Forest Reference Emission Level Research Articles

A novel deforestation risk and baseline allocation model for the next generation of nested REDD+ projects

Nature-based solutions that use a counterfactual scenario depend heavily on the methodology used to determine the business as usual (BAU) case, i.e., the “baseline.” Reducing emissions from deforestation and forest degradation (REDD+) projects traditionally set baselines using a “reference area” as a control for estimating BAU deforestation and emissions in the treatment (project) area. While the REDD+ market is shifting from project-based to nested approaches as countries increase their efforts to meet nationally determined contributions (NDCs) to the Paris agreement’s global climate target, methodologies for allocating national baselines are not yet formalized and tested, despite an urgent need to scale the market. We present a novel method for mapping deforestation risk and allocating national forest reference emission levels (FREL) to projects: baseline allocation for assessed risk (BAAR). This approach provides a spatial predictor of future deforestation using a dynamic vector, and a method for allocating a FREL to differentiated risk areas at the project level. Here, we present BAAR using 34 REDD+ projects in the Democratic Republic of the Congo (DRC). We demonstrate the importance of risk-based FREL allocations to balance fitness for purpose and scientific rigor. We show how BAAR can be used by governments to focus voluntary carbon market finance in areas at highest risk of imminent deforestation, while maintaining alignment with nationally determined contribution (NDC) goals.

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

BackgroundThe nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability.MethodsWe used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery.ResultsSOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions.ConclusionsIn the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.

Assessment of Forest Cover Changes in Vavuniya District, Sri Lanka: Implications for the Establishment of Subnational Forest Reference Emission Level

Assessment of forest cover changes is required to establish the forest reference emission level (FREL) at any scale. Due to civil conflict, such assessments have not yet been undertaken in Sri Lanka, especially in the conflict zone. Here, we assessed the forest cover changes in Vavuniya District, Sri Lanka, from 2001 to 2020, using a combination of the Google Earth Engine (GEE) platform and the phenology-based threshold classification (PBTC) method. Landsat 5 TM data for 2001, 2006, and 2010, and Landsat 8 OLI data for 2016 and 2020 were used to classify forest cover by categories, and their related changes could be assessed by four categories, namely dry monsoon forest, open forest, other lands, and water bodies. With an overall average accuracy of 87% and an average kappa coefficient of 0.83, forest cover was estimated at 57.6% of the total land area in 2020. There was an increase of 0.46% per annum for the entire district between 2001 and 2010, but a drastic loss of 0.60% per year was observed between 2010 and 2020. Specifically, the dry monsoon forest lost 0.30%, but open forest gained 3.62% annually over the same period. Loss and gain of forest cover resulted in carbon emissions and removals of 165,306.6 MgCO2 and 24,064.5 MgCO2 annually, respectively, over the same period. Our findings could be used to set the baseline trend of deforestation, based on which, a subnational forest reference emission level can be established as an emission benchmark, against which comparisons of carbon emissions following the implementation of REDD+ activities can be made, and result-based payment can be claimed under the Paris Agreement.

Estimation of baseline emissions, forest reference emission level, and carbon removals due to forest area changes in Afghanistan between 1993 and 2030

To benefit from reducing deforestation under the Paris Agreement, developing countries need to establish a forest reference emission level (FREL) but no FREL study exists in Afghanistan yet. This study is aim at determining the FREL for Afghanistan between 2020 and 2030 using the retrospective and prospective approaches. Data of forest area in 1993 and 2010 and a Tier-2 emission factor were used to obtain the baseline emissions in closed forest, open forest, undifferentiated open forest, and high shrubs. Carbon stocks in four carbon pools were considered. Loss of closed forest emitted approximately 7.2 TgCO 2 year −1 , while increase in areas of other forest categories resulted in carbon sequestration of approximately 2.6 TgCO 2 year −1 between 1993 and 2010. Depending on the chosen approaches, FRELs in Afghanistan can range from 1.3 TgCO 2 year −1 for retrospective approach to as high as 2.3 TgCO 2 year −1 for prospective approach between 2020 and 2030. Enhancement of carbon stocks and reducing deforestation could achieve emission reductions amounting up to 36.4% of the total emissions in Afghanistan. This study was the first attempt to determine the national FREL in Afghanistan, paving the way for understanding the impacts of future development on deforestation and carbon emissions in this country.

