Eamus, Derek, Huete, Alfredo, Cleverly, James, Nolan, Rachael H., Ma, Xuanlong, Tarin, Tonantzin, and Santini, Nadia S. (2016) Mulga, a major tropical dry open forest of Australia: recent insights to carbon and water fluxes. Environmental Research Letters, 11 (12). 125011.

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Abstract

Mulga, comprised of a complex of closely related Acacia spp., grades from a low open forest to tall shrublands in tropical and sub-tropical arid and semi-arid regions of Australia and experiences warm-to-hot annual temperatures and a pronounced dry season. This short synthesis of current knowledge briefly outlines the causes of the extreme variability in rainfall characteristic of much of central Australia, and then discusses the patterns and drivers of variability in carbon and water fluxes of a central Australian low open Mulga forest. Variation in phenology and the impact of differences in the amount and timing of precipitation on vegetation function are then discussed. We use field observations, with particular emphasis on eddy covariance data, coupled with modelling and remote sensing products to interpret inter-seasonal and inter-annual patterns in the behaviour of this ecosystem. We show that Mulga can vary between periods of near carbon neutrality to periods of being a significant sink or source for carbon, depending on both the amount and timing of rainfall. Further, we demonstrate that Mulga contributed significantly to the 2011 global land sink anomaly, a result ascribed to the exceptional rainfall of 2010/2011. Finally, we compare and contrast the hydraulic traits of three tree species growing close to the Mulga and show how each species uses different combinations of trait strategies (for example, sapwood density, xylem vessel implosion resistance, phenological guild, access to groundwater and Huber value) to co-exist in this semi-arid environment. Understanding the inter-annual variability in functional behaviour of this important arid-zone biome and mechanisms underlying species co-existence will increase our ability to predict trajectories of carbon and water balances for future changing climates.

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