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In the current era of global warming, the Himalayan forests are under tremendous pressure due to intensified anthropogenic activity, resulting in the loss of forest diversity. However, the potential of carbon (C) sinks for increasing carbon storage and/or sequestration is still uncertain. Therefore, the present study was undertaken to examine the C-sequestration and mitigation potential of eight different tree plantations, namely: Pinus roxburghii, Quercus leucotrichophora, Acacia mollissima, Acacia catechu, Alnus nitida, Albizia procera, Ulmus villosa, and Eucalyptus tereticornis in the mid-hills of the Indian Himalayas. The soil samples used in our study (humus, 0-20cm, 20-40cm, and 40-100 cm) were used to determine the soil and ecosystem Cdensity. The analysis revealed that the maximum tree biomass (300.19 Mg ha À1 ), vegetation biomass (305.43 Mg ha À1 ), vegetation carbon (153.59 Mg ha À1 ), and total ecosystem C density (369.93 Mg ha À1 ) occurred under U. villosa plantation. Similarly, P. roxburghii plantations had the maximum detritus C-density (7.25 Mg ha À1 ), whereas A. nitida (224.71 Mg ha À1 ) had the maximum soil C-density. The highest Csequestration was recorded under U. villosa (183.0 Mg ha À1 ). A significantly higher and lower rate of C-sequestration and CO 2 mitigation was observed in Ulmus villosa (5.9 and 21.64 Mg ha À1 yr À1 ) and Eucalyptus tereticornis (3.9 and 14.3 Mg ha À1 yr À1 ).Our study found that indigenous tree species such as U. villosa, A. procera, A. nitida, and Q. leucotrichophora should be encouraged for afforestation on degraded lands to support climate change mitigation strategies in the sub-temperate forest ecosystem.

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Soil loss due to erosion has a huge impact on worldwide economy and environment. Himalayan region is extremely vulnerable to erosion due to rugged terrain, erratic precipitation and excessive anthropogenic pressures. This study attempts to assess the spatial distribution of soil loss for managing soil disintegration rates in the western Himalayas using GIS modeling approach. Factors affecting soil erosion were assessed and mapped using primary data from the field and secondary data. Map layers were developed for each identified factors and modeled using weighted overlay analysis. The rainfall-runoff erosivity, soil erodibility, topographic, cover management and support parameters varied around 361.75 MJ mm/ha/h/yr, (0.024 - 0.051) t ha h/ha/MJ/mm, 0 to 585.372, 0 to 1 and 0 to 1 respectively. The yearly soil disintegration rate varied between 0 and 6098.44 t ha/yr. The maximum area (137165.30 ha) of the district’s total area (146295.142 ha) was under the less vulnerable class and the minimum (259.92 ha) was under the severely vulnerable category. The findings reported 70.24% of the area was under the less vulnerable class, followed by extremely vulnerable (10.48%) > highly vulnerable (7.40%) > severely vulnerable (7.19%) > moderately vulnerable (4.69%). The maximum (810 t/ha) and minimum (15 t/ha) mean soil loss was found under severely vulnerable and less vulnerable categories. The findings will provide site specific data regarding soil loss and vulnerability for effective management of soils in the eco-sensitive region.