# all figures and pairwise comparisons # ----------------------- figures text -------------------- # figure nr 2 (end-start) wmdata<-read.csv2("wmdata.csv", sep = ";", header = T, fill = T) wmdata <- wmdata[-c(62, 63, 64), ] # graph in "wm" treatment file ## Between each area ## Control sound newdataC <-subset(wmdata, Test_sound == "Control") newdata1 <- subset(newdataC, Area == "Captive" | Area == "Semi") glm1=glmer(newdata1$E_S_T~newdata1$Area+(1|newdata1$Individual), family = poisson) summary(glm1) # P = 0.0226 SE = 0.1494 Est = 0.3234 lsm1 = lsmeans(glm1, "Area", type = "response") pairs(lsm1) newdata2 <- subset(newdataC, Area == "Captive" | Area == "Wild") glm2=glmer(newdata2$E_S_T~newdata2$Area+(1|newdata2$Individual), family = poisson) summary(glm2) # P = 0.007461 SE = 0.1829 Est = 0.4895 lsm2 = lsmeans(glm2, "Area", type = "response") pairs(lsm2) newdata3 <- subset(newdataC, Area == "Wild" | Area == "Semi") glm3=glmer(newdata3$E_S_T~newdata3$Area+(1|newdata3$Individual), family = poisson) summary(glm3) # P = 0.3502 SE = 0.1598 Est = 0.1493 lsm3 = lsmeans(glm3, "Area", type = "response") pairs(lsm3) ## between areas, lion sound newdataL <-subset(wmdata, Test_sound == "Lion") newdata1.1 <- subset(newdataL, Area == "Captive" | Area == "Semi") glm1.1=glmer(newdata1.1$E_S_T~newdata1.1$Area+(1|newdata1.1$Individual), family = poisson) summary(glm1.1) # P = 0.0226 SE = 0.1494 Est = 0.3234 lsm1.1 = lsmeans(glm1.1, "Area", type = "response") pairs(lsm1.1) newdata2.1 <- subset(newdataL, Area == "Captive" | Area == "Wild") glm2.1=glmer(newdata2.1$E_S_T~newdata2.1$Area+(1|newdata2.1$Individual), family = poisson) summary(glm2.1) # P = 0.007461 SE = 0.1829 Est = 0.4895 lsm2.1 = lsmeans(glm2.1, "Area", type = "response") pairs(lsm2.1) newdata3.1 <- subset(newdataL, Area == "Wild" | Area == "Semi") glm3.1=glmer(newdata3.1$E_S_T~newdata3.1$Area+(1|newdata3.1$Individual), family = poisson) summary(glm3.1) # P = 0.3502 SE = 0.1598 Est = 0.1493 lsm3.1 = lsmeans(glm3.1, "Area", type = "response") pairs(lsm3.1) ## within each area newdata4 <- subset(wmdata, Area == "Captive") glm4=glmer(newdata4$E_S_T~newdata4$Test_sound+(1|newdata4$Individual), family = poisson) summary(glm4) lsm4 = lsmeans(glm4, "Test_sound", type = "response") pairs(lsm4) newdata5 <- subset(wmdata, Area == "Semi") glm5=glmer(newdata5$E_S_T~newdata5$Test_sound+(1|newdata5$Individual), family = poisson) summary(glm5) lsm5 = lsmeans(glm5, "Test_sound", type = "response") pairs(lsm5) newdata6 <- subset(wmdata, Area == "Wild") glm6=glmer(newdata6$E_S_T~newdata6$Test_sound+(1|newdata6$Individual), family = poisson) summary(glm6) lsm6 = lsmeans(glm6, "Test_sound", type = "response") pairs(lsm6) # used pairs to check if it has approximately the same values as just summary use # figure nr 3 (presence and hesitation) # graph in cswdata file # no within area comparisons needed, no lion/control differences shown in these graphs ## between area comparison ## presence <10m glm7=glmer(wmdata$Less_10m~wmdata$Area+(1|wmdata$Individual), family = binomial(link = "logit")) summary(glm7) lsm7 = lsmeans(glm7, "Area", type = "response") pairs(lsm7) ## time <10m wmdataY=subset(wmdata, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Area+(1|Individual),data=wmdataY) summary(Time10M_lmer) lsm = lsmeans(Time10M_lmer, "Area", type = "response") pairs(lsm) ## evidence hesitation glm8=glmer(wmdata$Hes_present~wmdata$Area+(1|wmdata$Individual), family = binomial(link = "logit")) summary(glm8) lsm8 = lsmeans(glm8, "Area", type = "response") pairs(lsm8) ## frequency hesitation glm9=glmer(wmdata$Total_hes~wmdata$Area+(1|wmdata$Individual), family = poisson) summary(glm9) lsm9 = lsmeans(glm9, "Area", type = "response") pairs(lsm9) # ------------------- supplementary figures -------------------- # figure nr 5 # presence and hesitation, with control vs lion sound # graphs in cswtreatment file # between area comparisons ## control sound newdataC <-subset(wmdata, Test_sound == "Control") ### presence <10m glm10=glmer(newdataC$Less_10m~newdataC$Area+(1|newdataC$Individual), family = binomial(link = "logit")) summary(glm10) lsm10 = lsmeans(glm10, "Area", type = "response") pairs(lsm10) ### time <10m wmdataY=subset(newdataC, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Area+(1|Individual),data=wmdataY) summary(Time10M_lmer) lsm = lsmeans(Time10M_lmer, "Area", type = "response") pairs(lsm) ### evidence of hesitation glm11=glmer(newdataC$Hes_present~newdataC$Area+(1|newdataC$Individual), family = binomial(link = "logit")) summary(glm11) lsm11 = lsmeans(glm11, "Area", type = "response") pairs(lsm11) ### frequency