--- title: "ClimateNA Data" author: "Regan Cross" date: "06/06/2019" output: html_document editor_options: chunk_output_type: console --- editor_options: chunk_output_type: console --- ```{r message=FALSE} library(tidyverse) library(reshape2) library(ggpubr) ``` ```{r ClimateNA data} clNA <- read.csv("data/climate_data/ClimateNAData.csv") levels(clNA$site) <- c(levels(clNA$site),"OPR", "OGC", "OBU", "OHF") clNA$site[clNA$site=="OPR-S"] <- "OPR" clNA$site[clNA$site=="OBU-S"] <- "OBU" clNA$site[clNA$site=="OHF-S"] <- "OHF" clNA$site[clNA$site=="OGC-S"] <- "OGC" clNA$period[clNA$period=="Decade_1951_1960"] <- "1951-1960" clNA$period[clNA$period=="Decade_1961_1970"] <- "1961-1970" clNA$period[clNA$period=="Decade_1971_1980"] <- "1971-1980" clNA$period[clNA$period=="Decade_1981_1990"] <- "1981-1990" clNA$period[clNA$period=="Decade_1991_2000"] <- "1991-2000" clNA$period[clNA$period=="Decade_2001_2010"] <- "2001-2010" clNA$period[clNA$period=="Decade_2011_2019"] <- "2011-2019" clNA <- clNA %>% droplevels() clNA$site <- factor(clNA$site, levels=c("CPR","CMK", "CMA", "CTD", "OPR", "OGC", "OBU", "OHF", "OSJ")) # lol use the right site codes levels(clNA$site) <- c(levels(clNA$site),"W611", "W441", "W290", "W176", "W133", "W102", "W36", "E0", "B60") clNA$site[clNA$site=="CPR"] <- "W611" clNA$site[clNA$site=="CMK"] <- "W441" clNA$site[clNA$site=="CMA"] <- "W290" clNA$site[clNA$site=="CTD"] <- "W176" clNA$site[clNA$site=="OPR"] <- "W133" clNA$site[clNA$site=="OGC"] <- "W102" clNA$site[clNA$site=="OBU"] <- "W36" clNA$site[clNA$site=="OHF"] <- "E0" clNA$site[clNA$site=="OSJ"] <- "B60" clNA <- clNA %>% droplevels() clNA$site <- factor(clNA$site, levels=c("W611", "W441", "W290", "W176", "W133", "W102", "W36", "E0", "B60")) # preliminary investigate some of the data pd <- position_dodge(0.3) ggplot(clNA, aes(x = period, y = MAT, group = site)) + geom_line(position = pd, alpha = 0.7) + geom_point(size = 3, aes(colour = site), position = pd, alpha = 0.8) + labs(y = "Mean annual temperature (°C)", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() # a bit jumbled here in terms of geography, but strong climate change ggplot(clNA, aes(x = period, y = MCMT, group = site)) + geom_line(position = pd, alpha = 0.7) + geom_point(size = 3, aes(colour = site), position = pd, alpha = 0.8) + labs(y = "Mean coldest month temperature (°C)", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() # here we are very predictably organized geographically but not much warming ggplot(clNA, aes(x = period, y = MWMT, group = site)) + geom_line(position = pd, alpha = 0.7) + geom_point(size = 3, aes(colour = site), position = pd, alpha = 0.8) + labs(y = "Mean warmest month temperature (°C)", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() # this shows a lot more warming than the coldest month temperature # interestingly it doesn't seem like the southernmost places are the warmest here # but there is warming again ggplot(clNA, aes(x = period, y = MAP, group = site)) + geom_line(position = pd, alpha = 0.7) + geom_point(size = 3, aes(colour = site), position = pd, alpha = 0.8) + labs(y = "Mean annual precipitation (mm)", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() # this shows separation of those three southern sites that did less well at OSJ # seasonal variables ggplot(clNA, aes(x = period, y = Tave_wt, group = site)) + geom_line(position = pd, alpha = 0.7) + geom_point(size = 3, aes(colour = site), position = pd, alpha = 0.8) + labs(y = "Winter mean temperature (°C)", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() # there is also all of this data broken down by month ``` ```{r four panel fig} # Appendix S6 sum_precip <- ggplot(clNA, aes(x = period, y = PPT_sm, group = site)) + geom_line(position = pd, alpha = 0.9, size = 