Background: Fabiola is an Italian quantitative ecologist with years of experience as a field biologist. She started her career at Sapienza University of Rome, where she earned a BS in Biology and a MS in Ecobiology working on population dynamics of small mammals in fragmented, human-modified landscapes (1, 2). After graduating, she kept working on small mammals as a researcher at Fondazione Ethoikos in Tuscany, Italy, this time focusing on how different forest management strategies impact their populations. Forever fascinated by nature’s intricacy, Fabiola soon realized that a deep knowledge of quantitative methods helps address the complex questions often faced by ecologists. To expand her skills, she got a postgraduate fellowship funded by Sapienza to work as a postgraduate associate at NINA, the Norwegian Institute of Nature Research in Trondheim, Norway. There, she extended her focus to methodological development and worked on a framework to estimate home range size of wolverines (Gulo gulo) from records collected through non-invasive genetic sampling. Fabiola’s dual passions for applied ecology and statistics shaped her doctoral dissertation. During her PhD at the University of Minnesota, Fabiola worked on new approaches to estimating activity patterns from camera trap data and explored methods for describing spatial and temporal correlation in detection/nondetection and other classes of binary data. Concurrently, to support the establishment of a Minnesota state-wide camera-trap project to monitor carnivores’ populations, Fabiola collected multiple years of data to assess how several species of carnivores uniquely respond to sampling strategies commonly adopted when studying these species.
Research: Fabiola’s work lies at the intersection of ecology and statistics. Her research interests range from mammal ecology to species conservation and quantitative ecology. She has collected data and worked on many species of mammals, from small rodents to large carnivores, using many different techniques, including live-trapping, telemetry and camera traps. She is a strong advocate for reproducibility and open science, and supports the development of new AI tools to address complex conservation challenges. Fabiola supports inclusive and collaborative science, has participated in Snapshot USA, and is now helping coordinate Snapshot Europe. Most of her recent work focuses on the use of camera traps for management and conservation, and on how best practices and new technologies can provide new insights and facilitate data sharing and collaborations when assessing ecological patterns and trends at large scales.
At the BGC Center: As a Postdoctoral Associate at the BGC Center and Max Planck - Yale Center for Biodiversity Movement and Global Change, Fabiola is using large camera-trap datasets and occupancy models to assess how human activities affect trends in the distribution of mammals and birds throughout their ranges. Camera traps provide fine resolution, replicated information on occurrences of several species within a certain area. Collating data from camera-trap projects spread across large spatial scales might provide insights on which types of human disturbance are driving trends in species distribution and which are the traits common to the species most affected by these human-induced stressors. Fabiola is also supporting the development of automated analytics for Wildlife Insights, a web-platform which promotes and supports the use and sharing of camera-trap and other remote sensor data for species conservation. Along with her collaborators, Fabiola is building a user-friendly web-interface which will help users analyze their data and quickly gain insights on activity patterns, detection rates, occupancy and species richness and other metrics often explored using camera-trap data.
