Susceptibility Risk Surface for Agrilius biguttatus
Susceptibility Potential Surface for Agrilius biguttatus (Fabricius.) Oak
Splendor Beetle.
Data format: Raster Dataset - ESRI GRID
File or table name: Susceptibility
Coordinate system: Albers Conical Equal Area
Theme keywords: : Forest Pest, Forest Insect, Invasive Species, Exotic, Oak Splendor Beetle, Agrilus biguttatus,
Susceptibility
Abstract: The Susceptibility Potential Surface for Agrilus biguttatus was produced for the Conterminous United
States (CUS) in 1 square kilometer (km²) units by the U.S. Forest Service, Forest Health Technology Enterprise
Team’s (FHTET) Agrilus biguttatus Steering Committee
FGDC and ESRI Metadata:
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•
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•
•
•
•
Identification Information
Data Quality Information
Spatial Data Organization Information
Spatial Reference Information
Entity and Attribute Information
Distribution Information
Metadata Reference Information
Metadata elements shown with blue text are defined in the Federal Geographic Data Committee's (FGDC) Content Standard for
Digital Geospatial Metadata (CSDGM). Elements shown with green text are defined in the ESRI Profile of the CSDGM. Elements
shown with a green asterisk (*) will be automatically updated by ArcCatalog. ArcCatalog adds hints indicating which FGDC elements
are mandatory; these are shown with gray text.
Identification Information:
Citation:
Citation information:
Originators: Downing, M.C.; F.H. Koch, R.A. Haack, F.J.; Sapio, W.D. Smith, D.M. Borchert. 2009.
National Risk map products and documentation for the Oak Splendor Beetle (Agrilus bigutatus). Ft.
Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team.
http://www.fs.fed.us/foresthealth/technology/invasives_agrilusbiguttatus_riskmaps.shtml
Title:
Susceptibility Potential Surface for Agrilus biguttatus
*File or table name: susceptibility (GRID)
*
Publication date: 20100309
*Geospatial data presentation form: raster digital data
Susceptibility Risk Surface for Agrilius biguttatus
Series information:
Series name: Version 2.0
Issue identification: 20100309
Publication information:
Publication place: Fort Collins, Colorado
Publisher: Marla C. Downing
Online linkage:
http://www.fs.fed.us/foresthealth/technology/invasives_agriliusbiguttatus_riskmaps.shtml
Larger work citation:
Citation information:
Originators: Downing, M.C.; F.H. Koch, R.A. Haack, F.J.; Sapio, W.D. Smith, D.M. Borchert. 2009.
National Risk map products and documentation for the Oak Splendor Beetle (Agrilus bigutatus). Ft.
Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team.
http://www.fs.fed.us/foresthealth/technology/invasives_agrilusbiguttatus_riskmaps.shtml
Title:
Susceptibility Potential Surface for Agrilus biguttatus Oak Splendor Beetle.
Description:
Abstract:
The Susceptibility Potential Surface for Agrilus biguttatus was produced for the conterminous United
States in 1 square kilometer (km²) units by the U.S. Forest Service (USFS), Forest Health Technology
Enterprise Team’s (FHTET) Agrilus biguttatus Steering Committee; a multidisciplinary team with
participation from USFS, Animal and Plant Health Inspection Service (APHIS), and North Carolina State
University (NCSU).
Two components used to create the Susceptibility Potential Surface were: 1) Introduction Potential and 2)
Establishment Potential. The introduction Potential and Establishment Potential were combined in an
equal weighted overlay to produce the final Susceptibility Surface.
The Introduction Potential Surface for Agrilus biguttatus was produced for the Conterminous United States
(CUS) in 1 square kilometer (km²) units by the U.S. Forest Service, Forest Health Technology Enterprise
Team’s (FHTET)Steering Committee; a multidisciplinary team with participation from United States Forest
Service (USFS), Animal and Plant Inspection Service (APHIS) and North Carolina State University.
