CO2 morphology data
J S CANE
2024
R Markdown
library(ggplot2)
library(lme4)## Loading required package: Matrixlibrary(MuMIn)
library(vegan)## Loading required package: permute## Loading required package: lattice## This is vegan 2.6-4library(emmeans)
library(lmerTest)##
## Attaching package: 'lmerTest'## The following object is masked from 'package:lme4':
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## lmer## The following object is masked from 'package:stats':
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## steplibrary(tibble)
library(plyr)
library(dplyr)##
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## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionlibrary(readr)
library(janitor)##
## Attaching package: 'janitor'## The following objects are masked from 'package:stats':
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## chisq.test, fisher.testlibrary(pbkrtest)
library(tidyr)##
## Attaching package: 'tidyr'## The following objects are masked from 'package:Matrix':
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## expand, pack, unpacklibrary(ggpubr)##
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## mutatelibrary(ggthemes)
library(stringr)
library(car)## Loading required package: carData##
## Attaching package: 'car'## The following object is masked from 'package:dplyr':
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## recodelibrary(glmmTMB) ## Warning in checkMatrixPackageVersion(): Package version inconsistency detected.
## TMB was built with Matrix version 1.5.3
## Current Matrix version is 1.5.4
## Please re-install 'TMB' from source using install.packages('TMB', type = 'source') or ask CRAN for a binary version of 'TMB' matching CRAN's 'Matrix' packagelibrary(nlme)##
## Attaching package: 'nlme'## The following object is masked from 'package:dplyr':
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## collapse## The following object is masked from 'package:lme4':
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## lmListlibrary(moments)
library(extrafont)## Registering fonts with RInput and sort data
library(readr)
Growth_Data <- read_csv("C:/Users/jc819096/OneDrive - James Cook University/DATA/Lab 3/Growth data/Growth_Data_FINAL.check.csv")## Rows: 2955 Columns: 19
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (12): Parental_number, Maternal, Maternal_GF, Maternal_GM, Paternal, Pat...
## dbl (7): Tank, Female, Male, Age, Length, Weight, Density
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.View(Growth_Data)
head(Growth_Data)## # A tibble: 6 × 19
## Tank Parental_number Female Male Maternal Maternal_GF Maternal_GM Paternal
## <dbl> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
## 1 1 72 42 220 DA D A EC
## 2 1 72 42 220 DA D A EC
## 3 1 72 42 220 DA D A EC
## 4 1 72 42 220 DA D A EC
## 5 1 72 42 220 DA D A EC
## 6 1 72 42 220 DA D A EC
## # ℹ 11 more variables: Paternal_GF <chr>, Paternal_GM <chr>, DOM <chr>,
## # DOD <chr>, Age <dbl>, Parental_treat <chr>, Temp <chr>, Control_CO <chr>,
## # Length <dbl>, Weight <dbl>, Density <dbl>#coding the factors
str(Growth_Data)## spc_tbl_ [2,955 × 19] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Tank : num [1:2955] 1 1 1 1 1 1 1 1 1 1 ...
## $ Parental_number: chr [1:2955] "72" "72" "72" "72" ...
## $ Female : num [1:2955] 42 42 42 42 42 42 42 42 42 42 ...
## $ Male : num [1:2955] 220 220 220 220 220 220 220 220 220 220 ...
## $ Maternal : chr [1:2955] "DA" "DA" "DA" "DA" ...
## $ Maternal_GF : chr [1:2955] "D" "D" "D" "D" ...
## $ Maternal_GM : chr [1:2955] "A" "A" "A" "A" ...
## $ Paternal : chr [1:2955] "EC" "EC" "EC" "EC" ...
## $ Paternal_GF : chr [1:2955] "E" "E" "E" "E" ...
## $ Paternal_GM : chr [1:2955] "C" "C" "C" "C" ...
## $ DOM : chr [1:2955] "11/01/2022" "11/01/2022" "11/01/2022" "11/01/2022" ...
## $ DOD : chr [1:2955] "9/05/2022" "9/05/2022" "10/05/2022" "10/05/2022" ...
## $ Age : num [1:2955] 118 118 119 119 125 125 125 125 125 125 ...
## $ Parental_treat : chr [1:2955] "HHCC" "HHCC" "HHCC" "HHCC" ...
## $ Temp : chr [1:2955] "zero" "zero" "zero" "zero" ...
## $ Control_CO : chr [1:2955] "CO" "CO" "CO" "CO" ...
## $ Length : num [1:2955] 31.4 29.6 30.7 33.4 32.3 ...
## $ Weight : num [1:2955] 0.936 0.76 0.923 1.045 1.148 ...
## $ Density : num [1:2955] 20 20 20 20 20 20 20 20 20 20 ...
## - attr(*, "spec")=
## .. cols(
## .. Tank = col_double(),
## .. Parental_number = col_character(),
## .. Female = col_double(),
## .. Male = col_double(),
## .. Maternal = col_character(),
## .. Maternal_GF = col_character(),
## .. Maternal_GM = col_character(),
## .. Paternal = col_character(),
## .. Paternal_GF = col_character(),
## .. Paternal_GM = col_character(),
## .. DOM = col_character(),
## .. DOD = col_character(),
## .. Age = col_double(),
## .. Parental_treat = col_character(),
## .. Temp = col_character(),
## .. Control_CO = col_character(),
## .. Length = col_double(),
## .. Weight = col_double(),
## .. Density = col_double()
## .. )
## - attr(*, "problems")=<externalptr>Growth_Data$Tank = factor (Growth_Data$Tank)
Growth_Data$Parental_number = factor (Growth_Data$Parental_number)
Growth_Data$Parental_treat = factor (Growth_Data$Parental_treat, levels=c("CCCC", "CCCH", "HHCC", "CCHC", "HHHC"))
Growth_Data$Maternal_GF = factor (Growth_Data$Maternal_GF)
Growth_Data$Maternal_GM = factor (Growth_Data$Maternal_GM)
Growth_Data$Paternal_GF = factor (Growth_Data$Paternal_GF)
Growth_Data$Paternal_GM = factor (Growth_Data$Paternal_GM)
Growth_Data$Temp = factor (Growth_Data$Temp)
Growth_Data$Control_CO = factor (Growth_Data$Control_CO)STANDARD LENGTH DATA
Exploring raw data
ggplot(Growth_Data, aes(y=Length, x=Density)) + geom_point()
ggplot(Growth_Data, aes(y=Weight, x=Age))+ geom_point()
ggplot(Growth_Data, aes(y=Length, x=Parental_treat)) + geom_boxplot()
ggplot(Growth_Data, aes(x=Length)) + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot(Growth_Data, aes(y=Length, x=Temp, colour=Parental_treat)) + geom_boxplot() +facet_grid(~factor(Control_CO))
### Raw data checks
qqPlot(Growth_Data$Length)
## [1] 549 2255shapiro.test(Growth_Data$Length)##
## Shapiro-Wilk normality test
##
## data: Growth_Data$Length
## W = 0.96946, p-value < 2.2e-16nortest::lillie.test(Growth_Data$Length)##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: Growth_Data$Length
## D = 0.059446, p-value < 2.2e-16leveneTest(Length ~ Parental_treat * Temp * Control_CO, data = Growth_Data)## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 3.1852 3.764e-06 ***
## 2935
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1kurtosis(Growth_Data$Length)## [1] 5.316165removing outliers (IQR to improve kurtosis)
Q <- quantile(Growth_Data$Length, probs=c(.25, .75), na.rm = FALSE)
iqr <- IQR(Growth_Data$Length)
up <- Q[2]+1.5*iqr # Upper Range
low<- Q[1]-1.5*iqr # Lower Range
eliminated <- subset(Growth_Data, Growth_Data$Length > (low) & Growth_Data$Length < (up))
nrow(Growth_Data)## [1] 2955nrow(eliminated)## [1] 2811check data now that outliers have been removed
qqPlot(eliminated$Length)
## [1] 1760 976shapiro.test(eliminated$Length)##
## Shapiro-Wilk normality test
##
## data: eliminated$Length
## W = 0.99687, p-value = 1.525e-05nortest::lillie.test(eliminated$Length)##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: eliminated$Length
## D = 0.018016, p-value = 0.03496leveneTest(Length ~ Parental_treat * Temp * Control_CO, data = eliminated)## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 3.0697 8.276e-06 ***
## 2791
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1kurtosis(eliminated$Length)## [1] 2.970551model
SL_model.1 = lmer(Length ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1|Tank), data = eliminated) post model checks
performance::check_model(SL_model.1, check="homogeneity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1, check="outliers") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1, check="qq") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1, check="normality") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1, check="linearity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1, check="pp_check")## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
#Homogeneity
plot(SL_model.1)
#normality
hist(residuals(SL_model.1), col="darkgray")
shapiro.test(residuals(SL_model.1))##
## Shapiro-Wilk normality test
##
## data: residuals(SL_model.1)
## W = 0.99185, p-value = 1.593e-11qqnorm(resid(SL_model.1))
qqline(resid(SL_model.1))
#model fit
library(sjPlot)
plot_model(SL_model.1, type = "diag")## [[1]]## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]
## [[2]]$Tank## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
##
## [[3]]
##
## [[4]]## `geom_smooth()` using formula = 'y ~ x'
#outlier test
outlierTest(SL_model.1)## No Studentized residuals with Bonferroni p < 0.05
## Largest |rstudent|:
## rstudent unadjusted p-value Bonferroni p
## 1399 -3.698924 0.0002207 0.62039model analysis
summary(SL_model.1)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Length ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) +
## (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1 | Tank)
## Data: eliminated
##
## REML criterion at convergence: 13665.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5941 -0.5731 0.0497 0.6606 3.1372
##
## Random effects:
## Groups Name Variance Std.Dev.
## Tank (Intercept) 1.3840 1.1765
## Paternal_GF (Intercept) 1.9930 1.4117
## Maternal_GF (Intercept) 0.1256 0.3544
## Paternal_GM (Intercept) 3.5679 1.8889
## Maternal_GM (Intercept) 0.4383 0.6621
## Residual 6.9195 2.6305
## Number of obs: 2811, groups:
## Tank, 183; Paternal_GF, 5; Maternal_GF, 4; Paternal_GM, 3; Maternal_GM, 3
##
## Fixed effects:
## Estimate Std. Error df
## (Intercept) 30.20178 1.42228 4.71142
## Parental_treatCCCH 0.67972 0.64398 125.74864
## Parental_treatHHCC 1.65420 0.68572 119.43781
## Parental_treatCCHC 1.64537 0.75970 125.93531
## Parental_treatHHHC 1.94077 0.76712 136.28960
## Tempzero 0.37515 0.61737 118.69274
## Control_COcontrol 0.20844 0.62357 122.91701
## Parental_treatCCCH:Tempzero 0.37785 0.86392 117.43732
## Parental_treatHHCC:Tempzero -0.03525 0.86602 117.62717
## Parental_treatCCHC:Tempzero -0.15907 0.85867 114.88098
## Parental_treatHHHC:Tempzero 0.08002 0.99585 124.89379
## Parental_treatCCCH:Control_COcontrol 0.45477 0.86683 129.60100
## Parental_treatHHCC:Control_COcontrol 0.63246 0.88594 125.76207
## Parental_treatCCHC:Control_COcontrol 0.05823 0.86421 117.52948
## Parental_treatHHHC:Control_COcontrol -0.27750 1.04209 128.81455
## Tempzero:Control_COcontrol 0.18827 0.86933 120.01582
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.39131 1.19397 135.26260
## Parental_treatHHCC:Tempzero:Control_COcontrol 0.77257 1.25076 123.63753
## Parental_treatCCHC:Tempzero:Control_COcontrol 0.05882 1.21311 116.03118
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.27165 1.45601 126.54347
## t value Pr(>|t|)
## (Intercept) 21.235 7.36e-06 ***
## Parental_treatCCCH 1.055 0.2932
## Parental_treatHHCC 2.412 0.0174 *
## Parental_treatCCHC 2.166 0.0322 *
## Parental_treatHHHC 2.530 0.0125 *
## Tempzero 0.608 0.5446
## Control_COcontrol 0.334 0.7387
## Parental_treatCCCH:Tempzero 0.437 0.6627
## Parental_treatHHCC:Tempzero -0.041 0.9676
## Parental_treatCCHC:Tempzero -0.185 0.8534
## Parental_treatHHHC:Tempzero 0.080 0.9361
## Parental_treatCCCH:Control_COcontrol 0.525 0.6007
## Parental_treatHHCC:Control_COcontrol 0.714 0.4766
## Parental_treatCCHC:Control_COcontrol 0.067 0.9464
## Parental_treatHHHC:Control_COcontrol -0.266 0.7904
## Tempzero:Control_COcontrol 0.217 0.8289
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.328 0.7436
## Parental_treatHHCC:Tempzero:Control_COcontrol 0.618 0.5379
## Parental_treatCCHC:Tempzero:Control_COcontrol 0.048 0.9614
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.187 0.8523
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Correlation matrix not shown by default, as p = 20 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need itAnova(SL_model.1)## Analysis of Deviance Table (Type II Wald chisquare tests)
##
## Response: Length
## Chisq Df Pr(>Chisq)
## Parental_treat 33.5481 4 9.224e-07 ***
## Temp 7.9887 1 0.004707 **
## Control_CO 7.8300 1 0.005139 **
## Parental_treat:Temp 0.6489 4 0.957479
## Parental_treat:Control_CO 3.7788 4 0.436772
## Temp:Control_CO 0.5346 1 0.464688
## Parental_treat:Temp:Control_CO 0.9565 4 0.916318
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(emmeans(SL_model.1, pairwise ~ Control_CO *Temp ))## NOTE: Results may be misleading due to involvement in interactions
emmeans(SL_model.1, pairwise ~ Control_CO *Temp )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Control_CO Temp emmean SE df lower.CL upper.CL
## CO elevated 31.4 1.36 4.14 27.7 35.1
## control elevated 31.8 1.36 4.14 28.0 35.5
## CO zero 31.8 1.36 4.13 28.1 35.6
## control zero 32.5 1.36 4.15 28.8 36.3
##
## Results are averaged over the levels of: Parental_treat
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CO elevated - control elevated -0.3820 0.297 157 -1.286 0.5731
## CO elevated - CO zero -0.4279 0.289 148 -1.482 0.4510
## CO elevated - control zero -1.1405 0.299 155 -3.816 0.0011
## control elevated - CO zero -0.0458 0.292 156 -0.157 0.9986
## control elevated - control zero -0.7585 0.299 169 -2.536 0.0580
## CO zero - control zero -0.7127 0.294 153 -2.425 0.0766
##
## Results are averaged over the levels of: Parental_treat
## Degrees-of-freedom method: kenward-roger
## P value adjustment: tukey method for comparing a family of 4 estimatesplot(emmeans(SL_model.1, pairwise ~ Parental_treat ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(SL_model.1, pairwise ~ Parental_treat)## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Parental_treat emmean SE df lower.CL upper.CL
## CCCC 30.5 1.38 4.31 26.8 34.3
## CCCH 31.5 1.39 4.37 27.8 35.3
## HHCC 32.7 1.40 4.32 28.9 36.5
## CCHC 32.2 1.40 4.44 28.4 35.9
## HHHC 32.5 1.39 4.52 28.8 36.1
##
## Results are averaged over the levels of: Temp, Control_CO
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CCCC - CCCH -0.998 0.376 158.2 -2.651 0.0661
