However, a new study by an MIT researcher finds that scientists may have to rethink the relationship between the ocean’s circulation and its long-term capacity to store carbon. As the ocean gets weaker, it could release more carbon from the deep ocean into the atmosphere instead.

The reason has to do with a previously uncharacterized feedback between the ocean’s available iron, upwelling carbon and nutrients, surface microorganisms, and a little-known class of molecules known generally as “ligands.” When the ocean circulates more slowly, all these players interact in a self-perpetuating cycle that ultimately increases the amount of carbon that the ocean outgases back to the atmosphere.

“By isolating the impact of this feedback, we see a fundamentally different relationship between ocean circulation and atmospheric carbon levels, with implications for the climate,” says study author Jonathan Lauderdale, a research scientist in MIT’s Department of Earth, Atmospheric, and Planetary Sciences. “What we thought is going on in the ocean is completely overturned.”

Lauderdale says the findings show that “we can’t count on the ocean to store carbon in the deep ocean in response to future changes in circulation. We must be proactive in cutting emissions now, rather than relying on these natural processes to buy us time to mitigate climate change.”

His study will appear in the journal Nature Communications.

Box flow

In 2020, Lauderdale led a study that explored ocean nutrients, marine organisms, and iron, and how their interactions influence the growth of phytoplankton around the world. Phytoplankton are microscopic, plant-like organisms that live on the ocean surface and consume a diet of carbon and nutrients that upwell from the deep ocean and iron that drifts in from desert dust.

The more phytoplankton that can grow, the more carbon dioxide they can absorb from the atmosphere via photosynthesis, and this plays a large role in the ocean’s ability to sequester carbon.

For the 2020 study, the team developed a simple “box” model, representing conditions in different parts of the ocean as general boxes, each with a different balance of nutrients, iron, and ligands — organic molecules that are thought to be byproducts of phytoplankton. The team modeled a general flow between the boxes to represent the ocean’s larger circulation — the way seawater sinks, then is buoyed back up to the surface in different parts of the world.

This modeling revealed that, even if scientists were to “seed” the oceans with extra iron, that iron wouldn’t have much of an effect on global phytoplankton growth. The reason was due to a limit set by ligands. It turns out that, if left on its own, iron is insoluble in the ocean and therefore unavailable to phytoplankton. Iron only becomes soluble at “useful” levels when linked with ligands, which keep iron in a form that plankton can consume. Lauderdale found that adding iron to one ocean region to consume additional nutrients robs other regions of nutrients that phytoplankton there need to grow. This lowers the production of ligands and the supply of iron back to the original ocean region, limiting the amount of extra carbon that would be taken up from the atmosphere.

Unexpected switch

Once the team published their study, Lauderdale worked the box model into a form that he could make publicly accessible, including ocean and atmosphere carbon exchange and extending the boxes to represent more diverse environments, such as conditions similar to the Pacific, the North Atlantic, and the Southern Ocean. In the process, he tested other interactions within the model, including the effect of varying ocean circulation.

He ran the model with different circulation strengths, expecting to see less atmospheric carbon dioxide with weaker ocean overturning — a relationship that previous studies have supported, dating back to the 1980s. But what he found instead was a clear and opposite trend: The weaker the ocean’s circulation, the more CO₂ built up in the atmosphere.

“I thought there was some mistake,” Lauderdale recalls. “Why were atmospheric carbon levels trending the wrong way?”

When he checked the model, he found that the parameter describing ocean ligands had been left “on” as a variable. In other words, the model was calculating ligand concentrations as changing from one ocean region to another.

On a hunch, Lauderdale turned this parameter “off,” which set ligand concentrations as constant in every modeled ocean environment, an assumption that many ocean models typically make. That one change reversed the trend, back to the assumed relationship: A weaker circulation led to reduced atmospheric carbon dioxide. But which trend was closer to the truth?

Lauderdale looked to the scant available data on ocean ligands to see whether their concentrations were more constant or variable in the actual ocean. He found confirmation in GEOTRACES, an international study that coordinates measurements of trace elements and isotopes across the world’s oceans, that scientists can use to compare concentrations from region to region. Indeed, the molecules’ concentrations varied. If ligand concentrations do change from one region to another, then his surprise new result was likely representative of the real ocean: A weaker circulation leads to more carbon dioxide in the atmosphere.

“It’s this one weird trick that changed everything,” Lauderdale says. “The ligand switch has revealed this completely different relationship between ocean circulation and atmospheric CO₂ that we thought we understood pretty well.”

Slow cycle

To see what might explain the overturned trend, Lauderdale analyzed biological activity and carbon, nutrient, iron, and ligand concentrations from the ocean model under different circulation strengths, comparing scenarios where ligands were variable or constant across the various boxes.

This revealed a new feedback: The weaker the ocean’s circulation, the less carbon and nutrients the ocean pulls up from the deep. Any phytoplankton at the surface would then have fewer resources to grow and would produce fewer byproducts (including ligands) as a result. With fewer ligands available, less iron at the surface would be usable, further reducing the phytoplankton population. There would then be fewer phytoplankton available to absorb carbon dioxide from the atmosphere and consume upwelled carbon from the deep ocean.

“My work shows that we need to look more carefully at how ocean biology can affect the climate,” Lauderdale points out. “Some climate models predict a 30 percent slowdown in the ocean circulation due to melting ice sheets, particularly around Antarctica. This huge slowdown in overturning circulation could actually be a big problem: In addition to a host of other climate issues, not only would the ocean take up less anthropogenic CO₂ from the atmosphere, but that could be amplified by a net outgassing of deep ocean carbon, leading to an unanticipated increase in atmospheric CO₂ and unexpected further climate warming.”

