Forests2014, 5(10), 2425-2439; doi:10.3390/f5102425 - published 30 September 2014 Show/Hide Abstract
Abstract: Reducing emissions from deforestation and forest degradation (REDD+) is an international climate policy instrument that is expected to tap into the large mitigation potential for conservation and better management of the world’s forests through financial flows from developed to developing countries. This paper describes the results and lessons learned from a pioneering REDD+ pilot project in Nepal, which is based on a community forest management approach and which was implemented from 2009–2013 with support from NORAD’s Climate and Forest Initiative. The major focus of the project was to develop and demonstrate an innovative benefit-sharing mechanism for REDD+ incentives, as well as institutionally and socially inclusive approaches to local forest governance. The paper illustrates how community-based monitoring, reporting, and verification (MRV) and performance-based payments for forest management can be implemented. The lessons on REDD+ benefit sharing from this demonstration project could provide insights to other countries which are starting to engage in REDD+, in particular in South Asia.
Forests2014, 5(10), 2400-2424; doi:10.3390/f5102400 - published 29 September 2014 Show/Hide Abstract
Abstract: The Congo Basin forests are a prime location for implementing REDD+. National REDD+ policy processes are ongoing and many REDD+ pilot initiatives are being demonstrated. However, the level of national engagement, progress and distribution of REDD+ activities varies considerably in the different Congo Basin countries. This study therefore uses a set of criteria to assess national and international policy initiatives and approaches for advancing REDD+ implementation in Cameroon and the Democratic Republic Congo (DRC), two countries where more than two thirds of the Congo Basin forests are concentrated. Our findings show that (i) both countries have shown the highest political presence at the international climate negotiations but DRC has invested more in the size of its delegation and side events; (ii) REDD+ donors, initiatives, and funding are disproportionately skewed towards DRC making it technically more advanced; (iii) the high political interest and institutional reforms in DRC favors private sector investments in REDD+ programs; and (iv) the REDD+ policy process is internally-driven in Cameroon with a strong national ownership, while it is externally-driven in DRC with weak national ownership. To advance REDD+, the government of DRC should embark on capacity building programs that ensure the transfer of REDD+ technical know-how from international to national actors while Cameroon needs to speed-up governance reforms and be more flexible in order to attract influential international REDD+ actors. This paper further provides specific recommendations.
Forests2014, 5(9), 2377-2399; doi:10.3390/f5092377 - published 25 September 2014 Show/Hide Abstract
Abstract: Fine-scale biomass maps offer forest managers the prospect of more detailed and locally accurate information for measuring, reporting and verification activities in contexts, such as sustainable forest management, carbon stock assessments and ecological studies of forest growth and change. In this study, we apply a locally validated method for estimating aboveground woody biomass (AGWB) from Advanced Land Observing Satellite (ALOS) Phased Array-type L-band Synthetic Aperture Radar (PALSAR) data to produce an AGWB map for the lowland pine savannas of Belize at a spatial resolution of 100 m. Over 90% of these woodlands are predicted to have an AGWB below 60 tha−1, with the average woody biomass of these savannas estimated at 23.5 tha−1. By overlaying these spatial estimates upon previous thematic mapping of national land cover, we derive representative average biomass values of ~32 tha−1 and ~18 tha−1 for the previously qualitative classes of “denser” and “less dense” tree savannas. The predicted average biomass, from the mapping for savannas woodlands occurring within two of Belize’s larger protected areas, agree closely with previous biomass estimates for these areas based on ground surveys and forest inventories (error ≤20%). However, biomass estimates derived for these protected areas from two biomass maps produced at coarser resolutions (500 m and 1000 m) from global datasets overestimated biomass (errors ≥275% in each dataset). The finer scale biomass mapping of both protected and unprotected areas provides evidence to suggest that protection has a positive effect upon woody biomass, with the mean AGWB higher in areas protected and managed for biodiversity (protected and passively managed (PRPM), 29.5 tha−1) compared to unprotected areas (UPR, 23.29 tha−1). These findings suggest that where sufficient ground data exists to build a reliable local relationship to radar backscatter, the more detailed biomass mapping that can be produced from ALOS and similar satellite data at resolutions of ~100 m provides more accurate and spatially detailed information that is more appropriate for supporting the management of forested areas of ~10,000 ha than biomass maps that can be produced from lower resolution, but freely available global data sets.
Forests2014, 5(9), 2345-2376; doi:10.3390/f5092345 - published 25 September 2014 Show/Hide Abstract
Abstract: China’s Conversion of Cropland to Forests Program (CCFP) is the world’s largest afforestation-based Payments for Ecosystem Services (PES) program, having retired and afforested over 24 million ha involving 32 million rural households. Prior research has primarily focused on the CCFP’s rural welfare impacts, with few studies on program-induced environmental improvements, particularly at the household level. In this study, data from a 2010 survey covering 2808 rural households from across China was analyzed using an interval regression model to explain household-reported survival rates of trees planted on program-enrolled cropland. In addition to household-level factors, we explore the influence of local conditions and institutional configurations by exploiting the wide diversity of contexts covered by the data set. We find that households with more available labor and more forestry experience manage trees better, but that higher opportunity costs for both land and labor have the opposite effect. We also find that the local implementation regime- e.g., the degree of prior consultation with participants and regular monitoring - has a strong positive effect on reported survivorship. We suggest that the level of subsidy support to participating households will be key to survivorship of trees in planted CCFP forests for some time to come.
Forests2014, 5(9), 2327-2344; doi:10.3390/f5092327 - published 22 September 2014 Show/Hide Abstract
Abstract: Variable retention harvesting is acknowledged as a cost-effective conservation measure, but previous studies have focused on the environmental value and planning cost. In this study, a model is presented for optimizing harvesting cost using a high resolution map generated from airborne laser scanning data. The harvesting cost optimization model is used to calculate the objective value of different scenarios. By comparing the objective values, better estimates of the opportunity cost of woodland key habitats are found. The model can be used by a forest manager when evaluating what silvicultural treatments to implement or as an input for improving the nature reserve selection problem for woodland key habitats or retention patches. The model was tested on four real-world cases, and the results indicate that terrain transportation costs vary more than reported in the literature and that it may be worthwhile to divide the opportunity cost into its direct and indirect components.
Forests2014, 5(9), 2307-2326; doi:10.3390/f5092307 - published 19 September 2014 Show/Hide Abstract
Abstract: Continuous maps of forest parameters can be derived from airborne laser scanning (ALS) remote sensing data. A prediction model is calibrated between local point cloud statistics and forest parameters measured on field plots. Unfortunately, inaccurate positioning of field measures lead to a bad matching of forest measures with remote sensing data. The potential of using tree diameter and position measures in cross-correlation with ALS data to improve co-registration is evaluated. The influence of the correction on ALS models is assessed by comparing the accuracy of basal area prediction models calibrated or validated with or without the corrected positions. In a coniferous, uneven-aged forest with high density ALS data and low positioning precision, the algorithm co-registers 91% of plots within two meters from the operator location when at least the five largest trees are used in the analysis. The new coordinates slightly improve the prediction models and allow a better estimation of their accuracy. In a forest with various stand structures and species, lower ALS density and differential Global Navigation Satellite System measurements, position correction turns out to have only a limited impact on prediction models.