Biophysical vs. Social Availability of Wood in the Northeastern 

U.S.

Brett J. Butler, Marla Lindsay, Paul Catanzaro, David Kittredge, 

Zhao Ma, and Tom Stevens

Woody Biomass Energy Research SymposiumApril 28‐30, 2011  Burlington, VT

Conclusions

1. Social constraints are more important than biophysical constraints

– Especially owners’ attitudes and size of holdings

2. Hypothetical participation rate in Massachusetts is low

– Most influenced by harvest plans, attitudes towards biomass, and management plans

– Price is only marginally significant

2

Biomass Across the Northeastern U.S.

3

Source: Blackard et al. 2008. Mapping U.S. forest biomass.  Rem. Sens. Env. 

Biomass by Ownershipin the Northeastern U.S.

4

How Much Wood/Biomass/Timber is Really Available?

• How to define availability? 

• What are the constraints affecting availability?

• What are the implications?

5

Constraints ‐ Abstractly

6

Constraints – Mathematically

Where:

• BiomassA: total amount of available biomass

• Biomassi: amount of biomass represented by plot i

• ReductionRateij: biomass availability reduction rate

7

( )∑ ∏= =

⎟⎟⎠

⎞⎜⎜⎝

⎛⎟⎟⎠

⎞⎜⎜⎝

⎛−=

n

ii

k

jijA BiomassateReductionRBiomass

1 1

1

Physical and  Biological Constraints

• Physical– Slope

– Physiographic class

– Site productivity

• Biological– Stand size

8

Social Constraints

• Financial– Holding size– Accessibility– Development pressure

• Political– Riparian areas– Zoning regulations

• Landowner– Harvesting likelihood

9

Biomass Availability by Constraint

10

Biomass Availability by State

11

Published in 2010 in the Northern Journal of Applied Forestry

12

Massachusetts Landowner Biomass Survey

13

Approach

• Massachusetts family forest owners with 10+ ac

• n  = 439

• Asked about– Their land

– Ownership objectives

– Their opinions about woody biomass

– Aesthetics

– Willingness to participate14

Respondents

• Acreage– mean of 50 acres

• Farmers: – 20% of respondents

• Ownership objectives: – Beauty– Home– Privacy

• Timber Harvesting:  – 50% have– 23% “would never”

• Management Plan:– 20% of respondents

15

Aesthetics

16

A.

B.

C.

71%

Ranked as Top Choice

17%

12%

Attitudes Towards Biomass

17

Willingness to Harvest Biomass

Where:• y = probability of accepting biomass harvest offer• β = regression coefficients• x = explanatory variables• ε = error term

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εβ += ii xy*

i

i

x

x

i eey β

β

+==

1)1(Prob

Adjusted for uncertainty

Willingness to Harvest Biomass

Significant

• Price of biomass (+)

• Plans to harvest (+)

• Enrolled in current use (+)

• Has management plan (‐)

• Views biomass as a positive economic factor (+)

• Gender ‐male (+)

NON‐ Significant• Destination• Aesthetics• Home on woodland• Forested acres• Had harvested• Manages for timber• Manages for nature• Views biomass as a negative 

environmental impact• Age• Education• Income

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Supply Curve

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Conclusions

1. Social constraints are more important than biophysical constraints

– Especially owners’ attitudes and size of holdings

2. Hypothetical participation rate in Massachusetts is low

– Most influenced by harvest plans, attitudes towards biomass, and management plans

– Price is only marginally significant

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Comments or questions?

