## Abstract

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 <span classCombining double low line"inline-formula">C3</span> 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 <span classCombining double low line"inline-formula">C3</span> vegetation type. The model builds on the theory developed in <span classCombining double low line"cit" idCombining double low line"xref-text.1"><a hrefCombining double low line"#bib1.bibx139">Prentice et al.</a> (<a hrefCombining double low line"#bib1.bibx139">2014</a>)</span> and <span classCombining double low line"cit" idCombining double low line"xref-text.2"><a hrefCombining double low line"#bib1.bibx193">Wang et al.</a> (<a hrefCombining double low line"#bib1.bibx193">2017</a><a hrefCombining double low line"#bib1.bibx193">a</a>)</span> 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 <span classCombining double low line"inline-formula"R/i2/span 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 <span classCombining double low line"inline-formula">*R*2</span> 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 <span classCombining double low line"inline-formula">*R*2</span> 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<span classCombining double low line"inline-formula">-1</span> (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).

Original language | English |
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Pages (from-to) | 1545-1581 |

Number of pages | 37 |

Journal | Geoscientific Model Development |

Volume | 13 |

Issue number | 3 |

DOIs | |

State | Published - Mar 26 2020 |