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Assessing the Potential Risk of Emerald Ash Borer Establishment and Spread using GIS Michael P. Strager Jacquelyn M. Strager William D. Ayersman West Virginia.

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Presentation on theme: "Assessing the Potential Risk of Emerald Ash Borer Establishment and Spread using GIS Michael P. Strager Jacquelyn M. Strager William D. Ayersman West Virginia."— Presentation transcript:

1 Assessing the Potential Risk of Emerald Ash Borer Establishment and Spread using GIS Michael P. Strager Jacquelyn M. Strager William D. Ayersman West Virginia University

2 Overview Background on EAB in North America Mapping risk factors Modeling probability of spread Desired outcomes

3 Emerald Ash Borer (EAB) Native to Asia First detected in Detroit, Michigan (2002) Highly destructive to native ash species

4 Ash species in North America Importance in the ecosystem Urban and developed areas –25 million+ trees affected to date –High removal and replacement costs in the billions $$ –Loss of trees leads to reduced property values

5 Ash Tree and EAB populations

6 Cooperative EAB project APHIS Jan 2009

7 Project: EAB in the mid-Atlantic region EAB is not yet fully established in the study region Opportunity to focus monitoring and outreach Quarantined Counties

8 Mapping risk factors Focused on mapping anthropogenic factors related to introduction/spread of EAB: –Movement of trees (nursery stock) –Movement of wood and wood products

9 Risk factors: Hardwood firewood Parks and picnic areas Public and private campgrounds Vacation homes Retail sales of firewood EAB infested firewood, Troy Kimoto, CFIA

10 Mapping firewood usage Campgrounds

11 Risk factors: Sawmills Timber industry, particularly sawmills Wood haulers WV sawmill, Appalachian Hardwood Center photo

12 Mapping sawmills

13 Risk factors: Nurseries Ash species are valuable nursery crop Estimated 2 million ash trees / year Spread to Maryland was through nursery stock WV Division of Forestry tree nursery

14 Mapping nurseries Nurseries Home and garden suppliers

15 Other factors Population centers New home construction Interstate commerce Shipping

16 Data refinements Campgrounds –Size, type of facility –Origin of visitors Nurseries, sawmills –Size of facility –Materials handled –Source of materials

17 Maximum entropy approach A Bayesian technique Useful for making predictions from incomplete information – presence only Robust to colinearity between explanatory variables Stable distribution with limited training data Evaluates relative variable importance

18 Desired outcomes Target monitoring Public outreach and education

19 Benefits / technology transfer This project will assist federal and state agencies by Mapping and modeling locations with high potential for insect introductions through the movements of wood and wood-based materials. Using a GIS-based approach, a risk prioritization framework is being developed to assess and rank various mapped risk factors for EAB introduction and spread. Data will be useful for other pests


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