Asynchronous carbon sink saturation in African and Amazonian tropical forests (original) (raw)

Data availability

Source data to generate figures and tables are available from https://doi.org/10.5521/Forestplots.net/2019_1.

Code availability

R code to generate figures and tables is available from: https://doi.org/10.5521/Forestplots.net/2019_1.

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Acknowledgements

This paper is a product of the African Tropical Rainforest Observatory Network (AfriTRON), curated at ForestPlots.net. AfriTRON has been supported by numerous people and grants since its inception. We sincerely thank the people of the many villages and local communities who welcomed our field teams and without whose support this work would not have been possible: Sierra Leone (villages: Barrie, Gaura, Koya, Makpele, Malema, Nomo, Tunkia; teams in protected areas: the Gola Rainforest National Park), Liberia (villages: Garley town, River Gbeh, Glaro Freetown), Ghana (villages: Nkwanta, Asenanyo, Bonsa, Agona, Boekrom, Dadieso, Enchi, Dabiasem, Mangowase, Draw, Fure, Esuboni, Okumaninin, Kade, Asamankese, Tinte Bepo, Tonton), Nigeria (Oban village), Gabon (villages: Ekobakoba, Mikongo, Babilone, Makokou, Tchimbele, Mondah, Ivindo, Ebe, Ekouk, Oveng, Sette Cama; teams in protected areas: Ivindo National Park, Lope National Park, Waka National Park; teams in concessions: Ipassa station, Kingele station, Leke/Moyabi Rougier Forestry Concession), Cameroon (villages: Campo, Nazareth, Lomié, Djomédjo, Alat-Makay, Somalomo, Deng Deng, Eyumojok, Mbakaou, Myere, Nguti, Bejange, Kekpane, Basho, Mendhi, Matene, Mboh, Takamanda, Obonyi, Ngoïla; teams in protected areas: Ejagham forest reserve), Democratic Republic of Congo (villages: Yoko, Yangambi, Epulu, Monkoto), Republic of Congo (villages: Bomassa, Ekolongouma, Bolembe, Makao, Mbeli, Kabo, Niangui, Ngubu, Goualaki, Essimbi). We thank the field assistants whose expertise and enthusiasm is indispensable to successful fieldwork, including: M. E. Abang, U. P. Achui, F. Addai, E. J. Agbachon, J. Agnaka, A. J. Akaza, G. Alaman, G. Alaman, A. E. Alexander, K. Allen, M. Amalphi, D. Amandus, J. Andju, L. A. Limbanga, S. Asamoah, T. M. Ashu, M. Ashu, J. Asse, B. Augustine, H. Badjoko, M. Balimu, J. Baviogui-Baviogui, S. Benteh, A. Bertrand, A. Bettus, A. Bias, A. Bikoula, A. Bimba, P. Bissiemou, M. Boateng, E. Bonyenga, M. B. Ekaya, G. Bouka, J. Boussengui, D. B. Ngomo, C. Chalange, S. Chenikan, J. Dabo, E. Dadize, T. Degraft, J. Dibakou, J.-T. Dikangadissi, P. Dimbonda, E. Dimoto, C. Ditougou, D. Dorbor, M. Dorbor, V. Droissart, K. Duah, E. Ebe, O. J. Eji, E. B. Ekamam, J.-R. Ekomindong, E. J. Enow, H. Entombo, E. M. Ernest, C. Esola, J. Essouma, A. Gabriel, N. Genesis, B. Gideon, A. Godwin, E. Grear, D. J. Grear, M. Ismael, M. Iwango, M. Iyafo, N. Kamdem, B. Kibinda, A. Kidimbu, E. Kimumbu, J. Kintsieri, C. K. Opepa, A. Kitegile, T. Komo, P. Koué, A. Kouanga, J. J. Koumikaka, I. Liengola, E. Litonga, L. Louvouando, O. Luis, N. M. Mady, F. Mahoula, A. Mahundu, C. A. Mandebet, P. Maurice, K. Y. Mayossa, R. M. Nkogue, I. D. Mbe, C. Mbina, H. Mbona, A. Mboni, A. Mbouni, P. Menzo, M. Menge, A. Michael, A. Mindoumou, J. Minpsa, J. P. Mondjo, E. Mounoumoulossi, S. Mpouam, T. Msigala, J. Msirikale, S. Mtoka, R. Mwakisoma, D. Ndong-Nguema, G. Ndoyame, G. Ngongbo, F. Ngowa, D. Nguema, L. Nguye, R. Niangadouma, Y. Nkrumah, S. Nshimba, M. N. Mboumba, F. N. Obiang, L. Obi, R