Using SIMPPLLE in the Thunder-Basin and South Dakota
Grassland – Prairie Ecosystems
Jim Chew – RMRS
Rebecca McFarlan – RMRS
Jon Haufler - EMRI
SIMulating
Patterns and
Processes at
Landscape
scaLEs
Presentation Objectives:
To help understand how we can capture
knowledge with SIMPPLLE
To provide examples of some of the types of
output from SIMPPLLE
Presentation Objectives:
Capturing knowledge with SIMPPLLE
Types of output from SIMPPLLE
For these ecosystems, an initial source of knowledge
will come from:
Will use both the “narrative” and
the “state and transition” diagram
Will use both the “narrative” and
the “state and transition” diagram
This will be adjusted / supplemented by knowledge from
managers, resource specialists, academics
Relationships will go into SIMPPLLE’s
Vegetative Pathways
Relationships will go into SIMPPLLE’s
Vegetative Process logic
Relationships will go into SIMPPLLE’s
Treatment Logic
Relationships will go into SIMPPLLE’s
Regeneration Logic
All of these are separate – but interacting
parts of SIMPPLLE
Vegetative Pathways
Vegetative Process Logic
Treatment Logic
Regeneration Logic
Pathways are organized by an “ecological stratification”
and “species” within it.
A state and transition diagram
doesn’t go into
one SIMPPLLE pathway –
But may be parts of many pathways
Examples from other geographic areas where SIMPPLLE
has been applied.
Montana and North Idaho
Colorado Front Range
Groupings of habitat types
A simplified stratification of landscapes
using elevation.
For the Wyoming ecosystems, pathway stratification
will utilize
For the South Dakota ecosystems, pathway stratification
will utilize
Pathways contain the knowledge of “if” a disturbance
process occurred what would be the “next vegetative state”.
Can’t go from density 3 to
a higher density 4 with
“succession”
Occurrence tied to
“regional climate”
Takes a “wet” time step to
be able to achieve highest
densities
Drier time steps moves
plant communities to lower
densities
For a fire event that replaces an
entire community SIMPPLLE makes
the next state a “temporary” one
until the Regeneration logic identifies
what the new state would be.
This logic is implemented based
on the spatial relationships in each
unique landscape - what each plant
community has as its neighbors and each
species regeneration methods.
Wildlife browsing can be
generalized or made specific
to be bison, grasshoppers, etc.
at varying intensities.
The occurrence of a disturbance process depends on probabilities that
can be based on factors such as:
existing plant community attributes
existing plant community past processes
adjacent community processes
regional climate
Domestic grazing is
a treatment while wildlife
grazing is a disturbance
process
We have to specify the changes
a treatment makes
Can capture spatial relationships
with treatments
Na = found adjacent to a saline site
KEY: all separate – but interacting
parts of SIMPPLLE – provides significant flexibility to
incorporate knowledge from managers, resource specialists,
and academics.
Vegetative Pathways
Vegetative Process Logic
Treatment Logic
Regeneration Logic
Presentation Objectives:
Capturing knowledge with SIMPPLLE
Types of output from SIMPPLLE
Presentation Objectives:
Capturing knowledge with SIMPPLLE
Types of output from SIMPPLLE
historic conditions
future conditions with and without treatments
Following examples taken from Geographic Area #8 from East Side Assessment, Montana
1,500,291 acres
Forested habitat types
Nonforested habitat types
Extreme levels of stand replacing fire occur at intervals greater
than 5 decades, thus a 5 decade representation of historic conditions
could provide too small of a range of variability.
historic long term cycles modeled by
SIMPPLLE
acres
600000
400000
srf
200000
decade
Forested habitat types
36
29
22
15
8
1
0
Extremes of mixed severity fire levels sometimes coincide with
The stand replacing fire, but tend to occur more frequently.
