-Mordo, S., S. W. Breck, K. R. Wilson, and D. M. Theobald. 2008. Spatiotemporal Distribution of Black Bear-Human Conflicts in Colorado, USA. Journal of Wildlife Management 72(8):1853-1862. Baruch-Mordo S., S. W. Breck, K. R. Wilson, and J. Broderick. 2011. The Carrot or the Stick? Evaluation of Education and Enforcement as Management Tools for Human-Wildlife Conflicts. PLoS ONE 6(1):1-8. Bruskotter, J. T. 2013. The Predator Pendulum Revisited: Social Conflict Over Wolves and Their Management in the Western United States. Wildlife Society Bulletin 37(3): 674-679. Bruskotter, J. T., and R. S. Wilson. 2014. Determining Where the Wild Things will be: Using Psychological Theory to Find Tolerance for Large Carnivores. Conservation Letters 7(3):158165. Bruskotter, J. T., A. Singh, D. C. Fulton, and K. Slagle. 2015. Assessing Tolerance for Wildlife: Clarifying Relations Between Concepts and Measures. Human Dimensions of Wildlife 20(3):255-270. Burnham, K. P., and D. A. Anderson. 2010. Model selection and multimodel inference: a practical information-theoretic approach. 2nd Edition. Springer, New York, New York, USA. Carpenter, L. H., D. J. Decker, and J. F. Lipscomb. 2000. Stakeholder acceptance capacity in wildlife management. Human Dimensions of Wildlife 5(3):5-19. Carter, N. H., S. J. Riley, A. Shortridge, B. K. Shrestha, and J. G. Liu. 2014. Spatial Assessment of Attitudes Toward Tigers in Nepal. Ambio 43:125-137. Carter, N. H., S. J. Riley, and J. G. Liu. 2012. Utility of a psychological framework for carnivore conservation. Oryx 46(4):525-535. 12 �539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 Chapron, G., P. Kaczensky, J. D. C. Linnell, M. von Arx, D. Huber, et al. 2014. Recovery of large carnivores in Europe's modern human-dominated landscapes. Science 346(6216):15171519. Chase, L. D., T. L. Teel, M. R. Thornton-Chase, and M. J. Manfredo. 2016. A Comparison of Quantitative and Qualitative Methods to Measure Wildlife Value Orientations Among Diverse Audiences: A Case Study of Latinos in the American Southwest. Society and Natural Resources 29(5):572-587. Cortina, J. M. 1993. What is coefficient alpha - an examination of theory and applications. Journal of Applied Psychology 78(1):98-104. Decker, D. J., and K. G. Purdy. 1988. Toward a concept of wildlife acceptance capacity in wildlife management. Wildlife Society Bulletin 16(1):53-57. DeVellis, R. F. 2012. Scale development: theory and applications. 3rd Edition. SAGE, Thousand Oaks, California, USA. Dillman, D. A. 2014. Internet, phone, mail, and mixed-mode surveys: the tailored design method. 4th edition. Wiley, Hoboken, New Jersey, USA. Gigliotti, L., D. J. Decker, and L. H. Carpenter. 2000. Developing the wildlife stakeholder acceptance capacity concept: research needed. Human Dimensions of Wildlife 5(3):76-82. Gore M. L., B. A. Knuth, C. W. Scherer, and P. D. Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflict. Conservation Letters 1(3):136-145. Groves, R. M. 2006. Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly 70(5):646-675. Hristienko, H. and J. E. McDonald. 2007. Going into the 21(st) century: a perspective on trends and controversies in the management of the American black bear. Ursus 18(1):72-88. Inskip, C., Z. Fahad, R. Tully, T. Roberts, and D. MacMillan. 2014. Understanding carnivore killing behaviour: Exploring the motivation for tiger killing in the Sundarbans, Bangladesh. Biological Conservation 180:42. Inskip, C., N. Carter, S. Riley, T. Roberts, and D. MacMillan. 2016. Toward Human-Carnivore Coexistence: Understanding Tolerance for Tigers in Bangladesh. Plos One 11(1):20. Johnson, D. E. 1998. Applied multivariate methods for data analysts. Duxbury Press, Pacific Grove, California, USA. Johnson, H. E., S. W. Breck, S. Baruch-Mordo, D. L. Lewis, C. W. Lackey, K. R. Wilson, J. Broderick, J. S. Mao, and J. P. Beckmann. 2015. Shifting perceptions of risk and reward: 13 �584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 Dynamic selection for human development by black bears in the western United States. Biological Conservation 187:164-172. 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 Lowery, D. R., W. C. Morse, and T. D. Steury. 2012. Biological and Social Investigation of Human–Black Bear Conflicts in the Panhandle of Florida. Human Dimensions of Wildlife 17(3):193-206. Johnson, H. E., D. L. Lewis, S. A. Lischka, and S. W. Breck. 2018. Assessing ecological and social outcomes of a bear-proofing experiment. Journal of Wildlife Management DOI: 10.1002/jwmg.21472. Johnson, H.E., D. L. Lewis, T. L. Verzuh, C. F. Wallace, R. M. Much, L. K. Willmarth, and S. W. Breck. 2017. Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts. Journal of Applied Ecology DOI: 10.1111/13652664.13021. Kansky, R., M. Kidd, and A. T. Knight. 2016. A wildlife tolerance model and case study for understanding human wildlife conflicts. Biological Conservation 201:137-145. Kansky, R., and A. T. Knight. 2014. Key factors driving attitudes towards large mammals in conflict with humans. Biological Conservation 179:93-105. Laufenberg, J., H. E. Johnson, P. F. Doherty, and S. W. Breck. 