. Obi, E. L. Odjong, F. Okon, F. Olivieira, A. L. Owemicho, L. Oyeni-Amoni, A. Platini, P. Ploton, S. Quausah, E. Ramazani, B. S. Jean, L. Sagang, R. Salter, A. Seki, D. Shirima, M. Simo, I. Singono, A. E. Tabi, T. G. Tako, N. G. Tambe, T. Tcho, A. Teah, V. Tehtoe, B. J. Telephas, M. L. Tonda, A. Tresor, H. Umenendo, R. Votere, C. K. Weah, S. Weah, B. Wursten, E. Yalley, D. Zebaze, L. Cerbonney, E. Dubiez, H. Moinecourt, F. Lanckriet, S. Samai, M. Swaray, P. Lamboi, M. Sullay, D. Bannah, I. Kanneh, M. Kannah, A. Kemokai, J. Kenneh and M. Lukulay. For logistical and administrative support, we are indebted to international, national and local institutions: the Forestry Department of the Government of Sierra Leone, the Conservation Society of Sierra Leone, the Royal Society for the Protection of Birds (RSPB, UK), The Gola Rainforest National Park (Sierra Leone), the Forestry Development Authority of the Government of Liberia (FDA), the University of Liberia, the Forestry Commission of Ghana (FC), the Forestry Research Institute of Ghana (FORIG), University of Ibadan (Nigeria), the University of Abeokuta (Nigeria), the Ministère des Eaux, Forêts, Chasse et Pêche (MEFCP, Central African Republic), the Institut Centrafricain de Recherche Agronomique (ICRA, Central African Republic), The Service de Coopération et d’Actions Culturelles (SCAC/MAE, Central African Republic), The University of Bangui (Central African Republic), the Société Centrafricaine de Déroulage (SCAD, Central African Republic), the University of Yaounde I (Cameroon), the National Herbarium of Yaounde (Cameroon), the University of Buea (Cameroon), Bioversity International (Cameroon), the Ministry of Forests, Seas, Environment and Climate (Gabon), the Agence Nationale des Parcs Nationaux de Gabon (ANPN), Institut de Recherche en Écologie Tropicale du Gabon, Rougier-Gabon, the Marien Ngouabi University of Brazzaville (Republic of Congo), the Ministère des Eaux et Forêts (Republic of Congo), the Ministère de la Rercherche Scientifique et de l’Innovation Technologique (Republic of Congo), the Nouabalé-Ndoki Foundation (Republic of Congo), WCS-Congo, Salonga National Park (Democratic Republic of Congo), The Centre de Formation et de Recherche en Conservation Forestière (CEFRECOF, Epulu, Democratic Republic of Congo), the Institut National pour l’Étude et la Recherche Agronomiques (INERA, Democratic Republic of Congo), the École Régionale Postuniversitaire d’Aménagement et de Gestion intégrés des Forêts et Territoires tropicaux (ERAIFT Kinshasa, Democratic Republic of Congo), WWF-Democratic Republic of Congo, WCS-Democratic Republic of Congo, the Université de Kisangani (Democratic Republic of Congo), Université Officielle de Bukavu (Democratic Republic of Congo), Université de Mbujimayi (Democratic Republic of Congo), le Ministère de l'Environnement et Développement Durable (Democratic Republic of Congo), the FORETS project in Yangambi (CIFOR, CGIAR and the European Union; Democratic Republic of Congo), the Lukuru Wildlife Research Foundation (Democratic Republic of Congo), Mbarara University of Science and Technology (MUST, Uganda), WCS-Uganda, the Uganda Forest Department, the Commission of Central African Forests (COMIFAC), the Udzungwa Ecological Monitoring Centre (Tanzania) and the Sokoine University of Agriculture (Tanzania). We thank C. Chatelain (Geneva Botanic Gardens) for access to the African Plants Database. Grants that have funded the