Mapping of the Asian Longhorned Beetle’s Time to Maturity and Risk to Invasion at Contiguous United States Extent
Alexander P. Kappel (Corresponding Author)
Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610
R. Talbot Trotter
U.S. Forest Service, Northern Research Station, 51 Mill Pond Rd, Hamden, CT 06514
Melody A. Keena
U.S. Forest Service, Northern Research Station, 51 Mill Pond Rd, Hamden, CT 06514
John Rogan
Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610
Christopher A. Williams
Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610
Abstract
Anoplophoraglabripennis, the Asian Longhorned Beetle (ALB), is an invasive species of high economic and ecological relevance given the potential it has to cause tree damage, and sometimes mortality, in the United States. Because this pest is introduced by transport in wood-packing products from Asia, ongoing trade activities pose continuous risk of transport and opportunities for introduction. Therefore, a geographic understanding of the spatial distribution of risk factors associated with ALB invasions is needed. Chief among the multiple risk factors are (a) the potential for infestation based on host tree species presence/absence, and (b) the temperature regime as a determinant of ALB’s growth time to maturity. This study uses an empirical model of ALB’s time to maturity as a function of temperature, along with a model of heat transfer in the wood of the host and spatial data describing host species presence/absence data, to produce a map of risk factors across the conterminous United States to define potential for ALB infestation and relative threat of impact. Results show that the region with greatest risk of ALB infestation is the eastern half of the country, with lower risk across most of the western half due to low abundance of host species, less urban area, and prevalence of cold, high elevations. Risk is high in southeastern states primarily because of temperature, while risk is high in northeastern and northern central states because of high abundance of host species.
Keywords
Asian Longhorned Beetle, Anoplophoraglabripennis, Invasion, Colonization, Risk, Maturity, United States, Modeling, Degree Days, Temperature, Host Species, Distribution, Instar
5. Supporting Information
5.1 Supporting Figures
Figure1- A comparison of the two risk scenarios. Green areas contain species known to be at risk to ALB given a past observed vulnerability. These green areas define the spatial extent of the species scenario. Red areas contain species that have not yet been observed as vulnerable but that may be at risk due to membership in a genus which already contains other vulnerable species. These red areas plus the green areas define the spatial extent of the genus scenario.
Figure2- ALB years to maturity for viable host area defined by urban areas and genus scenario risk extent.
Figure3- The percent timber basal area at risk to ALB given a genus scenario risk extent.
Figure4- The mean basal area of vulnerable timber, given a genus scenario risk extent.
5.2 Supporting Tables
ALB Susceptible Species Layer ComponentsCommon / Scientific
1 / boxelder / Acer negundo
2 / black maple / Acer nigrum
3 / Norway maple / Acer platanoides
4 / red maple / Acer rubrum
5 / silver maple / Acer saccharinum
6 / sugar maple / Acer saccharum
7 / yellow buckeye / Aesculusflava
8 / Ohio buckeye / Aesculusglabra
9 / buckeye, horsechestnut spp. / Aesculus spp.
10 / mimosa, silktree / Albiziajulibrissin
11 / red alder / Alnusrubra
12 / river birch / Betulanigra
13 / paper birch / Betulapapyrifera
14 / gray birch / Betulapopulifolia
15 / hackberry / Celtisoccidentalis
16 / Russian-olive / Elaeagnusangustifolia
17 / white ash / Fraxinusamericana
18 / green ash / Fraxinuspennsylvanica
19 / honeylocust / Gleditsiatriacanthos
20 / sweetgum / Liquidambar styraciflua
21 / yellow-poplar / Liriodendron tulipifera
22 / white mulberry / Morus alba
23 / eastern hophornbeam / Ostryavirginiana
24 / American sycamore / Platanusoccidentalis
25 / black cottonwood / Populusbalsamifera
26 / silver poplar / Populus alba
27 / eastern cottonwood / Populusdeltoides
28 / quaking aspen / Populustremuloides
29 / Lombardy poplar / Populusnigra
30 / peach / Prunuspersica
31 / black locust / Robiniapseudoacacia
32 / white willow / Salix alba
33 / black willow / Salix nigra
34 / European mountain-ash / Sorbusaucuparia
35 / American basswood / Tiliaamericana
36 / white basswood / Tiliaamericana
37 / Carolina basswood / Tiliaamericana
38 / American elm / Ulmusamericana
39 / Siberian elm / Ulmuspumila
Table 1- List of tree species composing the species scenario risk extent. This list is made up of known susceptible species as referenced by Meng et al. (2015).
