Research Project Summary: Plant response to prescribed burning with varying season, weather, and fuel moisture in mixed-conifer forests of California



RESEARCH PROJECT SUMMARY CITATION:
Fryer, Janet L., compiler. 2007. Research Project Summary: Plant response to prescribed burning with varying season, weather, and fuel moisture in mixed-conifer forests of California. In: Fire Effects Information System, [Online]. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory (Producer). Available: http://www.fs.fed.us/database/feis/ [].

Sources: Unless otherwise indicated, the information in this Research Project Summary comes from the following papers:

Kauffman, John Boone. 1986. The ecological response of the shrub component to prescribed burning in mixed conifer ecosystems. Berkeley, CA: University of California, Berkeley. 235 p. Dissertation. [7].

Kauffman, J. Boone; Martin, R. E. 1985a. A preliminary investigation on the feasibility of preharvest prescribed burning for shrub control. In: Proceedings, 6th annual forestry vegetation management conference; (Date of conference unknown); Redding, CA. (Place of publication unknown). (Publisher unknown). 89-114. On file with: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory, Missoula, MT. [4].

Kauffman, J. Boone; Martin, Robert E. 1985b. Shrub and hardwood response to prescribed burning with varying season, weather, and fuel moisture. In: Donoghue, Linda R.; Martin, Robert E., eds. Weather--the drive train connecting the solar engine to forest ecosystems: Proceedings of the 8th conference on fire and forest meteorology; 1985 April 29-May 2; Detroit, MI. Bethesda, MD: Society of American Foresters: 279-286. [6].

Kauffman, J. Boone; Martin, R. E. 1987. Effects of fire and fire suppression on mortality and mode of reproduction of California black oak (Quercus kelloggii Newb.). In: Plumb, Timothy R.; Pillsbury, Norman H., technical coordinators. Proceedings of the symposium on multiple-use management of California's hardwood resources; 1986 November 12-14; San Luis Obispo, CA. Gen. Tech. Rep. PSW-100. Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station: 122-126. [5].

Kauffman, J. B.; Martin, R. E. 1989. Fire behavior, fuel consumption, and forest-floor changes following prescribed understory fires in Sierra Nevada mixed conifer forests. Canadian Journal of Forest Research. 19: 455-462. [2].

Kauffman, J. B.; Martin, R. E. 1990. Sprouting shrub response to different seasons and fuel consumption levels of prescribed fire in Sierra Nevada mixed conifer ecosystems. Forest Science. 36(3): 748-764. [3].

STUDY LOCATION AND SITE DESCRIPTION:
The study sites were located on the Blodgett Forest Research Station near Georgetown, California, in the Sierra Nevada; the Challenge Experimental Forest on the La Porte Ranger District of the Plumas National Forest in the Cascade Range; and the Quincy Ranger District of the Plumas National Forest [3,6]. These sites are referred to as Blodgett, Challenge, and Quincy in this summary.

BlodgettElevation at the study site is 1,310 m. The site is highly productive (site index classification=I-II) [3,6]. Mean annual precipitation is 1,700 mm. Terrain is generally level, with 1% to 12% slope [3].

Challenge―The study site is 4 km southeast of Challenge, California. Elevation is 1,005 m. Aspects are generally west with slope ranging from 35% to 50%. The site is highly productive (site index classification=I-II) [3,6]. Mean annual precipitation is 1,800 mm. Slope ranges from 35% to 55% [3].

Quincy―Study site elevation is 1,350 m. The site is less productive than the other 2 study sites (site index classification=III-IV) [3,6]. Mean annual precipitation is 900 mm. Slope ranges from 35% to 75% [3].

PREFIRE PLANT COMMUNITY:
BlodgettThe study site was in a dense, mixed-conifer forest. The stand was codominated by white fir (Abies concolor), Pacific ponderosa pine (Pinus ponderosa var. ponderosa; hereafter, ponderosa pine), and incense-cedar (Calocedrus decurrens) [6]. California black oak (Quercus kelloggii), tanoak (Lithocarpus densiflorus), and giant chinquapin (Chrysolepis chrysophylla) were hardwood associates. The study stand was second growth, approximately 70 years of age [3]. It was logged in the early 1900s and probably burned in a 1919 wildfire [7]. The understory was composed of mixed shrubs. Associated shrubs selected for study were Sierra gooseberry (Ribes roezlii), whitethorn ceanothus (Ceanothus cordulatus), deer brush (C. integerrimus), whiteleaf manzanita (Arctostaphylos viscida), greenleaf manzanita (A. patula), pine rose (Rosa pinetorum), Sierra mountain misery (Chamaebatia foliolosa), and Pacific dogwood (Cornus nuttallii) [3,7]. Groundlayer vegetation was sparse [7].

Challenge―The study site was a mixed-conifer forest codominated by ponderosa pine, coast Douglas-fir (Pseudotsuga menziesii var. menziesii; hereafter, Douglas-fir), and incense-cedar. California black oak was an overstory associate. The study site was logged in the 1870s, but a few old-growth ponderosa pines remained [3]. The understory was composed of mixed shrubs. Pacific madrone (Arbutus menziesii), tanoak, and Pacific dogwood grew in shrub form and were selected for study [6,7]. Other associated shrubs selected for study were deer brush, whiteleaf manzanita, Sierra gooseberry, pine rose, and Sierra mountain misery [3,7]. Poison-oak (Toxicodendron diversilobum) was also present. Groundlayer vegetation was sparse [7].

