library(tidyverse) library(multcomp) library(tibble) library(lubridate) library(ggplot2) library(ggpubr) library(glmmTMB) library(DHARMa) # Data preparation #### spiders <- c("Agyneta.rurestris","Erigone.atra","Erigone.dentipalpis", "Oedothorax.apicatus","Pardosa.agrestis","Tenuiphantes.tenuis") all_spiders <- c("Erigone.dentipalpis", "Oedothorax.apicatus", "Erigone.atra", "Tenuiphantes.tenuis", "Agyneta.rurestris", "Pardosa.agrestis", "Bathyphantes.gracilis", "Trochosa.ruricola", "Pardosa.spp.", "Pachygnatha.degeeri", "Araeoncus.humilis", "Oedothorax.retusus", "Pardosa.palustris", "Oedothorax.agrestis", "Drassyllus.spp.", "Gnaphosidae.spp.", "Porrhomma.spp.", "Diplostyla.concolor", "Micaria.spp.", "Pardosa.amentata", "Pelecopsis.parallela", "Pardosa.agricolae", "Phrurolithus.minimus", "Xysticus.cochi", "Xysticus.spp.", "Histopona.torpida", "Callilepis.nocturna", "Coelotes.terrestris", "Haplodrassus.minor", "Oedothorax.fuscus", "Ostearius.melanophygius", "Tenuiphantes.spp.", "Tetragnatidae.spp.", "Tibellus.oblungus", "Trochosa.spp.", "Diplocephalus.cristatus", "Robertus.spp.", "Ozyptila.simplex", "Pelecopsis.parallela", "Trachyzelothes.pedestris", "Walckenaeria.vigilax", "Centromerus.cavenarum", "Drassyllus.pusillus") spider_labels = c("Agyneta.rurestris" = "Agyneta\nrurestris", "Erigone.atra" = "Erigone\natra", "Erigone.dentipalpis" = "Erigone\ndentipalpis", "Oedothorax.apicatus" = "Oedothorax\napicatus", "Pardosa.agrestis" = "Pardosa\nagrestis", "Tenuiphantes.tenuis" = "Tenuiphantes\ntenuis") breaks_2021 <- as.POSIXct(c("2021-06-07", "2021-06-14","2021-06-21", "2021-06-28","2021-07-05","2021-07-12")) breaks_2022 <- as.POSIXct(c("2022-06-07", "2022-06-14","2022-06-21", "2022-06-28","2022-07-05","2022-07-12")) # 2021a (RS / RundS) s_UKA_RS_21<-read.csv("2021a spiders.csv",sep=";",header=T) s1_UKA_RS_21 <- s_UKA_RS_21 %>% mutate(across(c(ROW, DIRECTION, SURROUNDING, BLOCK, TREATMENT), as.factor), DATE = as.Date(DATE), TOTAL_SPIDERS = rowSums(across("Oedothorax.apicatus":last_col()), na.rm = TRUE)) s2_UKA_RS_21 <- s1_UKA_RS_21 %>% gather("SPIDER","COUNT","unidentifiable":last_col()) %>% mutate(SPIDER = as.factor(SPIDER)) s3_UKA_RS_21 <- subset(s2_UKA_RS_21, DATE < "2021-07-31") %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(x_mean = mean(COUNT, na.rm = T)) sx_UKA_RS_21 <- s2_UKA_RS_21 %>% group_by(SPIDER) %>% summarise(sum = sum(COUNT, na.rm = T)) s4_UKA_RS_21 <- s3_UKA_RS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(x_mean,na.rm = T)) ts4_UKA_RS_21 <- s4_UKA_RS_21 %>% filter(SPIDER %in% spiders) %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) %>% ungroup() %>% group_by(SPIDER) %>% filter(any(mean > 0)) %>% ungroup() s5_UKA_RS_21 <- s3_UKA_RS_21 %>% filter(SPIDER %in% "TOTAL_SPIDERS") %>% group_by(BLOCK,TREATMENT,DATE) %>% summarise(sum = sum(x_mean,na.rm = T)) ts5_UKA_RS_21 <- s5_UKA_RS_21 %>% group_by(TREATMENT,DATE) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) s6_UKA_RS_21 <- subset(s2_UKA_RS_21, DATE < "2021-07-31") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(x_mean = mean(COUNT, na.rm = T)) s7_UKA_RS_21 <- s6_UKA_RS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(x_mean,na.rm = T)) ts7_UKA_RS_21 <- s7_UKA_RS_21 %>% filter(SPIDER %in% spiders) %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) %>% ungroup() %>% group_by(SPIDER) %>% filter(any(mean > 0)) %>% ungroup() sa1_UKA_RS_21 <- subset(s2_UKA_RS_21, DATE > "2021-07-31" & DATE < "2021-10-01") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(t_mean = mean(COUNT, na.rm = T)) sa2_UKA_RS_21 <- subset(s2_UKA_RS_21, DATE > "2021-10-01") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(t_mean = mean(COUNT, na.rm = T)) sta1_UKA_RS_21 <- sa1_UKA_RS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(t_mean,na.rm = T)) sta2_UKA_RS_21 <- sa2_UKA_RS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(t_mean,na.rm = T)) sfa1_UKA_RS_21 <- sta1_UKA_RS_21 %>% filter(SPIDER %in% spiders) sfa2_UKA_RS_21 <- sta2_UKA_RS_21 %>% filter(SPIDER %in% spiders) ssfa1_UKA_RS_21 <- sfa1_UKA_RS_21 %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) ssfa2_UKA_RS_21 <- sfa2_UKA_RS_21 %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) surr_spider_RS_21 <- subset(s2_UKA_RS_21, DATE < "2021-07-31" & SPIDER %in% spiders & TREATMENT == "WT") %>% group_by(DATE,BLOCK,TREATMENT,SURROUNDING) %>% summarise(sum = sum(COUNT)) %>% group_by(TREATMENT,SURROUNDING,BLOCK) %>% summarise(mean = mean(sum, na.rm = T)) %>% group_by(TREATMENT,SURROUNDING) %>% summarise(t_mean = mean(mean, na.rm = T), se = sd(mean, na.rm = T)/sqrt(length(mean)), n = length(mean)) surr_spec_spider_RS_21 <- subset(s2_UKA_RS_21, DATE < "2021-07-31" & TREATMENT == "WT" & SPIDER %in% spiders) %>% group_by(BLOCK,TREATMENT,SURROUNDING,SPIDER) %>% summarise(mean1 = mean(COUNT, na.rm = T)) %>% group_by(TREATMENT,SURROUNDING,SPIDER) %>% summarise(t_mean = mean(mean1, na.rm = T), se = sd(mean1, na.rm = T)/sqrt(length(mean1)), n = length(mean1)) surr_date_spider_RS_21 <- subset(s2_UKA_RS_21, DATE < "2021-07-31" & SPIDER %in% spiders & TREATMENT == "WT") %>% group_by(DATE,BLOCK,TREATMENT,SURROUNDING) %>% summarise(sum = sum(COUNT)) %>% group_by(TREATMENT,SURROUNDING,DATE) %>% summarise(t_mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) # 2021b (MS) s_UKA_MS_21<-read.csv("2021b spiders.csv",sep=";",header=T) s1_UKA_MS_21 <- s_UKA_MS_21 %>% mutate(across(c(ROW, DIRECTION, SURROUNDING, BLOCK, TREATMENT), as.factor), DATE = as.Date(DATE), TOTAL_SPIDERS = rowSums(across("Oedothorax.apicatus":last_col()), na.rm = TRUE)) s2_UKA_MS_21 <- s1_UKA_MS_21 %>% gather("SPIDER","COUNT","unidentifiable":last_col()) %>% mutate(SPIDER = as.factor(SPIDER)) s3_UKA_MS_21 <- subset(s2_UKA_MS_21, DATE < "2021-07-31") %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(x_mean = mean(COUNT, na.rm = T)) sx_UKA_MS_21 <- s2_UKA_MS_21 %>% group_by(SPIDER) %>% summarise(sum = sum(COUNT, na.rm = T)) s4_UKA_MS_21 <- s3_UKA_MS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(x_mean,na.rm = T)) ts4_UKA_MS_21 <- s4_UKA_MS_21 %>% filter(SPIDER %in% spiders) %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) %>% ungroup() %>% group_by(SPIDER) %>% filter(any(mean > 0)) %>% ungroup() s5_UKA_MS_21 <- s3_UKA_MS_21 %>% filter(SPIDER %in% "TOTAL_SPIDERS") %>% group_by(BLOCK,TREATMENT,DATE) %>% summarise(sum = sum(x_mean,na.rm = T)) ts5_UKA_MS_21 <- s5_UKA_MS_21 %>% group_by(TREATMENT,DATE) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) s6_UKA_MS_21 <- subset(s2_UKA_MS_21, DATE > "2021-07-31") %>% group_by(DATE,BLOCK,TREATMENT,SPIDER) %>% summarise(x_mean = mean(COUNT, na.rm = T)) s7_UKA_MS_21 <- s6_UKA_MS_21 %>% group_by(BLOCK,TREATMENT,SPIDER) %>% summarise(sum = sum(x_mean,na.rm = T)) ts7_UKA_MS_21 <- s7_UKA_MS_21 %>% filter(SPIDER %in% spiders) %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) %>% ungroup() %>% group_by(SPIDER) %>% filter(any(mean > 0)) %>% ungroup() surr_spider_MS_21 <- subset(s2_UKA_MS_21, DATE < "2021-07-31" & SPIDER %in% spiders & TREATMENT %in% c("WT", "S")) %>% group_by(DATE,BLOCK,TREATMENT,SURROUNDING) %>% summarise(sum = sum(COUNT)) %>% group_by(TREATMENT,SURROUNDING,BLOCK) %>% summarise(mean = mean(sum, na.rm = T)) %>% group_by(TREATMENT,SURROUNDING) %>% summarise(t_mean = mean(mean, na.rm = T), se = sd(mean, na.rm = T)/sqrt(length(mean)), n = length(mean)) surr_spec_spider_MS_21 <- subset(s2_UKA_MS_21, DATE < "2021-07-31" & TREATMENT %in% c("WT", "S") & SPIDER %in% spiders) %>% group_by(BLOCK,TREATMENT,SURROUNDING,SPIDER) %>% summarise(mean1 = mean(COUNT, na.rm = T)) %>% group_by(TREATMENT,SURROUNDING,SPIDER) %>% summarise(t_mean = mean(mean1, na.rm = T), se = sd(mean1, na.rm = T)/sqrt(length(mean1)), n = length(mean1)) surr_date_spider_MS_21 <- subset(s2_UKA_MS_21, DATE < "2021-07-31" & SPIDER %in% spiders & TREATMENT %in% c("WT", "S")) %>% group_by(DATE,BLOCK,TREATMENT,SURROUNDING) %>% summarise(sum = sum(COUNT)) %>% group_by(TREATMENT,SURROUNDING,DATE) %>% summarise(t_mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) # 2022 (MS) s_UKA_MS_22<-read.csv("2022 spiders.csv",sep=";",header=T) s1_UKA_MS_22 <- s_UKA_MS_22 %>% mutate(across(c(ROW, BLOCK, TREATMENT), as.factor), DATE = as.Date(DATE), TOTAL_SPIDERS = rowSums(across("destroyed":last_col()), na.rm = TRUE)) s2_UKA_MS_22 <- s1_UKA_MS_22 %>% gather("SPIDER","COUNT","destroyed":last_col()) %>% mutate(SPIDER = as.factor(SPIDER)) s3_UKA_MS_22 <- s2_UKA_MS_22 %>% group_by(DATE,TREATMENT,BLOCK,SPIDER) %>% summarise(x_mean = mean(COUNT, na.rm = T)) sx_UKA_MS_22 <- s2_UKA_MS_22 %>% group_by(SPIDER) %>% summarise(sum = sum(COUNT, na.rm = T)) s4_UKA_MS_22 <- s3_UKA_MS_22 %>% group_by(TREATMENT,BLOCK,SPIDER) %>% summarise(sum = sum(x_mean,na.rm = T)) ts4_UKA_MS_22 <- s4_UKA_MS_22 %>% filter(SPIDER %in% spiders) %>% group_by(TREATMENT,SPIDER) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) %>% ungroup() %>% group_by(SPIDER) %>% filter(any(mean > 0)) %>% ungroup() s5_UKA_MS_22 <- s3_UKA_MS_22 %>% filter(SPIDER %in% "TOTAL_SPIDERS") %>% group_by(BLOCK,TREATMENT,DATE) %>% summarise(sum = sum(x_mean,na.rm = T)) ts5_UKA_MS_22 <- s5_UKA_MS_22 %>% group_by(TREATMENT,DATE) %>% summarise(mean = mean(sum, na.rm = T), se = sd(sum, na.rm = T)/sqrt(length(sum)), n = length(sum)) sx_UKA_RS_21$ID <- "RS_21" sx_UKA_MS_21$ID <- "MS_21" sx_UKA_MS_22$ID <- "MS_22" merged_data <- bind_rows(sx_UKA_RS_21, sx_UKA_MS_21, sx_UKA_MS_22) final_data <- merged_data %>% pivot_wider(names_from = ID, values_from = sum, values_fill = NA) # Calculations for Table A.2 #### summarise_s <- function(df) { df %>% group_by(SPIDER) %>% summarise(TOTAL_COUNT = sum(COUNT, na.rm = TRUE)) %>% arrange(desc(TOTAL_COUNT)) } s2_UKA_RS_21_sum <- summarise_s(s2_UKA_RS_21) s2_UKA_MS_21_sum <- summarise_s(s2_UKA_MS_21) s2_UKA_MS_22_sum <- summarise_s(s2_UKA_MS_22) all_gc <- bind_rows( s2_UKA_RS_21 %>% dplyr::select(SPIDER, COUNT), s2_UKA_MS_21 %>% dplyr::select(SPIDER, COUNT), s2_UKA_MS_22 %>% dplyr::select(SPIDER, COUNT) ) sum_per_species <- all_gc %>% group_by(SPIDER) %>% summarise(TOTAL_COUNT = sum(COUNT, na.rm = TRUE)) %>% arrange(desc(TOTAL_COUNT)) sum_per_species # Calculations for results and GLMM #### a <- s2_UKA_RS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch", SPIDER == "TOTAL_SPIDERS") %>% group_by(TREATMENT,BLOCK) %>% summarise(mean = mean(COUNT, na.rm = T)) a_sum <- a %>% group_by(TREATMENT) %>% summarise(mean = mean(mean)) a_sum 9.5/7.56 14.3/7.56 M.p <- glmmTMB(mean ~ TREATMENT + (1 | BLOCK), family = "gaussian", data = a) summary(M.p) M.p_simout <- simulateResiduals(M.p, n = 1000) testDispersion(M.p_simout) plot(M.p_simout, quantreg = FALSE) summary(glht(M.p, mcp(TREATMENT = "Dunnett"))) b <- s2_UKA_MS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch", SPIDER == "TOTAL_SPIDERS") %>% group_by(TREATMENT,BLOCK) %>% summarise(mean = mean(COUNT, na.rm = T)) b_sum <- b %>% group_by(TREATMENT) %>% summarise(mean = mean(mean)) b_sum 8.83/4.58 4.5/4.58 M.p <- glmmTMB(mean ~ TREATMENT + (1 | BLOCK), family = "gaussian", data = b) summary(M.p) M.p_simout <- simulateResiduals(M.p, n = 1000) testDispersion(M.p_simout) plot(M.p_simout, quantreg = FALSE) summary(glht(M.p, mcp(TREATMENT = "Dunnett"))) c <- s2_UKA_MS_22 %>% filter(SPIDER == "TOTAL_SPIDERS") %>% group_by(TREATMENT,BLOCK) %>% summarise(mean = mean(COUNT, na.rm = T)) c_sum <- c %>% group_by(TREATMENT) %>% summarise(mean = mean(mean)) c_sum 13.7/10.5 22.6/10.5 M.p <- glmmTMB(mean ~ TREATMENT + (1 | BLOCK), family = "gaussian", data = c) summary(M.p) M.p_simout <- simulateResiduals(M.p, n = 1000) testDispersion(M.p_simout) plot(M.p_simout, quantreg = FALSE) summary(glht(M.p, mcp(TREATMENT = "Dunnett"))) s2_UKA_RS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Erigone.dentipalpis") %>% group_by(TREATMENT) %>% summarise(SUM_COUNT = mean(COUNT, na.rm = T)) 3.77/1.67 6.20/1.67 s2_UKA_MS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Erigone.dentipalpis") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 4.58/2.18 2.90/2.18 s2_UKA_MS_22 %>% filter(SPIDER == "Erigone.dentipalpis") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 7/3.33 8/3.33 s2_UKA_RS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Erigone.atra") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 0.923/0.6 1.67/0.6 s2_UKA_MS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Erigone.atra") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 1.17/0.364 0.80/0.364 s2_UKA_MS_22 %>% filter(SPIDER == "Erigone.atra") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 0.75/0.0667 0.875/0.0667 s2_UKA_RS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Pardosa.agrestis") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 0.267/0.133 0.308/0.133 s2_UKA_MS_21 %>% filter(DATE < "2021-07-31", !(TREATMENT %in% c("WT","S")) | SURROUNDING == "mulch") %>% filter(SPIDER == "Pardosa.agrestis") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 0.0/0.0909 0.167/0.0909 s2_UKA_MS_22 %>% filter(SPIDER == "Pardosa.agrestis") %>% group_by(TREATMENT) %>% summarise(mean = mean(COUNT, na.rm = T)) 0.438/0.133 0.188/0.133 # Catch by date plots #### # 2021 RundS - A sampling_A <- tribble( ~sampling, ~start_date, ~end_date, "no sampling / identification", "2021-06-04", "2021-06-14", "sampling / identification", "2021-06-14", "2021-06-17", "no sampling / identification", "2021-06-17", "2021-07-07", "sampling / identification", "2021-07-07", "2021-07-12", "no sampling / identification", "2021-07-12", "2021-07-16") sampling_A <- sampling_A %>% mutate(start_date = as.POSIXct(start_date), end_date = as.POSIXct(end_date)) ts5_UKA_RS_21 <- ts5_UKA_RS_21 %>% mutate(DATE = as.POSIXct(DATE)) ggplot() + geom_col(data = ts5_UKA_RS_21, aes(x=DATE-hours(2), y=mean, fill=TREATMENT), position="dodge",width = 140000) + geom_segment(data = sampling_A, aes(color = sampling, x=start_date+hours(1), xend=end_date-hours(1), y=-1, yend=-1), linewidth = 0.7) + geom_errorbar(data = ts5_UKA_RS_21, aes(ymin = mean - se, ymax = mean + se, x=DATE-hours(2), y=mean, fill=TREATMENT), width = 45000, position = position_dodge(140000)) + labs(title = "spiders - trial 2021a", x = "", y = "mean catch per