Supporting biological information was gathered from USDA Forest Service Research Station experts,
scientific literature, and the Exotic Forest Pest (ExFor) website (North American Forest Commission, 2008)
http://spfnic.fs.fed.us/exfor/data/pestreports.cfm?pestidval=154&langdisplay=english
The Establishment component for A. biguttatus depicts where the pest could survive if it was introduced.
If the pest is known to have already been introduced, it may be desirable to prioritize locations where the
pest populations are most able to survive and may be expanding. In cases where it is unknown whether
the pest has been introduced the Establishment Component should be used in conjunction with the
Introduction component to develop a Susceptibility component for A. biguttatus. Supporting biological
information was gathered from USDA Forest Service Research Station experts, scientific literature, and the
Exotic Forest Pest (ExFor) website (North American Forest Commission, 2008)
http://spfnic.fs.fed.us/exfor/data/pestreports.cfm?pestidval=154&langdisplay=english
Susceptibility Risk Surface for Agrilius biguttatus
References
North American Forest Commission Exotic Forest Pest Information System (NAFC-ExFor). 2008. Invasive
Species information system for pests with potential to cause significant damage to North American forest
resources. Available at:
http://spfnic.fs.fed.us/exfor/data/pestreports.cfm?pestidval=154&langdisplay=english
Purpose:
The product’s intended use is to identify potential areas where A. biguttatus could be introduce,
established and survive in conterminous United States.
Introduction Potential
The Introduction Potential Surface for Agrilus biguttatus was produced for the Conterminous United States
(CUS) in 1 square kilometer (km²) units by the U.S. Forest Service, Forest Health Technology Enterprise
Team’s (FHTET) A. biguttatus Steering Committee. The product’s intended use is to develop a detection
strategy for Agrilus biguttatus. Three primary datasets with standardized values from 0 to 10 were used
as variables in the analysis. Each data set (Table 1) was used in a weighted overlay process where
Principal Ports = 33.4% and Markets = 33.3%, and Distribution centers = 33.3%. The final Introduction
Potential Surface output values also range from 0 to 10, with 10 having the highest potential of
introduction.
Each of the variables was used to depict potential locations where Agrilus biguttatus could be released into
the CUS. To delineate Agrilus biguttatus potential flight range, a curvilinear distance decay value was
assigned with a risk rating of 10 at the source location and decreasing to 0 at 5 kilometers away (Table 2).
Principal Ports. Source: Army Corps of Engineer, Waterborne Commerce, Foreign Cargo Statistics (1996
to 2003). A summary of imported tonnage of commodities that use Wood Packing Material (WPM), the
packing material associated with Buprestid species interceptions, recorded in the APHIS Pest Interception
Network (PIN) 309 database. Only commodities exported from countries where A. biguttatus is present
were included, countries of origin were not ranked. This point data was converted to 1 km² grid cells. For
a list of specific countries and see commodities see Appendix A.
United States Ports that received Commodities from Countries (listed below) were used:
The Ports shapefiles are the result of querying a data set summarizing 8 years (1996-2003) of foreign
marine cargo import information. These data have been compiled from Army Corps of Engineers
waterborne commerce statistics, and then sorted by commodity type, foreign country of shipment origin,
and U.S. port where the shipment arrived.
Markets. Source: Federal Highway Administration, Freight Management and Operations, Freight Analysis
Framework, Highway Truck Volume (HTV) and Capacity Data and Environmental Systems Research
Institute’s (ESRI) City polygon Data. Flow/capacity data was used to determine the number of truck trips
occurring within the city polygons, which were then used to define potential markets.
Using a polygon data set from Environmental Systems Research Institute (ESRI) that depicts Cities in the
United States an intersection was conducted. These City polygons were included as standard spatial data
Susceptibility Risk Surface for Agrilius biguttatus
with the shipment of ArcGIS ver 9.3 in the year 2005. Next, the ESRI City Polygons were intersected with
HTV. City polygons were selected that received any truck trips.
