Introduction

## Loading required package: sp

Goal

The aim of this article is to provide an assessment of the performance of fordyn (using either the basic and advanced sub-model) for the prediction of forest dynamics in Catalonia (NE of Spain). To this aim, we simulate forest dynamics between surveys of the Spanish National Forest Inventory and compare the model predictions of forest development against inventory data for a set of permanent plots. The evaluation focuses first on the growth (in diameter and height) of surviving trees, then turning the attention to the basal area of dead trees and overall changes in terms of basal area and density. Then, we evaluate changes in stand leaf area index and, finally, changes in shrub cover and mean shrub height.

Simulation procedure

We selected permanent plots between the second (IFN2) and the fourth (IFN4) without signs of management (i.e. the presence of stumps) and whose basal area did not decrease more than 10% between inventory surveys (to avoid the effect of disturbances).

Soil physical properties were drawn from SoilGrids (Hengl 2016), complemented by rock fragment content estimates derived from surface stoniness measurements in forest plots.

fordyn simulations were conducted for different periods:

  • IFN2 - IFN3 (~ 10 years)
  • IFN3 - IFN4 (~ 15 years)
  • IFN2 - IFN4 (~ 25 years)

The actual simulated period varied depending on the sampling years of the target plot. Daily weather data were obtained via interpolation on plot’s coordinates using package meteoland.

Default species-specific parameters were modified using the results of the meta-modelling exercise and the growth calibration exercise. These two exercises do not provide values for all the main species included here, so it is expected that evaluation results are worse for those species not included in those exercises.

Simulations were done for both the basic (i.e. Granier) and advanced (i.e. Sperry) transpiration/photosynthesis sub-models. On a server with 20 parallel threads, computational times for the longest simulation period (25 years) are around 4 hours (i.e. 2.5 min/plot) for the basic sub-model, versus around 6 days (i.e. 1.5 hr/plot) for the advanced submodel.

In the following sections, we provide the bias, root mean squared error (in absolute and relative terms) and explained variance (R-squared) of growth and mortality predictions at the tree-level and stand-level obtained by simulations with both sub-models. Scatter plots are provided for the IFN2-IFN4 simulation to represent the relationship between predicted and observed values, as well as the factors that may influence the direction and magnitude of prediction error (i.e. initial values, environmental conditions, …).

Detailed results of growth evaluation by tree species are provided in the last section.

Growth of surviving trees

Comparison of diameter/height growth of trees (DBH >= 7.5) that survived between surveys.

Annual diameter increment

Overall predictive capacity to predict diameter increase (cm/yr):
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 25240 0.2410220 0.2510570 0.0100350 4.1635364 0.1767103 73.31710 0.1433847
2.9.3 IFN23 Sperry 25240 0.2410220 0.2402085 -0.0008135 -0.3375314 0.1812412 75.19698 0.1141433
2.9.3 IFN34 Granier 33593 0.1809126 0.2203855 0.0394729 21.8187435 0.1549733 85.66195 0.0916600
2.9.3 IFN34 Sperry 33593 0.1809126 0.2019252 0.0210126 11.6147797 0.1598018 88.33095 0.0471833
2.9.3 IFN24 Granier 22252 0.2076439 0.2166992 0.0090553 4.3609864 0.1439791 69.33944 0.1208357
2.9.3 IFN24 Sperry 22252 0.2076439 0.2020704 -0.0055735 -2.6841817 0.1515521 72.98653 0.0795355

Predictive capacity plots (IFN2-IFN4):

Relationship between diameter increase and climatic variables (MAT, P/PET and available PAR; IFN2 - IFN4):

Annual height increment

Overall predictive capacity to predict height increase (cm/yr):
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 25240 11.307232 11.956505 0.6492722 5.7420970 12.870590 113.8262 0.0648013
2.9.3 IFN23 Sperry 25240 11.307232 11.395532 0.0883002 0.7809175 12.937981 114.4222 0.0582726
2.9.3 IFN34 Granier 33593 8.225607 9.805148 1.5795402 19.2027182 12.297555 149.5033 0.0382904
2.9.3 IFN34 Sperry 33593 8.225607 8.962846 0.7372384 8.9627226 12.173948 148.0006 0.0383640
2.9.3 IFN24 Granier 22252 9.448645 9.782408 0.3337628 3.5323879 9.493789 100.4778 0.0811256
2.9.3 IFN24 Sperry 22252 9.448645 9.083228 -0.3654166 -3.8673969 9.510176 100.6512 0.0812991

Predictive capacity plots (IFN2-IFN4):

Relationship between height increase and climatic variables (MAT, P/PET and available PAR; IFN2 - IFN4):

Stand-level basal area increment

Comparison of basal area increment of surviving trees does not take into account changes in density. In other words, densities from the first inventory are used to calculate stand-level basal area of surviving trees. Hence, the comparison is meant to evaluate the effect of diameter increment of surviving trees in terms of annual stand basal area increments (m2/ha/yr) for the period evaluated.

Predictive capacity table:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.3374811 0.3527152 0.0152341 4.5140597 0.1968105 58.31751 0.4827320
2.9.3 IFN23 Sperry 1775 0.3374811 0.3418611 0.0043800 1.2978476 0.2058298 60.99003 0.4693875
2.9.3 IFN34 Granier 1774 0.3142805 0.3883378 0.0740573 23.5640720 0.2110768 67.16192 0.3651096
2.9.3 IFN34 Sperry 1774 0.3142805 0.3660654 0.0517849 16.4772808 0.2305197 73.34838 0.3543001
2.9.3 IFN24 Granier 1614 0.3033475 0.3152380 0.0118905 3.9197740 0.1783411 58.79102 0.4523729
2.9.3 IFN24 Sperry 1614 0.3033475 0.3013088 -0.0020387 -0.6720638 0.1983854 65.39874 0.4275482

Predictive capacity plots (IFN2 - IFN4):

Relationship between basal area increase and climatic variables (MAT and P/PET; IFN2 - IFN4):

Spatial error distribution (IFN2 - IFN4):

Mortality

Basal area reduction

Annual reduction of basal area (m2/ha/yr) due to trees (DBH >= 7.5) that died during the evaluation period against model’s mortality prediction. In both cases, basal area is calculated using the initial diameter of the trees, so that density reductions are the only prediction that is actually evaluated (and not the possible growth of those trees during the simulation).

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.0341902 0.0388506 0.0046604 13.630747 0.0801998 234.5695 0.1189968
2.9.3 IFN23 Sperry 1775 0.0341902 0.0419123 0.0077221 22.585671 0.0921206 269.4358 0.0576708
2.9.3 IFN34 Granier 1774 0.0722102 0.0667947 -0.0054155 -7.499587 0.1278666 177.0757 0.0498639
2.9.3 IFN34 Sperry 1774 0.0722102 0.0561260 -0.0160842 -22.274097 0.1082715 149.9393 0.1219296
2.9.3 IFN24 Granier 1614 0.0473227 0.0478036 0.0004809 1.016222 0.0783685 165.6045 0.1397359
2.9.3 IFN24 Sperry 1614 0.0473227 0.0411657 -0.0061570 -13.010688 0.0700971 148.1257 0.2017773

Predictive capacity plots (IFN2 - IFN4):

Relationship between dead basal area and climatic variables (MAT and P/PET; IFN2 - IFN4):

Spatial distribution of errors (IFN2 - IFN4):

Density reduction

Annual reduction of density (ind/ha/yr) due to trees (DBH >= 7.5) that died during the evaluation period against model’s mortality prediction. This is very similar to evaluating the reduction in basal area

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 2.054616 2.166542 0.1119253 5.447503 6.504228 316.5665 0.0331148
2.9.3 IFN23 Sperry 1775 2.054616 2.247157 0.1925404 9.371109 6.805936 331.2509 0.0325920
2.9.3 IFN34 Granier 1774 4.354772 3.971894 -0.3828787 -8.792163 9.760872 224.1420 0.0762814
2.9.3 IFN34 Sperry 1774 4.354772 2.706162 -1.6486106 -37.857562 7.784626 178.7608 0.1248698
2.9.3 IFN24 Granier 1614 1.636702 3.030250 1.3935474 85.143602 5.473520 334.4236 0.1094426
2.9.3 IFN24 Sperry 1614 1.636702 2.128852 0.4921496 30.069585 3.548630 216.8158 0.1776700

Ingrowth

Basal area increase

Annual increase of basal area (m2/ha/yr) due to ingrowth of trees with diameters between 7.5 cm and 12.5 cm during the evaluated period.

Predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.0960568 0.0659898 -0.0300670 -31.301254 0.1678272 174.7166 0.0041963
2.9.3 IFN23 Sperry 1775 0.0960568 0.0749100 -0.0211468 -22.014921 0.1712049 178.2329 0.0019911
2.9.3 IFN34 Granier 1774 0.0754149 0.0738258 -0.0015891 -2.107102 0.1431620 189.8326 0.0013542
2.9.3 IFN34 Sperry 1774 0.0754149 0.0837412 0.0083263 11.040679 0.1472762 195.2880 0.0037749
2.9.3 IFN24 Granier 1614 0.0850140 0.0654634 -0.0195505 -22.996862 0.1259979 148.2084 0.0068521
2.9.3 IFN24 Sperry 1614 0.0850140 0.0748778 -0.0101362 -11.922960 0.1272278 149.6551 0.0094581

Predictive capacity plots (IFN2 - IFN4):

Relationship between ingrowth basal area and climatic variables (MAT and P/PET; IFN2 - IFN4):

Spatial distribution of errors (IFN2 - IFN4):

Density increase

Annual increase of density (ind/ha/yr) due to ingrowth of trees with diameters between 7.5 cm and 12.5 cm during the evaluated period.

Predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 15.16134 11.53614 -3.6252060 -23.910848 26.95886 177.8132 0.0054853
2.9.3 IFN23 Sperry 1775 15.16134 12.76076 -2.4005872 -15.833603 27.34091 180.3330 0.0024200
2.9.3 IFN34 Granier 1774 12.06283 12.67282 0.6099882 5.056758 23.43540 194.2778 0.0031139
2.9.3 IFN34 Sperry 1774 12.06283 14.26701 2.2041809 18.272502 23.89215 198.0642 0.0060823
2.9.3 IFN24 Granier 1614 12.31412 10.09821 -2.2159043 -17.994826 18.54517 150.6009 0.0100449
2.9.3 IFN24 Sperry 1614 12.31412 11.33373 -0.9803904 -7.961515 18.50525 150.2767 0.0133026

Overall stand-level change

Basal area changes

This includes annual changes in basal area (m2/ha/yr) due to growth of surviving trees, mortality reductions and ingrowth derived from sapling growth. In the observed data, basal area changes include also the incorporation of trees into large diameter classes that results from the variable-radius sampling design. Since it takes into account all processes together, this evaluation is the most rellevant of all.

