Agriculture Reference
In-Depth Information
their expertise, (2) estimate the time allowed to conduct the sampling, (3) delin-
eate and describe the sample area(s) that need sampling, (4) select an appropriate
sampling unit to get the project done on time and with the people and resources
available, and (5) decide on the equipment required for sampling. This informa-
tion can then be used to design a sampling approach using the following example.
Assume there is a 100-ac treatment unit that will be monitored for changes in fuel
loading and potential smoke emissions and there is only 1 month (20 working
days) to accomplish the initial measurements of the monitoring project. By select-
ing the First Order Fire Effects Model (FOFEM) program to estimate emissions
(Reinhardt et al. 1997 ), the set of surface fuel components that need loading esti-
mates are identified as litter, duff, 1, 10, 100, 1000 h, shrub, and herb (Table 3.1).
A 0.1 ac circular macroplot is selected as the sampling unit because protocols for
measuring all eight surface components and canopy fuels are easily nested in this
FAP. Assuming a two-person crew and a 1-h sampling time to measure loading for
all eight components including travel to the next plot, and assuming 1 h in each
8-h day is used for transportation to and from the site, we can then estimate the
potential number of plots for this project as 140 (seven plots per day, 20 working
days). This means that approximately 14 % of the project area may be sampled for
those fuel components (140 plots × 0.1 ac = 14 ac of 100 ac). Estimates of variabil-
ity for each fuel components obtained from other projects or from the literature
(see Keane et al. 2012b ) can be used to compute the number of plots needed for
a statistically credible sample (see Eq. (8.1) or Lutes et al. 2006 ). The statistical
estimate can be compared with the 140 plots to adjust the design criteria to create
a successful sample design, such as adding more people, increasing sampling time
(work 10 h days, add 10 days), reducing number of fuel components measured,
or modifying the sample design (e.g., distribute plots systematically or among
strata). The last important sampling item to be selected is the surface or canopy
fuel sampling technique to use at each of the plots. The next two sections detail the
diverse methods often employed by fuel specialists to sample fuel characteristics.
8.3
Surface Fuel Loading Sampling
Numerous techniques and methods have been developed to estimate surface fuel
loading for both research and management to allow for greater flexibility in match-
ing available resources with sampling objectives and constraints (Catchpole and
Wheeler 1992 ). These techniques are arranged below in order from easiest to most
difficult with a corresponding gradient from most to least uncertain (Table 8.1 ). The
first set of indirect methods is not recommended, but many fire managers have used
these methods in the past to estimate fuel loadings when no other information is
available and there aren't resources for other alternatives.
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