AfriTRON network including data in this paper are: a European Research Council Advanced Grant to O.L.P. and S.L.L. (T-FORCES; 291585; Tropical Forests in the Changing Earth System), a NERC grant to O.L.P., Y.M., and S.L.L. (NER/A/S/2000/01002), a Royal Society University Research Fellowship to S.L.L., a NERC New Investigators Grant to S.L.L., a Philip Leverhulme Award to S.L.L., a European Union FP7 grant to E.G. and S.L.L. (GEOCARBON; 283080), Valuing the Arc Leverhulme Program Grant to Andrew Balmford and S.L.L., a Natural Environment Research Council (NERC) Consortium Grant to Jon Lloyd and S.L.L. (TROBIT; NE/D005590/), the Gordon and Betty Moore Foundation to L.J.T.W and S.L.L., the David and Lucile Packard Foundation to L.J.T.W. and S.L.L., the Centre for International Forestry Research to T.S. and S.L.L. (CIFOR), and Gabon’s National Parks Agency (ANPN) to S.L.L. W.H. was funded by T-FORCES and the Brain programme of the Belgian Federal Government (BR/132/A1/AFRIFORD grant to Olivier Hardy and the BR/143/A3/HERBAXYLAREDD grant to H.B.). O.L.P., S.L.L., M.J.P.S, A.E.-M., A.L., G.L.-G., G.P. and L.Q. were supported by T-FORCES. Eight plots (codes ANK, IVI, LPG, MNG) included in AfriTRON are also part of the Global Ecosystem Monitoring network (GEM). Additional African data were included from the consortium MEFCP-ICRA-CIRAD (Centre de Coopération Internationale en Recherche Agronomique pour le Développement), the Tropical Ecology Assessment and Monitoring Network (TEAM), and the Forest Global Earth Observatory Network (ForestGEO; formerly the Center for Tropical Forest Science, CTFS). The TEAM network is a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and funded by the Gordon and Betty Moore Foundation and other donors. The ForestGEO Network is a collaboration between the Smithsonian Institution, other federal agencies of the United States, the Wildlife Conservation Society (WCS) and the World Wide Fund for Nature (WWF), and funded by the US National Science Foundation and other donors. The paper was made possible by the RAINFOR network in Amazonia, with multiple funding agencies and hundreds of investigators working in Amazonia, acknowledged in ref. 6, providing comprehensive published data and code and assisting in the onward analysis of their data; see ref. 6. Data from AfriTRON and RAINFOR are stored and curated by ForestPlots.net, a long-term cyber-infrastructure initiative hosted at the University of Leeds that unites permanent plot records and their contributing scientists from the world’s tropical forests. The development of ForestPlots.net and curation of most data analysed here was funded by many sources, including grants to O.L.P. (principally from ERC AdG 291585 ‘T-FORCES’, NERC NE/B503384/1 and the Gordon and Betty Moore Foundation 1656 ‘RAINFOR’), T.R.B. (the University of Leeds contribution to ‘AMAZALERT’, NERC (NE/I028122/1) with T. Pennington, the Gordon and Betty Moore Foundation (‘MonANPeru’) and a NERC Impact Accelerator grant for the initial development of the BiomasaFP R package), E.G. (‘GEOCARBON’ and NE/F005806/1 ‘AMAZONICA’) and S.L.L. (Royal Society University Research Fellowship, NERC New Investigators Award, NERC NE/P008755/1). We acknowledge the contributions of the ForestPlots.net developers (M. Burkitt, G. Lopez-Gonzalez) and the steering committee (T.R.B., A.L., S.L.L., O.L.P., L.Q., E. N. H. Coronado and B. S. Marimon) for advice on database development and management.

