EOS

Citation Keri Nicoll

Keri Nicoll is known internationally for her expertise in fair weather atmospheric electricity measurements and instrumentation development. Her pioneering research in instrumentation development has resulted in the creation of many new sensors (including space charge, conductivity, and energetic particle sensors) for balloon and small aircraft, some of which are now commercially available. This has enabled Keri to become a world leader in investigating fundamental questions related to charge and atmospheric electricity effects on cloud and aerosol microphysics, which are important for climate projections.

Keri is well recognized for her research achievements (54 journal papers in 10 years, which have been cited over 1,000 times) and her scientific leadership—leading (or coleading) 11 different projects. Her work on the Global Coordination of Atmospheric Electricity Measurements project (GloCAEM; https://glocaem.wordpress.com/) is particularly valuable, bringing global atmospheric electricity researchers together for the first time to create a new network and a publicly accessible data archive for atmospheric electricity measurements. The legacy of this project is likely to continue for many decades to come and since its completion has inspired many others to contribute data to the new archive. Further evidence of her high standing within the international community is her invitation to join three separate European Union cost actions (including leading one as a working group leader), International Space Science Institute (ISSI) teams, and her current role as training manager for the EU Marie Curie training network, SAINT.

Keri’s research activities have literally spanned the globe. She has led balloon and aircraft field campaigns in Antarctica, the Arctic, the Middle East, and Europe, and the instrumentation developed by her research group is highly sought after by researchers all over the world.

—Colin Price, Porter School of the Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel

 

Response

I am very honored to receive this year’s AGU Atmospheric and Space Electricity Early Career Award, and I thank Colin Price for his nomination and the Atmospheric and Space Electricity committee for their consideration of all the applications. I am also particularly grateful to such colleagues as Giles Harrison, Yoav Yair, Michael Rycroft, Martin Fullekrug, Karen Aplin, and Alec Bennett for their advice and stimulating science discussions over the past 10 or so years.

Atmospheric electricity is a subject I have long been passionate about, and I feel very fortunate to work in a field that has afforded me many exciting opportunities to perform new and interesting research in some unique locations. At the core of my research has been the development of small, disposable atmospheric electricity sensors (especially for airborne use), and I am particularly thankful to Giles Harrison for being such a fantastic mentor in this. Among his many other useful insights, Giles helped me realize very early in my career the satisfaction of turning a theoretical concept of a sensor into a physical device, which we launch into the air, make some measurements with, and discover something new about the atmosphere. The sensors that we have developed have enabled me to work with many different research groups around the world and get involved with multidisciplinary projects that have taken me from the top of volcanoes to the frozen Antarctic.

With its range of different science subjects, AGU highlights the importance of multidisciplinary science and the new discoveries that can be made when we merge knowledge and techniques from different subject areas, and I look forward to working with many more colleagues in the future to better understand Earth’s atmospheric electrical environment.

—Keri Nicoll, Department of Meteorology, University of Reading, Reading, U.K.

Scale-dependent feedbacks in space, which couple short-distance positive feedback with long-distance negative feedback, are considered a prime reason or even a necessary condition for self-organization that results in regular patterns of many kinds.

Building on previous research in geomorphology, Dong et al. [2021] introduce a competition model that captures scale-dependent feedbacks in time, revealing a new form of self-organization that may explain regular patterns found in nature. They illustrate the new concept by focusing on the evenly spaced cypress depressions in the Big Cypress National Preserve, South Florida, USA.

Neighboring cypress depressions compete for catching precipitation, which promotes weathering and therefore leads to expansion of the depression volume. As a depression grows, it retains more precipitation, further increasing the duration of wet periods and the associated weathering. The growth rate of the depressions decreases with size, which causes a movement of the divides between depressions in favor of the smaller depression, until all depressions are similar in size and shape.

The authors devised a mathematical model describing this process of regular pattern formation, which may be applicable to other landscape pattern formation processes both in geomorphology and in ecology.

Citation: Dong, X., Murray, A. B., & Heffernan, J. B. [2021]. Competition among limestone depressions leads to self-organized regular patterning on a flat landscape. Journal of Geophysical Research: Earth Surface, 126, e2021JF006072. https://doi.org/10.1029/2021JF006072

—Ton A. J. F. Hoitink, Editor, JGR: Earth Surface

This is an authorized translation of an Eos article. Esta es una traducción al español autorizada de un artículo de Eos.

En diciembre de 2019, la península de Reykjanes, que se adentra en el Océano Atlántico al suroeste de Reykjavík, la capital de Islandia, comenzó a experimentar intensos enjambres sísmicos. Desde entonces, los científicos de la Oficina Meteorológica de Islandia han estado rastreando y monitoreando la deformación de la superficie de la Tierra a medida que el magma se empuja (se intruye) en la corteza superficial. Tres intrusiones iniciales ocurrieron cerca del monte Thorbjörn, en las afueras de la ciudad de Grindavík. Una cuarta intrusión infló ligeramente el extremo más occidental de la península, y una quinta intrusión dio un salto hacia el este, más allá de Grindavík, hacia Krýsuvík, según Sara Barsotti, vulcanóloga italiana y coordinadora de peligros volcánicos en la Oficina Meteorológica de Islandia.

La Península de Reykjanes al suroeste de Islandia experimentó miles de sismos asociados a intrusiones de magma subterráneas a principios del 2021. Los primeros sismos fueron identificados cerca del Monte Thorbjörn y Krýsuvík. El sismo más grande (M5.7) sacudió la península entre Keilir y Fagradalsfjall. (El aeropuerto internacional de Keflavik y la ciudad capital de Rreykjavík son mostradas como escala). Fagradalsfjall se convirtió pronto en el volcán activo de Islandia más nuevo. Crédito: Google Earth.

Más de un año después de que comenzara esta agitación, el 24 de febrero, un gran terremoto de magnitud 5.7 sacudió la península entre Keilir y Fagradalsfjall, “marcando un punto de inflexión”, dijo Barsotti.

Poco después, la red sísmica de la Oficina Meteorológica de Islandia registró más de 50.000 terremotos en la península. Usando las herramientas de monitoreo a su disposición, los científicos encontraron un corredor de magma entre Keilir y Fagradalsfjall, dijo Barsotti. Este magma fluyó bajo tierra durante aproximadamente 3 semanas, con terremotos definiendo los bordes de la cámara subterránea. Luego, tanto la sismicidad como la deformación se desplomaron.

Para ese momento, algunos científicos plantearon la hipótesis de que la intrusión se congelaría dentro de la corteza, dijo Kristín Jónsdóttir, sismóloga de la Oficina Meteorológica de Islandia. “Entonces”, dijo, “comenzó la erupción”.

En contra de un cielo gris, lava naranja sale del Fagradalsfjall en el segundo día de la erupción. Al frente, lava enfriándose brilla en contraste con el basalto negro que ya está solidificado. Crédito: Toby Elliott/Unsplash Mantener a las multitudes seguras

El 19 de marzo, la lava comenzó a salir desde el borde de la intrusión cerca de Fagradalsfjall, y los islandeses acudieron en masa a las montañas sobre la fisura para hacer un picnic, jugar al fútbol o simplemente observar el espectáculo de luces de lava de la naturaleza. “Los islandeses… sienten que esto es parte de su vida”, dijo Barsotti. “Realmente quieren disfrutar de lo que su país es capaz [de darles]”.

People casually playing volleyball at the #volcano in #Fagradalsfjall, #Iceland yesterday

Betelgeuse has the most name recognition of the known supergiant stars, due partly to its proximity to the Sun (a mere 724 light-years away) and partly to its prominence in a well-known constellation (it’s Orion’s right shoulder). But if you’re looking for a star about to go supernova, Miguel Montargès has a few more promising candidates he can recommend. “I always say VY Canis Majoris,” he suggested. “It’s only 5 times farther away than Betelgeuse, but it’s also brighter because it’s much older,” though it’s hard to see through its thick blanket of obscuring dust.

Betelgeuse is young among supergiant stars, which include some of the largest and most evolved stars that still undergo nuclear fusion. By “young,” astronomers mean that Betelgeuse is still tens of thousands of years away from a catastrophic meltdown. That doesn’t stop the world from watching with bated breath whenever it behaves peculiarly.

Betelgeuse, circled in red, is the second-closest red supergiant star to Earth and the brightest star in the constellation Orion. (Red supergiant Antares in the constellation Scorpius is about 175 light-years closer.) Credit: ESO/N. Risinger (skysurvey.org), CC BY 4.0

The intrigue stems from the fact that astronomers are still learning how some of the physical processes that lead to a supernova manifest visibly, said Montargès, an astrophysicist at Observatoire de Paris in France. Betelgeuse, however, is not likely to take us by surprise. Montargès is part of a subfield of astronomers who regularly observe supergiant stars to better understand the very last stages of a star’s life cycle. “There are thousands of red supergiants in the galaxy, and I would say 100 or 200 that are nicely visible from Earth,” he said. “And of those, there are about 10-ish that we are observing regularly. Betelgeuse is the most observed by far.”

Montargès has been observing Betelgeuse for years to understand the processes rapidly propelling it toward its explosive end. In January 2019, he led an observing campaign on the Very Large Telescope (VLT) in Chile to study the star at the faintest point of its regular 400-day cycle of brightness variation. Months later, when he was just beginning to analyze those data, the first reports started coming in that Betelgeuse was dimming rapidly and unexpectedly. The period, now called the Great Dimming, prompted astronomers around the world to swing their telescopes toward Betelgeuse to catch whatever happened next.

Colder or Dustier? Actually, It Was Both

Proposals to observe with major telescopes like VLT can take weeks or months to be approved during normal review cycles. But thanks to the small allotment of telescope time known as director’s discretionary time (set aside for sudden and unexpected astronomical events), Montargès and his team could jump to the front of the queue. They applied to study the Great Dimming with VLT and the VLT Interferometer late in December 2019, and days later their request was approved. “I was asked to send in the observing commands immediately, and [the star] was observed the same night,” he said.

He initially set out to prove that nothing at all atypical was going on with Betelgeuse. “And I was wrong,” he quipped. As the dimming continued, the team applied for more discretionary observing time so they could see the entire event from beginning to end. They were awarded two more chances to observe Betelgeuse with VLT instruments: one right when the star was at its faintest and one as it started to brighten again. It was just in the nick of time: Paranal Observatory, which hosts VLT, closed because of COVID-19 safety concerns just 3 days after the researchers collected their final set of observations.

Researchers observed Betelgeuse with the Very Large Telescope before the Great Dimming (leftmost image) and then three times during the event (three subsequent images). These high-resolution images show that Betelgeuse’s southwestern quadrant (lower right area of the star) cooled significantly and was obscured by a newly formed dust cloud. Credit: ESO/M. Montargès et al., CC BY 4.0

These new observations, combined with archival data from professional and amateur astronomers around the world, revealed that Betelgeuse’s Great Dimming was caused by a large mass loss event on the star’s surface. The mass loss event cooled the star’s southwestern quadrant by an estimated 500°C, which then triggered the expelled gas to condense into dust, “like dew forming on the outside of a glass of ice water, except dark,” science communicator and astronomer Phil Plait explained on Twitter. The combination of the quick cooling and the dust obscuration made Betelgeuse’s southern hemisphere appear about 10 times fainter than it should have been (see video below).

Large mass loss events like this one, during which Betelgeuse created a cloud about a tenth of the mass of Earth, are theorized to be a regular occurrence during the supergiant phase of a star’s life. VY Canis Majoris, for example, may have already expelled half its original mass and is obscured by a thick veil of dust. However, Betelgeuse’s Great Dimming is the first time a large-scale mass loss event has been monitored in real time for this type of star. The researchers published these results in Nature on 16 June.

Are Great Dimmings Normal?

“Did we see this event on Betelgeuse because there is something special about this star, or [did] we see it because that’s the one that we’re observing the most?”Even though astronomers have pinned down the likely cause of Betelgeuse’s Great Dimming, they can’t answer whether supergiants lose most of their mass by a continuous stellar wind or through large mass loss events like this. “Did we see this event on Betelgeuse because there is something special about this star, or [did] we see it because that’s the one that we’re observing the most?” Montargès asked. Astronomers have never seen this type of event on another supergiant star, “but perhaps it is because we are not looking.”

Pandemic-related observatory closures in 2020 and 2021 stymied some of the researchers’ hoped-for follow-up observations, but they are continuing to apply for telescope time with VLT and other telescopes. A forthcoming proposal to observe Betelgeuse with the Atacama Large Millimeter/submillimeter Array (ALMA) aims to pin down the chemical composition of the dust that condensed from the expelled stellar material.

Farther down the line, Montargès explained, the continuous monitoring capabilities of the Vera C. Rubin Observatory, scheduled to come online in 2023, and the more sensitive eye of the Extremely Large Telescope, scheduled to come online in 2025, will help fill the gaps in our understanding of not just Betelgeuse but also other supergiant stars that remain under-studied.

—Kimberly M. S. Cartier (@AstroKimCartier), Staff Writer

Today in Eos, American Geophysical Union (AGU) Publications again recognizes a number of outstanding reviewers for their work in 2020, as selected by the editors of each journal.

Every article decision relies on dedicated individuals who take time out from their own research to volunteer their expertise.Peer review is central to communicating and advancing science. While there have never been more ways to distribute ideas and research outputs, a robust peer review ensures that we maintain the highest integrity in our scientific discourse. The peer review process is organized by our journal editors, but every article decision relies on dedicated individuals who take time out from their own research to volunteer their time and expertise. The work of these reviewers ensures proper evaluation of thousands of articles each year. We are truly thankful for their efforts.

As the uses for scientific literature have grown, so has the complexity of papers, which now typically include more authors bringing more techniques, data, simulations, and results. This increase in complexity has increased the challenge and role of reviewing. The outstanding reviewers listed here have provided in-depth evaluations, often through multiple revisions, that greatly improved the final published papers. Their contributions helped raise the quality of submissions received from around the world, providing valuable feedback that elevates the prominence of our journals to the high standards aligned with the AGU tradition.

Many Reviewers: A Key Part of AGU Journals

While we note these few outstanding reviewers here, we also acknowledge the broad efforts by many AGU reviewers in helping ensure the quality, timeliness, and reputation of AGU journals. We also welcome new and first-time reviewers who have joined the family of integrity stewards and have been providing authors valuable evaluations. In 2020, AGU received more than 18,100 submissions, which is up from the 16,700 submissions received in 2019, and published more than 7,163, up from 7,000 articles in 2019. Many of these submissions were reviewed multiple times—in all, 19,227 reviewers completed 42,564 reviews in 2020 compared to the 39,368 reviews completed in 2019.