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ALB Susceptible Genus Layer ComponentsCommon / Scientific / Common / Scientific
1 / Florida maple / Acer barbatum / 51 / sweetgum / Liquidambar styraciflua
2 / Rocky Mountain maple / Acer glabrum / 52 / southern crab apple / Malus angustifolia
3 / chalk maple / Acer leucoderme / 53 / sweet crab apple / Malus coronaria
4 / bigleaf maple / Acer macrophyllum / 54 / Oregon crab apple / Malus fusca
5 / boxelder / Acer negundo / 55 / prairie crab apple / Malus ioensis
6 / black maple / Acer nigrum / 56 / apple spp. / Malus spp.
7 / striped maple / Acer pensylvanicum / 57 / chinaberry / Melia azedarach
8 / Norway maple / Acer platanoides / 58 / white mulberry / Morus alba
9 / red maple / Acer rubrum / 59 / Texas mulberry / Morusmicrophylla
10 / silver maple / Acer saccharinum / 60 / red mulberry / Morusrubra
11 / sugar maple / Acer saccharum / 61 / mulberry spp. / Morus spp.
12 / mountain maple / Acer spicatum / 62 / eastern hophornbeam / Ostryavirginiana
13 / maple spp. / Acer spp. / 63 / sycamore spp. / Platanus spp.
14 / California buckeye / Aesculuscalifornica / 64 / silver poplar / Populus alba
15 / yellow buckeye / Aesculusflava / 65 / balsam poplar / Populusbalsamifera
16 / Ohio buckeye / Aesculusglabra / 66 / black cottonwood / Populusbalsamifera
17 / Texas buckeye / Aesculusglabra / 67 / eastern cottonwood / Populusdeltoides
18 / buckeye, horsechestnut spp. / Aesculus spp. / 68 / plains cottonwood / Populusdeltoides
19 / painted buckeye / Aesculus sylvatica / 69 / bigtooth aspen / Populusgrandidentata
20 / European alder / Alnusglutinosa / 70 / swamp cottonwood / Populusheterophylla
21 / red alder / Alnusrubra / 71 / Lombardy poplar / Populusnigra
22 / alder spp. / Alnus spp. / 72 / cottonwood and poplar spp. / Populus spp.
23 / yellow birch / Betulaalleghaniensis / 73 / quaking aspen / Populustremuloides
24 / sweet birch / Betulalenta / 74 / American plum / Prunusamericana
25 / river birch / Betulanigra / 75 / sweet cherry, domesticated / Prunusavium
26 / paper birch / Betulapapyrifera / 76 / Canada plum / Prunusnigra
27 / gray birch / Betulapopulifolia / 77 / pin cherry / Prunuspensylvanica
28 / birch spp. / Betula spp. / 78 / peach / Prunuspersica
29 / American hornbeam, musclewood / Carpinuscaroliniana / 79 / black cherry / Prunusserotina
30 / sugarberry / Celtislaevigata / 80 / cherry and plum spp. / Prunus spp.
31 / netleaf hackberry / Celtislaevigata / 81 / chokecherry / Prunusvirginiana
32 / hackberry / Celtisoccidentalis / 82 / black locust / Robiniapseudoacacia
33 / hackberry spp. / Celtis spp. / 83 / white willow / Salix alba
34 / cockspur hawthorn / Crataegus crus-galli / 84 / peachleaf willow / Salix amygdaloides
35 / downy hawthorn / Crataegusmollis / 85 / Bebb willow / Salix bebbiana
36 / hawthorn spp. / Crataegus spp. / 86 / coastal plain willow / Salix caroliniana
37 / Russian-olive / Elaeagnusangustifolia / 87 / black willow / Salix nigra
38 / American beech / Fagus grandifolia / 88 / weeping willow / Salix sepulcralis
39 / white ash / Fraxinusamericana / 89 / willow spp. / Salix spp.