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.3972023 0.3784107 -0.0187915 -4.730976 0.3183793 80.15547 0.1203408
2.9.3 IFN23 Sperry 1775 0.3972023 0.3745223 -0.0226800 -5.709925 0.3327688 83.77818 0.1170316
2.9.3 IFN34 Granier 1774 0.3370595 0.4030425 0.0659829 19.576047 0.3257997 96.65940 0.0382718
2.9.3 IFN34 Sperry 1774 0.3370595 0.4063208 0.0692612 20.548657 0.3497075 103.75243 0.0610861
2.9.3 IFN24 Granier 1614 0.3779819 0.3485672 -0.0294147 -7.782034 0.2809288 74.32335 0.0737416
2.9.3 IFN24 Sperry 1614 0.3779819 0.3613474 -0.0166345 -4.400868 0.3087092 81.67301 0.0837204

Predictive capacity plot (IFN2 - IFN4):

Relationship between overall basal area change and climatic variables (MAT and P/PET; IFN2 - IFN4):

Spatial distribution of errors (IFN2 - IFN4):

Density changes

This includes annual changes in density (ind/ha/yr) due to growth of surviving trees, mortality reductions and ingrowth derived from sapling growth. In the observed data, changes include also the incorporation of trees into large diameter classes that results from the variable-radius sampling design.

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 13.357940 9.419832 -3.9381083 -29.481403 29.29232 219.2877 0.0040231
2.9.3 IFN23 Sperry 1775 13.357940 10.553016 -2.8049243 -20.998179 29.54857 221.2060 0.0022281
2.9.3 IFN34 Granier 1774 8.605954 8.764622 0.1586673 1.843692 26.71431 310.4166 0.0065902
2.9.3 IFN34 Sperry 1774 8.605954 11.664005 3.0580501 35.534118 26.78752 311.2672 0.0031044
2.9.3 IFN24 Granier 1614 10.933822 7.841235 -3.0925866 -28.284591 21.10788 193.0512 0.0148830
2.9.3 IFN24 Sperry 1614 10.933822 10.241405 -0.6924164 -6.332794 20.96644 191.7577 0.0078613

Changes in leaf area index of trees > 7.5 cm

Overall predictive capacity using allometric equations:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.2929417 0.2922517 -0.0006900 -0.2355397 0.4526093 154.5049 0.0326050
2.9.3 IFN23 Sperry 1775 0.2929417 0.2965507 0.0036090 1.2320009 0.4698143 160.3781 0.0309913
2.9.3 IFN34 Granier 1774 0.2826026 0.3092020 0.0265993 9.4122713 0.4412830 156.1497 0.0525377
2.9.3 IFN34 Sperry 1774 0.2826026 0.3350054 0.0524027 18.5429042 0.4377824 154.9109 0.0816851
2.9.3 IFN24 Granier 1614 0.5878670 0.5195740 -0.0682929 -11.6170699 0.6869863 116.8608 0.0876206
2.9.3 IFN24 Sperry 1614 0.5878670 0.5808761 -0.0069909 -1.1891897 0.7208363 122.6189 0.0741648

Overall predictive capacity using state variables:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 0.2929417 0.8129123 0.5199706 177.4997 0.9370656 319.8813 0.0081521
2.9.3 IFN23 Sperry 1775 0.2929417 0.8167653 0.5238236 178.8150 0.9894157 337.7518 0.0127528
2.9.3 IFN34 Granier 1774 0.2826026 1.0725979 0.7899952 279.5428 1.1802941 417.6515 0.0182405
2.9.3 IFN34 Sperry 1774 0.2826026 1.1535709 0.8709683 308.1954 1.4045492 497.0050 0.0237107
2.9.3 IFN24 Granier 1614 0.5878670 1.4556562 0.8677893 147.6166 1.5026004 255.6021 0.0242077
2.9.3 IFN24 Sperry 1614 0.5878670 1.5936815 1.0058146 171.0956 1.8801653 319.8284 0.0202884

Shrub cover and mean height

Shrub percent cover changes

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1775 22.37465 19.75818 -2.616467 -11.693892 44.13387 197.2494 0.0281254
2.9.3 IFN23 Sperry 1775 22.37465 19.25347 -3.121176 -13.949612 43.82758 195.8805 0.0059419
2.9.3 IFN34 Granier 1774 22.18602 11.87560 -10.310421 -46.472603 54.41405 245.2628 0.0509630
2.9.3 IFN34 Sperry 1774 22.18602 20.55513 -1.630895 -7.351001 53.76405 242.3330 0.0236755
2.9.3 IFN24 Granier 1614 44.61958 25.26783 -19.351747 -43.370529 63.35317 141.9851 0.0065983
2.9.3 IFN24 Sperry 1614 44.61958 27.61571 -17.003868 -38.108536 64.55488 144.6784 0.0008235

Shrub mean height changes

Overall predictive capacity:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1572 6.285700 43.62822 37.518120 596.88053 84.74814 1348.2689 0.0127112
2.9.3 IFN23 Sperry 1560 5.810655 41.73444 36.015967 619.82630 89.44012 1539.2434 0.0061212
2.9.3 IFN34 Granier 1714 32.096347 42.78995 10.815421 33.69674 81.03306 252.4682 0.0216451
2.9.3 IFN34 Sperry 1714 32.050402 39.14764 7.140503 22.27898 87.99448 274.5503 0.0015234
2.9.3 IFN24 Granier 1401 34.074337 74.52546 40.524916 118.93090 114.60069 336.3255 0.0286464
2.9.3 IFN24 Sperry 1341 33.288672 75.66733 42.656877 128.14232 139.71147 419.6967 0.0007556

Detailed evaluation by tree species

In the following we provide detailed evaluation results for the most important species.

Abies alba

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 581 0.3248858 0.1757081 -0.1491777 -45.91695 0.2990908 92.06027 0.1832686
2.9.3 IFN23 Sperry 581 0.3248858 0.1731136 -0.1517722 -46.71555 0.3032952 93.35439 0.1565168
2.9.3 IFN34 Granier 733 0.3071834 0.1711968 -0.1359865 -44.26885 0.2688735 87.52867 0.1560679
2.9.3 IFN34 Sperry 733 0.3071834 0.1589369 -0.1482465 -48.25994 0.2798596 91.10507 0.0988316
2.9.3 IFN24 Granier 554 0.3204793 0.1660305 -0.1544488 -48.19306 0.2611898 81.49975 0.2643651
2.9.3 IFN24 Sperry 554 0.3204793 0.1640309 -0.1564483 -48.81699 0.2659607 82.98843 0.2023990

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 581 16.29681 6.442982 -9.853824 -60.46476 23.65973 145.1802 0.1394643
2.9.3 IFN23 Sperry 581 16.29681 6.404699 -9.892107 -60.69967 23.81142 146.1110 0.1112480
2.9.3 IFN34 Granier 733 13.82449 6.212174 -7.612316 -55.06399 20.92261 151.3445 0.1197799
2.9.3 IFN34 Sperry 733 13.82449 5.921157 -7.903334 -57.16908 21.25651 153.7598 0.0800358
2.9.3 IFN24 Granier 554 14.71605 6.065490 -8.650559 -58.78316 17.72375 120.4382 0.2402032
2.9.3 IFN24 Sperry 554 14.71605 6.102032 -8.614016 -58.53484 17.87170 121.4436 0.1759728

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 0.3337317 0.1687285 -0.1650032 -49.44187 0.2406100 72.09682 0.5174678
2.9.3 IFN23 Sperry 41 0.3337317 0.1669853 -0.1667464 -49.96420 0.2402116 71.97746 0.5463756
2.9.3 IFN34 Granier 47 0.3566043 0.1863233 -0.1702810 -47.75070 0.2474370 69.38698 0.5611664
2.9.3 IFN34 Sperry 47 0.3566043 0.1761593 -0.1804450 -50.60090 0.2620951 73.49746 0.4827352
2.9.3 IFN24 Granier 41 0.3439408 0.1575496 -0.1863911 -54.19280 0.2519176 73.24446 0.5630300
2.9.3 IFN24 Sperry 41 0.3439408 0.1581637 -0.1857770 -54.01426 0.2517635 73.19967 0.5207087

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 0.0625212 0.0137979 -0.0487233 -77.93083 0.1223226 195.6497 0.5949484
2.9.3 IFN23 Sperry 41 0.0625212 0.0086079 -0.0539133 -86.23202 0.1392203 222.6769 0.1918869
2.9.3 IFN34 Granier 47 0.0795714 0.0498879 -0.0296834 -37.30416 0.3016182 379.0536 0.0000323
2.9.3 IFN34 Sperry 47 0.0795714 0.0094474 -0.0701239 -88.12710 0.1538457 193.3430 0.1555239
2.9.3 IFN24 Granier 41 0.0678598 0.0373322 -0.0305276 -44.98623 0.1789016 263.6341 0.0747160
2.9.3 IFN24 Sperry 41 0.0678598 0.0105811 -0.0572787 -84.40743 0.1229091 181.1221 0.0263679

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 1.2737704 0.4306707 -0.8430997 -66.18930 3.153570 247.5776 0.9176891
2.9.3 IFN23 Sperry 41 1.2737704 0.1311441 -1.1426263 -89.70426 4.624829 363.0819 0.1253308
2.9.3 IFN34 Granier 47 1.2960226 0.7972839 -0.4987386 -38.48225 5.391271 415.9859 0.0000140
2.9.3 IFN34 Sperry 47 1.2960226 0.1678800 -1.1281425 -87.04652 4.373717 337.4723 0.1556176
2.9.3 IFN24 Granier 41 0.2579368 0.6663175 0.4083807 158.32590 2.266855 878.8414 0.0250615
2.9.3 IFN24 Sperry 41 0.2579368 0.3369402 0.0790035 30.62900 1.484051 575.3546 0.0033053

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 0.0535332 0.0136456 -0.0398876 -74.509998 0.1185935 221.5326 0.0201069
2.9.3 IFN23 Sperry 41 0.0535332 0.0401618 -0.0133714 -24.977736 0.1335188 249.4131 0.0314971
2.9.3 IFN34 Granier 47 0.0280916 0.0238658 -0.0042258 -15.042922 0.0912374 324.7857 0.0229693
2.9.3 IFN34 Sperry 47 0.0280916 0.0296891 0.0015975 5.686811 0.0775698 276.1319 0.0315755
2.9.3 IFN24 Granier 41 0.0350303 0.0438875 0.0088572 25.284551 0.0778693 222.2914 0.1460852
2.9.3 IFN24 Sperry 41 0.0350303 0.0342116 -0.0008186 -2.336952 0.0833706 237.9957 0.0357364

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 8.141885 2.505699 -5.6361866 -69.2245894 19.25209 236.4573 0.0205559
2.9.3 IFN23 Sperry 41 8.141885 6.600731 -1.5411538 -18.9287101 21.57432 264.9794 0.0263007
2.9.3 IFN34 Granier 47 4.181244 4.201945 0.0207011 0.4950939 14.56676 348.3835 0.0235852
2.9.3 IFN34 Sperry 47 4.181244 5.063148 0.8819047 21.0919215 11.91431 284.9467 0.0441502
2.9.3 IFN24 Granier 41 4.512880 6.729557 2.2166766 49.1188891 10.96519 242.9755 0.1357344
2.9.3 IFN24 Sperry 41 4.512880 5.008066 0.4951856 10.9727190 11.81659 261.8413 0.0185379

