School of BioSciences - Theses
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ItemUnderstanding the patterns of distribution and environmental responses in Australian grasshoppers based on historic field survey notebooks( 2022)What constitutes a species’ environment and distribution is of vital importance in ecology. Our understanding of the patterns of biogeographic distribution and their connection to the environmental responses of insects has been limited due to a lack of baseline data. The baseline distribution data for all species of a given group in a region can provide fundamental insights into biogeographic questions about historic patterns of diversity, endemism, and adaptive strategies to variable environments. Grasshoppers are one major group of insects for which a continent-wide perspective on distribution and response to environmental conditions can be obtained. This is because they were extensively surveyed in Australia for 54 years (1936-1989) as part of Commonwealth scientific expeditions for the Australian National Insect Collection. Field notebooks recorded by Dr Key and associates from those surveys can help fill the hole in our knowledge of invertebrate distribution patterns in Australia. In this thesis, I developed a database of historic occurrences of Australian grasshoppers based on those field notebooks. I transcribed and carefully geocoded field notebooks corresponding to surveys conducted in Western Australia (WA) and Tasmania. I collected 8975 geographic coordinates for 506 species having a confirmed or putative taxonomic name, based on our transcription and geolocation for 47 notebooks containing 590 pages (~24%, out of 2486 pages altogether). Of the 506 species identified from the notebook transcription, only 177 species had complete formal taxonomic names. I analyzed the occurrences that were recorded from WA using species distribution models (SDMs) to provide insights on the patterns of grasshopper diversity in Australia as well as their strategies of adaptation in response to variable climatic conditions. Overall, in this thesis I aimed to achieve the following goals: (i) digitize field notebooks and save them in a digital repository; (ii) transcribe and collect geographical coordinates of survey sites following the description of field notebooks; (iii) develop species richness maps of grasshoppers’ historic distribution; (iv) identify biases in the spatial distribution of survey locations; (v) identify similarities and differences in survey results among the lead surveyors; (vi) identify patterns of species composition; (vii) predict the distribution of grasshopper species richness; (viii) identify centers of endemism; (ix) quantify how well grasshopper centers of endemism are covered by the protected area networks; (x) develop ecological hypotheses of how grasshopper species respond to changing environmental conditions. In this thesis, I have fulfilled all the above aims. The database of historic occurrences created in this study can be regarded as robust because surveyors were consistent in survey methods and what they recorded. This study highlights the in-completeness of taxonomic description of Australian grasshoppers, although the vast majority of species have been given provisional names. The generalized dissimilarity modeling suggested at least four distinct grasshopper assemblages are distributed over the north, north-west, arid-interior, and south-west of WA. Grasshopper species richness varied spatially with higher richness present in the north of WA than in southwest based on both field observation and prediction from SDMs. In addition, the fit of SDMs was negatively correlated with the prevalence of each species and with an index of vagility (the ratio of wing length to body length). Observations from this study provide an important baseline perspective on Australian grasshoppers and highlights the need for more research on their present status, morphology, life-history, and phylogeny.
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ItemEvaluating uncertainty when applying the trait-based protocol for climate-change vulnerability in freshwater crayfish( 2018)Climate change has been recognized as one of the greatest threats to the persistence of biodiversity. Several approaches have been used to assess species’ vulnerability to climate change such as correlative niche models, mechanistic models, trait-based models, and combination of these model outputs. The trait-based protocol for climate-change vulnerability assessment (TVA) is increasingly used in a variety of taxa due to its suitability for assessing data-poor species. Yet, TVA has thus far remained unevaluated for potential uncertainties. In TVA, climate change-relevant traits are selected and scored against three dimensions: sensitivity, adaptive capacity, and exposure to climate change. In this thesis, I applied TVA to assess climate-change vulnerability in a data-poor invertebrate taxon (freshwater crayfish; 574 species) and explored the potential sources of uncertainty in TVA. I found that climate-change vulnerable crayfish are distributed globally with high concentrations in the USA and Australia, reflecting global pattern of crayfish richness. Ninety-one species are already identified as vulnerable to climate change in the IUCN Red List. I identified hotspots of species vulnerable to climate change that require additional conservation action. I assessed multiple sources of uncertainty including trait selection, the use of arbitrary thresholds for quantitative traits, and climate model choices. I quantified that in TVA, it is likely that as more trait variables are included in the study, more species are identified as vulnerable to climate change. The use of arbitrary thresholds in TVA was relatively robust to produce species’ vulnerability ranking. However, I found that the number of species identified as vulnerable to climate change varied greatly (79-156) depending on which individual climate model was used. TVAs are an effective tool to understand climate change vulnerabilities of data-poor species, however, assessors applying the protocol should be aware of these uncertainty sources and perform sensitivity analyses to better understand their impact on TVA results.