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A unified explanation for the morphology of raised peatlands

Nature volume 625, pages 79–84 (2024)Cite this article

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Abstract

Raised peatlands, or bogs, are gently mounded landforms that are composed entirely of organic matter1,2,3,4 and store the most carbon per area of any terrestrial ecosystem5. The shapes of bogs are critically important because their domed morphology4,6,7 accounts for much of the carbon that bogs store and determines how they will respond to interventions8,9 to stop greenhouse gas emissions and fires after anthropogenic drainage10,11,12,13. However, a general theory to infer the morphology of bogs is still lacking4,6,7. Here we show that an equation based on the processes universal to bogs explains their morphology across biomes, from Alaska, through the tropics, to New Zealand. In contrast to earlier models of bog morphology that attempted to describe only long-term equilibrium shapes4,6,7 and were, therefore, inapplicable to most bogs14,15,16, our approach makes no such assumption and makes it possible to infer full shapes of bogs from a sample of elevations, such as a single elevation transect. Our findings provide a foundation for quantitative inference about the morphology, hydrology and carbon storage of bogs through Earth’s history, as well as a basis for planning natural climate solutions by rewetting damaged bogs around the world.

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Fig. 1: Monotonic relationship between bog morphology and solution to Poisson’s equation in global peatlands.
Fig. 2: Distribution of bog sites in geographic and climate space.
Fig. 3: The bog-function approach subsumes existing models of bog morphology.
Fig. 4: Estimating whole-bog morphology and irrecoverable carbon stocks from a single elevation transect.

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Data availability

The lidar and topographic data used in this study are available from the Estonian Topographic Database, the Natural Resources of Canada High Resolution Digital Elevation Model (HRDEM) project, USGS National Map (products LPC AK POW P2 2018 and LPC ARRA-LFTNE MAINE 2010), Minnesota Geospatial Information Office, National Land Survey of Finland, the Brunei Darussalam Survey Department and OpenTopography (collection Huntly, Waikato, New Zealand 2015–2019). The derived data reported in this paper have been deposited in the PANGAEA open access data archive, https://doi.org/10.1594/PANGAEA.931195. Source data are provided with this paper.

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Acknowledgements

We are grateful to J. Ratcliffe for pointing us to lidar data for Kopuatai and to J. Cobb, A. Konings, J. Ratcliffe, H. A. Stone and D. Wardle for critical comments on the manuscript. This research was supported by the National Research Foundation Singapore through the Singapore-MIT Alliance for Research and Technology’s Center for Environmental Sensing and Modeling interdisciplinary research programme and grant nos. NRF2016-ITCOO1-021 and NRF2019-ITC001-001, by the US National Science Foundation under grants no. 1923491 and 2039771 and by the Office for Space Technology and Industry (OSTIn), Singapore’s national space office, through its Space Technology Development Programme (grant no. S22-02005-STDP). This work comprises EOS contribution 552. Lidar and topographic data were provided by the Estonian Topographic Database, the Natural Resources of Canada High Resolution Digital Elevation Model (HRDEM) project, USGS National Map, Minnesota Geospatial Information Office, National Land Survey of Finland, Brunei Darussalam Survey Department and OpenTopography.

Author information

Authors and Affiliations

  1. Singapore-MIT Alliance for Research and Technology (SMART), Singapore, Singapore

    Alexander R. Cobb & Charles F. Harvey

  2. Earth Observatory of Singapore, Nanyang Technological University, Singapore, Singapore

    René Dommain

  3. Asian School of the Environment, Nanyang Technological University, Singapore, Singapore

    René Dommain

  4. National Museum of Natural History, Smithsonian Institution, Washington, DC, USA

    René Dommain

  5. School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore

    Kimberly Yeap

  6. School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore

    Hannan Cao

  7. Department of Earth System Science, Stanford University, Stanford, CA, USA

    Nathan C. Dadap

  8. Institute of Geosciences, University of Potsdam, Potsdam, Germany

    Bodo Bookhagen

  9. Department of Earth & Environmental Sciences, University of Minnesota, Minneapolis, MN, USA

    Paul H. Glaser

  10. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Charles F. Harvey

Authors
  1. Alexander R. Cobb
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  2. René Dommain
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  3. Kimberly Yeap
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  4. Hannan Cao
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  5. Nathan C. Dadap
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  6. Bodo Bookhagen
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  7. Paul H. Glaser
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  8. Charles F. Harvey
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Contributions