Distribution Centers. Sources: National Transportation Atlas Database (2003). Distribution centers that
handle commodities that likely use WPM during transport were considered; 1496 distribution center
records were used, and 1510 locations were removed from the analysis. The Distribution Centers
Polygons were selected from the ESRI City polygon data set (listed above). Then a distance decay
function illustrated in table 2 was applied to these data. An additional 193 distribution centers were
added. Cartesian coordinates were also provided by national retailers, including: FedEx, IKEA, Kmart,
KOHL’s, Lowe’s, OfficeMax, PETCO, Target, The Home Depot, and Wal-Mart.
Analysis
Finally, each data set was used in a weighted overlay process where Principal Ports = 33.4% and
Markets = 33.3%, and Distribution centers = 33.3%.
Table 1
Introduction Variables
Principal Ports
Markets
Distribution Centers
Value Ranges
0 - 10
0 - 10
0 – 10
Table 2
Distance Decay for Probable Flight Range of Agrilus biguttatus
Distance (kilometers)
0
>
>
>
=
(Source)
1 and < = 2
2 and < = 3
3 and < = 4
> 5
GRID Value
10
8
3
1
0
(Extreme)
(High)
(Moderate)
(Low)
(Little or No)
Establishment Potential
The Establishment Potential Surface for Agrilus biguttatus was produced for the conterminous United
States in 1 square kilometer (km²) units by the U.S. Forest Service (USFS), Forest Health Technology
Enterprise Team’s (FHTET) Agrilus biguttatus Steering Committee; a multidisciplinary team with
participation from USFS, Animal and Plant Health Inspection Service (APHIS), and North Carolina State
University (NCSU).
The Establishment component for A. biguttatus depicts where the pest could survive if it was introduced.
If the pest is known to have already been introduced, it may be desirable to prioritize locations where the
Susceptibility Risk Surface for Agrilius biguttatus
pest populations are most able to survive and may be expanding. In cases where it is unknown whether
the pest has been introduced the Establishment Component should be used in conjunction with the
Introduction component to develop a Susceptibility component for A. biguttatus. Supporting biological
information was gathered from USDA Forest Service Research Station experts, scientific literature, and the
Exotic Forest Pest (ExFor) website (North American Forest Commission, 2008)
http://spfnic.fs.fed.us/exfor/data/pestreports.cfm?pestidval=154&langdisplay=english
Purpose:
The product’s intended use in conjunction with the Introduction Potential Surface is to develop a
Susceptibility Potential Surface for A. biguttatus. Three datasets were used as parameters in the
establishment analysis to determine the level of risk (hazard potential) A. biguttatus poses in areas
where it could survive:
1. Natural Host (i.e. Quercus spp from FIA) (Appendix B)
2. Drought (from 2007 – 2009) (Appendix C)
3. Urban Forest
Natural Host
Source: USDA Forest Service, Forest Inventory and Analysis (FIA) program.
Only species of Oaks (Quercus spp) contained in the FIA were considered (Appendix B). The Oak data
were used as a presence absence input. That is, Oak, size, Trees/Acre, or basal area were not considered.
Drought
Source: USDA Forest Service, Forest Health Technology Enterprise Team (FHTET) (Appendix C).
Extreme late spring or early summer drought conditions from the years of 2007 – 2009 were considered.
These data were partitioned into 4 classes: 0 = No drought conditions were observed for all three years,
3 = drought conditions occurred for one year in the three year time period, 6 = drought conditions
occurred for two years in the three year time period, and 10 = drought conditions occurred for three
years in the three year time period.
Urban Forest
Source: USDA Forest Service, Forest Health Technology Enterprise Team (FHTET).
The National Land Classification Data (NLCD) types Deciduous Forest or Mixed Forest was used as our
urban forest input subset type. These data were filtered by urban areas as described by the City Light
data set (Imhoff et al. 1997). The urban forest subset cell values were calculated by summing up the
total area, in percent, of the NLCD cell (native cell size of NLCD is 30 meters by 30 meters) occupied
within a 1 Km2 grid cell. Next, the data were partitioning into ten integer classes (1 – 10) using Jenks’
Natural breaks.
