Engineers program marine robots to take calculated risks

We know far less about the Earth’s oceans than we do about the surface of the moon or Mars. The sea floor is carved with expansive canyons, towering seamounts, deep trenches, and sheer cliffs, most of which are considered too dangerous or inaccessible for autonomous underwater vehicles (AUV) to navigate.

But what if the reward for traversing such places was worth the risk?

MIT engineers have now developed an algorithm that lets AUVs weigh the risks and potential rewards of exploring an unknown region. For instance, if a vehicle tasked with identifying underwater oil seeps approached a steep, rocky trench, the algorithm could assess the reward level (the probability that an oil seep exists near this trench), and the risk level (the probability of colliding with an obstacle), if it were to take a path through the trench.  

“If we were very conservative with our expensive vehicle, saying its survivability was paramount above all, then we wouldn’t find anything of interest,” Ayton says. “But if we understand there’s a tradeoff between the reward of what you gather, and the risk or threat of going toward these dangerous geographies, we can take certain risks when it’s worthwhile.”

Ayton says the new algorithm can compute tradeoffs of risk versus reward in real time, as a vehicle decides where to explore next. He and his colleagues in the lab of Brian Williams, professor of aeronautics and astronautics, are implementing this algorithm and others on AUVs, with the vision of deploying fleets of bold, intelligent robotic explorers for a number of missions, including looking for offshore oil deposits, investigating the impact of climate change on coral reefs, and exploring extreme environments analogous to Europa, an ice-covered moon of Jupiter that the team hopes vehicles will one day traverse.

“If we went to Europa and had a very strong reason to believe that there might be a billion-dollar observation in a cave or crevasse, which would justify sending a spacecraft to Europa, then we would absolutely want to risk going in that cave,” Ayton says. “But algorithms that don’t consider risk are never going to find that potentially history-changing observation.”

Ayton and Williams, along with Richard Camilli of the Woods Hole Oceanographic Institution, will present their new algorithm at the Association for the Advancement of Artificial Intelligence conference this week in Honolulu.

A bold path

The team’s new algorithm is the first to enable “risk-bounded adaptive sampling.” An adaptive sampling mission is designed, for instance, to automatically adapt an AUV’s path, based on new measurements that the vehicle takes as it explores a given region. Most adaptive sampling missions that consider risk typically do so by finding paths with a concrete, acceptable level of risk. For instance, AUVs may be programmed to only chart paths with a chance of collision that doesn’t exceed 5 percent.

But the researchers found that accounting for risk alone could severely limit a mission’s potential rewards. 

“Before we go into a mission, we want to specify the risk we’re willing to take for a certain level of reward,” Ayton says. “For instance, if a path were to take us to more hydrothermal vents, we would be willing to take this amount of risk, but if we’re not going to see anything, we would be willing to take less risk.”

The team’s algorithm takes in bathymetric data, or information about the ocean topography, including any surrounding obstacles, along with the vehicle’s dynamics and inertial measurements, to compute the level of risk for a certain proposed path. The algorithm also takes in all previous measurements that the AUV has taken, to compute the probability that such high-reward measurements may exist along the proposed path.

If the risk-to-reward ratio meets a certain value, determined by scientists beforehand, then the AUV goes ahead with the proposed path, taking more measurements that feed back into the algorithm to help it evaluate the risk and reward of other paths as the vehicle moves forward.

The researchers tested their algorithm in a simulation of an AUV mission east of Boston Harbor. They used bathymetric data collected from the region during a previous NOAA survey, and simulated an AUV exploring at a depth of 15 meters through regions at relatively high temperatures. They looked at how the algorithm planned out the vehicle’s route under three different scenarios of acceptable risk.

In the scenario with the lowest acceptable risk, meaning that the vehicle should avoid any regions that would have a very high chance of collision, the algorithm mapped out a conservative path, keeping the vehicle in a safe region that also did not have any high rewards — in this case, high temperatures. For scenarios of higher acceptable risk, the algorithm charted bolder paths that took a vehicle through a narrow chasm, and ultimately to a high-reward region.

