PARENT SESSION
Oral Session #29: Invasions: Predicting and understanding invasibility. Presiding: K. Kearns.
Tuesday, August 7, 2001. 1:00 PM to 4:45 PM. Madison Ballroom C.
Combining species-habitat approaches to understand exotic plant invasions in the Grand Staircase-Escalante National Monument, Utah USA.
Otsuki, Yuka1, Stohlgren, Thomas2, Guenther, Debra3, Evangelista, Paul3, Villa, Cindy3, 1 2 3
ABSTRACT- Useful generalizations for predicting the risk of exotic invasive species are difficult to develop because majority of studies use data from contingent qualitative observations. We examined 34 exotic species and 142 0.1-ha plots in 14 vegetation types in the Grand Staircase-Escalante National Monument to better understand landscape-scale patterns of invasion. Exotic species were classified into four groups based on invasive patterns (dominant generalist, co-dominant generalist, specialist, and rare) using cluster analysis. Most species were found to be rare while only one was highly invasive and five others were either invasive in specific habitat or widespread in small amounts. Multiple linear regression showed that 52% of the variance in log 10 exotic species richness was explained by vegetation type, and showed positive correlations with soil phosphorus and total non-foliar ground cover. To evaluate how well this general prediction model can detect the invasive patterns of individual species, logistic regression analyses were conducted using the three variables (vegetation type, siol phosphorous, and total non-foliar ground cover) for seven major exotic species. The results suggested that these three variables are important predictors for most exotics especially species such as Poa pratensis whose habitats were in moister sites, explaining between 45-60% of variance in species invasibility, but poor predictors (<5%) for species like Erodium cicutarium which invade drier habitats.
KEY WORDS: species invasive index, predictive model, vegetation gradient, landscape scale invasive patterns