Geological Sciences

How deep is that snow? Machine learning helps us know

Rachel Sauer — Thu, 10 Jul 2025 13:30:00 +0000

How deep is that snow? Machine learning helps us know Rachel Sauer Thu, 07/10/2025 - 07:30

Blake Puscher

CU Boulder researchers apply machine learning to snow hydrology in Colorado mountain drainage basins, finding a new way to accurately predict the availability of water

Determining how much water is contained as snow in mountain drainage basins is very important for water management, because measuring it is a necessary part of predicting the availability of water—especially in places that rely on snowmelt for their water supply, like Colorado and other western states.

Snow water equivalent is the amount of water in a mass of snow or snowpack. The depth of this water is a fraction of the snow depth, and this fraction is obtained by multiplying the depth by the snow density, which is expressed as a percentage of the density of water. If there are 10 inches of snow with a density of 10%, the snow water equivalent is 1 inch.

A persistent challenge is that snow water content is calculated from both snow depth and snow density, yet it remains unfeasible to directly measure snow density over a large area. Traditionally, this issue has been addressed with remote sensing, which allows for consistent and relatively large-scale measurements. However, remote sensing methods have their own limitations, which has prompted the search for an alternative in machine-learning technology.

CU Boulder researchers Jordan Herbert (left), a PhD candidate, and Eric Small, a professor of geological sciences, developed a model that can estimate the snow density at times when and in places where it has not been observed or sensed.

In their study on the subject, �Թ�� of Colorado Boulder Ph.D. candidate Jordan Herbert and Professor Eric Small of the Department of Geological Sciences developed a model that can estimate the snow density at times when and in places where it has not been observed or sensed. This model is split into different scenarios, each trained on a different subset of the data, and while performance varied, all scenarios were more accurate than extrapolation from remote sensing methods, according to Herbert and Small.

Model performance analyses also demonstrated that information from Airborne light detection and ranging (LIDAR) can be transferred to different times and places within the region it was collected.

LIDAR and SNOTEL data

LIDAR surveys are an important tool in snow hydrology, as they provide detailed information about snow properties, specifically through their detection of snow depth.

“You fly the plane twice,” Small says, “once when there’s no snow, once when there is snow. The laser reflects off the surface, and if you know where the plane is and the distance to the surface, then you know the height of the snow relative to the ground surface.” This is called differential LIDAR altimetry.

While LIDAR is very useful in snow hydrology, it does have some limitations. The first is that it only measures snow depth, but snow density (either measured or modeled) is also needed to determine snow water equivalent. This isn’t a unique limitation, however, because snow density cannot be surveyed in the same way as snow depth.

“Measuring snow density in the field reveals just how variable the snowpack is,” Herbert explains. “Depending on if you dig a snow pit under a tree or on a north versus south facing aspect, you can get a completely different answer.”

This is a major limitation of on-site observations. Density also varies with depth, and remote sensing signals will be affected by the amount of liquid water content in snow, which makes measuring snow density remotely or over a broad scale impossible for the foreseeable future.

The second and more easily addressed issue with LIDAR surveys is the logistical issues associated with necessary plane flights.

“You can’t fly a plane all the time,” Small says. “It’s too expensive, and we don’t have enough planes to fly everywhere.” Planes also cannot be flown when the weather is bad, and surveys only provide a snapshot of snow depth, which can change rapidly as snow falls or melts.

“Measuring snow density in the field reveals just how variable the snowpack is. Depending on if you dig a snow pit under a tree or on a north versus south facing aspect, you can get a completely different answer,” says CU Boulder researcher Jordan Herbert. (Photo: Pixabay)

These limitations can be worked around by using the LIDAR data to train computer models. “Based on that,” Small says, “you can use the LIDAR information to make predictions in the absence of LIDAR at another time or date or location. So, you’re leveraging the scientific information from LIDAR to improve your knowledge generally.”

Snow telemetry (SNOTEL) is an automated system of snow and climate sensors run by the National Resource Conservation Service, which is part of the U.S. Department of Agriculture. There are about a thousand SNOTEL sites across the western United States—small wilderness areas filled with sensing equipment that measures precipitation, snow mass and snow depth.

“All snow hydrology is based on data from these stations,” Small says. “The problem is that they only cover a small area. If you take all the SNOTEL stations in the western U.S. and put them next to each other, they’d be about the size of a football field, so they’re vastly under sampling. That’s why people want to use LIDAR to fill in all the spaces around them.”

The random forest model

Linear regression makes quantitative predictions based on one or more variables, but it becomes difficult to perform when many of these variables interact with each other in complex ways. In this case, some examples are elevation, solar radiation, slope, tree cover and so on. The difficulty of working with all these variables can be minimized by a modeling tool called a regression tree.

“A binary regression tree splits your sample into two groups, and it splits that sample to figure out which variable has the most effect on the thing you're trying to predict,” Small explains. The branching structure created by these splits gives the model its name and is designed to minimize errors. Each branching point is a condition like true/false or yes/no, the answer to which determines the path taken.

Regression trees are useful in that they fit the data better than multiple linear regression models, which are the other option when it comes to using linear regression when there are many variables involved. The better a model fits the observed data, the better it will be at predicting data that have not been observed, Small says.

However, regression trees have their own limitations.

“The downside of a binary regression tree is that it only gives you categorized values,” Small says. “For example, snow depth could be 70 centimeters, 92 centimeters or 123 centimeters. You end up with a map that just has these particular values.” This issue can be solved by combining multiple regression trees into a random forest model.

“What a random forest does,” Small explains, “is take a bunch of these binary regression trees and samples them randomly to give you continuous distributions of the variable that you care about. So instead of it being in these categories, it's more like how we think about snow depth.”

“All snow hydrology is based on data from (SNOTEL) stations. The problem is that they only cover a small area. If you take all the SNOTEL stations in the western U.S. and put them next to each other, they’d be about the size of a football field, so they’re vastly under sampling," says CU Boulder Professor Eric Small. (Photo: Ruvin Miksanskiy/Pexels)

Machine learning

While using binary regression trees allows the predictive model discussed in this study to fit the data better, there are other things to consider, Small says. “In machine learning and other statistics, there’s this trade-off between how well a model can fit the information you give it and how generalizable it is. If I keep adding training data, training the model and tuning the parameters, I can have it fit the data pretty well, but then it becomes fixated on those very specific data, and it’s not going to make good predictions elsewhere.”