The team also ran the algorithm through 10,000 numerical simulations, generating random environments in each simulation through which to plan a path, and found that the algorithm “trades off risk against reward intuitively, taking dangerous actions only when justified by the reward.”

A risky slope

Last December, Ayton, Williams, and others spent two weeks on a cruise off the coast of Costa Rica, deploying underwater gliders, on which they tested several algorithms, including this newest one. For the most part, the algorithm’s path planning agreed with those proposed by several onboard geologists who were looking for the best routes to find oil seeps.

Ayton says there was a particular moment when the risk-bounded algorithm proved especially handy. An AUV was making its way up a precarious slump, or landslide, where the vehicle couldn’t take too many risks.

“The algorithm found a method to get us up the slump quickly, while being the most worthwhile,” Ayton says. “It took us up a path that, while it didn’t help us discover oil seeps, it did help us refine our understanding of the environment.”

“What was really interesting was to watch how the machine algorithms began to ‘learn’ after the findings of several dives, and began to choose sites that we geologists might not have chosen initially,” says Lori Summa, a geologist and guest investigator at the Woods Hole Oceanographic Institution, who took part in the cruise.  “This part of the process is still evolving, but it was exciting to watch the algorithms begin to identify the new patterns from large amounts of data, and couple that information to an efficient, ‘safe’ search strategy.” 

In their long-term vision, the researchers hope to use such algorithms to help autonomous vehicles explore environments beyond Earth.

“If we went to Europa and weren’t willing to take any risks in order to preserve a probe, then the probability of finding life would be very, very low,” Ayton says. “You have to risk a little to get more reward, which is generally true in life as well.”

This research was supported, in part, by Exxon Mobile, as part of the MIT Energy Initiative, and by NASA.

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Sallie “Penny” Chisholm awarded the 2019 Crafoord Prize

MIT Institute Professor Sallie “Penny” Chisholm of the departments of Civil and Environmental Engineering and Biology is the recipient of the 2019 Crafoord Prize.

Announced on Jan. 17, Chisholm was awarded the prize “for the discovery and pioneering studies of the most abundant photosynthesizing organism on Earth, Prochlorococcus.”

Prochlorococcus is a type of phytoplankton found in the ocean that is able to photosynthesize like plants on land.  The process of photosynthesis is responsible for the oxygen humans breathe, which makes it critical to life on Earth. Prochlorococcus accounts for approximately 10 percent of all ocean photosynthesis, which draws carbon dioxide out of the atmosphere, provides it with oxygen, and forms the base of the food chain.

While the organism is the most abundant photosynthesizer on the planet (the total amount of Prochlorococcus on Earth has been estimated to be 3*10²⁷, or 3,000,000,000,000,000,000,000,000,000), it wasn’t until the mid-1980’s that Prochlorococcus was discovered by Chisholm and colleagues at the Woods Hole Oceanographic Institution. The reason the organism remained unknown for so long can be attributed to its small size. The tiny bacteria is half of a micrometer in size, 1/100 the width of a human hair, making it the smallest photosynthesizing organism.

Since its discovery, Chisholm and her team have found that although each cell has only 2,000 genes, the species as a whole has more than 80,000 different genes in its gene pool, which is four times more than the genetic makeup of humans. This vast diversity of genes distributed among the global population contributes to why Prochlorococcus is able to exist prominently in various environments containing different levels of light, heat, and nutrients.

Chisholm, who has been at MIT since 1976, now studies how Prochlorococcus interacts with various components of seawater and other microorganisms found in the ocean; its role in shaping the ocean ecosystem over evolutionary time; and how its populations may shift in response to climate change.

In April, Chisholm delivered a TED Talk that dove deeper into the properties of Prochlorococcus, comparing the organism’s genetic diversity to iPhone apps, and expanded on the the beauty of this microorganism as the smallest living thing that can convert solar energy and carbon dioxide into fuel through photosynthesis. Understanding its simple design could aid in efforts to engineer artificial photosynthesis machines — reducing our dependency on fossil fuels.  

