School of BioSciences - Theses

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    Evaluating uncertainty when applying the trait-based protocol for climate-change vulnerability in freshwater crayfish
    Hossain, Md Anwar ( 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.