International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Travis Woolley A B , David C. Shaw A , Lisa M. Ganio A and Stephen Fitzgerald A
+ Author Affiliations
- Author Affiliations

A Oregon State University, 204 Peavy Hall, Corvallis, OR 97331, USA. Email: dave.shaw@oregonstate.edu; lisa.ganio@oregonstate.edu; stephen.fitzgerald@oregonstate.edu

B Corresponding author. Email: travis.woolley@oregonstate.edu

International Journal of Wildland Fire 21(1) 1-35 https://doi.org/10.1071/WF09039
Submitted: 23 April 2009  Accepted: 8 February 2011   Published: 18 November 2011

Abstract

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed burns and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate and interpret logistic regression models; explanatory variables in logistic regression models; factors influencing scope of inference and model limitations; model validation; and management applications. Logistic regression is currently the most widely used and available technique for predicting post-fire tree mortality. Over 100 logistic regression models have been developed to predict post-fire tree mortality for 19 coniferous species following wild and prescribed fires. The most widely used explanatory variables in post-fire tree mortality logistic regression models have been measurements of crown (e.g. crown scorch) and stem (e.g. bole char) injury. Prediction of post-fire tree mortality improves when crown and stem variables are used collectively. Logistic regression models that predict post-fire tree mortality are the basis of simple field tools and contribute to larger fire-effects models. Future post-fire tree mortality prediction models should include consistent definition of model variables, model validation and direct incorporation of physiological responses that link to process modelling efforts.

Additional keywords: fire behaviour, fire injury, modelling, prescribed fire, wildland fire.


References

Adams DC, Jackson JF (1995) Estimating the allometry of tree bark. American Midland Naturalist 134, 99–106.
Estimating the allometry of tree bark.CrossRef |

Agee JK (1993) ‘Fire Ecology of Pacific Northwest Forests.’ (Island Press: Washington, DC)

Andrews PL, Bevins CD, Seli RC (2008) BehavePlus fire modeling system, version 4.0: user’s guide. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-106WWW. (Ogden, UT)

Bevins CD (1980) Estimating survival and salvage potential of fire-scarred Douglas-fir. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Note INT-RN-287. (Ogden, UT)

Borchert M, Schreiner D, Knowd T, Plumb T (2002) Predicting post-fire survival in Coulter pine (Pinus coulteri) and gray pine (Pinus sabiniana) after wildfire in central California. Western Journal of Applied Forestry 17, 134–138.

Breece CR, Kolb TE, Dickson BG, McMillin JD, Clancy KM (2008) Prescribed fire effects of bark beetle activity and tree mortality in south-western ponderosa pine forests. Forest Ecology and Management 255, 119–128.
Prescribed fire effects of bark beetle activity and tree mortality in south-western ponderosa pine forests.CrossRef |

Brown JK, DeByle NV (1987) Fire damage, mortality, and suckering aspen. Canadian Journal of Forest Research 17, 1100–1109.
Fire damage, mortality, and suckering aspen.CrossRef |

Burnham KP, Anderson DR (2002) ‘Model Selection and Inference. A Practical Information-theoretic Approach.’ 2nd edn (Springer-Verlag: New York)

Butler BW, Dickinson MB (2010) Tree injury and mortality in fires: developing process-based models. Fire Ecology 6, 55–79.
Tree injury and mortality in fires: developing process-based models.CrossRef |

Christensen G, Fight R, Barbour JR (2002) A method to simulate fire hazard reduction treatments using readily available tools. In ‘Second Forest Vegetation Simulator (FVS) Conference’,12–14 February 2002, Fort Collins, CO. (Eds NL Crookston, RN Havis) USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-25, pp. 91–96. (Ogden, UT)

Conklin DA, Geils BW (2008) Survival and sanitation of dwarf mistletoe-infected ponderosa pine following prescribed underburning. Western Journal of Applied Forestry 23, 216–222.

Connaughton CA (1936) Fire damage in the ponderosa pine type in Idaho. Journal of Forestry 34, 46–51.

Dickinson MB, Johnson EA (2001) Fire effects on trees. In ‘Forest Fires: Behavior and Ecological Effects’. (Eds EA Johnson, K Miyanishi) pp. 477–525. (Academic Press: New York)

Dickinson MB, Johnson EA (2004) Temperature-dependent rate models of vascular cambium cell mortality. Canadian Journal of Forest Research 34, 546–559.
Temperature-dependent rate models of vascular cambium cell mortality.CrossRef |

Dietrich JH (1979) Recovery potential of fire-damaged south-western ponderosa pine. USDA Forest Service Rocky Mountain Forest and Range Experiment Station, Research Note RM-379. (Fort Collins, CO)

Fahnestock GR, Hare RC (1964) Heating of tree trunks in surface fires. Journal of Forestry 62, 799–809.