Predicting carbon emissions, emissions reductions, and carbon removal due to deforestation and plantation forests in Southeast Asia

Periodic assessment of the forest carbon stocks is needed as part of the global efforts to reduce deforestation and forest degradation and mitigate climate change. Here, we assessed carbon stocks, carbon emissions, removals, and reductions due to deforestation and management of the natural (NFs) and plantation forests (PFs) in Southeast Asia. We found that area of NFs declined about 1.09 million ha or 0.52% yr−1 over the last 20 years but only approximately 0.29 million ha was converted to PFs. Between 2000 and 2030, Southeast Asia emitted 477.7 TgCO2 yr−1 from NFs but gained 44.0 TgCO2 yr−1 in PFs. As area of production forest continues to decline, future timber production in the region is likely to come from the PFs. Using the retrospective approach, forest reference emission level in Southeast Asia was estimated at 431.2 TgCO2 yr−1 during the implementation period of the Paris Agreement between 2020 and 2030. If REDD+ activities were implemented to reduce deforestation and forest degradation and enhance forest carbon stocks, 1922.1 TgCO2 of carbon credits could be achieved and the net carbon revenues were US$8–180 billion between 2020 and 2030 depending on the chosen carbon prices.

Comprehensive Accounting for REDD+ Programs: A Pragmatic Approach as Exemplified in Guyana

Completeness is an important element for Reducing Emissions from Deforestation and forest Degradation (REDD+) accounting to ensure transparency and accountability. However, including a full accounting for all emission sources in a REDD+ program is often resource-intensive and cost-prohibitive, especially considering that some emission sources comprise far less than 10% of total emissions and are thus considered insignificant according to Intergovernmental Panel on Climate Change (IPCC) guidance. This is evident in forest reference emission level (FREL)/forest reference level (FRL) submissions to the United Nations Framework Convention on Climate Change (UNFCCC). Of the 50 countries that have submitted FRELs to date, only half of them include degradation in their FRELs even though degradation is often a significant source of emissions. Half of the countries that do include degradation use satellite imagery without necessarily specifying degrading activities or separating anthropogenic activities. Guyana provides an example of an approach that enables inclusion of all emission sources while considering the significance of each when developing an accounting approach. Since submitting its FREL in 2014, Guyana has made stepwise improvements to its emission estimates so that the country is now able to report on all deforestation and degradation activities resulting in emissions, whether significant or not. Based on the example of Guyana’s efforts, the authors recommend a simple approach to move towards complete accounting in a cost-effective manner. This approach can be scaled to other countries with other activities that results in greenhouse gas emissions from deforestation and forest degradation. Such complete accounting allows for higher accountability in REDD+ systems and can lead to greater effectiveness in reducing emissions.

Reducing Global Environmental Uncertainties in Reports of Tropical Forest Carbon Fluxes to REDD+ and the Paris Agreement Global Stocktake

The magnitude of net carbon dioxide emissions resulting from global forest carbon change, and hence the contribution of forests to global climate change, is highly uncertain, owing to the lack of direct measurement by Earth observation and ground data collection. This paper uses a new method to evaluate this uncertainty with greater precision than before. Sources of uncertainty are divided into conceptualization and measurement categories and distributed between the spatial, vertical and temporal dimensions of Earth observation. The method is applied to Forest Reference Emission Level (FREL) reports and National Greenhouse Gas Inventories (NGGIs) submitted to the UN Framework Convention on Climate Change (UNFCCC) by 12 countries containing half of tropical forest area. The two sets of estimates are typical of those to be submitted to the Reducing Emissions from Deforestation and Degradation (REDD+) mechanism of the UNFCCC and the 2023 Global Stocktake of its Paris Agreement, respectively. Assembling the Uncertainty Fingerprint of each estimate shows that Uncertainty Scores are between 10 and 14 for the NGGIs and 5 and 10 for the FREL reports, and so both exceed the threshold of 2 when it is advisable to evaluate uncertainty by standard statistical methods. Conceptualization uncertainties account for 60% of all uncertainties in the NGGIs and 47% in the FREL reports, e.g., there is incomplete coverage of forest carbon fluxes, and limited disaggregation of fluxes between different ecosystem types and forest carbon pools. Of the measurement uncertainties, all FREL reports base forest area estimates on at least medium resolution satellite data, compared with only 3 NGGIs; after REDD+ Readiness schemes, mean area mapping frequency has fallen to 2.3 years in Latin America and 3.0 years in Asia, but only 8.3 years in Africa; and carbon density estimates are based on national forest inventory data in all FREL reports but only 4 NGGIs. The effectiveness of the Global Stocktake and REDD+ monitoring will therefore be constrained by considerable uncertainties, and to reduce these requires a new phase of REDD+ Readiness to ensure more frequent national forest inventories and forest carbon mapping.

Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors

National circumstances should be considered in establishing and adjusting forest reference emission levels (FRELs/FRLs) under the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+ Programme). Myanmar, one of the world’s least developed countries may face accelerating deforestation under an open and democratic political system that desires rapid economic development. This research analyzes the impacts of population growth and economic development on forest areas in Myanmar by using panel data analysis, an econometrics approach based on panel data of forest areas, population, and gross domestic product (GDP) by states and regions in 2005, 2010, and 2015. This research revealed that per capita GDP and population density gave statistically significant negative impacts on forest areas. Using the regression model obtained above, medium population growth projections, and three GDP development scenarios, annual forest areas from 2016 to 2020 were forecast. The forecasting results showed possible higher deforestation under higher economic development. Finally, this research showed the necessity of adjusting the current average deforestation for RELs in the REDD+ scheme in Myanmar and the direction in which the adjustment should go.

Determining a Carbon Reference Level for a High-Forest-Low-Deforestation Country

Research Highlights: A transparent approach to developing a forest reference emissions level (FREL) adjusted to future local developments in Southern Cameroon is demonstrated. Background and Objectives: Countries with low historical deforestation can adjust their forest reference (emission) level (FREL/FRL) upwards for REDD+ to account for likely future developments. Many countries, however, find it difficult to establish a credible adjusted reference level. This article demonstrates the establishment of a FREL for southern Cameroon adjusted to societal megatrends of strong population—and economic growth combined with rapid urbanization. It demonstrates what can be done with available information and data, but most importantly outlines pathways to further improve the quality of future FREL/FRL’s in light of possibly accessing performance-based payments. Materials and Methods: The virtual FREL encompasses three main elements: Remotely sensed activity data; emission factors derived from the national forest inventory; and the adjustment of the reference level using a land use model of the agriculture sector. Sensitivity analysis is performed on all three elements using Monte Carlo methods. Results: Deforestation during the virtual reference period 2000–2015 is dominated by non-industrial agriculture (comprising both smallholders and local elites) and increases over time. The land use model projections are consistent with this trend, resulting in emissions that are on average 47% higher during the virtual performance period 2020–2030 than during the reference period 2000–2015. Monte Carlo analysis points to the adjustment term as the main driver of uncertainty in the FREL calculation. Conclusions: The available data is suitable for constructing a FREL for periodic reporting to the UNFCCC. Enhanced coherence of input data notably for activity data and adjustment is needed to apply for a performance-based payment scheme. Expanding the accounting framework to include forest degradation and forest gain are further priorities requiring future research.

Comparative Study of Methods to Estimate Historical Peat Burnt Area in Gaung – Batang Tuaka River of Peat Hydrological Unit (KHG)

As a country with 14.9 ha of peatland, Indonesia is a major contributor of GHG emissions, especially from peat ecosystems. These emissions were caused by peat decomposition and peat fires. However, accurate estimation of peat burnt area was still a barrier that prevented the inclusion of peat fire emission in the document of Forest Reference Emission Level (FREL) as a followup document to REDD+ activities. This research has the objective to analyse two different approaches to estimate peat burnt area used in the FREL document and the most recent semi-automatic approach suggested by the Ministry of Environment and Forestry (MoEF). The study focused on the Gaung – Batang Tuaka River Peat Hydrological Unit (KHG), as one of the KHG priorities in Indonesia. The results showed that the average total annual burnt area from the FREL approach was 58% higher than that of the semi-automatic approach, which could lead to an overestimate of peat fire emissions from this approach. The burnt area identified in this study was found to occur within the production forest area. As stepwise approach is allowed for FREL submission, improvements to a higher precision method are necessary to increase the accuracy of burnt area estimation.

