Woodwell Climate’s Dr. Sue Natali appointed to DOI adaptation science council

“There’s nothing quite like ArcticGRO,” says Dr. Zolkos. “It’s unique in that it measures a comprehensive suite of chemical parameters across the Arctic’s largest rivers, uses consistent sampling and analytical methods across the rivers, and sampling occurs at the same times and locations. The consistency of ArcticGRO is increasingly valuable, because it is building a dataset which allows scientists around the world to detect, monitor, and understand northern environmental change in ways that no other scientific program does.”

We never would have known

A few thousand miles south of the Arctic circle, on the marshy coastline of Massachusetts, another long-term ecological research project has entered its third decade as well. The brainchild of Senior Scientist Dr. Linda Deegan, the TIDE project is unique even among long-term studies. Rather than simply monitoring the nutrient flows in the salt marshes of Plum Island Estuary, the TIDE project has been altering nutrients in carefully controlled amounts to understand the long term impacts of human development in coastal ecosystems.

TIDE focuses on nitrogen, an element of most fertilizers and a common pollutant from developed areas in the uplands. Previous studies of nitrogen impacts indicated coastal marsh plants could absorb a lot of nitrogen with no ill effects. But that dynamic was only examined on short time scales, and in small plots of marsh. Whether there were changes that might require many years or many acres to be detected, was unknown.

Thus TIDE was designed to increase nitrogen concentrations in the water to mimic coastal eutrophication across three marshes in the Plum Island estuary and document which effects might cascade through the system. The initial grant was for five years, but Dr. Deegan and her collaborators wanted to keep the project running for at least a decade, if not more, expecting the changes might be slow to reveal themselves.

After years of observations, Dr. Deegan says she remembers the exact moment they discovered a significant change.

“Several of the senior scientists—myself included—came back at the end of a long field day each of them saying, ‘I don’t remember it being this hard to walk through the nutrient enriched marsh when we started this project. Am I just getting older or has something changed?’ And then one of the new students said, ‘I thought that marsh was always like that—well, it’s not like that in the other sites where we haven’t added nitrogen.’”

So they followed the hunch, made some new measurements, and found the structure of the marsh had changed significantly with the added nitrogen. The plants, suddenly awash in a necessary component for growth, no longer needed to dedicate their energy to making roots to seek out nutrients; their root systems were shallower and less dense, thus less capable of holding the marsh together. At the same time, nitrogen-consuming microbes were breaking down organic matter in search of carbon to fuel the chemical processes that allow them to take up nitrogen. This combination made the marsh creek edges more susceptible to erosion by tides and storms.

It took more years than most experiments are run for, but increased susceptibility to erosion steadily altered the shape of stream channels. The ground along the edges of the streams, previously held in place by a deep network of roots, now collapsed underfoot. Chunks of marsh fell off the edges as the roots no longer held the marsh together. As the years went on, fish and other organisms that travel along stream floors to seek out food began to suffer from difficult terrain, resulting in slower growth and fewer fish.

These findings, published in Nature, upended the way people thought about the effects of eutrophication on marshes. “And we never would have known any of that,” says Dr. Deegan. “If we hadn’t done the project at an ecosystem scale and over such a long time.”

A pipe you can turn off

Over the decades, the TIDE project not only faced the challenges of running a consistent project for so long, but also of justifying making intentional changes to an otherwise healthy ecosystem. The question lingered: If the goal is to protect ecosystems from human disruption, what do we gain from knowingly tinkering with them?

Humans have already accidentally conducted thousands of ecological change experiments across the globe. Casually inflicted pollution, deforestation, or extinction with no control group, no careful observations, no time limits or safeguards—by scientific standards these are reckless and poorly designed experiments.

In Dr. Deegan’s mind, this makes controlled studies like TIDE even more significant.

“We need to know the true impact of the changes that we are already imposing on the environment. And once we do, we need to be able to halt those changes that threaten the integrity of an ecosystem.” Says Dr. Deegan. “This is a pipe I can easily turn off. Not like when you build a housing development and then you’re stuck with all those houses and their impacts forever.”

