Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and relative risk ratios for strengths of belief in having experienced the effects of climate change based on education level (have/have not university education) among German respondents (S8 Table).

<p>Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and relative risk ratios for strengths of belief in having experienced the effects of climate change based on education level (have/have not university education) among German respondents (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155137#pone.0155137.s013" target="_blank">S8 Table</a>).</p

Questions assessing respondents' perceptions and behaviour relating to climate change, and socio-demographic variables; possible responses to the questions; and percentage responses of respondents (or other summary statistics, where noted) who answered yes and no to the question <i>Have you adapted your forest management in response to climate change</i>? (n = 828).

<p>n =  Numbers of responses. Test statistics for Wilcoxon rank sum test (W), Student's t-test (t), and χ²-test (χ²). Mean, median and ranges calculated from raw data before imputation.</p

Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and value profile, and relative risk ratios for strengths of belief in the local effects of climate change based on the education level (have/have not university education) and value profile using the model for Swedish respondents (S5 Table).

<p>Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and value profile, and relative risk ratios for strengths of belief in the local effects of climate change based on the education level (have/have not university education) and value profile using the model for Swedish respondents (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155137#pone.0155137.s010" target="_blank">S5 Table</a>).</p

The predictive power of alternative models of adaptation of forest management to climate change.

<p>Receiver operating characteristics curves summarizing the predictive power of alternative models, showing changes in proportions of adaptors and non-adaptors correctly classified by each model as the threshold is varied. The area under curve (AUC) is: 0.852 for the model including both personal belief variables and socio-demographic variables (solid curve, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050182#pone-0050182-t002" target="_blank">Table 2</a>); 0.778 for the model based on strength of belief in local effects of climate change alone (dot-dashed curve, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050182#pone.0050182.s002" target="_blank">Table S2</a>); 0.824 for the model based on both personal belief variables (dashed curve, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050182#pone.0050182.s003" target="_blank">Table S3</a>); and 0.700 for the model based on socio-demographic variables alone (dotted curve, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050182#pone.0050182.s004" target="_blank">Table S4</a>). The diagonal thin dotted line represents the ROC curve that would have been obtained if probability values were selected randomly from a uniform distribution and unrelated to the data.</p

Predicted probabilities for strengths of belief in having experienced the effects of climate change based on value profile and relative risk ratios for strengths of belief in having experienced the effects of climate change based on value profile (Forest users/other) among Swedish respondents (S7 Table).

<p>Predicted probabilities for strengths of belief in having experienced the effects of climate change based on value profile and relative risk ratios for strengths of belief in having experienced the effects of climate change based on value profile (Forest users/other) among Swedish respondents (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155137#pone.0155137.s012" target="_blank">S7 Table</a>).</p

Sensitivity of the predicted probability of having taken measures to adapt to personal belief variables.

<p>Simulated 95% confidence intervals for the predicted probability were estimated using the model including both the two personal belief variables and socio-demographic variables (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050182#pone-0050182-t002" target="_blank">Table 2</a>). Each confidence band was based on 10,000 simulations drawn while keeping all explanatory variables, except the variable (A) strength of belief in local effects of climate change and (B) strength of belief in having experienced climate change, at values contributing most strongly to high (solid lines) and low (dotted lines) probability of having taken measures to adapt, respectively. Confidence bands were simulated for all levels of the two personal beliefs variables used in the model, respectively.</p

Value profile interpretations per country.

<p>Value profile interpretations per country.</p

Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and relative risk ratios for strengths of belief in the local effects of climate change based on education level (have/have not university education) among German respondents (S6 Table).

<p>Predicted probabilities for strengths of belief in the local effects of climate change based on no university education and relative risk ratios for strengths of belief in the local effects of climate change based on education level (have/have not university education) among German respondents (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155137#pone.0155137.s011" target="_blank">S6 Table</a>).</p

Relationship of climate change risk perception with university education.

<p>Relationships of risk perception in terms of the strength of belief in the local effects of climate change, the strength of belief in having experienced the effects of climate change and university education for Swedish (a) and German (b) respondents. The size of the respective compartment is proportional to the number of observations in the respective category. Pearson residuals outside of ±2 correspond to a significant difference for individual cells at approximately α = 0.05. Positive Pearson residuals are delineated in blue and negative residuals in red. The graphs are based on raw data before imputation. NU–No university education; U–University education.</p

Diagnostic statistics of a model for predicting adaptive measures to climate change taken by forest owners based on personal belief variables and socio-demographic variables.

<p>S.b. climate change, Strength of belief in local effects of climate change; S.b. exp. climate change, Strength of belief in having experienced climate change (and/or its consequences); High, Professional education or equivalent, and/or University education or equivalent. The model was fitted to five imputed datasets using logistic regression. Diagnostic statistics given for the logistic regression model include explanatory variables that are not significant at α = 0.05. The null deviance = 1105.649, the degrees of freedom for the null model = 844, residual deviance = 767.212, and the residual degrees of freedom = 836. The model fits the data significantly better than the null model (p<0.0001).</p