Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Widespread inhibition of daytime ecosystem respiration

Abstract

The global land surface absorbs about a third of anthropogenic emissions each year, due to the difference between two key processes: ecosystem photosynthesis and respiration. Despite the importance of these two processes, it is not possible to measure either at the ecosystem scale during the daytime. Eddy-covariance measurements are widely used as the closest ‘quasi-direct’ ecosystem-scale observation from which to estimate ecosystem photosynthesis and respiration. Recent research, however, suggests that current estimates may be biased by up to 25%, due to a previously unaccounted for process: the inhibition of leaf respiration in the light. Yet the extent of inhibition remains debated, and implications for estimates of ecosystem-scale respiration and photosynthesis remain unquantified. Here, we quantify an apparent inhibition of daytime ecosystem respiration across the global FLUXNET eddy-covariance network and identify a pervasive influence that varies by season and ecosystem type. We develop partitioning methods that can detect an apparent ecosystem-scale inhibition of daytime respiration and find that diurnal patterns of ecosystem respiration might be markedly different than previously thought. The results call for the re-evaluation of global terrestrial carbon cycle models and also suggest that current global estimates of photosynthesis and respiration may be biased, some on the order of magnitude of anthropogenic fossil fuel emissions.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Code availability

Code used in the analysis presented in this paper is available online in two repositories. The first contains the modified REddyProc partitioning algorithms and can be accessed at https://github.com/trevorkeenan/REddyProc. The second contains the post-partitioning data processing pipeline code and can be accessed at https://github.com/trevorkeenan/inhibitionPaperCode.

Data availability

This work used openly available FLUXNET 2015 v3 Tier 1 eddy-covariance data acquired and shared by the FLUXNET community. All related data is publicly available for download at http://fluxnet.fluxdata.org.

References

  1. 1.

    Baldocchi, D. TURNER REVIEW No. 15. ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Aust. J. Bot. 56, 1 (2008).

    CAS  Google Scholar 

  2. 2.

    Pastorello, G. et al. A new data set to keep a sharper eye on land-air exchanges. Eos (Washington, DC) 1–6 (17 April 2017); https://doi.org/10.1029/2017EO071597

  3. 3.

    Wohlfahrt, G. & Gu, L. The many meanings of gross photosynthesis and their implication for photosynthesis research from leaf to globe. Plant Cell Environ. 38, 2500–2507 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Granier, A. et al. The carbon balance of a young Beech forest. Funct. Ecol. 14, 312–325 (2000).

    Google Scholar 

  5. 5.

    Barford, C. C. et al. Factors controlling long- and short-term sequestration of atmospheric CO2 in a mid-latitude forest. Science (80-.). 294, 1688–1691 (2001).

    CAS  PubMed  Google Scholar 

  6. 6.

    Janssens, I. A. et al. Productivity overshadows temperature in determining soil and ecosystem respiration across European forests. Glob. Chang. Biol. 7, 269–278 (2001).

    Google Scholar 

  7. 7.

    Suyker, A. E. & Verma, S. B. Year-round observations of the net ecosystem exchange of carbon dioxide in a native tallgrass prairie. Glob. Change Biol. 7, 279–289 (2001).

    Google Scholar 

  8. 8.

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

    Google Scholar 

  9. 9.

    Gilmanov, T. G. et al. Gross primary production and light response parameters of four Southern Plains ecosystems estimated using long-term CO2 -flux tower measurements. Global Biogeochem. Cycles 17, 1071 (2003).

    Google Scholar 

  10. 10.

    Yi, C. et al. A nonparametric method for separating photosynthesis and respiration components in CO2 flux measurements. Geophys. Res. Lett. 31, 1–5 (2004).

    Google Scholar 

  11. 11.

    Wohlfahrt, G., Bahn, M., Haslwanter, A., Newesely, C. & Cernusca, A. Estimation of daytime ecosystem respiration to determine gross primary production of a mountain meadow. Agric. For. Meteorol. 130, 13–25 (2005).

    Google Scholar 

  12. 12.

    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).

    Google Scholar 

  13. 13.

    Hagen, S. C. et al. Statistical uncertainty of eddy flux-based estimates of gross ecosystem carbon exchange at Howland Forest, Maine. J. Geophys. Res. Atmos. 111, 1–12 (2006).

    Google Scholar 

  14. 14.

    Stoy, P. C. et al. An evaluation of models for partitioning eddy covariance-measured net ecosystem exchange into photosynthesis and respiration. Agric. For. Meteorol. 141, 2–18 (2006).

