Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms
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 chlorophy...
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doaj-0b6b22d20cd8456090966d690c3ed40f2020-11-25T02:28:20ZengMDPI AGRemote Sensing2072-42922018-08-01109138610.3390/rs10091386rs10091386Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future StormsAshley E. Van Beusekom0Nora L. Álvarez-Berríos1William A. Gould2Maya Quiñones3Grizelle González4USDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926, USAUSDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926, USAUSDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926, USAUSDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926, USAUSDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926, USAThe 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.http://www.mdpi.com/2072-4292/10/9/1386Hurricane Mariageneralized linear modelremote sensingforest fragmentationU.S. CaribbeanLuquillo Experimental Forest |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ashley E. Van Beusekom Nora L. Álvarez-Berríos William A. Gould Maya Quiñones Grizelle González |
spellingShingle |
Ashley E. Van Beusekom Nora L. Álvarez-Berríos William A. Gould Maya Quiñones Grizelle González Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms Remote Sensing Hurricane Maria generalized linear model remote sensing forest fragmentation U.S. Caribbean Luquillo Experimental Forest |
author_facet |
Ashley E. Van Beusekom Nora L. Álvarez-Berríos William A. Gould Maya Quiñones Grizelle González |
author_sort |
Ashley E. Van Beusekom |
title |
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms |
title_short |
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms |
title_full |
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms |
title_fullStr |
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms |
title_full_unstemmed |
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms |
title_sort |
hurricane maria in the u.s. caribbean: disturbance forces, variation of effects, and implications for future storms |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-08-01 |
description |
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. |
topic |
Hurricane Maria generalized linear model remote sensing forest fragmentation U.S. Caribbean Luquillo Experimental Forest |
url |
http://www.mdpi.com/2072-4292/10/9/1386 |
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