Emily Gaenzle

Date of Award


Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Ecology and Environmental Sciences


John R. Moring

Second Committee Member

Alexander Huryn

Third Committee Member

Joan G. Trial


Predicting patterns in species distribution and abundance for resource management and conservation is a major focus of applied ecology. The primary objective of this study was to determine if there is a predictable relationship between stream geomorphology and fish community structure, native species richness, and native salmonid abundance in Maine. Specifically, I examined relationships between fish assemblages and geomorphic stream types, as delineated by the Rosgen classification system (Rosgen 1996). Fifty-three stream reaches in Maine were classified, and fish communities within the reaches were characterized using backpack electrofishing. Species richness was lowest in A-type streams (i.e., steep, entrenched, confined), which supported brook trout (Salvelims fontimlis) and slimy sculpins (Coftus cognatus). Richness was highest in C-type streams (i.e., low gradient, meandering with broad, well defined flood plains). Salmonids were in greatest abundance in B- (i.e., moderately entrenched, moderate gradient) and C-type streams. A secondary objective was to identfiy environmental correlates of fish community structure using a geographic information system (GIs). Specifically, I examined relationships between fish community attributes (e.g., species richness, species distribution) and watershed landcover, proximity to dams, biophysical region, and elevation. Fish species richness was negatively correlated with elevation and was significantly different among different biophysical regions in the state. Atlantic salmon (Salmo salur) distribution was significantly correlated to watershed landcover. The ability to predict species distribution and abundance based on physical stream characteristics and biophysical region has important implications for watershed and fisheries management. Collecting data on geomorphic variables is more efficient and is less invasive than sampling fish communities through the use of electrofishers and gill nets. GIs is an important tool that can be used to predict species richness and distribution. Data on broad-scale environmental variables, such as landcover and elevation, are easily obtained using GIs coverages, thus reducing the need for extensive field work. Ultimately, the ability to identie which stream reaches may contain diverse fish assemblages and/or abundant salmonid populations will contribute to decision-making for watershed conservation and channel restoration efforts.