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 0.2839633 0.1745975 -0.1093658 -38.51407 0.2942799 103.63307 0.2323714
2.9.3 IFN23 Sperry 41 0.2839633 0.2043301 -0.0796332 -28.04347 0.2830959 99.69452 0.2400354
2.9.3 IFN34 Granier 47 0.3158355 0.1671022 -0.1487334 -47.09203 0.4687509 148.41614 0.0124649
2.9.3 IFN34 Sperry 47 0.3158355 0.2046929 -0.1111426 -35.19003 0.3424142 108.41537 0.1132763
2.9.3 IFN24 Granier 41 0.3449944 0.1778356 -0.1671587 -48.45260 0.3404229 98.67490 0.0861575
2.9.3 IFN24 Sperry 41 0.3449944 0.2023436 -0.1426507 -41.34872 0.2930576 84.94563 0.1085571

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 41 7.907260 2.075028 -5.8322324 -73.757942 20.37133 257.6281 0.0046192
2.9.3 IFN23 Sperry 41 7.907260 6.469587 -1.4376730 -18.181684 22.05840 278.9638 0.0051263
2.9.3 IFN34 Granier 47 3.873059 3.404661 -0.4683978 -12.093743 13.50186 348.6098 0.0011254
2.9.3 IFN34 Sperry 47 3.873059 4.895269 1.0222097 26.392828 12.11612 312.8308 0.0155789
2.9.3 IFN24 Granier 41 6.167707 6.321242 0.1535353 2.489341 11.23445 182.1496 0.1374349
2.9.3 IFN24 Sperry 41 6.167707 5.325178 -0.8425292 -13.660332 12.47478 202.2595 0.0142452

Fagus sylvatica

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 878 0.2623334 0.2073334 -0.0550000 -20.96571 0.2090688 79.69585 0.1336271
2.9.3 IFN23 Sperry 878 0.2623334 0.2112657 -0.0510677 -19.46672 0.2145563 81.78762 0.0755360
2.9.3 IFN34 Granier 1148 0.2237397 0.1995035 -0.0242361 -10.83230 0.1693463 75.68899 0.0996930
2.9.3 IFN34 Sperry 1148 0.2237397 0.1976363 -0.0261033 -11.66684 0.1781869 79.64027 0.0380644
2.9.3 IFN24 Granier 842 0.2499840 0.2032646 -0.0467194 -18.68896 0.1741470 69.66325 0.1524445
2.9.3 IFN24 Sperry 842 0.2499840 0.1993547 -0.0506293 -20.25303 0.1883202 75.33287 0.0495041

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 878 16.94559 9.136901 -7.808689 -46.08095 18.07897 106.68834 0.0440046
2.9.3 IFN23 Sperry 878 16.94559 9.558608 -7.386983 -43.59236 18.00341 106.24247 0.0381348
2.9.3 IFN34 Granier 1148 13.05423 8.405259 -4.648968 -35.61274 17.81713 136.48551 0.0046308
2.9.3 IFN34 Sperry 1148 13.05423 8.641139 -4.413087 -33.80581 18.11142 138.73990 0.0000127
2.9.3 IFN24 Granier 842 14.97444 8.671560 -6.302881 -42.09093 14.47779 96.68335 0.0317603
2.9.3 IFN24 Sperry 842 14.97444 8.798918 -6.175523 -41.24043 14.75573 98.53945 0.0156628

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 0.2141684 0.1735453 -0.0406231 -18.967814 0.1421099 66.35426 0.6168019
2.9.3 IFN23 Sperry 93 0.2141684 0.1864878 -0.0276806 -12.924694 0.1496995 69.89804 0.5946819
2.9.3 IFN34 Granier 99 0.2098880 0.1883435 -0.0215444 -10.264738 0.1246596 59.39340 0.6403028
2.9.3 IFN34 Sperry 99 0.2098880 0.1972817 -0.0126063 -6.006195 0.1408179 67.09196 0.6141650
2.9.3 IFN24 Granier 93 0.2117429 0.1732333 -0.0385095 -18.186938 0.1365205 64.47466 0.6194588
2.9.3 IFN24 Sperry 93 0.2117429 0.1813430 -0.0303998 -14.356963 0.1537594 72.61609 0.5754245

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 0.0128669 0.0162426 0.0033756 26.235108 0.0488393 379.5729 0.0001213
2.9.3 IFN23 Sperry 93 0.0128669 0.0137818 0.0009149 7.110223 0.0436716 339.4102 0.0059575
2.9.3 IFN34 Granier 99 0.0251491 0.0234591 -0.0016900 -6.719896 0.0557730 221.7699 0.2789124
2.9.3 IFN34 Sperry 99 0.0251491 0.0176272 -0.0075218 -29.909052 0.0509225 202.4826 0.1836860
2.9.3 IFN24 Granier 93 0.0181819 0.0199993 0.0018174 9.995436 0.0369747 203.3600 0.1968418
2.9.3 IFN24 Sperry 93 0.0181819 0.0145835 -0.0035984 -19.791089 0.0375810 206.6945 0.0681115

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 0.5030180 0.7851911 0.2821732 56.096041 2.929598 582.4042 0.0059283
2.9.3 IFN23 Sperry 93 0.5030180 0.5532235 0.0502055 9.980858 1.781220 354.1066 0.1059830
2.9.3 IFN34 Granier 99 1.4949666 1.3456507 -0.1493158 -9.987904 5.561581 372.0204 0.3860488
2.9.3 IFN34 Sperry 99 1.4949666 0.6300918 -0.8648748 -57.852448 3.818657 255.4343 0.3561007
2.9.3 IFN24 Granier 93 0.6638779 1.3932259 0.7293479 109.861758 2.856867 430.3301 0.4521545
2.9.3 IFN24 Sperry 93 0.6638779 0.5848368 -0.0790411 -11.905969 1.697174 255.6455 0.2831643

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 0.0334581 0.0384183 0.0049602 14.82521 0.1143012 341.6254 0.0005832
2.9.3 IFN23 Sperry 93 0.0334581 0.0154226 -0.0180355 -53.90480 0.1041600 311.3152 0.0104887
2.9.3 IFN34 Granier 99 0.0235301 0.0323900 0.0088599 37.65341 0.0794750 337.7587 0.0034803
2.9.3 IFN34 Sperry 99 0.0235301 0.0368692 0.0133391 56.68955 0.0879608 373.8223 0.0009118
2.9.3 IFN24 Granier 93 0.0292275 0.0369485 0.0077210 26.41682 0.0799973 273.7053 0.0166448
2.9.3 IFN24 Sperry 93 0.0292275 0.0370566 0.0078291 26.78656 0.0734826 251.4154 0.0164801

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 5.418058 7.206323 1.788266 33.00566 18.92406 349.2776 0.0012745
2.9.3 IFN23 Sperry 93 5.418058 2.877612 -2.540446 -46.88850 16.47746 304.1211 0.0116106
2.9.3 IFN34 Granier 99 4.052478 6.421286 2.368809 58.45334 14.73418 363.5844 0.0035200
2.9.3 IFN34 Sperry 99 4.052478 6.552309 2.499831 61.68650 15.49839 382.4423 0.0033742
2.9.3 IFN24 Granier 93 4.451677 6.070922 1.619245 36.37382 12.47007 280.1207 0.0120335
2.9.3 IFN24 Sperry 93 4.451677 5.714846 1.263169 28.37512 11.06609 248.5826 0.0056297

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 0.2382169 0.1937376 -0.0444794 -18.671783 0.2207718 92.67677 0.3352583
2.9.3 IFN23 Sperry 93 0.2382169 0.1860143 -0.0522026 -21.913910 0.2128521 89.35221 0.3956369
2.9.3 IFN34 Granier 99 0.1917045 0.1984485 0.0067440 3.517939 0.1882287 98.18693 0.3453787
2.9.3 IFN34 Sperry 99 0.1917045 0.2188030 0.0270985 14.135554 0.2129479 111.08136 0.2751532
2.9.3 IFN24 Granier 93 0.2270473 0.1906403 -0.0364070 -16.034968 0.1975026 86.98745 0.3074487
2.9.3 IFN24 Sperry 93 0.2270473 0.2071451 -0.0199021 -8.765640 0.2082754 91.73217 0.3333056

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 93 5.246704 6.421132 1.174428 22.38411 20.14204 383.8990 0.0065094
2.9.3 IFN23 Sperry 93 5.246704 2.324388 -2.922316 -55.69813 17.45794 332.7410 0.0162710
2.9.3 IFN34 Granier 99 2.032230 5.075635 3.043405 149.75688 15.62872 769.0428 0.0175586
2.9.3 IFN34 Sperry 99 2.032230 5.922217 3.889987 191.41464 16.15671 795.0235 0.0015636
2.9.3 IFN24 Granier 93 3.810054 4.798758 0.988704 25.94987 13.62157 357.5163 0.0146571
2.9.3 IFN24 Sperry 93 3.810054 5.376227 1.566172 41.10631 11.74192 308.1825 0.0004029

Pinus halepensis

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 3290 0.3451130 0.3876252 0.0425122 12.31833 0.2157046 62.50261 0.0795771
2.9.3 IFN23 Sperry 3290 0.3451130 0.3026675 -0.0424455 -12.29902 0.2224183 64.44795 0.1042456
2.9.3 IFN34 Granier 4562 0.2441193 0.3117245 0.0676052 27.69353 0.1762431 72.19550 0.0455876
2.9.3 IFN34 Sperry 4562 0.2441193 0.1981882 -0.0459310 -18.81500 0.1813604 74.29173 0.0593012
2.9.3 IFN24 Granier 2576 0.2837014 0.3159174 0.0322160 11.35559 0.1744211 61.48053 0.0488389
2.9.3 IFN24 Sperry 2576 0.2837014 0.2070511 -0.0766503 -27.01794 0.1900243 66.98039 0.1033127

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 3290 13.83568 17.947883 4.1121997 29.7216944 14.76508 106.71740 0.0127020
2.9.3 IFN23 Sperry 3290 13.83568 13.878267 0.0425827 0.3077745 14.32631 103.54612 0.0197361
2.9.3 IFN34 Granier 4562 10.16668 13.033520 2.8668380 28.1983632 12.03005 118.32817 0.0027032
2.9.3 IFN34 Sperry 4562 10.16668 8.016958 -2.1497242 -21.1447952 11.03477 108.53856 0.0159772
2.9.3 IFN24 Granier 2576 11.40008 13.506063 2.1059807 18.4733810 10.62837 93.23062 0.0006878
2.9.3 IFN24 Sperry 2576 11.40008 8.783201 -2.6168816 -22.9549355 10.09282 88.53284 0.0377835

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 0.2369726 0.2699030 0.0329303 13.89626 0.1534315 64.74652 0.6785207
2.9.3 IFN23 Sperry 477 0.2369726 0.2075703 -0.0294023 -12.40746 0.1604483 67.70751 0.5965321
2.9.3 IFN34 Granier 494 0.2057077 0.2708458 0.0651381 31.66539 0.1593632 77.47072 0.6163864
2.9.3 IFN34 Sperry 494 0.2057077 0.1662921 -0.0394155 -19.16095 0.1513368 73.56885 0.4875346
2.9.3 IFN24 Granier 398 0.2031947 0.2283065 0.0251118 12.35847 0.1454044 71.55911 0.6068515
2.9.3 IFN24 Sperry 398 0.2031947 0.1411542 -0.0620406 -30.53257 0.1557230 76.63729 0.5274892

