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      MIT geologists discover where energy goes during an earthquake

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      The ground-shaking that an earthquake generates is only a fraction of the total energy that a quake releases. A quake can also generate a flash of heat, along with a domino-like fracturing of underground rocks. But exactly how much energy goes into each of these three processes is exceedingly difficult, if not impossible, to measure in the field.Now MIT geologists have traced the energy that is released by “lab quakes” — miniature analogs of natural earthquakes that are carefully triggered in a controlled laboratory setting. For the first time, they have quantified the complete energy budget of such quakes, in terms of the fraction of energy that goes into heat, shaking, and fracturing.They found that only about 10 percent of a lab quake’s energy causes physical shaking. An even smaller fraction — less than 1 percent — goes into breaking up rock and creating new surfaces. The overwhelming portion of a quake’s energy — on average 80 percent — goes into heating up the immediate region around a quake’s epicenter. In fact, the researchers observed that a lab quake can produce a temperature spike hot enough to melt surrounding material and turn it briefly into liquid melt.The geologists also found that a quake’s energy budget depends on a region’s deformation history — the degree to which rocks have been shifted and disturbed by previous tectonic motions. The fractions of quake energy that produce heat, shaking, and rock fracturing can shift depending on what the region has experienced in the past.“The deformation history — essentially what the rock remembers — really influences how destructive an earthquake could be,” says Daniel Ortega-Arroyo, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “That history affects a lot of the material properties in the rock, and it dictates to some degree how it is going to slip.”The team’s lab quakes are a simplified analog of what occurs during a natural earthquake. Down the road, their results could help seismologists predict the likelihood of earthquakes in regions that are prone to seismic events. For instance, if scientists have an idea of how much shaking a quake generated in the past, they might be able to estimate the degree to which the quake’s energy also affected rocks deep underground by melting or breaking them apart. This in turn could reveal how much more or less vulnerable the region is to future quakes.“We could never reproduce the complexity of the Earth, so we have to isolate the physics of what is happening, in these lab quakes,” says Matěj Peč, associate professor of geophysics at MIT. “We hope to understand these processes and try to extrapolate them to nature.”Peč (pronounced “Peck”) and Ortega-Arroyo reported their results on Aug. 28 in the journal AGU Advances. Their MIT co-authors are Hoagy O’Ghaffari and Camilla Cattania, along with Zheng Gong and Roger Fu at Harvard University and Markus Ohl and Oliver Plümper at Utrecht University in the Netherlands.Under the surfaceEarthquakes are driven by energy that is stored up in rocks over millions of years. As tectonic plates slowly grind against each other, stress accumulates through the crust. When rocks are pushed past their material strength, they can suddenly slip along a narrow zone, creating a geologic fault. As rocks slip on either side of the fault, they produce seismic waves that ripple outward and upward.We perceive an earthquake’s energy mainly in the form of ground shaking, which can be measured using seismometers and other ground-based instruments. But the other two major forms of a quake’s energy — heat and underground fracturing — are largely inaccessible with current technologies.“Unlike the weather, where we can see daily patterns and measure a number of pertinent variables, it’s very hard to do that very deep in the Earth,” Ortega-Arroyo says. “We don’t know what’s happening to the rocks themselves, and the timescales over which earthquakes repeat within a fault zone are on the century-to-millenia timescales, making any sort of actionable forecast challenging.”To get an idea of how an earthquake’s energy is partitioned, and how that energy budget might affect a region’s seismic risk, he and Peč went into the lab. Over the last seven years, Peč’s group at MIT has developed methods and instrumentation to simulate seismic events, at the microscale, in an effort to understand how earthquakes at the macroscale may play out.“We are focusing on what’s happening on a really small scale, where we can control many aspects of failure and try to understand it before we can do any scaling to nature,” Ortega-Arroyo says.MicroshakesFor their new study, the team generated miniature lab quakes that simulate a seismic slipping of rocks along a fault zone. They worked with small samples of granite, which are representative of rocks in the seismogenic layer — the geologic region in the continental crust where earthquakes typically originate. They ground up the granite into a fine powder and mixed the crushed granite with a much finer powder of magnetic particles, which they used as a sort of internal temperature gauge. (A particle’s magnetic field strength will change in response to a fluctuation in temperature.)The researchers placed samples of the powdered granite — each about 10 square millimeters and 1 millimeter thin — between two small pistons and wrapped the ensemble in a gold jacket. They then applied a strong magnetic field to orient the powder’s magnetic particles in the same initial direction and to the same field strength. They reasoned that any change in the particles’ orientation and field strength afterward should be a sign of how much heat that region experienced as a result of any seismic event.Once samples were prepared, the team placed them one at a time into a custom-built apparatus that the researchers tuned to apply steadily increasing pressure, similar to the pressures that rocks experience in the Earth’s seismogenic layer, about 10 to 20 kilometers below the surface. They used custom-made piezoelectric sensors, developed by co-author O’Ghaffari, which they attached to either end of a sample to measure any shaking that occurred as they increased the stress on the sample.They observed that at certain stresses, some samples slipped, producing a microscale seismic event similar to an earthquake. By analyzing the magnetic particles in the samples after the fact, they obtained an estimate of how much each sample was temporarily heated — a method developed in collaboration with Roger Fu’s lab at Harvard University. They also estimated the amount of shaking each sample experienced, using measurements from the piezoelectric sensor and numerical models. The researchers also examined each sample under the microscope, at different magnifications, to assess how the size of the granite grains changed — whether and how many grains broke into smaller pieces, for instance.From all these measurements, the team was able to estimate each lab quake’s energy budget. On average, they found that about 80 percent of a quake’s energy goes into heat, while 10 percent generates shaking, and less than 1 percent goes into rock fracturing, or creating new, smaller particle surfaces. “In some instances we saw that, close to the fault, the sample went from room temperature to 1,200 degrees Celsius in a matter of microseconds, and then immediately cooled down once the motion stopped,” Ortega-Arroyo says. “And in one sample, we saw the fault move by about 100 microns, which implies slip velocities essentially about 10 meters per second. It moves very fast, though it doesn’t last very long.”The researchers suspect that similar processes play out in actual, kilometer-scale quakes.“Our experiments offer an integrated approach that provides one of the most complete views of the physics of earthquake-like ruptures in rocks to date,” Peč says. “This will provide clues on how to improve our current earthquake models and natural hazard mitigation.”This research was supported, in part, by the National Science Foundation. More

