Si P L Problem: Design and Evaluate Fuel Treatment Alternatives at the...

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Problem: Design and Evaluate Fuel Treatment Alternatives at the Landscape Scale
Simulating Vegetative Patterns and Processes at Landscape Scales
SIMPPLLE is a stochastic simulation model that predicts changes
in vegetation patterns over time and space using
interrelationships of fire and other natural processes.
The Modeling Approach
Strategy: Use both stochastic simulation
(SIMPPLLE) and optimization (MAGIS) to plan and
evaluate fuel treatment options. This approach
takes advantage of the strengths of each type of
model system and provides analysis that neither
can provide alone.
Multiple-Resource Analysis and Geographic Information System
MAGIS is a decision support system which optimizes land management and
transportation-related activities on a spatial and temporal basis by resolving
multiple and sometimes conflicting objectives
The Modeling Approach
Schedule of Treatments in Time
and Space
Schedule of Treatments in Time
and Space
MAGIS
SIMPPLLE
Step 2: Develop Fuel Treatment
Scenarios with MAGIS
MAGIS
SIMPPLLE
MAGIS is used to develop four fuel treatment scenarios for the landscape.
Candidate treatments for National Forest stands outside the designated
Wilderness included broadcast burning, mechanical thinning followed by
broadcast burning, precommercial thinning, and several types of
commercial timber harvest. Inside the Wilderness area, the candidate
treatments are limited to prescribed burning without mechanical thinning.
Step 1: Simulate Processes for
‘No Action’ with SIMPPLLE
SIMPPLLE is used to run 20 stochastic simulations over five decades
for the ‘no action’ management alternative with fire suppression. The
natural processes modeled are light and severe western spruce
budworm, mountain pine beetle in both lodgepole pine and ponderosa
pine, root disease, and three intensities of wildfire: light-severity fire,
mixed-severity fire, and stand-replacing fire.
The frequency of
occurrence over five decades for each process is recorded by stand.
Location & Severity of
Disturbance Processes
Issues applying to selected scenarios
Issue
Scn 1
Scn 2
Scn 3
Prescribed Fire in Wilderness
X
X
Minimum Risk, Decade 1
X
X
Minimum Risk, Decade 3
X
X
No New Road Construction
X
X
X
X
Decade Harvest <= 10,000 ccf
X
X
X
X
Step 4: Calculate and Compare
Overall Effects and Costs
Scn 4
In the sample problem, all scenarios reduced the acres of stand-replacing fire
and low-intensity fire, and accordingly reduced the fire suppression costs
over the five decades modeled. However, when the treatment costs and
revenues are included, a net savings in cost relative to “no action” is
predicted for only Scenarios 2 and 4.
Acres of prescribed burning and
Acres
of prescribed
burning and
harvesting
by decade.
harvesting by decade.
Risk Index Map for No Action
12500
Acres of Hiding Cover by Decade from
Treatments and Natural Processes
10000
1 2 00 0
Acres
15000
7500
Discounted Net Cost Including the
Treatment Revenues, Treatment
Costs, and Fire Suppression Costs
1 0 00 0
6 00 0
8 00 0
5 00 0
5000
Acres
2500
0
S cn 1
S cn 2
S cn 3
S cn 4
$ (T hous ) 1
Location & Severity of
Disturbance Processes
6 00 0
4 00 0
R x B u rn , D e c 1
R x B u rn , D e c 3
H a rve s t, D e c 2
R x B u rn , D e c 2
H a rve s t, D e c 1
H a rve s t, D e c 3
2 00 0
4 00 0
3 00 0
2 00 0
1 00 0
0
N o Ac t
Scn 1
Scn 2
Scn 3
Scn 4
0
N o A ct
D ecade 1
D ec a d e 2
D ecade 4
D ec a d e 5
D e c ad e 3
Percent Change in Sediment from
Current Condition, Including both
Treatments and Natural Processes
Risk values
1-2
3-4
5-6
7-8
10
light spruce budworm
>= 50%
mountain pine beetle
>= 50%
stand replacing fire
<= 10%
severe spruce budworm >= 50%
stand replacing fire
11 - 20%
stand replacing fire
>=21%
Step 3: Apply MAGIS Fuel
Treatment Scenarios in SIMPPLLE
to Simulate Processes
The four management scenarios developed by MAGIS are
imported into SIMPPLLE to model the effect of these treatment
schedules on the extent and frequency of natural processes,
and on fire suppression costs. Twenty simulations are run for
five decades for each scenario.
7000
'
5000
A c re s
6000
4000
3000
2000
1000
0
No Act
By J. Greg Jones,
Jimmie Chew, and
Janet Sullivan
Scn 1
L ig h t - s e v e r it y f ir e
s t a n d - r e p la c in g f ir e
Scn 2
Scn 3
Scn 4
m ix e d - s e v e r it y f ir e
25
20
% C ha n g e 1
0
15
10
5
0
N o Act
S cn 1
Scn 2
D ecad e 1
Decade 2
D ecad e 4
Decade 5
S cn 3
Scn 4
Decade 3
S cn 1
S cn 2
S cn 3
Scn 4
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