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 0.0171807 0.0304376 0.0132569 77.1612346 0.0606438 352.9755 0.1104570
2.9.3 IFN23 Sperry 477 0.0171807 0.0281920 0.0110112 64.0904328 0.0562628 327.4759 0.1729275
2.9.3 IFN34 Granier 494 0.0466047 0.0450994 -0.0015053 -3.2298422 0.0749353 160.7893 0.1500704
2.9.3 IFN34 Sperry 494 0.0466047 0.0410615 -0.0055432 -11.8940848 0.0703523 150.9554 0.2199615
2.9.3 IFN24 Granier 398 0.0276508 0.0322612 0.0046104 16.6736882 0.0496302 179.4890 0.2048946
2.9.3 IFN24 Sperry 398 0.0276508 0.0278328 0.0001820 0.6582254 0.0443709 160.4687 0.3105615

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 0.9141541 1.598389 0.6842352 74.84900 4.945893 541.0350 0.0387912
2.9.3 IFN23 Sperry 477 0.9141541 1.340620 0.4264655 46.65138 3.958686 433.0436 0.1567807
2.9.3 IFN34 Granier 494 2.6017289 2.026513 -0.5752160 -22.10899 5.358694 205.9666 0.1621544
2.9.3 IFN34 Sperry 494 2.6017289 1.633206 -0.9685226 -37.22612 4.953363 190.3874 0.3130151
2.9.3 IFN24 Granier 398 0.9628414 1.785348 0.8225068 85.42494 3.138659 325.9788 0.1960244
2.9.3 IFN24 Sperry 398 0.9628414 1.331821 0.3689801 38.32200 1.781292 185.0037 0.4196342

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 0.0438144 0.0327355 -0.0110789 -25.285911 0.1241979 283.4637 0.0118466
2.9.3 IFN23 Sperry 477 0.0438144 0.0413632 -0.0024512 -5.594566 0.1356866 309.6851 0.0000002
2.9.3 IFN34 Granier 494 0.0230843 0.0351662 0.0120819 52.338245 0.0870189 376.9615 0.0008095
2.9.3 IFN34 Sperry 494 0.0230843 0.0388531 0.0157689 68.309921 0.0847325 367.0572 0.0006137
2.9.3 IFN24 Granier 398 0.0286826 0.0289126 0.0002299 0.801704 0.0721259 251.4620 0.0022324
2.9.3 IFN24 Sperry 398 0.0286826 0.0323054 0.0036228 12.630480 0.0729096 254.1942 0.0029571

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 6.500345 4.790142 -1.7102030 -26.309418 17.87446 274.9771 0.0111423
2.9.3 IFN23 Sperry 477 6.500345 6.428670 -0.0716752 -1.102637 19.66642 302.5442 0.0000114
2.9.3 IFN34 Granier 494 3.354195 4.931760 1.5775647 47.032586 11.73716 349.9249 0.0000588
2.9.3 IFN34 Sperry 494 3.354195 6.334950 2.9807548 88.866471 12.74533 379.9818 0.0000714
2.9.3 IFN24 Granier 398 3.871624 4.142104 0.2704799 6.986212 9.55088 246.6892 0.0023564
2.9.3 IFN24 Sperry 398 3.871624 5.216579 1.3449552 34.738786 10.23052 264.2435 0.0008334

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 0.2439406 0.2639985 0.0200580 8.222486 0.2740271 112.3336 0.2147018
2.9.3 IFN23 Sperry 477 0.2439406 0.2169603 -0.0269802 -11.060166 0.2798736 114.7302 0.1642981
2.9.3 IFN34 Granier 494 0.1807259 0.2660785 0.0853526 47.227646 0.2833437 156.7809 0.0650272
2.9.3 IFN34 Sperry 494 0.1807259 0.1707646 -0.0099613 -5.511831 0.2766589 153.0820 0.0252954
2.9.3 IFN24 Granier 398 0.2117019 0.2431536 0.0314517 14.856608 0.2199638 103.9026 0.1765911
2.9.3 IFN24 Sperry 398 0.2117019 0.1624416 -0.0492603 -23.268695 0.2325089 109.8284 0.0740022

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 477 5.7511493 3.191753 -2.5593962 -44.502343 20.49982 356.4474 0.0143372
2.9.3 IFN23 Sperry 477 5.7511493 5.214555 -0.5365943 -9.330209 21.80384 379.1214 0.0009526
2.9.3 IFN34 Granier 494 0.7589133 3.133988 2.3750746 312.957306 16.04044 2113.6067 0.0046566
2.9.3 IFN34 Sperry 494 0.7589133 4.729197 3.9702840 523.153827 16.28182 2145.4123 0.0088772
2.9.3 IFN24 Granier 398 3.0614036 3.644043 0.5826392 19.031767 12.63915 412.8548 0.0186809
2.9.3 IFN24 Sperry 398 3.0614036 4.669142 1.6077382 52.516376 12.86855 420.3480 0.0034856

Pinus nigra

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 2460 0.2558898 0.3084823 0.0525925 20.552784 0.1624684 63.49154 0.0258013
2.9.3 IFN23 Sperry 2460 0.2558898 0.2793620 0.0234722 9.172785 0.1649767 64.47177 0.0421616
2.9.3 IFN34 Granier 3321 0.1715706 0.2716321 0.1000615 58.320909 0.1665795 97.09097 0.0002235
2.9.3 IFN34 Sperry 3321 0.1715706 0.2119063 0.0403358 23.509723 0.1497371 87.27436 0.0192770
2.9.3 IFN24 Granier 2014 0.2117903 0.2669436 0.0551533 26.041464 0.1520186 71.77790 0.0002560
2.9.3 IFN24 Sperry 2014 0.2117903 0.2162414 0.0044511 2.101643 0.1449316 68.43166 0.0392910

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 2460 13.008362 18.36914 5.360779 41.21025 13.759154 105.77161 0.0202986
2.9.3 IFN23 Sperry 2460 13.008362 16.65015 3.641788 27.99574 13.278948 102.08009 0.0435860
2.9.3 IFN34 Granier 3321 9.923332 15.13471 5.211382 52.51645 12.597435 126.94764 0.0000337
2.9.3 IFN34 Sperry 3321 9.923332 11.79298 1.869648 18.84093 11.120683 112.06602 0.0289577
2.9.3 IFN24 Granier 2014 11.082126 15.07059 3.988464 35.99006 10.272929 92.69817 0.0054392
2.9.3 IFN24 Sperry 2014 11.082126 12.23322 1.151090 10.38691 8.978396 81.01691 0.0880869

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 0.1973055 0.2442557 0.0469502 23.795702 0.1505157 76.28562 0.6800344
2.9.3 IFN23 Sperry 299 0.1973055 0.2218152 0.0245097 12.422221 0.1498109 75.92841 0.6785288
2.9.3 IFN34 Granier 332 0.1485922 0.2477795 0.0991873 66.751334 0.1898917 127.79385 0.6286336
2.9.3 IFN34 Sperry 332 0.1485922 0.1914779 0.0428857 28.861342 0.1667533 112.22210 0.5897071
2.9.3 IFN24 Granier 253 0.1706274 0.2200110 0.0493836 28.942377 0.1568859 91.94649 0.6184239
2.9.3 IFN24 Sperry 253 0.1706274 0.1791179 0.0084905 4.976033 0.1503393 88.10969 0.6486463

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 0.0124471 0.0118526 -0.0005946 -4.776786 0.0445620 358.0104 0.0992300
2.9.3 IFN23 Sperry 299 0.0124471 0.0116539 -0.0007932 -6.372444 0.0444200 356.8689 0.1079484
2.9.3 IFN34 Granier 332 0.0174871 0.0157463 -0.0017408 -9.954494 0.0457070 261.3759 0.1108188
2.9.3 IFN34 Sperry 332 0.0174871 0.0148268 -0.0026603 -15.213127 0.0451960 258.4535 0.1369015
2.9.3 IFN24 Granier 253 0.0132369 0.0138174 0.0005806 4.385924 0.0352192 266.0688 0.0894560
2.9.3 IFN24 Sperry 253 0.0132369 0.0114430 -0.0017939 -13.552181 0.0319832 241.6220 0.2513125

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 0.7776704 0.5297469 -0.2479235 -31.88028 3.248881 417.7710 0.0268965
2.9.3 IFN23 Sperry 299 0.7776704 0.5205545 -0.2571159 -33.06232 3.245173 417.2941 0.0292123
2.9.3 IFN34 Granier 332 1.1926192 0.6427536 -0.5498656 -46.10572 3.758500 315.1467 0.0764763
2.9.3 IFN34 Sperry 332 1.1926192 0.5615563 -0.6310629 -52.91403 3.715426 311.5350 0.1548815
2.9.3 IFN24 Granier 253 0.5679904 0.6477849 0.0797946 14.04858 2.388511 420.5197 0.0405233
2.9.3 IFN24 Sperry 253 0.5679904 0.5073832 -0.0606072 -10.67045 2.099800 369.6893 0.2159129

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 0.0322431 0.0408395 0.0085963 26.66102 0.1202017 372.7980 0.0181666
2.9.3 IFN23 Sperry 299 0.0322431 0.0413613 0.0091182 28.27950 0.1073440 332.9206 0.0076816
2.9.3 IFN34 Granier 332 0.0176960 0.0418604 0.0241645 136.55369 0.0858957 485.3972 0.0012826
2.9.3 IFN34 Sperry 332 0.0176960 0.0386218 0.0209259 118.25231 0.0808740 457.0195 0.0019380
2.9.3 IFN24 Granier 253 0.0210942 0.0342740 0.0131798 62.48102 0.0702191 332.8842 0.0233006
2.9.3 IFN24 Sperry 253 0.0210942 0.0329578 0.0118637 56.24142 0.0719719 341.1934 0.0003215

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 4.863574 6.599629 1.736055 35.69505 18.416823 378.6685 0.0188409
2.9.3 IFN23 Sperry 299 4.863574 6.463916 1.600342 32.90465 16.463161 338.4992 0.0022273
2.9.3 IFN34 Granier 332 2.787991 6.505783 3.717792 133.35022 13.125190 470.7759 0.0005866
2.9.3 IFN34 Sperry 332 2.787991 6.250377 3.462386 124.18928 12.526857 449.3148 0.0011921
2.9.3 IFN24 Granier 253 2.916620 4.997221 2.080602 71.33607 9.795172 335.8399 0.0203836
2.9.3 IFN24 Sperry 253 2.916620 5.101795 2.185176 74.92153 10.588404 363.0368 0.0007211

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 0.2096273 0.2734867 0.0638593 30.46326 0.2517444 120.0914 0.2822120
2.9.3 IFN23 Sperry 299 0.2096273 0.2517364 0.0421090 20.08757 0.2432199 116.0249 0.3200936
2.9.3 IFN34 Granier 332 0.1577085 0.2754339 0.1177253 74.64742 0.2421147 153.5204 0.3083784
2.9.3 IFN34 Sperry 332 0.1577085 0.2188713 0.0611628 38.78215 0.2169896 137.5890 0.3103837
2.9.3 IFN24 Granier 253 0.1822697 0.2529334 0.0706637 38.76879 0.2262218 124.1138 0.3051596
2.9.3 IFN24 Sperry 253 0.1822697 0.2122525 0.0299828 16.44967 0.2097442 115.0736 0.3578467

