Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-6957-2022
https://doi.org/10.5194/gmd-15-6957-2022
Model description paper
 | 
16 Sep 2022
Model description paper |  | 16 Sep 2022

Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest

Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar

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Cited articles

Ariza-Carricondo, C., Mauro, F., Op de Beeck, M., Roland, M., Gielen, B., Vitale, D., Ceulemans, R., and Papale, D.: A comparison of different methods for assessing leaf area index in four canopy types, Central European Forestry Journal, 65, 67–80, https://doi.org/10.2478/forj-2019-0011, 2019. a, b, c
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Balzarolo, M., Valdameri, N., Fu, Y. H., Schepers, L., Janssens, I. A., and Campioli, M.: Different determinants of radiation use efficiency in cold and temperate forests, Global Ecol. Biogeogr., 28, 1649–1667, https://doi.org/10.1111/geb.12985, 2019. a
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Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
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