## CCCC - HHCC -2.146 0.475 84.6 -4.522 0.0002
## CCCC - CCHC -1.610 0.610 112.1 -2.640 0.0700
## CCCC - HHHC -1.910 0.470 170.8 -4.064 0.0007
## CCCH - HHCC -1.148 0.468 80.7 -2.454 0.1117
## CCCH - CCHC -0.611 0.609 94.5 -1.005 0.8526
## CCCH - HHHC -0.912 0.572 162.2 -1.594 0.5034
## HHCC - CCHC 0.536 0.459 109.3 1.168 0.7696
## HHCC - HHHC 0.236 0.561 66.4 0.420 0.9933
## CCHC - HHHC -0.300 0.627 102.9 -0.479 0.9891
##
## Results are averaged over the levels of: Temp, Control_CO
## Degrees-of-freedom method: kenward-roger
## P value adjustment: tukey method for comparing a family of 5 estimatesplot(emmeans(SL_model.1, pairwise ~ Temp ))## NOTE: Results may be misleading due to involvement in interactions
emmeans(SL_model.1, pairwise ~ Temp )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Temp emmean SE df lower.CL upper.CL
## elevated 31.6 1.35 4.04 27.8 35.3
## zero 32.2 1.35 4.04 28.4 35.9
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## elevated - zero -0.593 0.208 158 -2.854 0.0049
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Degrees-of-freedom method: kenward-rogerplot(emmeans(SL_model.1, pairwise ~ Control_CO ))## NOTE: Results may be misleading due to involvement in interactions
emmeans(SL_model.1, pairwise ~ Control_CO )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Control_CO emmean SE df lower.CL upper.CL
## CO 31.6 1.35 4.04 27.9 35.3
## control 32.1 1.36 4.04 28.4 35.9
##
## Results are averaged over the levels of: Parental_treat, Temp
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CO - control -0.547 0.21 152 -2.607 0.0101
##
## Results are averaged over the levels of: Parental_treat, Temp
## Degrees-of-freedom method: kenward-roger#for graphs
JSLEMM = (emmeans(SL_model.1, ~ Parental_treat * Temp * Control_CO) %>% as.data.frame)
JSLEMM## Parental_treat Temp Control_CO emmean SE df lower.CL upper.CL
## CCCC elevated CO 30.20178 1.431385 5.03 26.52838 33.87517
## CCCH elevated CO 30.88150 1.436140 5.00 27.19061 34.57239
## HHCC elevated CO 31.85598 1.448126 5.00 28.13299 35.57897
## CCHC elevated CO 31.84715 1.449657 5.09 28.14116 35.55314
## HHHC elevated CO 32.14255 1.474119 5.73 28.49347 35.79163
## CCCC zero CO 30.57693 1.426214 4.95 26.89891 34.25494
## CCCH zero CO 31.63450 1.438403 5.04 27.94492 35.32408
## HHCC zero CO 32.19588 1.443003 4.93 28.46998 35.92179
## CCHC zero CO 32.06323 1.448753 5.08 28.35719 35.76927
## HHHC zero CO 32.59771 1.459056 5.50 28.94657 36.24886
## CCCC elevated control 30.41022 1.428798 4.98 26.73403 34.08641
## CCCH elevated control 31.54471 1.438197 5.04 27.85650 35.23293
## HHCC elevated control 32.69688 1.452528 5.06 28.97730 36.41646
## CCHC elevated control 32.11382 1.449718 5.09 28.40767 35.81998
## HHHC elevated control 32.07349 1.487801 5.95 28.42505 35.72194
## CCCC zero control 30.97365 1.427493 4.97 27.29660 34.65069
## CCCH zero control 32.09467 1.430950 4.93 28.40094 35.78839
## HHCC zero control 33.99763 1.463035 5.22 30.28331 37.71194
## CCHC zero control 32.57699 1.450091 5.10 28.87136 36.28263
## HHHC zero control 32.98859 1.494838 6.06 29.34032 36.63685
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95plot modeled data
#combine column for x axis
JSLEMM_graph <- JSLEMM %>%
unite(Temp:Control_CO, col="Juv_treat", sep="_", remove=FALSE)
JSLEMM_graph## Parental_treat Juv_treat Temp Control_CO emmean SE
## 1 CCCC elevated_CO elevated CO 30.20178 1.431385
## 2 CCCH elevated_CO elevated CO 30.88150 1.436140
## 3 HHCC elevated_CO elevated CO 31.85598 1.448126
## 4 CCHC elevated_CO elevated CO 31.84715 1.449657
## 5 HHHC elevated_CO elevated CO 32.14255 1.474119
## 6 CCCC zero_CO zero CO 30.57693 1.426214
## 7 CCCH zero_CO zero CO 31.63450 1.438403
## 8 HHCC zero_CO zero CO 32.19588 1.443003
## 9 CCHC zero_CO zero CO 32.06323 1.448753
## 10 HHHC zero_CO zero CO 32.59771 1.459056
## 11 CCCC elevated_control elevated control 30.41022 1.428798
## 12 CCCH elevated_control elevated control 31.54471 1.438197
## 13 HHCC elevated_control elevated control 32.69688 1.452528
## 14 CCHC elevated_control elevated control 32.11382 1.449718
## 15 HHHC elevated_control elevated control 32.07349 1.487801
## 16 CCCC zero_control zero control 30.97365 1.427493
## 17 CCCH zero_control zero control 32.09467 1.430949
## 18 HHCC zero_control zero control 33.99763 1.463035
## 19 CCHC zero_control zero control 32.57699 1.450091
## 20 HHHC zero_control zero control 32.98859 1.494838
## df lower.CL upper.CL
## 1 5.027728 26.52838 33.87517
## 2 5.003729 27.19061 34.57239
## 3 4.997935 28.13299 35.57897
## 4 5.093447 28.14116 35.55314
## 5 5.727317 28.49346 35.79163
## 6 4.947132 26.89891 34.25494
## 7 5.036082 27.94492 35.32408
## 8 4.927177 28.46998 35.92179
## 9 5.082443 28.35719 35.76927
## 10 5.495543 28.94657 36.24886
## 11 4.984918 26.73403 34.08641
## 12 5.039909 27.85650 35.23293
## 13 5.064503 28.97730 36.41646
## 14 5.093420 28.40767 35.81998
## 15 5.946692 28.42505 35.72194
## 16 4.966046 27.29660 34.65069
## 17 4.931794 28.40094 35.78839
## 18 5.216838 30.28331 37.71194
## 19 5.100304 28.87135 36.28263
## 20 6.064930 29.34032 36.63685cbPalette <- c("#56B4E9", "#E69F00", "#D55E00","#009E73", "#999999")
#better labels#
graph <- ggplot(JSLEMM_graph, aes (x = Juv_treat, y=emmean, colour=Parental_treat)) + geom_pointrange(aes (ymin = emmean-SE, ymax = emmean+SE), position=position_dodge(width=1), size=1) +
facet_grid(~factor(Juv_treat, levels =c( "zero_control","elevated_control", "zero_CO", "elevated_CO"),labels=str_wrap(c("Control", "Elevated Temperature", "Elevated CO2", "Elevated Temperature & CO2"), width = 10)), scales = "free_x") + labs(x="Juvenile treatment", y="Standard length (mm)") +
scale_x_discrete(breaks = c( "zero_control","elevated_control", "zero_CO", "elevated_CO"), labels = str_wrap(c("Control", "Warm temperature", "Elevated CO2", "Warm temperature & Elevated CO2"), width = 13)) +
scale_colour_manual(values=cbPalette, name = "Cross-generation treatment", labels = c("Control", "Parental development", "Grandparental development", "Grandparental post-maturation", "Continuous grandparent")) +
theme_calc() + theme(text = element_text(size=20)) + theme(panel.spacing = unit(1, "cm", data = NULL)) + theme_classic()+ theme(strip.text.x = element_blank())
print(graph)
ggsave("SL_graph.eps", graph, height = 6, width = 14, dpi = 320)model with kurtosis and no data removed to highlight the bad model fit but same overall results
SL_model.1FULL = lmer(Length ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1|Tank), data = Growth_Data)
performance::check_model(SL_model.1FULL, check="homogeneity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1FULL, check="outliers") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1FULL, check="qq") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1FULL, check="normality") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1FULL, check="linearity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(SL_model.1FULL, check="pp_check")## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
#Homogeneity
plot(SL_model.1FULL)
#normality
hist(residuals(SL_model.1FULL), col="darkgray")
shapiro.test(residuals(SL_model.1FULL))##
## Shapiro-Wilk normality test
##
## data: residuals(SL_model.1FULL)
## W = 0.94996, p-value < 2.2e-16qqnorm(resid(SL_model.1FULL))
qqline(resid(SL_model.1FULL))
#model fit
library(sjPlot)
plot_model(SL_model.1FULL, type = "diag")## [[1]]## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]
## [[2]]$Tank## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
##
## [[3]]
##
## [[4]]## `geom_smooth()` using formula = 'y ~ x'
#outlier test
outlierTest(SL_model.1FULL)## rstudent unadjusted p-value Bonferroni p
## 2095 -5.250383 1.6264e-07 0.00048061
## 2817 -5.243242 1.6901e-07 0.00049941
## 298 -4.973457 6.9564e-07 0.00205560
## 2779 -4.937559 8.3542e-07 0.00246870
## 2255 -4.915337 9.3511e-07 0.00276330
## 1227 -4.659100 3.3177e-06 0.00980380
## 1679 -4.603537 4.3307e-06 0.01279700
## 845 -4.477836 7.8287e-06 0.02313400
## 621 -4.452292 8.8136e-06 0.02604400
## 1444 -4.404996 1.0958e-05 0.03238100#results
summary(SL_model.1FULL)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Length ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) +
## (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1 | Tank)
## Data: Growth_Data
##
## REML criterion at convergence: 15747.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.1161 -0.4431 0.0765 0.5929 3.4050
##
## Random effects:
## Groups Name Variance Std.Dev.
## Tank (Intercept) 3.1838 1.7843
## Paternal_GF (Intercept) 3.7106 1.9263
## Maternal_GF (Intercept) 0.3366 0.5802
## Paternal_GM (Intercept) 5.8093 2.4103
## Maternal_GM (Intercept) 0.5167 0.7188
## Residual 10.9163 3.3040
## Number of obs: 2955, groups:
## Tank, 183; Paternal_GF, 5; Maternal_GF, 4; Paternal_GM, 3; Maternal_GM, 3
##
## Fixed effects:
## Estimate Std. Error df
## (Intercept) 29.888281 1.858556 4.923076
## Parental_treatCCCH 0.451202 0.922468 122.709784
## Parental_treatHHCC 1.987886 0.981278 123.344384
## Parental_treatCCHC 1.552921 1.083389 116.755852
## Parental_treatHHHC 1.826940 1.088891 129.419356
## Tempzero 0.124457 0.886083 118.474923
## Control_COcontrol 0.065786 0.892308 121.581809
## Parental_treatCCCH:Tempzero 0.090954 1.245493 116.242515
## Parental_treatHHCC:Tempzero -0.001289 1.249262 117.338213
## Parental_treatCCHC:Tempzero 0.118886 1.241676 114.906112
## Parental_treatHHHC:Tempzero 0.701619 1.423228 121.266061
## Parental_treatCCCH:Control_COcontrol 1.336669 1.237250 129.012687
## Parental_treatHHCC:Control_COcontrol 1.193180 1.266004 122.863242
## Parental_treatCCHC:Control_COcontrol 0.356183 1.247852 117.058063
## Parental_treatHHHC:Control_COcontrol 1.046066 1.473551 125.261394
## Tempzero:Control_COcontrol 0.349127 1.252115 118.608940
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.485518 1.704654 135.027498
## Parental_treatHHCC:Tempzero:Control_COcontrol 1.230518 1.790639 120.227666
## Parental_treatCCHC:Tempzero:Control_COcontrol -0.373408 1.756948 115.389313
## Parental_treatHHHC:Tempzero:Control_COcontrol -0.744567 2.075553 122.476345
## t value Pr(>|t|)
## (Intercept) 16.081 1.91e-05 ***
## Parental_treatCCCH 0.489 0.6256
## Parental_treatHHCC 2.026 0.0449 *
## Parental_treatCCHC 1.433 0.1544
## Parental_treatHHHC 1.678 0.0958 .
## Tempzero 0.140 0.8885
## Control_COcontrol 0.074 0.9414
## Parental_treatCCCH:Tempzero 0.073 0.9419
## Parental_treatHHCC:Tempzero -0.001 0.9992
## Parental_treatCCHC:Tempzero 0.096 0.9239
## Parental_treatHHHC:Tempzero 0.493 0.6229
## Parental_treatCCCH:Control_COcontrol 1.080 0.2820
## Parental_treatHHCC:Control_COcontrol 0.942 0.3478
## Parental_treatCCHC:Control_COcontrol 0.285 0.7758
## Parental_treatHHHC:Control_COcontrol 0.710 0.4791
## Tempzero:Control_COcontrol 0.279 0.7809
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.285 0.7762
## Parental_treatHHCC:Tempzero:Control_COcontrol 0.687 0.4933
## Parental_treatCCHC:Tempzero:Control_COcontrol -0.213 0.8321
## Parental_treatHHHC:Tempzero:Control_COcontrol -0.359 0.7204
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Correlation matrix not shown by default, as p = 20 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need itAnova(SL_model.1FULL)## Analysis of Deviance Table (Type II Wald chisquare tests)
##
## Response: Length
## Chisq Df Pr(>Chisq)
## Parental_treat 31.3538 4 2.593e-06 ***
## Temp 1.9563 1 0.1619105
## Control_CO 11.1874 1 0.0008235 ***
## Parental_treat:Temp 1.0069 4 0.9087535
## Parental_treat:Control_CO 5.3065 4 0.2572650
## Temp:Control_CO 0.2833 1 0.5945181
## Parental_treat:Temp:Control_CO 1.3886 4 0.8461763
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1CONDITION DATA (based on log weight for a given log length)
Transorming raw data
#?log
Growth_Data$log_weight = log10(Growth_Data$Weight)
Growth_Data$log_length = log10(Growth_Data$Length)
head(Growth_Data)## # A tibble: 6 × 21
## Tank Parental_number Female Male Maternal Maternal_GF Maternal_GM Paternal
## <fct> <fct> <dbl> <dbl> <chr> <fct> <fct> <chr>
## 1 1 72 42 220 DA D A EC
## 2 1 72 42 220 DA D A EC
## 3 1 72 42 220 DA D A EC
## 4 1 72 42 220 DA D A EC
## 5 1 72 42 220 DA D A EC
## 6 1 72 42 220 DA D A EC
## # ℹ 13 more variables: Paternal_GF <fct>, Paternal_GM <fct>, DOM <chr>,
## # DOD <chr>, Age <dbl>, Parental_treat <fct>, Temp <fct>, Control_CO <fct>,
## # Length <dbl>, Weight <dbl>, Density <dbl>, log_weight <dbl>,
## # log_length <dbl>Exploring raw data
#exploring raw data and outliers
ggplot(Growth_Data, aes(y=Weight, x=Length)) + geom_point()
ggplot(Growth_Data, aes(y=log_weight, x=Parental_treat)) + geom_boxplot()
ggplot(Growth_Data, aes(y=log_weight, x=log_length)) + geom_point()
ggplot(Growth_Data, aes(x=log_weight)) + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Raw data checks
qqPlot(Growth_Data$log_weight)
## [1] 1679 2255shapiro.test(Growth_Data$log_weight)##
## Shapiro-Wilk normality test
##
## data: Growth_Data$log_weight
## W = 0.94686, p-value < 2.2e-16nortest::lillie.test(Growth_Data$log_weight)##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: Growth_Data$log_weight
## D = 0.070895, p-value < 2.2e-16leveneTest(log_weight ~ Parental_treat * Temp * Control_CO, data = Growth_Data)## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 19 2.2377 0.001598 **
## 2935
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1kurtosis(Growth_Data$log_weight)## [1] 6.939252model
Cond_model.1 = lmer(log_weight ~ Parental_treat * Temp * Control_CO + log_length + (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1| Tank) + Density, data = Growth_Data) ## boundary (singular) fit: see help('isSingular')summary(Cond_model.1)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: log_weight ~ Parental_treat * Temp * Control_CO + log_length +
## (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) +
## (1 | Paternal_GM) + (1 | Tank) + Density
## Data: Growth_Data
##
## REML criterion at convergence: -12144.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5701 -0.5829 0.0698 0.6330 10.5009
