Gravity model formulation for an extensive National Parkway Site

The purpose of this study was to collect specific information on the characteristics and intensity of local Blue Ridge Parkway use and to use that information to develop a recreation use model of local Parkway visitation. Data were obtained from a self-administered mail-back questionnaire sent to a random sample of people living in the 29 counties adjacent to the Parkway.We developed two recreation use projection/demand models that employ three variables (distance, alternative recreation sites, and population density) to predict visitation to different Parkway areas from various local origins. The derived model estimates indicated that about one-fourth of all Parkway visits in 1978 were one-day visits made by area residents.     

An external validity test of intended behavior: Comparing revealed preference and intended visitation in response to climate change

We compare revealed preference and survey response estimates of changes in National Park visitation behavior from climate change. The revealed preference model is estimated from a time-series regression analysis of past visitation as a function of historic weather variability. We find no statistical difference between the revealed preference regression estimates and intended behavior estimates from a visitor survey for the total number of National Park visits. Confidence intervals for the two models overlap, and the mean estimates of the change in visitation are within 12% of each other. The paper concludes with the implications for natural resource planners and managers who must frequently evaluate the effects of alternative policies before the selection of a preferred alternative, and also must plan for accommodating changes in visitor use.     

Wildfire effects on hiking and biking demand in New Mexico: a travel cost study

We use a travel cost model to test the effects of wild and prescribed fire on visitation by hikers and mountain bikers in New Mexico. Our results indicate that net benefits for mountain bikers is $150 per trip and that they take an average of 6.2 trips per year. Hikers take 2.8 trips per year with individual net benefits per trip of $130. Both hikers' and mountain bikers' demand functions react adversely to prescribed burning. Net benefits for both groups fall as areas recover from prescribed burns. Because both visitation and annual recreation benefits decrease to these two types of visitors, this gives rise to multiple use costs associated with prescribed burning. With respect to wildfire, hikers and mountain bikers both exhibit decreased visitation as areas recover from wildfires, however, only hikers indicate an increase in per trip net benefits. Bikers' demand effectively drops to zero. These results differ from previous findings in the literature and have implications for efficient implementation of the National Fire Plan and whether prescribed burning is a cost effective tool for multiple use management of National Forests. Specifically, that fire and recreation managers cannot expect recreation users to react similarly to fire across recreation activities, or different geographic regions. What is cost effective in one region may not be so in another.     

Approximating the distribution of recreational visits from on-site survey data

While convenient and often used, on-site surveys are biased by the fact that users who visit the site more often are proportionately more likely to be sampled. This so-called avidity or size biased sampling results in over-estimating the visitation patterns of the average user. This analysis develops a rule of thumb method that may easily be applied by recreation site managers to visitation data collected on-site in order to infer behavior of the average user of the site. The key assumption that drives the derivation is that the visitation data of users is logarithmically distributed. To evaluate the methodology, we analyze several data sets of recreational users assuming that they reflect the populations of users and from these construct hypothetical on-site samples.     

An Assessment of the Economic Effectiveness of Recreation Policy Using Contingent Valuation

Arrangements within the UK to enhance recreation opportunities in the countryside are currently implemented in a somewhat ad hoc manner. This paper analyses the economic effectiveness of such provision in Grampian Region, Scotland. This is achieved by quantifying, using the contingent valuation method, the economic benefits accruing from recreation enhancements and comparing these benefits with the level of expenditure currently being undertaken on these improvements. The subsequent analysis provides a strategic framework for the assessment of recreation needs in the region, thus enabling future priorities for provision to be identified. It is argued that the quantification of public preferences for recreation enhancements provides a powerful tool to aid strategic planning of recreation provision. The issue of using public funds to finance recreation facilities in the countryside is also discussed.     

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.     

Application of the wilderness travel simulation model to the Appalachian Trail in Vermont

The wilderness travel simulation model estimates complex recreation use patterns in park and wilderness environments. The model was applied to a section of the Appalachian Trail in Vermont, a linear, long-distance, multiple-access trail system characteristic of the eastern United States. Many portions of the trail, including the study area, are now experiencing high use. The model estimated the average number of trail encounters per party day to be 3.3 and the average number of camp encounters per party night to be 2.3. Other measures of recreation use were also estimated that should prove useful to trail management and administration. Three trail management scenarios were tested, providing several preliminary insights to managers: the desirability of use redistributions as opposed to across-the-board reductions and needed emphasis on spatial use patterns and campsite encounters. Only minor modifications to the program were needed in applying the model to the trail environment and the model functioned accurately according to the validity tests performed.     

