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

P Choler, William Sea, P Briggs, Michael Raupach, Ray Leuning

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)907-920
Number of pages14
JournalBiogeosciences
Volume7
Issue number3
DOIs
Publication statusPublished - 2010
Externally publishedYes

Fingerprint

tropical grasslands
grassland
nonlinear models
linear models
leaves
phenology
soil water
plant growth
soil water balance
Northern Territory
moderate resolution imaging spectroradiometer
model validation
ground cover plants
vegetation cover
Queensland
soil moisture
time series analysis
calibration
grasslands
grasses

Cite this

Choler, P ; Sea, William ; Briggs, P ; Raupach, Michael ; Leuning, Ray. / A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands. In: Biogeosciences. 2010 ; Vol. 7, No. 3. pp. 907-920.
@article{a1c35c3e22a94573a5334947f6ffc01f,
title = "A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands",
abstract = "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.",
author = "P Choler and William Sea and P Briggs and Michael Raupach and Ray Leuning",
year = "2010",
doi = "10.5194/bg-7-907-2010",
language = "English",
volume = "7",
pages = "907--920",
journal = "Biogeosciences",
issn = "1726-4170",
publisher = "European Geosciences Union",
number = "3",

}

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands. / Choler, P; Sea, William; Briggs, P; Raupach, Michael; Leuning, Ray.

In: Biogeosciences, Vol. 7, No. 3, 2010, p. 907-920.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

AU - Choler, P

AU - Sea, William

AU - Briggs, P

AU - Raupach, Michael

AU - Leuning, Ray

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

U2 - 10.5194/bg-7-907-2010

DO - 10.5194/bg-7-907-2010

M3 - Article

VL - 7

SP - 907

EP - 920

JO - Biogeosciences

JF - Biogeosciences

SN - 1726-4170

IS - 3

ER -