Corbett, E. A. (Department of Biological Sciences, Southeastern Oklahoma State University, Durant, OK 74701-0609) and R. C. Anderson (Behavior, Ecology, Evolution and Systematics Section, Department of Biological Sciences 4120, Illinois State University, Normal, IL 61790-4120). Landscape analysis of Illinois and Wisconsin remnant prairies. J. Torrey Bot. Soc. 133(2): 267–279. 2006.—We examined Illinois and Wisconsin remnant prairie data to determine regional patterns of species composition as influenced by landforms with different topographic positions and soil properties resulting from glacial history. Three data sets were used, including 84 sites from Wisconsin sampled in the 1950s; 216 sites from Illinois sampled as part of the Illinois Natural Areas Inventory (INAI) in the 1970s; and a subset of 29 INAI sites resampled in 1998. These data sets are the best characterization of remnant prairie vegetation in the two states after most of the original prairies were lost. Data were analyzed using detrended correspondence analysis (DCA), principal components analysis (PCA), and canonical correspondence analysis (CCA). CCA was used only for the INAI sites resampled in 1998 that had a complete set of soils data. Results from all analyses were similar. We determined that an interaction between topographic position and soil texture, which affected moisture availability, was most important in influencing species composition and abundance in Illinois and Wisconsin remnant prairies. Separation of dominant prairie species in Illinois and Wisconsin followed similar patterns, if differences in community designation for similar vegetation types were considered. However, Wisconsin and Illinois sites separated on DCA axis 2, which was negatively correlated with calcium and phosphorus. The first DCA ordination axis for INAI prairie sites was correlated with a topographically-based Integrated Moisture Index (IMI). For the 1998 INAI data, PCA was used to reduce soil variables to fewer dimensions and resulting axis 1 scores were used in stepwise multiple regression analysis to determine relationships between environmental variables and DCA ordination axis scores. The IMI was the first variable entered in the stepwise multiple regression model; however, PCA axis 1 stand scores based on soil variables did not meet criteria for entry into the model. For all data sets, including the CCA ordination of the resampled INAI sites, there was a secondary separation at the dry end of the moisture gradient between hill prairies and dry sand prairies, which was related to differences in soil texture and availability of calcium and phosphorus. In general, soil nutrients and texture were less important than topographically controlled moisture availability in determining prairie species composition and abundance at this scale of analysis.
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Vol. 133 • No. 2