Informing Carrying Capacity Decision Making in Yosemite National Park, USA Using Stated Choice Modeling

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1 Journal of Park and Recreation Administration Volume 23, Number 751 Spring 2005 pp Informing Carrying Capacity Decision Making in Yosemite National Park, USA Using Stated Choice Modeling Peter Newman Robert Manning Donald Dennis Ward McKonly EXECUTIVE SUMMARY: Recreation experiences have social, ecological, and managerial dimensions. Park and protected area managers are forced to make trade-offs among these dimensions causing management to be more complex. This study evaluates how visitors to Yosemite National Park wilderness make tradeoffs among indicators of quality that represent social, ecological and managerial dimensions of the recreation experience. It is likely that most visitors want unimpeded access to parks but also want areas protected from excessive resource impacts, want to avoid undesirable levels of crowding and congestion, and heavy handed management restrictions. However, these desires often conflict, and tradeoffs must be made. Understanding visitors preferences and acceptable tradeoffs will aid managers in deciding how best to mitigate recreational impacts while not hindering, to an unacceptable degree, the freedoms and other qualities often associated with experiences in parks and protected areas. The study was conducted in the summer of 2001 and employed a paired comparison questionnaire in which respondents reported their preferences between alternative wilderness settings. Results from this study were programmed into Excel to create a wilderness management alternative predictive model that enables managers to understand the relationships among various levels of standards of quality. Results suggest signs of human use at campsites was the most important indicator of those used in the study. Moreover, Yosemite wilderness visitors were willing to tolerate increases in certain forms of regulation in order to obtain a high quality recreation experience. Findings can be used to help formulate standards of quality, and evaluate and predict visitor support for potential management alternatives. The examples in this paper illustrate how the evaluation of relative tradeoffs among social, ecological, and managerial setting attributes provide contextual, multi-dimensional information for protected area management decision making. KEYWORDS: Yosemite National Park, trade-offs, wilderness experiences, Carrying Capacity Decision-Making, predictive models AUTHORS: Peter Newman is an Assistant Professor, Colorado State University, 232 Forestry Building, Colorado State University, Fort Collins CO pnewman@cnr.colostate.edu. (970) Robert Manning is a Professor, University of Vermont; Donald Dennis is a Research Forester, USDA Forest Service Northeastern Research Station; and Ward McKonly is a Graduate Research Assistant, Colorado State

2 76 University. The authors would like to acknowledge Dr. Steven R. Lawson at Virginia Tech University, Dr. Jan W. van Wagtendonk, at the USGS Yosemite Field Station, and Laurel Boyers, and Mark Fincher, at the Yosemite National Park Wilderness Office for their shared knowledge, frequent consultation and support. We would also like to thank the Yosemite Fund and the Earthwatch Institute for funding this study. Introduction Management of national parks is replete with conflicting interests (Runte, 1997). For example, the National Park Service (NPS) is charged with preserving important natural and cultural resources while making them accessible to the public. Moreover, visitors often yearn for solitude in a pristine environment but also want the freedom from management constraints that is associated with the wilderness ideal. These paradoxes are at the heart of many park management decisions and force managers (and visitors) to make trade-offs among competing values. The question then becomes, What do visitors wish to trade-off in order to achieve a desirable condition? Answering this question could help inform difficult carrying capacity related decisions. This paper explores these questions concerning carrying capacity by applying a stated choice model in Yosemite National Park wilderness. Carrying capacity related decision-making can be very challenging when trying to meet legal mandates, and the diverse tastes and preferences of park visitors. However, the literature suggests that these challenges may be addressed through the development of explicit management objectives and associated indicators and standards of quality (Manning, 1999a, 2001). Management objectives are broad narrative statements outlining the recreation experience to be provided and the desired condition of the resource. Indicators of quality are measurable, manageable variables reflecting the essence of management objectives. Standards of quality define the minimum acceptable condition of indicator variables (Manning, 1999a, 1999b). Once indicators and standards of quality have been formulated, indicator variables are monitored and management action is taken to ensure that standards of quality are maintained. This management-by-objectives approach is at the heart of contemporary protected areas management frameworks including Limits of Acceptable Change (LAC) (Stankey et al., 1985), Visitor Impact Management (Graefe, Kuss,& Vaske, 1990) and Visitor Experience Resource Protection (VERP) (Hoff & Lime, 1997). Research to support formulation of indicators and standards of quality has generally relied on normative theory and related empirical techniques (Heberlein, 1977; Jackson, 1965; Manning, 1999a; Vaske, Shelby, Graefe, & Heberlein, 1986). In this research approach, visitors are often asked to render judgments about acceptable conditions of indicator variables that represent the social, ecological, and managerial components of recreation experiences. However, this may not adequately address the potential trade-

