120°W
80°W
Emerald Ash Borer (EAB) Agrilus planipennis Fairmaire
50°N
30°N
100°W
60°W
Detection Likelihood Composite Model
Detection Likelihood
50°N
30°N
Composite Model
Low
Moderate
Moderate High
High
Emerald Ash Borer (EAB) Detection Likelihood Composite
This map depicts the likelihood of a positive EAB detection as a
composite of the MaxEnt Detection Likelihood outputs developed
using EAB presence data from 2002 to 2012 and a seperate model
using only 2012 EAB locations. The two Detection Likelihood models
were combined by taking the maximum value between the two models
at each 1 km cell. Likelihood values are classified into: Low, Moderate,
Moderate High, and High classes.
100°W
0 50 100
200
300
400
500
Miles
Albers Equal Area Conic Projection
Map produced by FHTET, IL
Fort Collins, CO on 11-16-2012
File: EAB_Detection_Likelihood_composite.mxd
Project: EAB Risk Analysis 2013
80°W
Summary of Emerald Ash Borer Agrilus planipennis Fairmaire
Detection Likelihood Composite Model;
November 16, 2012
The Detection Likelihood Composite model for the Emerald Ash Borer (EAB), Agrilus planipennis, was produced for the Contiguous 48 United States (CONUS) at a 1
square kilometer (1 km2) resolution by the U.S. Forest Service, Forest Health Protection, Forest Health Technology Enterprise Team's (Downing et al. 2012) in collaboration with
Animal and Plant Health Service, Plant Protection and Quarantine (APHIS PPQ). The intended use of the Detection Likelihood Composite model 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 with selected site variables and then maps the probability of EAB presence in a geographic context. Two Detection Likelihood models were developed: 1) using
all known EAB presence locations from 2002 to 2012; and 2) a separate model, using only positive EAB locations from the 2012 field season. The two Detection Likelihood models
were combined into a composite model by taking the maximum value between the two models at each 1 km cell. The 2002 to 2012 Detection Likelihood model puts more emphasis
on previously known EAB infested areas, whereas the 2012 Detection Likelihood model puts more emphasis on the frontier of the EAB expanding range. By combining the two
detection models we emphasize the likelihood of detection along the frontier while continuing to utilize all known EAB locations to define the known EAB range. 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 2012 Positives MaxEnt model
Variable
Description and Source
Elevation
Digital Elevation Model (DEM 30 m) from National Elevation Dataset (NED) resampled (bilinear interpolation) to
1km resolution and converted from meters to feet.
Distance to Rest Euclidean distance from Rest Areas (POI Factory 2012 http://www.poi-factory.com/node/14656). Rest Area point
Area
locations were identified as potential introduction locations.
Traffic Volume
Traffic Volume point locations, from across the U.S., were compiled from TrafficMetrix and used to interpolate a
Traffic Volume raster using simple variable distance kriging.
Drainage Index
Drainage Index is based on soil taxonomy and drainage classes from SSURGO and STATSGO soil data.
Road Density
Developed from a rasterized 2003 Tele Atlas Dynamp Transportation v. 5.2 layer, for each state at 100 m. Density was
calculated by summing the number of 100 m 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
Campground
Urban Areas
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
potential introduction locations.
Urban areas within the ash range identified as having a population greater than 100 persons per square mile from the
2000 census (Withrow 2010).
Table 2: Detection Likelihood Classes
MaxEnt
Value
0 to 0.05
0.05 to 0.25
0.25 to 0.50
0.50 to 1
Likelihood
Class
Low
Moderate
Moderate High
High
Contractor Support
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
Fort Collins, CO 80526-8121
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. 2012. 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