40 / Carolina ash / Fraxinuscaroliniana / 90 / American mountain-ash / Sorbusamericana
41 / Oregon ash / Fraxinuslatifolia / 91 / European mountain-ash / Sorbusaucuparia
42 / black ash / Fraxinusnigra / 92 / American basswood / Tiliaamericana
43 / green ash / Fraxinuspennsylvanica / 93 / white basswood / Tiliaamericana
44 / pumpkin ash / Fraxinusprofunda / 94 / Carolina basswood / Tiliaamericana
45 / blue ash / Fraxinusquadrangulata / 95 / basswood spp. / Tilia spp.
46 / ash spp. / Fraxinus spp. / 96 / winged elm / Ulmusalata
47 / Texas ash / Fraxinustexensis / 97 / American elm / Ulmusamericana
48 / waterlocust / Gleditsiaaquatica / 98 / cedar elm / Ulmuscrassifolia
49 / honeylocust spp. / Gleditsia spp. / 99 / Siberian elm / Ulmuspumila
50 / honeylocust / Gleditsiatriacanthos / 100 / slippery elm / Ulmusrubra
101 / September elm / Ulmusserotina
102 / elm spp. / Ulmus spp.
103 / rock elm / Ulmusthomasii
Table 2- List of tree species composing the genus scenario risk extent. This list is made up of species belonging to known susceptible genera as referenced by Meng et al. (2015).
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State Summary Statistics: Genus Vulnerability ScenarioName / Mean / STD / Min / Max / % Area / % Timber
1 / District of Columbia / 1.568 / 0.019 / 1.540 / 1.616 / 100.000 / 42.011
2 / West Virginia / 2.235 / 0.561 / 1.594 / 4.553 / 98.657 / 50.667
3 / Connecticut / 2.504 / 0.149 / 1.751 / 3.441 / 98.507 / 51.446
4 / New Hampshire / 3.665 / 1.212 / 2.488 / 9.630 / 97.742 / 50.164
5 / Massachusetts / 2.697 / 0.353 / 2.395 / 3.773 / 96.138 / 44.903
6 / Vermont / 3.828 / 0.828 / 2.480 / 6.595 / 95.728 / 66.754
7 / Alabama / 1.143 / 0.243 / 0.751 / 1.660 / 95.517 / 23.522
8 / Pennsylvania / 2.605 / 0.477 / 1.589 / 3.726 / 95.306 / 59.385
9 / Maine / 4.114 / 0.876 / 2.600 / 9.633 / 95.139 / 41.583
10 / New York / 3.123 / 0.757 / 1.644 / 7.606 / 94.968 / 65.703
11 / South Carolina / 1.209 / 0.209 / 0.808 / 2.416 / 94.857 / 24.356
12 / Rhode Island / 2.488 / 0.035 / 2.405 / 2.633 / 94.741 / 38.620
13 / Georgia / 1.090 / 0.289 / 0.764 / 2.468 / 93.851 / 20.614
14 / North Carolina / 1.560 / 0.383 / 1.282 / 3.778 / 93.803 / 34.490
15 / Virginia / 1.774 / 0.370 / 1.386 / 4.518 / 93.664 / 35.606
16 / Tennessee / 1.561 / 0.212 / 1.321 / 4.389 / 91.936 / 37.282
17 / New Jersey / 1.909 / 0.346 / 1.589 / 2.677 / 89.763 / 32.681
18 / Mississippi / 1.087 / 0.227 / 0.770 / 1.482 / 89.343 / 27.292
19 / Michigan / 3.215 / 0.721 / 1.770 / 7.649 / 87.334 / 55.671
20 / Kentucky / 1.613 / 0.094 / 1.389 / 2.474 / 86.994 / 44.442