Our thanks are a small recognition of the large responsibility that reviewers bear in improving our science and its role in society.This increase has happened in the past year while each AGU journal worked to shorten the time from submission to first decision and publication or consistently maintained industry-leading standards. Several AGU journals regularly return first decisions within 1 month of submission, and most others do so now within 2 months. Reviewers represent a key part of this improvement. We look back at 2020 here, but we have already seen that in 2021, during the pandemic and unrest, members of our amazing community have continued to accept invitations to peer review article submissions.

Editorials in each journal (some already published, some upcoming) express our appreciation along with recognition lists. Our thanks are a small recognition of the large responsibility that reviewers bear in improving our science and its role in society.

Additional Thanks

We are working to highlight the valuable role of reviewers through events (though they may be virtual) at Fall Meeting and other meetings.

Each reviewer also receives a discount on AGU and Wiley books. We will continue to work with the Open Researcher and Contributor Identification network (ORCID) to provide official recognition of reviewers’ efforts, so that reviewers receive formal credit there. As of 5 May we have over 71,700 ORCIDs linked to GEMS user accounts as compared to 59,962 at this time last year.

Getting Your Feedback

We are working to improve the peer review process itself, using new online tools. We conducted a full survey in 2020, and we continue to provide a short questionnaire for feedback after each review is completed.

We value your feedback, including ideas about how we can recognize your efforts even more, improve your experience, and increase your input on the science.

We look forward to hearing from you. If you’d like to respond directly, feel free to take our survey.

Once again: Thanks!

—Matt Giampoala (mgiampoala@agu.org), Vice President, Publications, AGU; and Carol Frost, Chair, AGU Publications Committee

 

 

 

 

 

 

 

Sarah Aarons Scripps Institution of Oceanography, University of California, San Diego Rose Cory Geophysical Research Letters

 

 

 

 

 

Franciscus Aben University College London JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Eldert L. Advokaat University of Birmingham Tectonics editors Tectonics

 

 

 

 

 

Hoori Ajami University of California, Riverside Water Resources Research editors Water Resources Research

 

 

 

 

 

Mark Allen University of Durham Tectonics editors Tectonics

 

 

 

 

 

Grace Andrews University of Southampton Rose Cory Geophysical Research Letters

 

 

 

 

 

Sylvain Barbot University of Southern California Germán Prieto Geophysical Research Letters

 

 

 

 

 

Roberto Basili Istituto Nazionale di Geofisica e Vulcanologia Tom Parsons AGU Advances

 

 

 

 

 

Cameron Batchelor University of Wisconsin–Madison Valerie Trouet Geophysical Research Letters

 

 

 

 

 

Timothy Bates University of Washington JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Sarah N. Bentley Northumbria University Space Weather editors Space Weather

 

 

 

 

 

Tom G. Beucler University of Lausanne and University of California, Irvine Journal of Advances in Modeling Earth Systems editors Journal of Advances in Modeling Earth Systems (JAMES)

 

 

 

 

 

Kevin Bladon Oregon State University Water Resources Research editors Water Resources Research

 

 

 

 

 

Lina Boljka University of Bergen JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Pierre Boué Université Grenoble Alpes JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Ian Brooks University of Leeds Hui Su Geophysical Research Letters

 

 

 

 

 

Josephine Brown University of Melbourne Earth’s Future editors Earth’s Future

 

 

 

 

 

Manuela Brunner University of Freiburg Water Resources Research editors Water Resources Research

 

 

 

 

 

Ishi Buffam Swedish University of Agricultural Sciences JGR-Biogeosciences editors JGR-Biogeosciences

 

 

 

 

 

William Burt University of Alaska Fairbanks JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Michael P. Byrne University of St. Andrews and University of Oxford Alessandra Giannini Geophysical Research Letters

 

 

 

 

 

Miguel Angel Cabrera Universidad de los Andes JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Harish Chandra Physical Research Laboratory Sana Salous Radio Science

 

 

 

 

 

Daniel Chavas Purdue University Suzana Camargo Geophysical Research Letters

 

 

 

 

 

Marie-Luce Chevalier Institute of Geology, Chinese Academy of Geological Sciences Tectonics editors Tectonics

 

 

 

 

 

John Chiang University of California, Berkeley Hui Su Geophysical Research Letters

 

 

 

 

 

Gabriele Chiogna Technical University of Munich Water Resources Research editors Water Resources Research

 

 

 

 

 

Xinzhao Chu University of Colorado Boulder Earth and Space Science editors Earth and Space Science

 

 

 

 

 

Hye-Yeong Chun Yonsei University JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Julia Cole University of Michigan Fabio Florindo Reviews of Geophysics

 

 

 

 

 

Brian D. Collins U.S. Geological Survey JGR-Earth Surface editors JGR-Earth Surface

 

 

 

 

 

Mathias Collins National Oceanic and Atmospheric Administration Water Resources Research editors Water Resources Research

 

 

 

 

 

Kristen Corbosiero The University at Albany Suzana Camargo Geophysical Research Letters

 

 

 

 

 

Kenneth Cummins University of Arizona and Florida Institute of Technology JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Chimene Laure Daleu University of Reading Alessandra Giannini Geophysical Research Letters

 

 

 

 

 

Francisco Delgado Universidad de Chile Christian Huber Geophysical Research Letters

 

 

 

 

 

Meagan Eagle Woods Hole Coastal and Marine Science Center/U.S. Geological Survey JGR-Biogeosciences editors JGR-Biogeosciences

 

 

 

 

 

Jennifer Eccles University of Auckland JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

David Evans Goethe-Universität Frankfurt Paleoceanography and Paleoclimatology editors Paleoceanography and Paleoclimatology

 

 

 

 

 

Ian Faloona University of California, Davis Christopher Cappa Geophysical Research Letters

 

 

 

 

 

Michel Faure Institut des Sciences de la Terre d’Orléans/Université d’Orléans-CNRS Tectonics editors Tectonics

 

 

 

 

 

Grant Ferguson University of Saskatchewan Water Resources Research editors Water Resources Research

 

 

 

 

 

Christopher Fisher University of Western Australia Geochemistry, Geophysics, Geosystems editors Geochemistry, Geophysics, Geosystems

 

 

 

 

 

David D. Flagg Marine Meteorology Division, U.S. Naval Research Laboratory Yu Gu Geophysical Research Letters

 

 

 

 

 

Gwenn Flowers Simon Fraser University JGR-Earth Surface editors JGR-Earth Surface

 

 

 

 

 

Heather L. Ford Queen Mary University of London Paleoceanography and Paleoclimatology editors Paleoceanography and Paleoclimatology

 

 

 

 

 

Sven Frei University of Bayreuth Water Resources Research editors Water Resources Research

 

 

 

 

 

Melodie French Rice University JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Martin Galis Comenius University in Bratislava and Slovak Academy of Sciences JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Rolando Garcia National Center for Atmospheric Research JGR-Space Physics editors JGR-Space Physics

 

 

 

 

 

Sarah N. Giddings Scripps Institution of Oceanography, University of California, San Diego JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Patricia M. Glibert University of Maryland Center for Environmental Science JGR-Biogeosciences editors JGR-Biogeosciences

 

 

 

 

 

Maxime Grandin University of Helsinki Mary Hudson AGU Advances

 

 

 

 

 

Carlo Gualtieri University of Naples Federico II Water Resources Research editors Water Resources Research

 

 

 

 

 

Mike Hapgood RAL Space, Science and Technology Facilities Council Andrew Yau Geophysical Research Letters

 

 

 

 

 

Elima Hassanzadeh Polytechnique Montréal Earth’s Future editors Earth’s Future

 

 

 

 

 

Xiaogang He National University of Singapore Valeriy Ivanov Geophysical Research Letters

 

 

 

 

 

Nicholas G. Heavens Imperial College London JGR-Planets editors JGR-Planets

 

 

 

 

 

Agnès Helmstetter Université Grenoble Alpes JGR-Earth Surface editors JGR-Earth Surface

 

 

 

 

 

Jonathan Herman University of California, Davis Water Resources Research editors Water Resources Research

 

 

 

 

Jennifer Hertzberg International Ocean Discovery Program, Texas A&M University Geochemistry, Geophysics, Geosystems editors Geochemistry, Geophysics, Geosystems

 

 

 

 

 

Takehiko Hiraga University of Tokyo JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

William Hockaday Baylor University JGR-Biogeosciences editors JGR-Biogeosciences

 

 

 

 

 

Cathy Hohenegger Max Planck Institute for Meteorology Journal of Advances in Modeling Earth Systems editors Journal of Advances in Modeling Earth Systems (JAMES)

 

 

 

 

 

Quan Hua Australian Nuclear Science and Technology Organisation Valerie Trouet Geophysical Research Letters

 

 

 

 

 

Wenxin Huai Wuhan University Water Resources Research editors Water Resources Research

 

 

 

 

 

Chengxin Jiang The Australian National University JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Cathleen Jones NASA Jet Propulsion Laboratory, California Institute of Technology Water Resources Research editors Water Resources Research

 

 

 

 

 

McArthur Jones, Jr. Space Science Division, U.S. Naval Research Laboratory JGR-Space Physics editors JGR-Space Physics

 

 

 

 

 

Jason Kean U.S. Geological Survey Harihar Rajaram Geophysical Research Letters

 

 

 

 

 

Minseok Kim University of Arizona Water Resources Research editors Water Resources Research

 

 

 

 

Vassili Kitsios Commonwealth Scientific and Industrial Research Organisation and Monash University Journal of Advances in Modeling Earth Systems editors Journal of Advances in Modeling Earth Systems (JAMES)

 

 

 

 

 

 

Wouter J. M. Knoben University of Saskatchewan Centre for Hydrology Water Resources Research editors Water Resources Research

 

 

 

 

 

Julian Koch Geological Survey of Denmark and Greenland Water Resources Research editors Water Resources Research

 

 

 

 

 

Nicolas Kolodziejczyk University of Brest Kathleen Donohue Geophysical Research Letters

 

 

 

 

 

Alexandra Konings Stanford University Valeriy Ivanov Geophysical Research Letters

 

 

 

 

 

Tobias Kukulka University of Delaware JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Evgeniy V. Kulakov University of Oslo JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Zachary M. Labe Colorado State University Harihar Rajaram Geophysical Research Letters

 

 

 

 

 

Phoebe Lam University of California, Santa Cruz JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Timothy James Lang Marshall Space Flight Center, NASA JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Jason Leach Canadian Forest Service, Natural Resources Canada Water Resources Research editors Water Resources Research

 

 

 

 

 

Solène Lejosne University of California, Berkeley JGR-Space Physics editors JGR-Space Physics

 

 

 

 

 

Jing Li Peking University Kaicun Wang Geophysical Research Letters

 

 

 

 

 

Zhonghui Liu The University of Hong Kong Paleoceanography and Paleoclimatology editors Paleoceanography and Paleoclimatology

 

 

 

 

 

Lifeng Luo Michigan State University JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Yali Luo Chinese Academy of Meteorological Sciences JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Kristina A. Lynch Dartmouth College Andrew Yau Geophysical Research Letters

 

 

 

 

Qianli Ma Center for Space Physics, Boston University and University of California, Los Angeles Gang Lu Geophysical Research Letters

 

 

 

 

 

Yuxia Ma Lanzhou University Gabriel Filippelli GeoHealth

 

 

 

 

 

Giuseppe Mascaro Arizona State University Earth’s Future editors Earth’s Future

 

 

 

 

 

Kathryn Materna U.S. Geological Survey JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Mesfin Mekonnen The University of Alabama Earth’s Future editors Earth’s Future

 

 

 

 

 

Lieke Melsen Wageningen University Water Resources Research editors Water Resources Research

 

 

 

 

 

Chris W. Milliner California Institute of Technology Earth and Space Science editors Earth and Space Science

 

 

 

 

 

Ali Mirchi Oklahoma State University Earth’s Future editors Earth’s Future

 

 

 

 

 

Motoki Nagura Japan Agency for Marine-Earth Science and Technology JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Noboru Nakamura University of Chicago JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Yosio Nakamura The University of Texas at Austin JGR-Planets editors JGR-Planets

 

 

 

 

 

Kaitlin Naughten British Antarctic Survey JGR-Oceans editors JGR-Oceans

 

 

 

 

 

Megan Newcombe University of Maryland, College Park Geochemistry, Geophysics, Geosystems editors Geochemistry, Geophysics, Geosystems

 

 

 

 

 

Sharon E. Nicholson Florida State University JGR-Atmospheres editors JGR-Atmospheres

 

 

 

 

 

Hannes Nickisch Philips Research Hamburg Earth and Space Science editors Earth and Space Science

 

 

 

 

 

Edwin Nissen University of Victoria JGR-Solid Earth editors JGR-Solid Earth

 

 

 

 

 

Yoshiharu Omura Kyoto University Andrew Yau Geophysical Research Letters

 

 

Yuichi Otsuka Nagoya University Space Weather editors Space Weather

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Gang Lu Geophysical Research Letters

 

 

 

 

 

Michel Parrot Laboratoire de Physique et Chimie de l’Environnement et de l’Espace Sana Salous Radio Science

 

 

 

 

 

Eric Josef Ribeiro Parteli Universität Duisburg-Essen JGR-Earth Surface editors JGR-Earth Surface

 

 

 

 

 

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Alan Rhoades Lawrence Berkeley National Laboratory Christina Patricola Geophysical Research Letters

 

 

 

 

 

Camille Risi Laboratoire de Météorologie Dynamique Hui Su Geophysical Research Letters

 

 

 

 

 

Frances Rivera-Hernández Georgia Institute of Technology Andrew Dombard Geophysical Research Letters

 

 

 

 

 

Andrew Roberts Los Alamos National Laboratory Journal of Advances in Modeling Earth Systems editors Journal of Advances in Modeling Earth Systems (JAMES)

 

 

 

 

 

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James Ruppert University of Oklahoma Suzana Camargo Geophysical Research Letters

 

 

 

 

 

Mojtaba Sadegh Boise State University Earth’s Future editors Earth’s Future

 

 

 

 

 

Timothy Scheibe Pacific Northwest National Laboratory Water Resources Research editors Water Resources Research

 

 

 

 

 

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Farming practices of the Vikings and their ancestors could provide inspiration for resilient food systems today. That’s thanks to a study exploring how Scandinavian societies adapted their agricultural activities in a period of European history marked by stark climate fluctuations.

The Viking Age kicked off around 800 as societies in Scandinavia expanded, partly as a result of a rise in temperature that allowed agriculture to flourish. Historians believe that a growth in population and the pressure it placed on available farmland were reasons why Vikings began venturing beyond their homelands.