Brett Butler

U.S. Forest Service, Amherst, MA

bbutler01@fs.fed.us

www.fia.fs.fed.us/nwos

www.FamilyForestResearchCenter.org

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EXTRA SLIDES

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For example:

PLOTi BIOi RR1 RR2 RR3 BIOA

1 100 0.00 0.00 0.00 ((1‐0)x(1‐0)x(1‐0))*100 100

2 100 0.75 0.00 0.00 ((1‐0.75)x(1‐0)x(1‐0))*100 25

3 100 0.75 0.75 0.75 ((1‐0.75)x(1‐0.75)x(1‐0.75))*100

1.56

Total: 126.56

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Physical Constraints

25

Xeric Mesic Hydric

Physiographic Class

020

4060

8010

0

<25 25-49 50-74 75+

Slope

Percent

020

4060

8010

0

0-19 20-49 50-84 85-119 120+

Site Productivity

Cubic feet per acre per year

020

4060

8010

0

Biological Constraint

26

Small Medium Large

Tree Size

020

4060

8010

0

Financial Constraints

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1-19 20-49 50-99 100-499 500+

Size of Forest Holdings

Acres

020

4060

8010

0

<0.5 0.5-0.9 1.0+

Distance to Nearest Road

Miles

020

4060

8010

0

<1000 1000-1999 2000-2999 3000+

Human Population Pressure

Population gravity index

020

4060

8010

0

Political Constraints

28

<50 50-99 100-149 150-499 500+

Distance to Nearest Water

Feet0

2040

6080

100

<50 50-99 100-149 150-499 500+

Human Population Density

People per square mile

020

4060

8010

0

Landowner Constraints

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0 1 2 3

Ownership Attitude

Attitude index

020

4060

8010

0

Sensitivity Analysis: Threshold

30

Sensitivity Analysis: Reduction Rate

31

Contingent Valuation (CV) Biomass Survey

• Model– Willing to harvest residual woody biomass as part of a traditional harvest (yes/no)

• Preference Uncertainty in CV– Addressed with commonly used approach– Respondents rate certainty on scale 1‐5– Recoded a “yes” as a “no” if respondent was at all uncertain (answered 1‐4)

• Our approach safeguards against hypothetical bias in CV

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Background

• Biomass is a hot topic

• Our project:– Biomass conversion

– Feedstock and economics

– Biomass supply• Landowners’ concerns

• Factors influencing participation

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Biomass Opinion Questions

• Negative environmental impact [Factor 1]– Leaving it is important to wildlife habitat– Removing it depletes soil nutrients– Using it increases air pollution– Harvesting it significantly deforests

• Positive economic impact [Factor 2]– Using it could positively impact local economy– Harvesting it could supply renewable energy– Using it could positively impact US ability to address climate change

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Willingness to Harvest Biomass

Variable Coefficient z P>|z|Price of biomass 0.0021 2.13 0.033Destination: local school 0.22 ‐0.48 0.630Destination: electric power plant ‐0.25 ‐.054 0.590

Aesthetics (Picture 1) ‐0.29 ‐0.76 0.450Home on woodland ‐0.08 ‐0.18 0.860

Forested acres ‐0.002 ‐0.62 0.534

Had harvested 0.27 0.59 0.554

Plans to harvest 1.07 2.25 0.024

Chapter 61 enrolled 0.88 1.95 0.051

Management plan ‐1.23 ‐2.27 0.024

Manages for timber ‐0.45 ‐0.90 0.370

Manages for nature ‐0.05 ‐0.11 0.913

Biomass factor: neg env’l impact ‐0.20 ‐0.95 0.342

Biomass factor: pos econ impact 0.51 2.22 0.02735

Willingness to harvest biomass

36

Variable Coefficient z P>|z|

Age (65+) 0.05 0.12 0.908

Education (≤ High School) 0.27 0.46 0.647

Education (Graduate Degree) 0.30 0.61 0.540

Income less than $50,000 ‐0.02 ‐0.03 0.976

Income more than $100,000 ‐0.22 ‐0.51 0.612

Gender (male=1) 1.02 1.70 0.089

Constant ‐3.74 ‐3.97 0.000

Estimated Participation Rates

37

aAll other variables are set to their mean value, see Table 2.

Supply response0

100

200

300

400

500

Bio

mas

s pric

e pe

r acr

e

0 10 20 30 40 50 60 70 80 90 100Participation rate

Average respondent

38