Capturing forest dependency in the central Himalayan region: Variations between Oak (Quercus spp.) and Pine (Pinus spp.) dominated forest landscapes.

Our study explores the nexus between forests and local communities through participatory assessments and household surveys in the central Himalayan region. Forest dependency was compared among villages surrounded by oak-dominated forests (n = 8) and pine-dominated forests (n = 9). Both quantitative and qualitative analyses indicate variations in the degree of dependency based on proximity to nearest forest type. Households near oak-dominated forests were more dependent on forests (83.8%) compared to households near pine-dominated forests (69.1%). Forest dependency is mainly subsistence-oriented for meeting basic household requirements. Livestock population, cultivated land per household, and non-usage of alternative fuels are the major explanatory drivers of forest dependency. Our findings can help decision and policy makers to establish nested governance mechanisms encouraging prioritized site-specific conservation options among forest-adjacent households. Additionally, income diversification with respect to alternate livelihood sources, institutional reforms, and infrastructure facilities can reduce forest dependency, thereby, allowing sustainable forest management.

Geospatial quantification and analysis of environmental changes in urbanizing city of Kolkata (India).

Over the past five decades, the fragile wetland ecosystem surrounding the city of Kolkata has witnessed extensive changes in the name of urban development. In this study, we elaborate relationships among biophysical parameters and land surface temperature (LST) in Kolkata city and nearby surrounding areas where rapid urbanization has occurred. LST and associated surface physical characteristics were assessed using Landsat images acquired for the years 1989, 2006, and 2010. The satellite data was used to study the spatiotemporal urban footprint and correlation among normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI) and LST. Land use land cover (LULC) maps prepared using supervised classification had overall accuracy of 90, 88, and 86 % and kappa coefficient of 0.8726, 0.8455, and 0.8212 for 1989, 2006, and 2010, respectively. The spatial expansion as a consequence of increasing urban population is 108.94 km(2) over past two decades. The urban built-up in and around the city extends up to 88.71 km(2) in 1989, 144.64 km(2) in 2006, and 197.65 km(2) in 2010. These changes have attributed in elevating surface temperature in the study region. Analysis of biophysical parameters shows LST and NDBI having a positive correlation, LST and NDVI having negative correlation, while NDBI and NDWI having a perfectly negative correlation. Satellite estimated temperatures of the surface show a warming trend evident from increasing mean surface temperature values from 27.36 °C in 1989 to 30.025 °C in 2006 and 33.023 °C in 2010. The magnitude and extent of the estimates of LST are consistent with the urbanization pattern throughout the city and adjoining areas.