21 / Delaware / 1.631 / 0.018 / 1.592 / 1.726 / 85.003 / 43.644
22 / Maryland / 1.752 / 0.360 / 1.518 / 3.488 / 84.989 / 46.562
23 / Wisconsin / 3.001 / 0.512 / 2.384 / 4.595 / 81.461 / 56.806
24 / Arkansas / 1.362 / 0.126 / 0.858 / 1.652 / 80.903 / 20.644
25 / Missouri / 1.602 / 0.055 / 1.370 / 1.797 / 73.783 / 19.040
26 / Ohio / 2.147 / 0.340 / 1.627 / 2.658 / 72.660 / 62.073
27 / Louisiana / 0.822 / 0.060 / 0.712 / 1.252 / 69.279 / 25.450
28 / Indiana / 1.852 / 0.307 / 1.512 / 2.480 / 61.043 / 56.223
29 / Oklahoma / 1.348 / 0.090 / 0.866 / 1.704 / 59.610 / 21.283
30 / Minnesota / 3.414 / 0.721 / 2.438 / 6.622 / 59.071 / 52.436
31 / Florida / 0.736 / 0.054 / 0.592 / 0.847 / 58.789 / 9.217
32 / Washington / 4.883 / 1.597 / 1.723 / 9.674 / 44.309 / 6.506
33 / Illinois / 1.769 / 0.294 / 1.471 / 2.504 / 44.110 / 46.924
34 / Texas / 0.846 / 0.149 / 0.619 / 1.693 / 39.372 / 12.463
35 / Iowa / 2.098 / 0.347 / 1.649 / 2.627 / 31.906 / 54.539
36 / Oregon / 4.329 / 1.475 / 1.778 / 9.800 / 30.774 / 4.590
37 / Kansas / 1.575 / 0.055 / 1.400 / 2.373 / 29.231 / 57.447
38 / California / 2.309 / 1.365 / 0.619 / 9.986 / 22.806 / 1.445
39 / Idaho / 5.367 / 1.769 / 1.751 / 9.677 / 21.704 / 2.295
40 / Nebraska / 2.058 / 0.369 / 1.633 / 2.773 / 17.156 / 49.372
41 / Colorado / 5.827 / 2.190 / 1.586 / 9.677 / 16.025 / 12.498
42 / Montana / 5.611 / 2.207 / 2.493 / 9.668 / 12.273 / 2.729
43 / Utah / 5.281 / 2.000 / 0.803 / 9.666 / 12.138 / 6.559
44 / North Dakota / 3.061 / 0.488 / 2.490 / 4.562 / 11.286 / 67.991
45 / Wyoming / 6.242 / 2.089 / 2.485 / 9.677 / 10.051 / 5.704
46 / South Dakota / 3.017 / 1.217 / 1.740 / 8.594 / 9.579 / 14.779
47 / New Mexico / 4.490 / 2.348 / 0.822 / 9.644 / 4.431 / 1.697
48 / Nevada / 4.651 / 2.155 / 0.627 / 9.663 / 3.626 / 1.315
49 / Arizona / 2.678 / 2.447 / 0.619 / 9.636 / 3.602 / 1.190
Table 3- Summary statistics for states and District of Columbia, sorted by percent area at risk, given the genus scenario. ‘% Area’ refers to the vulnerable grid cell percent of a state’s area and ‘% Timber’ refers to the vulnerable percent of a state’s timber basal area. Mean, standard deviation, min, and max, refer to time to maturity.
Summary Statistics for Top 100 Most Populated Metropolitan AreasName / Mean / Std. Dev. / Min / Max
1 / McAllen, TX / 0.628 / 0.002 / 0.625 / 0.633
2 / Miami, FL / 0.631 / 0.013 / 0.614 / 0.666
3 / Cape Coral, FL / 0.658 / 0.004 / 0.641 / 0.666
4 / Phoenix--Mesa, AZ / 0.670 / 0.012 / 0.649 / 0.786
5 / North Port--Port Charlotte, FL / 0.671 / 0.003 / 0.668 / 0.677
