Comparing Multi-Scale Predictors Of Fish Growth: Towards A Regional Framework For Fish Management
Tyler Wagner, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824; (517) 353-2267; FAX (517) 432-1699; wagnerty@msu.edu
Mary T. Bremigan, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824
Kendra Spence Cheruvelil, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824
Patricia A. Soranno, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824
Nancy A. Nate, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824
James E. Breck, Department of Fisheries and Wildlife, 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824
Fish growth rates are highly variable among lakes. Because fish growth rates are fundamental to sport fish production and ecological interactions in lakes, managers of large areas seek tools for grouping lakes with similar fish growth rates. Developing these tools is difficult because factors controlling fish growth rates operate at multiple spatial scales. Identifying whether local or regional controlling factors explain the most variability among lakes will greatly assist the development of regional management plans. We used a multi-level modeling approach to determine if variability in mean length at age could be partitioned by ecoregion sections, a commonly used grouping, and further explained by local water quality and lake morphometry characteristics. We used mean length at age data from annual agency surveys conducted during 1974-1984 for two age classes of seven common warm and cool-water fish species. These years coincided with water quality and land use data collection for this region. Nearly all the variability in mean length at age occurred within ecoregions, suggesting that the ecoregion framework is ineffective at partitioning variance in mean length at age. Within ecoregions, water quality and lake morphometric characteristics accounted for 2 - 23% of the variation in mean length at age. Measures of lake productivity, specifically total nitrogen, were the most common significant covariate, with mean length at age increasing with increasing lake productivity. Classifying lakes at a smaller spatial scale, by major river watershed, partitioned variance in 3 out of 14 analyses. Watershed land use, geology and average lake chlorophyll a explained 39 - 100% of the variability between watersheds; however the total between-watershed variability was small, ranging from 1.8 - 3.7% of the total variance. Our results suggest that the development of an effective regional framework for managing inland lakes is species and scale-dependent and will require a substantial effort to understand sources of variability. These results also suggest that managers should not depend on previously developed classifications to effectively group lakes with similar growth rates.