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Genomics and Applied Biology, 2010, Vol.1, No.1
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Table 3 The estimated mean carbon particulate emissions from the Richland Furnace State Forest in Southern Ohio if all surface fuels
were consumed during a wildfire
Carbon emission component (t/ha)
CO
2
CO
CH
4
Total carbon
emissions (t/ha)
Treatment
Mean
Standard
deviation
Mean
Standard
deviation
Mean
Standard
deviation
Mean
Standard
deviation
50%
stocking
82.24a
50.33
7.79a
4.77
0.37a
0.23
90.39a
55.32
70%
stocking
63.86a
24.49
6.05a
2.32
0.29a
0.11
70.19a
26.92
Control
31.54b
6.98
2.99b
0.66
0.14b
0.03
34.66b
7.67
Note: Lowercases mean followed by the same letter aren't significantly different between forest floor fuels (Duncan's MRT, p=0.05)
and Levan-Green, 2005). Factors that will determine
the type of combustion is fire intensity (temperature),
type of fuel (fine vs coarse), and moisture.
Dead fuels are often categorized into fuel diameter
classes named according to the timelag principle
(Pyne et al., 1996), where small diameter fuels change
rapidly in response to weather changes, while larger
diameter fuels are slower to respond. A timelag is the
time required for a fuel particle to reach 63% of the
difference between the initial moisture content and
the equilibrium moisture content (or equilibrium with
changed atmospheric conditions). The categories are
named for the “midpoint” of the response time of
each fuel category: 1-hour fuels respond in less than
2 hours, 10 hours fuels respond in 2 to 20 hours, 100
hours fuels respond in 20 to 200 hours, and 1 000
hours fuels respond in greater than 200 hours. The
data in this study did not permit the separation of 1
hour fuels from 10 hours fuels. Accordingly, these
two categories were combined in the fuel analysis.
Harvesting created more deadwood fuels overall;
however the total fuel loading is probably not the
best indicator of fire behavior. Higher amounts of
the 1 to 10hours fuels were created as a result of
harvesting even though it was found not to be
significantly higher than the control (table 4). It is
these fuels, commonly referred to as fine fuels,
which will most likely determine fire intensity and
sustainability (Schoennagel et al., 2004). These fine
fuels primarily determine fire behavior and rate of
spread (Anderson and Brown, 1987; Brown and
Davis, 1973; Brown, 1970; Davis, 1959). With the
higher loading of fine fuels in the treatment areas, a
prescribed burn will more than likely be better
sustained through these areas with higher intensity
than a burn in the control. The more open forest
canopy will allow these fuels to dry more quickly
and thus make them more available. Harvesting
created more heavy fuels (100 hours and 1 000
hours) compared to the control (Table 4).
Table 4 The mean fuel loading (t/ha) following harvesting treatments compared to the control by fuel time-lag category in the
Richland Furnace State Forest, Southern Ohio
Fuel time-lag category (h)
1~10
100
1 000
Treatment
Mean
Standard
deviation
Mean
Standard
deviation
Mean
Standard
deviation
50% stocking
25.08 Aa
26.33
15.63 Ab
5.50
13.36 Ab
12.91
70% stocking
23.47 Aa
13.43
13.23 Ab
4.10
5.28 Bc
4.98
Control
14.38 Aa
2.53
4.10 Bb
0.82
2.29 Bb
2.81
Note: The same capital letter is not significantly different between treatments and control within each fuel category; The same
lowercase is not significantly different between fuel categories within each treatment and control (Duncan's MRT, p=0.05)