A.R.C. conceived the study, performed the analysis, prepared the figures and drafted the paper. A.R.C., C.H., K.Y. and R.D. identified and outlined bog sites with lidar data and developed the workflow for the creation of digital terrain maps and meshing of bog polygons. B.B., C.F.H. and P.H.G. supervised and provided feedback on the study design. A.R.C., B.B., C.F.H., N.C.D. and R.D. participated in editing of the final manuscript and all authors contributed to review and data interpretation.

Corresponding author

Correspondence to Alexander R. Cobb.

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The authors declare no competing interests.

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Nature thanks Julie Loisel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Inferring morphology of bogs with ditching.

Analysis of a bog cut by a ditch in Lost River peatland, Minnesota. Bog boundaries, lidar-derived surface elevations and approximations to bog morphology obtained by transforming the solution to Poisson’s equation to bog-surface elevations as in Fig. 1. Top, analysis of peatland boundary, ignoring ditch. If the ditch is ignored, the rank correlation between surface elevations and Poisson elevations is lower (0.98) because the assumptions underlying our approach are not valid in the ditch, in which open-channel flow occurs. Bottom, analysis of a subdomain that excludes the ditch, showing excellent agreement with the lidar topography (ρ = 0.99). The correlation coefficient is also improved (0.98 versus 0.96), despite the smaller total relief within the subdomain boundary (2.45 m versus 4.21 m) relative to microtopographic relief (about 0.3 m). Satellite images: Google, Landsat/Copernicus.

Extended Data Fig. 2 Reanalysis of topography, time-averaged water table and hydraulic transmissivity in a dynamic model.

a, Location of flowtube on the Mendaram bog for the simulation shown in Fig. 7 of ref. 7. Satellite image: CNES/Airbus, Google, Maxar Technologies. b, Simulated water level, relative to local depressions, in the bog interior and at the bog margin, driven by recharge derived from weather station rainfall. The data intervals that are shown correspond to calendar years 2001, 2003 and 2007. c, Minimum and maximum water tables within the flowtube for 2001, 2003 and 2007 (2007 overlies other years). d, Distribution of water level for 2001, 2003 and 2007 (same colour scheme as b) for bog interior (solid lines) and margin (dashed lines); interior and margin time series are plotted in b but are not distinguishable. e,f, Hydraulic transmissivity in the model as a function of water level (black line) and time-averaged transmissivity and water level along the flowtube (coloured points) in the three simulation years. g, Average transmissivity divided by net recharge versus surface elevation for 2001, 2003 and 2007. h, Bog surface (dashed line) and time-averaged water table ⟨H⟩ (coloured lines) versus Poisson elevation ϕ for 2001, 2003 and 2007 (2007 overlies other years).

Extended Data Fig. 3 Inferring morphology of bogs with incomplete elevation data.

a, Milot: available elevation data exclude southeast corner of bog. b, Mendaram: elevation data end at national boundary. c, Rivers bounding Mendaram bog are obscured by floating vegetation but visible in high-resolution images. d, Estimated bog crest (groundwater divide) and flowlines used as no-flow (Neumann) boundaries. The location of the groundwater divide was estimated from available elevation data and the larger topographic setting (b). Satellite images: CNES/Airbus, Google, Maxar Technologies.

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Cobb, A.R., Dommain, R., Yeap, K. et al. A unified explanation for the morphology of raised peatlands. Nature 625, 79–84 (2024). https://doi.org/10.1038/s41586-023-06807-w

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