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James Cook University (2011)

Assessing climate change vulnerability : novel methods for understanding potential impacts on Australian tropical savanna birds

Reside, April Elizabeth

Titre : Assessing climate change vulnerability : novel methods for understanding potential impacts on Australian tropical savanna birds

Auteur : Reside, April Elizabeth

Université de soutenance : James Cook University

Grade : Doctor of Philosophy (PhD) 2011

Résumé partiel
The current global biodiversity decline is predicted to be amplified by escalating anthropogenic change. Climate change stands as one of the major threats to biodiversity, and evidence for changing climate such as rising temperatures and altered precipitation have been well-documented. These changes have led to changes in species distributions, assemblages and interactions. The abilities of species to withstand or adapt to climate change are compromised by the synergies between climate change and the other drivers of decline, particularly habitat loss through land modification. The level of threat to biodiversity, coupled with large gaps in the scientific knowledge of many aspects of global biota particularly in the southern hemisphere, necessitates large-scale vulnerability assessments. These vulnerability assessments can be used to focus finite conservation resources to maximise conservation gain. Tropical northern Australia houses a large proportion of Australi’s biodiversity, however many species in northern Australia are under threat from climate change, land modification and introduced species. Most of northern Australia is tropical savanna, a biome that covers nearly one-quarter of mainland Australia. Australian Tropical Savannas (ATS) have been substantially less modified than the landscapes of southern Australia, and are consequently considered to be largely intact. However, alarming population declines have been recorded for mammals and granivorous birds that occur within the ATS. Despite the extent and species richness of the ATS, and the need for further conservation attention, no assessments of the vulnerability of ATS fauna to climate change have been conducted to date. This thesis addresses the need for further understanding of the vulnerability to climate change of birds of the ATS, in two stages. I begin by improving methods for understanding the distributions of ATS birds, firstly by testing whether training distribution models of ATS birds on short-term weather variables better explains distributions when compared with standard long-term climate models (Chapter 2 ; Reside et al., 2010). Next, I test whether the inclusion of coarse-resolution historic species data decreases the performance of models that are otherwise composed of recent, high resolution species data (Chapter 3 ; Reside et al., 2011ba). The second stage of this thesis predicts the impact of major threats to ATS birds : increasing fire frequency (Chapter 4 ; Reside et al., 2011ab) and climate change (Chapter 5 ; Reside et al., In Review), by modelling the response of species distributions to predicted change. Finally, I use the predictions of species sensitivity to changes in fire regimes, the predictions of distribution change due to climate change, and information on their life history and ecology to generate an overall vulnerability assessment (Chapter 6 ; Reside et al., In prep). Species distribution modelling (SDM) is a frequently-used tool for estimating species’ ranges, and predicting how species will respond to future change. However, the SDM process needs to be scrutinised for relevance to the species and system being modelled and the question being addressed. This thesis examines two issues concerning SDM of ATS birds. Firstly, whether the standard method of using long-term (c. 30 year) climate data averages adequately explains the dynamic ranges of ATS birds. ATS birds are highly mobile, with many species tracking resource availability throughout the landscape. Many species have large distributions, and use either nomadic or migratory movements to respond to changes across their range. I found that SDM was improved for ATS birds by training the models on the climatic variables averaged over a short time frame (three, six and 12 months), when compared with models trained on climatic variables averaged over 30 years.


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