Vulnerability assessment of coastal fishing communities for building resilience and adaptation: Evidences from Tamil Nadu, India

Highlights: • The vulnerability indicators that affect fisheries and coastal households are identified. • A vulnerability assessment framework is piloted in fishing villages of a coastal district of Tamil Nadu, South India. • The decision matrix provided in this paper aids in identifying the drivers and buffers for coastal vulnerability. • This approach for location-specific intervention planning can be validated and used in other tropical coastal villages. The coastal communities are the most vulnerable to climate vagaries, which affect their habitat and livelihood alike. Vulnerability assessments undertaken using quantitative or qualitative methods at macro- or micro-level need to capture the location and context so as to be able to use them towards improving mitigation and resilience strategies at the community level, where the impact is felt. The characteristics of the marine fishing villages differ from those of other villages in any coastal block / district in a State, making a strong case for a marine village-specific vulnerability assessment as well as intervention planning. This work, capturing this grassroots reality and deriving vulnerability indicators that affect fisheries and coastal households, pilots a novel socio-economic vulnerability (SEVI_PH) and cumulative vulnerability (CVI_PH) framework in marine fishing villages of Thoothukudi, a coastal district of Tamil Nadu in India, and compares it with an existing framework (SEVI_SV) that relies on secondary data. A set of 54 indicators reflecting vulnerability components such as exposure, sensitivity (fishery and social) and adaptive capacity (economic, development drivers and alternate livelihood activity) has been developed. Primary data were collected from 1741 households residing in all the 24 marine fishing villages in Thoothukudi district to estimate various sub-indices and indices of SEVI_PH, SEVI_SV and CVI_PH. Significant differences (p < 0.01) in sensitivity index (SI) and adaptive capacity index (ACI) were observed among the fishing villages, which however, got masked at taluk and district level due to aggregation, underscoring the importance of household based village level assessment of vulnerability. Overall, 42 % of the fishing villages were socio-economically highly vulnerable, while about 71 % of the villages had high cumulative vulnerability index. While the overall social and economic status of fishing households were lower compared to non-fishing population, it could be ascertained that there was relatively less inequity among them. The study also found significant disparities and differences (p < 0.05) across the villages/taluks in terms of exposure, sensitivity as well as socio-economic capabilities to respond, adapt and develop resilience. The two dimensional decision matrix plotted against SI and ACI median threshold values presented a greater contrast and helped in identifying the key drivers (or contributing factors) and buffers (or ameliorating factors) for coastal vulnerability of marine fishing villages to aid in location-specific intervention planning. The study also highlighted the need for imparting need-based location-specific training programmes at the village and taluk level for vulnerability reduction.