Author information

Author notes

1. These authors contributed equally: Wannes Hubau, Simon L. Lewis

Authors and Affiliations

1. School of Geography, University of Leeds, Leeds, UK
   Wannes Hubau, Simon L. Lewis, Oliver L. Phillips, Martin J. P. Sullivan, Timothy R. Baker, Serge K. Begne, Amy C. Bennett, Roel J. W. Brienen, Greta C. Dargie, Adriane Esquivel-Muelbert, Martin Gilpin, Emanuel Gloor, Aurora Levesley, Gabriela Lopez-Gonzalez, Jon C. Lovett, Georgia C. Pickavance, Lan Qie & Joey Talbot
2. Service of Wood Biology, Royal Museum for Central Africa, Tervuren, Belgium
   Wannes Hubau, Hans Beeckman, Thales de Haulleville, Emmanuel Kasongo Yakusu, Elizabeth Kearsley, Benjamin Toirambe & John Tshibamba Mukendi
3. Department of Environment, Laboratory of Wood Technology (Woodlab), Ghent University, Ghent, Belgium
   Wannes Hubau & Emmanuel Kasongo Yakusu
4. Department of Geography, University College London, London, UK
   Simon L. Lewis, Aida Cuní-Sanchez & Alexander Koch
5. Mensuration Unit, Forestry Commission of Ghana, Kumasi, Ghana
   Kofi Affum-Baffoe
6. Department of Environment and Geography, University of York, York, UK
   Aida Cuní-Sanchez & Andrew R. Marshall
7. Forestry Development Authority of the Government of Liberia (FDA), Monrovia, Liberia
   Armandu K. Daniels & Darlington Tuagben
8. DR Congo Programme, Wildlife Conservation Society, Kinshasa, Democratic Republic of Congo
   Corneille E. N. Ewango & Jacques M. Mukinzi
9. Centre de Formation et de Recherche en Conservation Forestière (CEFRECOF), Epulu, Democratic Republic of Congo
   Corneille E. N. Ewango
10. Faculté de Gestion de Ressources Naturelles Renouvelables, Université de Kisangani, Kisangani, Democratic Republic of Congo
    Corneille E. N. Ewango, Emmanuel Kasongo Yakusu, Faustin M. Mbayu & John Tshibamba Mukendi
11. School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth, UK
    Sophie Fauset
12. Salonga National Park, Kinshasa, Democratic Republic of Congo
    Jacques M. Mukinzi
13. World Wide Fund for Nature, Gland, Switzerland
    Jacques M. Mukinzi
14. Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
    Douglas Sheil
15. Plant Systematic and Ecology Laboratory, Higher Teachers’ Training College, University of Yaounde I, Yaounde, Cameroon
    Bonaventure Sonké, Hermann Taedoumg, Serge K. Begne & Lise Zemagho
16. Department of Natural Sciences, Manchester Metropolitan University, Manchester, UK
    Martin J. P. Sullivan
17. Center for International Forestry Research (CIFOR), Bogor, Indonesia
    Terry C. H. Sunderland, Christian A. Amani & Patrick Boundja
18. Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada
    Terry C. H. Sunderland
19. Bioversity International, Yaounde, Cameroon
    Hermann Taedoumg
20. Faculty of Forestry, University of Toronto, Toronto, Ontario, Canada
    Sean C. Thomas
21. Ministry of Forests, Seas, Environment and Climate, Libreville, Gabon
    Lee J. T. White, Vianet Mihindou & Natacha Nssi Bengone
22. Institut de Recherche en Écologie Tropicale, Libreville, Gabon
    Lee J. T. White & Katharine A. Abernethy
23. Department of Biological and Environmental Sciences, University of Stirling, Stirling, UK
    Lee J. T. White, Katharine A. Abernethy & Kathryn J. Jeffery
24. Forestry Research Institute of Ghana (FORIG), Kumasi, Ghana
    Stephen Adu-Bredu & Ernest G. Foli
25. Université Officielle de Bukavu, Bukavu, Democratic Republic of Congo
    Christian A. Amani
26. UK Centre for Ecology & Hydrology, Penicuik, UK
    Lindsay F. Banin
27. Ministère des Eaux, Forêts, Chasse et Pêche (MEFCP), Bangui, Central African Republic
    Fidèle Baya
28. Institut Centrafricain de Recherche Agronomique (ICRA), Bangui, Central African Republic
    Fidèle Baya
29. Forêts et Sociétés (F&S), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Montpellier, France
    Fabrice Benedet & Sylvie Gourlet-Fleury
30. Forêts et Sociétés (F&S), Université de Montpellier, Montpellier, France
    Fabrice Benedet & Sylvie Gourlet-Fleury
31. The Institute of Tropical Forest Conservation (ITFC), Mbarara University of Science and Technology (MUST), Mbarara, Uganda
    Robert Bitariho
32. Faculté des Sciences et Techniques, Laboratoire de Botanique et Écologie, Université Marien Ngouabi, Brazzaville, Republic of Congo
    Yannick E. Bocko
33. Isotope Bioscience Laboratory-ISOFYS, Ghent University, Ghent, Belgium
    Pascal Boeckx
34. Congo Programme, Wildlife Conservation Society, Brazzaville, Republic of Congo
    Patrick Boundja, Terry Brncic & Mireille B. N. Hockemba
35. Rougier-Gabon, Libreville, Gabon
    Eric Chezeaux
36. Faculty of Science, Department of Botany and Plant Physiology, University of Buea, Buea, Cameroon
    George B. Chuyong & Marie Noel Djuikouo Kamdem
37. Nicholas School of the Environment, Duke University, Durham, NC, USA
    Connie J. Clark, Vincent P. Medjibe & John R. Poulsen
38. School of GeoSciences, University of Edinburgh, Edinburgh, UK
    Murray Collins & Edward T. A. Mitchard
39. Grantham Research Institute on Climate Change and the Environment, London, UK
    Murray Collins
40. Inventory and Monitoring Program, National Park Service, Fredericksburg, VA, USA
    James A. Comiskey
41. Smithsonian Institution, Washington, DC, USA
    James A. Comiskey