##
## Random effects:
## Groups Name Variance Std.Dev.
## Tank (Intercept) 1.480e-04 1.216e-02
## Paternal_GF (Intercept) 1.798e-04 1.341e-02
## Maternal_GF (Intercept) 7.533e-13 8.679e-07
## Paternal_GM (Intercept) 1.371e-04 1.171e-02
## Maternal_GM (Intercept) 1.181e-04 1.087e-02
## Residual 8.266e-04 2.875e-02
## Number of obs: 2955, groups:
## Tank, 183; Paternal_GF, 5; Maternal_GF, 4; Paternal_GM, 3; Maternal_GM, 3
##
## Fixed effects:
## Estimate Std. Error df
## (Intercept) -4.276e+00 2.239e-02 8.172e+01
## Parental_treatCCCH 7.219e-03 6.624e-03 1.485e+02
## Parental_treatHHCC 5.243e-03 6.945e-03 1.521e+02
## Parental_treatCCHC -8.833e-03 7.763e-03 1.522e+02
## Parental_treatHHHC 3.475e-04 7.889e-03 1.610e+02
## Tempzero -5.547e-03 6.402e-03 1.465e+02
## Control_COcontrol 2.938e-03 6.441e-03 1.520e+02
## log_length 2.905e+00 1.125e-02 2.870e+03
## Density -2.487e-03 3.478e-04 2.215e+02
## Parental_treatCCCH:Tempzero -1.289e-03 8.980e-03 1.434e+02
## Parental_treatHHCC:Tempzero -5.895e-03 8.983e-03 1.451e+02
## Parental_treatCCHC:Tempzero -3.171e-03 8.912e-03 1.411e+02
## Parental_treatHHHC:Tempzero -5.152e-03 1.028e-02 1.512e+02
## Parental_treatCCCH:Control_COcontrol -6.617e-03 8.997e-03 1.582e+02
## Parental_treatHHCC:Control_COcontrol -3.843e-03 9.166e-03 1.534e+02
## Parental_treatCCHC:Control_COcontrol -5.523e-03 8.970e-03 1.448e+02
## Parental_treatHHHC:Control_COcontrol -1.594e-02 1.067e-02 1.568e+02
## Tempzero:Control_COcontrol -4.399e-03 9.017e-03 1.474e+02
## Parental_treatCCCH:Tempzero:Control_COcontrol -1.427e-03 1.244e-02 1.634e+02
## Parental_treatHHCC:Tempzero:Control_COcontrol -3.818e-03 1.292e-02 1.501e+02
## Parental_treatCCHC:Tempzero:Control_COcontrol 2.342e-03 1.261e-02 1.423e+02
## Parental_treatHHHC:Tempzero:Control_COcontrol 1.195e-02 1.500e-02 1.532e+02
## t value Pr(>|t|)
## (Intercept) -190.981 < 2e-16 ***
## Parental_treatCCCH 1.090 0.278
## Parental_treatHHCC 0.755 0.451
## Parental_treatCCHC -1.138 0.257
## Parental_treatHHHC 0.044 0.965
## Tempzero -0.866 0.388
## Control_COcontrol 0.456 0.649
## log_length 258.316 < 2e-16 ***
## Density -7.152 1.24e-11 ***
## Parental_treatCCCH:Tempzero -0.144 0.886
## Parental_treatHHCC:Tempzero -0.656 0.513
## Parental_treatCCHC:Tempzero -0.356 0.722
## Parental_treatHHHC:Tempzero -0.501 0.617
## Parental_treatCCCH:Control_COcontrol -0.735 0.463
## Parental_treatHHCC:Control_COcontrol -0.419 0.676
## Parental_treatCCHC:Control_COcontrol -0.616 0.539
## Parental_treatHHHC:Control_COcontrol -1.494 0.137
## Tempzero:Control_COcontrol -0.488 0.626
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.115 0.909
## Parental_treatHHCC:Tempzero:Control_COcontrol -0.296 0.768
## Parental_treatCCHC:Tempzero:Control_COcontrol 0.186 0.853
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.797 0.427
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Correlation matrix not shown by default, as p = 22 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Anova(Cond_model.1)## Analysis of Deviance Table (Type II Wald chisquare tests)
##
## Response: log_weight
## Chisq Df Pr(>Chisq)
## Parental_treat 10.8488 4 0.02832 *
## Temp 23.9182 1 1.005e-06 ***
## Control_CO 3.9461 1 0.04698 *
## log_length 66727.2586 1 < 2.2e-16 ***
## Density 51.1446 1 8.581e-13 ***
## Parental_treat:Temp 1.7949 4 0.77342
## Parental_treat:Control_CO 2.2153 4 0.69624
## Temp:Control_CO 0.7242 1 0.39477
## Parental_treat:Temp:Control_CO 1.2211 4 0.87462
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1post model checks
performance::check_model(Cond_model.1, check="homogeneity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
#performance::check_model(Cond_model.1, check="outliers")
performance::check_model(Cond_model.1, check="qq") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(Cond_model.1, check="normality") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
performance::check_model(Cond_model.1, check="linearity") ## Model has interaction terms. VIFs might be inflated.
## You may check multicollinearity among predictors of a model without
## interaction terms.
#performance::check_model(Cond_model.1, check="pp_check")
#Homogeneity
plot(Cond_model.1)
#normality
hist(residuals(Cond_model.1, col="darkgray"))
shapiro.test(residuals(Cond_model.1))##
## Shapiro-Wilk normality test
##
## data: residuals(Cond_model.1)
## W = 0.96812, p-value < 2.2e-16qqnorm(resid(Cond_model.1))
qqline(resid(Cond_model.1))
#model fit
library(sjPlot)
plot_model(Cond_model.1, type = "diag")## [[1]]## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]
## [[2]]$Tank## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
##
## [[3]]
##
## [[4]]## `geom_smooth()` using formula = 'y ~ x'
#outlier test
outlierTest(Cond_model.1)## rstudent unadjusted p-value Bonferroni p
## 2328 10.722098 2.4562e-26 7.2579e-23
## 2593 6.071848 1.4276e-09 4.2186e-06
## 2146 5.360536 8.9430e-08 2.6426e-04
## 2514 4.686995 2.8992e-06 8.5672e-03
## 127 4.609247 4.2144e-06 1.2453e-02removing outliers
Growth_Data_no_outliers = Growth_Data[-c(2328, 2593, 2156, 127, 2514),]Growth_Data_no_outliers = Growth_Data[-c(2256,2515,2091,127,2436),] #high density model
rerun model
Cond_model.1.noout = lmer(log_weight ~ Parental_treat * Temp * Control_CO + log_length + (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM) + (1| Tank) + Density, data = Growth_Data_no_outliers) ## boundary (singular) fit: see help('isSingular')post model checks
#Homogeneity
plot(Cond_model.1.noout)
#normality
hist(residuals(Cond_model.1.noout), col="darkgray")
shapiro.test(residuals(Cond_model.1.noout))##
## Shapiro-Wilk normality test
##
## data: residuals(Cond_model.1.noout)
## W = 0.99062, p-value = 5.261e-13qqnorm(resid(Cond_model.1.noout))
qqline(resid(Cond_model.1.noout))
#model fit
library(sjPlot)
plot_model(Cond_model.1.noout, type = "diag")## [[1]]## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]
## [[2]]$Tank## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GF## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Paternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
## [[2]]$Maternal_GM## `geom_smooth()` using formula = 'y ~ x'
##
##
## [[3]]
##
## [[4]]## `geom_smooth()` using formula = 'y ~ x'
#outlier test
outlierTest(Cond_model.1.noout)## rstudent unadjusted p-value Bonferroni p
## 2145 5.588078 2.5075e-08 7.397e-05model analysis
summary(Cond_model.1.noout)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: log_weight ~ Parental_treat * Temp * Control_CO + log_length +
## (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) +
## (1 | Paternal_GM) + (1 | Tank) + Density
## Data: Growth_Data_no_outliers
##
## REML criterion at convergence: -12321.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6913 -0.5952 0.0784 0.6592 5.3999
##
## Random effects:
## Groups Name Variance Std.Dev.
## Tank (Intercept) 1.492e-04 1.221e-02
## Paternal_GF (Intercept) 1.610e-04 1.269e-02
## Maternal_GF (Intercept) 2.377e-13 4.876e-07
## Paternal_GM (Intercept) 1.258e-04 1.122e-02
## Maternal_GM (Intercept) 1.186e-04 1.089e-02
## Residual 7.702e-04 2.775e-02
## Number of obs: 2950, groups:
## Tank, 183; Paternal_GF, 5; Maternal_GF, 4; Paternal_GM, 3; Maternal_GM, 3
##
## Fixed effects:
## Estimate Std. Error df
## (Intercept) -4.279e+00 2.173e-02 8.030e+01
## Parental_treatCCCH 7.303e-03 6.583e-03 1.481e+02
## Parental_treatHHCC 5.096e-03 6.901e-03 1.517e+02
## Parental_treatCCHC -9.506e-03 7.713e-03 1.521e+02
## Parental_treatHHHC -2.425e-04 7.831e-03 1.601e+02
## Tempzero -6.497e-03 6.366e-03 1.463e+02
## Control_COcontrol 2.932e-03 6.398e-03 1.513e+02
## log_length 2.906e+00 1.087e-02 2.860e+03
## Density -2.451e-03 3.440e-04 2.184e+02
## Parental_treatCCCH:Tempzero -1.072e-03 8.932e-03 1.432e+02
## Parental_treatHHCC:Tempzero -5.050e-03 8.931e-03 1.448e+02
## Parental_treatCCHC:Tempzero -3.856e-03 8.866e-03 1.410e+02
## Parental_treatHHHC:Tempzero -3.953e-03 1.022e-02 1.508e+02
## Parental_treatCCCH:Control_COcontrol -6.599e-03 8.933e-03 1.578e+02
## Parental_treatHHCC:Control_COcontrol -3.769e-03 9.104e-03 1.527e+02
## Parental_treatCCHC:Control_COcontrol -5.519e-03 8.917e-03 1.444e+02
## Parental_treatHHHC:Control_COcontrol -1.585e-02 1.060e-02 1.560e+02
## Tempzero:Control_COcontrol -4.754e-03 8.966e-03 1.471e+02
## Parental_treatCCCH:Tempzero:Control_COcontrol -3.171e-04 1.235e-02 1.637e+02
## Parental_treatHHCC:Tempzero:Control_COcontrol -3.399e-03 1.284e-02 1.496e+02
## Parental_treatCCHC:Tempzero:Control_COcontrol 4.339e-03 1.254e-02 1.421e+02
## Parental_treatHHHC:Tempzero:Control_COcontrol 1.197e-02 1.490e-02 1.526e+02
## t value Pr(>|t|)
## (Intercept) -196.935 < 2e-16 ***
## Parental_treatCCCH 1.109 0.269
## Parental_treatHHCC 0.738 0.461
## Parental_treatCCHC -1.233 0.220
## Parental_treatHHHC -0.031 0.975
## Tempzero -1.021 0.309
## Control_COcontrol 0.458 0.647
## log_length 267.326 < 2e-16 ***
## Density -7.126 1.49e-11 ***
## Parental_treatCCCH:Tempzero -0.120 0.905
## Parental_treatHHCC:Tempzero -0.565 0.573
## Parental_treatCCHC:Tempzero -0.435 0.664
## Parental_treatHHHC:Tempzero -0.387 0.699
## Parental_treatCCCH:Control_COcontrol -0.739 0.461
## Parental_treatHHCC:Control_COcontrol -0.414 0.679
## Parental_treatCCHC:Control_COcontrol -0.619 0.537
## Parental_treatHHHC:Control_COcontrol -1.496 0.137
## Tempzero:Control_COcontrol -0.530 0.597
## Parental_treatCCCH:Tempzero:Control_COcontrol -0.026 0.980
## Parental_treatHHCC:Tempzero:Control_COcontrol -0.265 0.792
## Parental_treatCCHC:Tempzero:Control_COcontrol 0.346 0.730
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.803 0.423
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Correlation matrix not shown by default, as p = 22 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Anova(Cond_model.1.noout)## Analysis of Deviance Table (Type II Wald chisquare tests)
##
## Response: log_weight
## Chisq Df Pr(>Chisq)
## Parental_treat 12.4832 4 0.01410 *
## Temp 26.7168 1 2.356e-07 ***
## Control_CO 3.5471 1 0.05965 .
## log_length 71463.2053 1 < 2.2e-16 ***
## Density 50.7747 1 1.036e-12 ***
## Parental_treat:Temp 1.5847 4 0.81155
## Parental_treat:Control_CO 2.1637 4 0.70569
## Temp:Control_CO 0.5628 1 0.45314
## Parental_treat:Temp:Control_CO 1.2356 4 0.87220
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1plot(emmeans(Cond_model.1.noout, pairwise ~Temp ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(Cond_model.1.noout, pairwise ~ Temp )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Temp emmean SE df lower.CL upper.CL
## elevated 0.0548 0.0109 5.95 0.0280 0.0816
## zero 0.0444 0.0109 5.94 0.0176 0.0712
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## elevated - zero 0.0104 0.00214 159 4.855 <.0001
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Degrees-of-freedom method: kenward-rogerplot(emmeans(Cond_model.1.noout, pairwise ~ Control_CO * Temp ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(Cond_model.1.noout, pairwise ~ Control_CO * Temp )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Control_CO Temp emmean SE df lower.CL upper.CL
## CO elevated 0.0565 0.011 6.19 0.0297 0.0833
## control elevated 0.0531 0.011 6.20 0.0263 0.0799
## CO zero 0.0472 0.011 6.16 0.0204 0.0740
## control zero 0.0415 0.011 6.20 0.0147 0.0684
##
## Results are averaged over the levels of: Parental_treat
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CO elevated - control elevated 0.00342 0.00306 159 1.115 0.6808
## CO elevated - CO zero 0.00928 0.00298 149 3.111 0.0119
## CO elevated - control zero 0.01493 0.00308 157 4.842 <.0001
## control elevated - CO zero 0.00587 0.00305 156 1.922 0.2232
## control elevated - control zero 0.01152 0.00306 169 3.762 0.0013
## CO zero - control zero 0.00565 0.00306 154 1.845 0.2563
##
## Results are averaged over the levels of: Parental_treat
## Degrees-of-freedom method: kenward-roger
## P value adjustment: tukey method for comparing a family of 4 estimatesplot(emmeans(Cond_model.1.noout, pairwise ~ Control_CO ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(Cond_model.1.noout, pairwise ~ Control_CO)## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Control_CO emmean SE df lower.CL upper.CL
## CO 0.0518 0.0109 5.95 0.0250 0.0786
## control 0.0473 0.0109 5.96 0.0205 0.0741
##
## Results are averaged over the levels of: Parental_treat, Temp
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CO - control 0.00453 0.0022 154 2.063 0.0408
