Scientists trace the journey of radiocarbon through trees and soil to the atmosphere.
Canoers travel down the Flambeau River in northern Wisconsin. In this region, scientists collected radiocarbon data so that they could track the carbon as it cycles through trees and soil before it is released back into the air. Credit: Jereme Rauckman, CC BY 2.0
Source: Journal of Geophysical Research: Biogeosciences

In the face of global climate change, scientists are always in search of better models to accurately measure carbon in an ecosystem. In particular, they look to determine how quickly carbon can cycle through plants and soil until it reaches the atmosphere again.

This rate helps them to project global climates in both the near and distant future and the regional effects that these changes may have on temperature, sea levels, rainfall, and crop growth. The closer scientists get to accurately measuring carbon and its sources and sinks, the closer they get to forecasting the future.

Carbon-14, or radiocarbon, is one isotope used to track the movement of carbon from the atmosphere. Radiocarbon is sequestered by trees via photosynthesis, moved to the ground, and finally released again into the atmosphere. Nuclear weapons testing during the middle of the 20th century temporarily elevated radiocarbon in the atmosphere, and consequently, carbon stored in terrestrial ecosystems on timescales of decades has elevated levels of radiocarbon compared to the radiocarbon levels in the present-day atmosphere. Because of this difference, scientists can use radiocarbon to determine how long it takes carbon to cycle through vegetation, into soils, and back to the atmosphere.

In a recent study, LaFranchi et al. collected air samples at the WLEF tall tower in northern Wisconsin, an area surrounded by forest and wetland ecosystems with a relatively sparse human population. The authors took the samples at a height of 369 meters above the ground from 2010 through the end of 2012. From this, they gathered 114 radiocarbon observations over the 3 years of sampling.

After collecting the radiocarbon data from the tower, the researchers ran it through a series of atmospheric carbon simulations to retrace the origins of the carbon samples. These simulations combined weather models, fossil fuel and nuclear emissions data, a global fire emissions database, and a terrestrial biosphere model (modeling the amount of carbon that is released from soils and vegetation). These simulations created a full picture of where the radiocarbon in the atmosphere was coming from.

The measurements showed a seasonal increase in radiocarbon abundance in the summers and declines in the winters, particularly in the first year of sampling (2010). Although fossil fuel, which is devoid of radiocarbon and thus lessens its fraction in the atmosphere, had the largest effect on radiocarbon abundance in the atmosphere throughout the year, the researchers were surprised to find that forests and vegetation respiration made a larger contribution than expected.

Their results indicate that the radiocarbon input to the atmosphere from soils and vegetation was 2 to 3 times higher than predicted by their ecosystem model. The likely source for this overabundance is the boreal forests of central and northwestern Canada. These massive forests are globally significant for their large carbon storage but are vulnerable to climate change, which could cause more carbon to be released in the future.

The authors hope that the radiocarbon approach used in the study could help hone in on the intricacies of the carbon cycle for future research, in particular, how the natural carbon cycle responds to human-caused climate change. They also hope that their study will help lead to a better understanding of the short-term feedbacks of carbon released into the atmosphere. (Journal of Geophysical Research: Biogeosciences, doi:10.1002/2015JG003271, 2016)

—Alexandra Branscombe, Freelance Writer


Branscombe, A. (2016), Isotopes track carbon cycle in northern Wisconsin wilderness, Eos, 97, Published on 09 November 2016.

Text © 2016. The authors. CC BY-NC-ND 3.0
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