**4. Discussion**

182 Studies on Environmental and Applied Geomorphology

(Heitmeyer and Westphal, 2007; Heitmeyer, 2008b). Each HGM evaluation is much more than simply combining GIS layers. An HGM evaluation reviews the physical setting, climate and hydrology, and the distribution and characteristics of presettlement habitats to establish a potential natural landscape. The HGM then reviews changes due to development and succession to make restoration and management decisions based on the likelihood of natural communities to recover from disturbance and in light of future disturbances. Potential vegetation maps assembled from hydrologic, geomorphic, and soils data are

simply tools to visualize and quantify landscape response to management actions.

Fig. 10. A portion of a HGM map for the St. Louis region.

The near term intent is to complete an initial set of potential natural vegetation maps to help inform forest and land management plans for the entire UMRS (National Great Rivers Research and Education Center, 2010). The hydrology and geomorphology base layers described above were an important precursor to the rapid completion of the project. When the initial potential vegetation maps are complete, or as project needs dictate, potential vegetation maps for alternative floodplain management plans can be modeled to estimate There are many environmental and economic management needs that can be addressed with ecosystem modeling. Hydraulic models have become so precise that their results are routinely used for engineering design to simulate alternative design features (Silberstein, 2006). We believe the HGM approach for potential vegetation community assessment can achieve a similar standard for ecosystem restoration alternative analysis. The methods are not precise to species levels, nor very small spatial scale, at this stage of development but they do match well with the scale of most wildlife refuges and management areas that are the focus of most natural resource management and restoration activity. They also scale nicely for landscape ecology metrics and regional ecosystem management (USACE, 2011). HGM models have been developed for many floodplain systems (Klimas et al. 2009; U.S. Army Corps of Engineers, 2010), and they gain wide agency acceptance when developed collaboratively between managers and scientists.

These HGM methods for the UMRS are still quite simple in their statistical capacity and ability to model land cover occurrence. Future work will explore more rigorous landscape metrics that examine adjacency of land cover classes and associations with physical landscape features. The fundamental premise of the Hydrogeomorphic Method (HGM) is that vegetative communities segregate according to a single, or some combination of landscape features (e.g. geomorphology, hydrology, soil type). Indeed floodplain topography influences the frequency and duration flooding, which both directly influences plants via control over the length of oxic and anoxic phases, and indirectly influences plant communities by changing the physical properties of the soil (e.g. texture, pH, fertility). However, few studies have quantified the degree to which different plant communities segregate along key environmental gradients. By quantifying nonrandom associations among hydrology, soils and vegetation, land managers can increase their odds of successfully matching species and community types to suitable site conditions, thereby improving the odds of successful restoration.

To test the hypothesis that various plant communities segregate according to a given landscape feature or some combination of landscape features, an electivity index can be used (Jacobs, 1974; Jenkins, 1979; Pastor and Broschart, 1990). An electivity index calculates the juxtaposition of one cover type from one GIS data layer with some other landscape feature in a separate data layer.

These methods allow one to empirically test the hypothesis that a particular vegetation cover class 'elects' for a given landscape feature. If a particular cover class indeed elects for a given landscape feature, then it provides land managers with a prescription of broad-scale conditions that may be required for successful establishment of a given plant community under a given set of environmental conditions (Dr. Nathan DeJager, U.S. Geological Survey, Upper Midwest Environmental Sciences Center, La Crosse, Wisconsin, contributed text).

Hydro-Geomorphic Classification

Department of Forest Ecology and Management.

Madison, Paul West – The Nature Conservancy.

Louis, St. Louis, MO, and St. Paul, St Paul, MN.

Great Plains, USA. *Geoarchaeology* 17:141-154.

River Valley. *Geomorphology* 101:362-377.

**6. References** 

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investigations, flow frequency analyses, and flood risk assessments that provided data that were adapted for this study. The Upper Mississippi River Environmental Management Program administered by the U.S. Army Corps of Engineers and U.S. Geological Survey supported land cover mapping, future landscape analysis recommendations, and technical assistance. The U.S. Army Corps of Engineers, Navigation and Ecosystem Sustainability Program provided support to Dr. Theiling and Dr. Heitmeyer. Finally, The Nature Conservancy Great Rivers Partnership graciously supported development of the systemwide presettlement land cover data through a grant to the University of Wisconsin

Many individuals supported data development and analysis: John Burant – U.S. Army Corps of Engineers, Nathan DeJager – U.S. Geological Survey, Tim Fox – U.S. Geological Survey, Edwin Hajic – Illinois State Museum, Ken Lubinski – U.S. Geological Survey, David Mladenoff – University of Wisconsin - Madison, J.C. Nelson – U.S. Geological Survey, John Nelson – Illinois Nature Preserves Commission, Jim Ross – U.S. Army Corps of Engineers, Michael Reuter – The Nature Conservancy, Ted Sickley – University of Wisconsin -

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A multiple reference condition analysis has been proposed for UMRS ecosystem restoration planning (Nestler and Theiling, 2010). Sufficient data exist to evaluate hydrologic and geomorphic ecosystem drivers and land cover in presettlement, several historic snapshots, and contemporary conditions for nearly the entire 2.8 million acres. The virtual reference condition (i.e., simulated hydrology, potential vegetation, or geomorphic features), or plausible alternative future condition, is an important tool to estimate future without project condition and the response to alternative restoration plans (Figure 11; USACE, 2000). It is possible to simulate alternative floodplain management scenarios and extrapolate benefits as simple acreage estimates (Figure 11, bottom), potential vegetation (Heitmeyer, 2008; 2010), or any range of habitat suitability (USFWS, 1980) or ecosystem services metrics that can be attributed to potential land cover estimates.

Fig. 11. Examples for UMRS benefits that may be attained by alternative floodplain management plans. LTRM\_WTR = low flow surface water, WS\_2YR = 50 percent exceedence/2-year flood, Levee = leveed area, WS\_Pool = potential inundation under Pumps Off scenario.

#### **5. Acknowledgements**

An Army Corps of Engineers, Long Term Training Program grant from the Rock Island District and Headquarters supported much of Dr. Theiling's effort. The U.S. Army Corps of Engineers, St. Paul, Rock Island, and St. Louis Districts collaborated on archaeological investigations, flow frequency analyses, and flood risk assessments that provided data that were adapted for this study. The Upper Mississippi River Environmental Management Program administered by the U.S. Army Corps of Engineers and U.S. Geological Survey supported land cover mapping, future landscape analysis recommendations, and technical assistance. The U.S. Army Corps of Engineers, Navigation and Ecosystem Sustainability Program provided support to Dr. Theiling and Dr. Heitmeyer. Finally, The Nature Conservancy Great Rivers Partnership graciously supported development of the systemwide presettlement land cover data through a grant to the University of Wisconsin Department of Forest Ecology and Management.

Many individuals supported data development and analysis: John Burant – U.S. Army Corps of Engineers, Nathan DeJager – U.S. Geological Survey, Tim Fox – U.S. Geological Survey, Edwin Hajic – Illinois State Museum, Ken Lubinski – U.S. Geological Survey, David Mladenoff – University of Wisconsin - Madison, J.C. Nelson – U.S. Geological Survey, John Nelson – Illinois Nature Preserves Commission, Jim Ross – U.S. Army Corps of Engineers, Michael Reuter – The Nature Conservancy, Ted Sickley – University of Wisconsin - Madison, Paul West – The Nature Conservancy.
