Tuesday, August 5, 2008
Exhibit Hall CD, Midwest Airlines Center
Jacqueline M. White1, M. Forbes Boyle2, Lee Anne Jacobs3, R. Todd Jobe4, Kristen M. Kostelnik5, Elizabeth R. Matthews6, Jeffrey E. Ott7, Alan S. Weakley3, Thomas R. Wentworth8, Brooke E Wheeler9 and Robert K. Peet10, (1)Curriculum for the Environment and Ecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, (2)Department of Biology, University of North Carolina - Chapel Hill, Chapel Hill, NC, (3)Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, (4)Geography Department, University of North Carolina, Chapel Hill, NC, Chapel Hill, NC, (5)Plant Biology, Michigan State University, East Lansing, MI, (6)California Phenology Project, University of California Santa Barbara, (7)Department of Biology, University of North Carolina, Chapel Hill, NC, (8)Plant & Microbial Biology, NC State University, Raleigh, NC, (9)Curriculum in Ecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, (10)University of North Carolina
Background/Question/Methods Geographic affinities of floras are relevant to understanding patterns in ecology and biogeography because the distribution of geographic affinities at a locale suggests species sorting by history and environment. Previous work using qualitative cluster and vector approaches for characterizing geographic affinities of different plant communities has found variation in such affinities along environmental gradients. However, qualitative approaches are limited because cross-site and cross-observer results are not always comparable. We improve upon this method for characterizing geographic affinities by developing a quantitative approach using vectors drawn from focal locales to the area-weighted centroids of species’ ranges.We demonstrate this technique using the physiographic regions of North Carolina (Mountains, Piedmont and Coastal Plain). We calculate the mean vector for the regional flora as a measure of the geographic affinity of that region. Within the regions we compare the mean vectors of the total flora to those of finer-scale vegetation types.
Results/Conclusions
Regional patterns confirm expectations that the Applachian Mountain flora has more northern affinities than those of the Piedmont or Coastal Plain. However, variance in geographic affinities at the regional scale is higher than for finer-scale vegetation types. We partition the variance at each scale using cluster analysis of the distributions of vector directions and lengths. These results illustrate that regional floras are more reflective of biogeographic history, but that local floras are a subset of this larger species pool with more narrow geographic affinities reflecting sorting by environment. This novel quantitative technique for characterizing geographic affinities improves on previous methods by removing bias and subjectivity from the analysis. This standardized approach has applications for characterizing community uniqueness, prioritizing conservation areas, and identifying crossroads of biodiversity.