2018. Compounding effects of human development and a natural food shortage on a large carnivore population along a human development-wildland interface. Biological Conservation 224:188-198. Lischka, S. A., S. J. Riley, and B. A. Rudolph. 2008. Effects of impact perception on acceptance capacity for white-tailed deer. Journal of Wildlife Management 72:502-509. Lischka, S.A., T. L. Teel, H. E. Johnson, S. A. Reed, A. DonCarlos, S. W. Breck, and K. R. Crooks. 2018. A conceptual model to guide understanding of ecological and social factors leading to human-wildlife conflicts. Biological Conservation. Manfredo, M. J., T. T. Teel, M. Gavin, and D. Fulton. 2014. Considerations in representing individuals in social-ecological models. In M. J. Manfredo, A. Rechkemmer, & J.J. Vaske, Understanding Society and Natural Resources: Forging New Strands of Integration Across the Social Sciences, Springer Press, New York. Manfredo, M. J., T. L. Teel, and A. M. Dietsch. 2016. Implications of human value shift and persistence for biodiversity conservation. Conservation Biology 30(2): 287-296. Manfredo, M. J., T. L. Teel, L. Sullivan and A. M. Dietsch. 2017. Values, trust, and cultural backlash in conservation governance: The case of wildlife management in the United States. Biological Conservation 214: 303-311. 14 �628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 Morzillo, A. T., A. G. Mertig, J. W. Hollister, N. Garner, and J. G. Liu. 2010. Socioeconomic Factors Affecting Local Support for Black Bear Recovery Strategies. Environmental Management 45(6):1299-1311. Naughton-Treves, L., Grossberg, R., and Treves, A. 2003. Paying for Tolerance: Rural Citizens' Attitudes Toward Wolf Depredation and Compensation. Conservation Biology 17(6):1500 1511. Peterson, M. N., J. L. Birckhead, K. Leong, M. J. Peterson, and T. R. Peterson. 2010. Rearticulating the myth of human-wildlife conflict. Conservation Letters 3:74-82. Riley, S. J., D. J. Decker, L. H. Carpenter, J. F. Organ, W. F. Siemer, G. F. Mattfeld, and G. Parsons. 2002. The essence of wildlife management. Wildlife Society Bulletin 30(2):585-593. Riley, S. J., and D. J. Decker. 2000. Wildlife stakeholder acceptance capacity for cougars in Montana. Wildlife Society Bulletin 28(4):931-939. Struebig, M. J., M. Linkie, N. J. Deere, D. J. Martyr, B. Millyanawati, S. C. Faulkner, S. C. Le Comber, F. M. Mangunjaya, N. Leader-Williams, J. E. McKay, and F. A. V. St John. 2018. Addressing Human-tiger Conflict Using Socio-ecological Information on Tolerance and Risk. Nature Communications 9(1). Slagle, K., R. Zajac, J. Bruskotter, R. Wilson, and S. Prange. 2013. Building tolerance for bears: A communications experiment. Journal of Wildlife Management 77(4):863-869. Teel, T. L., and M. J. Manfredo. 2009. Understanding the Diversity of Public Interests in Wildlife Conservation. Conservation Biology 24(1):128-139. Treves, A., and J. Bruskotter. 2014. Tolerance for Predatory Wildlife. Science 344(6183):475476. Treves, A., and Martin K.A. 2011. Hunters as stewards of wolves in Wisconsin and the Northern Rocky Mountains, USA. Society and Natural Resources 24:984-994. United States Census Bureau. 2017. Durango, Colorado QuickFacts. [online] URL: https://www.census.gov/quickfacts/table/BZA115214/0822035,08067 Vaske, J. J. 2008. Survey research and analysis: Applications in parks, recreation and human dimensions. Venture, State College, PA. Wilbur, R. C., S.A. Lischka, J. R. Young, and H. E. Johnson. 2018. Experience, attitudes, and demographic factors influence the probability of reporting human–black bear interactions. Wildlife Society Bulletin 42:22-31. 15 �672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Design of experiments in animal ecology. Pages 79-107 in Analysis and Management of Animal Populations. Academic Press, San Diego, USA. Woodroffe, R., S. Thirgood, and A. Rabinowitz (Eds.) 2005. People and wildlife: conflict or coexistence? Cambridge University Press, Cambridge, UK. Zar, J. H. 1999. Biostatistical Analysis. 4th ed. Prentice Hall, Upper Saddle River, New Jersey, USA. Zajac, R. M., J. T. Bruskotter, R. S. Wilson, and S. Prange. 2012. Learning to live with black bears: A psychological model of acceptance. Journal of Wildlife Management 76(7):1331-1340. Zinn, H. C., M. J. Manfredo, and J. J. Vaske. 2000. Social psychological bases for stakeholder acceptance capacity. Human Dimensions of Wildlife 5(3):20-33. 16 �688 689 690 691 692 693 694 695 696 697 TABLES AND FIGURES Table 1. Model comparison of factors affecting tolerance for black bears in the vicinity of Durango, Colorado, USA (n=747). Results are from the “Living with black bears in Durango” survey, conducted January-April, 2014. Tolerance, the response variable, was measured as a desired change in the bear population over the next 2 years, on a 5-point Likert scale with 1 = decrease greatly and 5 = increase greatly. Gender and Education were categorical variables, while all other variables were continuous. We selected among models based on Akaike’s Information Criterion (AIC) and Pearson’s adjusted R2 statistics. Model Global Psychological 698 699 700 Variables Benefit, Risk, Social value similarity, Social trust, Personal control, Positive impacts, Negative impacts, Domination, Mutualism, Nuisance conflicts, Safety conflicts, Age, Gender, Education Benefit, Risk, Social value