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Spatiotemporal inequality in land water availability amplified by global tree restoration

Nature Water volume 2, pages 863–874 (2024)Cite this article

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Abstract

Afforestation can influence evapotranspiration (E) and precipitation (P), thereby altering water availability (known as P − E) on land. However, such effects on P − E have rarely been examined in the context of seasonal and spatial variations in background P − E conditions. Here we show the impacts of global tree restoration on P − E under spatiotemporally varying P − E conditions. Afforestation amplifies seasonal contrasts in P − E, resulting in higher P − E in the high P − E season and/or lower P − E in the low P − E season, over approximately two-thirds of the land area. Afforestation also amplifies spatial contrasts in P − E, leading to higher P − E in the high P − E regions but lower P − E in the low P − E regions. This study underscores the importance of considering background P − E conditions when evaluating the hydrological effects of afforestation, with important implications for both forestry and water management.

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Fig. 1: Schematic diagram of the impacts of afforestation on P − E.
Fig. 2: Global tree restoration potential and its hydrological effects.
Fig. 3: Seasonal contrasts in the response of P − E to afforestation.
Fig. 4: Spatial contrasts in the hydrological effects of afforestation.
Fig. 5: Changes in the P − E contrast between afforested pixels and their downwind footprints (δ(P − E)).
Fig. 6: Impacts of afforestation on country-level water availability (P − E).

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Data availability

The dataset mapping the existing tree cover is from Hansen et al.64 (https://doi.org/10.1126/science.1244693; available on request). The dataset mapping the global tree restoration potential is from Bastin et al.31 (https://doi.org/10.1126/science.aax0848; available on request). The dataset mapping the biophysical effects of vegetation cover changes is available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/ECOCLIM/Biophysical-effects-vgt-change/v2.0/. The moisture tracking dataset developed by Link et al.34 is available at https://doi.org/10.1594/PANGAEA.908705. The moisture tracking dataset developed by Tuinenburg et al.35 is available at https://doi.org/10.1594/PANGAEA.912710. The GLEAM dataset is available at https://www.gleam.eu/. The MSWEP dataset is available at https://www.gloh2o.org/mswep/. The Global Aridity Index and Potential Evapotranspiration Database is available at https://doi.org/10.6084/m9.figshare.7504448.v5 (ref. 37). The Gridded Population of the World version 4 dataset is available at https://sedac.ciesin.columbia.edu/data/collection/gpw-v4/sets/browse.

Code availability

The data used in this study were processed by the software MATLAB. The processing MATLAB codes are available at https://box.nju.edu.cn/f/f2ad9e2bc1e84741b41e/.

References

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

    Article  CAS  PubMed  Google Scholar 

  2. Canadell, J. G. & Raupach, M. R. Managing forests for climate change mitigation. Science 320, 1456–1457 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Lawrence, D. & Vandecar, K. Effects of tropical deforestation on climate and agriculture. Nat. Clim. Change 5, 27–36 (2015).

    Article  Google Scholar 

  5. Spracklen, D. V., Baker, J. C. A., Garcia-Carreras, L. & Marsham, J. H. The effects of tropical vegetation on rainfall. Annu. Rev. Env. Resour. 43, 193–218 (2018).

    Article  Google Scholar 

  6. te Wierik, S. A., Cammeraat, E. L. H., Gupta, J. & Artzy-Randrup, Y. A. Reviewing the impact of land use and land-use change on moisture recycling and precipitation patterns. Water Resour. Res. 57, e2020 WR029234 (2021).

    Article  Google Scholar 

  7. Branch, O. & Wulfmeyer, V. Deliberate enhancement of rainfall using desert plantations. Proc. Natl Acad. Sci. USA 116, 18841–18847 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Leite-Filho, A. T. et al. Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon. Nat. Commun. 12, 2591 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Smith, C., Baker, J. C. A. & Spracklen, D. V. Tropical deforestation causes large reductions in observed precipitation. Nature 615, 270–275 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Spracklen, D. V., Arnold, S. R. & Taylor, C. M. Observations of increased tropical rainfall preceded by air passage over forests. Nature 489, 282–285 (2012).

    Article  CAS  PubMed  Google Scholar 

  11. Staal, A. et al. Forest-rainfall cascades buffer against drought across the Amazon. Nat. Clim. Change 8, 539–543 (2018).

    Article  Google Scholar 

  12. Meier, R. et al. Empirical estimate of forestation-induced precipitation changes in Europe. Nat. Geosci. 14, 473–478 (2021).

