Fig. 1: Raw percentage distributions for climate change risk perceptions and trust in scientists.

Panel a presents the results for climate change risk perceptions and Panel b presents the results for trust in scientists. For Panel a, the valid n = 3074 in 2013 (n = 107 missing); valid n = 1863 in 2017 (n = 71 missing); valid n = 2488 in 2021; valid n = 2317 in 2023. *p < 0.05. †p < 0.01. ‡p < 0.001. Climate change risk perceptions were measured by asking participants: ‘Which of the following statements best describes your beliefs about climate change and the Great Barrier Reef?’. The means were adjusted for by applying a population weight for age and gender combined (i.e., population proportion divided by the sample proportion). The odds ratio (OR) between successive years was obtained from ordinal logit regression models (including the population weight), repeated with a different baseline comparison year (see Table S3). SE = Standard Error. For Panel b, the valid n = 3016 in 2013 (n = 165 missing); valid n = 1851 in 2017 (n = 83 missing); valid n = 2411 in 2021 (n = 77 missing); valid n = 2246 in 2023 (n = 71 missing). *p < 0.05. †p < 0.01. ‡p < 0.001. Trust in scientists was measured by asking participants: ‘Considering the information you receive about the Great Barrier Reef, how much do you trust the information that comes from the following groups?’ with ‘scientists from research institutions (e.g., CSIRO, Universities)’ as one of the options. The means were adjusted for by applying a population weight for age and gender combined (i.e., population proportion divided by the sample proportion). The t-scores (t) between successive years were obtained from contrasts requested post hoc to the population-weighted linear regression model (see Table S6). SE = Standard Error.