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      Simpler models can outperform deep learning at climate prediction

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      Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better.The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models.Their analysis also reveals that a benchmarking technique commonly used to evaluate machine-learning techniques for climate predictions can be distorted by natural variations in the data, like fluctuations in weather patterns. This could lead someone to believe a deep-learning model makes more accurate predictions when that is not the case.The researchers developed a more robust way of evaluating these techniques, which shows that, while simple models are more accurate when estimating regional surface temperatures, deep-learning approaches can be the best choice for estimating local rainfall.They used these results to enhance a simulation tool known as a climate emulator, which can rapidly simulate the effect of human activities onto a future climate.The researchers see their work as a “cautionary tale” about the risk of deploying large AI models for climate science. While deep-learning models have shown incredible success in domains such as natural language, climate science contains a proven set of physical laws and approximations, and the challenge becomes how to incorporate those into AI models.“We are trying to develop models that are going to be useful and relevant for the kinds of things that decision-makers need going forward when making climate policy choices. While it might be attractive to use the latest, big-picture machine-learning model on a climate problem, what this study shows is that stepping back and really thinking about the problem fundamentals is important and useful,” says study senior author Noelle Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and the Department of Earth, Atmospheric and Planetary Sciences (EAPS).Selin’s co-authors are lead author Björn Lütjens, a former EAPS postdoc who is now a research scientist at IBM Research; senior author Raffaele Ferrari, the Cecil and Ida Green Professor of Oceanography in EAPS and co-director of the Lorenz Center; and Duncan Watson-Parris, assistant professor at the University of California at San Diego. Selin and Ferrari are also co-principal investigators of the Bringing Computation to the Climate Challenge project, out of which this research emerged. The paper appears today in the Journal of Advances in Modeling Earth Systems.Comparing emulatorsBecause the Earth’s climate is so complex, running a state-of-the-art climate model to predict how pollution levels will impact environmental factors like temperature can take weeks on the world’s most powerful supercomputers.Scientists often create climate emulators, simpler approximations of a state-of-the art climate model, which are faster and more accessible. A policymaker could use a climate emulator to see how alternative assumptions on greenhouse gas emissions would affect future temperatures, helping them develop regulations.But an emulator isn’t very useful if it makes inaccurate predictions about the local impacts of climate change. While deep learning has become increasingly popular for emulation, few studies have explored whether these models perform better than tried-and-true approaches.The MIT researchers performed such a study. They compared a traditional technique called linear pattern scaling (LPS) with a deep-learning model using a common benchmark dataset for evaluating climate emulators.Their results showed that LPS outperformed deep-learning models on predicting nearly all parameters they tested, including temperature and precipitation.“Large AI methods are very appealing to scientists, but they rarely solve a completely new problem, so implementing an existing solution first is necessary to find out whether the complex machine-learning approach actually improves upon it,” says Lütjens.Some initial results seemed to fly in the face of the researchers’ domain knowledge. The powerful deep-learning model should have been more accurate when making predictions about precipitation, since those data don’t follow a linear pattern.They found that the high amount of natural variability in climate model runs can cause the deep learning model to perform poorly on unpredictable long-term oscillations, like El Niño/La Niña. This skews the benchmarking scores in favor of LPS, which averages out those oscillations.Constructing a new evaluationFrom there, the researchers constructed a new evaluation with more data that address natural climate variability. With this new evaluation, the deep-learning model performed slightly better than LPS for local precipitation, but LPS was still more accurate for temperature predictions.“It is important to use the modeling tool that is right for the problem, but in order to do that you also have to set up the problem the right way in the first place,” Selin says.Based on these results, the researchers incorporated LPS into a climate emulation platform to predict local temperature changes in different emission scenarios.“We are not advocating that LPS should always be the goal. It still has limitations. For instance, LPS doesn’t predict variability or extreme weather events,” Ferrari adds.Rather, they hope their results emphasize the need to develop better benchmarking techniques, which could provide a fuller picture of which climate emulation technique is best suited for a particular situation.“With an improved climate emulation benchmark, we could use more complex machine-learning methods to explore problems that are currently very hard to address, like the impacts of aerosols or estimations of extreme precipitation,” Lütjens says.Ultimately, more accurate benchmarking techniques will help ensure policymakers are making decisions based on the best available information.The researchers hope others build on their analysis, perhaps by studying additional improvements to climate emulation methods and benchmarks. Such research could explore impact-oriented metrics like drought indicators and wildfire risks, or new variables like regional wind speeds.This research is funded, in part, by Schmidt Sciences, LLC, and is part of the MIT Climate Grand Challenges team for “Bringing Computation to the Climate Challenge.” More

