Research ArticleECOLOGY

Increased atmospheric vapor pressure deficit reduces global vegetation growth

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Science Advances  14 Aug 2019:
Vol. 5, no. 8, eaax1396
DOI: 10.1126/sciadv.aax1396
  • Fig. 1 Global mean vapor pressure deficit (VPD) anomalies of vegetated area over the growing season.

    Anomalies are relative to the mean of 1982–2015 when data from all datasets are available. Vegetation areas were determined using the MODIS land cover product. Blue line and gray area illustrate the mean and SD of VPD simulated by six CMIP5 models under the RCP4.5 scenario.

  • Fig. 2 Comparison of oceanic evaporation (Eocean) trends during the two periods of 1957–1998 and 1999–2015.

    (A) Time series of globally averaged oceanic evaporation. (B) Spatial pattern on differences of oceanic evaporation trends between 1999–2015 and 1957–1998. Gray shaded area in (A) indicates ±1 SD. The inset in (B) shows the frequency distributions of the corresponding differences.

  • Fig. 3 Comparisons of NDVI trends over the globally vegetated areas from 1982 to 2015.

    (A) Time series of NDVI. The numbers show the change rates of NDVI, and * indicates the significant changes at a significance level of P < 0.05. (B) Probability density function of NDVI trends during the two periods, with bars indicating the proportion of increased (gray) and decreased (black) responses. (C) Mean monthly NDVI trends between the two periods. Shaded area in (A) and error bars in (C) indicate ±1 SD.

  • Fig. 4 Comparison of NDVI trends over the globally vegetated areas between two periods of 1982–1998 and 1999–2015.

    (A) NDVI trend of 1982–1998. (B) NDVI trend of 1999–2015. (C) Differences of NDVI trend between 1999–2015 and 1982–1998. The insets (I) show the relative frequency (%) distribution of significant decreases (Dec*; P < 0.05), decreases (Dec), increases (Inc), and significant increases (Inc*), and the insets (II) show the frequency distributions of the corresponding ranges.

  • Fig. 5 Spatial patterns of correlations between VPD and satellite-based NDVI/LAI.

    Partial correlations between detrended CRU VPD and detrended satellite-based NDVI/LAI were shown: GIMMS NDVI (A), GLASS LAI (B), GLOBMap LAI (C), LAI3g LAI (D), and TCDR LAI (E) during 1982–2015 (GLOBMap and LAI3g from 1982–2011). The insets in (A) to (E) show the relative frequency (%) distribution of significant negative correlations (Neg*; P < 0.05; dark green), negative correlations (Neg; light green), positive correlations (Pos; light red), and significant positive correlations (Pos*; P < 0.05; dark red). (F) Number of satellite-based NDVI/LAI datasets with the same sign of correlation: e.g., (5, –) indicates that all five satellite-based NDVI/LAI datasets showed negative correlations with VPD.

  • Fig. 6 Long-term changes of global GPP and environmental regulations.

    (A) Time series of global GPP estimates derived from EC-LUE and MODIS-GPP models. (B) GPP sensitivity to climate variables, NDVI/fPAR, and atmospheric CO2 concentration. (C) Contributions of climate variables, NDVI/fPAR, and atmospheric CO2 concentration to GPP changes over the two periods. Three climate variables are included: vapor pressure deficit (VPD), air temperature (Ta), and photosynthetically active radiation (PAR).

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/8/eaax1396/DC1

    Fig. S1. Five-year moving average of VPD.

    Fig. S2. Spatial distributions of the difference of VPD trends (kPa year−1) before and after TP years.

    Fig. S3. Spatial pattern of VPD changes between 1982–1986 and 2011–2015 derived from CRU dataset.

    Fig. S4. Interannual variability of SVP (red dots and lines), AVP (green dots and lines), and air temperature (Ta; blue dots and lines) derived from four datasets.

    Fig. S5. Global mean LAI and linear trends during 1982–2015.

    Fig. S6. Differences of LAI trends over the globally vegetated areas between before and after TP years.

    Fig. S7. Model validation of random forest models for simulating NDVI.

    Fig. S8. Environmental regulations on long-term changes of global NDVI.

    Fig. S9. Correlations of LUE and VPD at the different temperature ranges taking DE-Tha site as an example.

    Fig. S10. Correlations between VPD and tree-ring width.

    Fig. S11. Comparison on changes of global mean GPP trend simulated by ecosystem models.

    Fig. S12. Projected future changes in VPD.

    Fig. S13. Validation of EC-LUE model.

    Table S1. Climate and satellite datasets used in this study.

    Table S2. Responses of GPP simulated by EC-LUE, MODIS, and TRENDY models to climate variables, satellite-based NDVI and fPAR, and atmospheric CO2 concentration.

    Table S3. Name, location, and durations of the study EC sites used for revised EC-LUE model calibration and validation.

    Table S4. Correlations between VPD and LUE at different temperature ranges.

    Table S5. CMIP5 models used to estimate VPD from 1850 to 2100.

    Table S6. Correlation matrixes for global VPD simulated by the six CMIP5 ESMs and four historical datasets (CRU, ERA-Interim, HadISDH, and MERRA).

    Table S7. Model parameters of EC-LUE for different vegetation types.

  • Supplementary Materials

    This PDF file includes:

    • Fig. S1. Five-year moving average of VPD.
    • Fig. S2. Spatial distributions of the difference of VPD trends (kPa year−1) before and after TP years.
    • Fig. S3. Spatial pattern of VPD changes between 1982–1986 and 2011–2015 derived from CRU dataset.
    • Fig. S4. Interannual variability of SVP (red dots and lines), AVP (green dots and lines), and air temperature (Ta; blue dots and lines) derived from four datasets.
    • Fig. S5. Global mean LAI and linear trends during 1982–2015.
    • Fig. S6. Differences of LAI trends over the globally vegetated areas between before and after TP years.
    • Fig. S7. Model validation of random forest models for simulating NDVI.
    • Fig. S8. Environmental regulations on long-term changes of global NDVI.
    • Fig. S9. Correlations of LUE and VPD at the different temperature ranges taking DE-Tha site as an example.
    • Fig. S10. Correlations between VPD and tree-ring width.
    • Fig. S11. Comparison on changes of global mean GPP trend simulated by ecosystem models.
    • Fig. S12. Projected future changes in VPD.
    • Fig. S13. Validation of EC-LUE model.
    • Table S1. Climate and satellite datasets used in this study.
    • Table S2. Responses of GPP simulated by EC-LUE, MODIS, and TRENDY models to climate variables, satellite-based NDVI and fPAR, and atmospheric CO2 concentration.
    • Table S3. Name, location, and durations of the study EC sites used for revised EC-LUE model calibration and validation.
    • Table S4. Correlations between VPD and LUE at different temperature ranges.
    • Table S5. CMIP5 models used to estimate VPD from 1850 to 2100.
    • Table S6. Correlation matrixes for global VPD simulated by the six CMIP5 ESMs and four historical datasets (CRU, ERA-Interim, HadISDH, and MERRA).
    • Table S7. Model parameters of EC-LUE for different vegetation types.

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