Wednesday, August 6, 2008: 8:20 AM
103 DE, Midwest Airlines Center
Ines Ibanez, School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, John A. Silander, Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT and Adam M. Wilson, Ecology & Evolutionary Biology, Yale University, New Haven, CT
Background/Question/Methods To ensure the successful control and eradication efforts of invasive plant species, we need information that can identify areas prone to plant invasions and criteria that can point out which particular populations may become the focus of further spread. Specifically, our work aimed to identify hotspots of invasive plant species in the region of New England, in the northeast USA. We also evaluated the environmental conditions, climate, landscape structure, and habitat type that gave rise to successful populations of the studied invasive species. In this study, we combined extensive data sets on invasive species presence/absence and abundance (
www.IPANE.org project), together with climate, habitat and land cover data. From here we estimated invasive species richness as a function of those environmental variables by developing a spatially explicit general linear model within a hierarchical Bayesian framework. In a second analysis we used an ordinal logistic regression model to quantified invasive species abundance as a function of the same set of variables, i.e., climate, habitat and land cover.
Results/Conclusions Our results show which locations in the region, the south and west in particular, seem prone to successful plant invasions given the combination of climatic, habitat and land cover (a surrogate for human influence) conditions particular to the sites. Maps of potential abundance for the most common invasive plant species, Berberis thumbergii, Celastrus orbiculatus, Euonymus alata, Elaeagnus umbellata, and Rosa multiflora, allowed us to point out the specific conditions that promote successful population growth of these species, thus identifying populations likely to become foci of further spread.
Results show the importance of a multivariate approach, where variable other than climate, in this case habitat and land cover, also play an important role on the spread and success of invasive plant species. These outcomes can now be used by ecologists and natural resources managers of the region on their work for invasive species control. In addition, these models can be extrapolated to other regions and species.