similarity, Social trust, Personal control Positive impacts, Negative impacts Domination, Mutualism Nuisance conflicts, Safety conflicts Age, Gender, Education Impacts Values Conflict Demographic † Reference class = Male ‡ Reference class = Less than high school diploma 17 AIC ΔAIC R2 -519.01 0 0.46 -488.61 30.40 0.43 -232.99 -203.81 -141.46 -148.91 286.02 315.20 377.55 370.10 0.19 0.15 0.08 0.06 �701 702 703 704 705 706 707 708 Table 2. Linear regression (n = 747) of global model of factors affecting tolerance for black bears in the vicinity of Durango, Colorado, USA. Results are from the “Living with Black Bears in Durango” survey, conducted January-April 2014. Tolerance, the response variable, was measured as a desired change in the bear population over the next 2 years, on a 5-point Likert scale with 1 = decrease greatly and 5 = increase greatly. The R2 value of this global model was 0.46. Gender and Education were categorical variables, while all other variables were continuous. * indicates 95% CIs excluded zero. Variable Intercept Nuisance conflicts Safety conflicts Positive impacts* Negative impacts* Benefit* Risk* Social trust* Social value similarity Personal control Mutualism Domination* Age* Gender† Education‡ Some post-secondary education Bachelor's degree or higher 709 710 711 712 † Unstandardized β 3.437 -0.024 0.048 0.016 -0.014 0.294 -0.233 -0.090 0.016 0.066 0.030 -0.098 -0.004 -0.085 0.105 -0.041 Reference class = Male class = High school diploma or less ‡ Reference 18 Standardized Values 95% CIs β SE Lower Upper 2.853 0.027 2.771 2.879 -0.051 0.027 -0.104 0.003 0.030 0.028 -0.026 0.085 0.068 0.027 0.016 0.120 -0.115 0.032 -0.178 -0.051 0.289 0.036 0.218 0.361 -0.229 0.040 -0.307 -0.151 -0.098 0.038 -0.164 -0.016 0.014 0.041 -0.066 0.095 0.064 0.034 -0.002 0.129 0.039 0.034 -0.029 0.106 -0.110 0.034 -0.178 -0.043 -0.059 0.029 -0.117 -0.002 -0.045 0.030 -0.104 0.014 0.046 -0.019 0.049 0.048 -0.050 -0.114 0.143 0.076 �713 714 715 716 717 718 719 Table 3. Linear regression (n = 2,552) of the impact of the bear-proofing experiment on tolerance for black bears in the vicinity of Durango, Colorado, USA. Results are from the “Living with Black Bears in Durango” survey, conducted January-April 2012 and 2016. Tolerance, the response variable, was measured as a desired change in the bear population over the next 2 years, on a 5-point Likert scale with 1 = decrease greatly and 5 = increase greatly. All predictors were categorical variables. * indicates 95% CIs that excluded zero. Variable Intercept Treatment†,* Site‡, * Time§ Treatment × Time 720 721 722 723 Unstandardized β 2.852 -0.156 0.090 -0.017 0.079 Standardized Values 95% CIs Β SE Lower Upper 2.853 0.027 2.771 2.879 -0.155 0.056 -0.264 -0.046 0.133 0.042 0.050 0.216 -0.041 0.055 -0.148 0.067 0.097 0.079 -0.059 0.252 † Reference class = Control class = North § Reference class = Pre-treatment (2012) ‡ Reference 19 �724 725 726 727 Figure 1. A priori models assessed to understand tolerance for black bears, including the Conflict Model (Decker and Purdy 1998), Impacts Model (Riley et al. 2002), Psychological Model (Zajac et al. 2012; Bruskotter and Wilson 2014); Values Model (Zinn 2000), and Demographic Model (Kansky and Knight 2014). 728 20 �729 730 731 732 733 734 Figure 2. Items included in Conflict Model of tolerance for black bears. Bars represent the percent of respondents who had experienced each human-bear conflict. Results from “Living with black bears in Durango” survey, conducted January–April 2014 in Durango, Colorado, USA. Individuals were asked to report whether they had experienced each conflict within the previous 2 years. We categorized items as Nuisance conflicts (N) or Safety conflicts (S). Had a bear break into my garbage (N) Knew someone harassed by a bear (S) Had a bear damage trees/garden (N) Had a bear damage other property (N) Had a bear damage feeder/grill (N) Was harassed by a bear (S) Had a bear attack my pets (S) Had a bear enter my home (S) Knew someone attacked by a bear (S) Had a bear attack my livestock (S) Was attacked by a bear (S) 735 736 737 0% 10% 21 20% 30% 40% 50% �738 739 740 741 742 743 744 745 746 Figure 3. Standardized regression coefficients from regression model of factors affecting tolerance for black bears (n = 747). Results are from the “Living with Black Bears in Durango” survey, conducted January-April 2014 in Durango, Colorado, USA. Midpoints represent the coefficient values, and error bars show the 95% confidence intervals. * indicates 95% CIs that excluded zero. † Reference class = Male class = High school or less ‡ Reference 22 �Figure 4. Trends in tolerance for black bears and human-bear conflicts before and after bearresistant garbage containers were distributed to treatment areas in Durango, Colorado, USA, 2011-2016. Data from 2011-2012 (shaded area) were collected before bear-resistant containers were distributed to treatment areas, and data collected 2013-2016 were collected after containers were deployed. No garbage containers were distributed in control areas. Bars represent the mean values for tolerance among residents of control (black) and treatment (grey) areas in 2012, 2014, and 2016. Dashed lines represent the number of garbage-related