Community Resilience to Climate Change: Theory, Research and Practice

129 DISCUSSION We have proposed a tool to explore perceived levels of household resilience to climate extremes in Tanzania, and how objective characteristics map onto these assessments. We seek to contribute to a nascent body of literature on the measurement of resilience- related capacities. The results of the nationally representative survey point to a logical association between the previous experience of flooding and perceived severe risk associated with flooding at the household and community levels. Respondents who had received advanced warning of flooding in the past were more likely to perceive it as a serious problem, both for their households and their communities, than those who had not. This association could be a function of the severity of the previous flood—more efforts are likely to be taken to warn people of more extreme events in areas where floods are more severe—but it could also reflect that people who believe flooding is serious are more likely to seek out advance warning. The survey results also suggest that low resilience-related capacities appear to be a concern in Tanzania where most households reported limited capacities to be prepared for, respond to, or change their livelihood strategies in response to an extreme flood. The scores across the three capacities were fairly similar; around one-third of respondents felt they were likely to be prepared in the event of a flood, one-quarter felt they could recover fully within six months, and 4 in 10 felt they could change their livelihood if needed. It is intriguing, however, that a greater proportion of respondents felt able to change their livelihood strategies than to prepare for, and to a much greater extent, cope with, an extreme flood. This may suggest that perceived levels of adaptive capacity are higher relative to the other two resilience capacities. The share is somewhat lower among people with less education and fewer assets (though only the wealth differences are statistically significant); however, fully 30% of respondents without education and one-third of those from households in the poorest asset quintile felt that they would be able to adapt. The results could, in part, be explained by increasing levels of livelihood diversity and flexibility with regards to sources of income and livelihood among Tanzanians (Hedges et al. 2016). In future work, it would be advisable to probe understandings of the adaptive capacity-related question, including whether people associate it with longer term change rather than short-term coping strategies, and the sorts of livelihood strategies people feel they can adopt. The correlations among responses to the three questions were positive but lower than expected (less than 0.5), reflecting considerable diversity among households with respect to the three capacities. These moderate correlations (and the relatively low Cronbach’s alpha of 0.62) also point to a lack of internal consistency, though principal components analysis showed that they loaded strongly onto a single factor. To better understand these three components, we treat them separately and defer the question of whether an index of resilience-related capacities could be useful to follow-up research. What is perhaps most interesting is that though a small number of weak relationships are apparent, most socio-demographic variables do not exhibit statistically significant differences with regards to perceived resilience-related capacities, e.g., age, education, occupation, wealth status, and place of residence. This is important given that these factors feature in objective assessments and are typically assumed to be strongly associated with household resilience (see FAO 2016). In this, our findings align with those of Béné et al. (2016b) who find that among coastal fishing communities in Ghana, Fiji, Vietnam, and Sri Lanka, none of the demographic characteristics that they analyzed apart from assets had a demonstrable impact on subjective resilience, which they characterize as “individual perception and self-confidence about their own ability to handle future events” (Béné et al. 2016b:21). It is perhaps notable that the strongest relationship we find among the demographic variables is between belonging to the upper wealth quintile and the perceived capacity to adapt. Moreover, our data show that relationships between socioeconomic variables and perceived resilience-related capacities are broadly similar among respondents who had recently experienced a flood, i.e., in the previous two years, and those that had not. Several areas are worth considering. On the one hand, these results could indicate that traditionally measured objective characteristics do not have a strong influence on individual perceptions of a household’s ability to prepare, recover from, and adapt to climate risk. If replicated in other areas and through different means, this could in turn cast doubt on the suitability of objective characteristics as effective measures of household resilience overall (Levine 2014). On the other hand, a subjective approach to assessing household resilience may be a poor reflection of overall resilience: those with a low resilience may perceive themselves to be more resilient than they are, and vice versa. Part of the difficulty in establishing which of these two positions is applicable is that there is no present means of validating one or the other. Both objective and subjective measures are approximations of a somewhat intangible, contextual, and evolving concept. This is similar in many ways to difficulties faced in defining and measuring concepts such as well-being, risk perception, and happiness (Deeming 2013). More needs to be done to examine the effects of different characterizations and framings of resilience within subjective survey modules so as to establish the robustness of comparative subjective scores. Additional considerations relate to the validity of the survey questions themselves, response structures, or the means of administering the survey by telephone (see Leo et al. 2015). Each may have affected the results of the survey and explain several of the counterintuitive findings. In addition, several of the variables focus on individual characteristics such as gender and education, making it difficult to differentiate between personal and household- level dynamics. To confront this subjective-objective mismatch, further qualitative work is recommended, to seek to establish which factors are more closely associated with community-wide assessments of preparation, recovery, and adaptation. Ultimately a long- term cohort study and natural experiment may be needed to effectively assess howwell proposed measures of resilience, objective and subjective, measure actual resilience as demonstrated in the face of natural disasters.