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Increasing impacts of extreme droughts on vegetation productivity under climate change

Nature Climate Change volume 9, pages 948–953 (2019)Cite this article

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Abstract

Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions.

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Fig. 1: Temporal changes in annual drought frequency relative to the historical period of 1850–1999.
Fig. 2: Spatial distribution of drought frequency during 2075–2099 relative to the historical period of 1850–1999.
Fig. 3: Temporal changes in GPP anomalies associated with droughts relative to the historical period of 1850–1999.
Fig. 4: Spatial distribution of GPP anomalies associated with droughts during 2075–2099 relative to the historical period of 1850–1999.

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Data availability

The ESM output data that support the findings of this study are available from the CMIP5 site (https://esgf-node.llnl.gov/projects/cmip5/).

Code availability

The processing R codes are available from the corresponding author upon request.

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Acknowledgements

This work was funded by the Next Generation Ecosystem Experiment–Tropics project and the Survival/Mortality project sponsored by the DOE Office of Science, Office of Biological and Environmental Research, the Laboratory Directed Research and Development program of the Los Alamos National Laboratory and the Univerisity of California’s Laboratory Fees Research Program (grant no. LFR-18-542511). In addition, B.O.C acknowledges support from Laboratory Directed Research and Development Program Project 8872 of the Oak Ridge National Laboratory and E.W. acknowledges support from the NASA Modeling, Analysis, and Prediction Program (grant no. NNH16ZDA001N-MAP). This submission is under public release with the approved LA-UR-14-23309. We thank D. Lawrence and C. Koven for their helpful feedback on the initial manuscript. We thank N. Kiang from NASA Goddard Institute for Space Studies for sharing the PFT distribution map in GISS models, P. Milly from NOAA’s Geophysical Fluid Dynamics Laboratory for sharing the PFT distribution in GFDL models and J. Tjiputra from University of Bergen for sharing the PFT distributions in NorESM1 models for this study. We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the climate modelling groups (Supplementary Table 1) for producing and making available their model output. For CMIP5, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Author information

Authors and Affiliations

  1. Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    Chonggang Xu, Liang Wei, Sanna Sevanto & Richard S. Middleton

  2. Earth Systems Analysis and Modeling Division, Pacific Northwest National Laboratory, Richland, WA, USA

    Nate G. McDowell

  3. Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA

    Rosie A. Fisher

  4. Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique, Toulouse, France

    Rosie A. Fisher

  5. Key Laboratory of Western China’s Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China

    Liang Wei

  6. Department of Biology and School of Earth, Environmental, and Marine Sciences, The University of Texas Rio Grande Valley, Edinburg, TX, USA

    Bradley O. Christoffersen

  7. Center for Climate Systems Research, Columbia University and NASA Goddard Institute for Space Studies, New York, NY, USA

    Ensheng Weng

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  1. Chonggang Xu
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Contributions

All authors contributed to the manuscript writing. C.X. and N.G.M. initially designed the experiment. C.X. implemented the analysis. L.W. helped with data exploration for evaluating the results; R.A.F., S.S., B.O.C. and R.S.M. provided suggestions for improvement of the experimental design and analysis. E.W. provided support on water limitation functions and PFT mapping on GFDL and NOAA models.

Corresponding author

Correspondence to Chonggang Xu.

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Competing interests

The authors declare no competing interests.

Additional information

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

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

Extended data

Extended Data Fig. 1 Quantification of drought impacts on GPP.

The droughts were defined based on the cumulative probability distribution of plant accessible soil water (PASW) for a specific month during the historical period of 1850–1999 (a) and the drought impacts on GPP were estimated using smoothing splines (b). The month of May was used in this figure for demonstration purposes. See Methods for details.

Extended Data Fig. 2 Temporal changes in proportions of total number of drought events contributed by different types of droughts.

The p-values were calculated to check if there is a significant difference between future period of 2075–2099 and historical period of 1850–1999 using the bootstrap sampling approach laid out in Supplementary Note 5.2. The grey horizontal dotted line shows the mean value during 2075–2099.

Extended Data Fig. 3 Temporal changes of deviations in monthly relative humidity [%] from the mean for drought months.

The grey horizontal dotted line shows the mean value during 2075–2099. Negative values indicate drought-months have lower humidity.

Extended Data Fig. 4 Temporal changes of deviation in monthly mean precipitation (mm) from the mean for drought months.

The grey horizontal dotted line shows the mean value during 2075–2099. Negative values indicate drought-months have lower precipitation.

Extended Data Fig. 5 Temporal changes of deviations in monthly mean temperature (oC) from the mean for drought months.

The grey horizontal dotted line shows the mean value during 2075–2099. Positive values indicate drought-months have higher temperature.

Extended Data Fig. 6 Temporal changes of deviation in monthly mean radiation (w/m2) from the mean for drought months.

The grey horizontal dotted line shows the mean value during 2075–2099. Positive values indicate drought-months have higher radiations.

Extended Data Fig. 7 Temporal changes in ratio of monthly carbon release (kg carbon/m2 ground/month) from fire to the mean for drought months.

Values > 1 indicate that the mean carbon release was larger in drought months compared to the mean as estimated by the spline approach. The grey horizontal dotted line shows the mean value during 2075–2099.

Extended Data Fig. 8 Temporal changes of reduction in global GPP (Pg C/year) associated with all droughts relative to the historical period of 1850-1999.

The relative reductions were calculated on a model-specific basis, dividing GPP reduction (kg C/m2/year) over a specific period by that over the historical period. The grey horizontal dotted line shows the mean value during 2075–2099. The p-values were calculated to check if there is a significant difference between future period of 2075–2099 and historical period of 1850–1999 using the bootstrap sampling approach laid out in Supplementary Note 5.1.

Extended Data Fig. 9 Temporal changes in drought severity (GPP reduction per drought event) relative to the historical period of 1850–1999.

The relative severities were calculated on a model-specific basis, dividing drought severity (kg C/m2/event) over a specific period by that over the historical period. Values of > 1 indicate stronger impact of individual drought events on GPP compared to the historical period; while values < 1 indicates weaker impact of individual drought events. The grey horizontal dotted line shows the mean value during 2075–2099. The p-values were calculated to check if there is a significant difference between future period of 2075–2099 and historical period of 1850–1999 using the approach laid out in Supplementary Note 5.1.

Extended Data Fig. 10 Temporal changes in proportions of total drought-associated GPP reductions contributed by different droughts.

The p-values were calculated to check if there is a significant difference between future period of 2075–2099 and historical period of 1850–1999 using the bootstrap sampling approach laid out in Supplementary Note 5.2. The grey horizontal dotted line shows the mean value during 2075–2099.

Supplementary information

Supplementary information

Supplementary Notes 1–5, Table 1 and Figs. 1–12.

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Xu, C., McDowell, N.G., Fisher, R.A. et al. Increasing impacts of extreme droughts on vegetation productivity under climate change. Nat. Clim. Chang. 9, 948–953 (2019). https://doi.org/10.1038/s41558-019-0630-6

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