|
Non-stratified
|
Global in-likelihood
|
d
|
e
|
j
|
Stratified
|
Global in-likelihood
|
D
|
e
|
j
|
|---|
|
Lagrange C++
| | | | |
Lagrange C++
| | | | |
|
*NS0
|
−73.5273
|
0.2700
|
0.0102
|
-
|
*TS1
|
−88.2411
|
0.6363
|
0.0003
|
-
|
|
*NS1
|
−73.8920
|
0.3872
|
0.0146
|
-
|
TS2
|
−93.1298
|
0.7224
|
0.0005
|
-
|
|
Root optimization
| | | | |
Root optimization
| | | | |
|
*NS1_PR-sH
|
−72.1124
|
0.4854
|
0.0053
|
-
|
*TS2_PR-sH
|
−94.3276
|
0.6718
|
0.0005
|
-
|
|
NS1_PR-nH
|
−74.5323
|
0.3517
|
0.0114
|
-
|
TS2_PR-nH
|
−97.4394
|
0.6162
|
0.0025
|
-
|
|
NS1_PR-nH-eC
|
−76.5541
|
0.3825
|
0.0118
|
-
|
TS2_PR-nH-eC
|
−97.6103
|
0.6174
|
0.0017
|
-
|
|
NS1_PR-sH-eC
|
−76.6322
|
0.3313
|
0.0086
|
-
|
TS2_PR-nH-sH
|
−97.8598
|
0.5802
|
0.0019
|
-
|
|
NS1_PR-nH-sH
|
−77.1248
|
0.3048
|
0.0083
|
-
|
TS2_PR-sH-eC
|
−98.4153
|
0.5613
|
0.0001
|
-
|
|
NS1_nH
|
−78.4231
|
0.3522
|
0.0141
|
-
|
TS2_sH
|
−99.4647
|
0.7906
|
0.0050
|
-
|
|
NS1_PR
|
−80.0185
|
0.3219
|
0.0059
|
-
|
TS2_nH
|
−101.7850
|
0.6684
|
0.0089
|
-
|
|
NS1_sH
|
−80.2485
|
0.2874
|
0.0082
|
-
|
TpS2_PR
|
−103.8450
|
0.6690
|
0.0063
|
-
|
|
BioGeoBEARS DEC model
| | | | |
BioGeoBEARS DEC model
| | | | |
|
*NS1-
j
|
−78.7492
|
0.0020
|
0.0000
|
0.0709
|
*TS1-
j
|
−63.8944
|
0.0581
|
0.0042
|
0.5821
|
|
NS1
|
−97.9848
|
0.0054
|
0.0069
|
-
|
TS1
|
−76.7373
|
0.1211
|
0.0098
|
-
|
- The best models from each type of analyses are highlighted in bold text and marked with an asterisk (*). Parameter d is the rate of “dispersal" or range expansion, e is the rate of “extinction” or range contraction, and j is the relative weight of jump dispersal. j is cladogenetic, and d and e are anagenetic processes. Model-comparison between the BioGeoBEARS models resulted in Akaike weights favouring TS1-j with a relative probability of 0.999 of it being the best model. Similarly, LRT between TS1 and TS1-j, the two best models, rejected TS1 as the null model with fewer parameters with p-value of 4.02e−07.
