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Conservation slows down emission increase from a tropical peatland in Indonesia

Nature Geoscience volume 14, pages 484–490 (2021)Cite this article

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Abstract

Tropical peatlands are threatened by climate change and land-use changes, but there remain substantial uncertainties about their present and future role in the global carbon cycle due to limited measurements. Here, we present measurements of carbon dioxide and methane emissions between mid-2017 and mid-2020 as well as nitrous oxide emissions between 2019 and 2020 at two contrasting sites at a coastal peatland in Sumatra, Indonesia. We find that greenhouse-gas emissions from intact peatland increased substantially due to an extreme drought caused by a positive Indian Ocean Dipole phase combined with El Niño. The emission in the degraded site was two times greater than that at the intact site. The smaller emission from the intact peatland suggests that protecting the remaining intact tropical peatlands from degradation offers important climate benefits, avoiding greenhouse-gas emissions of 24 ± 5 tCO2e ha−1 yr−1 (average ± standard deviation) at our study site in Indonesia.

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Fig. 1: Location of the study area, Kampar Peninsula, Sumatra, Indonesia.
Fig. 2: Intact and degraded tropical peatland in Sumatra, Indonesia is emitting CO2 and CH4 to the atmosphere.
Fig. 3: The GWL is a key driver of the net ecosystem exchange for both CO2 and CH4.

Data availability

All data that support the findings of this study are archived on https://doi.org/10.5281/zenodo.4835696.

References

  1. Dommain, R., Couwenberg, J. & Joosten, H. Development and carbon sequestration of tropical peat domes in south-east Asia: links to post-glacial sea-level changes and Holocene climate variability. Quat. Sci. Rev. 30, 999–1010 (2011).

    Article  Google Scholar 

  2. Dargie, G. C. et al. Age, extent and carbon storage of the central Congo Basin peatland complex. Nature 542, 86–90 (2017).

    Article  Google Scholar 

  3. Lähteenoja, O. et al. The large Amazonian peatland carbon sink in the subsiding Pastaza-Marañón foreland basin, Peru. Glob. Change Biol. 18, 164–178 (2012).

    Article  Google Scholar 

  4. Warren, M., Hergoualc’h, K., Kauffman, J. B., Murdiyarso, D. & Kolka, R. An appraisal of Indonesia’s immense peat carbon stock using national peatland maps: uncertainties and potential losses from conversion. Carbon Balance Manag. 12, 12 (2017).

    Article  Google Scholar 

  5. Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 23, 3581–3599 (2017).

    Article  Google Scholar 

  6. Xu, J., Morris, P. J., Liu, J. & Holden, J. PEATMAP: refining estimates of global peatland distribution based on a meta-analysis. Catena 160, 134–140 (2018).

    Article  Google Scholar 

  7. Gallego-Sala, A. V. et al. Latitudinal limits to the predicted increase of the peatland carbon sink with warming. Nat. Clim. Change 8, 907–913 (2018).

    Article  Google Scholar 

  8. Loisel, J. et al. Expert assessment of future vulnerability of the global peatland carbon sink. Nat. Clim. Change 11, 70–77 (2021).

    Article  Google Scholar 

  9. Wang, S., Zhuang, Q., Lähteenoja, O., Draper, F. C. & Cadillo-Quiroz, H. Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate. Proc. Natl Acad. Sci. USA 115, 12407–12412 (2018).

    Article  Google Scholar 

  10. Li, W. et al. Future precipitation changes and their implications for tropical peatlands. Geophys. Res. Lett. 34, L01403 (2007).

    Article  Google Scholar 

  11. Dommain, R., Couwenberg, J., Glaser, P. H., Joosten, H. & Suryadiputra, I. N. N. Carbon storage and release in Indonesian peatlands since the last deglaciation. Quat. Sci. Rev. 97, 1–32 (2014).

    Article  Google Scholar 

  12. Cobb, A. R. et al. How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands. Proc. Natl Acad. Sci. USA 114, E5187–E5196 (2017).

    Article  Google Scholar 

  13. Swails, E. et al. The response of soil respiration to climatic drivers in undrained forest and drained oil palm plantations in an Indonesian peatland. Biogeochemistry 142, 37–51 (2019).

    Article  Google Scholar 

  14. Yu, Z., Loisel, J., Brosseau, D. P., Beilman, D. W. & Hunt, S. J. Global peatland dynamics since the Last Glacial Maximum. Geophys. Res. Lett. 37, L13402 (2010).

    Article  Google Scholar 

  15. Morris, P. J. et al. Global peatland initiation driven by regionally asynchronous warming. Proc. Natl Acad. Sci. USA 115, 4851–4856 (2018).

