REPORT SFRC-86/05 

Response of a Muhlenbergia 

Prairie to Repeated Burning: 

Changes in Above-ground Biomass 

NATIONAL 

L APR 2 4 1986 - 

1 URBAN & REG. COPS. LIBRARY 

Everglades National Park, South Florida Research Center, P.0. Box 279, Homestead$ 33030 
Response of a Muhlenber-gia Prairie to Repeated Burning: 

Changes in Above-ground Biomass 

Report SFRC-86/05 

Alan Herndon and- Dale Taylor 

National Park Service 

South Florida Research Center 

Everglades National Park 

Homestead, Florida 33030 
Herndon, Alan, and.Dale Taylor. 1986. Response of a Muhlenbergia Prairie 

to Repeated Burning: Changes in Above-ground Biomass. South Florida 

Research Center Report ~F'~~-86/05. 

LIST OF TABLES 

Tables Page 

1. Designations and treatments for study areas.....................14 

2. Number of samples required to detect given differences 

in mean fuel loads between treatment areas......................15 

3. ANOVA tables for test of spatial homogeneity in mean 

fuel loads......................................................l6 

4. Homogeneous groupings of the treatment areas with 

respect to mean fuel loads......................................17 

5. ANOVA table for test of temporal homogeneity in 

mean fuel loads of the unburned control,.......,................18 

6. Three-way ANOVA table for burned treatment areas................19 

7. Homogeneous groupings of the treatment areas with 

respect to mean Cladium biomass.................................20 

8. Average yearly inundation of the treatment areas.,...,..........Zl 

9. ANOVA table for test of differences between one- and 

two-year fuel accumulations.....................................22 

LIST OF APPENDICES 

Appendix 

1. Above-ground biomass measured in meter square 

samples for all treatment areas and sampling 

periods ......................................................... 23 

2. Means and variances of log-transformed above 

ground biomass values (fuel loads) obtained 

in the treatment areas........................................ ..5!~ 
LIST OF FIGURES 

Figure Page 

1. Base map showing treatment area locations......................61 

2. Scatter diagram of mean and standard deviation 

for untransformed fuel samples.................................62 

3. Probit graph for transformed fuel samples......................63 

4. Means and 95% confidence intervals for aboveground biomass.................................................64 

5. Means and 95% con£ idence intervals for 

Cladium biomass..............................,,................66 

6. Change in Cladium biomass with time in the 

annual burn treatment areas....................................68 

7. Scatter diagram of fuel load against soil depth 

in meter square samples showing a promising 

relationship..... .............................................. 69 

8. Scatter diagram of fuel load against soil depth 

in meter square samples showing a typical 

relationship........................................... ........ 70 

9. Scatter diagram of fuel load against average 

soil depth in treatment areas..................................71 

10. Scatter diagram of fuel load against average 

inundation in treatment areas..................................72 

11. Variation in mean fuel load with time for 

treatment areas Dl, D3, and C..................................73 

12. Variation in live fuel load with time for 

treatment area D6....................,.........................76 

13. Scatter diagram of transformed live fuel against 

transformed total fuel.........................................77 
INTRODUCTION 

Xuhlenbergia prairie is one of the most extensive plant communities in the 

Taylor Slough region of Everglades National Park (Olmsted et al. 1980). 

This community occupies higher ground than any other prairie type in the 

Everglades and is consequently the most frequently burned. In the past, 

many fires that started outside the park have crossed into the park 

through the extensive Muhlenbergia prairies along the eastern boundary of 

the Taylor Slough region and some fires that started in the park crossed 

in the-other direction (Taylor 1981). This led to the establishment of a 

regular burning program along the park boundary (Fire Management Plan, 

1977). Muhlenbergia prairies along the northern and eastern park 

boundaries were scheduled for frequent burning to reduce fuel loads and 

lessen the chance of fires crossing the boundaries. Similar fuel 

reduction burns were also scheduled at several locations well within the 

boundaries to protect structures or natural sites deemed to be of special 

importance. These prescribed fuel-reduction burns have generally been 

carried out during the dry, relatively cool, months from November through 

March while available evidence indicates that the prairies historically 

burned during the summer months (Taylor 1981). 

A fire-ecology study was established in December 1978 to investigate the 

effects of repeated boundary burns on the structure and vegetational 

composition of the Muhlenbergia prairie type. In particular, the effect 

of season of burn and burning frequency on subsequent vegetative recovery; 

and the long-term structural changes associated with different burning 

regimes were the major concerns of the study. Another question of 

particular concern involved the effect of different fire regimes on the 

endangered Cape Sable Seaside Sparrow (Amospiza maritima mirabilis). A 

large percentage of the extant populations of this sparrow live in 

Muhlenbergia prairies (Werner 1975; Bass and Kushlan 1981). Cover, which 

is strongly influenced by recent fire history at least, seems to be the 

most important factor determining the suitability of any particular 

prairie site for use by this species (Werner 1975; Kushlan et al. 1982; 

Taylor 1984). The entire study included vegetation analysis, mammal 

trapping, arthropod sampling, and studies on the Cape Sable Seaside 

Sparrow. In this report, one aspect of the vegetation analysis, the 

response of above ground biomass (fuel load), is discussed. 

We report the results of the first six year cycle in the experiment. 

First, we discuss the sampling requirements for the biomass measurements 

at length to provide a basis for future analyses. Then, we report some 

results concerning the short-term recovery of above-ground biomass in our 

study sites. Finally, we are able to discuss some factors which lead to 

the observed heterogeneity in the pattern of biomass distributed on the 

prairie surface. 

MATERIALS AND METHODS 

Descri~tion of the Studv Site 

Muhlenbergia prairie is characterized by the co-dominance of the 

clump-forming grass Muhlenbergia filipes and small plants of the 

rhizomatous sedge, Cladium jamaicense. Other important members of this 
vegetation type are the sedge, Rhynchospora tracyi, and the grass, 

Schizachyrium rhizomatum. Many other species of graminoids and herbs are 

also found growing in this prairie type, and some may even be locally 

dominant (Olmsted et al. 1980). Typically, the vegetative cover is uneven 

with plants appearing to be randomly distributed. Sinkholes, often 

containing tall tussocks of Cladium, are scattered irregularly throughout 

the prairie. These sinkholes may have much higher - or lower biomass per 

unit area than the surrounding level prairie. For a more detailed 

description of this vegetation type see Olmsted et al. (1980). 

Plocs for the Muhlenbergia prairie fire ecology study were set up in 

prairie north of the Main Park Road (US 27) about 2.5 kilometers (1 mile) 

west of Taylor Slough Bridge (Figure 1). This site differs from the 

prairie area discussed by Olmsted et al. (1980) in occupying higher ground 

and being less subject to inundation. The average period of inundation 

(defined as standing water covering at least 502 of the prairie surface) 

at this site is approximately 45 days per year (see below). Records 

indicated that no fires had occurred within the study site for at least 

ten years prior to the start of the experiment. We assumed the site was 

no longer changing under the influence of a previous fire. 

Experimental Design 

The overall experimental design is factorial with season of burn and 

frequency of burn as factors. Seasons chosen for burning correspond to 

distinct biological periods, during which plants might be expected to show 

different responses to burning. December-January burn plots are scheduled 

tor burning in late December or early January. This represents the early 

part of the dry season and the middle of tne cool season. Most plant 

species in the prairie are not actively growing at this time; very few are 

flowering or fruiting. February-March burns are scheduled for late 

February or early March, the middle of the dry season. Many plant species 

in the prairie are actively growing at this time despite continued drying 

of the soil. Flowering and fruiting activity is again common following 

the winter lull. July burns are scheduled for early July. This month 

normally corresponds to the beginning of the wet season and is 

characterized by warm temperatures and active plant growth. Frequent, 

unpredictable, rainstorms make burns difficult to carry out in this 

month. A control plot was also included in the design to allow us to 

determine whether seasonal or long-term trends in fuel accumulation were 

present. 

Season of burn was chosen as a factor because there has apparently been a 

substantial difference between the natural fire season and the times of 

years most prescribed burns have been carried out. Over 80% of all 

prescribed burns in Everglades National Park have been carried out in the 

months from November through March (Taylor 1981). This is due to 

difficulties encountered in carrying out a prescribed burning program 

during the summer months. Still, natural fires are set most frequently 

and burn the greatest acreage at the end of the dry season (Taylor 1981). 

