Biogeosciences
Biogeosciences
BG
Articles | Volume 19, issue 6
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

Viewed

Total article views: 5,055 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,431 1,506 118 5,055 297 87 126
  • HTML: 3,431
  • PDF: 1,506
  • XML: 118
  • Total: 5,055
  • Supplement: 297
  • BibTeX: 87
  • EndNote: 126
Views and downloads (calculated since 14 Oct 2021)
Cumulative views and downloads (calculated since 14 Oct 2021)

Viewed (geographical distribution)

Total article views: 5,055 (including HTML, PDF, and XML) Thereof 4,876 with geography defined and 179 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Nov 2025
Download
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint