Understanding the discourse of forest restoration and biomass utilization to guide collaborative forest resource planning

Jessica Clement, Nathaniel Anderson, Pam Motley, and Tony Cheng

What’s ahead?• Background• Goals and Objectives• Methods: The Q-study• Results• Discussion and Questions

Research PersonnelColorado Forest Restoration Institute, CSU• Jessica Clement• Tony ChengUncompahgre Partnership • Pam Motley (now with West Range

Reclamation)Rocky Mountain Research Station• Nate Anderson

Partners• Uncompahgre Partnership/GEO Grant• RMRS• CSU- CFRI• GMUG National Forests• Public Lands Partnership

Participants, advisors and stakeholders in the study

What themes characterize stakeholders’ subjective

perceptions and discourse about restoration treatments

and biomass utilization?

Goals• Understand regional dialogue• Understand different perspectives• Guide communication, cooperation and

collaboration• Maximize benefits• Minimize conflict

Objectives• Identify distinct themes that characterize

different perspectives on this issue• Examine nuances of those themes• Characterize patterns quantitatively • Identify places where frames overlap and

diverge

Methods

The “Q-Study”• Focus on “Frames”• Frame – “a representation of reality that

defines the key elements of a situation and its potential outcomes”

• Quantifying the subjective• Risk aversion versus risk taking

Methods

The “Q-Study”1. Compile a database of statements2. Sample the database to select 36

representative statements

Methods

Statement Categories• Aesthetic• Recreation• Ecological• Cultural/Historic• Process/Policy• Economic

Photo: Uncompahgre Partnership

Methods

Sample Statements• “Forest treatments should minimize visual

disturbances whenever possible.”• “I don’t think forest treatments have

negative impacts on recreationists.”• “It is important to me that forest treatments

pay for themselves.”• “I am concerned that biomass harvest will

lead to overharvesting and threaten forests.”

Methods

The “Q-Study”1. Compile a database of statements2. Sample the database to select 36

representative statements3. Compile a “person sample”

– NOT a simple random sample of individuals– NOT an opinion survey– Select participants to represent as many

perspectives as possible

MethodsStakeholder Group

Participants

Recreation (motorized and non-motorized groups) 5Representatives of other collaboratives 4Grazing permittees 1Conservation groups 7Federal agency 5State agency 3Local government 5Energy utility industry 3Forest products industry 4Biomass utilization interests 2Landowners 3Total 42

Methods

The “Q-Study”4. Data collection

– Q-sorts of the 36 statements by participants– Followed by a structured interview

5. Multivariate statistical analysis– Concentrate relationships of many variables

into a few pairs of variables called “factors”6. Interpret the statistical results thorough

correlations with statements and people

Methods

The “Q-Sort”STRONGLY DISAGREE STRONGLY AGREE

-5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ResultsFACTOR 1: Bio-centric Utilization• 20 of 41 participants• 34% of variation in the data• Generally supportive of biomass utilization for

ecological reasons, with an emphasis on accomplishing treatments to improve ecosystem health and avoid severe fires.

• “The Plateau contains important habitat for various species of wildlife. Treatment activities should not degrade habitat.”

Results

FACTOR 2: Industry-oriented Utilization• 10 of 41 participants• 19% of variation in the data• Supportive of biomass utilization to

generate economic benefits, including job creation in new and existing industries. Also aware of and supportive of other values.

• “It is critically important to industry to have a sustainable, predictable supply of material.”

ResultsFACTOR 3: Industrialist• 3 of 41 participants• 6% of variation in the data• Highly correlated with statements

characterizing open burning of biomass as a wasteful activity. High emphasis on jobs. Low support for other values.

• “Using woody biomass instead of wasting it by burning or scattering on the ground has numerous benefits.”

Results

FACTOR 4: Access-oriented Utilization• 3 of 41 participants• 5% of variation in the data• Emphasis on access and motorized

recreation with support for industry.• “I love to explore the large network of Off

Highway Vehicle roads and trails that the Uncompahgre Plateau offers.”

Results

FACTOR 5: Risk-averse Eco-centric • 3 of 41 participants• 4% of variation in the data• Ecological emphasis generally skeptical of

utilization and disagreeing with statements supporting utilization for economic reasons.

• “Treatment emphasis should be on improving and maintaining ecosystem health.”

Results• Loadings relate sorts to factors• Respondents load uniquely to one factor

Participant # Factor 1 Factor 2 Factor 3 Factor 4 Factor 521 0.8310 4 0.8001 18 0.7826 34 0.7638 24 0.7589 7 0.7308 16 0.7105 33 0.6755 13 0.6713 40 0.6629 14 0.6585 8 0.6532 3 0.6420 15 0.5978 17 0.5892 41 0.5712 5 0.5405 32 0.5248 6 0.5021 12 0.4670

Participant # Factor 1 Factor 2 Factor 3 Factor 4 Factor 528 0.7896 38 0.7860 30 0.7642 2 0.7516 10 0.7503 37 0.7275 11 0.6991 31 0.6522 29 0.6419 19 0.5151 23 0.7355 25 0.7012 1 0.6109 35 0.7479 26 0.7116 9 0.6639 27 0.6388 39 0.6172 36 0.6037 Q-sorts loaded on each factor at p < .01.

Take Home Messages• The dominant perspectives tend to

appreciate multiple values• The dominant perspectives are not highly

correlated with polarizing statements• Is collaborative forest planning the cause or the effect? Or both?• How can we use this information?

Photo: Uncompahgre Partnership

Contact InformationNate Anderson, Research Forester Rocky Mountain Research StationPO Box 7669, 200 East BroadwayMissoula, MT 59807nathanielmanderson@fs.fed.us(406) 329-3398