In popular culture today, a lot of focus is placed on Viking raids and attacks on religious sites, partly because many firsthand accounts were written by besieged Christian scholars. But archaeological evidence suggests that above all else Vikings were agriculturalists who cultivated crops and reared livestock, often on self-sufficient farms.

Less is known about farming practices in pre-Viking societies, those existing in an era known as the Dark Ages Cold Period. During this half millennium between 300 and 800, northern Europe experienced cold climates driven by volcanoes spewing gases and dust into the atmosphere, which reduced the amount of solar radiation reaching Earth’s surface.

Digging in the Mud Near Rakni’s Mound

The new research finds evidence that a community in Norway responded to this climate turbulence by regularly adapting its cereal production and animal husbandry practices. It is one of the first studies from a multidisciplinary project called Volcanic Eruptions and their Impacts on Climate, Environment, and Viking Society in 500–1250 CE (VIKINGS).

“Our findings demonstrate that climate already changed in the past—it is not something new—and societies had to adapt to it already 1,500 years ago.”“Our findings demonstrate that climate already changed in the past, it is not something new, and societies had to adapt to it already 1,500 years ago. This shows that we also have to adapt to the rapid climate change we observe today in order to maintain and improve our food production,” said Manon Bajard of the University of Oslo, who presented the research in April at the 2021 general assembly of the European Geosciences Union.

Bajard’s team analyzed sediments from Lake Ljøgottjern in southeastern Norway. Lake Ljøgottjern is located next to Rakni’s mound, one of the largest barrows in northern Europe. Previous archaeological studies have dated the mound’s construction to the mid-6th century and found extensive evidence of farming and food preparation activities in the area.

Constructed between the 5th and 6th centuries, Rakni’s mound is one of the largest barrows in northern Europe and near the site of new research into the farming practices of pre-Viking societies. Credit: Øyvind Holmstad/Wikimedia, CC BY-SA 3.0

Bajard and her colleagues steered a raft to Ljøgottjern’s deepest section, where lake bed sediments are least affected by lateral flows. By lowering a weighted tube, the team retrieved a 6-meter sediment core. Muds have been accumulating at Lake Ljøgottjern since the last glacial retreat more than 10,000 years ago, so the sediments contain clues about the area’s history.

Mud cores from Lake Ljøgottjern contain sediments dating back to the last glacial retreat. Credit: VIKINGS project/University of Oslo

To analyze the core, Bajard’s group used carbon-14 dating to identify the section corresponding to 300–800. Past temperature fluctuations were reconstructed from calcium deposits: During warmer periods, there was more biotic activity in the lake, which resulted in a greater accumulation of calcium carbonate deposits on the lake bed.

The key finding was that warmer phases were dominated by the cultivation of crops, whereas cooler phases were dominated by livestock farming. Manon’s team, as well as archaeologists working at Rakni’s mound, suggest that it is, perhaps, not surprising that farmers would rely more on animals during colder periods (when crop yields are reduced) and are reexamining archaeological evidence to support this theory.

Pollen grains in the core revealed the types and extents of staple crops, which included rye, wheat, and barley. Overall, cold periods corresponded to reduced crop yields, with barley being the most affected by climate shifts.

Animal grazing near the lake was inferred from the core’s quantity of Sordaria, fungi that thrive on animal feces. Small quantities of DNA recovered from the core also revealed the presence of cows, pigs, and sheep.

Strategic Farmers

Bajard said Viking ancestors may have strategically prioritized the best land close to the community for crops. During warmer periods when harvests were more robust, animals were relocated to areas less suitable for crops, perhaps land that was still forested.

“Later, during the Viking Age and Middle Ages, both activities were occurring at the same time, but it was much warmer then, so the cultivation area could have been extended,” Bajard said.

“Over generations, hard-won experience taught a farmer what works and [that] experiments could be fatal.”To build a more complete picture of how farming practices evolved, Bajard’s team will try to collect more DNA samples from near the lake to start quantifying how the mix of animal types varied over time.

Peter Hambro Mikkelsen, an environmental archaeologist at Aarhus University in Denmark not involved in the VIKINGS research, said food producers today might learn from this community’s ability to diversify. “Over generations, hard-won experience taught a farmer what works and [that] experiments could be fatal. As opposed to modern farming where specialization is the key to large-scale production, traditional agriculture KNOWS that when weather fails, livestock can perish—and the enemy can be at the gates of one’s village.”

—James Dacey (@JamesDacey), Science Writer

The Earth and space sciences present ideal use cases for machine learning (ML) applications because the problems being addressed are globally important and the data are often freely available, voluminous, and of high quality.Machine learning (ML), loosely defined as the “ability of computers to learn from data without being explicitly programmed,” has become tremendously popular in technical disciplines over the past decade or so, with applications including complex game playing and image recognition carried out with superhuman capabilities. The Earth and space sciences (ESS) community has also increasingly adopted ML approaches to help tackle pressing questions and unwieldy data sets. From 2009 to 2019, for example, the number of studies involving ML published in AGU journals approximately doubled.

In many ways, ESS present ideal use cases for ML applications because the problems being addressed—like climate change, weather forecasting, and natural hazards assessment—are globally important; the data are often freely available, voluminous, and of high quality; and computational resources required to develop ML models are steadily becoming more affordable. Free computational languages and ML code libraries are also now available (e.g., scikit-learn, PyTorch, and TensorFlow), contributing to making entry barriers lower than ever. Nevertheless, our experience has been that many young scientists and students interested in applying ML techniques to ESS data do not have a clear sense of how to do so.

The Tools of the Trade

An ML algorithm can be thought of broadly as a mathematical function containing many free parameters (thousands or even millions) that takes inputs (features) and maps those features into one or more outputs (targets). The process of “training” an ML algorithm involves optimizing the free parameters to map the features to the targets accurately.

There are two broad categories of ML algorithms relevant in most ESS applications: supervised and unsupervised learning (a third category, reinforcement learning, is used infrequently in ESS). Supervised learning, which involves presenting an ML algorithm with many examples of input-output pairs (called the “training set”), can be further divided, according to the type of target that is being learned, as either categorical (classification; e.g., does a given image show a star cluster or not?) or continuous (regression; e.g., what is the temperature at a given location on Earth?). In unsupervised learning, algorithms are not given a particular target to predict; rather, an algorithm’s task is to learn the natural structure in a data set without being told what that structure is.

Supervised learning is more commonly used in ESS, although it has the disadvantage that it requires labeled data sets (in which each training input sample must be tagged, or labeled, with a corresponding output target), which are not always available. Unsupervised learning, on the other hand, may find multiple structures in a data set, which can reveal unanticipated patterns and relationships, but it may not always be clear which structures or patterns are “correct” (i.e., which represent genuine physical phenomena).

Applications in Earth and Space Sciences

Books and classes about ML often present a range of algorithms but leave people to imagine specific applications of these algorithms on their own.Books and classes about ML often present a range of algorithms that fall into one of the above categories but leave people to imagine specific applications of these algorithms on their own. However, in practice, it is usually not obvious how such approaches (some seemingly simple) may be applied in a rich variety of ways, which can create an imposing obstacle for scientists new to ML. Below we briefly describe various themes and ways in which ML is currently applied to ESS data sets (Figure 1), with the hope that this list—necessarily incomplete and biased by our personal experience—inspires readers to apply ML in their research and catalyzes new and creative use cases.

Fig. 1. Ten ideas for applying machine learning (ML) in the Earth and space sciences, roughly organized by the degree of involvement of physics-based models (horizontal scale) and the degree to which ML codes are available and readily applicable versus being in development and requiring significant customization (vertical scale). Credit: Jacob Bortnik 1. Pattern Identification and Clustering

One of the simplest and most powerful applications of ML algorithms is pattern identification, which works particularly well with very large data sets that cannot be traversed manually and in which signals of interest are faint or highly dimensional. Researchers, for example, applied ML in this way to detect signatures of Earth-sized exoplanets in noisy data making up millions of light curves observed by the Kepler space telescope. Detected signals can be further split into groups through clustering, an unsupervised form of ML, to identify natural structure in a data set.

Conversely, atypical signals may be teased out of data by first identifying and excluding typical signals, a process called anomaly or outlier detection. This technique is useful, for example, in searching for signatures of new physics in particle collider experiments.

2. Time Series and Spatiotemporal Prediction

An important and widespread application of supervised ML is the prediction of time series data from instruments or from an index (or average value) that is intended to encapsulate the behavior of a large-scale system. Approaches to this application often involve using past data in the time series itself to predict future values; they also commonly involve additional inputs that act as drivers of the quantities measured in the time series. A typical example of ML applied to time series in ESS is its use in local weather prediction, with which trends in observed air temperature and pressure data, along with other quantities, can be predicted.

In many instances, however, predicting a single time series of data is insufficient, and knowledge of the temporal evolution of a physical system over regional (or global) spatial scales is required. This spatiotemporal approach is used, for example, in attempts to predict weather across the entire globe as a function of time and 3D space in high-capacity models such as deep neural networks.

3. Emulators and Surrogates

Physics-based simulations can take days or weeks to run on even the most powerful computers. An alternate solution is to train ML models to act as emulators for physics-based models.Traditional, physics-based simulations (e.g., global climate models) are often used to model complex systems, but such models can take days or weeks to run on even the most powerful computers, limiting their utility in practice. An alternate solution is to train ML models to act as emulators for physics-based models or to replicate computationally intensive portions within such models. For example, global climate models that run on a coarse grid (e.g., 50- to 100-kilometer resolution) can include subgrid processes, like convection, modeled using ML-based parameterizations. Results with these approaches are often indistinguishable from those produced by the original model alone but can run millions or billions of times faster.

4. Boundary or Driving Conditions

Many physics-based simulations proceed by integrating a set of partial differential equations (PDEs) that rely on time-varying boundary conditions and other conditions that drive interior parts of the simulation. The physics-based model then propagates information from these boundary and driver conditions into the simulation space—imagine, for example, a 3D cube being heated at its boundary faces with time-varying heating rates or with thermal conductivity that varies spatiotemporally within the cube. ML models can be trained to reflect the time-varying parameterizations both within and along the simulation boundaries of a physical model, which again may be computationally cheaper and faster.

5. Interpretability and Knowledge Discovery

If a spatiotemporal ML model of a physical system can be trained to produce accurate results under a variety of input conditions, then the implication is that the model implicitly accounts for all the physical processes that drive that system, and thus, it can be probed to gain insights into how the system works. Certain algorithms (e.g., random forests) can automatically provide a ranking of “feature importance,” giving the user a sense of which input parameters affect the output most and hence an intuition about how the system works.

More sophisticated techniques, such as layerwise relevance propagation, can provide deeper insights into how different features interact to produce a given output at a particular location and time. For example, a neural network trained to predict the evolution of the El Niño–Southern Oscillation (ENSO), which is predominantly associated with changes in sea surface temperature in the equatorial Pacific Ocean, revealed that precursor conditions for ENSO events occur in the South Pacific and Indian Oceans.

6. Accelerating Inversions

A ubiquitous challenge in ESS is to invert observations of a physical entity or process into fundamental information about the entity or the causes of the process (e.g., interpreting seismic data to determine rock properties). Historically, inverse problems are solved in a Bayesian framework requiring multiple runs of a forward model, which can be computationally expensive and often inaccurate. ML offers alternative methods to approach inverse problems, either by using emulators to speed up forward models or by using physics-informed machine learning to discover hidden physical quantities directly. ML models trained on prerun physics-based model outputs can be used for rapid inversion.

7. Creating High-Resolution Global Data Sets

Satellite observations often provide global, albeit low-resolution and sometimes indirect (i.e., proxy-based), measurements of quantities of interest, whereas local measurements provide more accurate and direct observations of those quantities at smaller scales. A popular and powerful use for ML models is to estimate the relationship between global proxy satellite observations and local accurate observations, which enables the creation of estimated global observations on the basis of localized measurements. This approach often includes the use of ML to create superresolution images and other data products.

8. Uncertainty Quantification

Typically, uncertainty in model outputs is quantified using a single metric such as the root-mean-square of the residual (the difference between model predictions and observations). ML models can be trained to explicitly predict the confidence interval, or inherent uncertainty, of this residual value, which not only serves to indicate conditions under which model predictions are trustworthy (or dubious) but can also be used to generate insights about model performance. For instance, if there is a large error at a certain location in a model output under specific conditions, it could suggest that a particular physical process is not being properly represented in the simulation.

9. Physics-Informed Neural Networks

Domain experts analyzing data from a given system, even in relatively small quantities, are often able to extrapolate the behavior of the system—at least conceptually—because of their understanding of and trained intuition about the system based on physical principles. In a similar way, laws and relationships that govern physical processes and conserved quantities can be explicitly encoded into neural network algorithms, resulting in more accurate and physically meaningful models that require less training data.

10. Finding and Solving Governing Equations

In certain applications, the values of terms or coefficients in PDEs that drive a system—and thus that should be represented in a model—are not known. Various ML algorithms were developed recently that automatically determine PDEs that are consistent with the available physical observations, affording a new and powerful discovery tool.

In still newer work, ML methods are being developed to directly solve PDEs. These methods offer accuracy comparable to traditional numerical integrators but can be dramatically faster, potentially allowing large-scale simulations of complex sets of PDEs that have otherwise been unattainable.

Addressing Urgent Challenges

The Earth and space sciences are poised for a revolution centered around the application of existing and rapidly emerging ML techniques to large and complex ESS data sets being collected. These techniques have great potential to help scientists address some of the most urgent challenges and questions about the natural world facing us today. We hope the above list sparks creative and valuable new applications of ML, particularly among students and young scientists, and that it becomes a community resource to which the ESS community can add more ideas.

Acknowledgments

We thank the AGU Nonlinear Geophysics section for promoting interdisciplinary, data-driven research, for supporting the idea of writing this article, and for suggesting Eos as the ideal venue for dissemination. The authors gratefully acknowledge the following sources of support: J.B. from subgrant 1559841 to the University of California, Los Angeles, from the University of Colorado Boulder under NASA Prime Grant agreement 80NSSC20K1580, the Defense Advanced Research Projects Agency under U.S. Department of the Interior award D19AC00009, and NASA/SWO2R grant 80NSSC19K0239 and E.C. from NASA grants 80NSSC20K1580 and 80NSSC20K1275. Some of the ideas discussed in this paper originated during the 2019 Machine Learning in Heliophysics conference.

