Table. 3.

Parameter estimates and model performance statistics of each model for different components of trees (stem, branch, foliage, and total above ground tree biomass) for twelve tree species

Biomass component Model Parameter estimates Model performance statistics
α SE β1 SE β2 SE β3 SE RMSE R2 Adj-R2 AIC SBC
AGBStem 1 –1.3994 0.2264 1.5387 0.0916 0.47 0.73 0.73 –44.04 –131.04
2 –1.6520 0.1936 0.6715 0.0320 0.39 0.81 0.81 –74.48 –161.48
3 –2.7620 0.2719 1.0695 0.0565 0.42 0.78 0.78 –61.35 –148.35
4 –2.0187 0.2430 1.0729 0.1258 1.0633 0.2127 0.42 0.78 0.78 –59.56 –144.06
5 –1.5288 0.2226 1.1163 0.1574 0.7037 0.2168 0.43 0.77 0.77 –56.86 –141.36
6 –2.0010 0.2419 0.9225 0.1570 0.3543 0.2235 0.9212 0.2298 0.41 0.79 0.79 –62.78 –144.78
7α –1.6919 0.1955 0.6063 0.0591 0.2602 0.1985 0.38b 0.82b 0.82b –77.29b –161.79b
8α –1.8296 0.2078 0.4814 0.0898 0.1751 0.2022 0.4059 0.2207 0.38b 0.83b 0.82b –79.27b –161.27b
9α –2.8544 0.2830 1.5033 0.1501 1.6775 0.3246 0.3872 0.1929 0.38b 0.82b 0.82b –76.85b –158.85b
AGBBranch 1 –114.7558 10.0734 61.3428 4.0425 20.96 0.67 0.67 641.61 554.61
2 –119.9720 9.4900 25.9467 1.5569 19.52 0.71 0.71 628.86 541.86
3 –168.8799 12.6504 42.5634 2.6089 19.04 0.73 0.72 624.39 537.39
4 –136.6919 11.2524 46.9626 5.4368 34.4510 9.1737 19.15 0.73 0.72 626.34 541.84
5 –121.4085 10.0591 45.8423 6.5831 26.8940 9.1595 19.34 0.72 0.71 628.18 543.68
6α –136.7456 11.1713 40.0727 6.7233 16.5493 9.6287 28.1061 9.8273 18.65b 0.74b 0.73b 622.60b 540.60b
7α –123.7342 9.5985 21.7083 2.6907 17.5747 9.1444 18.73b 0.74b 0.73b 622.36b 537.86b
8α –131.6154 10.1205 15.0013 4.0433 13.1760 9.2358 21.8506 9.9403 18.64b 0.74b 0.74b 622.45b 540.45b
9 –155.9457 13.4546 54.4668 6.9053 39.9823 14.8594 21.0635 8.9666 19.40 0.72 0.71 629.61 547.61
AGBFoliage 1 0.7843 0.3205 0.5706 0.1296 0.75 0.18 0.17 41.57 –45.43
2α 0.4326 0.3084 0.2926 0.0510 0.71b 0.25b 0.24b 33.07b –53.93b
3 0.3152 0.4175 0.3890 0.0867 0.75 0.18 0.17 41.37 –45.64
4 0.2056 0.4849 0.6048 0.2411 0.2853 0.4180 0.75 0.18 0.16 43.09 –41.41
5 0.2127 0.4040 0.1638 0.2695 0.9330 0.3600 0.72 0.24 0.22 36.88 –47.62
6 0.3593 0.4740 0.2083 0.2806 1.0499 0.4110 –0.2755 0.4610 0.73 0.24 0.21 38.50 –43.50
7α 0.3693 0.3114 0.1893 0.0942 0.4124 0.3163 0.71b 0.27b 0.25b 33.44b –51.06b
8 0.0561 0.4176 0.3297 0.1974 0.5111 0.3883 –0.2781 0.4468 0.71 0.27 0.24 35.04 –46.96
9α –0.9496 0.4234 0.5282 0.2246 2.3492 0.4857 0.4286 0.2886 0.67b 0.35b 0.33b 24.18b –57.83b
AGBTotal 1 –0.1108 0.2361 1.5765 0.0955 0.53 0.71 0.71 –21.56 –108.56
2 –0.3789 0.2017 0.6896 0.0333 0.44 0.80 0.79 –52.84 –139.84
3 –1.4200 0.2958 1.0775 0.0614 0.50 0.73 0.73 –29.37 –116.37
4 –0.5956 0.2632 1.2118 0.1363 0.8325 0.2304 0.50 0.74 0.73 –28.86 –113.36
5 –0.3013 0.2230 0.9545 0.1577 1.0361 0.2172 0.45 0.79 0.78 –47.56 –132.06
6 –0.5533 0.2524 0.8511 0.1638 0.8496 0.2331 0.4916 0.2397 0.45 0.79 0.78 –46.28 –128.28
7α –0.4699 0.1987 0.5410 0.0601 0.5932 0.2019 0.41b 0.83b 0.82b –65.60b –150.11b
8α –0.6207 0.2108 0.4041 0.0911 0.4999 0.2052 0.4446 0.2240 0.40b 0.83b 0.83b –67.43b –149.43b
9α –1.8245 0.2666 1.4358 0.1414 1.9921 0.3057 0.6154 0.1817 0.38b 0.86b 0.85b –80.68b –162.68b

α: constant; β1, β2, β3: fitted parameters; SE: standard error; RMSE: root mean square error; R2: coefficient of determination; AIC: Akaike information criterion; SBC: Schwarz Bayesian information Criterion; AGB: aboveground biomass.

aThe best-fit models.

bThe statistical values pivotal for the selection of the relevant regression model, which is more suitable for biomass prediction.
J Ecol Environ 2024;48:- https://doi.org/10.5141/jee.24.036
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