    Google Scholar 

  15. 15.

    Gilmanov, T. G. et al. Partitioning European grassland net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using light response function analysis. Agric. Ecosyst. Environ. 121, 93–120 (2007).

    CAS  Google Scholar 

  16. 16.

    Desai, A. R. et al. Cross-site evaluation of eddy covariance GPP and RE decomposition techniques. Agric. For. Meteorol. 148, 821–838 (2008).

    Google Scholar 

  17. 17.

    van Gorsel, E. et al. Application of an alternative method to derive reliable estimates of night-time respiration from eddy covariance measurements in moderately complex topography. Agric. For. Meteorol. 148, 1174–1180 (2008).

    Google Scholar 

  18. 18.

    Scanlon, T. M. & Sahu, P. On the correlation structure of water vapor and carbon dioxide in the atmospheric surface layer: a basis for flux partitioning. Water Resour. Res. 44, 1–15 (2008).

    Google Scholar 

  19. 19.

    Lasslop, G. et al. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation. Glob. Change Biol. 16, 187–208 (2010).

    Google Scholar 

  20. 20.

    Scanlon, T. M. & Kustas, W. P. Partitioning carbon dioxide and water vapor fluxes using correlation analysis. Agric. For. Meteorol. 150, 89–99 (2010).

    Google Scholar 

  21. 21.

    Sulman, B. N., Roman, D. T., Scanlon, T. M., Wang, L. & Novick, K. A. Comparing methods for partitioning a decade of carbon dioxide and water vapor fluxes in a temperate forest. Agric. For. Meteorol. 226–227, 229–245 (2016).

    Google Scholar 

  22. 22.

    Bruhn, D. et al. Estimating daytime ecosystem respiration from eddy-flux data. Biosystems 103, 309–313 (2011).

    CAS  PubMed  Google Scholar 

  23. 23.

    Beer, C. et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834–838 (2010).

    CAS  Google Scholar 

  24. 24.

    Jung, M. et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res. 116, 1–16 (2011).

    Google Scholar 

  25. 25.

    Jung, M. et al. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541, 516–520 (2017).

    CAS  PubMed  Google Scholar 

  26. 26.

    Williams, M. et al. Improving land surface models with FLUXNET data. Biogeosciences 6, 1341–1359 (2009).

    CAS  Google Scholar 

  27. 27.

    Running, S. W. et al. A global terrestrial monitoring network integrating tower fluxes, flask sampling, ecosystem modeling and EOS satellite data. System 127, 108–127 (1999).

    Google Scholar 

  28. 28.

    Kok, B. On the interrelation of respiration and photosynthesis in green plants. Biochim. Biophys. Acta 3, 625–631 (1949).

    CAS  Google Scholar 

  29. 29.

    Wehr, R. et al. Seasonality of temperate forest photosynthesis and daytime respiration. Nature 534, 680–683 (2016).

    CAS  PubMed  Google Scholar 

  30. 30.

    Atkin, O. K. et al. Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. New Phytol. 206, 614–636 (2015).

    CAS  PubMed  Google Scholar 

  31. 31.

    Amthor, J. The McCree–de Wit–Penning de Vries–Thornley respiration paradigms: 30 years later. Ann. Bot. 86, 1–20 (2000).

    CAS  Google Scholar 

  32. 32.

    Tcherkez, G. et al. Leaf day respiration: low CO2 flux but high significance for metabolism and carbon balance. New Phytol. 216, 986–1001 (2017).

    CAS  PubMed  Google Scholar 

  33. 33.

    Farquhar, G. D. & Busch, F. A. Changes in the chloroplastic CO2 concentration explain much of the observed Kok effect: a model. New Phytol. 214, 570–584 (2017).

    CAS  PubMed  Google Scholar 

  34. 34.

    Buckley, T. N., Vice, H. & Adams, M. A. The Kok effect in Vicia faba cannot be explained solely by changes in chloroplastic CO2concentration. New Phytol. 216, 1064–1071 (2017).

    CAS  PubMed  Google Scholar 

  35. 35.

    Amthor, J. S. & Baldocchi, D. D. Terrestrial higher plant respiration and net primary production. in Terrestrial Global Productivity 33–59 (Academic Press, 2001).

  36. 36.

    Morgenstern, K. et al. Sensitivity and uncertainty of the carbon balance of a Pacific Northwest Douglas-fir forest during an El Niño/La Niña cycle. Agric. For. Meteorol. 123, 201–219 (2004).

