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

Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA

Walter G. Thies A D , Douglas J. Westlind A , Mark Loewen B and Greg Brenner C
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Pacific Northwest Research Station, Forestry Sciences Laboratory, 3200 Jefferson Way, Corvallis, OR 97331, USA.

B USDA Forest Service, Malheur National Forest, Emigrant Creek Ranger District, Hines, OR 97738, USA. Present address: Dixie National Forest, Cedar City, UT 84720, USA.

C Pacific Analytics, PO Box 219, Albany, OR 97321-0065, USA.

D Corresponding author. Email: wthies@fs.fed.us

International Journal of Wildland Fire 15(1) 19-29 https://doi.org/10.1071/WF05025
Submitted: 28 February 2005  Accepted: 22 September 2005   Published: 6 March 2006

Abstract

Prescribed burning is a management tool used to reduce fuel loads in western interior forests. Following a burn, managers need the ability to predict the mortality of individual trees based on easily observed characteristics. Astudy was established in six stands of mixed-age ponderosa pine (Pinus ponderosa Dougl. ex Laws.) with scattered western junipers at the south end of the Blue Mountains near Burns, Oregon, USA. Stands were thinned in either 1994 or 1995. Three treatments, a fall burn, a spring burn, and an unburned control, were randomly assigned to 12-ha experimental units within each stand. Prescribed burns occurred during mid-October of 1997 or mid-June of 1998 and were representative of operational burns, given weather and fuel conditions. Within each experimental unit, six 0.2-ha plots were established to evaluate responses to the burns. Ponderosa pine plot trees (n =3415) alive 1 month after the burns were evaluated and observed for four growing seasons. Nine fire damage and tree morphological variables were evaluated by logistic regression. A five-factor full model and a two-factor reduced model are presented for projecting probability of mortality. Significant variables in the full model included measures of crown, bole, and basal damage.

Additional keywords: Blue Mountains; modeling.


References


Avila OB , Burkhart HE (1992) Modeling survival of loblolly pine trees in thinned and unthinned plantations. Canadian Journal of Forest Research  22, 1878–1882.
Battaglin WA , Ulery RL , Winterstein T , Welborn T (2003) ‘Estimating the susceptibility of surface water in Texas to non-point-source contamination by use of logistic regression modeling.’ US Department of the Interior, US Geological Survey. Water-Resources Investigations Report 03-4205.

Beck N (1996) Reporting heteroskedasticity-consistent standard errors. The Political Methodologist  7((2)), 4–6.
Carey V (1998) ‘GEE: Generalized linear models for dependent data, gee S-function, version 4.13.’ (Statlib, Department of Statistics, Carnegie Mellon University: Pittsburgh, PA) Available at http://lib.stat.cmu.edu/S/ [Verified May 2004]

Davis JR , Ffolliott PF , Cleary WP (1968) ‘A fire prescription for consuming ponderosa pine duff.’ USDA Forest Service, Rocky Mountain Forest and Range Experiment Station Research Note RM-115. (Fort Collins, CO)

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

Diggle PJ , Liang KY , Zeger SL (1994) ‘Analysis of longitudinal data.’ (Clarendon Press: Oxford)

Duncan RS , Chapman CA (2003) Tree–shrub interactions during early secondary forest succession in Uganda. Restoration Ecology  11, 198–207.
Crossref | GoogleScholarGoogle Scholar | Finney MA (1999) ‘Fire-related mortality in ponderosa pine in eastern Montana.’ Intermountain Fire Sciences Laboratory Final Report INT-93800-RJVA. (Missoula, MT)

Fowler JF , Sieg CH (2004) ‘Post-fire mortality of ponderosa pine and Douglas-fir: a review of methods to predict tree death.’ USDA Forest Service, Rocky Mountain Research Station General Technical Report RMRS-GTR-132. (Fort Collins, CO)

Hamilton DA (1974) ‘Event probabilities estimated by regression.’ USDA Forest Service, General Technical Report INT-152. (Ogden, UT)