Author Information

Jacob Bortnik (jbortnik@gmail.com), University of California, Los Angeles; and Enrico Camporeale, Space Weather Prediction Center, NOAA, Boulder, Colo.; also at Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder

Beneath Florida’s cities and swamps lies a complex network of karst conduits. The same chemical weathering that carves truck-sized tunnels through the calcium carbonate rock also leads to sinkholes at the surface. For Florida insurance agents, sinkholes are a headache. But for the state’s hydrogeologists, every sinkhole is an opportunity to understand the aquifer below.

Sinkholes allow surface water, as well as contaminants, to flood into an aquifer. By mapping the network of entry points and exit springs, hydrogeologists can better understand the underground system and better protect drinking water at the source. That understanding is important to populations outside Florida: Karst aquifers provide drinking water for 25% of people on Earth.

Isotope analysis helps hydrogeologists trace water origins, but the technique’s use has generally been limited to sinkhole lakes and springs no more than 4 kilometers apart. Recently, however, a team in Florida used isotope ratios to connect points 32 kilometers apart. It’s the farthest hydraulic connection between a sinkhole and a spring yet documented and the first connection involving a first-magnitude spring (those discharging an average of 100 cubic feet—2.8 cubic meters—of water per second).

“Dyeing” to Know Greenhalgh introduces tracer dye into the sinkhole at Lake Miccosukee. Credit: Ming Ye

“Normally, for hydrogeology, we only care about subsurface water flows,” explained Ming Ye, a hydrogeologist at Florida State University and a coauthor of the research, published in Groundwater in April. But when studying sinkholes, he said, scientists have to consider surface water flows, too.

In 2010, two sinkholes appeared at the edge of Lake Miccosukee in north central Florida, and in 2018 Ye and his colleagues used a technique called dye tracing to detect water flows from sinkhole to spring.

Dye tracing requires guesswork, Ye said. It’s “like hunting a treasure.”

Florida Geological Survey technicians poured lime-green fluorescein dye into the sinkholes, then placed monitors at likely outflow sites downslope. None detected the diluted dye. The researchers also placed cheaper charcoal packets at less likely locations. One of those sites, Natural Bridge Spring, 32 kilometers away, turned up evidence of the dye.

Heavy Signatures

Connecting the dots with dye was only step one. The team next explored whether isotopes could also establish the hydraulic connection.

Isotope signatures are a common method for assessing groundwater origins. A small percentage of oxygen molecules are 18O, “heavy isotopes” that evaporate less readily than common 16O isotopes, giving lake signatures a substantially higher proportion of 18O than groundwater or rainfall. Knowing the isotope signatures of the sinkhole, spring, and groundwater, the researchers determined that roughly 8.5% of Natural Bridge Spring water originated at Lake Miccosukee.

That mixing fraction was based on pairs of water samples. Using weekly water samples, the researchers compared isotopes from Natural Bridge Spring to isotopes collected earlier at Lake Miccosukee. They found that the dye reached the spring 18 days after application at Lake Miccosukee, and the presence of the dye at Natural Bridge Spring peaked at day 34. Removing the effects of rainfall, the isotope ratios at both sites were perfectly correlated 35 days apart, demonstrating a hydraulic connection and validating the expected transit time.

Connecting Dots Underground

The researchers now plan to reverse the process, tying a spring back to its source and using isotopes as a primary confirmation method.

The method would remove the guesswork of dumping dye into a sinkhole and expand the understanding of the karst aquifer at lower cost and effort.By collecting regular water samples from area springs and sinkhole lakes, researchers can look for isotope ratio trends over time. Possible connections can be confirmed with dye tracing. The method would remove the guesswork of dumping dye into a sinkhole and expand the understanding of the karst aquifer at lower cost and effort, researchers said.

“What they’re exposing here is a very sound method to backtrack type of infiltration,” said Joanna Doummar, an assistant professor of hydrogeology at American University of Beirut who was not involved in the research.

Using isotopes to connect the dots allows hydrogeologists a wider window of sampling and evidence. “[Dye] tracing is very important, but it’s very static,” said Doummar. “It doesn’t tell you how this is varying through time.”

Ultimately, knowledge of the subsurface system will help water managers protect spring water at its upslope entry point. Knowing the transit time and mixing fraction will also help managers gauge threats, as contaminants may decay or dilute while traveling through the aquifer.

“It’s really important, given the heterogeneity of this infiltration, to detect all these areas and identify all the transit times,” Doummar said. “With the assumptions that [Ye and his team] have taken, which are very legitimate, they have exposed a method to backtrack the percentage of water coming from the sinkhole.”

Until the system is developed, Ye and his collaborators will continue treasure hunting. A 1,618-hectare Florida lake completely drained into a sinkhole in early June, offering another chance to explore the aquifer with bags of organic dye.

—J. Besl (@J_Besl), Science Writer

Methane is a potent greenhouse gas, second to carbon dioxide in its overall influence on anthropogenic warming at Earth’s surface, so scientists are keen to keep a close eye on emissions of the gas, both natural and anthropogenic. Thorough records of methane emissions from the landscape allow researchers to better understand processes that contribute emissions, forecast changes in ecosystems, validate models of land–atmosphere exchanges, and estimate regional and continental methane budgets. But collecting such records from a variety of environments over broad spatial and temporal scales is a massive endeavor. Aiding in this task is the National Ecological Observatory Network (NEON).

The National Ecological Observatory Network’s capabilities and data can aid scientists in answering pressing questions about how our environment functions and how it is changing.NEON, which comprises numerous sites distributed across the United States and Puerto Rico, will have its newly implemented and community-championed methane concentration data online and openly available by summer 2022. The addition of methane concentration measurements at NEON’s 47 terrestrial sites—spanning the observatory’s 20 designated ecoclimatic domains—will support and facilitate new research investigating greenhouse gas emissions and budgets across the observatory.

Improving understanding of methane emissions across the country is just one example of how NEON’s capabilities and data can aid scientists in answering pressing questions about how our environment functions and how it is changing. Incorporating feedback from the research community is fundamental to NEON’s role in promoting successful science, as is keeping the community updated on developments and pathways for using the observatory. With this in mind, we describe here the available tools and ways to use NEON and invite you to leverage the observatory in your research.

What Is NEON?

NEON is a continental-scale observation facility designed to enable characterization and quantification of complex and rapidly changing ecological processes as well as forecasting of future conditions. The observatory network began construction in 2012 and entered its operational phase in 2019. Today the network includes 47 field sites distributed throughout the major terrestrial ecosystems of the United States and Puerto Rico, plus 34 freshwater aquatic sites located in streams, lakes, and rivers (Figure 1).

Fig. 1. NEON includes 47 field sites and 34 freshwater aquatic sites distributed throughout 20 designated ecoclimatic domains (numbered here) in the United States and Puerto Rico. Credit: NEON

Throughout the network, NEON instruments and staff collect environmental data to characterize trajectories of change in plants, animals, soils, nutrients, freshwater, and the atmosphere. This information composes NEON’s catalog of 181 open-access data products that can be freely downloaded via the NEON Data Portal. Identifying and implementing standardized infrastructure and instrumentation capable of collecting data across a variety of field environments—as well as methodologies that allow for direct comparisons of data among all sites—was a demanding undertaking. For example, installing an array of soil sensors in ecosystems ranging from deserts to tundra required significant engineering flexibility and site-specific expertise. Also challenging were designing and constructing a cyberinfrastructure framework capable of ingesting, processing, formatting, and serving all of NEON’s data and associated metadata in a scalable manner.

NEON also provides an expansive collection of physical specimens and samples that are available to the research community for analysis. Each year, NEON catalogs more than 100,000 individual specimens and samples of soils, vegetation, microbes, insects and other invertebrates, and tissue (e.g., blood, hair, DNA) from fish and other vertebrates into searchable and publicly available archives at the NEON Biorepository Data Portal.

Other archives to which NEON contributes include the Megapit Soil Archive (soils collected and characterized from each NEON site during their initial construction), the NEON Initial Characterization Soils Archive (soils collected during initial operations in partnership with the Natural Resources Conservation Service), and tick samples in the U.S. National Tick Collection at Georgia Southern University.

Leveraging Assignable Assets

The scientific community can use and supplement the observatory’s resources through the Assignable Assets (AA) program. This program allows researchers to leverage the combination of NEON’s robust and diverse standardized observations with the flexibility and creativity of community-led research to advance and innovate in their work (see sidebar).

Resources available via the AA program include specialized equipment and boots-on-the-ground research support at NEON sites. For example, the AA program maintains a fleet of five Mobile Deployment Platforms (MDPs), which are fully instrumented (they largely use the same sensors as NEON’s fixed sites) and can be deployed in environments across the network, provided there is sufficient road access.

A Mobile Deployment Platform (MDP) instrument hut (left) and an instrumented tower (right) are seen here during commissioning at the NEON Kings Creek site at the Konza Prairie Biological Station in Kansas (aquatic sensors not shown). NEON’s fleet of five MDPs use the same sensors, processing algorithms, and data quality assurance/quality control criteria as standard NEON sites, allowing researchers to generate standardized NEON data, but they can be rapidly deployed to recent disturbance events or ongoing research projects. Credit: Michael SanClements

Collaborating with NEON

The AA program serves as the entry point to collaborations with NEON, and projects are initiated by filing a formal request through NEON’s website. NEON evaluates not the scientific merit of projects but, rather, the feasibility of completing them while maintaining the efficacy of core NEON measurements.

The AA program is “cost-recoverable,” meaning NEON requires reimbursement for costs (e.g., labor) associated with approved projects. As such, we request that principal investigators (PIs) work with the NEON AA team to ensure the feasibility of their project and to fine-tune expected costs for inclusion in proposals to funding agencies.

NEON collaborators (left to right) Dave Bowling, Zoe Pierrat, and Troy Magney install a photosynthesis spectrometer on the NEON tower at Ordway-Swisher Biological Station in Melrose, Fla., as part of an AA project. The spectrometer, which measures solar-induced chlorophyll fluorescence and changes in plant pigments, will be used to develop better satellite-based methods for measuring photosynthesis from space. Credit: Troy Magney

The level of coordination and planning needed for proposed AA projects scales with the complexity of the request. A simple request, such as a researcher or educational group asking to arrange a site tour or an introduction to NEON staff at a domain support facility, is typically accommodated within 2 weeks. A moderately complex request could involve, for example, a PI asking to deploy simple temperature monitors (iButtons) and collect soil or sediment samples at a few sites over one or two field seasons. In this case, we would encourage the researcher to engage the AA program at least 6 weeks prior to any proposal deadlines to ensure feasibility, evaluate costs, and, if needed, secure a letter of support to include in funding proposals.

For even more substantial requests involving, for example, deployment of an MDP, addition of specialized sensors to multiple NEON towers, or an extensive multisite and multiyear field sampling campaign, PIs should begin coordination and planning with the AA program several months prior to any proposal submission deadline. This extended timeline is necessary, as PIs must work closely with the observatory to iterate deployment details (e.g., locations, dates, and timelines); facilitation of permits and permissions; schedules; and access to infrastructure, power, and communications.

An MDP allows scientists to incorporate standardized NEON measurement systems—atmospheric, terrestrial, and aquatic—into planned or ongoing research projects at stand-alone sites or sites within other research networks, such as the Long-Term Agroecosystem Research Network, Long Term Ecological Research (LTER) Network, AmeriFlux, or the Critical Zone Collaborative Network. MDPs use data processing algorithms and quality assurance/quality control criteria identical to the instruments at NEON field sites. MDPs thus help tie external research sites into the NEON network and can expand data synthesis, hypothesis testing, and the applicability of research findings to larger regional or even continental scales.

MDPs can also serve as test beds for new technologies. This summer, NEON will deploy an MDP to Ohio State University as part of a proof-of-concept artificial intelligence (AI) and cyberinfrastructure project that will serve as the basis for an adaptive AI system for in-the-field environmental sensing.

NEON also has three Airborne Observation Platforms (AOPs), each comprising a sophisticated remote sensing package deployed on a Twin Otter aircraft. These payloads include a high-resolution digital camera; lidar instrumentation to provide 3D structural information about the landscape; and an imaging spectrometer to allow identification of plant species and communities, map vegetation health, and provide data on canopy chemical constituents.

For example, in work supported by the National Science Foundation (NSF) in conjunction with the University of Colorado (CU) Boulder, an AOP was used to map postfire burns at several sites where fire emissions had been previously observed during the CU Boulder Biomass Burning Fluxes of Trace Gases and Aerosols campaign. This research aimed to relate wildfire emission characteristics to ecosystem parameters to improve the prediction of environmental and human health impacts from wildfires. AOP data provided information on total area burned and allowed partners from the U.S. Forest Service to calculate biomass lost.

Through the AA program, scientists can request an MDP or flight time with the AOP, request samples, coordinate visits to NEON field sites to conduct their own sampling campaigns, and deploy their own instruments to existing NEON infrastructure [e.g., Kramer and Chadwick, 2018; Chlus et al., 2020; Dangal and Sanderman, 2020; Hall et al., 2020; Zhang et al., 2021]. NEON’s field science staff and 18 domain support facilities are additional resources and can help principal investigators (PIs) with logistics, sample collection and processing, and sensor deployment [e.g., Blair et al., 2020; Chadwick et al., 2020; Chaudhary et al., 2020; Heckman et al., 2020; Seyednasrollah et al., 2021].

Targets of Opportunity

Bala Chaudhary (rear) and Paul Metzler pose while installing dust collectors at the Niwot Ridge NEON site in Colorado. The work is part of an Assignable Assets (AA) project to examine the role of wind in dispersing arbuscular mycorrhizal fungi [Chaudhary et al., 2020]. Credit: Paul MetzlerEvents like floods, fires, hurricanes, and earthquakes, or perturbations such as dramatic predator population shifts, can drive rapid ecological change and often present time-sensitive “targets of opportunity” for research [Whitman et al., 2021]. These disturbances often occur without warning and outside the boundaries of NEON sites. NEON’s mobile sensing systems offer the capacity to investigate targets of opportunity, and the AA program is equipped to expedite review of time-sensitive requests to help PIs take advantage of these fleeting research opportunities.In 2016, for example, the Chimney Tops 2 Fire burned 4,167 hectares of Great Smoky Mountains National Park, including the NEON site contained within the park’s boundaries. Leveraging rapid response funding from NSF, researchers worked with the NEON AA program to access the site immediately following the fire and collect samples for a study of pyrogenic carbon mobility [Matosziuk et al., 2020].

Evolving to Meet Community Needs

As NEON evolves over its planned 30-year life span, the observatory is working to increase the discoverability and accessibility of its core data products and infrastructure, while also building new inroads for assimilating and responding to community feedback. Sustaining core functionality while evaluating evolving scientific priorities, new methodologies, and advances in instrumentation and computing will be a continual challenge over the life span of the observatory. Creating channels for bidirectional communication with the community is, and will continue to be, critical to NEON’s ability to balance its resources with community priorities and shifting technologies, and we look forward to growing these conversations and collaborations over time.