Fire frequency was chosen as a factor although no historical information 

on fire recurrence rates in the Everglades was available for comparison to 

boundary burning practices. There was adequate biological precedent to 
suggest that burning frequency would have a major effect on plant 

recovery. 

Table 1 shows the designations given to the various combinations of 

treatments in this experiment. No six-year burn treatment was planned for 

July due to concerns about the manageability of such a fire. Each 

treatment was applied to a single area of approximately 35 ha (50 acres) 

which contained three vegetation sampling plots (30 X 50 m) and one mammal 

trapping grid (50 X 90 m). 

Fuel Sampling 

Above-ground biomass was sampled primarily to determine the fuel available 

for burning in the prairie and is often called fuel load in the remainder 

of this study. Fuel loads were sampled at irregular intervals in each 

treatment area between December 1978 and July 1982 (Appendix 1). Fuel 

loads were again sampled in all plots between December 1984 and July 1985, 

six years after the start of the experiment. The treatment areas are 

scheduled to be burned at the seasons and intervals specified in Table 1 

for the next several years. This will make it possible to study the 

intermediate and long-term effects of these burning schedules on the 

Muhlenbergia prairie. 

An individual fuel sample consisted of all plant material above the 

surface of the ground which was contained in a vertical column defined by 

a one meter square frame resting on the surface. Standing plant material 

was clipped at the surface and loose material laying on the ground was 

collected. In some cases plant litter on the ground was thickly covered 

by a layer of periphyton. Since periphyton does not burn under current 

prescription burning practices, such litter was not collected. This 

involved a subjective decision concerning what to collect, but it is 

unlikely to have influenced our results very much. Loose litter made only 

a minor contribution to the total biomass at our study site. We have also 

observed that there is never a thick layer of loose plant litter on the 

ground in other Muhlenbergia prairie sites. 

Fuel samples were collected near the vegetation plots and the mammal plot 

in each treatment area. Individual collection sites were chosen by 

throwing a meter-square frame in the vicinity of these fixed plots. Such 

a non-random placement of sample sites was chosen to insure that samples 

were spread out over the entire area. The lack of randomization at this 

level is not expected to create any difficulties since most important 

changes within the prairie seemed to occur on scales different from the 

spacing between the permanent plots. Another nonrandom factor in our fuel 

collection was the decision to not collect samples from sinkhole areas. 

These sinkholes often contain luxuriant stands of Cladium and have a much 

greater biomass of plant material per unit area than the level prairie 

surface, but they are scattered and have no significant influence on fire 

behavior. Prediction of fire behavior was one of our primary aims, so we 

decided to concentrate on sampling the level prairie. Inclusion of 

sinkhole samples in the study would probably lead to little or no change 

in the mean values obtained, but would greatly increase the variance of 

the mean. 
Three fuel samples were collected in treatment areas C, Dl, D3, D6, Fly 

F3, and F6 (see Figure 1) before the initial burns in those areas. 

Unfortunately, three samples proved to be too few to characterize pre-burn 

fuel conditions in those areas. The number of pre-burn samples was 

increased to ten in treatment areas F1 and F3, but loss of samples during 

processing reduced the number of available measurements. An attempt was 

made to collect ten fuel samples from each treatment area during sampling 

periods from July 1979 through June 1980. Starting in July 1981, an 

attempt was made to collect twelve samples from each treatment area during 

sampling periods. Losses of samples during processing and time 

constraints imposed by other ongoing projects led to a reduction in the 

number of samples collected during some of the sampling periods. More 

than twelve samples were collected from two treatment areas during one 

sampling period. It was also necessary to modify sampling in the C 

treatment area after December 1980 when a prescribed burn in the Dl area 

escaped and burned approximately one-quarter of C. The burned area of C 

was sampled independently of the unburned area thereafter. 

Fuel load sampling periods were originally scheduled at four month 

intervals following burns. During the wet season (June-October), however, 

water levels were often high enough to interfere with or even preclude 

tuel sample collection. This and time limitations led to the sampling 

dates recorded in Appendix 1. 

Following collection, most of the fuel samples were separated into live 

and dead components. Sawgrass (Cladium jamaicense) was also separated 

from the remainder of the sample in most cases. The resulting groups were 

oven-dried at either 90 OC (from December 1978 through June 1980) or 

70 OC (during the remainder of the project) and weighed to the nearest 

0.1 gram. Only graminoids and herbs were encountered during our fuel 

sampling, so all of our figures refer to fine fuels. Samples collected at 

the end of the study were dried and weighed without separating live and 

dead components. 

Soil Depth and Hydroperiod Measurements 

Soil depths were measured concurrently with fuel sample collection from 

July 1980 through July 1981. Depths were measured by pushing a 

small-diameter rod (approximately 4 mm) through the soil to bedrock. Five 

measurements were made at each square-meter sampling site: one at each of 

the corners and one in the middle. 

Average hydroperiod was calculated for the different treatment areas using 

measurements of water depths in the vegetation plots from 7 to 11 June 

1982. During this period, a continuous sheet of surface water covered the 

prairie from our experimental plots to Taylor Slough Bridge. We 

calculated the number of subplots which would be flooded for any given 

stage at Taylor Slough Bridge by assuming that any drop in water level at 

the Bridge would correspond to an identical drop in water level in our 

experimental plots. Then, using the record of stage from Taylor Slough 

Bridge for the period 1961 to 1982, we calculated the average number of 

days per year 25%, 50%, and 75% of the vegetation subplots would have been 

f looded . 
RESULTS 

Statistical Properties of Fuel Sample Data and Analysis Methods 

Data for all fuel samples collected during the course of this study are 

given in Appendix 1. We calculated means and standard deviations for each 

set of samples and plotted these values against each other (Figure 2). 

The standard deviation of a sample generally increases with the mean. 

This is characteristic of values that follow a log-normal distribution. 

Such a departure from normality is commonly encountered in biomass 

measurements (Green 1979) and is serious enough to invalidate most 

parametric tests applied to such data. .We transformed the raw data to 

obtain an approximately normal distribution by adding one to each raw 

value and taking the natural logarithm of the sum (Sokol and Rohlf 1969; 

Green 1979). A probit analysis (Bliss 1967) confirmed that the 

transformed data followed a near-normal distribution (Figure 3). These 

analyses were carried out on one-year post burn and two-year post burn 

data because all treatment areas (control excepted) were the same age 

post-fire, and were all presumably at the same stage of regrowth from the 

initial burns. In probit analysis, departures from normality show up as 

departures from a straight line on the graph. Data from both data sets 

produce fairly straight lines although the data for two-year post burn 

samples shows a slight tendency towards leptokurtosis. 

We used transformed (normalized) fuel values and parametric statistical 

tests, principally factorial or one-way ANOVA routines, for all 

comparisons between different treatment areas. The means and variances of 

the transformed values for each set of samples are given in Appendix 2. 

It is possible to estimate the number of observations needed to test for a 

given level of true difference between the mean fuel loads of two 

treatment areas with controlled probabilities for the acceptance of an 

incorrect null hypothesis (4) and the rejection of a correct null 

hypothesis (6). We used the iterative method given in Sokol and Rohlf 

(1969) for this purpose on our data. Samples from all treatment areas at 

three corresponding stages (preburn, one year post-burn, two year 

post-burn) were pooled to estimate the necessary population means and 

variances. Results are given in Table 2. The number of samples needed to 

detect a given difference between two treatment areas depends on which 

pooled group of samples is used. This is expected since the mean fuel 

loads at the various stages is different, but it does point out that 

comparisons between treatment areas should be made at corresponding stages 

with respect to burning. In all cases, the detection of a 5% difference 

in log-transformed mean fuel loads between two areas requires a more 

intensive sampling program than we used. It appears that 102 differences 

in log-transformed mean fuel loads between areas are efficiently detected 

by our sampling program. The 104 difference in log-transformed fuel loads 

corresponds to a 30-504 difference in untransformed fuel loads, so the 

only changes we are able to detect by collecting 12 samples per treatment 

area are quite large. Changes of this magnitude are obvious on visual 

inspection of the sites. 

F.\.U. URBAN & REG. DOGS. LIBWRY 
Fire Behavior 

Our first major finding was that one-year fuel accumulatioas would not 

carry fires in our plots. With two years of accumulated fuel in the 

plots, fires burned, but left large patches of unburned fuel throughout 

the treatment area. In treatment areas with three-year fuel 

accumulations, fires burned nearly all above-ground plant material and 

left no unburned patches. These results held regardless of the season of 

year during which burning was attempted. 

