Star Trek Science, Listening to Pando. May 12, 2023, Part 2
Star Trek’s Science Advisor Reveals The Real Astrophysics On Screen
Few pop culture properties have lasted quite as long as Star Trek. A dozen Star Trek television shows have aired over the last sixty years—not to mention countless movies, novels, and comic books.
Science concepts have always been integral to the Star Trek franchise: from warp speed travel to dilithium. But how much does the series actually accurately depict?
Ira speaks with astrophysicist Dr. Erin Macdonald, science consultant for Star Trek about the legacy of the franchise, and how accurate the science is within the series.
Listen To The Largest Tree On Earth
For this story, we’re taking a trip to south central Utah and into the Fishlake National Forest to visit the largest tree on earth, an aspen named Pando. The strange thing about Pando is that it doesn’t really look like the world’s biggest tree. It has rolling hills with thousands of tall, lean aspens swaying in the wind.
But Pando is there, hiding in plain sight. All those tree trunks you see aren’t actually individual trees. Technically, they’re branches, and that’s because Pando is one massive tree—sprawling more than 100 acres, with 47,000 branches growing from it.
There is a lot to learn about Pando, and our guests turned to sound to understand the tree better. Together, they created an “acoustic portrait” to hear all the snaps, splinters, and scuttles that happen in and around the tree.
Ira talks with Jeff Rice, a sound artist and co-founder of the Acoustic Atlas at the Montana State University Library, and Lance Oditt, executive director of the non-profit Friends of Pando, which is dedicated to preserving the tree.
Transcripts for each segment will be available the week after the show airs on sciencefriday.com.
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.