Analysis for Ossanna & Gornish (2022), “Efficacy of labile carbon addition to reduce fast-growing, invasive non-native plants: A review and meta-analysis”, Journal of Applied Ecology.
code_nonnative-moderator-analysis.html,
code_native-moderator-analysis.html).library(tidyverse)
library(metafor)
# Load data ---------------------------------------------------------------
raw <- read.csv("data/raw/Table-S2_meta-analysis.csv")
# Data wrangling ----------------------------------------------------------
raw$plant_apgfs <- paste(raw$plant_anper, raw$plant_gfs, sep = " ") # create combined annual/perennial and grass/forb/shub column
raw$C_app_tm <- raw$duration_first - raw$duration_last # calculate total months applying C
# Calculate SD from SE for biomass
trt.cntrl.se.sd <- c("biomass_mean_trt", "biomass_SE_trt", "biomass_SD_trt",
"biomass_mean_cntrl", "biomass_SE_cntrl", "biomass_SD_cntrl")
to.drop <- c("biomass_SE_trt", "biomass_SE_cntrl", "to_sd_trt", "to_sd_cntrl")
biomass <- raw %>%
select(!(contains("cover"))) %>%
select(!contains("density")) %>%
filter(!is.na(biomass_mean_trt)) %>%
mutate_at(trt.cntrl.se.sd, as.numeric) %>%
mutate(to_sd_trt = biomass_SE_trt * sqrt(n_trt)) %>% # convert treatment SE to SD
mutate(to_sd_cntrl = biomass_SE_cntrl * sqrt(n_cntrl)) %>% # convert control SE to SD
mutate(biomass_SD_trt = paste(biomass_SD_trt, to_sd_trt)) %>% # combine calculated treatment SDs with provided SDs into single column
mutate(biomass_SD_trt = str_remove(biomass_SD_trt, pattern = "NA"), .keep = "unused") %>% # remove "NA" (each row will have either a calculated SD or a provided SD, so there will be one NA and one number pasted together)
mutate(biomass_SD_cntrl = paste(biomass_SD_cntrl, to_sd_cntrl)) %>% # combine calculated control SD with existing SD into single column
mutate(biomass_SD_cntrl = str_remove(biomass_SD_cntrl, pattern = "NA"), .keep = "unused") %>% # remove "NA" (each row will have either a calculated SD or a provided SD, so there will be one NA and one number pasted together)
select(-all_of(to.drop)) %>%
mutate_at(c("biomass_SD_trt", "biomass_SD_cntrl"), as.numeric) %>%
rename(mean_trt = biomass_mean_trt) %>% # standardize names to eventually combine biomass, cover, and density
rename(mean_cntrl = biomass_mean_cntrl) %>%
rename(SD_trt = biomass_SD_trt) %>%
rename(SD_cntrl = biomass_SD_cntrl)
biomass$res <- rep("biomass", nrow(biomass))
# Calculate SD from SE for cover
trt.cntrl.se.sd <- c("cover_mean_trt", "cover_SE_trt", "cover_SD_trt",
"cover_mean_cntrl", "cover_SE_cntrl", "cover_SD_cntrl")
to.drop <- c("cover_SE_trt", "cover_SE_cntrl", "to_sd_trt", "to_sd_cntrl")
cover <- raw %>%
select(!(contains("biomass"))) %>%
select(!contains("density")) %>%
filter(!is.na(cover_mean_cntrl)) %>%
mutate_at(trt.cntrl.se.sd, as.numeric) %>%
mutate(to_sd_trt = cover_SE_trt * sqrt(n_trt)) %>%
mutate(to_sd_cntrl = cover_SE_cntrl * sqrt(n_cntrl)) %>%
mutate(cover_SD_trt = paste(cover_SD_trt, to_sd_trt)) %>%
mutate(cover_SD_trt = str_remove(cover_SD_trt, pattern = "NA"), .keep = "unused") %>%
