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Increasing contribution of peatlands to boreal evapotranspiration in a warming climate

Abstract

The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.

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Fig. 1: Multimodel mean projection of changes in growing season ΔVPDGS by the end of the twenty-first century.
Fig. 2: Eddy covariance flux tower locations and spatial pattern of dryness index in the boreal biome.
Fig. 3: ET and gs response to VPD.
Fig. 4: A comparison of peatland and forest ET under current and future climates.

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Data availability

Source data for Figs. 1–4 and Extended Data Figs. 1–3 are provided with the paper. Eddy covariance flux tower data used in this study can be accessed through the AmeriFlux (https://ameriflux.lbl.gov/), FLUXNET (https://fluxnet.fluxdata.org/data/fluxnet2015-dataset/), or European Fluxes Database Cluster (http://www.europe-fluxdata.eu/) webpages (see Supplementary Data). Site data that are not accessible through these webpages (see Supplementary Data) are available from the corresponding author on request. Monthly climate data and PET can be accessed through the East Anglia Climate Research Unit webpage (https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.02/). Most CMIP5 model output is archived and made available through the Earth System Grid Federation (https://esgf.llnl.gov/). CanESM2 model output can be downloaded through the Canadian Centre for Climate Modelling and Analysis (http://climate-modelling.canada.ca/data/cgcm4/CanESM2/index.shtml) and CESM1-CAM5 model output is available through the Climate Data Gateway at the National Center for Atmospheric Research (https://www.earthsystemgrid.org/). Peatland maps are freely available through the Research Data Leeds Repository (http://archive.researchdata.leeds.ac.uk/251/) and on request from the corresponding author. MODIS data can be accessed for all flux tower sites through the Global Subset Tool: MODIS/VIIRS Products (https://modis.ornl.gov/cgi-bin/MODIS/global/subset.pl). The global FLUXCOM land-atmosphere energy flux data product can be accessed through the FLUXCOM webpage (http://www.fluxcom.org/EF-Products/). Global monthly mean LAI climatology can be accessed through the ORNL Distributed Active Archive Center for Biogeochemical Dynamics (https://daac.ornl.gov/VEGETATION/guides/Mean_Seasonal_LAI.html).

Code availability

All MATLAB code used in this study is available through the corresponding author’s GitHub repository72 (https://github.com/manuelhelbig/BWF_Synthesis; https://doi.org/10.5281/zenodo.3653056) and is available from the corresponding author on request. The software used to generate all results is MATLAB 2016a.

References

  1. Brandt, J. P., Flannigan, M. D., Maynard, D. G., Thompson, I. D. & Volney, W. J. A. An introduction to Canada’s boreal zone: ecosystem processes, health, sustainability, and environmental issues. Environ. Rev. 21, 207–226 (2013).

    Article  Google Scholar 

  2. Verpoorter, C., Kutser, T., Seekell, D. A. & Tranvik, L. J. A global inventory of lakes based on high-resolution satellite imagery. Geophys. Res. Lett. 41, 6396–6402 (2014).

    Article  Google Scholar 

  3. 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 

  4. Bradshaw, C. J. A. & Warkentin, I. G. Global estimates of boreal forest carbon stocks and flux. Glob. Planet. Change 128, 24–30 (2015).

    Article  Google Scholar 

  5. Le Quéré, C. et al. Global carbon budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018).

    Article  Google Scholar 

  6. Goulden, M. L. et al. Sensitivity of boreal forest carbon balance to soil thaw. Science 279, 214–217 (1998).

    Article  CAS  Google Scholar 

  7. Kauppi, P. E., Posch, M. & Pirinen, P. Large impacts of climatic warming on growth of boreal forests since 1960. PLoS ONE 9, e111340 (2014).

