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| Titel |
Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis |
| VerfasserIn |
L. M. Verheijen, V. Brovkin, R. Aerts, G. Bönisch, J. H. C. Cornelissen, J. Kattge, P. B. Reich, I. J. Wright, P. M. Bodegom |
| 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. 8 ; Nr. 10, no. 8 (2013-08-15), S.5497-5515 |
| Datensatznummer |
250085299
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| Publikation (Nr.) |
 copernicus.org/bg-10-5497-2013.pdf |
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| Zusammenfassung |
| In many current dynamic global vegetation models (DGVMs), including those
incorporated into Earth system models (ESMs), terrestrial vegetation is
represented by a small number of plant functional types (PFTs), each with
fixed properties irrespective of their predicted occurrence. This contrasts
with natural vegetation, in which many plant traits vary systematically
along geographic and environmental gradients. In the JSBACH DGVM, which is
part of the MPI-ESM, we allowed three traits (specific leaf area (SLA),
maximum carboxylation rate at 25 °C (Vcmax25) and maximum
electron transport rate at 25 °C (Jmax25)) to vary within
PFTs via trait–climate relationships based on a large trait database. The
R2adjusted of these relationships were up to 0.83 and 0.71 for
Vcmax25 and Jmax25, respectively. For SLA, more variance
remained unexplained, with a maximum R2adjusted of 0.40. Compared
to the default simulation, allowing trait variation within PFTs resulted in
gross primary productivity differences of up to 50% in the tropics, in > 35%
different dominant vegetation cover, and a closer match with a natural
vegetation map. The discrepancy between default trait values and natural
trait variation, combined with the substantial changes in simulated
vegetation properties, together emphasize that incorporating climate-driven
trait variation, calibrated on observational data and based on ecological
concepts, allows more variation in vegetation responses in DGVMs and as such
is likely to enable more reliable projections in unknown climates. |
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