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Willingness of nonindustrial private forest owners in Norway to supply logging residues for wood energyAuthor(s): Hanne K. Sjolie; Dennis Becker; Daniel Habesland; Birger Solberg; Berit Hauger Lindstad; Stephanie Snyder; Mike Kilgore
Source: Small-scale Forestry. 15(1): 29-43.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionNorway has set ambitious targets for increasing bioenergy production. Forest residue extraction levels are currently very low, but residues have the potential to be an important component of the wood energy supply chain. A representative sample of Norwegian nonindustrial private forest owners having at least 8 ha (20 acres) of productive forest land was surveyed about their willingness to supply logging residues for wood energy production. About 59 % responded that they were willing to do so. Logistic regression analyses revealed that the following factors were positively associated with the likelihood of being willing to supply logging residues: total forest area, education level, living in a region with active timber markets and a history of forest production, and having positive perceptions of residue extraction and forestry’s role in mitigating climate change. Four variables were negatively associated with the likelihood to supply residues: living on property, being older than 65 years, having family or friends who are opposed to residue extraction, and having negative perceptions of residue extraction. The study provides insight regarding nonindustrial forest owners’ attitudes towards extraction of forest residues that may aid policymakers designing effective means to meet national bioenergy production goals.
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CitationSjølie, Hanne K.; Becker, Dennis; Håbesland, Daniel; Solberg, Birger; Lindstad, Berit Hauger; Snyder, Stephanie; Kilgore, Mike. 2016. Willingness of nonindustrial private forest owners in Norway to supply logging residues for wood energy. Small-scale Forestry. 15(1): 29-43.
KeywordsBioenergy, family forest owners, logistic regression, factor analysis
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