Modeling Vegetation Mosaics in Sub-Alpine Tasmania Under Various Fire RegimesModeling Earth Systems and Environment
- National Parks -- Australia,
- Ecology -- Simulation methods,
- Applied ecology
AbstractWestern Tasmania, Australia contains some of the highest levels of biological endemism of any temperate region in the world, including vegetation types that are conservation priorities: fire-sensitive rainforest dominated by endemic conifer species in the genus Athrotaxis; and fire-tolerant buttongrass moorlands. Current management focuses on fire suppression, but increasingly there are calls for the use of prescribed fire in flammable vegetation types to manage these ecosystems. The long-term effects of climate and alternative management strategies on the vegetated landscape are unknown. To help identify controls over successional trajectories, we parameterized a spatially explicit landscape-scale model of vegetation and fire (FireBGCv2) for a study area in Cradle Mountain-Lake St Clair National Park in western Tasmania using new data on fine-scale topography, plant communities, and fuels loads. Our parameterized model displays a high level of agreement with previous empirical and modeling studies for the region. The model was experimentally tested for three different levels of ignition suppression (0, 50, and 90 %); simulations ran for 1000 years and were replicated 10 times. The different scenarios yielded distinct fire return intervals, with cascading effects on successional dynamics and vegetation composition. Model results indicate that fire-sensitive endemic conifer rainforest will be restricted to upland refugia that total far less area than its present distribution, even under maximal ignition suppression. Because the distribution of vegetation types was unstable temporally and across stochastic replicates, present distributions may be a legacy of previous climate, Aboriginal fire management, or both.
Citation InformationYospin, G.I., Wood, S.W., Holz, A. et al. Model. Earth Syst. Environ. (2015) 1: 16.