Growing up in New Jersey, Emily Wilson regularly passed tidal marshes without giving them much thought. They were part of the coastal landscape—stretches of green and blue she saw from the road.
It wasn't until she began studying environmental science as an undergraduate that she realized how remarkable they were—plants thriving in salty, waterlogged environments amidst the constant ebb and flow of tides.
Today, as a Boston University PhD candidate in Earth & Environment , Wilson studies those same ecosystems—and has discovered that the plants she once drove past may hold important information to more accurately track the global climate.
Tidal marshes are important natural climate solutions because they remove carbon dioxide from the atmosphere and store large amounts of carbon in their soils. But they also emit methane, a potent greenhouse gas. Accurately accounting for both is critical to understanding their overall climate benefit—and to policies and carbon markets that put a value on protecting and restoring wetlands.
A new study led by Wilson and published in the Proceedings of the National Academy of Sciences (PNAS) finds that plant species are a far better predictor of methane emissions from tidal marshes than salinity, which scientists have relied on for decades.
"We found that plant species are a robust proxy for methane fluxes, outperforming all previously described proxies," Wilson says. "Because plant species are easier to identify than directly measuring methane fluxes and are often already mapped, this approach provides researchers and managers with a practical means of estimating methane emissions across tidal marshes."
How Plants Became Part of the Equation
The discovery builds on more than a decade of research in the lab of Robinson "Wally" Fulweiler , a BU professor of Earth & Environment and Biology. Earlier work in Fulweiler's lab examined a wide range of environmental conditions that scientists thought might influence greenhouse gas emissions.
"Most of them were not related," Fulweiler says. Instead, plants stood out. "Plants live in certain environments; they reflect the long-term conditions—that is they integrate environmental signals."
Those observations, combined with a growing body of research from other scientists, led Wilson to ask whether plants could predict methane emissions not just within individual marshes, but across tidal marshes worldwide.
"Going into this study, our hypothesis was that plants were a strong predictor of methane fluxes based on our own research and conclusions from other papers," Wilson says. "But beyond studies conducted at one to a few tidal marshes there was no consensus that plant species could be used to estimate fluxes at larger scales."
To find out, Wilson compiled more than 2,000 methane measurements from 87 published studies around the world. Using machine learning models, Wilson, Fulweiler, and fellow Earth & Environment Ph.D. candidate Sawyer Balint found that plant species alone explained 62 percent of the variability in methane emissions. When combined with latitude, season, and salinity, that figure increased to 71 percent.
Why It Matters
For decades, scientists have used salinity as a relatively simple way to estimate methane emissions from tidal marshes. But researchers now know that methane can be produced even under salty conditions, complicating the long-standing relationship between salinity and methane.
That matters beyond the lab. Governments and conservation organizations increasingly look to tidal marshes as natural climate solutions, but calculating the benefits of protecting or restoring them means accounting for the methane they emit as well as the carbon they store.
"The default assumption for a lot of these policies and frameworks is that if it's above a certain salinity then you just don't think about methane emissions," Wilson says. Using plants could provide a more practical way to refine those estimates, particularly because plant communities can be identified in the field or mapped using aerial imagery.
"Accurately assessing carbon budgets is important for how we protect and manage tidal marshes," Fulweiler says. "It has important implications for how we determine the net carbon balance of these systems, which is also critical for carbon finance markets. A plant proxy is a low-cost and efficient way to estimate methane."
The study also suggests methane may play a larger role in the carbon balance of some tidal marshes than previously assumed. Depending on the plants present and how methane's warming effect is calculated, methane emissions can offset between 1 and 39 percent of the carbon some marshes sequester.
That doesn't mean tidal marshes aren't valuable carbon sinks. Instead, more accurately accounting for methane gives scientists, policymakers, and land managers a clearer picture of their overall climate benefits.
Nor does it mean restoration efforts should favor plants associated with lower methane emissions.
"Salt marshes that are biodiverse, also supply benefits for a host of organisms, including humans," Wilson says. "There are some plants that are productive and good at taking up carbon dioxide. There are others that are great at providing habitat for birds, such as the salt marsh sparrow."
What Comes Next
Wilson and her colleagues hope to develop high-resolution global maps
of tidal marsh vegetation that could allow scientists to estimate methane emissions across entire coastlines. They also want to understand why certain plants are associated with different methane emissions and whether plant species could help predict other greenhouse gases, including carbon dioxide and nitrous oxide.
"We want to dive deeper into the 'why' of our research," Wilson says. "This is only the beginning, and there are many next steps."
For Wilson, that means continuing to explore the plants that drew her to this research.
"The plants we see in salt marshes are incredible because they have these adaptations that allow them to survive or thrive in these extremely stressful environments," she says. "It's interesting that you can use their unique traits to estimate large-scale biogeochemical processes."
