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orth. entral Research Station. MOFEP Data to Adds to Other Studies -- Coarse Woody Debris Estimation -- Landscape-scale Forest Planning -- Cavity Tree Estimation. Stephen R. Shifley Zaofei Fan Frank R. Thompson III William Dijak David R. Larsen Josh Millspaugh. Michael Larson - PowerPoint PPT PresentationTRANSCRIPT
MOFEP Data to Adds to Other Studies -- Coarse Woody Debris Estimation -- Landscape-scale Forest Planning -- Cavity Tree Estimation
orthentral Research Station
• Stephen R. Shifley• Zaofei Fan• Frank R. Thompson III• William Dijak• David R. Larsen • Josh Millspaugh
• Michael Larson • Martin Spetich• John Kabrick • Randy Jensen • Brian Brookshire,• Laura Brookshire
Harvest Patterns Year 10Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 20Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 30Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 40Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 50Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 60Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 70Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 80Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 90Even-aged harvestingMOFEP sites 7 and 8
Harvest Patterns Year 100Even-aged harvestingMOFEP sites 7 and 8
Wind and Weather DisturbanceWind/weather disturbances Wind/weather disturbances creating crown openings affecting creating crown openings affecting 0.1 to 2.5 ha per event have a 0.1 to 2.5 ha per event have a return interval of approximately return interval of approximately 670 years 670 years
Tornados are a factor, but one we Tornados are a factor, but one we could not simulate spatially with could not simulate spatially with LANDISLANDIS
Fires once were common Fires once were common -- -- Every 5-10 years in 1800’sEvery 5-10 years in 1800’s
With active suppression the mean fire With active suppression the mean fire return interval return interval is now about 300 years.is now about 300 years.
-- Crown fires are rare-- Crown fires are rare-- Prescribed fires can be simulated-- Prescribed fires can be simulated
Initial Age ClassesMOFEP sites 7 and 8 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 10-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 20-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 40-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 60-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 80-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 100-year simulationMOFEP sites 7 and 8
Even-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Initial Age ClassesMOFEP sites 7 and 8 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Initial Age ClassesMOFEP sites 7 and 8
0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 10-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 20-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 40-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 60-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 80-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 100-year simulationMOFEP sites 7 and 8
Uneven-aged harvesting 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 20-year simulationMOFEP sites 7 and 8100-year simulation
No harvest 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 40-year simulationMOFEP sites 7 and 8100-year simulation
No harvest 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 60-year simulationMOFEP sites 7 and 8100-year simulation
No harvest 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 80-year simulationMOFEP sites 7 and 8100-year simulation
No harvest 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 100-year simulationMOFEP sites 7 and 8100-year simulation
No harvest 0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
Age Classes after 100-year simulationMOFEP sites 7 and 8
0- 29 yrs
30- 59 yrs
60- 89 yrs
90-119 yrs
120-149 yrs
150-179 yrs
> 180 yrs
EAM
UAMNo Harvest
Tree size classes - year 100
No Harv.
Even 10%
Uneven 5%
5 km
Ovenbird
Late successional
Edge sensitive
Tree age & Landtype
Pine
Edge
OvenbirdHabitat Model
0.25 km
Ovenbird Habitat Suitability
No harvest Even-age 10%Y
ear
50Y
ear
200
Black bear habitat
• Fall food– Hard mast
• Summer food– Soft mast (tree age & land type)
• Interspersion of food types– Circular moving window
• Road density– Auxiliary map
photo courtesy of Elaine Bindler
Black Bear Habitat Suitability
4 km wide
Habitat model links
Ovenbird
Prairie warbler
Hooded warbler
Pine warbler
Wild turkey
Ruffed grouse
Gray squirrel
Black bear
Bobcat
Red bat
Northern bat
Redback salamander
Could we create a working hypothesis of MOFEP change over the life of the experiment?
• Vegetation pattern• Woody species composition• Volume • CWD• Cavities• Wildlife habitat• …
Cavity tree estimation at multiple spatial scales
Tree level
Stand level
Landscape level
Probability of cavity trees
• Tree level– Live, dead– Dbh– Species group– Decay class if dead
• Stand level
• Landscape level
Probability of cavity trees
• Tree level
• Stand level– Stand age class– Dbh class probability distribution
• Landscape level
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 20 40 60 80 100 120 140 160
Cavity tree density (trees/ha)
Cu
mu
lati
ve
pro
ba
bil
ity
Old growth
Sawtimber
Seedling/sapling
Pole
Fitted Weibull curves of cavity tree density by stand size class
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 20 40 60 80 100 120 140 160
Cavity tree density (trees/ha)
Cu
mu
lati
ve
pro
ba
bil
ity
Old growth
Sawtimber
Seedling/sapling
Pole
Fitted Weibull curves of cavity tree density by stand size class
Probability of cavity trees
• Tree level
• Stand level
• Landscape level– Acres by age class
• Seed/sap, pole, sawtimber, old-growth
Initial efforts were in the SE Missouri Ozarks
DevelopedAgriculturalDeciduousConiferousMixedForested WetlandWaterBarren
N̂
Land use classification, southeast Missouri
Ellington
Bunker
Eminence Clearwater Lake
5,040 sq.. km
80 km
63 k
m
Goal: Develop A Landscape Model• Simulates the impact of various disturbances on forests.
