Fuel Sampling - Wildland Fuel Fundamentals and Applications - page 138

Many other cover sampling techniques, such as relative frequency, could be modi-
fied for certain sampling environments to quantify loading (Lutes et al. 2006 ).
The problem with the modification of cover methods to estimate loadings is that
canopy cover, regardless of how it's measured, may be poorly correlated with fuel
loadings (Catchpole and Wheeler 1992 ). The depth of the litter layer, for example,
is more correlated with loading than litter ground cover. Woody particle diameters,
especially log diameters, are more important for computing loading than their pro-
jected cover. Many of these cover methods provide repeatable estimates with low
bias compared to visual techniques. However, the use of cover methods to assess all
fuel component loadings would not be recommended.
The volume method involves sampling the dimensions of a fuel particle or com-
ponent to compute volume then multiplying volume by particle density or bulk
density to get loading. An advantage of the volume method is that it can be used at
particle, component, and fuelbed scale. Fuel component volume can indirectly cal-
culated as discussed in Sect. 8.3.1.2 where the proportion measured cover (percent-
age cover divided by 100) is multiplied by height (m), sampling area (m 2 ), and bulk
density (kg m −3 ). Hood and Wu ( 2006 ) used the cover-volume approach to calculate
loadings of masticated fuelbeds. Fuel component or particle dimensions can also be
measured to directly estimate volume. Litter loading, for example, can be estimated
by (1) measuring litter depths within a 1 m 2 microplot, (2) computing an average
depth (m), (3) multiplying by sample unit FAP area (1 m 2 ) to calculate volume, and
(4) calculating loading by multiplying volume (m 3 ) by bulk density (kg m −3 ) and
dividing by area of microplot (m 2 ). However, volume can also be used to estimate
the mass of a fuel particle by (1) measuring particle dimensions (length, width, and
depth), (2) estimating a volume by multiplying length, width, and depth, and then
(3) multiplying particle volume by particle density to get dry weight. Loading can
then be calculated by summing all particle dry weights over sample unit (FAP) area.
As mentioned, bulk and particle density estimates for many fuel components can be
found in the literature (Brown 1981 ; Keane et al. 2012b ) or it can be estimated by
destructively sampling a small proportion of the plots.

8.3.2.5 Destructive Sampling

As mentioned, destructive sampling involves removing fuel by clipping and col-
lecting, drying the material, and weighing the dry mass of material. An alterna-
tive is to (1) collect and weigh the wet fuel in the field; (2) subsample that fuel
to dry and weigh to estimate a moisture content, and then (3) use the subsampled
moisture content to adjust the wet field weight to dry weight. Destructive sampling
can be scaled for any sampling design or objective. Fuel particles can be collected
individually, as a group (shrub or tree), or on FAPs. Destructive sampling almost
always involves subsampling a fuel component or fuelbed so statistical methods are
often required to summarize subsampled estimates to describe the sampling area.
Often, destructive sampling is used to create predictive biomass equations for a fuel
component or entity, such as a tree or shrub. This predictive equation can then be