Fernandes PM, Vega JA, Jimenez E, Rigolot E (2008) Fire resistance of European pines. Forest Ecology and Management 256, 246–255.
Fire resistance of European pines.CrossRef |

Filip GM, Schmitt CL, Scott DW, Fitzgerald SA (2007) Understanding and defining mortality in western conifer forests. Western Journal of Applied Forestry 22, 105–115.

Finney MA (1999) Fire-related tree mortality in ponderosa pine in eastern Montana. USDA Forest Service, Intermountain Fire Sciences Laboratory, Final Report INT-93800-RJVA. (Missoula, MT)

Finney MA, Martin RE (1993) Modeling effects of prescribed fire on young-growth coast redwood trees. Canadian Journal of Forest Research 23, 1125–1135.
Modeling effects of prescribed fire on young-growth coast redwood trees.CrossRef |

Flack V, Chang P (1987) Frequency of selecting noise variables in subset regression analysis: a simulation study. The American Statistician 41, 84–86.
Frequency of selecting noise variables in subset regression analysis: a simulation study.CrossRef |

Fowler JF, Sieg CH (2004) Post-fire mortality of ponderosa pine and Douglas-fir. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-132. (Fort Collins, CO)

Geiszler DR, Gara RI, Driver CH, Gallucci VF, Martin RE (1980) Fire, fungi, and beetle influences on a lodgepole pine ecosystem of south-central Oregon. Oecologia 46, 239–243.
Fire, fungi, and beetle influences on a lodgepole pine ecosystem of south-central Oregon.CrossRef |

Hanson CT, North MP (2009) Post-fire survival and flushing in three Sierra Nevada conifers with high initial crown scorch. International Journal of Wildland Fire 18, 857–864.
Post-fire survival and flushing in three Sierra Nevada conifers with high initial crown scorch.CrossRef |

Hare RC (1965) Contribution of bark to fire resistance of southern trees. Journal of Forestry 63, 248–251.

Harmon ME (1984) Survival of trees after low-intensity surface fires in Great Smoky Mountains National Park. Ecology 65, 796–802.
Survival of trees after low-intensity surface fires in Great Smoky Mountains National Park.CrossRef |

Harrington MG (1987) Ponderosa pine mortality from spring, summer, and fall crown scorching. Western Journal of Applied Forestry 2, 14–16.

Harrington MG (1993) Predicting Pinus ponderosa mortality from dormant season and growing-season fire injury. International Journal of Wildland Fire 3, 65–72.
Predicting Pinus ponderosa mortality from dormant season and growing-season fire injury.CrossRef |

Harrington MG, Hawksworth FG (1990) Interactions of fire and dwarf mistletoe on mortality of south-western ponderosa pine. In ‘Effects of Fire Management of South-western Natural Resources’. pp. 234–240. (Fort Collins, CO)

Hawksworth FG (1977) The 6-class dwarf mistletoe rating system. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, General Technical Report RM-48. (Fort Collins, CO)

Herman FR (1950) Survival of fire-damaged ponderosa pine. USDA Forest Service, Southwestern Forest and Range Experiment Station, Research Note SWFRES-RN-119. (Tucson, AR)

Herman FR (1954) A guide for marking fire-damaged ponderosa pine in the southwest. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Research Note RM-13. (Fort Collins, CO)

Hood SM (2008) Delayed tree mortality following fire in western conifers. USDA Forest Service, Rocky Mountain Research Station, JFSP Final Report 05-2-1-105. (Missoula, MT)

Hood SM, Bentz B (2007) Predicting post-fire Douglas-fir beetle attacks and tree mortality in the northern Rocky Mountains. Canadian Journal of Forest Research 37, 1058–1069.
Predicting post-fire Douglas-fir beetle attacks and tree mortality in the northern Rocky Mountains.CrossRef |

Hood SM, McHugh CW, Ryan KC, Reinhardt ED, Smith SL (2007) Evaluation of a post-fire tree mortality model for western USA conifers. International Journal of Wildland Fire 16, 679–689.
Evaluation of a post-fire tree mortality model for western USA conifers.CrossRef |