of hesitation glm12=glmer(newdataC$Total_hes~newdataC$Area+(1|newdataC$Individual), family = poisson) summary(glm12) lsm12 = lsmeans(glm12, "Area", type = "response") pairs(lsm12) # between area comparison ## lion sound newdataL <-subset(wmdata, Test_sound == "Lion") ### presence <10m glm10.1=glmer(newdataL$Less_10m~newdataL$Area+(1|newdataL$Individual), family = binomial(link = "logit")) summary(glm10.1) lsm10.1 = lsmeans(glm10.1, "Area", type = "response") pairs(lsm10.1) ### time <10m wmdataY=subset(newdataL, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Area+(1|Individual),data=wmdataY) summary(Time10M_lmer) lsm2 = lsmeans(Time10M_lmer, "Area", type = "response") pairs(lsm2) ### evidence of hesitation glm11.1=glmer(newdataL$Hes_present~newdataL$Area+(1|newdataL$Individual), family = binomial(link = "logit")) summary(glm11.1) lsm11.1 = lsmeans(glm11.1, "Area", type = "response") pairs(lsm11.1) ### frequency of hesitation glm12.1=glmer(newdataL$Total_hes~newdataL$Area+(1|newdataL$Individual), family = poisson) summary(glm12.1) lsm12.1 = lsmeans(glm12.1, "Area", type = "response") pairs(lsm12.1) # within area comparison ### presence <10m newdata7 <- subset(wmdata, Area == "Captive") glm13=glmer(newdata7$Less_10m~newdata7$Test_sound+(1|newdata7$Individual), family = binomial(link = "logit")) summary(glm13) lsm13 = lsmeans(glm13, "Test_sound", type = "response") pairs(lsm13) newdata8 <- subset(wmdata, Area == "Semi") glm14=glmer(newdata8$Less_10m~newdata8$Test_sound+(1|newdata8$Individual), family = binomial(link = "logit")) summary(glm14) lsm14 = lsmeans(glm14, "Test_sound", type = "response") pairs(lsm14) newdata9 <- subset(wmdata, Area == "Wild") glm15=glmer(newdata9$Less_10m~newdata9$Test_sound+(1|newdata9$Individual), family = binomial(link = "logit")) summary(glm15) lsm15 = lsmeans(glm15, "Test_sound", type = "response") pairs(lsm15) ### time <10m newdata7 <- subset(wmdata, Area == "Captive") wmdataY=subset(newdata7, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Test_sound+(1|Individual),data=wmdataY) summary(Time10M_lmer) lsm3 = lsmeans(Time10M_lmer, "Test_sound", type = "response") pairs(lsm3) newdata8 <- subset(wmdata, Area == "Semi") wmdataY=subset(newdata8, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Test_sound+(1|Individual),data=wmdataY) summary(Time10M_lmer) # number of grouping factors too small lsm4 = lsmeans(Time10M_lmer, "Test_sound", type = "response") pairs(lsm4) newdata9 <- subset(wmdata, Area == "Wild") wmdataY=subset(newdata9, Less_10m=="1") wmdataY$logTime_less_10m = log(wmdataY$Time_less_10m+1) Time10M_lmer=lmer(wmdataY$logTime_less_10m~Test_sound+(1|Individual),data=wmdataY) summary(Time10M_lmer) lsm5 = lsmeans(Time10M_lmer, "Test_sound", type = "response") pairs(lsm5) # number of grouping factors way too small ### evidence of hesitation newdata7 <- subset(wmdata, Area == "Captive") glm16=glmer(newdata7$Hes_present~newdata7$Test_sound+(1|newdata7$Individual), family = binomial(link = "logit")) summary(glm16) lsm16 = lsmeans(glm16, "Test_sound", type = "response") pairs(lsm16) newdata8 <- subset(wmdata, Area == "Semi") glm17=glmer(newdata8$Hes_present~newdata8$Test_sound+(1|newdata8$Individual), family = binomial(link = "logit")) summary(glm17) lsm17 = lsmeans(glm17, "Test_sound", type = "response") pairs(lsm17) newdata9 <- subset(wmdata, Area == "Wild") glm18=glmer(newdata9$Hes_present~newdata9$Test_sound+(1|newdata9$Individual), family = binomial(link = "logit")) summary(glm18) lsm18 = lsmeans(glm18, "Test_sound", type = "response") pairs(lsm18) ### frequency of hesitation newdata7 <- subset(wmdata, Area == "Captive") glm19=glmer(newdata7$Total_hes~newdata7$Test_sound+(1|newdata7$Individual), family = poisson) summary(glm19) lsm19 = lsmeans(glm19, "Test_sound", type = "response") pairs(lsm19) newdata8 <- subset(wmdata, Area == "Semi") glm20=glmer(newdata8$Total_hes~newdata8$Test_sound+(1|newdata8$Individual), family = poisson) summary(glm20) lsm20 = lsmeans(glm20, "Test_sound", type = "response") pairs(lsm20) newdata9 <- subset(wmdata, Area == "Wild") glm21=glmer(newdata9$Total_hes~newdata9$Test_sound+(1|newdata9$Individual), family = poisson) summary(glm21) lsm21 = lsmeans(glm21, "Test_sound", type = "response") pairs(lsm21) # figure nr 6 # learning # graphs in cswlearning file # only have within area comparisons ## captive ### presence <10m newdata7 <- subset(wmdata, Area == "Captive") glmL1=glmer(newdata7$Less_10m~newdata7$Test_nr+(1|newdata7$Individual), family = binomial(link = "logit")) summary(glmL1) lsmL1 = lsmeans(glmL1, "Test_nr", type = "response") pairs(lsmL1) # doesnt work