Climate change is perhaps the most all-encompassing of these involuntary experiments. As ArcticGRO’s and TIDEs results indicate, ecosystem responses to human disturbance, whether it is climate warming or nutrient over enrichment, are complex. Understanding and adapting to these responses will depend on continued monitoring, observation and experimentation.

A testament to the people

In the world of research, rife with limited grants and time-bound fellowships, ArcticGRO and TIDE have been uniquely successful. Research Associate, Hillary Sullivan, who has been part of the TIDE project since 2012, attributes this to the dedication of the researchers, who showed up year after year to get the research done even when funding wasn’t certain or while enduring a global pandemic.

“These large scale projects are a testament to the people that are involved in the effort, and the work that goes in behind the scenes to keep it running,” says Sullivan.

Both ArcticGRO and TIDE plan to continue. ArcticGRO is seeking additional funding to analyze new chemical constituents and continue providing invaluable data for scientists and educators to understand how rivers are responding to a warming climate. “ArcticGRO has improved our understanding of the Arctic, and our work is just getting started,” says Dr. Zolkos. “Continuing will be essential for generating new insights on climate change, northern ecosystems, and societal implications.”

TIDE has now shifted to a new phase of study — observing the legacy of the added nitrogen on marsh recovery in the face of climate change induced sea level rise. Nitrogen additions were halted 6 years ago and researchers hope to gain insights into marsh restoration and ways to improve their resilience to sea level rise.

Thinking in the long-term is not something humans have historically excelled at, Dr. Deegan admits. But the more we try to expand our curiosity past immediate cause and effect, the better we get at understanding nature. If you want to understand an ecosystem, you have to think like an ecosystem—which means longer time scales and larger areas that encompass every aspect of the system.

“Nature tends to take the long view and people tend to take the short,” says Dr. Deegan. “So if you can stick with it for the long view, I think you see things in a very different way.”

Arctic wetlands are known emitters of the strong greenhouse gas methane. Well-drained soils, on the other hand, remove methane from the atmosphere. In the Arctic and boreal biomes, well-drained upland soils cover more than 80% of the land area, but their potential importance for drawing methane from the atmosphere—the underlying mechanisms, environmental controls and even the magnitude of methane uptake—have not been well understood.

A recent study led by researchers from the University of Eastern Finland and University of Montreal, in collaboration with Woodwell Climate Research Scientist, Dr. Anna Virkkala, has expanded our understanding of these dynamics, finding that Arctic soil methane uptake may be larger than previously thought. The results show uptake increasing under dry conditions and with availability of a type of soil organic carbon that can be used in microbial uptake processes.

The study was primarily conducted at Trail Valley Creek, a tundra site in the Western Canadian Arctic. The authors used a unique experimental set-up consisting of 18 automated chambers for continuous measurements of methane fluxes. No other automated chamber system exists this far North in the Canadian Arctic, and only few exist above the Arctic circle globally, most of which are installed at methane-emitting sites.

The high-resolution measurements of methane uptake (more than 40,000 flux measurements) revealed previously unknown daily and seasonal dynamics: while methane uptake in early and peak summer was largest during the afternoons, coinciding with maximum soil temperature, uptake during late summer peaked during the night. The study shows that the strongest methane uptake coincided with peaks of ecosystem carbon dioxide respiration—meaning that as methane is removed from the atmosphere, carbon dioxide production in the soil is high. Complementing flux measurements at Trail Valley Creek with measurements at other sites spread across the Canadian and Finnish Arctic showed that the availability of soil organic carbon and other nutrients may promote methane consumption in Arctic soils.

“The methane cycle has previously been primarily studied in wetlands because of their high methane emissions, but this study shows that drier ecosystems are also very important in the methane cycle,” says Dr. Virkkala.

These findings are highly relevant for estimating the current Arctic carbon budget, and for predicting the future response of Arctic soil methane uptake to a changing climate. According to the study, high-latitude warming itself, occurring up to four times faster in the Arctic than the rest of the world, will promote atmospheric methane uptake to a lesser extent than the associated large-scale drying.

