Preliminary Report
Challange Cost-Share Agreement
between
The University of Arizona, School of Renewable Natural Resources &
Coronado National Forest
Sierra Vista Ranger District,
USDA Forest Service Contract No: CCS-95-0035
Report Written May 7, 1996
With growing pressure on national forest lands by outdoor enthusiasts, the U.S. Forest Service (NFS) through it's multiple use mandate must attempt to accommodate a wide variety of recreation activities, uses and interests. While much planning in the past has at best been reactive to public needs and desires to meet this goal, there is a strong commitment to proactive forest recreation planning. In order to accomplish this goal, recreation managers are turning to the research community to assist them in acquiring a more indepth understanding of societal needs, recreational demands and expected experiential or beneficial outcomes of such recreational use. Developing parallel to this growing pressure on forest lands, has been the recent USDA Forest Service directive for ecosystem management. Ecosystem management calls for the explicit consideration of the human management dimension in planning for and implementing management objectives on forest lands. Within the human dimension of ecosystem management, recreation and amenity uses of forest lands, and associated benefits of those uses, constitute an important component for land management decisions. With this need to acquire a rich understanding of recreational use, behavior and associated perceived benefits to make more informed management decisions, explicit functional relationships between manageable characteristics of forest lands and recreational uses of those lands must be sought. Such explicit relationships would provide clear linkages between management activities for recreational and non-recreational uses of forest lands, and between management activities for recreational uses and the outcomes, including beneficial outcomes of those activities.
What is not clear at the present are the potentials for examining benefits and their relationship to design and planning of recreation facilities. There are some basic questions that can be asked to acquire a better understanding of recreational use and beneficial outcomes of that use on forest lands such as; What are the reasons visitors come to certain forest environments?; What are the types of recreational activities they engage in? What are the appropriate forest settings for these activities? What are the perceived beneficial outcomes of these activities? What types of management actions can be implemented to achieve these recreational experiences and associated benefits? While these questions could take a life time to answer, this study will attempt through public surveys to address some of these questions.
The purpose of this study is to assess the experience preferences and associated beneficial outcomes of the visitors to the Huachuca Mountains of Coronado National Forest. This study will identify preferences for recreational experiences, appropriate setting characteristics, activities, facilities, services and beneficial outcomes of these experiences.
The following is brief summary of the result of the initial on-site field survey. While data is actively being collected on the detailed take home survey, which should yield many more results, this report is a quick peek at what is to come. The data analyzed in this report was captured October thru December 1995. The random sampling was undertaken in three canyons as identified by Forest Service recreation management specialists. Those canyons were Miller, Carr and Brown. Each offers a range of recreation opportunities to it's visitors. This report summarizes the finding of this on-site portion of the visitor survey. The report will be organized in the following sections: visitor characteristics and demographics; visitor recreational experience preferences for activities, visitor preferences for physical settings and appropriate activity levels, visitor's perceived beneficial outcomes of recreational experiences and ability to acquire such outcomes.
The data collected on-site was analyzed in three different way. First, SPSS, a commonly used statistical package was used to perform frequency analysis on the visitor characteristics and demographics data to obtain an initial overview of type of recreators who visit the area. Raw mean scores on all the rest of the data was undertaken to obtain information on how what the distribution of ratings were in order to assess the statistical differences in each of the questions. In addition, to acquire some sense of what the reliability and validity of the assessment techniques employed ie. the survey, RMRATE, a statistical package was used. RMRATE provides a measure of the level of agreement between individual's and groups of observer's responses to the measured stimuli (Brown et al. 1990). Correlation coefficients are computed to assess the internal consistency and reliability of responses to individual stimuli. An initial test measured the individual observer-to-observer relationships, a second related the observer's responses to the group, and a third assessed the correspondence between the test group, and each other group from the population.
