Results and Discussion

Overview - The shoreline figures portray a complex nearshore environment along Minnesota's North Shore. All of the figures show substrate patches consisting of a variety of substrate types ranging from fine sands to large boulders and bedrock. The substrate patches appear in a range of sizes from tens of square meters to over a 100,000 square meters in area. Furthermore, the depth and steepness of the nearshore region are quite variable along the areas surveyed.

The survey data are summarized for comparative purposes with respect to ten sections of approximately equal length (11 kilometers) along the shoreline from Duluth to Grand Marais (Tables 1 and 2). The ten sections of shoreline vary considerably with respect to the eight substrate categories. In general, sand, sand and cobble, cobble, and conglomerate categories were the most frequently encountered substrate types. However, the proportions of available habitat that these categories represented diverged among the sections and among the two depth categories shown in the table. For example, sand and other fine particles represented more than 30 percent of available shallow habitat in the Lester River to French River section while this category represented only three percent of available shallow habitat in the Gooseberry to Split Rock Lighthouse section (Table 1). On average, all sections of the shoreline between Duluth and Gooseberry Falls had higher amounts of fine substrates than nearshore areas farther up the shoreline. Also, deeper habitats tended to have greater amounts of fine materials than shallow habitats. This tendency reflects the movement of these substrates from the shoreline into deeper portions of the lake and the erosion of these materials from shallow areas with wave action.

Fisheries Habitat - As an example of how these data can be used to directly relate substrate and depth information to potential lake trout spawning habitats, we combined the eight substrate types into two categories that indicate good and poor potential spawning habitats. Since lake trout typically prefer larger substrates with little or no fine materials for spawning (Marsden et al., 1995), we combined areas comprising cobble, boulders, conglomerate, and rough bedrock into the "good" spawning habitat category and combined the sand, sand and cobble, sand over bedrock, and smooth bedrock substrates into the "poor" spawning habitat category. It should be noted that these analyses refer to spawning habitat only and that other life stages of lake trout may utilize habitats in the nearshore regions that are considered poor spawning habitat. The results of this analysis clearly show the relative amounts of potential good and poor spawning habitat among the ten shoreline sections (Figure 17). Among the sections with complete survey coverage, the Grand Marais to Red Cliff area had the greatest amounts of potential "good" spawning habitat where well over 50 percent of the total potential spawning area was in the "good" category. The sections between the Lester River and the Encampment River had somewhat less than 50 percent of the total area in the potential "good" spawning category but each section still had more than 100 hectares of "good" spawning habitats. The three sections with partial survey coverage all had a high proportion of "good" spawning habitats.

The largest portion of "good" spawning habitat in all sections with full surveys was from shallow habitats (< 60 ft) (Figure 18). This trend was most notable in the three sections between the Lester River and Two Harbors. The tendency for deep habitats (>60 ft) to have higher amounts of fine substrate materials resulted in a smaller contribution of deep water habitat to potential "good" spawning habitat. These trends point out the importance of relatively shallow water directly adjacent to the shoreline as potential spawning areas for lake trout. Such areas are frequently impacted by upland land uses. We anticipate that these maps will be useful for making informed land use decisions that could affect lake trout spawning habitat in the future.

Other Data Uses - We have provided four additional figures which illustrate other potential uses for the survey data. These are essentially the same data as displayed in the other figures but they have been manipulated and enhanced in a GIS environment to serve other purposes. The first image (Figure A) is simply a larger scale image, with ten foot contours, centered on a proposed shoreline development area in the McQuade Road area near Duluth. The second two figures (Figures B and C) are enhanced images of a fisheries research site near the Split Rock River. Figure C is part of a flyover movie of this site. Finally, Figure D shows a 3D image of the Silver Bay harbor that has been merged with a georeferenced aerial photo of the general area. The resulting image nicely portrays the shoreline characteristics, bathymetric contours, and substrates near the harbor site as they were in 1995. In addition, we developed a 3D movie which allows the viewer to see the Silver Bay site as it would look during a normal flyover and then as it would look if the water was completely transparent. The movie clip provides an intriguing way to portray fisheries habitat.

Summary - The graphical results of this study provide another tool for lake trout management on Minnesota's North Shore that can be used by fisheries professionals and other interested lay persons alike. Our study points out the usefulness of these readily available technologies for both visual communication of ideas relating to fisheries management as well as a means for quantifying key habitat components required by a fish species. The data provided with this CD-ROM are in a common format that can be manipulated for other purposes within a GIS environment or other data analysis systems. These base maps can be expanded with new data or layered with additional information to examine other natural resource management issues involving land use planning, fisheries management, or basic science related to understanding Lake Superior's ecosystem.

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