conflicts observed in control (black) and treatment (grey) areas. Results from “Living with black bears in Durango” survey, conducted January–April 2012, 2014, and 2016 and field observations of garbage-related conflicts (2011-2016) in Durango, Colorado, USA (Johnson et al. 2018). Tolerance was measured as a desired change in the bear population over the next 2 years, on a 5-point Likert scale with 1 = decrease greatly and 5 = increase greatly. Mean Tolerance 5 250 200 4 150 3 100 2 50 1 0 2011 2012 Control 2013 2014 Treatment 2015 Control 760 761 762 763 23 2016 Treatment Conflicts observed 747 748 749 750 751 752 753 754 755 756 757 758 759 �764 765 766 767 768 769 770 APPENDIX A. Supporting information on calculation of predictor variables for models of Tolerance. Table A.1. Items included in Impacts model of tolerance for black bears (n = 747). Results from “Living with black bears in Durango” survey, conducted January–April 2014 in Durango, Colorado, USA. Respondents were asked to report whether they had experienced the listed impacts, and whether they thought the impacts were important. Tables report different settings in which impacts could occur: (a) impacts that occurred around home, (b) impacts that occurred in town, and (c) impacts that occurred in a natural area outside town. (a) Around home Percent Impacts Identified Positive Impacts Feel excited about seeing a wild animal when I see a bear around home. 54% Feel that the area where I live is good wildlife habitat when I see a bear around home. 51% Feel connected to nature when I see a bear around home. 50% Feel confident that black bear hunting in this area will be good when I see a bear around home. 13% Negative Impacts Worry that a black bear will be killed by CPW when I see a bear around home. 48% Feel concerned that black bears are acting in unnatural ways when I see a bear around home. 35% Worry that a black bear will be killed by a hunter when I see a bear around home. 23% Worry about my pets or animals being attacked by a black bear when I see a bear around home. 20% Worry about me or my family being attacked by a black bear when I see a bear around home. 18% Feel upset that humans are living in black bear habitat when I see a bear around home. 14% Worry about the cost of damage to my garden or trees from black bears when I see a bear around home. 14% Worry about a black bear breaking into my garbage when I see a bear around home. 15% Worry about the hassle dealing with damage to my garden or trees from black bears when I see a bear around home. 13% Worry about the cost of damage to my home, vehicle or property from bears when I see a bear around home. 14% Worry about the hassle dealing with damage to my home, vehicle or property when I see a bear around home. 13% 771 24 �772 (b) In town Percent Identified Impacts Positive Impacts Feel excited about seeing a wild animal when I see a bear in town. Feel that the area near where I live is good wildlife habitat when I see a bear in town. Feel connected to nature when I see a bear in town. Feel confident that black bear hunting in this area will be good when I see a bear in town. Negative Impacts Worry that a black bear will be killed by CPW when I see a bear in town. Feel concerned that black bears are acting in unnatural ways when I see a bear in town. Worry that a black bear will be killed by a hunter when I see a bear in town. Worry about me or my family being attacked by a black bear when I see a bear in town. Worry about my pets or animals being attacked by a black bear when I see a bear in town. Worry about the cost of dealing with damage to my garden or trees from black bears when I see a bear in town. Worry about a black bear breaking into my garbage when I see a bear in town. Worry about the hassle dealing with damage to my garden or trees from black bears when I see a bear in town. Worry about the cost of dealing with damage to my home, vehicle or property from bears when I see a bear in town. Worry about the hassle dealing with damage to my home, vehicle or property from bears when I see a bear in town. Feel upset that humans are living in black bear habitat when I see a bear in town. 773 774 25 50% 45% 43% 13% 50% 37% 23% 16% 18% 15% 14% 14% 14% 13% 15% �775 (c) In a natural area outside town Percent Identified Impacts Positive Impacts Feel that the area near where I live is good wildlife habitat when I see a bear in a natural area outside town. Feel connected to nature when I see a bear in a natural area outside town. Feel excited about seeing a wild animal when I see a bear in a natural area outside town. Feel confident that black bear hunting in this area will be good when I see a bear in a natural area outside town. Negative Impacts Worry that a black bear will be killed by CPW when I see a bear in a natural area outside town. Feel concerned that black bears are acting in unnatural ways when I see a bear in a natural area outside town. 22% 17% Feel upset that humans are living in black bear habitat when I see a bear in a natural area outside town. 16% Worry that a black bear will be killed by a hunter when I see a bear in a natural area outside town. 12% Worry about my pets or animals being attacked by a black bear when I see