Abstract
Abstract. Accurately representing the response of ecosystems to environmental change in land surface models (LSMs) is crucial to making accurate predictions of future climate. Many LSMs do not correctly capture plant respiration and growth fluxes, particularly in response to extreme climatic events. This is in part due to the unrealistic assumption that total plant carbon expenditure (PCE) is always equal to gross carbon accumulation by photosynthesis. We present and evaluate a simple model of labile carbon storage and utilisation (SUGAR) designed to be integrated into an LSM, which allows simulated plant respiration and growth to vary independent of photosynthesis. SUGAR buffers simulated PCE against seasonal variation in photosynthesis, producing more constant (less variable) predictions of plant growth and respiration relative to an LSM that does not represent labile carbon storage. This allows the model to more accurately capture observed carbon fluxes at a large-scale drought experiment in a tropical moist forest in the Amazon, relative to the Joint UK Land Environment Simulator LSM (JULES). SUGAR is designed to improve the representation of carbon storage in LSMs and provides a simple framework that allows new processes to be integrated as the empirical understanding of carbon storage in plants improves. The study highlights the need for future research into carbon storage and allocation in plants, particularly in response to extreme climate events such as drought.
Highlights
Representing the balance between plant photosynthesis, growth and autotrophic respiration in the land surface model (LSM) component of Earth System Models (ESMs) is crucial to making accurate projections of global climate in the future
We present and evaluate a simple model of labile carbon storage and utilisation (SUGAR) designed to be integrated into an LSM, which allows simulated plant respiration and growth to vary independent of photosynthesis
We present the coefficient of variation (CV) of the basin-averaged gross primary productivity (GPP) and simulated plant carbon expenditure (PCE) for each value of fNSC
Summary
Representing the balance between plant photosynthesis, growth and autotrophic respiration in the land surface model (LSM) component of Earth System Models (ESMs) is crucial to making accurate projections of global climate in the future. In reality growth and respiration are not so strictly coupled to photosynthesis and plants regularly experience periods when the supply of carbon from photosynthesis does not equal the demands of growth and respiration (Körner, 2003; Muller et al, 2011). This asynchrony between supply and demand is facilitated by reserve pools of labile carbon known collectively as non-structural carbohydrates (NSCs). NSCs act as a buffer, allowing key functional processes to be maintained, even when photosynthetic accumulation is low This buffering is important during periods of environmental stress, which can lead to reduced productivity over seasonal to multi-annual timescales. Without simulating NSC storage, LSMs remain unable to capture this asynchrony between GPP and PCE and fail to correctly simulate forest-level respiration and growth fluxes
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