42. Department of Plant Sciences, University of Cambridge, Cambridge, UK
    David A. Coomes
43. TERRA, Forest is Life, Gembloux Agro-Bio Tech, University of Liège, Liège, Belgium
    Jean-Louis Doucet
44. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
    Adriane Esquivel-Muelbert
45. Department of Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
    Ted R. Feldpausch
46. The Gola Rainforest National Park, Kenema, Sierra Leone
    Alusine Fofanah
47. National Herbarium, Yaounde, Cameroon
    Christelle Gonmadje
48. Forest Global Earth Observatory (ForestGEO), Smithsonian Tropical Research Institute, Washington, DC, USA
    Jefferson S. Hall & David Kenfack
49. Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
    Alan C. Hamilton
50. Royal Botanic Garden Edinburgh, Edinburgh, UK
    David J. Harris & Axel Dalberg Poulsen
51. Lukuru Wildlife Research Foundation, Kinshasa, Democratic Republic of Congo
    Terese B. Hart
52. Division of Vertebrate Zoology, Yale Peabody Museum of Natural History, New Haven, CT, USA
    Terese B. Hart
53. Département Hommes et Environnement, Muséum National d’Histoire Naturel, Paris, France
    Annette Hladik
54. École Normale Supérieure (ENS), Département des Sciences et Vie de la Terre, Laboratoire de Géomatique et d’Écologie Tropicale Appliquée, Université Marien Ngouabi, Brazzaville, Republic of Congo
    Suspense A. Ifo
55. School of Biological Sciences, University of Bristol, Bristol, UK
    Tommaso Jucker
56. Department of Environment, Laboratory of Computational & Applied Vegetation Ecology (Cavelab), Ghent University, Ghent, Belgium
    Elizabeth Kearsley & Hans Verbeeck
57. Tropical Ecology, Assessment and Monitoring (TEAM) Network, Arlington, VA, USA
    David Kenfack & Emanuel H. Martin
58. Department of Earth Sciences, University of Hong Kong, Hong Kong, China
    Alexander Koch
59. Uganda Programme, Wildlife Conservation Society, Kampala, Uganda
    Miguel E. Leal
60. A Rocha International, Cambridge, UK
    Jeremy A. Lindsell
61. Centre for Conservation Science, The Royal Society for the Protection of Birds, Sandy, UK
    Jeremy A. Lindsell
62. Faculté des Sciences, Laboratoire d’Écologie et Aménagement Forestier, Université de Kisangani, Kisangani, Democratic Republic of Congo
    Janvier Lisingo & Jean-Remy Makana
63. Royal Botanic Gardens, Kew, London, UK
    Jon C. Lovett
64. Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK
    Yadvinder Malhi & Sam Moore
65. Tropical Forests and People Research Centre, University of the Sunshine Coast, Sippy Downs, Queensland, Australia
    Andrew R. Marshall
66. Flamingo Land Ltd, Kirby Misperton, UK
    Andrew R. Marshall
67. Fleming College, Peterborough, Ontario, Canada
    Jim Martin
68. Udzungwa Ecological Monitoring Centre, Mang’ula, Tanzania
    Emanuel H. Martin
69. Commission of Central African Forests (COMIFAC), Yaounde, Cameroon
    Vincent P. Medjibe
70. Agence Nationale des Parcs Nationaux, Libreville, Gabon
    Vincent P. Medjibe, Vianet Mihindou & Fidèle Evouna Ondo
71. Sokoine University of Agriculture, Morogoro, Tanzania
    Pantaleo K. T. Munishi
72. University of Abeokuta, Abeokuta, Nigeria
    Lucas Ojo
73. School of Biological Sciences, University of Southampton, Southampton, UK
    Kelvin S.-H. Peh
74. Department of Zoology, Conservation Science Group, University of Cambridge, Cambridge, UK
    Kelvin S.-H. Peh
75. School of Life Sciences, University of Lincoln, Lincoln, UK
    Lan Qie
76. Bureau Waardenburg, Culemborg, The Netherlands
    Jan Reitsma
77. Department of Biology, University of Florence, Florence, Italy
    Francesco Rovero
78. Tropical Biodiversity Section, MUSE—Museo delle Scienze, Trento, Italy
    Francesco Rovero
79. Department of Plant & Soil Science, School of Biological Sciences, University of Aberdeen, Aberdeen, UK
    Michael D. Swaine
80. Institute for Transport Studies, University of Leeds, Leeds, UK
    Joey Talbot
81. UK Research & Innovation, Innovate UK, London, UK
    James Taplin
82. Department of Geography, National University of Singapore, Singapore, Singapore
    David M. Taylor
83. Biology Department, Washington State University, Vancouver, WA, USA
    Duncan W. Thomas
84. Ministère de l’Environnement et Développement Durable, Kinshasa, Democratic Republic of Congo
    Benjamin Toirambe
85. Faculté des Sciences Appliquées, Université de Mbujimayi, Mbujimayi, Democratic Republic of Congo
    John Tshibamba Mukendi
86. Friends of Ecosystem and the Environment, Monrovia, Liberia
    Darlington Tuagben
87. Yale School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA
    Peter M. Umunay
88. Wildlife Conservation Society, New York, NY, USA
    Peter M. Umunay
89. School of Geography, University of Nottingham, Nottingham, UK
    Geertje M. F. van der Heijden
90. International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, FL, USA
    Jason Vleminckx
91. Faculté des Sciences, Service d’Évolution Biologique et Écologie, Université Libre de Bruxelles, Brussels, Belgium
    Jason Vleminckx
92. School of Natural Sciences, University of Bangor, Bangor, UK
    Simon Willcock
93. Independent Researcher, Bad Aussee, Austria
    Hannsjörg Wöll
94. W.R.T. College of Agriculture and Forestry, University of Liberia, Monrovia, Liberia
    John T. Woods

