Antje M. Moffat talks with
ScienceWatch.com and answers a few questions about
this month's New Hot Paper in the field of Agricultural
Article Title: Comprehensive comparison of
gap-filling techniques for eddy covariance net carbon
AM, et al.
Journal: AGR FOREST METEOROL, Volume: 147, Issue: 3-4,
Year: DEC 10 2007
* Max Planck Inst Biogeochem, Hans Knoll Str 10, D-07745
* Max Planck Inst Biogeochem, D-07745 Jena, Germany.
* Univ Tuscia, DISAFRI, I-01100 Viterbo, Italy.
(addresses have been truncated)
Why do you think your paper is highly
As the result of a collaborative effort of 18 scientists, this paper
provides the most up-to-date and comprehensive understanding of techniques
used to perform an important data assimilation step, the "gap-filling."
This step is necessary to infer daily to annual estimates of the carbon
dioxide uptake of an ecosystem from fragmented half-hourly flux
These biosphere-atmosphere observations are taken by a worldwide network of
hundreds of micrometeorological tower sites called "FLUXNET," which
coordinates regional and global analysis. The flux tower sites use eddy
covariance methods to measure the exchanges of carbon dioxide
(CO2), water vapor, and energy between terrestrial ecosystems
and the atmosphere. Our study laid one important basis for harmonized data
processing within the network and serves as a reference paper, reviewing
and evaluating all of the commonly used gap-filling techniques.
Does it describe a new discovery, methodology, or
synthesis of knowledge?
"Without well-calibrated, long-term
observations of carbon exchange in diverse
ecosystems, we lack the basis on which to
evaluate and improve climate change
predictions of future atmospheric CO2 and
The paper is a synthesis of techniques devised over the last decade. It is
not a new discovery, per se, but rather a powerful finding about the
robustness of the algorithms we use to infer long-term carbon exchange from
noisy, gap-filled, short-term observations.
Would you summarize the significance of your paper
in layman's terms?
CO2, a major greenhouse gas, is emitted to the atmosphere from
the burning of fossil fuels. Land and ocean ecosystems absorb about half of
these emissions and scientists are trying to understand the mechanisms that
control this uptake. To quantify the temporal dynamics, the variability to
climate, and the sensitivity to future climate change, tower sites
measuring the carbon flux over ecosystems have been installed in a wide
range of vegetations and climate zones all over the world.
Unfortunately, these finicky, high temporal resolution measurements have
inherent limitations, consequently becoming fragmented in time. Since these
data gaps complicate our ability to infer the long-term variability of the
ecosystem's carbon uptake, several groups of scientists worldwide have
independently developed dozens of techniques to infer the missing data.
This paper presents the first comprehensive evaluation of these techniques,
quantifies the uncertainty induced by this data assimilation step, and
finds that many of these techniques are robust and agree well with each
other. This agreement strengthens prior findings that have been made about
the ecosystem carbon exchange.
How did you become involved in this research, and
were there any problems along the way?
While working in industry, I decided to go back into science and begin a
Ph.D. in environmental science. This very interdisciplinary field gives me
the chance to apply my background in physics to my interests in plants and
nature. After intensely working with the carbon flux data sets and
developing my own gap-filling technique, I took the lead of this comparison
The main challenge was in collecting, organizing, and synthesizing the
model run results of all the different techniques as well as the 17
valuable inputs, along with 17 different—and sometimes
opposing—opinions, from my collaborators, into a coherent whole.
After doing this by email, with me as the central node in a star network, I
was glad to get funding for a workshop. It was so much easier and more
effective to have roundtable discussions. The workshop also generated the
groundwork for further collaboration and papers.
Where do you see your research leading in the
Modeling complex ecosystem responses is one of the major challenges for
understanding and predicting the effects of global change. Usually, these
responses are implemented in models as prescribed functional relationships.
In contrast, I am working on the development of a methodology that allows
these relationships to be characterized directly from the data.
It is based on a very general non-linear function class, feedforward
artificial neural networks, and not only makes use of their capability to
empirically model the response, but also aims to answer the question of
what controls the carbon flux in terrestrial ecosystems. In the future, I
hope to make wider use of this methodology, working at the interface
between modeling and experiment and gaining insight into the underlying
Do you foresee any social or political implications
for your research?
Not as an individual, but as part of a community concerned with the effects
of climate change on terrestrial ecosystems. Depending on how plants and
soils respond, changes in the magnitude of this uptake could further
ameliorate or exacerbate the greenhouse effect.
Without well-calibrated, long-term observations of carbon exchange in
diverse ecosystems, we lack the basis on which to evaluate and improve
climate change predictions of future atmospheric CO2 and climate
By analogy to the meteorological observation networks laid in the
19th century to allow weather forecasts and now also climate
change analysis, today, carbon cycle observation networks, such as the
biosphere-atmosphere FLUXNET, are needed. These observations help to reduce
the uncertainty in future climate scenarios and improve political
decision-making regarding the best options to respond to negative effects
of future warming.
Antje Maria Moffat
Max-Planck-Institute for Biogeochemistry
Jena, Germany Web
KEYWORDS: EDDY COVARIANCE; CARBON FLUX; NET ECOSYSTEM EXCHANGE
(NEE); FLUXNET; REVIEW OF GAP-FILLING TECHNIQUES; GAP-FILLING