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Table 2 Influence of timing on migration duration and number of stopover and migratory days

From: Timing is critical: consequences of asynchronous migration for the performance and destination of a long-distance migrant

Response

Leg

Predictor

Estimate (SE)

t value

p value

R2 marginal

R2 conditional

Migration duration

1

Intercept

11.51 (3.15)

3.66

0.12

0.88

  

Date

− 3.92 (1.24)

− 3.17

0.002**

  
  

Age (juv.)

− 1.86 (3.38)

− 0.55

0.582

  
 

2

Intercept

7.26 (3.44)

2.11

0.01

0.88

  

Date

0.07 (0.55)

0.14

0.893

  
  

Age (juv.)

1.79 (3.73)

0.48

0.632

  
 

3

Intercept

11.10 (0.88)

12.68

0.09

0.09

  

Date

− 1.10 (0.47)

− 2.34

0.019*

  
  

Age (juv.)

0.78 (1.00)

0.77

0.439

  

Migratory days

1

Intercept

3.73 (0.31)

11.95

0.01

0.12

  

Date

− 0.07 (0.13)

− 0.58

0.565

  
  

Age (juv.)

0.19 (0.31)

0.62

0.534

  
 

2

Intercept

2.69 (0.41)

6.54

0.05

0.75

  

Date

− 0.11 (0.15)

− 0.70

0.483

  
  

Age (juv.)

0.62 (0.41)

1.49

0.136

  
 

3

Intercept

9.40 (0.56)

16.88

0.13

0.13

  

Date

− 0.78 (0.30)

− 2.61

0.009**

  
  

Age (juv.)

1.10 (0.64)

1.72

0.085

  

Stopover days

1

Intercept

8.08 (3.10)

2.61

0.11

0.95

  

Date

− 3.65 (1.18)

− 3.09

0.002**

  
  

Age (juv.)

− 2.39 (3.35)

− 0.71

0.475

  
 

2

Intercept

1.70 (0.51)

3.32

0.02

0.02

  

Date

− 0.32 (0.27)

− 1.16

0.244

  
  

Age (juv.)

− 0.32 (0.59)

− 0.55

0.581

  
 

3

Intercept

1.87 (0.62)

3.02

0.03

0.62

  

Date

− 0.29 (0.28)

− 1.04

0.296

  
  

Age (juv.)

− 0.49 (0.68)

− 0.72

0.472

  
  1. Results of the LMMs, testing the influence of timing of white stork migration and age on migration duration and on the number of migratory and stopover days, using bird ID and year as random factors. The variable “Date” has been scaled by subtracting the mean date and dividing by the standard deviation