    Article  CAS  Google Scholar 

  13. Wang-Erlandsson, L. et al. Remote land use impacts on river flows through atmospheric teleconnections. Hydrol. Earth Syst. Sci. 22, 4311–4328 (2018).

    Article  Google Scholar 

  14. Li, Y. et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv. 4, eaar4182 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Van Dijke, A. J. H. et al. Shifts in regional water availability due to global tree restoration. Nat. Geosci. 15, 363–368 (2022).

    Article  Google Scholar 

  16. Feng, X. M. et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Change 6, 1019–1022 (2016).

    Article  Google Scholar 

  17. Zhao, M. et al. Ecological restoration impact on total terrestrial water storage. Nat. Sustain. 4, 56–62 (2020).

    Article  Google Scholar 

  18. Ricciardi, L., D’Odorico, P., Galli, N., Chiarelli, D. D. & Rulli, M. C. Hydrological implications of large-scale afforestation in tropical biomes for climate change mitigation. Philos. T. R. Soc. B. 377, 20210319 (2022).

    Article  Google Scholar 

  19. Greve, P. et al. Global assessment of trends in wetting and drying over land. Nat. Geosci. 7, 716–721 (2014).

    Article  CAS  Google Scholar 

  20. Padrón, R. S. et al. Observed changes in dry-season water availability attributed to human-induced climate change. Nat. Geosci. 13, 477–481 (2020).

    Article  Google Scholar 

  21. Zhang, Y. et al. Future global streamflow declines are probably more severe than previously estimated. Nat. Water 1, 261–271 (2023).

    Article  Google Scholar 

  22. Zeng, Z. Z. et al. Impact of earth greening on the terrestrial water cycle. J. Climate 31, 2633–2650 (2018).

    Article  Google Scholar 

  23. Teo, H. C. Large-scale reforestation can increase water yield and reduce drought risk for water-insecure regions in the Asia-Pacific. Global Change Biol. 28, 6385–6403 (2022).

    Article  CAS  Google Scholar 

  24. Cui, J. et al. Global water availability boosted by vegetation-driven changes in atmospheric moisture transport. Nat. Geosci. 15, 982–988 (2022).

    Article  CAS  Google Scholar 

  25. Staal, A. et al. Feedback between drought and deforestation in the Amazon. Environ. Res. Lett. 15, 044024 (2020).

    Article  Google Scholar 

  26. Tuinenburg, O. A., Bosmans, J. H. C. & Staal, A. The global potential of forest restoration for drought mitigation. Environ. Res. Lett. 17, 034045 (2022).

    Article  Google Scholar 

  27. Insua-Costa, D., Senande-Rivera, M., Llasat, M. C. & Miguez-Macho, G. The central role of forests in the 2021 European floods. Environ. Res. Lett. 17, 064053 (2022).

    Article  Google Scholar 

  28. Frank, D. et al. Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Glob. Change Biol. 21, 2861–2880 (2015).

    Article  Google Scholar 

  29. Yin, Y. et al. Cropland carbon uptake delayed and reduced by 2019 midwest floods. AGU Adv. 1, 1–15 (2020).

    Article  Google Scholar 

  30. Chen, J. Y., Qiu, B., Guo, W. D., Li, L. F. & Miao, X. Divergent response of crops and natural vegetation to the record-breaking extreme precipitation event in 2020 modulated by topography. Environ. Res. Lett. 18, 064047 (2023).

    Article  Google Scholar 

  31. Bastin, J. F. et al. The global tree restoration potential. Science 365, 76–79 (2019).

    Article  CAS  PubMed  Google Scholar 

  32. Duveiller, G., Hooker, J. & Cescatti, A. The mark of vegetation change on Earth’s surface energy balance. Nat. Commun. 9, 679 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Duveiller, G., Hooker, J. & Cescatti, A. A dataset mapping the potential biophysical effects of vegetation cover change. Sci. Data 5, 180014 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Link, A., van der Ent, R., Berger, M., Eisner, S. & Finkbeiner, M. The fate of land evaporation—a global dataset. Earth Syst. Sci. Data 12, 1897–1912 (2020).

    Article  Google Scholar 

  35. Tuinenburg, O. A., Theeuwen, J. J. E. & Staal, A. High-resolution global atmospheric moisture connections from evaporation to precipitation. Earth Syst. Sci. Data 12, 3177–3188 (2020).

