Comment on “Barriers to enhanced and integrated climate change adaptation and mitigation in Canadian forest management”
- Wellstead, Adam Department of Social Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA.
- Biesbroek, Robbert Public Administration and Policy Group, Wageningen University, Hollandseweg 1, 6700 EW, Wageningen, the Netherlands.
- Cairney, Paul Department of Politics and History, University of Sterling, Sterling, FK9 4LA, U.K.
- Davidson, Debra Department of Resource Economics and Environmental Sociology, University of Alberta, Edmonton, AB T6G 2P5, Canada.
- Dupuis, Johann IDHEAP, Swiss Graduate School of Public Administration, University of Lausanne, Quartier, Mouline, Lausanne CH-1015, Switzerland.
- Howlett, Michael Department of Political Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada.
- Rayner, Jeremy Johnson-Shoyama Graduate School of Public Policy, University of Saskatchewan, 101 Diefenbaker Place, Saskatoon, SK S7N 5B8, Canada.
- Stedman, Richard Department of Natural Resources, Cornell University, 104 Fernow Hall, Ithaca, NY 14850, USA.
Published in:
- Canadian Journal of Forest Research. - Canadian Science Publishing. - 2018, vol. 48, no. 10, p. 1241-1245
English
We comment on the recent comprehensive review “Barriers to enhanced and integrated climate change adaptation and mitigation in Canadian forest management” by Williamson and Nelson (2017, Can. J. For. Res. 47: 1567–1576, doi: 10.1139/cjfr-2017-0252 ). They employ the popular barriers analysis approach and present a synthesis highlighting the numerous barriers facing Canadian forest managers. The underlying functionalist assumptions of such an approach are highly problematic from both a scholarly and a practical policy perspective. We argue that social scientists engaged in climate change research who want to influence policy-making should understand and then empirically apply causal mechanisms. Methods such as process tracing and qualitative comparative analysis (QCA) are promising tools that can be employed in national- or local-level assessments.
- Language
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- English
- Open access status
- bronze
- Identifiers
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- DOI 10.1139/cjfr-2017-0465
- ISSN 0045-5067
- Persistent URL
- https://folia.unifr.ch/global/documents/297774
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