1. Great Environmental Indicators (GLEI) Lakes

2. http://glei.nrri.umn.edu/default/Reports.htm

6. Objectives Quantify stressor-response relationships for novel and existing indicators; Develop predictive models to infer ecological status; Develop integrative metrics among sub- components

7. SOLEC Indicator Classes SOLEC differentiates between indicator types: Pressure (= stressor) indicators (e.g. contaminants) State (= response) indicators (e.g. fish populations)

8. Multimetric & Multivariate Approach LANDSCAPE segment-sheds & watersheds LOCAL -Habitat quality, -Habitat quantity STATE INDICATORS Geology Elevation Hydrography Climate Land Use/Cover Habitat patch Hydrology Food web Substrate Nutrient dynamics Diatoms Vegetation Macrobenthos Fish Amphibians Birds Water Quality Contaminants INTEGRATED INDICATORS -Habitat -Chemical -Biotic -Physical -Hydrologic REFERENCEDEGRADED PRESSURE INDICATORS Shoreline Units High energy shore Embayment Coastal marsh River-influenced wetland Protected wetland

9. Spatial Scale T e m p o r a l S c a l e meters10km days year 10yr month 100yr vegetation Contaminants, diatoms (cores) fish Spatial & Temporal Scales WQ invertebrates birds amphibians

10. 3 types of wetlands Protected wetland (Barrier beach) open shoreline riverine influenced wetland 2 types of shoreline High energy low energy (embayment) Stratified Random Sample

11. Site Selection vs Site Characterization Need to move quickly into the field. No complete inventory of geomorphic types or anthropogenic stressors. Data for site selection can be coarse, but across the Great Lakes Basin. Site characterization data should be high resolution, but only needed for sampled sites.

12. Site Selecton - Segment Sheds as Summary units –Watersheds for lengths of shoreline beginning and ending ½ way between 2 nd order and higher streams (n = 762). –Data summarized across US side of Great Lakes 2 nd order Segments

13. Lake Ontario 90 Lake Erie 102 Lake Huron 148 Lake St. Clair 12 Lake Michigan 157 Lake Superior 236 Connecting Channels 17 TOTAL 762

14. Stressor Gradient (cont.) DATA SOURCE Agriculture fertilizer and herbicide use (NRCS) Ag Runoff (erosion, pesticides, and nitrogen; NRCS) Distance to nearest AOC (Areas Of Concern; EPA) National Atmospheric Deposition Program (NADP) Population density (US Census Bureau) Land use by cropland type (NRCS) Erosion from agricultural land (NRCS) Fertilizer use on agricultural land (NRCS) Confined animal facility waste treatment (NRCS)

15. DATA SOURCE Shoreline alteration (MRV; ACOE) Land use, general (USGS-NLCD) N, P runoff potential (USGS-NAWQA SPARROW) NPDES categories (EPA) Urbanization amount/rate (NRCS) Wetland amount (total; NRCS) Wetland types, hydric soils, and erosion (NRCS-NRI) Road area, 4 types (US CENSUS TIGER) Soil properties (NRCS STATSGO) Toxic Release Inventory points (EPA from BASINS ) Stressor Gradient (cont.)

16. Classify Stressors Purpose: to reduce overlap in the types of information from different stressor source Seven ‘natural’ categories Agricultural / Ag-chemical (n = 21) Atmospheric Deposition (n = 11) Human Population / Development (n = 14) Landcover (n = 23) Point-source / Pollution (n = 79) Shoreline (n = 6) Soils (n = 53)

17. Define Segment-shedsCompile Stressor DataEvaluate & Categorize Stressors Data organization Select Segment-sheds Select Sampling Locations within Segment-sheds Site selection Cluster AnalysisSecond-round PCAs Ordering sites in stressor-space (multivariate statistics) PCAs of Individual Stressor Cat. 1234567

18. Anthropogenic Stressor Gradient Anthropogenic Stressor Gradient Summarized 217 variables from 19 different sources to identify a multi-deminsional stressor gradient (Represented using PC’s of 7 natural categories) Site Selecton (cont.)

20. Site Characterization Identified specific watershed for sampled sites –GPS from the field –Locale polygons created for each sub-component team. –Complex polygons for each sampled area –Watersheds delineated for complexes –Stressors summarized. GPS points from field Locale Polygons from GPSComplex polygons from locale polygons Watersheds for Complexes

21. High Energy Site

22. Scalable Watersheds – Arc Hydro ArcHydro data model – developed to “pre- process” elevation data to more efficiently delineate watersheds. –AGREE drainage enforcement using NHD line- work –Fill sinks, flow direction, flow accumulation, stream identification, sub-catchment delineation.

23. ArcHydro – Cont. Catchments are delineated for each stream confluence and river mouth along coast. –Catchments for river systems are dissolved together. Catchment

24. Grand River Watersheds

25. Extending Watersheds to the Coast

26. ArcHydro – Cont. Along the coast, areas between river mouths, but outside of watersheds remain. We refer to these mostly small coastal watersheds draining directly to the coast but without significant streams as “Coastal Interfluves”.

27. Extending Watersheds to the Coast Coastal Interfluves

28. ArcHydro – Cont. Both stream and interfluve sheds are then ordered and numbered along the coast from west to east. This provides a framework for scaling stressor summaries up and down the coast.

32. Additional Efforts Lake Erie Integrated Habitat Map –Both US and Canadian sides of Lake Erie basin. Canadian Great Lakes Anthropogenic Stressor Gradient. –Currently summarizing stressors in the same way as we have done for GLEI for Canadian side of Great Lakes Basin Full ArcHydro implementation for Saint Louis River (Lake Superior), Maumee and Grand River watersheds (Lake Erie). –Provides for “accumulated stress” or landscape characterization down the drainage network.

33. LAND COVER – Great Lakes

36. N = 9,860

37. Accumulated SumRel stressor score for the Saint Louis River Watershed