The observer-to-observer reliability statistic is an indication of the projected correlation between two individual's selected from an observer population. The group-to-group statistic relates to the projected correlation between group mean ratings from respondent groups of equal size. This measure estimates conformity of agreement between the respondent group tested, and any other respondent group from the same population. Observer-to-group correlations indicate the extent to which an individual's ratings conform with ratings from other observers within a population. For this analysis, group-to-group measures of reliability are extremely important because there is an assumption when setting up the study and assessing the data that you have adequately sampled the visitor population. This coefficient then indicates that the visitor sample could be compared to any other population of similar characteristics and would achieve the same degree of no agreement. Perfect agreement in the coefficients would result in a value close to 1.00. A value of .855 would suggest a very strong agreement with any other group, indicating that both visitor population sampled and the information they provide to us is statistically valid and reliable.
The third statistical analysis performs principal component analysis on the data. Since different observer's almost never agree perfectly in their ratings of a set of stimuli (questions). For a detailed discussion of this technique see Brown et al. (1990). Basically, this method explains the interconnections among a set of observers' in terms of a smaller set of inferred variables called "components". Each component is a weighted sum of observer ratings, with the weights mathematically define to capture the maximum amount of observers' variance, subject to the constraint that the components must be uncorrelated among themselves. This technique is employed to understand the underlying dimensions of choice for activities, benefits etc. It produced two kinds of output, first eigenvalues which represent the amount of variance in the total data set accounted for by each of the components; second component loadings and component scores. These score indicate how strongly observers' ratings are related to each component. If an observer has a high loading on a particular component, it means that the component is highly correlated with the observers' ratings. Component scores (which we are interested here) show the location of each of the stimuli (questions) on each of the dimensions represented by the components. The higher the score the more agreement.
Of the three areas sampled as outlined in Table #1, over 42 percent of those surveyed undertook recreation activities in Carr Canyon, followed by Miller and Brown. Of those sampled 60% were Male while only 40% were females.
Over 45% of those sampled fell within the 31 - 40 age group, followed by under 30 and closely by over 50. The 19% over fifty suggests that the heavy retirement population of sierra vista at this time are representative of those currently using the canyons as much as the middle age group.Canyon Sampled Percent
Miller 32% Carr 42% Brown 26%
Table #1: Percentage of those Sampled in Huachuca Mountain Study Sites
Age Percent
11-30 21% 31-40 45% 41-50 15% Over50 19% Table #2 Age Group Distribution
When the data is analyzed from the mail-back survey, we may find that a high percentage of those who visit the surrounding forest service lands are visitors from outside the city limits of Sierra Vista. In addition, those sampled in this preliminary survey (See Table 3), it was found the 33% recreate in the canyons with their families, while 47% or nearly half those sampled tend to recreate with friends.
Group(s) Percent
Alone 10% Couple 7% Family 33% Extended 3% Friends 47% Groups 0% ----------- Total 100% (n=56) Table #3 Recreator Group(s) Diversity
These findings differ extensively from those found in other studies in the state by the author who has found that in the Santa Catalina Mountains, a strong representation of the visitors tend to come alone to experience the wilderness setting. In Sedona, Coconino National Forest it was found that local residents where strongly representative of those sampled in the canyon(s) and tended to hike alone and as much as 3-4 times a week.
Reasons for Coming to the Forest Percent
See Fall Color 10% Horseback Riding 1% Get Away from Citylife 3% Talk with Friends 1% Photography 3% Reading 5% Meditating 3% Hiking and Walking outdoors 30% Family time 8% Prospecting 1% Visiting from out of Town 1% Picnicking and Enjoying Nature 10% Hunting 1% Camping 1% Archaeological Hunt 1% Biking 10% Sightseeing 1% Handglyding 10% --------- Total 100% Table #4 - Reasons for Visiting the Huachuca Mountain Canyons
Table 4 is a summary of the open-ended question on the survey to solicit responses from visitors as to some of the reasons why visitors were drawn to the canyons of the Huachuca Mountains. We have extracted those reasons and aggregated them into the following descriptive categories. I have bold faced the ones that standout as primary reasons for coming.
It is clear from table 4 that there are two distinct classes of reasons why people visit the area. The first is for passive recreational activities such as hiking and walking outdoors and picnicking were the strongest reason for visiting the area(s) while others were drawn by the active recreational activities such as biking and handglyding which equally made up the significant rankings. It seems from this descriptive technique however, that many simply come to hike and enjoy the sounds and sights of nature and don't require the intensive physical satisfaction found in many other public land settings.
