Keeping Tight Lines: Understanding the Impact of Variable Snowpack Depth on Brown Trout and Proposing a Mathematical Analysis of Fly-Fishing

Abstract

Trout are viewed as a challenge in the realm of fly-fishing, requiring delicate presentations and putting up tough, acrobatic fights once hooked on a fly. This two-part thesis analyzes if climate change is posing a threat to brown trout in the Upper Colorado River and applies mathematics to field data to determine whether the revered art of flyfishing for trout is a completely random process. Climate change currently poses a threat to river ecosystems that rely on springtime runoff of snowpacks that act as essential water reservoirs during the winter months. Rising mean surface air temperatures in the Western United States are leading to anomalous snowpack depths in the Rocky Mountains. These snowpacks’ depths have a strong, positive correlation to mean daily maximum stream temperatures and are leading to statistically significant changes in stream temperatures in recent years. Although these changing stream temperatures have not significantly affected brown trout populations in the Colorado River, they pose a threat if the changes in snowpack depth continue. The second part of this thesis applies different models to data sets from field research from the Colorado River and Green River to determine probabilites of certain wait times as well as the likelihood of catching a certain number of fish on any given day. Using three separate processes, this study determines fishing to be non-random, asserting that the practice of catching fish has patterns. The study provides an unorthodox approach to fly-fishing: a statistical analysis.