##
## Results are averaged over the levels of: Parental_treat, Temp
## Degrees-of-freedom method: kenward-rogerplot(emmeans(Cond_model.1.noout, pairwise ~ Parental_treat ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(Cond_model.1.noout, pairwise ~ Parental_treat )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Parental_treat emmean SE df lower.CL upper.CL
## CCCC 0.0530 0.0112 6.66 0.0261 0.0799
## CCCH 0.0564 0.0114 6.82 0.0292 0.0835
## HHCC 0.0528 0.0114 6.31 0.0253 0.0803
## CCHC 0.0399 0.0116 6.65 0.0122 0.0675
## HHHC 0.0458 0.0114 7.13 0.0189 0.0728
##
## Results are averaged over the levels of: Temp, Control_CO
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## CCCC - CCCH -0.003388 0.00398 124.3 -0.852 0.9136
## CCCC - HHCC 0.000164 0.00499 42.5 0.033 1.0000
## CCCC - CCHC 0.013109 0.00638 81.6 2.056 0.2495
## CCCC - HHHC 0.007153 0.00482 170.7 1.484 0.5741
## CCCH - HHCC 0.003552 0.00454 71.3 0.783 0.9347
## CCCH - CCHC 0.016497 0.00597 133.1 2.761 0.0505
## CCCH - HHHC 0.010541 0.00603 98.1 1.749 0.4093
## HHCC - CCHC 0.012945 0.00453 144.7 2.858 0.0387
## HHCC - HHHC 0.006989 0.00593 17.7 1.178 0.7635
## CCHC - HHHC -0.005956 0.00684 32.9 -0.870 0.9057
##
## Results are averaged over the levels of: Temp, Control_CO
## Degrees-of-freedom method: kenward-roger
## P value adjustment: tukey method for comparing a family of 5 estimates#for graphs
CONDEMM = (emmeans(Cond_model.1.noout, ~ Parental_treat * Temp * Control_CO) %>% as.data.frame)
CONDEMM## Parental_treat Temp Control_CO emmean SE df lower.CL
## CCCC elevated CO 0.05594815 0.01191667 8.42 0.02870764
## CCCH elevated CO 0.06325117 0.01203797 8.47 0.03575662
## HHCC elevated CO 0.06104376 0.01201392 7.97 0.03332123
## CCHC elevated CO 0.04644189 0.01218396 8.28 0.01850777
## HHHC elevated CO 0.05570563 0.01252046 10.20 0.02788125
## CCCC zero CO 0.04945109 0.01189770 8.33 0.02220270
## CCCH zero CO 0.05568216 0.01204125 8.47 0.02818094
## HHCC zero CO 0.04949645 0.01195439 7.86 0.02184095
## CCHC zero CO 0.03608843 0.01216710 8.27 0.00818854
## HHHC zero CO 0.04525529 0.01233214 9.58 0.01761424
## CCCC elevated control 0.05888022 0.01190436 8.39 0.03164888
## CCCH elevated control 0.05958417 0.01201782 8.44 0.03212056
## HHCC elevated control 0.06020647 0.01209120 8.15 0.03241206
## CCHC elevated control 0.04385517 0.01219094 8.29 0.01591072
## HHHC elevated control 0.04278680 0.01260775 10.54 0.01488918
## CCCC zero control 0.04762941 0.01189335 8.34 0.02039543
## CCCH zero control 0.04694432 0.01195508 8.24 0.01951248
## HHCC zero control 0.04050644 0.01218917 8.39 0.01262489
## CCHC zero control 0.03308725 0.01219433 8.29 0.00513648
## HHHC zero control 0.03954993 0.01276666 11.15 0.01149815
## upper.CL
## 0.08318866
## 0.09074571
## 0.08876628
## 0.07437600
## 0.08353001
## 0.07669947
## 0.08318338
## 0.07715195
## 0.06398833
## 0.07289634
## 0.08611156
## 0.08704777
## 0.08800087
## 0.07179962
## 0.07068443
## 0.07486338
## 0.07437617
## 0.06838799
## 0.06103803
## 0.06760170
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95#back-transform data
CONDEMM$emmean10 = 10^(CONDEMM$emmean)
CONDEMM$emmean.low = 10^(CONDEMM$emmean-CONDEMM$SE)
CONDEMM$emmean.high = 10^(CONDEMM$emmean+CONDEMM$SE)
CONDEMM## Parental_treat Temp Control_CO emmean SE df lower.CL
## CCCC elevated CO 0.05594815 0.01191667 8.42 0.02870764
## CCCH elevated CO 0.06325117 0.01203797 8.47 0.03575662
## HHCC elevated CO 0.06104376 0.01201392 7.97 0.03332123
## CCHC elevated CO 0.04644189 0.01218396 8.28 0.01850777
## HHHC elevated CO 0.05570563 0.01252046 10.20 0.02788125
## CCCC zero CO 0.04945109 0.01189770 8.33 0.02220270
## CCCH zero CO 0.05568216 0.01204125 8.47 0.02818094
## HHCC zero CO 0.04949645 0.01195439 7.86 0.02184095
## CCHC zero CO 0.03608843 0.01216710 8.27 0.00818854
## HHHC zero CO 0.04525529 0.01233214 9.58 0.01761424
## CCCC elevated control 0.05888022 0.01190436 8.39 0.03164888
## CCCH elevated control 0.05958417 0.01201782 8.44 0.03212056
## HHCC elevated control 0.06020647 0.01209120 8.15 0.03241206
## CCHC elevated control 0.04385517 0.01219094 8.29 0.01591072
## HHHC elevated control 0.04278680 0.01260775 10.54 0.01488918
## CCCC zero control 0.04762941 0.01189335 8.34 0.02039543
## CCCH zero control 0.04694432 0.01195508 8.24 0.01951248
## HHCC zero control 0.04050644 0.01218917 8.39 0.01262489
## CCHC zero control 0.03308725 0.01219433 8.29 0.00513648
## HHHC zero control 0.03954993 0.01276666 11.15 0.01149815
## upper.CL emmean10 emmean.low emmean.high
## 0.08318866 1.137492 1.106704 1.169135
## 0.09074571 1.156781 1.125157 1.189294
## 0.08876628 1.150916 1.119515 1.183199
## 0.07437600 1.112864 1.082076 1.144527
## 0.08353001 1.136856 1.104550 1.170108
## 0.07669947 1.120601 1.090318 1.151725
## 0.08318338 1.136795 1.105709 1.168755
## 0.07715195 1.120718 1.090290 1.151996
## 0.06398833 1.086647 1.056626 1.117521
## 0.07289634 1.109827 1.078756 1.141793
## 0.08611156 1.145197 1.114233 1.177022
## 0.08704777 1.147055 1.115749 1.179239
## 0.08800087 1.148700 1.117160 1.181130
## 0.07179962 1.106255 1.075633 1.137748
## 0.07068443 1.103537 1.071961 1.136042
## 0.07486338 1.115911 1.085765 1.146893
## 0.07437617 1.114152 1.083900 1.145248
## 0.06838799 1.097758 1.067376 1.129004
## 0.06103803 1.079163 1.049284 1.109894
## 0.06760170 1.095343 1.063612 1.128019
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95plot modeled data
#combine column for x axis
CONDEMM_graph <- CONDEMM %>%
unite(Temp:Control_CO, col="Juv_treat", sep="_", remove=FALSE)
CONDEMM_graph## Parental_treat Juv_treat Temp Control_CO emmean SE
## 1 CCCC elevated_CO elevated CO 0.05594815 0.01191667
## 2 CCCH elevated_CO elevated CO 0.06325117 0.01203797
## 3 HHCC elevated_CO elevated CO 0.06104376 0.01201392
## 4 CCHC elevated_CO elevated CO 0.04644189 0.01218396
## 5 HHHC elevated_CO elevated CO 0.05570563 0.01252046
## 6 CCCC zero_CO zero CO 0.04945109 0.01189770
## 7 CCCH zero_CO zero CO 0.05568216 0.01204125
## 8 HHCC zero_CO zero CO 0.04949645 0.01195439
## 9 CCHC zero_CO zero CO 0.03608843 0.01216710
## 10 HHHC zero_CO zero CO 0.04525529 0.01233214
## 11 CCCC elevated_control elevated control 0.05888022 0.01190436
## 12 CCCH elevated_control elevated control 0.05958417 0.01201782
## 13 HHCC elevated_control elevated control 0.06020647 0.01209120
## 14 CCHC elevated_control elevated control 0.04385517 0.01219094
## 15 HHHC elevated_control elevated control 0.04278680 0.01260775
## 16 CCCC zero_control zero control 0.04762941 0.01189335
## 17 CCCH zero_control zero control 0.04694432 0.01195507
## 18 HHCC zero_control zero control 0.04050644 0.01218917
## 19 CCHC zero_control zero control 0.03308725 0.01219433
## 20 HHHC zero_control zero control 0.03954993 0.01276666
## df lower.CL upper.CL emmean10 emmean.low emmean.high
## 1 8.424899 0.028707637 0.08318866 1.137491 1.106704 1.169135
## 2 8.468521 0.035756622 0.09074571 1.156781 1.125157 1.189294
## 3 7.969658 0.033321235 0.08876628 1.150916 1.119515 1.183199
## 4 8.275809 0.018507773 0.07437600 1.112863 1.082076 1.144526
## 5 10.197201 0.027881252 0.08353001 1.136856 1.104549 1.170108
## 6 8.329500 0.022202705 0.07669947 1.120601 1.090319 1.151725
## 7 8.470062 0.028180942 0.08318338 1.136795 1.105709 1.168755
## 8 7.855324 0.021840946 0.07715195 1.120718 1.090290 1.151996
## 9 8.267940 0.008188541 0.06398833 1.086647 1.056626 1.117521
## 10 9.582067 0.017614241 0.07289634 1.109827 1.078756 1.141793
## 11 8.389303 0.031648882 0.08611156 1.145197 1.114233 1.177022
## 12 8.440100 0.032120561 0.08704777 1.147055 1.115749 1.179239
## 13 8.148052 0.032412057 0.08800087 1.148700 1.117160 1.181130
## 14 8.285829 0.015910719 0.07179962 1.106255 1.075633 1.137748
## 15 10.540959 0.014889179 0.07068443 1.103537 1.071961 1.136042
## 16 8.337673 0.020395427 0.07486338 1.115911 1.085766 1.146893
## 17 8.235473 0.019512478 0.07437617 1.114152 1.083900 1.145248
## 18 8.391647 0.012624888 0.06838799 1.097758 1.067376 1.129004
## 19 8.288398 0.005136475 0.06103803 1.079164 1.049284 1.109894
## 20 11.154606 0.011498149 0.06760170 1.095342 1.063612 1.128019cbPalette <- c("#56B4E9", "#E69F00", "#D55E00","#009E73", "#999999")
#better labels#
graph <- ggplot(CONDEMM_graph, aes (x = Juv_treat, y=emmean10, colour=Parental_treat)) + geom_pointrange(aes (ymin = emmean.low, ymax = emmean.high), position=position_dodge(width=1), size=1) +
facet_grid(~factor(Juv_treat, levels =c( "zero_control","elevated_control", "zero_CO", "elevated_CO"),labels=str_wrap(c("Control", "Elevated Temperature", "Elevated CO2", "Elevated Temperature & CO2"), width = 10)), scales = "free_x") + labs(x="Juvenile treatment", y="Weight (g)") +
scale_x_discrete(breaks = c( "zero_control","elevated_control", "zero_CO", "elevated_CO"), labels = str_wrap(c("Control", "Warm temperature", "Elevated CO2", "Warm temperature & Elevated CO2"), width = 10)) +
scale_colour_manual(values=cbPalette, name = "Cross-generation treatment", labels = c("Control", "Parental development", "Grandparental development", "Grandparental post-maturation", "Continuous grandparent")) +
theme_calc() + theme(text = element_text(size=20)) + theme(panel.spacing = unit(1, "cm", data = NULL)) + theme_classic()+ theme(strip.text.x = element_blank())
print(graph)
ggsave("COND_graph.eps", graph, height = 6, width = 14, dpi = 320)Survival check
head(Growth_Data)## # A tibble: 6 × 21
## Tank Parental_number Female Male Maternal Maternal_GF Maternal_GM Paternal
## <fct> <fct> <dbl> <dbl> <chr> <fct> <fct> <chr>
## 1 1 72 42 220 DA D A EC
## 2 1 72 42 220 DA D A EC
## 3 1 72 42 220 DA D A EC
## 4 1 72 42 220 DA D A EC
## 5 1 72 42 220 DA D A EC
## 6 1 72 42 220 DA D A EC
## # ℹ 13 more variables: Paternal_GF <fct>, Paternal_GM <fct>, DOM <chr>,
## # DOD <chr>, Age <dbl>, Parental_treat <fct>, Temp <fct>, Control_CO <fct>,
## # Length <dbl>, Weight <dbl>, Density <dbl>, log_weight <dbl>,
## # log_length <dbl>S_data = Growth_Data %>% group_by(Tank, Parental_treat, Temp, Control_CO, Maternal_GF, Maternal_GM, Paternal_GF, Paternal_GM) %>% summarise(density = mean(Density)) %>% as.data.frame## `summarise()` has grouped output by 'Tank', 'Parental_treat', 'Temp',
## 'Control_CO', 'Maternal_GF', 'Maternal_GM', 'Paternal_GF'. You can override
## using the `.groups` argument.S_data## Tank Parental_treat Temp Control_CO Maternal_GF Maternal_GM Paternal_GF
## 1 1 HHCC zero CO D A E
## 2 2 HHCC elevated CO D A E
## 3 3 CCCH zero CO A E F
## 4 4 CCCH elevated CO A E F
## 5 5 CCHC zero CO D C A
## 6 6 CCHC elevated CO D C A
## 7 7 CCCC zero CO A E F
## 8 8 CCCC elevated CO A E F
## 9 9 HHCC zero CO D A A
## 10 10 HHCC elevated CO D A A
## 11 11 CCCC zero CO D A A
## 12 12 CCCC elevated CO D A A
## 13 13 HHCC zero CO D A C
## 14 14 HHCC elevated CO D A C
## 15 15 CCHC zero CO A C D
## 16 16 CCHC elevated CO A C D
## 17 17 HHHC zero CO A E C
## 18 19 CCCH zero CO F A D
## 19 20 CCCH elevated CO F A D
## 20 21 CCHC zero CO D C E
## 21 22 CCHC elevated CO D C E
## 22 23 CCCH zero CO D A A
## 23 24 CCCH elevated CO D A A
## 24 25 CCCC zero control A E F
## 25 26 CCCC elevated control A E F
## 26 27 CCCC zero control C A A
## 27 28 CCCC elevated control C A A
## 28 29 HHHC zero control D C C
## 29 30 HHHC elevated control D C C
## 30 31 CCCH zero control A E F
## 31 32 CCCH elevated control A E F
## 32 33 CCHC zero control D C A
## 33 34 CCHC elevated control D C A
## 34 35 HHHC zero control C A A
## 35 36 HHHC elevated control C A A
## 36 37 CCCH zero control C A D
## 37 38 CCCH elevated control C A D
## 38 39 CCCC zero control A E C
## 39 40 CCCC elevated control A E C
## 40 41 CCHC zero control D C D
## 41 42 CCHC elevated control D C D
## 42 43 HHCC zero control A C D
## 43 44 HHCC elevated control A C D
## 44 45 HHCC zero control D A E
## 45 46 HHCC elevated control D A E
## 46 47 CCHC zero control D A E
## 47 48 CCHC elevated control D A E
## 48 49 CCCC zero control A E F
## 49 50 CCCC elevated control A E F
## 50 51 CCCH zero control D A A
## 51 52 CCCH elevated control D A A
## 52 53 HHCC zero control D A E
## 53 54 HHCC elevated control D A E
## 54 55 CCHC zero control D C A
## 55 56 CCHC elevated control D C A
## 56 57 HHHC zero control A E C
## 57 58 HHHC elevated control A E C
## 58 59 CCHC zero control D C E
## 59 60 CCHC elevated control D C E
## 60 61 CCCC zero control D A A
## 61 62 CCCC elevated control D A A
## 62 64 HHCC elevated control D A C
## 63 65 CCCH zero control A E F
## 64 66 CCCH elevated control A E F
## 65 67 CCCH zero control F A D
## 66 68 CCCH elevated control F A D
## 67 69 CCHC zero control A C D
## 68 70 CCHC elevated control A C D
## 69 71 HHCC zero control D A A
## 70 72 HHCC elevated control D A A
## 71 73 CCHC zero CO D C A
## 72 74 CCHC elevated CO D C A
## 73 75 CCCC zero CO A E F
## 74 76 CCCC elevated CO A E F
## 75 77 CCCC zero CO C A A
## 76 78 