Prochlorococcus has even inspired Chisholm to educate future generations of scientists through a series of children’s books called the “Sunlight Series,” with co-author and illustrator Molly Bang. The series describes the Earth’s natural processes in layman’s terms and through imagery. While none of Chisholm’s books mention Prochlorococcus by name, Chisholm says the simplicity of Prochlorococcus compelled her to create the series.

Chisholm will present her prize lecture in Sweden at Lund University on May 13, and will receive her prize at the Royal Swedish Academy of Sciences prize award ceremony on May 15, in the presence of H. M. King Carl XVI Gustaf and H. M. Queen Silvia of Sweden.

The Crafoord Prize is awarded in partnership between the Royal Swedish Academy of Sciences and the Crafoord Foundation, with the academy responsible for selecting the Crafoord Laureates. Awards are presented in one of four disciplines each year: mathematics and astronomy, geosciences, biosciences, or polyarthritis (such as rheumatoid arthritis).

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Exploring New England's coastal ecosystems in the dead of winter

In early January 2018, a nor’easter pummeled the East Coast. A record-breaking high tide rendered many streets in Boston impassable and seawater rushed down Seaport Boulevard in Boston’s Seaport District. A deluge of water poured down the steps leading down to the Aquarium subway station, forcing it to close.

Less than a week later, in a dry classroom on MIT’s campus, a group of students discussed how coastal cities like Boston can cope with worsening floods due to rising sea levels.

“We live in a coastal city, so obviously we are being significantly impacted by sea level rise,” says Valerie Muldoon, a third-year mechanical engineering student. “We talked about the bad nor’easter earlier in January and brainstormed ways to mitigate the flooding.”

Muldoon and her fellow students were enrolled in 2.981 (New England Coastal Ecology), a class that meets during MIT’s Independent Activities Period. The course is offered through the MIT Sea Grant College Program, which is affiliated with MIT’s Department of Mechanical Engineering.

MIT Sea Grant instructors Juliet Simpson, a research engineer, and Carolina Bastidas, a research scientist, use the four-week class to introduce students to the biological makeup of coastal ecosystems, to the crucial role these areas play in protecting the environment, and to the effects human interaction and climate change have had on them.

“We want to give a taste of coastal communities in New England to the students at MIT — especially those who come from abroad or other parts of the U.S.,” says Bastidas, a marine biologist who focuses her research primarily on coral and oyster reefs.

Muldoon, who is a double minor in energy studies and environment and sustainability, says she was “so excited to see a Course 2 class on coastal ecology.”

“I’m passionate about protecting the environment, so the topic really resonated with me,” she says.

The course begins with an introduction to the different types of coastal ecosystems found in the New England area, such as rocky intertidal regions, salt marshes, eelgrass meadows, and kelp forests. In addition to providing an overview of the makeup of each environment, the course instructors also discuss the physiology of the countless organisms who live in them.

Halfway through the course, students learn about how human impacts like climate change, eutrophication, and increased development have affected coastal habitats.

“We focus on climate change as it impacts coastal communities like rocky shores and salt marshes,” says Simpson, a coastal ecologist who studies how plants and algae respond to human interference. “There are a lot of interesting implications for sea level rise for intertidal organisms.”

Sea level rise, for example, has forced organisms that live in salt marshes to migrate upland. Changes in both water and air temperature also have a drastic effect on the inhabitants of coastal regions.

“As temperatures rise, all of those organisms are going to need to adapt or the communities are going to change, possibly dramatically,” explains Simpson.

Protecting coastal ecosystems has far reaching implications that go beyond the animals and plants that live there, because they offer a natural defense against climate change. Many coastal are natural hot spots for carbon capture and sequestration. Salt marshes and seagrass meadows all capture vast amounts of carbon that can be stored for several thousand years in peat.

“I was shocked at how much carbon the plants in these ecosystems can hold through sequestration,” recalls Muldoon.

