Generalized Models: An Application to Identify Environmental Variables That Significantly Affect the Abundance of Three Tree Species
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Variables and Sample
2.3. Data Analysis
3. Results
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Quercus macdougallii | AR | AST | ASP | ELEV | AI | GSP | MTCM | MTWM | FFP | SMRSPRPB | SPRP | |
Maximum | 48 | 90 | 9 | 2968 | 0.047 | 2144 | 13.5 | 18.5 | 364 | 5.9 | 168 | |
Minimum | 1 | 10 | 2 | 2001 | 0.014 | 1024 | 7.8 | 12.1 | 208 | 5.2 | 84 | |
SD | 14.4 | 28.1 | 2.4 | 530.3 | 0.009 | 432 | 2.3 | 3 | 65.5 | 1 | 33.6 | |
Mean | 17.6 | 32.3 | 6.9 | 2649.2 | 0.024 | 1615.5 | 9.6 | 13.8 | 264.7 | 5.6 | 129.8 | |
Pinus patula | AR | AST | ASP | ELEV | AI | MAP | GSP | MMIN | DD5 | D100 | SMRP | |
Maximum | 185 | 95 | 9 | 3002 | 0.047 | 3063 | 2220 | 7.4 | 3906 | 32 | 1019 | |
Minimum | 1 | 10 | 1 | 2001 | 0.013 | 1318 | 1022 | 2.9 | 1699 | 12 | 447 | |
SD | 29.7 | 23.5 | 2.5 | 224.4 | 0.007 | 441.1 | 304.2 | 0.9 | 403.3 | 4.5 | 145.6 | |
Mean | 21.8 | 38.4 | 5.9 | 2635.9 | 0.024 | 2140.1 | 1581.8 | 4.5 | 2322.8 | 22.1 | 709.7 | |
Pinus pseudostrobus | AR | AST | ASP | ELEV | AI | MAT | GSP | MTWM | MMAX | D100 | WINP | |
Maximum | 174 | 95 | 360 | 3002 | 0.048 | 15.9 | 2220 | 18.7 | 25.3 | 32 | 441 | |
Minimum | 1 | 10 | 1 | 1983 | 0.013 | 9.5 | 1016 | 12 | 17.4 | 12 | 157 | |
SD | 26.7 | 24 | 116 | 226.2 | 0.007 | 1.113 | 302.7 | 1.0977 | 1.329 | 4.535329 | 69.54 | |
Mean | 16.9 | 44 | 207 | 2613 | 0.024 | 11.39 | 1564 | 13.666 | 19.55 | 21.79208 | 291.6 |
Predictors | Quercus macdougallii | Pinus patula | Pinus pseudostrobus | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
GLM | GAM | GLM | GAM | GLM | GAM | |||||||
Parms | p-Values | EDF | p-Values | Parms | p-Values | EDF | p-Values | Parms | p-Values | EDF | p-Values | |
Intercept | 7.724 | <0.001 * | 2.6 | <0.001 * | 10.21 | <0.001 * | 2.8 | <0.001 * | 15.89 | <0.001 * | 2.6 | <0.001 * |
AST | −0.002 | 0.430 | 2.8 | <0.001 * | −0.002 | <0.001 * | 4.0 | <0.001 * | 0.004 | <0.001 * | 7.6 | <0.001 * |
ASP | 0.032 | 0.125 | 2.4 | <0.001 * | 0.068 | <0.001 * | 2.0 | <0.001 * | 0.001 | 0.489 | 4.9 | <0.001 * |
GSP | −0.002 | 0.001 * | 1.9 | <0.001 * | −0.002 | <0.001 * | 4.0 | <0.001 * | −0.004 | <0.001 * | 4.9 | <0.001 * |
AI | −84.66 | <0.001 * | 1.0 | <0.001 * | −168 | <0.001 * | 5.0 | <0.001 * | −265.3 | <0.001 * | 4.9 | <0.001 * |
SME | 250.29 | 322.59 | 810.15 | 774.45 | 686.91 | 706.6 | ||||||
