Modeling spatial and temporal dynamics of wind flow and potential fire behavior following a mountain pine beetle outbreak in a lodgepole pine forest

Agricultural and Forest Meteorology

Volumn 204, Issue , 2015, Pages 79-93

  Hoffman, Chad M ^a   Linn, Rodman ^b   Parsons, Russell ^c   Sieg, Carolyn ^d   Winterkamp, Judith ^b  

^a Veterinary Dentistry and Oral Surgery   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

^c ROCKY MOUNTAIN RESEARCH STATION   (United States)

^d ROCKY MOUNTAIN RESEARCH STATION   (United States)

Author keywords

Bark beetle; Fire behavior; Heterogeneous fuels; HIGRAD FIRETEC; Turbulence

Indexed keywords

BEETLE; CONIFEROUS FOREST; FIRE BEHAVIOR; MORTALITY; MOUNTAIN ENVIRONMENT; NUMERICAL MODEL; PEST SPECIES; PLANT-HERBIVORE INTERACTION; POPULATION STRUCTURE; SPATIOTEMPORAL ANALYSIS; TURBULENCE; WIND VELOCITY;

COLEOPTERA; PINUS CONTORTA; PINUS MUGO; SCOLYTINAE;

EID: 84922573907     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2015.01.018     Document Type: Article

References (49)