Hood SM, Bentz B, Gibson KE, Ryan KC, DeNitto G (2007b) Assessing post-fire Douglas-fir mortality and Douglas-fir beetle attacks in the northern Rocky Mountains. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-199. (Fort Collins, CO)

Hood SM, Bentz B, Gibson KE, Ryan KC, DeNitto G (2007c) Assessing post-fire Douglas-fir mortality and Douglas-fir beetle attacks in the northern Rocky Mountains. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-199 Supplement. (Fort Collins, CO)

Hood SM, Smith SL, Cluck D (2007d) Delayed tree mortality following fire on northern California. USDA Forest Service, Pacific Southwest Research Station, General Technical Report PSW-GTR-203. (Albany, CA)

Hood SM, Cluck DR, Smith SL, Ryan KC (2008) Using bark char codes to predict post-fire cambium mortality. Fire Ecology 4, 57–73.
Using bark char codes to predict post-fire cambium mortality.CrossRef |

Hood SM, Smith SL, Cluck DR (2010) Predicting mortality for five California conifers following wildfire. Forest Ecology and Management 260, 750–762.
Predicting mortality for five California conifers following wildfire.CrossRef |

Hosmer DW, Lemeshow S (2000) ‘Applied Logistic Regression.’ (Wiley: New York)

Jones JL, Webb BW, Jimenez DM, Reardon J, Butler BW (2004) Development of an advanced one-dimensional stem heating model for application in surface fires. Canadian Journal of Forest Research 34, 20–30.
Development of an advanced one-dimensional stem heating model for application in surface fires.CrossRef |

Kavanagh KL, Dickinson MB, Bova AS (2010) A way forward for fire-caused tree mortality prediction: modeling a physiological consequence of fire. Fire Ecology 6, 80–94.
A way forward for fire-caused tree mortality prediction: modeling a physiological consequence of fire.CrossRef |

Keen FP (1943) Ponderosa pine tree classes redefined. Journal of Forestry 41, 249–253.

Keyser TL, Smith FW, Lentile LB, Shepperd WD (2006) Modeling post-fire mortality of ponderosa pine following a mixed-severity wildfire in the Black Hills: the role of tree morphology and direct fire effects. Forest Science 52, 530–539.

Kobziar L, Moghaddas JJ, Stephens SL (2006) Tree mortality patterns following prescribed fires in a mixed conifer forest. Canadian Journal of Forest Research 36, 3222–3238.
Tree mortality patterns following prescribed fires in a mixed conifer forest.CrossRef |

Kolb TE, Agee JK, Fule PZ, McDowell NG, Pearson K, Sala A, Waring RH (2007) Perpetuating old ponderosa pine. Forest Ecology and Management 249, 141–157.
Perpetuating old ponderosa pine.CrossRef |

Linn RR, Cunningham P (2005) Numerical simulations of grass fires using a coupled atmosphere–fire model: basic fire behaviour and dependence on wind speed. Journal of Geophysical Research 110, D13107
Numerical simulations of grass fires using a coupled atmosphere–fire model: basic fire behaviour and dependence on wind speed.CrossRef |

Littke WR, Gara RI (1986) Decay in fire-damaged lodgepole pine in south-central Oregon. Forest Ecology and Management 17, 279–287.
Decay in fire-damaged lodgepole pine in south-central Oregon.CrossRef |

Lynch DW (1959) Effects of a wildfire on mortality and growth of young ponderosa pine trees. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Note 66. (Ogden, UT)

Maloney PE, Smith TF, Jensen CE, Innes J, Rizzo DM, North MP (2008) Initial tree mortality and insect and pathogen response to fire and thinning restoration treatments in an old-growth mixed conifer forest of the Sierra Nevada, California. Canadian Journal of Forest Research 38, 3011–3020.
Initial tree mortality and insect and pathogen response to fire and thinning restoration treatments in an old-growth mixed conifer forest of the Sierra Nevada, California.CrossRef |

McCullough DG, Werner RA, Neumann D (1998) Fire and insects in northern and boreal forest ecosystems of North America. Annual Review of Entomology 43, 107–127.
Fire and insects in northern and boreal forest ecosystems of North America.CrossRef | 1:CAS:528:DyaK1cXktlWlsg%3D%3D&md5=6947c319318d1fb9f0c2ff37b5979433CAS |

McHugh CW, Kolb TE (2003) Ponderosa pine mortality following fire in northern Arizona. International Journal of Wildland Fire 12, 7–22.
Ponderosa pine mortality following fire in northern Arizona.CrossRef |