Authors

1. Wannes Hubau
2. Simon L. Lewis
3. Oliver L. Phillips
4. Kofi Affum-Baffoe
5. Hans Beeckman
6. Aida Cuní-Sanchez
7. Armandu K. Daniels
8. Corneille E. N. Ewango
9. Sophie Fauset
10. Jacques M. Mukinzi
11. Douglas Sheil
12. Bonaventure Sonké
13. Martin J. P. Sullivan
14. Terry C. H. Sunderland
15. Hermann Taedoumg
16. Sean C. Thomas
17. Lee J. T. White
18. Katharine A. Abernethy
19. Stephen Adu-Bredu
20. Christian A. Amani
21. Timothy R. Baker
22. Lindsay F. Banin
23. Fidèle Baya
24. Serge K. Begne
25. Amy C. Bennett
26. Fabrice Benedet
27. Robert Bitariho
28. Yannick E. Bocko
29. Pascal Boeckx
30. Patrick Boundja
31. Roel J. W. Brienen
32. Terry Brncic
33. Eric Chezeaux
34. George B. Chuyong
35. Connie J. Clark
36. Murray Collins
37. James A. Comiskey
38. David A. Coomes
39. Greta C. Dargie
40. Thales de Haulleville
41. Marie Noel Djuikouo Kamdem
42. Jean-Louis Doucet
43. Adriane Esquivel-Muelbert
44. Ted R. Feldpausch
45. Alusine Fofanah
46. Ernest G. Foli
47. Martin Gilpin
48. Emanuel Gloor
49. Christelle Gonmadje
50. Sylvie Gourlet-Fleury
51. Jefferson S. Hall
52. Alan C. Hamilton
53. David J. Harris
54. Terese B. Hart
55. Mireille B. N. Hockemba
56. Annette Hladik
57. Suspense A. Ifo
58. Kathryn J. Jeffery
59. Tommaso Jucker
60. Emmanuel Kasongo Yakusu
61. Elizabeth Kearsley
62. David Kenfack
63. Alexander Koch
64. Miguel E. Leal
65. Aurora Levesley
66. Jeremy A. Lindsell
67. Janvier Lisingo
68. Gabriela Lopez-Gonzalez
69. Jon C. Lovett
70. Jean-Remy Makana
71. Yadvinder Malhi
72. Andrew R. Marshall
73. Jim Martin
74. Emanuel H. Martin
75. Faustin M. Mbayu
76. Vincent P. Medjibe
77. Vianet Mihindou
78. Edward T. A. Mitchard
79. Sam Moore
80. Pantaleo K. T. Munishi
81. Natacha Nssi Bengone
82. Lucas Ojo
83. Fidèle Evouna Ondo
84. Kelvin S.-H. Peh
85. Georgia C. Pickavance
86. Axel Dalberg Poulsen
87. John R. Poulsen
88. Lan Qie
89. Jan Reitsma
90. Francesco Rovero
91. Michael D. Swaine
92. Joey Talbot
93. James Taplin
94. David M. Taylor
95. Duncan W. Thomas
96. Benjamin Toirambe
97. John Tshibamba Mukendi
98. Darlington Tuagben
99. Peter M. Umunay
100. Geertje M. F. van der Heijden
101. Hans Verbeeck
102. Jason Vleminckx
103. Simon Willcock
104. Hannsjörg Wöll
105. John T. Woods
106. Lise Zemagho

Contributions

S.L.L. conceived and managed the AfriTRON forest plot recensus programme, O.L.P., T.C.H.S., L.J.T.W. and Y.M. contributed to its development. W.H., S.L.L., O.L.P., B.S. and M.J.P.S. developed the study. W.H., S.L.L., O.L.P., K.A.-B., H.B., A.C.-S., C.E.N.E., S.F., D.S., B.S., T.C.H.S., S.C.T., K.A.A., S.A.-B., C.A.A., T.R.B., L.F.B., F. Baya, S.K.B., F. Benedet, R.B., Y.E.B., P. Boeckx, P. Boundja, T.B., E.C., G.B.C., C.J.C., M.C., J.A.C., D.C., A.K.D., G.C.D., T.d.H., M.D.K., J.-L.D., T.R.F., A.F., E.G.F., M.G., C.G., S.G.-F., J.S.H., A.C.H., D.J.H., T.B.H., M.B.N.H., A.H., S.A.I., K.J.J., T.J., E.K.Y., E.K., D.K., M.E.L., J.A.L., J.L., J.C.L., J.-R.M., Y.M., A.R.M., J.M., E.H.M., F.M.M., V.P.M., V.M., E.T.A.M., S.M., J.M.M., P.K.T.M., N.N.B., L.O., F.E., K.S.-H.P., A.D.P., J.R.P., L.Q., J.R., F.R., M.D.S., H.T., J. Talbot, J. Taplin, D.M.T., D.W.T., B.T., J.T.M., D.T., P.M.U., G.v.d.H., H.V., J.V., L.J.T.W., S.W., H.W., J.T.W. and L.Z. contributed data (with larger field contributions by S.L.L., W.H., A.C.-S., B.S., H.T., A.K.D., C.E.N.E., J.M.M., K.A.-B. and S.F.). O.L.P., T.R.B., S.L.L. and G.L.-G. conceived and managed forestplots.net; O.L.P., T.R.B., S.L.L., E.G., G.L.-G., G.C.P., A.L., R.J.W.B., T.R.F. and M.J.P.S. developed it. W.H., M.J.P.S., S.L.L., O.L.P., R.J.W.B., A.L., G.L.-G., A.E.-M., A.K., E.G., T.R.B., A.C.B. and G.C.P. contributed analysis tools. W.H. and S.L.L. analysed the data (with important contributions from M.J.P.S.). S.L.L. and W.H. wrote the paper. All co-authors read and approved the manuscript (with important insights provided by O.L.P., S.F., R.J.W.B., E.G., H.B., D.S., M.J.P.S., S.G.-F., P.B., H.V. and S.C.T).

