Preprints
https://doi.org/10.5194/gmd-2021-410
https://doi.org/10.5194/gmd-2021-410
Submitted as: development and technical paper
14 Jan 2022
Submitted as: development and technical paper | 14 Jan 2022
Status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

The Impact of Hurricane Disturbances on a Tropical Forest: Implementing a Palm Plant Functional Type and Hurricane Disturbance Module in ED2-HuDi V1.0

Jiaying Zhang1, Rafael L. Bras1, Marcos Longo2,3, and Tamara Heartsill Scalley4 Jiaying Zhang et al.
  • 1School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
  • 3Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
  • 4USDA Forest Service, International Institute of Tropical Forestry, Río Piedras, PR, United States

Abstract. Hurricanes commonly disturb and damage tropical forests. It is predicted that changes in climate will result in changes in hurricane frequency and intensity. Modeling is needed to investigate the potential response of forests to future disturbances. Unfortunately, existing models of forests dynamics are not presently able to account for hurricane disturbances. We implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model—Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimates (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of −21 %, −12 %, and −15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1%, −8 %, −2 %, and +9 % differences in the percentages of Early, Mid, Late, and Palm PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (< 1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

Jiaying Zhang et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-410', Anonymous Referee #1, 15 Feb 2022
  • RC2: 'Comment on gmd-2021-410', Anonymous Referee #2, 20 Feb 2022
  • RC3: 'Comment on gmd-2021-410', Anonymous Referee #3, 22 Feb 2022
  • AC1: 'Author response to referee comments', Jiaying Zhang, 08 Apr 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-410', Anonymous Referee #1, 15 Feb 2022
  • RC2: 'Comment on gmd-2021-410', Anonymous Referee #2, 20 Feb 2022
  • RC3: 'Comment on gmd-2021-410', Anonymous Referee #3, 22 Feb 2022
  • AC1: 'Author response to referee comments', Jiaying Zhang, 08 Apr 2022

Jiaying Zhang et al.

Jiaying Zhang et al.

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Short summary
We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from a hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.