Conclusions

The results on assessment of the ash resource, estimates of past spread of EAB, and preliminary efforts to create a model of spread leave us with the following conclusions:

• There is a great deal of ash resource in the Eastern United States, especially in the northern half of the region. For many States, ash makes up a sizeable portion of the total basal area.
• As of spring 2006, the front border of the current EAB infestation is just now reaching the areas with the largest amount of available ash, e.g., in northeast Ohio, northwest Pennsylvania, and western New York.
• Though much of the current expanding range of EAB in northwest Ohio and northeast Indiana is dominated by agriculture, our high-resolution analysis shows plenty of ash exists for EAB expansion in this zone in small woodlots, riparian woods, small wetlands, and miscellaneous parcels bordering the agricultural fields.
• The map of our estimate of the expansion of the front from 1998 to 2005 shows a fairly consistent pattern of roughly 20 km/ yr. This rate of expansion would necessarily have to include both the biological dispersal capacity of the insect and some short-distance movement assisted by humans, (e.g., on or in vehicles, plant material, wood material, etc.).
• The components of the insect-ride model (roads, campgrounds, wood products industries, population density, and urban centers) have been acquired and processed to create a weighting scheme based on various factors, including buffer distances and number of people involved in the endeavor. When combined, every 270-m pixel in the study area has been scored for its likelihood of enhancing EAB spread.
• The gravity model yielded a relative scoring of potential EAB invasion among campgrounds based on traffic from the core EAB zone and attractiveness of the campgrounds.
• Preliminary test results of movement of the front from the EAB Shift model shows the probability of colonization diminishes quickly away from the front, and that the insect-ride components modify those results through the multiplier effects.
• We hope to use these data along with GIS and modeling tools to better understand the potential rate of spread, which could inform management decisions that will hopefully slow the spread of this destructive pest.

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