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A Simple Ecohydrological Model Captures Essentials of Seasonal Leaf Dynamics in Semi-arid Tropical Grasslands : Volume 6, Issue 5 (02/09/2009)

By Choler, P.

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Book Id: WPLBN0004005371
Format Type: PDF Article :
File Size: Pages 30
Reproduction Date: 2015

Title: A Simple Ecohydrological Model Captures Essentials of Seasonal Leaf Dynamics in Semi-arid Tropical Grasslands : Volume 6, Issue 5 (02/09/2009)  
Author: Choler, P.
Volume: Vol. 6, Issue 5
Language: English
Subject: Science, Biogeosciences, Discussions
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Briggs, P., Raupach, M., Sea, W., Leuning, R., & Choler, P. (2009). A Simple Ecohydrological Model Captures Essentials of Seasonal Leaf Dynamics in Semi-arid Tropical Grasslands : Volume 6, Issue 5 (02/09/2009). Retrieved from

Description: CSIRO Marine and Atmospheric Research, P.O. Box 3023, Canberra, ACT, 2601, Australia. 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 yr 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.

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

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