remote sensing Article
Elevation Regimes Modulated the Responses of Canopy Structure of Coastal Mangrove Forests to Hurricane Damage Qiong Gao and Mei Yu * Department of Environmental Sciences, University of Puerto Rico, Rio Piedras, San Juan, PR 00926, USA; q.gao@ites.upr.edu * Correspondence: meiyu@ites.upr.edu
Citation: Gao, Q.; Yu, M. Elevation Regimes Modulated the Responses of Canopy Structure of Coastal Mangrove Forests to Hurricane Damage. Remote Sens. 2022, 14, 1497.
Abstract: Mangrove forests have unique ecosystem functions and services, yet the coastal mangroves in tropics are often disturbed by tropical cyclones. Hurricane Maria swept Puerto Rico and nearby Caribbean islands in September 2017 and caused tremendous damage to the coastal mangrove systems. Understanding the vulnerability and resistance of mangrove forests to disturbances is pivotal for future restoration and conservation. In this study, we used LiDAR point clouds to derive the canopy height of five major mangrove forests, including true mangroves and mangrove associates, along the coast of Puerto Rico before and after the hurricanes, which allowed us to detect the spatial variations of canopy height reduction. We then spatially regressed the pre-hurricane canopy height and the canopy height reduction on biophysical factors such as the elevation, the distance to rivers/canals within and nearby, the distance to coast, tree density, and canopy unevenness. The analyses resulted in the following findings. The pre-hurricane canopy height increased with elevation when elevation was low and moderate but decreased with elevation when elevation was high. The canopy height reduction increased quadratically with the pre-hurricane canopy height, but decreased with elevation for the four sites dominated by true mangroves. The site of Palma del Mar dominated by Pterocarpus, a mangrove associate, experienced the strongest wind, and the canopy height reduction increased with elevation. The canopy height reduction decreased with the distance to rivers/canals only for sites with low to moderate mean elevation of 0.36–0.39 m. In addition to the hurricane winds, the rainfall during hurricanes is an important factor causing canopy damage by inundating the aerial roots. In summary, the pre-hurricane canopy structures, physical environment, and external forces brought by hurricanes interplayed to affect the vulnerability of coastal mangroves to major hurricanes.
https://doi.org/10.3390/rs14061497 Academic Editor: Chandra Giri
Keywords: urban mangroves; LiDAR; canopy structure; hurricane damage; Caribbean
Received: 9 February 2022 Accepted: 18 March 2022 Published: 20 March 2022
1. Introduction
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Growing under multiple physiological stresses, coastal mangroves possess unique ecosystem functions to maintain high carbon sequestration [1,2], to purify coastal water, to host a number of vertebrate and invertebrate species [3], to offset the sea level rise via vertical accretion [4,5], and to protect societal properties of coastal communities during tropical storms [6]. However, the canopies of coastal mangroves are likely to be severely damaged by tropical storms, thus greatly reducing the functions of mangrove forests [7–9]. Understanding the vulnerability and resistance of mangroves under storm disturbance is vital to restore and to conserve coastal wetlands. In addition to the great wind speed of storms, several biophysical features may elucidate the vulnerability of tropical forests to disturbance; emergent trees or higher canopy, smaller tree diameter, lower tree density, and lower soil-root anchorage may incur more canopy damage [10,11]. Mangroves with higher canopy tend to intercept more wind force, trees with smaller dimeter have a small shear modulus, a lower tree density makes the wind easier to traverse the canopy, and a lower soil-root anchorage makes the coastal
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Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Remote Sens. 2022, 14, 1497. https://doi.org/10.3390/rs14061497
https://www.mdpi.com/journal/remotesensing