In absence of soil erosion plots for determination of erodibility index (K) for erosion models like Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE) to estimate soil erosion, empirical relations are used. In the present study, soil erodibility index was determined for entire Ri-bhoi district of Meghalaya based on soil physical and chemical properties through empirical relationship and presented in a map form. Dominant land uses of the district were identified through geo-spatial tools which were viz. agriculture, forest, jhum land and wasteland. Soil samples from surface depth (01–15 cm) were collected from areas of different dominant land uses. Twenty five sampling points were selected under each land use type and geo-coded them on the base map of Ri-bhoi district. Apart from K-index, Clay Ratio, Modified Clay Ratio and Critical Soil Organic Matter were also determined for understanding the effect of primary soil particles on erodibility. In agriculture land use system K-index values were found in the range of 0.08–0.41 with an average of 0.25 ± 0.02. In case of jhum, forest and wasteland these were in the range of 0.08–0.42 with an average of 0.20 ± 0.01; 0.09–0.40 with an average of 0.22 ± 0.02, and 0.10–0.34 with an average value of 0.23 ± 0.02, respectively. Clay ratio (2.74) and Modified clay ratio (2.41) were observed to be higher in forest LUS, lower clay ratio (1.97) and modified clay ratio (1.81) were found in the wasteland indicating erosion susceptibility in forested area. The values of Critical Level of Organic Matter (CLOM) for the district ranged from 4.72 to 16.56. Out of 100 samples, only one sample had CLOM value less than 5 and rest 99 samples had values more than 5 indicating that the soils of the district had moderate to stable soil structure and offer resistance to erosion. All the indices values of geo-coded points were then interpolated in the Arc-GIS environment to produce land use based maps for Ri-bhoi district of Meghalaya. As K-index is a quantitative parameter which is used in models, the index can be then interpolated for estimation of soil erosion through USLE or RUSLE for any given situation.

The 18 September 2011 Sikkim Himalaya earthquake of Mw 6.9 (focal depth 50 km, NEIC report) with maximum intensity of VII on MM scale (www.usgs. gov) occurred in the Himalayan seismic belt (HSB), to the north of the main central thrust. Neither this thrust nor the plane of detachment envisaged in the HSB model, however, caused this strong devastating earthquake. The EngdahlHilst-Buland (EHB) relocated past earthquakes recorded during 1965-2007 and the available global centroid moment tensor) solutions are critically examined to identify the source zone and stress regime of the September 2011 earthquake. The depth section plot of these earthquakes shows that a deeper (10-50 km) vertical fault zone caused the main shock in the Sikkim Himalaya. The NW (North-West) and NE (North-East) trending transverse fault zones cutting across the eastern Himalaya are the source zones of the earthquakes. Stress inversion shows that the region is dominated by horizontal NNW-SSE (North of North-West-South of South-East) compressional stress and low angle or near horizontal ENE-WSW (East of North-East-West of South-West) tensional stress; this stress regime is conducive for strike-slip faulting earthquakes in Sikkim Himalaya and its vicinity. The Coulomb stress transfer analysis indicates positive values of Coulomb stress change DS f for failure in the intersecting deeper fault zone that produced the four immediate felt aftershocks (M ! 4.0).

A field experiment was conducted during the rabi seasons of 2010 to 2013 to find out the optimum time of sowing and plant spacing for broccoli (var. KTS-1) seed production. Seedlings raised by sowing on four different dates viz. 10 th October, 30 th October, 20 th November and 10 th December were transplanted at two spacing viz. 45 cm x 45 cm and 60 cm x 45 cm. Yield and yield attributing characters were significantly influenced by the treatments. Sowing on 10 th October produced the highest head yield (137.81q/ha) while 10 December sowing produced the lowest head yield (6.75 q/ha) of broccoli. Closer spacing (45 cm x 45 cm) gave significantly higher head yield (88.28 q/ha) than planting at 60 cm x 45 cm distance. The highest seed yield (177 kg/ha) was obtained on planting 10 October sown seedlings at 45 cm x 45 cm distance and was the most remunerative (B: C ratio of 6.44) among all the treatment combinations. Plants from delayed sowing of 20 th November and 10 th December failed to produce viable seeds under agro-climatic condition of Assam.

A number of related enzymes like glutathione S-transferases (GSTs) and fatty acid ethyl ester synthases (FAEESs) have been implicated in detoxification and drug resistance. The anionic class of GSTs, π, and closely related FAEES-III exhibit tissue-specific and developmentally regulated expression, and the former has been shown to be overex-pressed or amplified in a variety of tumors. The GSTPl gene has previously been cloned and cytogenetically localized to human 11q13 by in situ hybridization. Using a series of previously described radiation-reduced somatic cell hybrids, we have sublocahzed GSTP1 to 11q13. We isolated a genomic clone containing the entire GSTPl gene and sequenced it. Analysis of the 5’ region revealed 23 (TAAAA) tandem repeats interrupted by a single TA and TAA insertion. This repeat number differs among individuals. Eleven alleles in a mostly Caucasian sample were observed. This repeat has a polymorphism information content of 0.74. Linkage analysis of the Venezuelan reference pedigree places GSTP1 5 cM distal to PYGM and 4 cM proximal to FGF3 thereby providing a genetic marker half-way between these two loci. The sublocalization and genetic characterization of GSTPl facilitates linkage analysis of several disease genes mapped to this chromosome band as well as the correlation of genetic and physical markers in the region.

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Soil erosion from arable lands removes the top fertile soil layer (comprised of humus/organic matter) and therefore requires fertilizer application which affects the overall sustainability. Hence, determination of soil erosion from arable lands is crucial to planning conservation measures. A modeling approach is a suitable alternative to estimate soil loss in ungauged catchments. Soil erosion primarily depends on soil texture, structure, infiltration, topography, land uses, and other erosive forces like water and wind. By analyzing these parameters, coupled with geospatial tools, models can estimate storm wise and annual average soil losses. In this study, a hilly watershed called Nongpoh was considered with the objective of prioritizing critical erosion hazard areas within the micro-catchment based on average annual soil loss and land use and land cover and making appropriate management plans for the prioritized areas. Two soil erosion models namely Revised Universal Soil Loss Equation (RUSLE) and Modified Morgan–Morgan–Finney (MMF) models were used to estimate soil loss with the input parameters extracted from satellite information and automatic weather stations. The RUSLE and MMF models showed similar results in estimating soil loss, except the MMF model estimated 7.74% less soil loss than the RUSLE model from the watershed. The results also indicated that the study area is under severe erosion class, whereas agricultural land, open forest area, and scrubland were prioritized most erosion prone areas within the watershed. Based on prioritization, best management plans were developed at catchment scale for reducing soil loss. These findings and the methodology employed can be widely used in mountainous to hilly watersheds around the world for identifying best management practices (BMP).

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