trap") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control","straw","triticale/vetch")) + scale_color_manual(name = NULL, values = c("cadetblue3","darkgreen")) + theme_light() + theme( axis.text.x = element_text(size = 10), axis.text.y = element_text(size = 10), legend.title = element_text(size = 10), legend.text = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90, vjust = 0.5), plot.title = element_text(hjust = 0.98, size = 11, vjust = 0), legend.position = "none", panel.grid.minor.x = element_blank(), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -5, r=10)) + scale_x_datetime(breaks = breaks_2021, date_labels = "%d %b", limits = as.POSIXct(c("2021-06-04","2021-07-17"))) + scale_y_continuous( breaks = seq(0, 100, by = 10), limits = c(-2, NA), expand = expansion(mult = c(0, 0.02))) ggsave(filename = "Spider Dates - trial 2021a.pdf", width = 17, height = 4.35, units = "cm") # 2021 MS - B sampling_B <- tribble( ~sampling, ~start_date, ~end_date, "no sampling / identification", "2021-06-04", "2021-06-15", "sampling / identification", "2021-06-15", "2021-06-18", "no sampling / identification", "2021-06-18", "2021-07-12", "sampling / identification", "2021-07-12", "2021-07-16") sampling_B <- sampling_B %>% mutate(start_date = as.POSIXct(start_date), end_date = as.POSIXct(end_date)) ts5_UKA_MS_21 <- ts5_UKA_MS_21 %>% mutate(DATE = as.POSIXct(DATE)) ggplot() + geom_col(data = ts5_UKA_MS_21, aes(x=DATE-hours(2), y=mean, fill=TREATMENT), position="dodge",width = 140000) + geom_segment(data = sampling_B, aes(color = sampling, x=start_date+hours(1), xend=end_date-hours(1), y=-1, yend=-1), linewidth = 0.7) + geom_errorbar(data = ts5_UKA_MS_21, aes(ymin = mean - se, ymax = mean + se, x=DATE-hours(2), y=mean, fill=TREATMENT), width = 45000, position = position_dodge(140000)) + labs(title = "spiders - trial 2021b", x = "", y = "mean catch per trap") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control","straw","triticale/vetch")) + scale_color_manual(name = NULL, values = c("cadetblue3","darkgreen")) + theme_light() + theme( axis.text.x = element_text(size = 10), axis.text.y = element_text(size = 10), legend.title = element_text(size = 10), legend.text = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90, vjust = 0.5), plot.title = element_text(hjust = 0.98, size = 11, vjust = 0), legend.position = "none", panel.grid.minor.x = element_blank(), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -5, r=10)) + scale_x_datetime(breaks = breaks_2021, date_labels = "%d %b", limits = as.POSIXct(c("2021-06-04","2021-07-17"))) + scale_y_continuous( breaks = seq(0, 100, by = 10), limits = c(-2, 26), expand = expansion(mult = c(0, 0.02))) ggsave(filename = "Spider Dates - trial 2021b.pdf", width = 17, height = 3.5, units = "cm") # 2022 MS - C sampling_C <- tribble( ~sampling, ~start_date, ~end_date, "no sampling / identification", "2022-06-04", "2022-06-10", "sampling / identification", "2022-06-10", "2022-06-13", "no sampling / identification", "2022-06-13", "2022-07-07", "sampling / identification", "2022-07-07", "2022-07-11", "no sampling / identification", "2022-07-11", "2022-07-16") sampling_C <- sampling_C %>% mutate(start_date = as.POSIXct(start_date), end_date = as.POSIXct(end_date)) ts5_UKA_MS_22 <- ts5_UKA_MS_22 %>% mutate(DATE = as.POSIXct(DATE)) new_row <- data.frame( TREATMENT = "S", DATE = as.POSIXct("2022-06-04 00:00:00", tz = "UTC"), mean = 0, se = 0, n = 0) ts5_UKA_MS_22_dummy <- rbind(ts5_UKA_MS_22, new_row) ggplot() + geom_col(data = ts5_UKA_MS_22_dummy, aes(x=DATE-hours(2), y=mean, fill=TREATMENT), position="dodge",width = 140000) + geom_segment(data = sampling_C, aes(color = sampling, x=start_date+hours(1), xend=end_date-hours(1), y=-1, yend=-1), linewidth = 0.7) + geom_errorbar(data = ts5_UKA_MS_22_dummy, aes(ymin = mean - se, ymax = mean + se, x=DATE-hours(2), y=mean, fill=TREATMENT), width = 45000, position = position_dodge(140000)) + labs(title = "spiders - trial 2022", x = "", y = "mean catch per trap") + scale_fill_manual(name = NULL, values =c("#EE6677","#4477AA","#228833","#CCBB44"), labels = c("control","straw","silage","triticale/vetch"), drop = FALSE) + scale_color_manual(name = NULL, values = c("cadetblue3","darkgreen")) + theme_light() + theme( axis.text.x = element_text(size = 10), axis.text.y = element_text(size = 10), legend.text = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90, vjust = 0.5), plot.title = element_text(hjust = 0.98, size = 11, vjust = 0), panel.grid.minor.x = element_blank(), legend.position = "bottom", panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -5, r=10), legend.box.margin = margin(t = -8, unit = "mm")) + scale_x_datetime(breaks = breaks_2022, date_labels = "%d %b", limits = as.POSIXct(c("2022-06-04","2022-07-17"))) + scale_y_continuous( breaks = seq(0, 100, by = 10), limits = c(-2, NA), expand = expansion(mult = c(0, 0.02))) + guides(fill = guide_legend(nrow = 2), color = guide_legend(nrow = 2)) ggsave(filename = "Spider Dates - trial 2022.pdf", width = 17, height = 6.5, units = "cm") # Total catch by species plots #### # 2021 RundS trt_order_car3 <- c('C', 'S', 'WT') ggplot(ts7_UKA_RS_21, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car3))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2021a - June/July") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control", "straw","triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.95, size = 11, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), legend.position = "none", plot.margin = margin(b = -11, r = 1)) + scale_y_continuous( limits = c(-0.2, 18), breaks = seq(0, 17.5, by = 2.5), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2021a.pdf", width = 7.6, height = 7, units = "cm") # 2021 MS trt_order_car3 <- c('C', 'S', 'WT') ggplot(ts4_UKA_MS_21, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car3))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2021b - June/July") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control", "straw","triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.95, size = 11, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), legend.position = "none", plot.margin = margin(b = -11, r = 1)) + scale_y_continuous( limits = c(-0.2, 18), breaks = seq(0, 17.5, by = 2.5), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2021b.pdf", width = 7.6, height = 7, units = "cm") # 2022 MS trt_order_car4 <- c('C', 'SIL', 'WT') ggplot(ts4_UKA_MS_22, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car4))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2022 - June/July") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#228833","#CCBB44"), labels = c("control", "silage", "triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.95, size = 11, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), legend.position = "none", plot.margin = margin(b = -11, r = 1)) + scale_y_continuous( limits = c(-0.2, 18), breaks = seq(0, 17.5, by = 2.5), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2022.pdf", width = 7.6, height = 7, units = "cm") # 2021 RundS September