    Article  CAS  Google Scholar 

  8. Turetsky, M. R. et al. Global vulnerability of peatlands to fire and carbon loss. Nat. Geosci. 8, 11–14 (2015).

    Article  CAS  Google Scholar 

  9. Koven, C. D. Boreal carbon loss due to poleward shift in low-carbon ecosystems. Nat. Geosci. 6, 452–456 (2013).

    Article  CAS  Google Scholar 

  10. Allison, S. D. & Treseder, K. K. Warming and drying suppress microbial activity and carbon cycling in boreal forest soils. Glob. Change Biol. 14, 2898–2909 (2008).

    Article  Google Scholar 

  11. Gentine, P. et al. Coupling between the terrestrial carbon and water cycles—a review. Environ. Res. Lett. 14, 083003 (2019).

    Article  CAS  Google Scholar 

  12. Woo, M., Thorne, R., Szeto, K. & Yang, D. Streamflow hydrology in the boreal region under the influences of climate and human interference. Philos. Trans. R. Soc. B 363, 2249–2258 (2008).

    Article  Google Scholar 

  13. Fisher, J. B. et al. The future of evapotranspiration: global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources. Water Resour. Res. 53, 2618–2626 (2017).

    Article  Google Scholar 

  14. Lafleur, P. M. & Rouse, W. R. The influence of surface cover and climate on energy partitioning and evaporation in a subarctic wetland. Bound. Layer Meteorol. 44, 327–347 (1988).

    Article  Google Scholar 

  15. Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).

    Article  Google Scholar 

  16. Novick, K. A. et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes. Nat. Clim. Change 6, 1023–1027 (2016).

    Article  CAS  Google Scholar 

  17. Brümmer, C. et al. How climate and vegetation type influence evapotranspiration and water use efficiency in Canadian forest, peatland and grassland ecosystems. Agric. For. Meteorol. 153, 14–30 (2012).

    Article  Google Scholar 

  18. Barr, A. G., Betts, A. K., Black, T. A., McCaughey, J. H. & Smith, C. D. Intercomparison of BOREAS northern and southern study area surface fluxes in 1994. J. Geophys. Res. Atmos. 106, 33543–33550 (2001).

    Article  Google Scholar 

  19. Massmann, A., Gentine, P. & Lin, C. When does vapor pressure deficit drive or reduce evapotranspiration. J. Adv. Model. Earth Syst. 11, 3305–3320 (2019).

    Article  Google Scholar 

  20. Admiral, S. W. & Lafleur, P. M. Partitioning of latent heat flux at a northern peatland. Aquat. Bot. 86, 107–116 (2007).

    Article  Google Scholar 

  21. Williams, T. G. & Flanagan, L. B. Effect of changes in water content on photosynthesis, transpiration and discrimination against 13CO2 and C18O16O in Pleurozium and Sphagnum. Oecologia 108, 38–46 (1996).

    Article  Google Scholar 

  22. Oren, R. et al. Survey and synthesis of intra- and interspecific variation in stomatal sensitivity to vapour pressure deficit. Plant Cell Environ. 22, 1515–1526 (1999).

    Article  Google Scholar 

  23. Kellner, E. Surface energy fluxes and control of evapotranspiration from a Swedish Sphagnum mire. Agric. For. Meteorol. 110, 101–123 (2001).

    Article  Google Scholar 

  24. Helbig, M. et al. Regional atmospheric cooling and wetting effect of permafrost thaw-induced boreal forest loss. Glob. Change Biol. 22, 4048–4066 (2016).

    Article  Google Scholar 

  25. Chaudhary, N., Miller, P. A. & Smith, B. Modelling past, present and future peatland carbon accumulation across the Pan-Arctic region. Biogeosciences 14, 4023–4044 (2017).

    Article  Google Scholar 

  26. Qiu, C. et al. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales. Geosci. Model Dev. 11, 497–519 (2018).

    Article  CAS  Google Scholar 

  27. Wu, Y., Verseghy, D. L. & Melton, J. R. Integrating peatlands into the coupled canadian land surface scheme (class) v3.6 and the canadian terrestrial ecosystem model (CTEM) v2.0. Geosci. Model Dev. 9, 2639–2663 (2016).

