PhD Opportunity – Deakin University, supervised by Professor John Arnould
Despite weighing only 500-600 g, with an estimated population size of ca23 million, the short-tailed shearwater (STSW) is Australia’s most numerous bird and the most significant avian marine predator in Australia, consuming over 300,000 tonnes of krill, fish and squid over the annual summer breeding season.
Its nesting distribution is restricted to south-eastern Australia, currently one of the fastest warming oceanic regions in the world. The anticipated oceanographic changes are likely to alter the diversity, distribution and abundance of prey for seabirds in the region with the potential to impact their breeding distributions. The wedge-tailed shearwater (WTSW) has a circumpolar distribution in sub-tropical/temperate regions. It breeds sympatrically with the STSW on islands along the New South Wales coast and allopatrically further north.
Over the last few decades, the abundance of WTSW has been observed to increase in NSW while the STSW has been decreasing in numbers and the northern extent of its distribution is receding. A new colony of WTSW recently established (alongside STSW) at Gabo Island, eastern Victoria, making it now the most southerly known breeding colony for the species (by several hundred km), a potential direct impact of the strengthening East Australia Current.
The presence of this rapidly growing colony provides a unique opportunity to compare the breeding and foraging ecology of both sympatric species in an area where one is expanding. Such information is crucial for understanding the factors which will control the breeding distribution, reproductive success and population trajectories of both species in response to climate change.
The project will involve GPS tracking to determine at-sea movements, accelerometry to assess foraging behaviour and energy expenditure, stable isotope analyses to investigate trophic niches and colony monitoring to assess reproductive success and nesting habitat needs.
The ideal candidate for this PhD project would have extensive field experience, well-developed statistical/numerical skills and writing ability.
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