Fire regime• The nature of fires occurring over an

extended period of time

• General, long-term pattern of recurring fires over a particular time and place

• Typically includes frequency and severity

• Ideally includes size, spatial pattern, season, and variability

Describing fire regimes• Frequency: how often, usually characterized

as interval in years between fires• Extent: typical size• Magnitude:

• Intensity • Severity

• Rotation• Seasonality• Predictability • Spatial patterns

Fire frequency• Point frequency

• Fire return interval• Weibull mean fire interval• Probability of occurrence

• Area frequency both express the length of time necessary to burn an area equivalent to the study area• Rotation • Fire cycle is calculated based on the distribution

of ages in a time-since-fire map • Number of fires in a given area

Quantifying fire regimes: point fire frequency

• Measures• Mean fire interval (Heinselman 1973, Agee 1993)• Wiebull mean fire interval (Johnson 1992, Finney

1995, Grissino-Meyer 1999)

• Explicitly spatial, but represent spatial patterns as aggregates of point samples

Fire severity: degree of ecosystem change• Tree mortality • Heat penetration into the soil (Lea and Morgan

1993)• Degree to which fires consume organic biomass on

and within the soil (Lenihan et al. 1998)• Change in color of ash and soil (Wells et al. 1979,

Ryan and Noste 1985)• Combination of fire effects (Turner et al. 1994)

Fire intensity• Physical description of fire behavior

• Defined as the amount of energy released by a flaming front

• Closely correlated with flame length (Albini 1976)

Understanding fire regimes across spatial and temporal scales is challenging

• Fire is a stochastic, spatially complex disturbance process

• Data are from points or from small areas and often from relatively short time series

• Extrapolation is difficult

• Interpretations are often biased by truncated time series (Finney 1995), which causes us to overestimate fire frequency.

Understanding fire regimes across spatial and temporal scales is challenging

• Climate, vegetation, and topography all interact with fire

• Legacy of past events varies

• Fire and fire effects are inherently variable and heterogeneous

• Fire regimes are not static

Errors• Imperfect recording of fire events

• Not all fires scar trees• Subsequent fires may consume evidence

• Sampling may not detect all fires

• Heterogeneity and variability

• Autocorrelation in time and space

Frequent, light surface fires (2)

Infrequent, light surface fires (1)

Infrequent, severe surface fires (3)

Short-return interval, crown fires (4)

Very long-return interval, crown fires (6)

Long-return interval, crown fires (5)

Frequent, low-intensity surface fires (1)

Infrequent, low-intensity surface fires (2)

Infrequent, high-intensity surface fires (3)

Short-return interval, stand-replacement fires (4)

Very long-return interval, stand-replacement fires (6)

Variable: Frequent, low-intensity surface & long-return interval stand-replacement fires (5)

Heinselman Kilgore Flora Volume Hardy et al. Morgan et al.

No natural fires (0)

Understory fires, (forest)

Stand replacement fires (forest & grasslands)

Variable or mixed fires (forest)

Non fire regimes

<35 yr. Low Severity fires (forest)

<35 yr. Stand-replacement fires (forest & grassland)

35-100+ yr. Stand replacement fires (forest & grassland)

200+ yr. Stand replacement fires (forest)

35-100+ yr. Mixed severity fires (forest)

No burn

Nonlethal fires (forest)

Nonlethal fires (grassland)

Stand replacement fires (forest)

Mixed fires (forest)

Rarely burns

Why map fire regimes?• Assessment and planning

• Contrasting past to present

• Modeling

• Understanding the influence of climate, topography, and vegetation

• Identifying gaps in knowledge

Departures• Changes in fire intervals can be used to

prioritize fire and fuels management based upon “ecological need” (Caprio et al. 1997)

• http://www.nps.gov/seki/fire/frid97.htm

Departures• Fire Return Interval Departure = (RImax - TSLF)/RImax

• RImax = maximum average return interval for vegetation class

• TSLF = time since last fire, yrs• Moderate (0 to –2), high (-2 to –5), and extreme (> -5)

Fire Regime Condition Class

• Condition classes (relative to historical fire intervals)• I: No significant departure (<1 fire interval)• II: Moderate departure in fire freq. (>1 interval)• III: Significantly altered fire freq. (by multiple

intervals) and vegetation from historical range• In condition class III, critical ecosystem elements

may be lost when fires occur. In all condition classes vegetation composition and structure has changed, more for condition class II and the most for condition class III.

