Population size estimates are given both on the "Summary" tab and the "Data table and detailed info" tab of the factsheet for each species at http://datazone.birdlife.org/species/search. They are also available through the IUCN Red List API at https://apiv3. iucnredlist.org/ and the IUCN Red List Advanced Search at https://www.iucnredlist.org/search.

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Compilation and scrutiny of all accessible specimen and observer records of the long-tailed woodnymph Thalurania watertonii, a hummingbird currently listed as ‘Endangered’ on the IUCN Red List, eliminates Guyana, Pará, Maranhão, Ceará, Rio Grande do Norte and Paraíba from its range and sets aside both Sergipe and Bahia as unproven, leaving 29 certain localities, 15 in Pernambuco and 14 in Alagoas, north-east Brazil, all of them in Atlantic Forest and not Cerrado or Caatinga. Among them are records from ten IUCN category I‒IV protected areas (seven in Pernambuco, two in Alagoas and one shared between the two). Remote sensing analysis shows all confirmed localities to contain a total of c.292 km2 of forest (with an extent of occurrence (EOO) and area of occupancy (AOO) of 16,090 and 910 km2, respectively), thus indicating the species qualifies for ‘Vulnerable’ (rather than ‘Endangered’) on the IUCN Red List. However, within the species’ range, we find a maximum total of 2568 km2 of forest, unexplored patches of which may host important populations of this and other threatened species endemic to the ‘Pernambuco Centre of Endemism’. Range-wide research is urgently needed into the condition of these sites and the status of the species within them as well as the general densities, ecology and true distribution of the species, which is now known to breed from October to March, to feed on at least 25 plant species and possibly to need shallow clean-water streams, in order to identify the key measures needed to ensure its survival.

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 these models only predict a species′ Red List category, without indicating which Red List criteria may be triggered by which such approaches cannot easily be used in 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 predicting threatened species compared to a criterion–blind model (higher sensitivity), but less good at predicting not threatened species (lower specificity). As expected, different covariates were important for predicting threat status under different criteria, for example change in annual temperature was important to predict criteria related to population trends, while clutch size 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 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.

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