ggplot(ssfa1_UKA_RS_21, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car3))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2021a - early September") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control", "straw","triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.95, size = 10, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -11, r = 1), legend.position = "none") + scale_y_continuous( limits = c(-0.1, 9), breaks = seq(0, 8, by = 2), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2021a - September.pdf", width = 7.6, height = 6.1, units = "cm") # 2021 RS October ggplot(ssfa2_UKA_RS_21, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car3))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2021a - October (after harvest)") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control", "straw","triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.95, size = 10, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -11, r = 1), legend.position = "none") + scale_y_continuous( limits = c(-0.1, 9), breaks = seq(0, 8, by = 2), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2021a - October.pdf", width = 7.6, height = 6.1, units = "cm") # 2021 MS August ggplot(ts7_UKA_MS_21, aes(x = SPIDER, y = mean, fill = factor(TREATMENT, levels = trt_order_car3))) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap", title = "spiders - trial 2021b - late August") + scale_fill_manual(name = "treatments:", values =c("#EE6677","#4477AA","#CCBB44"), labels = c("control", "straw", "triticale/vetch")) + theme_light() + scale_x_discrete(labels = spider_labels) + theme( axis.text.x = element_text(size = 8.5, angle = 45, hjust = 1, lineheight = 0.75), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.98, size = 10, vjust = 0), panel.border = element_rect(colour = "lightgray", linewidth = 0.5), plot.margin = margin(b = -11, r = 1), legend.position = "none") + scale_y_continuous( limits = c(-0.1, 9), breaks = seq(0, 8, by = 2), expand = c(0, 0)) ggsave(filename = "Spider Species - trial 2021b - August.pdf", width = 7.6, height = 6.1, units = "cm") # Surroundings #### combined_surr_s <- bind_rows(surr_spec_spider_RS_21, surr_spec_spider_MS_21, .id = "TRIAL") %>% mutate(TRIAL = case_when( TRIAL == "1" ~ "A", TRIAL == "2" ~ "B")) %>% mutate(TRIAL_TREATMENT = paste(TRIAL,TREATMENT,sep = "_")) names3 <- c( `A_WT` = "spiders\ntrial 2021a - triticale/vetch", `B_S` = "spiders\ntrial 2021b - straw", `B_WT` = "spiders\ntrial 2021b - triticale/vetch" ) ggplot(combined_surr_s, aes(x = SPIDER, y = t_mean, fill = SURROUNDING)) + geom_bar(position = "dodge", stat = "identity", width = 0.6) + geom_errorbar(aes(ymin = t_mean - se, ymax = t_mean + se), width = 0.1, position = position_dodge(0.6)) + labs(x = "", y = "mean catch sums per trap") + scale_fill_manual(name = "surrounding:", values =c("#1B9E77","#E7298A"), labels = c("mulch","no mulch"))+ scale_x_discrete(labels = spider_labels) + theme_light() + theme( axis.text.x = element_text(size = 7.5, angle = 45, hjust = 1, lineheight = 0.7), axis.text.y = element_text(size = 10), axis.title.y = element_text(size = 10, angle = 90), plot.title = element_text(hjust = 0.98, size = 9, vjust = 0), plot.margin = margin(b = -11, r = 1), strip.text = element_text( size = 10, color = "black"), strip.background = element_rect( fill = "gray90", color = "gray70"), legend.position = "none") + facet_grid(.~TRIAL_TREATMENT, labeller = as_labeller(names3)) ggsave(filename = "Surrounding - spider species.pdf", width = 17, height = 9, units = "cm")