Spatial Heterogeneity in Fuel Loads 

Statistical analysis of the results based on the experimental design is 

valid only if there is no systematic spatial heterogeneity in average fuel 

loads of the treatment areas. Spatial homogeneity in fuel loads is not 

required, but if the fuel loads are heterogenous, they must be randomly 

distributed with respect to the factors in the experimental design. This 

is especially critical because we did not replicate treatments. 

We first tested for homogeneity of the treatment areas with respect to 

fuel load using the pre-burn data. A single-classification ANOVA with 

unequal replications was used for this test. The results are shown in 

Table 3. A similar single-classification ANOVA was used to test the 

homogeneity of the treatment areas (excluding C) with respect to fuel load 

at one-year post burn (Table 3) and two years post-burn (Table 3). 

Significant inhomogeneity among treatment areas with respect to total fuel 

load was noted in all cases, indicating that there were significantly 

different average fuel loads in some of the treatment areas. Spatial 

heterogeneity of fuel loads on the scale of our treatment areas must, 

therefore, be considered as a possible source of difficulty in the 

analysis of our data. 

Homogeneous groupings of the treatment areas with respect to fuel load 

were determined using the Duncan multiple range test for one year 

post-burn and two years post-burn samples (Table 4). As can be seen, the 

significant differences in mean fuel loads occur mostly between treatment 

areas with extreme values and a homogeneous group of treatment areas with 

medial values. There appears to be a correlation between the factor 

season-of-burn and mean fuel load in the results two-year post-burn (Fig. 

4), but this correlation is not corroborated by the results one-year 

post-burn or results from later years (Fig. 4, discussed in detail 

below). Changes in the positions of treatment areas with respect to each 

other suggest that the apparent correlation is an artifact of sampling. 

No correlation is evident between frequency of burn and mean fuel load for 

treatment areas at the same age post-fire. We interpret this as evidence 

that the spatial heterogeneity in fuel loads is randomly distributed with 

respect to both factors in our experimental design. 

Temporal Stability of Fuel Loads 

Our unburned control area (C) allowed us to check on the stability of 

total fuel load with time in the absence of fire. Figure 8 shows 

transformed total fuel load at each sampling period for the unburned area 

(see also Appendix 2). There was evident variability in means at 

different 
times. The significance of this variability was tested using a singleclassification ANOVA with sample period as the variable of 

classification. As shown in Table 5, this test revealed no significant 

differences among samples. 

The fuel load samples tested above were collected during all seasons over 

the course of the six years. The lack of significant differences shows 

that fuel loads in the control plot were at equilibrium (in the sense of 

not changing with time). It also suggests that no significant seasonal 

changes in fuel load occur in Muhlenbergia prairie under conditions of 

equilibrium. 

Effects of Treatments 

Treatment effects were investigated using fuel loads collected two years, 

three years, and six years after the start of the burning cycles in each 

area. These samples were collected at different seasons, but they provide 

the only series of samples for which all of the treatment areas are at 

comparable ages post-fire. Since no evidence was found for seasonal 

changes in fuel loads in the control plot (see above), the differing 

seasons of collection should not alter our results. 

A three-way ANOVA, using season of burn, fire frequency, and year of data 

collection as factors, confirms that significant differences in fuel load 

exist among the treatment areas in the different years (Table 6). As 

expected, fire frequency has the strongest effect, followed by year of 

data collection. Season of burn has a significant but lesser effect. We 

cannot separate season of burn effects from the effect of initial 

inhomogeneities, so it is possible that the apparent effect due to season 

is actually a reflection of site differences. Interactions between 

factors can not be tested since the experimental design is not balanced 

(there is no plot corresponding to a July, six-year cycle burn). 

Two years after the start of the burning, all burned treatment areas were 

at the same stage of post-fire recovery. The total above-ground biomass 

at two years is about two-thirds of that in the control area (Figure 4). 

Identification of homogeneous groupings in this set of data using the 

Duncan multiple range test shows that areas burned in different seasons 

were clustered in a non-random fashion (Table 4). This clustering seems 

to be a reflection of sampling errors and site inhomogeneities rather than 

a true season of burn effect (see Spatial Heterogeneity in Fuel Loads and 

below). 

Three years after the start of the experiment (Fig. 41, the annual burn 

treatment areas had been growing one year since burning. The three- and 

six-year burn areas had all been growing for three years since burning. 

Fuel loads in the annual burn plots were now distinctly lower than fuel 

loads in the three- and six-year areas. Average fuel loads in the threeand six-year areas had not increased much from that found at two years, 

and were still significantly lower than that in the control area. The 

Duncan multiple,range test confirmed the separation of the annual burn 

areas from the others (Table 4). No clustering of treatment areas 

according to season of burn was found in this series of samples. 
In year six of the experiment (Figure 41, the annual burn plots were a 

patchwork of one- and two-year roughs. Roughly half of each annual burn 

plot burned each year with the burned areas usually taking the form of 

long strips through the plot. Three year burn plot had been growing for 

three years since last burned, and six year plots had remained unburned 

for six years. As expected, the annual burn plots had the lowest average 

fuel loads. No difference was found between the average fuel loads in the 

three-year, six-year, or control (sixteen years since last burned) plots 

despite the differences in the period of fuel accumulation able 4). 

An unexpected result of this experiment was the effect frequent burning 

was found to have on Cladium jamaicense, sawgrass. During fuel sample 

collection in year six, it became obvious that Cladium was much less 

abundant than expected in the annual burn plots. A large drop in Cladium 

abundance was recorded between years two and three (Figure 5 and Table 

7). Low levels of Cladium biomass were found again in year six. 

The pattern of Cladium biomass changes shown in Figure 5 is similar to the 

changes seen in total biomass (Figure 41, but Cladium recovery in the 

annual burn plots seems to be proportionately lower than total biomass 

recovery. In year six, total above-ground biomass in the annual burn 

areas was about 352 of the value in the three-year, six-year, and control 

areas. At the same time, above-ground Cladium biomass in the annual burn 

plots was about 20% of the value in the other plots. 

Cladium biomass in the annual burn areas was plotted to look for evidence 

of progressive reduction with time (Figure 6). After the drop in biomass 

between year two and year three, no change was seen from year three to 

year six. The drastic drop in Cladium biomass in treatment area Jl was 

the result of flooding in this treatment area (by Tropical Storm Dennis) 

shortly after the prescribed burn in year two. This flooding submerged 

the regrowing Cladium and killed it. However, no obvious explanations are 

available for the poor recovery of Cladium in treatment areas Dl and F1. 

Phvsical Determinants of Fuel Load 

We studied two physical factors which were expected to affect the 

distribution of plants on a small scale; soil depth and average yearly 

inundation (hydroperiod). The purpose was to see how well we could use 

knowledge of the physical factors to replace the time-consuming direct 

measurement of fuel loads. 

Soil depth seemed to correlate well with fuel load in the field; heavier 

plant growth was found on deeper soils and sparse growth occurred on very 

shallow soils. To check the strength of the relationship quickly, we 

plotted total fuel in a one meter square sample against the median of five 

soil depth measurements made in that square meter. An encouraging 

relationship.was found in only one case (Figure 7). More typical were the 

results shown in Figure 8. The use of mean, as opposed to median, soil 

depths was tried in a few cases and found to give no better results. We 

had to conclude that soil depth could not help predict fuel loads in 

individual meter-square samples. There remained the possibility that fuel 

load was correlated with soil depth over a larger scale, so we sought to 

explain the differences in mean fuel loads between the treatment areas by 
differences in soil depth. To do this, the mean of soil depths for all 

meter-square samples from each treatment area at one year post-burn and 

two years post-burn were plotted against the mean fuel load for that 

treatment area (Figure 9). No relationship was found between soil depth 

and fuel load on this scale either. 