Process
Natural Host was modified by the drought producing a Disturbed Natural Host data set that contains
values of 1, 3, 6, and 10. The Urban Forest was combined with the Disturbed Natural Host via a overly
process. If Disturbed Natural Host was spatially coincident with Urban Forest the cell value was assigned
to the Disturbed Natural Host data set.
References
Susceptibility Risk Surface for Agrilius biguttatus
Imhoff, M. L., W. T. Lawrence, C. D. Elvidge, T. Paul, E. Levine, M. V. Privalsky, and V. Brown. 1997.
Using Nighttime DMSP/OLS Images of City Lights to Estimate the Impact of Urban Land Use on Soil
Resources in the United States. REMOTE SENS. ENVIRON. 59:105–117.
Susceptibility Potential
The Introduction Potential and the Establishment Potential were combined in an equal-weighted overlay to
produce the final Susceptibility Potential Surface. The final data were partitioned into five susceptibility
classes: 1) Little or No, 2) Low, 3) Moderate, 4) High, and 5) Extreme using Jenks’ Natural Breaks.
*Language of dataset: en
Time period of content:
Time period information:
Single date/time:
Calendar date: 20100309
Currentness reference:
publication date
Status:
Progress: Planned
Maintenance and update frequency: As needed
Spatial domain:
Bounding coordinates:
*West bounding coordinate: -131.718010
*East bounding coordinate: -50.048796
*North bounding coordinate: 54.232833
*South bounding coordinate: 17.231111
Local bounding coordinates:
*Left bounding coordinate: -2356278.5
*Right bounding coordinate: 2257721.5
*Top bounding coordinate: 3172335.3125
*Bottom bounding coordinate: 268335.3125
Place:
Place keywords: Conterminous United States
Place keyword thesaurus: Lower 48 States
Access constraints: None
Use constraints:
None
Point of contact:
Contact information:
Contact organization primary:
Contact person: Marla C. Downing
Contact organization: Forest Health Technology Enterprise Team (FHTET) Forest Health Protection
Contact position: FHTET Lead, Biological Scientist
Susceptibility Risk Surface for Agrilius biguttatus
Contact address:
Address type: mailing and physical address
Address:
2150 Centre Avenue, Bldg A, Suite 331
City: Fort Collins
State or province: Colorado
Postal code: 80526-1891
Country: USA
Contact voice telephone: 970-295-5843
Contact electronic mail address: mdowning@fs.fed.us
Hours of service: 9:00 AM - 5:00 PM MT
Data set credit:
Michael F. Tuffly
Steering Committee:
Marla C. Downing, FHTET Lead
Daniel M. Borchert, APHIS PPQ
Frank H. Koch, NCSU
Frank J. Sapio, USFS FHTET
Bill D. Smith, USFS SRS
Robert A. Haack USFS NRS
Roger D. Magarey NCSU
Security information:
Security classification: Unclassified
*Native dataset format: Raster Dataset
*Native data set environment:
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.1.0.722
Cross reference:
Citation information:
Originators: Downing, M.C.; F.H. Koch, R.A. Haack, F.J.; Sapio, W.D. Smith, D.M. Borchert. 2009.
National Risk map products and documentation for the Oak Splendor Beetle (Agrilus bigutatus). Ft.
Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team.
http://www.fs.fed.us/foresthealth/technology/invasives_agrilusbiguttatus_riskmaps.shtml
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Spatial Reference Information:
Susceptibility Risk Surface for Agrilius biguttatus
Horizontal coordinate system definition:
Coordinate system name:
*Projected coordinate system name: NAD_1983_Albers
*Geographic coordinate system name: GCS_North_American_1983
Planar:
Map projection:
*Map projection name: Albers Conical Equal Area
Albers conical equal area:
*Standard parallel: 29.500000
*Standard parallel: 45.500000
*Longitude of central meridian: -96.000000
*Latitude of projection origin: 23.000000
*False easting: 0.000000
*False northing: 0.000000
Planar coordinate information:
*Planar coordinate encoding method: row and column
Coordinate representation:
*Abscissa resolution: 1000
*Ordinate resolution: 1000
*Planar distance units: meters
Geodetic model:
*Horizontal datum name: North American Datum of 1983
*Ellipsoid name: Geodetic Reference System 80
*Semi-major axis: 6378137.000000
*Denominator of flattening ratio: 298.257222
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Entity and Attribute Information:
Detailed description:
*Name: establishment
Entity type:
*Entity type label: susceptibility
*Entity type: Table
*Entity type count: 10
Entity type definition:
Susceptibility Potential Surface for Agrilus biguttatus
Attribute:
*Attribute label: ObjectID
*Attribute alias: ObjectID
*Attribute definition:
Internal feature number.
*Attribute definition source:
ESRI
*Attribute type: OID
*Attribute width: 4
Susceptibility Risk Surface for Agrilius biguttatus
*Attribute precision: 0
*Attribute scale: 0
Attribute domain values:
*Unrepresentable domain:
Sequential unique whole numbers that are automatically generated.
Attribute measurement frequency:
Unknown
Attribute:
*Attribute label: Value
*Attribute alias: Value
Attribute definition:
Integer Value from 0 - 10 where 0 equals little or no susceptibility and 10 equals
extremely high susceptibility. For graphical reasons these data were reclassed into 5
classes: 0 = Little or No, 1 – 3 = Low, 4 – 6 = Moderate, 7 – 8 = High, and 9 – 10 =
Extreme.
*Attribute
*Attribute
*Attribute
*Attribute
type: Integer
width: 0
precision: 0
scale: 0
Attribute value accuracy information:
Attribute value accuracy: As Reported
Attribute measurement frequency:
As needed
Attribute:
*Attribute label: Count
*Attribute alias: Count
Attribute definition:
The frequency of 1000 by 1000 meter GRID cells
Attribute definition source:
ESRI
*Attribute
*Attribute
*Attribute
*Attribute
type: Double
width: 0
precision: 0
scale: 0
Attribute measurement frequency:
As needed
Distribution Information:
Susceptibility Risk Surface for Agrilius biguttatus
Resource description: Downloadable Data
Standard order process:
Digital form:
Digital transfer information:
*Transfer size: 12.78 Megabytes (uncompressed)
*Dataset size: 12.78 Megabytes (uncompressed)
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Metadata Reference Information:
*Metadata date: 20100309
*Language of metadata: en
Metadata contact:
Contact information:
Contact organization primary:
Contact person: Marla C. Downing
Contact organization: Forest Health Technology Enterprise Team (FHTET) USDA Forest Service
Contact position: FHTET, Lead and Biological Scientist
Contact address:
Address type: mailing and physical address
Address:
2150 Centre Avenue, Bldg A, Suite 331
City: Fort Collins
State or province: Colorado
Postal code: 80526-1891
Country: USA
Contact voice telephone: 970-295-5843
Contact electronic mail address: mdowning@fs.fed.us
Hours of service: 9:00 AM - 5:00 PM MT
*Metadata standard name: FGDC Content Standards for Digital Geospatial Metadata
*Metadata standard version: FGDC-STD-001-1998
*Metadata time convention: local time
Metadata security information:
Metadata security classification: Unclassified
Appendix A
Susceptibility Risk Surface for Agrilius biguttatus
COMM_NAME
All Manufactured Equipment, Machinery and Products
Building Cement & Concrete; Lime; Glass
Forest Products, Lumber, Logs, Woodchips
Primary Iron and Steel Products (Ingots,Bars,Rods,etc.)
