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MOFEP Data to Adds to Other Studies -- Coarse Woody Debris Estimation -- Landscape-scale Forest Planning -- Cavity Tree Estimation orth entral 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

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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 Presentation

Transcript of orth

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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

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Harvest Patterns Year 10Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 20Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 30Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 40Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 50Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 60Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 70Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 80Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 90Even-aged harvestingMOFEP sites 7 and 8

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Harvest Patterns Year 100Even-aged harvestingMOFEP sites 7 and 8

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Tree size classes - year 100

No Harv.

Even 10%

Uneven 5%

5 km

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Ovenbird

Late successional

Edge sensitive

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Tree age & Landtype

Pine

Edge

OvenbirdHabitat Model

0.25 km

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Ovenbird Habitat Suitability

No harvest Even-age 10%Y

ear

50Y

ear

200

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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

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Black Bear Habitat Suitability

4 km wide

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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

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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• …

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Cavity tree estimation at multiple spatial scales

Tree level

Stand level

Landscape level

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Probability of cavity trees

• Tree level– Live, dead– Dbh– Species group– Decay class if dead

• Stand level

• Landscape level

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Probability of cavity trees

• Tree level

• Stand level– Stand age class– Dbh class probability distribution

• Landscape level

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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

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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

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Probability of cavity trees

• Tree level

• Stand level

• Landscape level– Acres by age class

• Seed/sap, pole, sawtimber, old-growth

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Initial efforts were in the SE Missouri Ozarks

DevelopedAgriculturalDeciduousConiferousMixedForested WetlandWaterBarren

Land use classification, southeast Missouri

Ellington

Bunker

Eminence Clearwater Lake

5,040 sq.. km

80 km

63 k

m

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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

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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.

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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

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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

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Required Input Maps (raster)

• Land units• Initial vegetation cover and age class

• Additional maps required to simulate harvest– Management areas– Stand boundaries

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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

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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

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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

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Output Maps for Each Decade of Simulation

• Vegetation cover

• Vegetation age class

• Fire damage

• Wind damage

• Type and location of harvest

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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

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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

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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

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Number of Snags by Dbh Class

0

5

10

15

20

Dbh (cm)

Tre

es

/ha

Dead O-GDead SEFDead MOFEP

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Down Wood Volume

0

10

20

30

40

50

Dark HollowEngelmannSchnabelBig SpringRoaring SinkinMOFEP

Vo

lum

e (

cu.m

/ha)

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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

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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

%

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Harvest Patterns Year 10Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 20Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 30Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 40Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 50Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 60Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 70Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 80Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 90Uneven-aged harvesting

MOFEP sites 7 and 8

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Harvest Patterns Year 100Uneven-aged harvesting

MOFEP sites 7 and 8