CCCC elevated CO C A A
## 77 79 CCCH zero CO C A D
## 78 80 CCCH elevated CO C A D
## 79 81 CCCC zero CO A E C
## 80 82 CCCC elevated CO A E C
## 81 83 HHCC zero CO A C D
## 82 84 HHCC elevated CO A C D
## 83 85 HHHC zero CO D C C
## 84 86 HHHC elevated CO D C C
## 85 87 CCHC zero CO D A E
## 86 88 CCHC elevated CO D A E
## 87 89 HHCC zero CO D A E
## 88 90 HHCC elevated CO D A E
## 89 91 CCHC zero CO D C D
## 90 92 CCHC elevated CO D C D
## 91 93 HHHC zero CO A E C
## 92 94 HHHC elevated CO A E C
## 93 95 CCCH zero CO A E F
## 94 96 CCCH elevated CO A E F
## 95 97 CCCH elevated control A E F
## 96 98 CCCH zero control A E F
## 97 99 HHHC elevated control D C C
## 98 100 HHHC zero control D C C
## 99 101 CCCH elevated control C A D
## 100 101 CCCH zero control C A D
## 101 102 CCCH elevated control C A D
## 102 102 CCCH zero control C A D
## 103 103 HHCC elevated control A C D
## 104 104 HHCC zero control A C D
## 105 105 CCHC elevated control D C D
## 106 106 CCHC zero control D C D
## 107 107 CCCC zero control A E F
## 108 108 CCCC elevated control A E F
## 109 109 CCCC zero control C A A
## 110 110 CCCC elevated control C A A
## 111 111 CCHC zero control D A E
## 112 112 CCHC elevated control D A E
## 113 113 HHHC zero control A E C
## 114 114 HHHC elevated control A E C
## 115 115 CCCC zero control A E C
## 116 116 CCCC elevated control A E C
## 117 117 HHCC elevated CO D A C
## 118 118 HHCC zero CO D A C
## 119 119 CCHC elevated CO A C D
## 120 120 CCHC zero CO A C D
## 121 121 HHCC elevated CO D A A
## 122 122 HHCC zero CO D A A
## 123 123 CCHC elevated CO D C E
## 124 124 CCHC zero CO D C E
## 125 125 CCCH elevated CO F A D
## 126 126 CCCH zero CO F A D
## 127 127 CCCH zero CO A E F
## 128 128 CCCH elevated CO A E F
## 129 129 CCCH zero CO D A A
## 130 130 CCCH elevated CO D A A
## 131 131 CCCC zero CO A E F
## 132 132 CCCC elevated CO A E F
## 133 133 HHHC zero CO A E C
## 134 134 HHHC elevated CO A E C
## 135 135 CCCC zero CO D A A
## 136 136 CCCC elevated CO D A A
## 137 137 CCCC zero CO A E F
## 138 138 CCCC elevated CO A E F
## 139 139 CCCH zero CO C A D
## 140 140 CCCH elevated CO C A D
## 141 141 CCHC zero CO D C D
## 142 142 CCHC elevated CO D C D
## 143 143 HHHC zero CO C A A
## 144 144 HHHC elevated CO C A A
## 145 145 CCHC zero CO D A E
## 146 146 CCHC elevated CO D A E
## 147 147 CCCC elevated CO C A A
## 148 148 CCCC zero CO C A A
## 149 149 HHHC elevated CO D C C
## 150 150 HHHC zero CO D C C
## 151 151 CCCC elevated CO A E C
## 152 152 CCCC zero CO A E C
## 153 153 HHCC elevated CO A C D
## 154 154 HHCC zero CO A C D
## 155 155 CCCH elevated CO A E F
## 156 156 CCCH zero CO A E F
## 157 157 CCCH elevated control A E F
## 158 158 CCCH zero control A E F
## 159 159 CCCC elevated control A E F
## 160 160 CCCC zero control A E F
## 161 161 CCHC elevated control D C E
## 162 162 CCHC zero control D C E
## 163 163 HHCC elevated control D A A
## 164 164 HHCC zero control D A A
## 165 165 CCCC elevated control D A A
## 166 166 CCCC zero control D A A
## 167 167 CCCH elevated control D A A
## 168 168 CCCH zero control D A A
## 169 169 CCHC elevated control A C D
## 170 170 CCHC zero control A C D
## 171 171 HHCC elevated control D A C
## 172 172 HHCC zero control D A C
## 173 175 CCCH elevated control F A D
## 174 176 CCCH zero control F A D
## 175 177 HHCC zero control D A A
## 176 178 HHCC elevated control D A A
## 177 179 HHCC elevated CO D A A
## 178 180 HHCC zero CO D A A
## 179 181 HHCC zero CO D A A
## 180 182 HHCC elevated CO D A A
## 181 183 HHCC elevated control D A A
## 182 184 HHCC zero control D A A
## 183 186 HHHC zero CO C A A
## 184 187 HHHC elevated CO C A A
## 185 188 HHHC elevated control C A A
## Paternal_GM density
## 1 C 20
## 2 C 17
## 3 E 19
## 4 E 19
## 5 C 19
## 6 C 19
## 7 E 15
## 8 E 16
## 9 C 16
## 10 C 18
## 11 E 20
## 12 E 19
## 13 A 15
## 14 A 8
## 15 A 20
## 16 A 17
## 17 A 11
## 18 A 18
## 19 A 15
## 20 A 19
## 21 A 17
## 22 E 15
## 23 E 11
## 24 A 11
## 25 A 9
## 26 E 17
## 27 E 15
## 28 A 17
## 29 A 17
## 30 A 17
## 31 A 17
## 32 C 16
## 33 C 15
## 34 E 14
## 35 E 3
## 36 A 17
## 37 A 17
## 38 A 16
## 39 A 12
## 40 A 18
## 41 A 19
## 42 A 7
## 43 A 5
## 44 C 19
## 45 C 20
## 46 C 16
## 47 C 14
## 48 E 18
## 49 E 17
## 50 E 15
## 51 E 5
## 52 C 20
## 53 C 20
## 54 C 19
## 55 C 16
## 56 A 10
## 57 A 9
## 58 A 18
## 59 A 20
## 60 E 20
## 61 E 20
## 62 A 11
## 63 E 19
## 64 E 19
## 65 A 18
## 66 A 17
## 67 A 18
## 68 A 19
## 69 C 16
## 70 C 16
## 71 C 19
## 72 C 15
## 73 A 17
## 74 A 18
## 75 E 16
## 76 E 21
## 77 A 15
## 78 A 19
## 79 A 15
## 80 A 13
## 81 A 19
## 82 A 17
## 83 A 20
## 84 A 19
## 85 C 18
## 86 C 18
## 87 C 19
## 88 C 19
## 89 A 18
## 90 A 17
## 91 A 15
## 92 A 13
## 93 A 16
## 94 A 20
## 95 A 17
## 96 A 19
## 97 A 18
## 98 A 18
## 99 A 20
## 100 A 20
## 101 A 19
## 102 A 19
## 103 A 18
## 104 A 14
## 105 A 20
## 106 A 20
## 107 A 15
## 108 A 15
## 109 E 19
## 110 E 19
## 111 C 17
## 112 C 21
## 113 A 14
## 114 A 17
## 115 A 12
## 116 A 9
## 117 A 19
## 118 A 17
## 119 A 19
## 120 A 19
## 121 C 17
## 122 C 17
## 123 A 17
## 124 A 17
## 125 A 16
## 126 A 20
## 127 E 19
## 128 E 20
## 129 E 11
## 130 E 18
## 131 E 21
## 132 E 13
## 133 A 20
## 134 A 18
## 135 E 20
## 136 E 16
## 137 A 12
## 138 A 4
## 139 A 18
## 140 A 18
## 141 A 18
## 142 A 20
## 143 E 7
## 144 E 6
## 145 C 20
## 146 C 20
## 147 E 18
## 148 E 19
## 149 A 20
## 150 A 16
## 151 A 12
## 152 A 16
## 153 A 6
## 154 A 18
## 155 A 20
## 156 A 19
## 157 E 14
## 158 E 20
## 159 E 17
## 160 E 14
## 161 A 14
## 162 A 14
## 163 C 9
## 164 C 15
## 165 E 19
## 166 E 20
## 167 E 3
## 168 E 11
## 169 A 19
## 170 A 19
## 171 A 6
## 172 A 11
## 173 A 15
## 174 A 14
## 175 E 12
## 176 E 14
## 177 E 18
## 178 E 17
## 179 E 19
## 180 E 20
## 181 E 19
## 182 E 10
## 183 E 15
## 184 E 13
## 185 E 15ggplot(S_data, aes(y=density, x=Temp, colour=Parental_treat)) + geom_boxplot() +facet_grid(~factor(Control_CO))
#presence absence
head(S_data)## Tank Parental_treat Temp Control_CO Maternal_GF Maternal_GM Paternal_GF
## 1 1 HHCC zero CO D A E
## 2 2 HHCC elevated CO D A E
## 3 3 CCCH zero CO A E F
## 4 4 CCCH elevated CO A E F
## 5 5 CCHC zero CO D C A
## 6 6 CCHC elevated CO D C A
## Paternal_GM density
## 1 C 20
## 2 C 17
## 3 E 19
## 4 E 19
## 5 C 19
## 6 C 19survival_prop <- mutate(S_data, absence= 21-density)
head(survival_prop)## Tank Parental_treat Temp Control_CO Maternal_GF Maternal_GM Paternal_GF
## 1 1 HHCC zero CO D A E
## 2 2 HHCC elevated CO D A E
## 3 3 CCCH zero CO A E F
## 4 4 CCCH elevated CO A E F
## 5 5 CCHC zero CO D C A
## 6 6 CCHC elevated CO D C A
## Paternal_GM density absence
## 1 C 20 1
## 2 C 17 4
## 3 E 19 2
## 4 E 19 2
## 5 C 19 2
## 6 C 19 2survival <- cbind(survival_prop$density, survival_prop$absence)
survival## [,1] [,2]
## [1,] 20 1
## [2,] 17 4
## [3,] 19 2
## [4,] 19 2
## [5,] 19 2
## [6,] 19 2
## [7,] 15 6
## [8,] 16 5
## [9,] 16 5
## [10,] 18 3
## [11,] 20 1
## [12,] 19 2
## [13,] 15 6
## [14,] 8 13
## [15,] 20 1
## [16,] 17 4
## [17,] 11 10
## [18,] 18 3
## [19,] 15 6
## [20,] 19 2
## [21,] 17 4
## [22,] 15 6
## [23,] 11 10
## [24,] 11 10
## [25,] 9 12
## [26,] 17 4
## [27,] 15 6
## [28,] 17 4
## [29,] 17 4
## [30,] 17 4
## [31,] 17 4
## [32,] 16 5
## [33,] 15 6
## [34,] 14 7
## [35,] 3 18
## [36,] 17 4
## [37,] 17 4
## [38,] 16 5
## [39,] 12 9
## [40,] 18 3
## [41,] 19 2
## [42,] 7 14
## [43,] 5 16
## [44,] 19 2
## [45,] 20 1
## [46,] 16 5
## [47,] 14 7
## [48,] 18 3
## [49,] 17 4
## [50,] 15 6
## [51,] 5 16
## [52,] 20 1
## [53,] 20 1
## [54,] 19 2
## [55,] 16 5
## [56,] 10 11
## [57,] 9 12
## [58,] 18 3
## [59,] 20 1
## [60,] 20 1
## [61,] 20 1
## [62,] 11 10
## [63,] 19 2
## [64,] 19 2
## [65,] 18 3
## [66,] 17 4
## [67,] 18 3
## [68,] 19 2
## [69,] 16 5
## [70,] 16 5
## [71,] 19 2
## [72,] 15 6
## [73,] 17 4
## [74,] 18 3
## [75,] 16 5
## [76,] 21 0
## [77,] 15 6
## [78,] 19 2
## [79,] 15 6
## [80,] 13 8
## [81,] 19 2
## [82,] 17 4
## [83,] 20 1
## [84,] 19 2
## [85,] 18 3
## [86,] 18 3
## [87,] 19 2
## [88,] 19 2
## [89,] 18 3
## [90,] 17 4
## [91,] 15 6
## [92,] 13 8
## [93,] 16 5
## [94,] 20 1
## [95,] 17 4
## [96,] 19 2
## [97,] 18 3
## [98,] 18 3
## [99,] 20 1
## [100,] 20 1
## [101,] 19 2
## [102,] 19 2
## [103,] 18 3
## [104,] 14 7
## [105,] 20 1
## [106,] 20 1
## [107,] 15 6
## [108,] 15 6
## [109,] 19 2
## [110,] 19 2
## [111,] 17 4
## [112,] 21 0
## [113,] 14 7
## [114,] 17 4
## [115,] 12 9
## [116,] 9 12
## [117,] 19 2
## [118,] 17 4
## [119,] 19 2
## [120,] 19 2
## [121,] 17 4
## [122,] 17 4
## [123,] 17 4
## [124,] 17 4
## [125,] 16 5
## [126,] 20 1
## [127,] 19 2
## [128,] 20 1
## [129,] 11 10
## [130,] 18 3
## [131,] 21 0
## [132,] 13 8
## [133,] 20 1
## [134,] 18 3
## [135,] 20 1
## [136,] 16 5
## [137,] 12 9
## [138,] 4 17
## [139,] 18 3
## [140,] 18 3
## [141,] 18 3
## [142,] 20 1
## [143,] 7 14
## [144,] 6 15
## [145,] 20 1
## [146,] 20 1
## [147,] 18 3
## [148,] 19 2
## [149,] 20 1
## [150,] 16 5
## [151,] 12 9
## [152,] 16 5
## [153,] 6 15
## [154,] 18 3
## [155,] 20 1
## [156,] 19 2
## [157,] 14 7
## [158,] 20 1
## [159,] 17 4
## [160,] 14 7
## [161,] 14 7
## [162,] 14 7
## [163,] 9 12
## [164,] 15 6
## [165,] 19 2
## [166,] 20 1
## [167,] 3 18
## [168,] 11 10
## [169,] 19 2
## [170,] 19 2
## [171,] 6 15
## [172,] 11 10
## [173,] 15 6
## [174,] 14 7
## [175,] 12 9
## [176,] 14 7
## [177,] 18 3
## [178,] 17 4
## [179,] 19 2
## [180,] 20 1
## [181,] 19 2
## [182,] 10 11
## [183,] 15 6
## [184,] 13 8
## [185,] 15 6s_glmer = glmer(survival ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) + (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM), data = survival_prop , family="binomial") model analysis
summary(s_glmer)## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: survival ~ Parental_treat * Temp * Control_CO + (1 | Maternal_GF) +
## (1 | Maternal_GM) + (1 | Paternal_GF) + (1 | Paternal_GM)
## Data: survival_prop
##
## AIC BIC logLik deviance df.resid
## 1135.0 1212.3 -543.5 1087.0 161
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.0849 -0.8397 0.3283 1.2176 3.0426
##
## Random effects:
## Groups Name Variance Std.Dev.
## Paternal_GF (Intercept) 0.21485 0.4635
## Maternal_GF (Intercept) 0.09429 0.3071
## Paternal_GM (Intercept) 0.17269 0.4156
## Maternal_GM (Intercept) 0.02675 0.1636
## Number of obs: 185, groups:
## Paternal_GF, 5; Maternal_GF, 4; Paternal_GM, 3; Maternal_GM, 3
##
## Fixed effects:
## Estimate Std. Error z value
## (Intercept) 1.45947 0.41390 3.526
## Parental_treatCCCH 0.45859 0.25540 1.796
## Parental_treatHHCC -0.20611 0.25070 -0.822
## Parental_treatCCHC 0.08185 0.31322 0.261
## Parental_treatHHHC -0.02164 0.26628 -0.081
## Tempzero 0.56943 0.23556 2.417
## Control_COcontrol 0.04772 0.21873 0.218
## Parental_treatCCCH:Tempzero -0.76890 0.34933 -2.201
## Parental_treatHHCC:Tempzero -0.01589 0.34411 -0.046
## Parental_treatCCHC:Tempzero -0.22324 0.37779 -0.591
## Parental_treatHHHC:Tempzero -0.51561 0.35819 -1.439
## Parental_treatCCCH:Control_COcontrol -0.85715 0.32340 -2.650
## Parental_treatHHCC:Control_COcontrol -0.54782 0.31002 -1.767
## Parental_treatCCHC:Control_COcontrol -0.12243 0.34970 -0.350
## Parental_treatHHHC:Control_COcontrol -0.41504 0.34894 -1.189
## Tempzero:Control_COcontrol -0.31266 0.32708 -0.956
## Parental_treatCCCH:Tempzero:Control_COcontrol 1.15148 0.47338 2.432
## Parental_treatHHCC:Tempzero:Control_COcontrol -0.27576 0.46502 -0.593
## Parental_treatCCHC:Tempzero:Control_COcontrol -0.10474 0.51491 -0.203
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.55561 0.51081 1.088
## Pr(>|z|)
## (Intercept) 0.000422 ***
## Parental_treatCCCH 0.072565 .
## Parental_treatHHCC 0.411018
## Parental_treatCCHC 0.793850
## Parental_treatHHHC 0.935226
## Tempzero 0.015635 *
## Control_COcontrol 0.827290
## Parental_treatCCCH:Tempzero 0.027731 *
## Parental_treatHHCC:Tempzero 0.963162
## Parental_treatCCHC:Tempzero 0.554577
## Parental_treatHHHC:Tempzero 0.150014
## Parental_treatCCCH:Control_COcontrol 0.008038 **
## Parental_treatHHCC:Control_COcontrol 0.077220 .
## Parental_treatCCHC:Control_COcontrol 0.726259
## Parental_treatHHHC:Control_COcontrol 0.234262
## Tempzero:Control_COcontrol 0.339117
## Parental_treatCCCH:Tempzero:Control_COcontrol 0.014997 *
## Parental_treatHHCC:Tempzero:Control_COcontrol 0.553185
## Parental_treatCCHC:Tempzero:Control_COcontrol 0.838812
## Parental_treatHHHC:Tempzero:Control_COcontrol 0.276718
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Correlation matrix not shown by default, as p = 20 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need itAnova(s_glmer)## Analysis of Deviance Table (Type II Wald chisquare tests)
