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Fulltext Forest production predicted from satellite image analysis for the Southeast Asia region

Potter C, Klooster S, Genovese V, Hiatt C

Carbon Balance Manag, 2013;8(1):9.
PMID: 24016254 DOI: 10.1186/1750-0680-8-9

The objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010. These CASA model results have been designed to be spatially detailed enough to support carbon cycle assessments in different wooded land cover classes, e.g., open woodlands, wetlands, and forest areas.
Fulltext Time-series maps of aboveground biomass in dipterocarps forests of Malaysia from PALSAR and PALSAR-2 polarimetric data

Omar H, Misman MA

Carbon Balance Manag, 2018 Oct 19;13(1):19.
PMID: 30341540 DOI: 10.1186/s13021-018-0108-2

BACKGROUND: Malaysia typically suffers from frequent cloud cover, hindering spatially consistent reporting of deforestation and forest degradation, which limits the accurate reporting of carbon loss and CO2 emissions for reducing emission from deforestation and forest degradation (REDD+) intervention. This study proposed an approach for accurate and consistent measurements of biomass carbon and CO2 emissions using a single L-band synthetic aperture radar (SAR) sensor system. A time-series analysis of aboveground biomass (AGB) using the PALSAR and PALSAR-2 systems addressed a number of critical questions that have not been previously answered. A series of PALSAR and PALSAR-2 mosaics over the years 2007, 2008, 2009, 2010, 2015 and 2016 were used to (i) map the forest cover, (ii) quantify the rate of forest loss, (iii) establish prediction equations for AGB, (iv) quantify the changes of carbon stocks and (v) estimate CO2 emissions (and removal) in the dipterocarps forests of Peninsular Malaysia.
RESULTS: This study found that the annual rate of deforestation within inland forests in Peninsular Malaysia was 0.38% year-1 and subsequently caused a carbon loss of approximately 9 million Mg C year-1, which is equal to emissions of 33 million Mg CO2 year-1, within the ten-year observation period. Spatially explicit maps of AGB over the dipterocarps forests in the entire Peninsular Malaysia were produced. The RMSE associated with the AGB estimation was approximately 117 Mg ha-1, which is equal to an error of 29.3% and thus an accuracy of approximately 70.7%.
CONCLUSION: The PALSAR and PALSAR-2 systems offer a great opportunity for providing consistent data acquisition, cloud-free images and wall-to-wall coverage for monitoring since at least the past decade. We recommend the proposed method and findings of this study be considered for MRV in REDD+ implementation in Malaysia.
Fulltext Recycling of phenolic compounds in Borneo's tropical peat swamp forests

Yule CM, Lim YY, Lim TY

Carbon Balance Manag, 2018 Feb 07;13(1):3.
PMID: 29417248 DOI: 10.1186/s13021-018-0092-6

BACKGROUND: Tropical peat swamp forests (TPSF) are globally significant carbon stores, sequestering carbon mainly as phenolic polymers and phenolic compounds (particularly as lignin and its derivatives) in peat layers, in plants, and in the acidic blackwaters. Previous studies show that TPSF plants have particularly high levels of phenolic compounds which inhibit the decomposition of organic matter and thus promote peat accumulation. The studies of phenolic compounds are thus crucial to further understand how TPSF function with respect to carbon sequestration. Here we present a study of cycling of phenolic compounds in five forests in Borneo differing in flooding and acidity, leaching of phenolic compounds from senescent Macaranga pruinosa leaves, and absorption of phenolics by M. pruinosa seedlings.
RESULTS: The results of the study show that total phenolic content (TPC) in soil and leaves of three species of Macaranga were highest in TPSF followed by freshwater swamp forest and flooded limestone forest, then dry land sites. Highest TPC values were associated with acidity (in TPSF) and waterlogging (in flooded forests). Moreover, phenolic compounds are rapidly leached from fallen senescent leaves, and could be reabsorbed by tree roots and converted into more complex phenolics within the leaves.
CONCLUSIONS: Extreme conditions-waterlogging and acidity-may facilitate uptake and synthesis of protective phenolic compounds which are essential for impeded decomposition of organic matter in TPSF. Conversely, the ongoing drainage and degradation of TPSF, particularly for conversion to oil palm plantations, reverses the conditions necessary for peat accretion and carbon sequestration.
Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency

Heinrich V, House J, Gibbs DA, Harris N, Herold M, Grassi G, et al.

Carbon Balance Manag, 2023 Nov 20;18(1):22.
PMID: 37982938 DOI: 10.1186/s13021-023-00240-2

BACKGROUND: The application of different approaches calculating the anthropogenic carbon net flux from land, leads to estimates that vary considerably. One reason for these variations is the extent to which approaches consider forest land to be "managed" by humans, and thus contributing to the net anthropogenic flux. Global Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent and consistent approach to estimate forest carbon fluxes. These can be compared against results reported in National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely measuring, reporting and verification (MRV). Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare a Global EO-based dataset of forest carbon fluxes to results reported in NGHGIs.
RESULTS: Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (- 0.2 GtCO2yr-1), while Brazil's NGHGI reported a net carbon source (+ 0.8 GtCO2yr-1). After adjusting the EO estimate to use the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory's methodology, the EO net flux became a source of + 0.6 GtCO2yr-1, comparable to the NGHGI. Remaining discrepancies are due largely to differing carbon removal factors and forest types applied in the two datasets. In Indonesia, the EO and NGHGI net flux estimates were similar (+ 0.6 GtCO2 yr-1), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO2 yr-1; Global EO: + 0.2 GtCO2 yr-1). Spatially explicit datasets on forest types were not publicly available for analysis from either NGHGI, limiting the possibility of detailed adjustments.
CONCLUSIONS: By adjusting the EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences can be explained. Despite limited spatial data available for Indonesia and Malaysia, our comparison indicated specific aspects where differing approaches may explain divergence, including uncertainties and inaccuracies. Our study highlights the importance of enhanced transparency, as set out by the Paris Agreement, to enable alignment between different approaches for independent measuring and verification.