Date of Award

Spring 5-14-2016

Level of Access Assigned by Author

Campus-Only Thesis

Degree Name

Master of Science (MS)


Forest Resources


Sandra de Urioste-Stone

Second Committee Member

Aaron Weiskittel

Third Committee Member

Todd Gabe


Tourism is an important component for many economies globally. In Maine specifically, tourism is one of the largest industries. Therefore, any changes to tourism flows or expenditures could have a significant impact on communities in Maine. Weather and climate are influential to tourists, impacting when and where people travel and the quality of their experience. Understanding the impact of weather on tourism spending is important because climate change is altering the average weather, so this would provide insight into how spending could change in the future. Additionally, understanding visitors’ perceptions on weather and climate change is useful to understand and influence behavior. This study begins by utilizing secondary data to investigate the impact of past weather (2004-2014) on tourism-related spending at three geographically distinct Maine locations, including Mount Desert Island, Bethel, and Millinocket. A nonparametric method (boosted regression trees) was used to first assess which of twenty-two weather variables were influential predictors of spending. Following this, a parametric model was constructed to statistically evaluate monthly tourism-related spending and predict spending under increased temperatures, since climate change is expected to continue increasing temperatures across Maine. Results show that warmer temperatures in the summer and fall will increase tourism spending, while warmer temperature in the winter will decrease spending up until 4.6°C. This is likely because warmer temperatures across the U.S. may make a comparatively cooler climate, like that of Maine, more appealing in warmer months, but reduce the opportunity to participate in snow-dependent activities. To better assess how weather impacts tourists, the second part of this study surveyed 704 tourists throughout Maine. Segmentation analysis based on activities participated in was used to split them into three groups: non-nature-based tourists, nature-based generalists, and nature-based specialists. Non-nature-based tourists had the lowest influence of weather, the lowest belief in climate change, and spent on average greater than $40 more per person per night. These two studies, using statistical models and visitor surveys, are complementary ways of investigating the impacts of weather on tourism spending and flows by both analyzing secondary data and gaining perspective from visitors’ perceptions. Results are useful to provide insight as to how tourism expenditure might change with a changing climate.