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 299 4.120112 6.069883 1.949771 47.32326 19.47738 472.7393 0.0053530
2.9.3 IFN23 Sperry 299 4.120112 5.943362 1.823251 44.25246 17.82874 432.7247 0.0040316
2.9.3 IFN34 Granier 332 2.133934 5.863030 3.729096 174.75219 14.53151 680.9728 0.0017855
2.9.3 IFN34 Sperry 332 2.133934 5.802592 3.668659 171.91998 14.63469 685.8079 0.0010471
2.9.3 IFN24 Granier 253 2.531671 5.040474 2.508803 99.09674 11.82512 467.0877 0.0094190
2.9.3 IFN24 Sperry 253 2.531671 5.176030 2.644360 104.45117 12.05899 476.3253 0.0011559

Pinus sylvestris

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 5735 0.2624103 0.2782603 0.0158500 6.040146 0.1763768 67.21412 0.0044670
2.9.3 IFN23 Sperry 5735 0.2624103 0.2880083 0.0255979 9.754925 0.1788676 68.16334 0.0044030
2.9.3 IFN34 Granier 7174 0.2004406 0.2586554 0.0582147 29.043383 0.1587823 79.21662 0.0003373
2.9.3 IFN34 Sperry 7174 0.2004406 0.2599221 0.0594815 29.675351 0.1674667 83.54928 0.0006846
2.9.3 IFN24 Granier 5067 0.2301231 0.2515565 0.0214334 9.313867 0.1447991 62.92245 0.0016348
2.9.3 IFN24 Sperry 5067 0.2301231 0.2557069 0.0255838 11.117421 0.1515710 65.86517 0.0016593

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 5735 13.532836 15.13643 1.603596 11.84967 12.588856 93.02452 0.0266769
2.9.3 IFN23 Sperry 5735 13.532836 15.68074 2.147901 15.87178 12.824279 94.76416 0.0233785
2.9.3 IFN34 Granier 7174 9.943236 13.11621 3.172975 31.91089 12.207179 122.76868 0.0175592
2.9.3 IFN34 Sperry 7174 9.943236 13.20190 3.258668 32.77271 12.439680 125.10696 0.0215288
2.9.3 IFN24 Granier 5067 11.449844 13.03288 1.583034 13.82581 9.066559 79.18500 0.0458568
2.9.3 IFN24 Sperry 5067 11.449844 13.28096 1.831117 15.99251 9.433095 82.38623 0.0378802

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 0.2807627 0.2930273 0.0122647 4.368336 0.1924925 68.56057 0.5639624
2.9.3 IFN23 Sperry 496 0.2807627 0.3055486 0.0247859 8.828067 0.2010509 71.60886 0.5667575
2.9.3 IFN34 Granier 522 0.2350824 0.3055257 0.0704433 29.965386 0.1935338 82.32594 0.6092187
2.9.3 IFN34 Sperry 522 0.2350824 0.3099564 0.0748740 31.850123 0.2141304 91.08739 0.6123292
2.9.3 IFN24 Granier 458 0.2545322 0.2716278 0.0170955 6.716447 0.1735631 68.18903 0.5797712
2.9.3 IFN24 Sperry 458 0.2545322 0.2790564 0.0245242 9.635011 0.1892343 74.34589 0.5674542

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 0.0319119 0.0406648 0.0087530 27.4286401 0.0619124 194.0106 0.3043714
2.9.3 IFN23 Sperry 496 0.0319119 0.0406586 0.0087467 27.4090824 0.0619111 194.0065 0.3043801
2.9.3 IFN34 Granier 522 0.0567274 0.0518344 -0.0048930 -8.6255267 0.0900577 158.7552 0.2164592
2.9.3 IFN34 Sperry 522 0.0567274 0.0514657 -0.0052617 -9.2754632 0.0896250 157.9924 0.2245876
2.9.3 IFN24 Granier 458 0.0416362 0.0413656 -0.0002705 -0.6497635 0.0565140 135.7330 0.3974533
2.9.3 IFN24 Sperry 458 0.0416362 0.0408292 -0.0008070 -1.9381752 0.0568289 136.4893 0.3914893

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 1.666455 1.504857 -0.1615988 -9.697156 4.161693 249.7332 0.3422814
2.9.3 IFN23 Sperry 496 1.666455 1.504652 -0.1618032 -9.709423 4.161675 249.7322 0.3422736
2.9.3 IFN34 Granier 522 2.527976 1.642409 -0.8855672 -35.030675 4.946214 195.6590 0.1595086
2.9.3 IFN34 Sperry 522 2.527976 1.601697 -0.9262797 -36.641153 4.845950 191.6928 0.2146625
2.9.3 IFN24 Granier 458 1.078167 1.566766 0.4885995 45.317628 2.102586 195.0149 0.2947451
2.9.3 IFN24 Sperry 458 1.078167 1.506604 0.4284377 39.737616 2.059250 190.9955 0.2862689

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 0.0380071 0.0365579 -0.0014492 -3.812977 0.1150870 302.8041 0.0081088
2.9.3 IFN23 Sperry 496 0.0380071 0.0393270 0.0013199 3.472892 0.1205697 317.2294 0.0000005
2.9.3 IFN34 Granier 522 0.0209448 0.0383259 0.0173811 82.985488 0.0931770 444.8701 0.0007440
2.9.3 IFN34 Sperry 522 0.0209448 0.0427661 0.0218214 104.185188 0.0975040 465.5290 0.0041890
2.9.3 IFN24 Granier 458 0.0229485 0.0421446 0.0191960 83.648118 0.0833227 363.0851 0.0003126
2.9.3 IFN24 Sperry 458 0.0229485 0.0375312 0.0145827 63.545181 0.0772080 336.4397 0.0002515

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 5.437764 5.799984 0.3622203 6.66120 16.77417 308.4755 0.0119841
2.9.3 IFN23 Sperry 496 5.437764 6.257897 0.8201326 15.08217 17.74264 326.2856 0.0000002
2.9.3 IFN34 Granier 522 3.058468 5.807781 2.7493135 89.89185 13.68525 447.4545 0.0013888
2.9.3 IFN34 Sperry 522 3.058468 6.761718 3.7032501 121.08187 14.68344 480.0913 0.0044491
2.9.3 IFN24 Granier 458 3.154621 5.925117 2.7704956 87.82340 11.33599 359.3455 0.0018194
2.9.3 IFN24 Sperry 458 3.154621 5.247110 2.0924889 66.33091 10.54285 334.2033 0.0000716

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 0.2708541 0.2873193 0.0164652 6.078993 0.2926359 108.0419 0.1853760
2.9.3 IFN23 Sperry 496 0.2708541 0.3020137 0.0311596 11.504194 0.3016487 111.3694 0.1860409
2.9.3 IFN34 Granier 522 0.1997108 0.2967895 0.0970786 48.609605 0.2905982 145.5095 0.2042864
2.9.3 IFN34 Sperry 522 0.1997108 0.3084545 0.1087437 54.450589 0.3127175 156.5852 0.2035943
2.9.3 IFN24 Granier 458 0.2462700 0.2894987 0.0432286 17.553350 0.2598092 105.4977 0.2161621
2.9.3 IFN24 Sperry 458 0.2462700 0.2967514 0.0504813 20.498358 0.2815493 114.3254 0.2159113

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 496 3.5114523 4.340299 0.8288472 23.60411 18.08350 514.9864 0.0140321
2.9.3 IFN23 Sperry 496 3.5114523 4.753245 1.2417922 35.36406 19.10260 544.0086 0.0002893
2.9.3 IFN34 Granier 522 0.5269553 4.165372 3.6384168 690.46019 16.13783 3062.4658 0.0000120
2.9.3 IFN34 Sperry 522 0.5269553 5.253547 4.7265918 896.96249 17.15675 3255.8255 0.0021526
2.9.3 IFN24 Granier 458 1.7337891 5.253321 3.5195323 202.99657 13.40961 773.4279 0.0039107
2.9.3 IFN24 Sperry 458 1.7337891 4.818449 3.0846596 177.91435 13.08821 754.8903 0.0013060

Pinus uncinata

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 2298 0.2008612 0.1165946 -0.0842666 -41.95267 0.1753474 87.29777 0.0355711
2.9.3 IFN23 Sperry 2298 0.2008612 0.1348837 -0.0659775 -32.84731 0.1662416 82.76441 0.0508878
2.9.3 IFN34 Granier 2848 0.1664953 0.1176723 -0.0488229 -29.32392 0.1388770 83.41200 0.0000613
2.9.3 IFN34 Sperry 2848 0.1664953 0.1380961 -0.0283991 -17.05703 0.1339936 80.47892 0.0010126
2.9.3 IFN24 Granier 2139 0.1814906 0.1149656 -0.0665250 -36.65481 0.1332196 73.40303 0.0179076
2.9.3 IFN24 Sperry 2139 0.1814906 0.1331151 -0.0483755 -26.65454 0.1238572 68.24440 0.0399330

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 2298 9.489485 5.975979 -3.513506 -37.02526 10.731454 113.08784 0.0620335
2.9.3 IFN23 Sperry 2298 9.489485 6.922512 -2.566972 -27.05070 10.536314 111.03146 0.0532495
2.9.3 IFN34 Granier 2848 10.630800 5.811764 -4.819036 -45.33089 11.135944 104.75171 0.0601085
2.9.3 IFN34 Sperry 2848 10.630800 6.858666 -3.772134 -35.48307 10.963954 103.13386 0.0327517
2.9.3 IFN24 Granier 2139 9.933420 5.700436 -4.232983 -42.61355 8.430390 84.86896 0.0893507
2.9.3 IFN24 Sperry 2139 9.933420 6.604616 -3.328804 -33.51116 8.154796 82.09454 0.0672899

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 0.2780166 0.1478584 -0.1301583 -46.81672 0.2028723 72.97128 0.6633819
2.9.3 IFN23 Sperry 149 0.2780166 0.1718108 -0.1062058 -38.20125 0.1816499 65.33778 0.6734270
2.9.3 IFN34 Granier 153 0.2624445 0.1755295 -0.0869150 -33.11748 0.1702353 64.86524 0.5805546
2.9.3 IFN34 Sperry 153 0.2624445 0.2069129 -0.0555317 -21.15940 0.1568397 59.76109 0.5600639
2.9.3 IFN24 Granier 149 0.2486968 0.1410802 -0.1076167 -43.27223 0.1635645 65.76864 0.7122247
2.9.3 IFN24 Sperry 149 0.2486968 0.1655975 -0.0830993 -33.41390 0.1399465 56.27193 0.7378589

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 0.0685725 0.0445654 -0.0240071 -35.00984 0.0958757 139.8165 0.3726499
2.9.3 IFN23 Sperry 149 0.0685725 0.0445654 -0.0240071 -35.00984 0.0958757 139.8165 0.3726499
2.9.3 IFN34 Granier 153 0.0827843 0.0542638 -0.0285206 -34.45164 0.1124489 135.8335 0.3414284
2.9.3 IFN34 Sperry 153 0.0827843 0.0542637 -0.0285206 -34.45174 0.1124489 135.8335 0.3414283
2.9.3 IFN24 Granier 149 0.0703331 0.0436521 -0.0266811 -37.93527 0.0849146 120.7321 0.4958553
2.9.3 IFN24 Sperry 149 0.0703331 0.0436509 -0.0266823 -37.93700 0.0849152 120.7328 0.4958532

