Community Resilience to Climate Change: Theory, Research and Practice

127 which in turn builds confidence in their ability to deal with flood risk, or that floods have been experienced in areas where households have higher resilience-related capacities. Perhaps of most interest, having had early warning is consistently and strongly associated with all three capacities (Fig. 3). For example, 45% of those with early warning of a previous flood reported it unlikely that they would be prepared for extreme flooding, compared with 70% of those who had not had such a warning. For the capacity to recover, the figures were 57% and 79%, respectively, while for the capacity to adapt, they were 40% and 64%. In other words, the differences associated with early warning ranged between 22 and 25 percentage points. The most common source of early warning is through local and national radio (75%) with television (18%) and newspapers (3%) being far less common. It could be that respondents in more resilient households are more likely to obtain information regarding upcoming extreme weather events, or conversely, that the receipt of such information improves household resilience (indeed both mechanisms could be in play, or an unobserved trait could influence both aspects). But given that the provision of early warning information is such an important policy lever, greater exploration of the hypothesis that making information about flooding available improves resilience-related capacities is warranted, in line with similar research on risk perceptions of flooding (Miceli et al. 2008). Fig. 2. Relationships between resilience-related capacities and socioeconomic variables. Multivariate analysis To understand better factors associated with the perceived capacity to be prepared for, to recover from, and to adapt to extreme flooding, and how they relate to one another, we conducted seemingly unrelated regressions using ordinal logistic models with the capacity variables as the dependent variables. Across all the models, it is immediately apparent that the regressors have negligible explanatory power, explaining at most 2% of variation in these capacities.[13] Very few variables display a statistically significant