Model/predictors | K | ∆ AIC | w
i
| TSS | R2 |
---|
Region
| | |
GVI
| |
SF
|
9
|
0.321
|
0.271
|
0.303
|
0.425
|
Region
| | |
GVI
|
I (Region* GVI)
|
SF
|
10
|
2.069
|
0.113
|
0.318
|
0.425
|
Region
|
PSea
| |
GVI
| |
SF
|
10
|
1.965
|
0.119
|
0.308
|
0.425
|
Region
| PSea | I (Region* PSea) | GVI | I (Region* GVI) | SF | 12 | 5.260 | 0.023 | 0.324 | 0.427 |
Region
| PSea | | | | SF | 9 | 20.886 | 0.000 | 0.328 | 0.371 |
Region
| PSea | I (Region* PSea) | | | SF | 10 | 22.727 | 0.000 | 0.306 | 0.372 |
|
PSea
| |
GVI
| |
SF
|
8
|
1.406
|
0.157
|
0.305
|
0.417
|
| | |
GVI
| |
SF
|
7
|
0.000
|
0.318
|
0.306
|
0.415
|
| PSea | | | | SF | 7 | 18.428 | 0.000 | 0.342 | 0.368 |
| | | | | SF | 6 | 19.752 | 0.000 | 0.355 | 0.359 |
- Abbreviations of the predictors used in each of the 10 models for logit link, are as follows (without the intercept): Region for regional variable (combination of 2 binaries); GVI for vegetation productivity; PSea for precipitation seasonality; I (Region* GVI and Region*PSea) for interaction terms; and SF for six spatial filters used. Best supported models are shown in bold. K is the number of model parameters, ∆ AIC are AIC differences, wi Akaike weights of each model; and TSS is the true skill statistics score of each model (see Methods section for more explanation on the last three).