    Google Scholar 

  37. 37.

    Chambers, J. Q. et al. Respiration from a tropical forest ecosystem: partitioning of sources and low carbon use efficiency. Ecol. Appl. 14, S72–S88 (2004).

    Google Scholar 

  38. 38.

    Heskel, M. A., Atkin, O. K., Turnbull, M. H. & Griffin, K. L. Bringing the Kok effect to light: a review on the integration of daytime respiration and net ecosystem exchange. Ecosphere 4, 1–14 (2013).

    Google Scholar 

  39. 39.

    Baldocchi, D. D. & Harley, P. C. Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest. I. Leaf model parametrization. Plant Cell Environ. 18, 1157–1173 (1995).

    Google Scholar 

  40. 40.

    Gong, X. Y., Schäufele, R., Lehmeier, C. A., Tcherkez, G. & Schnyder, H. Atmospheric CO2 mole fraction affects stand-scale carbon use efficiency of sunflower by stimulating respiration in light. Plant Cell Environ. 40, 401–412 (2017).

    CAS  PubMed  Google Scholar 

  41. 41.

    Oikawa, P. Y. et al. Revisiting the partitioning of net ecosystem exchange of CO2 into photosynthesis and respiration with simultaneous flux measurements of 13CO2 and CO2, soil respiration and a biophysical model, CANVEG. Agric. For. Meteorol. 234–235, 149–163 (2017).

    Google Scholar 

  42. 42.

    Hollinger, D. Y. et al. Forest–atmosphere carbon dioxide exchange in eastern Siberia. Agric. For. Meteorol. 90, 291–306 (1998).

    Google Scholar 

  43. 43.

    MIGLIETTA, F. et al. Severe drought effects on ecosystem CO2 and H2O fluxes in three Mediterranean evergreen ecosystems: revision of current hypotheses? Glob. Change Biol. 8, 999–1017 (2002).

    Google Scholar 

  44. 44.

    Falge, E. et al. Seasonality of ecosystem respiration and gross primary production as derived from FLUXNET measurements. Agric. For. Meteorol. 113, 53–74 (2002).

    Google Scholar 

  45. 45.

    Law, B. E., Hall, R., Forestry, C. & State, O. Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agric. For. Meteorol. 113, 97–120 (2002).

    Google Scholar 

  46. 46.

    Rambal, S., Joffre, R., Ourcival, J. M., Cavender-Bares, J. & Rocheteau, A. The growth respiration component in eddy CO2 flux from a Quercus ilex mediterranean forest. Glob. Change Biol. 10, 1460–1469 (2004).

    Google Scholar 

  47. 47.

    Gilmanov, T. G., Johnson, D. A. & Saliendra, N. Z. Growing season CO2 fluxes in a sagebrush-steppe ecosystem in Idaho: Bowen ratio/energy balance measurements and modeling. Basic Appl. Ecol. 4, 167–183 (2003).

    Google Scholar 

  48. 48.

    Weerasinghe, L. K. et al. Canopy position affects the relationships between leaf respiration and associated traits in a tropical rainforest in Far North Queensland. Tree. Physiol. 34, 564–584 (2014).

    CAS  PubMed  Google Scholar 

  49. 49.

    Turnbull, M. H. et al. Light inhibition of foliar respiration in response to soil water availability and seasonal changes in temperature in Mediterranean holm oak (Quercus ilex) forest. Funct. Plant Biol. 44, 1178–1193 (2017).

    Google Scholar 

  50. 50.

    Giasson, M.-A. et al. Soil respiration in a northeastern US temperate forest: a 22-year synthesis. Ecosphere 4, art140 (2013).

    Google Scholar 

  51. 51.

    Falge, E., Graber, W., Siegwolf, R. & Tenhunen, J. D. A model of the gas exchange response ofPicea abies to habitat conditions. Trees 10, 277–287 (1996).

    Google Scholar 

  52. 52.

    Brooks, J. R., Hinckley, T. M., Ford, D. E. & Sprugel, D. G. Foliage dark respiration in Abies amabilis (Dougl.) Forbes: variation within the canopy. Tree Physiol. 9, 325–338 (1991).

    CAS  PubMed  Google Scholar 

  53. 53.

    Wohlfahrt, G. & Galvagno, M. Revisiting the choice of the driving temperature for eddy covariance CO2 flux partitioning. Agric. For. Meteorol. 237–238, 135–142 (2017).

    PubMed  PubMed Central  Google Scholar 

  54. 54.