Quincy―The site was a mixed-conifer forest codominated by ponderosa pine, Douglas-fir, and incense-cedar. Sugar pine (Pinus lambertiana) was an overstory associate. A salvage cut was conducted on the site after insect kill in the 1960s and 1970s; otherwise, Quincy was unlogged. The understory was composed of mixed shrubs including shrubby California black oak. Other associated shrubs selected for study were deer brush, creeping ceanothus (Ceanothus prostratus), pine rose, pale serviceberry (Amelanchier pallida), and thimbleberry (Rubus parviflorus) [3,7]. Small incense-cedar and Douglas-fir were also in the understory, sometimes forming dense thickets. Groundlayer vegetation was diverse; western fescue (Festuca occidentalis) and Quincy lupine (Lupinus dalesiae) were most abundant [7].

In this study, sprouting hardwoods (tanoak, giant chinquapin, Pacific madrone, California black oak, and canyon live oak) were generally designated as shrubs and included in shrub statistical analyses [3]. Qualitative descriptions were given for fire responses of large trees [7].

Study sites are classified in the following plant communities and probably historically experienced the fire regimes described below:

Table 1. Fire regime information on the vegetation community studied in this Research Project Summary. Fire regime characteristics are taken from the LANDFIRE Rapid Assessment Vegetation Models LANDFIRE Rapid Assessment Vegetation Model [9]. This vegetation model was developed by local experts using available literature and expert opinion as documented in the PDF file linked from the name of the Potential Natural Vegetation Group listed below.
Vegetation Community (Potential Natural Vegetation Group) Fire severity* Fire regime characteristics
Percent of fires Mean interval
(years)
Minimum interval
(years)
Maximum interval
(years)
California mixed evergreen Replacement 10% 140 65 700
Mixed 58% 25 10 33
Surface or low 32% 45 7 15
Mixed conifer (North Slopes) Replacement 5% 250    
Mixed 7% 200    
Surface or low 88% 15 10 40
Mixed conifer (South Slopes) Replacement 4% 200    
Mixed 16% 50    
Surface or low 80% 10    
*Fire Severities
Replacement: Any fire that causes greater than 75% top removal of a vegetation-fuel type, resulting in general replacement of existing vegetation; may or may not cause a lethal effect on the plants.
Mixed: Any fire burning more than 5% of an area that does not qualify as a replacement, surface, or low-severity fire; includes mosaic and other fires that are intermediate in effects.
Surface or low: Any fire that causes less than 25% upper layer replacement and/or removal in a vegetation-fuel class but burns 5% or more of the area
[1,8].

PLANT PHENOLOGY:
Plants had ceased growing but were not yet dormant at the time of the early fall fires. Late fall fires coincided with leaf drop. Early spring fires were conducted before the growing season started. Late spring burning was done when plants were actively expanding leaves and stems [6].

FIRE SEASON AND SEVERITY CLASSIFICATION:
early fall/moderate
late fall/low
early spring/low
late spring/moderate

FIRE DESCRIPTION:
This study used experimental fires to reduce fuel loads and determine whether prescribed surface fire can be used as a method of shrub control prior to conifer harvest in mixed-conifer stands. Sprouting woody plants can interfere with growth of young conifers, creating a reforestation problem after tree harvest [4]. Research objectives were to describe shrub response to fires in various seasons and fuel consumption levels and to construct predictive equations of shrub mortality under various fire, fuel, and weather variables. This Research Project Summary focuses on the first objective. Regression equations for predicting shrub mortality are presented in these papers: [3,7].

There were 4 fire treatments and an unburned control at each site. Burning was conducted in 1983 and 1984. Treatments included an early fall (September), high-consumption burn; a late fall (October), moderate-consumption burn; an early spring (April and early May), moderate-consumption burn; and a late spring (late May and June), high-consumption burn [3]. Prescription guidelines called for windspeeds of <7 miles/hour, relative humidities >15%, and air temperatures ranging from 10 to 25 C [4]. Early fall, high-consumption burning was conducted before a significant rain occurred, when moisture content of the lower duff layer was <10%. Late fall, moderate-consumption burning was done 1 to 2 weeks after a significant rain. Early spring fires were set as early as possible while still meeting the prescription criteria. Late spring burning was conducted after at least 1 month with no precipitation [3]. Just prior to the experimental fires at Blodgett, mean basal area was 72.6 m/ha [3], and downed woody fuel load ranged from 131 to 177 t/ha. Total prefire fuel loads averaged 143 t/ha, with duff comprising 60% to 80% of the total fuel load [7]. At Challenge, mean basal area before burning was 80.5 m/ha [3], and downed woody fuel load ranged from 124 to 163 t/ha. Total prefire fuel loads averaged 149 t/ha at Challenge, with duff comprising 74% to 84% of total fuel load [7]. At Quincy, mean basal area before burning was 48.0 m/ha [3], and downed woody fuel load ranged from 75 to 102 t/ha. Total prefire fuel loads averaged 87 t/ha, with duff comprising 62% to 81% of total fuel load [7]. On all sites, litter and duff comprised 62% to 84% of total fuel loads [2,3,6]. Fires were implemented using a strip-head ignition pattern [3]. Fire conditions were [2,5,6,7]:

Table 2. Weather, fuel, and fire behavior variables for the 3 research sites. Values are means (SE).