Protecting these areas is essential to continue this natural sequestration of carbon and prevent carbon already stored there from leaking out. Coastal ecosystems are also instrumental in protecting coastal cities, like Boston, from flooding due to sea level rise.

“We talk about the ecology of coastal cities and how flooding from storms and sea level rise impacts human communities,” adds Simpson.

The class culminates in a field trip to Odiorne Point State Park in New Hampshire, where students get to interact with the communities they’ve learned about. Using fundamental techniques in ecology, students collect data about the species living in the salt marsh and rocky shore nearby. 

Bastidas and Simpson will expand the class’ scope beyond New England in a new course — 2.982 (Ecology and Sustainability of Coastal Ecosystems) — which will be offered in fall 2019.

While the effects of climate change on coastal ecosystems often paint a dire picture, the instructors want students to focus on the positive.

“Rather than have students focus on the gloom and doom aspect, we want to encourage them to come up with novel solutions for dealing with climate change and carbon emissions,” adds Bastidas.

Muldoon sees a special role for mechanical engineers like herself in developing such solutions.

“I think it’s so important for mechanical engineering students to take classes like this one because we are definitely going to be needed to help mitigate the problems that come with sea level rise,” she says.

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New climate model to be built from the ground up

The following news article is adapted from a press release issued by Caltech, in partnership with the MIT School of Science, the Naval Postgraduate School, and the Jet Propulsion Laboratory.

Facing the certainty of a changing climate coupled with the uncertainty that remains in predictions of how it will change, scientists and engineers from across the country are teaming up to build a new type of climate model that is designed to provide more precise and actionable predictions. 

Leveraging recent advances in the computational and data sciences, the comprehensive effort capitalizes on vast amounts of data that are now available and on increasingly powerful computing capabilities both for processing data and for simulating the Earth system. 

The new model will be built by a consortium of researchers led by Caltech, in partnership with MIT; the Naval Postgraduate School (NPS); and the Jet Propulsion Laboratory (JPL), which Caltech manages for NASA. The consortium, dubbed the Climate Modeling Alliance (CliMA), plans to fuse Earth observations and high-resolution simulations into a model that represents important small-scale features, such as clouds and turbulence, more reliably than existing climate models. The goal is a climate model that projects future changes in critical variables such as cloud cover, rainfall, and sea ice extent more accurately — with uncertainties at least half the size of those in existing models.

"Projections with current climate models — for example, of how features such as rainfall extremes will change — still have large uncertainties, and the uncertainties are poorly quantified," says Tapio Schneider, Caltech's Theodore Y. Wu Professor of Environmental Science and Engineering, senior research scientist at JPL, and principal investigator of CliMA. "For cities planning their stormwater management infrastructure to withstand the next 100 years' worth of floods, this is a serious issue; concrete answers about the likely range of climate outcomes are key for planning."

The consortium will operate in a fast-paced, start-up-like atmosphere, and hopes to have the new model up and running within the next five years — an aggressive timeline for building a climate model essentially from scratch. 

"A fresh start gives us an opportunity to design the model from the outset to run effectively on modern and rapidly evolving computing hardware, and for the atmospheric and ocean models to be close cousins of each other, sharing the same numerical algorithms," says Frank Giraldo, professor of applied mathematics at NPS.

Current climate modeling relies on dividing up the globe into a grid and then computing what is going on in each sector of the grid, as well as how the sectors interact with each other. The accuracy of any given model depends in part on the resolution at which the model can view the Earth — that is, the size of the grid's sectors. Limitations in available computer processing power mean that those sectors generally cannot be any smaller than tens of kilometers per side. But for climate modeling, the devil is in the details — details that get missed in a too-large grid. 

For example, low-lying clouds have a significant impact on climate by reflecting sunlight, but the turbulent plumes that sustain them are so small that they fall through the cracks of existing models. Similarly, changes in Arctic sea ice have been linked to wide-ranging effects on everything from polar climate to drought in California, but it is difficult to predict how that ice will change in the future because it is sensitive to the density of cloud cover above the ice and the temperature of ocean currents below, both of which cannot be resolved by current models.

