The concerns about climate change in recent decades have heightened the need for effective methods for assessing and reporting forest biomass and Carbon Stocks (CS) at local, national, continental, and global scales. Accurate assessment of Aboveground Biomass (AGB) is critical for the sustainable management of forests, especially in the Chure region, a fragile and young mountainous in the lesser Himalaya of Nepal. This paper presents the modeling and mapping approach and shows how medium-resolution Sentinel-2 multispectral instrument (MSI) data can be used instead of hyperspectral data in inaccessible areas of the Chure region. The data were collected and analyzed from 72 circular sample plots. 60 (43 random sample plots) were used to create the model, while the remaining 40 (29 plots) were used for model validation. This study involved calculating 12 different vegetation indices and correlating them with plot-level AGB. Five models, including linear, logarithmic, quadratic, power, and exponential, were created, but the best model was found to be the quadratic model using normalized difference vegetation indices (NDVIs) with an R² value of 0.777 and a correlation coefficient of 0.881. The models AIC and BIC values were 313.60 and 320.65, respectively. The validity of the model was performed using observed and predicted AGB values, resulting in an r value of 0.9128, an R² value of 0.8332, and an RMSE value of 10.7657th⁻¹. Finally, the developed regression equation was used to map AGB in the study area. The AGB per pixel ranges from 0 to 129.18th⁻¹, whereas the amount of CS ranges from 0 to 61.01th⁻¹. Among the different vegetation indices used in the study, NDVI was found to be more precise in estimating and mapping biomass and carbon stocks in this study. Therefore, the study recommends using the quadratic model of NDVI for accurate estimation of AGB and CS in the Chure region of Sainamaina municipality.

Crop productivity is directly dependent on soil fertility. High organic carbon content in soil is vital as it leads to improved soil quality, increased productivity, and stable soil aggregates. In addition, with the signing of the climate agreement, there is growing interest in carbon sequestration in landscapes. This paper looks at how soil organic carbon (SOC) can be increased so that it contributes not only to the reduction of atmospheric CO₂, but also translates to the increased food production, thereby enhancing food security. This synergy between climate change mitigation and enhancing food security is even more relevant for mountain landscapes of the Hindu Kush Himalayan (HKH) region where there remains huge potential to increase CO₂ sequestration and simultaneously address food security in the chronic food deficit villages. Soil samples were collected from seven transects each in Bajhang and Mustang and from four land use types in each transect. Samples of soils were taken from two depths in each plot: 0–15 cm and 15–30 cm below the soil surface to compare the top soil and subsoil dynamics of the soil nutrients. The lab analysis was performed to assess the soil texture, soil acidity in “power of hydrogen” (pH), and macro-nutrients reflecting soil fertility. Secondary data was used to analyze the level of food deficit in the villages. The pH value of soil from Bajhang ranged from 5.3 to 9.1. The pH value of soil ranged from 5.7 to 8.8 in Mustang. SOC contents of sampled soils from Bajhang ranged from 0.20% to 7.69% with a mean amount of 2.47% ± 0.17%. SOC contents of sampled soils from Mustang ranged from 0.51% to 8.56% with a mean amount of 2.60% ± 0.25%. By land use type, forest land had the highest carbon (C) content of 53.61 t·ha⁻¹ in Bajhang, whereas in Mustang, agricultural land had the highest C content of 52.02 tons·ha⁻¹. Based on these data, we can say that there is potential for increasing SOC through improved soil health and crop production holistic soil management should be practiced for higher productivity, and incorporating livestock for farmyard manure would fertilize cultivated soils, which increases soil productivity. Increasing productivity would aid in enhancing the access and availability of food in these mountain villages.

Despite the potentiality of community forests to receive payment in turn its contribution of global carbon abatement, inadequate technical difficulties and scientifc base limit the carbon estimation and claim for the payment of carbon compensation in international market. This paper intends to provide an overview of participatory biomass and carbon estimation of CF in Nepal. Synthesized methodologies of national inventory guidelines, IPCC, McDicken and literature estimates were used to execute inventory and calculate the biomass and carbon density. The study found that GPS consumes less time to mapping boundary and laying out sample plots permanently with less systematic and personal errors than using compass survey. The ground based inventory is time consuming, the study concludes that the making capable local users in handling GPS and promoting participatory inventory and carbon calculation avoids the cost thereby make CFs able to claim in access to international carbon market. Key Words: GPS, Biomass, Abatement, Compensation, International carbon market DOI: 10.3126/init.v2i1.2528 The Initiation Vol.2(1) 2008 pp91-98