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      Study links rising temperatures and declining moods

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      Rising global temperatures affect human activity in many ways. Now, a new study illuminates an important dimension of the problem: Very hot days are associated with more negative moods, as shown by a large-scale look at social media postings.Overall, the study examines 1.2 billion social media posts from 157 countries over the span of a year. The research finds that when the temperature rises above 95 degrees Fahrenheit, or 35 degrees Celsius, expressed sentiments become about 25 percent more negative in lower-income countries and about 8 percent more negative in better-off countries. Extreme heat affects people emotionally, not just physically.“Our study reveals that rising temperatures don’t just threaten physical health or economic productivity — they also affect how people feel, every day, all over the world,” says Siqi Zheng, a professor in MIT’s Department of Urban Studies and Planning (DUSP) and Center for Real Estate (CRE), and co-author of a new paper detailing the results. “This work opens up a new frontier in understanding how climate stress is shaping human well-being at a planetary scale.”The paper, “Unequal Impacts of Rising Temperatures on Global Human Sentiment,” is published today in the journal One Earth. The authors are Jianghao Wang, of the Chinese Academy of Sciences; Nicolas Guetta-Jeanrenaud SM ’22, a graduate of MIT’s Technology and Policy Program (TPP) and Institute for Data, Systems, and Society; Juan Palacios, a visiting assistant professor at MIT’s Sustainable Urbanization Lab (SUL) and an assistant professor Maastricht University; Yichun Fan, of SUL and Duke University; Devika Kakkar, of Harvard University; Nick Obradovich, of SUL and the Laureate Institute for Brain Research in Tulsa; and Zheng, who is the STL Champion Professor of Urban and Real Estate Sustainability at CRE and DUSP. Zheng is also the faculty director of CRE and founded the Sustainable Urbanization Lab in 2019.Social media as a windowTo conduct the study, the researchers evaluated 1.2 billion posts from the social media platforms Twitter and Weibo, all of which appeared in 2019. They used a natural language processing technique called Bidirectional Encoder Representations from Transformers (BERT), to analyze 65 languages across the 157 countries in the study.Each social media post was given a sentiment rating from 0.0 (for very negative posts) to 1.0 (for very positive posts). The posts were then aggregated geographically to 2,988 locations and evaluated in correlation with area weather. From this method, the researchers could then deduce the connection between extreme temperatures and expressed sentiment.“Social media data provides us with an unprecedented window into human emotions across cultures and continents,” Wang says. “This approach allows us to measure emotional impacts of climate change at a scale that traditional surveys simply cannot achieve, giving us real-time insights into how temperature affects human sentiment worldwide.”To assess the effects of temperatures on sentiment in higher-income and middle-to-lower-income settings, the scholars also used a World Bank cutoff level of gross national income per-capita annual income of $13,845, finding that in places with incomes below that, the effects of heat on mood were triple those found in economically more robust settings.“Thanks to the global coverage of our data, we find that people in low- and middle-income countries experience sentiment declines from extreme heat that are three times greater than those in high-income countries,” Fan says. “This underscores the importance of incorporating adaptation into future climate impact projections.”In the long runUsing long-term global climate models, and expecting some adaptation to heat, the researchers also produced a long-range estimate of the effects of extreme temperatures on sentiment by the year 2100. Extending the current findings to that time frame, they project a 2.3 percent worsening of people’s emotional well-being based on high temperatures alone by then — although that is a far-range projection.“It’s clear now, with our present study adding to findings from prior studies, that weather alters sentiment on a global scale,” Obradovich says. “And as weather and climates change, helping individuals become more resilient to shocks to their emotional states will be an important component of overall societal adaptation.”The researchers note that there are many nuances to the subject, and room for continued research in this area. For one thing, social media users are not likely to be a perfectly representative portion of the population, with young children and the elderly almost certainly using social media less than other people. However, as the researchers observe in the paper, the very young and elderly are probably particularly vulnerable to heat shocks, making the response to hot weather possible even larger than their study can capture.The research is part of the Global Sentiment project led by the MIT Sustainable Urbanization Lab, and the study’s dataset is publicly available. Zheng and other co-authors have previously investigated these dynamics using social media, although never before at this scale.“We hope this resource helps researchers, policymakers, and communities better prepare for a warming world,” Zheng says.The research was supported, in part, by Zheng’s chaired professorship research fund, and grants Wang received from the National Natural Science Foundation of China and the Chinese Academy of Sciences.  More

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      Eco-driving measures could significantly reduce vehicle emissions

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      Any motorist who has ever waited through multiple cycles for a traffic light to turn green knows how annoying signalized intersections can be. But sitting at intersections isn’t just a drag on drivers’ patience — unproductive vehicle idling could contribute as much as 15 percent of the carbon dioxide emissions from U.S. land transportation.A large-scale modeling study led by MIT researchers reveals that eco-driving measures, which can involve dynamically adjusting vehicle speeds to reduce stopping and excessive acceleration, could significantly reduce those CO2 emissions.Using a powerful artificial intelligence method called deep reinforcement learning, the researchers conducted an in-depth impact assessment of the factors affecting vehicle emissions in three major U.S. cities.Their analysis indicates that fully adopting eco-driving measures could cut annual city-wide intersection carbon emissions by 11 to 22 percent, without slowing traffic throughput or affecting vehicle and traffic safety.Even if only 10 percent of vehicles on the road employ eco-driving, it would result in 25 to 50 percent of the total reduction in CO2 emissions, the researchers found.In addition, dynamically optimizing speed limits at about 20 percent of intersections provides 70 percent of the total emission benefits. This indicates that eco-driving measures could be implemented gradually while still having measurable, positive impacts on mitigating climate change and improving public health.

