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| Titel |
A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands |
| VerfasserIn |
P. Choler, W. Sea, P. Briggs, M. Raupach, R. Leuning |
| 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 ; 7, no. 3 ; Nr. 7, no. 3 (2010-03-08), S.907-920 |
| Datensatznummer |
250004584
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| Publikation (Nr.) |
 copernicus.org/bg-7-907-2010.pdf |
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| Zusammenfassung |
Modelling leaf phenology in water-controlled ecosystems remains a difficult
task because of high spatial and temporal variability in the interaction of
plant growth and soil moisture. Here, we move beyond widely used linear
models to examine the performance of low-dimensional, nonlinear
ecohydrological models that couple the dynamics of plant cover and soil
moisture. The study area encompasses 400 000 km2 of semi-arid
perennial tropical grasslands, dominated by C4 grasses, in the Northern
Territory and Queensland (Australia). We prepared 8-year time series
(2001–2008) of climatic variables and estimates of fractional vegetation
cover derived from MODIS Normalized Difference Vegetation Index (NDVI) for
400 randomly chosen sites, of which 25% were used for model calibration
and 75% for model validation.
We found that the mean absolute error of linear and nonlinear models did not
markedly differ. However, nonlinear models presented key advantages: (1)
they exhibited far less systematic error than their linear counterparts; (2)
their error magnitude was consistent throughout a precipitation gradient
while the performance of linear models deteriorated at the driest sites, and
(3) they better captured the sharp transitions in leaf cover that are
observed under high seasonality of precipitation. Our results showed that
low-dimensional models including feedbacks between soil water balance and
plant growth adequately predict leaf dynamics in semi-arid perennial
grasslands. Because these models attempt to capture fundamental
ecohydrological processes, they should be the favoured approach for
prognostic models of phenology. |
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