This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: 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 amid the constant ebb and flow of tides. Today, as a Boston University doctoral candidate in Earth & Environment, Wilson studies those same ecosystems—and has discovered that the plants she once drove past may hold important information for more accurately tracking 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 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." 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 doctoral candidate Sawyer Balint found that plant species alone explained 62% of the variability in methane emissions.
Extract — continue reading at the source.
