Summary1. Expert knowledge is used routinely to inform listing decisions under the IUCN Red List criteria. Differences in opinion arise between experts in the presence of epistemic uncertainty, as a result of different interpretations of incomplete information and differences in individual beliefs, values and experiences. Structured expert elicitation aims to anticipate and account for such differences to increase the accuracy of final estimates. 2. A diverse panel of 16 experts independently evaluated up to 125 parameters per taxon to assess the IUCN Red List category of extinction risk for nine Australian bird taxa. Each panellist was provided with the same baseline data. Additional judgments and advice were sought from taxon specialists outside the panel. One question set elicited lowest and highest plausible estimates, best estimates and probabilities that the true values were contained within the upper and lower bounds. A second question set elicited yes ⁄ no answers and a degree of credibility in the answer provided. 3. Once initial estimates were obtained, all panellists were shown each others' values. They discussed differences and reassessed their original values. Most communication was carried out by email. 4. The process took nearly 6 months overall to complete, and required an average of 1 h and up to 13 h per taxon for a panellist to complete the initial assessment. 5. Panellists were mostly in agreement with one another about IUCN categorisations for each taxon. Where they differed, there was some evidence of convergence in the second round of assessments, although there was persistent non-overlap for about 2% of estimates. The method exposed evidence of common subjective biases including overconfidence, anchoring to available data, definitional ambiguity and the conceptual difficulty of estimating percentages rather than natural numbers. 6. This study demonstrates the value of structured elicitation techniques to identify and to reduce potential sources of bias and error among experts. The formal nature of the process meant that the consensus position reached carried greater weight in subsequent deliberations on status. The structured process is worthwhile for high profile or contentious taxa, but may be too time intensive for less divisive cases.

In the development of a species distribution model based on regression techniques such as generalized linear or additive modelling (GLM/GAM), a basic assumption is that records of species presence and absence are real. However, a common concern in many studies examining species distributions is that absences cannot be inferred with certainty. This is particularly the case where the species is rare, difficult to detect and/or does not occupy all available habitat considered suitable. The western ground parrot (Pezoporus wallicus flaviventris) of southern Western Australia, Australia, is a case in point, as not only is it rare and difficult to detect, but it is also unlikely to occupy all available suitable habitat. A recent survey of ground parrots provided the opportunity to develop a predictive distribution model. As the data were susceptible to false absences, these were replaced with randomly selected ‘pseudo’ absences and modelled using GLM. As a comparison, presence‐only information was modelled using a relatively new approach, MAXENT, a machine‐learning technique that has been shown to perform comparatively well. The predictive performance of both models, as assessed by the receiver operating characteristic plot (ROC) was high (AUC > 0.8), with MAXENT performing only marginally better than the GLM. These approaches both indicated that the ground parrot prefers areas relatively high in altitude, distant from rivers, gently sloping to level habitat, with an intermediate cover of vegetation and where there is a mosaic of vegetation ages. In this case, the use of presence‐only information resulted in the identification of important environmental attributes defining the occurrence of the ground parrot, but additional factors that account for the inability of the bird to occupy all suitable habitat should be a component of model refinement.

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;

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Flowering phenology and seed set characteristics of five species o/Banksia were .studied in relation to the nectarivorous birds which feed at their inflorescences. Within the Banksia woodland at the study site near Perth, the flowering sea.sons of the Banksia species were sequential and only slightly overlapping, providing a year-round nectar source. Although honeyeaters visited alt five species, seed set was very low in each case. Caging experiments indicated that, in B. atlenuata at least, alternative pollinators may plav a more important role in pollination than do nectar-feeding birds. It is suggested that non-avian pollinators, predatory insects, and characteristics of the breeding system may also have been important in the evolution of the observed flowering phenology and patterns of seed set.