McHugh CW, Kolb TE, Wilson JL (2003) Bark beetle attacks on ponderosa pine following fire in Northern Arizona. Environmental Entomology 32, 510–522.
Bark beetle attacks on ponderosa pine following fire in Northern Arizona.CrossRef |

Mell W, Jenkins MA, Gould J, Cheney P (2007) A physics-based approach to modelling grassland fires. International Journal of Wildland Fire 16, 1–22.
A physics-based approach to modelling grassland fires.CrossRef |

Mellen K, Marcot BG, Ohmann JL, Waddell KL, Willhite EA, Hostetler BB, Livingston SA, Ogden C (2002) DecAID: a decaying wood advisory model for Oregon and Washington. USDA Forest Service, Pacific Southwest Research Station, General Technical Report PSW-GTR-181. (Albany, CA)

Michaletz ST, Johnson EA (2006) A heat transfer model of crown scorch in forest fires. Canadian Journal of Forest Research 36, 2839–2851.
A heat transfer model of crown scorch in forest fires.CrossRef |

Michaletz ST, Johnson EA (2007) How forest fires kill trees: a review of the fundamental biophysical processes. Scandinavian Journal of Forest Research 22, 500–515.
How forest fires kill trees: a review of the fundamental biophysical processes.CrossRef |

Michaletz ST, Johnson EA (2008) A biophysical process model of tree mortality in surface fires. Canadian Journal of Forest Research 38, 2013–2029.
A biophysical process model of tree mortality in surface fires.CrossRef |

Miller JM, Patterson JE (1927) Preliminary studies on the relation of fire injury to bark beetle attack in western yellow pine. Journal of Agricultural Research 34, 597–613.

Moghaddas JJ, Craggs L (2007) A fuel treatment reduces fire severity and increases suppression efficiency in a mixed conifer forest. International Journal of Wildland Fire 16, 673–678.
A fuel treatment reduces fire severity and increases suppression efficiency in a mixed conifer forest.CrossRef |

Mutch LS, Parsons DJ (1998) Mixed-conifer forest mortality and establishment before and after fire in Sequoia National Park, California. Forest Science 44, 341–355.

Perrakis DB, Agee JK (2006) Seasonal fire effects on mixed-conifer forest structure and ponderosa pine resin properties. Canadian Journal of Forest Research 36, 238–254.
Seasonal fire effects on mixed-conifer forest structure and ponderosa pine resin properties.CrossRef |

Peterson DL (1985) Crown scorch volume and scorch height: estimates of post-fire tree condition. Canadian Journal of Forest Research 15, 596–598.
Crown scorch volume and scorch height: estimates of post-fire tree condition.CrossRef |

Peterson DL, Arbaugh MJ (1986) Post-fire survival in Douglas-fir and lodgepole pine: comparing the effects of crown and bole damage. Canadian Journal of Forest Research 16, 1175–1179.
Post-fire survival in Douglas-fir and lodgepole pine: comparing the effects of crown and bole damage.CrossRef |

Peterson DL, Arbaugh MJ (1989) Estimating post-fire survival of Douglas-fir in the Cascade Range. Canadian Journal of Forest Research 19, 530–533.
Estimating post-fire survival of Douglas-fir in the Cascade Range.CrossRef |

Peterson DL, Ryan KC (1986) Modeling post-fire conifer mortality for long-range planning. Environmental Management 10, 797–808.
Modeling post-fire conifer mortality for long-range planning.CrossRef |

Raffa KF, Aukema BH, Bentz BJ, Carroll AL, Hicke JA, Turner MG, Romme WH (2008) Cross-scale drivers of natural disturbances prone to anthropogenic amplification: dynamics of biome-wide bark beetle eruptions BioScience 58, 501–518.

Raymond CL, Peterson DL (2005) Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA. Canadian Journal of Forest Research 35, 2981–2995.
Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA.CrossRef |

Regelbrugge JC, Conard SG (1993) Modeling tree mortality following wildfire in Pinus ponderosa forests in the central Sierra Nevada of California. International Journal of Wildland Fire 3, 139–148.
Modeling tree mortality following wildfire in Pinus ponderosa forests in the central Sierra Nevada of California.CrossRef |

Rego FC, Rigolot E (1990) Heat transfer through bark – a simple predictive model. In ‘Fire in Ecosystem Dynamics’. (Eds JG Goldammer, MJ Jenkins) pp. 157–161. (SPB Academic Publishing: The Hague)

Reinhardt ED, Crookston NL (2003) The fire and fuels extension to the Forest Vegetation Simulator. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-116. (Ogden, UT)

Reinhardt ED, Ryan KC (1988) How to estimate tree mortality resulting from underburning. Fire Management Notes 49, 30–36.