Land management regimes and forest types play an important role in the productivity and accumulation of terrestrial carbon pools. While it is commonly accepted that forests enhance carbon sequestration and conventional agriculture causes carbon depletion, the effects of agro-forestry are not well documented. This study investigated the carbon stocks in biomass and soil, along with the selected soil properties in agro-forestry plots compared to community forests (CF) and upland farms in Chitwan, Gorkha and Rasuwa districts of Central Nepal during the year 2012-2013. We determined the total above ground biomass carbon, soil organic carbon (SOC) stocks and soil properties (bulk density, organic carbon per cent, pH, total nitrogen (TN), available phosphorus (P), exchangeable potassium (K), and cation exchange capacity (CEC)) on samples taken from four replicates of 500 m² plots each in community forests, agro-forestry systems and agricultural land. The soil was sampled in two increments at 0-15 cm and 15-30 cm depths and intact cores removed for bulk density and SOC determination, while loose samples were separately collected for the laboratory analysis of other soil properties. The mean SOC percent and corresponding soil carbon stocks to 30 cm depth were generally highest in CF (3.71 and 3.69 per cent, and 74.98 and 76.24 t ha^-1, respectively), followed by leasehold forest (LHF) (2.26 and 1.13 per cent and 40.72 and 21.34 t ha^-1, respectively) and least in the agricultural land (3.05 and 1.09 per cent, and 63.54 and 19.42 t ha^-1, respectively). This trend was not, however, observed in Chitwan, where agriculture (AG) had the highest SOC content (1.98 per cent) and soil carbon stocks (42.5 t ha^-1), followed by CF (1.8 per cent and 41.2 t ha^-1) and leasehold forests (1.56 per cent and 35.3 t ha^-1) although the differences were not statistically significant. Other soil properties were not significantly different among land use types with the exceptions of pH, total N, available P and CEC in the Chitwan plots. Typically, SOC and soil carbon stocks (to 30cm depth) were positively correlated with each other and with TN and CEC. The AGB-C was expectantly highest in Rasuwa district CF (ranging from 107.3 to 260.3 t ha^-1) due to dense growth and cool climate, followed by Gorkha (3.1 to 118.4 t ha^-1), and least in Chitwan (17.6 to 95.2 t ha^-1). The highest C stocks for agro-forestry systems in both above ground and soil were observed in Rasuwa, followed by Chitwan district. Besides forests, agro-forestry systems also hold good potential to store and accumulate carbon, hence they have scope for contributing to climate change mitigation and adaptation with co-benefits. Journal of Forest and Livelihood 13(1) May, 2015, page: 56-68

As part of the REgional Carbon Cycle Assessment and Processes‐2 (RECCAP‐2) project of the Global Carbon Project, here we estimate the GHG budgets (anthropogenic and natural sources and sinks) for the South Asia (SA) region as a whole and each country (Afghanistan, Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri Lanka) for the decade of 2010–2019 (2010s). Countries in the region are experiencing a rapid rise in fossil fuel consumption and demand for agricultural land, leading to increased deforestation and higher greenhouse gas emissions. This study synthesizes top‐down (TD) and bottom‐up (BU) dynamic global vegetation model results, BU GHG inventories, ground‐based observation upscaling, and direct emissions for major GHGs. The fluxes for carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) analyzed include fossil fuel emissions, net biome productivity, land use change, inland waters, wetlands, and upland and submerged soils. Our analysis shows that the overall total GHG emissions contributed to a net increase of 34%–43% during the 2010s compared to the 2000s, primarily driven by industrial activities. However, terrestrial ecosystems acted as a notable exception by serving as a CO₂ sink in the 2010s, effectively sequestering atmospheric carbon. The sink was significantly smaller than overall carbon emissions. Overall, the 2010s GHG emissions based on BU and TD were 4,517 ± 639.8 and 4,532 ± 807.5 Tg CO₂ eq, with CO₂, CH₄, and N₂O emissions of 2165.2 ± 297.1, 1,404 ± 95.9, and 712 ± 466 Tg CO₂ eq based on BU models 2,125 ± 515.1, 1,531 ± 205.2, and 876 ± 446.0 Tg CO₂ eq based on TD models. Total emissions from SA in the 2010s accounted for approximately 8% of the global share. The terrestrial CO₂ sinks estimated by the BU and TD models were 462.9 ± 195.5 and 210.0 ± 630.4 Tg CO₂, respectively. Among the SA countries, India was the largest emitter contributing to 80% of the region's total GHG emissions, followed by Pakistan (10%) and Bangladesh (7%).