We were also able to investigate the effect of average yearly inundation 

(hydroperiod) on mean fuel loads in the treatment areas. Using methods 

described above, we could estimate the number of days for which 252, 50%, 

and 75% of the vegetation subplots in a given treatment area were under 

water (Table 8). These estimates are crude because local rainstorms can 

alter the relationship between water levels at Taylor Slough Bridge and 

our study site, but the relative hydroperiods of the treatment areas 

should be correctly indicated. If the vegetation subplots provide a. 

representative sample of the treatment area, 50% of the treatment area 

surface will be under water when 50% of the vegetation plots are under 

water. We define a treatment area as flooded when 50% of the subplots it. 

contains are under water, and plot the average number of days per year a 

treatment area is flooded against the mean total fuel load at two years 

post-burn in the area (Figure 10). Mean fuel load within a treatment area 

is positively correlated with the hydroperiod of the area, with a 

correlation coefficient of -825. This correlation is significantly 

different from zero (p less than .005 that the sample could have been 

chosen from a population with a correlation coefficient of zero). It 

appears that a knowledge of the inundation periods in different parts of 

the Muhlenbergia prairie could be useful in determining the spatial 

distribution of mean fuel loads which could lead to improvements in the 

prediction of fire behavior in this vegetation type. 

DISCUSSION 

Fire Behavior and Fuel Buildup 

Since the major aim of the boundary burning program is hazard reduction 

through the reduction of fuel loads, it is useful to determine the rate of 

fuel buildup in Muhlenbergia prairie following a prescribed burn. 

Examples of fuel recovery in our treatment areas are given in Figure 11 

which shows the change in mean total fuel loads with time for treatment 

areas Dl and D3. These graphs are plotted on the same scale to facilitate 

comparison. Figure 11 also shows the mean total fuel loads in the 

unburned control (C) with time for comparison. The buildup of fuel 

following fire is quite rapid in all cases. Total fuel load is near 

pre-burn levels by two years post-burn (Figure 11). 

There is a difference in the patterns of recovery shown by the live and 

dead components of the fuel load. The live component increases even more 

rapidly than the total fuel (see Fig. 12 for an example). It recovers to 

approximately 90% of its pre-burn value within one year. There is a 

slight, but significant, increase in its value during the second year of 

recovery (Table 9). A constant level, presumably reflecting the 

equilibrium value of the site, is reached within the second year. Dead 

fuel increases relatively slowly, and appears to be accumulating steadily 
throughout the first two years post-fire. The difference between mean 

dead fuel accumulations at one and two years post-fire is highly 

significant (Table 9). During the third year post-fire, dead fuel 

accumulation starts to level off. It reaches a constant value (where the 

production of dead fuel is balanced by decomposition) approximately three 

years after burning. Since total fuel load is the sum of live fuel and 

dead fuel, it also reachs a constant value at approximately threesyears 

post- fire. 

Comparing fire behavior in the treatment areas with mean fuel loads, we 

see that fires burned cleanly only when fuel loads were near the carrying 

capacity for the area. It can be seen, further, that the minimum total 

fuel load required to burn this Muhlenbergia prairie area lies between 130 

and 180 gm/m2. Perhaps more relevant is the observation that the minimum 

dead fuel load required to carry a fire lies betz+een 76 and 112 gu/m2. 

Without doubt, the minimum fuel load required to carry a fire depends on 

weather conditions, but the values given above ~r,ovide limits that can be 

used to guide further studies. 

LiveIDead Fuel Relationshiv 

Differing rates of recovery for live and dead fuels leads to a change in 

the ratio of live/dead fuel with tFme post-fire. The significance of this 

cnange and the means of testing differences in the ratios is not clear at 

this time, so only a preliminary discussion is given. First, the use of 

liveldead ratios or proportions in parametric tests is not desirable 

(Green 1979; Sokol and Rohlf 19699). Even if the original variables are 

normally distributed, the distribution function of a ratio or proportion 

is usually not normal. It is more likely to be highly skewed, in fact. 

As an alternative to using these ill-defined variables, it is suggested by 

Green (1979) that regressicn lines between the variables of interest be 

determined, and that tests be r7in on the slopes or coefficients of the 

regression lines. 

The three examples in Figure 13 show that the relationship between live 

fuel and total fuel is reasonably linear, so a regression approach to 

testing hypotheses concerning the proportion of live fuel is possible. 

Also, from Figure 13, it is evident that the slope of the regression lines 

does not change much between sampling periods. In fact, regression line 

slopes'are relatively uniform (with a value near 1) for all treatment 

areas and sampling periods checked. 

A test for uniformity of slopes between regression lines from treatment 

area D6 samples collected in March 1981 and samples from the same area 

collected in May 1981 revealed no significant differences, although these 

particular lines were chosen because their slopes, 1.483 and .870, 

respectively, represented rather extreme differences for our samples. 

Significant differences in the regression slopes on these lines would 

presumably represent differences in the relative rates of net live fuel 

production and net dead fuel production. Such differences might be 

expected to occur in comparisons involving different vegetation types, but 

they appear to be insignificant within our experimental area. From the 

standpoint of fire management practice, live/dead fuel ratios are 
unimportant since they change most rapidly in the first few months 

post-burn. By the time sufficient fuel has accumulated for fire to carry, 

the liveldead ratio has stabilized. 

Hydroperiod and Fuel Load 

The observed correlation between fuel load and average hydroperiod may be 

due to the influence of nitrogen-fixing blue-green algae on nutrient 

cycles in the prairie. It is possible that sites with a longer 

hydroperiod, that is, a longer growing season for the blue-green algae, 

would benefit from a greater overall input of fixed nitrogen into the 

soil. 

Cladium Response to Frequent Burning 

The apparent reduction in Cladium biomass in the annual burn treatment 

areas needs further study. Proportionately lower recovery rates for 

Cladium than other species in the Muhlenbergia prairie may be responsible 

for our observations. If so, the gradual displacement of Cladium by more 

swiftly recovering species would be likely under conditions of frequent 

burning. 

CONCLUSIONS 

1. Above ground biomass data from Muhlenbergia prairie has a log-normal 

distribution and should be transformed if parametric statistical methods 

are to be used for analysis. 

2. Approximately 10 meter-square samples are needed to estimate the logtransformed mean fuel load of a 35 ha area with 10% accuracy. 

3. Mean above-ground biomass values are heterogeneous on the scale of the 

35 ha treatment areas in Muhlenbergia prairie. 

4. Fuel loads in the unburned control area did not change over the six 

years of sampling. There seems to be a constant equilibrium value of fuel 

load for each area of the prairie. Once this value is attained, no 

further significant change in fuel load occurs until the area is burned 

again. 

5. Live fuel recovers quickly, reaching nearly 85% of preburn values 

within one year post-fire. It reaches equilibrium by the end of two years 

post-fire. 

6. Total fuel reaches or approaches equilibrium by the end of the third 

year post-fire. 

7. A two year accumulation of fuel is necessary to carry fire in our 

experimental area. In terms of fuel loads, between 130 and 180 gm/m2 

total fuel or 76 and 112 gm/m2 dead fuel is necessary. 

8. Fuel carrying capacity in a given area is not strongly influenced by 

soil depth. 
9. Fuel carrying capacity in a given area is strongly influenced by the 

hydroperiod of that area. 

10. Frequent burning reduces the above-ground biomass of Cladium 

jamaicense, sawgrass, in Muhlenbergia prairie, and possibly leads to its 

displacement by competing species. 

ACKNOWLEDGEMENTS 

Most of the technicians associated with the Fire Ecology program at 

Everglades National Park spent a great deal of time and effort gathering 

the data upon which this report is based. Jim Craig, Lynette McLamb, and 

Ken Vernick helped set up the permanent plots and collected much of the 

data during the first two years of the study. Later, Todd Steiner, 

Barbara Lenczewski, Donna Blake, Anthony Caprio, and Lewis Sharman 

continued the process of data collection. Their efforts are much 

appreciated. 

Burning of the treatment areas was planned and carried out by the 

Resources Management staff. Phil Koepp was responsible for all burning 

during the first year of the project. Since then, Bob Doren has 

supervised all burns in our experimental area. 
LITERATURE CITED 

Bass, 0. L., and Kushlan, J. A. 1982. Status of the Cape Sable Sparrow. 

Report T-672. Homestead, FL: Everglades National Park, South Florida 

Research Center. 

Bliss, C. I. 1967. Statistics in Biology, Vol. 1. New York, New York: 

McGraw-Hill. 

Everglades National Park. 1977. Fire Management Plan. Homestead, FL: 

Everglades National Park. 

Green, R. H. 1979. Sampling design and statistical methods for 

environmental biologists. New York, New York: J. Wiley. 