    Article  Google Scholar 

  36. Breil, M., Davin, E. L. & Rechid, D. What determines the sign of the evapotranspiration response to afforestation in European summer. Biogeosciences 18, 1499–1510 (2021).

    Article  Google Scholar 

  37. Zomer, R. J., Xu, J. & Trabucco, A. Version 3 of the global aridity index and potential evapotranspiration database. Sci. Data 9, 409 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Ferguson, C. R. & Wood, E. F. Observed land‒atmosphere coupling from satellite remote sensing and reanalysis. J. Hydrometeorol. 12, 1221–1254 (2012).

    Article  Google Scholar 

  39. Wei, J. F., Dirmeyer, P. A., Wisser, D., Bosilovich, M. G. & Mocko, D. M. Where does the irrigation water go? An estimate of the contribution of irrigation to precipitation using MERRA. J. Hydrometeorol. 14, 275–289 (2013).

    Article  CAS  Google Scholar 

  40. Tawfik, A. B., Dirmeyer, P. A. & Santanello, J. A. The heated condensation framework. Part II: climatological behavior of convective initiation and land‒atmosphere coupling over the conterminous United States. J. Hydrometeorol. 16, 1946–1961 (2015).

    Article  Google Scholar 

  41. Peng, S. S. et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Windisch, M. G., Davin, E. L. & Seneviratne, S. I. Prioritizing forestation based on biogeochemical and local biogeophysical impacts. Nat. Clim. Change 11, 867–871 (2021).

    Article  CAS  Google Scholar 

  43. Alkama, R. et al. Vegetation-based climate mitigation in a warmer and greener world. Nat. Commun. 13, 606 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Fu, B. J. et al. Hydrogeomorphic ecosystem responses to natural and anthropogenic changes in the Loess Plateau of China. Annu. Rev. Earth Planet. Sc. 45, 223–243 (2017).

    Article  CAS  Google Scholar 

  45. Hasler, N., Werth, D. & Avissar, R. Effects of tropical deforestation on global hydroclimate: a multimodel ensemble analysis. J. Clim. 22, 1124–1141 (2009).

    Article  Google Scholar 

  46. Swann, A. L. S., Fung, I. Y. & Chiang, J. C. H. Mid-latitude afforestation shifts general circulation and tropical precipitation. Proc. Natl Acad. Sci. USA 109, 712–716 (2012).

    Article  CAS  PubMed  Google Scholar 

  47. Portmann, R. et al. Global forestation and deforestation affect remote climate via adjusted atmosphere and ocean circulation. Nat. Commun. 13, 5569 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Staal, A. et al. Targeted rainfall enhancement as an objective of forestation. Global Change Bio. 30, e17096 (2024).

    Article  CAS  Google Scholar 

  49. Pitman, A. J. et al. Uncertainties in climate responses to past land cover change: first results from the LUCID intercomparison study. Geophys. Res. Lett. 36, L14814 (2009).

    Article  Google Scholar 

  50. Boysen, L. R. et al. Global climate response to idealized deforestation in CMIP6 models. Biogeosciences 17, 5615–5638 (2020).

    Article  CAS  Google Scholar 

  51. Luo, X. et al. The biophysical impacts of deforestation on precipitation: results from the CMIP6 model intercomparison. J. Climate 35, 3293–3311 (2022).

    Article  Google Scholar 

  52. Khanna, J., Medvigy, D., Fueglistaler, S. & Walko, R. Regional dry-season climate changes due to three decades of Amazonian deforestation. Nat. Clim. Change 7, 200–204 (2017).

    Article  Google Scholar 

  53. Xu, R. et al. Contrasting impacts of forests on cloud cover based on satellite observations. Nat. Commun. 13, 670 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Li, W., Li, L., Ting, M. & Liu, Y. M. Intensification of Northern Hemisphere subtropical highs in a warming climate. Nat. Geosci. 5, 830–834 (2012).

    Article  CAS  Google Scholar 

  55. Voigt, A. & Shaw, T. Circulation response to warming shaped by radiative changes of clouds and water vapour. Nat. Geosci. 8, 102–106 (2015).

    Article  CAS  Google Scholar 

  56. Chemke, R. & Yuval, J. Human-induced weakening of the Northern Hemisphere tropical circulation. Nature 617, 529–532 (2023).

