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| Titel |
A new empirical method to predict carbon dioxide evasion from boreal lakes |
| VerfasserIn |
Adam Hastie, Ronny Lauerwald, Gesa Weyhenmeyer, Sebastian Sobek, Pierre Regnier |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250133449
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| Publikation (Nr.) |
 EGU/EGU2016-14061.pdf |
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| Zusammenfassung |
| Carbon dioxide evasion from lakes (F CO2) is an important component of the global carbon
budget. In this study, empirical models have been developed to predict CO2 partial pressure
(pCO2) in boreal lakes at the 0.5˚ grid scale, with the aim of producing the first map of
F CO2 from these high latitude aquatic systems. Approximately 57,000 samples of lake pCO2
from Sweden and Finland were used to train the models. Significant seasonality in pCO2 was
identified and thus data were split into two categories based on water temperature; 0-4.5˚ C
and >4.5˚ C. The lake pCO2 data and various globally available, environmental parameters
such as elevation, terrestrial net primary production (NPP) and climate (temperature T,
rainfall R) were spatially aggregated to a 0.5˚ resolution. Preliminary results from
multiple regression analyses suggest that a significant proportion of the variability in
boreal lake pCO2 can be explained using these globally available parameters. For
water temperatures above 4.5˚ C, the explained proportion of the variability in lake
pCO2 is particularly high (r2= 0.7). Following further refinement and validation, a
map of estimated lake pCO2 for the entire boreal region will be established. This
map will then be combined with lake surface area data from the GLObal WAter
BOdies database (GLOWABO, Verpoorter et al., 2014), and a calculation of gas
exchange velocity k to produce the first map of boreal lake F CO2. Finally, IPCC
projections of the selected environmental predictors (T, NPP, and R) will be used to
estimate future F CO2 from boreal lakes and their sensitivity to climate change. |
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