Blodgett Research Station

Variable

Treatment

Early fall, high consumption Late fall, moderate consumption Early spring, moderate consumption Late spring, high consumption
Date 28 Sept. 1984 8 Oct. 1983 17 May 1984 26 June 1984
Time 11:00-17:75 14:00-15:23 11:40-17:00 8:56-14:45
Fuel moisture content, 10-hr timelag fuelsticks (%) 9-11.5 13.15 10-11 7-11
Relative humidity (%) 25-48 49-63 31-57 21-72
Temperature (C) 19-23 16-18 16-17 17-27
Windspeed (km/hr) 0-8 0-3 0-3 0-3
Lower duff (Oa) moisture content (%) 23.2a* (4.6) 90.1b (7.8) 135.0c (16.3) 51.6a (10.6)
Soil moisture (%) na 34.8 (5.5) 58.2a (4.2) 42.9 (1.9)
Flame length (cm) 73.7a (12.4) 26.5ab (5.9) 63.5b (2.5) 85.1a (23.5)
Fireline intensity (kJ/m/s) 15.6 (4.5) 152.1a (55.6) 97.0 (8.4) 254.6a (163.5)
Rate of spread (cm/s) 2.1 (11.2) 0.3 (0.5) 1.8 (10.8) 1.6 (6.3)
Residence time (sec) 85.9 (13.4) 104.5 (75.7) 61.2 (10.9) 71.1 (5.9)
Duff consumption (%) 11 (na**) 63.3 (4.8) 11.5a (3.4) 76.3 (4.3)
Duff consumption (t/ha) na 68.0 (10.3) 11.0a (3.2) 61.0 (1.2)
Total fuel consumption (%) na 64.5 (7.3) 16.8a (6.5) 62.5 (4.6)
Total fuel consumption (t/ha) na 111.5a (36.8) 26.9b (11.5) 80.0ab (12.3)
Shrubs top-killed (%) na 100 (0.0) 98.0 (20) 100 (0.0)
Total shrub mortality***
(%)
na 49.0a (11.1) 16.3b (3.9) 72.4c (3.8)
*Different superscripts within the same row indicate a significant difference among treatments (P≤0.05).
**na=not available.
***Mortality measured in postfire year 2.

Challenge Experimental Forest

Variable

Treatment

Early fall, high consumption Late fall, moderate consumption Early spring, moderate consumption Late spring, high consumption
Date 26 Sept. 1983 20 Oct. 1983 16 May 1984 20 June 1984
Time 16:21-19:30 9:45-15:00 9:15-1240 10:29-14:18
Fuel moisture content, 10-hr timelag fuelsticks (%) 9-9.5 9.5-10 8-11 8-9
Relative humidity (%) 54-67 46-64 52-61 37-52
Temperature (C) 16-22 16-22 16-18 21-24
Windspeed (km/hr) 0-5 0-3 0-8 0-3
Lower duff (Oa) moisture content (%) 16 (2) 43 (6) 32 (10) 120 (17)
Duff moisture (%) 15.7 (1.7) 43.4 (5.8) 30.9 (8.9) 119.5a (17.3)
Soil moisture (%) 11.1a* (0.9) 22.3b (1.4) 44.1b (3.6) 25.7c (2.9)
Flame length (cm) 30.5a (4.7) 56.3ab (7.6) 70.9bc (5.2) 97.1c (15.2)
Fireline intensity (kJ/m/s) 21.2a (3.8) 85.9ab (9.8) 125.8ab (5.2) 272.7b (101.9)
Rate of spread (cm/s) 1.5 (2.1) 1.4 (2.8) 1.6 (8.5) 4.0 (25)
Residence time (sec) 47.8 (21.9) 51.3 (11.2) 55.7 (4.4) 85.6a (5.2)
Duff consumption (%) 93.6 (1.3) 83.4 (4.2) 69.7a (4.4) 91.6 (2.2)
Duff consumption (t/ha) 111.2 (13.6) 105.8 (27.1) 72.3 (7.3) 111.3 (16.8)
Total fuel consumption (%) 92.1a (1.4) 77.5b (4.1) 56.2c (2.5) 82.4b (3.3)
Total fuel consumption (t/ha) 148.2 (15.3) 117.2 (8.8) 69.2a (3.3) 135.8 (17.4)
Shrubs top-killed (%) 99.3 (0.7) 98.9 (1.1) 95.2 (4.8) 100 (0.0)
Total shrub mortality**
(%)
80.1 (4.0) 74.2 (5.9) 36.0a (SD not given) 83.5 (3.6)
*Different superscripts within the same row indicate a significant difference among treatments (P≤0.05).
**Mortality measured in postfire year 2.

Quincy study area

Variable

Treatment

Early fall, high consumption Late fall, moderate consumption Early spring, moderate consumption Late spring, high consumption
Date 15 Sept. 1983 12 Oct. 1983 7 May 1984 24 May 1984
Time 10:49-16:15 9:45-16:47 10:37-14:15 9:23-14:20
Fuel moisture content, 10-hr timelag fuelsticks (%) 5-9 10-14.5 7 8
Relative humidity (%) 15-38 46-67 21-39 29-57
Temperature (C) 22-29 9-20 14-20 13-21
Windspeed (km/hr) 0-3 0-3 0-11 0-11
Lower duff (Oa) moisture content (%) 8.7a (1.3)* 63.0b (10.2) 35.0c (9.2) 18.7a (3.1)
Soil moisture (%) 3.6a (0.5) 11.3b (1.3) 20.3c (2.0) 11.0b (2.2)
Flame length (cm) 44.1 (12.7) 31.0 (1.9) 50.7 (6.4) 60.1 (14.6)
Fireline intensity (kJ/m/s) 56.0ab (23.4) 20.8a (2.5) 63.9ab (17.7) 110.6b (44.7)
Rate of spread (cm/s) 3.5 (16.1) 1.8 (6.1) 3.0 (15.6) 3.0 (15.6)
Residence time (sec) 61.8 (18.8) 37.0 (6.4) 49.3 (4.4) 49.5 (8.4)
Duff consumption (%) 72.4 (3.4) 70.0 (6.8) 82.8 (2.9) 86.2 (2.9)
Duff consumption (t/ha) 47.9 (4.8) 40.1 (2.0) 50.6 (2.0) 53.1 (8.1)
Total fuel consumption (%) 77.2 (3.7) 56.2 (13.0) 77.3 (5.6) 77.4 (5.4)
Total fuel consumption (t/ha) 79.7 (11.1) 49.5 (10.8) 59.3 (4.9) 58.9 (10.7)
Shrubs top-killed (%) 98.5 (1.5) 81.8 (6.8) 91.5 (6.1) 93.8 (4.3)
Total shrub mortality**
(%)
57.3a (7.6) 21.4b (1.6) 30.9b (7.3) 56.7a(8.5)
*Different superscripts within the same row indicate a significant difference among treatments (P≤0.05).
**Mortality measured in postfire year 2.