Historical Fire Regimes of the United StatesVersion 2.0 Version 1.0

Legend

0-35 yr. frequency, Non-lethal Severity0-35 yr. frequency, Stand Replacement Severity35-100+ yr. frequency, Mixed Severity35-100+ yr. frequency, Stand Replacement Severity

200+ yr. frequency, Stand Replacement SeverityAgriculture (Only Version 1.0)

WaterBarren http://www.fs.fed.us/fire/fuelman

http://www.fs.fed.us/fire/fuelman

Fire history methods

Natural archives of fire history data • Dated fire scars in tree rings: yr and season

• Time-since-fire maps reconstructed from ages of trees, usually from even-aged stands burned in stand-replacing fires

• Charcoal from sediment in lakes and bogs

• Networks of precisely dated fire-scar samples and sites have been used to estimate area burned based upon the proportion of sites scarred in a given year

Fire history from fire-scarred trees• Multiple fire scars from

single trees and groups of trees

• Works best for surface fires that burned relatively frequently

• Cross-date to identify exact year of scar

• Prepare surface and magnify to identify season of fire. This is done by examining the cells damaged by fire

Dated fire scars on trees• Low severity fires

• Some trees survive

• Part of cambium is killed

• Crossdate fire scars using dendrochronology (http://web.utk.edu/~grissino/)

• Composite dates from multiple individual trees

• Calculate fire frequency from distribution of intervals between fires

Strengths of fire-scar data• Extraordinary time depth -- typically 300 to 500

years, and more than 2,000 years in giant sequoia (Swetnam 1993)• Long records encompass extreme events

• High temporal resolution: fires are dated to the year, and often season, of occurrence

• When accurately dated it is possible to correlate fire events across spatial scales, and to compare the highly synchronized events (or asynchronous events) with independent temporal and spatial data

• Can infer other things: climate, suppression-release

Limitations• We know more about fire frequency than fire size,

severity, rotation, variability, and other characteristics of fire regimes

• Accuracy and precision of fire history data are seldom quantified

• Variability of fire regime characteristics over time and space is seldom evaluated

• Few fire history data available for grasslands, shrublands and woodlands

Fire history from mixed and stand-replacing fires

• Stand age reconstruction

• Time-since-fire maps

Time-since-fire maps• Stand-replacing fires• Even-aged cohorts of trees

established post-fire • Assume patch age-class

distribution is relatively stable over time (steady-state shifting mosaic)

• Assume frequency of disturbance is spatially homogeneous, stationary Poisson process

• If small, old stands are not detected or aged accurately, the frequency of disturbance is overestimated

Human archives • Operational databases of fire occurrence• Atlases: maps of fire perimeters and locations • Remotely sensed fire location, perimeter and

severity • Interviews, personal diaries, or literature searches• Land survey records • Aerial photographs • The National Interagency Fire Management

Integrated Database (NIFMID)

Fire atlases• Compilations of mapped fire perimeters• Paper or digital• Include date and perimeter of fires, but typically do

not include information on fire severity, rate of spread, or perimeters of small fires

• Only larger fires (>50 or 100 ac) are included, but they likely to represent a large proportion of area burned

• Errors in spatial location and date of fire occurrence are difficult to assess, likely vary through time and and can be severely limiting

Fire atlases• Perimeters often only approximate

• Spatial pattern of burned areas within the mapped perimeters is seldom known

• Can do spatial analyses of fire location, area burned through time, and frequency

• Typically only larger fires are mapped

• Accuracy likely varies through time

• Accuracy has not been assessed

Fire atlas boundary

Gila NF W ilderness DistrictBoundary

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

20 -Century Fire Perimeters -- G ila/Aldo Leopold Wilderness AreasNew Mexico

th

AZ NM

N

Rollins/LTRR

20 k

Fire frequency from fire atlases

• “Wall-to-wall”• Example is from the

Gila/Aldo Leopold Wilderness complex in New Mexico and the Selway-Bitterroot Wilderness Area in Idaho and Montana