    Lasslop, G. et al. On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning. Biogeosciences 9, 5243–5259 (2012).

    CAS  Google Scholar 

  55. 55.

    Landhäusser, S. M., Desrochers, A. & Lieffers, V. J. A comparison of growth and physiology in Picea glauca and Populus tremuloides at different soil temperatures. Sci. York 1929, 1922–1929 (2001).

    Google Scholar 

  56. 56.

    Migliavacca, M. et al. Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests. Glob. Change Biol. 21, 363–376 (2015).

    Google Scholar 

  57. 57.

    Law, B. E., Cescatti, A. & Baldocchi, D. D. Leaf area distribution and radiative transfer in open-canopy forests: implications for mass and energy exchange. Tree. Physiol. 21, 777–787 (2001).

    CAS  PubMed  Google Scholar 

  58. 58.

    Moyano, F. E., Kutsch, W. L. & Rebmann, C. Soil respiration fluxes in relation to photosynthetic activity in broad-leaf and needle-leaf forest stands. Agric. For. Meteorol. 148, 135–143 (2008).

    Google Scholar 

  59. 59.

    Migliavacca, M. et al. Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites. Glob. Change Biol. 17, 390–409 (2011).

    Google Scholar 

  60. 60.

    Goulden, M. L., Munger, J. W., Fan, S. M., Daube, B. C. & Wofsy, S. C. Measurements of carbon sequestration by long-term eddy covariance: methods and a critical evaluation of accuracy. Glob. Change Biol. 2, 169–182 (1996).

    Google Scholar 

  61. 61.

    Lavigne, M. B. et al. Comparing nocturnal eddy covariance measurements to estimates of ecosystem respiration made by scaling chamber measurements at six coniferous boreal sites. J. Geophys. Res. 102, 977–985 (1997).

    Google Scholar 

  62. 62.

    Law, B. E., Baldocchi, D. D. & Anthoni, P. M. Below-canopy and soil CO2 fluxes in a ponderosa pine forest. Agric. For. Meteorol. 94, 171–188 (1999).

    Google Scholar 

  63. 63.

    van Gorsel, E. et al. Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2. Agric. For. Meteorol. 149, 1919–1930 (2009).

    Google Scholar 

  64. 64.

    Leuning, R., Zegelin, S. J., Jones, K., Keith, H. & Hughes, D. Measurement of horizontal and vertical advection of CO2 within a forest canopy. Agric. For. Meteorol. 148, 1777–1797 (2008).

    Google Scholar 

  65. 65.

    De Araújo, A. C. et al. Nocturnal accumulation of CO2 underneath a tropical forest canopy along a topographical gradient. Ecol. Appl. 18, 1406–1419 (2008).

    PubMed  Google Scholar 

  66. 66.

    Atkin, O. K., Evans, J. R., Ball, M. C., Lambers, H. & Pons, T. L. Leaf respiration of snow gum in the light and dark: interactions between temperature and irradiance. Plant Physiol. 122, 915–924 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Ayub, G., Smith, R. A., Tissue, D. T. & Atkin, O. K. Impacts of drought on leaf respiration in darkness and light in Eucalyptus saligna exposed to industrial-age atmospheric CO2 and growth temperature. New Phytol. 190, 1003–1018 (2011).

    PubMed  Google Scholar 

  68. 68.

    Mclaughlin, B. C., Xu, C. Y., Rastetter, E. B. & Griffin, K. L. Predicting ecosystem carbon balance in a warming Arctic: the importance of long-term thermal acclimation potential and inhibitory effects of light on respiration. Glob. Change Biol. 20, 1901–1912 (2014).

    Google Scholar 

  69. 69.

    Atkin, O. K., Scheurwater, I. & Pons, T. High thermal acclimation potential of both photosynthesis and respiration in two lowland Plantago species in contrast to an alpine congeneric. Glob. Change Biol. 12, 500–515 (2006).

    Google Scholar 

  70. 70.

    Crous, K. Y. et al. Light inhibition of leaf respiration in field-grown Eucalyptus saligna in whole-tree chambers under elevated atmospheric CO2 and summer drought. Plant Cell Environ. 35, 966–981 (2012).

    CAS  PubMed  Google Scholar 

  71. 71.

    Zaragoza-Castells, J., Sánchez-Gómez, D., Valladares, F., Hurry, V. & Atkin, O. K. Does growth irradiance affect temperature dependence and thermal acclimation of leaf respiration? Insights from a Mediterranean tree with long-lived leaves. Plant Cell Environ. 30, 820–833 (2007).