1. Bone C., White J.C., Wulder M.A., Robertson C., Nelson T.A. Impact of forest fragmentation on patterns of mountain pine beetle-caused tree mortality. Forests 2013, 4:279-295.
2. Brown J.K. Ratios of surface area to volume for common fine fuels. For. Sci. 1970, 16(1):101-105.
3. Brown J. Fire cycles and community dynamics in lodgepole pine forests. Management of Lodgepole Pine Ecosystems: Symposium Proceedings 1975, 429-456. Washington State Cooperative Extension Service. D. Baumgartner (Ed.).
4. Cassagne N., Pimont F., Dupuy J.L., Linn R.R., Mårell A., Oliveri C., Rigolot E. Using a fire propagation model to assess the efficiency of prescribed burning in reducing the fire hazard. Ecol. Modell. 2011, 222(8):1502-1514.
5. Cole W.E., Amman G.D. Mount Ain Pine Beetle Dynamics in Lodgepole Pine Forests. General Technical Report INT-GTR-89 1980, USDA Forest Service Intermountain Forest and Range Experiment Station, Ogden, UT.
6. DeRose R.J., Long J.N. Wildfire and spruce beetle outbreak: simulation of interacting disturbances in the central Rocky Mountains. Ecoscience 2009, 16(1):28-38.
7. Donato D.C., Harvey B.J., Romme W.H., Simard M., Turner M.G. Bark beetle effects on fuel profiles across a range of stand structures in Douglas-fir forests of Greater Yellowstone. Ecol. Appl. 2013, 23(1):3-20.
8. Dupont S., Brunet Y. Edge flow and canopy structure: a large-eddy simulation study. Boundary-Layer Meteorol. 2008, 126(1):51-71.
9. Finnigan J. Turbulence in plant canopies. Annu. Rev. Fluid Mech. 2000, 32:519-571.
10. Gardiner B.A. Wind and wind forces in a plantation spruce forest. Boundary-Layer Meteorol. 1994, 67(1-2):161-186.
11. Geiszler D.R., Gara R.I. Mountain pine beetle attack dynamics in lodgepole pine. The Ory and Practice of Mountain Pine Beetle Management in Lodgepole Pine forests 1978, 182-187. University of Idaho, Moscow, Idaho. A.A. Berryman, G.D. Amman, R.W. Stark (Eds.).
12. Geiszler D.R., Gallucci V.F., Gara R.I. Modeling the dynamics of mountain pine beetle aggregation in a lodgepole pine stand. Oecologia 1980, 46:244-253.
13. Graf M., Reid M.L., Aukema B.H., Lindgren B.S. Association of tree diameter with body size and lipid content of mountain pine beetles. Can. Entomol. 2012, 144(3):467-477.
14. Hicke J.A., Johnson M.C., Hayes J.L., Preisler H.K. Effects of bark beetle-caused tree mortality on wildfire. For. Ecol. Manage. 2012, 271:81-90.
15. Hoffman C., Morgan P., Mell W., Parsons R., Strand E.K., Cook S. Numerical simulation of crown fire hazard immediately after bark beetle-caused mortality in lodgepole pine forests. For. Sci. 2012, 58(2):178-188.
16. Hoffman C.M., Sieg C.H., McMillin J.D., Fulé P.Z. Fuel loadings 5 years after a bark beetle outbreak in south-western USA ponderosa pine forests. Int. J. Wildland Fire 2012, 21(3):306-312.
17. Hoffman C.M., Morgan P., Mell W., Parsons R., Strand E., Cook S. Surface fire intensity influences simulated crown fire behavior in lodgepole pine forests with recent mountain pine beetle-caused tree mortality. For. Sci. 2013, 59(4):390-399.
18. Jenkins M.J., Hebertson E., Page W., Jorgensen C.A. Bark beetles, fuels, fires and implications for forest management in the Intermountain West. For. Ecol. Manage. 2008, 254(1):16-34.
19. Jenkins M.J., Page W.G., Hebertson E.G., Alexander M.E. Fuels and fire behavior dynamics in bark beetle-attacked forests in Western North America and implications for fire management. For. Ecol. Manage. 2012, 275:12.
20. Johnson P.C., Coster J.E. Probability of attack by southern pine beetle in relation to distance from an attractive host tree. For. Sci. 1978, 24(4):574-580.
21. Jolly W.M., Parsons R.A., Hadlow A.M., Cohn G.M., McAllister S.S., Popp J.B., Hubbard R.M., Negron J.F. Relationships between moisture chemistry, and ignition of Pinus contorta needles during the early stages of mountain pine beetle attack. For. Ecol. Manage. 2012, 269:52-59.
22. Keane R.E., Reinhardt E.D., Scott J., Gray K., Reardon J. Estimating forest canopy bulk density using six indirect methods. Can. J. For. Res. 2005, 35(3):724-739.
23. Klutsch J.G., Battaglia M.A., West D.R., Costello S.L., Negrón J.F. Evaluating potential fire behavior in lodgepole pine-dominated forests after a mountain pine beetle epidemic in north-central Colorado. W. J. Appl. For. 2011, 26(3):101-109.
24. Linn R.R. A Transport Model for Prediction of Wildfire Behavior. LA-13334-T 1997, Los Alamos National Laboratory, Los Alamos, NM.
25. Linn R.R., Cunningham P. Numerical simulations of grass fires using a coupled atmosphere-fire model: basic fire behavior and dependence on wind speed. J. Geophys. Res. D: Atmos. (1984-2012) 2005, D13:110.