To that end, NEON consults with a diverse set of 180 scientists and educators from across academia, government, and industry who make up more than 20 technical working groups (TWGs) and advise NEON on wide-ranging technical issues. TWG recommendations that involve changes to the scope or science requirements of NEON, or significant potential enhancements of it, are vetted with help from a community-based advisory body. These collaborative pathways allow for communication among NSF, NEON, and the scientific community and enable appropriate evolution of NEON to maintain its value in facilitating forefront science and education.

In addition, frequent workshops, presentations, facility tours, and other events—whether instigated within NEON or by members of the external research community—provide opportunities to optimize NEON. For example, over 2 days in 2019, the first NEON Science Summit, organized by CU Boulder, brought together 170 participants to explore major questions that can be addressed at continental scales using NEON data. NEON scientists and other staff provided guidance on data products and captured community feedback to enhance the delivery of NEON data, including, for example, through the creation of concise user guides for NEON data products.

With exciting developments on the horizon such as the NSF Center for Advancement and Synthesis of Open Environmental Data and Sciences, which will coordinate open data assets at NEON, LTER, and other programs to speed the research discovery process, we anticipate many new ways that NEON’s data and samples will be used across the community. We encourage researchers to explore opportunities to become involved with NEON, engage with our staff at meetings, and, most important, provide feedback to help us best meet the research community’s evolving needs.

Acknowledgments

NEON is sponsored by NSF and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON program. ORCID numbers for the authors are 0000-0002-1962-3561 (SanClements) and 0000-0002-8455-3213 (Mabee).

As Earth’s climate changes, so too will its oceans. Water temperatures are climbing, sea levels are rising, and ocean currents are shifting. Researchers typically use radar altimeters, which send a microwave pulse toward the ocean and measure the time it takes to rebound, to study the ocean surface, but the usefulness of altimetry data is limited to large areas and long temporal scales. In a new study, Le Goff et al. turn to maritime data to create a more precise picture of ocean currents.

Historically, data on ocean surface currents were based on ships’ logs, which tracked how intense currents affected a vessel’s course or speed. But today’s ships are equipped with much more precise geopositioning technologies. Merchant ships continually transmit their position, bearing, and speed through the Automatic Identification System (AIS), providing mountains of data that are more precise than ever before. Previous studies have shown that surface current velocities from AIS data match well with those predicted by high-frequency radar measurements.

Here the research team focused on the northern reaches of the Agulhas Current, a strong current that roughly follows the continental shelf break off the eastern coast of South Africa. The current, which has surface velocities of up to 2 meters per second, passes through a region with heavy maritime traffic. Using AIS data from vessels in transit through the region in 2016 and mathematical modeling, the team was able to reconstruct the surface current. The authors used surface current estimates collected by satellites and drifting buoys to validate the AIS-based observations. The study shows how AIS data could be a critical part of a more comprehensive current monitoring system.

According to the authors, the methods could be applied to other regions with heavy maritime traffic, such as the Mediterranean Sea. Monitoring ocean currents is critical: As Earth’s climate changes, so too will ocean surface currents, leading to changes in sea surface temperature and salinity that will ripple throughout marine ecosystems. (Journal of Geophysical Research: Oceans, https://doi.org/10.1029/2021JC017228, 2021)

—Kate Wheeling, Science Writer

This is an authorized translation of an Eos article. 本文是Eos文章的授权翻译。

2017年10月，天文学家首次发现了一个正在穿越太阳系的星际物体。这个星际来客被命名为 ‘Oumuamua，它是一个扁平的发光体，大约有半个街区那么长。

从那以后，科学家们一直在追踪许多线索，试图判定‘Oumuamua的组成，以及它的来源。一些人假设它是由氢冰或水冰组成的，而另一些人则推测它可能是一艘外星飞船。

如今，Jackson和Desch提出了一项新的分析，推测这个神秘物体主要是由氮冰组成的，可能是从另一个太阳系中围绕恒星运行的类冥王星的表面喷射出来的。

这项新分析考虑了‘Oumuamua 的大小、亮度、它在星际空间中所暴露的条件，以及它除重力影响之外的加速度分量。根据这些特征，研究人员缩小了潜在材料的范围，发现最符合所有线索的物质是氮冰。

作者指出，氮在我们的太阳系中不是一种外来物质。例如，冥王星和海王星最大的卫星海卫一都被氮冰包裹着。因此，‘Oumuamua可能起源于一颗类冥王星的系外行星，从其表面喷射出大量的冰碎片。

进一步的计算表明，‘Oumuamua可能是在大约5亿年前，在一个可能位于银河系英仙臂的太阳系中被发射到太空的。这颗系外行星的喷射可能是由于轨道不稳定造成的，类似于我们太阳系早期的历史。(Journal of Geophysical Research: Planets, https://doi.org/10.1029/2020JE006706, 2021)

—科学作家Sarah Stanley

This translation was made by Wiley. 本文翻译由Wiley提供。

Share this article on WeChat. 在微信上分享本文。

Sea-level rise is a global problem that is one consequence of the changing climate. The direct and indirect impacts of sea-level rise affect many sectors of society. Sea-level rise is projected to worsen in the coming decades, providing urgency for science-based information that is available to stakeholders to underpin adaptation measures. A commentary by Hamlington et al. [2021] addresses how NASA and NOAA, two government agencies in the United States that provide sea-level observations and science, can coordinate efforts to serve the needs of stakeholders. The authors recommend continued monitoring of sea-level change, development of integrated science products, improved collaboration with other organizations that distribute sea-level science and guidance on regional and local levels, and coordination of delivery of sea-level products to stakeholders with diverse needs. Coordination across NOAA and NASA on sea-level science has the added benefit of broader collaboration on issues of coastal hazards and resiliency.

Citation: Hamlington, B., Osler, M., Vinogradova, N. & Sweet, W. [2021]. Coordinated Science Support for Sea-Level Data and Services in the United States. AGU Advances, 2, e2021AV000418. https://doi.org/10.1029/2021AV000418

—Eileen Hofmann Editor, AGU Advances

Over recent years, technological advances have led to new types of seismological measurement strategies for both academic and industry applications, including those that allow for very dense (“large N”) sensor deployments. In particular, existing optical fiber cables, such as those used for internet communications, can be transformed into strings of thousands of quasi-seismometers along many kilometers of cable. Li et al. [2021] show the promise of doing this in a rapid response setting, where an objective might be to record seismic activity after an earthquake. By installing a cable interrogation unit at a single strand of fiber near the magnitude 7.1 2019 Ridgecrest event, the authors were able to dramatically increase the number of recorded aftershocks. This demonstrates the potential to complement permanent seismometer networks to allow zooming into fault zone structure and dynamics at unprecedented levels of detail. 

Citation: Li, Z., Shen, Z., Yang, Y. et al. [2021]. Rapid Response to the 2019 Ridgecrest Earthquake with Distributed Acoustic Sensing. AGU Advances, 2, e2021AV000395. https://doi.org/10.1029/2021AV000395

—Thorsten W. Becker, Editor, AGU Advances

This is an authorized translation of an Eos article. Esta es una traducción al español autorizada de un artículo de Eos.

El monitoreo ambiental es fundamental tanto para comprender el mundo como para desarrollar políticas para protegerlo. Las redes de observatorios ambientales (EONs,  por sus siglas en inglés) permiten a los científicos recopilar, compartir y sintetizar datos para hacer nuevos descubrimientos, así como decisiones políticas informadas a escalas regionales y globales. Pero las redes de observatorios no siempre están distribuidas de manera uniforme; algunas regiones del mundo están mejor monitoreadas que otras. Por lo tanto, los investigadores deben evaluar la representatividad de las EONs no solo para aumentar su número en regiones subrepresentadas, sino también para evaluar su aplicabilidad a cuestiones de investigación y políticas.

En un nuevo estudio, Villarreal y Vargas llevaron a cabo una evaluación de este tipo de FLUXNET, un EON conocido como la “red de redes” que mide el intercambio de materia, como dióxido de carbono, agua y metano, y energía entre la tierra y la atmósfera. Aunque investigaciones anteriores habían evaluado las EONs utilizando parámetros climáticos y de vegetación, aquí los autores evaluaron la representatividad de los sitios de covarianza de remolinos dentro de FLUXNET utilizando modelos de distribución de especies. El equipo se centró en América Latina, una región biodiversa con grandes impactos en los ciclos del carbono y del agua mucho más allá de sus fronteras.

A pesar de su enorme impacto ecológico, la densidad de los sitios FLUXNET en América Latina es menor que en los Estados Unidos o Europa. El equipo identificó 41 sitios de covarianza de remolinos registrados con FLUXNET en América Latina a partir de 2018 y evaluó la capacidad de la red para monitorear patrones de productividad primaria bruta (GPP, por sus siglas en inglés), evapotranspiración y variabilidad en múltiples factores ambientales, incluidos el clima, la topografía y el suelo. Luego, los autores utilizaron una técnica estadística multivariante para determinar cuántos sitios FLUXNET más son necesarios en América Latina para mejorar la representatividad de la red para GPP y evapotranspiración.

Descubrieron que los sitios FLUXNET existentes representaban casi la mitad de la GPP y más de un tercio de los patrones de evapotranspiración. Para el clima, el terreno y las propiedades del suelo, esos números fueron del 34%, 36% y 34%, respectivamente. Desafortunadamente, los datos de estos sitios no están ampliamente disponibles. Actualmente, señalan los autores, los modelos deben basarse en datos de sitios FLUXNET fuera de América Latina para hacer predicciones sobre patrones dentro de la región.

El análisis multivariado mostró que agregar 200 sitios de estudio en América Latina podría casi duplicar la representatividad general tanto de la GPP como de la evapotranspiración. Sin embargo, con sitios en una ubicación óptima, se podría lograr el mismo aumento con solo 60 sitios, aunque la incertidumbre sería mucho mayor.

Mientras tanto, los autores piden una mayor coordinación e intercambio de datos entre los investigadores de América Latina y advierten contra la “investigación en helicóptero”, en la que investigadores de instituciones de países desarrollados recopilan datos con poca o ninguna participación de los investigadores locales. En última instancia, las contribuciones locales serán fundamentales para aumentar la representatividad de los sitios FLUXNET en toda la región. (Journal of Geophysical Research: Biogeosciences, https://doi.org/10.1029/2020JG006090, 2021)

—Kate Wheeling, Escritora de ciencia

This translation by Daniela Navarro-Pérez (@DanJoNavarro) was made possible by a partnership with Planeteando. Esta traducción fue posible gracias a una asociación con Planeteando.

NASA’s Operation IceBridge (OIB) was an airborne mission to survey changing land and sea ice across the Arctic, Antarctic, and Alaska that operated between 2009 and 2021. OIB flew 15 different aircraft nearly one thousand times over 13 years with a variety of instruments to understand how the ice in those regions was changing, why those changes were occurring, and how we might project future changes. It was one of the largest and longest-running scientific airborne survey of the polar regions ever. A recent article published in Reviews of Geophysics examines the 13 year mission. We asked the authors about the findings from OIB and what these might mean for future missions.

What was OIB’s primary goal?

The mission’s primary goal was to bridge the nine-year gap in observations between two successive NASA satellites, ICESat, which operated from 2003 to 2009, and ICESat-2, which launched in 2018 and continues to operate today. These satellites deployed laser altimeters to survey the whole of the Earth. Without OIB, knowledge of changes in ice mass would’ve been substantially limited between 2009 and 2018, and our ability to interpret those changes would’ve suffered even more so.

What kinds of data were collected about land and sea ice, and what methods were used to collect them?

Because we were primarily concerned with the data gap in laser altimetry from these two satellites, we deployed a downward-pointing laser altimeter on every flight. Along with that core instrument, we also deployed radar sounders to measure ice and snow thickness, gravimeters to measure bathymetry, magnetometers to detect geologic boundaries, and cameras to detect changes in surface types (for example, open water leads between sea ice floes).

Summer melt on Greenland’s Steenstrup Glacier taken during OIB. Credit: NASA/John Sonntag

What were some of the most significant advances in our understanding of the polar cryosphere as a result of this program?

For glaciers and ice sheets, OIB dramatically improved knowledge of yearly changes in outlet glaciers, their total thickness, snowfall rates and their evolution over time, bathymetry both within fjords and beneath floating ice shelves, and the hydrology of water on the surface, within and beneath ice sheets.

For sea ice, OIB significantly advanced our understanding of the variability in sea ice freeboard, thickness and its snow cover across both space and time. The self-consistent and operational analyses of laser altimetry, imagery and snow radar measurements were especially important in making sense of sea ice properties.

Were there any surprising or unanticipated discoveries on this mission?

So many surprises! For ice sheets, the highlights included a method for densifying OIB thickness measurements within difficult-to-sound deep channels that was self-consistent with satellite data. OIB radar data also helped reveal the extent of a shallow firn aquifer within the Greenland Ice Sheet, how vulnerable many Greenland and Antarctic outlet glaciers were to ocean-driven melting at their grounding zones, and the dominance of surface melting in driving retreat of Alaskan glaciers. For sea ice, OIB data revealed that snow thickness on Arctic sea ice had decreased significantly since data were gathered manually decades ago.

NASA’s P-3 aircraft on the tarmac at Thule Air Base, northwestern Greenland. Credit: NASA/Goddard/Michael Studinger

Although the OIB mission is now complete, how will the data continue to be of use?

While our campaigns are now over, a few more datasets are still trickling in, and most OIB datasets have arguably yet to fully explored. All the data are archived at the National Snow Ice and Data Center, which is part of a set of NASA-sponsored archiving facilities that make the data available in perpetuity. OIB collected hundreds of terabytes of data, and it will take years if not decades to fully interpret it all. We expect the unexpected – new discoveries using OIB data – will continue for years to come.

That expectation formed part of our motivation in writing this review article. We want to enable future scientists who begin exploring OIB datasets – even just a few years from now – to understand why OIB was designed and conducted the way it was, and what its direct participants considered to be its most essential outcomes, so that those future scientists can put what they discover into context.

—Joseph A. MacGregor (joseph.a.macgregor@nasa.gov; 0000-0002-5517-2235), Linette Nicole Boisvert ( 0000-0003-4778-4765), and Brooke Medley ( 0000-0002-9838-3665), NASA Goddard Space Flight Center, USA

The changes to teaching and learning at colleges and universities that many of us thought would last a few weeks in the spring of 2020 have turned into more than a year’s worth of disruptions. For both students and instructors, these disruptions have interrupted, set back, and, in some cases, irrevocably altered personal and professional lives and relationships, and they have severely strained mental—if not also physical—health.