Corresponding author

Correspondence toWannes Hubau.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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Extended data figures and tables

Extended Data Fig. 1 Map showing the locations of the 244 plots included in this study.

Dark green represents all lowland closed-canopy forests, submontane forests and forest-agriculture mosaics; light green shows swamp forests and mangroves, blue circles represent plot clusters, referred to by three-letter codes (see Supplementary Table 1 for the full list of plots). Clusters <50 km apart are shown as one point for display only, with the circle size corresponding to sampling effort in terms of hectares monitored. Land cover data are from The Land Cover Map for Africa in the Year 2000 (GLC2000 database)101,[102](/articles/s41586-020-2035-0#ref-CR102 "Mayaux, P. et al. The Land Cover Map for Africa in the Year 2000 GLC2000 database, https://forobs.jrc.ec.europa.eu/products/glc2000/products.php

             (European Commission Joint Research Centre, 2003)."). This map was created using the R statistical platform, version 3.2.1 (ref. [62](/articles/s41586-020-2035-0#ref-CR62 "R Development Core Team R: A Language and Environment for Statistical Computing 
              http://www.R-project.org/
              
             (2015).")), which is under the GNU Public License.

Extended Data Fig. 2 Long-term aboveground carbon dynamics of 244 African structurally intact old-growth tropical forest inventory plots.

Points in the scatterplots indicate the mid-census interval date, with horizontal bars connecting the start and end date for each census interval for net aboveground biomass carbon change (a), carbon gains (from woody production from tree growth and newly recruited stems) (b), and carbon losses (from tree mortality) (c). Examples of time series for three individual plots are shown in purple, yellow and green. Associated histograms show the distribution of the plot-level net aboveground biomass carbon (with a three-parameter Weibull probability density distribution fitted in blue, showing that the carbon sink is significantly larger than zero; one-tailed _t_-test: P < 0.001) (d), carbon gains (e) and carbon losses (f).

Extended Data Fig. 3 AIC from correlations between the carbon gain in tropical forest inventory plots and changes in atmospheric CO2, temperature (MAT) or drought (MCWD), each calculated over ever-longer prior intervals.

Panels show the AIC from linear mixed effects models of carbon gains from 565 African and Amazonian plots and corresponding changes in atmospheric CO2 (CO2-change) (a), MAT (MAT-change) (b), and drought (MCWD-change) (c). For CO2 the AIC minimum was observed when predicting the carbon gain from the change in CO2 calculated over a 56-year-long prior interval length. We use this length of time to calculate our CO2-change parameter. Such a value is expected because forest stands will respond most strongly to CO2 when most individuals have grown under the new rapidly changing condition, which should be at its maximum at a time approximately equivalent to the CRT of a forest stand30,90 (mean of 62 years in this pooled African and Amazonian dataset). For MAT the AIC minimum was 5 years, which we use as the prior interval to calculate our MAT-change parameter. This length is consistent with experiments showing temperature acclimation of leaf- and plant-level photosynthetic and respiration processes over approximately half-decadal timescales31,91. For MCWD the AIC minimum is not obvious, while the slope of the correlation, shown in d, shows no overall trend and oscillates between positive or negative values, meaning there is no relationship between carbon gains and the change in MCWD over intervals longer than 1 year; therefore MCWD-change is not included in our models. This result suggests that once a drought ends, its impact on tree growth fades rapidly, as seen in other studies14,92. Furthermore, in the moist tropics wet-season rainfall is expected to recharge soil water, and hence lagged impacts of droughts are not expected.

Extended Data Fig. 4 Potential forest dynamics-related drivers of carbon gains and losses in structurally intact old-growth African and Amazonian tropical forest inventory plots.

The aboveground carbon gains, from woody production (a, b), and aboveground carbon losses, from tree mortality (c, d), are plotted against the CRT, and wood density for African (blue) and Amazonian (brown) inventory plots. Linear mixed effects models were performed with census intervals (n = 1,566) nested within plots (n = 565) to avoid pseudo-replication, using an empirically derived weighting based on interval length and plot area (see Methods). Significant regression lines from the linear mixed effects models for the complete dataset are shown as a solid line; non-significant regressions are shown as a dashed line. Each dot represents a time-weighted mean plot-level value; the shading of the dot represents total monitoring length, with empty circles corresponding to plots monitored for ≤5 years and solid circles for plots monitored for >20 years. Carbon loss data are presented untransformed for comparison with carbon gains; linear mixed effects models on transformed data to fit normality assumptions do not change the significance of the results. Note that CRT is calculated differently for the carbon gains and losses models (see Methods).