0.3) + geom_point(size = 1.7, aes(colour = site), position = pd, alpha = 0.9) + labs(x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + scale_y_continuous(breaks = seq(0, 125, 25), limits = c(0, 125), name = "Summer precipitation (mm)", expand = c(0,0)) + theme_classic() + theme(legend.position = "none", axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank(), axis.text.y = element_text(size=5, colour = "black"), axis.title.y = element_text(size =6), axis.line = element_line(size = 0.2), axis.ticks = element_line(size = 0.2)); sum_precip win_precip <- ggplot(clNA, aes(x = period, y = PPT_wt, group = site)) + geom_line(position = pd, alpha = 0.9, size = 0.3) + geom_point(size = 1.7, aes(colour = site), position = pd, alpha = 0.9) + labs(x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + scale_y_continuous(breaks = seq(400, 1000, 200), limits = c(350, 1000), name = "Winter precipitation (mm)", expand = c(0,0)) + theme_classic() + theme(legend.position = "none", axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank(), axis.text.y = element_text(size=5, colour = "black"), axis.title.y = element_text(size =6), axis.line = element_line(size = 0.2), axis.ticks = element_line(size = 0.2)); win_precip chill_dd <- ggplot(clNA, aes(x = period, y = DD.0, group = site)) + geom_line(position = pd, alpha = 0.9, size = 0.3) + geom_point(size = 1.7, aes(colour = site), position = pd, alpha = 0.9) + labs(y = "Chilling degree-days below 0°C", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + scale_y_continuous(breaks = seq(20, 50, 10), limits = c(15, 50), expand = c(0,0)) + theme_classic() + theme(legend.position = "none", axis.text.x = element_text(angle = 45, vjust = 0.5, colour = "black", size = 5), axis.title.y = element_text(size =6), axis.title.x = element_text(size =6), axis.text.y = element_text(size=5, colour = "black"), axis.line = element_line(size = 0.2), axis.ticks = element_line(size = 0.2)); chill_dd grow_dd <- ggplot(clNA, aes(x = period, y = DD.5, group = site)) + geom_line(position = pd, alpha = 0.9, size = 0.3) + geom_point(size = 1.7, aes(colour = site), position = pd, alpha = 0.9) + labs(y = "Growing degree-days above 5°C", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + scale_y_continuous(breaks = seq(2100, 2900, 200), limits = c(2100, 2900), expand = c(0,0)) + theme_classic() + theme(legend.position = "none", axis.text.x = element_text(angle = 45, vjust = 0.5, colour = "black", size = 5), axis.title.y = element_text(size =6), axis.title.x = element_text(size =6), axis.text.y = element_text(size=5, colour = "black"), axis.line = element_line(size = 0.2), axis.ticks = element_line(size = 0.2)); grow_dd forleg <- ggplot(clNA, aes(x = period, y = DD.5, group = site)) + geom_line(position = pd, alpha = 0.9) + geom_point(size = 1.5, aes(colour = site), position = pd, alpha = 0.9) + labs(y = "Growing degree-days above 5°C", x = "Time period") + scale_colour_manual(name = "Site", values = c("darkred", "#e31a1c", "#ff7f00", "gold1", "#33a02c", "#1f78b4", "#6a3d9a", "midnightblue", "black")) + theme_classic() + theme(legend.title = element_text(size = 6, colour = "black"), legend.title.align = 0.5, legend.text = element_text(size = 5, colour = "black"), legend.spacing = unit(0.3, "cm"), legend.margin = margin(1, 1, 1, 1, unit = "pt"), legend.key.size = unit(0.4, "cm"), axis.text.x = element_text(angle = 45, vjust = 0.5, colour = "black", size = 5)); forleg leg <- get_legend(forleg) gg <- ggarrange(sum_precip, win_precip, chill_dd, grow_dd, ncol=2, nrow=2, align = "v", heights = c(1,1.25), common.legend = TRUE, legend = "right", legend.grob = leg); gg ggsave("Demography_manuscript/dem_figs/supp_figs/SuppClimateNAFig.pdf", plot= gg, device="pdf", units="in", width=4.5, height=3.5, dpi=600) ```