a bear in a natural area outside town. Worry about me or my family being attacked by a black bear when I see a bear in a natural area outside town. 10% 9% 776 777 26 59% 56% 54% 14% �778 779 780 781 782 783 Table A.2. Items included in scale measures for Benefit and Risk model of acceptance capacity for black bears. Results from “Living with black bears in Durango” survey, conducted January–April 2014 in Durango, Colorado, USA. Items included in Benefit, Risk, Social trust, Personal control, and Social value similarity variables were measured on a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. Factor analysis was used to calculate single values for each scale variable based on each respondent’s pattern of responses. Cronbach’s α > 0.60 indicates high internal consistency in multi-item scales. Variable Benefit Risk Items in Scale The presence of black bears improves the quality of life in Durango. Black bears improve the health of the environment in the Durango area. Black bears living in this area are an inconvenience. (Reverse coded) Black bears provide recreational opportunities for many Durango-area residents. I fear having an encounter with black bears. Encounters with black bears are likely to result in serious injuries or human deaths. I am vulnerable to the risks posed by black bears. Black bears will be more of a problem for Durango in the future. Conflict with black bears will be reduced if people learn to live with bears. (Reverse coded) I can prevent conflicts with black bears by making changes around my home. (Reverse coded) Social Trust I am not familiar with the risks posed by black bears. All residents of Durango are equally exposed to conflicts with black bears. I am confident CPW knows how to use appropriate methods to manage black bears. I am confident CPW responds appropriately to black bear conflicts. I am confident CPW will listen to concerns about black bear management from ordinary people. I am confident CPW can effectively manage black bears. 784 27 Factor Loading 0.87 0.86 0.73 0.64 0.73 0.72 0.68 0.64 0.59 α 0.78 0.70 0.43 Removed Removed 0.94 0.91 0.90 0.90 0.93 �Personal Control I can have an influence on wildlife management decisions. I have the ability to protect my property from wildlife. 0.51 0.43 I have very little ability voice my opinions regarding wildlife management. (Reverse coded) 0.41 Whether or not I have a conflict with a black bear is mostly a matter of luck. Black bear conflicts are not a matter of luck, but rather result from bad personal decisions. (Reverse coded) Social When it comes to bear management, I believe CPW shares values similar to mine. Value Similarity When it comes to bear management, I believe CPW shares opinions similar to mine. When it comes to bear management, I believe CPW shares goals similar to mine. When it comes to bear management, I believe CPW takes actions similar to those I would. 785 786 28 0.56 Removed Removed 0.97 0.97 0.95 0.92 0.97 �787 788 789 790 791 Table A.3. Items included in scale measures for Values model of tolerance for black bears. Results from “Living with black bears in Durango” survey, conducted January–April 2014 in Durango, Colorado, USA. Domination and Mutualism items were measured on a 7-point Likert scale, where 1 = strongly disagree and 7 = strongly agree. Cronbach’s α > 0.60 indicates high internal consistency in multi-item scales. Variable Domination Mutualism Items in scale Appropriate Use Beliefs Humans should manage wildlife populations so that humans benefit. The needs of humans should take priority over wildlife protection. Wildlife are on earth primarily for people to use. Hunting Beliefs Hunting does not respect the lives of animals. (Reverse coded) People who want to hunt should be provided the opportunity to do so. We should strive for a world where there’s an abundance of wildlife for hunting and fishing. Hunting is cruel and inhumane to animals. (Reverse coded) Social Affiliation Beliefs Animals should have rights similar to the rights of humans. I view all living things as part of one big family. Wildlife are like my family and I want to protect them. We should strive for a world where humans and wildlife can live side by side without fear. Caring Beliefs I care about animals as much as I do other people. I feel a strong emotional bond with animals. I value the sense of companionship I receive from animals. 792 793 29 Cronbach’s α 0.76 0.86 �794 795 796 797 798 799 Appendix B. Supporting information about modeling of Tolerance. Table B.1 Correlations (Pearson’s r) among predictor variables in global model of Tolerance. Results from “Living with black bears in Durango” survey, conducted January–April 2014 in Durango, Colorado, USA. Items with r>0.5, were subject to further multicollinearity diagnostics. Benefit Risk Social trust Social value similarity Personal control Domination Mutualism Safety conflicts Nuisance conflicts Positive impacts Negative impacts Gender Age Education Social Value Similarity Benefit 1 -0.61 0.24 Risk Social Trust Personal Control 1 -0.24 1 0.26 -0.31 0.69 1 0.32 -0.37 0.44 0.53 1 -0.30 0.33 0.37 -0.30 -0.06 0.14 -0.09 0.24 -0.29 0.41 -0.17 -0.17 0.26 0.17 Safety Conflicts Nuisance Conflicts Positive Impacts Domination Mutualism -0.18 0.31 1 -0.56 1 -0.28 -0.34 0.21 -0.18 1 -0.22 -0.23 -0.21 0.12 -0.06 0.30 1 -0.03 -0.05 0.01 0.08 -0.10 0.09 0.05 0.10 1 -0.32 0.44 -0.19 -0.22 -0.24 0.05 -0.02 0.30 0.26 0.23 -0.08 -0.26 0.13 -0.02 0.29 -0.07 0.06 0.01 -0.03 0.06 -0.06 -0.04 0.11 -0.10 0.01 -0.27 0.11 -0.06 0.19 -0.08 -0.02 -0.10 0.04 -0.01 0.02 -0.01 0.05 0.04 -0.15 0.01 800 801 30 �802 Negative Impacts Negative impacts Gender Age Education Gender Age Education 1 0.03 0.05 1 -0.03 1 1 0.18 0.02 0.03 803 31 �804 805 806 807 808 809 Appendix C. Questions from the survey instrument used to calculate predictor variable. 