Electronic Supplementary Material (ESM 3)

Sonerud GA (2022) Predation of boreal owl nests by pine martens in the boreal forest does not vary as predicted by the alternative prey hypothesis

Source code

Oecologia

Geir A. Sonerud
Faculty of Environmental Sciences and Natural Resource Management
Norwegian University of Life Sciences 
P. O. Box 5003, NO-1432 Ås
Norway

E-mail: geir.sonerud@nmbu.no 


require(ggplot2)
require(GGally)
require(reshape2)
require(lme4)
require(compiler)
require(parallel)
require(boot)
require(lattice)
require(ggeffects)
require(splines)
library(readr)
library(MuMIn)
library(sjmisc)
##################################
my_log <- file("Sonerud_samletNYEST.txt") # File name of output log
sink(my_log, append = TRUE, type = "output") # Writing console output to log file
sink(my_log, append = TRUE, type = "message")
cat(readChar(rstudioapi::getSourceEditorContext()$path, # Writing currently opened R script to file
             file.info(rstudioapi::getSourceEditorContext()$path)$size))

#Read data
DataMartenVerification_MicrotinesCurr_SR <- read_csv("~/Sonerud/Marten_owl/nye/DataMartenVerification_MicrotinesCurr_SR_Corr.csv", 
                                          col_types = cols(Microtines = col_number(), 
                                                           Marten_verified = col_number(),
                                                           Year = col_number()))
View(DataMartenVerification_MicrotinesCurr_SR)#Se på data
# estimate the model and store results in m
m1 <- glmer(Marten_verified ~ Microtines +
              (1 | Year), data = DataMartenVerification_MicrotinesCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)

summary(m1)
##############################
#Read data
DataMartenVerification_MicrotinesChange_SR <- read_csv("~/Sonerud/Marten_owl/nye/DataMartenVerification_MicrotinesChange_SR_Corr.csv", 
                                                       col_types = cols(Microtines = col_number(), 
                                                                        Marten_verified = col_number(),
                                                                        Year = col_number()))
View(DataMartenVerification_MicrotinesChange_SR)
# estimate the model and store results in m
m2 <- glmer(Marten_verified ~ Microtines +
              (1 | Year), data = DataMartenVerification_MicrotinesChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
summary(m2)

#######################
#Read data
DataMartenVerification_ClutchSize_SR <- read_csv("~/Sonerud/Marten_owl/nye/DataMartenVerification_ClutchSize_SR.csv", 
                                                 col_types = cols(Clutch_size = col_number(), 
                                                                  Marten_verified = col_number(),
                                                                  Year = col_number()))
View(DataMartenVerification_ClutchSize_SR)

m3 <- glmer(Marten_verified ~ Clutch_size +
              (1 | Year), data = DataMartenVerification_ClutchSize_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
summary(m3)

######################
## Modell 4 Analyse ##
######################
########################################
#Clutch
#Read data
DataToClutchSizeMicrotines45 <- read_csv("~/Sonerud/Marten_owl/nye/DataToClutchSizeMicrotines45.csv", 
                                        col_types = cols(Clutch_size = col_number(), Microtines = col_number(), 
                                                         Year = col_number()))
View(DataToClutchSizeMicrotines45)
# estimate the model and store results in m
m4 <- glmer(Clutch_size  ~ Microtines+
              (1 | Year), data = DataToClutchSizeMicrotines45, family = poisson)
summary(m4)
r.squaredGLMM(m4)


#############################################
##################
########################
#CurrMicr
#Read data
DataPredBorealowl_MicrotinesCurr_SR <- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_MicrotinesCurr_SR.csv", 
                                            col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                             Microtines = col_number(),  
                                                             Predation = col_number(),  
                                                             Year = col_number()))
                                                             
View(DataPredBorealowl_MicrotinesCurr_SR)

# estimate the model and store results in m
m5 <- glmer(Predation ~ CavityAge*DistEdge*Microtines+
              (1 | Year), data = DataPredBorealowl_MicrotinesCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m5)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m5_t <- glmer(Predation ~ CavityAge+DistEdge+Microtines+
              (1 | Year), data = DataPredBorealowl_MicrotinesCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
summary(m5_t)

