Patterns and Controls of Hurricane-Caused Forest Damage: A Landscape-Scale Analysis of Treefall Direction Following Hurricane Katrina∗

We particularly appreciate the assistance of Ron Smith, Tate Thriffiley, Clint Roberts, Jeff Cotter, and Wayne Stone, all of the U.S. Department of Agriculture Forest Service; and Skeeter Dixon, Scott Franklin, Amanda Veverka, and the graduate students in John A. Kupfer's “Katrina Seminar,” in which this article was first developed. Comments from several anonymous reviewers greatly improved the quality of this article. Funding was provided by the Coastal Resiliency Information Systems Initiative for the Southeast (CRISIS), Office of Research and Health Sciences, University of South Carolina. We also would like to acknowledge the National Oceanic and Atmospheric Administration's Hurricane Research Division and the U.S. Army Corps of Engineers, for developing data and products used in this study.

Abstract

To clarify broad-scale patterns and controls of treefall directionality from Hurricane Katrina, we examined fall directions across a 4,500 km² landscape mosaic in southern Mississippi using georeferenced, planar-rectified aerial photographs. Analyses using directional statistics, measures of local spatial autocorrelation, and general linear modeling indicated that treefall was significantly directional for nearly all of our locations and constrained primarily by mesoscale surface wind directions and landscape setting. None of our plots exhibited fall angles consistent with damage caused by wind reversals following the passage of the storm or by microbursts or tornadoes spawned by the hurricane. When coupled with results from other studies focused on hurricane-caused damage, these results suggest that it is possible to develop empirical, landscape-scale models of wind impacts or stand vulnerability using basic site information (e.g., topography, soils), biotic conditions (e.g., land cover, forest attributes), and generalized, but readily available, estimates of surface wind flow patterns.

Analizamos la dirección de la caída de los árboles en un mosaico de paisaje de 4,500 km2 en el sur de Mississippi usando fotografías aéreas geográficamente relacionadas y plano-rectificadas con el objetivo de aclarar los patrones y controles a gran escala de la dirección de la caída de los árboles durante el huracán Katrina. Los análisis con estadística direccional, las medidas de autocorrelación espacial local y el modelado linear general indicaron que la caída de los árboles fue significativamente direccional en casi todas nuestras áreas de estudio, y estuvo limitada principalmente por la dirección de los vientos superficiales mesoescalares y la configuración del terreno. Ninguno de los sitios exhibió ángulos congruentes con daños causados por el cambio de dirección de los vientos después del paso de la tormenta ni por microrráfagas o tornados producidos por el huracán. Cuando se asocian con los resultados de otros estudios que se enfocan en los daños de los huracanes, estos resultados sugieren que es posible desarrollar modelos empíricos a escala de paisaje del impacto de los vientos o la vulnerabilidad de la posición usando información básica del sitio (como topografía, suelos), condiciones bióticas (como cobertura del suelo, características forestales), y cálculos generalizados, pero rápidamente disponibles, de los patrones de flujo del viento superficial.

Key Words:

• blowdown
• directional statistics
• Mississippi
• scale
• spatial analysis

关键词:

• 吹倒
• 方向统计法
• 密西西比
• 尺度
• 空间分析

Palabras claves:

• derribamiento
• estadística direccional
• Mississippi
• escala
• análisis espacial

Notes

We particularly appreciate the assistance of Ron Smith, Tate Thriffiley, Clint Roberts, Jeff Cotter, and Wayne Stone, all of the U.S. Department of Agriculture Forest Service; and Skeeter Dixon, Scott Franklin, Amanda Veverka, and the graduate students in John A. Kupfer's “Katrina Seminar,” in which this article was first developed. Comments from several anonymous reviewers greatly improved the quality of this article. Funding was provided by the Coastal Resiliency Information Systems Initiative for the Southeast (CRISIS), Office of Research and Health Sciences, University of South Carolina. We also would like to acknowledge the National Oceanic and Atmospheric Administration's Hurricane Research Division and the U.S. Army Corps of Engineers, for developing data and products used in this study.