Carbon stocks for different land cover types in Mainland Tanzania

BackgroundDeveloping countries participating in the mitigation mechanism of reducing emissions from deforestation and forest degradation (REDD+), are required to establish a forest reference emission level (FREL), if they wish to seek financial support to reduce carbon emissions from deforestation and forest degradation. However, establishment of FREL relies heavily on the accurate estimates of carbon stock as one of the input variable for computation of the emission factors (EFs). The product of an EF and activity data, such as the area of deforestation, results in the total emissions needed for establishment of FREL. This study presents the carbon stock estimates for different land cover classes based on an analysis of Tanzania’s national forest inventory data generated through the National Forest Resources Monitoring and Assessment (NAFORMA).ResultsCarbon stocks were estimated in three carbon pools, namely aboveground, belowground, and deadwood for each of the three land cover classes (i.e. Forest, non-forest, and wetland). The weighted average carbon stock was 33.35 t C ha−1 for forest land, 4.28 t ha−1 for wetland and 5.81 t ha−1 for non-forest land. The uncertainty values were 0.9% for forest land, 11.3% for wetland and 1.8% for non-forest land. Average carbon stocks for land cover sub-classes, which make up the above mentioned major land cover classes, are also presented in our study.ConclusionsThe values presented in this paper correspond to IPCC tier 3 and can be used for carbon estimation at the national scale for the respective major primary vegetation type for various purposes including REDD+. However, if local based estimates values are needed, the use of auxiliary data to enhance the precision of the area of interest is recommended.

National REDD+ outcompetes gold and logging: The potential of cleaning profit chains

Abstract Prominent recent evaluations of global research on REDD+ progress (Reducing Emissions from Deforestation and forest Degradation) conclude that ‘progress has been slower than expected’, ‘deforestation and degradation are deeply-rooted in powerful business-as-usual interests’ and that ‘[f]or the most part, new coalitions calling for change in forest governance have failed to overcome business-as-usual deforestation.’ Others have earlier pointed out that REDD+ will incentivize land grabbing (potentially endangering customary use rights of forest-dependent citizens), and will remain financially uncompetitive against current commercial forest uses. Combining nationwide data over a decade from Guyana’s United Nations-approved Forest Reference Emission Level (FREL) submission and national documents, we found that REDD+ implemented at national level would annually add almost a quarter to the country’s budget, and should not incentivize land grabbing as it places little direct value on forest, but financial penalties (lost income) on forest damage. We show quantitatively that national REDD+ in Guyana is competitive on a hectare basis when viewed from the resource owner’s perspective, even against high value commodities such as gold and timber (the country’s main emission drivers), and at a preliminary US$5 carbon price. Hidden by the latter appears a very lopsided distribution of overall net revenue between the state and private sector commodity chains (∼1:99 and ∼1:1200). We show government or electorate pressure towards more equitable distribution, or ‘cleaning profit chains’, would both be justified and highly worthwhile, without job loss. Investing part of this homegrown finance in further securing lawful and rational management of exhaustible forest-based resources has several additional economic, social and environmental benefits, including for forest-dependent citizens. Society awareness of current revenue ratios, REDD+ income losses, and potential returns of interventions may add helpful (i.e. economic, domestic) motivation for forest governance change in sovereign countries. Weak law enforcement, prevailing across the tropics, enhances lopsided sharing, and linked political leverage could undermine plans that would interfere with private income streams, e.g. rural social development, tenure, forest/biodiversity conservation. Interventions may therefore additionally enhance these sectors’ performances. Assessing and cleaning private profit chains may more generally have potential for REDD+ and global climate change mitigation goals, along with its many associated social and environmental co-benefits.

Current achievements to reduce deforestation in Kalimantan

Indonesia has developed its forest reference emission level (FREL), using a historical reference period of 1990-2012. Based on official Ministry of Environment and Forestry (MoEF) data, this paper analyses gross deforestation rates and emissions from deforestation in the five provinces of the island of Kalimantan which occurred in the time after 2012, i.e. 2013 until 2015, and puts them in relation to the average annual deforestation and emission rates of each province in the reference period. Even though the overall linear trend of deforestation and emission rates in Kalimantan from 1990 until 2015 goes down, this trend is not reflected in all of the five provinces equally. West and North Kalimantan’s rates even seem to be on the rise. The potentials to achieve emission reduction targets thus remain unequal for each province in Kalimantan Island.

Approximating Forest Resource Dynamics in Peninsular Malaysia Using Parametric and Nonparametric Models, and Its Implications for Establishing Forest Reference (Emission) Levels under REDD+

