Understanding the Impact of Major Hurricanes on Tropical Forests

Using computer models and field data, researchers found that tropical forests recover from major hurricanes as long as they are infrequent.

Forest canopy damage in Puerto Rico following Hurricane Maria in 2017.

Forest canopy damage in Puerto Rico following Hurricane Maria in 2017. Most trees lost branches and canopy, but palms were much less damaged by the hurricane because of their flexibility.

[Courtesy International Institute of Tropical Forestry.‌]

The Science

Existing ecosystem models for tropical forests do not account for damage caused by hurricanes, which is problematic as hurricanes are becoming stronger because of climate change. A team of scientists modified an ecosystem model to simulate hurricane damage in tropical forests using data from a forest in Puerto Rico to test and improve the model predictions. Using the improved model, they tested how long it takes for tropical forests to recover from hurricane damage.

The Impact

The ecosystem model accurately simulated observed forest damage from Hurricane Hugo and how fast forests recovered from the hurricane. The study found that damaged forests could accumulate more carbon than undamaged forests because hurricanes killed many small trees, allowing large trees to grow even larger. These results indicate that infrequent hurricanes may have little impact on long-term forest carbon cycling. With this model, researchers can explore other effects on forests resulting from changes in hurricane frequency and strength.


To develop the ecosystem model, the research team accounted for three observations. First, more trees die when hurricane winds exceed 90 miles an hour. Second, hurricanes cause more damage to forests that have only a few large trees. Third, palms are more resistant to hurricane damage than trees. The team used data from the Luquillo Experimental Forest in Puerto Rico to validate the model. The model correctly simulated the widespread loss of trees following Hurricane Hugo and forest growth and changes in tree and palm abundances over the following 30 years.

The team used the validated model to study the long-term impacts of hurricane disturbances. The team conducted three simulations: one without any hurricane damage, one with severe damage similar to Hugo, and one with moderate damage similar to Maria. The model predicted large losses of biomass immediately following the hurricane disturbances. However, over 80 years after the hurricane, the damaged forests recovered. Surprisingly, forests damaged by Hurricane Maria showed 5% more biomass than undamaged forests. This result occurred because the hurricane killed small trees, which reduced the competition for light and water and allowed surviving trees to grow larger.

Principal Investigator

Marcos Longo
Lawrence Berkeley National Laboratory
[email protected]

Program Manager

Brian Benscoter
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]


This research was supported by the Next-Generation Ecosystem Experiments-Tropics (NGEE-Tropics), which is funded by the Biological and Environmental Research (BER) Program within the U.S. Department of Energy’s (DOE) Office of Science; Georgia Institute of Technology; National Science Foundation; K. Harrison Brown Family Chair; NASA Postdoctoral Program, administered by the Universities Space Research Association under contract with NASA; U.S. Department of Agriculture (USDA) Forest Service, and USDA Forest Service International Institute of Tropical Forestry works in collaboration with the University of Puerto Rico. The research carried out at the Jet Propulsion Laboratory, California Institute of Technology, was under a contract with NASA.


Zhang, J., R. L. Bras, M. Longo, and T. Heartsill Scalley. "The Impact of Hurricane Disturbances on a Tropical Forest: Implementing a Palm Plant Functional Type and Hurricane Disturbance Module in ED2-HuDi V1.0." Geoscientific Model Development 15 5107–26  (2022). https://doi.org/10.5194/gmd-15-5107-2022.