P-model v1.0: an optimality -based light use efficiency model for simulating ecosystem gross primary production

被引:75
|
作者
Stocker, Benjamin D. [1 ,2 ,3 ]
Wang, Han [4 ]
Smith, Nicholas G. [5 ]
Harrison, Sandy P. [6 ]
Keenan, Trevor F. [7 ,8 ]
Sandoval, David [9 ]
Davis, Tyler [9 ,10 ]
Prentice, I. Colin [4 ,9 ,11 ]
机构
[1] CREAF, Campus UAB, Bellaterra 08193, Catalonia, Spain
[2] Stanford Univ, Earth Syst Sci, Stanford, CA 94305 USA
[3] ETH, Dept Environm Syst Sci, Inst Agr Sci, Univ Str 2, CH-8092 Zurich, Switzerland
[4] Tsinghua Univ, Dept Earth Syst Sci, Beijing 100084, Peoples R China
[5] Texas Tech Univ, Dept Biol Sci, Lubbock, TX 79409 USA
[6] Univ Reading, Geog & Environm Sci, Reading RG6 6AH, Berks, England
[7] Lawrence Berkeley Natl Lab, Earth & Environm Sci Area, Berkeley, CA 94709 USA
[8] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA
[9] Imperial Coll London, Dept Life Sci, AXA Chair Biosphere & Climate Impacts, Silwood Pk Campus, Ascot SL5 7PY, Berks, England
[10] Coll William & Mary, Ctr Geospatial Anal, Williamsburg, VA 23185 USA
[11] Macquarie Univ, Dept Biol Sci, N Ryde, NSW 2109, Australia
基金
瑞士国家科学基金会; 欧盟地平线“2020”;
关键词
CARBON-DIOXIDE EXCHANGE; PHOTOSYNTHETICALLY ACTIVE RADIATION; TEMPERATURE RESPONSE FUNCTIONS; NET PRIMARY PRODUCTION; BLACK SPRUCE FOREST; SUB-ALPINE FOREST; INTERANNUAL VARIABILITY; SCOTS PINE; DECIDUOUS FOREST; PONDEROSA PINE;
D O I
10.5194/gmd-13-1545-2020
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar-von Caemmerer-Berry model for C-3 photosynthesis with an optimality principle for the carbon assimilation-transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C-3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R-2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) - similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R-2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R-2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106-122 Pg C yr(-1) (mean of 2001-2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting - rather than prescribing - light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).
引用
收藏
页码:1545 / 1581
页数:37
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