| Literature DB >> 29684041 |
Guillaume Peterson St-Laurent1, Shannon Hagerman2, Robert Kozak2, George Hoberg3.
Abstract
The role of forest management in mitigating climate change is a central concern for the Canadian province of British Columbia. The successful implementation of forest management activities to achieve climate change mitigation in British Columbia will be strongly influenced by public support or opposition. While we now have increasingly clear ideas of the management opportunities associated with forest mitigation and some insight into public support for climate change mitigation in the context of sustainable forest management, very little is known with respect to the levels and basis of public support for potential forest management strategies to mitigate climate change. This paper, by describing the results of a web-based survey, documents levels of public support for the implementation of eight forest carbon mitigation strategies in British Columbia's forest sector, and examines and quantifies the influence of the factors that shape this support. Overall, respondents ascribed a high level of importance to forest carbon mitigation and supported all of the eight proposed strategies, indicating that the British Columbia public is inclined to consider alternative practices in managing forests and wood products to mitigate climate change. That said, we found differences in levels of support for the mitigation strategies. In general, we found greater levels of support for a rehabilitation strategy (e.g. reforestation of unproductive forest land), and to a lesser extent for conservation strategies (e.g. old growth conservation, reduced harvest) over enhanced forest management strategies (e.g. improved harvesting and silvicultural techniques). We also highlighted multiple variables within the British Columbia population that appear to play a role in predicting levels of support for conservation and/or enhanced forest management strategies, including environmental values, risk perception, trust in groups of actors, prioritized objectives of forest management and socio-demographic factors.Entities:
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Year: 2018 PMID: 29684041 PMCID: PMC5912731 DOI: 10.1371/journal.pone.0195999
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Expected directionality of the explanatory variables’ effect on levels of support for forest carbon mitigation strategies based on their relative levels of human-intervention.
A positive sign indicates a positive relationship, a negative sign indicates a negative relationship and a positive/negative sign indicates that the relationship could either be positive or negative.
| Explanatory variable | Directionality | |
|---|---|---|
| Less human intervention | More human intervention | |
| - Anthropocentric orientation | +/- | + |
| - Biocentric orientation | + | +/- |
| - Belief on the human-cause of climate change | + | + |
| - Perceived risk of climate change | + | + |
| - Personal experience with climate change | + | + |
| - Climate change and forest management | +/- | +/- |
| - Experts | +/- | + |
| - Environmental groups and First Nation leaders | + | +/- |
| - Economic and social | - | + |
| - Environmental | + | +/- |
Description of the eight forest carbon mitigation strategies.
Fig 1Mean scores representing the degree of knowledge about four different topics related to climate change in the context of forests and their management, with 1 = not at all knowledgeable and 5 = very knowledgeable.
Knowledge scale items and factor loadings.
Factors’ loadings in bold indicate that they have been selected in a factor.
| Loading | |
|---|---|
| The role of forests in regulating climate by reducing greenhouse gas emissions and increasing carbon removals from the atmosphere. | |
| The potential consequences of climate change on BC's forests. | |
| The current forest management practices implemented in BC's forests. | |
| Strategies involving BC's forests to reduce climate change. |
Environmental value scale items and factor loadings.
Factors’ loadings in bold indicate that they have been selected in a factor.
| Loading | ||
|---|---|---|
| Forests should be managed to meet the needs of as many people as possible. | 0.397 | |
| The primary use of forests should be for products that are useful to humans. | -0.219 | |
| Forests that are not used for the benefit of humans are a waste of our natural resources. | -0.336 | |
| Forests are valuable only if they produce jobs and income for people. | -0.342 | |
| Forests give us a sense of peace and well-being. | -0.109 | |
| Whether or not I get to visit the forest as much as I like, it is important for me to know that forests exist in BC. | -0.183 | |
| Forests have a right to exist for their own sake, regardless of human concerns and uses. | -0.175 | |
| Humans should have more love, respect and admiration for forests. | -0.136 | |
Fig 2Mean scores representing the level to which respondents trust the groups of actors when it comes to providing information about climate change issues in BC’s forests, with -2 = strongly distrust and 2 = strongly trust.
Trust scale items and factor loadings.
Factors’ loadings in bold indicate that they have been selected in a factor.
| Loading | |||
|---|---|---|---|
| Industry | 0.236 | ||
| BC's provincial government | 0.110 | ||
| Canadian federal government | 0.274 | 0.110 | |
| Scientists | 0.198 | ||
| Environmental groups | |||
| First Nations leaders | |||
| Professional foresters | 0.285 | 0.170 | |
Fig 3Ranking in order of relative importance (from the most to the less important) of five possible outcomes to consider when selecting forest management strategies to mitigate climate change in BC’s forests.
Fig 4Mean scores representing the degree of support for, or opposition to the climate change mitigation strategies, with -2 = strongly oppose and 2 = strongly support.
Scale items and factor loadings of respondents’ support or opposition to climate mitigation strategies.
Factors’ loadings in bold indicate that they have been selected in a factor.
| Loading | ||
|---|---|---|
| Reduced harvest strategy | – | |
| Old growth conservation strategy | 0.123 | |
| Bioenergy strategy | 0.225 | |
| Harvest efficiency strategy | 0.143 | |
| Increased harvest strategy | -0.247 | |
| Increased growth rate strategy | 0.193 | |
| Longer-lived wood product strategy | 0.168 | |
| Rehabilitation | 0.418 | 0.407 |
Models of multiple linear regressions for each category of mitigation strategies.
Bold items were found to be significant.
| Independent variables | Conservation strategies | Enhanced forest management strategies |
|---|---|---|
| Intercept | ||
| Cause of CC (Mostly human activities) | 0.03 | 0.03 |
| Perceived risk of CC | 0.04 | |
| Experience with CC (No experience) | 0.006 | 0.02 |
| Knowledge of CC and forestry | -0.02 | 0.007 |
| Anthropocentric | 0.03 | |
| Biocentric | ||
| Outcome (cost) | -0.06 | |
| Outcome (CC mitigation) | -0.05 | 0.03 |
| Outcome (biodiversity) | -0.02 | -0.05 |
| Outcome (economic local impact) | -0.02 | |
| Outcome (CC adaptation; baseline) | N/A | N/A |
| Trust (scientist) | 0.01 | |
| Trust (industry) | -0.03 | |
| Trust (federal) | -0.05 | 0.009 |
| Trust (provincial) | 0.04 | 0.02 |
| Trust (ENGO) | -0.02 | |
| Trust (forester) | ||
| Trust (First Nations) | -0.01 | |
| Age | 0.0002 | |
| Gender (male) | -0.04 | |
| Education (high) | 0.01 | |
| Employment in forest sector (employed) | ||
| Political orientation (conservative) | -0.06 | |
| Political orientation (liberal) | 0.03 | 0.04 |
| Political orientation (no party; baseline) | N/A | N/A |
| Residence type (rural) | -0.03 | -0.02 |
| Residence type (urban) | -0.004 | -0.06 |
| Residence type (suburban; baseline) | N/A | N/A |
| Adjusted R2 | 0.39 | 0.10 |
| F value |
* p ≤ 0.05;
** p<0.01;
*** p<0.001
Fig 5A conceptual framework highlighting the variables that affect level of support for conservation and forest management mitigation strategies.
Positive (blue boxes) and negative (red boxes) signs respectively indicate positive and negative impact on level of support. Lighter (p ≤ 0.05), medium (p<0.01) and darker (p<0.001) colour shading refer to the calculated probabilities (p-values) of the variables in the linear regression. Dotted boxes identify variables that did not significantly factor into the regressions, but were correlated with risk perception of climate change.