As discussed in the statistical analysis section of this report, it is important that a statement of the degree of reliability and validity of the visitor samples that are used for the quantitative analysis be made. In the return survey, this will be an important element as well if management decisions are to be made from the findings. To ensure significant visitor sample have been obtained an analysis was performed on the data to measure the individual observer-to-observer relationships, a second related the observer's responses to the group, and a third assessed the correspondence between the test group, and each other group from the population. These techniques have been explained earlier in the statistical analysis section. Table #5 is a summary of the findings of this analysis for each of the remaining questions in the survey.
Question_#_Description * O-to-O G-to-G O-to-G Variance
4a. Time Spent Performing Recreation Activity .131 .869 .450 45% 4b. Suitability to Perform Recreation Activity .129 .875 .423 48% 5a. Importance of Recreation Setting .657 .989 .838 73% 5b. Availability of Recreation Setting. .558 .984 .792 71% 6a. Desireability to Achieve Rec. Experience. .363 .955 .595 50% 6b. Ability to Attain Desired Rec Experience. .255 .921 .494 46% 7a. Desireability to Achieve Rec Benefits. .110 .807 .493 52% 7b. Ability to Attain Desired Rec Benefits. .140 .854 .555 50%
*O-to-O = Observer to Observer Reliability Coefficient G-to-G = Group to Group Reliability Coefficient O-to-G = Observer to Group Reliability Coefficient Percentage of Variance Factors is the variance accounted for by each component.
Table #5- Correspondence Among Observers
An evaluation of the computer correlation coefficients to assess the internal consistency and reliability of responses to the individual stimuli outlined in Table #5 generally reveals high levels of consistency in both the observer and group categories. The group to group correlations indicated high reliability values ranging from .807 to .989. A perfect agreement would result in a coefficient of 1.00. In addition, observer to group correlations indicated moderate to high reliability values ranging from .423 to .838. These measures of agreement correspond with finding of previous investigations which studied recreation behavior with similar groups in similar landscapes (Kaufman et al. 1995,1996; Gimblett et al. 1996). For example, question 5a with a coefficient of .989 and 71% percentage on variance factors indicates that there is extremely high reliability on the group that we have used as compared with any group to answer this question. We have extremely high reliability in the way the group has answer what they consider to be important recreation settings and that 71% of the variance in that answer can be explained by the first factor. By analyzing the first factor in the principle component analysis then, we should be able to clearly discern what is important about those settings.
The use of principal component analysis to uncover underlying dimensions of choice has been well documented and utilized (Schroeder, 1987). Table #5 identifies the percentage of variance for the first component score for each of the questions in the survey. The first principal component represents the best fit to the group's ratings that can be obtained on a one dimensional scale. The proportion of variance accorded for by the first component is a measure of the concensus among the observers. As can be seen from Table #5, the first component accounts for between 45 and 73 percent of the variance in the data and represents the best fit. This simply means that half more than half of the variance in the ratings can be captured in a one-dimensional scale and this first component can be used as an excellent indicator of what is going on in the data. For this reason, the remaining analysis to identify what the important responses are in the data set was done based on the first component factor.
Overall then, from Table 5 it can be said that the visitor sample used in this analysis is a reliable and credible source and is representative of any other group that would participate in the study. In most cases even if many more visitors were sampled, that the coefficients may not get any better, which suggests that the more the better is not true in this case.