This is called “overfitting,” and it can be described simply as the model becoming too used to patterns in the data it was trained on. In anticipating these patterns, the model will make incorrect predictions that would have been right in the same place or under the same circumstances as the training data were collected, but aren’t otherwise.

This explains the different performance of the three different versions of the model: the site-specific model, the regional model and the site-specific and regional (SS+Reg) model. The site-specific model makes predictions about a given basin using LIDAR data from the same basin that was collected at other dates, whereas the regional model makes predictions about a basin using data from other basins and at other dates. The SS+Reg model was trained using all available data.

The SS+Reg model was the most accurate, but all models were generally accurate, both compared to models from prior studies and remote sensing methods. Because models of the sort used in this study output on the 50-meter scale, this scale was used to compare this study’s models to existing ones, and the former were more accurate. The models’ outputs were at a scale of 50 meters, but these were upscaled to 1- and 4-kilometer scales as well.

The 1- and 4-kilometer scales are more typically used in water management applications, and all three models became more accurate when applied to these scales, outperforming SNOTEL. This means that the models were more accurate than extrapolation from observation data. The success of both the SS+Reg and regional models indicates that information gained from LIDAR is transferable to different times and locations within the Rocky Mountain Region.

Besides fitting the data well and being adaptable to different scales between the three model scenarios, this approach is also beneficial because it does not rely on modeling physical processes (like snow formation, accumulation and melt) or on uncertain weather data. This makes it so that, once a model is trained, it doesn’t take long to make predictions. “The big gain is that it's much more computationally efficient and it just takes a fraction of the time,” Small says. “It's about 100 times faster.”

Herbert says “machine learning has been a huge benefit to my research, with the results to back it up. It’s freed up my time in the winter to put skis on and dig more snow pits to get the density data we desperately need.”

“For whatever reason, all our physically based models and our knowledge of science just gets in our way of making predictions,” Small explains, “because we've tried to boil it down to these simple equations, but it's not simple.”

"Machine learning has been a huge benefit to my research, with the results to back it up. It’s freed up my time in the winter to put skis on and dig more snow pits to get the density data we desperately need."

Expanding to other regions

The primary limitation of the snow density-measuring framework that the researchers created for this study was its reliance on on-site and LIDAR data for snow depth measurements. Small says that this could be addressed by bringing in other data sets, which would provide a more independent test of success than models’ ability to predict snow density in regions they were not trained on.

One of these data sets, the fractional snow-covered area (how much of the ground is covered by snow), could be measured using LIDAR equipment mounted to a satellite rather than relying on airplanes. While LIDAR has been used with satellite technology, this doesn’t address the limitations of plane-mounted LIDAR, because as Small says, “the (satellite) overpass interval is very slow. It’s about 90 days before it comes back to the place you’re looking at. So, you get a snapshot very infrequently, but it’s everywhere on the planet.”

The next step of developing this kind of model is to apply it to other regions, and it remains to be seen how easily that translation can be made, Herbert says.

“We’ve just begun running the model in California to see if the model works in regions with different climates,” he says. “We want to see how transferable data from one region is to another, and California is an ideal test site since it has more LIDAR than anywhere else in the world.”

The presence of LIDAR is important because these data were the most useful when it came to statistical model validation, or making sure that the models were accurate and reliable, compared to data limited by the small-area reporting of SNOTEL and the variability of on-the-ground snow density measurements. Without data to judge models’ predictions against, it is impossible to determine how well they do, because the actual snow depth is unknown.

Also, because LIDAR isn’t available everywhere, it is important to continue developing other methods of validation, the researchers say. Small says reducing reliance on LIDAR will help the innovative modeling framework apply to many parts of the country.

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CU Boulder researchers apply machine learning to snow hydrology in Colorado mountain drainage basins, finding a new way to accurately predict the availability of water.

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Life endured inside the snowball

Rachel Sauer — Wed, 13 Nov 2024 18:31:15 +0000

Life endured inside the snowball Rachel Sauer Wed, 11/13/2024 - 11:31

Liam Courtney-Davies , Rebecca Flowers and Christine Siddoway

Evidence from Snowball Earth found in ancient rocks on Colorado’s Pikes Peak—it’s a missing link

Around 700 million years ago, the Earth cooled so much that scientists believe massive ice sheets encased the entire planet like a giant snowball. This global deep freeze, known as Snowball Earth, endured for tens of millions of years.

Yet, miraculously, early life not only held on, but thrived. When the ice melted and the ground thawed, complex multicellular life emerged, eventually leading to life-forms we recognize today.

CU Boulder researchers Liam Courtney-Davies (left) and Rebecca Flowers (right), along with Colorado College colleague Christine Siddoway, have found that life endured during Snowball Earth.

The Snowball Earth hypothesis has been largely based on evidence from sedimentary rocks exposed in areas that once were along coastlines and shallow seas, as well as climate modeling. Physical evidence that ice sheets covered the interior of continents in warm equatorial regions had eluded scientists – until now.

In new research published in the Proceedings of the National Academy of Sciences, our team of geologists describes the missing link, found in an unusual pebbly sandstone encapsulated within the granite that forms Colorado’s Pikes Peak.

Solving a Snowball Earth mystery on a mountain

Pikes Peak, originally named Tavá Kaa-vi by the Ute people, lends its ancestral name, Tava, to these notable rocks. They are composed of solidified sand injectites, which formed in a similar manner to a medical injection when sand-rich fluid was forced into underlying rock.

A possible explanation for what created these enigmatic sandstones is the immense pressure of an overlying Snowball Earth ice sheet forcing sediment mixed with meltwater into weakened rock below.

An obstacle for testing this idea, however, has been the lack of an age for the rocks to reveal when the right geological circumstances existed for sand injection.

We found a way to solve that mystery, using veins of iron found alongside the Tava injectites, near Pikes Peak and elsewhere in Colorado.

Earth was covered in ice during the Cryogenian Period, but life on the planet survived. (Illustration: NASA)

Iron minerals contain very low amounts of naturally occurring radioactive elements, including uranium, which slowly decays to the element lead at a known rate. Recent advancements in laser-based radiometric dating allowed us to measure the ratio of uranium to lead isotopes in the iron oxide mineral hematite to reveal how long ago the individual crystals formed.

The iron veins appear to have formed both before and after the sand was injected into the Colorado bedrock: We found veins of hematite and quartz that both cut through Tava dikes and were crosscut by Tava dikes. That allowed us to figure out an age bracket for the sand injectites, which must have formed between 690 million and 660 million years ago.