3 offs inherent among such indicators of quality. For example, protected area visitors may favor relatively pristine resource conditions, but also want generally unimpeded access to protected areas and freedom from management control. However, all of these conditions may not be possible, especially when there is heavy demand for protected area use. A more contextual, multi-dimensional approach to formulating indicators and standards of quality may be warranted. Choice models provide a contextual approach that can inform the development of indicators and standards of quality. While this approach has inherent strengths in providing a highly contextual approach, model estimates cannot be generalized outside of the model parameters. That is, model estimates are only relative to the other indicators included in that model. Literature Review Stated choice modeling was developed in marketing research to measure consumer preferences and trade-offs among product attributes (Green, Tull, & Albaum, 1988; Louviere, Hensher, & Swait, 2000). In these applications, alternative product choices are developed as combinations of product attributes. For example, a range of engine horsepower, luxury features, and prices might define hypothetical automobiles. Respondents are asked to express their preferences among these product choices, and data analysis reveals which attributes are most important to respondents and the effect of each attribute level on consumer preference. Choice modeling has been applied to natural resources management in a variety of studies (Adamowicz, Bhardwaj, & Macnab, 1993; Boxall, Adamowicz, Swait, Williams, & Louviere, 1996; Bullock, Elston, & Chalmers, 1998; Dennis, 1998; Heider & Ewing, 1990; Lawson & Manning, 2002; Mackenzie, 1993; Schroeder, Dwyer, Louviere, & Anderson, 1990). For example, Heider & Ewing (1990) used a stated choice experiment to evaluate alternatives among Caribbean vacation destinations. Profiles comprising the choice sets were developed from 27 possible vacation destination attributes, including proximity to beaches, variables related to accommodations and distance to airport. The results were used to create a model of tourists preferences that could be used to estimate the probability of tourists selecting various vacation destinations depending on changes in the levels of the destination s attributes. More recently, Lawson and Manning (2002) applied stated choice modeling to wilderness visitors in Denali National Park. Indicators of quality, representing alternative wilderness management conditions, were used in lieu of product attributes. Potential standards of quality comprise the range of conditions in such attributes. Alternative standards of quality for six indicator variables in Denali National Park and Preserve were combined to form alternative wilderness scenarios. These scenarios were presented to respondents (backpackers in the park) in pairs, and respondents were asked to indicate the scenario they preferred. Findings revealed 77

4 78 the relative importance of the six indicators of quality and helped to empirically inform the setting of standards of quality for these indicator variables. This research extends the work of Lawson and Manning (2002) by incorporating a visual approach to the evaluation of resource related indicators of quality in the wilderness portion of Yosemite National Park. Moreover, an interactive, predictive model was developed that enables wilderness managers to better understand study data and more fully utilize these data in wilderness management decision making. Methods The design for this research included assigning a range of potential standards of quality to six potential indicator variables for the wilderness portion of Yosemite National Park. Permutations of these variables were then arranged into sets of paired wilderness scenarios, for example, visitors could choose between alternatives where they would find high amounts of freedom (e.g., high likelihood of obtaining first choice permit, can camp at any location) but lower amounts of solitude (e.g., camp in sight and sound of other visitors each night, sees several parties a day on a trail) or, to the contrary, lower amounts of freedom and higher amounts of solitude. Wilderness visitors and respondents were asked to choose their preferred scenario. Selection of Indicators of Quality Workshops were held in Yosemite National Park during the fall of 2000 with more than a dozen park managers and rangers. Over 30 potential indicators of quality of the wilderness experience were discussed, covering social, ecological, and managerial dimensions. Because using all thirty indicators in a choice model would be too burdensome, researchers and managers decided to limit the number indicators in the model to six. Indicator selection was based on criteria used in the literature (Manning, 1999a; Stankey et al., 1985). After a day of discussing long lists of potential indicators representing resource, social, and managerial conditions of visitor experiences, workshop participants were asked to vote for the indicators they believed were the most salient and feasible. Based on continued discussion with park managers and review of the literature, six indicators were chosen to represent the most pertinent social, ecological, and managerial conditions of Yosemite wilderness and these indicator variables are shown in Table 1. Three potential standards of quality (low levels, current levels, and high levels) were also identified for each indicator variable representing a realistic range of social, resource, and managerial conditions. One of the ecological indicators Signs of human use at campsites - lended itself to a visual representation. Figure 1 shows the three photos used in this study to illustrate potential signs of human use at campsites. The range of campsite conditions was based on the Wilderness Impact Monitoring System (WIMS) used in Yosemite National Park (Boyers, Fincher, &