Recreation Activities Miller Canyon Brown Canyon Carr Canyon Mean FS * Mean FS Mean FS ------------------------------------------------------------------------------
Backpack Camping 3.46 -.573 L 4.00 -.173 3.17 .245 Picnicking 3.18 -.638 L 4.14 .688 H 3.50 .894 Driving for Pleasure 2.79 .065 3.57 .775 H 2.92 -.463 L Hiking (day use) 3.29 -.526 4.43 .441 3.75 .957 H Mountain Biking 2.89 0.22 H 3.710 1.20 L 2.751 -.55 L -.444 L Camping near vehicle 2.61 -.294 3.43 .009 3.33 .527 Nature Study 3.46 -.417 4.29 .287 3.58 .924 H Horseback riding 2.89 -.034 4.00 -.392 L 2.92 -.273 Mountain Climbing 2.82 .016 3.86 .150 2.83 -.288 Photography 2.93 .000 3.71 -.082 2.92 -.280 Meditation 2.93 -.032 3.71 -.082 2.92 -.280 Prospecting 2.89 -.009 3.71 -.082 2.92 -.280 Hunting 2.89 -.060 3.71 -.082 2.92 -.280 Running 2.86 -.008 3.71 -.082 2.92 -.280 Plant_id 2.82 -.310 3.71 -.082 2.92 -.280 Hand Glyding 3.43 2.598 H 3.71 -.082 3.58 -.280
* Factor Scores from Principal Component Analysis H - Highest two stimuli on component L - Lowest two stimuli on component
In order to identify how important stimulus or components of the questions are to the visitor, an examination of the factor or component loadings on the first principal component is undertaken. These loadings then represent the majority or aggregate concensus of the observers. This measure of relative strength of observer's loadings or rating scores are represented by a capital H, for highest and L for lowest. This measure assists in interpreting what the dimension actually represents. In this study we are using the measure as an indicator of what variables are considered important to the respondents. One caution however when using H and L as indicators is that since the data is scaled to expose the underlying dimension, a negative L such as in the case of Miller Canyon backpacking and picnicking does not mean it necessarily was rated lowest, but that it resides simply on one end of a bipolar scale or dimension. In other words it is not necessarily disliked by the visitors. If you look at
Table 6: Mean ratings of Suitability to Perform Recreational Activities for Miller, Brown and Carr Canyon the mean ratings in the table as well, it assists in identifying what is going on as well. If standard deviations were examined in conjunction with mean and factor scores it probably would make it more clear. But in any case, these scores assist in better understanding how the visitor scores are falling out.
Table #6 & #7 summarize the mean ratings for recreation activity and time spent respectively for each of the surveyed sites. The mean rating are based on a five point rating scale, where five represents highly suitable for that activity and one not suitable at all. In addition, component loading scores have been added in to illustrate how the respondents are loading on the different activities for the first principal component.
An examination of the findings in Table #6 for each of the canyons illustrates some interesting similarities and differences. While table 4 has provided an indication of the reasons visitors are coming to the Huachuca Mountains, the analysis of the suitability of recreation activities provides an indication of how suitable the area is to perform a recreational activity through the eyes of the visitor. The factor rankings clearly illustrate the visitors perceive backpacking and picnicking as being suitable activities are at one end of the recreation activity scale in Miller Canyon while hand glyding and Mountain Biking are the other important activities. Again the passive/active scale is happening. When compared with Brown and Carr Canyon there are some extreme differences which would be expected. In Brown Canyon it appears that Driving for Pleasure and Picnicking are popular activities and Mountain biking and Horseback riding are others. The rest of the activities in Brown may have significant mean scores, but do not have the group concensus as do those mentioned. The visitors surveyed at Carr Canyon on the other hand tend to perceive the area as being highly suitable to engage in hiking and studying nature activities with some emphasis on mountain biking and driving for pleasure.
Time Spent Miller Canyon Brown Canyon Carr Canyon on Activities Mean FS * Mean FS Mean FS --------------------------------------------------------------------------------
Backpack Camping 3.56 .245 2.33 1.434 H 3.20 .555 H Picnicking 3.04 .894 2.00 .117 2.90 -.282 Driving for Pleasure 2.36 -.463 L 1.67 -1.348 L 2.60 -.287 L Hiking (day use) 3.16 .957 H 2.56 .966 3.20 .262 Mountain Biking 2.88 -.55 L 1.781 .09 2.801 -.245 .125 Camping near vehicle 2.76 .527 1.89 -.522 L 3.50 1.450 H Nature Study 3.44 .924 H 2.22 1.416 H 2.90 .114 Horseback riding 2.84 -.273 1.78 -.084 2.70 -.303 L Mountain Biking 2.68 -.28 2.110 -.35 2.601 -.177 .236 Photography 2.84 -.280 1.89 -.273 2.70 -.177 Meditation 2.72 -.280 1.89 -.352 2.60 -.177 Prospecting 2.80 -.280 1.89 -.251 2.80 -.177 Hunting 2.80 -.280 1.89 -.278 2.80 .007 Running 2.70 -.280 1.89 -.266 2.70 -.209 Plant_id 2.80 -.280 1.89 -.162 2.60 -.177 Hand Gyding 2.88 -.280 1.89 -.131 2.60 -.177
* Factor Scores from Principal Component Analysis H - Highest two stimuli on component L - Lowest two stimuli on component Table 7: Mean ratings of Time spent on the Recreational Activities of Choice for Miller, Brown and Carr Canyon
All in all when comparing each of the canyons it appears that picnicking, hiking and nature study are consistently considered important recreation activities with mountain biking and hand glyding even though weakly correlated in Brown and Carr other recreation activity considerations. This actually correlates strongly later on when the benefits of recreation are examined and improving physical fitness is not a dominant desire.
