Adoption of the Pmodel as a useful tool to analyze plant photosynthesis levels on the Tibetan Plateau

The Tibetan Plateau (TP), known as the “Third Pole,” is the highest and most extensive plateau in the world, with an average altitude of more than 4,000 m above sea level (a.s.l.) and covering an area of approximately 2.5 million km2. The unique alpine meadow ecosystem on the TP, accounting for more than 10% of China’s carbon sink capacity, is sensitive to climate change. Gross primary productivity (GPP) represents the amount of carbon dioxide absorbed by plants via photosynthesis and is a key indicator for the function of alpine ecosystems.

Several light use efficiency (LUE) models have been used to estimate GPP (Sun et al., 2019; Chen et al., 2021). Such models require parameter calibrations to achieve their best results given TP’s unique and complex topographic environment. However, due to the large spatial heterogeneity and the sparse GPP observation sites, the calibrated-parameters would inevitably introduce uncertainties when upscaling site-based parameters to the whole TP.

Based on the Eco-Evolutionary Optimality principle, Pmodel, that uses a form of LUE modeling, has been proven to perform well on modelling GPP in various ecosystems without any biome-dependent parameters (Wang et al., 2017).

Here, we used the observation from eddy-covariance flux sites to evaluate the predictability of P model in alpine meadows. Three flux sites with different vegetation types were chosen: Haibei site (shrub meadow), Dangxiong site (alpine meadow) and NamCO site (alpine grassland). Compared with the flux-observed GPP, Pmodel could well capture the variations of GPP in alpine ecosystems at site and regional levels. Without any biome-dependent parameter in the Pmodel, the correlation coefficient (r) between simulated and observed GPP were 0.91 at NamCO site, 0.87 at Dangxiong site and 0.94 at Haibei site, which is roughly comparable to the performance using other LUE model with parameter calibration (Gao et al., 2014). These results confirmed the advantages of using P model to simulate GPP for alpine ecosystem on TP especially in the absence of sufficient ground observations on TP.

Figure 1. Comparisons of the simulated GPP and the observed GPP at (a) NamCo site, (b) Dangxiong site and (c) Haibei site. N is the number of samples.


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Sun, J., Y. Chen, K. Yang, H. Lu, L. Zhao & D. Zheng. (2021). Influence of Organic Matter on Soil Hydrothermal Processes in the Tibetan Plateau: Observation and Parameterization. Journal of Hydrometeorology, 22(10), 2659-2674. 10.1175/JHM-D-21-0059.1

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