So, what happened?

The time frame means these sandstones formed during the Cryogenian Period, from 720 million to 635 million years ago. The name is derived from “cold birth” in ancient Greek and is synonymous with climate upheaval and disruption of life on our planet – including Snowball Earth.

While the triggers for the extreme cold at that time are debated, prevailing theories involve changes in tectonic plate activity, including the release of particles into the atmosphere that reflected sunlight away from Earth. Eventually, a buildup of carbon dioxide from volcanic outgassing may have warmed the planet again.

The Tava found on Pikes Peak would have formed close to the equator within the heart of an ancient continent named Laurentia, which gradually over time and long tectonic cycles moved into its current northerly position in North America today.

Dark red to purple bands of Tava sandstone dissect pink and white granite. (Photo: Liam Courtney-Davies)

The origin of Tava rocks has been debated for over 125 years, but the new technology allowed us to conclusively link them to the Cryogenian Snowball Earth period for the first time.

The scenario we envision for how the sand injection happened looks something like this:

A giant ice sheet with areas of geothermal heating at its base produced meltwater, which mixed with quartz-rich sediment below. The weight of the ice sheet created immense pressures that forced this sandy fluid into bedrock that had already been weakened over millions of years. Similar to fracking for natural gas or oil today, the pressure cracked the rocks and pushed the sandy meltwater in, eventually creating the injectites we see today.

Clues to another geologic puzzle

Not only do the new findings further cement the global Snowball Earth hypothesis, but the presence of Tava injectites within weak, fractured rocks once overridden by ice sheets provides clues about other geologic phenomena.

Time gaps in the rock record created through erosion and referred to as unconformities can be seen today across the United States, most famously at the Grand Canyon, where in places, over a billion years of time is missing. Unconformities occur when a sustained period of erosion removes and prevents newer layers of rock from forming, leaving an unconformable contact.

Our results support that a Great Unconformity near Pikes Peak must have been formed prior to Cryogenian Snowball Earth. That’s at odds with hypotheses that attribute the formation of the Great Unconformity to large-scale erosion by Snowball Earth ice sheets themselves.

We hope the secrets of these elusive Cryogenian rocks in Colorado will lead to the discovery of further terrestrial records of Snowball Earth. Such findings can help develop a clearer picture of our planet during climate extremes and the processes that led to the habitable planet we live on today.

Liam Courtney-Davies is a postdoctoral associate in the Department of Geological Sciences at the �Թ�� of Colorado Boulder; Rebecca Flowers is a CU Boulder professor of geological sciences. Christine Siddoway is a professor of geology at Colorado College.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Evidence from Snowball Earth found in ancient rocks on Colorado’s Pikes Peak—it’s a missing link.

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Why did a frozen Earth coincide with an evolutionary spurt?

Anonymous — Thu, 08 Aug 2024 17:39:03 +0000

Why did a frozen Earth coincide with an evolutionary spurt? Anonymous (not verified) Thu, 08/08/2024 - 11:39

Clint Talbott

CU Boulder geologists Lizzy Trower and Carl Simpson win $1 million in support from W.M. Keck Foundation to try to solve an evolutionary puzzle and to extend Earth’s temperature record by 2 billion years

What happened during the “Snowball Earth” period is perplexing: Just as the planet endured about 100 million years of deep freeze, with a thick layer of ice covering most of Earth and with low levels of atmospheric oxygen, forms of multicellular life emerged.

Lizzy Trower (top) and Carl Simpson. Trower image courtesy of Lizzy Trower; Simpson photo by CU photographer Glenn Asakawa. At the top of the page: A screen capture from a video of algae clumping together in Simpson's lab. Video by Andrea Halling.

Why? The prevailing scientific view is that such frigid temperatures would slow rather than speed evolution. But fossil records from 720 to 635 million years ago show an evolutionary spurt preceding the development of animals. Two �Թ�� of Colorado Boulder scientists aim to help solve this puzzle.

If they succeed, they would not only help unravel an evolutionary mystery, but also extend the temperature record of Earth by 2 billion years.

Carl Simpson, a macroevolutionary paleobiologist at CU Boulder, has found evidence that cold seawater could have jump-started—rather than suppressed—evolution from single-celled to multicellular life forms. But to demonstrate that very cold temperatures could have sped up evolution, he needs an accurate temperature record from that period.

Temperature records using existing methods are accurate only to 500 million years ago. That could change, though: Lizzy Trower, a chemical sedimentologist, has developed a novel method of measuring global temperature from 500 million to 2.5 billion years ago.

Together, Trower and Simpson hope to test Simpson’s hypothesis against temperature records from Trower’s novel tool, and they recently won a $1 million grant from the W.M. Keck Foundation to do so.

Both the fossil record and calculations based on a “DNA clock”—which calculates the age of current organisms based on the rate of mutations over eons—indicate that multicellular organisms emerged during Snowball Earth.

Simpson, who is an assistant professor of geological sciences and curator of invertebrate paleontology at the CU Museum of Natural History, has spent a lot of time since coming to CU Boulder trying to understand the connection between extreme, prolonged cold and evolution. He describes a breakthrough stemming from a “knuckleheaded” approach: “trying to imagine what the unicellular ancestor of an animal would have been experiencing” during Snowball Earth.

During this “cold, salty and dark” period, there would have been up to a kilometer of ice at the Equator, and liquid water below the ice would have been very cold, about -5 degrees C (about 23 degrees F).

“One thing that you learn about small organisms from a physics point of view is that they don't experience the world the same way that we do, as larger-bodied organisms,” Simpson said. Unicellular organisms are affected by the viscosity, or thickness, of sea water.

The increase in viscosity—which increases as water temperature falls—could yield an evolutionary advantage to those single-celled organisms that clumped together, using their combined propulsion efforts to their mutual advantage. In his laboratory, Simpson and colleagues have found that a type of green algae responds as he hypothesized it would.

Video of algae clumping together in Simpson's lab. (Credit: Andrea Halling)

“And basically, that would trigger the origin of animals, potentially,” he said.

How cold was it?

However, there is uncertainty about how cold it was and how much that cold varied during Snowball Earth. Current methods suggest that the average global temperature in this period was about 20 degrees C, or 68 degrees F, levels that wouldn’t turn the planet into a snowball. That’s where Trower comes in.