#Bank
DataPredBorealowl_BankVoleCurr_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_BankVolesCurr_SR.csv", 
                                                col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                                 Bank = col_number(),  
                                                                 Predation = col_number(),  
                                                                 Year = col_number()))
m5Bank <- glmer(Predation ~ CavityAge*DistEdge*Bank+
              (1 | Year), data = DataPredBorealowl_BankVoleCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
dd <- dredge(m5Bank)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m5Bank_t <- glmer(Predation ~ CavityAge+DistEdge+Bank+
                  (1 | Year), data = DataPredBorealowl_BankVoleCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
                nAGQ = 10)
summary(m5Bank_t)
#Microtus
DataPredBorealowl_MicrotinesCurr_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_MicrotusCurr_SR.csv", 
                                             col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                              Microtus = col_number(),  
                                                              Predation = col_number(),  
                                                              Year = col_number()))
View(DataPredBorealowl_MicrotinesCurr_SR)
m5M <- glmer(Predation ~ CavityAge*DistEdge*Microtus+
               (1 | Year), data = DataPredBorealowl_MicrotinesCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
dd <- dredge(m5M)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m5M_t <- glmer(Predation ~ CavityAge+DistEdge+Microtus+
               (1 | Year), data = DataPredBorealowl_MicrotinesCurr_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
summary(m5M_t)

#Wood
DataPredBorealowl_WoodCurr_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_WoodLemmingCurr_SR.csv", 
                                               col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                                Wood = col_number(),  
                                                                Predation = col_number(),  
                                                                Year = col_number()))
m5W <- glmer(Predation ~ CavityAge*DistEdge*Wood+
               (1 | Year), data = NewPredBorealowl_CurrMicrotines, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
dd <- dredge(m5W)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m5W_t <- glmer(Predation ~ CavityAge+DistEdge+Wood+
               (1 | Year), data = NewPredBorealowl_CurrMicrotines, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
summary(m5W_t)
#################################################################
#################################################################
#################################################################

#PrevCurr
#Read data

DataPredBorealowl_MicrotinesChange_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_MicrotinesChange_SR.csv", 
                                                col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                                 Microtines = col_number(),  
                                                                 Predation = col_number(),  
                                                                 Year = col_number()))

View(DataPredBorealowl_MicrotinesChange_SR)

# estimate the model and store results in m
m6 <- glmer(Predation ~ CavityAge*DistEdge*Microtines+
              (1 | Year), data = DataPredBorealowl_MicrotinesChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m6)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m6_t <- glmer(Predation ~ CavityAge+DistEdge+Microtines+
                (1 | Year), data = DataPredBorealowl_MicrotinesChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m6_t)

m6_red <- glmer(Predation ~ CavityAge+Microtines+
                (1 | Year), data = DataPredBorealowl_MicrotinesChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m6_red)

#Bank
DataPredBorealowl_BankVoleChange_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_BankVoleChange_SR.csv", 
                                             col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                              Bank = col_number(),  
                                                              Predation = col_number(),  
                                                              Year = col_number()))
m6Bank <- glmer(Predation ~ CavityAge*DistEdge*Bank+
                  (1 | Year), data = DataPredBorealowl_BankVoleChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
                nAGQ = 10)
dd <- dredge(m6Bank)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m6Bank_t <- glmer(Predation ~ CavityAge+DistEdge+Bank+
                    (1 | Year), data = DataPredBorealowl_BankVoleChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
                  nAGQ = 10)
summary(m6Bank_t)

#Microtus
DataPredBorealowl_MicrotusChange_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_MicrotusChange_SR.csv", 
                                               col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                                Microtus = col_number(),  
                                                                Predation = col_number(),  
                                                                Year = col_number()))
View(DataPredBorealowl_MicrotusChange_SR)
m6M <- glmer(Predation ~ CavityAge*DistEdge*Microtus+
               (1 | Year), data = DataPredBorealowl_MicrotusChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
dd <- dredge(m6M)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m6M_t <- glmer(Predation ~ CavityAge+DistEdge+Microtus+
                 (1 | Year), data = DataPredBorealowl_MicrotusChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
               nAGQ = 10)
summary(m6M_t)


m6M_red <- glmer(Predation ~ CavityAge+Microtus+
                 (1 | Year), data = DataPredBorealowl_MicrotusChange_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
               nAGQ = 10)
summary(m6M_red)

#Wood
DataPredBorealowl_WoodLemming_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredBorealowl_WoodLemmingChange_SR.csv", 
                                         col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                          Wood = col_number(),  
                                                          Predation = col_number(),  
                                                          Year = col_number()))
m6W <- glmer(Predation ~ CavityAge*DistEdge*Wood+
               (1 | Year), data = DataPredBorealowl_WoodLemming_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
dd <- dredge(m6W)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])
m6W_t <- glmer(Predation ~ CavityAge+DistEdge+Wood+
                 (1 | Year), data = DataPredBorealowl_WoodLemming_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
               nAGQ = 10)
summary(m6W_t)
#################################################################
#################################################################
#######################
#Read data
DataPredBorealowl_ClutchSize45_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredationBorealowl_ClutchSize45_SR.csv", 
                                                 col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                                  Predation = col_number(), ClutchSize = col_number(), 
                                                                  Year = col_number()))