Primary Non-Ferrous Metal Products;Fabricated Metal Prods
Sand, Gravel, Stone, Rock, Limestone, Soil, Dredged Material
Paper & Allied Products
Primary Wood Products; Veneer; Plywood
AND
CNTRY_NAME
Algeria
Azerbaijan
Belarus
Czech Republic
Egypt
France
Germany
Hungary
Libya
Morocco
Netherlands
Poland
Russia
Spain
Sudan
Tunisia
Ukraine
United Kingdom
Appendix B
FIA Oak Species
FIA Code
801
801
802
803
804
Scientific Name
Quercus agrifolia
Quercus agrifolia var. oxyadenia
Quercus alba
Quercus arizonica
Quercus bicolor
Quercus chapmanii
805
806
807
809
810
811
812
812
814
815
803
843
816
817
842
818
819
820
821
822
823
840
824
825
841
826
827
829
844
813
830
831
845
832
833
834
836
808
835
828
837
Susceptibility Risk Surface for Agrilius biguttatus
Quercus chrysolepis
Quercus coccinea
Quercus douglasii
Quercus ellipsoidalis
Quercus emoryi
Quercus engelmannii
Quercus falcata
Quercus falcata var. falcata
Quercus gambelii
Quercus garryana
Quercus graciliformis
Quercus gravesii
Quercus grisea
Quercus hypoleucoides
Quercus ilicifolia
Quercus imbricaria
Quercus incana
Quercus kelloggii
Quercus laevis
Quercus laurifolia
Quercus lobata
Quercus lyrata
Quercus macrocarpa
Quercus margarettiae
Quercus marilandica
Quercus michauxii
Quercus minima
Quercus muehlenbergii
Quercus nigra
Quercus oblongifolia
Quercus oglethorpensis
Quercus pagoda
Quercus palustris
Quercus phellos
Quercus prinoides
Quercus prinus
Quercus rubra
Quercus rugosa
Quercus shumardii
Quercus similis
Quercus sinuata var. sinuata
Quercus stellata
Quercus texana
Quercus turbinella
Quercus velutina
838
839
Susceptibility Risk Surface for Agrilius biguttatus
Quercus virginiana
Quercus wislizeni
Appendix C
Drought Calculation
Agrilus biguttatus: Late Spring-Early Summer Drought 2007-2009
Frank Koch, Bill Smith
We used gridded data (approximately 4 km2 spatial resolution) created with the PRISM climate mapping system to
perform our analyses. The gridded data (WGS72 projection) were downloaded from the PRISM Group web site
(http://www.prism.oregonstate.edu). When these analyses were performed, final versions of total precipitation, mean
daily minimum temperature, and mean daily maximum temperature grids were available for every month from January
1895 until October 2009.
Methods
We adopted an approach, utilizing the PRISM climate grids, in which a moisture index value for a given location (i.e.,
a grid cell) is calculated based on both precipitation and potential evapotranspiration values for that location during the
time period of interest. Potential evapotranspiration measures the loss of soil moisture through plant uptake and
transpiration (Akin 1991). It does not measure actual moisture loss, but rather the loss that would occur under ideal
conditions (i.e., if there was no possible shortage of moisture for plants to transpire) (Akin 1991, Thornthwaite 1948).
The inclusion of both precipitation and potential evapotranspiration provides a fuller accounting of a location’s water
balance than precipitation alone. So, to complement the PRISM monthly precipitation grids, we computed monthly
potential evapotranspiration (PET) grids using the Thornthwaite formula (Akin 1991, Thornthwaite 1948):
[1]
PETm = 1.6 L(10
Tm a
)
I
where PETm = the potential evapotranspiration for a given month m in cm; L = a correction factor for the hours of
daylight and number of days in a month for all locations at a particular latitude; Tm = the mean temperature for month m
in degrees C; a = an arbitrary exponent calculated by a = 6.75 ×10-7I3 – 7.71 × 10-5I2 + 1.792 × 10-2I + 0.49239; and I =
1.514
12
T 
an annual heat index, calculated as I = ∑  i 
i =1  5 
, where Ti is the mean temperature for each month i of the year. To
Susceptibility Risk Surface for Agrilius biguttatus
implement Equation 1 spatially, we created a grid of latitude values for determining the L adjustment for any given 4km2 grid cell in the conterminous United States [see Thornthwaite (1948) for a table of L correction factors]. We
calculated the mean monthly temperature grids as the mean of the corresponding PRISM daily minimum and maximum
monthly temperature grids.
