Climate stress poses a threat to the agricultural sector, which is vital for both the economy and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability is crucial. This study proposes a framework to estimate the impact climate stress on agriculture in terms of three objectives: assessing the regional vulnerability (exposure, sensitivity, and adaptive capacity), analysing the climate variability, and measuring agricultural performance under climatic stress. The vulnerability of twenty-two sub-regions in Jammu, Kashmir, and Ladakh is assessed using indicators to determine the collective susceptibility of the agricultural framework to climate change. An index-based approach with min–max normalization is employed, ranking the districts based on their relative performances across vulnerability indicators. This work assesses the impact of socio-economic and climatic indicators on the performance of agricultural growth using the benchmark Ricardian approach. The parameters of the agricultural growth function are estimated using a linear combination of socio-economic and exposure variables. Lastly, the forecasted trends of climatic variables are examined using a long short-term memory (LSTM)-based recurrent neural network, providing an annual estimate of climate variability. The results indicate a negative impact of annual minimum temperature and decreasing land holdings on agricultural GDP, while cropping intensity, rural literacy, and credit facilities have positive effects. Budgam, Ganderbal, and Bandipora districts exhibit higher vulnerability due to factors such as low literacy rates, high population density, and extensive rice cultivation. Conversely, Kargil, Rajouri, and Poonch districts show lower vulnerability due to the low population density and lower level of institutional development. We observe an increasing trend of minimum temperature across the region. The proposed LSTM synthesizes a predictive estimate across five essential climate variables with an average overall root mean squared error (RMSE) of 0.91, outperforming the benchmark ARIMA and exponential-smoothing models by 32–48%. These findings can guide policymakers and stakeholders in developing strategies to mitigate climate stress on agriculture and enhance resilience.

Union territory of Jammu and Kashmir, one of the leading producers of temperate fruits in India, is in the process of adopting high-density apple cultivation. Establishment of high-density apple orchard involves a very high cost which gets compensated by higher productivity during its productive life. Considering the profitability of cultivating high-density apple a need was felt to examine its quality and yield potential that could guide the Government to formulate a roadmap for its dissemination in its domain area. High-density apple (variety-Super Chief Sandidge) was recently introduced from Italy. It is reported to be very productive and quality wise, retains a high score of consumer acceptability, accordingly efforts are being made to extend its adoption in the union territory of Jammu and Kashmir. To formulate a policy for its adoption, ex-ante evaluation was carried out by employing economic surplus model on the experimental data collected from the technical expert group of scientists involved in its cultivation, assessment, evaluation and dissemination. The results reveal that productivity of apple has increased by 53.6 mt/ha and labor employment has increased by 676 man days/ha due to the adoption of high-density apple technology. The results further revealed that with an expected expansion of high-density apple orchards over 30% of the target area NPV, IRR and BC ratio would amount to 16.43 Billion US $, 62% and 98.60.

This study comprehensively investigated the livelihood security scenario of fisher households employing the CARE framework with little modifications, in Kashmir, India. Primary data for this study was collected from selected fisher households, and a regression function was fitted to quantify the determinants of livelihood security. The findings revealed that fishing has been their dominant livelihood option. The landholding owned by the households was meagre enough to carry out farming or domesticate animals on commercial lines. Poor capital endowments place them at less livelihood security level; however, the respondents with diversified income have a relatively higher index value for livelihood. The regression estimates indicated that barring social and natural capital, all forms of capital have a significant role to play in securing their livelihood. Poor livelihood security, coupled with less income flow, has made their survival vulnerable to various distresses and health disorders, including the prevalence of infant and maternal mortality. Their dietary intake was undesirably less than their dietary recommendations. The COVID-19 pandemic was perceived as a shock to their livelihood security. Further, public investment, which is pertinent for the growth of the fisheries sector, has shown a discouraging trend. The study concluded with a few policy suggestions for securing the livelihood of the fisher community.

To arrive at good land governance imperatives, we study land degradation in Jammu & Kashmir. The panel regression estimates indicate that rural literacy and direct institutional credit to farmers reduce land degradation in the state and rural population density and urban population growth increase it. Public investment in agricultural production is critical for land development, irrigation, and forestry, but it has declined recently in absolute and proportionate terms, and poor execution of acts and reforms have brought about deficits in land governance. The study suggests options for making the state's land governance policy efficient and developing its resources.

Considering the crucial role of institutional support in the livestock growth, an attempt was made to analyze the development of livestock sector in relationship with public investment in livestock sector and selected infrastructure variables in J&K. Livestock sector has shown a significant growth and has increasingly contributed to the state gross domestic product over the years. Government has been pro-active with towards the development of livestock sector with various schemes; however, the public investment has experienced a deceleration and its intensity has reduced over the years. The stock of animal health institutions has increased though their density has remained almost stagnant. Livestock productivity model was development to quantify the impact of public sector investment, infrastructure and other variables on livestock productivity. The estimates of the model revealed that public investment in livestock sector and infrastructure variables including animal health infrastructure have significant contribution in the growth of livestock productivity. The study concluded with an emphasized upon the creation of necessary infrastructure and the reversal of the declining trend of investment to this sector among other policy options suggested for the sustained growthof livestock inthe territory.