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This paper examines heterogeneity in the preferences for OHV recreation by applying the random parameters Poisson model to a data set of off-highway vehicle (OHV) users at four National Forest sites in North Carolina. The analysis develops estimates of individual consumer surplus and finds that estimates are systematically affected by the random parameter specification. There is also substantial evidence that accounting for individual heterogeneity improves the statistical fit of the models and provides a more informative description of OHV riders.

This study employs a Markov chain model of vegetation dynamics to examine the economic and ecological benefits of post-fire revegetation in the Great Basin sagebrush steppe. The analysis is important because synergies between wildland fire and invasive weeds in this ecosystem are likely to result in the loss of native biodiversity, less predictable forage availability for livestock and wildlife, reduced watershed stability and water quality, and increased costs and risk associated with firefighting. The analysis is based on a parameterized state-and-transition model of vegetation change for Wyoming big sagebrush community in the Great Basin sagebrush steppe. This conceptual model was formulated into a quantitative, predictive model by implementing it as a Markov chain process that links vegetation change, management, and costs. Simulation results were used to develop cost curves for achieving ecological goals and to evaluate uncertainty in future vegetation conditions. The Markov chain model shows that post-fire revegetation using either a native seed mix or crested wheatgrass was more effective than no revegetation for achieving ecosystem objectives. Further, post-fire revegetation with either seed mix cost less than no revegetation because of resulting reductions in fire suppression costs. Consequently, post-fire revegetation makes both ecological and economic sense, and the choice of seed mix should depend on the prioritization of management objectives. Identifying the economic and ecological tradeoffs of different management strategies should enable improved management of the sagebrush-steppe, and Markov processes provide a straight-forward method for identifying these trade-offs.

This analysis breaks down the congestion levels experienced during specific parts of a wilderness canoe trip. By explicitly addressing the heterogeneity in preferences for congestion during a trip, we were able to determine the relative value canoeists place on solitude at different points of a trip. Our econometric model utilizes a random effects probit framework to efficiently estimate the welfare impacts of congestion on each trip portion. The welfare effects of congestion levels vary across wilderness areas, parts of a trip and individuals.

Surveys of visitors to National Forests in Colorado were conducted to determine whether different fire ages and presence of crown fires have different effects on hiking and mountain biking recreation visits and benefits. Actual and intended behavior data were combined using a count-data travel cost model. The intended behavior trip questions asked about changes in number of trips due to the presence of a high-intensity crown fire, prescribed fire, and a 20-year-old high-intensity fire at the area respondents were visiting. Using the estimated recreation demand function, years since a non-crown fire had statistically significant positive effect on the trip demand of hikers. In contrast, presence of crown fires had no statistically significant effect on the quantity of hiker trips, but had a significant and negative effect on mountain biking trips. Crown fires also had a large effect on the value per trip, with crown fires increasing the value per hiking trip but lowering the value per mountain biking trip.

W-133 Western Regional Project Technical Meeting on Benefits and Costs of Resources Policies Affecting Public and Private Land, Kauai, Hawaii, February 28 to March 1, 2000