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| Titel |
Improved light and temperature responses for light-use-efficiency-based GPP models |
| VerfasserIn |
I. McCallum, O. Franklin, E. Moltchanova, L. Merbold, C. Schmullius, A. Shvidenko, D. Schepaschenko, S. Fritz |
| 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 ; 10, no. 10 ; Nr. 10, no. 10 (2013-10-17), S.6577-6590 |
| Datensatznummer |
250085367
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| Publikation (Nr.) |
 copernicus.org/bg-10-6577-2013.pdf |
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| Zusammenfassung |
Gross primary production (GPP) is the process by which carbon enters
ecosystems. Models based on the theory of light use efficiency (LUE) have
emerged as an efficient method to estimate ecosystem GPP. However, problems
have been noted when applying global parameterizations to biome-level
applications. In particular, model–data comparisons of GPP have shown that
models (including LUE models) have difficulty matching estimated GPP. This
is significant as errors in simulated GPP may propagate through models
(e.g. Earth system models). Clearly, unique biome-level characteristics
must be accounted for if model accuracy is to be improved. We hypothesize
that in boreal regions (which are strongly temperature controlled),
accounting for temperature acclimation and non-linear light response of
daily GPP will improve model performance.
To test this hypothesis, we have chosen four diagnostic models for
comparison, namely an LUE model (linear in its light response) both with
and without temperature acclimation and an LUE model and a big leaf model
both with temperature acclimation and non-linear in their light response.
All models include environmental modifiers for temperature and vapour
pressure deficit (VPD). Initially, all models were calibrated against five
eddy covariance (EC) sites within Russia for the years 2002–2005, for a
total of 17 site years. Model evaluation was performed via 10-out
cross-validation.
Cross-validation clearly demonstrates the improvement in model performance
that temperature acclimation makes in modelling GPP at strongly
temperature-controlled sites in Russia. These results would indicate that inclusion of
temperature acclimation in models on sites experiencing cold temperatures is
imperative. Additionally, the inclusion of a non-linear light response
function is shown to further improve performance, particularly in less
temperature-controlled sites. |
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