1 yield implications of variable retention harvesting vr team: mario di lucca, ken polsson, jim...

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1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches B. C. Ministry of Forests, Victoria Western Mensurationist Meeting Victoria, July 3, 2003

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Page 1: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Yield Implications of Variable Retention Harvesting

VR Team: Mario Di Lucca, Ken Polsson,

Jim Goudie, and Tim Bogle

Research & Timber Supply BranchesB. C. Ministry of Forests, Victoria

Western Mensurationist Meeting

Victoria, July 3, 2003

Page 2: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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In the Fraser TSA

From a Timber Supply Perspective

Page 3: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Variable Retention (VR)Impacts on Sustainable Harvest Levels

• Will VR reduce harvest levels?• If so, by how much?• What are the ecological merits of aggregated vs. dispersed retention?• What are the G&Y impacts?• What are the economic implications?

Page 4: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Variable Retention (VR)• Background

– J. Franklin (UW) “New Forestry”– Clayoquot Scientific Panel (1995)– Weyerhaeuser (1998) &– TASS simulations - Goudie (1998)

• Timber supply analysts request VR volume estimates for the Fraser TSA

• Research Branch develops tools to predict VR yields of:– regenerated stands– excluding retained trees

Page 5: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Strip shelterwood Uniform shelterwood

Group retentionTraditional clearcut

Retained stand age 100 years - Regenerated stand age 10

TASS Simulations (Goudie, 1998)Weyerhaeuser

Page 6: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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1. Simulate Actual Site

TASSTASSCutblockVariables

VRYield Curves

TSRTSR

Methods to Estimate Variable Retention Yield Curves using TASS

Page 7: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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1. Simulate Actual Site

TASSTASS

TSRTSR

CutblockVariables

VRYield Curves

TSRTSR

CutblockVariables

TASS TASS VRAFFunction

TIPSYTIPSY

2. Derive Relationships

VRYield Curves

SimulationVariables

Methods to Estimate Variable Retention Yield Curves using TASS

Page 8: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Method 1. Simulate Actual Site in the Fraser TSA

TASS layout

60 years old cutblock

after VR harvest

Page 9: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Cutblock Statistics(ArcInfo)

Cutblock area: 31.02 haRetention area: 4.38 ha

(15 groups ranging from 0.05 to 2.1 ha)Percent retention: 14%Perimeter or edge retained: 111 m/ha

Page 10: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS Simulations

Simulate VR cutblock scenario:• Plant: 4444 trees/ha Fd on site 35 (age 0)• Grow to: age 60• Harvest to mimic cutblock layout• Plant: 1400 Cw trees/ha• Grow to: age 160 & harvest

Simulate comparable clearcut scenario & calculate:VRAF = VR vol/Clearcut vol = 0.82 (age 100)

Page 11: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF 14% Retention Regenerated Stand Yields

0

400

800

1200

1600

2000

2400

0 20 40 60 80 100 120 140 160 180

Stand Age (years)

Me

rch

Vo

lum

e

Previous Stand

Average Reduction1.00

0.83Clearcut VR

Clearcut vs. Regenerated (VR) Yields

Page 12: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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• Matrix of TASS simulations• Select important variables &• Derive VRAF equations:

VRAF(sp) = f (edge, % retention, SI, overstory age or height, etc.)

Method 2. Derive Relationships

Page 13: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Method 2. Derive Relationships

Matrix of TASS simulations (1107 runs):• Site Index: 25, 30 & 35• Harvest ages: 70, 130 & 200 years• Retention level: 10, 20 & 30%• 15 rectangular group sizes: 0.01 to 4 ha• Number of groups: 1 to 9• 27 dispersed tree regimes: 20 to 240 trees/ha

Constants:

• Original stand: 5000 trees/ha FDc natural • Regenerated stand: 1200 trees/ha planted &

600 trees/ha natural • Retained groups: rectangularity of 1:6.25

Page 14: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Run 1: 1 group - 1.5 ha

(15 ha)

Run 2: 152 groups - 0.01 ha

(1 ha)

Run 3: 718 groups (trees) - 0.0015 ha

(1 ha)

Partial matrix of TASS simulationsSI 30, Overstory age 70 & 10% Retention

Page 15: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Regenerated Merch Volume10% Retention

0

200

400

600

800

1000

10 20 30 40 50 60 70 80 90 100 110 120

Age

Merc

h V

ol

Clearcut

Variable Run 1 Run 2 Run 3No. groups 1 152 718Group Size (ha) 1.5 0.01 0.0015Average Yield Reduction 0.911 0.729 0.718

152 groups 718 groups

Partial matrix of TASS simulations

1 group

Page 16: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF 10% Retention

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

10 20 30 40 50 60 70 80 90 100 110 120

Age

VR

AF

Clearcut

1 group

152 groups718 groups

Avg. Yield Reduction

Partial matrix of TASS simulations

1.00

0.91

0.72

0.73

VRAF = VR volume/Clearcut volume

Page 17: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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• Matrix of TASS simulations• Select important variables &• Derive VRAF equations:

VRAF(sp) = f (edge, % retention, SI, overstory age or height, etc.)

