Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms

Ashley Van Beusekom,Grizelle González,Nora Álvarez-Berríos,William Gould,Maya Quiñones

doi:10.3390/rs10091386

Abstract

The impact of Hurricane Maria on the U.S. Caribbean was used to study the causes of remotely-sensed spatial variation in the effects of (1) vegetation index loss and (2) landslide occurrence. The vegetation index is a measure of canopy ‘greenness’, a combination of leaf chlorophyll, leaf area, canopy cover and structure. A generalized linear model was made for each kind of effect, using idealized maps of the hurricane forces, along with three landscape characteristics that were significantly associated. In each model, one of these characteristics was forest fragmentation, and another was a measure of disturbance-propensity. For the greenness loss model, the hurricane force was wind, the disturbance-propensity measure was initial greenness, and the third landscape characteristic was fraction forest cover. For the landslide occurrence model, the hurricane force was rain, the disturbance-propensity measure was amount of land slope, and the third landscape characteristic was soil clay content. The model of greenness loss had a pseudo R2 of 0.73 and showed the U.S. Caribbean lost 31% of its initial greenness from the hurricane, with 51% lost from the initial in the Luquillo Experimental Forest (LEF) from Hurricane Maria along with Hurricane Irma. More greenness disturbance was seen in areas with less wind sheltering, higher elevation and topographic sides. The model of landslide occurrence had a pseudo R2 of 0.53 and showed the U.S. Caribbean had 34% of its area and 52% of the LEF area with a landslide density of at least one in 1 km2 from Hurricane Maria. Four experiments with parameters from previous storms of wind speed, storm duration, rainfall, and forest structure over the same storm path and topographic landscape were run as examples of possible future scenarios. While intensity of the storm makes by far the largest scenario difference, forest fragmentation makes a sizable difference especially in vulnerable areas of high clay content or high wind susceptibility. This study showed the utility of simple hurricane force calculations connected with landscape characteristics and remote-sensing data to determine forest susceptibility to hurricane effects.

Highlights

It has been estimated that when Hurricane Maria hit Puerto Rico on 20 September 2017, 23 to 31 million trees were severely damaged or killed [1]
The gale strength wind kinetic energy in one meter of air over the U.S Caribbean from the passage of Hurricane Maria and Irma was calculated as 232 petajoules (PJ, 1 PJ = 1015 J), 87 PJ of which came from Irma alone
The model indicates that an average of 0.17 Enhanced Vegetation Index (EVI) was lost over the U.S Caribbean from Hurricane Maria and Irma

Summary

Introduction

It has been estimated that when Hurricane Maria hit Puerto Rico on 20 September 2017, 23 to 31 million trees were severely damaged or killed [1]. It is accepted that hurricanes cause massive vegetation disturbance and are the primary driver of forest transformation in the hurricane-belt of the tropics [2]. Hurricanes and their effects have been widely studied because they are a major cause of loss of life and property [3]. Studies of hurricane effects on forests and ecosystem function overwhelmingly look at specific ecosystem components or are syntheses of such studies. These run the gamut from short- and long-term effects of wind and rain to secondary effects of altered post-hurricane conditions [4,5]. The determinants of forest susceptibility to hurricane effects still lack landscape-wide characterizations that capture within-landscape patterns of effects related to hurricane force intensity, topography, and forest structure

Methods

Results

Discussion

Conclusion