mutate(cover_SD_cntrl = paste(cover_SD_cntrl, to_sd_cntrl)) %>%
mutate(cover_SD_cntrl = str_remove(cover_SD_cntrl, pattern = "NA"), .keep = "unused") %>%
select(-all_of(to.drop)) %>%
mutate_at(c("cover_SD_trt", "cover_SD_cntrl"), as.numeric) %>% # warning because one Burke point is blank (was <1)
rename(mean_trt = cover_mean_trt) %>%
rename(mean_cntrl = cover_mean_cntrl) %>%
rename(SD_trt = cover_SD_trt) %>%
rename(SD_cntrl = cover_SD_cntrl)
cover$res <- rep("cover", nrow(cover))
# Calculate SD from SE for density
trt.cntrl.se.sd <- c("density_mean_trt", "density_SE_trt", "density_SD_trt",
"density_mean_cntrl", "density_SE_cntrl", "density_SD_cntrl")
to.drop <- c("density_SE_trt", "density_SE_cntrl", "to_sd_trt", "to_sd_cntrl")
density <- raw %>%
select(!(contains("cover"))) %>%
select(!contains("biomass")) %>%
filter(!is.na(density_mean_trt)) %>%
mutate_at(trt.cntrl.se.sd, as.numeric) %>%
mutate(to_sd_trt = density_SE_trt * sqrt(n_trt)) %>%
mutate(to_sd_cntrl = density_SE_cntrl * sqrt(n_cntrl)) %>%
mutate(density_SD_trt = paste(density_SD_trt, to_sd_trt)) %>%
mutate(density_SD_trt = str_remove(density_SD_trt, pattern = "NA"), .keep = "unused") %>%
mutate(density_SD_cntrl = paste(density_SD_cntrl, to_sd_cntrl)) %>%
mutate(density_SD_cntrl = str_remove(density_SD_cntrl, pattern = "NA"), .keep = "unused") %>%
select(-all_of(to.drop)) %>%
filter(density_SD_trt != " NA") %>%
mutate_at(c("density_SD_trt", "density_SD_cntrl"), as.numeric) %>%
rename(mean_trt = density_mean_trt) %>%
rename(mean_cntrl = density_mean_cntrl) %>%
rename(SD_trt = density_SD_trt) %>%
rename(SD_cntrl = density_SD_cntrl)
density$res <- rep("density", nrow(density))
# Combine only biomass and cover for exotic (density responded differently)
all.1res.ex <- rbind(biomass, cover)
# Combine all response variables for native
all.1res.nt <- rbind(biomass, cover, density)ex <- all.1res.ex %>%
filter(str_detect(plant_category, "exotic"))
ex <- escalc(measure = "SMD",
n1i = n_trt,
n2i = n_cntrl,
m1i = mean_trt,
m2i = mean_cntrl,
sd1i = SD_trt,
sd2i = SD_cntrl,
data = ex)
ex <- ex %>%
filter(!is.na(yi)) # 568 to 488 obsex$dfc <- NA
for(i in 1:nrow(ex)) {
if(ex$duration_first[i] == 3) {
ex$dfc[i] <- "3"
} else if(between(ex$duration_first[i], 5, 6)) {
ex$dfc[i] <- "5-6"
} else if(between(ex$duration_first[i], 7, 12)) {
ex$dfc[i] <- "7-12"
} else if(between(ex$duration_first[i], 12, 18)) {
ex$dfc[i] <- "12-18"
} else if(between(ex$duration_first[i], 19, 24)) {
ex$dfc[i] <- "19-24"
} else if(between(ex$duration_first[i], 25, 36)) {
ex$dfc[i] <- "25-36"
} else if(between(ex$duration_first[i], 37, 50)) {
ex$dfc[i] <- "37-50"
} else if(between(ex$duration_first[i], 100, 200)) {
ex$dfc[i] <- "100-200"
} else {
ex$dfc[i] <- ">200"
}
}
ex$dfc <- factor(ex$df, levels = c("3", "5-6", "7-12", "12-18", "19-24", "25-36", "37-50", "100-200", ">200"))
ex$dlc <- NA
for(i in 1:nrow(ex)) {
if(between(ex$duration_last[i], 0, 1.5)) {
ex$dlc[i] <- "0-1.5"
} else if(ex$duration_last[i] == 2) {
ex$dlc[i] <- "2"
