Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

Abstract

The United Nations’ expanded program for Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to mobilize capital from developed countries in order to reduce emissions from these sources while enhancing the removal of greenhouse gases (GHGs) by forests. To achieve this goal, an agreement between the Parties on reference levels (RLs) is critical. RLs have profound implications for the effectiveness of the program, its cost efficiency, and the distribution of REDD+ financing among countries. In this paper, we introduce a methodological framework for setting RLs for REDD+ applications in tropical forests in Xishuangbanna, China, by coupling the Good Practice Guidance on Land Use, Land Use Change, and Forestry of the Intergovernmental Panel on Climate Change and land use scenario modeling. We used two methods to verify the accuracy for the reliability of land classification. Firstly the accuracy reached 84.43%, 85.35%, and 82.68% in 1990, 2000, and 2010, respectively, based on high spatial resolution image by building a hybrid matrix. Then especially, the 2010 Globeland30 data was used as the standard to verify the forest land accuracy and the extraction accuracy reached 86.92% and 83.66% for area and location, respectively. Based on the historical land use maps, we identified that rubber plantations are the main contributor to forest loss in the region. Furthermore, in the business-as-usual scenario for the RLs, Xishuangbanna will lose 158,535 ha (158,535 × 104 m2) of forest area in next 20 years, resulting in approximately 0.23 million t (0.23 × 109 kg) CO2e emissions per year. Our framework can potentially increase the effectiveness of the REDD+ program in Xishuangbanna by accounting for a wider range of forest-controlled GHGs.

Spatial–Temporal Dynamics of Forest Extent Change in Southwest China in the Recent 20 Years

“…Due to the large areas of plantations, the results of hotspots in this region will become complicated, which may reflect the harvest cycles within plantation boundaries. In addition, the economic development in Xishuangbanna in Yunnan Province has promoted the cultivation of commodity agriculture such as rubber and tea in the last two decades, hence inevitably resulting in significant forest loss [49]. Many of the sporadic hotspots intersected with the widely known tropical rainforest area in these regions potentially suggesting that the primary forest is being destroyed there.…”

Identification of Socio-Economic Impacts as the Main Drivers of Carbon Stocks in China’s Tropical Rainforests: Implications for REDD+

“…Deforestation in Xishuangbanna emitted almost 90 million tons of carbon stocks for the period 1976–2003 and will lead to a further 4 million tons of carbon emissions under current deforestation rate in the next 20 years [ 45 , 46 , 47 ]. Such forestland conversion will also cause significant loss of biodiversity, substantial soil erosion, and large declines in other ecosystem services, including the production of clean water, water conservation, and the supply of non-timber forest products [ 48 ]. As a result, it is important to balance economic growth and conservation goals for local policy makers in this rapidly developing region.…”

Land Degradation Assessment with Earth Observation

“…One of the papers of the Special Issue deals with the humid tropics. In their study, Liu et al [16] propose a framework for the improved accounting of reference levels (RLs) for the United Nations' Reducing Emissions from Deforestation and Forest Degradation (REDD+) programme. They combine the Intergovernmental Panel on Climate Change's (IPCC) Good Practice Guidance on Land Use, Land Use Change and Forestry with a land use change modelling approach and apply this to an area in southern China.…”