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Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency

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 a...

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Detalles Bibliográficos
Autores principales: Heinrich, Viola, House, Jo, Gibbs, David A., Harris, Nancy, Herold, Martin, Grassi, Giacomo, Cantinho, Roberta, Rosan, Thais M., Zimbres, Barbara, Shimbo, Julia Z., Melo, Joana, Hales, Tristram, Sitch, Stephen, Aragão, Luiz E. O. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662451/
https://www.ncbi.nlm.nih.gov/pubmed/37982938
http://dx.doi.org/10.1186/s13021-023-00240-2
Descripción
Sumario: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 GtCO(2)yr(−1)), while Brazil’s NGHGI reported a net carbon source (+ 0.8 GtCO(2)yr(−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 GtCO(2)yr(−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 GtCO(2) yr(−1)), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO(2) yr(−1); Global EO: + 0.2 GtCO(2) 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13021-023-00240-2.