Modeling red oak borer, Enaphalodes rufulus (Haldeman), damage using in situ and ancillary landscape data

Forest Ecology and Management

Volumn 255, Issue 3-4, 2008, Pages 931-939

  Aquino, Leah D ^a   Tullis, Jason A ^a   Stephen, Fred M ^a  

^a UNIVERSITY OF ARKANSAS   (United States)

Author keywords

Cerambycidae; Native insect pest; Quercus; Red oak borer; Tree damage modeling

Indexed keywords

BIODIVERSITY; DECISION TREES; LANDFORMS; LEARNING SYSTEMS; VEGETATION;

CERAMBYCIDAE; NATIVE INSECT PESTS; RED OAK BORER; TREE DAMAGE MODELING;

FORESTRY;

BEETLE; DECIDUOUS FOREST; ECOLOGICAL MODELING; HAZARD ASSESSMENT; IN SITU MEASUREMENT; MORTALITY; PEST DAMAGE; POPULATION DECLINE;

BIODIVERSITY; FORESTRY; PLANTS; QUERCUS;

ARKANSAS; MISSOURI; NORTH AMERICA; OKLAHOMA [UNITED STATES]; OZARK NATIONAL FOREST; UNITED STATES;

CERAMBYCIDAE; COLEOPTERA; ENAPHALODES RUFULUS; HEXAPODA; QUERCUS; QUERCUS RUBRA;

EID: 39049156891     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2007.10.011     Document Type: Article

References (38)

