### Packages
library(ggplot2)
library(dplyr) 
library(tidyr)


##### t-test for Exploration scores in the novel arena test and Year #####
Analysis <- read.csv("E:SUPPLEMENTARY_DATA_1.csv", sep=",",header=TRUE)
Analysis<- subset(Analysis, Exploration_UniqueSectorVisits != "na")
Analysis$Exploration_UniqueSectorVisits <- as.numeric(Analysis$Exploration_UniqueSectorVisits)
Analysis$Exploration_TotalSectorVisits <- as.numeric(Analysis$Exploration_TotalSectorVisits)
Analysis$Year_novel_arena <- as.numeric(Analysis$Year_novel_arena)

t.test(Exploration_UniqueSectorVisits~Year_NovelArenaTest, data= Analysis)
t.test(Exploration_TotalSectorVisits~Year_NovelArenaTest, data= Analysis)


##### Consistency within context novel arena test #####
Analysis$Species <- factor(Analysis$Species, levels = c("SGF", "MGF", "STF", "MTF","GFC", "YW"))

###### Spearman's Correlations among novel arena test scores ######
cor.test(Analysis$Exploration_UniqueSectorVisits, Analysis$Exploration_TotalSectorVisits, method = "spearman", exact = FALSE)

#### Plot
Figure_S1 <- ggplot(Analysis, aes(x=Exploration_UniqueSectorVisits, y=Exploration_TotalSectorVisits)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 2, 16, 17, 4, 8)) +
  xlab("Novel Arena (unique sectors)") +
  ylab("Novel Arena (total sectors)") +
  theme_classic()
Figure_S1 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
   scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(-35, 260))


##### Validation across context between novel arena test and novel object test #####
Analysis<- subset(x =Analysis, subset = Exploration_LatencyTo10Meters != "na")
Analysis$Exploration_LatencyTo10Meters <- as.numeric(Analysis$Exploration_LatencyTo10Meters)
Analysis$Exploration_InverseLatencyTo10Meters <- as.numeric(Analysis$Exploration_InverseLatencyTo10Meters)


###### Principal Component Analysis from the novel arena test scores ######
local({
  .PC <- princomp(~Exploration_TotalSectorVisits+Exploration_UniqueSectorVisits, cor=TRUE, data=Analysis)
  cat("\nComponent loadings:\n")
  print(unclass(loadings(.PC)))
  cat("\nComponent variances:\n")
  print(.PC$sd^2)
  cat("\n")
  print(summary(.PC))
  screeplot(.PC)
  Analysis <<- within(Analysis, {
    PC_Exploration <- .PC$scores[,1]
  })
})


###### Spearman's Correlations between novel arena test and novel object test ######
cor.test(Analysis$PC_Exploration, Analysis$Exploration_InverseLatencyTo10Meters, method = "spearman", exact = FALSE)

Figure_1 <- ggplot(Analysis, aes(x=PC_Exploration, y=Exploration_InverseLatencyTo10Meters)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 16, 17, 8)) +
  xlab("Novel arena (PC_Exploration)") +
  ylab("Novel object (latency to 10m)") +
  theme_classic()
Figure_1 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
  scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(0, 10))



##### Spearman's Correlations between Foraging scores and Neophilia scores #####

Analysis <- read.csv("E:SUPPLEMENTARY_DATA_2.csv", sep=",",header=TRUE)

cor.test(Analysis$ForagingTechnique_DiversityIndex, Analysis$%Ind_Into10m_PerTrial, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingSubstrate_DiversityIndex, Analysis$%Ind_Into10m_PerTrial, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingAverage_DiversityIndex_Diversity, Analysis$%Ind_Into10m_PerTrial, method = "spearman", exact = FALSE)

cor.test(Analysis$ForagingTechnique_DiversityIndex, Analysis$%Ind_Into3m_PerTrial, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingSubstrate_DiversityIndex, Analysis$%Ind_Into3m_PerTrial, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingAverage_DiversityIndex_Diversity, Analysis$%Ind_Into3m_PerTrial, method = "spearman", exact = FALSE)

cor.test(Analysis$ForagingTechnique_DiversityIndex, Analysis$Latency_to_10_m, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingSubstrate_DiversityIndex, Analysis$Latency_to_10_m, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingAverage_DiversityIndex_Diversity, Analysis$Latency_to_10_m, method = "spearman", exact = FALSE)

cor.test(Analysis$ForagingTechnique_DiversityIndex, Analysis$Latency_to_3_m, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingSubstrate_DiversityIndex, Analysis$Latency_to_3_m, method = "spearman", exact = FALSE)
cor.test(Analysis$ForagingAverage_DiversityIndex_Diversity, Analysis$Latency_to_3_m, method = "spearman", exact = FALSE)


#### Plots (Just statistical significant correlations)
Analysis$Species <- factor(Analysis$Species, levels = c("SGF", "MGF", "STF", "MTF","GFC", "YW"))

Figure_2 <- ggplot(Analysis, aes(x=ForagingAverage_DiversityIndex, y=Latency_to_3_m)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 2, 16, 17, 4, 8)) +
  xlab("Average Foraging Diversity") +
  ylab("Latency to 3m") +
  theme_classic()
Figure_2 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
  scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(-1.1, 3.5))


Figure_3 <- ggplot(Analysis, aes(x=ForagingTechnique_DiversityIndex, y=%Ind_Into3m_PerTrial)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 2, 16, 17, 4, 8)) +
  xlab("Foraging Technique") +
  ylab("% Response to 3m") +
  theme_classic()
Figure_3 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
  scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(-6, 33))


Figure_S3 <- ggplot(Analysis, aes(x=ForagingTechnique_DiversityIndex, y=Latency_to_3_m)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 2, 16, 17, 4, 8)) +
  xlab("Foraging Technique") +
  ylab("Latency to 3m") +
  theme_classic()
Figure_S3 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
  scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(-0.8, 4))


Figure_S4 <- ggplot(Analysis, aes(x=ForagingSubstrate_DiversityIndex, y=Latency_to_3_m)) + 
  geom_jitter(height = 0.03,width = 0.04, alpha= 0.7, size = 10,  stroke= 3, aes(shape= Species)) +
  stat_smooth(method="lm", se=T, colour = "black", fullrange=T) +
  scale_shape_manual(values = c(1, 2, 16, 17, 4, 8)) +
  xlab("Foraging Substrate") +
  ylab("Latency to 3m") +
  theme_classic()
Figure_S4 + theme(axis.text=element_text(size= 20), axis.title = element_text(size=35)) +
  scale_color_brewer(palette="Dark2") + theme(legend.position = "bottom") +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) +
  theme(axis.text=element_text(size= 30), axis.title = element_text(size=50)) + 
  theme(axis.text = element_text(face="bold")) + theme(axis.title = element_text(face="bold"))+ 
  theme(legend.title = element_blank()) + 
  theme(legend.key.height= unit(0.75, 'cm'), legend.key.width= unit(0.75, 'cm')) +
  theme(legend.text = element_text(size=35)) +
  theme(legend.position = "right") +
  theme(legend.background = element_rect(size=1, linetype="solid", colour ="black"))+
  coord_cartesian( ylim = c(-1.5, 4))