5 79 Table 1 Yosemite Wilderness Setting Attributes and Levels van Wagtendonk, 1999). The campsite condition classification system for WIMS uses a scale from 1 (barely discernible) to 5 (heavily impacted). The photos used in this study represent conditions 1, 3 and 5 from the WIMS system. Sampling Respondents were randomly selected from visitors who received wilderness use permits between June 26 and September 5, Sampling was conducted in and around the wilderness permit stations in Yosemite Valley, Tuolumne, Wawona, Big Oak Flat, and Hetch-Hetchy, representing all of the geographic regions of the park. This sampling strategy allowed the research team to capture representative numbers and types of visitors to the Yosemite wilderness seeking a diversity of wilderness experiences. At the start of each sampling day, the interviewer selected the first visitor and asked if he/she would be willing to participate in the survey.

6 80 Figure 1 The Photos Utilized in this Study Representing Three Levels of Human Use at Wilderness Camping Sites Photo 1 WIMS Level 1 Photo 3 WIMS Level 3 Photo 5 WIMS Level 5

7 Willing respondents completed the stated choice questionnaire which was administered on a laptop computer. When the first visitors completed the questionnaire, the next visitor was selected and the procedure continued throughout each sampling day. A total of 713 out of 864 contacted visitors agreed to complete the computer-administered questionnaire representing a response rate of 83%. Of the 713 questionnaires completed, 35 were incomplete and unuseable for a total n of 678. This sample represents 6102 paired comparisons (678 questionnaires each with nine paired comparisons). Analytical Model This study used an orthogonal fractional factorial design. The indicators and associated standards of quality were organized into four blocks of nine paired comparisons (Green & Srinivasan, 1978; Louviere et al., 2000; Seiden, 1954). In each of the nine pairwise comparisons, respondents were presented with two alternative Yosemite wilderness-scenarios, A and B and then asked which they preferred. A sample comparison is shown in Figure Figure 2 Example of Paired Comparison Question-Scenarios

8 82 As stated above, this research design involved assigning a range of potential standards of quality to selected indicators of quality, then developing alternative scenarios that represent permutations of such indicators and standards of quality. A logistic regression was then performed where the dependent variable was coded as 1 or 0 representing the respondents choice (choice A = 0, choice B=1). The independent variables included the vector of differences between the effects codes 1 of each attribute level (hypothetical standard of quality) of the adjacent paired comparison. For a full description of this model, see Opaluch, Swallow, Weaver, Wesselles, and Wichelns (1993). Finally, the statistical model was programmed into an Excel database in order to create a wilderness management scenario calculator 2. The calculator enables wilderness managers to predict visitor preferences for hypothetical wilderness management scenarios and the relationship among alternative indicators and standards of quality. Results The regression coefficients and p values for each indicator variable are presented in Table 2. All coefficients are significantly different than zero at the <.001% level, except the coefficients associated with the following three variables: Encounter 5 15 other groups a day while hiking, Most get a permit for at least their second choice trip and Able to camp out of sight and sound of other groups most nights. The overall model is significant at the.01 level according to the model chi-square statistic (Wald c 2 =18.76, p=.000) and predicted 68.5% of the responses correctly. 1 As stated earlier, the independent variables are made up of the differences between the levels (effect codes) of each attribute of the adjacent profile. Effects coding was used to represent the wilderness setting attributes in the predictive model run in Excel. Effects coding requires that one level of the indicator of quality (i.e., each wilderness setting attribute) be selected as the baseline or excluded level. For this study, the first level of each scenario was selected as the excluded level (e.g., Encounter fewer than 5 other groups a day while hiking. for the Number of other groups encountered per day while hiking attribute). As a result, each wilderness setting attribute was represented in the statistical model by two indicator variables, one associated with the intermediate level of the attribute (e.g., Encounter 5 15 other groups a day while hiking. for the Number of other groups encountered per day while hiking attribute) and one associated with the high level of the attribute (e.g., Encounter more than 15 other groups a day while hiking. for the Number of other groups encountered per day while hiking attribute). To code for the first level of an attribute, both indicator variables were assigned values of 1. To code for the second or intermediate level of the attribute, the indicator variable for the intermediate level of the attribute was coded 1 and the indicator variable for the third level was coded 0. To code for the third or high level of the attribute, the indicator variable for the intermediate level of the attribute was coded 0 and the indicator variable for the third level was coded 1 (Boxall et al., 1996; Lawson & Manning, 2002). The result of effects coding is that the coefficients of the indicator variables represent the ordinal utility (or disutility if the coefficient is negative) associated with the corresponding level of the attribute. The ordinal utility (or disutility) of the first level of the attribute is equal to the negative sum of the coefficients of the indicator variables corresponding to the attribute. For a full description of the model see Opaluch et al. (1993) and Wichelns et al. (1993). 2 For a full description of the methods used to calculate public preference for hypothetical wilderness management scenarios, see Opaluch et al. (1993) and Wichelns et al. (1993).