“The Arctic methane budget has remained highly uncertain,” remarks the paper’s lead author, Dr. Carolina Voigt. “Our research provides one potential mechanism that might explain those uncertainties, and highlights the importance of methane measurements in drier ecosystems to calculate more accurate methane budgets.”

Climate change is having profound effects on the chemical composition of large Arctic rivers, signaling changes both on land and in the coastal ocean, according to new international research examining chemical signatures in rivers across Canada, Alaska and Russia.

The study, the result of a two-decade effort by the Arctic Great Rivers Observatory, analyzed nearly twenty years of water chemistry and discharge data collected from six rivers that comprise 60 percent of the Arctic Ocean watershed.

The researchers tracked river water ions, key nutrients, and dissolved organic carbon, among other indicators. They found that chemical concentrations changed substantially over the past two decades, but trends across chemical groups were different, with some increasing, some decreasing, and others showing little change.

The international scientific collaboration tracked river water ions, key nutrients and dissolved organic carbon among other metrics. Chemical concentrations changed substantially over the past two decades, but trends across chemical groups were different with some increasing, some decreasing, and some showing little change.

“The only way that this divergence in trends is possible is if multiple factors of change are being brought to bear on the Arctic system at the same time,” says Woodwell Research Assistant, Anya Suslova and co-author on the paper. “We know that permafrost is thawing, vegetation is changing and moving northward, and processing of nutrients and organic matter may be happening more quickly. Global climate change appears to be causing many systems that are critical for ecosystem function to change at the same time—and that change is showing up in the chemical composition of river water.”

Key nutrients observed in river water are declining, according to the study. This trend suggests warming temperatures are increasing biological uptake of nutrients on land or in aquatic ecosystems, leading to an overall decrease despite factors like wildfire and permafrost thaw releasing more nutrients into the waterways.

ArcticGRO represents a partnership between researchers at Woodwell Climate Research Center, University of Alberta, the Marine Biological Laboratory, Florida State University, and the University of New Hampshire, as well as scientific and community collaborators in Siberia and the North American Arctic.

“The success of this study is largely due to its collaborative nature,” says Dr. Max Holmes, Woodwell Climate President and CEO, and founder of the ArcticGRO project. “Without the dedication of scientists and community members across the Arctic, we never would have been able to generate the comprehensive dataset that allowed us to uncover these insights.”

Because trends in river water chemistry are not always acting in the same direction, Dr. Holmes and Suslova say the study will help give scientists a blueprint for thinking about how Arctic change will play out.

“It’s been around a long time, actually,” muses Senior Scientist, Dr. Jennifer Francis. “It’s gotten more sophisticated, sure, and a lot of the applications are new. But the concept of artificial intelligence is not.”

Dr. Francis has been working with it for almost two decades, in fact. Although, back when she started working with a research tool called “neural networks,” they were less widely known in climate science and weren’t generally referred to as artificial intelligence.

But recently, AI seems to have come suddenly out of the woodwork, infusing nearly every field of research, analysis, and communication. Climate science is no exception. From mapping thawing Arctic tundra, to tracking atmospheric variation, and even transcribing audio interviews into text for use in this story, AI in varying forms is woven into the framework of how Woodwell Climate creates new knowledge.

AI helps climate scientists track trends and patterns

The umbrella term of artificial intelligence encompasses a diverse set of tools that can be trained to do tasks as diverse as imitating human language (à la ChatGPT), playing chess, categorizing images, solving puzzles, and even restoring damaged ancient texts.

Dr. Francis uses AI to study variations in atmospheric conditions, most recently weather whiplash events— when one stable weather pattern suddenly snaps to a very different one (think months-long drought in the west disrupted by torrential rain). Her particular method is called self-organizing maps which, as the name suggests, automatically generates a matrix of maps showing atmospheric data organized so Dr. Francis can detect these sudden snapping patterns.