The forced adaptations have also exposed unresolved and problematic realities in academia that long predate the pandemic, leading to difficult discussions but also creating welcome space for fresh perspective and growth. We reflect here on some of the negative and positive outcomes we’ve seen over the past year, as informed by our own experiences with students and colleagues.

Displaced and Disrupted

When colleges and universities turned to remote instruction, many undergraduate students returned to family homes, where they lost the autonomy they had been cultivating.Pandemic disruptions to teaching, learning, and life took many forms. When colleges and universities instituted social distancing measures and turned to remote instruction, undergraduate students were rushed off campus. Many returned to family homes, where they were isolated from friends and lost the autonomy they had been cultivating while living independently. Subjected once again to household rules set by parents or other guardians, these students were essentially infantilized during the pandemic. Yet their institutions expected them to be mature adults and to keep to academic schedules as if nothing had changed. Many of our students, as they relayed to us, felt untethered, overwhelmed, and unable to sift through endless directions and FAQ pages from the schools about rapidly evolving pandemic protocols.

Meanwhile, graduate students lost access to facilities integral to their research, from offices to laboratory analytical equipment to field sites. They were expected to teach and learn online skillfully and to adjust without complaint. Their support networks became frayed as colleagues and mentors dispersed from campus.

For some students, the burdens of these changes were especially acute. We both work at large public institutions, where up to one quarter of our students are the first in their family to attend college and up to 20% are international students. These students’ lives were suddenly and disproportionately upended by displacement, underresourcing, isolation, and, in some cases, repatriation.

At the same time students were doing their best to adjust to the new landscape of higher education, so too were faculty and instructors. Among other challenges, individuals had to adapt in-person course materials, teaching styles, and mentoring duties to fully remote environments on the fly. They had to reconfigure research programs to account for pandemic restrictions. And many faced the added complexity of maintaining professional responsibilities while simultaneously caring full-time for loved ones also displaced from their usual routines. We, like many of our colleagues, often reminded ourselves of the phrase “I am not working at home because of the pandemic; I’m at home due to the pandemic—trying to work.”

Remote teaching brought important changes to student-teacher relationships. Prior to the pandemic, we took for granted the simple joys of greeting students when they arrived at class, helping facilitate discussions around our course content, and getting to know students—their career aspirations, their challenges, and their interests. During the pandemic, we have still held classes and office hours, conducted research, and mentored students—but all virtually. Although Zoom and other such tools are amazing technological innovations that have enabled us to perform our work, they tend to dull the emotional and personal connections that face-to-face contact builds.

Emotional Tolls

Although we hope the vaccines developed to protect against COVID-19 will enable a full return to prepandemic life, the experiences we have shared with students and colleagues throughout the pandemic will remain with us, with some hanging as shadows over the coming years of social and economic recovery. Of course, these experiences have also been influenced strongly by events not directly related to the pandemic, such as the attack on the U.S. Capitol and the murders of George Floyd and others as well as the large-scale demonstrations in support of racial justice. Among other effects, these events have brought heightened attention to systemic racism and injustice in many institutions, including our own, and have added substantially to the emotional and physical stress of the pandemic for many in academia, particularly people of color.

The pandemic has forced academia to grapple with declining mental health among students and faculty, a trend that began well before 2020.Against this backdrop, the pandemic has forced academia to grapple with declining mental health among students and faculty, a trend that began well before 2020 [National Academies of Sciences, Engineering, and Medicine (NASEM), 2021a], particularly in science. Research has shown that in many cases, student learning and grades have improved during the pandemic, although these successes came with emotional costs. Prior to COVID-19, in spring 2019, three out of five college students reported experiencing extreme anxiety, and two out of five reported debilitating depression sometime in the preceding 12 months [American College Health Association, 2019]. In the past academic year, the trends in mental health have drastically worsened [NASEM, 2021a] as students have been deprived of the ability to engage with others; to participate in educational extracurricular activities and travel; and to pursue many professional and personal opportunities such as internships, fieldwork, and spring break. Moreover, many of our students have contracted COVID-19, including students in our research groups and in all of the courses we teach, and those who have not tested positive themselves have still had to deal with the virus affecting friends and family.

Faculty, who have long faced tremendous dysfunction in career expectations and work-life balance—especially for early-career faculty, women, and faculty of color—are also depressed, stressed, and burned out [NASEM, 2021b]. As of last fall, almost 9 out of 10 faculty surveyed agreed (33%) or strongly agreed (54%) that our jobs had become more difficult, 40% reported considering leaving the profession, and 48% of that number were early-career faculty. These stark figures partly reflect the emotional toll of taking on roles as informal, mostly untrained, and often poorly equipped mental health counselors to our students, which left faculty and students at risk.

We put ourselves through secondary trauma in supporting our students, colleagues, family, and friends while trying to carry on ourselves and maintain our own well-being.Faculty members became critical elements in the support networks for many of our students, requiring us to share additional empathy and to develop new ways to connect, in virtual environments, with students suffering emotionally and physically. We also became critical conduits for sharing university-wide information, from academic schedule changes and new grading modalities to rent relief options in the community and plans for packing up dorms and apartments. This role required keeping up to date with frequently changing policies and information so we could share it clearly and quickly.

Make no mistake: This emotional work, called affective labor, is difficult—and it is labor indeed. Affective labor is the work associated with managing one’s own feelings when things are going to pieces around you—when others are upset, frightened, or angry. We put ourselves through secondary trauma in supporting our students, colleagues, family, and friends while trying to carry on ourselves and maintain our own well-being.

Because this care work has been borne mostly by women faculty and faculty of color, resulting impacts on careers—such as decreased research productivity and delayed promotions—will fall disproportionately on these groups and will affect academia for years to come.

Lights in the Tunnel

Despite the disruptions and added affective burdens placed on students and faculty throughout the pandemic, there have been some positive outcomes to emerge. We speak here not about the learned benefits of technology or of asynchronous learning and other pedagogical adaptations but, rather, of the emotional rewards we experienced during this time.

Students and faculty members bonded like teammates in spring 2020. We struggled with the technology needed for remote instruction, our students struggled with the technology, and we all learned it together. When pets, children, and spouses made visits to our home offices, our students loved seeing us get rattled, because it reminded them of our humanity. They started sharing their pets on screen, and everyone enjoyed getting to know more about one another. Students also shared the stresses of their family situations. We made as many adjustments as we could to help them get through each semester, including changing deadlines, amending or canceling assignments, and just simply listening to them.

Not surprisingly, the camaraderie waned as the pandemic progressed, and by the end of the spring 2021 semester, many students were exhausted from remote learning and the loss of the college environment. This transition only increased the emotional workload for faculty and led to increased frustration and fatigue.

The door to richer teaching and learning experiences has been opened during the pandemic.Nonetheless, the door to richer teaching and learning experiences has been opened during the pandemic. Faculty have opportunities to embrace the role we play in helping students transition to adulthood and to recognize that course content is not the only currency of value to our students. It humanizes us, and our students, when we take the time to get to know them, to open up ourselves, and to admit to the stresses, emotions, and frustrations with which we struggle.

Faculty in science, technology, engineering, and mathematics (STEM) disciplines have historically taken a pass on doing this sort of emotional work. In our classrooms, we traffic in content—observations, calculations, and hypotheses—not in personal stories and cultural issues. We have often told ourselves, “Science doesn’t see color or gender,” “I couldn’t possibly deal with racism because I teach science,” and “Science is not driven by society,” although in each case there is much evidence to the contrary. If we have learned nothing else from the pandemic, we have seen that both we and our students value a more personal approach to instruction.

Outside the classroom as well, there are many things that faculty can do to help themselves and each other: foster, renew, and make new connections with mentors, advisers, colleagues, friends, and family; and develop or continue activities that provide a sense of community among instructors. At the University of Michigan, for example, faculty have set up monthly teaching circles—held virtually during the pandemic—at both departmental and college levels. Teaching has often been a lonely endeavor and not the topic of hallway discussions at research universities, so these regular opportunities to meet have enabled needed support networks and chances to learn and grow professionally. The AGU Education section also provides resources and a venue in which to find, connect with, and support other Earth and space science faculty, both professionally as colleagues and personally as friends.

The affective labor of connecting more deeply with students and colleagues takes time and energy—but it matters. It can make a big difference in helping STEM faculty and their students recover from the myriad disruptions of the pandemic and reshape what postsecondary teaching and learning look like.



Before COVID, before the swine flu, there was the bird flu outbreak of the mid-2000s. An international group of scientists came together to combat the deadly virus, including Ilaria Capua, now director of the One Health Center of Excellence at the University of Florida (UF) in Gainesville. Little did she know that that experience would not be the most trying moment of her career.

In 2013, Capua was elected to national office in Italy, the only scientist to have been so. Her triumph would be short-lived, however, as she was charged in a criminal case in which plaintiffs accused her of being the mind behind illegal trafficking of viruses—of profiting off her profession. While the legal process dragged on, she was recruited by UF. A few weeks after moving to the United States, she was cleared of all charges.

In this episode of AGU’s podcast Third Pod from the Sun, AGU chatted with Capua about her work with viruses, overcoming a smear campaign, and the value of being surrounding by great peers and team members.

This episode was produced by Kelly McCarthy and Shane M. Hanlon and mixed by Kayla Surrey and Shane M. Hanlon.

—Shane M. Hanlon (@EcologyOfShane), Program Manager, Sharing Science, AGU

 

Episode Transcript

Shane Hanlon (00:01): Hi Nanci.

Nanci Bompey (00:02): Hi Shane.

Shane Hanlon (00:03): It’s good seeing you as always.

Nanci Bompey (00:04): Good seeing you via video again, yes.

Shane Hanlon (00:08): I know. I know. So, we’re still in a pandemic but do you mind me asking, are you vaccinated?

Nanci Bompey (00:16): No, fine to ask. Yes. Got my second vaccine last weekend, so by this coming weekend I’ll be good to go I guess.

Shane Hanlon (00:24): That’s very exciting, yeah.

Nanci Bompey (00:24): How about yourself?

Shane Hanlon (00:25): Yes. Yeah. We did a two shot one, my partner and I, and we… Actually, yesterday, as of this recording, was our two weeks. So, we’re officially out in the world. What’s yours? I want to ask you, what are you going to do? What’s on your list, the first thing you’re doing once you can?

Nanci Bompey (00:48): We were talking about that and I think it’s like you’re still kind of hesitant to do things even so.

Shane Hanlon (00:53): Sure.

Nanci Bompey (00:53): Which is kind of funny. But we are planning to go on a trip to see my mom.

Shane Hanlon (00:58): Oh, okay.

Nanci Bompey (00:58): Haven’t seen her in over a year or whatever it is. So, I’m going up in a couple of weeks to see her. So, that will be nice. We can actually go inside and have dinner and hang out.

Shane Hanlon (01:08): Yeah.

Nanci Bompey (01:08): So, yeah. What about you? Were you like, “We’re doing this when we’re good to go?”

Shane Hanlon (01:14): I want to go to the Drafthouse.

Nanci Bompey (01:17): To see a movie?

Shane Hanlon (01:18): Or something. Yeah. Yeah. So Nancy and I lived close to each other outside of DC and there’s this theater that’s a staple in our neighborhood and it’s like a dinner theater type thing. You can see movies or shows or whatever. And I haven’t been there in yeah, like a year and a half and they’re doing like small capacity and all of that, but yeah, I think we’re going to try to do something coming up soon. Try to make the best of it.

Nanci Bompey (01:38): Yeah, we talked about you know Dune is coming up in the fall and so Richard’s like the biggest Dune fan. So definitely go to the movie is which was a regular staple of ours, so yeah, same.

Shane Hanlon (01:51): Maybe we’ll make post pan… or at least for us, post-pandemic date of it.

Nanci Bompey (01:55): Yes.

Shane Hanlon (02:00): Welcome to the American Geophysical Union’s Podcast about the scientists and the methods behind the science. These are the stories you won’t read in the manuscript or hear in a lecture I’m Shane Hanlon.

Nanci Bompey (02:09): And I’m Nanci Bompey.

Shane Hanlon (02:11): And this is Third Pod From the Sun.

Shane Hanlon (02:15): Okay, so we don’t need to regale everyone with our plans Nanci. We can take that, as the corporate folks say, offline. I’m disgusted with myself. I wish people could see the face I just made. But we are talking about the pandemic, not just because we’re in it, but because our story for today is about another type of I guess non-human pandemic. Another type of-

Nanci Bompey (02:41): Outbreak. It was a… Yeah, yeah yeah yeah. Disease outbreak, I guess.

Shane Hanlon (02:45): Right, and so it’s bird flu. So to bring us more on this, we want to bring in the producer for this episode, Kelly McCarthy.

Kelly McCarthy (02:53): Hi Shane. How are you? Hi Nanci.

Nanci Bompey (02:55): Hi Kelly.

Shane Hanlon (02:57): So yeah, why don’t you just let us know what we’re chatting about today.

Kelly McCarthy (03:00): Yeah. So at the European Geosciences Meeting in 2019, we sat down with a virologist turned member of the Italian parliament who’s going to talk about her science and kind of her path today.

Ilaria Capua (03:15): Hello. My name is Ilaria Capua. Ilaria is the Italian for Hillary. It helps people remember. I’m the Director of the One Health Center of Excellence at the University of Florida in Gainesville. My favorite virus and the viruses I would say that I spend most of my career working with are influenza viruses. I was very active during the bird flu crisis, which occurred around the mid 2000s, and actually bird flu is still a significant problem in many parts of the world.

News Anchor (03:57): China mobilizes resources to combat a new strain of bird flu after a third death is reported while fears spread wider and faster than the disease itself.

News Anchor (04:07): Two-thirds of the 400 people who’ve contracted bird flu have died.

Ilaria Capua (04:12): And thanks to European leadership in their research division, my group, which was based in Padova in Italy, became over the years one of the leading groups in influenza viruses that could jump from animals to humans. And we were very active.

Shane Hanlon (04:37): I love this idea. This is like the scientific ideal, this collaboration and people working together coming to solve this giant problem. This is exactly how it’s supposed to work, right?

Kelly McCarthy (04:49): Exactly how it’s supposed to work, except as with any well-intentioned plan, people can misinterpret things and there can be some unintended negative outcomes.

Ilaria Capua (05:00): As it happens in life, you get sometimes unexpected requests and in 2013, I was asked by the Prime Minister in office at the time to run for election in the national elections. The reason why I was asked was because at the time, Mario Monti recognized that there was a very significant need of people coming from different areas of society and who were successful in their field to join the political debate. And so I agreed to do it. I ran for election and I was elected.