1. How would you like to see the number of black bears in the area where you live change in the next 2 years? (Please circle only one.) Increase greatly 810 811 812 813 814 1 Stay the same 2 3 4 Decrease greatly I am not sure. 5 6 2. Below are several general statements about the risks and benefits of black bears in this area. Please check the box that best describes your level of agreement with each statement. Strongly disagree a. The presence of black bears improves quality of life for people living in and around Durango. b. Black bears provide recreational opportunities for many Durango-area residents. c. Black bears improve the health of the environment in the Durango area. d. Black bears living in this area are an inconvenience. e. Black bears will be more of a problem for Durango in the future. f. I am not familiar with the risks posed by black bears. g. I am vulnerable to the risks posed by black bears. h. I can prevent conflicts with black bears by making changes around my home. i. Conflict with black bears will be reduced if people learn to live with bears. j. Encounters with black bears are likely to result in serious injuries or human deaths. k. I fear having an encounter with black bears. l. All residents of Durango are equally exposed to conflicts with black bears. m. I am not concerned about the risks posed by black bears. Neither Strongly agree I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 815 816 32 �817 818 819 3. How often have you experienced the following interactions with black bears in the past 2 years in the area where you live? (Please check one for each item.) a. Saw black bears in the wild, on open space or public land b. Saw black bears in urban or suburban areas of town c. Saw black bears near my home d. Had a black bear break into or attempt to break into my garbage e. Had a black bear get into or damage my fruit trees or garden f. Had a black bear get into or damage my bird feeder, pet feeder, or grill g. Had a black bear damage other property (e.g. fences, car, garage) h. Had a black bear harass or attack my pets i. Had a black bear harass or attack my livestock j. Had a black bear enter or attempt to enter my home k. Knew someone who was harassed by a black bear l. Knew someone who was attacked by a black bear m. Was harassed or felt threatened by a black bear myself n. Was attacked by a black bear myself 820 821 33 0 times 1-2 times 3-4 times 5 or more times I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]1 [ ]2 [ ]2 [ ]3 [ ]3 [ ]4 [ ]4 [ ]5 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]5 [ ]5 [ ]5 [ ]5 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 �822 823 4. People have different experiences when they interact with black bears in and around Durango. Please tell us what each of the listed interactions makes you think about. I am Seeing black bears near my home makes me... Yes No not sure. a. feel connected to nature. [ ]1 [ ]2 [ ]3 b. worry about a black bear breaking into my garbage. [ ]1 [ ]2 [ ]3 c. worry about damage to my garden or trees from black bears. [ ]1 [ ]2 [ ]3 d. worry about damage to my home, vehicle or property from bears. [ ]1 [ ]2 [ ]3 e. worry about me or my family being attacked by a black bear. [ ]1 [ ]2 [ ]3 f. worry about my pets or animals being attacked by a black bear. [ ]1 [ ]2 [ ]3 g. worry that a black bear will be killed. [ ]1 [ ]2 [ ]3 h. confident that black bear hunting in this area will be good. [ ]1 [ ]2 [ ]3 i. feel excited about seeing a wild animal. [ ]1 [ ]2 [ ]3 j. feel that the area where I live is good wildlife habitat. [ ]1 [ ]2 [ ]3 k. feel upset that humans are living in black bear habitat. [ ]1 [ ]2 [ ]3 l. feel concerned that black bears are acting in unnatural ways. [ ]1 [ ]2 [ ]3 Seeing black bears around town makes me… Yes No I am not sure. a. feel connected to nature. b. worry about a black bear breaking into my garbage. c. worry about damage to my garden or trees from black bears. d. worry about damage to my home, vehicle or property from bears. e. worry about me or my family being attacked by a black bear. f. worry about my pets or animals being attacked by a black bear. g. worry that a black bear will be killed. h. confident that black bear hunting in this area will be good. i. feel excited about seeing a wild animal. j. feel that the area near where I live is good wildlife habitat. k. feel upset that humans are living in black bear habitat. l. feel concerned that black bears are acting in unnatural ways. [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 Seeing black bears in a natural area outside of town… Yes No I am not sure. a. feel