Abstract
Abstract. Leaf seasonality impacts a variety of important biological, chemical, and physical Earth system processes, which makes it essential to represent leaf phenology in ecosystem and climate models. However, we are still lacking a general, robust parametrisation of phenology at global scales. In this study, we use a simple process-based model, which describes phenology as a strategy for carbon optimality, to test the effects of the common simplification in global modelling studies that plant species within the same plant functional type (PFT) have the same parameter values, implying they are assumed to have the same species traits. In a previous study this model was shown to predict spatial and temporal dynamics of leaf area index (LAI) well across the entire global land surface provided local grid cell parameters were used, and is able to explain 96 % of the spatial variation in average LAI and 87 % of the variation in amplitude. In contrast, we find here that a PFT level parametrisation is unable to capture the spatial variability in seasonal cycles, explaining on average only 28 % of the spatial variation in mean leaf area index and 12 % of the variation in seasonal amplitude. However, we also show that allowing only two parameters, light compensation point and leaf age, to be spatially variable dramatically improves the model predictions, increasing the model's capability of explaining spatial variations in leaf seasonality to 70 and 57 % of the variation in LAI average and amplitude, respectively. This highlights the importance of identifying the spatial scale of variation of plant traits and the necessity to critically analyse the use of the plant functional type assumption in Earth system models.
Highlights
The ability to understand and predict leaf seasonal cycles, a process known as leaf phenology, is essential to our understanding of Earth systems processes, through its impact on the carbon and water cycles (White et al, 1999; Wilson and Baldocchi, 2000) and climate (Hayden, 1998)
Relative root mean squared error values are much higher for the plant functional type (PFT) model than for the local model, 0.52 ± 0.5 compared to only 0.24 ± 0.03
In this paper we explored the extent to which plants within the same PFT exhibit the same phenological characteristics using a process-based global phenology model
Summary
The ability to understand and predict leaf seasonal cycles, a process known as leaf phenology, is essential to our understanding of Earth systems processes, through its impact on the carbon and water cycles (White et al, 1999; Wilson and Baldocchi, 2000) and climate (Hayden, 1998). Models make use of the plant functional type (PFT) concept In this approach, a small number of PFTs are defined, each with a corresponding set of parameters, a given grid cell is assigned to one, or a mixture of, these PFTs. more recently efforts are being made to include a more biologically detailed representation in the form of plant traits. All model parameter values are assigned to each PFT either based on ground measurements or through parameter estimation This approach has the underlying assumption that all plants within such a PFT show an identical behaviour (Sitch et al, 2003), an assumption applied to all processes represented in such models, including leaf phenology. Such an assumption is necessary because of the lack of available measurements
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