fire history of the australian alps references · powerpoint presentation . clarke, w. b. ......
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- REFERENCES
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114
APPENDIX I
Estimating Pre-Record Bushfire Frequency
Early European Period
A very conservative estimate was made of the frequency of fire for the Kosciuszko
National Park for the early European period as follows:
• NPWS (2003) have recorded 157 definite lightning ignited fires within
Kosciuszko National Park for approximately the period 1960 to 2000, giving an
average of 4 lightning fires in a given year. These records are incomplete due to
the difficulty in determining an exact cause of ignition for many fires. Ignition
causes are known in this period for approximately 60% of fires, so assuming the
proportion of ignition causes is representative of the Park in general, it is probable
that the actual number of natural fires in KNP is on average actually 6 fires per
annum.
• Assuming no other ignition causes (a highly improbable assumption but necessary
due to the lack of data), and assuming that the quoted figure (Luke 1961) of
‘burning off’ in NSW being the cause of 8 fires for every natural fire was
representative of KNP during this earlier period; the average number of bushfires
in KNP during this period was probably about 50 fires per annum.
This can be given as:
F = FN . RH
Equation 1
Where F is the number of fires occurring in a year, FN is the number of fires that
occur in a year due to natural (non-human) ignitions, and RH is the ratio of human
ignitions to natural ignitions.
Aboriginal Management Period
As stated in the chapter examining Aboriginal fire management in the Alps, all
available dendrochronological evidence on the subject points toward a total (planned th th
and unplanned) fire frequency between 1/5 and 1/7 that of the average fire
frequency during the early European period. Using the estimates given above, this
places fire frequency during Aboriginal management as being in the range of 7 to 10
fires per annum. Considering that the recorded history of lightning strikes averages
about 6 fires per annum, this would suggest that intentional burning produced less
than 5 fires in KNP each year. Although the oral tradition for the area indicates that
great care was taken with fire, it is possible that with large numbers of groups
camping throughout the mountains, some of these fires were also unplanned events
resulting from escaped campfires, signals or other domestic fire uses.
The accuracy of this figure is reliant upon the accuracy of the early-European
frequency estimate, and the degree to which the recorded areas of fire scarring
represent the whole of the mountains.
115
APPENDIX II
The Historical Influence of Fuel Age on Fire
Extinction in the Australian Alps
Methods
ArcView GIS data (NPWS 2004) was interrogated to identify all unplanned fires in
the records for Kosciuszko National Park and its immediate surrounds that either
burnt through or into land that had already been burnt within the preceding 15 years.
Every contact with previously burnt land was then given a classification as to whether
the edge of the unplanned fire had stopped or been stopped within the burnt area, or if
it had burnt through. Where the fire appeared to have stopped within the burnt area, it
was classed as ‘effective’, and where it had burnt through it was classed as ‘not
effective’. The criteria used to decide this more precisely are given in Table 1, and an
example of each is given in figure 1.
The effectiveness of each fuel age was calculated according to:
E = NE / N
Equation 1
Where E is the effectiveness of that fuel age class, NE is the number of effective burnt
areas, and N is the total number of burnt areas encountered in that age class.
There are many other factors aside from fuel age that may have influenced the final
burnt area boundaries; for instance a fire may have been stopped within a prescription
burnt area not because the area provided any reduction in fire intensity, but because
additional resources were employed in that area for protection of assets. Alternatively
a fire may have burnt completely through an area of young fuels at very low intensity,
but had not been stopped in that area because it provided no strategic advantage.
Mapped fire boundaries are also limited in accuracy by the priorities in fire
suppression or recovery at the time of mapping, and some areas may have been
mapped as burnt by the unplanned fire when they were not. In order to account for
this, the study was carried out considering the correlation between % effectiveness
and the fuel age of:
a) all previously burnt areas within 15 years
b) only burnt areas >= 20 Ha
c) only burnt areas >= 100 Ha
d) only burnt areas >= 500 Ha
The study showing the strongest correlation between E and fuel age was used to form
a linear function describing the effect of fuel age on E.
