AI for Ecology, Biodiversity, and Conservation: Computer Vision, Remote Sensing and Citizen Science | Tanya Berger-Wolf
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Show Notes
How can AI help close critical data gaps in biodiversity monitoring and turn images and sensor data into actionable conservation decisions? In this episode Tanya Berger-Wolf, a computational ecologist, director of TDAI@OSU, and co-founder of the Wildbook project (Wild Me), walks through practical applications of AI for ecology, biodiversity monitoring, and conservation.
We cover core techniques—computer vision, machine learning, and remote sensing—and their use in image-based monitoring with camera traps, drones, and species identification. Tanya explains individual identification and longitudinal tracking, habitat mapping and change detection, and the data challenges of labeling, class imbalance, and sparse observations. The conversation addresses integration of heterogeneous datasets, model robustness (domain shift and transfer learning), and ethical considerations including Indigenous knowledge and equity. You’ll also hear about scalable platforms like Wildbook, citizen science workflows for crowdsourcing and quality control, policy relevance, open data and FAIR principles, edge deployment in the field, and building sustainable monitoring programs.
Listen to gain concrete insights on tools, pitfalls, and next steps for applying AI to conservation—what works now, what remains hard, and resources to explore further.
Resources Mentioned
Tools, books, papers, and other resources mentioned in this episode
- service Wildbook Platform organizing wildlife photo ID data by individual animal
- company Wild Me Nonprofit building AI solutions for conservation behind Wildbook
- dataset IUCN Red List Official biodiversity tracker; many species data deficient
- company Imageomics Institute NSF-funded institute extracting biological traits from images
- company AI and Biodiversity Change (ABC) Global Center New center studying climate change impact on biodiversity
- tool scikit-learn Off-the-shelf models host used in ecology research
- company NASA US agency collecting abundant remote sensing climate data
- company NOAA US agency whose whale data feeds the Wildbook catalog
- person Dan Rubenstein Princeton behavioral ecologist whose zebra studies sparked photo ID work
- person Chuck Stewart Computer vision researcher who improved animal photo identification
- person Mark Hauber Ornithologist collaborating on machine learning for bird eggs
- tool BearID Facial identification project for bears, being incorporated into Wildbook
- company Kenya Wildlife Service Government partner using Wildbook and co-running Grevy's zebra census
- company African Wildlife Foundation Conservation organization using the Wildbook platform
- community Great Grevy's Rally Citizen-science event enabling first full species census
- other GPAI Report on AI and Biodiversity Recent report outlining challenges and opportunities for AI
- other Endangered Species Act US law requiring impact assessments on endangered species
This list is generated from the episode transcript with AI and may contain inaccuracies. If you notice something wrong, let us know.
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