    Article  CAS  Google Scholar 

  28. Bechtold, M. et al. PEAT-CLSM: a specific treatment of peatland hydrology in the NASA catchment land surface model. J. Adv. Model. Earth Syst. 11, 2130–2162 (2019).

    Article  Google Scholar 

  29. Poulter, B. et al. Plant functional type mapping for earth system models. Geosci. Model Dev. 4, 993–1010 (2011).

    Article  Google Scholar 

  30. Abramowitz, G., Leuning, R., Clark, M. & Pitman, A. Evaluating the performance of land surface models. J. Clim. 21, 5468–5481 (2008).

    Article  Google Scholar 

  31. Green, J. K. et al. Large influence of soil moisture on long-term terrestrial carbon uptake. Nature 565, 476–479 (2019).

    Article  CAS  Google Scholar 

  32. Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int. J. Climatol. 34, 623–642 (2014).

    Article  Google Scholar 

  33. Yurova, A., Tolstykh, M., Nilsson, M. & Sirin, A. Parameterization of mires in a numerical weather prediction model. Water Resour. Res. 50, 8982–8996 (2014).

    Article  Google Scholar 

  34. Lemordant, L., Gentine, P., Swann, A. S., Cook, B. I. & Scheff, J. Critical impact of vegetation physiology on the continental hydrologic cycle in response to increasing CO2. Proc. Natl Acad. Sci. USA 115, 4093–4098 (2018).

    Article  CAS  Google Scholar 

  35. Ewers, B. E., Gower, S. T., Bond-Lamberty, B. & Wang, C. K. Effects of stand age and tree species on canopy transpiration and average stomatal conductance of boreal forests. Plant Cell Environ. 28, 660–678 (2005).

    Article  Google Scholar 

  36. Green, J. K. et al. Regionally strong feedbacks between the atmosphere and terrestrial biosphere. Nat. Geosci. 10, 410–414 (2017).

    Article  CAS  Google Scholar 

  37. Trenberth, K. E. Atmospheric moisture recycling: role of advection and local evaporation. J. Clim. 12, 1368–1381 (1999).

    Article  Google Scholar 

  38. Ford, T. W. & Frauenfeld, O. W. Surface–atmosphere moisture interactions in the frozen ground regions of Eurasia. Sci. Rep. 6, 19163 (2016).

    Article  CAS  Google Scholar 

  39. Konings, A. G., Katul, G. G. & Porporato, A. The rainfall–no rainfall transition in a coupled land-convective atmosphere system. Geophys. Res. Lett. 37, L14401 (2010).

    Article  Google Scholar 

  40. Sikma, M. & Vilà-Guerau de Arellano, J. Substantial reductions in cloud cover and moisture transport by dynamic plant responses. Geophys. Res. Lett. 46, 1870–1878 (2019).

    Article  Google Scholar 

  41. Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

    Article  CAS  Google Scholar 

  42. Teuling, A. J. et al. Contrasting response of European forest and grassland energy exchange to heatwaves. Nat. Geosci. 3, 722–727 (2010).

    Article  CAS  Google Scholar 

  43. Alekseychik, P. et al. Surface energy exchange in pristine and managed boreal peatlands. Mires Peat 20, 1–26 (2018).

    Google Scholar 

  44. Zoltai, S. C. & Vitt, D. H. Canadian wetlands: environmental gradients and classification. Vegetatio 118, 131–137 (1995).

    Article  Google Scholar 

  45. Sulman, B. N. et al. CO2 fluxes at northern fens and bogs have opposite responses to inter-annual fluctuations in water table. Geophys. Res. Lett. 37, L19702 (2010).

    Article  CAS  Google Scholar 

  46. Girardin, M. P. et al. Negative impacts of high temperatures on growth of black spruce forests intensify with the anticipated climate warming. Glob. Change Biol. 22, 627–643 (2016).