Kushlan, J. A., Bass, 0. L., Loope, L. L., Robertson, W. B., Rosendahl, 

P. C., and Taylor, D. L. 1982. Cape Sable Sparrow Management Plan. 

Report M-660. Homestead, FL: Everglades National Park, South Florida 

Research Center. 

Olmsted, I. L., Loope, L. L., and Rintz, R. E. 1980. A Survey and 

Baseline Analysis of Aspects of the Vegetation of Taylor Slough, 

Everglades National Park. Report T-586. Homestead, FL: Everglades 

National Park, South Florida Research Center. 

Sokol, R. R., and Rohlf, F. J. 1969. Biometry. San Francisco: Freeman. 

Taylor, D. L. 1981. Fire History and Fire Records for Everglades 

National Park, 1948-1979. Report T-586. Homestead, FL: Everglades 

National Park, South Florida Research Center. 

Taylor, D. L. 1984. Fire management and the Cape Sable Seaside Sparrow. 

- In Seaside Sparrows, E. Potter, ed. Proc. of North Carolina Biological 

Survey. North Carolina State Museum. 

Werner, H. W. 1975. The Biology of the Cape Sable Sparrow. Report to 

the United States Fish and Wildlife Service. Homestead, FL: Everglades 

National Park. 
Table 1. Designations and treatments for study areas. 

Treatments 

Season of Burned Burned on a Burned on a 

Burning annually 3 year cycle 6 year cycle Unburned .......................................................................... 

DecemberJanuary Burn 

FebruaryMarch Burn 

Juiy Burn J 1 53 - - -- 
Table 2. Estimated number of samples needed from each treatment area to 

detect the tabulated differences in the means between two treatment areas 

with a detection probability of 95% at a significance level of 5%. 

Samples from all treatment areas at the same stage of recovery from 

burning were pooled to determine the overall variability in the fuel load 

data. Log-transformed values of fuel load are used. 

Pooled Group Detectable difference in means 

5% 10% 15% 20% .......................................................................... 

Preburn 5 0 14 7 5 

One year post-burn 38 10 6 4 

Two years post-burn 24 7 4 3 
Table 3. ANOVA tables for test of homogeneity in initial, one year 

post-burn, and two year post-burn mean fuel loads between treatment 

areas. Log-transformed values of total fuel load used. 

Initial fuel loads 

Between Areas 

Within Areas 

Total 

One year post-burn 

Between Areas 

Within Areas 

Total 

Two years post-burn 

Between Areas 

Within Areas 

Total 
Table 4. Homogeneous groupings of the treatment areas with respect to 

mean fuel loads as determined by the Duncan multiple range test (Sokol & 

Rohlf 1969). Groups of means determined to be homogeneous are 

underlined. Log-transformed values of total fuel are used. 

Year one 

Treatment area C F3 D3 F1 J1 F6 Dl D6 53 

Mean fuel load 5.85 5.01 4.97 4.85 4.80 4.79 4.74 4.66 4.43 

Year two 

Treatment area C F3 F1 F6 D3 Dl D6 Jl .I3 

Mean fuel load 5.99 5.65 5.50 5.49 5.45 5.31 5.26 5.20 5.09 

Year three 

Treatment area C 53 D3 F3 F6 D6 F1 Dl J 1 

Mean fuel load 5.80 5.62 5.46 5.41 5.34 5.32 4.70 4.65 4.42 

Year six 

Treatment area D3 C F6 F 3 D6 53 J1 El D i 

Mean fuel load 6.03 5.94 5.89 5.89 5.80 5.69 4.95 4.95 4.93 
Table 5. ANOVA test for homogeneity among collection periods with respect 

to mean total fuel in unburned treatment area (C). Log-transformed values 

of total fuel used. 

Be tween periods 1.39 5 .278 1.43 ns 

Within periods 11.48 - 5 9 .195 

Total 12.84 6 3 
Table 6. Three-way ANOVA of two-, three-, and ~ix-~ear fuel loads in the 

burned treatment areas. Log-transformed values of total above-ground 

biomass were used. 

.......................................................................... Sum of Mean 

Squares DF Squares F .......................................................................... 

WIN EFFECTS 40.50 6 6.75 42.5 

Year 7.90 2 3.95 24.9 

Season 1.59 2 .79 5.0 

Frequency 27.05 2 13.53 85.1 

KES IDUAL 46.08 290 .16 

TOTAL 86.58 296 .29 
Table 7. Homogeneous groupings of treatment areas with respect to 

above-ground Cladium biomass determined by the Duncan multiple range test. 

Year two 

Treatment area C D6 F1 F3 F6 D3 53 Dl J1 

Cladium biomass 4.31 4.21 3.96 3.75 3.73 3.62 3.57 3.50 3.34 

Year three 

Treatment a~ea D6 C F6 F3 D3 53 F1 Dl J1 

Cladium biomass 4.33 4.19 4.03 3.89 3.75 3.45 3.32 2.69 1.61 

Year six 

Treatment area D6 F3 C D3 F6 53 F1 Dl J1 

Cladium biomass 4.88 4.44 4.37 4.35 4.33 4.17 3.41 2.79 1.73 
Table 8. Average number of days per year the listed percentage of 

vegetation subplots in the listed treatment areas were inundated during 

the period 1961 to 1982. 

.......................................................................... 25% of 50% of 75% of 

Treatment subplots subplots subplots 

area inundated inundated inundated .......................................................................... 
Table 9. ANOVA table for test of homogeneity between one year and two 

year post-burn mean fuel for all treatment areas. Log-transformed fuel 

values are used. 

Live fuel 

Among years post-burn .711 1 .711 9.75 

Within years 1.021 - 14 .073 

Total 1.731 15 

Dead fuel 

Among years post-burn 1.956 1 1.956 39.24 

Within years .698 - 14 .050 

Total 2.654 15 
Appendix 

treatment 

of gm per 

1. Above-ground biomass measured in meter square samples for all 

areas and sampling periods. All measurements are given in units 

m2. 

Treatment area C, December 1979 

Sample Total 

Live Dead 

Date 

Dec 78 I I 

Treatment area C, February 1980 

Sample Cladium Other Date 

Live Dead Live Dead 

13 Feb 80 I1 

6 Dec 79 I I 

I I 

13 Feb 80 

Treatment area C, April 1980 

Sample Cladium Other Date 

Live Dead Live Dead 

22 Apr 80 I I 

I I 

I I 

I I 

It 

11 
Appendix 1. Continued. 

Treatment area C, August 1980 

Sample C 1 ad ium 

Live Dead 

Treatment area C, December 1980 

Sample Cladium 

Live Dead 

Treatment area C (unburned), February 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

21 Aug 80 I0 

26 Aug 80 I I 

II 

Date 

10 Dec 80 I I 

18 Dec 80 I I 

I I 

15 Dec 80 I I 

Date 

6 Feb 81 II 

10 Feb 81 I1 
Appendix 1. Continued. 

Treatment area C (unburned), May 1981 

Sample Cladium Other 

Live Dead Live Dead 

Treatment area C (unburned), December 1981 

Sample Cladium Other 

Live Dead 

Treatment area C (unburned), January 1985 

Sample Cladium Other 

Live Dead 

Date 

4 May 81 I1 

I1 

3 May 81 I I 

Date 

29 Dec 81 1 I 

30 Dec 81 1 I 

29 Dec 81 I I 

11 

30 Dec 81 I I 

I I 

Date 

18 Jan 85 11 

I1 
Appendix 1. Continued. 

Treatment area C (burned), May 1981 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Treatment area C (burned), January 1982 

Sample Cladium Other 

Live Dead Live Dead 

Treatment area C (burned), June 1985 

Sample 

v1-1 

Vl-2 

V1-3 

V1-4 

V1-5 

V 1-6 

V1-7 

V1-8 

V1-9 

v1-10 

v1-11 

v1-12 

Cladium 

Live Dead 

Other 

Date 

3 May 81 I I 

I* 

I1 

II 

It 

II 

II 

II 

Date 

6 Jan 82 I I 

Date 

6 June 85 I I 

11 June 85 II 
Appendix 1. Continued. 

Treatment area Dl, December 1978 

Sample Total 

Live Dead 

Treatment area Dl, July 1979 

Sample Cladium Other 

Live Dead Live Dead 

Treatment area Dl, December 1979 

Sarnple Cladium Other 

Live Dead Live Dead 

Date 

Dec 78 i1 

9 Jul 79 11 

Date 

4 Dec 79 11 
Appendix 1. Continued. 

Treatment area Dl, April 1980 

Sample C 1 ad ium 

Live Dead 

Treatment area Dl, August 1980 

Sample Cladium 

Live Dead 

Treatment area Dl, December 1980 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

8 Apr 80 I I 

Date 

8 Aug 80 1 I 

14 Aug 80 

8 Aug 80 11 

Date 

2 Dec 80 11 

3 Dec 80 11 

11 

4 Dec 80 It 

3 Dec 80 11 
Appendix 1. Continued. 

Treatment area Dl, April 1981 

Sample Cladium 

Live Dead 

Treatment area Dl, November 1981 

Sample Cladium 

Live Dead 

Treatment area Dl, December 1982 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

L ive Dead 

Other 

Date 

10 Apr 81 I I 

8 Apt 81 I1 

I! 