Fuel consumption varied with season, prescription, and site. Fuel reduction was generally least with early spring, moderate-consumption fires, although the late-fall, moderate-consumption fire reduced fuels least at Quincy. There were no significant differences between fire treatments in total amount of fuels consumed at the Quincy site. (See Table 2 for details.)

Among sites, open physiognomy promoted fuel drying, which increased fuel reduction during burning. The Quincy site was most open, so fuels were usually drier than on the other sites. In contrast, although the early spring fire on the Blodgett site was the last of the 3 early spring fires, fuel reduction was least on the Blodgett site. A dense canopy, level terrain, and high elevation all contributed to increased fuel moisture levels at Blodgett compared to other sites. Low percent duff moisture content was highly correlated (R=5.1, P<0.001) with duff consumption. The authors credited duff moisture as the best predictor of fuel consumption [6].

Minimizing fireline intensity reduces risk of a crown fire. Fireline intensity was not correlated with either duff moisture content (R=0) or duff consumption (R=0.02). It was apparently related to weather variables (relative humidity and wind speed), flammability of vegetation, slope and aspect, fine fuel moisture, and burn pattern. The authors stated that "fireline intensity was related to the skill and expertise of the person doing the actual burning". Fireline intensity was highest in the late spring, high-consumption fires at all sites [6].

FIRE EFFECTS ON PLANT COMMUNITY:
Mortality: Species physiological capacity to grow in the postfire environment, fuel load, fire season, and plant size class affected plant survivorship. The authors stress that "assessing the degree to which each variable affected postfire shrub response is difficult due to their interrelationships" [7], but when comparing mortality rates, fuel consumption was the most significant factor in predicting plant mortality [4]. Plant survivorship is detailed below by life form.

Shrubs― Prescribed fires resulted in significant increases in shrub mortality (including shrubby hardwoods) compared to unburned controls [3]. Shrub mortality on the unburned control was <2%, while mortality on burned sites ranged from 21% to 88% (see Table 2 and Table 5).

Species response― Among all shrub species studied, whitethorn ceanothus and giant chinquapin were most resistant to fire mortality, and manzanitas were most susceptible. Lignotubers and root crowns of whitethorn ceanothus and giant chinquapin, respectively, were more deeply buried compared to other shrubs, and Kauffman [7] attributed their higher survival to this protection. Some tanoaks had lignotubers located in the duff layer, and such tanoaks showed high mortality after high-consumption fires [7].

Fuels― Composition and biomass of fuel loads affected shrub mortality. Sites with highest fuel biomass and thickest duff layers (Challenge and Blodgett) had higher mortality than Quincy, the site with the lowest fuel biomass and thinnest duff layer (see Table 2). Additionally, greater amounts of fuels were consumed at Challenge and Blodgett [7]. As a result, shrub mortality was significantly greater (P<0.05) in postfire year 2 at Challenge and Blodgett compared to Quincy in all treatments except on the early spring, moderate-consumption burn. The authors suggested that high flame temperatures at the shrub root crowns caused high shrub mortality at Challenge and Blodgett [5,6].

Kauffman and Martin [3] suggest that differences in soil moisture, along with season of burning, may partially explain significant differences in mortality for California black oak shrubs in response to spring fires at Quincy. Although duff consumption was similar for early and late spring fires (77-79%), soil moisture content during the early spring fire (x=20.3%) was nearly twice soil moisture content during the late spring fire (x=11.0%). Soils with greater moisture content may have lower temperatures while burning, thereby lowering California black oak mortality [3].

Fire season― Season of burning probably modified the ability of shrubs to sprout after fire. Fires set before the growing season began (early spring, moderate-consumption burns) resulted in least shrub mortality across all study sites [7]. Early fall, high-consumption and late spring, high-consumption burns resulted in highest mortality for small California black oaks and tanoaks. Across sites, high-consumption fires caused greatest shrub mortality. At Quincy, the late spring, high-consumption fire, which corresponded with periods of rapid aboveground growth, caused significantly greater shrub mortality compared to early spring, moderate-consumption fire even though there were no significant differences in the percent and amount (t/ha) of duff consumed [6]. However, all fire treatments resulted in significantly (P<0.05) higher mortality than the control, with the smallest hardwood shrubs showing highest rates of mortality [5]. At Quincy, there were no significant differences in fuel reduction between early and late spring fires (77.3% and 77.4%, respectively); however, California black oak mortality was 24% greater in the late spring treatment (P<0.10) [3,7]. Shrub mortality was least after the early spring fires, which were conducted prior to initiation of spring growth [3].

Size classes― Hardwood survivorship tended to increase with increasing plant size. Survivorship was analyzed by size class for shrubby California black oaks and tanoaks. Size classes and size class survivorship by fire season are shown in Table 4. The trend of best survivorship for the largest shrubs was most evident in late fall and early spring, moderate-consumption fires. After late fall, moderate-consumption fire at Challenge, for example, 71% of tanoaks in the largest size class (>200 g dry weight biomass) survived, while only 11% in the smallest size class (<26 g dry weight biomass) survived [3]. Comparing survivorship of California black oak at Quincy, the population at Quincy showed greatest survivorship across fire treatments. Quincy had the greatest number of large California black oaks. Blodgett had the smallest California black oaks, and among study sites, California black oak showed least survivorship at Blodgett [7].