Trower, an associate professor of geological sciences, studies grains of sand made from calcium carbonate and called ooids. These sand grains can gather material and get larger as they roll around, “as opposed to any other type of sand grain, which generally just gets smaller the more it’s transported around,” she said.

Trower’s idea was to explore whether the size of ooids could reveal things about the environments in which they formed. Ooids are affected by two kinds of processes: physical and chemical.

Physically, the sand grains are abraded as they roll around and collide with other grains. These abrasions and collisions make the grains shrink.

Chemically, the sand grains can grow with the precipitation of new minerals. Originally, Trower framed these reactions as reflecting the seawater in which they’re forming. “So, for example, if it's more super-saturated with respect to these calcium carbonate minerals, then the rate of mineral precipitation is faster, and that might explain why you would get ooids that are larger.”

But her calculations based on water viscosity didn’t suggest that ooids would grow as large as they did during Snowball Earth. Giant ooids from this period have been found in some places worldwide. Trower is focusing on a form of calcium carbonate called ikaite, which forms only in very cold conditions and which was discovered in a Norwegian fjord.

The ooids built on these rare, cold-loving carbonate minerals can grow comparatively large, greater than 2 millimeters in diameter. Trower notes that ooids of this size and composition form only in certain temperatures; thus, the diameter of these ooids could be a proxy measurement of Earth’s temperature for the last 2.5 billion years.

Answering a big question

With funding from the W.M. Keck Foundation, Trower, Simpson and colleagues will collect giant ooid samples from around the world, measure them and analyze the samples to determine the nature of minerals they were originally composed of.

Watch Lizzy Trower's talk, “Science Perseverance: What I Learned about Being a Scientist from a Grain of Sand,” in which she tells the story of her love for ooids, her journey from curious student to accomplished researcher, and the unexpected lessons learned along the way.

“That, in turn, can tell us something about the chemistry and water temperature in which they formed,” Trower said, noting that those results would be compared against the physical record.

The goal is to answer a big question: “Does the fossil record agree with the predictions we would make based on this theory from this new record of temperature?”

Undertaking such potentially ground-breaking research is both nerve-wracking and also quite exciting, Simpson and Trower said.

Anne Sheehan, professor and chair of the Department of Geological Sciences, praised the scientists: “The project benefits not only from the talent and creativity of Trower and Simpson but also from their willingness to step outside of their disciplines and take risks. This work exemplifies how cross-disciplinary collaboration can push the boundaries of Earth science and drive groundbreaking discoveries.”

Nancy J. Stevens, professor and research institute director of the CU Natural History Museum, observed: “The origin of complex multicellular life is an exciting puzzle to solve, and it would be remiss not to point out how Trower and Simpson have selected a topic and approach that mirror the contemporary research landscape. Organisms able to join forces to unlock new solutions can navigate challenging environments, and ultimately evolve and thrive.”

Trower and Simpson’s work also has potential implications for the human quest to find life elsewhere in the universe, Trower said. If extremely harsh and cold environments can spur evolutionary change, “then that is a really different type of thing to look for in exoplanets (potentially life-sustaining planets in other solar systems), or think about when and where (life) would exist.”

Based in Los Angeles, the W. M. Keck Foundation was established in 1954 by the late W. M. Keck, founder of the Superior Oil Co. The Foundation’s grant making is focused primarily on pioneering efforts in the areas of medical research, science and engineering and undergraduate education. The Foundation also maintains a Southern California Grant Program that provides support for the Los Angeles community, with a special emphasis on children and youth. For more information, please visit www.wmkeck.org.

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When it comes to rock bands, age does matter

Anonymous — Thu, 25 Jul 2024 18:41:22 +0000

When it comes to rock bands, age does matter Anonymous (not verified) Thu, 07/25/2024 - 12:41

Liam Courtney-Davies

Australia’s largest iron ore deposits are 1 billion years younger than previously thought

Iron ore is the key ingredient in steel production. One of the fundamental resources for the Australian economy, it contributes A$124 billion in national income each year.

This is not surprising, considering Western Australia is home to some of Earth’s largest iron ore deposits, and 96% of Australia’s iron ore comes from this state. Yet despite the metal’s significance, we still don’t know exactly how and when iron deposits formed within the continent.

In new research published in the Proceedings of the National Academy of Sciences, we answer some of these questions by directly measuring radioactive elements in iron oxide minerals which form the basis of these resources.

Liam Courtney-Davies is a postdoctoral associate in the CU Boulder Department of Geological Sciences.

We found that several of Western Australia’s richest iron deposits—such as Mt. Tom Price and Mt. Whaleback—are up to 1 billion years younger than previously understood. This redefines how we think about iron deposits at all scales: from the mining site to supercontinents. It also provides clues on how we might be able to find more iron.

Where does iron ore come from?

Billions of years ago, Earth’s oceans were rich in iron. Then early bacteria started photosynthesising and rapidly introduced huge amounts of oxygen into the atmosphere and oceans. This oxygen combined with iron in the oceans, causing it to settle on the sea floor.

Today, these 2.45-billion-year-old sedimentary rock deposits are called banded iron formations. They represent a unique archive of the interactions between Earth’s continents, oceans and atmosphere through time. And, of course, banded iron formations are what we mine for iron ore.

These sedimentary deposits have distinctive, rhythmic bands of reddish iron and paler silica. They were alternately laid down on the sea floor seasonally. Such remarkable rocks can be visited today in Karijini National Park, WA.

The iron content of these banded iron formations is generally less than 30%. For the rock to become economically viable to mine, it must be naturally converted by later processes to around 60% iron.

The nature of this rock conversion is still debated. In simplest terms, a fluid—such as water—will both remove silica and introduce more iron during an “upgrading” process which transforms the rock’s original makeup.

The geochronology (age dating) of this chemical transformation and upgrading is not well understood, largely because the tools required to directly date the iron minerals have only recently become available.

Previous age estimates for the Pilbara iron deposits were indirect but suggested they were at least 2.2 billion years old.

What did we find out?

You may think of iron ore as rusty, red-coloured dust. However, it’s typically a hard, heavy, steely-blue material. When crushed into a fine powder, iron ore turns red. So the red landscape we see across the Pilbara today is a result of the weathering of iron minerals from beneath our feet.

A banded iron formation at Australia's Fortescue Falls. (Photo: Graeme Churchard/Wikimedia Commons)

We extracted microscopic scale “fresh” iron minerals from drill core samples at several of the most significant Western Australian iron deposits.

