Abstract
Abstract. The relative complexity of the mechanisms underlying savanna ecosystem dynamics, in comparison to other biomes such as temperate and tropical forests, challenges the representation of such dynamics in ecosystem and Earth system models. A realistic representation of processes governing carbon allocation and phenology for the two defining elements of savanna vegetation (namely trees and grasses) may be a key to understanding variations in tree–grass partitioning in time and space across the savanna biome worldwide. Here we present a new approach for modelling coupled phenology and carbon allocation, applied to competing tree and grass plant functional types. The approach accounts for a temporal shift between assimilation and growth, mediated by a labile carbohydrate store. This is combined with a method to maximize long-term net primary production (NPP) by optimally partitioning plant growth between fine roots and (leaves + stem). The computational efficiency of the analytic method used here allows it to be uniquely and readily applied at regional scale, as required, for example, within the framework of a global biogeochemical model.We demonstrate the approach by encoding it in a new simple carbon–water cycle model that we call HAVANA (Hydrology and Vegetation-dynamics Algorithm for Northern Australia), coupled to the existing POP (Population Orders Physiology) model for tree demography and disturbance-mediated heterogeneity. HAVANA-POP is calibrated using monthly remotely sensed fraction of absorbed photosynthetically active radiation (fPAR) and eddy-covariance-based estimates of carbon and water fluxes at five tower sites along the North Australian Tropical Transect (NATT), which is characterized by large gradients in rainfall and wildfire disturbance. The calibrated model replicates observed gradients of fPAR, tree leaf area index, basal area, and foliage projective cover along the NATT. The model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, mediated by shifting above- versus below-ground resources, and not from imposed hypotheses about the controls on tree–grass co-existence. Results support the hypothesis that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
Highlights
Savannas constitute one of the world’s most extensive biomes and provide ecosystem services as rangelands and marginal agricultural lands for one-fifth of the world’s population (Lehmann et al, 2009)
We demonstrate the approach by encoding it in a new simple carbon–water cycle model that we call HAVANA (Hydrology and Vegetation-dynamics Algorithm for Northern Australia), coupled to the existing POP
We demonstrate the approach by encoding it in a simple carbon/water cycle model that we call HAVANA (Hydrology and Vegetation-dynamics Algorithm for Northern Australia), coupled to the POP (Population Orders Physiology) model for tree demography and disturbance-mediated heterogeneity (Haverd et al, 2013b, 2014)
Summary
Savannas constitute one of the world’s most extensive biomes and provide ecosystem services as rangelands and marginal agricultural lands for one-fifth of the world’s population (Lehmann et al, 2009). One exception is the adaptive dynamic global vegetation model of Scheiter and Higgins (2009), which is specialized for the simulation of savannas It uses an individual plant’s carbon status to determine the transition between active and dormant states, dynamically allocating carbon based on resource (light or water) limitation. The novelty of the approach lies in the dynamic constraint of plant growth such that the long-term change in store (net primary production minus growth) is zero (a requirement for carbon conservation) This is combined with the use of an optimal response method for analytically predicting the partitioning of plant growth between fine roots and (leaves + stem), which optimizes long-term NPP. The model is evaluated against a suite of observations that are sensitive to the tree– grass ratio along the transect, namely eddy-covariance-based estimates of carbon and water fluxes at five tower sites, dynamics of remotely sensed fPAR, tree leaf area index derived from digital hemispheric photography and satellite observations, and gradients of tree basal area and foliage projective cover
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