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Table 2 Temporal variation in nest initiation

From: Nest initiation and flooding in response to season and semi-lunar spring tides in a ground-nesting shorebird

 

Response - # of initiated nests

Gaussian

Poisson

Model

Effect type

Effect

Estimate

95% CI

Estimate

95% CI

Complex

Fixed

Intercept

0.943

0.64

1.247

−0.302

−0.591

−0.02

  

Spring tide cycle number

−0.195

−0.325

−0.065

−0.236

−0.375

−0.105

  

Cos (Day of spring tide cycle)

0.105

0.002

0.208

0.096

−0.016

0.202

  

Sin (Day of spring tide cycle)

0.043

−0.09

0.174

0.038

−0.103

0.176

  

Cos × Spring tide cycle number

−0.06

−0.163

0.041

−0.048

−0.168

0.069

  

Sin × Spring tide cycle number

0.016

−0.122

0.147

0.019

−0.127

0.168

 

Random (variance)

First or second half : Spring tide cycle : Year (intercept)

9%

  

29%

  
 

Spring tide cycle : Year (intercept)

7%

  

19%

  
  

Year (intercept)

13%

  

40%

  
  

Residual – Gaussian/Observation (intercept) - Poisson

71%

  

12%

  

Simple

Fixed

Intercept

1.349

0.954

1.747

0.205

−0.193

0.575

  

Spring tide cycle number

−0.11

−0.188

−0.034

− 0.138

−0.216

−0.059

  

Cos (Day of spring tide cycle)

0.104

0.001

0.211

0.033

−0.114

0.171

  

Sin (Day of spring tide cycle)

0.04

−0.098

0.17

0.108

0.002

0.214

 

Random (variance)

First or second half : Spring tide cycle: Year (intercept)

9%

  

30%

  
 

Spring tide cycle: Year (intercept)

7%

  

19%

  
  

Year (intercept)

13%

  

40%

  
  

Residual – Gaussian/Observation (intercept) - Poisson

72%

  

12%

  
  1. The posterior estimates (medians) of the effect sizes with the 95% CIs derived from a posterior distribution of 5000 simulated values generated by the ‘sim’ function in R. Variance components were estimated by the ‘lmer’ function in R. To account for non-independence of data points ‘Year’, ‘Spring tide cycle number’ within year and indication whether the nest was initiated in the ‘First or Second half’ of the spring tide cycle were fitted as random intercepts. Overdispersion was modelled by adding ‘Observation’ level as random intercept. ‘Spring tide cycle number’ is standardized within the year, so that the first spring tide cycle in the given year corresponds to the cycle when the first nest was initiated. ‘Day of spring tide cycle’ was transformed to radians (2 * number of days after the last spring tide * π/length of the given spring tide cycle [~ 14.75]) and fitted as sine and cosine of radians