Modelling visitor groups' intentions to displace from an urban trail: a combined stated preference and video monitoring approach

Depending on gender and activity, overcrowding and safety concerns may detract from urban green space use. Differences in use displacement intentions from a recreational trail in a forest in Vienna were investigated for male and female walkers as well as male and female dog-walkers (N = 425) using an image-based stated preference model. The trail scenarios were depicted as digitally calibrated images that systematically displayed combinations of levels of crowding with different mixes of user types and visitor behaviour. Visitors were asked whether the presented recreation scenario was so unacceptable that they would shift their use away from the presented trail. Hours and days of stated non-use of the recreation trail by various user groups are estimated by integrating the results of the behavioural model with annual visitation data. Use displacement intentions differed by gender and activity. High use levels were a greater concern for all respondents than very low use levels, particularly for female dog-walkers. However, only a small proportion of the recorded hours were heavily used. Safety concerns about very low use levels reduced the potential times of forest use for female walkers without a dog.     

IMPACTS OF WATER QUALITY IMPROVEMENT ON SITE VISITATION: A PROBABILISTIC MODELING APPROACH1

ABSTRACT: The influence of perceptions of water quality on the likelihood of recreating at a particular recreation site is investigated using a logit model. The model is estimated for St. Albans Bay, Vermont. A hypothetical improvement in water quality was shown to greatly increase the probability of at least one visit to the bay during a season. This implies that many recreationists who do not use the bay at present will do so if water quality improves. A demand model for predicting site visitation must, therefore, include current nonusers in the sample. Failure to do so would result in misleading predictions about future demand for the bay.     

Impacts of changes in water quality on recreation behavior and benefits in Finland

The implementation of the European Union Water Framework Directive (WFD) requires nationally generalizable estimates of the benefits of protecting inland and coastal waters. As an alternative to benefit transfers and meta-analyses, we utilize national recreation inventory data combined with water quality data to model recreation participation and estimate the benefits of water quality improvements. Using hurdle models, we analyze the association of water clarity in individuals' home municipalities with the three most common water recreation activities – swimming, fishing and boating. The results show no effect on boating, but improved water clarity would increase the frequency of close-to-home swimming and fishing, as well as the number of fishers. Furthermore, to value the potential benefits of the WFD, we estimate the consumer surplus of a water recreation day using a travel cost approach. A water policy scenario with a 1-m improvement in water clarity for both inland and coastal waters indicates that the consumer surplus would increase 6% for swimmers and 15% for fishers. In contrast to previously estimated abatement costs to improve water quality, net benefits could turn out to be positive. Our study is a promising example of applying existing national recreation inventory data to estimate the benefits of water quality improvements for the purposes of the WFD.     

Valuation of National Park System Visitation: The Efficient Use of Count Data Models, Meta-Analysis, and Secondary Visitor Survey Data

The National Park Service (NPS) currently manages a large and diverse system of park units nationwide which received an estimated 279 million recreational visits in 2011. This article uses park visitor data collected by the NPS Visitor Services Project to estimate a consistent set of count data travel cost models of park visitor willingness to pay (WTP). Models were estimated using 58 different park unit survey datasets. WTP estimates for these 58 park surveys were used within a meta-regression analysis model to predict average and total WTP for NPS recreational visitation system-wide. Estimated WTP per NPS visit in 2011 averaged $102 system-wide, and ranged across park units from $67 to $288. Total 2011 visitor WTP for the NPS system is estimated at $28.5 billion with a 95% confidence interval of $19.7–$43.1 billion. The estimation of a meta-regression model using consistently collected data and identical specification of visitor WTP models greatly reduces problems common to meta-regression models, including sample selection bias, primary data heterogeneity, and heteroskedasticity, as well as some aspects of panel effects. The article provides the first estimate of total annual NPS visitor WTP within the literature directly based on NPS visitor survey data.     

Economic Value of Instream Flow for Non-Commercial Whitewater Boating Using Recreation Demand and Contingent Valuation Methods

Whitewater river kayaking and river rafting require adequate instream flows that are often adversely affected by upstream water diversions. However, there are very few studies in the USA of the economic value of instream flow to inform environmental managers. This study estimates the economic value of instream flow to non-commercial kayakers derived using a Travel Cost Method recreation demand model and Contingent Valuation Method (CVM), a type of Contingent Behavior Method (CBM). Data were obtained from a visitor survey administered along the Poudre River in Colorado. In the dichotomous choice CVM willingness to pay (WTP) question, visitors were asked if they would still visit the river if the cost of their trip was $Y higher, and the level of $Y was varied across the sample. The CVM yielded an estimate of WTP that was sensitive to flows ranging from $55 per person per day at 300 Cubic Feet per Second (CFS) to a maximum $97 per person per day at flows of 1900 CFS. The recreation demand model estimated a boater’s number of trips per season. We found the number of trips taken was also sensitive to flow, ranging from as little as 1.63 trips at 300 CFS to a maximum number of 14 trips over the season at 1900 CFS. Thus, there is consistency between peak benefits per trip and number of trips, respectively. With an average of about 100 non-commercial boaters per day, the maximum marginal values per acre foot averages about $220. This value exceeds irrigation water values in this area of Colorado.     