In response to the question of the amount of time spent on recreational activity, table #7 summarizes those findings. Time spent on activities is a good indicator of both the importance of activities and reasons visitors come to the forest. A high amount of time is spent studying nature and hiking in Miller Canyon. On a scale of 1 to 4 where 1 is equal to 1 hr. and 4 is equal to 1 day, the mean scores clearly illustrate that those engaged in studying nature and hiking undertake those activities on the average of half to a full day. In Brown canyon, backpack camping and nature study dominate the ratings again spending a day at least performing those activities and spending very little time camping near vehicle and driving for pleasure. This suggests that visitors like to park to get out into the wilderness in this canyon away from vehicles and other recreators.
Visitors to Carr Canyon spend at least a day undertaking backpack camping and camping near vehicle. Visitors spend the least amount of time deriving for pleasure and horseback riding in this canyon. It is interesting to note here that even though mountain biking and hand glyding are perceived as being highly suitable activities in Miller Canyon, very few visitors spend anytime undertaking these activities.
In response to the recreational setting question, on a five point scale, again five being extremely important and there being availability of such settings, while one being considered not very important with not being available, Table 8 summarizes those results. Again the mean ratings for each illustrate that a total undeveloped area with not facilities is highly desireable and important to the users surveyed as is slightly developed recreation areas as a compromize. The highly developed recreation areas with RV is simply not considered important to visitors surveyed. This makes sense considering that most visitors tend to spend a majority of their time when visiting undertaking backpack camping, hiking and nature study with few desiring camping near vehicle.
While recreation settings are important to the recreators using the area, their availability is another question. The results of this preliminary sample indicates that while totally undeveloped areas with no facilities are desired, their availability is scarce. Respondents ratings indicate that more undeveloped facilities are desired. In the case of slightly developed, it appears that the 2.22 mean rating indicates that their is sufficient numbers of these campsites available to the public. As is the case of the RV hookups.
Recreational Settings Importance Availability Type of Area Mean FS * Mean FS ----------------------------------------------------------------------------------------
A totally undeveloped area with no facilities 3.94 3.468 H 3.94 4.811 H A slightly developed recreation area featuring 3.20 1.273 H 2.22 -2.002 H A highly developed recreation areas 1.08 -4.741 L 1.61 -2.809 L
* Factor Scores from Principal Component Analysis H - Highest two stimuli on component L - Lowest two stimuli on component
Table 8. Overall ratings for perceived importance of facilities in areas and the availability of each area to the recreator
While earlier analysis has assessed time spend on activities, perceived suitability of the area to perform activities and importance of recreational settings, the next section attempts to get at the questions of recreational experiences and benefits. One of the questions still debated in recreation management is how to plan and manage for recreation experiences. While the Recreation Opportunity Spectrum (ROS) provides a framework to assess the landscape in terms of recreation opportunities, the assumption is that if the forest provides the opportunities, the visitor will come. This work tends to take the reverse approach. Since so very little is known about the Huachuca Mountains in terms of the types of experiences and beneficial outcomes recreators expect to acquire or obtain when visiting these areas.
