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Evaluations of Duck Habitat and Estimation of Duck Population Sizes with a Remote-Sensing-Based System


The U.S. Fish and Wildlife Service has long been involved in monitoring wetland conditions and duck populations. Cooperative breeding-ground surveys by the United States and Canada (Martin et al. 1979; Reynolds 1987) have provided data essential to management of continental waterfowl populations. However, these surveys were designed for obtaining data that are used primarily for setting annual hunting regulations and were not intended for obtaining data for the management of national wildlife refuges and wetland management districts or for evaluating differences of habitat use by ducks among landownership classes.

To meet the unfilled need for data from local areas, Hammond (1969) developed a system for measuring duck use and production on refuges and in waterfowl production areas in the prairie pothole region of the United States. That system was frequently modified to meet the needs and resources of individual managers, and some of the parameters that were used in the procedure were later shown to be erroneous. In addition, the Hammond system did not allow comparisons of duck use and production among lands owned by the U.S. Fish and Wildlife Service, easements by the service, and private lands. This is a critical need by managers in the prairie pothole region. With our system, we attempted to overcome some of the shortcomings of the previous system.

Here we describe a remote-sensing-based system for estimating the number and area of ponds, the sizes of breeding duck populations, and the number of young ducks recruited to the population each fall in the prairie pothole region of Minnesota, North Dakota, South Dakota, and Montana. The area of upland habitat, number of ponds, and areas of ponds in 18 waterfowl management districts (all districts in the Dakotas and in Minnesota but only the most eastern districts in Montana) were estimated.

Our goals were to design a system that provides consistent estimates among areas and years, to maximize the use of existing data, to rapidly execute complex procedures with microcomputers, and to develop a database that documents changes in the estimated parameters.

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