To capture the large-scale impact of these small-scale features, the team will develop high-resolution simulations that model the features in detail in selected regions of the globe. Those simulations will be nested within the larger climate model. The effect will be a model capable of "zooming in" on selected regions, providing detailed local climate information about those areas and informing the modeling of small-scale processes everywhere else.

"The ocean soaks up much of the heat and carbon accumulating in the climate system. However, just how much it takes up depends on turbulent eddies in the upper ocean, which are too small to be resolved in climate models," says Raffaele Ferrari, a Cecil and Ida Green Professor of Oceanography at MIT. "Fusing nested high-resolution simulations with newly available measurements from, for example, a fleet of thousands of autonomous floats could enable a leap in the accuracy of ocean predictions."

While existing models are often tested by checking predictions against observations, the new model will take ground-truthing a step further by using data-assimilation and machine-learning tools to "teach" the model to improve itself in real time, harnessing both Earth observations and the nested high-resolution simulations. 

"The success of computational weather forecasting demonstrates the power of using data to improve the accuracy of computer models; we aim to bring the same successes to climate prediction," says Andrew Stuart, Caltech's Bren Professor of Computing and Mathematical Sciences.

Each of the partner institutions brings a different strength and research expertise to the project. At Caltech, Schneider and Stuart will focus on creating the data-assimilation and machine-learning algorithms, as well as models for clouds, turbulence, and other atmospheric features. At MIT, Ferrari and John Marshall, also a Cecil and Ida Green Professor of Oceanography, will lead a team that will model the ocean, including its large-scale circulation and turbulent mixing. At NPS, Giraldo will lead the development of the computational core of the new atmosphere model in collaboration with Jeremy Kozdon and Lucas Wilcox. At JPL, a group of scientists will collaborate with the team at Caltech's campus to develop process models for the atmosphere, biosphere, and cryosphere.

Funding for this project is provided by the generosity of Eric and Wendy Schmidt (by recommendation of the Schmidt Futures program); Mission Control Earth, an initiative of Mountain Philanthropies; Paul G. Allen Philanthropies; Caltech trustee Charles Trimble; and the National Science Foundation.

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Ernst Frankel, shipping expert and professor emeritus of ocean engineering, dies at 95

Ernst G. Frankel MME ’60, SM ‘60, professor emeritus of ocean engineering who served on MIT’s faculty for 36 years, passed away on Nov. 18 at the age of 95. Frankel, who was also a former professor of management at the Sloan School of Management, was a leading expert in shipping, shipbuilding, and port management.

Born in 1923 in Beuthen, Germany, Frankel served in the Royal Navy during World War II. He also served in the Israeli navy in 1948. After the war, he pursued his bachelor’s degree in marine engineering at London University. He worked for eight years as chief engineer of Zim Navigation Company in Israel, before moving to America and enrolling in MIT to study ocean engineering.

He graduated MIT in 1960 with a master’s of science in ocean engineering and a master’s of marine mechanical engineering. In his graduate thesis, he examined the effects of surge, pitch, and heave on semisubmerged displacement vessels in regular waves. After graduating, he joined the faculty of the then-named Department of Naval Architecture and Marine Engineering. He remained on the faculty until his retirement in 1995.

Throughout his career, Frankel authored 21 books and over 700 academic papers. In 1971, he was named head of the Interdepartmental Commodity Transportation and Economic Development Laboratory, which he also helped establish.

In addition to his work at MIT, Frankel acted as an advisor to a number of governments, international organizations, and shipping companies. He was a member of the Board of Directors of Neptune Orient Lines, one of the world’s largest shipping companies, as well as an advisor to the Panama Canal Authority. He also served as a port, shipping, and aviation advisor to the World Bank, a senior advisor on ports to the secretary general of the International Maritime Organization, and a member of the U.N.-sponsored World Maritime University’s Visiting Committee.

Frankel received a number of accolades throughout his career including a Gold Medal from the government of Great Britain in 1956. He was also a member of the Society of Naval Architects and Marine Engineers and the Transportation Science Section Council.