Leveraging recent advancements in radiometric dating, we measured naturally occurring radioactive elements in the rocks. In particular, the ratio of uranium to lead isotopes in a sample can reveal how long ago individual mineral grains crystallised.

Using the newly generated iron mineral age data, we constructed the first-ever timeline of the formation of Western Australia’s major iron deposits.

We discovered that all major iron ore deposits in the region formed between 1.4 and 1.1 billion years ago, making them up to 1 billion years younger than previous estimates.

These deposits formed in conjunction with major tectonic events, especially the breakup and reemergence of supercontinents. It shows just how dynamic our planet’s history is, and how complex the processes are that led to the formation of the iron ore we use today.

Now that we know that giant ore deposits are linked to changes in the supercontinent cycle, we can use this knowledge to better predict the places where we are more likely to discover more iron ore.

Liam Courtney-Davies is a postdoctoral associate in the Department of Geological Sciences at the �Թ�� of Colorado Boulder.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Australia’s largest iron ore deposits are 1 billion years younger than previously thought.

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Oh, poop! What looks like a rock is filled with clues

Anonymous — Mon, 13 Nov 2023 20:05:32 +0000

Oh, poop! What looks like a rock is filled with clues Anonymous (not verified) Mon, 11/13/2023 - 13:05

Rachel Sauer

In studying dinosaur discards, CU Boulder scientist Karen Chin has gained expertise recently honored with the Bromery Award and detailed in a new children’s book

It was never Karen Chin’s plan to become the poop lady.

In fact, she started out as a naturalist, leading national park visitors on journeys of discovery via tiny, iridescent insect wings and soaring, ancient conifers, and everything in between.

“I wasn’t just interested in mammals or birds or plants; I was interested in how everything fit together, even the soil and the insects and the fungi and everything like that,” she says. “I realized that dung, it has such an ignominious reputation, but it really reflects the transfer of carbon resources throughout the ecosystem, which powers everything.

“Carbon resources are like money in the natural world—they’re how things are transferred back and forth. How carbon goes back into the ecosystem is very important, and dung provides a record of that. Fossil dung, which I study, provides a record of how that happened in the prehistoric world.”

Karen Chin, a �Թ�� of Colorado Boulder professor of geological sciences and curator of paleontology in the CU Museum of Natural History, is a recognized authority on dinosaur diets and dung.

From her initial curiosity about ecosystems to finding clues in dung, Chin, a �Թ�� of Colorado Boulder professor of geological sciences, has become a preeminent authority on dinosaur diets and the resulting dung that, some 75 million years later, is called a coprolite because it’s now fossilized.

In recognition of her contributions to science, not only was she recently recognized with the Geological Society of America’s Randolph W. “Bill” and Cecile T. Bromery Award for Minorities, but her story is featured in the newly published children’s book “The Clues Are in the Poo: The Story of Dinosaur Scientist Karen Chin.” The book recently was awarded the National Science Teaching Association's award for Outstanding Science Trade Books for Students K–12.

The book details her journey from being a child who loved nature but not dinosaurs, and who learned to love science from her father, to a researcher and educator who emphasizes that science is for everyone and open to all.

“I was very lucky because my father was a scientist, so I, myself, never doubted that I could be one, too,” she explains. “I could watch him and see that he did well. When you’re a child, you’re not thinking of discrimination so much, but now I know that he likely faced some. But growing up I thought, ‘My dad’s a scientist, so I can be one.’

“I realize how fortunate I was, because not everyone who has brown skin has a scientist in their family. So, for children who have aspirations to be a scientist and maybe don’t have scientist role models in their family, if they see me, a scientist of color, I hope that tells them it’s a possibility for them, too.”

Poop wasn’t the plan

But back to the poop: It was not the original plan.

Growing up in California, she was mesmerized by the natural world, memorizing the names of plants and insects and spending hours quietly watching the subtle changes in the life all around her. Her father, a former Tuskegee Airman, was a materials scientist who supported her love for science, even though women in science were few, and women of color even fewer.

"The Clues are in the Poo" children's book was created in collaboration between Karen Chin, author Jane Kurtz and illustrator Francisco Riolobos.

In college, she dreamed of working for the National Park Service and before graduating was hired as a seasonal interpretive ranger at Kings Canyon National Park in California. They had no official women’s uniforms when she received the job offer.

After working as a park interpreter for several summer seasons, she realized she wanted to get deeper into the science and accepted a job preparing dinosaur bones. One day, writing exhibit text for her boss, noted paleontologist Jack Horner, she learned that people had discovered fossil feces “and I thought that was the silliest thing,” Chin recalls. “How could soft material fossilize? I ran to Jack and said, ‘Did you know people say they found fossil dung?’

“Jack is kind of taciturn and he said, ‘Yep, and I found some, too.’ I asked, ‘Where? Where?’ He showed me what he thought was fossil dung, and studying those fossils turned into my doctoral dissertation. When I made a thin section of it—I ground it very, very thin so I could look at it through a light microscope—I could see plant cells from 75 million years ago that had gone through the dinosaur. That blew my mind, and I realized that this was a real window on dinosaur-plant interactions and the world they lived in.”

Studying coprolites is one of the more challenging areas of paleontology because unlike, say, vertebrate paleontology—in which scientists find a bone, it’s obviously a bone and they can tell you the dinosaur to which it belonged—coprolites look like rocks. Often, there’s nothing obviously indicating that it came out the back end of a dinosaur tens of millions of years ago, Chin says.

“First I have to say, ‘I suspect this is a coprolite’ and then offer the evidence for why I think it is,” she says. “Then I need to explain what it can tell us about the ancient world, even though I may not be able to tell you who produced the feces.

“I see coprolite study as high-risk, high-reward research because it’s challenging and you don’t know whether some avenues you explore will tell you that much. Because it is challenging, I think people have shied away from studying coprolites, but you can discover some really amazing things.”

Her research has included finding fossilized muscle tissue in a tyrannosaur coprolite (from an older relative of T. rex), a hugely exciting discovery, and revising what had previously been theorized about the diets of herbivorous dinosaurs. Studying coprolites revealed that at certain times of year some duck-billed dinosaurs ate wood, which doesn’t seem especially nutritious and Chin initially interpreted the woody content to be an inescapable consequence of eating conifers with tiny leaves.

Karen Chin works in the Kaiparowits Formation of southern Utah.

