Soil organic carbon estimation along an altitudinal gradient of chir pine forests in the Garhwal Himalaya, India: A field inventory to remote sensing approach

Abstract

Chir pine (Pinus roxburghii, Sarg.) forests are dominant in the Indian Himalayan region and act as a huge carbon (C) sink. However, measuring the C sink in soil is complex and time-intensive, and therefore the present study attempts to estimate the soil organic carbon (SOC) through a remote sensing (RS) approach. We estimated SOC stock of chir pine forests along an altitudinal gradient at three soil depths (0-30, 30-60 and 60-100 cm) in the Garhwal Himalaya, Uttarakhand. Fourteen forest stands at four altitudes, viz., <1000 m above sea level (m asl), 1001-1400 m asl, 1401-1800 m asl and >1801 m asl were surveyed and served for data collection. A model for predicting SOC was developed through stepwise regression analysis based on vegetation information and altitude as independent variables with the field data on SOC.For vegetation information, we used the normalized difference vegetation index (NDVI) measured through remote sensing (RS). The mean SOC stock up to 100 cm depth was increased with increasing altitude and were in the order of 69.

Land degradation and development in India: Status quo, challenges and opportunities

“…They found that FRB was highest for the uppermost, organo‐mineral‐rich soil depth (0–20 cm) at 1 m distance from the tree bole and decreased with increasing soil depth, increasing girth size of tree bole and distance from the tree bole while fine root runover (FRT) showed the opposite pattern. Due to difficulties in quantifying carbon stocks in forests across large scales, Kumar, Kumar, et al (2022) developed new remote sensing tool for carbon quantification. They found soil organic carbon increased with altitude and was positively correlated with normalized difference vegetation index (NDVI) in chir pine ( Pinus roxburghii ) forests in Uttarakhand.…”

“…They found soil organic carbon increased with altitude and was positively correlated with normalized difference vegetation index (NDVI) in chir pine ( Pinus roxburghii ) forests in Uttarakhand. They found that these proxies could be used to accurately predict soil organic carbon stocks (Kumar, Kumar, et al, 2022). This tool can be helpful in monitoring carbon capture and sequestration targets set by India in its INDCs.…”

Nutrient return through decomposing Coriaria nepalensis litter in degraded hills of Kumaun Himalaya, India

“…All analyses were carried out in triplicate. Total Nitrogen (N) concentration was determined by the micro-Kjeldahl method (Jackson, 1958;Kumar et al, 2022). Phosphorous (P) concentration was estimated by the Olsen's method (Olsen et al, 1954;Wieczorek et al, 2022) using spectrophotometer and the potassium, i.e., exchangeable potassium was determined by flame photometer (Black, 1965;Banerjee and Prasad, 2020) in Soil testing laboratory, Tea Development Board, Bhowali, Nainital.…”

Traditional Uses and Ethno-Medicinal Plants: Insights From the Korba District of Chhattisgarh, India

“…Vegetation analysis is an important tool to study species composition and phyto-sociological structure of the plant community. It helps to quantify various lands, conservation management of endangered species, soil and water (Kumar et al, 2022). Vegetation analysis plays a very important role in adaptation of plants to future climate change (Pandey et al, 2022).…”