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. 2012 Oct 4;5:222. doi: 10.1186/1756-3305-5-222

Table 4.

Population size, migration and dispersal estimates

 
Linkage Diseq.
Temporal (MLNE)
Temporal (TM3)
Mean NC
95% HPD
 
(LDNe)
(Likelihood)
(Bayesian)
  Mean NE (95% CI) Mean NE (95% CI) Mean NE (95% CI)    
Clusters 3 & 4
310
(258–380)
243
(181–327)
240
(223–250)
4121
(2422–6109)
Cluster 2
121
(88–180)
45
(35–61)
33
(22–47)
1199
(470–2191)
Cluster 1
157
(98–326)
212
(106–611)
178
(105–285)
1299
(412–2621)
 
NE/NC
σ (km)
σ (km)
σ2(km2)
m
WN
 
 
(1D)
(2D)
(2D)
(2D)
(2D)
 
 
Based on LDNe estimates
 
 
Clusters 3 & 4
0.075
15.16
14.14
200.06
0.033
64
 
 
Cluster 2
0.101
4.53
3.59
12.92
0.025
19
 
 
Cluster 1 0.121 3.94 2.49 6.21 0.013 13    

Estimates were computed for clusters 1, 2 and the group comprising clusters 3 and 4. Effective population size (NE) was computed using both a linkage disequilibrium method (in LDNe) and two temporal methods (a likelihood approach implemented in MLNE and a Bayesian approach implemented in TM3). Mean NE and parametric 95% confidence intervals are shown. Census size (NC) was computed using a sequential Bayesian method [51]. Mean NC and 95% highest probability density (HPD) intervals are shown. Dispersal distance (σ) was estimated using both a one-dimensional (1D) (FST/(1-FST) ~ a + bGD; GD = geographic distance in kilometers) and a two-dimensional (2D) (FST/(1-FST) ~ a + bln(GD); ln(GD) = log of geographic distance) isolation-by-distance model. Dispersal surface (σ2), migration (m) and Wright’s neighborhood size (WN) estimates from the 2D model are also reported. σ, σ2, m and WN in cluster 1 were only computed for female individuals (the model was not significant when males were considered) and are shown in italic type.