“This method is perfect for what we’re looking for because it removes the human biases. We can feed it daily maps of, say, what the jetstream looks like, and then the neural network finds characteristic patterns and tells us exactly which days the atmosphere is similar to each pattern. There are no assumptions,” says Dr. Francis.

This aptitude for pattern recognition is a core function of many types of neural networks. In the Arctic program, AI is used to churn through thousands of satellite images to detect patterns that indicate specific features in the landscape using a technique originally honed for use in the medical industry to read CT scan images.

Data science specialist, Dr. Yili Yang, uses AI models trained to identify features called retrogressive thaw slumps (RTS) in permafrost-rich regions of the Arctic. Thaw slumps form in response to subsiding permafrost and can be indicators of greater thawing on the landscape, but they are hard to identify in images.

“Finding one RTS is like finding a single building in a city,” Dr. Yang says. It’s time consuming, and it really helps if you already know what you’re looking for. Their trained neural network can pick the features out of high-resolution satellite imagery with fairly high accuracy.

Research Assistant Andrew Mullen uses a similar tool to find and map millions of small water bodies across the Arctic. A neural network generated a dataset of these lakes and ponds so that Mullen and other researchers could track seasonal changes in their area.

And there are opportunities to use AI not just for the data creation side of research, but trend analysis as well. Associate Scientist Dr. Anna Liljedahl leads the Permafrost Discovery Gateway project which used neural networks to create a pan-Arctic map of ice wedge polygons—another feature that indicates ice-rich permafrost in the ground below and, if altered over time, could suggest permafrost thaw.

“Our future goals for the Gateway would utilize new AI models to identify trends or patterns or relationships between ice wedge polygons and elevation, soil or climate data,” says Dr. Liljedahl.

How do neural networks work?

The projects above are examples of neural-network-based AI. But how do they actually work?

The comparison to human brains is apt. The networks are composed of interconnected, mathematical components called “neurons.” Also like a brain, the system is a web of billions upon billions of these neurons. Each neuron carries a fragment of information into the next, and the way those neurons are organized determines the kind of tasks the model can be trained to do.

“How AI models are built is based on a really simple structure—but a ton of these really simple structures stacked on top of each other. This makes them complex and highly capable of accomplishing different tasks,” says Mullen.

In order to accomplish these highly specific tasks, the model has to be trained. Training involves feeding the AI input data, and then telling it what the correct output should look like. The process is called supervised learning, and it’s functionally similar to teaching a student by showing it the correct answers to the quiz ahead of time, then testing them, and repeating this cycle over and over until they can reliably ace each test.

In the case of Dr. Yang’s work, the model was trained using input satellite images of the Arctic tundra with known retrogressive thaw slump features. The model outputs possible thaw slumps which are then compared to the RTS labels hand-drawn by Research Assistant Tiffany Windholz. It then assesses the similarity between the prediction and the true slump, and automatically adjusts its billions of neurons to improve the similarity. Do this a thousand times and the internal structure of the AI starts to learn what to look for in an image. Sharp change in elevation? Destroyed vegetation and no pond? Right geometry? That’s a potential thaw slump.

Just as it would be impossible to pull out any single neuron from a human brain and determine its function, the complexity of a neural network makes the internal workings of AI difficult to detail—Mullen calls it a “black box”—but with a large enough training set you can refine the output without ever having to worry about the internal workings of the machine.

Speeding up and scaling up

Despite its reputation in pop culture, and the uncannily human way these algorithms can learn, AI models are not replacing human researchers. In their present form, neural networks aren’t capable of constructing novel ideas from the information they receive—a defining characteristic of human intelligence. The information that comes out of them is limited by the information they were trained on, in both scope and accuracy.

But once a model is trained with enough accurate data, it can perform in seconds a task that might take a human half an hour. Multiply that across a dataset of 10,000 individual images and it can condense months of image processing into a few hours. And that’s where neural networks become crucial for climate research.

“They’re able to do that tedious, somewhat simple work really fast,” Mullen says. “Which allows us to do more science and focus on the bigger picture.”

