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 2 ) and below-ground carbon storage (105–288 Pg...
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| Vydáno v: | Environmental research letters Ročník 19; číslo 9; s. 94019 - 94032 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Bristol
IOP Publishing
01.09.2024
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| ISSN: | 1748-9326, 1748-9326 |
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| Abstract | 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
2
) 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
2
(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
Campinarana
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. |
|---|---|
| AbstractList | 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 ^2 ) 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 ^2 (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 Campinarana 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. 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 km2) 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 km2 (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 Campinarana 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. 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 2 ) 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 2 (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 Campinarana 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. |
| Author | Mitchard, Edward T A Águila, Jhon Del Roucoux, Katherine H Draper, Frederick C Paukku, Stella Winton, R Scott Herrera, Rafael Montoya, Encarni W Tobler, Mathias Åkesson, Christine M Wittmann, Florian Householder, J Ethan Lähteenoja, Outi Del Castillo Torres, Dennis Cole, Lydia E S Schöngart, Jochen Fernandez Piedade, Maria Teresa Baker, Timothy R Reyna, José Córdova Oroche, César J van der Zon, Marieke Lawson, Ian T Grández, Julio Aymard Corredor, Gerardo A Reyna, David de Jong, Johan Honorio Coronado, Eurídice N Dávila, Nállarett Hidalgo Pizango, C Gabriel Janovec, John P Fluet-Chouinard, Etienne Wheeler, Charlotte E Hastie, Adam |
| Author_xml | – sequence: 1 givenname: Adam orcidid: 0000-0003-2098-3510 surname: Hastie fullname: Hastie, Adam organization: University of Edinburgh School of GeoSciences, Edinburgh, United Kingdom – sequence: 2 givenname: J Ethan surname: Householder fullname: Householder, J Ethan organization: Karlsruhe Institute for Technology Wetland Ecology, Institute for Geography and Geoecology, Karlsruhe, Germany – sequence: 3 givenname: Eurídice N surname: Honorio Coronado fullname: Honorio Coronado, Eurídice N organization: Kew—Richmond Royal Botanic Gardens, Surrey, TW9 3AE, United Kingdom – sequence: 4 givenname: C Gabriel orcidid: 0000-0003-3170-9939 surname: Hidalgo Pizango fullname: Hidalgo Pizango, C Gabriel organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 5 givenname: Rafael surname: Herrera fullname: Herrera, Rafael organization: Instituto Venezolano de Investigaciones Científicas (IVIC) , Caracas, Venezuela – sequence: 6 givenname: Outi surname: Lähteenoja fullname: Lähteenoja, Outi organization: Helsinki , Finland – sequence: 7 givenname: Johan orcidid: 0000-0002-1077-2210 surname: de Jong fullname: de Jong, Johan organization: Wageningen University & Research Forest Ecology and Forest Management, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands – sequence: 8 givenname: R Scott surname: Winton fullname: Winton, R Scott organization: Stanford University Department of Earth System Science, Stanford Doerr School of Sustainability, Stanford, CA, United States of America – sequence: 9 givenname: Gerardo A surname: Aymard Corredor fullname: Aymard Corredor, Gerardo A organization: Jardín Botánico de Bogotá José Celestino Mutis , Calle 63 #68–95, Bogotá, D.C, Colombia – sequence: 10 givenname: José surname: Reyna fullname: Reyna, José organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 11 givenname: Encarni orcidid: 0000-0002-4690-190X surname: Montoya fullname: Montoya, Encarni organization: CSIC Geosciences Barcelona, c/Lluis Solé i Sabaris s/n, 08028 Barcelona, Spain – sequence: 12 givenname: Stella surname: Paukku fullname: Paukku, Stella organization: ETH Zurich , Zurich, Switzerland – sequence: 13 givenname: Edward T A surname: Mitchard fullname: Mitchard, Edward T A organization: University of Edinburgh School of GeoSciences, Edinburgh, United