three factors: exposure to risks or shocks, resilience or the capac-ity to respond to shocks, and initial economic situation (relativeposition above the poverty line). Bene (2009) adopted this defini-tion and proposed a refined model of calculation under four terms(Eq. (3)). When applying his model to our data subsets, it leadsto a slightly lower average estimated vulnerability among WA-MPA households. This finding could, at first glance, appear to bean interpretable and convenient result.
Yet the observed deviation is small, as if the vulnerability indexcalculated here had not managed to capture the entire extent ofthe difference between the situations of WA-MPA households andREM-MPA households. This means having to look into the possi-bility of a blind spot in the method used to calculate economicvulnerability. A more detailed analysis of WA-MPA householdvs. REM-MPA household differences across the four vulnerabilityterms, especially the second term (ii) concerning the “degree ofdependence on the main activity”, shows that this calculation termpenalises WA-MPA households (Table 7). The term (which reflectsthe extent of relying on a single activity) enters into the calculationas a factor that necessarily raises the vulnerability index. This is inline with many theories that consider the diversity of activities tobe a source of resilience. Yet we believe that there is a possibility ofa misinterpretation on this point. A less diversified activity strategy(such as a smaller number of fishing techniques used by WA-MPAhouseholds) may, in certain cases, reflect a greater guarantee ofsteady income from the household’s main activity. This, in turn,could mean that the activity is less exposed to catch downturnsand market conditions. In other words, it could reflect the house-hold’s greater “professional security”. As a result, the household inquestion can concentrate on the professional activity it knows howto do the easiest and the best. This appears to be case in this study.