Estimating visitor use of protected areas by modeling accessibility: A ...

THEOBALD, NORMAN, NEWMAN / Journal of Conservation Planning Vol 6 (2010) 1—20DISCUSSIONWe developed models of accessibility to understand thespatial distribution of potential visitor use in RockyMountain National Park, and illustrated how thesepatterns of use could be summarized for managers whoare interested to understand the resource condition ofdifferent areas of the park. We provided a brief illustrationof how the accessibility measure can inform an issue ofmanagement concern in the park – specifically aboutpathways for exotic species such as cheat grass, and inparticular the relationship between visitor use anddistribution (and future spread) of exotic species. Weshowed that cheat grass occurs in more accessible areas– roughly 80% of plots with cheat grass are within onehour’s travel time.We also placed our work into a decision makingframework by examining how levels of accessibility variedfor different management zones within the park. That is,as specified in park planning documents, the expectationis that “front country” areas have high levels of visitor use,while “back country” areas (called “outstanding naturalareas”) should have low levels of use. Travel time showsthat there is a mixture of values, showing more variabilityof impacts due to visitation. Travel time tracks moreclosely to road distance in the front-country zone, while ittracks more closely to the trail distance for the backcountryzone.A few limitations to our approach should be noted. Mostdata we used were fine-scale (1:24,000), but the spatialposition of the roads in particular (from 1:100,000 scale)should be refined in future efforts. The goal ofaccessibility modeling is not to estimate the distribution ofvisitors (e.g., a density map of visitors); rather to estimatehow accessible any location in a park is to an averagevisitor, with the explicit assumption that more accessibleareas tend to have more visitor use. A useful next stepwould be to estimate the number of park visitors movingacross the landscape by incorporating destinations/attractions (e.g., peaks, lakes, waterfalls, etc.), perhapsusing recreation choice modeling (e.g., Termansen et al.2004). This might also include more nuanced aspects ofvisitor use such as type of use (day/overnight), mode(hike, bike, horse, motorized, etc.), duration, and valuesorientation to use. Finally, although we have verifiedaccessibility times in the field in an informal way, arigorous study that develops empirical estimates of traveltime for different users, mode of use, and permeabilitymodifiers as a function of different land cover types wouldmake estimates of travel time more precise.CONCLUSIONWildlife managers are increasingly concerned aboutassessing potential effects of visitor use on the naturalresources in parks and protected areas. Although somemonitoring programs have been developed (e.g., USForest Service National Visitor Use Monitoring program),there remains a paucity of information about detailed uselevels and especially the spatial patterns of use (White etal. 2007). Consequently, developing estimates of visitoruse through landscape modeling provides criticalinformation to managers. We described several importantrefinements to accessibility modeling and illustrated ourmethod for Rocky Mountain National Park. We found thatour accessibility model better differentiates front- andback-country use patterns compared to more traditionalmeasures, and demonstrated its utility as a strongexplanatory variable to understand importantmanagement issues such as monitoring of exotic plantspecies distribution.ACKNOWLEDGEMENTSWe thank our colleagues from the National Park Service,including J. Connor, B. Frakes, L. Gamble, B. Schweiger,and R. Thomas, as well as S. Linn for editing andassistance with trail data from the Colorado Trails project.18