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- Title
Global datasets of leaf photosynthetic capacity for ecological and earth system research.
- Authors
Chen, Jing M.; Wang, Rong; Liu, Yihong; He, Liming; Croft, Holly; Luo, Xiangzhong; Wang, Han; Smith, Nicholas G.; Keenan, Trevor F.; Prentice, I. Colin; Zhang, Yongguang; Ju, Weimin; Dong, Ning
- Abstract
The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax , based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r2=0.79,RMSE=15.46µ mol m -2 s -1 , P<0.001) and compare well with 3672 ground-based measurements (r2=0.69,RMSE=13.8µ mol m -2 s -1 and P<0.001 for SIF; r2=0.55,RMSE=18.28µ mol m -2 s -1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC, and SIF + LCC are available at 10.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal%5fvcmax%5fR and 10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022).
- Subjects
ECOLOGICAL carrying capacity; ECOSYSTEMS; CHLOROPHYLL spectra; REMOTE sensing; SOIL acidity; LAND cover; CARBON cycle
- Publication
Earth System Science Data, 2022, Vol 14, Issue 9, p4077
- ISSN
1866-3508
- Publication type
Article
- DOI
10.5194/essd-14-4077-2022