However, Chin realized that the wood tissues were different because they’d been rotted by fungus before the dinosaur ingested them, “so I needed to revise my interpretation,” Chin says. “Dinosaurs could have obtained cellulose from rotted wood, but if they were after cellulose, why not just eat leaves? Because we found these coprolites in the same horizon as nesting grounds, I hypothesized that when the dinosaurs were reproducing, they changed their diet to incorporate more protein. By feeding on rotted wood, which has lots of insects and crustaceans and snails hanging out in it, they were accessing a predictable source of protein.

“I don’t know if we’ll ever be able to definitively prove this hypothesis, but the discovery was really exciting and has changed our views of dinosaurs. For a long time, we thought of herbivorous dinosaurs as only eating leaves, but through the coprolites we know they sometimes ate rotted wood and ingested invertebrates.”

‘Everyone’s welcome in science’

Not only is Chin recognized for her expertise in coprolites, but for her rare gift of drawing even the most science agnostic into fascinating prehistoric tableaus to roam with dinosaurs. Plus, dinosaurs and poop?

“That’s the perfect marriage of two things kids find fascinating,” says Oregon-based children’s author Jane Kurtz, who wrote “The Clues Are in the Poo” in collaboration with Chin. “I remember thinking, ‘Wouldn’t it be fun to do something with dinosaur poo?’ Karen is quoted in a lot of other sources I’d been reading for a book I wrote about two early paleontologists who got in a bitter fight about identifying and naming Brontosaurus. So, just in that way that curious people do, and writers do, I was poking around and all roads seemed to lead to Karen.”

Kurtz emailed Chin about writing a children’s book based on her life, that would celebrate science and curiosity and be the book that Kurtz wishes she’d had as a girl who loved bugs and frogs and needed a science role model.

When Kurtz asked Chin how she felt about possibly publishing a picture book that would feature her, she was initially reticent to promote herself, but added that “’I know that young people of color really need to see themselves in this field’,” Kurtz recalls. “So, she addressed that straight on, and I thought, wow, perfect, she’s absolutely right, and we’re in a time of children’s books where people are being very careful to think about voices that have been left out.

Karen Chin working in southern Utah (left) and Montana.

“I told her that I felt I was left out of the science conversation as child, and I have a feeling there were lots and lots of people like me. I think everyone has the capacity to be fascinated by science. There are lots of books about dinosaurs, but there aren’t that many books that focus on how we know what we know about dinosaurs. To me, that’s the really intriguing question.”

That question also animates Chin’s passion for science and science education. She acknowledges that a lot of kids grow up loving dinosaurs and wanting to be paleontologists, which might explain why she often has English and physics and language majors in her upper-level paleobiology classes.

“I try to teach it so that everybody can get something out of it, but I also recognize that there are not that many jobs in paleontology and I think students realize that, too,” Chin says. “So, I tell the students that my goal is that if I run into you three years from now in Boulder and I ask you a very technical thing—for example, what kind of animal is a bryozoan?—I won’t expect you to remember some of those details. But I do hope you learned ‘how to learn’ and that you are committed to lifelong learning.

“I think one of the most important things I can teach is science literacy, so that when students see something—such as an article that makes a claim—they should be asking, ‘OK, where’ the evidence?’ and thinking about whether the article presents a reasonable conclusion. You don’t have to pursue a career in science to be a part of it. Everyone’s welcome in science.”

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In studying dinosaur discards, CU Boulder scientist Karen Chin has gained expertise recently honored with the Bromery Award and detailed in a new children’s book.

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Shemin Ge elected as fellow of American Geophysical Union

Anonymous — Thu, 14 Sep 2023 21:04:59 +0000

Shemin Ge elected as fellow of American Geophysical Union Anonymous (not verified) Thu, 09/14/2023 - 15:04

CU Boulder geological sciences professor is an expert on ‘induced seismicity,’ when earthquakes are triggered by energy development

Shemin Ge, professor of geological sciences at the �Թ�� of Colorado Boulder and an expert in how earthquakes can be triggered by human activity, has been elected as an American Geophysical Union’s (AGU) Fellow, the union announced this week.

Shemin Ge

Ge is among 53 scholars in the 2023 Class of Fellows. AGU, the world's largest Earth and space sciences association, annually recognizes a select number of individuals for its highest honors. Since 1962, the AGU Union Fellows Committee has selected less than 0.1% of members as new fellows.

Ge was selected because of her outstanding scientific achievements, contributions to furthering scientific advancement and exemplary leadership, the organization said, adding that Ge also embodies AGU’s vision of a thriving, sustainable and equitable future powered by discovery, innovation and action.

Equally important, the AGU said, is that Ge works with integrity, respect and collaboration while creating deep engagement in education, diversity and outreach.

Ge is a hydrogeologist who studies groundwater in the Earth’s crust, with a focus on understanding how groundwater flow interacts with and is affected by other geologic processes and how theses interactions advance science and offer insights on societally relevant issues.

One focus of her research is the mechanical interaction between groundwater and rock deformation, which was motivated by an apparent spatial association between some mountain belts and ore deposits in foreland basins adjacent to those mountain belts.

Episodic orogenic deformation could drive mineral-bearing groundwater flow to concentrate ore deposits and enable secondary petroleum migration, Ge’s website notes. A new focus in groundwater-rock deformation research is to seek causal mechanisms for induced seismicity beneath dammed reservoirs and around deep wastewater disposal wells.

Another area of Ge’s research is studying the impact of climate change on groundwater resources, focusing on high-altitude regions where variations in temperature and precipitation are expected. Relying on the fundamental theory of energy and fluid transport in porous media, this research looks into snowmelt infiltrating seasonally frozen ground and permafrost into deeper subsurface and discharging back to surface waters downstream.

“I am deeply honored and extremely grateful for the support I have received from CU and many colleagues, as well as my fortune of working with a stream of bright students throughout the years,” Ge said.

“This recognition further inspires me to continue addressing emerging scientific challenges in water resources and natural or human-induced geohazards through research and teaching.”

Ge joined the CU Boulder faculty in 1993 and has been recognized with a 2019-20 Fulbright U.S. Scholar award to study water-induced earthquakes in Hong Kong. She was named a fellow of the Geological Society of America in 2006, and she won the society’s O.E. Meinzer Award in 2018.

Ge holds a PhD in hydrogeology from Johns Hopkins �Թ�� and master’s and bachelor’s degrees in geotechnical engineering from the �Թ�� of British Columbia, Vancouver, and Wuhan �Թ�� of Technology in Wuhan, China, respectively.