    Article  CAS  PubMed  Google Scholar 

  57. Pitman, A. J. et al. Importance of background climate in determining impact of land-cover change on regional climate. Nat. Clim. Change 1, 472–275 (2012).

    Article  Google Scholar 

  58. Kumar, S. et al. Land use/cover change impacts in CMIP5 climate simulations: a new methodology and 21st century challenges. J. Geophys. Res.-Atmos. 118, 6337–6353 (2013).

    Article  Google Scholar 

  59. Zhang, Z. J., Zhang, F. J., Wang, L. C., Lin, A. W. & Zhao, L. Biophysical climate impact of forests with different age classes in mid- and high-latitude North America. Forest Ecol. Manag. 494, 119327 (2021).

    Article  Google Scholar 

  60. Su, Y. X. et al. Asymmetric influence of forest cover gain and loss on land surface temperature. Nat. Clim. Change 13, 823–831 (2023).

    Article  Google Scholar 

  61. 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  PubMed  PubMed Central  Google Scholar 

  62. Yang, Y. T., Roderick, M. L., Zhang, S. L., McVicar, T. R. & Donohue, R. J. Hydrologic implications of vegetation response to elevated CO2 in climate projections. Nat. Clim. Change 9, 44–48 (2019).

    Article  Google Scholar 

  63. Mankin, J. S., Seager, R., Smerdon, J. E., Cook, B. I. & Williams, A. P. Mid-latitude freshwater availability reduced by projected vegetation responses to climate change. Nat. Geosci. 12, 983–988 (2019).

    Article  CAS  Google Scholar 

  64. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article  CAS  PubMed  Google Scholar 

  65. Veldman, J. W. et al. Comment on ‘The global tree restoration potential’. Science 366, eaay7976 (2019).

    Article  PubMed  Google Scholar 

  66. Beck, H. E. et al. MSWEP V2 global 3‑hourly 0.1° precipitation: methodology and quantitative assessment. B. Am. Meteorol. Soc. 100, 473–500 (2019).

    Article  Google Scholar 

  67. van der Ent, R. J. & Savenije, H. H. G. Oceanic sources of continental precipitation and the correlation with sea surface temperature. Water Resource Res. 49, 3993–4004 (2013).

    Article  Google Scholar 

  68. Kays, P. W. et al. Analysing precipitationsheds to understand the vulnerability of rainfall dependent regions. Biogeosciences 9, 733–746 (2012).

    Article  Google Scholar 

  69. Martens, B. et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017).

    Article  Google Scholar 

  70. Center for International Earth Science Information Network (CIESIN) - Columbia University. Gridded Population of the World, version 4 (GPWv4): Population Count, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC) https://doi.org/10.7927/H4JW8BX5 (2018).

Download references

Acknowledgements

This research is supported by the Natural Science Foundation of China (42375115 awarded to J.G. and 42105023 awarded to B.Z.). J.G. also acknowledges support from the Fundamental Research Funds for the Central Universities (2024300330) and the Jiangsu Collaborative Innovation Center of Climate Change.

Author information

Author notes

  1. These authors contributed equally: Beilei Zan, Jun Ge.

Authors and Affiliations

  1. Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing, China

    Beilei Zan, Qiaohong Sun & Jiangfeng Wei

  2. School of Emergency Management, Nanjing University of Information Science and Technology, Nanjing, China

    Beilei Zan

  3. Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China

    Jun Ge & Xing Luo

  4. Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, China

    Jun Ge

  5. ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

    Mengyuan Mu

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  1. Beilei Zan
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Contributions

J.G. and J.W. conceived and designed the overall study. B.Z. and J.G. performed the data analysis with help from M.M., Q.S., X.L. and J.W. in the interpretation of the results. B.Z. drafted the paper. J.G. and J.W. edited the paper. All the authors discussed and revised the paper.

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Correspondence to Jun Ge or Jiangfeng Wei.

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Extended data

Extended Data Fig. 1 The hydrological effects of afforestation.

a–c, Impacts of afforestation on annual evapotranspiration (E) (a), precipitation (P) (b) and water availability (P–E) (c). The pie chart insets show the proportion (%) of land area with a positive (green) or negative (yellow) response. The land area is calculated using a spatially weighted mean to account for the change in pixel size with latitude. d–f, Latitudinal and monthly variations in the responses of E (d), P (e) and P–E (f) to afforestation. The latitudinal value is averaged over land. The results are calculated based on the Duveiller et al.33 and Link et al.34 datasets.

