Stressor gradients and spatial narratives of the St. Louis River Estuary, a joint Minnesota and Wisconsin Sea Grant study, connected aquatic science research with spatially-explicit stories of local resource issues and place-based geo-quests to enhance spatial awareness and stewardship of the estuary. The goal of this paper is to report and reflect on an integrated study that combined environmental humanities and technology with aquatic science in a spatial context. Our study was organized into three objectives around research, outreach, and evaluation. First, we summarized anthropogenic stressors within high resolution watersheds and linked the watershed stress estimates to aquatic habitats within the estuary. Second, we designed tools to deliver place-based environmental science and technology to targeted users to increase awareness, learning, and the potential for long-term stewardship. And third, we evaluated the responses of targeted end users to their interaction with the project's integrated science and innovative delivery methods. Finally, central to all three objectives, we created a dynamic website to facilitate regional to national coastal outreach and education goals. We found significant correlations between the stressor index and the water quality and biotic data, along with variability attributed to landscape elements. Connecting this science with the place-based experiences we collected is expected to expand the scope and reach of state, bi-national and non-governmental outreach programs. The project also has direct applications to classroom science education. Developing this integrated proj e c t c o n t r i b u t e d t o o u r s h a r e d environmental and cultural aspects of the estuary for place-based education, and offers several lessons for future work of this nature.
We compiled macroinvertebrate data collected from 1995 to 2014 from the St. Louis River Area of Concern (AOC) of Lake Superior. Our objective was to define depth-adjusted cutoff values for benthos condition classes to provide an analytical tool for quantifying progress toward achieving removal targets for the degraded benthos beneficial use impairment. We used quantile regression to model the limiting effect of depth on selected benthos metrics, including taxa richness, percent non-oligochaete individuals, combined percent Ephemeroptera, Trichoptera, and Odonata individuals, and density of ephemerid mayfly nymphs (Hexagenia). We created a scaled trimetric index from the first three metrics. Metric values above the 75th percentile quantile regression model prediction were defined as being in relatively excellent condition in the context of the degraded beneficial use impairment for that depth. We set the cutoff between good and fair condition as the 50th percentile model prediction, and we set the cutoff between fair and poor condition as the 25th percentile model prediction. We examined sampler type, geographic zone, and substrate type for confounding effects. Based on these analyses we combined data across sampler types and created separate models for each of three geographic zone. We used the resulting condition-class cutoff values to determine the relative benthic condition for three adjacent habitat restoration project areas. The depth-limited pattern of ephemerid abundance we observed in the St. Louis River AOC also occurred elsewhere in the Great Lakes. We provide tabulated model predictions for application of our depth-adjusted condition class cutoff values to new sample data.
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