<p>Supplementary Materials</p><p>Table S1. Micro-meteorological measurements for A. pinsapo populations along an altitudinal gradient (low elevation, 1200 m; high elevation, 1550 m) during two consecutive years. Tmax is the mean of the maximum daily temperatures; Tmin is the mean of the minimum daily temperatures; Tm is the mean temperatures (all expressed in ºC). GDD stands for accumulated growing degree days. P is the monthly precipitation (mm). All the variables were measured in situ by two data loggers and rain gauges.</p><p>Tmax Tmin Tm GDD P (mm) Month Low High Low High Low High Low High Low High Jan 8.57 7.13 2.19 0.18 4.61 3.48 - - 35 40 Feb 9.24 7.89 2.52 0.49 5.12 3.99 0.5 - 25 29 Mar 10.32 9.11 2.56 0.54 5.69 4.58 2 1 161 188 Apr 12.01 11.03 4.44 2.40 7.51 6.65 18 12 172 201 May 12.96 11.81 5.98 4.42 8.84 8.01 50 33 78 91 Jun 24.38 23.70 13.42 13.03 18.58 17.63 307 261 20 23 Jul 24.09 24.17 15.90 15.70 20.63 19.54 637 557 0 0 Aug 22.91 22.84 15.29 15.09 19.72 18.61 929 816 0 0 Sep 20.60 20.21 13.04 12.86 17.39 16.22 - - 0 0 Oct 13.39 12.05 9.48 9.33 11.90 10.60 - - 78 94 Nov 9.10 7.20 3.41 3.32 6.61 5.18 - - 131 157 Dec 4.41 1.88 1.39 1.31 3.19 1.67 - - 90 108 Jan 4.73 4.73 -0.67 -0.67 1.82 1.82 - - 0 0 Feb 3.30 1.77 -0.65 -1.85 1.33 -0.04 - - 0 0 Mar 8.16 5.66 3.57 2.79 5.77 4.17 10 1 166 199 Apr 14.78 11.05 7.86 5.00 11.50 7.94 73 22 49 59 May 17.49 16.64 10.72 9.61 14.25 13.05 207 128 0 0 Jun 22.17 22.27 14.53 13.51 18.37 17.60 458 356 0 0 Jul 24.54 24.38 17.39 16.16 21.07 19.99 801 665 0 0 Aug 23.96 24.16 17.13 16.19 20.61 19.71 1130 966 0 0 Sep 18.69 17.47 13.09 11.07 15.91 13.55 - - 0 0 Oct 13.67 12.86 9.73 7.61 11.75 9.97 - - 77 81 Nov 7.09 5.78 4.05 2.00 5.59 4.07 - - 91 95 Dec 5.41 4.61 3.13 -0.73 4.21 2.36 - - 34 36 2</p><p>FigureS1. Foliar nutrient content of two years-old needles of A. pinsapo populations along the altitudinal gradient (low elevation, 1200 m; high elevation, 1550 m). 3 Regression models</p><p>Linear Regresion for xylem water potential and VPD. Equation: Polynomial; Linear f=y0+a*x R Rsqr Adj Rsqr Standard Error of Estimate 0.5412 0.2929 0.2775 0.2957 Coefficient Std. Error t P VIF y0 -0.9655 0.0923 10.4584 <0.0001 4.6775< a -0.4495 0.1030 -4.3653 <0.0001 4.6775<</p><p>Analysis of Variance: Uncorrected for the mean of the observations: DF SS MS Regression 2 85.6611 42.8306 Residual 46 4.0231 0.0875 Total 48 89.6842 1.8684</p><p>Corrected for the mean of the observations: DF SS MS F P Regression 1 1.6666 1.6666 19.0560 <0.0001 Residual 46 4.0231 0.0875 Total 47 5.6897 0.1211</p><p>Exponential Regresion for stomatal conductance and VPD. Equation: Exponential Decay; Single, 2 Parameter f = a*exp(-b*x) R Rsqr Adj Rsqr Standard Error of Estimate 0.5994 0.3593 0.3420 0.1444 Coefficient Std. Error t P VIF a 0.7260 0.1979 3.6678 0.0008 8.1073< b 1.3826 0.3757 3.6799 0.0007 8.1073<</p><p>Analysis of Variance: Uncorrected for the mean of the observations: DF SS MS Regression 2 2.2731 1.1366 Residual 37 0.7712 0.0208 Total 39 3.0443 0.0781</p><p>Corrected for the mean of the observations: DF SS MS F P Regression 1 0.4324 0.4324 20.7475 <0.0001 Residual 37 0.7712 0.0208 Total 38 1.2036 0.0317</p><p>Logarithmic Regression for soil water content and stomatal conductance Equation: Logarithm; 2 Parameter I 4 f=if(x>0; y0+a*ln(abs(x)); 0) R Rsqr Adj Rsqr Standard Error of Estimate 0.6901 0.4762 0.4620 0.1305 Coefficient Std. Error t P VIF y0 -0.6269 0.1470 -4.2634 0.0001 49.4875< a 0.3194 0.0551 5.7998 <0.0001 49.4875<</p><p>Analysis of Variance: Uncorrected for the mean of the observations: DF SS MS Regression 2 2.4139 1.2069 Residual 37 0.6304 0.0170 Total 39 3.0443 0.0781</p><p>Corrected for the mean of the observations: DF SS MS F P Regression 1 0.5731 0.5731 33.6378 <0.0001 Residual 37 0.6304 0.0170 Total 38 1.2036 0.0317</p><p>Logarithmic Regression for soil water content and xylem water potential Equation: Logarithm; 2 Parameter I f=if(x>0; y0+a*ln(abs(x)); 0) R Rsqr Adj Rsqr Standard Error of Estimate 0.7160 0.5127 0.5021 0.2507 Coefficient Std. Error t P VIF y0 -2.9514 0.2346 - 12.5802 <0.0001 42.0354< a 0.6008 0.0864 6.9562 <0.0001 42.0354<</p><p>Analysis of Variance: Uncorrected for the mean of the observations: DF SS MS Regression 2 89.0987 44.5493 Residual 46 2.8912 0.0629 Total 48 91.9899 1.9165</p><p>Corrected for the mean of the observations: DF SS MS F P Regression 1 3.0413 3.0413 48.3886 <0.0001 Residual 46 2.8912 0.0629 Total 47 5.9325 0.1262</p>