Hamilton DA (1990) Extending the range of applicability of an individual tree mortality model. Canadian Journal of Forest Research  20, 1212–1218.
Hardin JW , Hilbe JM (2003) ‘Generalized estimating equations.’ (Chapman & Hall/CRC: Boca Raton, FL)

Harrington MG (1987) Ponderosa pine mortality from spring, summer, and fall crown scorching. Western Journal of Applied Forestry  2, 14–16.
Harrington MG , Hawksworth FG (1990) Interactions of fire and dwarf mistletoe on mortality of southwestern ponderosa pine. In ‘Effects of fire management of southwestern natural resources: Symposium proceedings’. pp. 234–240. (Tech. coord. JS Krammes) USDA Forest Service, Rocky Mountain Forest and Range Experiment Station General Technical Report RM-191. (Fort Collins, CO)

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 13. (Fort Collins, CO)

Hosmer D , Lemeshow S (2000) ‘Applied logistic regression.’ 2nd edn. (John Wiley and Sons: New York)

Kerns BK, Thies WG , Niwa CG (2006) Season of prescribed burn in ponderosa pine forests: implications for native and exotic plant species. Ecoscience  13, in press..
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 INT-66. (Ogden, UT)

MathSoft (1999) ‘S-Plus 2000.’ (Data Analysis Products Division, MathSoft: Seattle, WA)

McCullagh P , Nelder JA (1991) ‘Generalized linear models.’ 2nd edn. (Chapman and Hall: London)

McHugh CW (2001) Probability of ponderosa pine morality following fire in northern Arizona. MS Thesis, Northern Arizona University, Flagstaff, AZ.

McHugh CW , Kolb TE (2003) Ponderosa pine mortality following fire in northern Arizona. International Journal of Wildland Fire  12, 7–22.
Crossref | GoogleScholarGoogle Scholar | Menard S (1995) ‘Applied logistic regression analysis. Quantitative Applications in the Social Sciences No. 106.’ (Sage Publications: Thousand Oaks, CA)

Monserud RA (1976) Simulation of forest tree mortality. Forest Science  22, 438–444.
Ramsey FL , Schafer DW (1997) ‘The statistical sleuth, a course in methods of data analysis.’ (Duxbury Press: London)

Regelbrugge JC , Conard SG (1993) Modeling tree mortality following wildfire in Pinus ponderosa forests in the central Sierra of California. International Journal of Wildland Fire  3, 139–148.
Crossref | GoogleScholarGoogle Scholar | Ryan KC (1983) Techniques for assessing fire damage to trees. In ‘Proceedings of the symposium: fire its field effects’. (Ed. JE Lotan) pp. 2–10. (Intermountain Fire Council: Missoula, MT)

Ryan KC , Reinhardt ED (1988) Predicting post-fire mortality of seven western conifers. Canadian Journal of Forest Research  18, 1291–1297.
Saveland JM , Bakken SR , Neuenschwander LF (1990) ‘Predicting mortality from scorch height from prescribed burning for ponderosa pine in northern Idaho.’ University of Idaho, College of Forestry, Wildlife and Range Sciences Bulletin Number 53. (Moscow, ID)

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.
Crossref | GoogleScholarGoogle Scholar | Wagener WW (1961) ‘Guidelines for estimating the survival of fire-damaged trees in California.’ USDA Forest Service, Pacific Southwest Forest and Range Experiment Station Miscellaneous Paper PSW-60. (Berkeley, CA)

White H (1982) Maximum likelihood estimation of misspecified models. Econometrica  53, 1–16.
Wyant JG , Zimmerman GT (1983) Factors contributing to post-fire tree mortality in central Rocky Mountain forests. In ‘Proceedings of the Society of American Foresters National Convention’. (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, 49–59.


Zeger SL , Liang K-Y (1986) Longitudinal data analysis for discrete and continuous outcomes. Biometrics  42, 121–130.

PubMed |