2022 ESA Annual Meeting (August 14 - 19)

PS 49-163 Using threat information to predict bird extinction risk

5:00 PM-6:30 PM
ESA Exhibit Hall
Janaina De Andrade Serrano, McGill University;Andrea Corkal,McGill University;Laura Pollock,McGill University;
Background/Question/Methods

The IUCN Red List is the most comprehensive index of global species extinction risk. However, species assessments are typically based on published data and expert input on factors related to each species' extinction risk. There are also many species for which we don’t have enough data on demographic trends to evaluate risk. Consequently, we still have limited knowledge about how and where threats are most influential on population dynamics. One strategy to address this gap is to identify traits that predict species vulnerability from better known species and project those results to lesser known species. However, predicting extinction risk from traits alone without considering the type of threats to which species are exposed can lead to confounding effects. That is because some traits might either increase or decrease extinction risk depending on the threat. For example, larger vertebrates are most at risk by hunting and smaller vertebrates are at most at risk by habitat loss. In this study, we model extinction risk and probability of species threat for birds within Canada (471 threatened and non-threatened species). We compare models that use the typical approach of modeling extinction risk as a function of traits to models that incorporate threats directly.

Results/Conclusions

We did not find strong relationships between body mass, migration distance and clutch size and overall extinction risk alone. However, we did find that some traits were related to particular threats. We found that harvesting is a driver for the extinction of large bird species. Climate change was more likely to threaten small clutch sized and long distance migrating species. Habitat loss threatens poorly fecund species with low dispersal ability. Our results suggest that adding threats can improve overall model performance in predicting the IUCN Red List extinction risk and help assess extinction risk of less studied species.