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| Titel |
Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED) |
| VerfasserIn |
R. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, A. Spessa, D. Lawrence, G. Bonan |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 11 ; Nr. 8, no. 11 (2015-11-06), S.3593-3619 |
| Datensatznummer |
250116660
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| Publikation (Nr.) |
 copernicus.org/gmd-8-3593-2015.pdf |
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| Zusammenfassung |
| We describe an implementation of the Ecosystem Demography (ED) concept in the
Community Land Model. The structure of CLM(ED) and the physiological and
structural modifications applied to the CLM are presented. A major motivation
of this development is to allow the prediction of biome boundaries directly
from plant physiological traits via their competitive interactions. Here we
investigate the performance of the model for an example biome boundary in
eastern North America. We explore the sensitivity of the predicted biome
boundaries and ecosystem properties to the variation of leaf properties using
the parameter space defined by the GLOPNET global leaf trait database.
Furthermore, we investigate the impact of four sequential alterations to the
structural assumptions in the model governing the relative carbon economy of
deciduous and evergreen plants. The default assumption is that the costs and
benefits of deciduous vs. evergreen leaf strategies, in terms of carbon
assimilation and expenditure, can reproduce the geographical structure of
biome boundaries and ecosystem functioning. We find some support for this
assumption, but only under particular combinations of model traits and
structural assumptions. Many questions remain regarding the preferred methods
for deployment of plant trait information in land surface models. In some
cases, plant traits might best be closely linked to each other, but we also
find support for direct linkages to environmental conditions. We advocate
intensified study of the costs and benefits of plant life history strategies
in different environments and the increased use of parametric and structural
ensembles in the development and analysis of complex vegetation models. |
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