    Article  Google Scholar 

  47. Clenciala, E., Kucera, J., Ryan, M. G. & Lindroth, A. Water flux in boreal forest during two hydrologically contrasting years; species specific regulation of canopy conductance and transpiration. Ann. Sci. For. 55, 47–61 (1998).

    Article  Google Scholar 

  48. Helbig, M., Humphreys, E. R. & Todd, A. Contrasting temperature sensitivity of CO2 exchange in peatlands of the Hudson Bay Lowlands, Canada. J. Geophys. Res. Biogeosci. 124, 2126–2143 (2019).

    Article  CAS  Google Scholar 

  49. Fenner, N. & Freeman, C. Drought-induced carbon loss in peatlands. Nat. Geosci. 4, 895–900 (2011).

    Article  CAS  Google Scholar 

  50. Charman, D. J. Summer water deficit variability controls on peatland water-table changes: implications for Holocene palaeoclimate reconstructions. The Holocene 17, 217–227 (2007).

    Article  Google Scholar 

  51. Rydin, H. Effect of water level on desiccation of Sphagnum in relation to surrounding Sphagna. Oikos 45, 374–379 (1985).

    Article  Google Scholar 

  52. Waddington, J. M. et al. Hydrological feedbacks in northern peatlands. Ecohydrol. 8, 113–127 (2014).

    Article  Google Scholar 

  53. Waddington, J. M., Kellner, E., Strack, M. & Price, J. S. Differential peat deformation, compressibility, and water storage between peatland microforms: Implications for ecosystem function and development. Water Resour. Res. 46, W07538 (2010).

  54. Nijp, J. J. et al. Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections. Sci. Total Environ. 580, 1389–1400 (2017).

    Article  CAS  Google Scholar 

  55. Heijmans, M. M. P. D., van der Knaap, Y. A. M., Holmgren, M. & Limpens, J. Persistent versus transient tree encroachment of temperate peat bogs: effects of climate warming and drought events. Glob. Change Biol. 19, 2240–2250 (2013).

    Article  Google Scholar 

  56. Sulman, B. N., Desai, A. R. & Mladenoff, D. J. Modeling soil and biomass carbon responses to declining water table in a wetland-rich landscape. Ecosystems 16, 491–507 (2013).

    Article  CAS  Google Scholar 

  57. Carpino, O. A., Berg, A. A., Quinton, W. L. & Adams, J. R. Climate change and permafrost thaw-induced boreal forest loss in northwestern Canada. Environ. Res. Lett. 13, 084018 (2018).

    Article  Google Scholar 

  58. Buermann, W., Bikash, P. R., Jung, M., Burn, D. H. & Reichstein, M. Earlier springs decrease peak summer productivity in North American boreal forests. Environ. Res. Lett. 8, 024027 (2013).

    Article  Google Scholar 

  59. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51, 933–938 (2001).

    Google Scholar 

  60. Hollinger, D. Y. et al. Seasonal patterns and environmental control of carbon dioxide and water vapour exchange in an ecotonal boreal forest. Glob. Change Biol. 5, 891–902 (1999).

    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  CAS  Google Scholar 

  62. 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 

  63. Humphreys, E. R. et al. Summer carbon dioxide and water vapor fluxes across a range of northern peatlands. J. Geophys. Res. Biogeosciences 111, G04011 (2006).

    Article  CAS  Google Scholar 

  64. Verma, S. B. Aerodynamic Resistances to Transfers of Heat, Mass and Momentum (eds Black, T. A. et al.) Vol. 177, 13–20 (International Association of Hydrological Sciences, 1989); http://hydrologie.org/redbooks/a177/iahs_177_0013.pdf

  65. Medlyn, B. E. et al. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Glob. Change Biol. 17, 2134–2144 (2011).

    Article  Google Scholar 

  66. Moore, T. R., Bubier, J. L., Frolking, S. E., Lafleur, P. M. & Roulet, N. T. Plant biomass and production and CO2 exchange in an ombrotrophic bog. J. Ecol. 90, 25–36 (2002).

