120°W 100°W 80°W 60°W Emerald Ash Borer (EAB) Agrilus ... · Table 1: Variables used in A....
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60°W 80°W 80°W 100°W 100°W 120°W 50°N 50°N 30°N 30°N 0 100 200 300 400 500 50 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 Emerald Ash Borer (EAB) Agrilus planipennis Fairmaire Detection Likelihood Composite Model Detection Likelihood 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.
Transcript of 120°W 100°W 80°W 60°W Emerald Ash Borer (EAB) Agrilus ... · Table 1: Variables used in A....
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Albers Equal Area Conic Projection
Map produced by FHTET, ILFort Collins, CO on 11-16-2012File: EAB_Detection_Likelihood_composite.mxdProject: EAB Risk Analysis 2013
Emerald Ash Borer (EAB) Agrilus planipennis Fairmaire Detection Likelihood Composite Model
Detection Likelihood Composite Model
LowModerateModerate HighHigh
Emerald Ash Borer (EAB) Detection Likelihood CompositeThis map depicts the likelihood of a positive EAB detection as acomposite of the MaxEnt Detection Likelihood outputs developedusing EAB presence data from 2002 to 2012 and a seperate modelusing only 2012 EAB locations. The two Detection Likelihood modelswere combined by taking the maximum value between the two modelsat each 1 km cell. Likelihood values are classified into: Low, Moderate, Moderate High, and High classes.
Table 1: Variables used in A. planipennis Detection Likelihood 2012 Positives MaxEnt model
Table 2: Detection Likelihood Classes
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).
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 Area
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.
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
1, 3, 5 year moisture surplus and deficit for 2011 developed from PRISM climate data (Koch 2011).
Distance to Campground
Euclidean distance from campgrounds identified by federal and state cooperators. Campgrounds were identified as potential introduction locations.
Urban Areas Urban areas within the ash range identified as having a population greater than 100 persons per square mile from the 2000 census (Withrow 2010).
MaxEnt Value
Likelihood Class
0 to 0.05 Low 0.05 to 0.25 Moderate 0.25 to 0.50 Moderate High 0.50 to 1 High
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
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 [email protected]