1. Adamski, J.C., Petersen, J.C., Freiwald, D.A., Davis, J.V., 1995. Environmental and Hydrologic Setting of the Ozark Plateaus Study Unit, Arkansas, Kansas, Missouri, and Oklahoma. USGS Water Res. Investig. Rep. 94-4022. Little Rock, AR, 69 p.
2. Bates C.G. Transect of a mountain valley. Ecology 4 (1923) 54-62
3. Bauer E., and Kohavi R. An empirical comparison of voting classification algorithms: bagging, boosting, and variants. Machine Learn. 36 (1999) 105-139
4. Carreiras J.M.B., Pereira J.M.C., and Shimabukuro Y.E. Land-cover mapping in the Brazilian Amazon using SPOT-4 vegetation data and machine learning classification methods. Photogramm. Eng. Remote Sensing 72 (2006) 897-910
5. Collin H., Huang C., Yang L., and Wylie B. Development of a Circa 2000 Landcover database for the United States. ASPRS 2002 Annual Convention (2002), American Society for Photogrammetry and Remote Sensing, Washington, DC 13
6. Continuous Inventory of Stand Conditions USDA Forest Service (CISC), 1993. The database component of the silvicultural examination and prescription process as documented in the Silvicultural Examination and Prescription Handbook, FSH 2409.26d, R8 Amendment 2409.26d-93-1.
7. Donley D.E. Wood borer losses in Appalachian oak. Southern Lumberman 8 (1974) 115-118
8. Donley D.E. Oviposition by the red oak borer. Enaphalodes rufulus Coleoptera: Cerambycidae. Entomol. Soc. Am. 71 (1978) 496-498
9. Donley D.E., and Acciavatti R.E. Forest Insect and Disease Leaflet 163 (1980), USDA Forest Service p. 6
10. Fierke M.K., Kinney D.L., Salisbury V.B., Crook D.J., and Stephen F.M. Development and comparison of intensive and extensive sampling methods and preliminary within tree population estimates of red oak borer (Coleoptera: Cerambycidae) in the Ozark Mountains of Arkansas. Environ. Entomol. 34 (2005) 184-192
11. Fierke M.K., Kinney D.L.., Salisbury V.B., Crook D.J., and Stephen F.M. A rapid estimation procedure for within-tree populations of red oak borer (Coleoptera: Cerambycidae). Forest Ecol. Manage. 215 (2005) 163-168
12. Fierke M.K., Kelley M.B., and Stephen F.M. Site and stand variables influencing red oak borer, Enaphalodes rufulus (Coleoptera: Cerambycidae), population densities and tree mortality. Forest Ecol. Manage. 247 (2007) 227-236
13. Franklin J. Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients. Prog. Phys. Geogr. 19 (1995) 474-499
14. Gahegan M. Is inductive machine learning just another wild goose (or might it lay the golden egg)?. Int. J. Geogr. Inform. Sci. 17 (2003) 69-92
15. Graney, D.L., 1977. Site index predictions for red oaks and white oak in the Boston Mountains of Arkansas. U.S. Department of Agriculture Forest Service Research Paper SO-139.
16. Guisan A., and Zimmermann N.E. Predictive habitat distribution models in ecology. Ecol. Modelling 135 (2000) 147-186
17. Hanks L.M. Influence of the larval host plant on reproductive strategies of cerambycid beetles. Ann. Rev. Entomol. 44 (1999) 483-505
18. Hay C.J. The life history of a red oak borer and its behavior in red, black and scarlet oak. Proceedings of the North-Central Branch, vol. 24 (1969), Entomological Society of America 125-128
19. Hay C.J. Survival and mortality of red oak borer larvae on black, scarlet, and northern red oak in eastern Kentucky. Ann. Entomol. Soc. Am. 67 (1974) 981-986
20. Huang C., Yang L., Homer C., Coan M., Rykus R., Zhang Z., Wylie B., Hegge K., Zhu Z., Lister A., Hoppus M., Rymcio R., DeBlander L., Cooke W., McRoberts R., Wendt D., and Weyerman D. Synergistic use of FIA plot data and Landsat 7 ETM+ images for large area forest mapping. Thirty-Fifth Annual Midwest Forest Mensurationists Meeting and Third Annual Forest Inventory and Analysis Symposium. Traverse City, MI (2001)
21. Huang X., and Jensen J.R. A machine-learning approach to automated knowledge-base building for remote sensing image analysis with GIS data. Photogramm. Eng. Remote Sensing 63 (1997) 1185-1194
22. Husch B., Beers T.W., and Kershaw Jr. J.A. Forest Mensuration. fourth ed. (2003), John Wiley & Sons, Inc., Hoboken, NJ p. 443
23. Jensen J.R. Introductory Digital Image Processing: A Remote Sensing Perspecitve. third ed. (2005), Prentice Hall, Upper Saddle River, New Jersey p. 526
24. Levin S.A. The problem of pattern and scale in ecology. Ecology 73 (1992) 1943-1967
25. McIver D.K., and Friedl M.A. Using prior probabilities in decision-tree classification of remotely sensed data. Remote Sensing Environ. 81 (2002) 253-261
26. Nelson T., Boots B., and Wulder M.A. Spatial-temporal analysis of mountain pine beetle infestations to characterize pattern, risk, and spread at the landscape level. Mountain Pine Beetle Symposium: Challenges and Solutions (2004), Kelowna, British Columbia
27. Oak S.W., Tainter F., Williams J., and Starkey D. Oak decline risk rating for the southeastern United States. Ann. Sci. For. 53 (1996) 721-730
28. Pell, W.F., Bukenhofer, G.A., 1999. Ozark-Ouachita highlands assessment. Terrestrial Vegetation and Wildlife. United States Department of Agriculture Forest Service. Southern Research Station General Technical Report SRS-35.
29. Potzger J.E. Microclimate and a notable case of its influence on a ridge in Central Indiana. Ecology 20 (1939) 29-37
30. Quinlan R. See5: An Informal Tutorial (2006), RuleQuest Research, St. Ives, New South Wales, Australia
31. Solomon J.D. Guide to Insect Borers in North American Broadleaf Trees and Shrubs (1995), USDA Forest Service Agriculture Handbook, AH-706 pp. 422-426
32. Starkey, D., Mangini, S., Oliveria, F., Clarke, S., Bruce, B., Kertz, R., Menard, R., 2000. Forest health evaluation of oak mortality and decline on the Ozark National Forest, 1999. USDA Forest Health Protection Rep. 2000-02-02. Alexandria, LA, 31 pp.
33. Stephen F.M., Salisbury V.B., and Oliveria F.L. Red oak borer, Enaphalodes rufulus (Coleoptera: Cerambycidae), in the Ozark Mountains of Arkansas, U.S.A.: an unexpected and remarkable forest disturbance. Integr. Pest Manage. Rev. 6 (2001) 247-252
34. Stoeckler J.H., and Curtis W.R. Soil moisture regime in Southwestern Wisconsin as affected by aspect and forest type. J. Forestry 58 (1960) 892-896
35. Stringer J.W., Kimmerer T.W., Overstreet J.C., and Dunn J.P. Oak mortality in eastern Kentucky. S. J. Appl. For. 13 (1989) 86-91
36. USDA Natural Resource Conservation Survey (NRCS), 1995. Soil Survey Geographic (SSURGO) Database Data User Information. United States Natural Resources and Conservation Service. Ft. Worth, TX. National Cartography and GIS Center. Miscellaneous Publication Number 1527.
37. USDA Forest Service. Forest Inventory and Analysis. Southern Research Station Field Guide (2001), Southern Research Station, Asheville, NC
38. Xian G., Zhu Z., Hoppus M., and Fleming M. Application of decision tree-techniques to forest group and basal area mapping using satellite imagery and forest inventory data. ISPRS Commission I Symposium 2002 (2002), International Society for Photogrammetry and Remote Sensing, Denver, Colorado 8