    CAS  PubMed  Google Scholar 

  72. 72.

    Heskel, M. A. et al. Thermal acclimation of shoot respiration in an Arctic woody plant species subjected to 22 years of warming and altered nutrient supply. Glob. Change Biol. 20, 2618–2630 (2014).

    Google Scholar 

  73. 73.

    Way, D. A., Holly, C., Bruhn, D., Ball, M. C. & Atkin, O. K. Diurnal and seasonal variation in light and dark respiration in field-grown Eucalyptus pauciflora. Tree. Physiol. 35, 840–849 (2015).

    CAS  PubMed  Google Scholar 

  74. 74.

    Heskel, M. A., Tang, J. & Way, D. Environmental controls on light inhibition of respiration and leaf and canopy daytime carbon exchange in a temperate deciduous forest. Tree Physiol. 38, 1886–1902 (2018).

    CAS  PubMed  Google Scholar 

  75. 75.

    Crous, K. Y., Wallin, G., Atkin, O. K., Uddling, J. & Ekenstam, A. A. Acclimation of light and dark respiration to experimental and seasonal warming are mediated by changes in leaf nitrogen in Eucalyptus globulus. Tree. Physiol. 37, 1069–1083 (2017).

    CAS  PubMed  Google Scholar 

  76. 76.

    Xu, L. & Baldocchi, D. D. Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California. Agric. For. Meteorol. 123, 79–96 (2004).

    Google Scholar 

  77. 77.

    Lasslop, G., Reichstein, M., Detto, M., Richardson, A. D. & Baldocchi, D. D. Comment on Vickers et al.: self-correlation between assimilation and respiration resulting from flux partitioning of eddy-covariance CO2 fluxes. Agric. For. Meteorol. 150, 312–314 (2010).

    Google Scholar 

  78. 78.

    Efron, B. & Hastie, T. Computer Age Statistical Inference (Cambridge Univ. Press, Cambridge, 2016).

  79. 79.

    Moffat, A. M. A new methodology to interpret high resolution measurements of net carbon fluxes between terrestrial ecosystems and the atmosphere. PhD Thesis, Friedrich-Schiller-Universität (2012).

  80. 80.

    Huntingford, C. et al. Implications of improved representations of plant respiration in a changing climate. Nat. Commun. 8, 1602 (2017).

    PubMed  PubMed Central  Google Scholar 

  81. 81.

    Loreto, F., Velikova, V. & Di Marco, G. Respiration in the light measured by 12CO2 emission in 13CO2 atmosphere in maize leaves. Aust. J. Plant. Physiol. 28, 1103–1108 (2001).

    Google Scholar 

  82. 82.

    Tcherkez, G. et al. Tracking the origins of the Kok effect, 70 years after its discovery. New Phytol. 214, 506–510 (2017).

    PubMed  Google Scholar 

  83. 83.

    Lloyd, J. & Taylor, J. A. On the temperature dependence of soil respiration. Funct. Ecol. 8, 315–323 (1994).

    Google Scholar 

  84. 84.

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

    CAS  Google Scholar 

  85. 85.

    Peisker, M. & Apel, H. Inhibition by light of CO2 evolution from dark respiration: comparison of two gas exchange methods. Photosynth. Res. 70, 291–298 (2001).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

T.F.K. was supported by the NASA Terrestrial Ecology Program IDS Award no. NNH17AE86I. D.P. thanks the RINGO project funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 730944. We also acknowledge support from the Director, Office of Science, Office of Biological and Environmental Research of the US Department of Energy under the AmeriFlux Management Project. This work used eddy-covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia and USCCC. The ERA-Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy-covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project and Fluxdata project of FLUXNET, with the support of CDIAC and the ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux and AsiaFlux offices. We especially acknowledge all the principal investigators who contributed data to the FLUXNET Tier 1 dataset.

Author information

Affiliations

Authors

Contributions

T.F.K. designed and performed the analysis and led the drafting of the manuscript. M.M. and T.W. developed the original REddyProc software and advised on modifications. All authors provided feedback on the analysis and the manuscript.

Corresponding author

Correspondence to Trevor F. Keenan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figures 1–8 and Supplementary Table 1

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Keenan, T.F., Migliavacca, M., Papale, D. et al. Widespread inhibition of daytime ecosystem respiration. Nat Ecol Evol 3, 407–415 (2019). https://doi.org/10.1038/s41559-019-0809-2

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing