A multi-scale assessment of hurricane impacts on agricultural landscapes based on land use and topographic features

• Published in: Agriculture, ecosystems & environment Vol. 128; no. 1; pp. 12 - 20
• Main Authors: Philpott, Stacy M., Lin, Brenda B., Jha, Shalene, Brines, Shannon J.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.10.2008; Amsterdam; New York: Elsevier; Elsevier Science
• Subjects: agricultural land; agroecosystems; Agronomy. Soil science and plant productions; altitude; Animal and plant ecology; Animal, plant and microbial ecology; Biological and medical sciences; botanical composition; Chiapas; Climatology. Bioclimatology. Climate change; Coffea arabica; Coffee agroecosystem; coffee products; Earth, ocean, space; Ecosystem service; Erosion; Exact sciences and technology; External geophysics; forests; Fundamental and applied biological sciences. Psychology; General agroecology; General agroecology. Agricultural and farming systems. Agricultural development. Rural area planning. Landscaping; General agronomy. Plant production; General aspects; Generalities. Agricultural and farming systems. Agricultural development; Global change; Heavy rainfall; hurricanes; land use; Landslides; Meteorology; Mexico; plant density; rain; risk assessment; rivers; slope; spatial variation; specialty crops; stand structure; Synecology; topography; vegetation; vegetation cover; wind; Mexico; Central America; America; Mexico, Chiapas; Landslides; Heavy rainfall; Global change; Mexico; Coffee agroecosystem; Chiapas; Ecosystem service; Erosion; Modification; Rural environment; Rural landscape; Environmental factor; Land use; Agroecosystem; Dynamical climatology; Climate change; Rain; Ecosystem; Topography; Ecosystem services; Atmospheric precipitation; Hurricane; Chiapas Mexico Coffee agroecosystem Ecosystem service Erosion Global change Heavy rainfall Landslides
• ISSN: 0167-8809; 1873-2305
• DOI: 10.1016/j.agee.2008.04.016

Agricultural systems are increasingly vulnerable to the effects of extreme climate events. Yet strategies to reduce risk and vulnerability have not been greatly explored. Here, we examine the vulnerability of coffee agroforestry systems varying in management intensity (e.g. land use) and topographic features to disturbance related to Hurricane Stan in Chiapas, Mexico—a hurricane categorized by heavy rains and mild winds. An approximately 50 km 2 area was chosen within a coffee-growing region where data were collected on a variety of topographic and landscape features (aspect, slope, elevation, distance to river) and vegetation characteristics (canopy cover, vegetation structure, tree density) as predictive factors of vegetation, economic, and landslide damage at three distinct spatial scales. At the plot level, we collected vegetation data later compiled into a vegetation complexity index. At the farm level, we collected data to understand the effect of the hurricane on economic damage and farm area affected by landslides. We also recorded number and volume of roadside landslides as a measure of post-hurricane disturbance. We then conducted a geo-spatial analysis to determine which factors contribute most to landslide occurrence at landscape scales. We found no effect of coffee management on vegetation damage or on economic losses at the plot or farm scale. At the farm scale, increasing management intensity (i.e. reduction in vegetation complexity) correlated with increased proportion of farm area affected by landslides ( P = 0.014). Additionally, reduction in vegetation complexity was correlated with increased number ( P = 0.0224) and volume ( P = 0.062) of roadside landslides at the landscape level. Topographic and landscape features, such as distance to river ( P = 0.004) and wind exposure/aspect ( P = 0.044) strongly influenced landslide frequency at the landscape scale. Forest proximity and proportion of forest cover did not significantly influence the frequency or extent of landslide damage. We created hazard maps using the vegetation complexity index, distance to river, and wind exposure as the heaviest weighted factors to assess areas of the terrain with the greatest vulnerability. These maps present a practical result of this study, and offer a template in which land management policy can develop to lower regional vulnerability to landslide risk. These results show that farmers may be able to reduce vulnerability to extreme storm events by carefully managing their farms. Although farmers may not be able to control negative topographic features of their farms, increasing vegetation complexity within farms may be an efficient strategy to reduce some susceptibility to hurricane disturbance.