Forest reference (emission) levels (FREL/FRLs) are baselines for REDD+, and 34 countries have submitted their FREL/FRLs to UNFCCC by January 2018. Most of them used simple historical average without considering the stages of forest transition. This research suggested that the period of calculating FREL/FRLs of simple historical average should be properly chosen if these countries are occupying multiple stages or sub-stages of forest transition. Moreover, as a case study, this research applied both parametric and nonparametric models to approximate forest area dynamics with regard to per capita GDP in Peninsular Malaysia from 1971 to 2016. This research found that, in the case of Peninsular Malaysia, among the parametric models, the biexponential model outperformed the other growth models, while two of the nonparametric models i.e. Friedman local averaging and Nadaraya–Watson kernel smoothing models are the best among all the models on the basis of their RSS, RMSE, and MAE indices. Based on the results of our leave-last-five-out CV, however, the research found that the biexponential and Nadaraya–Watson kernel smoothing models performed best, although the performance of the other two nonparametric models remains unknown. Nonparametric model results indicated that Peninsular Malaysia experienced four sub-stages since 1971 and each sub-stage had different linear trends, yet it still did not reach the turning point of forest transition. This research also found that a linear projection using historical deforestation data when the per capita GDP level reached US$8000 was appropriate for setting FREL/FRLs.

National REDD+ Implications for Tenured Indigenous Communities in Guyana, and Communities’ Impact on Forest Carbon Stocks

Early project-level initiatives of ‘reducing emissions from deforestation and forest degradation’ (REDD+) have left a negative impression among many forest-dependent peoples (FDP) across the tropics. As countries move towards national-level implementation and results-based payments, it is timely to analyze the effects of ‘national REDD+’ on FDP. We use Guyana’s technically approved United Nations Forest Reference Emission Level (FREL) submission and Opt-In Mechanism to assess how fifteen indigenous communities with tenured forestland may financially benefit from national REDD+, and evaluate whether, and to what extent, Guyana forms a best-case scenario. In addition, we provide a first-time assessment whether field estimates of the average carbon density of mature forests managed by fifteen forest-dependent communities (beyond rotational farming lands) equals that of nearby unmanaged mature forest, as this could affect REDD+ payment levels. We conclude that, notwithstanding some pending issues, Guyana’s national REDD+ program could be very beneficial for FDP, even under a modest United States (US) $5 unit carbon price. We present economic evidence to support forest governance change domestically in sovereign developing countries that may ease FDP tenure and national REDD+ implementation. The average carbon density was locally substantially less in FDP-managed forest, but had little effect on the overall carbon stock of the titled forest area, and is considered modest when incorporating ecological and socioeconomic attributes. Partnerships with FDP when combined with advances in remote sensing could have potential for economic monitoring of forest emissions across the tropics.

Ina

Forest Reference Emission Level (FREL) is one of four required elements for developing countries in implementing REDD+ activities, and serves as a benchmark in assessing REDD+ performance. This study assessed the emission level from mangrove deforestation in Mahakam Delta - East Kalimantan, aiming to enhance the baseline for subnational FREL document. Over the observation period of 1980-2001, conversion of mangrove forest into aquaculture ponds has resulted in a massive mangrove loss, with an estimation of 3,183 hectare/year, or equivalent to the release of 0.46 Tg CO2e/year. If soil pool was also included in the calculation, mangrove deforestation in Mahakam Delta between 1980 and 2001 emitted 2.9 TgCO2e/year. The CO2 emission from aquaculture ponds may couple with mangrove deforestation, which released 52 Gg CO2 /year from the pond floor. After 2001, the rate of mangrove deforestation decreased, allowing mangrove forests to recover with the expansion rate of 1,546 hectare/ year during 2001-2011 or equivalent to the carbon sequestration or removal of 0.67-4.7 TgCO2e/year. The results of the study suggest the way to improve the existing FREL by raising the importance of mangrove as “blue” carbon, with reference of the 2013 IPCC Guideline: Wetland Supplement.

CHARACTERISTICS OF THE REMOTE SENSING DATA USED IN THE PROPOSED UNFCCC REDD+ FOREST REFERENCE EMISSION LEVELS (FRELS)

Developing countries must submit forest reference emission levels (FRELs) to the UNFCCC to receive incentives for REDD+ activities (e.g. reducing emissions from deforestation/forest degradation, sustainable management of forests, forest carbon stock conservation/enhancement). These FRELs are generated based on historical CO2 emissions in the land use, land use change, and forestry sector, and are derived using remote sensing (RS) data and in-situ forest carbon measurements. Since the quality of the historical emissions estimates is affected by the quality and quantity of the RS data used, in this study we calculated five metrics (i-v below) to assess the quality and quantity of the data that has been used thus far. Countries could focus on improving on one or more of these metrics for the submission of future FRELs. Some of our main findings were: (i) the median percentage of each country mapped was 100%, (ii) the median historical timeframe for which RS data was used was 11.5 years, (iii) the median interval of forest map updates was 4.5 years, (iv) the median spatial resolution of the RS data was 30m, and (v) the median number of REDD+ activities that RS data was used for operational monitoring of was 1 (typically deforestation). Many new sources of RS data have become available in recent years, so complementary or alternative RS data sets for generating future FRELs can potentially be identified based on our findings; e.g. alternative RS data sets could be considered if they have similar or higher quality/quantity than the currently-used data sets.