    Article  Google Scholar 

  16. Ruwaimana, M., Anshari, G. Z., Silva, L. C. R. & Gavin, D. G. The oldest extant tropical peatland in the world: a major carbon reservoir for at least 47,000 years. Environ. Res. Lett. 15, 114027 (2020).

    Article  Google Scholar 

  17. Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).

    Article  Google Scholar 

  18. Cai, W. et al. Increased frequency of extreme Indian Ocean Dipole events due to greenhouse warming. Nature 510, 254–258 (2014).

    Article  Google Scholar 

  19. Saji, N. H., Goswami, B. N., Vinayachandran, P. N. & Yamagata, T. A dipole mode in the tropical Indian Ocean. Nature 401, 360–363 (1999).

    Article  Google Scholar 

  20. Alsepan, G. & Minobe, S. Relations between interannual variability of regional-scale Indonesian precipitation and large-scale climate dodes during 1960–2007. J. Clim. 33, 5271–5291 (2020).

    Article  Google Scholar 

  21. Hirano, T. et al. Effects of disturbances on the carbon balance of tropical peat swamp forests. Glob. Change Biol. 18, 3410–3422 (2012).

    Article  Google Scholar 

  22. Tang, A. C. et al. A Bornean peat swamp forest is a net source of carbon dioxide to the atmosphere. Glob. Change Biol. 26, 6931–6944 (2020).

    Article  Google Scholar 

  23. Leifeld, J. & Menichetti, L. The underappreciated potential of peatlands in global climate change mitigation strategies. Nat. Commun. 9, 1071 (2018).

    Article  Google Scholar 

  24. Leifeld, J., Wüst-Galley, C. & Page, S. Intact and managed peatland soils as a source and sink of GHGs from 1850 to 2100. Nat. Clim. Change 9, 945–947 (2019).

    Article  Google Scholar 

  25. Miettinen, J., Shi, C. & Liew, S. C. Land-cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Glob. Ecol. Conserv. 6, 67–78 (2016).

    Article  Google Scholar 

  26. Roucoux, K. H. et al. Threats to intact tropical peatlands and opportunities for their conservation. Conserv. Biol. 31, 1283–1292 (2017).

    Article  Google Scholar 

  27. Hooijer, A. et al. Subsidence and carbon loss in drained tropical peatlands. Biogeosciences 9, 1053–1071 (2012).

    Article  Google Scholar 

  28. Hoyt, A. M., Chaussard, E., Seppalainen, S. S. & Harvey, C. F. Widespread subsidence and carbon emissions across Southeast Asian peatlands. Nat. Geosci. 13, 435–440 (2020).

    Article  Google Scholar 

  29. Deshmukh, C. S. et al. Impact of forest plantation on methane emissions from tropical peatland. Glob. Change Biol. 26, 2477–2495 (2020).

    Article  Google Scholar 

  30. Prananto, J. A., Minasny, B., Comeau, L.-P., Rudiyanto, R. & Grace, P. Drainage increases CO2 and N2O emissions from tropical peat soils. Glob. Change Biol. 26, 4583–4600 (2020).

    Article  Google Scholar 

  31. Myhre, G. et al. in IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 659–740 (Cambridge Univ. Press, 2013).

  32. Murdiyarso, D., Lilleskov, E. & Kolka, R. Tropical peatlands under siege: the need for evidence-based policies and strategies. Mitig. Adapt. Strateg. Glob. Change 24, 493–505 (2019).

    Article  Google Scholar 

  33. Strategy for Responsible Peatland Management 6th edn (eds Clarke, D. & Rieley, J. O.) (International Peatland Society, 2019).

  34. Sulistiyanto, Y. Nutrient Dynamics in Different Sub-Types of Peat Swamp Forest in Central Kalimantan, Indonesia. Doctoral dissertation, Nottingham Univ. (2004).

  35. Hirano, T., Kusin, K., Limin, S. & Osaki, M. Evapotranspiration of tropical peat swamp forests. Glob. Change Biol. 21, 1914–1927 (2015).

    Article  Google Scholar 

  36. Nishimua, T. et al. Mortality and growth of trees in peat-swamp and heath forests in Central Kalimantan after severe drought. Plant Ecol. 188, 165–177 (2007).

    Article  Google Scholar 

  37. Kelly, T. J. et al. The vegetation history of an Amazonian domed peatland. Palaeogeogr. Palaeoclimatol. Palaeoecol. 468, 129–141 (2017).

    Article  Google Scholar 

  38. Cobb, A. R., Dommain, R. R., Tan, F., Heng, N. H. E. & Harvey, C. F. Carbon storage capacity of tropical peatlands in natural and artificial drainage networks. Environ. Res. Lett. 15, 23–25 (2020).

