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Table 4 Criteria for selecting linear regression models to biomass estimation of some woody species inigenous in the Atlantic Rain Forest, Brazil

From: Selection criteria for linear regression models to estimate individual tree biomasses in the Atlantic Rain Forest, Brazil

Data set

Model

SSR

\( R^{2}_{adj.} \)

Syx

Syx%

AIC

BIC

1. M. skvortzovii growing in natural forest (biomass in kg)

1

0.048772 (3)

0.8958 (3)

0.0417 (3)

16.02 (3)

− 185.73 (3)

− 182.45 (3)

2

0.038193 (1)

0.9184 (1)

0.0369 (1)

14.17 (1)

− 193.07 (1)

− 189.79 (1)

3

0.055108 (4)

0.8823 (4)

0.0444 (4)

17.02 (4)

− 182.07 (4)

− 178.79 (4)

4

0.057474 (5)

0.8727 (5)

0.0461 (5)

17.71 (5)

− 178.13 (5)

− 174.12 (5)

5

0.063102 (6)

0.8652 (6)

0.0475 (6)

18.22 (6)

− 178.00 (6)

− 174.72 (6)

6

0.039924 (2)

0.9147 (2)

0.0378 (2)

14.49 (2)

− 191.74 (2)

− 188.46 (2)

2. M. skvortzovii growing in natural forest (biomass in g)

1

48,772 (3)

0.8958 (3)

41.74 (3)

16.02 (3)

228.73 (3)

232.02 (3)

2

38,193 (1)

0.9184 (1)

36.93 (1)

14.17 (1)

221.40 (1)

224.68 (1)

3

55,108 (4)

0.8823 (4)

44.36 (4)

17.02 (4)

232.40 (4)

235.68 (4)

4

57,474 (5)

0.8727 (5)

46.14 (5)

17.71 (5)

236.34 (5)

240.34 (5)

5

63,102 (6)

0.8652 (6)

47.47 (2)

18.22 (6)

236.46 (6)

239.74 (6)

6

39,924 (2)

0.9147 (2)

37.76 (6)

14.49 (2)

222.73 (2)

226.01 (2)

3. Native mixed-species natural stand

1

5,422,069 (3)

0.9079 (3)

440.05 (3)

29.47 (3)

370.07 (3)

373.35 (3)

2

4,300,629 (2)

0.9269 (2)

391.91 (2)

26.25 (2)

363.35 (2)

366.40 (2)

3

6,385,976 (5)

0.8915 (5)

477.57 (5)

31.98 (5)

374.98 (5)

378.26 (5)

4

6,702,675 (6)

0.8819 (6)

498.24 (6)

33.37 (6)

379.10 (6)

383.11 (6)

5

6,002,299 (4)

0.8980 (4)

463.00 (4)

31.01 (4)

373.12 (4)

376.40 (4) 

6

3,228,136 (1)

0.9452 (1)

339.54 (1)

22.74 (1)

354.51 (1)

357.79 (1)

4. Native mixed restoration plantation (complete series)

1

24,955 (4)

0.7539 (4)

11.84 (4)

69.87 (4)

891.74 (4)

898.12 (4)

2

25,745 (5)

0.7461 (5)

12.03 (5)

70.96 (5)

897.34 (5)

903.73 (5)

3

28,006 (6)

0.7238 (6)

12.54 (6)

74.02 (6)

912.50 (6)

918.89 (6)

4

19,337 (1)

0.8082 (1)

10.45 (1)

61.67 (1)

847.82 (1)

857.40 (1)

5

21,009 (2)

0.7928 (2)

10.86 (2)

64.11 (2)

860.76 (2)

867.14 (2)

6

24,333 (3)

0.7601 (3)

11.69 (3)

68.99 (3)

887.19 (3)

893.58 (3)

5. Native mixed-species restoration plantation (Reduced series without outliers)

1

7307 (2)

0.7778 (1)

15.25 (1)

25.58 (1)

168.35 (1)

171.63 (1)

2

8274 (3)

0.7219 (3)

17.06 (3)

28.61 (3)

175.07 (3)

178.36 (3)

3

9034 (6)

0.6912 (4)

17.98 (4)

30.15 (4)

178.22 (4)

181.50 (4)

4

8402 (4)

0.6556 (5)

19.33 (5)

32.41 (5)

178.27 (5)

182.07 (5)

5

8950 (5)

0.6492 (6)

19.51 (6)

32.70 (6)

177.19 (6)

180.33 (6)

6

7070 (1)

0.7363 (2)

16.62 (2)

27.86 (2)

173.48 (2)

176.76 (2)

6. Native mixed-species restoration plantation (reduced series with outliers)

1

6516 (1)

0.4590 (2)

16.15 (2)

37.22 (2)

171.79 (2)

175.07 (2)

2

8154 (3)

0.3874 (3)

17.19 (3)

39.61 (3)

175.51 (3)

178.79 (3)

3

9054 (4)

0.3312 (6)

17.96 (6)

41.38 (6)

178.15 (5)

181.43 (4)

4

9713 (5)

0.3549 (4)

17.64 (4)

40.64 (4)

178.65 (6)

182.66 (6)

5

10,274 (6)

0.3374 (5)

17.88 (5)

41.19 (5)

177.87 (4)

181.15 (5)

6

7732 (2)

0.4766 (1)

15.89 (1)

36.61 (1)

170.79 (1)

174.07 (1)

  1. Number in parenthesis represent the ranking for the best fitting models
  2. SSR sum of squared residuals, \( R^{2}_{adj.} \) adjusted coefficient of determination, Syx residual standard deviation, Syx% residual standard deviation in percentage, AIC Akaike information criterion, BIC Schwartz’s information criterion