Recreational Experiences Miller Canyon Brown Canyon Carr Canyon Des. Attain Des. Attain Des. Attain * ---------------------------------------------------------------------------------------------------
Learn more about nature -1.70 L -2.481 L -2.18 L .583 L -1.951 L -1.541 L* Get Away from demands of Life 1.11 H .858 H 1.07 H -.366 L .088 L .738 H Sense of Adventure in Wilderness -.53 L 1.521 H -.224 L -1.72 L 1.26 H -.258 L Spend time with my family 1.11 H .099 H 1.40 H 1.50 H .610 H 1.061 H
* Factor Scores from Principal Component Analysis for desireability and attaining experience H - Highest two stimuli on component L - Lowest two stimuli on component
Table 9. Factor Scores from Principal Component Analysis for desireability and attaining experience for each of the sampled sites.
For this reason visitors were asked to rate from a selected group of four experiences their desireability and ability to attain such experiences. The hypothesis here is that there should strong correlations between the types of experiences sought and the benefits desired. The assumption being that recreators come to a specific landscape with a preconceived set of desires, goals and expectations. These desires and expectations are thought to be satisfied depending on a variety of factors including the landscape setting type, encounters and crowding. The ability of the recreator to attain those experiences and beneficial outcomes can be thought of as a form of goal-attainment resulting in visitor satisfaction. If a recreator seeks to learn more about nature and is able to attain that experience or benefit through the recreation experience, then theoretically there is a high degree of satisfaction in the outing. If they do not achieve such benefit, then satisfaction declines, leaving the recreator with only a partially fulfilled recreation experience. Recreation management is thought to be the one mechanism that can assist visitors in acquiring satisfying outings. But first, it is apparent there must be a general understanding of what experiences are sought and what benefits are desireable.
Table 9 clearly illustrates that getting away from usual demands of life and spending time with family or friends in these setting were highly sought after, while learning more about nature and being in a wilderness area and experience a sense of adventure were secondary experiential goals of the visitors sampled. Spending time with family can been seen to be the most prevalent finding of all. This analysis suggests that in each of the sampled sites, that not only were visitors seeking to spend time with family but could attain that experience. This strongly suggests that for family activities, the forest is doing a consistent job at providing those recreational activities. In the case of get away from usual demands of life, in both Miller and Brown Canyons this was a highly desired recreational experience and could only be attained satisfactorily in Miller. Brown and Carr either it was desired and not attained or visa versa. What is surprising is the learning more about nature experience. It was consistently rated lowest as a desired recreation experience. However, a quick look at Table 10 will reveal that it is a desireable benefit and could be attained in most canyons.
In Miller Canyon there appears to be a high sense of wilderness adventure in the landscape as opposed to both Brown and Carr.
Benefits of Recreation Outing Miller Canyon Brown Canyon Carr Canyon Des. Attain Des. Attain Des. Attain * _________________________________________________________________________________________________________________
Increase your understanding of environment 1.651 H 1.03 H 1.721 H -1.631 L -1.75q L .989 H Reduce feelings of tension and stress -.537 L -.14 L .580 H -.352 H .110 L .387 H Improve your physical fitness .560 H .88 H -2.390 L -.425 L .464 H .386 Bring family/friends together -1.671 L -1.80 L .086 L 2.411 H 1.171 H -1.761 L
* Factor Scores from Principal Component Analysis H - Highest two stimuli on component L - Lowest two stimuli on component
Table 10. Over rating of the above four benefits, ability to obtain or attain those benefits during a recreational
experience and factor rating scores for each.
An examination of factor rankings and mean scores in Table 10 clearly demonstrates a mixed bag of beneficial outcomes both sought and attained. One striking finding is that in Miller a strong recreational benefit is to obtain an increased understanding of the natural environment. This was desireable and attained in that canyon. However in Brown it was desired but not attained and reverse in Carr.
Visitors to Miller canyon desire to improve their physical fitness and can as do those in Carr Canyon who cannot attain that benefit. The difference resides in the fact that those visiting Miller could and those visiting Carr could not. One can only speculate from the examination of Table 6 that since mountain biking was ranked low as a suitable activity in area, that perhaps better facilities need to be developed to promote this activity.
From the selected list of benefits for the sites surveyed that the benefits that it was desirable for recreators to seek an increased understanding and awareness of the natural environment and to reduce tension and stress were rated highest and the ability of the recreator to obtain those benefits was extremely high as well. Those who sought out to accomplish those benefits were capable of doing do. Those that were of least importance were to improve physical fitness and bring family/friends together. These finding may suggest to recreation management particular emphasis that could be directed at enhancing these benefits through site management.
