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This study introduces Multi-dimensional Disparity Index (MDI) to measure multi-form of disparity in different level of governments referencing Nepal. The measurement scale of MDI was developed by adopting Santos and Alkire's (2011) approaches. A wide range of thematic experts was consulted, employing the Semi-Delphi approach to determine its dimensions and indicators. The MDI in this study includes six dimensions and 34 indicators composited with dimension-wise indices like Economy Disparity Index [ECODI], Educational Disparity Index [EDUDI], Health Disparity Index [HDI], Geography and Climatic Vulnerability Index [GCVI], Living Standard Disparity Index [LSDI], and Demography Disparity Index [DDI]. Overall, the study revealed the extent of multi-dimensional disparity across three tiers of government in Nepal. More specifically, Nepal scored 0.388 MDI value. Karnali and Bagmati provinces are accounted as the highest and least deprived. This study contributes essential knowledge, particularly in exploring the dimensions and their indicators and develops an approach to measure multi-dimensional disparities. Most existing approaches for assessing disparities are mono-dimensional and measure the disparities in a single aspect. In this context, MDI provides a broader approach to consider multiple dimensions and measures multiple aspects in a country like Nepal, where disparity manifests at multiple levels. [ABSTRACT FROM AUTHOR]

Understanding the spatial spreading patterns of plant-available sulphur (S) (AS) and plant-available micronutrients (available zinc (AZn), available iron (AFe), available copper (ACu), available manganese (AMn) and available boron (AB)) in soils, especially in coastal agricultural soils subjected to various natural and anthropogenic activities, is vital for sustainable crop production by adopting site-specific nutrient management (SSNM) strategies. We studied the spatial distribution patterns of AS, AZn, AFe, ACu, AMn, and AB in cultivated soils of coastal districts of India using geostatistical approaches. Altogether 39,097 soil samples from surface (0 to 15 cm depth) layers were gathered from farm lands of 68 coastal districts. The analysis of soil samples was carried out for soil pH, electrical conductivity (EC), soil organic carbon (SOC) and AS, AZn, AFe, ACu, AMn, and AB. Soil pH, EC and SOC varied from 3.70 to 9.90, 0.01 to 7.45 dS m-1 and 0.02 to 3.74%, respectively. The concentrations of AS, AZn, AFe, ACu, AMn, and AB varied widely in the study area with their corresponding mean values were 37.4±29.4, 1.50±1.53, 27.9±35.1, 2.14±1.74, 16.9±18.4 and 1.34±1.52 mg kg-1, respectively. The coefficient of variation values of analyzed soil parameters varied from 14.6 to 126%. The concentrations of AS, AZn, AFe, ACu, AMn, and AB were negatively and significantly correlated with soil pH and positively and significantly correlated with SOC. The geostatistical analysis indicated stable, Gaussian and exponential best-fit semivariogram models with moderate to strong spatial dependence for available nutrients. The generated spatial spreading maps revealed different distribution patterns for AS, AZn, AFe, ACu, AMn, and AB. There were variations in spatial spreading patterns of AS, AZn, AFe, ACu, AMn, and AB in east- and west-coastal area. About 62, 35, 12, 0.4, 23 and 45% of the study area had deficiency of AS, AZn, AFe, ACu, AMn, and AB, respectively. The spatial spreading maps will be highly useful for SSNM in the cultivated coastal soils of the country. This study could also be used as a base for assessing spatial spreading patterns of soil parameters in cultivated coastal areas of other parts of the world. [ABSTRACT FROM AUTHOR]