##
## Response: survival
## Chisq Df Pr(>Chisq)
## Parental_treat 21.9836 4 0.0002019 ***
## Temp 10.0559 1 0.0015186 **
## Control_CO 21.5229 1 3.496e-06 ***
## Parental_treat:Temp 1.6272 4 0.8039006
## Parental_treat:Control_CO 9.2115 4 0.0560242 .
## Temp:Control_CO 0.1219 1 0.7269540
## Parental_treat:Temp:Control_CO 11.4530 4 0.0219181 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1library(DHARMa)## This is DHARMa 0.4.6. For overview type '?DHARMa'. For recent changes, type news(package = 'DHARMa')plot(s_glmer)
plot(simulateResiduals(s_glmer))
plot(emmeans(s_glmer, pairwise ~ Control_CO, type = "response"))## NOTE: Results may be misleading due to involvement in interactions
emmeans(s_glmer, pairwise ~ Control_CO, type="response" )## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Control_CO prob SE df asymp.LCL asymp.UCL
## CO 0.839 0.0514 Inf 0.712 0.917
## control 0.784 0.0644 Inf 0.633 0.884
##
## Results are averaged over the levels of: Parental_treat, Temp
## Confidence level used: 0.95
## Intervals are back-transformed from the logit scale
##
## $contrasts
## contrast odds.ratio SE df null z.ratio p.value
## CO / control 1.44 0.116 Inf 1 4.531 <.0001
##
## Results are averaged over the levels of: Parental_treat, Temp
## Tests are performed on the log odds ratio scaleplot(emmeans(s_glmer, pairwise ~ Parental_treat, type="response" ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(s_glmer, pairwise ~ Parental_treat, type="response")## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Parental_treat prob SE df asymp.LCL asymp.UCL
## CCCC 0.844 0.0517 Inf 0.715 0.921
## CCCH 0.835 0.0550 Inf 0.698 0.917
## HHCC 0.756 0.0738 Inf 0.586 0.872
## CCHC 0.828 0.0574 Inf 0.686 0.914
## HHHC 0.793 0.0645 Inf 0.639 0.892
##
## Results are averaged over the levels of: Temp, Control_CO
## Confidence level used: 0.95
## Intervals are back-transformed from the logit scale
##
## $contrasts
## contrast odds.ratio SE df null z.ratio p.value
## CCCC / CCCH 1.069 0.154 Inf 1 0.463 0.9906
## CCCC / HHCC 1.745 0.285 Inf 1 3.416 0.0057
## CCCC / CCHC 1.124 0.258 Inf 1 0.510 0.9864
## CCCC / HHHC 1.416 0.222 Inf 1 2.217 0.1735
## CCCH / HHCC 1.633 0.262 Inf 1 3.060 0.0188
## CCCH / CCHC 1.052 0.247 Inf 1 0.216 0.9995
## CCCH / HHHC 1.325 0.266 Inf 1 1.404 0.6249
## HHCC / CCHC 0.644 0.124 Inf 1 -2.285 0.1497
## HHCC / HHHC 0.812 0.158 Inf 1 -1.074 0.8199
## CCHC / HHHC 1.260 0.287 Inf 1 1.015 0.8488
##
## Results are averaged over the levels of: Temp, Control_CO
## P value adjustment: tukey method for comparing a family of 5 estimates
## Tests are performed on the log odds ratio scaleplot(emmeans(s_glmer, pairwise ~ Temp, type="response" ) )## NOTE: Results may be misleading due to involvement in interactions
emmeans(s_glmer, pairwise ~ Temp, type="response")## NOTE: Results may be misleading due to involvement in interactions## $emmeans
## Temp prob SE df asymp.LCL asymp.UCL
## elevated 0.794 0.0621 Inf 0.647 0.891
## zero 0.831 0.0535 Inf 0.700 0.912
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Confidence level used: 0.95
## Intervals are back-transformed from the logit scale
##
## $contrasts
## contrast odds.ratio SE df null z.ratio p.value
## elevated / zero 0.786 0.0632 Inf 1 -2.999 0.0027
##
## Results are averaged over the levels of: Parental_treat, Control_CO
## Tests are performed on the log odds ratio scaleplot(emmeans(s_glmer, pairwise ~ Temp * Control_CO* Parental_treat, type="response") )
emmeans(s_glmer, pairwise ~ Temp * Control_CO* Parental_treat, type="response")## $emmeans
## Temp Control_CO Parental_treat prob SE df asymp.LCL asymp.UCL
## elevated CO CCCC 0.811 0.0633 Inf 0.657 0.906
## zero CO CCCC 0.884 0.0435 Inf 0.768 0.946
## elevated control CCCC 0.819 0.0615 Inf 0.667 0.910
## zero control CCCC 0.854 0.0522 Inf 0.720 0.930
## elevated CO CCCH 0.872 0.0484 Inf 0.744 0.941
## zero CO CCCH 0.848 0.0552 Inf 0.707 0.928
## elevated control CCCH 0.752 0.0778 Inf 0.572 0.873
## zero control CCCH 0.852 0.0539 Inf 0.713 0.930
## elevated CO HHCC 0.778 0.0734 Inf 0.604 0.890
## zero CO HHCC 0.859 0.0529 Inf 0.721 0.935
## elevated control HHCC 0.680 0.0912 Inf 0.483 0.828
## zero control HHCC 0.672 0.0928 Inf 0.473 0.824
## elevated CO CCHC 0.824 0.0635 Inf 0.665 0.917
## zero CO CCHC 0.868 0.0513 Inf 0.732 0.941
## elevated control CCHC 0.813 0.0662 Inf 0.649 0.910
## zero control CCHC 0.801 0.0689 Inf 0.633 0.904
## elevated CO HHHC 0.808 0.0664 Inf 0.645 0.907
## zero CO HHHC 0.816 0.0635 Inf 0.660 0.911
## elevated control HHHC 0.745 0.0804 Inf 0.560 0.870
## zero control HHHC 0.797 0.0707 Inf 0.625 0.902
##
## Confidence level used: 0.95
## Intervals are back-transformed from the logit scale
##
## $contrasts
## contrast odds.ratio SE df null
## elevated CO CCCC / zero CO CCCC 0.566 0.1333 Inf 1
## elevated CO CCCC / elevated control CCCC 0.953 0.2085 Inf 1
## elevated CO CCCC / zero control CCCC 0.737 0.1666 Inf 1
## elevated CO CCCC / elevated CO CCCH 0.632 0.1615 Inf 1
## elevated CO CCCC / zero CO CCCH 0.772 0.1907 Inf 1
## elevated CO CCCC / elevated control CCCH 1.420 0.3236 Inf 1
## elevated CO CCCC / zero control CCCH 0.749 0.1833 Inf 1
## elevated CO CCCC / elevated CO HHCC 1.229 0.3081 Inf 1
## elevated CO CCCC / zero CO HHCC 0.706 0.1902 Inf 1
## elevated CO CCCC / elevated control HHCC 2.026 0.4907 Inf 1
## elevated CO CCCC / zero control HHCC 2.098 0.5232 Inf 1
## elevated CO CCCC / elevated CO CCHC 0.921 0.2886 Inf 1
## elevated CO CCCC / zero CO CCHC 0.652 0.2152 Inf 1
## elevated CO CCCC / elevated control CCHC 0.993 0.3080 Inf 1
## elevated CO CCCC / zero control CCHC 1.066 0.3279 Inf 1
## elevated CO CCCC / elevated CO HHHC 1.022 0.2721 Inf 1
## elevated CO CCCC / zero CO HHHC 0.968 0.2469 Inf 1
## elevated CO CCCC / elevated control HHHC 1.475 0.3819 Inf 1
## elevated CO CCCC / zero control HHHC 1.097 0.3101 Inf 1
## zero CO CCCC / elevated control CCCC 1.685 0.3986 Inf 1
## zero CO CCCC / zero control CCCC 1.303 0.3170 Inf 1
## zero CO CCCC / elevated CO CCCH 1.117 0.3031 Inf 1
## zero CO CCCC / zero CO CCCH 1.364 0.3595 Inf 1
## zero CO CCCC / elevated control CCCH 2.510 0.6164 Inf 1
## zero CO CCCC / zero control CCCH 1.324 0.3460 Inf 1
## zero CO CCCC / elevated CO HHCC 2.172 0.5789 Inf 1
## zero CO CCCC / zero CO HHCC 1.249 0.3547 Inf 1
## zero CO CCCC / elevated control HHCC 3.581 0.9259 Inf 1
## zero CO CCCC / zero control HHCC 3.708 0.9840 Inf 1
## zero CO CCCC / elevated CO CCHC 1.628 0.5309 Inf 1
## zero CO CCCC / zero CO CCHC 1.152 0.3943 Inf 1
## zero CO CCCC / elevated control CCHC 1.755 0.5671 Inf 1
## zero CO CCCC / zero control CCHC 1.884 0.6041 Inf 1
## zero CO CCCC / elevated CO HHHC 1.806 0.5066 Inf 1
## zero CO CCCC / zero CO HHHC 1.711 0.4616 Inf 1
## zero CO CCCC / elevated control HHHC 2.608 0.7132 Inf 1
## zero CO CCCC / zero control HHHC 1.938 0.5740 Inf 1
## elevated control CCCC / zero control CCCC 0.774 0.1755 Inf 1
## elevated control CCCC / elevated CO CCCH 0.663 0.1700 Inf 1
## elevated control CCCC / zero CO CCCH 0.809 0.2009 Inf 1
## elevated control CCCC / elevated control CCCH 1.490 0.3411 Inf 1
## elevated control CCCC / zero control CCCH 0.786 0.1931 Inf 1
## elevated control CCCC / elevated CO HHCC 1.289 0.3244 Inf 1
## elevated control CCCC / zero CO HHCC 0.741 0.2002 Inf 1
## elevated control CCCC / elevated control HHCC 2.125 0.5168 Inf 1
## elevated control CCCC / zero control HHCC 2.201 0.5510 Inf 1
## elevated control CCCC / elevated CO CCHC 0.966 0.3035 Inf 1
## elevated control CCCC / zero CO CCHC 0.684 0.2262 Inf 1
## elevated control CCCC / elevated control CCHC 1.041 0.3239 Inf 1
## elevated control CCCC / zero control CCHC 1.118 0.3448 Inf 1
## elevated control CCCC / elevated CO HHHC 1.072 0.2863 Inf 1
## elevated control CCCC / zero CO HHHC 1.016 0.2598 Inf 1
## elevated control CCCC / elevated control HHHC 1.548 0.4019 Inf 1
## elevated control CCCC / zero control HHHC 1.150 0.3261 Inf 1
## zero control CCCC / elevated CO CCCH 0.857 0.2252 Inf 1
## zero control CCCC / zero CO CCCH 1.046 0.2666 Inf 1
## zero control CCCC / elevated control CCCH 1.926 0.4546 Inf 1
## zero control CCCC / zero control CCCH 1.016 0.2564 Inf 1
## zero control CCCC / elevated CO HHCC 1.666 0.4299 Inf 1
## zero control CCCC / zero CO HHCC 0.958 0.2644 Inf 1
## zero control CCCC / elevated control HHCC 2.748 0.6860 Inf 1
## zero control CCCC / zero control HHCC 2.845 0.7303 Inf 1
## zero control CCCC / elevated CO CCHC 1.249 0.3986 Inf 1
## zero control CCCC / zero CO CCHC 0.884 0.2966 Inf 1
## zero control CCCC / elevated control CCHC 1.346 0.4256 Inf 1
## zero control CCCC / zero control CCHC 1.446 0.4532 Inf 1
## zero control CCCC / elevated CO HHHC 1.386 0.3779 Inf 1
## zero control CCCC / zero CO HHHC 1.313 0.3435 Inf 1
## zero control CCCC / elevated control HHHC 2.001 0.5311 Inf 1
## zero control CCCC / zero control HHHC 1.487 0.4294 Inf 1
## elevated CO CCCH / zero CO CCCH 1.221 0.3149 Inf 1
## elevated CO CCCH / elevated control CCCH 2.247 0.5352 Inf 1
## elevated CO CCCH / zero control CCCH 1.185 0.3019 Inf 1
## elevated CO CCCH / elevated CO HHCC 1.944 0.5256 Inf 1
## elevated CO CCCH / zero CO HHCC 1.118 0.3216 Inf 1
## elevated CO CCCH / elevated control HHCC 3.205 0.8409 Inf 1
## elevated CO CCCH / zero control HHCC 3.319 0.8925 Inf 1
## elevated CO CCCH / elevated CO CCHC 1.458 0.4866 Inf 1
## elevated CO CCCH / zero CO CCHC 1.031 0.3607 Inf 1
## elevated CO CCCH / elevated control CCHC 1.571 0.5199 Inf 1
## elevated CO CCCH / zero control CCHC 1.687 0.5540 Inf 1
## elevated CO CCCH / elevated CO HHHC 1.616 0.5036 Inf 1
## elevated CO CCCH / zero CO HHHC 1.532 0.4634 Inf 1
## elevated CO CCCH / elevated control HHHC 2.334 0.7122 Inf 1
## elevated CO CCCH / zero control HHHC 1.735 0.5657 Inf 1
## zero CO CCCH / elevated control CCCH 1.840 0.4218 Inf 1
## zero CO CCCH / zero control CCCH 0.971 0.2392 Inf 1
## zero CO CCCH / elevated CO HHCC 1.592 0.4181 Inf 1
## zero CO CCCH / zero CO HHCC 0.915 0.2567 Inf 1
## zero CO CCCH / elevated control HHCC 2.626 0.6676 Inf 1
## zero CO CCCH / zero control HHCC 2.719 0.7097 Inf 1
## zero CO CCCH / elevated CO CCHC 1.194 0.3910 Inf 1
## zero CO CCCH / zero CO CCHC 0.845 0.2904 Inf 1
## zero CO CCCH / elevated control CCHC 1.287 0.4176 Inf 1
## zero CO CCCH / zero control CCHC 1.382 0.4449 Inf 1
## zero CO CCCH / elevated CO HHHC 1.324 0.4036 Inf 1
## zero CO CCCH / zero CO HHHC 1.255 0.3708 Inf 1
## zero CO CCCH / elevated control HHHC 1.912 0.5701 Inf 1
## zero CO CCCH / zero control HHHC 1.421 0.4542 Inf 1
## elevated control CCCH / zero control CCCH 0.528 0.1186 Inf 1
## elevated control CCCH / elevated CO HHCC 0.865 0.2101 Inf 1
## elevated control CCCH / zero CO HHCC 0.497 0.1304 Inf 1
## elevated control CCCH / elevated control HHCC 1.427 0.3335 Inf 1
## elevated control CCCH / zero control HHCC 1.477 0.3564 Inf 1
## elevated control CCCH / elevated CO CCHC 0.649 0.2020 Inf 1
## elevated control CCCH / zero CO CCHC 0.459 0.1508 Inf 1
## elevated control CCCH / elevated control CCHC 0.699 0.2156 Inf 1
## elevated control CCCH / zero control CCHC 0.751 0.2294 Inf 1
## elevated control CCCH / elevated CO HHHC 0.720 0.2076 Inf 1
## elevated control CCCH / zero CO HHHC 0.682 0.1902 Inf 1
## elevated control CCCH / elevated control HHHC 1.039 0.2925 Inf 1
## elevated control CCCH / zero control HHHC 0.772 0.2350 Inf 1
## zero control CCCH / elevated CO HHCC 1.640 0.4247 Inf 1
## zero control CCCH / zero CO HHCC 0.943 0.2612 Inf 1
## zero control CCCH / elevated control HHCC 2.704 0.6774 Inf 1
## zero control CCCH / zero control HHCC 2.800 0.7209 Inf 1
## zero control CCCH / elevated CO CCHC 1.230 0.3988 Inf 1
## zero control CCCH / zero CO CCHC 0.870 0.2964 Inf 1
## zero control CCCH / elevated control CCHC 1.325 0.4258 Inf 1
## zero control CCCH / zero control CCHC 1.423 0.4536 Inf 1
## zero control CCCH / elevated CO HHHC 1.364 0.4121 Inf 1
## zero control CCCH / zero CO HHHC 1.292 0.3786 Inf 1
## zero control CCCH / elevated control HHHC 1.969 0.5819 Inf 1
## zero control CCCH / zero control HHHC 1.463 0.4643 Inf 1
## elevated CO HHCC / zero CO HHCC 0.575 0.1442 Inf 1
## elevated CO HHCC / elevated control HHCC 1.649 0.3623 Inf 1
## elevated CO HHCC / zero control HHCC 1.707 0.3859 Inf 1
## elevated CO HHCC / elevated CO CCHC 0.750 0.2198 Inf 1
## elevated CO HHCC / zero CO CCHC 0.530 0.1651 Inf 1
## elevated CO HHCC / elevated control CCHC 0.808 0.2342 Inf 1
## elevated CO HHCC / zero control CCHC 0.868 0.2490 Inf 1
## elevated CO HHCC / elevated CO HHHC 0.832 0.2447 Inf 1
## elevated CO HHCC / zero CO HHHC 0.788 0.2243 Inf 1
## elevated CO HHCC / elevated control HHHC 1.201 0.3445 Inf 1
## elevated CO HHCC / zero control HHHC 0.892 0.2734 Inf 1
## zero CO HHCC / elevated control HHCC 2.868 0.6924 Inf 1
## zero CO HHCC / zero control HHCC 2.970 0.7346 Inf 1
## zero CO HHCC / elevated CO CCHC 1.304 0.4051 Inf 1
## zero CO HHCC / zero CO CCHC 0.923 0.3024 Inf 1
## zero CO HHCC / elevated control CCHC 1.405 0.4322 Inf 1
## zero CO HHCC / zero control CCHC 1.509 0.4599 Inf 1
## zero CO HHCC / elevated CO HHHC 1.446 0.4488 Inf 1
## zero CO HHCC / zero CO HHHC 1.371 0.4129 Inf 1
## zero CO HHCC / elevated control HHHC 2.088 0.6335 Inf 1
