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Evaluating the Vulnerability of Maine Forests to Wind Damage

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Evaluating the Vulnerability of Maine Forests to Wind Damage Previous Advances in Threat Assessment and Their Application to Forest and Rangeland Management Evaluating the Vulnerability of Maine Forests to Wind Damage Thomas E. Perry and Jeremy S. Wilson Understanding windthrow risk throughout the land- scape can provide insights into natural vegetation patterns Thomas E. Perry, research professional and Jeremy S. and habitat types. Risk evaluation can also be used to help Wilson, associate professor of forest management, Univer- predict how current forests may change without harvesting sity of Maine, Orono, ME 04469. and subsequent impacts to forest health. Risk evaluation can help managers (1) evaluate where to locate plantations, Abstract (2) decide which regeneration strategies are appropriate, Numerous factors, some of which cannot be controlled, are (3) determine where thinning and other partial harvests are continually interacting with the forest resource, introducing acceptable, and (4) determine what species composition or risk to management, and making consistent predictable rotation length is desirable for individual sites. Predicting management outcomes uncertain. Included in these factors damage, or potential for damage, provides the opportunity are threats or hazards such as windstorms and wildfire. for impacts to be considered during prescription develop- Factors influencing the probability (risk) of windthrow or ment, allowing for revision of management objectives or windsnap occurring can be grouped into four broad catego- incorporation of mitigative actions into management plans ries: regional climate, topographic exposure, soil properties, (Mitchell 1998). and stand characteristics. Of these categories, stand char- Currently, little is known about the extent of both acteristics are most commonly and easily modified through catastrophic and endemic wind damage in Maine. As a forest management. To augment our understanding of the result, this project’s aim was to explore the nature of wind interaction between forest management and wind damage disturbance throughout the State’s large forest ownerships. vulnerability in Maine, we developed a wind damage To augment our understanding of the interaction between model that reflects site and stand characteristics. Model forest management and wind damage vulnerability, this calibration used information from published literature and project developed a generalized wind damage model that experiences of regional managers. The model was evaluated reflects topographic exposure (distance-limited Topex) using spatially explicit wind damage records from a (Ruel and others 1997), soil conditions (rooting depth), and 40 800-ha managed forest area in northern Maine. A stand characteristics (density, edge, height, species compo- comparison of means analysis identified significant dif- sition, and treatment history). Results from similar model- ferences in vulnerability index values between categorical ing projects in British Columbia suggest that these risk populations of stands that have either recorded blowdown or factors are consistent in varied locations, and this indicates no recorded blowdown during the last 15 years. that general models may be applicable to landscapes other Keywords: GIS, natural disturbance, vulnerability than the ones for which they were developed (Lanquaye- assessment, wind modeling, windthrow risk. Opoku and Mitchell 2005). This model was calibrated using information from published literature and experiences of Introduction regional managers. We then evaluated it using spatially “Windthrow is a complex process resulting from interac- explicit wind damage records from a 40 800-ha area of tions between natural and anthropogenic factors” (Ruel managed forest in northern Maine. 1995). Understanding the interactions between these factors and the inherent risk to stands from this disturbance has Methods numerous benefits to natural resource managers. Windthrow Windthrow risk in many parts of the world has been is affected by several factors; climate, topography, physical modeled and assessed. Empirical models are best suited and biological stand attributes, soil characteristics, and for areas with complex, heterogeneous stand structure and silviculture all play a role in the dynamics of wind distur- composition (Lanquaye-Opoku and Mitchell 2005, Mitchell bance (Ruel 1995). 237 GENERAL TECHNICAL REPORT PNW-GTR-802 Figure 1—Flow chart of cumulative risk grid development shows the grouping and integration of individual variables into composite risk variables. Composite stand and site risk variables are then combined into a cumulative windthrow risk variable. All variables are indexed between 0 and 1 (high to low risk) and are combined additively. and others 2001) like the forests of Maine. This empiri- were used to generate a spatially explicit vulnerability index cal approach typically utilizes regression models relating value. Mitchell (1995, 1998) advocated grouping the fac- wind damage to physical stand components. Generally, tors into three broad categories—exposure, soils, and stand the models produce a probability value rating or index of characteristics—to form a windthrow triangle, a conceptual damage potential based on the stand’s suite of environ- model of the relationships among these interacting factors. mental conditions. Index modeling of spatial phenomena For this model, factors were broken down further into site is enhanced with GIS, which allows for the integration of and stand parameters and combined to generate the cumula- spatially explicit model parameters. tive windthrow risk index (Figure 1). Data for model vari- Logistic regression is commonly used for evaluating ables, including a spatially referenced database of windthrow these models and isolating highly correlated component history, was acquired from various sources and covered an variables (Lanquaye-Opoku and Mitchell 2005, Mitchell area of private landholdings in the northern portion of the and others 2001). Rather than using logistic regression, this State. project produced a generalized model, retaining variables that would not be statistically significant in a logistic regres- Site: Exposure sion analysis. This approach is unique because it attempts to Topographic exposure is a critical variable in assessing stand create a model that may be applicable regionally and not be vulnerability. Several indices have been created to describe limited to the landscape where it was developed. relative topographic exposure or topographic protection. Eight environmental parameters (elevation, soil rooting Topex wind exposure index has been used for some time to depth, topographic exposure, stand species type, stand assess windthrow risk in Great Britain (Miller 1985). The height, stand density, stand history, and exposed edges) importance of topographic exposure in modeling windthrow 238 Advances in Threat Assessment and Their Application to Forest and Rangeland Management risk has been demonstrated in other areas with forest-based a raster selecting the minimum depth of the two available economies. According to Ruel and others (2002), this vari- data sources and indexed between 0 and 1. able accounts for over 77 percent of the British wind hazard rating system’s total score. Distance-limited Topex was Site: Elevation chosen for this project because of its relatively easy cal- Elevation was also incorporated into the site component of culation and strong correlation to wind tunnel simulation the model. Elevation values from a 30-m resolution digital (Ruel and others 1997). Topographic exposure rasters were elevation model (DEM) of the study were recalculated generated using a model developed and provided by The into an index between 0 and 1. Elevation had statistically Windthrow Research Group, University of British Colum- significant correlation with wind damage in cut-block edge bia, Vancouver, Canada. The scripts calculate an index of vulnerability modeling by Mitchell and others (2001). exposure that is the summation of the maximum and mini- Studies by Worrall and Harrington (1988) in Crawford mum angles to the skyline within a user-specified distance. Notch, New Hampshire, found that gap size from chronic The index can be calculated in the eight cardinal directions wind stress and windsnap or windthrow increased strongly and weighted according to user preferences. Ten exposure with elevation from over 60 percent of the gap area at 764 grids were produced for this project, simulating unweighted m (2,521 feet) to almost 85 percent of the gap area at 1130 exposure at two limiting distances (1000 m and 1500 m) and m (3,729 feet). Gap formation led to subsequent mortality exposure in the eight cardinal directions (limiting distance from chronic wind stress and windthrow in gap edge trees. of 1000 m). This trend was confirmed by Perkins and others (1992) on Camel’s Hump in Vermont. These trends are driven by Site: Soils surface friction acting counter to the force of the wind. Forest soils are also a major component in understand- Windspeed will increase locally with elevation because ing susceptibility of a forest stand to wind damage. Soil surface friction will decrease (Bair 1992). aeration, ease penetration by roots (rooting depth), and moisture-holding capacity all affect the pattern of root Stand: Composition and Characteristics development. Generally, loose dry soils facilitate deeper Variables describing stand composition and characteristics rooting and spreading than do shallow clayey soils (Mergen were extracted from the forest landowner
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