historic long term cycles modeled by
SIMPPLLE
acres
600000
400000
srf
200000
msf
decade
Forested habitat types
36
29
22
15
8
1
0
SPECIES DISTRIBUTION FOR GA8
before a decade of extreme stand replacing fire levels
SPECIES DISTRIBUTION FOR GA8
after a decade of extreme stand replacing fire levels
Thousands of Acres
acres
600000
400000
srf
200000
msf
decade
Forested habitat types
36
29
22
15
8
1
0
WB
AF
WB-AF
ES
ES-AF
LP
historic long term cycles
LP-AF
DF-LP
DF-LP-ES
DF-AF
DF-LP-AF
DF
PP
PP-DF
QA
QA-MC
Xeric-shrubs
Mesic-shrubs
Native -forbs
WB
AF
WB-AF
ES-AF
ES
LP
LP-AF
DF-LP
DF-LP-ES
0
DF-LP-AF
0
DF
100
DF-AF
100
PP
200
PP-DF
200
QA
300
QA-MC
400
300
Mesic-shrubs
400
Native -forbs
500
Upland-grasses
500
Upland-grasses
Thousands of Acres
SIZE CLASS DISTRIBUTION FOR GA8
after a decade of extreme stand replacing fire levels
SIZE CLASS DISTRIBUTION FOR GA8
before a decade of extreme stand replacing fire levels
historic long term cycles
acres
600000
400000
srf
200000
msf
decade
Forested habitat types
36
29
22
15
8
1
0
VLMU
VLTS
VERY-LARGE
LTS
LMU
LARGE
MTS
MMU
VLMU
VLTS
VERY-LARGE
LMU
LTS
LARGE
MMU
MTS
MEDIUM
PTS
PMU
POLE
SS
Closed-herb
Open-herb
Open-tall-shrub
Closed-low-shrub
Open-mid-shrub
0
Open-low-shrub
0
PMU
100
MEDIUM
100
PTS
200
POLE
200
SS
300
Closed-herb
300
Open-herb
400
Closed-low-shrub
400
Open-tall-shrub
500
Open-low-shrub
500
Open-mid-shrub
Thousands of Acres
Thousands of Acres
Thousands
Acres
Comparison of Current and Historic
Range of Variability Simulated for a Decade
Forested Habitat Types
600
500
400
300
200
100
0
hist-qa
cur-qamc
hist-lp
cur-lp
High, low, and median values from 5, 5-decade simulations for current
conditions and 5, 10-decade simulations for historic conditions.
histxericshrubs
Species
cur-xericshrubs
histmesicshrubs
curmesicshrubs
Probability of
occurrence
Current mesic shrubs are below the range of what existed historically. Mesic
Shrubs on forested habitat types varied with fire cycles.
h is t- me s ic - c u r- m e s ic s h ru b s
s h ru b s
Probability of
occurrence
SIMPPLLE quantification of
historic fire
Long term simulation to let disturbance
processes interact to recreate a historic
landscape
FRENCHTOWN FACE - DRAFT EIS
HISTORIC FIRE
OVER 500 YEARS
45000
40000
35000
ACRES
30000
25000
20000
15000
10000
5000
0
0
5
10
15
20
25
30
35
DECADE
LSF
MSF
SRF
40
45
50
Historic Species
simulated by
SIMPPLLE
Historic Species
simulated by
SIMPPLLE
Current Species
Historic condition
derived
From 500 year
simulation starting from
present
Frenchtown Face Total Acres of Fire over 50 Years
6,000
Acres
Comparison of
Total Fire per
Alternative
5,000
4,000
SRF
3,000
MSF
2,000
LSF
1,000
0
Values are
based on
averages from
30 simulations
ALT 1
ALT 2
ALT 5
Alternatives
Frenchtown Face - 50 Years of Fire
100%
90%
80%
Percent
70%
60%
SRF
MSF
LSF
50%
40%
30%
20%
10%
0%
ALT 1
ALT 2
ALT 5
Alte rnative s
HISTO RIC
FRENCHTOWN FACE
Post Treatment - Ponderosa Pine-Douglas-fir Acreage
40,000
35,000
30,000
20,000
15,000
10,000
5,000
0
ALT 1
ALT 2
ALT 5
Historic
Alternatives
Post treatment
Ponderosa PineDouglas-fir (top)
and Ponderosa
Pine (bottom)
acreage after 5
decades, 30
simulations.
FRENCHTOWN FACE
Post Treatment - Ponderosa Pine Acreage
25,000
20,000
Acres
Acres
25,000
Landscape
Comparison of
Alternatives and
Historic conditions
15,000
10,000
5,000
0
ALT 1
ALT 2
ALT 5
Alternatives
Historic
Using SIMPPLLE in the Thunder-Basin and South Dakota
Grassland – Prairie Ecosystems
Jim Chew – RMRS
Rebecca McFarlan – RMRS
Jon Haufler - EMRI
SIMulating
Patterns and
Processes at
Landscape
scaLEs