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

P Choler,M Raupach,P Briggs,R Leuning,W Sea

doi:10.5194/bg-7-907-2010

Abstract

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.

Highlights

Most recent advances in empirical models of leaf phenology, i.e. the time dependence of Leaf Area Index (LAI), have been made for temperate deciduous forests where temperature is the main controlling factor (Chuine, 2000)
water by roots (We) found that the mean absolute error of linear and nonlinear models did not markedly differ
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

Summary

Introduction

Most recent advances in empirical models of leaf phenology, i.e. the time dependence of Leaf Area Index (LAI), have been made for temperate deciduous forests where temperature is the main controlling factor (Chuine, 2000). Leaf phenology in water-limited ecosystems remains poorly captured by current broad empirical approaches (Botta et al, 2000). Water is the main controlling factor of ecosystem functioning for more than 50% of the land mass (Churkina and Running, 1998; Huxman et al, 2004). Soil water balance, which has long been recognized as a key driver of plant growth in water-limited ecosystems (Walker and Langridge, 1996; Farrar et al, 1994), is highly variable at the landscape scale and difficult to predict in global models. Contrary to temperature or heat, water is a depletable resource exploited by plants at a rate dependent on both resource (soil water availability) and leaf biomass

Methods

Results

Discussion

Conclusion