## zero CO HHCC / zero control HHHC 1.552 0.4995 Inf 1
## elevated control HHCC / zero control HHCC 1.035 0.2228 Inf 1
## elevated control HHCC / elevated CO CCHC 0.455 0.1291 Inf 1
## elevated control HHCC / zero CO CCHC 0.322 0.0973 Inf 1
## elevated control HHCC / elevated control CCHC 0.490 0.1374 Inf 1
## elevated control HHCC / zero control CCHC 0.526 0.1460 Inf 1
## elevated control HHCC / elevated CO HHHC 0.504 0.1447 Inf 1
## elevated control HHCC / zero CO HHHC 0.478 0.1324 Inf 1
## elevated control HHCC / elevated control HHHC 0.728 0.2034 Inf 1
## elevated control HHCC / zero control HHHC 0.541 0.1619 Inf 1
## zero control HHCC / elevated CO CCHC 0.439 0.1245 Inf 1
## zero control HHCC / zero CO CCHC 0.311 0.0939 Inf 1
## zero control HHCC / elevated control CCHC 0.473 0.1326 Inf 1
## zero control HHCC / zero control CCHC 0.508 0.1408 Inf 1
## zero control HHCC / elevated CO HHHC 0.487 0.1430 Inf 1
## zero control HHCC / zero CO HHHC 0.462 0.1312 Inf 1
## zero control HHCC / elevated control HHHC 0.703 0.2013 Inf 1
## zero control HHCC / zero control HHHC 0.523 0.1599 Inf 1
## elevated CO CCHC / zero CO CCHC 0.707 0.2089 Inf 1
## elevated CO CCHC / elevated control CCHC 1.078 0.2940 Inf 1
## elevated CO CCHC / zero control CCHC 1.157 0.3122 Inf 1
## elevated CO CCHC / elevated CO HHHC 1.109 0.3675 Inf 1
## elevated CO CCHC / zero CO HHHC 1.051 0.3422 Inf 1
## elevated CO CCHC / elevated control HHHC 1.601 0.5185 Inf 1
## elevated CO CCHC / zero control HHHC 1.190 0.4041 Inf 1
## zero CO CCHC / elevated control CCHC 1.523 0.4451 Inf 1
## zero CO CCHC / zero control CCHC 1.636 0.4733 Inf 1
## zero CO CCHC / elevated CO HHHC 1.568 0.5445 Inf 1
## zero CO CCHC / zero CO HHHC 1.486 0.5078 Inf 1
## zero CO CCHC / elevated control HHHC 2.264 0.7699 Inf 1
## zero CO CCHC / zero control HHHC 1.682 0.5975 Inf 1
## elevated control CCHC / zero control CCHC 1.074 0.2860 Inf 1
## elevated control CCHC / elevated CO HHHC 1.029 0.3382 Inf 1
## elevated control CCHC / zero CO HHHC 0.975 0.3148 Inf 1
## elevated control CCHC / elevated control HHHC 1.486 0.4769 Inf 1
## elevated control CCHC / zero control HHHC 1.104 0.3720 Inf 1
## zero control CCHC / elevated CO HHHC 0.958 0.3125 Inf 1
## zero control CCHC / zero CO HHHC 0.908 0.2908 Inf 1
## zero control CCHC / elevated control HHHC 1.384 0.4406 Inf 1
## zero control CCHC / zero control HHHC 1.029 0.3439 Inf 1
## elevated CO HHHC / zero CO HHHC 0.948 0.2558 Inf 1
## elevated CO HHHC / elevated control HHHC 1.444 0.3925 Inf 1
## elevated CO HHHC / zero control HHHC 1.073 0.3141 Inf 1
## zero CO HHHC / elevated control HHHC 1.524 0.3993 Inf 1
## zero CO HHHC / zero control HHHC 1.132 0.3207 Inf 1
## elevated control HHHC / zero control HHHC 0.743 0.2120 Inf 1
## z.ratio p.value
## -2.417 0.6483
## -0.218 1.0000
## -1.348 0.9988
## -1.796 0.9638
## -1.048 1.0000
## 1.540 0.9933
## -1.179 0.9998
## 0.822 1.0000
## -1.290 0.9993
## 2.916 0.2795
## 2.972 0.2469
## -0.261 1.0000
## -1.297 0.9993
## -0.023 1.0000
## 0.208 1.0000
## 0.081 1.0000
## -0.126 1.0000
## 1.503 0.9950
## 0.326 1.0000
## 2.205 0.7977
## 1.089 0.9999
## 0.408 1.0000
## 1.177 0.9998
## 3.747 0.0249
## 1.075 1.0000
## 2.909 0.2838
## 0.782 1.0000
## 4.934 0.0001
## 4.939 0.0001
## 1.495 0.9953
## 0.413 1.0000
## 1.740 0.9737
## 1.976 0.9126
## 2.107 0.8539
## 1.992 0.9065
## 3.504 0.0568
## 2.234 0.7795
## -1.131 0.9999
## -1.602 0.9893
## -0.852 1.0000
## 1.741 0.9736
## -0.980 1.0000
## 1.009 1.0000
## -1.109 0.9999
## 3.100 0.1812
## 3.151 0.1592
## -0.109 1.0000
## -1.150 0.9999
## 0.130 1.0000
## 0.363 1.0000
## 0.260 1.0000
## 0.061 1.0000
## 1.681 0.9817
## 0.493 1.0000
## -0.586 1.0000
## 0.178 1.0000
## 2.776 0.3722
## 0.063 1.0000
## 1.979 0.9113
## -0.156 1.0000
## 4.048 0.0080
## 4.073 0.0072
## 0.698 1.0000
## -0.368 1.0000
## 0.941 1.0000
## 1.176 0.9998
## 1.196 0.9998
## 1.041 1.0000
## 2.612 0.4954
## 1.374 0.9984
## 0.773 1.0000
## 3.398 0.0791
## 0.668 1.0000
## 2.458 0.6167
## 0.386 1.0000
## 4.440 0.0015
## 4.461 0.0014
## 1.129 0.9999
## 0.087 1.0000
## 1.364 0.9985
## 1.591 0.9901
## 1.541 0.9932
## 1.410 0.9978
## 2.778 0.3712
## 1.689 0.9808
## 2.661 0.4574
## -0.119 1.0000
## 1.772 0.9683
## -0.315 1.0000
## 3.797 0.0209
## 3.832 0.0183
## 0.541 1.0000
## -0.491 1.0000
## 0.776 1.0000
## 1.004 1.0000
## 0.921 1.0000
## 0.768 1.0000
## 2.173 0.8170
## 1.099 0.9999
## -2.843 0.3260
## -0.596 1.0000
## -2.664 0.4551
## 1.520 0.9942
## 1.618 0.9881
## -1.389 0.9981
## -2.371 0.6837
## -1.161 0.9998
## -0.938 1.0000
## -1.141 0.9999
## -1.373 0.9984
## 0.135 1.0000
## -0.850 1.0000
## 1.910 0.9351
## -0.213 1.0000
## 3.971 0.0108
## 3.999 0.0097
## 0.637 1.0000
## -0.409 1.0000
## 0.875 1.0000
## 1.106 0.9999
## 1.026 1.0000
## 0.875 1.0000
## 2.292 0.7403
## 1.200 0.9998
## -2.207 0.7968
## 2.276 0.7513
## 2.367 0.6864
## -0.982 1.0000
## -2.037 0.8873
## -0.736 1.0000
## -0.495 1.0000
## -0.627 1.0000
## -0.837 1.0000
## 0.637 1.0000
## -0.372 1.0000
## 4.364 0.0021
## 4.401 0.0018
## 0.855 1.0000
## -0.246 1.0000
## 1.107 0.9999
## 1.350 0.9987
## 1.190 0.9998
## 1.047 1.0000
## 2.428 0.6405
## 1.366 0.9985
## 0.162 1.0000
## -2.777 0.3718
## -3.749 0.0248
## -2.544 0.5494
## -2.314 0.7247
## -2.386 0.6718
## -2.665 0.4548
## -1.136 0.9999
## -2.052 0.8807
## -2.903 0.2877
## -3.869 0.0160
## -2.671 0.4499
## -2.443 0.6285
## -2.450 0.6230
## -2.721 0.4124
## -1.230 0.9996
## -2.121 0.8463
## -1.172 0.9998
## 0.274 1.0000
## 0.541 1.0000
## 0.312 1.0000
## 0.153 1.0000
## 1.454 0.9967
## 0.513 1.0000
## 1.441 0.9970
## 1.701 0.9793
## 1.295 0.9993
## 1.158 0.9999
## 2.402 0.6598
## 1.465 0.9963
## 0.267 1.0000
## 0.088 1.0000
## -0.078 1.0000
## 1.234 0.9996
## 0.295 1.0000
## -0.130 1.0000
## -0.301 1.0000
## 1.020 1.0000
## 0.084 1.0000
## -0.199 1.0000
## 1.351 0.9987
## 0.241 1.0000
## 1.607 0.9889
## 0.439 1.0000
## -1.040 1.0000
##
## P value adjustment: tukey method for comparing a family of 20 estimates
## Tests are performed on the log odds ratio scaleplot(emmeans(s_glmer, pairwise ~ Temp * Control_CO* Parental_treat) )
emmeans(s_glmer, pairwise ~ Temp * Control_CO* Parental_treat)## $emmeans
## Temp Control_CO Parental_treat emmean SE df asymp.LCL asymp.UCL
## elevated CO CCCC 1.459 0.414 Inf 0.6482 2.27
## zero CO CCCC 2.029 0.424 Inf 1.1985 2.86
## elevated control CCCC 1.507 0.414 Inf 0.6948 2.32
## zero control CCCC 1.764 0.418 Inf 0.9440 2.58
## elevated CO CCCH 1.918 0.433 Inf 1.0687 2.77
## zero CO CCCH 1.719 0.428 Inf 0.8789 2.56
## elevated control CCCH 1.109 0.417 Inf 0.2917 1.93
## zero control CCCH 1.748 0.427 Inf 0.9116 2.58
## elevated CO HHCC 1.253 0.425 Inf 0.4210 2.09
## zero CO HHCC 1.807 0.436 Inf 0.9514 2.66
## elevated control HHCC 0.753 0.419 Inf -0.0676 1.57
## zero control HHCC 0.718 0.421 Inf -0.1070 1.54
## elevated CO CCHC 1.541 0.437 Inf 0.6850 2.40
## zero CO CCHC 1.888 0.449 Inf 1.0070 2.77
## elevated control CCHC 1.467 0.435 Inf 0.6145 2.32
## zero control CCHC 1.395 0.433 Inf 0.5471 2.24
## elevated CO HHHC 1.438 0.428 Inf 0.5983 2.28
## zero CO HHHC 1.492 0.423 Inf 0.6621 2.32
## elevated control HHHC 1.071 0.423 Inf 0.2414 1.90
## zero control HHHC 1.367 0.437 Inf 0.5106 2.22
##
## Results are given on the logit (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio
## elevated CO CCCC - zero CO CCCC -0.56943 0.236 Inf -2.417
## elevated CO CCCC - elevated control CCCC -0.04772 0.219 Inf -0.218
## elevated CO CCCC - zero control CCCC -0.30450 0.226 Inf -1.348
## elevated CO CCCC - elevated CO CCCH -0.45859 0.255 Inf -1.796
## elevated CO CCCC - zero CO CCCH -0.25912 0.247 Inf -1.048
## elevated CO CCCC - elevated control CCCH 0.35083 0.228 Inf 1.540
## elevated CO CCCC - zero control CCCH -0.28852 0.245 Inf -1.179
## elevated CO CCCC - elevated CO HHCC 0.20611 0.251 Inf 0.822
## elevated CO CCCC - zero CO HHCC -0.34743 0.269 Inf -1.290
## elevated CO CCCC - elevated control HHCC 0.70620 0.242 Inf 2.916
## elevated CO CCCC - zero control HHCC 0.74108 0.249 Inf 2.972
## elevated CO CCCC - elevated CO CCHC -0.08185 0.313 Inf -0.261
## elevated CO CCCC - zero CO CCHC -0.42804 0.330 Inf -1.297
## elevated CO CCCC - elevated control CCHC -0.00714 0.310 Inf -0.023
## elevated CO CCCC - zero control CCHC 0.06407 0.308 Inf 0.208
## elevated CO CCCC - elevated CO HHHC 0.02164 0.266 Inf 0.081
## elevated CO CCCC - zero CO HHHC -0.03218 0.255 Inf -0.126
## elevated CO CCCC - elevated control HHHC 0.38896 0.259 Inf 1.503
## elevated CO CCCC - zero control HHHC 0.09219 0.283 Inf 0.326
## zero CO CCCC - elevated control CCCC 0.52171 0.237 Inf 2.205
## zero CO CCCC - zero control CCCC 0.26494 0.243 Inf 1.089
## zero CO CCCC - elevated CO CCCH 0.11084 0.271 Inf 0.408
## zero CO CCCC - zero CO CCCH 0.31031 0.264 Inf 1.177
## zero CO CCCC - elevated control CCCH 0.92026 0.246 Inf 3.747
## zero CO CCCC - zero control CCCH 0.28091 0.261 Inf 1.075
## zero CO CCCC - elevated CO HHCC 0.77554 0.267 Inf 2.909
## zero CO CCCC - zero CO HHCC 0.22200 0.284 Inf 0.782
## zero CO CCCC - elevated control HHCC 1.27563 0.259 Inf 4.934
## zero CO CCCC - zero control HHCC 1.31051 0.265 Inf 4.939
## zero CO CCCC - elevated CO CCHC 0.48758 0.326 Inf 1.495
## zero CO CCCC - zero CO CCHC 0.14139 0.342 Inf 0.413
## zero CO CCCC - elevated control CCHC 0.56229 0.323 Inf 1.740
## zero CO CCCC - zero control CCHC 0.63350 0.321 Inf 1.976
## zero CO CCCC - elevated CO HHHC 0.59107 0.281 Inf 2.107
## zero CO CCCC - zero CO HHHC 0.53725 0.270 Inf 1.992
## zero CO CCCC - elevated control HHHC 0.95839 0.274 Inf 3.504
## zero CO CCCC - zero control HHHC 0.66162 0.296 Inf 2.234
## elevated control CCCC - zero control CCCC -0.25677 0.227 Inf -1.131
## elevated control CCCC - elevated CO CCCH -0.41087 0.256 Inf -1.602
## elevated control CCCC - zero CO CCCH -0.21140 0.248 Inf -0.852
## elevated control CCCC - elevated control CCCH 0.39855 0.229 Inf 1.741
## elevated control CCCC - zero control CCCH -0.24080 0.246 Inf -0.980
## elevated control CCCC - elevated CO HHCC 0.25383 0.252 Inf 1.009
## elevated control CCCC - zero CO HHCC -0.29971 0.270 Inf -1.109
## elevated control CCCC - elevated control HHCC 0.75392 0.243 Inf 3.100
## elevated control CCCC - zero control HHCC 0.78880 0.250 Inf 3.151
## elevated control CCCC - elevated CO CCHC -0.03413 0.314 Inf -0.109
## elevated control CCCC - zero CO CCHC -0.38032 0.331 Inf -1.150
## elevated control CCCC - elevated control CCHC 0.04058 0.311 Inf 0.130
## elevated control CCCC - zero control CCHC 0.11179 0.308 Inf 0.363
## elevated control CCCC - elevated CO HHHC 0.06936 0.267 Inf 0.260
## elevated control CCCC - zero CO HHHC 0.01554 0.256 Inf 0.061
## elevated control CCCC - elevated control HHHC 0.43668 0.260 Inf 1.681
## elevated control CCCC - zero control HHHC 0.13991 0.284 Inf 0.493
## zero control CCCC - elevated CO CCCH -0.15410 0.263 Inf -0.586
## zero control CCCC - zero CO CCCH 0.04537 0.255 Inf 0.178
## zero control CCCC - elevated control CCCH 0.65533 0.236 Inf 2.776
## zero control CCCC - zero control CCCH 0.01598 0.252 Inf 0.063
## zero control CCCC - elevated CO HHCC 0.51060 0.258 Inf 1.979
## zero control CCCC - zero CO HHCC -0.04294 0.276 Inf -0.156
## zero control CCCC - elevated control HHCC 1.01070 0.250 Inf 4.048
## zero control CCCC - zero control HHCC 1.04557 0.257 Inf 4.073
## zero control CCCC - elevated CO CCHC 0.22265 0.319 Inf 0.698
## zero control CCCC - zero CO CCHC -0.12355 0.336 Inf -0.368
## zero control CCCC - elevated control CCHC 0.29736 0.316 Inf 0.941
## zero control CCCC - zero control CCHC 0.36856 0.314 Inf 1.176
## zero control CCCC - elevated CO HHHC 0.32614 0.273 Inf 1.196
## zero control CCCC - zero CO HHHC 0.27232 0.262 Inf 1.041
## zero control CCCC - elevated control HHHC 0.69346 0.265 Inf 2.612
## zero control CCCC - zero control HHHC 0.39668 0.289 Inf 1.374
## elevated CO CCCH - zero CO CCCH 0.19947 0.258 Inf 0.773
## elevated CO CCCH - elevated control CCCH 0.80942 0.238 Inf 3.398
## elevated CO CCCH - zero control CCCH 0.17007 0.255 Inf 0.668
## elevated CO CCCH - elevated CO HHCC 0.66470 0.270 Inf 2.458
## elevated CO CCCH - zero CO HHCC 0.11116 0.288 Inf 0.386
## elevated CO CCCH - elevated control HHCC 1.16479 0.262 Inf 4.440
## elevated CO CCCH - zero control HHCC 1.19967 0.269 Inf 4.461
## elevated CO CCCH - elevated CO CCHC 0.37674 0.334 Inf 1.129
## elevated CO CCCH - zero CO CCHC 0.03055 0.350 Inf 0.087
## elevated CO CCCH - elevated control CCHC 0.45145 0.331 Inf 1.364
## elevated CO CCCH - zero control CCHC 0.52266 0.328 Inf 1.591
## elevated CO CCCH - elevated CO HHHC 0.48023 0.312 Inf 1.541
## elevated CO CCCH - zero CO HHHC 0.42641 0.303 Inf 1.410
## elevated CO CCCH - elevated control HHHC 0.84755 0.305 Inf 2.778
## elevated CO CCCH - zero control HHHC 0.55078 0.326 Inf 1.689
## zero CO CCCH - elevated control CCCH 0.60995 0.229 Inf 2.661
## zero CO CCCH - zero control CCCH -0.02940 0.246 Inf -0.119
## zero CO CCCH - elevated CO HHCC 0.46523 0.263 Inf 1.772
## zero CO CCCH - zero CO HHCC -0.08831 0.280 Inf -0.315
## zero CO CCCH - elevated control HHCC 0.96532 0.254 Inf 3.797
## zero CO CCCH - zero control HHCC 1.00020 0.261 Inf 3.832
## zero CO CCCH - elevated CO CCHC 0.17727 0.327 Inf 0.541
## zero CO CCCH - zero CO CCHC -0.16892 0.344 Inf -0.491
## zero CO CCCH - elevated control CCHC 0.25198 0.325 Inf 0.776
## zero CO CCCH - zero control CCHC 0.32319 0.322 Inf 1.004
## zero CO CCCH - elevated CO HHHC 0.28076 0.305 Inf 0.921
## zero CO CCCH - zero CO HHHC 0.22694 0.296 Inf 0.768
## zero CO CCCH - elevated control HHHC 0.64808 0.298 Inf 2.173
## zero CO CCCH - zero control HHHC 0.35131 0.320 Inf 1.099
## elevated control CCCH - zero control CCCH -0.63935 0.225 Inf -2.843
## elevated control CCCH - elevated CO HHCC -0.14473 0.243 Inf -0.596
## elevated control CCCH - zero CO HHCC -0.69826 0.262 Inf -2.664
## elevated control CCCH - elevated control HHCC 0.35537 0.234 Inf 1.520
## elevated control CCCH - zero control HHCC 0.39025 0.241 Inf 1.618
## elevated control CCCH - elevated CO CCHC -0.43268 0.311 Inf -1.389
## elevated control CCCH - zero CO CCHC -0.77887 0.329 Inf -2.371
## elevated control CCCH - elevated control CCHC -0.35797 0.308 Inf -1.161
## elevated control CCCH - zero control CCHC -0.28677 0.306 Inf -0.938
## elevated control CCCH - elevated CO HHHC -0.32919 0.289 Inf -1.141
## elevated control CCCH - zero CO HHHC -0.38301 0.279 Inf -1.373
## elevated control CCCH - elevated control HHHC 0.03813 0.282 Inf 0.135
## elevated control CCCH - zero control HHHC -0.25865 0.304 Inf -0.850
## zero control CCCH - elevated CO HHCC 0.49463 0.259 Inf 1.910
## zero control CCCH - zero CO HHCC -0.05891 0.277 Inf -0.213
## zero control CCCH - elevated control HHCC 0.99472 0.251 Inf 3.971
## zero control CCCH - zero control HHCC 1.02960 0.257 Inf 3.999
## zero control CCCH - elevated CO CCHC 0.20667 0.324 Inf 0.637
## zero control CCCH - zero CO CCHC -0.13952 0.341 Inf -0.409
## zero control CCCH - elevated control CCHC 0.28138 0.321 Inf 0.875
## zero control CCCH - zero control CCHC 0.35259 0.319 Inf 1.106
## zero control CCCH - elevated CO HHHC 0.31016 0.302 Inf 1.026
## zero control CCCH - zero CO HHHC 0.25634 0.293 Inf 0.875
## zero control CCCH - elevated control HHHC 0.67748 0.296 Inf 2.292
## zero control CCCH - zero control HHHC 0.38071 0.317 Inf 1.200
## elevated CO HHCC - zero CO HHCC -0.55354 0.251 Inf -2.207
## elevated CO HHCC - elevated control HHCC 0.50010 0.220 Inf 2.276
## elevated CO HHCC - zero control HHCC 0.53497 0.226 Inf 2.367
## elevated CO HHCC - elevated CO CCHC -0.28796 0.293 Inf -0.982
## elevated CO HHCC - zero CO CCHC -0.63415 0.311 Inf -2.037
## elevated CO HHCC - elevated control CCHC -0.21324 0.290 Inf -0.736
## elevated CO HHCC - zero control CCHC -0.14204 0.287 Inf -0.495
## elevated CO HHCC - elevated CO HHHC -0.18446 0.294 Inf -0.627
## elevated CO HHCC - zero CO HHHC -0.23828 0.285 Inf -0.837
## elevated CO HHCC - elevated control HHHC 0.18286 0.287 Inf 0.637
## elevated CO HHCC - zero control HHHC -0.11392 0.306 Inf -0.372
## zero CO HHCC - elevated control HHCC 1.05363 0.241 Inf 4.364
## zero CO HHCC - zero control HHCC 1.08851 0.247 Inf 4.401
## zero CO HHCC - elevated CO CCHC 0.26558 0.311 Inf 0.855
## zero CO HHCC - zero CO CCHC -0.08061 0.328 Inf -0.246
## zero CO HHCC - elevated control CCHC 0.34029 0.308 Inf 1.107
## zero CO HHCC - zero control CCHC 0.41150 0.305 Inf 1.350
## zero CO HHCC - elevated CO HHHC 0.36907 0.310 Inf 1.190
## zero CO HHCC - zero CO HHHC 0.31525 0.301 Inf 1.047
## zero CO HHCC - elevated control HHHC 0.73639 0.303 Inf 2.428
## zero CO HHCC - zero control HHHC 0.43962 0.322 Inf 1.366
## elevated control HHCC - zero control HHCC 0.03488 0.215 Inf 0.162
## elevated control HHCC - elevated CO CCHC -0.78805 0.284 Inf -2.777
## elevated control HHCC - zero CO CCHC -1.13424 0.303 Inf -3.749
## elevated control HHCC - elevated control CCHC -0.71334 0.280 Inf -2.544
## elevated control HHCC - zero control CCHC -0.64213 0.277 Inf -2.314
## elevated control HHCC - elevated CO HHHC -0.68456 0.287 Inf -2.386
## elevated control HHCC - zero CO HHHC -0.73838 0.277 Inf -2.665
## elevated control HHCC - elevated control HHHC -0.31724 0.279 Inf -1.136
## elevated control HHCC - zero control HHHC -0.61401 0.299 Inf -2.052
## zero control HHCC - elevated CO CCHC -0.82293 0.283 Inf -2.903
## zero control HHCC - zero CO CCHC -1.16912 0.302 Inf -3.869
## zero control HHCC - elevated control CCHC -0.74822 0.280 Inf -2.671
## zero control HHCC - zero control CCHC -0.67701 0.277 Inf -2.443
## zero control HHCC - elevated CO HHHC -0.71944 0.294 Inf -2.450
## zero control HHCC - zero CO HHHC -0.77326 0.284 Inf -2.721
## zero control HHCC - elevated control HHHC -0.35212 0.286 Inf -1.230
## zero control HHCC - zero control HHHC -0.64889 0.306 Inf -2.121
## elevated CO CCHC - zero CO CCHC -0.34619 0.295 Inf -1.172
## elevated CO CCHC - elevated control CCHC 0.07471 0.273 Inf 0.274
## elevated CO CCHC - zero control CCHC 0.14592 0.270 Inf 0.541
## elevated CO CCHC - elevated CO HHHC 0.10349 0.331 Inf 0.312
## elevated CO CCHC - zero CO HHHC 0.04967 0.326 Inf 0.153
## elevated CO CCHC - elevated control HHHC 0.47081 0.324 Inf 1.454
## elevated CO CCHC - zero control HHHC 0.17404 0.340 Inf 0.513
## zero CO CCHC - elevated control CCHC 0.42090 0.292 Inf 1.441
## zero CO CCHC - zero control CCHC 0.49211 0.289 Inf 1.701
## zero CO CCHC - elevated CO HHHC 0.44968 0.347 Inf 1.295
## zero CO CCHC - zero CO HHHC 0.39586 0.342 Inf 1.158
## zero CO CCHC - elevated control HHHC 0.81700 0.340 Inf 2.402
## zero CO CCHC - zero control HHHC 0.52023 0.355 Inf 1.465
## elevated control CCHC - zero control CCHC 0.07120 0.266 Inf 0.267
## elevated control CCHC - elevated CO HHHC 0.02878 0.329 Inf 0.088
## elevated control CCHC - zero CO HHHC -0.02504 0.323 Inf -0.078
## elevated control CCHC - elevated control HHHC 0.39610 0.321 Inf 1.234
## elevated control CCHC - zero control HHHC 0.09932 0.337 Inf 0.295
## zero control CCHC - elevated CO HHHC -0.04242 0.326 Inf -0.130
## zero control CCHC - zero CO HHHC -0.09625 0.320 Inf -0.301
## zero control CCHC - elevated control HHHC 0.32489 0.318 Inf 1.020
## zero control CCHC - zero control HHHC 0.02812 0.334 Inf 0.084
## elevated CO HHHC - zero CO HHHC -0.05382 0.270 Inf -0.199
## elevated CO HHHC - elevated control HHHC 0.36732 0.272 Inf 1.351
## elevated CO HHHC - zero control HHHC 0.07054 0.293 Inf 0.241
## zero CO HHHC - elevated control HHHC 0.42114 0.262 Inf 1.607
## zero CO HHHC - zero control HHHC 0.12436 0.283 Inf 0.439
## elevated control HHHC - zero control HHHC -0.29678 0.285 Inf -1.040
## p.value
## 0.6483
## 1.0000
## 0.9988
## 0.9638
## 1.0000
## 0.9933
## 0.9998
## 1.0000
## 0.9993
## 0.2795
## 0.2469
## 1.0000
## 0.9993
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.9950
## 1.0000
## 0.7977
## 0.9999
## 1.0000
## 0.9998
## 0.0249
## 1.0000
## 0.2838
## 1.0000
## 0.0001
## 0.0001
## 0.9953
## 1.0000
## 0.9737
## 0.9126
## 0.8539
## 0.9065
## 0.0568
## 0.7795
## 0.9999
## 0.9893
## 1.0000
## 0.9736
## 1.0000
## 1.0000
## 0.9999
## 0.1812
## 0.1592
## 1.0000
## 0.9999
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.9817
## 1.0000
## 1.0000
## 1.0000
## 0.3722
## 1.0000
## 0.9113
## 1.0000
## 0.0080
## 0.0072
## 1.0000
## 1.0000
## 1.0000
## 0.9998
## 0.9998
## 1.0000
## 0.4954
## 0.9984
## 1.0000
## 0.0791
## 1.0000
## 0.6167
## 1.0000
## 0.0015
## 0.0014
## 0.9999
## 1.0000
## 0.9985
## 0.9901
## 0.9932
## 0.9978
## 0.3712
## 0.9808
## 0.4574
## 1.0000
## 0.9683
## 1.0000
## 0.0209
## 0.0183
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.8170
## 0.9999
## 0.3260
## 1.0000
## 0.4551
## 0.9942
## 0.9881
## 0.9981
## 0.6837
## 0.9998
## 1.0000
## 0.9999
## 0.9984
## 1.0000
## 1.0000
## 0.9351
## 1.0000
## 0.0108
## 0.0097
## 1.0000
## 1.0000
## 1.0000
## 0.9999
## 1.0000
## 1.0000
## 0.7403
## 0.9998
## 0.7968
## 0.7513
## 0.6864
## 1.0000
## 0.8873
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.0021
## 0.0018
## 1.0000
## 1.0000
## 0.9999
## 0.9987
## 0.9998
## 1.0000
## 0.6405
## 0.9985
## 1.0000
## 0.3718
## 0.0248
## 0.5494
## 0.7247
## 0.6718
## 0.4548
## 0.9999
## 0.8807
## 0.2877
## 0.0160
## 0.4499
## 0.6285
## 0.6230
## 0.4124
## 0.9996
## 0.8463
## 0.9998
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.9967
## 1.0000
## 0.9970
## 0.9793
## 0.9993
## 0.9999
## 0.6598
## 0.9963
## 1.0000
## 1.0000
## 1.0000
## 0.9996
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 1.0000
## 0.9987
## 1.0000
## 0.9889
## 1.0000
## 1.0000
##
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: tukey method for comparing a family of 20 estimates#for graphs
JSurvEMM = (emmeans(s_glmer, ~ Parental_treat * Temp * Control_CO, type = "response") %>% as.data.frame)
JSurvEMM## Parental_treat Temp Control_CO prob SE df asymp.LCL
## CCCC elevated CO 0.8114509 0.06332549 Inf 0.6566144
## CCCH elevated CO 0.8719218 0.04839717 Inf 0.7443406
## HHCC elevated CO 0.7778809 0.07337432 Inf 0.6037307
## CCHC elevated CO 0.8236558 0.06345805 Inf 0.6648562
## HHHC elevated CO 0.8081175 0.06641898 Inf 0.6452685
## CCCC zero CO 0.8837979 0.04351337 Inf 0.7682517
## CCCH zero CO 0.8479470 0.05523970 Inf 0.7065873
## HHCC zero CO 0.8589867 0.05287199 Inf 0.7213936
## CCHC zero CO 0.8684711 0.05131547 Inf 0.7324379
## HHHC zero CO 0.8163249 0.06345694 Inf 0.6597429
## CCCC elevated control 0.8186441 0.06153763 Inf 0.6670345
## CCCH elevated control 0.7518744 0.07775598 Inf 0.5724224
## HHCC elevated control 0.6798897 0.09115580 Inf 0.4830958
## CCHC elevated control 0.8125407 0.06621856 Inf 0.6489742
## HHHC elevated control 0.7446929 0.08042386 Inf 0.5600664
## CCCC zero control 0.8537051 0.05224894 Inf 0.7199088
## CCCH zero control 0.8516985 0.05389711 Inf 0.7133370
## HHCC zero control 0.6722521 0.09279113 Inf 0.4732641
## CCHC zero control 0.8014528 0.06887360 Inf 0.6334579
## HHHC zero control 0.7969403 0.07072915 Inf 0.6249571
## asymp.UCL
## 0.9064201
## 0.9408921
## 0.8895041
## 0.9166455
## 0.9069831
## 0.9457989
## 0.9281299
## 0.9347719
## 0.9409213
## 0.9106127
## 0.9104852
## 0.8727535
## 0.8283776
## 0.9104119
## 0.8698437
## 0.9298191
## 0.9298458
## 0.8240198
## 0.9041073
## 0.9023768
##
## Confidence level used: 0.95
## Intervals are back-transformed from the logit scaleplot modeled data
#combine column for x axis
JSurvEMM_graph <- JSurvEMM %>%
unite(Temp:Control_CO, col="Juv_treat", sep="_", remove=FALSE)
JSurvEMM_graph## Parental_treat Juv_treat Temp Control_CO prob SE df
## 1 CCCC elevated_CO elevated CO 0.8114509 0.06332549 Inf
## 2 CCCH elevated_CO elevated CO 0.8719218 0.04839717 Inf
## 3 HHCC elevated_CO elevated CO 0.7778809 0.07337432 Inf
## 4 CCHC elevated_CO elevated CO 0.8236558 0.06345805 Inf
## 5 HHHC elevated_CO elevated CO 0.8081175 0.06641898 Inf
## 6 CCCC zero_CO zero CO 0.8837979 0.04351337 Inf
## 7 CCCH zero_CO zero CO 0.8479470 0.05523970 Inf
## 8 HHCC zero_CO zero CO 0.8589867 0.05287199 Inf
## 9 CCHC zero_CO zero CO 0.8684711 0.05131547 Inf
## 10 HHHC zero_CO zero CO 0.8163249 0.06345694 Inf
## 11 CCCC elevated_control elevated control 0.8186441 0.06153763 Inf
## 12 CCCH elevated_control elevated control 0.7518744 0.07775598 Inf
## 13 HHCC elevated_control elevated control 0.6798897 0.09115580 Inf
## 14 CCHC elevated_control elevated control 0.8125407 0.06621856 Inf
## 15 HHHC elevated_control elevated control 0.7446929 0.08042386 Inf
## 16 CCCC zero_control zero control 0.8537051 0.05224894 Inf
## 17 CCCH zero_control zero control 0.8516985 0.05389711 Inf
## 18 HHCC zero_control zero control 0.6722521 0.09279113 Inf
## 19 CCHC zero_control zero control 0.8014528 0.06887360 Inf
## 20 HHHC zero_control zero control 0.7969403 0.07072915 Inf
## asymp.LCL asymp.UCL
## 1 0.6566144 0.9064201
## 2 0.7443406 0.9408921
## 3 0.6037307 0.8895041
## 4 0.6648562 0.9166455
## 5 0.6452685 0.9069831
## 6 0.7682517 0.9457989
## 7 0.7065873 0.9281299
## 8 0.7213936 0.9347719
## 9 0.7324379 0.9409213
## 10 0.6597429 0.9106127
## 11 0.6670345 0.9104852
## 12 0.5724224 0.8727535
## 13 0.4830958 0.8283776
## 14 0.6489742 0.9104119
## 15 0.5600664 0.8698437
## 16 0.7199088 0.9298191
## 17 0.7133370 0.9298458
## 18 0.4732641 0.8240198
## 19 0.6334579 0.9041073
## 20 0.6249571 0.9023768cbPalette <- c("#56B4E9", "#E69F00", "#D55E00","#009E73", "#999999")
#better labels#
graph <- ggplot(JSurvEMM_graph, aes (x = Juv_treat, y=prob, colour=Parental_treat)) + geom_pointrange(aes (ymin = prob-SE, ymax = prob+SE), position=position_dodge(width=1), size=1) +
facet_grid(~factor(Juv_treat, levels =c( "zero_control","elevated_control", "zero_CO", "elevated_CO"),labels=str_wrap(c("Control", "Elevated Temperature", "Elevated CO2", "Elevated Temperature & CO2"), width = 10)), scales = "free_x") + labs(x="Juvenile treatment", y="Probability of survival") +
scale_x_discrete(breaks = c( "zero_control","elevated_control", "zero_CO", "elevated_CO"), labels = str_wrap(c("Control", "Warm temperature", "Elevated CO2", "Warm temperature & Elevated CO2" ), width = 16)) +
scale_colour_manual(values=cbPalette, name = "Cross-generation treatment", labels = c("Control", "Parental development", "Grandparental development", "Grandparental post-maturation", "Continuous grandparent")) +
theme_calc() + theme(text = element_text(size=20)) + theme(panel.spacing = unit(1, "cm", data = NULL)) + theme_classic()+ theme(strip.text.x = element_blank())
print(graph)
ggsave("Survival_graph.eps", graph, height = 6, width = 14, dpi = 320)