      An animated GIF compares what 20% eco-driving adoption looks like to 100% eco-driving adoption.Image: Courtesy of the researchers

      “Vehicle-based control strategies like eco-driving can move the needle on climate change reduction. We’ve shown here that modern machine-learning tools, like deep reinforcement learning, can accelerate the kinds of analysis that support sociotechnical decision making. This is just the tip of the iceberg,” says senior author Cathy Wu, the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering (CEE) and the Institute for Data, Systems, and Society (IDSS) at MIT, and a member of the Laboratory for Information and Decision Systems (LIDS).She is joined on the paper by lead author Vindula Jayawardana, an MIT graduate student; as well as MIT graduate students Ao Qu, Cameron Hickert, and Edgar Sanchez; MIT undergraduate Catherine Tang; Baptiste Freydt, a graduate student at ETH Zurich; and Mark Taylor and Blaine Leonard of the Utah Department of Transportation. The research appears in Transportation Research Part C: Emerging Technologies.A multi-part modeling studyTraffic control measures typically call to mind fixed infrastructure, like stop signs and traffic signals. But as vehicles become more technologically advanced, it presents an opportunity for eco-driving, which is a catch-all term for vehicle-based traffic control measures like the use of dynamic speeds to reduce energy consumption.In the near term, eco-driving could involve speed guidance in the form of vehicle dashboards or smartphone apps. In the longer term, eco-driving could involve intelligent speed commands that directly control the acceleration of semi-autonomous and fully autonomous vehicles through vehicle-to-infrastructure communication systems.“Most prior work has focused on how to implement eco-driving. We shifted the frame to consider the question of should we implement eco-driving. If we were to deploy this technology at scale, would it make a difference?” Wu says.To answer that question, the researchers embarked on a multifaceted modeling study that would take the better part of four years to complete.They began by identifying 33 factors that influence vehicle emissions, including temperature, road grade, intersection topology, age of the vehicle, traffic demand, vehicle types, driver behavior, traffic signal timing, road geometry, etc.“One of the biggest challenges was making sure we were diligent and didn’t leave out any major factors,” Wu says.Then they used data from OpenStreetMap, U.S. geological surveys, and other sources to create digital replicas of more than 6,000 signalized intersections in three cities — Atlanta, San Francisco, and Los Angeles — and simulated more than a million traffic scenarios.The researchers used deep reinforcement learning to optimize each scenario for eco-driving to achieve the maximum emissions benefits.Reinforcement learning optimizes the vehicles’ driving behavior through trial-and-error interactions with a high-fidelity traffic simulator, rewarding vehicle behaviors that are more energy-efficient while penalizing those that are not.The researchers cast the problem as a decentralized cooperative multi-agent control problem, where the vehicles cooperate to achieve overall energy efficiency, even among non-participating vehicles, and they act in a decentralized manner, avoiding the need for costly communication between vehicles.However, training vehicle behaviors that generalize across diverse intersection traffic scenarios was a major challenge. The researchers observed that some scenarios are more similar to one another than others, such as scenarios with the same number of lanes or the same number of traffic signal phases.As such, the researchers trained separate reinforcement learning models for different clusters of traffic scenarios, yielding better emission benefits overall.But even with the help of AI, analyzing citywide traffic at the network level would be so computationally intensive it could take another decade to unravel, Wu says.Instead, they broke the problem down and solved each eco-driving scenario at the individual intersection level.“We carefully constrained the impact of eco-driving control at each intersection on neighboring intersections. In this way, we dramatically simplified the problem, which enabled us to perform this analysis at scale, without introducing unknown network effects,” she says.Significant emissions benefitsWhen they analyzed the results, the researchers found that full adoption of eco-driving could result in intersection emissions reductions of between 11 and 22 percent.These benefits differ depending on the layout of a city’s streets. A denser city like San Francisco has less room to implement eco-driving between intersections, offering a possible explanation for reduced emission savings, while Atlanta could see greater benefits given its higher speed limits.Even if only 10 percent of vehicles employ eco-driving, a city could still realize 25 to 50 percent of the total emissions benefit because of car-following dynamics: Non-eco-driving vehicles would follow controlled eco-driving vehicles as they optimize speed to pass smoothly through intersections, reducing their carbon emissions as well.In some cases, eco-driving could also increase vehicle throughput by minimizing emissions. However, Wu cautions that increasing throughput could result in more drivers taking to the roads, reducing emissions benefits.And while their analysis of widely used safety metrics known as surrogate safety measures, such as time to collision, suggest that eco-driving is as safe as human driving, it could cause unexpected behavior in human drivers. More research is needed to fully understand potential safety impacts, Wu says.Their results also show that eco-driving could provide even greater benefits when combined with alternative transportation decarbonization solutions. For instance, 20 percent eco-driving adoption in San Francisco would cut emission levels by 7 percent, but when combined with the projected adoption of hybrid and electric vehicles, it would cut emissions by 17 percent.“This is a first attempt to systematically quantify network-wide environmental benefits of eco-driving. This is a great research effort that will serve as a key reference for others to build on in the assessment of eco-driving systems,” says Hesham Rakha, the Samuel L. Pritchard Professor of Engineering at Virginia Tech, who was not involved with this research.And while the researchers focus on carbon emissions, the benefits are highly correlated with improvements in fuel consumption, energy use, and air quality.“This is almost a free intervention. We already have smartphones in our cars, and we are rapidly adopting cars with more advanced automation features. For something to scale quickly in practice, it must be relatively simple to implement and shovel-ready. Eco-driving fits that bill,” Wu says.This work is funded, in part, by Amazon and the Utah Department of Transportation. More

