Rising temperatures and altered precipitation regimes due to climate change are likely to affect the competitiveness and abundance of invasive plants, ultimately leading to shifts in invasive plant distribution.  Species distribution models (also known as ecological niche or envelope models) describe suitable climatic conditions for invasion based on the species geographic distribution.  These models are increasingly being used to forecast future shifts in invasion risk as both climate change projections and invasive species distribution data become more widely available.  Here, I constructed distribution models for several prominent invasive species in the western U.S. based on distribution maps collected from county invasive plant experts working for the department of agriculture.  Climatic predictor variables were empirically derived for each species based on variables that created the best model fit.  The potential effects of climate change on invasive plant distribution were tested using sensitivity analysis to rising temperature and altered precipitation within the range of conditions projected for the western U.S. by 10 general circulation models from the IPCC 4^th assessment report.  

Results/Conclusions

Model results show potential for both expansion and contraction of most western invasive species, but the magnitude of these changes is highly dependent on the amount of temperature rise and seasonal changes in precipitation.  Some species are highly sensitive to climate changes, while others are minimally influenced.  This sensitivity can be used to identify species most likely to shift with climate change.  The analysis also highlights important climate variables that might not be identified based on invasive plant physiology alone because they derive from competitive interactions with native species.  These types of sensitivity analyses are needed to support integrated ecological forecasting assessments, as they create hypotheses that can later be tested through experiments, observations, and mechanistic modeling efforts.  Projections from distribution models can also be used to build scenarios of future change, which are needed to develop adaptive management strategies for ecological conservation.