Reinhardt ED, Keane RE, Brown JK (1997) First-Order Fire Effects Model: FOFEM 4.0, user’s guide. USDA Forest Service, Intermountain Research Station, General Technical Report INT-GTR-344. (Ogden UT)

Ritchie MW, Skinner CN, Hamilton TA (2007) Probability of tree survival after wildfire in an interior pine forest of northern California: effects of thinning and prescribed fire. Forest Ecology and Management 247, 200–208.
Probability of tree survival after wildfire in an interior pine forest of northern California: effects of thinning and prescribed fire.CrossRef |

Ryan KC (1982a) Evaluating potential tree mortality from prescribed burning. In ‘Site Preparation and Fuels Management on Steep Terrain’. (Ed. DM Baumgartner) pp. 167–179. (Washington State University: Spokane, WA)

Ryan KC (1982b) Techniques for assessing fire damage to trees. In ‘Proceedings of the Symposium: Fire, its Field Effects’, 19–21 October 1982, Jackson, WY. (Ed. JE Lotan) pp. 1–11. (Intermountain Fire Council: Missoula, MT

Ryan KC (1990) Predicting prescribed fire effects on trees in the interior west. Forestry Canada, Northwest Region Information Report NOR-X-309.

Ryan KC, Amman GD (1994) Interactions between fire-injured trees and insects in the Greater Yellowstone area. In ‘Plants and their environments: Proceedings of the first Biennial Scientific Conference on the Greater Yellowstone Ecosystem’, 16–17 September 1991, Yellowstone National Park, WY. (Ed. DG Despain) USDI, National Park Service, Natural Resource Publication Office, Technical Report NPS/NRYELL/NRTR-93/XX, pp. 259–271. (Denver, CO)

Ryan KC, Frandsen WH (1991) Basal injury from smoldering fires in mature Pinus ponderosa Laws. International Journal of Wildland Fire 1, 107–118.
Basal injury from smoldering fires in mature Pinus ponderosa Laws.CrossRef |

Ryan KC, Reinhardt ED (1988) Predicting post-fire mortality of seven western conifers. Canadian Journal of Forest Research 18, 1291–1297.
Predicting post-fire mortality of seven western conifers.CrossRef |

Ryan KC, Peterson DL, Reinhardt ED (1988) Modeling long-term fire-caused mortality of Douglas-fir. Forest Science 34, 190–199.

Safford HD, Schmidt DA, Carlson CH (2009) Effects of fuel treatments on fire severity in an area of wildland–urban interface, Angora Fire, Lake Tahoe Basin, California. Forest Ecology and Management 258, 773–787.
Effects of fuel treatments on fire severity in an area of wildland–urban interface, Angora Fire, Lake Tahoe Basin, California.CrossRef |

Salman KA (1934) Entomological factors affecting salvaging of fire-injured trees. Journal of Forestry 32, 1016–1017.

Saveland JM, Neuenschwander LF (1990) A signal detection framework to evaluate models of tree mortality following fire damage. Forest Science 36, 66–76.

Schwilk DW, Knapp EE, Ferrenberg SM, Keeley JE, Caprio AC (2006) Tree mortality from fire and bark beetles following early- and late-season prescribed fires in a Sierra Nevada mixed-conifer forest. Forest Ecology and Management 232, 36–45.
Tree mortality from fire and bark beetles following early- and late-season prescribed fires in a Sierra Nevada mixed-conifer forest.CrossRef |

Scott DW, Schmitt CL, Spiegel LH (2002) Factors affecting survival of fire-injured trees: a rating system for determining relative probability of survival of conifers in the Blue and Wallowa Mountains. USDA Forest Service, Blue Mountains Pest Management Service Center, BMPMSC-03-01. (La Grande, OR)

Sieg CH, McMillin JD, Fowler JF, Allen KK, Negron JF, Wadleigh LL, Anhold JA, Gibson KE (2006) Best predictors for post-fire mortality of ponderosa pine trees in the Intermountain West. Forest Science 52, 718–728.