9 Table 2 Levels of Indicator of Quality Variables with their Estimated Coefficients 83

10 84 Table 2 presents the study variables, their associated levels, and the results of the model in order of relative importance to the Yosemite wilderness visitor. The absolute magnitude of the coefficients reflects the relative importance of the corresponding level of the attribute to wilderness visitors. The greater the relative magnitude of a coefficient, the more it adds to or detracts from respondents preference for the wilderness setting. A larger negative coefficient indicates that the corresponding level of the attribute detracts substantially from respondents preference associated with the wilderness setting. A larger positive coefficient indicates that the corresponding level of the attribute substantially increases respondents preference for the wilderness setting. Moreover, the absolute magnitude among attributes denotes the preference visitors have for those attributes. The model indicates that signs of human use at campsites is the most important indicator of quality. Photo number three (Figure 1), representing a highly impacted campsite, has the highest associated magnitude of any of the six variables (-.700). Both photo number 1 (.351) and photo number 2 (.348), had approximately equal magnitudes, in other words, wilderness visitors were indifferent between these two conditions (Table 2). Discussion The relationships among the coefficients for the attribute levels (alternative standards of quality) offer important information. These relationships represent potential visitor trade-offs and suggest that lesser preferred standards of quality of a scenario may be tolerated if that same scenario has certain attributes with more preferred standards of quality. For example, with respect to the availability of permits that suggests that visitors may accept use restrictions in order to obtain a higher quality experience. The difference between Most visitors are able to get a permit for their preferred trip (.143) and Most visitors are able to get a permit for at least their second choice trip, (.040) is a net change of.103. These data suggest that visitors would accept a lower chance of receiving a permit in order to receive improvements in other conditions such as encountering fewer people on trails and encountering fewer stock parties or signs of stock parties on the trails. In other words, it would take the latter two attributes as represented by the value of the coefficients to make up for the former attribute and associated value of the coefficient. Knowledge about these relationships can inform managers concerning the tradeoffs inherent in park and protected area management. The relationships among the indicator variables provides contextual and multi-dimensional information that can inform management decision making. The results suggest that Yosemite National Park wilderness visitors support some degree of management over where and how many visitors may camp and also support visitor use limits. For example, Yosemite wilderness visitors remained indifferent as regulations over where visitors may camp increased from, Allowed to camp in any zone on any night, to Required to camp in specified zones (Table 2). However, preference

11 dropped off dramatically at the most restrictive level of Required to camp in designated sites, producing the lowest preference levels with respect to campsite regulations. The model coefficients can also be used to predict the overall preferences of Yosemite National Park wilderness visitors for a variety of wilderness management scenarios that were not directly tested in the study questionnaire. Because this model utilized 6 attributes each with three levels (see Table 1), there are 3 6 or 729 potential wilderness scenarios. The ability to explore relationships inherent among the scenarios, provides valuable contextual information about public preferences for wilderness management. Past approaches to understanding public preference relied on visitors to render judgments about uni-dimensional components of the wilderness experience. In other words, visitors are able to choose the best case scenario, which is not always available. The approach used here forced visitors to make trade-offs among various wilderness conditions. This multi-dimensional approach creates more realistic scenarios, and asks visitors to think more like protected area managers do on a day to day basis (i.e. balancing use and preservation by protecting resources and visitor experiences). Testing a multitude of these scenarios may be important to managers seeking to understand public preferences in a multi-dimensional context. Management Scenario Calculator Utilizing the estimated coefficients from this study, a management scenario calculator was created in Excel. Using the calculator, managers can create and test various permutations of wilderness standards of quality and estimate the level of preference these scenarios would receive from Yosemite National Park wilderness visitors (Figure 3). Figure 3 Wilderness Management Scenario Calculator 85

