The colorful leaves piling up in your backyard
this fall can be thought of as natural stores of carbon. In the
springtime, leaves soak up carbon dioxide from the atmosphere,
converting the gas into organic carbon compounds. Come autumn, trees
shed their leaves, leaving them to decompose in the soil as they are
eaten by microbes. Over time, decaying leaves release carbon back into
the atmosphere as carbon dioxide.
In fact, the natural decay of
organic carbon contributes more than 90 percent of the yearly carbon
dioxide released into Earth’s atmosphere and oceans. Understanding the
rate at which leaves decay can help scientists predict this global flux
of carbon dioxide, and develop better models for climate change. But
this is a thorny problem: A single leaf may undergo different rates of
decay depending on a number of variables: local climate, soil, microbes
and a leaf’s composition. Differentiating the decay rates among various
species, let alone forests, is a monumental task.
Instead, MIT
researchers have analyzed data from a variety of forests and ecosystems
across North America, and discovered general trends in decay rates among
all leaves. The scientists devised a mathematical procedure to
transform observations of decay into distributions of rates. They found
that the shape of the resulting curve is independent of climate,
location and leaf composition. However, the details of that shape — the
range of rates that it spans, and the mean rate — vary with climatic
conditions and plant composition. In general, the scientists found that
plant composition determines the range of rates, and that as
temperatures increase, all plant matter decays faster.
“There is a
debate in the literature: If the climate warms, do all rates become
faster by the same factor, or will some become much faster while some
are not affected?” says Daniel Rothman, a co-founder of MIT’s Lorenz Center,
and professor of geophysics in the Department of Earth, Atmospheric and
Planetary Sciences. “The conclusion is that all rates scale uniformly
as the temperature increases.”
Rothman and co-author David Forney, a PhD graduate in the Department of Mechanical Engineering, have published the results of their study, based largely on Forney’s PhD thesis, in the Journal of the Royal Society Interface.
Litter delivery
The
team obtained data from an independent 10-year analysis of North
American forests called the Long-term Intersite Decomposition Experiment
Team (LIDET) study. For this study, researchers collected leaf litter —
including grass, roots, leaves and needles — from 27 locations
throughout North and Central America, ranging from Alaskan tundra to
Panamanian rainforests.
The LIDET researchers separated and
weighed each litter type, and identified litter composition and nutrient
content. They then stored the samples in porous bags and buried the
bags, each filled with a different litter type, in each of the 27
geographic locations; the samples were then dug up annually and
reweighed. The data collected represented the mass of litter, of
different composition, remaining over time in different environments.
Forney
and Rothman accessed the LIDET study’s publicly available data online,
and analyzed each dataset: the litter originating at one location,
subsequently divided and distributed at 27 different locations, and
weighed over 10 years.
The team developed a mathematical model to
convert each dataset’s hundreds of mass measurements into rates of
decay — a “numerically delicate” task, Rothman says. They then plotted
the converted data points on a graph, yielding a surprising result: The
distribution of decay rates for each dataset looked roughly the same,
forming a bell curve when plotted as a function of the order of
magnitude of the rates — a surprisingly tidy pattern, given the
complexity of parameters affecting decay rates.
“Not only are
there different environments like grasslands and tundra and rainforest,
there are different environments at the microscale too,” Forney says.
“Each plant is made up of different tissues … and these all have
different degradation pathways. So there’s heterogeneity at many
different scales … and we’re trying to figure out if there’s some sort
of commonality.”
Common curves
Going a
step further, Forney and Rothman looked for parameters that affect leaf
decay rates. While each dataset resembled a bell curve, there were
slight variations among them. For example, some curves had higher peaks,
while others were flatter; some curves shifted to the left of a graph,
while others lay more to the right. The team looked for explanations for
these slight variations, and discovered the two parameters that most
affected the details of a dataset’s curve: climate and leaf composition.
In
general, the researchers observed, warmer climates tended to speed the
decay of all plants, whereas colder climates slowed plant decay
uniformly. The implication is that as temperatures increase, all plant
matter, regardless of composition, will decay more quickly, with the
same relative speedup in rate.
The team also found that plant
matter such as needles that contain more lignin — a sturdy building
block — have a smaller range of decay rates than leafier plants that
contain less lignin and more nutrients that attract microbes. “This is
an interesting ecological finding,” Forney says. “Lignin tends to shield
organic compounds, which may otherwise degrade at a faster rate.”
Mark
Harmon, principal investigator for the LIDET study and a professor of
forest science at Oregon State University, says the team’s results add
evidence to a long-held debate over rising temperature’s effect on
organic decay: As temperatures rise, decomposition will likely speed up,
releasing more carbon dioxide into the atmosphere, which in turn
creates warmer temperatures, further speeding decay in a positive
feedback loop.
“There is a wide range of results on temperature
response,” says Harmon, who was not involved in the study. “Some have
proposed that materials that are hard to decompose will respond more to
temperature increases, and others have proposed the opposite. The
current study indicates they may be the same,” meaning the positive
feedback from rising temperatures may not be as strong as others have
predicted.
Rothman adds that in the future, the team may use the
model to predict the turnover times of various ecosystems — a finding
that may improve climate change models, and help scientists understand
the flux of carbon dioxide around the globe.
“It’s a really messy
problem,” Rothman says. “It’s as messy as the pile of leaves in your
backyard. You would think that each pile of leaves is different,
depending on which tree it’s from, where the pile is in your backyard
and what the climate is like. What we’re showing is that there’s a
mathematical sense in which all of these piles of leaves behave in the
same way.”
Written by: Jennifer Chu, MIT
Contact: Sarah McDonnell, MIT
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