Stephens SL, Finney MA (2002) Prescribed fire mortality of Sierra Nevada mixed conifer tree species: effects of crown damage and forest floor combustion. Forest Ecology and Management 162, 261–271.
Prescribed fire mortality of Sierra Nevada mixed conifer tree species: effects of crown damage and forest floor combustion.CrossRef |

Stephens SL, Moghaddas JJ (2005) Experimental fuel treatment impacts on forest structure, potential fire behavior, and predicted tree mortality in a California mixed conifer forest. Forest Ecology and Management 215, 21–36.
Experimental fuel treatment impacts on forest structure, potential fire behavior, and predicted tree mortality in a California mixed conifer forest.CrossRef |

Swezy MD, Agee JK (1991) Prescribed-fire effects on fine-root and tree mortality in old-growth ponderosa pine. Canadian Journal of Forest Research 21, 626–634.
Prescribed-fire effects on fine-root and tree mortality in old-growth ponderosa pine.CrossRef |

Thies WG, Westlind DJ, Loewen M (2005) Season of prescribed burn in ponderosa pine forests in eastern Oregon: impact on pine mortality. International Journal of Wildland Fire 14, 223–231.
Season of prescribed burn in ponderosa pine forests in eastern Oregon: impact on pine mortality.CrossRef |

Thies WG, Westlind DJ, Loewen M, Brenner G (2006) Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA. International Journal of Wildland Fire 15, 19–29.
Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA.CrossRef |

Thies WG, Westlind DJ, Loewen M, Brenner G (2008) A field guide to predict delayed mortality of fire-damaged ponderosa pine: application and validation of the Malheur Model. USDA Forest Service, Pacific Northwest Research Station, General Technical Report PNW-GTR-769. (Portland, OR)

Thomas TL, Agee JK (1986) Prescribed fire effects on mixed conifer forest structure at Crater Lake, Oregon. Canadian Journal of Forest Research 16, 1083–1087.

van Mantgem P, Schwartz M (2003) Bark heat resistance of small trees in Californian mixed conifer forests: testing some model assumptions. Forest Ecology and Management 178, 341–352.
Bark heat resistance of small trees in Californian mixed conifer forests: testing some model assumptions.CrossRef |

van Mantgem P, Schwartz M (2004) An experimental demonstration of stem damage as a predictor of fire-caused mortality for ponderosa pine. Canadian Journal of Forest Research 34, 1343–1347.
An experimental demonstration of stem damage as a predictor of fire-caused mortality for ponderosa pine.CrossRef |

van Mantgem P, Stephenson NL, Mutch LS, Johnson VG, Esperanza AM, Parson DJ (2003) Growth rate predicts mortality of Abies concolor in both burned and unburned stands. Canadian Journal of Forest Research 33, 1029–1038.
Growth rate predicts mortality of Abies concolor in both burned and unburned stands.CrossRef |

Vines RG (1968) Heat transfer through bark, and the resistance of trees to fire. Australian Journal of Botany 16, 499–514.
Heat transfer through bark, and the resistance of trees to fire.CrossRef |

Wagener WW (1961) Guidelines for estimating the survival of fire-damaged trees in California. USDA Forest Service, Pacific Southwest Forest and Range Experimental Station, Miscellaneous Paper 60. (Berkeley, CA)

Wallin KF, Kolb TE, Skov KR, Wagner MR (2003) Effects of crown scorch on ponderosa pine resistance to bark beetles in Northern Arizona. Environmental Entomology 32, 652–661.
Effects of crown scorch on ponderosa pine resistance to bark beetles in Northern Arizona.CrossRef |

Waring RH (1987) Characteristics of trees predisposed to die. Bioscience 37, 569–574.
Characteristics of trees predisposed to die.CrossRef |

Waring RH, Pittman GB (1985) Modifying lodgepole pine stands to change susceptibility to mountain pine beetle attack. Ecology 66, 889–897.
Modifying lodgepole pine stands to change susceptibility to mountain pine beetle attack.CrossRef |

Weatherby JC, Mocettini P, Gardner B (1994) A biological evaluation of tree survivorship within the Lowman fire boundary, 1989–1993. USDA Forest Service, Intermountain Region Forest Pest Management, Report R4-94-06. (Boise, ID)

Wyant JG, Zimmerman GT (1983) Factors contributing to postfire tree mortality in central Rocky Mountain forests. Proceedings of the Society of American Foresters National Convention.16–20 October, Portland, OR. (Eds ML Duryea, GN Brown) pp. 271–275. (Society of American Foresters: Bethesda, MD)

Wyant JG, Omi PN, Laven RD (1986) Fire induced tree mortality in a Colorado ponderosa pine/Douglas-fir stand. Forest Science 32, 48–59.



Export Citation Cited By (20)