View(DataPredBorealowl_ClutchSize45_SR)

# estimate the model and store results in m
m7 <- glmer(Predation ~ CavityAge*DistEdge*ClutchSize+
              (1 | Year), data = DataPredBorealowl_ClutchSize45_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m7)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m7_t <- glmer(Predation ~ CavityAge+DistEdge+ClutchSize+
                (1 | Year), data = DataPredBorealowl_ClutchSize45_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m7_t)


##################
#Read data
DataPredationBorealowl_ClutchSize_SR<- read_csv("~/Sonerud/Marten_owl/nye/DataPredationBorealowl_ClutchSize_SR.csv", 
                                             col_types = cols(CavityAge = col_number(), DistEdge = col_number(), 
                                                              Predation = col_number(), ClutchSize = col_number(), 
                                                              Year = col_number()))

View(DataPredationBorealowl_ClutchSize_SR)

# estimate the model and store results in m
m8 <- glmer(Predation ~ CavityAge*DistEdge*ClutchSize+
              (1 | Year), data = DataPredationBorealowl_ClutchSize_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m8)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m8_t <- glmer(Predation ~ CavityAge+DistEdge+ClutchSize+
                (1 | Year), data = DataPredationBorealowl_ClutchSize_SR, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m8_t)
################################################
#Read data
PredTo_Box1year_MicrotinesCurr<- read_csv("~/Sonerud/Marten_owl/nye/PredTo_Box1year_MicrotinesCurr.csv", 
                                                col_types = cols(DistEdge = col_number(), 
                                                                 Microtines= col_number(), 
                                                                 Predation = col_number(), 
                                                                 Year = col_number()))

View(PredTo_Box1year_MicrotinesCurr)

# estimate the model and store results in m
m9 <- glmer(Predation ~ DistEdge*Microtines+
              (1 | Year), data = PredTo_Box1year_MicrotinesCurr, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m9)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m9_t <- glmer(Predation ~ DistEdge+Microtines+
                (1 | Year), data = PredTo_Box1year_MicrotinesCurr, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m9_t)

############################

#Read data
PredTo_Box1year_ClutchSize<- read_csv("~/Sonerud/Marten_owl/nye/PredTo_Box1year_ClutchSize.csv", 
                                          col_types = cols(DistEdge = col_number(), 
                                                           ClutchSize= col_number(), 
                                                           Predation = col_number(), 
                                                           Year = col_number()))

View(PredTo_Box1year_ClutchSize)

# estimate the model and store results in m
m10 <- glmer(Predation ~ DistEdge*ClutchSize+
               (1 | Year), data = PredTo_Box1year_ClutchSize, family = binomial, control = glmerControl(optimizer = "bobyqa"),
             nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m10)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m10_t <- glmer(Predation ~ DistEdge+ClutchSize+
                 (1 | Year), data = PredTo_Box1year_ClutchSize, family = binomial, control = glmerControl(optimizer = "bobyqa"),
               nAGQ = 10)
summary(m10_t)

m10_red <- glmer(Predation ~ ClutchSize+
                 (1 | Year), data = PredTo_Box1year_ClutchSize, family = binomial, control = glmerControl(optimizer = "bobyqa"),
               nAGQ = 10)
summary(m10_red)


####################################
#Read data
PredTo_Box1year_MicrotinesChange<- read_csv("~/Sonerud/Marten_owl/nye/PredTo_Box1year_MicrotinesChange.csv", 
                                            col_types = cols(DistEdge = col_number(), 
                                                             Microtines= col_number(), 
                                                             Predation = col_number(), 
                                                             Year = col_number()))

View(PredTo_Box1year_MicrotinesChange)

# estimate the model and store results in m
m11 <- glmer(Predation ~ DistEdge*Microtines+
              (1 | Year), data = PredTo_Box1year_MicrotinesChange, family = binomial, control = glmerControl(optimizer = "bobyqa"),
            nAGQ = 10)
options(na.action = na.fail)
dd <- dredge(m11)
subset(dd, delta < 5)
summary(get.models(dd, 1)[[1]])
summary(get.models(dd, 2)[[1]])

m9_t <- glmer(Predation ~ DistEdge+Microtines+
                (1 | Year), data = PredTo_Box1year_MicrotinesChange, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m11_t)

m9_red1 <- glmer(Predation ~ Microtines+
                (1 | Year), data = PredTo_Box1year_MicrotinesChange, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m9_red1)


m9_red2<- glmer(Predation ~ DistEdge+Microtines+
                (1 | Year), data = PredTo_Box1year_MicrotinesChange, family = binomial, control = glmerControl(optimizer = "bobyqa"),
              nAGQ = 10)
summary(m9_red2)


#####################
################################################
closeAllConnections() # Close connection to log file