Online Supplement 1
Variables present within our candidate set of survival models are summarized below.
Variable
Type
Description
Range of values
Treatment group
Categorical
Group
Before, After, and
Control
Max HHW
Continuous
Time Varying
Season
Categorical
Time Varying
Three group indicators
identifying invasive
Spartina Treatment
Maximum weekly water
level recorded at
NOAA’s Redwood
Creek tide gauge
Three time varying
indicators of season
MaxHHW_Seasonal
Continuous
Time Varying
Year
Categorical
Time Varying
Site
Categorical
Group
Sex
Categorical
Individual
Covariate
Categorical
Time Varying
Weekly Occasion
Maximum weekly water
level recorded at
NOAA’s Redwood
Creek tide gauge.
Effect allowed to vary
seasonally
Four time varying
indicators of year,
beginning with the
Breeding season
Four group indicators
identifying marsh of
capture
Binary indicator of
individual sex
Time varying indicator
of 166 (weekly) sample
occasions
Relative Variable
Importance
(Number of models)
0.48 (10)
2.272 meters to 3.108
meters
0.336 (9)
Winter:
15 Nov to 14 Mar
Breeding:
15 March to 14 July
Post Breeding:
15 July to 14 Nov
2.272 meters to 3.108
meters
0.567 (13)
2007, 2008, 2009, 2010
0.083 (7)
Arrowhead, Cogswell,
Colma, and Laumeister
0.034 (4)
0 (Female) or 1 (Male)
0.136 (5)
1 through 166
0 (1)
0.433 (6)
Our complete candidate model set included 28 models provided in the table below. Of these candidate
models 10 included only variables that specifically addressed our hypotheses concerning seasonal differences,
Spartina treatment, and/or tide level effects on survival. One model represented the null hypothesis that survival
rates did not differ according to any measured variable. The remaining 17 models (underlined in table) assessed
whether potential confounding relationships with survival were evident. We investigated three potential confounding
relationships on survival estimates: yearly variation, site level variation, and variation based on sex. Each effect was
modeled with the null model and in conjunction with the 4 competing models. However, due to issues of
multicollinearity and inability for models to converge, site and year were not modeled in conjunction with the model
containing the treatment effect. Such models are intractable given the longitudinal study design available. None of
the potentially confounding variables improved on either the Null or competing models but we retained them in the
analysis to provide robust model averaged parameter estimates. An assessment of the relative importance of each
variable is provided above. However, in order to match our a priori hypotheses, each variable was not equally
represented in the candidate model set and direct comparison of these relative importance values is not encouraged
(Burnham and Anderson 1998).
Model
Treatment + MaxHHW_Seasonal
MaxHHW_Seasonal
Treatment + MaxHHW + Season
Treatment + Season
Season + MaxHHW
Season
MaxHHW_Seasonal + Sex
Season + MaxHHW + Sex
Treatment + MaxHHW_Seasonal + Year
Season+ Sex
Treatment + MaxHHW + Season + Year
MaxHHW_Seasonal + Site
MaxHHW + Season + Year
Treatment + Season + Year
Season + MaxHHW + Site
Season + Year
Season+ Site
Treatment * Season
Treatment + MaxHHW_Seasonal + Sex
Treatment + MaxHHW
Treatment
Year
NULL – Constant Survival
Sex
Site
MaxHHW + Year
MaxHHW
Time model – Weekly Occasion
Delta AICc
AICc Weights
Model Likelihood
0.00
0.18
1.00
0.37
0.15
0.83
0.57
0.13
0.75
0.91
0.11
0.64
1.03
0.11
0.60
1.96
0.07
0.37
2.09
0.06
0.35
2.75
0.04
0.25
3.73
0.03
0.16
3.74
0.03
0.15
4.41
0.02
0.11
4.76
0.02
0.09
5.11
0.01
0.08
5.20
0.01
0.07
5.45
0.01
0.07
6.01
0.01
0.05
6.67
0.01
0.04
8.34
0.00
0.02
9.63
0.00
0.01
12.41
0.00
0.00
13.22
0.00
0.00
19.67
0.00
0.00
19.84
0.00
0.00
21.71
0.00
0.00
24.39
0.00
0.00
27.55
0.00
0.00
33.04
0.00
0.00
177.26
0.00
0.00
Parameter estimates and standard errors (logit scale) are presented below for the 6 models with ΔAICc <= 2.
Model 1: Treatment + MaxHHW_Seasonal
Parameter
Beta
Standard Error
Before Treatment – Intercept
6.90
1.85
After Treatment
-0.676
0.349
Native Marsh
-0.507
0.311
Winter Season MHHW
-1.19
0.684
Breeding MHHW
-0.741
0.693
Post-breeding Season MHHW
-0.881
0.699
Model 2: MaxHHW_Seasonal
Parameter
Beta
Standard Error
Intercept
6.78
1.83
Winter Season MHHW
-1.31
0.671
Breeding MHHW
-0.960
0.689
Post-breeding Season MHHW
-0.816
0.684
Parameter
Beta
Standard Error
Before Treatment, Winter Season – Intercept
6.52
1.86
After Treatment
-0.678
0.349
Native Marsh
-0.516
0.310
MHHW
-1.05
0.687
Breeding Season
0.83
0.21
Post-breeding Season
1.20
0.362
Parameter
Beta
Standard Error
Before Treatment, Winter Season – Intercept
3.72
0.288
After Treatment
-0.682
0.348
Native Marsh
-0.581
0.306
Breeding Season
0.876
0.288
Post-breeding Season
1.19
0.361
Parameter
Beta
Standard Error
Winter Season
6.37
1.84
Breeding
7.30
1.81
Post-breeding Season
7.68
1.86
MHHW
-1.16
0.675
Parameter
Beta
Standard Error
Winter Season
3.24
0.157
Breeding
4.24
0.231
Post-breeding Season
4.55
0.318
Model 3: Treatment + MaxHHW + Season
Model 4: Treatment + Season
Model 5: Season + MaxHHW
Model 6: Season