6 / Lakeland, FL / 0.680 / 0.002 / 0.677 / 0.685
7 / Tampa--St. Petersburg, FL / 0.685 / 0.010 / 0.666 / 0.712
8 / Palm Bay--Melbourne, FL / 0.689 / 0.003 / 0.682 / 0.696
9 / Orlando, FL / 0.691 / 0.006 / 0.685 / 0.712
10 / Deltona, FL / 0.713 / 0.010 / 0.699 / 0.729
11 / Houston, TX / 0.728 / 0.010 / 0.710 / 0.770
12 / New Orleans, LA / 0.732 / 0.010 / 0.712 / 0.756
13 / Tucson, AZ / 0.733 / 0.033 / 0.696 / 1.332
14 / San Antonio, TX / 0.741 / 0.019 / 0.712 / 0.822
15 / Las Vegas--Henderson, NV / 0.742 / 0.036 / 0.690 / 1.392
16 / Jacksonville, FL / 0.746 / 0.011 / 0.729 / 0.773
17 / Austin, TX / 0.762 / 0.009 / 0.748 / 0.786
18 / Baton Rouge, LA / 0.783 / 0.005 / 0.773 / 0.800
19 / Dallas--Fort Worth--Arlington, TX / 0.806 / 0.016 / 0.770 / 0.860
20 / Bakersfield, CA / 0.859 / 0.011 / 0.833 / 0.890
21 / Charleston--North Charleston, SC / 0.864 / 0.021 / 0.844 / 0.912
22 / El Paso, TX--NM / 0.866 / 0.108 / 0.789 / 1.356
23 / Jackson, MS / 0.887 / 0.015 / 0.863 / 0.923
24 / Los Angeles--Long Beach--Anaheim, CA / 1.020 / 0.126 / 0.838 / 1.740
25 / Riverside--San Bernardino, CA / 1.037 / 0.142 / 0.896 / 1.753
26 / Fresno, CA / 1.144 / 0.118 / 0.937 / 1.280
27 / San Diego, CA / 1.216 / 0.121 / 0.981 / 1.666
28 / Augusta-Richmond County, GA--SC / 1.222 / 0.055 / 0.989 / 1.310
29 / Columbia, SC / 1.265 / 0.087 / 0.921 / 1.356
30 / Birmingham, AL / 1.300 / 0.023 / 1.258 / 1.367
31 / Little Rock, AR / 1.316 / 0.011 / 1.290 / 1.345
32 / Memphis, TN--MS--AR / 1.342 / 0.013 / 1.321 / 1.370
33 / Stockton, CA / 1.354 / 0.002 / 1.351 / 1.359
34 / Oklahoma City, OK / 1.364 / 0.009 / 1.342 / 1.384
35 / Sacramento, CA / 1.372 / 0.042 / 1.348 / 1.592
36 / Atlanta, GA / 1.378 / 0.023 / 1.345 / 1.526
37 / Greenville, SC / 1.380 / 0.008 / 1.362 / 1.488
38 / Tulsa, OK / 1.381 / 0.003 / 1.373 / 1.392
39 / Virginia Beach, VA / 1.398 / 0.011 / 1.386 / 1.507
40 / Raleigh, NC / 1.400 / 0.029 / 1.375 / 1.507
41 / Charlotte, NC--SC / 1.408 / 0.054 / 1.367 / 1.573
42 / Chattanooga, TN--GA / 1.423 / 0.064 / 1.381 / 1.647
43 / Durham, NC / 1.451 / 0.042 / 1.392 / 1.523
44 / Nashville-Davidson, TN / 1.492 / 0.047 / 1.395 / 1.556
45 / Wichita, KS / 1.516 / 0.007 / 1.504 / 1.540
46 / Greensboro, NC / 1.518 / 0.009 / 1.477 / 1.537
47 / Winston-Salem, NC / 1.540 / 0.017 / 1.488 / 1.589
48 / Knoxville, TN / 1.540 / 0.021 / 1.474 / 1.600
49 / Richmond, VA / 1.545 / 0.021 / 1.490 / 1.586
50 / St. Louis, MO--IL / 1.553 / 0.019 / 1.515 / 1.597
Table 4- Summary statistics for top 100 (by population) metropolitan areas, sorted by mean time to maturity.