• In this example, only fires >50 ha in size are included

U n b u rn ed

B u rn e d O n c e

B u rn e d Tw ic e

B u rn e d T h ree o r M o re T im e s

20 k

N

GALW C

SBWA

Aerial photographs• Fire perimeter, size, location, severity, pattern

• One of the few sources of fire severity information other than detailed field sampling during or immediately after a fire

NIFMID• National Interagency Fire Management

Integrated Database

• Includes all fires by size class, location, and cause, but only for recent decades

• Individual fires are represented as points (not necessarily the ignition point), size class, whether human or lightning ignited

• Includes small fires, and thus can complement fire atlases and other databases

Remote sensing from planes or satellites

• Not used extensively

• Great potential for mapping post-fire tree mortality and severity

• Lightning occurrence

Fire History Data SourcesTemporal Scale Spatial Scale

Atlases 20th CenturyYear

Entire wilderness area,1:24,000

Time Series of Aerial Photos

1930s to presentYear

Selway-River Basin1:24,000

NIFMID FireReport Data

1974-1997Year, month and day

Point data

Dendroecol.Data

Multi-century Year and season

Points within basins30m DEM

Fire History Data SourcesStrengths Limitations

Atlases 1. Fire date and location 2. Large fires (>50 ha) only

1. Accuracy varies2. Only perimeters

Time Series of Aerial Photos

1. Fire date, perimeter, and severity

2. Fine-scale

1. ‘Lab’ intensive2. New technique

NIFMID FireReport Data

1. Date, location, and size class of all fires

2. Ignition source

1. Point data2. Limited: 1976-1996

Cross-dated fire scars in tree rings

1. Fire date and season2. Spatial location3. Multiple centuries

1. Point data2. ‘Lab’ intensive

Example of using multiple data sets• Compare and contrast fire patterns in two

areas• Selway-Bitterroot Wilderness Area (Idaho and

Montana)• Gila/Aldo Leopold Wilderness Complex (New

Mexico)

• What are the fire patterns through time?

• How are fire patterns related to topography, fire management policy, and to drought?

• From: Rollins et al. 2000

Study areas• SBWA

• 547,370 ha• 500 m to 1500 m

• GALWC• 486,673 ha• 1300 m to 1500 m

Developed lands

W estern redcedar

Grand firDouglas-fir

Lower subalpine

Persistent herblands

Upper subalpine

Rock/alpine

Water

n

Desert-scrub-grass

Douglas-fir

M ixed conifer

Pi on--oak-juniperñ

Ponderosa pine

Riparian

Spruce/fir

20 k

Selway-B itterrootW lderness Area

Gila/Aldo Leopold W ilderness Com plex

500 k

M oggollon M ountins

Area burned• Selway-Bitterroot Wilderness Area

• 474,237 ha burned in 437 fires from 1880 to 1996• 7 yrs of extensive fire, 72% of all area burned• 1889, 1910, 1919, 1929, 1934, and 1988

• Gila-Aldo Leopold Wilderness Complex• 147,356 ha burned in 232 fires from 1909 to 1993• 6 yrs of extensive fire, 71% of all area burned• 1909, 1946, 1951, 1985, 1992, 1993

Area burned during three different eras of fire management

Area burned and Palmer Drought Severity Index (PDSI)

Area burned by fire management eraArea burned (ha) % of study area Fire rotation (yr)

Selway-Bitterroot

1880-1935 482,030 60.9 92

1936-1974 9,622 1.2 3206

1975-1994 58,427 7.4 271

Gila/Aldo Leopold

1880-1946 32,601 6.7 552

1947-1974 34,742 7.1 406

1975-1993 80,424 16.5 114

Fire rotations (yr)Selway-Bitterroot Wilderness Area

All years1880-1996

Early1880-1934

Fire control1935-1975

Fire manage.1976-1996

W. Redcedar 368 41 396,498 359

Herblands 80 79 4,167 77

Grand fir 384 66 7,380 267

Douglas-fir 169 104 4,704 140

Lower subalpine

519 117 3,651 230

Upper subalpine

852 191 3,361 361

Rock/alpine 371 295 1,957 164

Fire rotations (yr)Gila-Aldo Leopold Wilderness Area

All years1909-1993

Early1909-1946

Fire control1947-1975

Fire manage.1976-1993

Desert scrub-grassland

15,573 120,514 40,782 4,324

Pinyon-oak-juniper

540 1,156 1,182 188

Ponderosa pine

200 382 410 74

Douglas-fir 180 353 205 84

Mixed conifer 245 612 145 207

Spruce-fir 537 508 435 998

Fire frequency by potential vegetation type (PVT)