Dr. Francis adds, “they can also elucidate patterns and connections that humans can’t see by gazing at thousands of maps or images.”

Another superpower of these AI models is their capability for generalization. Train a model to recognize ponds or ice wedges or thaw slumps with enough representative images and you can use it to identify the water bodies across the Arctic—even in places that would be hard to reach for field data collection.

All these qualities dramatically speed up the pace of research, which is critical as the pace of climate change itself accelerates. The faster scientists can analyze and understand changes in our environment, the better we’ll be able to predict, adapt to, and maybe lessen the impacts to come.

Carbon cycling is an essential part of life on the planet. Plants and animals use the element for cellular growth, it can be stored in rocks and minerals or in the ocean, and of course it can move into the atmosphere, where it contributes to a warming planet.

A new study led by Dr. Megan Behnke, a former Florida State University doctoral student and Woodwell Polaris Project participant who is now a researcher at the University of Alaska, found that plants and small organisms in Arctic rivers could be responsible for more than half the particulate organic matter (a carbon-rich nutrient) flowing to the Arctic Ocean. That’s a significantly greater proportion than previously estimated, and it has implications for how much carbon is sequestered in the ocean versus how much moves into the atmosphere.

Scientists have long measured the organic matter in rivers to understand how carbon cycles through watersheds. But this research, published in Proceedings of the National Academy of Sciences, shows that organisms in the Arctic’s major rivers are a crucial contributor to carbon export, accounting for 40 to 60 percent of the particulate organic matter—tiny bits of decaying organisms—flowing into the ocean.

“When people thought about these major Arctic rivers and many other rivers globally, they tended to think of them as sewers of the land, exporting the waste materials from primary production and decomposition on land,” said Dr. Rob Spencer, a professor in the Department of Earth, Ocean and Atmospheric Science at FSU, and collaborator on the paper. “This study highlights that there’s a lot of life in these rivers themselves and that a lot of the organic material that is exported is coming from production in the rivers.”

Scientists study carbon exported via waterways to better understand how the element cycles through the environment. As organic material on land decomposes, it can move into rivers, which in turn drain into the ocean. Some of that carbon supports marine life, and some sinks to the bottom of the ocean, where it is buried in sediments.

The study was supported by the Arctic Great Rivers Observatory, and it examines six major rivers flowing in the Arctic Ocean: The Yukon and Mackenzie in North America, and the Ob’, Yenisey, Lena, and Kolyma in Russia. Using data collected over almost a decade, they built models that used the stable and radioactive isotope signatures of carbon and the carbon-to-nitrogen ratios of the particulate organic matter to determine the contribution of possible sources to each river’s chemistry.

Not all particulate organic matter is created equal, the researchers found. Carbon from soils that gets washed downstream is more likely to be buried in the ocean than the carbon produced within a river. That carbon is more likely to stay floating in the ocean, be eaten by organisms there and eventually breathed out as carbon dioxide.

“It’s like the difference between a french fry and a stem of broccoli,” said Dr. Behnke. “That broccoli is going to stay in storage in your freezer, but the french fry is much more likely to get eaten.”

That means a small increase in a river’s biomass could be equivalent to a larger increase in organic material coming from the land. If the carbon in that organic matter moves to the atmosphere, it would affect the rate of carbon cycling and associated climate change in the Arctic.

“I always get excited as a scientist or a researcher when we find new things, and this study found something new in the way that these big Arctic rivers work and how they export carbon to the ocean,” Dr. Spencer said. “We have to understand the modern carbon cycle if we’re really going to begin to understand and predict how it’s going to change. This is really relevant for the Arctic at the rate that it’s warming and due to the vast carbon stores that it holds.”

The study was an international endeavor— a feature that, Dr. Behnke notes, is critical to Arctic work, especially as climate change advances.

“That pan-Arctic view of science is more important than ever,” Dr. Behnke said. “The changes that are occurring are far bigger than one institution in one country, and we need these longstanding collaborations. That’s critically important to continue.”