50°N
120°W 100°W 80°W
60°W
50°N
30°N Detection Likelihood
Positives 2002 to 2012
Low
Moderate
Moderate High
High
Emerald Ash Borer (EAB) Detection Likelihood
This map depicts the likelihood of a positive EAB detection and is based on the associations of eleven independent variables with
EAB presence data from 2002 to 2012. Detection Likelihood values were generated using the bootstrap option of the MaxEnt statistical technique. The analysis was limited to the ash range (including urban areas) for the U.S. Likelihood values are classified into: Low, Moderate, Moderate High, and High classes.
100°W
0 50 100 200
Miles
300 400
Albers Equal Area Conic Projection
500 Map produced by FHTET, IL
Fort Collins, CO on 11-16-2012
File: EAB_Detection_Likelihood.mxd
Project: EAB Risk Analysis 2013
80°W
30°N

The 2002 to 2012 Detection Likelihood model for the Emerald Ash Borer (EAB), Agrilus planipennis , was produced for the Contiguous 48 United States
(CONUS) at a 1 square kilometer (1 km
2
) resolution by the U.S. Forest Service, Forest Health Protection, Forest Health Technology Enterprise Team (FHTET), in collaboration with Animal and Plant Health Service, Plant Protection and Quarantine (APHIS PPQ) staff members. The intended use of the 2002 to 2012 Detection
Likelihood product is to inform the 2013 EAB sample design. Pest information for EAB was taken from the Exotic Forest Pest (ExFor) website
( http://foresthealth.fs.usda.gov/exfor ).
The likelihood of detecting EAB was modeled using the Maximum Entropy (MaxEnt) interpolation technique. MaxEnt identifies significant associations between presence and absence trap data from 2002 to 2012 with selected site variables and then maps the probability of EAB presence in a geographic context. This non-parametric approach has been demonstrated to have utility for generating species distributions, because of its treatment of locations where a species has not been observed as pseudo-absence locations. Pseudo-absence is defined as a species being absent from an area for one of three reasons: 1) the habitat cannot support the species, 2) the species has not completely filled its geographic niche, or 3) the species is present but was not detected. For a species such as EAB that is still emerging and expanding into its full geographic range this is an appropriate modeling approach.
Presence and absence EAB data from 2002 to 2012 was provided by APHIS PPQ and state cooperators. Independent variables were investigated and selected to represent where EAB is likely to establish (Table 1). A bias raster, based on the autocorrelation of positive EAB locations, was used to correct for sampling biases.
The MaxEnt bootstrap option was used to generate 100 iterations to develop an average Detection Likelihood model. For display purposes and ease of interpretation the data were partitioned into four classes (Table 2).
Table 1: Variables used in A. planipennis Detection Likelihood 2002 to 2012 Positives MaxEnt model
Variable Description and Source
Table 2: Detection Likelihood Classes
MaxEnt Likelihood
Elevation Digital Elevation Model (DEM 30m) from National Elevation Dataset (NED) resampled (bilinear interpolation) to
Value Class
Low
1km resolution and converted from meters to feet.
0 to 0.05
Distance to Rest Euclidean distance from Rest Areas (POI Factory 2012 http://www.poi-factory.com/node/14656 ). Rest Area point locations were identified as potential introduction locations.
0.05 to 0.25 Moderate
0.25 to 0.50 Moderate High Area
Traffic Volume Traffic Volume point locations, from across the U.S., were compiled from TrafficMetrix and used to interpolate a
High 0.50 to 1
Traffic Volume raster using simple variable distance kriging.
Contractor Support
Drainage Index Drainage Index is based on soil taxonomy and drainage classes from SSURGO and STATSGO soil data.
Road Density Developed from rasterized 2003 Tele Atlas Dynamp Transportation v. 5.2 layer for each state at 100m. Density was calculated by summing the number of 100m road pixels within a 1 km pixel.
Housing Density Housing density data developed using the 2000 U.S. census data.
Moisture
Surplus/ Deficit
Distance to
1, 3, 5 year moisture surplus and deficit for 2011 developed from PRISM climate data (Koch 2011).
Euclidean distance from campgrounds identified by federal and state cooperators. Campgrounds were identified as
Ian Leinwand
John Withrow
Point of Contact
Marla C. Downing
Forest Health Technology Enterprise
Team (FHTET), Forest Health
Protection, USDA Forest Service
2150 Centre’ Ave., Bldg A, Suite 331
Campground potential introduction locations.
Urban areas within the ash range identified as having a population greater than 100 persons per square mile from the
Fort Collins, CO 80526-8121
Urban Areas
2000 census (Withrow 2010).
Phone: 970-295-5843 mdowning@fs.fed.us
Downing, M. C., I. I. F. Leinwand, P. H. Chaloux, J. R. Withrow, and F. J. Sapio. 2011. Emerald Ash Borer (EAB) “ Agrilus planipennis Fairmaire Risk Assessment” U.S.
Forest Service Forest Health Technology Enterprise Team (FHTET) Forest Health Protection USDA Forest Service, http://www.fs.fed.us/foresthealth/technology/invasives_agrilusplanipennis_riskmaps.shtml