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 2.258640 1.326188 -0.9324525 -41.28380 3.896957 172.5355 0.2854984
2.9.3 IFN23 Sperry 149 2.258640 1.326188 -0.9324525 -41.28380 3.896957 172.5355 0.2854984
2.9.3 IFN34 Granier 153 2.666283 1.529639 -1.1366437 -42.63027 4.388343 164.5865 0.2244071
2.9.3 IFN34 Sperry 153 2.666283 1.529637 -1.1366460 -42.63036 4.388343 164.5865 0.2244072
2.9.3 IFN24 Granier 149 1.014270 1.299109 0.2848390 28.08314 1.674879 165.1314 0.2571726
2.9.3 IFN24 Sperry 149 1.014270 1.299084 0.2848132 28.08060 1.674887 165.1322 0.2571642

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 0.0451890 0.0436020 -0.0015870 -3.512019 0.1276956 282.5809 0.0019019
2.9.3 IFN23 Sperry 149 0.0451890 0.0529501 0.0077611 17.174688 0.1448776 320.6035 0.0249639
2.9.3 IFN34 Granier 153 0.0360767 0.0591179 0.0230412 63.867221 0.1022087 283.3092 0.0031524
2.9.3 IFN34 Sperry 153 0.0360767 0.0489456 0.0128689 35.670788 0.1078549 298.9598 0.0160268
2.9.3 IFN24 Granier 149 0.0342135 0.0616488 0.0274353 80.188432 0.0930687 272.0231 0.0000237
2.9.3 IFN24 Sperry 149 0.0342135 0.0679221 0.0337086 98.524189 0.1008855 294.8704 0.0000521

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 6.502543 8.077732 1.575189 24.22419 19.45573 299.2019 0.0004271
2.9.3 IFN23 Sperry 149 6.502543 9.367002 2.864459 44.05136 22.29634 342.8864 0.0217672
2.9.3 IFN34 Granier 153 5.197995 10.370444 5.172449 99.50855 17.00899 327.2222 0.0011182
2.9.3 IFN34 Sperry 153 5.197995 8.792194 3.594199 69.14588 17.77441 341.9474 0.0165833
2.9.3 IFN24 Granier 149 4.559891 9.596791 5.036899 110.46095 13.89822 304.7929 0.0000350
2.9.3 IFN24 Sperry 149 4.559891 9.943037 5.383145 118.05424 14.63174 320.8792 0.0027967

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 0.2853119 0.1504279 -0.1348840 -47.27598 0.3434424 120.37437 0.0895452
2.9.3 IFN23 Sperry 149 0.2853119 0.1844778 -0.1008340 -35.34168 0.3324430 116.51916 0.0988443
2.9.3 IFN34 Granier 153 0.2425902 0.1851561 -0.0574341 -23.67536 0.2754404 113.54141 0.0584804
2.9.3 IFN34 Sperry 153 0.2425902 0.2075603 -0.0350300 -14.43997 0.2787098 114.88915 0.0571897
2.9.3 IFN24 Granier 149 0.2721022 0.1664745 -0.1056277 -38.81912 0.2757251 101.33146 0.1187840
2.9.3 IFN24 Sperry 149 0.2721022 0.1998686 -0.0722336 -26.54651 0.2687846 98.78074 0.1114735

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 149 5.849145 6.751544 0.902399 15.42788 22.61941 386.7131 0.0004506
2.9.3 IFN23 Sperry 149 5.849145 8.040814 2.191669 37.46990 25.06728 428.5631 0.0077463
2.9.3 IFN34 Granier 153 4.220601 8.840805 4.620203 109.46789 19.24872 456.0658 0.0103830
2.9.3 IFN34 Sperry 153 4.220601 7.262557 3.041956 72.07399 20.68930 490.1979 0.0088353
2.9.3 IFN24 Granier 149 5.007985 8.297681 3.289696 65.68902 15.62815 312.0647 0.0000220
2.9.3 IFN24 Sperry 149 5.007985 8.726725 3.718740 74.25621 16.32875 326.0542 0.0020819

Quercus faginea

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1135 0.2083410 0.1928031 -0.0155379 -7.457921 0.1413544 67.84765 0.0557608
2.9.3 IFN23 Sperry 1135 0.2083410 0.2174100 0.0090691 4.353002 0.1395385 66.97602 0.0378643
2.9.3 IFN34 Granier 579 0.1310169 0.1373183 0.0063015 4.809652 0.1112301 84.89752 0.0529122
2.9.3 IFN34 Sperry 579 0.1310169 0.1902449 0.0592280 45.206411 0.1191519 90.94393 0.0520712
2.9.3 IFN24 Granier 1037 0.1734577 0.1571122 -0.0163455 -9.423332 0.1125941 64.91160 0.0628440
2.9.3 IFN24 Sperry 1037 0.1734577 0.1967670 0.0233093 13.438054 0.1135029 65.43553 0.0267260

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1135 8.282914 6.103908 -2.1790055 -26.30723 11.354373 137.0819 0.0048432
2.9.3 IFN23 Sperry 1135 8.282914 7.221045 -1.0618686 -12.81999 11.297277 136.3925 0.0039801
2.9.3 IFN34 Granier 579 3.700627 4.410598 0.7099711 19.18516 9.304260 251.4239 0.0003450
2.9.3 IFN34 Sperry 579 3.700627 6.641037 2.9404102 79.45709 9.570765 258.6255 0.0133455
2.9.3 IFN24 Granier 1037 5.696068 4.800268 -0.8958010 -15.72665 8.253095 144.8911 0.0057538
2.9.3 IFN24 Sperry 1037 5.696068 6.481332 0.7852636 13.78606 8.516075 149.5079 0.0014925

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 0.1094487 0.0986754 -0.0107733 -9.843221 0.0792618 72.41914 0.5779736
2.9.3 IFN23 Sperry 236 0.1094487 0.1196542 0.0102055 9.324453 0.0862592 78.81244 0.6155523
2.9.3 IFN34 Granier 127 0.0643630 0.0659891 0.0016260 2.526356 0.0598727 93.02339 0.5888888
2.9.3 IFN34 Sperry 127 0.0643630 0.0989198 0.0345568 53.690372 0.0816951 126.92855 0.7058045
2.9.3 IFN24 Granier 210 0.1004444 0.0840434 -0.0164010 -16.328458 0.0733928 73.06811 0.5813009
2.9.3 IFN24 Sperry 210 0.1004444 0.1207059 0.0202615 20.171828 0.0963527 95.92638 0.5586032

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 0.0053933 0.0162797 0.0108864 201.85080 0.0566134 1049.6980 0.0024362
2.9.3 IFN23 Sperry 236 0.0053933 0.0038633 -0.0015300 -28.36931 0.0196835 364.9611 0.0478079
2.9.3 IFN34 Granier 127 0.0083747 0.0456468 0.0372721 445.05462 0.0915392 1093.0418 0.0696161
2.9.3 IFN34 Sperry 127 0.0083747 0.0036622 -0.0047125 -56.27095 0.0330105 394.1678 0.3055136
2.9.3 IFN24 Granier 210 0.0094895 0.0386425 0.0291531 307.21542 0.0711683 749.9722 0.2500400
2.9.3 IFN24 Sperry 210 0.0094895 0.0040936 -0.0053959 -56.86205 0.0228806 241.1165 0.2398281

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 0.6166907 1.7984542 1.1817635 191.62985 7.460526 1209.7678 0.0045494
2.9.3 IFN23 Sperry 236 0.6166907 0.2658720 -0.3508188 -56.88731 2.664029 431.9879 0.0434564
2.9.3 IFN34 Granier 127 0.5766980 4.5915801 4.0148821 696.18453 8.995680 1559.8598 0.2849624
2.9.3 IFN34 Sperry 127 0.5766980 0.2395559 -0.3371421 -58.46077 2.228779 386.4724 0.2476570
2.9.3 IFN24 Granier 210 0.4865583 3.8358466 3.3492883 688.36320 7.747200 1592.2450 0.5504167
2.9.3 IFN24 Sperry 210 0.4865583 0.2804434 -0.2061149 -42.36181 1.474803 303.1093 0.3610187

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 0.0130634 0.0211669 0.0081036 62.03285 0.0749454 573.7062 0.0043294
2.9.3 IFN23 Sperry 236 0.0130634 0.0389798 0.0259164 198.38992 0.0988565 756.7461 0.0069505
2.9.3 IFN34 Granier 127 0.0037973 0.0142598 0.0104625 275.52332 0.0446746 1176.4763 0.0045210
2.9.3 IFN34 Sperry 127 0.0037973 0.0298458 0.0260485 685.96971 0.0661975 1743.2693 0.0003844
2.9.3 IFN24 Granier 210 0.0063430 0.0176933 0.0113503 178.94096 0.0449992 709.4281 0.0184554
2.9.3 IFN24 Sperry 210 0.0063430 0.0427215 0.0363784 573.51892 0.0799063 1259.7516 0.0075581

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 2.0885510 4.139675 2.051124 98.20801 13.538888 648.2431 0.0052365
2.9.3 IFN23 Sperry 236 2.0885510 6.859938 4.771387 228.45441 16.902136 809.2757 0.0077781
2.9.3 IFN34 Granier 127 0.7143175 2.944675 2.230358 312.23624 9.121483 1276.9508 0.0045633
2.9.3 IFN34 Sperry 127 0.7143175 5.184057 4.469740 625.73575 11.036892 1545.0962 0.0010823
2.9.3 IFN24 Granier 210 0.9174718 3.024347 2.106875 229.63919 7.077724 771.4378 0.0175663
2.9.3 IFN24 Sperry 210 0.9174718 6.302964 5.385492 586.99265 11.415748 1244.2615 0.0055690

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 -0.1692768 0.1026599 0.2719366 160.6462 0.5161274 304.9015 0.0662988
2.9.3 IFN23 Sperry 236 -0.1692768 0.1562227 0.3254994 192.2883 0.5924392 349.9825 0.3189295
2.9.3 IFN34 Granier 127 -0.1670882 0.0295985 0.1966867 117.7143 0.4001682 239.4952 0.0530578
2.9.3 IFN34 Sperry 127 -0.1670882 0.1268826 0.2939708 175.9375 0.5055027 302.5365 0.5773309
2.9.3 IFN24 Granier 210 -0.0772680 0.0539988 0.1312669 169.8851 0.2550247 330.0521 0.0086278
2.9.3 IFN24 Sperry 210 -0.0772680 0.1725817 0.2498497 323.3546 0.4044669 523.4598 0.3110973

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 236 -12.702170 2.3412212 15.043391 118.43166 32.40450 255.1100 0.0609177
2.9.3 IFN23 Sperry 236 -12.702170 6.5940659 19.296235 151.91291 38.03304 299.4216 0.0053558
2.9.3 IFN34 Granier 127 -11.564537 -1.6469046 9.917632 85.75901 22.28675 192.7163 0.1710288
2.9.3 IFN34 Sperry 127 -11.564537 4.9445013 16.509038 142.75572 29.30423 253.3973 0.0096475
2.9.3 IFN24 Granier 210 -6.818172 -0.8115001 6.006672 88.09798 12.86559 188.6955 0.3409367
2.9.3 IFN24 Sperry 210 -6.818172 6.5796198 13.397791 196.50124 21.76772 319.2604 0.0102316