    Article  Google Scholar 

  39. Kiew, F. et al. Carbon dioxide balance of an oil palm plantation established on tropical peat. Agric. For. Meteorol. 295, 108189 (2020).

    Article  Google Scholar 

  40. Yupi, H. M., Inoue, T., Bathgate, J. & Putra, R. Concentrations, loads and yields of organic carbon from two tropical peat swamp forest streams in Riau Province, Sumatra, Indonesia. Mires Peat 18, 14 (2016).

    Google Scholar 

  41. Evans, C. D., Renou-Wilson, F. & Strack, M. The role of waterborne carbon in the greenhouse gas balance of drained and re-wetted peatlands. Aquat. Sci. 78, 573–590 (2016).

    Article  Google Scholar 

  42. Jauhiainen, J. et al. Nitrous oxide fluxes from tropical peat with different disturbance history and management. Biogeosciences 9, 1337–1350 (2012).

    Article  Google Scholar 

  43. Neubauer, S. C. & Megonigal, J. P. Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18, 1000–1013 (2015).

    Article  Google Scholar 

  44. Wijedasa, L. S. et al. Carbon emissions from South-East Asian peatlands will increase despite emission-reduction schemes. Glob. Change Biol. 24, 4598–4613 (2018).

    Article  Google Scholar 

  45. Hansson, A. & Dargusch, P. An estimate of the financial cost of peatland restoration in Indonesia. Case Stud. Environ. 2, 1–8 (2017).

    Article  Google Scholar 

  46. Ward, C. et al. Wading through the swamp: what does tropical peatland restoration mean to national-level stakeholders in Indonesia? Restor. Ecol. 28, 817–827 (2020).

    Article  Google Scholar 

  47. Lilleskov, E. et al. Is Indonesian peatland loss a cautionary tale for Peru? A two-country comparison of the magnitude and causes of tropical peatland degradation. Mitig. Adapt. Strateg. Glob. Change 24, 591–623 (2019).

    Article  Google Scholar 

  48. Couwenberg, J. & Hooijer, A. Towards robust subsidence-based soil carbon emission factors for peat soils in south-east Asia, with special reference to oil palm plantations. Mires Peat 12, 1 (2013).

    Google Scholar 

  49. Kljun, N., Calanca, P., Rotach, M. W. & Schmid, H. P. A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP). Geosci. Model Dev. 8, 3695–3713 (2015).

    Article  Google Scholar 

  50. Cole, L. E. S., Bhagwat, S. A. & Willis, K. J. Long-term disturbance dynamics and resilience of tropical peat swamp forests. J. Ecol. 103, 16–30 (2015).

    Article  Google Scholar 

  51. Hapsari, K. A. et al. Environmental dynamics and carbon accumulation rate of a tropical peatland in Central Sumatra, Indonesia. Quat. Sci. Rev. 169, 173–187 (2017).

    Article  Google Scholar 

  52. Evans, C. D. et al. Rates and spatial variability of peat subsidence in Acacia plantation and forest landscapes in Sumatra, Indonesia. Geoderma 338, 410–421 (2019).

    Article  Google Scholar 

  53. Aubinet, M. et al. Estimates of the annual net carbon and water exchange of European forests: the EUROFLUX methodology. Adv. Ecol. Res. 30, 113–175 (2000).

    Article  Google Scholar 

  54. Vickers, D. & Mahrt, L. Quality control and flux sampling problems for tower and aircraft data. J. Atmos. Ocean. Technol. 14, 512–526 (1997).

    Article  Google Scholar 

  55. Wilczak, J. M., Oncley, S. P. & Stage, S. A. Sonic anemometer tilt correction algorithms. Bound.-Layer Meteorol. 99, 127–150 (2001).

    Article  Google Scholar 

  56. Massman, W. J. A simple method for estimating frequency response corrections for eddy covariance systems. Agric. For. Meteorol. 104, 185–198 (2000).

    Article  Google Scholar 

  57. Webb, E. K., Pearman, G. I. & Leuning, R. Correction of flux measurements for density effects due to heat andwater vapour transfer. Q. J. R. Meteorol. Soc. 106, 85–100 (1980).

    Article  Google Scholar 

  58. Xu, K. E. et al. The eddy-covariance storage term in air: consistent community resources improve flux measurement reliability. Agric. For. Meteorol. 279, 107734 (2019).

    Article  Google Scholar 

  59. Foken, T. & Wichura, B. Tools for quality assessment of surface-based flux measurements. Agric. For. Meteorol. 78, 83–105 (1996).