26. Linn R.R., Winterkamp J., Colman J., Edminster C. Modeling interactions between fire and atmosphere in discrete element fuel beds. Int. J. Wildland Fire 2005, 14(1):37-48.
27. Linn R.R., Sieg C.H., Hoffman C.M., Winterkamp J.L., McMillin J.D. Modeling wind fields and fire propagation following bark beetle outbreaks in spatially-heterogeneous pinyon-juniper woodland fuel complexes. Agric. For. Meteorol. 2013, 173:139-153.
28. Logan J.A., Bentz B.J., Powell J.A. Model analysis of spatial patterns in mountain pine beetle outbreaks. Theor. Pop. Bio. 1998, 53:236-255.
29. Mell W., Jenkins M.A., Gould J., Cheney P. A physics-based approach to modelling grassland fires. Int. J. Wildland Fire 2007, 16(1):1-22.
30. Mell W., Maranghides A., McDermott R., Manzello S.L. Numerical simulation and experiments of burning Douglas fir trees. Combust. Flame 2009, 156(10):2023-2041.
31. Mitchell R.G., Preisler H.K. Analysis of spatial patterns of lodgepole pine attacked by outbreak populations of the mountain pine beetle. For. Sci. 1991, 37(5):1390-1408.
32. Negrón J.F., Popp J.B. Probability of ponderosa pine infestation by mountain pine beetle in the Colorado Front Range. For. Ecol. Manage. 2004, 191(1):17-27.
33. Page W., Jenkins M.J. Predicted fire behavior in selected mountain pine beetle-infested lodgepole pine. For. Sci. 2007, 53(6):662-674.
34. Page W.G., Jenkins M.J., Alexander M.E. Crown fire potential in lodgepole pine forests during the red stage of mountain pine beetle attack. Forestry 2014, 87(3):347-361.
35. Perrakis D.D.B., Lanoville R.A., Taylor S.W., Hicks D. Modeling wildfire spread in mountain pine beetle-affected forest stands, British Columbia, Canada. Fire Ecol. 2014, 10(2):1-26.
36. Pimont F., Dupuy J.L., Linn R.R., Dupont S. Validation of FIRETEC wind-flows over a canopy and a fuel-break. Int. J. Wildland Fire 2009, 18(7):775-790.
37. Pimont F., Dupuy J.L., Linn R.R. Impacts of fuel-break structure on wind-flows and fire propagation simulated with FIRETEC. Ann. For. Sci. 2011, 68(3):523-530.
38. Raffa K.F., Aukema B.H., Bentz B.J., Carroll A.L., Hicke J.A., Turner M.G., Romme W.H. Cross-scale drivers of natural disturbances prone to anthropogenic amplification: the dynamics of bark beetle eruptions. Bioscience 2008, 58(6):501-517.
39. Raupach M.R., Coppin P.A., Legg B.J. Experiments on scalar dispersion within a model-plant canopy. 1. The turbulence structure. Boundary-Layer Meteorol. 1986, 35(1-2):21-52.
40. Reinhardt E., Scott J., Gray K., Keane R. Estimating canopy fuel characteristics in five conifer stands in the western United States using tree and stand measurements. Can. J. For. Res. 2006, 36(11):2803-2814.
41. Rothermel R.C. A Mathematical Model for Predicting Fire Spread in Wildland Fuels., Research Paper INT-115 1972, USDA, Forest Service Intermountain Forest and Range Experiment Station, Ogden, UT.
42. Rothermel R.C. How to Predict the Spread and Intensity of Forest and Range Fires, GTR-INT-143 1983, USDA, Forest Service Intermountain Forest and Range Experiment Station, Ogden, UT.
43. Rothermel R.C. Predicting behavior and size of crown fires in the Northern Rocky Mountains, Research Paper INT-438 1991, USDA, Forest Service Intermountain Forest and Range Experiment Station, Ogden, UT.
44. Safranyik L., Silversides R., McMullen L.H., Linton D.A. An empirical approach to modeling the local dispersal of the mountain pine beetle (Dendroctonus ponderosae Hopk.) (Col. Scolytidae) in relation to sources of attraction, wind direction and speed. J. Appl. Entomol. 1989, 108(1-5):498-511.
45. Schoennagel T., Veblen T.T., Negron J.F., Smith J.M. Effects of mountain pine beetle on fuels and expected fire behavior in lodgepole pine forests, Colorado, USA. PLoS One 2012, 7(1):e30002.
46. Scott J.H., Reinhardt E.D. Assessing Crown Fire Potential by Linking Models of Surface and Crown Fire Behavior, Research Paper RMRS-RP-29 2001, USDA Forest Service Rocky Mountain Research Station, Fort Collins, CO.
47. Simard M., Romme W.H., Griffin J.M., Turner M.G. Do mountain pine beetle outbreaks change the probability of active crown fire in lodgepole pine forests?. Ecol. Monogr. 2011, 81(1):3-24.
48. Van Wagner C.E. Conditions for the start and spread of crown fire. Can. J. For. Res. 1977, 7(1):23-34.
49. Wulder M.A., White J.C., Grills D., Nelson T., Coops N.C., Ebata T. Aerial overview survey of the mountain pine beetle epidemic in British Columbia: communication of impacts. BC J. Ecosyst. Manage. 2009, 10(1):45-58.