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      School of Architecture and Planning welcomes new faculty for 2025

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      Four new faculty members join the School of Architecture and Planning (SA+P) this fall, offering the MIT community creativity, knowledge, and scholarship in multidisciplinary roles.“These individuals add considerable strength and depth to our faculty,” says Hashim Sarkis, dean of the School of Architecture and Planning. “We are excited for the academic vigor they bring to research and teaching.”Karrie G. Karahalios ’94, MEng ’95, SM ’97, PhD ’04 joins the MIT Media Lab as a full professor of media arts and sciences. Karahalios is a pioneer in the exploration of social media and of how people communicate in environments that are increasingly mediated by algorithms that, as she has written, “shape the world around us.” Her work combines computing, systems, artificial intelligence, anthropology, sociology, psychology, game theory, design, and infrastructure studies. Karahalios’ work has received numerous honors including the National Science Foundation CAREER Award, Alfred P. Sloan Research Fellowship, SIGMOD Best Paper Award, and recognition as an ACM Distinguished Member.Pat Pataranutaporn SM ’18, PhD ’20 joins the MIT Media Lab as an assistant professor of media arts and sciences. A visionary technologist, scientist, and designer, Pataranutaporn explores the frontier of human-AI interaction, inventing and investigating AI systems that support human thriving. His research focuses on how personalized AI systems can amplify human cognition, from learning and decision-making to self-development, reflection, and well-being. Pataranutaporn will co-direct the Advancing Humans with AI Program.Mariana Popescu joins the Department of Architecture as an assistant professor. Popescu is a computational architect and structural designer with a strong interest and experience in innovative ways of approaching the fabrication process and use of materials in construction. Her area of expertise is computational and parametric design, with a focus on digital fabrication and sustainable design. Her extensive involvement in projects related to promoting sustainability has led to a multilateral development of skills, which combine the fields of architecture, engineering, computational design, and digital fabrication. Popescu earned her doctorate at ETH Zurich. She was named a “Pioneer” on the MIT Technology Review global list of “35 innovators under 35” in 2019.Holly Samuelson joins the Department of Architecture as an associate professor in the Building Technology Program at MIT, teaching architectural technology courses. Her teaching and research focus on issues of building design that impact human and environmental health. Her current projects harness advanced building simulation to investigate issues of greenhouse gas emissions, heat vulnerability, and indoor environmental quality while considering the future of buildings in a changing electricity grid. Samuelson has co-authored over 40 peer-reviewed papers, winning a best paper award from the journal Energy and Building. As a recognized expert in architectural technology, she has been featured in news outlets including The Washington Post, The Boston Globe, the BBC, and The Wall Street Journal. Samuelson earned her doctor of design from Harvard University Graduate School of Design. More

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      Why animals are a critical part of forest carbon absorption

