Bhaskar Singh Karky

Gender Equality Challenges to the REDD+ Initiative in Nepal

Abstract Despite widespread gender issues in natural resource management and rural livelihoods strategies, there has been little study of how new development strategies, such as Reduced Emissions from Deforestation and Forest Degradation (REDD+), consider gender issues. Gender consideration in REDD+ is especially important in mountainous countries like Nepal, where the majority of the rural population, especially women and socioeconomically disadvantaged households, depend on forests for many of their subsistence needs. Any changes in forest access or use rights or rules as a result of REDD+ would impact marginalized people whose inclusion, voice, and access to and control over forest resources are influenced by deeply gendered power relations and socio-institutional practices in Nepali society. This article analyzes ways the REDD+ initiatives in Nepal have considered gender issues identified in earlier studies. The main finding is that the REDD+ policy process is inadequate to account for underlying power dynamics, and thus is unable to achieve equity goals. In the absence of accounting for power, the consideration of gender issues in forest management by explicit inclusion of women in the payment criteria and policy discussions within REDD+ programs, including the REDD+ payment pilot project, is insufficient to redress gender imbalances. Forest actors such as the government and other project implementers—including community institutions—lack strategies and responsibilities for applying REDD+ initiatives that are gender equitable and ensure REDD+ benefits and decision-making opportunities for women and other marginalized people. To tap the potential of REDD+ to contribute to both climate change mitigation and mountain development, efforts are needed to make REDD+ national strategy- and policy-making gender sensitive. The critical areas to be addressed in Nepal include framing the REDD+ strategy within the forest ministrys Gender and Social Inclusion Strategy 2008, and then by judicious implementation ensuring access of poor and disadvantaged women and men to forest resources, carbon funds, and decision-making roles in order to undermine entrenched unequal relations.

Integration of WorldView-2 and airborne LiDAR data for tree species level carbon stock mapping in Kayar Khola watershed, Nepal

Abstract Integration of WorldView-2 satellite image with small footprint airborne LiDAR data for estimation of tree carbon at species level has been investigated in tropical forests of Nepal. This research aims to quantify and map carbon stock for dominant tree species in Chitwan district of central Nepal. Object based image analysis and supervised nearest neighbor classification methods were deployed for tree canopy retrieval and species level classification respectively. Initially, six dominant tree species ( Shorea robusta, Schima wallichii, Lagerstroemia parviflora, Terminalia tomentosa, Mallotus philippinensis and Semecarpus anacardium ) were able to be identified and mapped through image classification. The result showed a 76% accuracy of segmentation and 1970.99 as best average separability. Tree canopy height model (CHM) was extracted based on LiDAR’s first and last return from an entire study area. On average, a significant correlation coefficient ( r ) between canopy projection area (CPA) and carbon; height and carbon; and CPA and height were obtained as 0.73, 0.76 and 0.63, respectively for correctly detected trees. Carbon stock model validation results showed regression models being able to explain up to 94%, 78%, 76%, 84% and 78% of variations in carbon estimation for the following tree species: S. robusta, L. parviflora, T. tomentosa, S. wallichii and others (combination of rest tree species).

Robustness of model-based high-resolution prediction of forest biomass against different field plot designs

BackgroundParticipatory forest monitoring has been promoted as a means to engage local forest-dependent communities in concrete climate mitigation activities as it brings a sense of ownership to the communities and hence increases the likelihood of success of forest preservation measures. However, sceptics of this approach argue that local community forest members will not easily attain the level of technical proficiency that accurate monitoring needs. Thus it is interesting to establish if local communities can attain such a level of technical proficiency. This paper addresses this issue by assessing the robustness of biomass estimation models based on air-borne laser data using models calibrated with two different field sample designs namely, field data gathered by professional forester teams and field data collected by local communities trained by professional foresters in two study sites in Nepal. The aim is to find if the two field sample data sets can give similar results (LiDAR models) and whether the data can be combined and used together in estimating biomass.Results Results show that even though the sampling designs and principles of both field campaigns were different, they produced equivalent regression models based on LiDAR data. This was successful in one of the sites (Gorkha). At the other site (Chitwan), however, major discrepancies remained in model-based estimates that used different field sample data sets. This discrepancy can be attributed to the complex terrain and dense forest in the site which makes it difficult to obtain an accurate digital elevation model (DTM) from LiDAR data, and neither set of data produced satisfactory results.Conclusions Field sample data produced by professional foresters and field sample data produced by professionally trained communities can be used together without affecting prediction performance provided that the correlation between LiDAR predictors and biomass estimates is good enough.

Forest inventory and analysis in Gilgit-Baltistan: A contribution towards developing a forest inventory for all Pakistan

Purpose The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve. Design/methodology/approach Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation. Findings Representative circular 556 forest sample plots of 1,000 m2 contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813. Research limitations/implications Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned. Practical implications Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation. Originality/value This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.