Method 2. Derive Relationships

Page 18: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Select important variablesto estimate VRAF using TASS

• Species & Site Index • Overstory retained stand:

Edge length > f (group shape, size & number)

% retentionTop height /age

• Regenerated stand:Top height

Page 19: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Edge Effect

Uniform shelterwood(69/ha)

Strip shelterwood(1/ha)

Group retention (1/ha)

Traditional clearcut Group retention (4/ha)

Group retention (9/ha)

Retained stand age 100 years - Regenerated stand age 10

0 m edge 118 m edge 235 m edge

200 m edge 910 m edge352 m edge

No trees will grow under the overstory canopy (black areas)TASS Simulations (Goudie, 1998) of Weyerhaeuser treatments

Page 20: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF declines (< 1.00) as:

• Edge length increases by:– increasing number of groups

– decreasing group size

VRAF as affected by edge length, no. & group size

VRAF Douglas-fir SI 30 @ age 100 10% retention

0.60

0.70

0.80

0.90

1.00

0 100 200 300 400 500 600 700 800Length of Edge (m/ha)

Run 3: (718 Groups)

Run 1: (1 Group)

Run 2: (152 Groups)

Page 21: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF as affected by % Retention & Overstory Age

VRAF Site Index 35

0.4

0.5

0.6

0.7

0.8

0.9

1

10 20 30

Percent Retention (%)

VR

AF

Age 70 Age 130 Age 200

VRAF declines (< 1.00) as:

• % retention increases

• overstory age decreases

Page 22: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF as affected by Site Index & Overstory Topht

VRAF 20% Retention

0.6

0.65

0.7

0.75

0.8

20 30 40 50 60 70

Overstory Topht (m)

VR

AF

SI 25 SI 35SI 30

VRAF declines (< 1.00) as:

• SI increases

• overstory top height decreases

Page 23: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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• Matrix of TASS simulations• Select important variables &• Derive VRAF equations:

VRAF(sp) = f (edge, % retention, SI, overstory age or height, etc.)

Method 2. Derive Relationships

Page 24: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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10%

20%

30%

Page 25: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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VRAF Segmented Regression Function

VRAF = 1- (b * Edge + c * (Edge - x0) * d1 + f * (Edge - x1) * d2)

1st Slope: b = b0 + b1 * SI + b2 * retht + b3 * perc + b4 * tophtSlope change: c = c0 + c1 * SI + c2 * retht + c3 * perc + c4 * topht

2nd slope change: f = f0 + f1 * SI + f2 * retht + f3 * perc

Where:Edge = Edge length (m/ha)SI = Site indexRetht = Overstory top heightPerc = % retentionTopht = Regenerated top height

Page 26: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Fitted VRAF Function

VRAF Douglas-fir SI 30 @ age 100 10% retention

0.60

0.70

0.80

0.90

1.00

0 100 200 300 400 500 600 700 800Length of Edge (m/ha)

R2 = 0.993

Page 27: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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10%

20%

30%

Retention

Page 28: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Percent retention: 14%Edge length: 111 m/haOverstory height: 30 mOverstory age: 60 yrs.

TIPSY ver. 3.2

VRAF = 0.83

Fraser TSA Cutblock

Page 29: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Variable retention vs. clearcut yields & value at age 60

Treatment Merch. Volume Site Value m3/ha $/ha

Variable Retention 728 1514Clearcut 873 3181Difference -145 -1667

VRAF = 0.83

Page 30: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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CCCrown Cover % vs. Basal Area %

SI 30

05

101520253035

0 5 10 15 20 25 30

Basal Area (%)

Cro

wn

Co

ver

(%) Overstory Age

70130 200

CC % = b * ba ** c

Where: b = b0 + b1 * rethtc = c0 + c1 * SI

Page 31: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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0

20

40

60

80

100

120

140

0 5 10 15 20 25

decades from now

harvest ('000s

Assume clearcut with WTP reserves

VR accounting for area loss

VR accounting for area loss and regenerated volume impact

Variable Retention Harvesting Effects on Timber Supply

Page 32: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Variable Retention Summary

VRAF declines (< 1.00) and the relative yield of regenerated stands decreases as:

top height/age of overstory trees

% retention edge length SI top height of regenerated trees

Page 33: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Variable Retention Summary

The primary factor affecting VRAF is:

the amount and distribution of the

retained trees which will compete for the regenerated growing space

Page 34: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Current & Future Development

• incorporate VRAF into TIPSY

• address other species

• model impact of windthrow & pests

• incorporate VRAF into TASS III which

is linked to a light model

Page 35: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS with and without light model

TASS II

TASS III

Page 36: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS with and without light model

TASS II

TASS III

Page 37: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS with and without light model

TASS II

TASS III

Page 38: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS with and without light model

TASS II

TASS III

Page 39: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS II vs TASS III Aggregated Retention

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40

% Aggregated Retention

VR

AF

TASS III

TASS II

Page 40: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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TASS II vs TASS III Dispersed Retention

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40

% Dispersed Retention

VR

AF

TASS II

TASS III

Page 41: 1 Yield Implications of Variable Retention Harvesting VR Team: Mario Di Lucca, Ken Polsson, Jim Goudie, and Tim Bogle Research & Timber Supply Branches

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Questions?