1 I 

Date 

30 Nov 81 I1 

I1 

Date 

26 Dec 82 I1 

11 

I I 
Appendix 1. Continued. 

Treatment area Dl, December 1984 

Sample C 1 ad ium Other 

Live Dead 

'Treatment area D3, December 1978 

Sample Total 

Live Dead 

Treatment area D3, July 1979 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Date 

7 Dec 84 I I 

I I 

I I 

I I 

II 

I I 

I I 

11 

11 

I I 

I I 

Date 

Dec ,78 I I 

11 

Date 

10 Jul 79 I I 
Appendix 1. Continued. 

Treatment area D3, December 1979 

Sample Cladium 

Live Dead 

Treatment area D3, April 1980 

Sample Cladium 

Live Dead 

Treatment area D3, August 1980 

Sample Cladium 

L ive Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

4 Dec 79 II 

5 Dec 79 

Date 

15 Apr 80 11 

It 

II 

11 

11 

II 

11 

11 

II 

Date 

4 Aug 80 I1 

II 

Il 

I1 

11 

II 

I1 

11 

I1 

II 

II 
Appendix 1. Continued. 

Treatment area D3, December 1980 

Sample Cladium 

Live Dead 

Treatment area D3, May 1981 

Sample Cladium ' 

Live Dead 

Treatment area D3, December.1981 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

8 Dec 80 I I 

9 Dec 80 I I 

8 Dec 80 I I 

Date 

11 May 81 I I 

I I 

II 

II 

I I 

11 

I I 

II 

II 

It 

I I 

Date 

8 Dec 81 II 

7 Dec 81 It 

II 

I I 
Appendix 1. Continued. 

Treatment area D3, December 1984 

Sample Cladium Other Date 

Live Dead 

5 Dec 84 I I 

Treatment area D6, December 1978 

Sample Total 

Live Dead 

Date 

Dec 78 I1 

Treatment area D6, July 1979 

Sample Cladium 

Live Dead 

Other Date 

Live Dead 

38.4 21.6 12 Jul 79 

17.2 9.1 I I 

31.0 14.3 11 

8.7 15.5 I I 

12.0 12.0 I I 

11.0 10.8 11 Jul 79 
Appendix 1. Continued. 

Treatment area D6, December 1979 

Sample Cladium 

Live Dead 

Treatment area D6, April 1980 

Sample Cladium 

Live Dead 

Treatment area D6, August 1980 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

5 Dec 79 I I 

6 Dec 79 I I 

Date 

24 Apr 83 11 

Date 

6 Aug 80 I I 

II 

I I 

11 

11 

11 

II 

11 

11 

*I 

I I 
Appendix 1. Continued. 

Treatment area D6, March 1981 

Sample Cladium 

Live Dead 

Treatment area D6, May 1981 

Sample Cladium 

Live Dead 

Treatment area D6, December 1981 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

L ive Dead 

Date 

5 Mar 81 I I 

6 Mar 81 

11 

I I 

5 Mar 81 It 

6 Mar 81 I I 

Date 

8 May 81 t I 

I I 

I1 

I! 

II 

11 

II 

11 

. I1 

It 

Date 

23 Dec 81 I I 

II 

28 Dec 81 I I 
Appendix 1. Continued. 

Treatment area D6, December 1984 

Sample Cladium Other 

Live Dead 

Treatment area F1, March 1979 

Sample 

Treatment area F1, August 1979 

Total 

Live Dead 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Date 

3 Dec 84 It 

I1 

I I 

Date 

7 Mar 79 I I 

30 Aug 79 It 

tI 

It 

I I 

I I 

It 

It 
Appendix 1. Continued. 

Treatment area F1, October 1979 

Sample Cladium 

Live Dead 

Treatment area F1, February 1980 

Sample Cladium 

Live Dead 

Treatment area F1, June 1980 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

25 Oct 79 It 

30 Oct 79 It 

Date 

13 Feb 80 I I 

It 

12 Feb 80 I I 

Other Date 

Live Dead 

66.6 25 Jun 80 

30.6 It 

56.0 I I 

79.5 11 

84.2 26 Jun 80 

107.4- I1 

95.8 It 

78.0 25Jun80 
Appendix 1. Continued. 

Treatment area Fl, February 1981 

Sample Cladium Other 

Live Dead Live Dead 

Treatment area F1, June 1981 

Sample Cladium 

Live Dead 

Treatment area F1, November 1981 

Other 

Live Dead 

Sample Cladium Other 

Live Dead Live Dead 

Date 

3 Feb 81 i1 

2 Feb 81 11 

27 Jan 81 I I 

*I 

2 Feb 81 

Date 

10 Jun 81 11 

11 

It 

12 Jun 81 11 

Date 

9 Nov 81 I I 

12 Nov 81 I I 

II 

II 
Appendix 1. Continued. 

Treatment area F1, March 1982 

Sample Cladium 

Live Dead 

Treatment area Fl, February 1985 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Date 

4 Mar 82 I I 

24 Feb 82 I I 

Date 

16 Feb 84 11 

F. I.U. URBAN & REG. DOCS. LIBRARY 
Appendix 1. Continued. 

Treatnent area F3, March 1979 

Sample Total 

Live Dead 

Date 

7 Mar 79 11 

11 

Treatment area F3, August 1979 

Sample Cladium Other Date 

Live Dead Live Dead 

Treatment area F3, October 1979 

Sample Cladium 

Live Dead 

Other 

Live 

Date 

Dead 

31 Oct 79 

11 

30 Oet 79 II 

11 

It 

31 Oct 79 
Appendix 1. Continued. 

Treatment area F3, March 1980 

Sample Cladium 

Live Dead 

Treatment area F3, July 1980 

Sample Cladium 

Live Dead 

Treatment area F3, March 1981 

Sample C 1 ad ium 

Live Dead 

Other 

Live Dead 

Other 

Live ~ead 

Other 

Live Dead 

Date 

21 Mar 80 i1 

12 Feb 80 11 

Date 

15 Jul 80 II 

17 Jul 80 11 

11 

Date 

14 Mar 81 I I 

11 

I I 

15 Mar 81 I I 
Appendix 1. Continued. 

Treatment area F3, July 1981 

Sample Cladium 

Live Dead 

Treatment area F3, November 1981 

Sample C 1 ad ium 

Live Dead 

Treatment area F3, February 1982 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

7 Jul 81 I I 

28 Jun 81 

7 Jul 81 11 

28 Jun 81 11 

7 Jul 81 I I 

Date 

Nov 81 II 

Date 

23 Feb 82 I1 

$1 
Appendix 1. Continued. 

Treatment area F3, February 1985 

Sample C 1 ad ium Other 

Live Dead 

Treatment area F6, March 1979 

Sample Total 

Live Dead 

Date 

11 Feb 85 

I I 

8 Feb 85 I I 

Date 

Treatment area F6, August 1979 

Sample Cladium Other Cate 

Live Dead Live Dead 

46.1 32.2 24 Aug 79 

56.3 27.0 29 Aug 79 

50.6 23.6 II 

50.6 20.4 El 

25.7 57.0 It 

13.4 11.4 I1 

18.3 22.4 I1 

48.6 35.1 II 
Appendix 1. Continued. 

Treatment area F6, November 1979 

Sample Cladium 

Live Dead 

Treatment area F6, March 1980 

Sample Cladium 

Live Dead 

Treatment area F6, July 1980 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live 

Date 

7 Nov 79 II 

I I 

I1 

Date 

Dead 

Other 

L ive Dead 

21 Mar 80 It 

11 

II 

Date 

17 Jul 80 II 

II 
Appendix 1. Continued. 