116
TABLE 1. Criteria used to decide the effectiveness of burnt areas in fire suppression.
An area was considered effective if:
a) An unplanned fire has burnt into the previously burnt area and that part of the
front has stopped within its boundaries (figure 1)
b) An unplanned fire has burnt through a previously burnt area but has stopped
at a control line such as a watercourse or road bounding the other side of the
burnt area. This allows the possibility that the younger fuels reduced the
intensity of the fire so that the control line was able to hold it.
c) An unplanned fire has started within a previously burnt area, but not burnt a
final area greater than 1 Ha.
d) An unplanned fire has burnt up to the edge of a previously burnt area and
stopped at that point rather than entering. The exception to this is if contact
with the burnt area was prevented by a road, waterbody or some other control
line, or if evidence suggests that the previously burnt edge was the source of
ignition and the unplanned fire burnt away from it.
An area was considered not effective if:
a) An unplanned fire has burnt through it and come out the other side (figure 1)
b) An unplanned fire has burnt into it and stopped, but fire suppression records
show that back-burning was used as a containment strategy at that point rather
than relying on the potential reduced intensity provided by the younger fuels.
c) More of the unplanned burn has burnt within the block than outside of it
Tests for Significance
Fuel age classes were grouped to analyse statistically significant difference between
“old” and “young” fuels. Comparison between
a) 1-2 y.o. and 8-15 y.o. fuels
b) 1-2 y.o. and 3-7 y.o. fuels
c) 1-3 y.o. and 9-15 y.o. fuels
d) 1-3 y.o. and 4-8 y.o. fuels
e) 1-5 y.o. and 10-15 y.o. fuels, and
f) 1-8 y.o. and 10-15 y.o. fuels
Tests were carried out for burnt blocks >=100 Ha and blocks >= 500 Ha. Analysis
was performed using an unpaired Student’s t-test.
117
Figure 1. The area of 1 year old fuels t hat nearly spans t he 1964 Ravine Fire was ineffective in preventing its
south-east spread despite the fact that it was 5 km deep and 5648 Ha in size. Part of the south-eastern spread of the
fire was however halted in another area of both 1 year old and 3 year old fuels.
118
Results
Results for burnt areas >= 100 Ha and >= 500 Ha are given in tables 2 and 3 below,
and the effectiveness summary for all sized blocks is given in table 4 along with the
coefficient of correlation ρ. The results of Table 3 are given graphically in figure 2.
TABLE 2. Effectiveness of fuel age in fire suppression considering only burnt areas >=100 Ha
Fuel age class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Number 'Effective' 9 8 7 3 7 0 8 3 4 6 2 2 8 3 3
Number 'Not
Effective'
10 10 6 4 5 5 8 2 9 5 6 6 7 6 7
Number Samples 19 18 13 7 12 5 16 5 13 11 8 8 15 9 10
% Effective 47% 44% 54% 43% 58% 0% 50% 60% 31% 55% 25% 25% 53% 33% 30%
TABLE 3. Effectiveness of fuel age in fire suppression considering only burnt areas >=500 Ha
Fuel age class 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Number 'Effective' 8 5 6 3 4 0 8 2 3 5 2 1 6 1 3
Number 'Not
Effective'
8 9 5 4 4 1 7 1 6 4 4 5 7 5 7
Number Samples 16 14 11 7 8 1 15 3 9 9 6 6 13 6 10
% Effective 50% 36% 55% 43% 50% 0% 53% 67% 33% 56% 33% 17% 46% 17% 30%
Impact of Time Since Fire on
the Extinction Likelihood of Unplanned Fire Events
E
xti
nc
tio
n l
ike
lih
oo
d
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
36%
55%
43%
50%
53%
67%
33%
56%
33%
17%
46%
17%
30%
50% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
0% Fuel age
Figure 2. The impact of Burnt areas >=500 Ha in extinction likelihood
119
TABLE 4. Effectiveness of fuel age in fire suppression as affected by the size of the burnt area.