    Article  Google Scholar 

  67. Kelliher, F. M., Leuning, R., Raupach, M. R. & Schulze, E.-D. Maximum conductances for evaporation from global vegetation types. Agric. For. Meteorol. 73, 1–16 (1995).

    Article  Google Scholar 

  68. Myneni, R., Knyazikhin, Y. & Park, T. MOD15A2H v006: MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid (NASA, 2015); https://doi.org/doi:10.5067/MODIS/MOD15A2H.006

  69. Mao, J. & Yan, B. Global Monthly Mean Leaf Area Index Climatology, 1981–2015 (ORNL DAAC, 2019); https://doi.org/10.3334/ORNLDAAC/1653

  70. Ficklin, D. L. & Novick, K. A. Historic and projected changes in vapor pressure deficit suggest a continental-scale drying of the United States atmosphere. J. Geophys. Res. Atmospheres 122, 2061–2079 (2017).

    Article  Google Scholar 

  71. Jung, M. et al. The FLUXCOM ensemble of global land-atmosphere energy fluxes. Sci. Data 6, 74 (2019).

    Article  Google Scholar 

  72. Helbig, M. Analysis of Boreal Peatland and Forest Evapotranspiration (Zenodo, 2020); https://doi.org/10.5281/zenodo.3653056

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Acknowledgements

The research published in this paper is part of the project titled Boreal Water Futures, which is funded by the Global Water Futures programme of the Canada First Research Excellence Fund; additional information is available at www.globalwaterfutures.ca. We thank all the eddy covariance flux tower teams for sharing their data and we are grateful to the ESM groups for providing their model output through CMIP5. We thank the World Climate Research Programme’s Working Group on Coupled Modelling for leading the CMIP. We acknowledge the research group that made the peatland map freely available and we thank E. Chan (ECCC) for processing the shapefile PEATMAP to a raster map. We are grateful to E. Sahlée and A. Rutgersson for providing lake eddy covariance data to an earlier version of the manuscript, T. Zivkovic and S. Davidson for insightful feedback, and M. Khomik, A. Green, E. Kessel, G. Drewitt, P. Kolari and M. Provenzale for helping with data preparation. I.M. acknowledges funding from ICOS-FINLAND (grant no. 281255), the Finnish Center of Excellence (grant no. 307331) and the EU Horizon 2020 RINGO project (grant no. 730944). A.P. acknowledges funding through the research project no. 18–05–60203-Arktika (RFBR and Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science) and support for flux tower sites RU-ZOP and RU-ZOB through the Max Planck Society. A.D. and J.T. acknowledge funding from US National Science foundation (grant no. DEB-1440297) and a DOE Ameriflux Network Management Project award to the ChEAS core site cluster. T.A.B., A.G.B. and R.J. acknowledge support received through grants from the Fluxnet Canada ResearchNetwork (2002–2007; NSERC, CFCAS and BIOCAP) and the Canadian Carbon Program (2008–2012; CFCAS) and by an NSERC (Climate Change and Atmospheric Research) grant to the Changing Cold Regions Network (CCRN; 2012–2016) and an NSERC Discovery Grant. H. I. and M. U. acknowledge support by the Arctic Challenge for Sustainability (ArCS) project. J.K. and A.V. acknowledge funding from RFBR project no. 19–04–01234-a. B.A. acknowledges funding through NASA, NSERC, BIOCAP Canada, the Canadian Foundation for Climate and Atmospheric Sciences and the Canadian Foundation for Innovation for flux measurements at CA-MAN and through the Canadian Forest Service, the Natural Sciences and Engineering Research Council of Canada (NSERC), the FLUXNET-Canada Network (NSERC, the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS) and BIOCAP Canada), the Canadian Carbon Program (CFCAS), Parks Canada, the Program of Energy Research and Development (PERD), and Action Plan 2000 for flux measurements at CA-SF1, CA-SF2 and CA-SF3. M.B.N, M.O.L, M.P. and J.C. gratefully acknowledge funding from the Swedish research infrastructures SITES and ICOS Sweden and research grants from Kempe Foundations, (grant no. SMK-1743); VR (grant no. 2018–03966) and Formas, (grant no. 2016–01289) and M.P. gratefully acknowledges funding from Knut and Alice Wallenberg Foundation (grant no. 2015.0047). M.W. and I.F. acknowledge funding by the German Research Foundation (grant no. Wi 2680/2–1) and the European Union (grant no. 36993). B.R. and L.K. acknowledge support by the Cluster of Excellence ‘CliSAP’ (EXC177) of the University of Hamburg, funded by the German Research Foundation. O.S. acknowledges funding by the Canada Research Chairs, Canada Foundation for Innovation Leaders Opportunity Fund, and Natural Sciences and Engineering Research Council Discovery Grant Programs. H.I. acknowledges JAMSTEC and IARC/UAF collaboration study (JICS) and Arctic Challenge for Sustainability Project (ArCS).