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      A lot of attention has been paid to how climate change can drive biodiversity loss. Now, MIT researchers have shown the reverse is also true: Reductions in biodiversity can jeopardize one of Earth’s most powerful levers for mitigating climate change.In a paper published in PNAS, the researchers showed that following deforestation, naturally-regrowing tropical forests, with healthy populations of seed-dispersing animals, can absorb up to four times more carbon than similar forests with fewer seed-dispersing animals.Because tropical forests are currently Earth’s largest land-based carbon sink, the findings improve our understanding of a potent tool to fight climate change.“The results underscore the importance of animals in maintaining healthy, carbon-rich tropical forests,” says Evan Fricke, a research scientist in the MIT Department of Civil and Environmental Engineering and the lead author of the new study. “When seed-dispersing animals decline, we risk weakening the climate-mitigating power of tropical forests.”Fricke’s co-authors on the paper include César Terrer, the Tianfu Career Development Associate Professor at MIT; Charles Harvey, an MIT professor of civil and environmental engineering; and Susan Cook-Patton of The Nature Conservancy.The study combines a wide array of data on animal biodiversity, movement, and seed dispersal across thousands of animal species, along with carbon accumulation data from thousands of tropical forest sites.The researchers say the results are the clearest evidence yet that seed-dispersing animals play an important role in forests’ ability to absorb carbon, and that the findings underscore the need to address biodiversity loss and climate change as connected parts of a delicate ecosystem rather as separate problems in isolation.“It’s been clear that climate change threatens biodiversity, and now this study shows how biodiversity losses can exacerbate climate change,” Fricke says. “Understanding that two-way street helps us understand the connections between these challenges, and how we can address them. These are challenges we need to tackle in tandem, and the contribution of animals to tropical forest carbon shows that there are win-wins possible when supporting biodiversity and fighting climate change at the same time.”Putting the pieces togetherThe next time you see a video of a monkey or bird enjoying a piece of fruit, consider that the animals are actually playing an important role in their ecosystems. Research has shown that by digesting the seeds and defecating somewhere else, animals can help with the germination, growth, and long-term survival of the plant.Fricke has been studying animals that disperse seeds for nearly 15 years. His previous research has shown that without animal seed dispersal, trees have lower survival rates and a harder time keeping up with environmental changes.“We’re now thinking more about the roles that animals might play in affecting the climate through seed dispersal,” Fricke says. “We know that in tropical forests, where more than three-quarters of trees rely on animals for seed dispersal, the decline of seed dispersal could affect not just the biodiversity of forests, but how they bounce back from deforestation. We also know that all around the world, animal populations are declining.”Regrowing forests is an often-cited way to mitigate the effects of climate change, but the influence of biodiversity on forests’ ability to absorb carbon has not been fully quantified, especially at larger scales.For their study, the researchers combined data from thousands of separate studies and used new tools for quantifying disparate but interconnected ecological processes. After analyzing data from more than 17,000 vegetation plots, the researchers decided to focus on tropical regions, looking at data on where seed-dispersing animals live, how many seeds each animal disperses, and how they affect germination.The researchers then incorporated data showing how human activity impacts different seed-dispersing animals’ presence and movement. They found, for example, that animals move less when they consume seeds in areas with a bigger human footprint.Combining all that data, the researchers created an index of seed-dispersal disruption that revealed a link between human activities and declines in animal seed dispersal. They then analyzed the relationship between that index and records of carbon accumulation in naturally regrowing tropical forests over time, controlling for factors like drought conditions, the prevalence of fires, and the presence of grazing livestock.“It was a big task to bring data from thousands of field studies together into a map of the disruption of seed dispersal,” Fricke says. “But it lets us go beyond just asking what animals are there to actually quantifying the ecological roles those animals are playing and understanding how human pressures affect them.”The researchers acknowledged that the quality of animal biodiversity data could be improved and introduces uncertainty into their findings. They also note that other processes, such as pollination, seed predation, and competition influence seed dispersal and can constrain forest regrowth. Still, the findings were in line with recent estimates.“What’s particularly new about this study is we’re actually getting the numbers around these effects,” Fricke says. “Finding that seed dispersal disruption explains a fourfold difference in carbon absorption across the thousands of tropical regrowth sites included in the study points to seed dispersers as a major lever on tropical forest carbon.”Quantifying lost carbonIn forests identified as potential regrowth sites, the researchers found seed-dispersal declines were linked to reductions in carbon absorption each year averaging 1.8 metric tons per hectare, equal to a reduction in regrowth of 57 percent.The researchers say the results show natural regrowth projects will be more impactful in landscapes where seed-dispersing animals have been less disrupted, including areas that were recently deforested, are near high-integrity forests, or have higher tree cover.“In the discussion around planting trees versus allowing trees to regrow naturally, regrowth is basically free, whereas planting trees costs money, and it also leads to less diverse forests,” Terrer says. “With these results, now we can understand where natural regrowth can happen effectively because there are animals planting the seeds for free, and we also can identify areas where, because animals are affected, natural regrowth is not going to happen, and therefore planting trees actively is necessary.”To support seed-dispersing animals, the researchers encourage interventions that protect or improve their habitats and that reduce pressures on species, ranging from wildlife corridors to restrictions on wildlife trade. Restoring the ecological roles of seed dispersers is also possible by reintroducing seed-dispersing species where they’ve been lost or planting certain trees that attract those animals.The findings could also make modeling the climate impact of naturally regrowing forests more accurate.“Overlooking the impact of seed-dispersal disruption may overestimate natural regrowth potential in many areas and underestimate it in others,” the authors write.The researchers believe the findings open up new avenues of inquiry for the field.“Forests provide a huge climate subsidy by sequestering about a third of all human carbon emissions,” Terrer says. “Tropical forests are by far the most important carbon sink globally, but in the last few decades, their ability to sequester carbon has been declining. We will next explore how much of that decline is due to an increase in extreme droughts or fires versus declines in animal seed dispersal.”Overall, the researchers hope the study helps improves our understanding of the planet’s complex ecological processes.“When we lose our animals, we’re losing the ecological infrastructure that keeps our tropical forests healthy and resilient,” Fricke says.The research was supported by the MIT Climate and Sustainability Consortium, the Government of Portugal, and the Bezos Earth Fund. More

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      Designing across cultural and geographic divides

