Long-term ecological data confirm and refine conservation assessment of critically endangered swift parrots

Conservation assessments of threatened species are often limited by scarce data and parameter uncertainty. Predictive models, designed to incorporate this uncertainty, may be the only tool available to inform conservation assessments for data-deficient species, but they are used surprisingly rarely for this purpose. The swift parrot Lathamus discolor is the only critically endangered bird to be listed in Australia based on population viability analysis (PVA). We aimed to evaluate the accuracy of the 2015 conservation assessment, which used sparse information, by incorporating new detailed and long-term data. First, we updated a range of life history parameter estimates, and then we repeated the same PVA as per the original conservation assessment. This process confirmed our earlier finding that swift parrot nests were more likely to survive in places with high mature forest cover. We identify that high forest landscape integrity and abundant hollow-bearing trees best predict nest daily survival rates. Based on the updated PVA, we predict a 92.3% population decline over three generations (11 years). This supported the predictions of the original conservation assessment, and the main benefit of the additional data was improved confidence in projections (the magnitude and direction of the population decline were similar between the original and updated PVAs). Our results demonstrate that meaningful trends can be inferred for species with imperfect information about their life history. Using predictive models like PVAs can help managers identify which life history parameters impact most on demographic trends. This information can guide targeted data collection so that 'draft' models can be later updated to improve certainty around population predictions.

Automated summary

Conservation assessments for threatened species are often constrained by limited data and uncertainty. However, using predictive models that account for this uncertainty can provide valuable insights into population trends and guide conservation efforts.