Abstract
Background: Participatory 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.
| Original language | English |
|---|---|
| Article number | 29 |
| Journal | Carbon Balance and Management |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Dec 2015 |
| MoE publication type | A1 Journal article-refereed |
Funding
This work has been carried out with the financial and institutional supports from the Governments of Finland and Nepal under the Forest Resource Assessment (FRA) Nepal project and ICIMOD. We would like to thank Finnmap International for successful completion of the airborne laser scanning. Our special thanks go to our field teams and community forest user group mem‑ bers for timely and accurate field data collection. community-based REDD+ pilot at micro-watershed level. ICIMOD and its partners, the Federation of Community Forestry Users, Nepal (FECOFUN) and the Asia Network for Sustainable Agriculture and Bioresources (ANSAB) implemented a pilot project from 2009–2013, with support from the Norwegian Agency for Development Cooperation (NORAD) climate and forest Initiative [4]. The major focus of the project was to develop and demonstrate an innovative benefit-sharing mechanism for REDD+ incentives using institutionally and socially inclusive approaches to address the drivers of deforestation and forest degradation and improve forest governance [5] in three micro-watersheds, namely Kayarkhola in Chitwan, Ludikhola in Gorkha and Charanawati in Dolakha districts. The pilot project focused on sequestering carbon through community-based forest management. It is one of the first carbon offset demonstration projects in the world that involves local communities in monitoring the carbon in their forests and providing the necessary training for them to do so. Training on assessing forest carbon pools was provided to the local communities that manage the forest [6]. The trained local communities collected field plot data from 2010 to 2012. The results of this effort are summarized in [7].
Keywords
- Above-ground biomass
- LiDAR
- Participatory forest monitoring
- REDD+