Extended Data Fig. 5 Trends in predictor variables used to estimate long-term trends in aboveground carbon gains, carbon losses and the resulting net carbon sink in African and Amazonian structurally intact old-growth tropical forest inventory plot networks.

Mean annual CO2-change (a), MAT (b), MAT-change (c), MCWD (d), CRT (e) and wood density (f) for African plot locations in blue, and corresponding variables for Amazon plot locations in brown (g–l). Solid lines represent observational data where >75% of the plots were monitored; long-dashed lines are plot means where <75% of plots were monitored. Dotted lines are future values estimated from linear trends from the 1 January 1983 to 31 December 2014 (Africa) or 1 January 1983 to mid-2011 (Amazon) data (slope and P value reported in each panel), see Methods for details. Upper and lower confidence intervals (shaded area) for the past are calculated by respectively adding and subtracting 2_σ_ to the mean of each annual value. Upper and lower confidence intervals for the future (Africa: 1 January 2015 to 31 December 2039; Amazonia: mid-2011 to 31 December 2039) were estimated by adding and subtracting 2_σ_ from the slope of the regression model.

Extended Data Fig. 6 The change in carbon losses versus CRT of long-term structurally intact old-growth forest inventory plots in Africa and Amazonia.

For plots with two census intervals, we calculated the change in carbon losses (‘∆losses’) as the carbon losses (in Mg C ha−1 yr−1) of the second interval minus the carbon losses of the first interval, divided by the difference in mid-interval dates. For plots with more than two intervals, we calculated the change in carbon losses for each pair of subsequent intervals, then calculated the plot-level mean over all pairs, weighted by the time length between mid-interval dates. This analysis includes only plots with at least two census intervals that were monitored for a total of ≥20 years (that is, roughly one-third of the mean CRT of the pooled African and Amazon dataset; n = 116). Breakpoint regression was used to assess the CRT length below which forest carbon losses begin to increase. Plots with CRT <77 years show a recent long-term increase in carbon losses; longer CRT plots do not. Blue points are African plots, brown points are Amazonian plots.

Extended Data Fig. 7 Trends in net aboveground live biomass carbon, carbon gains and carbon losses from intensively monitored structurally intact old-growth tropical forest inventory plots in Africa.

Trends are calculated for the last 15 years of the twentieth century (a–c) and the first 15 years of the twenty-first century (d–f). Plots were selected from the full dataset if their census intervals cover at least 50% of the respective time windows, that is, they are intensely monitored (n = 56 plots for 1 January 1985 to 31 December 1999, and n = 134 plots for 1 January 2000 to 31 December 2014, respectively). Solid lines show mean values, and shading corresponds to the 95% CI, as calculated in Fig. 1. Dashed lines, slopes and P values are from linear mixed effects models, as in Fig. 1. The data shows a difference compared to Fig. 1, notably the sink decline after about 2010 driven by rising carbon losses. This is because in Fig. 1 we include all available plots over the 1 January 1983 to 31 December 2014 window, which includes clusters of plots monitored only in the 2010s, often monitored for a single census interval, that had low carbon loss and high carbon sink values.

Extended Data Fig. 8 Twenty-first-century trends in aboveground biomass carbon losses from structurally intact old-growth African tropical forest inventory plots with either long or short CRT.

a, b, All plots, that is, as in Fig. 1, but split into a long-CRT group (a) and a short-CRT group (b), each containing half of the 244 plots. c, d, Plots are restricted to those spanning >50% of the time window, that is, intensely monitored plots, as in Extended Data Fig. 7, but split into a long-CRT group (c) and a short-CRT group (d), each containing half of the 134 plots. Solid lines indicate mean values, shading the 95% CI, as for Fig. 1. Dashed lines, slopes and P values are from linear mixed effects models, as for Fig. 1. Carbon losses increase at a higher rate in the short-CRT than the long-CRT group of plots, in both datasets, although this increase is not statistically significant.

Extended Data Table 1 Models to predict carbon gains and losses in structurally intact old-growth African and Amazonian tropical forests

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Extended Data Table 2 Forest area estimates used to calculate total continental forest sink

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Hubau, W., Lewis, S.L., Phillips, O.L. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests.Nature 579, 80–87 (2020). https://doi.org/10.1038/s41586-020-2035-0

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• Received: 09 June 2019
• Accepted: 19 December 2019
• Published: 04 March 2020
• Version of record: 04 March 2020
• Issue date: 05 March 2020
• DOI: https://doi.org/10.1038/s41586-020-2035-0