In the 1970s and 1980s, Frankel expanded his expertise beyond ocean engineering and naval architecture, setting his sights on business and economics. He earned a master’s of business administration in operations management and a doctor of business administration in systems management from Boston University. He also received a PhD in transport economics from the University of Wales in 1985. 

This foundation in economics and business management led to a dual appointment in the Sloan School of Management. In addition to acting as professor of ocean engineering, in the early 1990s Frankel was named a professor of management at Sloan. 

After his retirement in 1995, Frankel remained active in both teaching and research. When Elon Musk announced the Hyperloop concept in 2013, Frankel received some unexpected media attention for research he conducted two decades prior. In the early 1990s, Frankel led a team that designed a vacuum tube which could possibly enable travel between Boston and New York City in 40 minutes — a concept similar to what Musk has been hoping to achieve.

In an interview with the BBC in 2014, Frankel said, “The advantage of a vacuum tube is that you can achieve high speeds. … We built a half-mile long tube at the playing fields of MIT, evacuated it, and then shot things through it in order to measure what sort of velocities we could obtain.”

Funeral services were held in Brookline, Massachusetts, on Nov. 20.

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Building the ultimate record of the ocean

Before the advent of modern observational and modeling techniques, understanding how the ocean behaved required piecing together disparate data — often separated by decades in time — from a handful of sources around the world. In the 1980s, that started to change when technological advancements, such as satellites, floats, drifters, and chemical tracers, made continuous, mass measurements possible.

Still, the resulting new datasets often existed independently of each other, obscuring the big picture of how the ocean circulates, transfers heat, affects climate, stores carbon, and more. That's why Carl Wunsch, professor emeritus of physical oceanography in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS) and member of the EAPS Program in Atmospheres, Oceans and Climate (PAOC), started spearheading an endeavor to reveal that big picture nearly 20 years ago.

Following on the heels of the World Ocean Circulation Experiment (WOCE), Wunsch founded a consortium that sought to combine global ocean datasets with state-of-the-art circulation models. Only with this combination of observation and theory could scientists fully understand the physical and dynamical state of the ocean, and thus its role in climate, Wunsh wrote for the journal Oceanography in 2009. The consortium, which came to be called Estimating the Circulation and Climate of the Ocean (ECCO), was a massive undertaking, including an international network of researchers and governmental bodies to exchange and analyze billions of ocean observations taken from all corners of the globe.

“It was like building a large telescope,” Wunsh says. “That’s what ECCO has been.”

Today, ECCO is largely heralded as the foundational framework for understanding the behavior of the entire ocean for decades to come. Last month, Wunsch and his collaborators published a progress report of sorts on ECCO efforts in The Bulletin of the American Meteorological Society, where they detail the best record of ocean circulation to date: a 20-year average of ocean climate and circulation, called a climatology, that obeys the laws of fluids and includes all of the data collected on the ocean from around the world since 1992.

In the article, “A Dynamically Consistent, Multivariable Ocean Climatology,” the authors outline recent updates to ECCO and explain the deep trove of information that makes it possible, including observations from all of the altimetric satellites that have flown since 1992; temperature and salinity data from depth sensors, expendable bathythermographs, and Argo profiles; and — perhaps most fascinating — data collected via sensors on deep-diving elephant seals.

With an immense volume of data — several billion observations — Wunsch and his collaborators write that the problem soon became how to combine the massive datasets and fit them to a model that would represent a three-dimensional time-evolving ocean over decades. Fortuitously, during ECCO’s initiation, a parallel effort at MIT was underway, led by EAPS Cecil and Ida Green Professor of Oceanography John Marshall, to develop a new ocean general circulation model, called the MIT General Circulation Model, which Wunsch adapted to become the dynamical engine of ECCO.

Detailed understanding of the accuracies and precisions of this methodology, including at least some approximation to an error estimate on all scales, is “an unglamorous but essential activity,” Wunsch says.