• Predicts the composite impacts (in aggregate) on a landscape composed of numerous forest stands.
• Predicts/contrasts changes in ecosystem attributes that result from alternative disturbance regimes.
1995
20252055
Our Basic Modeling Assumptions
• Vegetation change is relentless.• Vegetation is constantly responding to (recovering from)
disturbance.• To some degree (and to a greater degree than most other
ecosystem components), patterns of vegetation change are predictable.
• The landscape can be divided into ecologically similar units (ECS).
• If we know (or can predict) the vegetation conditions across a landscape at some future point in time, we can say significant things about other ecosystem components.
• Requires a team effort.
This work utilizes the LANDIS model
• Generic framework for simulating landscape change in response to disturbance
• Handles all the basic bookkeeping and mapping• Scaleable pixel size (0.1 ha)• Tracks presence/absence of tree species by age and location• High degree of stochastic variation• Simulates stochastic fire events• Simulates stochastic wind events • Newly completed harvest simulator• Can be calibrated for different forest conditions
Calibration Process for LANDIS
• Identify Land Units• Calibrate species reproduction and survival dynamics based
on life history characteristics– Longevity, shade tolerance, fire tolerance, dominance– Sprouting, age to sexual maturity, seed dispersal
• Calibrate wind and fire disturbance– Simulates stochastic fire events that differ by ELT– Simulates stochastic wind events that differ by ELT
Required Input Maps (raster)
• Land units• Initial vegetation cover and age class
• Additional maps required to simulate harvest– Management areas– Stand boundaries
Harvest Scenarios
• Even-aged management– Clearcut 10% of stands each decade– Oldest first– No adjacency constraints– Fire and wind disturbance turned on
• Uneven-aged management– Group openings averaging 0.2 ha (2 pixels)– Harvest 8% of area in each stand each decade– No adjacency constraints– Fire and wind disturbance turned on
• No Harvest– Fire and wind disturbance turned on
Wind and Fire Disturbance
Wind Fire
Mean return interval 800 yrs 300 yrs
Mean size 1 ha 8 ha
Minimum size 0.1 ha 0.1 ha
Maximum size 20 ha 600 ha
Severity N/ A Low-med
Wind and Fire Disturbance
Wind Fire Mean return interval 800 yrs 300 yrs
Mean Size 1 ha 8 ha
Minimum size 0.1 ha 0.1 ha
Maximum Size 20 ha 600 ha
Severity N/A Low-Med
Output Maps for Each Decade of Simulation
• Vegetation cover
• Vegetation age class
• Fire damage
• Wind damage
• Type and location of harvest
Strengths of This Approach
• Provides the big picture. Great tool to view
large scale forest change
• Compare management alternatives visually
• Analyze projected landscape characteristics
• Compare landscape statistics among
alternatives
• Assess change over time
• Make linkages to other resources
Limitations
• Not suitable for site-specific planning• Probabilistic model (+/-)• Requires GIS capability• Big effort to learn to use it • Requires maps of land units and stands for
most harvest simulations• Needs lots of computing horsepower for big
landscapes
LANDIS Representation of a Site (pixel)
Species 10 year age classes 1 = present, 0 = absent
maple 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
shortleaf 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
black oak 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
white oak 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Number of Snags by Dbh Class
0
5
10
15
20
Dbh (cm)
Tre
es
/ha
Dead O-GDead SEFDead MOFEP
Down Wood Volume
0
10
20
30
40
50
Dark HollowEngelmannSchnabelBig SpringRoaring SinkinMOFEP
Vo
lum
e (
cu.m
/ha)
Down Wood Size Distribution
05
1015
2025
3035
4045
50
10 20 30 40 50 60 70
Dbh class (cm)
Pie
ce
s/h
aSecond-GrowthOld-Growth
Dbh Distribution by Species
2 186 10 14 22 26 2 186 10 14 22 26
60
40
20
Dbh (inches) Dbh (inches)
Shortleaf PineShortleaf Pine
Red OakRed Oak
White OakWhite Oak
Big Spring MOFEP
%
Harvest Patterns Year 10Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 20Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 30Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 40Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 50Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 60Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 70Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 80Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 90Uneven-aged harvesting
MOFEP sites 7 and 8
Harvest Patterns Year 100Uneven-aged harvesting
MOFEP sites 7 and 8