Summary Statistics for Top 100 Most Populated Metropolitan Areas (Continued)Name / Mean / Std. Dev. / Min / Max
51 / Louisville/Jefferson County, KY--IN / 1.562 / 0.033 / 1.512 / 1.652
52 / Kansas City, MO--KS / 1.580 / 0.016 / 1.545 / 1.638
53 / Baltimore, MD / 1.609 / 0.029 / 1.559 / 1.723
54 / Oxnard, CA / 1.610 / 0.112 / 1.422 / 1.978
55 / Washington, DC--VA--MD / 1.620 / 0.035 / 1.540 / 1.704
56 / Albuquerque, NM / 1.627 / 0.046 / 1.584 / 2.480
57 / Cincinnati, OH--KY--IN / 1.654 / 0.019 / 1.627 / 1.726
58 / San Jose, CA / 1.666 / 0.052 / 1.603 / 1.822
59 / Philadelphia, PA--NJ--DE--MD / 1.690 / 0.088 / 1.589 / 2.408
60 / Omaha, NE--IA / 1.700 / 0.008 / 1.688 / 1.732
61 / Dayton, OH / 1.705 / 0.027 / 1.641 / 1.775
62 / Indianapolis, IN / 1.713 / 0.024 / 1.666 / 1.822
63 / Columbus, OH / 1.739 / 0.087 / 1.682 / 2.436
64 / Harrisburg, PA / 1.770 / 0.134 / 1.693 / 2.414
65 / Des Moines, IA / 1.774 / 0.058 / 1.729 / 2.367
66 / Salt Lake City--West Valley City, UT / 1.881 / 0.442 / 1.707 / 5.504
67 / New York--Newark, NY--NJ--CT / 1.910 / 0.300 / 1.644 / 2.677
68 / Toledo, OH--MI / 2.108 / 0.298 / 1.759 / 2.444
69 / San Francisco--Oakland, CA / 2.139 / 0.518 / 1.630 / 4.912
70 / Chicago, IL--IN / 2.144 / 0.321 / 1.723 / 2.504
71 / Ogden--Layton, UT / 2.241 / 0.453 / 1.715 / 4.578
72 / Provo--Orem, UT / 2.273 / 0.349 / 1.775 / 5.562
73 / Bridgeport--Stamford, CT--NY / 2.279 / 0.269 / 1.751 / 2.490
74 / Pittsburgh, PA / 2.305 / 0.231 / 1.737 / 2.482
75 / Allentown, PA--NJ / 2.327 / 0.189 / 1.844 / 2.485
76 / Cleveland, OH / 2.348 / 0.219 / 1.794 / 2.490
77 / New Haven, CT / 2.439 / 0.032 / 2.364 / 2.488
78 / Detroit, MI / 2.442 / 0.055 / 1.844 / 2.490
79 / Akron, OH / 2.447 / 0.014 / 2.408 / 2.480
80 / Providence, RI--MA / 2.466 / 0.026 / 2.395 / 2.603
81 / Minneapolis--St. Paul, MN--WI / 2.469 / 0.013 / 2.444 / 2.493
82 / Hartford, CT / 2.471 / 0.055 / 2.395 / 2.671
83 / Springfield, MA--CT / 2.474 / 0.040 / 2.395 / 2.693
84 / Youngstown, OH--PA / 2.475 / 0.005 / 2.463 / 2.485
85 / Boise City, ID / 2.477 / 0.009 / 2.460 / 2.589
86 / Madison, WI / 2.485 / 0.001 / 2.482 / 2.488
87 / Boston, MA--NH--RI / 2.488 / 0.032 / 2.427 / 2.847
88 / Albany--Schenectady, NY / 2.490 / 0.040 / 2.449 / 2.775
89 / Rochester, NY / 2.491 / 0.015 / 2.482 / 2.630
90 / Denver--Aurora, CO / 2.493 / 0.062 / 2.411 / 2.797
91 / Milwaukee, WI / 2.505 / 0.041 / 2.480 / 2.682
92 / Syracuse, NY / 2.520 / 0.062 / 2.485 / 2.737
93 / Worcester, MA--CT / 2.531 / 0.059 / 2.482 / 2.737
94 / Muskegon, MI / 2.537 / 0.051 / 2.488 / 2.627
95 / Buffalo, NY / 2.541 / 0.101 / 2.485 / 3.463
96 / Scranton, PA / 2.555 / 0.175 / 2.455 / 3.532
97 / Portland, OR--WA / 2.843 / 0.278 / 2.611 / 3.551
98 / Colorado Springs, CO / 2.908 / 0.514 / 2.474 / 8.589
99 / Spokane, WA / 2.992 / 0.344 / 2.688 / 3.545
100 / Seattle, WA / 3.568 / 0.298 / 2.756 / 5.564
Table 4 (continued)- Summary statistics for top 100 (by population) metropolitan areas, sorted by mean time to maturity.
1