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      In addition to the typical rigors of MIT classes, Terrascope Subject 2.00C/1.016/EC.746 (Design for Complex Environmental Issues) poses some unusual hurdles for students to navigate: collaborating across time zones, bridging different cultural and institutional experiences, and trying to do hands-on work over Zoom. That’s because the class includes students from not only MIT, but also Diné College in Tsaile, Arizona, within the Navajo Nation, and the University of Puerto Rico-Ponce (UPRP).Despite being thousands of miles apart, students work in teams to tackle a real-world problem for a client, based on the Terrascope theme for the year. “Understanding how to collaborate over long distances with people who are not like themselves will be an important item in many of these students’ toolbelts going forward, in some cases just as much as — or more than — any particular design technique,” says Ari Epstein, Terrascope associate director and senior lecturer. Over the past several years, Epstein has taught the class along with Joel Grimm of MIT Beaver Works and Libby Hsu of MIT D-Lab, as well instructors from the two collaborating institutions. Undergraduate teaching fellows from all three schools are also key members of the instructional staff.Since the partnership began three years ago (initially with Diné College, with the addition of UPRP two years ago), the class themes have included food security and sustainable agriculture in Navajo Nation; access to reliable electrical power in Puerto Rico; and this year, increasing museum visitors’ engagement with artworks depicting mining and landscape alteration in Nevada.Each team — which includes students from all three colleges — meets with clients online early in the term to understand their needs; then, through an iterative process, teams work on designing prototypes. During MIT’s spring break, teams travel to meet with the clients onsite to get feedback and continue to refine their prototypes. At the end of the term, students present their final products to the clients, an expert panel, and their communities at a hybrid showcase event held simultaneously on all three campuses.Free-range design engineering“I really loved the class,” says Graciela Leon, a second-year mechanical engineering major who took the subject in 2024. “It was not at all what I was expecting,” she adds. While the learning objectives on the syllabus are fairly traditional — using an iterative engineering design process, developing teamwork skills, and deepening communication skills, to name a few — the approach is not. “Terrascope is just kind of like throwing you into a real-world problem … it feels a lot more like you are being trusted with this actual challenge,” Leon says.The 2024 challenge was to find a way to help the clients, Puerto Rican senior citizens, turn on gasoline-powered generators when the electrical power grid fails; some of them struggle with the pull cords necessary to start the generators. The students were tasked with designing solutions to make starting the generators easier.Terrascope instructors teach fundamental skills such as iterative design spirals and scrum workflow frameworks, but they also give students ample freedom to follow their ideas. Leon admits she was a bit frustrated at first, because she wasn’t sure what she was supposed to be doing. “I wanted to be building things and thought, ‘Wow, I have to do all these other things, I have to write some kind of client profile and understand my client’s needs.’ I was just like, ‘Hand me a drill! I want to design something!’”When he took the class last year, Uziel Rodriguez-Andujar was also thrown off initially by the independence teams had. Now a second-year UPRP student in mechanical engineering, he’s accustomed to lecture-based classes. “What I found so interesting is the way [they] teach the class, which is, ‘You make your own project, and we need you to find a solution to this. How it will look, and when you have it — that’s up to you,’” he says.Clearing hurdlesTeaching the course on three different campuses introduces a number of challenges for students and instructors to overcome — among them, operating in three different time zones, overcoming language barriers, navigating different cultural and institutional norms, communicating effectively, and designing and building prototypes over Zoom.“The culture span is huge,” explains Epstein. “There are different ways of speaking, different ways of listening, and each organization has different resources.”First-year MIT student EJ Rodriguez found that one of the biggest obstacles was trying to convey ideas to teammates clearly. He took the class this year, when the theme revolved around the environmental impacts of lithium mining. The client, the Nevada Museum of Art, wanted to find ways to engage visitors with its artwork collection related to mining-related landscape changes.Rodriguez and his team designed a pendulum with a light affixed to it that illuminates a painting by a Native American artist. When the pendulum swings, it changes how the visitor experiences the artwork. The team built parts for the pendulum on different campuses, and they reached a point where they realized their pieces were incompatible. “We had different visions of what we wanted for the project, and different vocabulary we were using to describe our ideas. Sometimes there would be a misunderstanding … It required a lot of honesty from each campus to be like, ‘OK, I thought we were doing exactly this,’ and obviously in a really respectful way.”It’s not uncommon for students at Diné College and UPRP to experience an initial hurdle that their MIT peers do not. Epstein notes, “There’s a tendency for some folks outside MIT to see MIT students as these brilliant people that they don’t belong in the same room with.” But the other students soon realize not only that they can hold their own intellectually, but also that their backgrounds and experiences are incredibly valuable. “Their life experiences actually put them way ahead of many MIT students in some ways, when you think about design and fabrication, like repairing farm equipment or rebuilding transmissions,” he adds.That’s how Cauy Bia felt when he took the class in 2024. Currently a first-year graduate student in biology at Diné College, Bia questioned whether he’d be on par with the MIT students. “I’ve grown up on a farm, and we do a lot of building, a lot of calculations, a lot of hands-on stuff. But going into this, I was sweating it so hard [wondering], ‘Am I smart enough to work with these students?’ And then, at the end of the day, that was never an issue,” he says.The value of reflectionEvery two weeks, Terrascope students write personal reflections about their experiences in the class, which helps them appreciate their academic and personal development. “I really felt that I had undergone a process that made me grow as an engineer,” says Leon. “I understood the importance of people and engineering more, including teamwork, working with clients, and de-centering the project away from what I wanted to build and design.”When Bia began the semester, he says, he was more of a “make-or-break-type person” and tended to see things in black and white. “But working with all three campuses, it kind of opened up my thought process so I can assess more ideas, more voices and opinions. And I can get broader perspectives and get bigger ideas from that point,” he says. It was also a powerful experience culturally for him, particularly “drawing parallels between Navajo history, Navajo culture, and seeing the similarities between that and Puerto Rican culture, seeing how close we are as two nations.”Rodriguez-Andujar gained an appreciation for the “constant struggle between simplicity and complexity” in engineering. “You have all these engineers trying to over-engineer everything,” he says. “And after you get your client feedback [halfway through the semester], it turns out, ‘Oh, that doesn’t work for me. I’m sorry — you have to scale it down like a hundred times and make it a lot simpler.’”For instructors, the students’ reflections are invaluable as they strive to make improvements every year. In many ways, you might say the class is an iterative design spiral, too. “The past three years have themselves been prototypes,” Epstein says, “and all of the instructional staff are looking forward to continuing these exciting partnerships.” More

