Farm Level Knowledge, Risk Perception, Concern, and Adaptation to Climate Change: A Perspective from Saurastra and Kutch Region of Western India.

摘要

This dissertation investigates rural households' knowledge, risk perceptions, concern and adaptation to climate change in Saurastra and Kutch region of Western India. Quantitative surveys supplemented by a few qualitative interviews were used for data collection. Results suggest that people in rural Saurastra and Kutch are able to detect climate change correctly; however there exist misconceptions about climate change knowledge. They tended to confuse climate and weather and mismatched causes and mitigation measures of climate change. They perceived high risk, but were only moderately concerned about risk of climate change. The different environmental conditions of the area were found to significantly influence peoples' climate change knowledge, risk perception, concern and adaptation behavior. Family income, education, and to some extent climate change knowledge were observed to contribute positively to risk perceptions. However, family income contributed negatively to peoples' concern. Similarly education income and land ownership were significant determinants of rural households' adaptation choices. Risk perception and concern found to be positively related to climate change adaptation, but they were not a significant player in deciding rural households' adaptation options. While rural households adopted multiple strategies, they also perceived significant barriers for adaptation to climate change. The findings suggest that rural people rely more on experiential learning and use less analytical learning from other sources to base their decisions on. Inclusion of local scientific evidence in communication may better serve purposes of recalling personal experience and facilitate analytical learning of climate change consequences. Also access to credit, climate change information and new farm technologies would enhance rural households' ability to adapt climate change effectively.