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Authors and Affiliations

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Contributions

M.H. and J.M.W. designed the study. M.H., J.M.W. and J.R.M. developed the methodology. J.M.W., P.A., B.A., M.A., A.G.B., T.A.B., P.D.B., S.K.C, J.Chen, J.Chi, A.R.D., A.D., E.E., T.F., L.B.F., I.F., A.G., S.H., M.H., E.R.H., H.Ikawa, H.Iwata, P.-E.I., R.J., J.K., M.K., L.K., A.Lindroth, T.O., M.O.L., A.Lohila, T.M., I.M., P.M., P.A.M., D.F.N., E.M.N., M.B.N., M.P., R.M.P., R.P., A.P., W.L.Q., N.T.R., D.E.R., B.R.K.R., O.S., I.B.S., P.T., E.-S.T., J.-P.T., J.T., M.U., A.V., M.W., S.W. and V.Z. contributed eddy covariance flux data. M.H. analysed the data and wrote the first draft. All authors contributed to data interpretation and commented on the manuscript at all stages.

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Correspondence to Manuel Helbig.

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Peer review information Nature Climate Change thanks Claire Treat and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Anomalies of growing season (May-September) mean daily maximum vapour pressure deficit (VPDGS) for the boreal biome (circles, relative to the mean of 1981–2010).

The solid line shows five-year running mean. VPDGS is derived from the University of East Anglia Climate Research Unit [CRU] TS v4.03 dataset (Methods) and boreal biome grid cells are identified based on ref. 59.

Source data

Extended Data Fig. 2

Relationship between observed half-hourly afternoon (15h-18h) evaporative fraction and vapour pressure deficit for forest and peatland sites during the growing season. Shaded areas show standard errors.

Source data

Extended Data Fig. 3

Probability density function (PDF, solid lines) of observed growing season (May- September) forest (n = 305 growing seasons) and peatland (n = 122 growing seasons) evapotranspiration. Dashed lines show median growing season evapotranspiration.

Source data

Supplementary information

Supplementary Information

Supplementary Data 1

List of eddy covariance flux tower sites used in this study, including metadata for each site.

Source data

Source Data Fig. 1

Projected changes in vapour pressure deficit in the boreal biome.

Source Data Fig. 2

Dryness index map and flux tower site locations.

Source Data Fig. 3

VPD-ET/gs response curve data.

Source Data Fig. 4

Map of current and projected ratios of peatland versus forest ET.

Source Data Extended Data Fig. 1

VPD anomaly data for the boreal biome.

Source Data Extended Data Fig. 2

VPD-evaporative fraction response curve data.

Source Data Extended Data Fig. 3

Growing season ET data for boreal peatlands and forests.

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Helbig, M., Waddington, J.M., Alekseychik, P. et al. Increasing contribution of peatlands to boreal evapotranspiration in a warming climate. Nat. Clim. Chang. 10, 555–560 (2020). https://doi.org/10.1038/s41558-020-0763-7

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