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Global climatic drivers of leaf size

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Science  01 Sep 2017:
Vol. 357, Issue 6354, pp. 917-921
DOI: 10.1126/science.aal4760
  • Fig. 1 Global trends in leaf size (LS) in relation to latitude and climate.

    (A) Species are coded as simple-leaved (blue circles) or compound-leaved (orange squares; for which “leaf size” refers to that of the leaflets). Solid fitted line (quadratic regression, all species), logLS = 1.37 + 0.006 Lat – 0.0004 Lat2; R2 = 0.28, P < 0.0001. Shown in fig. S3, A and B, are equivalent graphs, with slopes fitted separately to simple- and compound-leaved species, and when considering leaf size of compound leaves to be that of the entire leaf rather than that of the leaflets. (B) Mean annual precipitation (logLS = 1.02 logMAP – 2.18; R2 = 0.22, P < 0.0001). (C) Annual equilibrium MI (logLS = 0.70 logMI + 1.00; R2 = 0.12, P < 0.0001). (D) Mean temperature during the growing season (logLS = 0.07 Tgs – 0.28; R2 = 0.21, P < 0.0001). (E) Annual daily radiation (logLS = 0.002 RAD + 0.54; R2 = 0.002, P = 0.002). In (A) to (E), fitted slopes were estimated by using linear mixed models (site and species treated as random effects); further details of leaf size–climate relationships are given in table S2. In (A) to (E), sample n = 13,641 species-site combinations and dashed lines show the 5th and 95th quantile regression fits. Further analysis by using quantile regression is presented in fig. S7.

  • Fig. 2 Global variation in leaf size as a function of site temperature and precipitation.

    Considering leaf size (LS) as a function of mean temperature of the warmest month (TWM) and mean annual precipitation (MAP), the best-fit surface estimated by multiple mixed-model regression was a twisted plane with the form logLS = – 0.27 TWM – 1.32 logMAP + 0.10 TWM × logMAP + 4.01 (all parameters P = 0.001; R2 = 0.34; n = 13,641 species-site combinations). Similar results were found in analyses involving irradiance rather than TWM, or annual moisture index (MI) rather than precipitation (figs. S5 and S6).

  • Fig. 3 Latitudinal trends in maximum leaf size as predicted by modeling leaf energy budgets.

    Theoretical constraints on maximum leaf size were modeled for each of the 682 sites in our global data set, based both on the risk of day-overheating and on the risk of night-chilling. Results are illustrated with sites grouped by annual moisture index (MI). (A) Arid sites (MI < 0.5). (B) Intermediate-aridity sites (0.5 < MI < 1.5). (C) Wet sites (MI > 1.5). Median trends through model output are indicated in red (day-overheating) and blue (night-chilling). Observed leaf sizes are shown in gray, with mean and 5th/95th quantile quadratic regressions shown in black (solid and dashed lines, respectively). Calculations made by using alternative values of key parameters resulted in slight upward or downward shifts of the constraint functions, without altering their general form (figs. S9 to S12).

  • Fig. 4 Predicted geographic trends in maximum leaf size.

    Each grid cell is color coded according to the smaller of the two predictions for maximum leaf size (daytime or nighttime) (fig. S13), made by using the same procedure as the site-specific modeling. Areas coded the deepest shade of blue are those where there may be no effective thermal constraint on maximum leaf size because sufficient water is generally available for effective transpirational cooling, and warm nighttime air temperatures prevent leaves from suffering radiative frost damage.

Supplementary Materials

  • Global climatic drivers of leaf size

    Ian J. Wright, Ning Dong, Vincent Maire, I. Colin Prentice, Mark Westoby, Sandra Díaz, Rachael V. Gallagher, Bonnie F. Jacobs, Robert Kooyman, Elizabeth A. Law, Michelle R. Leishman, Ülo Niinemets, Peter B. Reich, Lawren Sack, Rafael Villar, Han Wang, Peter Wil

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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    • Materials and Methods
    • Figures S1 to S13
    • Tables S1 to S4
    • References

    Data sets

    Data S1

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