DE | 8.8 | 46.9 | 14.08 | 25.6 | 11.45 | 20.3 | ||||||
AIC | 469.9 | 346.5 | 9825.7 | 8705.3 | 7540.3 | 7725.2 |
Quercus macdougallii | Pinus patula | Pinus pseudostrobus | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
COV | Model Type | DE | EDF | p-Values | COV | DE | EDF | p-Values | COV | DE | EDF | p-Values |
AST | M | 3.3 | 0.0019 * | AST | 3.8 | <0.001 * | AST | 7.7 | <0.001 * | |||
S | 14.2 | 3.7 | 1.3 | 4.6 | 3.5 | 4.8 | ||||||
ASP | M | 2.3 | 0.0003 * | ASP | 1.9 | <0.001 * | ASP | 5 | <0.001 * | |||
S | 3.8 | 1.9 | 6.3 | 4.9 | 4.4 | 4.9 | ||||||
ELEV | M | 3.8 | 0.0015 * | ELEV | 4.5 | <0.001 * | ELEV | 4.8 | <0.001 * | |||
S | 15.5 | 3.6 | 18.4 | 4.9 | 10.7 | 4.8 | ||||||
GSP | M | 1 | 0.4694 | MAP | 3.0 | <0.001 * | WINP | 4.9 | <0.001 * | |||
S | 23.6 | 4.9 | 17.5 | 4.9 | 11.0 | 3.9 | ||||||
SPRP | M | 1.9 | 0.0291 | GSP | 4.0 | <0.001 * | D100 | 4.1 | <0.001 * | |||
S | 23.8 | 4.9 | 17.8 | 5.0 | 9.7 | 4.6 | ||||||
SMRSPRPB | M | 1.2 | 0.5672 | SMRP | 1.9 | <0.001 * | GSP | 5 | <0.001 * | |||
S | 8.3 | 4.8 | 18.1 | 4.9 | 11.1 | 4.9 | ||||||
MTCM | M | 3.9 | 0.0221 | DD5 | 1.6 | <0.001 * | MMAX | 4.9 | <0.001 * | |||
S | 24.7 | 4.9 | 17.6 | 4.9 | 11.2 | 4.8 | ||||||
MTWM | M | 2 | 0.0400 | D100 | 1.9 | <0.001 * | MAT | 4.1 | <0.001 * | |||
S | 24.1 | 4.9 | 18.0 | 10.8 | 4.7 | |||||||
FFP | M | 1.9 | <0.001 * | MMIN | 4.8 | <0.001 * | MTWM | 4.9 | <0.001 * | |||
S | 18.9 | 4.3 | 18.6 | 4.9 | 11.0 | 4.7 | ||||||
INTERCEPT (M) | 2.5 | 2.8 | 2.5 | |||||||||
AIC (M) | 266 | 7940.5 | 6821 | |||||||||
SME (M) | 3462 | 7596 | 7008 | |||||||||
DE (M) | 76.8 | 33.6 | 31.9 | |||||||||
UBRE (M) | 2.84 | 19.70 | 17.69 |
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Antúnez, P.; Hernández-Díaz, J.C.; Wehenkel, C.; Clark-Tapia, R. Generalized Models: An Application to Identify Environmental Variables That Significantly Affect the Abundance of Three Tree Species. Forests 2017, 8, 59. https://doi.org/10.3390/f8030059
Antúnez P, Hernández-Díaz JC, Wehenkel C, Clark-Tapia R. Generalized Models: An Application to Identify Environmental Variables That Significantly Affect the Abundance of Three Tree Species. Forests. 2017; 8(3):59. https://doi.org/10.3390/f8030059
Chicago/Turabian StyleAntúnez, Pablo, José Ciro Hernández-Díaz, Christian Wehenkel, and Ricardo Clark-Tapia. 2017. "Generalized Models: An Application to Identify Environmental Variables That Significantly Affect the Abundance of Three Tree Species" Forests 8, no. 3: 59. https://doi.org/10.3390/f8030059