Quercus ilex

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 3918 0.1489045 0.1772410 0.0283365 19.03001 0.1104943 74.20480 0.0672058
2.9.3 IFN23 Sperry 3918 0.1489045 0.2026040 0.0536995 36.06308 0.1204250 80.87402 0.0369690
2.9.3 IFN34 Granier 5772 0.1105881 0.1519348 0.0413467 37.38798 0.0989712 89.49537 0.0712142
2.9.3 IFN34 Sperry 5772 0.1105881 0.1825545 0.0719664 65.07606 0.1150158 104.00373 0.0332283
2.9.3 IFN24 Granier 3693 0.1291420 0.1565345 0.0273925 21.21115 0.0888028 68.76371 0.0915264
2.9.3 IFN24 Sperry 3693 0.1291420 0.1886585 0.0595165 46.08612 0.1050948 81.37924 0.0378757

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 3918 5.950905 5.642813 -0.3080921 -5.177231 7.874177 132.3190 0.0088152
2.9.3 IFN23 Sperry 3918 5.950905 6.636050 0.6851446 11.513284 8.011895 134.6332 0.0064293
2.9.3 IFN34 Granier 5772 3.782069 4.621783 0.8397141 22.202507 8.239339 217.8527 0.0047156
2.9.3 IFN34 Sperry 5772 3.782069 5.841157 2.0590879 54.443425 8.600617 227.4051 0.0023248
2.9.3 IFN24 Granier 3693 4.747147 4.844661 0.0975141 2.054162 5.859919 123.4408 0.0043054
2.9.3 IFN24 Sperry 3693 4.747147 6.054492 1.3073446 27.539582 6.211643 130.8500 0.0014173

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 0.1431107 0.1715542 0.0284435 19.87518 0.0901055 62.96212 0.7222836
2.9.3 IFN23 Sperry 524 0.1431107 0.2040681 0.0609574 42.59458 0.1261918 88.17775 0.7398702
2.9.3 IFN34 Granier 610 0.1234432 0.1705182 0.0470749 38.13488 0.1078005 87.32802 0.6474181
2.9.3 IFN34 Sperry 610 0.1234432 0.2199635 0.0965203 78.19004 0.1724030 139.66175 0.6802270
2.9.3 IFN24 Granier 489 0.1323631 0.1618460 0.0294829 22.27426 0.0822241 62.12009 0.7369705
2.9.3 IFN24 Sperry 489 0.1323631 0.2108111 0.0784480 59.26724 0.1458464 110.18660 0.7400181

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 0.0059090 0.0110158 0.0051068 86.423533 0.0356261 602.9080 0.0242889
2.9.3 IFN23 Sperry 524 0.0059090 0.0057865 -0.0001226 -2.074552 0.0220340 372.8867 0.0282856
2.9.3 IFN34 Granier 610 0.0154508 0.0232249 0.0077741 50.315324 0.0799641 517.5393 0.0766743
2.9.3 IFN34 Sperry 610 0.0154508 0.0074214 -0.0080294 -51.967317 0.0406859 263.3250 0.1086174
2.9.3 IFN24 Granier 489 0.0096707 0.0173101 0.0076394 78.995294 0.0428467 443.0568 0.0795685
2.9.3 IFN24 Sperry 489 0.0096707 0.0063043 -0.0033664 -34.810068 0.0214081 221.3704 0.0989045

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 0.7206350 1.1965779 0.4759430 66.04494 4.545020 630.6966 0.0189368
2.9.3 IFN23 Sperry 524 0.7206350 0.5343830 -0.1862520 -25.84554 2.922075 405.4862 0.0287007
2.9.3 IFN34 Granier 610 1.7657018 2.4653587 0.6996569 39.62486 8.753283 495.7396 0.0782386
2.9.3 IFN34 Sperry 610 1.7657018 0.6222751 -1.1434267 -64.75763 5.258866 297.8343 0.0839876
2.9.3 IFN24 Granier 489 0.6802705 1.9473077 1.2670373 186.25492 5.102462 750.0637 0.0916957
2.9.3 IFN24 Sperry 489 0.6802705 0.5938822 -0.0863883 -12.69911 2.177322 320.0671 0.0313045

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 0.0872894 0.0548725 -0.0324169 -37.13724 0.1518624 173.9757 0.0000814
2.9.3 IFN23 Sperry 524 0.0872894 0.0638605 -0.0234289 -26.84044 0.1573253 180.2341 0.0000000
2.9.3 IFN34 Granier 610 0.0744236 0.0477143 -0.0267093 -35.88823 0.1375123 184.7697 0.0000190
2.9.3 IFN34 Sperry 610 0.0744236 0.0635388 -0.0108848 -14.62552 0.1393336 187.2169 0.0007798
2.9.3 IFN24 Granier 489 0.0917714 0.0472976 -0.0444738 -48.46153 0.1348858 146.9802 0.0035816
2.9.3 IFN24 Sperry 489 0.0917714 0.0694314 -0.0223400 -24.34308 0.1353008 147.4324 0.0057408

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 14.68018 10.267661 -4.412520 -30.05767 26.45366 180.1998 0.0000534
2.9.3 IFN23 Sperry 524 14.68018 11.142326 -3.537855 -24.09953 26.97664 183.7623 0.0002184
2.9.3 IFN34 Granier 610 12.36190 8.961435 -3.400469 -27.50764 23.54030 190.4261 0.0004095
2.9.3 IFN34 Sperry 610 12.36190 11.052437 -1.309467 -10.59276 23.34720 188.8641 0.0002484
2.9.3 IFN24 Granier 489 13.71557 7.347157 -6.368415 -46.43200 20.47223 149.2627 0.0011983
2.9.3 IFN24 Sperry 489 13.71557 9.880980 -3.834592 -27.95795 19.76626 144.1155 0.0093615

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 0.2098339 0.2148253 0.0049913 2.378693 0.2024605 96.48605 0.2083278
2.9.3 IFN23 Sperry 524 0.2098339 0.2624308 0.0525969 25.065944 0.2216350 105.62400 0.2537251
2.9.3 IFN34 Granier 610 0.1902548 0.1946943 0.0044395 2.333441 0.2023414 106.35283 0.1825470
2.9.3 IFN34 Sperry 610 0.1902548 0.2796430 0.0893882 46.983423 0.2426749 127.55257 0.2318815
2.9.3 IFN24 Granier 489 0.2215166 0.1903221 -0.0311946 -14.082264 0.1807040 81.57580 0.2241293
2.9.3 IFN24 Sperry 489 0.2215166 0.2862463 0.0647297 29.221159 0.2227084 100.53802 0.2436730

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 524 13.10901 9.071083 -4.0379219 -30.802657 27.63769 210.8298 0.0004681
2.9.3 IFN23 Sperry 524 13.10901 10.607943 -2.5010625 -19.078965 27.40938 209.0882 0.0002017
2.9.3 IFN34 Granier 610 10.94218 6.496076 -4.4461051 -40.632712 26.06156 238.1751 0.0016049
2.9.3 IFN34 Sperry 610 10.94218 10.430162 -0.5120195 -4.679318 24.81450 226.7783 0.0004097
2.9.3 IFN24 Granier 489 12.82621 5.477479 -7.3487353 -57.294656 21.88869 170.6559 0.0088750
2.9.3 IFN24 Sperry 489 12.82621 9.900998 -2.9252166 -22.806547 20.53866 160.1303 0.0061626

Quercus pubescens

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 256 0.2601437 0.2219477 -0.0381960 -14.68266 0.1643263 63.16751 0.1560524
2.9.3 IFN23 Sperry 256 0.2601437 0.1817317 -0.0784120 -30.14179 0.1791726 68.87446 0.1454331
2.9.3 IFN34 Granier 1936 0.1457380 0.1643728 0.0186348 12.78651 0.1209050 82.96049 0.0562826
2.9.3 IFN34 Sperry 1936 0.1457380 0.1976329 0.0518949 35.60834 0.1298686 89.11099 0.0183239
2.9.3 IFN24 Granier 236 0.2305138 0.1781990 -0.0523148 -22.69486 0.1607156 69.72060 0.1334099
2.9.3 IFN24 Sperry 236 0.2305138 0.1356624 -0.0948515 -41.14785 0.1762379 76.45438 0.1678664

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 256 11.922826 7.102031 -4.820796 -40.43333 15.139792 126.9816 0.0060401
2.9.3 IFN23 Sperry 256 11.922826 5.558861 -6.363965 -53.37631 15.687586 131.5761 0.0030231
2.9.3 IFN34 Granier 1936 3.860419 5.965957 2.105538 54.54170 11.383103 294.8670 0.0097857
2.9.3 IFN34 Sperry 1936 3.860419 7.723379 3.862960 100.06582 11.902783 308.3288 0.0096279
2.9.3 IFN24 Granier 236 9.232653 5.507702 -3.724951 -40.34540 9.322255 100.9705 0.0343227
2.9.3 IFN24 Sperry 236 9.232653 3.895550 -5.337103 -57.80682 10.317613 111.7513 0.0039732

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 0.0891238 0.0730349 -0.0160889 -18.052257 0.0614658 68.96674 0.6522246
2.9.3 IFN23 Sperry 79 0.0891238 0.0601712 -0.0289525 -32.485774 0.0706159 79.23352 0.6261577
2.9.3 IFN34 Granier 318 0.0901147 0.0974983 0.0073836 8.193565 0.0635313 70.50045 0.6635464
2.9.3 IFN34 Sperry 318 0.0901147 0.1318315 0.0417168 46.292963 0.0981401 108.90569 0.6820725
2.9.3 IFN24 Granier 76 0.0776113 0.0571347 -0.0204766 -26.383541 0.0590280 76.05599 0.5761773
2.9.3 IFN24 Sperry 76 0.0776113 0.0438234 -0.0337879 -43.534779 0.0717880 92.49685 0.4501398

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 0.0058549 0.0117108 0.0058558 100.015681 0.0379150 647.5750 0.0018919
2.9.3 IFN23 Sperry 79 0.0058549 0.0062388 0.0003839 6.556739 0.0233459 398.7403 0.0004846
2.9.3 IFN34 Granier 318 0.0101969 0.0377162 0.0275193 269.878600 0.0924166 906.3194 0.1619447
2.9.3 IFN34 Sperry 318 0.0101969 0.0051749 -0.0050220 -49.250433 0.0267774 262.6031 0.2180495
2.9.3 IFN24 Granier 76 0.0065697 0.0175178 0.0109480 166.643036 0.0460452 700.8685 0.0013526
2.9.3 IFN24 Sperry 76 0.0065697 0.0090813 0.0025116 38.229329 0.0221145 336.6117 0.0086960

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 0.6973683 1.1357761 0.4384078 62.86604 4.893603 701.7244 0.0039247
2.9.3 IFN23 Sperry 79 0.6973683 0.5127621 -0.1846062 -26.47184 2.931821 420.4122 0.0005366
2.9.3 IFN34 Granier 318 1.0071161 4.0602707 3.0531546 303.15816 10.229095 1015.6818 0.2931612
2.9.3 IFN34 Sperry 318 1.0071161 0.3109872 -0.6961289 -69.12102 3.258376 323.5353 0.3351003
2.9.3 IFN24 Granier 76 0.1307881 1.8128972 1.6821090 1286.13297 5.776029 4416.3257 0.0003739
2.9.3 IFN24 Sperry 76 0.1307881 0.6057423 0.4749542 363.14784 1.358486 1038.6924 0.0031350

