A multidimensional perspective to farmers' decision making determines the adaptation of the farming community.

Agricultural adaptation to climate change includes changes in agricultural management practices which will be quite effective in reducing the probability of crop failure and improving the socio economic condition of farmers. Knowledge about the decision making process of farmers can help in identifying the determinants of adaptation to them. It is very important to model the farmers' behaviour and decision making process to answer the reasons for farmers' suicides and inequalities arising out within the farmers belonging to same group. Our study identifies the factors responsible for increasing inequalities, crop failure and differential decision making capabilities of farmers by surveying 400 farmers in eighteen villages of Maharashtra, India. We analysed how combination of various factors such as social, economic, infrastructural and institutional affect the decision making process of farmers which brings out the novelty of the present work that can be replicated across a spectrum of such studies. Further, different adaptation options were categorized into the most and least preferred adaptive strategies by considering the farmers' perception. Our work has also identified which particular factor i.e. climatic, institutional, infrastructural or socio-economic is the major challenge towards the adaptation of farmers. The study has followed logit model in investigating the farmers' adaptation to multiple stressors. The study has also addressed the on-going argument regarding the scale of policy formulation i.e., whether policy formulation should take place at micro scale (Decentralization) or at larger region (State/National) level. Findings revealed that farmers perceive climate variability in terms of monsoon and temperature variability and respond as per their indigenous knowledge and experience. Model results revealed that institutional, social and climatic factors should be the focus point of government for improving the adaptation profile of farmers.

Agricultural susceptibility to monsoon variability: A district level analysis of Maharashtra, India.

Indian Summer Monsoon (ISM) variability has always been a feature affecting Indian agriculture. However, nature of this variability is varying in the backdrop of climate change, and as a consequence, agriculture is getting significantly affected and subsequently threatening food security. To address the climate variability, most of the studies conducted so far have focused on a coarse scale such as Central India or Western Ghats. However, finer scale analysis for identification and quantification of the link between agriculture vulnerability and climate variables has not yet been attempted in a comprehensive manner. The latter is essential, as considering state and national domain as a single entity for regional level policy formulations have led to under-representation of grievances and issue related to agriculture and farmers in the past. In order to address these issues, focus of the current study is on finer scale analysis of districts of Maharashtra state in Western India. Inter and intra-regional spatio-temporal heterogeneity in monsoon variability parameters was found across districts of Maharashtra. Here, we ranked the districts of Maharashtra using monsoon variability index which includes six different monsoon variability parameters (Wet/Dry Spells, frequency/intensity of extreme rainfall events, deviation from the long-period average and daily-scale variability) by using factor analysis. Monsoon variability index indicated that districts under Vidarbha and Marathwada regions are at highest risk and need immediate attention from decision-makers and scientists. This index was further linked to average yield and cropped area using Structural equation modeling that will help to determine the ideal cropping pattern for the most vulnerable districts. An empirical model of monsoon variability is also proposed at district level for the state of Maharashtra that can contribute to the currently operating 'State Action Plan on Climate Change (SAPCC)' or can be used to formulate a new action plan at district level i.e. 'District Action Plan on Climate Change (DAPCC)'. The current study differs from other studies in terms of its application, levels of spatial aggregation and areas of coverage. The findings can be utilized by farmers and policy makers while formulating agricultural policies, risk reduction measures, and adaptation mechanisms to address the adverse impacts of climate change.