SMART Forests: Linking Emerging Technologies for Biodiversity Research in Changing Environments

The global biodiversity crisis requires innovative solutions. In particular, there is an urgent need to procure real-time results from biodiversity monitoring for assessments and planning. New technologies have resulted in broader-scale surveys and larger data sets than previously imaginable, but there is a need to more quickly and precisely analyze these data. This project will begin assembling a framework for linking advanced technological solutions to improve the efficiency, accuracy, and generalizability of technological applications to remotely detect shifts in wildlife abundance and behavior across a rapidly changing landscape in the Congo Basin. More specifically, we outline the initial steps of a plan to address the global urgency for a more efficient pipeline of information from the deployment of camera traps in biodiversity assessments to the output of results for science, conservation, and education. By leveraging our existing expertise and rich archives of digital data from previous surveys, we aim to establish proof of concept for a more predictive science of animal behavior in wildlife conservation that could revolutionize evidence-based conservation of species and ecosystems at a global scale. While numerous algorithms have been developed that increase the efficiency of camera trap data screening on particular fronts, these have yet to be vertically integrated into a single framework. Our proposed initiative will draw together publicly available digital tools by creating a pipeline to score animal behavior from digital video data at near real-time rates and detect deviations from established baselines across ecosystems and generations. Fully assembling these components would represent a major contribution to conservation science by achieving a self-monitoring system that could predict patterns of wildlife behavior and test hypotheses across intact and anthropogenically altered ecosystems. We will work intentionally to make the each component customizable so that it can be applied to other environments and conservation contexts.

Principal Investigator

Crickette Sanz, WashU (Anthropology)