The indicators for physical capital are represented by means of irrigation, distance to the agricultural office, and main road accessibility during monsoon season.In several studies, access to irrigation has been considered as an important factor in adapting to climatic changes.With access to irrigation facilities, farmers can grow multiple crops throughout the year, which enhances their capacity to withstand climatic shocks.Proximity to the agricultural office could also enhance farmers’ adaptive capacity.It increases the possibility of getting relevant information and/or advice on technology, inputs, farmers’ schemes, training programs, etc., which can lead to better agricultural productions and, therefore, increased income of the farmer.Whereas road connectivity influences mobility and, thereby, households’ access to health care facilities, financial institutes, and markets.Although all the surveyed villages were connected with main roads, access to the above-mentioned facilities is observed to be difficult during the monsoon season.Therefore, road connectivity is measured during the monsoon season only.The availability and accessibility of financial resources that contribute to the wealth essential for agricultural activities are referred to as financial capital.The number of income sources, remittances from family members, and access to credit facilities were used as the indicators for financial capital.Diverse income sources uplift households’ financial condition, and at the same time, it creates an opportunity to reduce risk if one source of income is affected by the climatic shocks.A positive relationship is often reported between remittances and adaptive capacity.Households’ adaptive capability is boosted by the benefits of receiving remittances, expertise, and social networks from the host region of the migrated member.Besides, Banerjee et al.reported that households that receive remittances are more likely than non-recipient households to have greater access to formal financial institutions.Whereas credit facilities increase the cash flow, allowing farmers to engage in more capital-intensive technologies, thereby increasing their adaptability.

Access to credit also improves farmers’ flexibility to adjust production strategies in response to forecasted climatic circumstances, thus allowing them to recover faster.Human capital refers to the knowledge, skills, hydroponic bucket working capacity, and good health condition that are required to meet livelihood objectives.In this study, farming experience, educational attainment of the household head, and distance to the nearest primary health unit are selected as human capital indicators.Several studies have shown a link between agricultural experience and the likelihood of adopting adaption strategies.Farmers with extensive agricultural experience are indeed senior, and they often acquire resources through time, allowing them to invest in assets that contribute to increasing the adaptive capacity.It is often believed that educated farmers are more aware of the impacts of climate change and the importance of adaption strategies.As a result, better-educated household heads are more likely to implement climate change adaptation strategies.Health is a vital indicator of human capital since it is anticipated that families with limited access to health care would have more health issues, limiting their ability to work productively.Therefore, in this study, distance to the nearest primary health unit is used as an indicator of human capital.Social capital includes the features of social life , which are essential for achieving livelihood objectives.The indicators for the social capital are presented by group membership, presence of community position holders in the household, and total household members.Membership in social groups broadens individuals’ social networks and allows them to exchange and learn new information.In this study, several women were members of Self Help Groups.Members of SHGs get easy access to loans with which they acquire livelihood assets, create wealth, and set up small businesses to combat risks.The presence of community position holders also enhances a household’s adaptive capacity.Since most positions are elected, possessing a community position denotes a person’s social standing, as they are more likely to have a larger amount of social capital and, as a result, more access to common pools for adaptation.Some studies also reported that household size is positively associated with adaptation.People who live in the same house are more likely to be close, and it also serves as a support system and safety net.Individuals in larger families are more inclined to coordinate their efforts in supporting one another.It also increases the possibility of adopting a range of adaptation measures to combat the adversities associated with climate change.

In general, three approaches viz.equal weights, weights employing principal component analysis , and weights using expert judgment are used to assign weights to the indicators for constructing the index.As the equal weights might lead to underestimation of some indicators and PCA tend to provide physically inconsistent weights to the indicators ; therefore, the Analytical Hierarchy Process developed by Saaty was applied to determine the weights of the selected indicators under five capital assets.This method is a multi-criteria decision-making approach based on expert judgment and ensures the accuracy of these judgments as it has an inbuilt method to check the inconsistency of the judgments.Therefore, the basis of AHP is both psychology as well as mathematics.The weights were assigned in consultation with the key informants from each village and three agricultural experts who had plenty of knowledge regarding the study sites.In recent times AHP has been applied to assess the climate change vulnerability and adaptive capacity by numerous studies.The indicators used in this study were further reclassified into sub-classes, and relative ranks were assigned.The ranks were allocated between 1 and 3.After the identification of the levels of adaptive capacity, adaptation strategies for each level were identified and compared in order to understand the variation in adaptations based on the households’ adaptive capacity.The adaptation strategies of households were analyzed by asking questions on how the farming households made adjustments to the associated impacts of climate change.With the help of information gathered from the existing literature , discussion with the key informants, and reconnaissance survey, a list of impacts associated with the climatic adversities on the agricultural production and adaptation strategies were compiled.Later on, these were verified during the pilot survey.Then from the pre-determined list of adaptation strategies, the respondents were asked to indicate those which they practice to counter the adverse effects of the changes in climatic conditions.The majority of the households sampled in this study were male-headed , and the remaining 5.37 percent of the household heads were found to be widow female-headed.A high proportion of the households were Hindus , followed by Buddhists and Christians.Among the sample households, the concentration of the backward class communities was very high.The average age of the respondents was 48 years, with a maximum and minimum age of 85 and 25 years, respectively.The number of people residing in each household ranged from 2 to 12, with an average family size of 5.The study area has a noticeably low level of education, with more than half of the household heads being illiterate and only 18.79 percent having finished primary and secondary education.The average and maximum years of schooling of the respondents were about 2 and 8 years, respectively.Low levels of educational attainment in this region were due to a lack of local educational facilities, a poor financial condition in the household, early engagement in earning, and a lack of importance placed on formal education by the previous generations.

