The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

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Shrimp farming is a key subsector of Indian aquaculture which has seen a remarkable growth in the past decades and has a tremendous potential in future. The present studyanalyzes thetechnical efficiency of the shrimp famers of East Godavari district of Andhra Pradesh using the Stochastic Production Frontier Function with the technical inefficiency effects. The estimates mean technical efficiency of the farmers was 93.06 % which means the farmers operate at 6.94 % below the production frontier production. Age, education, experience of the farmers and their membership status in farmers associations and societies were found to have a significant effect on the technical efficiency. The variation in the technical efficiency also confirms the differences in theextent of adoption of the shrimp farming technology among the farmers. Proper technical training opportunities could facilitate the farmers to adopt the improved technologies to increase their farm productivity.

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The present study was conducted to analyse the extent of empowerment achieved by fisherwomen through participation in the entrepreneurial activities of self help groups (SHGs) functioning in the fisheries sector. Data were collected from 180 SHG members in the Kollam, Ernakulam and Kasargod districts of Kerala. Aquaculture (55.5%) and value addition of fish (45.5%) were the entrepreneurial activities adopted by fisherwomen SHGs. Empowerment level of each SHG member was quantified by modifying the existing empowerment dimensions into an Empowerment Index (EI), consisting of 8 sub-dimensions. Extent of empowerment was found out by taking the difference of empowerment index before and after joining the SHG. Among the eight empowerment dimensions, higher difference was observed in confidence building (0.43) followed by economic empowerment (0.42) and decision making pattern (0.41). The study revealed that the level of involvement in entrepreneurial activity has increased the empowerment in terms of confidence building, self-esteem, decision making pattern, psychological and economic empowerment. However, the existing fisheries extension interventions through extension contact and training were found to be associated with only self esteem and psychological empowerment. Therefore, new and innovative extension interventions are suggested in the paper to influence other sub-dimensions like economic empowerment, confidence building and decision making pattern.

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