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Species distribution models are widely used to identify potential and high‐quality habitat of endangered species to inform conservation decisions. However, their usefulness is constrained by the amount and quality of biodiversity data and the approaches for dealing with data deficiencies. Presence‐only data, used in presence/background modelling methods, are widely available but are often affected by sampling bias. Presence/absence modelling methods are less affected by biases, but data are less common. We modelled the distribution of a widely distributed, endangered species from Australia – the greater glider – and tested how predictions were influenced by data treatment and modelling framework. We collated available species data and fitted generalized linear models and boosted regression trees using presence/absence data, as well as using an augmented dataset that included additional presences alongside absences inferred from survey data. We also fitted presence/background models, adopting three common strategies for bias correction. We compared model performance quantitatively through evaluation metrics calculated internally and on held out data, and qualitatively by identifying areas of agreement of spatial predictions. We found that presence/background models with bias correction performed better than not corrected, though evaluation metrics did not favour a single strategy. Presence/absence models outperformed presence/background models in comparable metrics and delivered different spatial predictions. Importantly, differences in spatial predictions between models had the potential to substantially alter decisions about where to protect high‐quality habitat. The approach to inferring absences proved useful, as models fitted with these outperformed all other models. Dealing with sampling bias requires additional time and data management strategies, but we found that the time invested allowed improvement of models and more reliable predictions. Our results suggest that ancillary occurrence data and careful data handling can improve both presence/background and presence/absence models. Immunology research holds significant potential for enhanced inclusivity, but persistent challenges stem from limited awareness that improvement is needed in this field. At the 2023 Monash Sensory Science Exhibition, we presented tactile posters, using simple materials, for visually impaired participants to showcase our research on the pathogenesis and immunotherapy of rheumatoid arthritis. [ABSTRACT FROM AUTHOR]

Aim: After environmental disasters, species with large population losses may need urgent protection to prevent extinction and support recovery. Following the 2019–2020 Australian megafires, we estimated population losses and recovery in fire‐affected fauna, to inform conservation status assessments and management. Location: Temperate and subtropical Australia. Time period: 2019–2030 and beyond. Major taxa: Australian terrestrial and freshwater vertebrates; one invertebrate group. Methods: From > 1,050 fire‐affected taxa, we selected 173 whose distributions substantially overlapped the fire extent. We estimated the proportion of each taxon's distribution affected by fires, using fire severity and aquatic impact mapping, and new distribution mapping. Using expert elicitation informed by evidence of responses to previous wildfires, we estimated local population responses to fires of varying severity. We combined the spatial and elicitation data to estimate overall population loss and recovery trajectories, and thus indicate potential eligibility for listing as threatened, or uplisting, under Australian legislation. Results: We estimate that the 2019–2020 Australian megafires caused, or contributed to, population declines that make 70–82 taxa eligible for listing as threatened; and another 21–27 taxa eligible for uplisting. If so‐listed, this represents a 22–26% increase in Australian statutory lists of threatened terrestrial and freshwater vertebrates and spiny crayfish, and uplisting for 8–10% of threatened taxa. Such changes would cause an abrupt worsening of underlying trajectories in vertebrates, as measured by Red List Indices. We predict that 54–88% of 173 assessed taxa will not recover to pre‐fire population size within 10 years/three generations. Main conclusions: We suggest the 2019–2020 Australian megafires have worsened the conservation prospects for many species. Of the 91 taxa recommended for listing/uplisting consideration, 84 are now under formal review through national processes. Improving predictions about taxon vulnerability with empirical data on population responses, reducing the likelihood of future catastrophic events and mitigating their impacts on biodiversity, are critical. [ABSTRACT FROM AUTHOR]