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Understanding Farmer Perspectives on Climate Change Adaptation and Mitigation: The Roles of Trust in Sources of Climate Information, Climate Change Beliefs, and Perceived Risk.

Arbuckle JG, Morton LW, Hobbs J - Environ Behav (2015)

Bottom Line: Results indicate that beliefs varied with trust, and beliefs in turn had a significant direct effect on perceived risks from climate change.Support for adaptation varied with perceived risks, while attitudes toward GHG reduction (mitigation) were associated predominantly with variation in beliefs.Most farmers were supportive of adaptation responses, but few endorsed GHG reduction, suggesting that outreach should focus on interventions that have adaptive and mitigative properties (e.g., reduced tillage, improved fertilizer management).

View Article: PubMed Central - PubMed

Affiliation: Iowa State University, Ames, IA, USA.

ABSTRACT

Agriculture is vulnerable to climate change and a source of greenhouse gases (GHGs). Farmers face pressures to adjust agricultural systems to make them more resilient in the face of increasingly variable weather (adaptation) and reduce GHG production (mitigation). This research examines relationships between Iowa farmers' trust in environmental or agricultural interest groups as sources of climate information, climate change beliefs, perceived climate risks to agriculture, and support for adaptation and mitigation responses. Results indicate that beliefs varied with trust, and beliefs in turn had a significant direct effect on perceived risks from climate change. Support for adaptation varied with perceived risks, while attitudes toward GHG reduction (mitigation) were associated predominantly with variation in beliefs. Most farmers were supportive of adaptation responses, but few endorsed GHG reduction, suggesting that outreach should focus on interventions that have adaptive and mitigative properties (e.g., reduced tillage, improved fertilizer management).

No MeSH data available.


Related in: MedlinePlus

Model 1: Adaptation path diagram and standardized structural coefficients with 95% credible intervals in parentheses.*p < .05. **p < .01. ***p < .001.
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fig1-0013916513503832: Model 1: Adaptation path diagram and standardized structural coefficients with 95% credible intervals in parentheses.*p < .05. **p < .01. ***p < .001.

Mentions: The structural coefficients for Models 1 and 2 are presented on their respective paths in Figures 1 and 2, respectively. The Tucker–Lewis goodness-of-fit index (TLI) measures the incremental improvement in a model’s fit to the observed covariance structure over a model and typically ranges from 0 to 1 (Tucker & Lewis, 1973). For the Bayesian analysis, the posterior mean TLI can be computed from samples of the posterior distribution. The TLI for Model 1 is 0.784, and the TLI for Model 2 is 0.783, suggesting adequate fits. The models show key similarities in the relationships among trust, climate change belief, and perceived risk. The correlation between the two trust constructs (0.46) is measured to control for generalized trust, or the degree to which individuals tend to trust others (Hammar & Jagers, 2006).


Understanding Farmer Perspectives on Climate Change Adaptation and Mitigation: The Roles of Trust in Sources of Climate Information, Climate Change Beliefs, and Perceived Risk.

Arbuckle JG, Morton LW, Hobbs J - Environ Behav (2015)

Model 1: Adaptation path diagram and standardized structural coefficients with 95% credible intervals in parentheses.*p < .05. **p < .01. ***p < .001.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2 - License 3
Show All Figures
getmorefigures.php?uid=PMC4359208&req=5

fig1-0013916513503832: Model 1: Adaptation path diagram and standardized structural coefficients with 95% credible intervals in parentheses.*p < .05. **p < .01. ***p < .001.
Mentions: The structural coefficients for Models 1 and 2 are presented on their respective paths in Figures 1 and 2, respectively. The Tucker–Lewis goodness-of-fit index (TLI) measures the incremental improvement in a model’s fit to the observed covariance structure over a model and typically ranges from 0 to 1 (Tucker & Lewis, 1973). For the Bayesian analysis, the posterior mean TLI can be computed from samples of the posterior distribution. The TLI for Model 1 is 0.784, and the TLI for Model 2 is 0.783, suggesting adequate fits. The models show key similarities in the relationships among trust, climate change belief, and perceived risk. The correlation between the two trust constructs (0.46) is measured to control for generalized trust, or the degree to which individuals tend to trust others (Hammar & Jagers, 2006).

Bottom Line: Results indicate that beliefs varied with trust, and beliefs in turn had a significant direct effect on perceived risks from climate change.Support for adaptation varied with perceived risks, while attitudes toward GHG reduction (mitigation) were associated predominantly with variation in beliefs.Most farmers were supportive of adaptation responses, but few endorsed GHG reduction, suggesting that outreach should focus on interventions that have adaptive and mitigative properties (e.g., reduced tillage, improved fertilizer management).

View Article: PubMed Central - PubMed

Affiliation: Iowa State University, Ames, IA, USA.

ABSTRACT

Agriculture is vulnerable to climate change and a source of greenhouse gases (GHGs). Farmers face pressures to adjust agricultural systems to make them more resilient in the face of increasingly variable weather (adaptation) and reduce GHG production (mitigation). This research examines relationships between Iowa farmers' trust in environmental or agricultural interest groups as sources of climate information, climate change beliefs, perceived climate risks to agriculture, and support for adaptation and mitigation responses. Results indicate that beliefs varied with trust, and beliefs in turn had a significant direct effect on perceived risks from climate change. Support for adaptation varied with perceived risks, while attitudes toward GHG reduction (mitigation) were associated predominantly with variation in beliefs. Most farmers were supportive of adaptation responses, but few endorsed GHG reduction, suggesting that outreach should focus on interventions that have adaptive and mitigative properties (e.g., reduced tillage, improved fertilizer management).

No MeSH data available.


Related in: MedlinePlus