Kelly McCarthy (05:48): Were there any other scientists who were running at that time?

Ilaria Capua (05:53): No, I was the only one who was running at that time and I was very flattered that I was elected and I was very, very motivated to do things around a more meritocratic approach to science, around improving the way that funding was allocated. Again, trying to do things from a more meritocratic point of view. And then I was working on topics of relevance to me and of my areas of expertise, so mainly on emerging infections.

Ilaria Capua (06:40): Suddenly I was phoned up by a journalist and I was informed that there was this criminal case and that I was believed to be the criminal mind behind an illegal traffic of viruses and that I was being… I was basically trying to make personal profits out of my scientific profession. And of course this wasn’t… I mean, this wasn’t true and the criminal court case ended two-and-a-half years after the information was leaked to the press with verdict, which was that the facts never existed and therefore there was no case to answer, and actually that most of the facts that were narrated in the legal documents were non-existent or reality had been transformed.

Shane Hanlon (07:53): I can’t imagine, one being elected as a policymaker, that’s just-

Kelly McCarthy (07:57): The Prime Minister being like you should run for parliament

Nanci Bompey (08:00): And you’re the only scientist on this board on people.

Kelly McCarthy (08:04): Yeah, and you win.

Shane Hanlon (08:06): Yeah, and then during this process being accused of something that you didn’t do.

Kelly McCarthy (08:11): Right, I mean that whole situation is just wow.

Shane Hanlon (08:14): Yeah.

Nanci Bompey (08:15): Very frustrating.

Ilaria Capua (08:17): I had decided to run as a member of parliament, not because I wanted a political career, but because I wanted to do things for science. And so what I did was I was approached by the University of Florida who was looking for a director of their One Health Center. The University of Florida has recently developed to this preeminent recruitment campaign where they recruit scientists from different parts of the world and they were looking for someone with my experience and they were offering me a very interesting job. And so I decided to take it, although I had to say to them that I had this investigation which was pending on my head in Italy. I resigned as a member of parliament. I moved to Florida and after three weeks, the judge for preliminary investigation reviewed the papers and said that the facts were non-existent.

Ilaria Capua (09:23): And so three weeks after I got to the United States, I was completely cleared from all the accusations.

Nanci Bompey (09:34): Well, I mean that’s great. She went to the University of Florida with this stuff kind of hanging over her head, but they, not took a chance on her, but they knew that perhaps that the things weren’t true and they were confident in her.

Kelly McCarthy (09:46): I mean they reached out to her specifically because of her background and she talks a little bit about how grateful she is for the support from that team.

Ilaria Capua (09:53): I have to say that I have great gratitude to the University of Florida, to Jack Payne in particular, and Doug Archer, who are the people who wanted to recruit me. They did due diligence and what I found quite surprising was the fact that they did a few checks and they immediately figured out that it was all fake. And in fact, the investigation was so superficial that they mixed up the name of one virus with the name of another virus. And so it was clear that they didn’t really have a grasp of what was happening. And so for lay people, H7N1 and H7N3 are like similar viruses, but they’re not. They’re completely different viruses in our world.

Ilaria Capua (10:50): These things happen to scientists. Actually, there’s a prize which is awarded every year. It’s called a John Murdoch’s prize. And it’s in the name of the former editor of Nature and it’s about standing up for science and you would be surprised to see how many people are actually attacked or criminalized for doing their science.

Kelly McCarthy (11:22): How do you influence that world now? Do you feel a responsibility having had that experience yourself to continue to advocate for scientists around the world who might be experiencing this?

Ilaria Capua (11:35): So I know what it’s like. I know what it’s like to have your reputation literally ripped off from you and I think it’s one of the worst things that can happen to you. And that’s why I talk about it. I mean, it is important to share these experiences for how hard it can be, because it’s never easy to talk about this sort of, let’s say bumps in the road that you’ve had in your life. However, you also have to have the guts to behave as a senior scientist. I am a senior scientist and therefore I talk about the difficulties scientists can encounter. Because it is part of my job to inform younger scientists and mentor other faculty on issues like this.

Kelly McCarthy (12:33): So I had the opportunity to watch all of these young scientists come up to Ilaria after this talk she gave at the European Geosciences Union meeting, and it was really cool to see all these people from way outside her field just wanting to talk with her more and share their own stories. And she’s clearly an advocate and a mentor.

Nanci Bompey (12:51): Yeah, that’s great and it’s also interesting that like, obviously on this podcast and AGU, you think of oh we interview geoscientists, earth and space science, but it’s so broad. I guess the point is that all these science issues people have in common, but we also, geoscientists can help people learn about different… You know, it’s not just confined now anymore we realize to just studying one particular thing that has no effect on anything else. We have like stuff like geo health, how climate change is going to affect people’s health. It’s like a big emerging field and things like that.

Kelly McCarthy (13:28): Exactly. Yeah. And she actually shared a really good historical example about how that functions and working across disciplines.

Ilaria Capua (13:36): Let me give you an example. John Snow, who is not the guy of the Game of Thrones, but is the father of epidemiology who was an English man who discovered that cholera was transmitted through water. And he was the person who closed the water pump that was collecting water from the infected basin and overnight the deaths for cholera stopped. However, what is amusing is that John Snow, at his time, didn’t know that cholera was caused by a bacterium. I mean, they didn’t even have the tools to see what they were fighting.

Kelly McCarthy (14:24): Okay.

Ilaria Capua (14:26): But he had an intuition and the people who fixed the cholera problem were not scientists. They were the mayor, they were the police officers, they were a series of other people who were not involved in the medical profession and actually fixed the problem. And so where do I see us going? I see us going towards solutions that are not going to be driven only by the scientific community. They’re going to be driven by other people as well. And that’s why we need to engage. And this is something that I think scientists forget to tell their audiences, that we are scientists because we believe in a better world. And that is what motivates most of the scientists. And we should never forget this, regardless of what people out there say.

Ilaria Capua (15:43): So I think that scientists need to reposition themselves as how they are imagined by society. So I would like to launch a call to action to scientists in that okay some of us are nutters. Some of us are a little bit coo-coo. Some of us are nerds and geeks. But we are people who are motivated and are inspired by curiosity and about natural mechanisms of how things work. And so I think that we should actually, even if we haven’t achieved as much as we would’ve wanted, which happens in life, but we still have to be proud about being scientists.

Ilaria Capua (16:43): Of course not all scientists can be super scientists because that’s how distribution works. Some are good. Some are better. Some are super. But still, it’s the critical mass that makes a difference. It’s not the individual.

Nanci Bompey (17:09): So where are you falling on this distribution of scientists Shane? Are you good, better, or super? I’m going to go, you’re-

Shane Hanlon (17:17): I’m what?

Nanci Bompey (17:18): You’re good.

Shane Hanlon (17:19): That’s fine. I actually-

Nanci Bompey (17:21): I’m less than good considering I’m not a scientist anymore, but I know I shouldn’t put myself down like that.

Shane Hanlon (17:26): No, we’re always scientists, we’re just not always practicing.

Nanci Bompey (17:29): Yeah.

Shane Hanlon (17:29): That’s the distinction.

Nanci Bompey (17:30): Yes.

Shane Hanlon (17:30): Yes.

Nanci Bompey (17:31): But in all seriousness, I really like her thought here because it’s actually a lot of what… You know, in terms of the podcast, it’s this critical… she talks about this critical mass of science. Everyone has to be doing this stuff in order to move the science forward. And so you may not be the all-star science, but you are a little piece in this big scientific enterprise.

Shane Hanlon (17:47): Yeah. I mean, yeah, you don’t to be a big name or whatever else, but there’s a reason we do science and it’s knowledge, right?

Nanci Bompey (17:53): Yeah.

Shane Hanlon (17:53): So who cares who-

Nanci Bompey (17:55): Like this podcast. We’re just a little piece of this podcast enterprise moving the needle forward.

Shane Hanlon (18:00): We are doing our part to advance science communication. All right. That’s all from Third Pod From the Sun.

Nanci Bompey (18:09): Thanks so much to Kelly for bringing us this story. And of course to Ilaria for sharing her work with us.

Shane Hanlon (18:14): This podcast was produced by Kelly and mixed by Kayla Suri.

Nanci Bompey (18:19): We would love to hear your thoughts. Please rate and review us on Apple podcasts. You can listen to us wherever you get your podcasts and of course always at thirdpodfromthesun.com.

Shane Hanlon (18:28): Thanks all and we’ll see you next time.

Science at its Core • Cores 3.0: Future-Proofing Earth Sciences’ Historical Records   • Improving Access to Paleoclimate Data   • An Unbroken Record of Climate During the Age of Dinosaurs   • Narwhal Tusks Record Changes in the Marine Arctic   • Cold Curriculum for a Hot Topic   • The Catcher in the Ice   • Cutting to the Core  

We’ll probably never get a real Jurassic Park—and that’s almost certainly for the best—but we are learning quite a bit about what it was like to live during at least the final period of the dinosaurs.

In China’s Songliao Basin, a research team on a drilling project called SK (initiated in 2006) has recovered 8,200 total meters of sediments spanning the entire Cretaceous. During one phase they drilled as deep as 7,018 meters. Their work will give us a thorough and fascinating look at terrestrial climate change during a time of rapid evolutionary turnover.

The heart of the SK team’s research—and the theme of Eos’s July issue—is the study of cores. After completing the drilling phase last February, the team has now turned to inspecting their core samples. Read more in “An Unbroken Record of Climate During the Age of Dinosaurs,” where Chengshan Wang and colleagues explain what they’ve discovered about “Earth’s most intense greenhouse state of the past 150 million years” and what it could tell us about what humans are in for as our climate continues to rapidly change.

Through sediment cores and ice cores, permafrost cores, and even tree rings, scientists have discovered myriad vehicles that allow us to look into the past. Collecting these time machines can be enormously expensive and time-consuming and sometimes only through rare, if terrible, opportunities—such as the chance to collect 9-meter-diameter “cookies” from giant sequoias after loggers felled a third of what is now Sequoia National Park in California, as Thomas Swetnam explains in our feature story.

Given the investment in collecting them, what do researchers do with all these cores once they’ve completed their initial studies? They put them in core libraries, of course, for the benefit of future research. And much like our traditional community libraries, core libraries need support and funding to make sure they survive. In the feature linked above, we look at how several collection caretakers are “future-proofing” these records, sometimes in dramatic scenarios, such as when Tyler Jones rushed to protect a freezer of ice cores at the Institute of Arctic and Alpine Research, or INSTAAR, in Boulder, Colo., in 2013.

Finally, even the best-protected library can be challenging to use if there is no indexing system. Nikita Kaushal and colleagues write about their modern-day Dewey Decimal System for speleothems. Their clever standardization and categorization are already the basis of many papers by researchers who now have richer access to these paleoclimate cave specimens.

We finish off our look at core research with another delightful crossword puzzle from Russ Colson in the print issue. We hope you can find time to take a break, center yourself, and dig right into our core clues.

—Heather Goss (@heathermg), Editor in Chief

The Tethyan belt is a zone of tectonic activity and mountain ranges stretching from northwestern Africa and western Europe across Turkey, the Caucasus, and Iran to the southwest Pacific Ocean. It is the longest continuous orogenic belt on Earth. One of the sections of particular interest to geoscientists is the Mediterranean section due to its ongoing active tectonic activity.

A special collection published in Tectonics, Geodynamics, Crustal and Lithospheric Tectonics, and active deformation in the Mediterranean Regions, presents new and updated research on this section of the Tethyan belt. More than two dozen research papers explore subduction and mantle convection, volcanism and fluid circulation, structural geology and active tectonics, dynamic topography, and geomorphology. The volume is dedicated to Professor Renato Funiciello (1939–2009), who helped develop modern geological studies in Italy.

Geological science has the powerful ability to bridge gaps between different countries and cultures.Geological science has the powerful ability to bridge gaps between different countries and cultures. Renato Funiciello played a decisive role in creating these bridges.

Born in Libya, he was a true Mediterranean geologist, enthusiastic about both the sea and the science of rocks.

Renato’s life and work fits into a long standing tradition of cross-Mediterranean travel and activity, from the Roman Emperor, Septimius Severus, a North African from Leptis Magna (a Roman city in Libya) with a later career in Rome and responsible for expanding the Roman empire to its greatest extent to date, to Enrico Mattei, the post-war Italian industrialist who led Agip (the Italian national oil and gas company), negotiated agreements about the extraction of oil from Tunisia and Morocco, and after whom the trans-Mediterranean gas pipeline between Algeria and Italy is now named.

In Fall of 1980, two severe and deadly large earthquakes affected the Mediterranean region. The El Asnam event occurred in Algeria in October. This event was a 7.1 magnitude quake followed by a magnitude 6.2 aftershock, the largest in the Tell Atlas ranges for almost two centuries. The Irpinia earthquake occurred in Italy in November. This was a magnitude 6.9 quake, with three main shocks and as many as 90 aftershocks. These two events left thousands of people dead, injured, and displaced. For Renato, then a newly appointed lecturer in structural geology at the University of Rome, it was a unique opportunity to explore the significance of earthquake surface faulting. In the following period, he stimulated many lively discussions about it during different seminars and meetings all over Europe.

Renato generated a new spirit of research, setting out the fundamentals of crustal and lithospheric deformation in structural geology in collaboration with geophysicists. One could say that modern geology was born in Italy amongst a new group of young (at the time) and dashing geologists who now lead the fields of structural and earthquake geology. In fact, several contributions to this collection are from his former students.

Renato Funiciello, Professor of Geology at Università degli Studi Roma Tre (1993–2009). Photo courtesy of Francesca Funiciello

Renato had a large range of interests and contributed to many subfields of geology, ranging from lunar and planetary sciences, and seismic tomography to spatial geodesy, geo-archeology, and urban geology.

He also embraced the use of modern technologies in Earth sciences and applied them to the study of the Adria microplate (see Kiraly et al., 2018), magmatism in southwest Turkey (see Asti et al., 2019), seismic damage in Rome’s Colosseum area, recent volcanic activity at Albano Lake near Castelgandolfo (the Pope residence), and a geological tour of the Seven Hills of Rome.

His professional contributions to our field were far reaching. He was an author and co-author of more than 100 published scientific articles and was particularly committed to raising public awareness of geoscience and geo-risks.

In addition, he served as PI of a NASA project on lunar geology, President of the Scientific Council of the Italian National Research Council (CNR), Director of the Institute for Technologies Applied to Cultural Heritage (ITABC), Director of the International Institute of Geothermal Research (IIRG), and Vice President of the National Institute of Geophysics and Volcanology (INGV Rome).