Most of the respondents’ houses were built on a raised wooden platform to protect them against elephant attacks.Only 39.60 percent of the houses were cemented.Agriculture is the principal source of livelihood for the majority of sampled households, and the average landholding size held by the households is 0.85 hectare.The average farming experience of the respondents is 30.19 years.Agriculture is largely rainfed, and all the surveyed households use cow dung as organic compost in their fields.Besides, the sample household members were also found to be engaged under the “Mahatma Gandhi National Rural Employment Guarantee Act”, getting 100 days of paid work in a year.The indicators of the household adaptive capacity were compared and weighted using the AHP tool to show the contribution of each indicator to the levels of adaptive capacity.Table 4 reports the different weights of the indicators.The obtained Consistency Ratio value was 0.04,stackable planters which signifies the acceptance of all the derived weights for assessing adaptive capacity.Higher weight age of the indicators denotes more significance of the factors towards household adaptive capacity.Soil quality obtained the highest weight , followed by the type of land ownership , type of irrigation , access to the main road during monsoon , number of income sources in the household , access to credit , and landholding size.This implies that, in general, access to natural, physical, and financial capital is the primary contributor to the overall adaptive capacity of the farming households in the study area.Households’ adaptive capacity was also influenced by the social and human capital indicators but to a lesser extent.The findings are similar to the recent studies of Choden et al.in Bhutan, Y.C.Zanmassou et al.in West Africa, and in Bangladesh that the indicators based on sustainable livelihood capitals are effective at capturing the household adaptive capacity.However, the significance of the different capitals in determining the levels of adaptive capacity varied among the above-mentioned studies based on the spatial and temporal context.Overall, 28.19, 60.40, and 11.41 percent of the households have low, moderate, and high adaptive capacity levels, respectively.Therefore, based on the adaptive capacity index, the majority of the farming households had a moderate level of adaptive capacity, and the least had a higher adaptive capacity.

Similarly, Jamshidi et al.and Abdul-Razak and Kruse found a smaller percentage of farmers with high adaptive capacity in their studies.Fig.2b shows that the main difference between those with low adaptive capacity levels and those with moderate and high is the availability and accessibility of natural capitals.The scores of financial, human, and social assets for households with high adaptive capacity are also relatively higher than those with moderate and low adaptive capacity.The average score of physical capital is quite similar in all three levels of adaptive capacity.Besides, the Pearson Chi-Square test result suggests that the distribution of household adaptive capacity is significantly associated with the village location and the strength of the association is moderate in the Cramer’s V test.However, a substantial variation in the levels of adaptive capacity was found even within the villages.This finding concurs with Choden et al., who also reported that adaptive capacity varies greatly due to socioeconomic differences and access to different capital assets within the same geographical and agro-ecological situation.A high proportion of households having low adaptive capacity was from the village Turturi Khanda.The village scored the least in terms of soil quality, landholding size, type of irrigation, distance to the agricultural office, and main road accessibility during the monsoon season.Being situated in the Sub-Himalayan foothills and proximity to the Bhutan hills makes this village highly susceptible to flood events.Excess water coming from mountainous transboundary rivers during the monsoon has caused continuous intrusion of sands, pebbles, and silt in the farmlands of many households.Consequently, a large number of the sample household’s farmland have become infertile and partially infertile.Besides, communication during the monsoon also becomes difficult in this village due to the inaccessibility of the main road.Heavy reliance on rainfall as the only source of water for growing crops has increased their vulnerability even more as there is a significant decreasing trend of monsoon in this region, as reported by Datta and Das.In addition, there is considerable distance between the households and the agricultural office.As stated by the sample farmers from the Turturi khanda village, they never had any interaction with the extension service agents.Conse-quently, the knowledge about modern farming practices and techniques to increase productivity was found to be low amongst them.On the other hand, 21.43 percent of the low adaptive capacity households are from the Dalsinghpara village.The score for land ownership is remarkably low in this village as the households had no ownership right of the land.Since the households are primarily based on agriculture for their livelihoods, gaining ownership rights becomes imperative.However, the matter of land rights has become an unresolved and persistent issue for many people living in the hills and foothills of West Bengal, leading to their exclusion from facilities and schemes funded by both the central and state governments.Furthermore, the basic health care unit is located a long distance from the households, and in the case of a major illness, the villagers need to travel roughly 50 kms to obtain better health care facilities.