Treatment area F6, March 1981 

Sample Cladium 

Live Dead 

Treatment area F6, June 1981 

Sample Cladium 

Live Dead 

Treatment area F6, October 1981 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

11 Mar 81 11 

12 Mar 81 I I 

15 Mar 81 I I 

II 

I I 

Date 

12 Jun 81 II 

Date 

27 Oct $1 II 
Appendix 1. Continued. 

Treatment area F6, March 1982 

Sample Cladium Other Date 

Live Dead Live Dead 

V1-1 13.4 37.9 98.7 246.9 ' 24 Mar 82 

V1-2 9.2 31.8 34.0 123.6 II 

V1-3 8.8 50.1 58.5 192.7 11 

V2-1 9.4 26.1 33.0 56.4 I I 

V2-2 16.9 57.7 22.3 63.6 I I 

V2-3 24.3 66.8 22.0 53.9 I I 

Treatment area F6, February 1985 

Sample Cladium Other Date 

Live Dead 

1 Feb 85 I I 

Treatment ar.ea J1, July 1979 .. I 

Sample Cladium Other Date 

Live Dead Live Dead 

V1-1 12.7 16.4 10.8 112.1 13 Jul 79 

Vl-2 38.3 22.4 23.6 62.3 I1 

V1-3 54.9 28.2 22.6 101.6 I I 

V2-1 34.0 34.1 205.5 424.7 11 

V3-1 9.0 16.6 6.9 147.2 11 
Appendix 1. Continued. 

Treatment area J1, November 1979 

Sample Cladium Other Date 

Live Dead Live Dead 

Treatment area J1, March 1980 

Sample Cladium 

Live Dead 

Treatment area J1, July 1980 

Sample Cladium 

Live Dead 

'Other 

Live Dead 

28 Nov 79 II 

II 

It 

II 

I1 

It 

II 

I1 

11 

Date 

30 Mar 80 I1 

II 

I I 

I1 

Other Date 

Live Dead 

4 Jul 80 I I 

I I 

2 Jul 80 II 

I I 

4 Jul 80 II 
Appendix 1. Continued. 

Treatment area J1, January 1981 

Sample Cladium 

Live Dead 

Treatment area J1, February 1981 

Sample Cladium 

Live Dead 

Treatment area J1, July 1981 

Sample C 1 ad ium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

2 Jan 81 

5 Jan 81 

2 Jan 81 

5 Jan 81 

11 

11 

7 Jan 81 11 

11 

11 

11 

11 

Date 

3 Feb 81 11 

11 

11 

11 

11 

11 

11 

11 

Date 

5 Jul 81 1 I 

11 

11 

11 

1 I 

11 

11 

11 

11 

11 

11 
Appendix 1. Continued. 

Treatment area J1, July 1982 

Sample Cladium 

Live Dead 

Treatment area J1, July 1985 

Sample Cladium 

Live Dead 

Other Date 

2 Aug 82 II 

27 Jul 82 I I 

II 

28 Jul 82 I1 

11 

2 Aug 82 I I 

Date 

27 Jun 85 I I 

11 

1 Jul 85 I I 
Appendix 1. Continued. 

Treatment area 53, July 1979 

Sample Cladium 

Live Dead 

Treatment area 53, November 1979 

Sample Cladium 

Live Dead 

Treatment area 53, March 1980 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live 

Date 

13 Jul 79 lt 

11 Jul 79 11 

Date 

25 Oct 79 11 

26 Oct 79 11 

27 Nov 79 11 

11 

11 

Date 

Dead 

30 Mar 80 1 I 

It 

11 
Appendix 1. Continued. 

Treatment area 53, July 1980 

Sample Cladium 

Live Dead 

Treatment area 53, January 1981 

Sample Cladium 

Live Dead 

Treatment area 53, February 1981 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Other 

Live Dead 

Date 

4 Jul 80 11 

16 Jul 80 I I 

Date 

22 Jan 81 I I 

I I 

9 Jan 81 I I 

8 Jan 81 I I 

Date 

4 Feb 81 I I 

I1 

3 Feb 81 I I 

4 Feb 81 1 I 
Appendix 1. Continued. 

Treatment area 53, July 1981 

Sample Cladium 

Live Dead 

Treatment area 53, July 1982 

Sample Cladium 

Live Dead 

Other 

Live Dead 

Other 

Date 

17 Jul 81 11 

12 Jul 81 11 

Date 

13 Jul 82 11 

11 

12 Jul 82 I I 

8 Jul 82 II 

11 

6 Jul 82 11 

II 

I1 
Appendix 1. Continued. 

Treatment area 53, June 1985 

Sample Cladium 

Live Dead 

Other Date 

20 Jun 85 I1 
Appendix 2. Means and variances of log-transformed above ground biomass 

values (fuel loads) obtained in the treatment areas. 

Treatment area C, Unburned 

Date of Number of 

Samples Samples 

Total fuel 

mean 

variance 

Live fuel 

mean 

variance 

Dead fuel 

mean 

variance 

Dec 1978 3 

Feb 1980 10 

Apr 1980 10 

Aug 1980 12 

Dec 1980 12 

Feb 1981 9 

May 1981 11 

Dec 1981 12 

Treatment area C (vegetation plot 11, Burned December 1980 

Date of Number of Months Total fuel Live fuel Dead fuel 

Samples Samples Post-fire mean mean mean 

variance variance variance 

May 1982 9 5 3.5777 3.4311 1.7143 

.0678 .0597 .I874 

Jan 1982 12 12 4.8550 3.8582 4.3949 

.2452 .3313 .2133 
Appendix 2. Continued. 

Treatment area Dl, December-January burn, annual cycle 

Date of Number of Months Total fuel Live fuel 

Samples Samples Post-fire mean mean 

variance variance 

Dead fuel 

mean 

variance 

Dec 1978 3 preburn 5.2983 4.2890 

.2280 .2547 

Jul 1979 8 7 4.1532 3.8462 

.0820 .0844 

Dec 1979 10 12 4.7404 3.7967 

.I162 .2712 

Apr 1980 10 16 5.0213 4.0340 

.2195 .3098 

Aug 1980 12 2 0 4.9662 4.0278 

.0669 -1035 

Dec 1980 12 24 5.3133 4.4626 

.0947 ,1386 

Apr 1981 12 4 3.7668 2.9269 

.Oh72 .0725 

Nov 1981 12 11 4.6659 3.8183 

.r3783 .lo80 

Treatment area D3, December-January burn, 3 year cycle 

Date of Number of Months Total fuel Live fuel 

Samples Si11:iples Post-fire me an mean 

variance variance 

Dead fuel 

mean 

variance 

Dec 1978 .3 preburn 5.9813 4.7607 

.0305 ,0006 

Jul 1979 9 7 4.2477 3.6951 

.0670 .4 244 

Dec 1979 9 12 4.9683 4.1071 

.I426 .I268 

Apr 1980 10 16 5.0195 4.2200 

.0907 .2040 

Aug 1980 12 20 4.8503 3.9339 

.10 10 .0792 
Appendix 2. Continued. 

Dec 1980 12 24 5.4484 4.5321 

-0442 .0630 

May 1981 12 28 5.7311 4.5354 

.0497 .0773 

Dec 1981 12 3 6 5.4035 4.1748 

-1169 .I543 

Treatment area D6, December-January burn, 6 year cycle 

Date of Number of Months Total fuel Live fuel 

Samples Samples Post-burn mean mean 

variance variance 

Dec 1978 3 preburn 5.6597 4.4057 

.3028 .I152 

Jul 1979 6 7 3.9052 3.3880 

.I235 .2267 

Dec 1979 9 12 4.6633 3.7332 

.I350 .2397 

Apr 1980 10 16 4.7678 3.8842 

.lo23 .I911 

Aug 1980 12 20 4.5895 3.7059 

.0689 .093 1 

Mar 1981 12 2 7 5.2613 3.9201 

.0400 .0941 

May 1981 12 2 9 4.9953 3.7503 

.lo18 .I264 

Dec 1981 12 3 6 5.3150 4.0492 

.lo8 1 .I428 

Dead fuel 

mean 

variance 
Appendix 2. Continued. 

