Predicting Multiflora Rose Habitat on the Sewanee Domain Charlotte Henderson and Will Cowan Department of Biology and Environmental Studies Program Combined.

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Predicting Multiflora Rose Habitat on the Sewanee Domain Charlotte Henderson and Will Cowan Department of Biology and Environmental Studies Program Combined Class Project: Biol Advanced Conservation Biology (Dr. Evans) & EnSt Fundamentals of GIS (Dr. Van de Ven) Introduction Multiflora rose (Rosa multiflora) is an invasive species on the Sewanee Domain; planted as a solution to soil erosion, as an ornamental plant, and to act as a “natural fence” (USNPS, 2010). It can replace original vegetation because of fast growth, shade-tolerance, and tolerance to various soils and moistures (Hartzler, 1992). It has been seen to take hold in areas of previous clearing and disturbances (Gover, 2007). Multiflora predictions has never been mapped before on Sewanee domain. Our study was to create a model, through the application of GIS layers, to be used for multiflora prediction. Methods 1. We went to study site (Lake Cheston) to find elements associated with multiflora and what influences were prevalent Lake Cheston – dam, creek running from Lake Cheston, gravel parking lot edge, dry area of previous pine presence, edge next to volleyball court. 2. Observations were made as to multiflora rose presence: Areas of moist depression Areas in close proximity to an edge Areas with tulip poplar, smilax, privet, and mountain laurel 3. With our observations of multiflora presence, we used these applicable parameters as indicators for disturbed areas, through GIS mapping, to the Sewanee landscape: fire lanes and roads (15m buffer) different land types shrub forest types, dumps, and human disturbed areas concentration density of tulip poplar areas of moisture accumulation (via an elevation map) Figure 1. Multiflora rose (Bergmann, 2009) Results The overlapping layers of moisture and disturbance are places of predicted multiflora rose habitat. Places of multiflora abundance: Areas of moist depression Areas in close proximity to an edge (dam; gravel parking lot; volleyball court) Areas with tulip poplar, smilax, privet, and mountain laurel On our map, Lake Cheston is a place of multiflora presence. Now that we have mapped the predictions, they should be validated by future Conservation Biology classes. *There was no data for disturbances in Lost Cove Figure 3. Multiflora presence near dam, Lake Cheston, Sewanee, TN Figure 4. Multiflora presence near volleyball court, Lake Cheston, Sewanee, TN Conclusions Our goal was to create a model that can be used to predict the presence or future invasion of multiflora rose. The prediction of multiflora is important for the future management of this invasive species on the Domain. With our GIS map, management practices can be implemented in outlined areas. Our results indicate that any future efforts to control multiflora rose should focus on areas near human disturbance such as powerline cuts, roads and dumps. Our model must be validated by future classes. Figure 2. GIS map of potential multiflora rose habitat in Sewanee, TN as a function of roads/fire lanes, shrub forest types, dumps, disturbed areas, tulip poplar presence, and moisture. Further Information Charlotte Henderson – Will Cowan - Literature Cited Multiflora Rose (Rosa multiflora). Wisconsin Department of Natural Resources, Madison, Wisconsin. Bergmann, Carole and Jil M. Swearingen Least Wanted: Multiflora Rose. Plant Conservation Alliance’s Alien Plant Working Group, Maryland. Gover, Art, Jon Johnson, & Jim Sellmer Managing Multiflora Rose. Pennsylvania State University: College of Agricultural Sciences, University Park, PA. Hartzler, Robert G. and Michael D. K. Owen Multiflora Rose and Its Control. Iowa State University of Science and Technology, Ames, Iowa. U.S. National Parks Service (USNPS) Shrubs and Subshrubs: Multiflora Rose. U.S. Department of the Interior. Figure 5. Multiflora presence near dam, Lake Cheston, Sewanee, TN The observations taken from these sites are the basis for our predictions and model. The study occurred in Spring 2011.