Unglamorous as the methodology may be, the results are elegant solutions that adequately fit almost all types of ocean observations and that are, simultaneously, consistent with the model. These solutions are now being used to inform a wide range of research, ranging from ocean variability, biological cycles, coastal physics, and geodesy. Some studies have involved more immediate applications, like predicting physical flow and mixing fields, which influence the ecosystems of lobsters and cod. Others offer better resolution into big-picture issues, like ocean carbon absorption, sea level rise, climate forecasting, and paleoclimate. 

With ECCO, analyzing these problems is no longer confined to the use of single datasets, and researchers are freed from worries that basic properties such as energy conservation are violated in the analysis, says Wunsch.

“It’s a luxury to think about the long term,” he says. But, he adds, it is a scientific and social necessity and requires decades more data to go beyond 20 to 30 years.

Today the ECCO effort stands as proof that model-data combinations looking at decadal and longer time scales are possible, says Wunsch. But the consortium’s goals don’t end there.

“We want this climatology to be used for a greater variety of purposes, and we invite the use and critique of the result by the wider community,” he says. All of the data and the model are publicly available, Wunsch says, and if someone is interested, all they have to do is ask for help.

Wunsch, who is retired but still has an office in the Green Building at MIT, says gladly that his former students and group members have now taken over the ECCO effort. In fact, the article co-authors were all once Wunsch’s advisees: Associate Professor Patrick Heimbach of the University of Texas at Austin, Principal Scientist Ichiro Fukumori of the NASA Jet Propulsion Laboratory, and Rui M. Ponte of Atmospheric and Environmental Research (AER), Inc. 

Wunsch hopes that ECCO’s spread to the next generation of researchers will make it more resistant to fickle political and economic trends. Because understanding how the ocean is behaving under a changing climate — and how it is likely to change in the future — requires uninterrupted observations of the immense complexity of ocean circulation.

“There can’t be any gaps in data,” said Wunsh. “Gaps are deadly.”

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Oceanographers produce first-ever images of entire cod shoals

For the most part, the mature Atlantic cod is a solitary creature that spends most of its time far below the ocean’s surface, grazing on bony fish, squid, crab, shrimp, and lobster — unless it’s spawning season, when the fish flock to each other by the millions, forming enormous shoals that resemble frenzied, teeming islands in the sea.

These massive spawning shoals may give clues to the health of the entire cod population — an essential indicator for tracking the species’ recovery, particularly in regions such as New England and Canada, where cod has been severely depleted by decades of overfishing.

But the ocean is a murky place, and fish are highly mobile by nature, making them difficult to map and count. Now a team of oceanographers at MIT has journeyed to Norway — one of the last remaining regions of the world where cod still thrive — and used a synoptic acoustic system to, for the first time, illuminate entire shoals of cod almost instantaneously, during the height of the spawning season.

The team, led by Nicholas Makris, professor of mechanical engineering and director of the Center for Ocean Engineering, and Olav Rune Godø of the Norwegian Institute of Marine Research, was able to image multiple cod shoals, the largest spanning 50 kilometers, or about 30 miles. From the images they produced, the researchers estimate that the average cod shoal consists of about 10 million individual fish.

They also found that when the total population of cod dropped below the average shoal size, the species remained in decline for decades.

“This average shoal size is almost like a lower bound,” Makris says. “And the sad thing is, it seems to have been crossed almost everywhere for cod.”

Makris and his colleagues have published their results today in the journal Fish and Fisheries.

Echoes in the deep

For years, researchers have attempted to image cod and herring shoals using high-frequency, hull-mounted sonar instruments, which direct narrow beams below moving research vessels. These ships traverse a patch of the sea in a lawnmower-like pattern, imaging slices of a shoal by emitting high-frequency sound waves, and measuring the time it takes for the signals to bounce off a fish and back to the ship. But this method requires a vessel to move slowly through the waters to get counts; one survey can take many weeks to complete and typically samples only a small portion of any particular expansive shoal, often completely missing shoals between survey tracks and never capturing shoal dynamics

The team made use of the Ocean Acoutic Waveguide Remote Sensing, or OAWRS system, an imaging technique developed at MIT by Makris and co-author Purnima Ratilal, which emits low-frequency sound waves that can travel over a much wider range than high-frequency sonar. The sound waves are essentially tuned to bounce off fish, in particular, off their swim bladder — a gas-filled organ that reflects sound waves — like echoes off a tiny drum. As these echoes return to the ship, researchers can aggregate them to produce an instant picture of millions of fish over vast areas.

