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LANDSCAPE-SCALE MONITORING OF AN OPPORTUNIST: PHRAGMITES AUSTRALIS (CAV) STEUDEL IN GREAT LAKES COASTAL WETLANDS
Citation:
Lopez, R D., C M. Edmonds, E. Jaworski, A C. Neale, K B. Jones, D T. Heggem, J G. Lyon, AND D Garofalo. LANDSCAPE-SCALE MONITORING OF AN OPPORTUNIST: PHRAGMITES AUSTRALIS (CAV) STEUDEL IN GREAT LAKES COASTAL WETLANDS. Presented at International Association for Landscape Ecology, Alberta, Canada, April 2-6, 2003.
Impact/Purpose:
The objectives of this task are to:
Assess new remote sensing technology for applicability to landscape characterization; Integrate multiple sensor systems data for improved landscape characterization;
Coordinate future technological needs with other agencies' sensor development programs;
Apply existing remote sensing systems to varied landscape characterization needs; and
Conduct remote sensing applications research for habitat suitability, water resources, and terrestrial condition indicators.
Description:
Coastal wetlands of the Laurentian Great Lakes (LGL) are among the most fragmented ecosystems in the world, with a long history of human-induced disturbances, primarily as a result of agricultural conversions and hydrologic changes. A substantial number of remnant LGL coastal wetlands contain plant communities that are dominated by several opportunistic plant species,including the common need Phragmites australis (Cav.) Steudel. In North America P. australis communities have become large and monospecific in many coastal wetlands, supplanting other plant taxa within the wetlands Compared to wetlands with more heterogeneous plant communities, wetlands dominated by P. australis are less biologically diverse and provide less suitable habitat for other organisms. From an LGL resource management perspective, P. australis is considered a nuisance because it is persistent, produces large amounts of biomass, propagates easily, and is very difficult to control with mechanical or chemical techniques. Semi-automated remote-sensing techniques were used to map P. australis in ten coastal wetland regions of Lake Huron, Lake St. Clair, and Lake Erie. User's accuracy exceeds 90% for P. australis maps that describe areas of greatest stem density and greatest percent cover. Results of this study demonstrate how a combination of airborne remote-sensing and baseline ecological field sampling may improve the accuracy of mapping wetland vegetation, one of the least accurately mapped land cover classes. Because wetland biodiversity is an important component of ecosystem integrity and wetland field mapping is expensive, dangerous, and time consuming the semi-automated techniques described could improve the cost-effectiveness of wetland monitoring in the LGL. The techniques described also have potential applications in other plant communities, ecosystems, and regions.