This collection is a modest dedication to one of the greatest geologists and a dear colleague whom we remember with great fondness.

—Mustapha Meghraoui (m.meghraoui@unistra.fr;  0000-0002-3479-465X), Institut Terre & Environnement de Strasbourg, France

Science at its Core • Cores 3.0: Future-Proofing Earth Sciences’ Historical Records   • Improving Access to Paleoclimate Data   • An Unbroken Record of Climate During the Age of Dinosaurs   • Narwhal Tusks Record Changes in the Marine Arctic   • Cold Curriculum for a Hot Topic   • The Catcher in the Ice   • Cutting to the Core  

In September 2013, a major storm dumped a year’s worth of rain on the city of Boulder, Colo., in just 2 days. Walls of water rushed down the mountainsides into Boulder Creek, causing it to burst its banks and flood nearby streets and buildings.

Instead of trying to escape the flood, Tyler Jones, a biogeochemist at the Institute of Arctic and Alpine Research (INSTAAR) in Boulder, drove directly toward it. His motive? Mere meters from the overflowing creek, a large freezer housed the lab’s collection of precious ice cores.

“We didn’t know if the energy was going to fail in the basement,” Jones said. “So I am scrambling around with a headlamp on, less than a hundred yards from a major flood event, trying to figure out what is going on.”

The INSTAAR scientists were lucky that year, as their collection survived unscathed. But devastating core culls have happened in the past decade. In a 2017 freezer malfunction at the University of Alberta in Edmonton, Canada, part of the world’s largest collection of ice cores from the Canadian Arctic was reduced to puddles. “Thinking of those kinds of instances makes me lose sleep at night,” said Lindsay Powers, technical director of the National Science Foundation Ice Core Facility in Denver.

Collections of cores—including ice cores, tree ring cores, lake sediment cores, and permafrost cores—represent the work of generations of scientists and sometimes investments of millions of dollars in infrastructure and field research. They hold vast quantities of data about the planet’s history ranging from changes in climate and air quality to the incidence of fires and solar flares. “These materials cover anywhere from decades to centuries and even up to millions of years,” said Anders Noren, director of the Facilities for Continental Scientific Drilling and Coring in Minneapolis, which includes a library of core samples. “It’s a natural archive and legacy that we all share and can tap into—it’s a big deal.”

Historically, some individual scientists or groups have amassed core collections, and on occasion, centralized libraries of cores have emerged to house samples. But irrespective of the types of cores stored or their size, these collections have faced a series of growing pains. Consequently, facilities have had to adapt and evolve to keep pace and ensure that their collections are available for equitable scientific research.

“We spend a lot of time in science thinking about open access when it comes to data,” said Merritt Turetsky, director of INSTAAR. Scientists should be having similar conversations about open access to valuable core samples, she said. “It is important to make science fair.”

Cores and Cookies

After 30 years of collecting wood samples for his research, astronomer Andrew Ellicott Douglass founded the Laboratory of Tree-Ring Research (LTRR) in 1937. With its creation at the University of Arizona in Tucson, Douglass formalized the world’s first tree ring library. Its development in the years since is a paradigm for the way core libraries are subject to both luck and strategy.

Dendrochronologists use tools to extract cores from trees to date structures and reconstruct past events such as fire regimes, volcanic activity, and hydrologic cycles. In addition to these narrow cores, they can also saw across tree stumps to get a full cross section of the trunk, called a cookie.

At the Laboratory of Tree-Ring Research in Tuscon, Ariz, curators are cataloging a more than a century’s worth of wood samples. Credit: Peter Brewer

Douglass originally collected cores and cookies to study the cycle of sunspots, as astronomers had observed that the number of these patches on the Sun increased and decreased periodically. The number of sunspots directly affects the brightness of the Sun and, in turn, how much plants and trees grow. By looking at the thickness of the tree rings, Douglass hoped to deduce the number of sunspots in a given year and how that number changed over the years. Douglass also went on to date archaeological samples from the U.S. Southwest using his tree ring techniques. On the way, he amassed an impressive volume of wood.

Douglass’s successors at LTRR were equally fervent in their collection. Thomas Swetnam, the director of LTRR between 2000 and 2014, estimated that his collection of cores and cookies gathered in a single decade occupied about 100 cubic meters.

During the turn of the 20th century, loggers felled a third of the giant sequoias in what is now Sequoia National Park in California. The only upside to the environmental tragedy was that it afforded researchers like Swetnam, who studies past fire regimes, the opportunity to collect cookies. “We were able to go with very large chainsaws and cut slabs of wood out of these sequoia stumps, some of them 30 feet [9 meters] in diameter,” Swetnam said. “Then we would rent a 30-foot U-Haul truck, fill it up, and bring it back to the lab.”

Tree trunks, cores, and cookies are stored in a humidity-controlled environment at the Laboratory of Tree-Ring Research in Tuscon, Ariz. Credit: Peter Brewer

The laboratory’s collection catalogs about 10,000 years of history, Swetnam said. It also amounts to a big space issue. “We’re talking about probably on the order of a million samples, maybe more,” Swetnam said. “We’re not even sure exactly what the total count is.”

The tree ring samples had been temporarily stored under the bleachers of Arizona Stadium in Tucson for nearly 70 years, but with generous funding from a private donor, a new structure was built to house the laboratory and its collection in 2013. The building, shaped like a giant tree house, solved the space issue, and in 2017 the lab received further funding to hire its first curator, who was charged with the gigantean task of organizing more than a hundred years of samples.

“It is a very long term endeavor,” said Peter Brewer, the LTRR curator who now works with a 20-person team on the collection. Brewer set to standardizing the labeling for the samples and is the co-lead on an international effort to produce a universal data standard for dendrochronological data. With this in place, LTRR will soon be launching a public portal for its collections, where scientists can log on and request a sample loan. This portal will make the collection more accessible to researchers around the world.

Ice Issues

In the early 1900s, around the same time that Douglass was collecting his first wood samples, James E. Church devised a tool to sample ice cores 9 meters below the ground. By the 1950s, scientists were able to extract cores from depths of more than 400 meters in the Greenland Ice Sheet. In the following years, scientists have drilled deeper and deeper to extract and collect ice cores from glaciers around the world.

“Recovering ice from 2 miles beneath an ice sheet in extreme cold environments is a massive challenge. You can’t just go back and repeat that…. It’s a one-time deal.”Ice cores can reveal a slew of information, including data about past climate change and global atmospheric chemistry. “We’ve learned so much already about environmental challenges from ice cores, and we think that there is so much more to learn,” said Patrick Ginot of the Institute of Research for Development at the Institute of Environmental Geosciences in Grenoble, France.

Some labs, such as INSTAAR, maintain their own collections, but space can quickly become an issue, and there’s constant concern about keeping the samples frozen and safe. Taking into consideration the massive effort involved in securing a single ice core, each sample is akin to an irreplaceable work of art. “Recovering ice from 2 miles [3.2 kilometers] beneath an ice sheet in extreme cold environments is a massive challenge,” Jones said. “You can’t just go back and repeat that…. It’s a one-time deal.”

The National Ice Core Lab in Denver houses many ice cores collected by scientists on National Science Foundation–funded projects. The goal is to provide a fail-safe storage environment and open access to researchers wishing to use the samples. Denver’s altitude and low humidity make running the freezers more efficient, and a rolling rack system in a new freezer will increase storage capacity by nearly a third. The facility also has backups galore: “We have redundancy on everything, and everything is alarmed,” Powers said.

The carbon footprint of running giant freezers at −36°C is high, but the lab is in the process of installing a new freezer that uses carbon dioxide refrigeration, the most environmentally friendly refrigeration system on the market. “We are at work here promoting climate research, so we want to be using the best technology possible to have the lowest impact on our environment,” Powers said.

Science Without Borders

The ice core community has adapted to various challenges that come with sustaining their libraries and working toward making the samples available on an open-access basis. But other parts of the cryosphere community are still catching up, Turetsky said.

Turetsky collects hundreds of northern soil and permafrost cores each year with her INSTARR team, and scores of other permafrost researchers are amassing equal numbers of cores from across the United States and Canada on a yearly basis. The U.S. permafrost community has more samples than the U.S. ice core community—but still doesn’t have a centralized library.

“We can’t do our best science siloed by national borders. I would love to see sharing of permafrost samples or information be a type of international science diplomacy.”Turetsky said she is looking to learn from the ice core community while recognizing that the challenges are different for permafrost researchers. Because it is easier and less expensive to collect samples, the community hasn’t needed to join forces and pool resources in the same way the ice core community has, leading to a more distributed endeavor.

Turetsky’s vision is to establish a resource for storing permafrost samples that anyone can tap into, as well as for the U.S. permafrost community to come together to develop guiding principles for the data collected. The University of Alberta’s Permafrost Archives Science Laboratory, headed by Duane Froese, is a great example of a multiuser permafrost archive, Turetsky said. Ultimately, the community may need to think about a regional hub with international connections to propel scientific inquiry.

“We can’t do our best science siloed by national borders,” Turetsky said. “I would love to see sharing of permafrost samples or information be a type of international science diplomacy.”

A Race Against Time

The need for the cryosphere community (encompassing both ice core and permafrost researchers) to come together and collect data in such a way that they can be shared and used in the future has never been greater, Turetsky said. The Arctic is warming faster than anywhere else on the planet, and simultaneously warming sea ice, ice sheets, and permafrost have great potential to influence Earth’s future climate. “So not only are [ice and permafrost environments] the most vulnerable to change, they also will change and dictate our climate future,” Turetsky said.

In the worst-case scenario, the Arctic may lose all sea ice or permafrost, and scientists will lose the ability to collect core samples. “So it is a race against time to get cores, to learn, and to communicate to the public how dire the situation is,” Turetsky said.

“A good chunk of what we have no longer exists in the forests. All that is left are the representative pieces of wood that are in our archives.”Tree ring researchers are facing their own race against time, Swetnam said. As wildfires rage across the United States, scientists are trying to collect as much as possible from older trees before they are claimed by flames. “The history that’s contained in the rings is not renewable,” Swetnam said. “It’s there, and if it’s lost, it’s lost.”

That scientists may lose the ability to collect some samples makes maintaining core libraries and sharing their resources all the more important, Brewer said. “A good chunk of what we have no longer exists in the forests. All that is left are the representative pieces of wood that are in our archives.”

A Futuristic Vision

Recognizing threats posed by climate change, one group of cryosphere scientists has set out to create a visionary ice core library for future generations. Instead of housing core samples from around the world in one country, the group plans to store them in Antarctica, a continent dedicated to science and peace; the 1959 Antarctic Treaty specifies that “scientific observations and results from Antarctica shall be exchanged and made freely available.”

Ice cores stored in the temporary core storage in the underground ice cave constructed by the East Greenland Ice-Core Project. Credit: Tyler R. Jones/INSTAAR

And the ice cores won’t be stored in a building. They’ll be buried deep in the largest natural freezer of them all: the Antarctic Ice Sheet. This core library will act as a heritage data set, a legacy for future generations of scientists from all over the world. Researchers can access the cores in the interim, especially those taken from glaciers that no longer exist, and the Ice Memory project’s organizers are currently addressing how to grant access to the cores in a way that is equitable, as travel to Antarctica is cost prohibitive for many researchers.

The first stage of the project has focused on how to store the cores in the ice sheet. The plan is to store them about 10 meters deep, where the temperature is a stable −50°C throughout the year. “Even if there are a few degrees of warming in the next decades or centuries, it will still be kept at minus 50° or 45°,” said Ginot, one of the coordinators of the Ice Memory project.

Researchers from the French and Italian polar institutes have already trialed the best storage techniques on Dome Concordia in Antarctica. They dug 8-meter-deep, 100-meter-long trenches and inserted giant sausage-shaped balloons on the ice floors. Then they used the dug-out snow to cover the balloons and allowed the snow to harden. “When they disassembled the sausage, they had a cave under the snow,” Ginot said.

Constructing giant trenches at Dome Concordia in Antarctica. Digging these trenches was the first step in trialing how to store ice cores in underground caves. Credit: Armand Patoir, French Polar Institute IPEV

The project’s models forecast that the cavities will last for 20–30 years, at which time the scientists will create more caves at a minimal cost, Ginot said. The current focus of the team is to collect samples from glaciers that are quickly disappearing, such as the northern ice field near the summit of Mount Kilimanjaro in Tanzania.

Recognizing the Value

“We recognize that this is a library of information, and we’ve just read some of the pages of some of the books. But as long as the books are still there, we can go back and interrogate them.”Core libraries provide a vital window into events that happened before human records began, a repository for data to better understand Earth systems, and resources to help forecast future scenarios. Researchers believe that as science and technology evolve, they’ll be able to extract even more information from core collections. “We recognize that this is a library of information, and we’ve just read some of the pages of some of the books,” Swetnam said. “But as long as the books are still there, we can go back and interrogate them.”

While the libraries for ice, tree ring, and sediment cores are maintained, scientists are able to access the “books” for further analysis whenever they want.

“We see all kinds of cases where a new analytical technique becomes available, and people can ask new questions of these materials without having to go and collect them in the field,” Noren said. New analytical techniques have led to more accurate reconstruction of past temperatures from lake core sediments, for example, and by integrating several core data sets, scientists have revealed that humans began accelerating soil erosion 4,000 years ago.

The multifaceted value of the core collections has become even more pronounced during the COVID-19 pandemic, Noren said. Core libraries have allowed scientists to continue moving forward with their research even when they can’t do fieldwork. As recently as March 2021, for example, scientists published research on the multimillion-year-old record of Greenland vegetation and glacial history that was based on existing cores, not those collected by the scientists’ field research.

Although some libraries struggle with space constraints, maintaining suitable environmental conditions, cataloging samples, or ensuring open access, every scientist or curator of a core collection shares one concern: sustaining funding.

It costs money to run a core library: money to house samples, money to employ curators, and money to build systems that allow equal and fair access to data. Securing that financial support is a challenge. “Funding priority is about exciting research or a new instrument,” Brewer said. “Updating or maintaining a collection of scientific samples is not such an easy sell.”

Core libraries represent millions of years of history and hold keys to understanding and protecting Earth’s future. They are natural archives of ice-covered continents, forested lands, and ancient cultures. As such, they are a legacy to be preserved and protected for future generations, Noren said. “But if you view it from another lens, they are just storage,” he explained. “So we need to elevate that conversation and make it clear that these materials are essential for science.”

Author Information

Jane Palmer (@JanePalmerComms), Science Writer