Researchers at the University of Reading and Durham University collected an enormous dataset of brain and body sizes from around 1,500 species to clarify centuries of controversy surrounding brain size evolution.

Bigger brains relative to body size are linked to intelligence, sociality, and behavioural complexity — with humans having evolved exceptionally large brains. The new research, published today (Monday, 8 July), reveals the largest animals do not have proportionally bigger brains, challenging long-held beliefs about brain evolution.

Professor Chris Venditti, lead author of the study from the University of Reading, said: “For more than a century, scientists have assumed that this relationship was linear — meaning that brain size gets proportionally bigger, the larger an animal is. We now know this is not true. The relationship between brain and body size is a curve, essentially meaning very large animals have smaller brains than expected.”

Professor Rob Barton, co-author of the study from Durham University, said: “Our results help resolve the puzzling complexity in the brain-body mass relationship. Our model has a simplicity that means previously elaborate explanations are no longer necessary — relative brain size can be studied using a single underlying model.”

Beyond the ordinary

The research reveals a simple association between brain and body size across all mammals which allowed the researchers to identify the rule-breakers — species which challenge the norm.

Among these outliers includes our own species, Homo sapiens, which has evolved more than 20 times faster than all other mammal species, resulting in the massive brains that characterise humanity today. But humans are not the only species to buck this trend.

All groups of mammals demonstrated rapid bursts of change — both towards smaller and larger brain sizes. For example, bats very rapidly reduced their brain size when they first arose, but then showed very slow rates of change in relative brain size, suggesting there may be evolutionary constraints related to the demands of flight.

There are three groups of animals that showed the most pronounced rapid change in brain size: primates, rodents, and carnivores. In these three groups, there is a tendency for relative brain size to increase in time (the “Marsh-Lartet rule”). This is not a trend universal across all mammals, as previously believed.

Dr Joanna Baker, co-author of the study also from the University of Reading, said: “Our results reveal a mystery. In the largest animals, there is something preventing brains from getting too big. Whether this is because big brains beyond a certain size are simply too costly to maintain remains to be seen. But as we also observe similar curvature in birds, the pattern seems to be a general phenomenon — what causes this ‘curious ceiling’ applies to animals with very different biology.”

It is the year 1181 and in Japan the Genpei War (1180-85) has recently begun. It will lead to a shift in political power from aristocratic families to the new military-based shogunate, which will establish itself in the coastal city of Kamakura near modern-day Tokyo. A record of this tumultuous period was compiled in a diary format in the Azuma Kagami. It chronicled not only people’s lives and key events (with varying accuracy), but other daily observations, including the appearance of a new star.

“There are many accounts of this temporary guest star in historical records from Japan, China and Korea. At its peak, the star’s brightness was comparable to Saturn’s. It remained visible to the naked eye for about 180 days, until it gradually dimmed out of sight. The remnant of the SN 1181 explosion is now very old, so it is dark and difficult to find,” explained lead author Takatoshi Ko, a doctoral student from the Department of Astronomy at the University of Tokyo.

The remnant of this guest star, labeled supernova remnant (SNR) 1181, was found to have been created when two extremely dense, Earth-sized stars, called white dwarfs, collided. This created a rare type of supernova, called a Type Iax supernova, which left behind a single, bright and fast-rotating white dwarf. Aided by observations on its position noted in the historical document, modern astrophysicists finally pinpointed its location in 2021 in a nebula towards the constellation Cassiopeia.

Due to its rare nature and location within our galaxy, SNR 1181 has been the subject of much observational research. This suggested that SNR 1181 is made up of two shock regions, an outer region and an inner one. In this new study, the research group analyzed the latest X-ray data to construct a theoretical computer model to explain these observations, and which has recreated the previously unexplained structure of this supernova remnant.

The main challenge was that according to conventional understanding, when two white dwarfs collide like this, they should explode and disappear. However, this merger left behind a white dwarf. The spinning white dwarf was expected to create a stellar wind (a fast-flowing stream of particles) immediately after its formation. However, what the researchers found was something else.

“If the wind had started blowing immediately after SNR 1181’s formation, we couldn’t reproduce the observed size of the inner shock region,” said Ko. “However, by treating the wind’s onset time as variable, we succeeded in explaining all of the observed features of SNR 1181 accurately and unraveling the mysterious properties of this high-speed wind. We were also able to simultaneously track the time evolution of each shock region, using numerical calculations.”

The team was very surprised to find that according to their calculations, the wind may have started blowing only very recently, within the past 20-30 years. They suggest this may indicate that the white dwarf has started to burn again, possibly due to some of the matter thrown out by the explosion witnessed in 1181 falling back to its surface, increasing its density and temperature over a threshold to restart burning.

To validate their computer model, the team is now preparing to further observe SNR 1181 using the Very Large Array (VLA) radio telescope based in central New Mexico state in the U.S., and the 8.2 meter-class Subaru Telescope in the U.S. state of Hawaii.

“The ability to determine the age of supernova remnants or the brightness at the time of their explosion through archaeological perspectives is a rare and invaluable asset to modern astronomy,” said Ko. “Such interdisciplinary research is both exciting and highlights the immense potential for combining diverse fields to uncover new dimensions of astronomical phenomena.”