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Aim: The world's islands support disproportionate levels of endemic avian biodiversity despite suffering numerous extinctions. While intensive recent research has focused on island bird conservation or extinction, few global syntheses have considered these factors together from the perspective of morphological trait diversity. Here, we provide a global summary of the status and ecology of extant and extinct island birds, the threats they face and the implications of species loss for island functional diversity. Location: Global. Taxon: Birds. Methods: We provide a review of the literature on threatened and extinct island birds, with a particular focus on global studies that have incorporated functional diversity. Alongside this, we analyse IUCN Red List data in relation to distribution, threats and taxonomy. Using null models and functional hypervolumes, in combination with morphological trait data, we assess the functional diversity represented by threatened and extinct island endemic birds. Results and main conclusions: We find that almost half of all island endemic birds extant in 1500 CE are currently either extinct or threatened with extinction, with the majority of threatened extant species having declining population trends. We also found evidence of 66 island endemic subspecies extinctions. The primary threats to extant island endemic birds currently are agriculture, biological resource use, and invasive species. While there is overlap between the hotspots of threatened and extinct island endemics birds, there are some notable differences, including the Philippines and Indonesia, which support a substantial number of threatened species but have no recorded post‐1500 CE bird extinctions. Traits associated with threatened island endemic birds are large body mass, flightlessness, aquatic predator, omnivorous and vertivorous trophic niches, marine habitat affinity, and, paradoxically, higher dispersal ability. Critically, we find that threatened endemics (i) occupy distinct areas of beak morphospace, and (ii) represent substantial unique areas of the overall functional space of island endemics. We caution that the loss of threatened species may have severe effects on the ecological functions birds provide on islands. [ABSTRACT FROM AUTHOR]

Comparative extinction risk analysis—which predicts species extinction risk from correlation with traits or geographical characteristics—has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion‐specific models and compared it with the typical criterion‐blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion‐specific models were better at identifying threatened species compared to a criterion‐blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria‐specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re‐evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long‐standing research‐implementation gap. [ABSTRACT FROM AUTHOR]