Anthropogenic climate change poses a significant threat to the wellbeing of the planet. Many scientific studies have demonstrated the negative impacts climate change will have on the earths ecosystem functioning and biodiversity, ranging from disruption and alteration to, in the worst case, species extinction. Despite the fact that tropical rainforests have been acknowledged as biodiversity hotspots worldwide much of the work on the impacts of climate change to date has been conducted in temperate areas. This lack of study, coupled with high biodiversity, means more in-depth research in tropical regions is crucial to increase knowledge on how climate change will impact biodiversity globally.
This thesis focuses on a diverse taxa of mammals, echolocating insectivorous bats (order: Chiroptera), and determines current species' distributions within the Australian Wet Tropics World Heritage Area. The research presented within examines environmental factors that might explain these distributions, and combines this knowledge of current distributions with predicted changes in these environmental parameters to model future distribution change. This study begins by determining what species are present in rainforest habitats of the Wet Tropics through field surveys involving echolocation monitoring and trapping. Individual species, and regional and subregional community composition, were identified and analysis was performed to determine what environmental factors influence observed distributions. Species' probability of occurrence was found to be primarily driven by water availability (precipitation) as well as temperature and location within the region ('subregion': see Chapter 1, Figure 1.2b).
This initial research was built upon by supplementing baseline data gathered during field surveys with historical observation records (from museum and biodiversity atlases). Information on species occurrences was then combined with environmental data to produce Species Distribution Models (SDMs) for the region's bat diversity. These models provide a greater resolution of detail about climatically suitable habitat, current distributions, and the climatic variables driving each of the region's 28 bat species than just field surveys alone. Collated, these models provide information on the region's species richness overall. Rainforested areas to the centre of the region, and particularly the Atherton Uplands, were predicted to have the highest species richness while lowland coastal regions were generally predicted to be the least rich. This data was also analysed to refine methods for producing the most effective models possible. Distribution models for each of the 28 species were initially run using four different model parameters based on different levels of species occurrence data (global vs local) and background information (bias corrected vs bias-uncorrected backgrounds). The resulting outputs underwent quantitative and qualitative analysis to determine which of the four methods produced the most accurate output for each species. It was found that SDMs generally performed best using global species occurrence data against background layers that accounted for any sampling bias. This demonstrates that models built using observational data from only the focal region may misrepresent the distribution of a species, thus biasing resulting outputs. The results of this study could help to refine SDMs and provide a more accurate basis for climate modelling in the future.
To conclude, this research used refined modelling techniques and all gathered information (as outlined above) to build accurate and detailed SDMs predicting how species' distributions will alter under various future climate change scenarios. Modelling predicts that environmental conditions will become more suitable for almost half of the study species. However, conditions are predicted to become less favourable for the other half of species, resulting in distribution contractions. Total species movement is predicted to be high with species moving into upland, rainforested areas to the centre of the region and contracting out of lowland coastal areas. Modelling predicts that by 2085 the majority of bat diversity in the region will be concentrated in these upland, rainforested areas.
This research represents the first detailed description of the distributions of all echolocating bat species in the Wet Tropics World Heritage Area and presents the first models of their predicted response to climate change. Overall, this thesis concludes that climate change will impact bat species richness and diversity with almost 50% of species predicted to experience contractions in the amount of climatically suitable habitat available to them. This research adds to the growing body of evidence about the negative impacts of climate change and highlights the need for swift action to reduce emissions if we are to mitigate predicted global biodiversity loss