Kingdom – sequence: 14 givenname: Christine M surname: Åkesson fullname: Åkesson, Christine M organization: University of St Andrews School of Geography and Sustainable Development, St Andrews, United Kingdom – sequence: 15 givenname: Timothy R surname: Baker fullname: Baker, Timothy R organization: University of Leeds School of Geography, Leeds, United Kingdom – sequence: 16 givenname: Lydia E S surname: Cole fullname: Cole, Lydia E S organization: University of St Andrews School of Geography and Sustainable Development, St Andrews, United Kingdom – sequence: 17 givenname: César J orcidid: 0000-0002-0692-3186 surname: Córdova Oroche fullname: Córdova Oroche, César J organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 18 givenname: Nállarett surname: Dávila fullname: Dávila, Nállarett organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 19 givenname: Jhon Del surname: Águila fullname: Águila, Jhon Del organization: Universidad Nacional de la Amazonia Peruana (UNAP) , Iquitos, Peru – sequence: 20 givenname: Frederick C surname: Draper fullname: Draper, Frederick C organization: University of Liverpool School of Environmental Sciences, Liverpool, United Kingdom – sequence: 21 givenname: Etienne orcidid: 0000-0003-4380-2153 surname: Fluet-Chouinard fullname: Fluet-Chouinard, Etienne organization: Pacific Northwest National Laboratory Earth System Science Division, Richland, WA, United States of America – sequence: 22 givenname: Julio surname: Grández fullname: Grández, Julio organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 23 givenname: John P surname: Janovec fullname: Janovec, John P organization: Universidad Nacional Agraria La Molina Herbario Forestal UNALM, Facultad de Ciencias Forestales, Lima, Peru – sequence: 24 givenname: David surname: Reyna fullname: Reyna, David organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 25 givenname: Mathias surname: W Tobler fullname: W Tobler, Mathias organization: Conservation Science and Wildlife Health San Diego Zoo Wildlife Alliance, Escondido, CA, United States of America – sequence: 26 givenname: Dennis surname: Del Castillo Torres fullname: Del Castillo Torres, Dennis organization: Instituto de investigaciones de la Amazonía Peruana , Iquitos, Peru – sequence: 27 givenname: Katherine H surname: Roucoux fullname: Roucoux, Katherine H organization: University of St Andrews School of Geography and Sustainable Development, St Andrews, United Kingdom – sequence: 28 givenname: Charlotte E surname: Wheeler fullname: Wheeler, Charlotte E organization: University of Cambridge Department of Plant Sciences, The David Attenborough Building, Pembroke Street, Cambridge CB2 3QZ, United States of America – sequence: 29 givenname: Maria Teresa surname: Fernandez Piedade fullname: Fernandez Piedade, Maria Teresa organization: National Institute for Amazonian Research (INPA) Research Group in Ecology, Monitoring and Sustainable Use of Wetlands (MAUA), Manaus, Brazil – sequence: 30 givenname: Jochen surname: Schöngart fullname: Schöngart, Jochen organization: National Institute for Amazonian Research (INPA) Research Group in Ecology, Monitoring and Sustainable Use of Wetlands (MAUA), Manaus, Brazil – sequence: 31 givenname: Florian surname: Wittmann fullname: Wittmann, Florian organization: Karlsruhe Institute for Technology Wetland Ecology, Institute for Geography and Geoecology, Karlsruhe, Germany – sequence: 32 givenname: Marieke surname: van der Zon fullname: van der Zon, Marieke organization: Wageningen University & Research Forest Ecology and Forest Management, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands – sequence: 33 givenname: Ian T surname: Lawson fullname: Lawson, Ian T organization: University of St Andrews School of Geography and Sustainable Development, St Andrews, United Kingdom |
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| SubjectTerms | Amazonia Anthropogenic factors Carbon Carbon cycle Carbon sequestration Climate change Confidence intervals data-driven modelling ENVIRONMENTAL SCIENCES Human influences peat Peatlands Remote sensing River basins Seasonal variations Terrestrial ecosystems tropical peatlands Uncertainty wetlands |
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| Title | A new data-driven map predicts substantial undocumented peatland areas in Amazonia |
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