AGU will formally recognize this year’s recipients at AGU23, which in December will convene more than 25,000 attendees from over 100 countries in San Francisco and online.

AGU describes itself as a global community supporting more than half a million advocates and professionals in the Earth and space sciences. Through broad and inclusive partnerships, AGU aims to advance discovery and solution science that accelerate knowledge and create solutions that are ethical, unbiased and respectful of communities and their values.

CU Boulder geological sciences professor is an expert on ‘induced seismicity,’ when earthquakes are triggered by energy development.

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How we cracked the mystery of Australia’s prehistoric giant eggs

Anonymous — Thu, 26 Jan 2023 16:30:40 +0000

How we cracked the mystery of Australia’s prehistoric giant eggs Anonymous (not verified) Thu, 01/26/2023 - 09:30

Matthew James Collins , Beatrice Demarchi , Gifford Miller

Ancient eggshells remained unidentified until AI directed researchers toward an answer

It’s a long-running Australian detective story. From the 1980s onwards, researchers found eggshell fragments, and on rare occasions whole eggs, exposed in eroding sand dunes within the country’s arid zone (which covers most of Australia’s landmass).

A proportion of shells matched eggs laid by emus, but the rest belonged to a mystery species. Researchers initially identified the eggshells as belonging to a giant, extinct bird called Genyornis. But more recently, a group of scientists challenged this view.

With the help of artificial intelligence software, our team has now resolved this scientific controversy, showing that Genyornis was indeed the bird that laid these eggs. With colleagues based around the world, we have published the findings in Proceedings of the National Academy of Sciences.

Genyornis was a flightless bird between two metres and 2.5 metres tall that once roamed the Australian landmass. The eggshell fragments are an important line of evidence about this extinct creature, so being certain about the identity of the bird that laid them is vital.

Some of the shell fragments are 400,000 years old, while the youngest are about 50,000 years old. Previous work showed that some of the youngest eggshells had been burned, but not in the way a wildfire would. Instead, scientific tests point to humans cooking the eggs for food.

The time period where Genyornis shells disappear (50,000 years ago) coincides with what’s thought to be the first arrival of humans in Australia. The discovery therefore raises the possibility that our species contributed to its extinction.

Narrowing the candidates

The eggshell fragments were first recognised by Dom Williams, a geologist and vertebrate palaeontologist from Flinders �Թ�� in Adelaide, in 1981. He made the case that the fragments came from Genyornis, which belonged to a group of extinct creatures known as thunderbirds.

In the 1990s, a team including John Magee, at Australian National �Թ��, and Gifford Miller, one of the authors of this article, provided firm dates for similar shell fragments collected at thousands of arid zone sites. Genyornis was one of many large animals – known as “megafauna” – that once roamed Australia and vanished at around the same time. The work by Miller, Magee and others pinned a clear date of 50,000 years ago on this extinction event.

The association of the eggshells with Genyornis was widely accepted from the 1980s until recently, when it was challenged by a team of scientists from Flinders �Թ�� in Australia. Based upon the size and structure of the eggshells, they argued for a different parent. Their favoured candidate was Progura, a 10kg extinct relative of modern birds such as the brush turkey and malleefowl.

Living birds belonging to this group — known as megapodes – build earthen mounds to incubate their eggs. The scientific debate was fought out in academic journals, with neither side conceding.

Chasing a solution

Attempting to find a resolution, scientists who thought the eggs belonged to Genyornis turned to DNA. Despite the successful extraction of genetic information from eggs of New Zealand’s extinct Moa bird, state-of-the-art DNA sequencing technology drew a blank in this case. The molecules were too degraded after 50,000 years under the hot Australian sun.

Top of page: The giant bird Genyornis went extinct in Australia around 50,000 years ago. Gifford Miller, Author provided Above: DNA tells a genetic story, but to discover the truth about the eggshells researchers needed to focus their study on proteins.

However, proteins – the molecular building blocks of cells – can provide similar information and can last for longer than DNA. In our study, we used a technique called amino acid racemisation to identify the shell fragments with the best-preserved proteins.

As part of the work, our team was able to retrieve partial protein sequences from the Australian eggshells. We then used software called AlphaFold, from the Google-owned AI lab DeepMind, to generate predicted structures for the molecules – the first time this has been done for ancient proteins.

Two of us, Matthew Collins and Beatrice Demarchi, contacted the Bird 10,000 Genomes (B10K) Project. This has set itself the ambitious goal of sequencing the genomes of all bird species.

B10K project member Josefin Stiller took the reconstructed protein sequences and placed them within a “family tree” showing how proteins differ between bird species. The proteins were complete enough to resolve the position of the mystery eggs within the deep branches of this tree of protein sequences, but not sufficiently diagnostic to uniquely identify what the parent bird was.

However, as detailed in our latest paper, the protein sequences were able to conclusively rule out that the parent was a megapode. As there are no other candidate birds, we concluded – as Williams had first proposed in the 1980s – that the eggshells belonged to Genyornis.

This means we can confidently interpret other evidence locked in the shells with implications for how Genyornis went extinct and why the emus that lived alongside it survived.

Picky eater

Isotopes are different forms of chemical elements that can record information about factors such as diet and climate. Carbon isotopes within the eggshell fragments provide information on the birds’ diets and show that Genyornis was a pickier eater than the emu. Oxygen isotopes can be used to track aridity and show that conditions were increasingly dry around the time Genyornis eggshells disappear.

In previous work, Miller and his colleagues analysed the same isotopes in emu eggshells across the time window of Genyornis’ extinction and found that summer-season grasses abruptly disappear from the birds’ diets. This is consistent with a dramatic reduction in monsoon rains.

These findings suggest that Genyornis was already somewhat vulnerable to a changing environment, but another factor may have proved important to its ultimate fate.

When coupled with the lack of evidence from Genyornis skeletons for direct predation, the burnt eggshells suggest that – as is so common elsewhere in the world – human pressure was likely to have been a factor that finally drove these impressive birds to extinction.

Matthew James Collins, Professor of Palaeoproteomics, �Թ�� of Cambridge; Beatrice Demarchi, Associate professor, Università di Torino, and Gifford Miller, Distinguished Professor of Geological Sciences, �Թ�� of Colorado Boulder

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Ancient eggshells remained unidentified until AI directed researchers toward an answer.