Min Fuel 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 ρ burnt Age
area Class
(Ha)
0 48% 40% 33% 22% 26% 25% 50% 36% 28% 60% 23% 22% 41% 25% 27% -0.22
20 45% 42% 37% 31% 45% 29% 44% 56% 41% 62% 30% 27% 50% 30% 30% -0.17
100 47% 44% 54% 43% 58% 0% 50% 60% 31% 55% 25% 25% 53% 33% 30% -0.26
500 50% 36% 55% 43% 50% 0% 53% 67% 33% 56% 33% 17% 46% 17% 30% -0.32
The results of the Student’s t-test for the different age categories taken from blocks >=
100Ha are given in Table 5, and for blocks >= 500 Ha, Table 6.
TABLE 5. Student’s t-test results for fuel age categories using blocks >=100Ha in area
Group 1 Group 2 Mean 1 Mean 2 Variance 1 Variance 2 Significance
1-2 yrs 8-15yrs 45.5% 39.0% 4.5% 209.4% N.S.
1-2 yrs 3-7 yrs 45.5% 41.0% 4.5% 556.0% N.S.
1-3 yrs 9-15 yrs 48.3% 36.0% 26.3% 160.3 90%
1-3 yrs 4-8 yrs 48.3% 42.2% 26.3% 602.2% N.S.
1-5 yrs 10-15 yrs 49.2% 36.8% 42.7% 186.6% 95%
1-8 yrs 10-15 yrs 44.5% 36.8% 361.7% 186.6% N.S.
TABLE 6. Student’s t-test results for fuel age categories using blocks >=500Ha in area
Group 1 Group 2 Mean 1 Mean 2 Variance 1 Variance 2 Significance
1-2 yrs 8-15yrs 43.0% 37.4% 98.0% 317.4% N.S.
1-2 yrs 3-7 yrs 43.0% 40.2% 98.0% 525.7% N.S.
1-3 yrs 9-15 yrs 47.0% 33.1% 97.0% 203.1% 90%
1-3 yrs 4-8 yrs 47.0% 42.6% 97.0% 643.3% N.S.
1-5 yrs 10-15 yrs 46.8% 33.1% 54.7% 243.8% 90%
1-8 yrs 10-15 yrs 44.2% 33.1% 400.5% 243.8% N.S.
Great variation was shown between individual age classes (not grouped), with 8 year
old fuels being effective most often, and 6 year old fuels having never been recorded
as effective. As it is unrealistic to expect that there would be such difference between
these two age classes, the class groupings provided a valuable comparison.
Similar trends were apparent in the studies of both the blocks 100Ha and greater and
the blocks 500Ha and greater. Examination of grouped fuel age classes showed that in
all groups blocks were effective less than half the time, that is, fire burnt through
those blocks more often than it stopped or was stopped within them. 1 and 2 year old
fuels showed no significant advantage over either 3 to 7 year old or 8 to 15 year old
fuels. Both 1 to 3 year old and 1 to 5 year old fuels showed slightly significantly
greater effect than older fuels (9 to 15 and 10 to 15 years old).
120
Linear Regression
Linear regression of the data for burnt areas >=500 Ha gave a likelihood of
suppression effectiveness within a burnt area based on fuel age as:
E = -0.01Tf + 0.49, where 1 <= Tf <= 15
Equation 2
Where E is the likelihood of fire extinction within the burnt area, and Tf is the age of
the fuels in years.
Discussion
The study demonstrates that fuel age has had an impact on fire extinction in the Alps,
albeit a small one. The strongest correlation was that between fire extinction and age
of burnt areas >=500 Ha, although using the value of ρ 2 this only accounted for 10.4%
of the suppression effectiveness. Results however demonstrate that there is a slight
advantage in fuels less than 5 years old, suggesting that there is nearly a 1 in 2 chance
of fire extinction in such fuels, compared to a 1 in 3 chance in fuels 9 to 15 years old.