We used the precipitation (P) and PET grids to generate baseline moisture index grids for 1910-2009 for the
conterminous United States. Willmott and Feddema (1992) proposed a moisture index, MI′, with the following form:
[2]
P < PET
 P / PET − 1 ,

MI ' = 1 − PET / P ,
P ≥ PET

0
, P = PET = 0

This set of equations yields a dimensionless index scaled between -1 and 1. Though MI′ is typically calculated based on
annual values, for this analysis we were only interested in moisture conditions during late spring-early summer, roughly
a three-month time window of interest. So, we calculated MI′ based on the total P and PET values summed over three
months rather than an entire year. Notably, late spring-early summer represents a different time window depending on
geographic location (i.e., depending on latitude/elevation/climate). For this reason, we actually calculated nationwide
MI′ grids for three different three-month windows during each year 1910-2009: March-May, April-June, and May-July.
(At the end of our analysis, we ultimately combined three output grids for each year into a single grid; details on how
we did this are provided below.)
To determine departure from typical moisture conditions, we first created a normal grid, MI′norm, representing the mean
of the 100 individual MI′ grids generated for each three-month window (i.e., one grid for each year 1910-2009). We
also created a standard deviation grid, MI′SD, calculated from these individual grids as well as the MI′norm grid. We
subsequently calculated moisture difference z-scores, MDZi, from these components:
[3]
MDZ i =
MI 'i − MI ' norm
MI ' SD
where i = a particular year in the 100-year period 1910-2009. The MDZi scores may be classified in terms of degree of
moisture deficit or surplus as follows:
MDZi Score Moisture Status
<-2
Extreme drought (2.3 percent frequency)
-2 to -1.5
Severe drought (4.4% frequency)
-1.5 to -1
Moderate drought (9.2% frequency)
Susceptibility Risk Surface for Agrilius biguttatus
-1 to -0.5
Mild drought (15% frequency)
-0.5 to 0.5
Near normal conditions (38.2% frequency)
0.5 to 1
Mild moisture surplus (15% frequency)
1 to 1.5
Moderate moisture surplus (9.2% frequency)
1.5 to 2
Severe moisture surplus (4.4% frequency)
>2
Extreme moisture surplus (2.3% frequency)
To combine the three output MDZ grids for each year (i.e., one each for the March-May, April-June, May-July
windows) into a single nationwide grid, we first subset them using PRISM data related to frost-free period. Briefly, we
divided the conterminous U.S. into three geographic regions (Figure 1) based on the 30-year mean Julian date of the
last spring freeze: Zone 1, including all areas with a mean Julian date ≤ 90 (i.e., last freeze prior to April 1); Zone 2, all
areas with a mean Julian date between 90 and 120 (i.e., last freeze between April 1 and April 30); and Zone 3, all areas
with a mean Julian date > 120 (i.e., last freeze after April 30). Next, we matched each three-month window to the most
appropriate zone (Figure 1), and then clipped the corresponding MDZ grid to the zonal boundaries. Finally, we
mosaiced these clipped grids into a single grid covering the conterminous United States.
We re-projected the final output grids to Albers NAD83. For the A. biguttatus risk model (i.e., the map of
establishment risk), we generated binary (0/1) grids for the years 2007-2009 from the final MDZ grids; basically, MDZ
grid cells exhibiting severe or extreme drought (i.e., z-score < -1.5) were assigned a value of 1, while all other cells
Susceptibility Risk Surface for Agrilius biguttatus
were assigned a value of zero. The three binary grids were then added together using map algebra to create a three-level
map of drought risk.