Empty Forests and Extinction Filters

Conservationists face a challenge: more than a quarter of the world's mammal species are threatened with extinction. In an ideal world, we would know which species are vulnerable to what threats and how we can most effectively reduce species losses. The challenge is that many species are rare and unstudied, and we lack a clear understanding of what determines their vulnerability. This project seeks to remedy this by using wildlife photos and cutting-edge analyses and theory. Our main goal is to understand and predict vulnerabilities of tropical forest mammals to extinction. To accomplish this goal, the international project team is working on describing occupancy and activity patterns of mammal species across the tropics and exploring how these patterns are affected by different ecological and anthropogenic histories, contexts, and conditions. A key hypothesis to be tested during the project is the so-called extinction filter hypothesis. The idea is that species are more resilient to threats and conditions if they have survived similar threats or conditions in the past. The insights gained from our analyses will eventually be used to identify rules and relationships governing the vulnerability and persistence of tropical biodiversity. The project relies on camera-trap data collected by the Tropical Ecology Assessment and Monitoring (TEAM) Network, the largest standardized tropical forest monitoring system. This database comprises more than 200 mammal species, and over two million photos. During 2023, we have: 1. Expanded our network of collaborators to include researchers studying tropical forests with varying levels of protection. We are now collaborating on several analyses that seek to quantify the impact that protection and, conversely, the impact of anthropogenic disturbance have of mammal communities in tropical forests. 2. PhD student Andrea F. Vallejo Vargas has submitted her PhD thesis and will be defending it in February 2024. Her thesis provides a comprehensive analysis of the diel activity patterns of tropical forest mammals and the factors explaining variation therein. 3. Developed a novel statistical approach for quantifying and categorizing both diel and lunar behavior based on camera trap data. This analysis has resulted in a manuscript soon to be submitted to a scientific journal. 4. Increased the project team’s capacity in advanced Bayesian analysis; PhD student Andrea F. Vallejo Vargas and postdoctoral fellow Simon Schowanek now both use these methods to build custom models and employ them for both simulations and empirical data analysis. 5. Developed a custom model for testing hypotheses about and quantifying spatiotemporal interactions between multiple species based on non-invasive monitoring data. This analysis has resulted in a manuscript soon to be submitted to a scientific journal. 6. Continued expanding models for Bayesian multispecies occupancy analysis, including a new dynamic occupancy model which resulted in the publication of a scientific article and several popular science articles. 7. Published 4 scientific articles describing these results, and 6 articles are under review or in preparation. Our scientific work has been highlighted more than 30 international media outlets, including the The Guardian and Science Daily. 8. Gave 5 presentation at scientific conferences. 9. Results from the project are now included in the curriculum of several courses at NMBU (conservation biology, ecological research, statistical methods). 10. Initiated the Interdisciplinary Conservation Network for bringing together experts from across NMBU and beyond. This has become a popular meeting place where researchers from all disciplines (philosophy, economics, ecology, social sciences, law, etc.) meet and exchange ideas about national and international conservation topics. 11. Participated in the coordination of the Tropical Forest Arena, an open arena for information exchange and debates in Norway on issues related to tropical forests. 12. Continuously updated the project website, including project blogs.

Conservationists face a challenge: more than a quarter of the world's mammal species are 'threatened with extinction' (see http://www.iucnredlist.org/). In an ideal world, we would know which species are vulnerable to what threats and how we can most effectively reduce species losses. The challenge is that many species are rare and unstudied, and we lack a clear understanding of what determines their vulnerability. We address this challenge by making use of a unique opportunity. This opportunity exists in the form of over 3.4 million photographs recorded by automatic cameras ('camera traps'). These images were recorded in forests across the tropics and are the result of an immense systematic multi-year effort. The resulting data--comprising 244 mammal species, most of which are elusive and poorly known--along with cutting-edge analyses and theory, will clarify what makes species vulnerable. Using novel analytical approaches, we will explore the pattern of local species extinctions and re-colonizations, as well as where and when animals are active. This will permit a systematic characterization of animal presence and activity patterns across forests and continents that has never been previously achieved. How the species respond to local conditions and threats will be examined and the best means to predict these outcomes determined. One key proposal--the extinction filter hypothesis--is that history will help. Simply put, the idea is that species are more resilient to threats and conditions if they have survived similar threats and conditions in the past. We will test this, along with other ideas, to develop better guidelines for predicting which species are vulnerable to which threats under which circumstances. The project draws on not only a vast network of data but also of expertise. We foresee ground-breaking improvement in understanding and predicting species vulnerabilities, advancing both scientific knowledge and conservation practice.