Prescribed burning altered size class distribution of California black oak and tanoak. For shrubby hardwoods in the smallest size class, survivorship was low regardless of burn treatment. At Blodgett, for example, heat flux of even the low-consumption fires was sufficient to kill the smallest California black oaks. The smallest size class was composed of germinants and seedlings with meristematic root crowns still in the organic soil horizon. Before prescribed burning, most hardwoods were in the 2 smallest size classes. Differential mortality in small size classes resulted in a more uniform distribution of individuals among size classes after the fire. For the largest size class (around 5 kg aboveground dry weight), described as "subarboreal", mortality increased as consumption of the organic horizon increased. At Blodgett, all California black oaks in the largest size class survived the early spring fire, while only 14% of the largest California black oaks survived the early fall fire. At Challenge, 83% of the largest tanoaks survived the early spring fire, while only 45% survived the early fall fire [3].

Individual hardwoods may take longer to resume growth after top-kill than smaller shrubs. On all sites, 14% of shrubs that failed to sprout in postfire year 1 sprouted in postfire year 2. The majority of shrubs that first sprouted in postfire year 2 were California black oaks [7].

Shrubs and shrubby hardwood survivorship after prescribed fires is shown in Tables 3 and 4 below [3]:

Table 3. Percent survivorship of shrubs and shrubby hardwoods in postfire year 2. Species listed are those with large enough sample sizes for statistical analyses. Values are means ( 1 SD).
Species

Treatment

Early fall, high consumption Late fall, moderate consumption Early spring, moderate consumption Late spring, high consumption Unburned control
Blodgett
whitethorn ceanothus 40a* (55) 94b (24) 80ab (42) 50a (51) 80ab (41)
giant chinquapin 27a (46) 39a (50) 78a (50) 40a (50) 100b (0)
tanoak  13a (35) 50b (53) 100c (0) 17a (40) 100c (0)
California black oak 9a (29) 35b (49) 69c (47) 28ab (45) 100d (0)
all shrubs 12a (32) 51b (50) 73d (44) 33c (47) 96e (20)
Challenge
tanoak 18a (38) 25a (44) 67b (47) 21a (41) 99c (12)
all shrubs  17a (38) 25a (44) 63b (48) 19a (39) 99c (12)
Quincy
California black oak  45a (50) 78c (42) 69bc (46) 45a (50) 100d (0)
all shrubs 45a (50) 79c (41) 69bc (46) 56ab (50) 100d (0)
*Different letters indicate a significant difference in shrub survival among fire treatments (P<0.10).

Table 4. Percent shrubby hardwood survivorship, sorted by size class (dry weight biomass), after 2 postfire growing seasons in different fire treatments. Values are means ( 1 SD).
California black oak at Blodgett
Size class by biomass (g) Early fall, high consumption Late fall, moderate consumption Early spring, moderate consumption Late spring, high consumption Unburned control
0-39 17a* (41) 18a (40) 22a (44) 0a (0) 100b (0)
40-69 0a (0) 20a (44) 80b (42) 22a (44) 100b (0)
70-92 17a (39) 67ab (58) 70ab (48) 29ab (49) 100c (0)
93-127 0a (0) 25ab (50) 70bc (48) 29ab (48) 100c (0)
128-200 12a (0) 100b (0) 75b (50) 13a (35) 100b (0)
201-360 6a (25) 50ab (71) 60ab (55) 35a (50) 100b (0)
361+ 14a (38) 42a (53) 100b (0) 45a (52) 100b (0)
Total 9a (29) 35b (49) 69c (47) 28ab (45) 100d (0)
Tanoak at Challenge
0-25 3a (18) 11a (32) 48b (50) 3a (18) 96c (20)
26-50 8a (29) 15a (38) 78b (44) 11a (32) 100b (0)
51-100 9a (29) 7a (26) 91b (30) 13a (35) 100b (0)
101-150 20a (41) 13a (35) 78b (44) 14b (38) 100b (0)
151-200 33ab (50) 42abc (53) 86bc (38) 0a (0) 100c (0)
200+ 45a (50) 71abc (46) 83bc (38) 61ab (49) 100c (0)
Total 18a (38) 25a (44) 67b (47) 21a (41) 99c (12)
*Different letters indicate a significant difference among treatments within size classes (P<0.10).

Hardwood trees― All tree-sized California black oaks and tanoaks survived fire, and many produced root crown sprouts even though they were not top-killed [3]. A few large California black oaks that survived the fires had toppled by postfire year 2 [7]. No further information was given for tree-sized hardwoods.

Conifers― Density of conifers <2 m in height decreased significantly after all fire treatments at all sites. Incense-cedar showed greatest mortality among conifers, with mortalities near 100% on some plots. Incense-cedar was "all but eliminated" from the understory by all fire treatments [7]. Ponderosa pine, Douglas-fir, and sugar pine saplings (3-8 cm DBH) showed low mortalities. Many burned sites had 1,200 or more conifer saplings/ha. No conifers >20 cm DBH were killed by any fire treatment [4]. Ponderosa pines on all 3 study sites experienced "many attacks" by red turpentine beetles after spring, high-consumption burns, but the attacks had not caused any ponderosa pine mortality as of postfire year 3 [7].

Density and frequency of shrubs, shrubby hardwoods, and conifers on fire treatments and the unburned control are shown in Tables 5 and 6 [4,7].