Topography• 30 m DEMs• Level I and II

500 k

Gila/Aldo Leopold Wilderness Com plex

Selway-BitterrootWilderness Area

20k

Elevation Slope Aspect

Elevation

Slope

Aspect

N

Are fire patterns independent of elevation?

Fire frequencies and landscape characteristics: K-S two-sided probabilities

GALWC SBWA

Elev. Aspect Slope Insol. Elev. Aspect Slope Insol.

Unburned 0.43 1.00 1.00 1.00 0.00 0.82 0.97 1.00

Once 0.00 0.82 1.00 0.99 0.00 1.00 0.97 1.00

Twice 0.00 0.70 0.99 0.77 0.00 1.00 0.30 1.00

Three 0.00 0.99 0.13 0.04 0.00 0.70 0.22 0.48

Logistic regression models

2

Model Variable Coefficient T-ratio

Gila Wilderness

Area

Intercept -6.092 -20.92

Elevation 0.002 13.63

Slope 0.012 3.13

Distance From NE -0.029 -4.00

PCE = 82% = 0.043

2

Model Variable Coefficient T-Ratio

Selway-Bitterroot

Wilderness Area

Intercept 0.938 5.75

Elevation -0.002 -25.68

Slope 0.012 3.56

Distance From NE 0.20 2.99

PCE = 87% = 0.103

McFadden’s

McFadden’s

What is the fire evidence from lake sediments – Burnt Knob Lake

• ~4 m of sediment, pollen and charcoal • Recent deposition rate of 0.08 cm/yr or 12.23

years/cm• Periods of high fire activity occur between 13,000

and 11,500 14C yr B.P. and at ca. 6000, and 2250 14C yr B.P.

• Severe, probably stand-replacing fires occurred at ~13,000 14C yr B.P., ~12,000 14C yr B.P., and ~6000 14C yr B.P.

Fire history• 12 fire years in Burnt Knob Lake basin

between 1580 and 1883 based on dated fire scars in tree rings

• Charcoal peaks in lake sediments match fire events in AD 1900/1904, 1883, and 1838

• No evidence of 1910 fire in lake sediments, fire scars, or fire atlases

Age structure• Lodgepole pine and whitebark pine establish

very quickly following fire

• Many large diameter whitebark pines survive fires that are lethal to many surrounding trees

• Some pulses of regeneration are not related to fires

Climate from tree rings• Chronology spans the period 1197-1996, with

good sample depth from 1400-1996

• Based upon 38 series from whitebark pine (29 trees), with an interseries correlation of 0.510 and a mean sensitivity of 0.202

• These trees are more sensitive to temperature than drought

What drives and determines fire patterns across time and space?

• Regional climate entrains fire patterns at fine spatial scales, overriding the influence of local topography and vegetation, leading to synchrony at widely separated sites and across regions

Drivers• Local site productivity

• Topography

• Climate

• Fire exclusion policies

• land use

• Exotic plants

Questions • Why do we understand more about the

temporal patterns of fires than we do about the spatial patterns of fires?

Challenges and limitations• Little empirical data addresses both long time

periods and broad spatial scales, but these are rapidly developing.

New directions• Multiple, integrated data sets

• Climate change

• Fire and lightning

• Insects, drought, climate and fire

• Patterns across time and space

1968

1965

1992

19921938

1953

1989

1904

1953

1904

10

5

9

15

37

5

5

5

Gila/Aldo Leopold Wilderness ComplexMogollon Baldy - Langstroth Mesa Transect

1986 - 1997 fires per 100 ha

Lightning Ignitions

Human Ignitions

Lightning, fires, topography and vegetationGALWC, fires/100 ha,1986 - 1997

Lightning ignitions Human ignitions