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Table 4 Population size, migration and dispersal estimates

From: The population structure of Glossina fuscipes fuscipes in the Lake Victoria basin in Uganda: implications for vector control

 

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)

 

N E /N C

σ (km)

σ (km)

σ 2 (km 2 )

m

W N

  

(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

  
  1. 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 + b GD; GD = geographic distance in kilometers) and a two-dimensional (2D) (FST/(1-FST) ~ a + b ln(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.