Table 5: Density.pdf

Table 6: Frequency.pdf

Sprouting response: In all treatments, >80% of shrubs were top-killed; in most treatments, >90% of shrubs were top-killed. Species sprouting from root crowns tended to support a larger number of sprouts/plant compared to species sprouting from lignotubers. Giant chinquapin root crowns, for example, often supported 100 to 300 sprouts/root crown in postfire year 2. Ceanothus species also supported many sprouts. At Blodgett, mean number of whitethorn ceanothus basal stems ranged from 5 to 8 stems/root crown before fire and from 22 to 37 stems/root crown in postfire year 2. Generally for all sprouting species, large plants produced more sprouts than small plants. Postfire growth rate was generally fastest after moderate-consumption fires; however, Kauffman [7] emphasized that it is difficult to predict the effects of fire season on postfire growth of sprouting species. Much depends upon individual species response and the size class of individual burned plants. Postfire growth rates are shown in Table 7.

Tanoak was the dominant shrub at Challenge before the fires. Prefire cover was estimated at 9% to 15%. During 3 years of postfire study, tanoak cover was significantly reduced (P≤0.05) to less than 2% in all fire treatments. Tanoak cover on unburned plots increased to 18.1% to 27.8% during that time. Tanoak, California black oak, and giant chinquapin showed increasing ability to sprout with increasing size. Exceptions occurred when lignotubers or root crowns of very large individuals grew in the organic soil layer: fire usually killed such trees [7].

Comparing plant response to fuel consumption at postfire year 1, all sprouting species had lower rates of sprout growth in high-consumption fires. Tanoak and California black oak had highest sprouting growth rates after early spring, moderate-consumption fires. Whitethorn ceanothus and giant chinquapin had highest rates of sprout growth after late fall, moderate-consumption fires. Sprout growth of tanoak, California black oak, and whitethorn ceanothus was lowest after late spring, high-consumption fires. The growing season was well underway by late spring, which may account for this slow growth rate [7].

Some California black oaks, tanoaks, and Pacific dogwoods produced epicormic sprouts in response to burning [7]. This response was not quantified.

Sierra mountain misery is a shrub of particular concern on burned timber sites because it sprouts from roots crowns and deeply buried roots, so fire seldom kills it. It often forms continuous mats that interfere greatly with growth of young conifers. The experimental fires significantly reduced Sierra mountain misery density for all treatments except the early spring, moderate-consumption fires. Late spring, high-consumption fires reduced Sierra mountain misery most effectively, with reductions of 89% and 64% on the Blodgett and Challenge sites, respectively. Sierra mountain misery was not present at Quincy [4]. Sierra mountain misery only established from sprouts after fire [7]. See Table 5 and Table 6 for further information.

Changes in sprouting shrub physiognomy: Prescribed burning resulted in significant decreases in mean shrub basal diameter, height, crown volume, cover, and aboveground biomass. There were significant increases in the number of stems/plant. Shrubby California black oak and tanoak generally had more sprouts/root crown after fire compared to their prefire sprout counts. The ceanothus species (deer brush and whitethorn ceanothus) usually produced many more sprouts/root crown after fire compared to prefire counts. For all shrubs, number of sprouting stems was related to prefire shrub size, with large shrubs producing a greater number of sprouts, with larger biomasses, compared to small shrubs. Evergreen species such as tanoak partitioned more aboveground biomass in leaves (37-41% of total aboveground biomass) compared to deciduous species like California black oak (12-17% total aboveground biomass). Four shrubs were selected for intensive studies. Response of these sprouting shrubs to the experimental fires was as follows [3]:

Table 7. Basal diameter, number of stems, height, and crown cover for shrub species before late spring prescribed fires and for 2 growing seasons after late spring prescribed fires. Numbers are means ( 1 SD).
Species and location Year
Prefire (1983) Postfire yr 1 (1984) Postfire yr 2 (1985)
Tanoak at Challenge (n=133)
basal diameter (mm) 13.8a (14.3) 3.3b (1.3) 5.1c (1.8)
number stems/root crown 1.5a (1.2) 11.8b (11.8) 13.2b (19.6)
height (cm) 71.4a (70.5) 35.2b (19.7) 45.0a (21.8)
crown area (m) 0.7a (1.3) 0.1b (0.2) 0.4a (0.5)
total aboveground biomass (g) 223.8a (456.3) 23.7b (44.7) 58.6b (64.0)
California black oak at Quincy (n=87)
basal diameter (mm) 13.8a (15.2) 6.2b (98) 6.7b (8.7)
number stems/root crown 1.9a (1.7) 4.8b (3.0) 4.3b (3.5)
height (cm) 40.6 (45.1) 32.2 (59.9) 36.4 (34.7)
crown area (m) 0.49 (1.4) 0.07 (0.05) 0.18 (0.22)
total aboveground biomass (g) 250.4a (895.2) 22.8b (27.9) 38.8b (52.)
Whitethorn ceanothus at Blodgett (n=22)
basal diameter (mm) 14.1a (7.6) 2.0b (1.0) 3.5c (0.7)
number stems/root crown 5.0a (5.0) 27.0b (17.0) 31.0c (13.0)
height (cm) 64.7a (41.2) 21.2b (11.1) 25.0b (10.6)
crown area (m) 1.5a (1.7) 0.1b (0.1) 0.4b (0.3)
Giant chinquapin at Blodgett (n=25)
basal diameter (mm) 6.8a (5.1) 2.0b (1.1) 3.5c (0.9)
number stems/root crown 4.0a (5.0) 14.0b (20.0) 9.0b (11.0)
height (cm) 34.7 (34.8) 19.3 (15.4) 16.4 (9.1)
crown area (m) 0.24 (0.42) 0.04 (0.07) 0.05 (0.07)