connected to nature. b. worry about me or my family being attacked by a black bear. c. worry about my pets or animals being attacked by a black bear. d. worry that a black bear will be killed. e. feel excited about seeing a wild animal. f. confident that black bear hunting in this area will be good. g. feel that the area near where I live is good wildlife habitat. h. feel upset that humans are living in black bear habitat. i. feel concerned that black bears are acting in unnatural ways. [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 824 825 34 �826 827 5. How important to you are the following things you might experience because of your interactions with black bears in and around Durango? (Please check one for each item.) Very Somewhat Not at all important important important How important to you is… a. feeling connected to nature? b. the hassle of cleaning up garbage after a bear got in it? c. the hassle of dealing with black bear damage? d. the cost of dealing with black bear damage? e. the risk of injury to you or others from a bear attack? f. the risk of injury to your pets from a black bear attack? g. a black bear being killed because it caused damage? h. a black bear being killed by hunters? i. being able to hunt black bears in this area? j. black bears acting in a natural way? k. believing this area is good wildlife habitat? l. being excited about seeing a wild black bear? m. your concern about humans living in bear habitat? 828 829 830 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 I am not sure. [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 6. How much would you like the following items to change in the next 2 years? (Please check one for each item.) How much of a change would you like in… Large change Small change No change I am not sure. a. how often you see black bears near your home? b. how often you see black bears around town? c. how often you see bears in natural areas outside town? d. how connected you feel to nature in the area? e. how often you clean up garbage after a bear got in it? f. how often you deal with bear damage to property? g. the risk of injury to you or others from a bear attack? h. the risk of injury to your pets from a bear attack? i. the number of bears killed for causing damage? j. the number of bears killed by hunters? k. your ability to hunt bears in this area? l. how often bears in the area act in natural ways? m. the quality of this area as wildlife habitat? n. how often you feel excited about seeing a wild bear? o. the number of humans living in bear habitat? [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]3 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 [ ]4 831 832 35 �833 834 835 7. Below are several statements that describe how you might feel about CPW’s black bear management in the Durango area. Please check the box that best describes your level of agreement with each statement. I am confident that Colorado Parks and Wildlife… a. can effectively manage black bears. b. knows how to use appropriate methods to manage black bears. c. responds appropriately to black bear conflicts. d. will listen to concerns about black bear management from ordinary people. 836 837 838 839 Strongly Disagree Slightly Disagree Neither Slightly Agree Strongly Agree I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 8. Below are several statements about how your views about bear management compare with those of Colorado Parks and Wildlife. Please check the box that best describes your level of agreement with each statement. When it comes to bear management, I feel that Colorado Parks and Wildlife… a. shares values similar to mine. b. shares opinions similar to mine. c. takes actions similar to those I would. d. shares goals similar to mine. Neither Slightly Agree Strongly Agree I am not sure. [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 Strongly Disagree Slightly Disagree [ ]1 840 841 36 �842 843 844 9. Below are several statements that describe how you might feel you are able to control interactions with black bears and other wildlife. Please check the box that best describes your level of agreement with each statement. Strongly Disagree Slightly Disagree Neither Slightly Agree Strongly Agree I am not sure. a. I can have an influence on wildlife management decisions. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 b. I have the ability to protect my property from wildlife. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 c. I have very little ability voice my opinions regarding wildlife management. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 d. Whether or not I have a conflict with a black bear is mostly a matter of luck. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 e. Black bear conflicts are not a matter of luck, but rather result from bad personal decisions. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 f. I have very little ability to protect myself from black bear conflicts. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 g. I believe that my actions can reduce my risk of having a negative interaction with a bear. h. I believe that I am likely to have negative interactions with bears regardless of what I do try to prevent them. 845 846 37 �847 848 849 10. Below are statements representing different ways that people might think about wildlife. Please tell us how much you agree or disagree with each statement. (Please check the box that best describes your level of agreement for each item.) Strongly Disagree a. Humans should manage wildlife populations so that humans benefit. b. Animals should have rights similar to the rights of humans. c. We should strive for a world where there’s an abundance of wildlife for hunting and fishing. d. I view all living things as part of one big family. e. Hunting does not respect the lives of animals. f. I feel a strong emotional bond with animals. g. The needs of humans should take priority over wildlife protection. h. I care about animals as much as I do other people. i. Wildlife are on earth primarily for people to use. j. Hunting is cruel and inhumane to animals. k. We should strive for a world where humans and wildlife can live side by side without fear. l. I value the sense of companionship I receive from animals. m. Wildlife are like my family and I want to protect them. n. People who want to hunt should be provided the opportunity to do so. 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 11. Are you [ ]1 male or [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]1 [ ]2 [ ]2 [ ]3 [ ]3 [ ]4 [ ]4 [ ]5 [ ]5 [ ]6 [ ]6 [ ]7 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]7 [ ]2 female? (Please check one.) 12. In what year were you born? (Please indicate.) 19 _______ 13. What is your highest level of education? (Please check one.) [ ]1 Less than high school diploma [ ]2 High school graduate or GED [ ]3 Vocational or trade school [ ]4 Some college [ ]5 Associate’s Degree (2 year) [ ]6 Bachelor’s Degree (4 year) [ ]7 Graduate/Professional Degree 38 Strongly Agree Neither � 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 Understanding and managing human tolerance for a large carnivore in a residential system Description An account of the resource Human tolerance for interactions with large carnivores is an important determinant of their persistence on the landscape, yet the relative importance of factors affecting tolerance is not fully understood. Further, the impact of management efforts to alter tolerance has not been adequately assessed. We developed a model containing a comprehensive set of predictors drawn from prior studies and tested it through a longitudinal survey measuring tolerance for black bears (Ursus americanus) in the vicinity of Durango, Colorado, USA. Predictors included human-bear conflicts, outcomes of interactions with bears, perceptions of benefits and risks from bears, trust in managers, perceived similarity with the goals of managers, personal control over risks, value orientations toward wildlife, and demographic factors. In addition, we monitored changes in tolerance resulting from a bear-proofing experiment designed to reduced garbage-related conflicts in the community. Residents who perceived greater benefits associated with bears and more positive impacts from bear-related interactions had higher tolerance. Residents who perceived greater risks and more negative impacts and who had greater trust in managers, domination wildlife value orientations, and older age were less tolerant. Conflicts with bears were not an important predictor, supported by our finding that changes in conflicts resulting from our bear-proofing experiment did not affect tolerance. In contrast to conservation approaches that focus primarily on decreasing human-wildlife conflicts, our findings suggest that communication approaches aimed at increasing public tolerance for carnivores could be improved by emphasizing the benefits and positive impacts of living with these species. Bibliographic Citation A bibliographic reference for the resource. Recommended practice is to include sufficient bibliographic detail to identify the resource as unambiguously as possible. Lischka, S. A., T. L. Teel, H. E. Johnson, and K. R. Crooks. 2019. Understanding and managing human tolerance for a large carnivore in a residential system. Biological Conservation 238:1081–1089; doi.org/10.1016/j.biocon.2019.07.034 Creator An entity primarily responsible for making the resource Lischka, Stacy A. Teel, Tara L. Johnson, Heather E. Crooks, Kevin R. Subject The topic of the resource Human tolerance Human-bear conflict Black bear Extent The size or duration of the resource. 39 pages Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/InC-NC/1.0/">IN COPYRIGHT - NON-COMMERCIAL USE PERMITTED</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. Biological conservation Date Accepted Date of acceptance of the resource. Examples of resources to which a Date Accepted may be relevant are a thesis (accepted by a university department) or an article (accepted by a journal). 07/20/2019 Date Issued Date of formal issuance (e.g., publication) of the resource. 08/30/2019 Date Modified Date on which the resource was changed. 07/02/2019 Date Submitted Date of submission of the resource. Examples of resources to which a Date Submitted may be relevant are a thesis (submitted to a university department) or an article (submitted to a journal). 11/02/2018 Type The nature or genre of the resource Article