Even in the youngest fuels, fire in KNP has been more likely to pass through the burnt
area than stop or be stopped within its bounds, and the variability suggests that 90%
of the effectiveness in suppression is due to factors unrelated to fuel age. It is probable
that this variability relates to suppression activities, ambient weather and long-term
climatic conditions, and the response of different plant communities to fire of
different frequencies. If this last factor is the case, some vegetation types will show
greater rates of fire extinction at low fuel ages than this study suggests, where others
will show significantly less.
References
NPWS (2004). Snowy Mountains Region fire history database. Unpublished
GIS database
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APPENDIX III
Estimating Pre-Record Bushfire Extent
“Bushfire extent” here refers to the regularity of fire events of a particular size. The
indicative size used here is fires of 100,000Ha or larger. Such events are very rare,
and as explained in the main text rely on a confluence of events, the main limiting
factor being that of multiple, widespread ignitions. In the recent 40 – 50 years of
recorded fire history, such an event has only occurred once (2 simultaneous fires in
2003), and there are no other records of comparable natural ignition patterns.
Natural events such as bushfires and floods occur with a definable statistical
probability. Terminology such as a “one in one hundred year flood” refers to the size
of the flood that could be expected to occur on average every 100 years. It is of
course possible that such floods may occur in 2 consecutive years, but the likelihood
is very low (1 chance in 100). The likelihood can then be said to increase with every
year that goes by without such a flood. Such classifications are meaningful when
averaged over a long period of time, and are useful for characterising historical
periods.
The obvious difference between floods and fires is that fires have a residual effect
upon the landscape that affects the probability of future fires. The removal of fuels by
burning reduces the likelihood and potentially the spread of fires until those fuels
have re-accumulated. Similarly, an imposed fire regime that acts to increase fuels can
increase the likelihood and spread of fires for an area. This is discussed in detail for
the Alps in Appendix II. When considering fires, the incidence of a fire occurring
increases with the area being studied.
A statistical estimate of the frequency or return period per Ha (RPHa) of a 100,000 Ha
or larger fire can be made using the following data:
a) p - The current probability of such a fire
b) f- The frequency of bushfires for the period in question
c) E - The likelihood of fire to extinguish in fuels of a given age
d) Tf - The average age of the fuels for the period and area being examined
e) α - Adjustment factor to correct for the difference in average fuel age
compared to present day conditions
f) A – The area within which data was collected (Ha)
As given in Appendix II, E (probability of extinction) can be found from Tf according
to:
E = -0.01Tf + 0.49
Equation 1
Where 1 <= Tf <= 15. A value of 0.3 can be assumed for Tf vales greater than 15.
The return period per Ha RPHa can then be found using the relationship:
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A RPHa =
pf (1− Eα ) Equation 2
The return period RP for a study area of S Ha can then be found according to:
RP RP = Ha
S Equation 3
Estimates for the Early European and Aboriginal Management Periods.
Using the above process, the return period of a 100,000 Ha fire can be calculated for
the Alps as follows:
Analysis of NSW and ACT records for bushfire occurrence in the Alps since regular
records have been kept reveals that for the period 1959 to 2003, 1467 fires were
recorded within the total park area of 805,800 Ha. Of these, only 2 fires exceeded
100,000 Ha, both produced by the same lightning event in 2003. This gives a
probability of 2/1467 or
p = 0.0014. Also:
A = 805,800 and
S for the entire Alps = 1,611,660 Ha
For the early European period:
f was estimated in Appendix I to be 50
Tf was found from fire scar records to be 3.5
E (from Appendix II) for fuels 3.5 years old = 0.448
Giving RPHa = 18,672,160 years
And a value of RP for the Alps of 12 years.
For the Aboriginal Management period:
f was estimated in Appendix I to be 10
Tf was found from fire scar records to be 25
E (from Appendix II) = 0.3
Giving RPHa = 78,384,690 years
And a value of RP for the Alps of 49 years.
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