Extended Data Fig. 2 Seasonal contrasts in the response of water availability (P–E) to afforestation.

a, Seasonal variations in the multi-year (2001–2018) mean P − E (yellow line) and the P − E response to afforestation (green line) at a selected location of 6° N, 72° W. b–d, Impacts of afforestation on the annual range of P − E ((P − E)range) (b), the wet season P–E ((P–E)wet) (c) and the dry season P–E ((P–E)dry) (d) are shown. The violet star in b denotes the selected location of 6° N, 72° W. The pie chart insets show the proportion (%) of land area with a positive (green) or negative (yellow) response. The land area is calculated using a spatially weighted mean to account for the change in pixel size with latitude. e, Combined impacts of afforestation on (P–E)wet and (P–E)dry, and the corresponding proportions (%) of land area are shown in the pie chart inset. The results are calculated based on the Duveiller et al.33 and Link et al.34 datasets.

Extended Data Fig. 3 Spatial contrasts in the hydrological effects of afforestation.

Responses of evapotranspiration (E) (a), precipitation (P) (b) and water availability (P–E) (c) to afforestation and the proportion (%) of land area with a negative P–E response to afforestation (d) binned as a function of P–E. The land pixels are sorted and divided into 20 bins at intervals of 5% according to their monthly or annual P–E. Hatching in panels a–c denotes that changes in E (a), P (b) or P–E (c) are statistically significant (P < 0.05) according to two-sided Student’s t test. For panel d, the land area is calculated using a spatially weighted mean to account for the change in pixel size with latitude. The first 12 columns denote monthly values, and the last column (labeled as Y) denotes annual values. The results are calculated based on the Duveiller et al.33 and Link et al.34 datasets.

Extended Data Fig. 4 Changes in the P–E contrast between afforested pixels and their downwind footprints (δ(P–E)).

a, b, Maps of δ(P–E) when afforested pixels are in the wet (a) and dry (b) seasons, respectively. The pie chart insets show the proportion (%) of land area with a positive (green) or negative (yellow) value of δ(P–E). The land area is calculated using a spatially weighted mean to account for the change in pixel size with latitude. c, d, The proportion (%) of downwind land area in the wet season when the upwind afforested pixel is in the wet (c) or dry (d) P–E season. e, f, The proportion (%) of downwind land area in the dry season when the upwind afforested pixel is in the wet (e) or dry (f) season. The results are calculated based on the Duveiller et al.33 and Link et al.34 datasets.

Extended Data Fig. 5 Impacts of afforestation on country-level water availability (P–E).

The insets show seasonal variations in the water gain (yellow line), water loss (green line) and water budget (black line) for 14 selected countries that are among the top 30 countries ranked by tree restoration area. The water gain is the amount of precipitation in a country resulting from afforestation outside the country. The top country where the water comes from is shown in the top left corner of the inserts, and the corresponding monthly water amounts are shown in green bars. The water loss is the amount of evapotranspiration resulting from afforestation in a country that eventually precipitates outside the country. The top country to which the water flows is shown in the bottom left corner of the inserts, and the corresponding monthly water amounts are shown in brown bars. The water budget is the difference between the water gain and loss and is roughly equivalent to the P–E change. The results are calculated based on the Duveiller et al.33 and Link et al.34 datasets. Note that the European Union is included here, although it is not a country.

Extended Data Fig. 6 Global map of the aridity index (AI).

The AI is defined as the ratio of precipitation to potential evapotranspiration.

Extended Data Fig. 7 Spatial contrasts in the hydrological effects of afforestation and tree cover changes.

Potential changes in evapotranspiration that would occur if all grasslands and/or croplands in a pixel were converted to trees (a) and tree cover changes (b) binned as a function of P–E. The land pixels are sorted and divided into 20 bins at intervals of 5% according to their monthly or annual P–E. In panel a, hatching denotes that potential changes in evapotranspiration are statistically significant (p < 0.05) according to two-sided Student’s t test. The first 12 columns denote monthly values, and the last column denotes annual values.

Extended Data Table 1 The proportion (%) of land area with different combinations of changes in the wet season P–E ((P–E)wet), dry season P–E ((P–E)dry) and annual range of P–E ((P–E)range) caused by afforestation
Full size table

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Zan, B., Ge, J., Mu, M. et al. Spatiotemporal inequality in land water availability amplified by global tree restoration. Nat Water 2, 863–874 (2024). https://doi.org/10.1038/s44221-024-00296-5

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