12 86 To illustrate the wilderness management scenario calculator, consider the two wilderness management scenarios shown in Figure 3. Scenario 1 will be referred to as the solitude scenario and Scenario 2 as the freedom scenario. The numbers in each cell represent the level (low level =1, current level =2 and high level =3) of each attribute chosen to define the scenarios. The solitude scenario specifies that wilderness visitors would encounter fewer than five groups of people per day on the trail and have the ability to camp out of sight and sound of groups all nights. However, visitors are required to camp in designated campsites and only a minority of visitors receive a wilderness permit. The freedom scenario specifies that visitors would encounter more than 15 groups per day along trails, and have the ability to camp out of sight and sound of other groups only a minority of nights. However, visitors can camp wherever they choose, and most visitors receive a permit for their preferred trip. In both of these scenarios, signs of human use at campsites and the chance of encountering stock were held at the intermediate levels. The model estimates that nearly 60% of Yosemite wilderness visitors would prefer the solitude scenario and just over 40% would prefer the freedom scenario. This suggests that the majority of Yosemite wilderness visitors prefer to trade-off some freedoms in order to attain a higher degree of solitude. The wilderness management scenario calculator empowers managers to test all permutations of study variables and explore the relationships among the social, ecological and managerial attributes that contribute to wilderness experiences. Managers who better understand these relationships can make more informed decisions concerning the development of indicators and associated standards of quality and the allocation of experiential zoning and most importantly, the public who uses park resources. Conclusions Research to support formulation of indicators and standards of quality has generally relied on normative theory and related empirical techniques. We used a more contextual approach by developing an understanding of the acceptable tradeoffs among the different standards of quality. Stated choice analysis can be a useful way to integrate social, ecological and managerial indicators of quality into carrying capacity decision-making. The results of the model have several important implications for Yosemite National Park wilderness management. First, the indicators utilized in this study were all found to be significant components of the Yosemite wilderness visitor experience. In other words, the differences among the levels of the attributes showed that each indicator had a substantive impact on visitors preferences. Second, Yosemite wilderness visitors are willing to tolerate increases in certain forms of regulation, in order to obtain a high quality recreation experience and resource protection. This information would not have been apparent in previous, unidimensional approaches to informing the formulation of indicators and standards of quality. Moreover, results suggest that the public may under-

13 stand the trade-offs that protected area managers face on a day-to-day basis and that management is complex. Third, as is consistent across other studies that used visual and nonvisual approaches, (Lawson & Manning, 2002; Manning, 1999a; Newman & Dawson, 1996) signs of human use at campsites, was the most important setting attribute relative to the six included in the study. This suggests that management should consider placing a high priority on monitoring and improving campsite conditions and aesthetics. Fourth, the use of a visual approach (photos of signs of human use at campsites) based on a current monitoring system such as WIMS, allows managers to understand the potential effects of current campsite conditions on visitor experiences. Fifth, the overall magnitude of the coefficients provides important information about setting potential standards of quality to be formulated by wilderness managers. Finally, the calculator empowers managers to explore the data in a user friendly, computer interface. For example, if managers have a choice to increase visitor use restrictions or regulations, they can proactively determine potential changes in visitor preference. This empowers managers by allowing them to understand what visitors would trade-off in order to achieve a desirable condition. This tool allows managers to better understand public preferences and the cognitive relationships among social, ecological, and managerial components of the wilderness experience. Moreover, managers can make more informed management decisions in concert with park mandates that constantly force managers to balance use and preservation of natural and cultural resources. These examples illustrate how the evaluation of relative tradeoffs among social, ecological, and managerial setting attributes provide more contextual, multi-dimensional information for protected area management decision making. References Adamowicz, W. L., Bhardwaj, V. and Macnab, B. (1993). Experiments on the difference between willingness to pay and willingness to accept. Land Economics, 69, Boyers, L. Fincher, M., van Wagtendonk, J, (1999). Twenty-eight years of wilderness campsite monitoring in Yosemite National Park. In: Cole, D. N.; McCool, S. F. (2000) Proceedings: Wilderness Science in a time of Change Proceedings. RMRS-P-000.Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. Boxall, P. C., Adamowicz, W., Swait, J., Williams, M. and Louviere, J. (1996) A comparison of stated preferences for environmental valuation. Ecological Economics. 18(2), Bullock, C., Elston, D., and Chalmers, N. (1998) An application of economic choice experiments to traditional land use deer hunting and landscape change in the Scottish highlands. Journal of Environmental Management, 52, Dennis, D. (1998). Analyzing public inputs to multiple objective decisions on national forest using conjoint analysis. Forest Science, 443,

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