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Cross-campus open house will feature interdisciplinary climate change research, kick off U.N. Summit events

Anonymous — Thu, 10 Nov 2022 22:51:46 +0000

Cross-campus open house will feature interdisciplinary climate change research, kick off U.N. Summit events Anonymous (not verified) Thu, 11/10/2022 - 15:51

The College of Engineering and Applied Science, the College of Arts and Sciences and the Leeds School of Business are teaming up to highlight CU Boulder-led research to address climate change from 3-5 p.m. on Nov. 30 in the Olson Atrium of the Rustandy Building.

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Earth scientist wins $2.5 million grant to advance geochronology

Anonymous — Thu, 22 Sep 2022 19:25:27 +0000

Earth scientist wins $2.5 million grant to advance geochronology Anonymous (not verified) Thu, 09/22/2022 - 13:25

With National Science Foundation support, CU Boulder-led initiative aims to attract under-represented people to geosciences and foster grassroots ideas at frontier of ‘inclusive and collaborative science’

A team of researchers led by an Earth scientist at the �Թ�� of Colorado Boulder has won a $2.5 million grant from the National Science Foundation (NSF) to advance geochronology, the study of the age of Earth materials—a field that is key for understanding Earth processes and history.

NSF’s support will establish an initiative called Advancing Geochronology Science, Spaces, and Systems (AGeS-cubed or AGeS³). The effort aims to boost access to geochronology data and expertise to advance scientists’ understanding of Earth systems, launch a platform to attract under-represented minorities to the geosciences, and test grassroots ideas at the “frontier of inclusive and collaborative science.”

Rebecca Flowers

Rebecca Flowers, CU Boulder professor of Geological Sciences, is the principal investigator on the five-year effort. Her collaborators are CU Boulder Associate Professor Leilani Arthurs, Professor Ramon Arrowsmith of Arizona State �Թ�� and Vicki S. McConnell, executive director of the Geological Society of America.

Geochronology data are essential for addressing first-order questions in Earth system science related to climate change, biologic and landscape change, earthquake cyclicity and hazards and solid Earth evolution. But the National Academies have noted barriers persist to geochronology data access, technical innovation and training. Flowers and her colleagues intend to address these needs through three micro-grant programs.

Flowers recently answered five questions from this publication about the project, which was funded through the NSF’s Frontier Research in Earth Sciences Program. The questions and answers appear below:

Question: You and your colleagues note that the National Academy has repeatedly highlighted the challenges for geochronology data access, technical innovation and training; can you summarize the nature of those challenges?

Answer: The 2020 National Academies report “A Vision for Earth Sciences, 2020-2030: Earth in Time” (2020 Earth in Time report) emphasizes that there are challenges associated with the current funding model in which individual investigator-based labs are supported by awards to address specific research questions, with little or no funds provided to support lab infrastructure, technique development or training activities. Although there are hundreds of scientists in need of data from these labs, labs struggle to cover the costs of their operations and commonly are not in a position to serve these broader needs. This has hindered the development of new methods, instruments and collaborative applications that are required to address Earth science questions.

I have always been fascinated by the Earth and especially by the stories that rocks hold about Earth history. It’s amazing what individual, 100-micron-scale mineral crystals within rocks can tell us about mountain-belt-scale or even planetary-scale histories.

Q: You and your collaborators propose to launch an initiative to advance geochronology “science, spaces and systems,” and you propose to do this via strategic, micro-award grants. What can you tell us about the idea of focusing micro-grants, rather than larger grants, toward this end?

A: It has been suggested that micro-funding has a transformative impact on the sciences, just as micro-loans have done for many populations. The small and flexible AGeS grants can catalyze collaborations between geochronology labs and others in different disciplines, enabling important scientific advances that may not happen within the bubble of more standard grants.
A common element of the three micro-support programs is making small investments that promote interdisciplinary science and cumulatively advance the field.

Q: Researchers in the STEM disciplines often discuss how to attract more under-represented people to those fields. What can you tell us about the proposed platform to attract under-represented minorities to the geosciences?

A: The goals of the new AGeS-DiG (Diversity in Geochronology) program are to engage, train and educate students who have not traditionally had equal access to geochronology data and training, and to generate and test innovative ideas to expand geochronology access for these students. The AGeS-DiG program plans to make 30 awards of up to $15,000 each to support creative geochronology projects or initiatives that address these aims.
Priority will be given to projects that emphasize authentic research experiences, mentor multiple students and foster a cohort experience for participants. Examples of possible AGeS-DiG projects include opportunities for underserved groups to visit labs in-person to acquire data for project(s); training of an underrepresented cohort in geochronology methods and remote-data acquisition for a project; or other innovative concepts.

Q: You intend to “test grassroots ideas at a frontier of inclusive and collaborative science.” Could you share an example of a grassroots idea that could be tested in such a way?

A: The AGeS-TRaCE (TRaining and Community Engagement) program is a new funding mechanism that seeks and supports community-driven ideas for addressing geochronology needs, such as such as capturing, formalizing and disseminating not-yet-standardized geochronology knowledge that is not widely available and providing opportunities for collaborative discussion on key geochronology challenges related to human-, technical- or cyber-infrastructure.
Examples of AGeS-TRaCE projects include accessible webinars, tutorials and workshops on best practices, lab procedures, instrument design, statistics and uncertainties or data interpretation; and focused meetings to discuss interlaboratory calibration, spikes, new and emerging chronometers, data management systems, modeling tool development or other capabilities needed for the future.

Q: What drew you to focus on geology generally and geochronology specifically in your research?

A: I have always been fascinated by the Earth and especially by the stories that rocks hold about Earth history. It’s amazing what individual, 100-micron-scale mineral crystals within rocks can tell us about mountain-belt-scale or even planetary-scale histories.
As a geochronologist, I have my own “time machines” in the lab to learn about the past. The AGeS program is about providing a broader community of scientists with funding and collaborative access to these instruments to unravel important stories about the Earth.

With National Science Foundation support, CU Boulder-led initiative aims to attract under-represented people to geosciences and foster grassroots ideas at frontier of "inclusive and collaborative science."

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Peter Molnar, 1943-2022

Anonymous — Fri, 24 Jun 2022 17:54:37 +0000

Peter Molnar, 1943-2022 Anonymous (not verified) Fri, 06/24/2022 - 11:54

CIRES, Geological Sciences, CU Boulder mourn loss of exceptional scholar who inspired greatness

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