Making passage

In February and March of 2014, Makris and a team of students and researchers headed to Norway to count cod, herring, and capelin during the height of their spawning seasons. They towed OAWRS aboard the Knorr, a U.S. Navy research vessel that is operated by the Woods Hole Oceanographic Institution and is best known as the ship aboard which researchers discovered the remnants of the Titanic.

The ship left Woods Hole and crossed the Atlantic over two weeks, during which time the crew continuously battled storms and choppy winter seas. When they finally arrived at the southern coast of Norway, they spent the next three weeks imaging herring, cod, and capelin along the entire Norwegian coast, from the town of Alesund, north to the Russian border.

“The underwater terrain was as treacherous as the land, with submerged seamounts, ridges, and fjord channels,” Makris recalls. “Billions of herring actually would hide in one of these submerged fjords near Alesund during the daytime, about 300 meters down, and come up at night to shelves about 100 meters deep. Our mission there was to instantaneously image entire shoals of them, stretching for kilometers, and sort out their behavior.”

A window through a hurricane

As they moved up the Norwegian coast, the researchers towed a 0.5-kilometer-long array of passive underwater microphones and a device that emitted low-frequency sound waves. After imaging herring shoals in southern Norway, the team moved north to Lofoten, a dramatic archipelago of sheer cliffs and mountains, depicted most famously in Edgar Allen Poe’s “Descent into the Maelstrom,” in which the poet made note of the region’s abundance of cod.

To this day, Lofoten remains a primary spawning ground for cod, and there, Makris’ team was able to produce the first-ever images of an entire cod shoal, spanning 50 kilometers.

Toward the end of their journey, the researchers planned to image one last cod region, just as a hurricane was projected to hit. The team realized there would be only two windows of relatively calm winds in which to operate their imaging equipment.

“So we went, got good data, and fled to a nearby fjord as the eye wall struck,” Makris recalls. “We ended with 30-foot seas at dawn and the Norwegian coast guard, in a strangely soothing young voice, urging us to evacuate the area.” The team was able to image a slightly smaller shoal there, spanning about 10 kilometers, before completing the expedition.

On the brink

Back on dry land, the researchers analyzed their images and estimated that an average shoal size consists of about 10 million fish. They also looked at historical tallies of cod, in Norway, New England, the North Sea and Canada, and discovered an interesting trend: Those regions — like New England  — that experienced long-lasting declines in cod stocks did so when the total cod population dropped below roughly 10 million — the same number as an average shoal. When cod dropped below this threshold, the population took decades to recover, if it did at all.

In Norway, the cod population always stayed above 10 million and was able to recover, climbing back to preindustrial levels over the years, even after significant declines in the mid-20th century. The team also imaged shoals of herring  and found a similar trend through history: When the total population dropped below the level of an average herring spawning shoal, it took decades for the fish to recover.

Makris and Godø hope that the team’s results will serve as a measuring stick of sorts, to help researchers keep track of fish stocks and recognize when a species is on the brink.

“The ocean is a dark place, you look out there and can’t see what’s going on,” Makris says. “It’s a free-for-all out there, until you start shining a light on it and seeing what’s happening. Then you can properly appreciate and understand and manage.” He adds “Even if field work is difficult, time consuming, and expensive, it is essential to confirm and inspire theories, models, and simulations.”

This research was supported, in part, by the Norwegian Institute of Marine Research, the Office of Naval Research, and the National Science Foundation.

from MIT News - Oceanography and ocean engineering https://ift.tt/2D6HFfT

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