Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

The biomes of Western Australia: A vegetation-based approach using the zonality/ azonality conceptual framework

Macintyre, P.D. and Mucina, L. (2021) The biomes of Western Australia: A vegetation-based approach using the zonality/ azonality conceptual framework. New Zealand Journal of Botany .

Link to Published Version: https://doi.org/10.1080/0028825X.2021.1890154
*Subscription may be required

Abstract

Vegetation patterns of are the result of environmental drivers operating across a range of ecological and evolutionary scale. Those vegetation patterns at global and continental scales underpin the existence of large-scale functional entities called biomes. Traditionally, terrestrial biomes are recognised and distinguished by way of physiognomic traits thought to reflect the action of selective filters such as climate or disturbance (fire, grazing). This approach is well suited to recognising zonal biomes; it fails, however, to account for the role of other drivers such as soil and hydrology, potentially leading to over simplified representations of the biome patterns in ecologically complex regions such as Western Australia. It is, therefore, of vital importance to consider these patterns and processes and recognise the azonal biomes as well. Using a previously published physiognomic map of the vegetation of Western Australia, we adopted a bottom-up approach to translate the vegetation classification categories into a new biome classification of Western Australia that would more accurately account for the zonal and azonal structures recorded across the landscape. Five continental zonal biomes (Australian Eucalyptus Savanna, Australian Hummock Grassland, Mulga Shrubland, Australian Temperate Woodland, Australian Oceanic Temperate Forest) and one relict biome (Australian Vine Thicket) were identified. We further distinguished 34 types of azonal biomes, including three new ones: argillobiome, duplo-pedobiome and metallobiome. Predictive modelling (using Classification and Regression Trees) was used to define the potential extent of zonal biomes, with the model returning an overall accuracy of 90%. This study shows that a bottom-up approach based on vegetation maps can be used as an effective approximation for defining a robust classification of biome patterns. The predicted zonal biomes correspond well with existing traditional biogeographic classifications, yet some residual climatic discordance warrants further study.

Item Type: Journal Article
Murdoch Affiliation(s): Harry Butler Institute
Publisher: Taylor and Francis Ltd.
Copyright: © 2021 Informa UK Limited
URI: http://researchrepository.murdoch.edu.au/id/eprint/60117
Item Control Page Item Control Page