    Article  Google Scholar 

  60. Mauder, M. et al. A strategy for quality and uncertainty assessment of long-term eddy-covariance measurements. Agric. For. Meteorol. 169, 122–135 (2013).

    Article  Google Scholar 

  61. Papale, D. et al. Towards a standardized processing of net ecosystem exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biogeosciences 3, 571–583 (2006).

    Article  Google Scholar 

  62. Falge, E. et al. Gap-filling strategies for defensible annual sums of net ecosystem exchange. Agric. For. Meteorol. 107, 43–69 (2001).

    Article  Google Scholar 

  63. Kiew, F. et al. CO2 balance of a secondary tropical peat swamp forest in Sarawak, Malaysia. Agric. For. Meteorol. 248, 494–501 (2018).

    Article  Google Scholar 

  64. Moffat, A. M. et al. Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes. Agric. For. Meteorol. 147, 209–232 (2007).

    Article  Google Scholar 

  65. Papale, D. & Valentini, R. A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization. Glob. Change Biol. 9, 525–535 (2003).

    Article  Google Scholar 

  66. Xu, T. et al. Evaluating different machine learning methods for upscaling evapotranspiration from flux towers to the regional scale. J. Geophys. Res. Atmos. 123, 8674–8690 (2018).

    Article  Google Scholar 

  67. Kim, Y. et al. Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis. Glob. Change Biol. 26, 1499–1518 (2019).

    Article  Google Scholar 

  68. Wutzler, T. et al. Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences 15, 5015–5030 (2018).

    Article  Google Scholar 

  69. Reichstein, M. et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Glob. Change Biol. 11, 1424–1439 (2005).

    Article  Google Scholar 

  70. Finkelstein, P. L. & Sims, P. F. Sampling error in eddy correlation flux measurements. J. Geophys. Res. 106, 3503–3509 (2001).

    Article  Google Scholar 

  71. Deventer, M. J. et al. Error characterization of methane fluxes and budgets derived from a long-term comparison of open- and closed-path eddy covariance systems. Agric. For. Meteorol. 278, 107638 (2019).

    Article  Google Scholar 

  72. Serça, D., Delmas, R., Jambert, C. & Labroue, L. Emissions of nitrogen oxides from equatorial rain forest in central Africa: origin and regulation of NO emission from soils. Tellus B 46, 243–254 (1994).

    Article  Google Scholar 

  73. Iddris, N. A.-A., Corre, M. D., Yemefack, M., van Straaten, O. & Veldkamp, E. Stem and soil nitrous oxide fluxes from rainforest and cacao agroforest on highly weathered soils in the Congo Basin. Biogeosciences 17, 5377–5397 (2020).

    Article  Google Scholar 

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Acknowledgements

The establishment and operation of the EC towers and associated data collection were funded by Asia Pacific Resources International Ltd (APRIL) and Riau Ecosystem Restoration (RER).

Author information

Authors and Affiliations

  1. Asia Pacific Resources International Ltd, Pelalawan Regency, Indonesia

    Chandra S. Deshmukh, Dony Julius, Adibtya Asyhari, Nardi Nardi, Ari P. Susanto, Nurholis Nurholis, M. Hendrizal, Sofyan Kurnianto, Yogi Suardiwerianto & Yuandanis W. Salam

  2. Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA

    Ankur R. Desai

  3. Centre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, Leicester, UK

    Susan E. Page

  4. Indonesian Center for Agricultural Land Resources Research and Development, Bogor, Indonesia

    Fahmuddin Agus

  5. Faculty of Forestry Universitas Tanjungpura, Pontianak, Indonesia

    Dwi Astiani

  6. Department of Soil Science and Land Resource, Institut Pertanian Bogor, Bogor, Indonesia

    Supiandi Sabiham

  7. Birmingham Institute of Forest Research (BIFoR), School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Vincent Gauci

  8. Centre for Ecology and Hydrology, Bangor, UK

    Chris D. Evans

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  1. Chandra S. Deshmukh
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  2. Dony Julius
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Contributions

C.S.D., C.D.E. and S.E.P. conceived the study. C.S.D., D.J., A.P.S, Y.W.S and A.R.D. completed EC data processing. D.J., N. Nardi, A.P.S., N. Nurholis, M.H., C.S.D., S.K., Y.S. and A.A. performed the data collection, EC instrument calibration and maintenance. C.S.D. conceived the paper and wrote the initial draft, to which all authors provided critical contributions and approved the submission.

Corresponding author

Correspondence to Chandra S. Deshmukh.