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      in Environment

      Study shows how a common fertilizer ingredient benefits plants

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      Lanthanides are a class of rare earth elements that in many countries are added to fertilizer as micronutrients to stimulate plant growth. But little is known about how they are absorbed by plants or influence photosynthesis, potentially leaving their benefits untapped.Now, researchers from MIT have shed light on how lanthanides move through and operate within plants. These insights could help farmers optimize their use to grow some of the world’s most popular crops.Published today in the Journal of the American Chemical Society, the study shows that a single nanoscale dose of lanthanides applied to seeds can make some of the world’s most common crops more resilient to UV stress. The researchers also uncovered the chemical processes by which lanthanides interact with the chlorophyll pigments that drive photosynthesis, showing that different lanthanide elements strengthen chlorophyll by replacing the magnesium at its center.“This is a first step to better understand how these elements work in plants, and to provide an example of how they could be better delivered to plants, compared to simply applying them in the soil,” says Associate Professor Benedetto Marelli, who conducted the research with postdoc Giorgio Rizzo. “This is the first example of a thorough study showing the effects of lanthanides on chlorophyll, and their beneficial effects to protect plants from UV stress.”Inside plant connectionsCertain lanthanides are used as contrast agents in MRI and for applications including light-emitting diodes, solar cells, and lasers. Over the last 50 years, lanthanides have become increasingly used in agriculture to enhance crop yields, with China alone applying lanthanide-based fertilizers to nearly 4 million hectares of land each year.“Lanthanides have been considered for a long time to be biologically irrelevant, but that’s changed in agriculture, especially in China,” says Rizzo, the paper’s first author. “But we largely don’t know how lanthanides work to benefit plants — nor do we understand their uptake mechanisms from plant tissues.”Recent studies have shown that low concentrations of lanthanides can promote plant growth, root elongation, hormone synthesis, and stress tolerance, but higher doses can cause harm to plants. Striking the right balance has been hard because of our lack of understanding around how lanthanides are absorbed by plants or how they interact with root soil.For the study, the researchers leveraged seed coating and treatment technologies they previously developed to investigate the way the plant pigment chlorophyll interacts with lanthanides, both inside and outside of plants. Up until now, researchers haven’t been sure whether chlorophyll interacts with lanthanide ions at all.Chlorophyll drives photosynthesis, but the pigments lose their ability to efficiently absorb light when the magnesium ion at their core is removed. The researchers discovered that lanthanides can fill that void, helping chlorophyll pigments partially recover some of their optical properties in a process known as re-greening.“We found that lanthanides can boost several parameters of plant health,” Marelli says. “They mostly accumulate in the roots, but a small amount also makes its way to the leaves, and some of the new chlorophyll molecules made in leaves have lanthanides incorporated in their structure.”This study also offers the first experimental evidence that lanthanides can increase plant resilience to UV stress, something the researchers say was completely unexpected.“Chlorophylls are very sensitive pigments,” Rizzo says. “They can convert light to energy in plants, but when they are isolated from the cell structure, they rapidly hydrolyze and degrade. However, in the form with lanthanides at their center, they are pretty stable, even after extracting them from plant cells.”The researchers, using different spectroscopic techniques, found the benefits held across a range of staple crops, including chickpea, barley, corn, and soybeans.The findings could be used to boost crop yield and increase the resilience of some of the world’s most popular crops to extreme weather.“As we move into an environment where extreme heat and extreme climate events are more common, and particularly where we can have prolonged periods of sun in the field, we want to provide new ways to protect our plants,” Marelli says. “There are existing agrochemicals that can be applied to leaves for protecting plants from stressors such as UV, but they can be toxic, increase microplastics, and can require multiple applications. This could be a complementary way to protect plants from UV stress.”Identifying new applicationsThe researchers also found that larger lanthanide elements like lanthanum were more effective at strengthening chlorophyll pigments than smaller ones. Lanthanum is considered a low-value byproduct of rare earths mining, and can become a burden to the rare earth element (REE) supply chain due to the need to separate it from more desirable rare earths. Increasing the demand for lanthanum could diversify the economics of REEs and improve the stability of their supply chain, the scientists suggest.“This study shows what we could do with these lower-value metals,” Marelli says. “We know lanthanides are extremely useful in electronics, magnets, and energy. In the U.S., there’s a big push to recycle them. That’s why for the plant studies, we focused on lanthanum, being the most abundant, cheapest lanthanide ion.”Moving forward, the team plans to explore how lanthanides work with other biological molecules, including proteins in the human body.In agriculture, the team hopes to scale up its research to include field and greenhouse studies to continue testing the results of UV resilience on different crop types and in experimental farm conditions.“Lanthanides are already widely used in agriculture,” Rizzo says. “We hope this study provides evidence that allows more conscious use of them and also a new way to apply them through seed treatments.”The research was supported by the MIT Climate Grand Challenge and the Office for Naval Research. More