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 0.000000 0.0640595 0.0640595 Inf 0.1129618 Inf NA
2.9.3 IFN23 Sperry 79 0.000000 0.0517975 0.0517975 Inf 0.0987928 Inf NA
2.9.3 IFN34 Granier 318 0.022931 0.0250107 0.0020797 9.06932 0.0666660 290.7242 0.0108609
2.9.3 IFN34 Sperry 318 0.022931 0.0381563 0.0152252 66.39587 0.0822106 358.5129 0.0048009
2.9.3 IFN24 Granier 76 0.000000 0.0381625 0.0381625 Inf 0.0819286 Inf NA
2.9.3 IFN24 Sperry 76 0.000000 0.0441272 0.0441272 Inf 0.0741278 Inf NA

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 0.00000 12.664840 12.6648403 Inf 22.12580 Inf NA
2.9.3 IFN23 Sperry 79 0.00000 10.436225 10.4362247 Inf 19.67734 Inf NA
2.9.3 IFN34 Granier 318 3.79738 4.653572 0.8561915 22.54690 11.43664 301.1717 0.0126221
2.9.3 IFN34 Sperry 318 3.79738 6.348719 2.5513389 67.18681 13.28263 349.7841 0.0053325
2.9.3 IFN24 Granier 76 0.00000 6.895456 6.8954564 Inf 14.15673 Inf NA
2.9.3 IFN24 Sperry 76 0.00000 8.350982 8.3509816 Inf 14.12910 Inf NA

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 -0.2128612 0.1259154 0.3387766 159.15374 0.4329395 203.3905 0.0778531
2.9.3 IFN23 Sperry 79 -0.2128612 0.1066803 0.3195415 150.11728 0.4128702 193.9622 0.1773117
2.9.3 IFN34 Granier 318 0.0994825 0.0818858 -0.0175967 -17.68823 0.1524520 153.2450 0.1899403
2.9.3 IFN34 Sperry 318 0.0994825 0.1673866 0.0679040 68.25725 0.1643975 165.2526 0.2432266
2.9.3 IFN24 Granier 76 -0.1022525 0.0760209 0.1782734 174.34630 0.2351245 229.9450 0.0045565
2.9.3 IFN24 Sperry 76 -0.1022525 0.0843485 0.1866010 182.49047 0.2397396 234.4585 0.0500256

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 79 -13.481885 11.5290641 25.010949 185.51522 34.78344 258.0013 0.0203396
2.9.3 IFN23 Sperry 79 -13.481885 9.9234627 23.405348 173.60590 33.95803 251.8789 0.0030670
2.9.3 IFN34 Granier 318 2.610030 0.5933012 -2.016729 -77.26841 15.49942 593.8408 0.0571170
2.9.3 IFN34 Sperry 318 2.610030 6.0377320 3.427702 131.32808 14.29634 547.7464 0.0004613
2.9.3 IFN24 Granier 76 -6.282228 5.0825592 11.364787 180.90377 18.20315 289.7563 0.0854851
2.9.3 IFN24 Sperry 76 -6.282228 7.9211333 14.203361 226.08796 19.86664 316.2356 0.0053125

Quercus suber

Annual diameter increment

Prediction ability for diameter increase (cm/yr) of surviving trees:
version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1243 0.1410210 0.2068347 0.0658137 46.66945 0.1669355 118.37631 0.0088297
2.9.3 IFN23 Sperry 1243 0.1410210 0.2014637 0.0604427 42.86077 0.1678270 119.00850 0.0071823
2.9.3 IFN34 Granier 1427 0.1346440 0.1886441 0.0540001 40.10588 0.1454577 108.03138 0.0001814
2.9.3 IFN34 Sperry 1427 0.1346440 0.1482393 0.0135953 10.09724 0.1489167 110.60031 0.0002041
2.9.3 IFN24 Granier 1142 0.1398422 0.1876579 0.0478158 34.19266 0.1202655 86.00090 0.0069571
2.9.3 IFN24 Sperry 1142 0.1398422 0.1689032 0.0290610 20.78129 0.1213699 86.79063 0.0050891

Annual height increment

Prediction ability for height increase (cm/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 1243 4.260807 6.553254 2.292448 53.80313 7.174093 168.3740 0.0095388
2.9.3 IFN23 Sperry 1243 4.260807 6.470349 2.209542 51.85737 7.284835 170.9731 0.0087024
2.9.3 IFN34 Granier 1427 2.408686 5.994964 3.586277 148.88933 9.121639 378.6977 0.0067776
2.9.3 IFN34 Sperry 1427 2.408686 4.785585 2.376898 98.68028 8.859291 367.8059 0.0117383
2.9.3 IFN24 Granier 1142 3.200462 5.834757 2.634295 82.30983 5.927453 185.2062 0.0094382
2.9.3 IFN24 Sperry 1142 3.200462 5.456965 2.256503 70.50553 6.076619 189.8669 0.0049343

Growth basal area increment

Prediction ability for basal area increase due to growth (m2/ha/yr) of surviving trees:

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 0.1162374 0.1617277 0.0454903 39.135692 0.1127966 97.03986 0.4942661
2.9.3 IFN23 Sperry 147 0.1162374 0.1596585 0.0434211 37.355530 0.1188924 102.28417 0.4631770
2.9.3 IFN34 Granier 150 0.1211765 0.1615544 0.0403779 33.321578 0.1066299 87.99555 0.5060840
2.9.3 IFN34 Sperry 150 0.1211765 0.1293733 0.0081968 6.764307 0.1180207 97.39567 0.3177576
2.9.3 IFN24 Granier 144 0.1133569 0.1423114 0.0289545 25.542776 0.0923422 81.46148 0.5237030
2.9.3 IFN24 Sperry 144 0.1133569 0.1328259 0.0194690 17.174984 0.1032834 91.11345 0.4534160

Mortality

Prediction ability for basal area decrease due to mortality (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 0.0103218 0.0176510 0.0073292 71.00680 0.0337549 327.0247 0.0544494
2.9.3 IFN23 Sperry 147 0.0103218 0.0176502 0.0073284 70.99938 0.0337546 327.0224 0.0544544
2.9.3 IFN34 Granier 150 0.0392110 0.0308408 -0.0083703 -21.34667 0.0750039 191.2825 0.1497010
2.9.3 IFN34 Sperry 150 0.0392110 0.0215520 -0.0176591 -45.03592 0.0760461 193.9404 0.2275668
2.9.3 IFN24 Granier 144 0.0217277 0.0316763 0.0099486 45.78772 0.0518129 238.4647 0.1317459
2.9.3 IFN24 Sperry 144 0.0217277 0.0173618 -0.0043659 -20.09357 0.0369309 169.9715 0.2237142

Prediction ability for density decrease due to mortality (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 0.5610858 0.7709766 0.2098909 37.40798 2.219966 395.6553 0.0937794
2.9.3 IFN23 Sperry 147 0.5610858 0.7709625 0.2098767 37.40546 2.219965 395.6551 0.0937797
2.9.3 IFN34 Granier 150 2.2370471 1.8490620 -0.3879851 -17.34363 5.463273 244.2181 0.1666712
2.9.3 IFN34 Sperry 150 2.2370471 0.8918259 -1.3452212 -60.13379 5.496417 245.6997 0.2689673
2.9.3 IFN24 Granier 144 0.9504470 2.4098230 1.4593760 153.54628 5.139984 540.7965 0.1498226
2.9.3 IFN24 Sperry 144 0.9504470 0.7626415 -0.1878055 -19.75970 2.503221 263.3731 0.2179537

Ingrowth

Prediction ability for basal area increase due to ingrowth (m2/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 0.0307680 0.0125718 -0.0181963 -59.14012 0.0807822 262.5525 0.0013783
2.9.3 IFN23 Sperry 147 0.0307680 0.0124342 -0.0183338 -59.58720 0.0760801 247.2698 0.0413383
2.9.3 IFN34 Granier 150 0.0152949 0.0120131 -0.0032818 -21.45651 0.0542093 354.4270 0.0046299
2.9.3 IFN34 Sperry 150 0.0152949 0.0064306 -0.0088643 -57.95570 0.0492969 322.3092 0.0022936
2.9.3 IFN24 Granier 144 0.0198601 0.0076898 -0.0121703 -61.27995 0.0430578 216.8054 0.0323280
2.9.3 IFN24 Sperry 144 0.0198601 0.0092591 -0.0106010 -53.37823 0.0511043 257.3215 0.0085565

Prediction ability for density increase due to ingrowth (ind/ha/yr):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 4.493781 2.243367 -2.2504136 -50.07840 11.793168 262.4331 0.0003354
2.9.3 IFN23 Sperry 147 4.493781 2.160479 -2.3333020 -51.92292 10.832612 241.0579 0.0439688
2.9.3 IFN34 Granier 150 2.243832 2.019427 -0.2244055 -10.00099 7.909450 352.4974 0.0026081
2.9.3 IFN34 Sperry 150 2.243832 1.091775 -1.1520572 -51.34329 7.053376 314.3451 0.0021810
2.9.3 IFN24 Granier 144 2.642877 1.171964 -1.4709131 -55.65576 5.800612 219.4810 0.0185027
2.9.3 IFN24 Sperry 144 2.642877 1.246779 -1.3960978 -52.82493 6.561238 248.2612 0.0154725

Overall basal area changes

Prediction ability for overall basal area changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 0.1361603 0.1542198 0.0180595 13.263400 0.1437150 105.5483 0.2196664
2.9.3 IFN23 Sperry 147 0.1361603 0.1524657 0.0163054 11.975129 0.1572964 115.5229 0.1748304
2.9.3 IFN34 Granier 150 0.0981880 0.1471210 0.0489329 49.835940 0.1671329 170.2172 0.1280634
2.9.3 IFN34 Sperry 150 0.0981880 0.1215039 0.0233159 23.746146 0.1769179 180.1828 0.0632521
2.9.3 IFN24 Granier 144 0.1219790 0.1118721 -0.0101069 -8.285783 0.1262743 103.5213 0.1818564
2.9.3 IFN24 Sperry 144 0.1219790 0.1297381 0.0077591 6.360996 0.1418344 116.2777 0.1887382

Predictive capacity plots (IFN2-IFN4):

Relationship between basal area changes and climatic variables (MAT and P/PET; IFN2-IFN4):

Spatial distribution of errors (IFN2-IFN4):

Prediction ability for overall density changes (including growth, mortality and ingrowth):

version period transpirationMode n Obs Pred Bias Biasrel RMSE RMSErel R2
2.9.3 IFN23 Granier 147 3.8521751 1.4723905 -2.3797846 -61.77769 11.902571 308.9831 0.0110541
2.9.3 IFN23 Sperry 147 3.8521751 1.3895162 -2.4626589 -63.92905 11.288250 293.0357 0.0431200
2.9.3 IFN34 Granier 150 -0.3761505 0.1703646 0.5465151 145.29160 10.689872 2841.9132 0.0096702
2.9.3 IFN34 Sperry 150 -0.3761505 0.1999490 0.5760995 153.15663 9.380709 2493.8708 0.0144818
2.9.3 IFN24 Granier 144 1.6882040 -1.2374874 -2.9256914 -173.30201 8.087096 479.0355 0.0541903
2.9.3 IFN24 Sperry 144 1.6882040 0.5320192 -1.1561847 -68.48608 7.363092 436.1494 0.0016765