Modeling visitor use on high elevation mountain trails: An example from Longs Peak in Rocky Mountain National Park, USA

Increasing use on mountain summits has both social and ecological implications. High numbers of visitors climbing mountain summits can be a safety issue, particularly in areas where terrain or elevation leads to queueing that may cause time delays. Estimating visitor use levels at site specific locations en route to summits is needed to understand the potential benefits and impacts of visitor use in these locations. However, it can be difficult to obtain reliable and robust data to estimate use and develop statistical relationships because of the remote and harsh climates on mountain summits, as well as the financial and personnel requirements involved to collect the data in remote locations. In 2015, data were collected on the higher stretches of the Keyhole Route on Longs Peak in Rocky Mountain National Park, USA (RMNP) to better understand use levels near the summit and to explore potential statistical relationships to trailhead use data that are relatively easy to collect. Strong statistical relationships from robust regression analyses were found between trailhead use counts and daily and hourly use totals on the “Homestretch” which is a final section of the Keyhole Route. Additionally, a strong statistical relationship was found between total daily use and maximum hourly use on the Homestretch. The results suggest that trailhead counts are an accurate and reliable means from which to estimate use levels on upper portions of the Keyhole route. Moreover, this research demonstrates the usefulness of an approach using proxy variables to estimate visitor use along remote peaks where data collection can be difficult. These types of data can elucidate various options and decisions for park management teams who are charged with deciding if and how to manage high use areas.