Valuing freshwater salmon habitat on the west coast of Canada

Changes in land use can potentially reduce the quality of fish habitat and affect the economic value of commercial and sport fisheries that rely on the affected stocks. Parks and protected areas that restrict land-use activities provide benefits, such as ecosystem services, in addition to recreation and preservation of wildlife. Placing values on these other benefits of protected areas poses a major challenge for land-use planning. In this paper, we present a framework for valuing benefits for fisheries from protecting areas from degradation, using the example of the Strait of Georgia coho salmon fishery in southern British Columbia, Canada. Our study improves upon previous methods used to value fish habitat in two major respects. First, we use a bioeconomic model of the coho fishery to derive estimates of value that are consistent with economic theory. Second, we estimate the value of changing the quality of fish habitat by using empirical analyses to link fish population dynamics with indices of land use in surrounding watersheds. In our example, we estimated that the value of protecting habitat ecosystem services is C$0.93 to C$2.63 per ha of drainage basin or about C$1322 to C$7010 per km of salmon stream length (C$1.00=US$0.71). Sensitivity analyses suggest that these values are relatively robust to different assumptions, and if anything, are likely to be minimum estimates. Thus, when comparing alternative uses of land, managers should consider ecosystem services from maintaining habitat for productive fish populations along with other benefits of protected areas.     

THE CHUBB/BAUMAN METHOD FOR ESTIMATING THE RECREATION POTENTIAL OF RIVERS: A CRITICAL REVIEW1

ABSTRACT: The Chubb/Bauman (Ch/B) method for making quantitative estimates of recreation potential for rivers is based on the 1968/ 69 Leopold method for quantitative assessment of the scenic beauty of rivers. Both use classifications of environmental variables as the database. Unlike the Leopold method, the classifications used in the Ch/B method consistently reflect human preferences. The Ch/B method collects information on 67 variables, and uses a computer program to produce estimates of potential for 16 common recreation activities. This critique evaluates selected concepts and procedures of the Ch/B method partly by comparison with other available methods of recreation resource inventory. It considers the validity and utility of numerical weighting of variables, the use of numbers derived from place in a classification, and the transformation process. The quantitative techniques of the method exhibit serious flaws. Much of the data produced by the method appears to be quantitative but in fact is not, and it does not produce truly quantitative estimates of recreation potential. Classifications of generalized geographic or environmental variables are shown to have serious defects as a basis for evaluation of recreational potential.     

COMPETING WATER USES IN THE SOUTHWESTERN UNITED STATES: VALUING DROUGHT DAMAGES1

ABSTRACT: Economic benefit functions of water resource use are estimated for all major offstream and instream uses of Colorado River water. Specific benefit estimates are developed for numerous agricultural regions, for municipal uses, and for cooling water in thermal energy generation. Economic benefits of hydropower generation are given, as are those for recreation on Colorado River reservoirs and on one free-flowing reach. Marginal and total benefit estimates for Colorado River water use are provided. The estimates presented here represent a synthesis of previous work, providing in total a comprehensive set of economic demand functions for competing uses of Colorado River water. Non-use values (e.g., benefits of preserving endangered species) are not estimated.     

Recreational Value of an Oasis in Oman

Increasing demand for water to develop non-agricultural activities is causing water to be diverted to high-value uses at the expense of irrigation. However, agriculture provides a flow of amenities in the desert environment which are not either accounted or paid. Oases are spread all over the globe and are threatened for various reasons among which is the high pressure of demand for fresh water. This paper estimates the recreation use value of an oasis. The paper is based on the Misfat Al-Abryeen oasis in Oman, a man-made area of streams and woodland. The travel cost method is used through an on-site questionnaire distributed to 230 visitors. Around 75% of visitors to the oasis also visited other historical or ecological sites during the same day-trip. The econometric model is estimated using negative binomial regression with endogenous stratification. The average consumer surplus, or benefit, from visiting Misfat Al-Abryeen is estimated at US104.74 per individual per trip. The total social benefit from this oasis is estimated at 104.74 per individual per trip. The total social benefit from this oasis is estimated at 366,590 per year. These results underscore the importance of the role played by irrigated agriculture in the provision of amenity services for the tourism sector in a desert environment. The sustainability of the irrigation activity depends on the recognition of the recreation role of oases and the transfer of part of these benefits to the farmers who maintain the irrigation system. The implementation of an entrance fee to the oasis might increase farmers’ profit by 6–21%.     