Postfire shrub seedling establishment: Ceanothus and Manzanita spp. seedlings were most abundant after fire treatments compared to other shrub species. Greenleaf manzanita, whiteleaf manzanita, whitethorn ceanothus, and deer brush have persistent seed banks with seeds that require fire or other heat scarification to germinate. Pale serviceberry, Pacific madrone, Sierra mountain misery, Sierra gooseberry, pine rose, and thimbleberry also have persistent seed banks, but their nonrefractory seeds do not require heat scarification to germinate. Whitethorn ceanothus and whiteleaf manzanita seedlings were most common on burn treatments at Blodgett; deer brush and whiteleaf manzanita seedlings most common at Challenge; and deer brush, greenleaf manzanita, and prostrate ceanothus most common at Quincy. Of the species with nonrefractory seeds, only Sierra gooseberry seedlings were common after fire treatments. Sierra gooseberry was not present on Challenge and Quincy study sites before the fires, but was abundant on all 3 study sites after burning treatments [7]. Most ceanothus and manzanita species require heat scarification followed by overwinter stratification to germinate, so spring fires did not promote their seedling establishment on any of the study sites in postfire year 1. However, ceanothus and manzanita seedling establishment commenced on spring-burned plots in postfire year 2. For fall fire treatments, most ceanothus and manzanita germinants arose from the duff-mineral soil interface or just below the mineral soil surface the following spring [4,7]. Few seedlings were counted on study plots before the fires. After the fires, there was a general trend of denser seedling establishment after fall fires than after spring fires [7]. Whitethorn ceanothus seedling density was greatest on the late fall, moderate-consumption Blodgett fires. At Quincy, whiteleaf manzanita seedling density was 15 times greater on fall burns compared to spring burns. Greenleaf manzanita mostly emerged from seed cached by animals before fire treatments. After fire treatments, rodents dug up many seed caches with greenleaf manzanita emergents and consumed the new plants. Some greenleaf manzanita seedlings established from undisturbed caches, but rodent browsing and rodent digging disturbance caused high mortality for greenleaf manzanita seedlings [7]. Densities for ceanothus and manzanita seedlings that were selected for intensive counts are shown below [4].

Table 8. Mean seedling density (seedlings/ha) before fire (1983) and in postfire year 1 (1984)

Species

Fire treatment

Early fall/high Late fall/moderate Early spring/moderate Late spring/high
prefire postfire prefire postfire prefire postfire prefire postfire
Blodgett
whitethorn ceanothus not available 0 15,545* 0 0 33 0
greenleaf manzanita not available 0 3,834* 0 0 0 0
Quincy
deer brush 0 17,893** 0 1,534** 0 0 0 0
prostrate ceanothus (Ceanothus prostratus) 0 17,893** 0 1,534** 0 0   0
Challenge
deer brush 0 215,977** 0 264,486** 0 0 0 0
*Significant at P≤0.10
**Significant at P≤0.05.

Hardwood seedling establishment: For hardwoods, postfire seedling establishment rates were provided only for California black oak. Two growing seasons after the Blodgett fires, California black oak seedling establishment was significantly greater in nearly all burn treatments compared to the control. The exception was the early spring treatment, which did not significantly reduce duff biomass. For other fire treatments, California black oak germinants were 2 to 10 times greater on burned than on unburned treatments. California black oak seedling establishment was enhanced when the duff layer was reduced to <38 t/ha [5]:

Table 9. California black oak seedling density at Blodgett and Quincy, postfire year 2. Values are means
( 1 SD).
Blodgett
  Early fall/high Late fall/moderate Early spring/moderate Late spring/high Unburned control
Seedlings/ha 367 (327)  333 (152) 67a (67) 267 (200) 133a (133)
Seedling component of total study-site population (%) 79*  67* 15 80* 17
Postfire biomass of duff layer (t/ha) 7.7a** 37.8b 86.4b 20.1c 100.0
Quincy
Seedlings/ha 217 (158) 500 (273) 467 (232) 200 (133) 55a
Seedling component of total study-site population (%) 37* 52* 67* 40* 7
Postfire biomass of duff layer (t/ha) 17.9a 19.2a 10.8a 7.5a 80.0b
*Percentage of seedlings in population is significantly greater than the control (P<0.005).
**Different superscripts indicate a significant difference among treatments (P<0.005).

The authors speculated that most California black oak seedlings established from acorns cached by squirrels or Steller's jays. Although such animal caching was not observed on study sites, western gray squirrels and Douglas's squirrels were observed consuming cached California black oak acorns in the seed-to-germinant transition stage. The squirrels ate acorn portions of the plants, which were still attached to germinants. Most germinants survived this consumption despite loosing the last of their of their seed reserves [5].

Conifer seedling establishment: Several conifer species showed good seedling establishment after the fires. Kauffman [7] speculated that the fires killed conifer seeds on the ground, and that postfire conifer seedling establishment was from crown-stored seed. By postfire year 2, ponderosa pine, Douglas-fir, and white fir seedlings had established in significantly higher densities on burned sites at Blodgett and Challenge compared to controls (see Table 5 and Table 6). At Blodgett, white fir became the most abundant conifer after fire. White fir density increased 80% on late spring, high-consumption burns compared to prefire density, and ponderosa pine density increased 451% over prefire density. Jeffrey pine and sugar pine established in significantly greater numbers on burned Quincy sites compared to the control. For all sites, there was a positive relationship between increasing duff consumption and seedling density for white fir, Douglas-fir, and Pinus spp., indicating that except for incense-cedar, conifer seedling establishment was enhanced by reduction of duff biomass. Conifer establishment was generally highest after high-consumption fires that exposed mineral soil [7].

Fire effects on fungus: At Quincy, Kauffman [7] observed the cup fungus Pyronema omphalodes on fall burns in postfire year 1. Quantitative data were not collected for the fungus. In places, Pyronema omphalodes formed a continuous layer over mineral soil, and its presence may have reduced postfire soil erosion. By spring, when soils began to dry, the fungus was no longer apparent [7].

