Use of aerial photographs to predict lake selection and reproductive success of Common Loons in Michigan

TitleUse of aerial photographs to predict lake selection and reproductive success of Common Loons in Michigan
Publication TypeThesis
Year of Publication1986
AuthorsDahmer PAndrew
Academic DepartmentSchool of Natural Resources and Environment
DegreeMaster of Science
Number of Pages41 pp.
UniversityUniversity of Michigan
CityAnn Arbor, MI
KeywordsREPRODUCTIVE SUCCESS
Abstract

The purpose of this study was to identify key components of an environment whose relationship and interactions can collectively predict, from a random sample of lakes, which will be used by common loons for nesting, and which of those used will be more apt to support a loon pair that will successfully fledge young. Variables evaluated include physical parameters of each lake, human use factors, and nest site characteristics. Of these variables, those that can be remotely sensed from aerial photographs were determined. A probit analysis identifed lake circumference and the presence or absence of a nesting platform offshore as being the best combination of variables to predict lake use. Of 63 lakes, 74.6% were predicted correctly as to whether or not they were used by loons for nesting. Larger lakes with islands, bog mats, or hummocks for nesting were used more readily by loons. Lake area and the percent developed shoreline were the two variables that proved most useful in predicting if a pair of loons on a lake would successfully fledge young. Of the 25 lakes used by loons, 72.0% were correctly classified as successful or not. Lakes with larger surface areas and a smaller percent of their shoreline covered by homes, campsites and beaches harbored loons that were more successful at fledging young. All four variables mentioned above can be quantified remotely from aerial photographs. The use of aerial photographs and other remotely sensed data provides an accurate medium for resource evaluation which can substantially decrease expenses by minimizing the amount of cost-intensive field work.