Impacts of recreation and tourism on plant biodiversity and vegetation in protected areas in Australia

This paper reviews recent research into the impact of recreation and tourism in protected areas on plant biodiversity and vegetation communities in Australia. Despite the international significance of the Australian flora and increasing visitation to protected areas there has been limited research on recreational and tourism impacts in Australia. As overseas, there are obvious direct impacts of recreation and tourism such as clearing of vegetation for infrastructure or damage from trampling, horse riding, mountain biking and off road vehicles. As well, there are less obvious but potentially more severe indirect impacts. This includes self-propagating impacts associated with the spread of some weeds from trails and roads. It also includes the severe impact on native vegetation, including many rare and threatened plants, from spread of the root rot fungus Phytopthora cinnamomi. This review highlights the need for more recreational ecology research in Australia.     

Quantitative Identification of Disturbance Thresholds in Support of Aquatic Resource Management

The identification of disturbance thresholds is important for many aspects of aquatic resource management, including the establishment of regulatory criteria and the identification of stream reference conditions. A number of quantitative or model-based approaches can be used to identify disturbance thresholds, including nonparametric deviance reduction (NDR), piecewise regression (PR), Bayesian changepoint (BCP), quantile piecewise constant (QPC), and quantile piecewise linear (QPL) approaches. These methods differ in their assumptions regarding the nature of the disturbance-response variable relationship, which can make selecting among the approaches difficult for those unfamiliar with the methods. We first provide an overview of each of the aforementioned approaches for identifying disturbance thresholds, including the types of data for which the approaches are intended. We then compare threshold estimates from each of these approaches to evaluate their robustness using both simulated and empirical datasets. We found that most of the approaches were accurate in estimating thresholds for datasets with drastic changes in responses variable at the disturbance threshold. Conversely, only the PR and QPL approaches performed well for datasets with conditional mean or upper boundary changes in response variables at the disturbance threshold. The most robust threshold identification approach appeared to be the QPL approach; this method provided relatively accurate threshold estimates for most of the evaluated datasets. Because accuracy of disturbance threshold estimates can be affected by a number of factors, we recommend that several steps be followed when attempting to identify disturbance thresholds. These steps include plotting and visually inspecting the disturbance-response data, hypothesizing what mechanisms likely generate the observed pattern in the disturbance-response data, and plotting the estimated threshold in relation to the disturbance-response data to ensure the appropriateness of the threshold estimate.     

Measuring the Social Recreation Per-Day Net Benefit of the Wildlife Amenities of a National Park: A Count-Data Travel-Cost Approach

In this article, we apply count-data travel-cost methods to a truncated sample of visitors to estimate the Peneda-Gerês National Park (PGNP) average consumer surplus (CS) for each day of visit. The measurement of recreation demand is highly specific because it is calculated by number of days of stay per visit. We therefore propose the application of altered truncated count-data models or truncated count-data models on grouped data to estimate a single, on-site individual recreation demand function, with the price (cost) of each recreation day per trip equal to out-of-pocket and time travel plus out-of-pocket and on-site time costs. We further check the sensitivity of coefficient estimations to alternative models and analyse the welfare measure precision by using the delta and simulation methods by Creel and Loomis. With simulated limits, CS is estimated to be €194 (range €116 to €448). This information is of use in the quest to improve government policy and PNPG management and conservation as well as promote nature-based tourism. To our knowledge, this is the first attempt to measure the average recreation net benefits of each day of stay generated by a national park by using truncated altered and truncated grouped count-data travel-cost models based on observing the individual number of days of stay.     

Comparing the Economic Value of Mountain Biking Estimated Using Revealed and Stated Preference

This research compares non-market valuation techniques by applying a count data travel cost method (TCM) and dichotomous choice contingent valuation method (CVM) to a form of recreation for which it has not been previously applied: mountain biking. Due to mountain biking's increasing popularity these estimates of benefits may be useful in addressing conflicts. One of the most famous mountain biking sites in the US (Moab, Utah) was chosen as the site for which to apply these two models. The benefits that were estimated for trips taken in the spring of 1996 are US$205 and US$235,for the TCM and CVM, respectively.These values are not statistically different using conventional significant levels.