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| Titel |
Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications |
| VerfasserIn |
B. Ringeval, S. Houweling, P. M. van Bodegom, R. Spahni, R. van Beek, F. Joos, T. Röckmann |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 6 ; Nr. 11, no. 6 (2014-03-21), S.1519-1558 |
| Datensatznummer |
250117303
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| Publikation (Nr.) |
 copernicus.org/bg-11-1519-2014.pdf |
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| Zusammenfassung |
| Tropical wetlands are estimated to represent about 50% of the natural
wetland methane (CH4) emissions and explain a large fraction of the
observed CH4 variability on timescales ranging from
glacial–interglacial cycles to the currently observed year-to-year
variability. Despite their importance, however, tropical wetlands are poorly
represented in global models aiming to predict global CH4 emissions.
This publication documents a first step in the development of a process-based
model of CH4 emissions from tropical floodplains for global
applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model
(LPX hereafter) was slightly modified to represent floodplain hydrology,
vegetation and associated CH4 emissions. The extent of tropical
floodplains was prescribed using output from the spatially explicit hydrology
model PCR-GLOBWB. We introduced new plant functional types (PFTs) that
explicitly represent floodplain vegetation. The PFT parameterizations were
evaluated against available remote-sensing data sets (GLC2000 land cover and
MODIS Net Primary Productivity). Simulated CH4 flux densities were
evaluated against field observations and regional flux inventories. Simulated
CH4 emissions at Amazon Basin scale were compared to model simulations
performed in the WETCHIMP intercomparison project. We found that LPX
reproduces the average magnitude of observed net CH4 flux densities for
the Amazon Basin. However, the model does not reproduce the variability
between sites or between years within a site. Unfortunately, site information
is too limited to attest or disprove some model features. At the Amazon Basin
scale, our results underline the large uncertainty in the magnitude of
wetland CH4 emissions. Sensitivity analyses gave insights into the main
drivers of floodplain CH4 emission and their associated uncertainties.
In particular, uncertainties in floodplain extent (i.e., difference between
GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor
of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000,
lead to simulated Amazon-integrated emissions of
44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly
sensitive to vegetation distribution. Two simulations with the same mean PFT
cover, but different spatial distributions of grasslands within the basin,
modulated emissions by about 20%. Correcting the LPX-simulated NPP using
MODIS reduces the Amazon emissions by 11.3%. Finally, due to an
intrinsic limitation of LPX to account for seasonality in floodplain extent,
the model failed to reproduce the full dynamics in CH4 emissions but we
proposed solutions to this issue. The interannual variability (IAV) of the
emissions increases by 90% if the IAV in floodplain extent is accounted
for, but still remains lower than in most of the WETCHIMP models. While our
model includes more mechanisms specific to tropical floodplains, we were
unable to reduce the uncertainty in the magnitude of wetland CH4
emissions of the Amazon Basin. Our results helped identify and prioritize
directions towards more accurate estimates of tropical CH4 emissions,
and they stress the need for more research to constrain floodplain CH4
emissions and their temporal variability, even before including other
fundamental mechanisms such as floating macrophytes or lateral water fluxes. |
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