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Abstract Projected increases in hurricane intensity under a warming climate will have profound effects on many forest ecosystems. One key challenge is to disentangle the effects of wind damage from the myriad factors that influence forest structure and species distributions over large spatial scales. Here, we employ a novel machine learning framework with high‐resolution aerial photos, and LiDAR collected over 115 km2of El Yunque National Forest in Puerto Rico to examine the effects of topographic exposure to two hurricanes, Hugo (1989) and Georges (1998), and several landscape‐scale environmental factors on the current forest height and abundance of a dominant, wind‐resistant species, the palmPrestoea acuminata var. montana. Model predictions show that the average density of the palm was 32% greater while the canopy height was 20% shorter in forests exposed to the two storms relative to unexposed areas. Our results demonstrate that hurricanes have lasting effects on forest canopy height and composition, suggesting the expected increase in hurricane severity with a warming climate will alter coastal forests in the North Atlantic.
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Hurricane María tripled stem breaks and doubled tree mortality relative to other major storms.
Tropical cyclones are expected to intensify under a warming climate, with uncertain effects on tropical forest ecosystems. One key challenge to predicting how more intense storms will influence these ecosystems is to attribute hurricane impacts specifically to storm meteorological characteristics rather than differences in forest characteristics. Here we compare tree damage data collected in the same forest in Puerto Rico after Hurricanes Hugo (1989, category 3), Georges (1998, category 3), and María (2017, category 4). María killed twice as many trees as Hugo, and for all but two species, broke 2- to 12-fold more stems than the other two storms. Species with low density wood were particularly vulnerable to uprooting and breakage. Extensive tree inventories and a wind exposure model allow us to attribute these differences in impacts to storm meteorology. A better understanding of risk factors associated with tree species susceptibility to severe storms is key to predicting the future of forest ecosystems under climate warming.
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- Award ID(s):
- 1801315
- PAR ID:
- 10101521
- Date Published:
- Journal Name:
- Nature communications
- Volume:
- 10
- ISSN:
- 2041-1723
- Page Range / eLocation ID:
- 1362
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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