95th ESA Annual Meeting (August 1 -- 6, 2010)

PS 6-60 - Evaluating multiple extinction risks for the obligate fire seeder Leucopogon setiger under changing fire regimes and climate change

Monday, August 2, 2010
Exhibit Hall A, David L Lawrence Convention Center
Rebecca Swab, University of California, Riverside, CA, Helen M. Regan, Biology, University of California Riverside, Riverside, CA, David Keith, Department of Environment, Climate Change and Water, Hurstville, New South Wales, Australia, Tracey J. Regan, School of BioSciences, The University of Melbourne, Parkville, Australia and Mark Ooi, School of Biological Sciences, University of Wollongong, Wollongong, Australia
Background/Question/Methods

Many species, and in particular plants, are threatened by range shifts given proposed climatic changes.  For plants in fire prone ecosystems, changing fire regimes is also a potential extinction risk.  Evaluating which threat is most influential on species vulnerability is important for biodiversity conservation.   We evaluated the threats of habitat shift due to climate change and changing fire frequency for Leucopogon setiger, an obligate seeding shrub in the Australian heathland.  A spatially explicit stochastic matrix model, incorporating simulation of various fire return intervals, was linked with a dynamic bioclimate envelope model to evaluate relative vulnerability of L. setiger to these dual threats.
Results/Conclusions

Leucopogon setiger was found to be sensitive to fire frequency, with short (app. 5 years) or long (app. 30 years) fire frequencies reducing the expected minimum abundance. Spatial variability, or decoupling of fires across the landscape, reduced the negative impacts of altered fire return interval.  Shifting habitat did not appear to be a threat to Leucopogon setiger in comparison to the threat of changed fire return interval.  It is important to evaluate bioecological factors affecting species or functional types under global climate change, and linking bioclimate and population matrix models is a method of increasing accuracy of species vulnerability predictions, particularly for species with multiple extinction risk.  These models can help to focus management actions, which are necessary to preserve biodiversity under predicted climate change.