Utah Dino Bones, Salt Lake Migrations, Tree Canopies. Sept. 21, 2018, Part 1
If you stood in southeastern Utah over 200 million years ago, you’d be overlooking the ocean. The landlocked state wasn’t quite the same landscape of scarlet plateaus and canyons you might see today, but a coastal desert where sand dunes butted up right against the sea. And it was home to some of the earliest dinosaurs. In this region of Utah, today known as Indian Creek in Bears Ears National Monument, the remains of dinosaur relatives, known as protodinosaurs or “dinosaur aunts and uncles,” are buried in the Earth. Their bones tell the stories about the dawn of dinosaurs, prehistoric Utah, and a much warmer Earth.
In the northern reaches of Utah’s Great Salt Lake sits Gunnison Island, a narrow strip of land just a mile long and half a mile wide. Despite its small size, the island hosts the world’s second largest white pelican rookery, with an average of 20,000 birds and 6,000 nests. Biologist Jaimi Butler of Westminster College’s Great Salt Lake Institute calls the birds the “polar bears” of Great Salt Lake—because as lake waters drop, the birds’ island refuge is now threatened by humans, coyotes, and other predators. Butler and her team have installed cameras on the island, and citizen scientists can now use these “PELIcam” images to help Butler and her colleagues catalog the white pelican population on the island—and the appearance of predators, too.
Forest ecologist Nalini Nadkarni pioneered the exploration of tree canopies—the “new frontiers” of the forest, using hot air balloons, rock climbing gear, and cranes. There, high in the trees, she found soil coating the branches, much like the soil on the forest floor—and unique adaptations, like the water-gathering abilities of spiky bromeliads. In this segment, recorded live at the Eccles Theater in Salt Lake City, Nadkarni takes Ira on a tour of the forest canopy, talks about how fashion can be a tool for science communication, and describes her work communicating science to underserved populations, like inmates in prisons around the nation—from minimum security to Supermax.
Subscribe to this podcast. Follow our show on Instagram, TikTok, Facebook, and Bluesky @scifri and sign up for our newsletters. Got a science question that’s keeping you up at night? Call us: 877-472-4374
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.