Treatment area F1, February-March burn, annual cycle 

Date of Number of Months Total fuel Live fuel Dead fuel 

Samples Samples Post-fire mean mean mean 

variance variance variance 

Mar 1979 3 preburn 5.9590 4.3706 5.7333 

-0005 .0054 .0008 

Aug 1979 8 5 4.1660 3.6985 3.1870 

.I132 .I49 1 -1273 

Oct 1979 6 7 4.7697 4.1792 3.9668 

.I419 .I991 .0999 

Feb 1980 10 11 4.8529 3.9331 4.3439 

-0337 -0764 -0373 

Jun 1980 8 15 5.0123 4.0511 4.5280 

.0613 .0324 .I140 

Feb 1981 12 23 5 -4990 4.1732 5.1757 

-0893 -2633 .0736 

Jun 1981 12 3 4.0259 3.5011 3.0965 

.0922 .I608 .I573 

Nov 1981 12 8 4.5117 3 -9476 3.6627 

.I897 -1393 .3 520 

Mar 1982 12 12 4.7035 3.8256 4.1637 

.I977 .3234 .I342 

Treatment area F3, February-March burn, 3 year cycle 

Date of Number of Months Total fuel Live fuel Dead fuel 

Samples Samples Post-fire mean mean mean 

variance variance variance 

Mar 1979 3 preburn 6.4323 5.0377 6.1390 

-0221 -0934 .0300 

Aug 1979 8 5 4.7161 4.1433 3.8812 

.I548 .2062 -1482 

Oct 1979 8 7 4.9059 4.1961 4.1742 

,0804 -0590 .I336 

Mar 1980 10 12 5.0130 4.2844 4.3437 

-0943 .I355 .0992 
Appendix 2. Continued. 

Jul 1980 12 16 4.9478 4.0527 

.0830 -0949 

Mar 1981 12 24 5.6478 4.4526 

.0959 .I596 

Jul 1981 12 2 8 5.5922 4.3665 

.I356 .I458 

Nov 1981 6 32 5.5310 4.1317 

.0426 .0866 

Feb 1982 12 3 5 5 -4052 4.1449 

.I909 .2068 

Treatment area F6, February-March burn, 6 year cycle 

Date of Number of Months Total fuel Live fuel 

Samples Samples Post-fire mean mean 

variance variance 

Dead fuel 

mean 

variance 

Mar 1979 

Aug 1979 

Nov 1979 

Mar 1980 

Jul 1980 

Mar 1981 

Jun 1981 

Oct 1981 

Mar 1981 

preburn 

5 

8 

12 

16 

24 

27 

3 1 

3 5 
Appendix 2. Continued. 

Treatment area J1, July-August burn, annual cycle 

Date of Number of Months Total fuel Live fuel 

Samples Samples Post-fire mean mean 

variance variance 

Dead fuel 

mean 

variance 

Jul 1979 5 preburn 5.4236 4.0027 

.4205 1.0919 

Nov 1979 10 4 4.0810 3.5481 

.I308 .I130 

Mar 1980 10 8 4.3454 3.4637 

.lo06 .0909 

Jul 1980 12 12 4.7984 4.0879 

.I466 .I588 

Jan 1981 12 18 4.9502 3.8647 

.lo64 .I593 

Feb 1981 9 19 4.9847 3.7671 

.0572 .I200 

Jul 1981 12 24 5.1970 4.2210 

.2 143 .0453 

Jul 1982 2 1 12 4.4307 ---- 

.0878 ---- 

Treatment area 53, July-August burn, 3 year cycle 

Date of Number of Months Total fuel Live fuel 

Samples Samples Post-burn mean mean 

variance variance 

Dead fuel 

mean 

variance 

Jul 1979 8 preburn 5.8570 4.3493 

.0393 .0969 

Nov 1979 10 4 4.0086 3.5321 

.0665 .080 1 

Mar 1980 10 8 4.2087 3.3364 

.I409 .lo72 

Jul 1980 12 12 4.4278 3.7144 

.050 1 .0470 

Jan 1981 12 18 4.8390 3.8823 

.0690 .0954 
Appendix 2. Continued. 

Feb 1981 9 19 4.9403 3.7368 

.0472 .0723 

Jul 1981 12 24 5.0886 4.0993 

.0451 .0478 

Jul 1982 18 3 6 5.6264 ---- 

.0626 ---- 
r'l- L. J Treatment area 

- Mammal plot 

0 - Vegetation plot 

@3 - Tree Island 

TREATMENT CODES 

C - Control 

Dl - December, annual 

D3-December, 3 year 

06-December, 6 year 

F I -February, annual 

F3-February, 3year 

F6-February , 6year 

J I - July,annual 

J3-July,3year 

Figure 1. Base map showing treatment area locations. 

TOTAL FUEL (TRANSFORMED) 

Figure 3. Probit graph of transformed total fuel in meter square 

samples. These demonstrate that the log-transformed fuel 

values follow an approximately normal distribution. 
Figure 

1 I 1 I I I I I I I I I I 1 

CONTROL ONE YEAR THREE YEARS SIX YEARS 

FIRE RECURRENCE RATE 

- 

: 

- 

- 

YEAR3 

i TfT 

I I I I I 1 I I I I I I 

CONTROL ONE YEAR THREE YEARS SIX YEARS 

FIRE RECURRENCE RATE 

)leans and 95% confidence intervals for above-ground biomass samples at 

two-years, three-years, and six-years after the start of the experirnen 
0 I I I I I I I 1 I I I I 

CONTROL ONE YEAR THREE YEARS SIX YEARS 

FlRE RECURRENCE RATE 

Figure 4. Continued. 
0 I I I I I I I I I I I I 

CONTROL ONE YEAR THREE YEARS SIX MARS 

FIRE RECURRENCE RATE 

CONTROL 

I 

ONE YEAR THREE YEARS SIX MARS 

FIRE RECURRENCE RATE 

Figure 5. Means and 95% confidence intervals for Cladium biomass samples at 

two-years, three-years, and six-years after the start of the experiment. 
40 

30 

20 

10 

0 I I 1 1 1 I I 

CONTROL ONE YEAR THREE YEARS SIX EARS 

FIRE RECURRENCE RATE 

Figure 5. Continued. 
igure 6. Change in Cladium biomass with time in the annual burn 

treatment areas. 
260 - 

240 - 

220 - 

-200 - 

<U 

€ 2 180 - 

CI, 

- 160 - 

-J 

W 

140 - 

a 120 - 

F 

0 

I00 - 

80 - 

60 - 

40 - 

I I I I I I I I I 

4 8 12 16 20 24 28 >30 

SOIL DEPTH (Median of 5 Probes) 

Figure 7. Scatter diagram of fuel load in meter square samples plotted 

against soil depth at the sample site. This shows the 

strongedt relationsl~ip between soil depth and fuel load. 
SOIL DEPTH (cm) 

(Median of 5 Probes) 

Ft.gure 8. Scatter diagram of fuel load in meter square samples plotted 

against soil depth at the sample site. This shows a typical 

relationship between soil depth and fuel load. 
AVERAGE SOIL DEPTH 

Figure 9. Scatter diagram showing relationship between transformed fuel 

load and average soil depth in treatment areas. 
Average number of days per 

year 50% or more of the 

area was inundated 

Figure 10. Scatter diagram show-itlg relationship between transformed fuel 

load and average inundation of treatment areas. 
D M J S D M J S D MJ

1979 1980 198

MONTH SAMPLE COLLECTED 

Figure 11. Variation in mean fuel load with time for treatment areas Dl, D3, 




- rERRATA 

On page 23, the table headings were incorrectly placed. 

The page should have appeared as follows: 

Appendix 1. Above-ground biomass measured in meter square samples for all 

treatment areas snd sampling periods. All measurements are given in units 

of gm per m2. 

Treatment area C, December 1979 

Sample Total 

Live . Dead 

Date 

Dec 78 

I I 

11 

,Treatment area C, February 1980 

Sample Cladium Other Date 

Live Dead Live Dead 

580.1 13 Feb 80 

495.1 I1 

708.5 I I 

160.2 11 

85.4 1 I 

108.7 I I 

222.2 6 Dec 79 

138.8 I l 

340.6 I1 

101.7 13 Feb 80 

Treatment area C, April 1980 

Sample Cladium Other Date 

Live Dead Live Dead 

22 Apr 80 I I 

I I 

11 

II 

I1 

II 

I I 

I I 

I1