Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics

Yoshikai, Masaya; Nakamura, Takashi; Suwa, Rempei; Sharma, Sahadev; Rollon, Rene; Yasuoka, Jun; Egawa, Ryohei; Nadaoka, Kazuo

doi:https://doi.org/10.5194/bg-19-1813-2022

Articles | Volume 19, issue 6

https://doi.org/10.5194/bg-19-1813-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-19-1813-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 6

Research article

|

31 Mar 2022

Research article |

| 31 Mar 2022

Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics

Masaya Yoshikai, Takashi Nakamura, Rempei Suwa, Sahadev Sharma, Rene Rollon, Jun Yasuoka, Ryohei Egawa, and Kazuo Nadaoka

Supplement

https://doi.org/10.5194/bg-19-1813-2022-supplement

Model code and software

MasayaYoshikai/SEIB_mangrove (v1.0.0) M. Yoshikai https://doi.org/10.5281/zenodo.6388269

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Short summary

This study presents a new individual-based vegetation model to investigate salinity control on mangrove productivity. The model incorporates plant hydraulics and tree competition and predicts unique and complex patterns of mangrove forest structures that vary across soil salinity gradients. The presented model does not hold an empirical expression of salinity influence on productivity and thus may provide a better understanding of mangrove forest dynamics in future climate change.