In order to undertake a direct comparison of the variables or questions tested in this study, respondents scores from the principal component analysis were extracted and used to graph the relationships. The factor scores and loadings are a strong indicator of the importance of the stimuli being assessed. It is important in this study to not just determine what recreation facilities are desireable in certain settings, but to determine if there actually is a significant correlation between factors. For example, is there any correlation between recreators that participate in recreation activities and the experiences and benefits they seek? Is there a positive correlation between experiences and beneficial outcomes of those experiences? Can recreators generally obtain the benefits they desire? There are many questions that could be asked of the data. For this preliminary study, the basic relationships are graphed to provide some indication of their relationships as potential predictive variables of recreation satisfaction.
Figure #1 provides a simple correlation assessment between suitability to perform recreational activities and time spent undertaking those activities. It is clear from the mapping of these scores that there is a direct positive correlation between the suitability to perform activities and time. Recreators are consistent in the amount of time they spend doing certain types of recreational activities.
Figure #2 illustrates that the availability of the setting to perform recreational activities is correlated with the importance of the site, but generally received much higher ratings. There is a direct correlation between the two. This suggests that the type of setting still remains important in attaining an overall recreation experience and the sites sampled in this survey play a substantial role in providing the correct setting for the activities ranked highest. Secondly, it demonstrates that most recreators the rated the two elements did so in a similar manner.
Figure #3 demonstrates a consistent relationship between beneficial outcomes or desires of the recreation experience and the ability of the recreator to achieve that benefit. Since the data used for this analysis is based on all three sites lumped together, it is impossible to identify which of the benefits are important. That is explained in Table 9 and 10. What this reveals is general trends and correlations.
Figure #4 provides a view of the benefits of recreation experience against the ability to attain those benefits. While there is consistency between the desire to achieved certain benefits and the ability of the recreator to achieve those benefits, the ratings are not overall consistent between recreators. The variation in ratings suggests inconsistencies in the importance of the benefits to recreators experiences. This strongly suggests an inconsistency between benefits and all other variables measured in this survey. In otherwords, benefits may not be as useful a concept to measure recreation satisfaction as some are lead to believe.
Figure #5 provides a summary of all of the variables mapped together. It is obvious from the graph provided below that most of the variables; recreation suitability, time spent performing activity, settings and experiences are all highly correlated, while desireable benefits and attaining such benefits are not well correlated at all. This would suggest that benefits are a very hard concept to grasp for the recreator and that asking them to articulate benefits may be an inappropriate way to acquire such information. None the less benefit do provide additional information to the recreation manager, but information that perhaps is difficult at best to develop management outcomes for.
While this only a quick overview of on-site survey which is extremely limited in the number of questions solicited, this will provide you with a brief overview of what is happening in Miller, Brown and Carr Canyons. It is apparent from these initial findings that recreators visiting the area are seeking to engage in passive wilderness activities such as hiking, walking and above all to increase their understanding of the nature environment. It seems that nature interpretation is something that could assist this endeavor. Also, what is striking is that recreating to increase a level of physical fitness is not really a strongly desired benefit. The exception is in Carr Canyon where there is a desired need to improve physical fitness and where recreators could not achieve that benefit. This may be lack of structured facilities for such exercise regime. From a view of the recreation facilities, it is apparent that mountain biking may be the one that visitors are seeking to more of. Without knowing the current management strategies in each of the canyons it would be impossible to answer this question. Being with friends in a wilderness setting seems to be extremely important to visitors. There is a strong desire to make sure that highly developed recreation facilities do not get developed at the expense of those areas that are currently relatively undeveloped.
As far as the connection and determination of the importance of benefits to recreation experience, the jury is still out. It is apparent from Table 15 that there is very little correlation between desired and attained benefits and the other measured variables of recreators. The mail-back survey when analyzed may shed more light on this issue and provide more information to discriminate between classes of benefits and their individual contributions to recreation experience.
Brown, T.C., T.C. Daniel, H. W. Schroeder, G.E. Brink. Analysis of Ratings: A Guide to RMRATE. USDA Forest Service. Rocky Mountain