CHARACTERISTICS OF THE REMOTE SENSING DATA USED IN THE PROPOSED UNFCCC REDD+ FOREST REFERENCE EMISSION LEVELS (FRELS)

Abstract. Developing countries must submit forest reference emission levels (FRELs) to the UNFCCC to receive incentives for REDD+ activities (e.g. reducing emissions from deforestation/forest degradation, sustainable management of forests, forest carbon stock conservation/enhancement). These FRELs are generated based on historical CO2 emissions in the land use, land use change, and forestry sector, and are derived using remote sensing (RS) data and in-situ forest carbon measurements. Since the quality of the historical emissions estimates is affected by the quality and quantity of the RS data used, in this study we calculated five metrics (i-v below) to assess the quality and quantity of the data that has been used thus far. Countries could focus on improving on one or more of these metrics for the submission of future FRELs. Some of our main findings were: (i) the median percentage of each country mapped was 100%, (ii) the median historical timeframe for which RS data was used was 11.5 years, (iii) the median interval of forest map updates was 4.5 years, (iv) the median spatial resolution of the RS data was 30m, and (v) the median number of REDD+ activities that RS data was used for operational monitoring of was 1 (typically deforestation). Many new sources of RS data have become available in recent years, so complementary or alternative RS data sets for generating future FRELs can potentially be identified based on our findings; e.g. alternative RS data sets could be considered if they have similar or higher quality/quantity than the currently-used data sets.

Conversion from forests to pastures in the Colombian Amazon leads to contrasting soil carbon dynamics depending on land management practices.

Strategies to mitigate climate change by reducing deforestation and forest degradation (e.g. REDD+) require country- or region-specific information on temporal changes in forest carbon (C) pools to develop accurate emission factors. The soil C pool is one of the most important C reservoirs, but is rarely included in national forest reference emission levels due to a lack of data. Here, we present the soil organic C (SOC) dynamics along 20years of forest-to-pasture conversion in two subregions with different management practices during pasture establishment in the Colombian Amazon: high-grazing intensity (HG) and low-grazing intensity (LG) subregions. We determined the pattern of SOC change resulting from the conversion from forest (C3 plants) to pasture (C4 plants) by analysing total SOC stocks and the natural abundance of the stable isotopes (13) C along two 20-year chronosequences identified in each subregion. We also analysed soil N stocks and the natural abundance of (15) N during pasture establishment. In general, total SOC stocks at 30cm depth in the forest were similar for both subregions, with an average of 47.1±1.8MgCha(-1) in HG and 48.7±3.1MgCha(-1) in LG. However, 20years after forest-to-pasture conversion SOC in HG decreased by 20%, whereas in LG SOC increased by 41%. This net SOC decrease in HG was due to a larger reduction in C3-derived input and to a comparatively smaller increase in C4-derived C input. In LG both C3- and C4-derived C input increased along the chronosequence. N stocks were generally similar in both subregions and soil N stock changes during pasture establishment were correlated with SOC changes. These results emphasize the importance of management practices involving low-grazing intensity in cattle activities to preserve SOC stocks and to reduce C emissions after land-cover change from forest to pasture in the Colombian Amazon.

Forecasting forest areas and carbon stocks in Cambodia based on socio-economic factors

SUMMARY Establishing forest reference emission levels (RELs) and/or forest reference levels (RLs) is an important task for developing country parties considering taking part in the REDD+ scheme under the UNFCCC, especially for those countries experiencing corresponding economic development with land use changes. In this research, Cambodia’s forest areas and forest carbon stocks from 2011 to 2018 were forecasted, which can be used as a reference for establishing forest RELs in Cambodia. Conditional to the assumptions of population growth, the growth in agricultural gross value added, and the level of economic land concession implementations, the forecasts by panel data analysis to provinciallevel data showed that the forest area in Cambodia will decrease to 9.94 million ha in 2014 and 9.51 million ha in 2018 from 10.36 million ha in 2010 and that forest carbon stocks will decrease to 1.22 PgC in 2014 and 1.17 PgC in 2018 from 1.28 PgC in 2010.