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Table 2 Fit of Bayesian models for exponential, time-dependent and density-dependent gyrodactylid population growth to experimental data-sets

From: Population regulation in Gyrodactylus salaris – Atlantic salmon (Salmo salar L.) interactions: testing the paradigm

Dataset

Fish stock

and replicate

Exponential model

Time- dependent model

Density- dependent

model

Reference

A

Loneelva single worm

SQ 1.2882

SQ 0.2542

SQ 3.6544

2

DIC 29.61

DIC -20.70

DIC -8.667

Bi

Batnfjordselva

SQ 72.825

SQ 0.345

SQ 1.665

Unpublished

DIC 104.882

DIC – 4.452

DIC -3.380

Bii

Lierelva

SQ 1.57

SQ 0.2135

Failed to converge

Unpublished

DIC 15.464

DIC -38.464

C

Imsa

SQ 2.4703

SQ 0.3912

SQ 2.4374

Unpublished

DIC 25.839

DIC -80.125

DIC -36.162

D

Altaelva

SQ 14.461

SQ 1.6153

Failed to converge

20

DIC 157.55

DIC -135.64

Ei

Akerselva

SQ 9.4279

SQ 3.2636

Failed to converge

Unpublished

DIC 307.242

DIC 277.149

Eii

Akerselva

SQ 1.453579

SQ 0.862444

Failed to converge

Unpublished

DIC 169.796

DIC 80.931

Eiii

Akerselva

SQ 9.767961

SQ 3.461779

Failed to converge

Unpublished

DIC -157.044

DIC -154.38

F

Conon

SQ 18.9395

SQ 5.2759

SQ 9.39509

19

DIC 207.660

DIC 74.986

DIC 138.759

G

Shin

SQ 68.0709

SQ 11.3739

Failed to converge

19

DIC 394.026

DIC 139.259

H

Numedalslågen

SQ 12.04599

SQ 6.240825

Failed to converge

10

DIC 203.285

DIC 197.68

I

Lierelva

SQ 28.8556

SQ 9.526

Failed to converge

19

DIC 361.378

DIC 96.384

J

Indalsälv

SQ 6.59083

SQ 4.396193

SQ 3.541148

21

DIC 137.99

DIC 77.159

DIC 40.235

K

Neva

SQ 80.1418

SQ 8.46197

Failed to converge

20

DIC 198.842

DIC 120.456

L

Neva single worm

SQ 17.6825

SQ 7.54459

Failed to converge

2

DIC 86.573

DIC 57.064

M

Neva

SQ 28.3822

SQ 8.2056

Failed to converge

Unpublished

DIC 198.84

DIC 120.456

N

Namsen

SQ 0.4047

SQ 0.1839

Failed to converge

Unpublished

DIC 6.074

DIC 11.345

O

Altaelva

SQ 4.0926

SQ 0.58324

Failed to converge

Unpublished

DIC 123.98

DIC 11.626

  1. The Sum of Squares (SQ) and the Bayesian Deviance Information Criterion (DIC) are provided for each model