A new data-driven map predicts substantial undocumented peatland areas in Amazonia.

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km ) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

Funder

Funder name	Awards
Gordon and Betty Moore Foundation, United States	Grant no. 484
World Bank Group, United States
Inter-American Development Bank, United States / Fondo para la Innovación, Ciencia y Technologia, Venezuela	Grant no. PIBAP-2007-005
National Science Foundation, United States	0717453
Natural Environment Research Council, United Kingdom	NE/R000751/1 - Knowledge Exchange Fellowship (NE/V018760/1)
Leverhulme Trust, United Kingdom	RPG-2018-306
Univerzita Karlova v Praze, Czechia	PRIMUS/23/SCI/013 - Charles University Research Centre program UNCE/24/SCI/006
Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil	Process number 141727/2011-0 - Universal 14/2011
Green Climate Fund, South Korea
Korea International Cooperation Agency, South Korea
Univerzita Karlova v Praze, Czechia / University of St Andrews, United States	Joint Seed Funding
Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica, Peru	0000 0004 7773 3085
Instituto de Investigaciones de la Amazonía Peruana, Peru
Discovery Fund of Fort Worth, Texas, United States