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Competing interests

C.D.E., S.E.P., S.S., V.G., F.A. and D.A. contributed to this paper as part of their contribution to the Independent Peat Expert Working Group (IPEWG), which was set up by Asia Pacific Resources International Ltd (APRIL) to provide objective science-based advice on peatland management. The contribution of A.R.D. was also supported by APRIL to provide technical guidance on the EC data processing including quality controls and gap-filling protocols. C.S.D., D.J., N. Nardi, A.P.S., N. Nurholis, M.H., S.K., Y.S., A.A. and Y.W.S. are employed by APRIL to conduct data collection, instrument maintenance and calibration. The funders had no role in the interpretation of data, in the writing of the manuscript or in the decision to publish the results. The authors declare that all views expressed are their own.

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Peer review information Nature Geoscience thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang.

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Extended data

Extended Data Fig. 1 Rainfall and climate indices in the study area.

a, Comparison between monthly rainfall in the intact peatland, the degraded peatland, and Pekanbaru Airport (Riau, Sumatra) which represent the closest available long-term rainfall measurements in the region, (b) comparison between rainfall in Pekanbaru Airport during study period and long-term average of 30 years from 1991-2020 and (c) the relationship between rainfall in Pekanbaru Airport and climate indices represented with normalized anomaly of rainfall amount in July-August-September; ‘E’ and ‘L’ indicate El Niño and La Niña years, respectively; red and blue bars indicate positive and negative IOD years, respectively; grey bar shows neutral years. The Dipole Mode Index data were obtained from http://psl.noaa.gov/. Southern Oscillation Index were obtained from https://www.cpc.ncep.noaa.gov/data/indices/soi. The extended dry period in July-September 2019 coincided with a convergence of El-Niño and positive Indian Ocean Dipole.

Extended Data Fig. 2 Groundwater level controls net ecosystem CO2 exchanges.

Response of (a) measured half-hourly net ecosystem CO2 exchanges, (b) ecosystem respiration and (c) gross primary production to the groundwater level at the intact peatland (black) and the degraded peatland (red). Measured half-hourly data were grouped into daytime (06:00-18:00 LT) and nightime (18:00-06:00 LT). Then each dataset were sorted into 50 classes of groundwater level and averaged for each class. Subsequently, the daily value was computed from the average of daytime and nighttime values. The vertical bars represent the standard deviation for each class. d, Response of the 09:00-15:00 LT gross primary production to photosyntheic photon flux density at two different groundwater level classes based on median value. The selection of time window may have created biases in actual response curves of both ecosystems, but this bias would not change the interpretation. Data were binned by subgroups of 100 half-hourly values of gross primary production and corresponding photosynthetic photon flux density and then averaged for each class. All statistical tests used a significance level of 5%. Intact peatland shows higher light-use efficiency when groundwater level is shallow.

Extended Data Fig. 3 Relationship between net ecosystem CO2 exchange and groundwater level.

Data are derived from 30 site-years of the eddy covariance measurements in tropical peatlands in Southeast Asia. Solid line indicates linear relation with dashed lines for 95% confidence interval. The statistical test used a significance level of 5%. Carbon dioxide emissions increase with lower groundwater level.

Extended Data Fig. 4 The intact peatland emits lower soil N2O emissions than the degraded peatland.

Measurements of N2O emissions at the intact peatland (black) and the degraded peatland (red). The boxes show the median value and the interquartile range, and whiskers denote the full range of all chambers. The n values represent total number of soil N2O flux measurements.

Extended Data Fig. 5 The environmental variables at the intact peatland during the study period.

Variations in daily (a) photosynthetic photon flux density, (b) air temperature, (c) vapor pressure deficit and (d) soil temperature at the intact peatland. The vertical bar represents standard deviation.

Extended Data Fig. 6 The environmental variables at the degraded peatland during the study period.

Variations in daily (a) photosynthetic photon flux density, (b) air temperature, (c) vapor pressure deficit and (d) soil temperature at the degraded peatland. The vertical bar represents standard deviation.

Extended Data Table 1 Characteristics of the intact and the degraded peatland sites in Sumatra, Indonesia
Full size table
Extended Data Table 2 Annual average with standard deviation of environmental variables at the intact and the degraded peatland in Sumatra, Indonesia
Full size table
Extended Data Table 3 Annual net ecosystem CO2, CH4 and H2O (evapotranspiration) exchanges at the intact and the degraded peatland in Sumatra, Indonesia
Full size table

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Deshmukh, C.S., Julius, D., Desai, A.R. et al. Conservation slows down emission increase from a tropical peatland in Indonesia. Nat. Geosci. 14, 484–490 (2021). https://doi.org/10.1038/s41561-021-00785-2

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