VULNERABILITY TRAITS · Predicting extinction risk in declining species: The role of behavioral and ecological traits

Understanding and predicting the response of animal populations to anthropogenic activity is a major challenge in biodiversity conservation. Species are not equally affected by habitat loss and degradation. However, our current understanding of what makes some species more vulnerable than others is fragmentary, and we have limited tools to use that information for the management and assessment of imperiled populations. Identifying life history, ecological, and behavioral (LEB) traits associated with vulnerability could significantly improve conservation efforts by prioritizing research and encouraging proactive actions. Similarly, generating population models that explicitly consider these key traits and their interactions will strengthen our ability to assess and manage populations at risk. This study will address both of these needs. First, we will conduct a comprehensive comparative study of the families Felidae, Canidae, and Ursidae to reveal the relationship between widespread LEB traits, demography and vulnerability. These families are an ideal surrogate group to address this question because they are well-studied (with many spatial and temporal replicate studies) and encompass a diversity of vulnerability statuses, threats, and life histories. Secondly, we will identify functional relationships, interactions and trade-offs between key LEB traits and demographic parameters. Finally, we will integrate these functional relationships into LEB-explicit models. Anticipated results will advance conservation theory and practice in several ways. Understanding common vulnerability traits will encourage more effective and proactive management, and could help prioritize research by focusing the initial collection of data on the key traits. Defining functional relationships and generating LEB-explicit models will provide great insight into life history patterns and trait interaction, and improve our ability to predict wildlife responses to anthropogenic activities.