FIRE MANAGEMENT IMPLICATIONS:
Kauffman and Martin [5] state that prefire fuel loads on these 3 study sites resulted from an "unnatural buildup of downed woody materials". They speculate that the heat loads produced by fuel loads of 48 to 100 t/ha in the high-consumption burns were probably a rare occurrence prior to fire exclusion. Further, low-severity, presettlement surface fires were probably similar to the moderate-consumption study fires, which reduced fuels about 11 t/ha. For sprouting woody species, the effect of the low-consumption study fires was probably similar to effects of historic low-severity surface fires, with only the smallest size classes of sprouting species killed [5].

These experimental fires demonstrated that in the short term, prescribed understory fires can control shrubs and small incense-cedars in mixed-conifer stands of the southern Cascade Range and Sierra Nevada. Repeated understory burns at approximate 10-year intervals may provide long-term control of shrubs and small trees. With high-consumption fires in the most productive stands (Blodgett and Challenge), >80% of understory shrubs were killed [3]. This suggests that the optimum burning seasons for shrub control are late spring or early fall. These seasons correspond to times when shrub phenology combines with favorable fuel conditions, killing the highest percentage of shrubs possible under prescribed fire conditions. Fires prescribed to consume as much duff as possible were most effective in killing shrubs. Additionally, burning during the active growing season increased shrub mortality regardless of the amount of duff consumed, so timing fires to coincide with dry fuel conditions and active shrub growth may achieve greatest shrub mortality. If low shrub mortality is desired (for example, to enhance wildlife forage), the authors recommend burning in early spring before the active growing season [6].

For California black oak, this study suggests that acorn germination and seedling establishment are enhanced by fires that substantially reduce the duff layer. Kauffman and Martin [5] suggest that mineral soil or a light duff layer was the seed bed with which California black oak evolved, and that litter accumulations reduce seed bed quality and seedling establishment in California black oak. They recommend duff reductions to <40 t/ha to optimize California black oak seedling establishment [5].


APPENDIX: SPECIES INCLUDED IN THIS SUMMARY
This Research Project Summary contains fire response information on the following species. For further information, follow the highlighted links to the FEIS species reviews.

Table 10. Appendix

Common name Scientific name
Pacific madrone Arbutus menziesii
white fir Abies concolor
incense-cedar Calocedrus decurrens
giant chinquapin Chrysolepis chrysophylla
Pacific dogwood Cornus nuttallii
tanoak Lithocarpus densiflorus
Jeffrey pine Pinus jeffreyi
sugar pine Pinus lambertiana
Pacific ponderosa pine Pinus ponderosa var. ponderosa
coast Douglas-fir Pseudotsuga menziesii var. menziesii
California black oak Quercus kelloggii
pale serviceberry Amelanchier pallida
whiteleaf manzanita Arctostaphylos viscida
greenleaf manzanita Arctostaphylos patula
whitethorn ceanothus Ceanothus cordulatus
deer brush Ceanothus integerrimus
prostrate ceanothus Ceanothus prostratus
Sierra mountain misery Chamaebatia foliolosa
Sierra gooseberry Ribes roezlii
pine rose Rosa pinetorum
thimbleberry Rubus parviflorus

REFERENCES:


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2. Kauffman, J. B.; Martin, R. E. 1989. Fire behavior, fuel consumption, and forest-floor changes following prescribed understory fires in Sierra Nevada mixed conifer forests. Canadian Journal of Forest Research. 19: 455-462. [7645]
3. Kauffman, J. B.; Martin, R. E. 1990. Sprouting shrub response to different seasons and fuel consumption levels of prescribed fire in Sierra Nevada mixed conifer ecosystems. Forest Science. 36(3): 748-764. [13063]
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5. Kauffman, J. Boone; Martin, R. E. 1987. Effects of fire and fire suppression on mortality and mode of reproduction of California black oak (Quercus kelloggii Newb.). In: Plumb, Timothy R.; Pillsbury, Norman H., tech. coords. Proceedings of the symposium on multiple-use management of California's hardwood resources; 1986 November 12-14; San Luis Obispo, CA. Gen. Tech. Rep. PSW-100. Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station: 122-126. [5366]
6. Kauffman, J. Boone; Martin, Robert E. 1985. Shrub and hardwood response to prescribed burning with varying season, weather, and fuel moisture. In: Donoghue, Linda R.; Martin, Robert E., eds. Weather--the drive train connecting the solar engine to forest ecosystems: Proceedings, 8th conference on fire and forest meteorology; 1985 April 29-May 2; Detroit, MI. Bethesda, MD: Society of American Foresters: 279-286. [9796]
7. Kauffman, John Boone. 1986. The ecological response of the shrub component to prescribed burning in mixed conifer ecosystems. Berkeley, CA: University of California. 235 p. Dissertation. [19559]
8. LANDFIRE Rapid Assessment. 2005. Reference condition modeling manual (Version 2.1), [Online]. In: LANDFIRE. Cooperative Agreement 04-CA-11132543-189. Boulder, CO: The Nature Conservancy; U.S. Department of Agriculture, Forest Service; U.S. Department of the Interior (Producers). 72 p. Available: http://www.landfire.gov/downloadfile.php?file=RA_Modeling_Manual_v2_1.pdf [2007, May 24]. [66741]
9. LANDFIRE Rapid Assessment. 2007. Rapid assessment reference condition models, [Online]. In: LANDFIRE. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Sciences Lab; U.S. Geological Survey; The Nature Conservancy (Producers). Available: http://www.landfire.gov/models_EW.php [2008, April 18] [66533]

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