} else if(between(ex$duration_last[i], 3, 3.5)) {
ex$dlc[i] <- "3-3.5"
} else if(between(ex$duration_last[i], 4, 6)) {
ex$dlc[i] <- "4-6"
} else if(between(ex$duration_last[i], 7, 12)) {
ex$dlc[i] <- "7-12"
} else if(between(ex$duration_last[i], 13, 18)) {
ex$dlc[i] <- "13-18"
} else if(between(ex$duration_last[i], 19, 24)) {
ex$dlc[i] <- "19-24"
} else if(between(ex$duration_last[i], 36, 49)) {
ex$dlc[i] <- "36-49"
} else {
ex$dlc[i] <- ">100"
}
}
ex$dlc <- factor(ex$dl, levels = c("0-1.5", "2", "3-3.5", "4-6", "7-12", "13-18", "19-24",
"36-49", ">100"))
ex$cratc <- NA
for(i in 1:nrow(ex)) {
if(is.na(ex$C_rate[i])) {
ex$cratc[i] <- "idk"
} else if(between(ex$C_rate[i], 0, 100)) {
ex$cratc[i] <- "30-100"
} else if(between(ex$C_rate[i], 101, 160)) {
ex$cratc[i] <- "133-160"
} else if(between(ex$C_rate[i], 161, 200)) {
ex$cratc[i] <- "174-200"
} else if(between(ex$C_rate[i], 201, 300)) {
ex$cratc[i] <- "210-300"
} else if(between(ex$C_rate[i], 301, 400)) {
ex$cratc[i] <- "330-400"
} else if(between(ex$C_rate[i], 401, 500)) {
ex$cratc[i] <- "420-500"
} else if(between(ex$C_rate[i], 501, 600)) {
ex$cratc[i] <- "506-600"
} else if(between(ex$C_rate[i], 630, 700)) {
ex$cratc[i] <- "620-700"
} else if(between(ex$C_rate[i], 714, 999)) {
ex$cratc[i] <- "714-999"
} else if(between(ex$C_rate[i], 1000, 1330)) {
ex$cratc[i] <- "1000-1330"
} else if(between(ex$C_rate[i], 1600, 2000)) {
ex$cratc[i] <- "1600-2000"
} else if(between(ex$C_rate[i], 2001, 3000)) {
ex$cratc[i] <- "2110-3000"
} else if(between(ex$C_rate[i], 3001, 5000)) {
ex$cratc[i] <- "3346-5000"
} else {
ex$cratc[i] <- ">5000"
}
}
ex$cratc <- factor(ex$cratc, levels = c("30-100", "133-160", "174-200", "210-300", "330-400", "420-500",
"506-600", "620-700", "714-999", "1000-1330", "1600-2000",
"2110-3000", "3346-5000", ">5000"))
ex$capc <- NA
for(i in 1:nrow(ex)) {
if(ex$C_app[i] == 1) {
ex$capc[i] <- "1"
} else if(ex$C_app[i] == 2) {
ex$capc[i] <- "2"
} else if(between(ex$C_app[i], 3, 6)) {
ex$capc[i] <- "3-6"
} else if(between(ex$C_app[i], 7, 10)) {
ex$capc[i] <- "7-10"
} else if(between(ex$C_app[i], 15, 22)) {
ex$capc[i] <- "15-22"
} else if(between(ex$C_app[i], 32, 40)) {
ex$capc[i] <- "32-40"
} else {
ex$capc[i] <- ">40"
}
}
ex$capc <- factor(ex$capc, levels = c("1", "2", "3-6", "7-10", "15-22", "32-40", ">40"))
ex$capt <- NA
for(i in 1:nrow(ex)) {
if(ex$C_app_tm[i] == 0) {
ex$capt[i] <- "1 application total"
} else if(between(ex$C_app_tm[i], 0.001, 6)) {
ex$capt[i] <- "1-6"
} else if(between(ex$C_app_tm[i], 7, 12)) {
ex$capt[i] <- "7-12"
} else if(between(ex$C_app_tm[i], 13, 24)) {
ex$capt[i] <- "13-24"
} else if(between(ex$C_app_tm[i], 25, 36)) {
ex$capt[i] <- "25-36"
} else if(between(ex$C_app_tm[i], 37, 48)) {
ex$capt[i] <- "37-48"
} else {
ex$capt[i] <- ">48"
}
}
ex$capt <- factor(ex$capt, levels = c("1 application total", "1-6", "7-12", "13-24",
"25-36", "37-48", ">48"))
ex$plotc <- NA
for(i in 1:nrow(ex)) {
if(is.na(ex$plot[i])) {
ex$plotc[i] <- "idk"
} else if(ex$plot[i] < 1) {
ex$plotc[i] <- "<1"
} else if(ex$plot[i] == 1) {
ex$plotc[i] <- "1"
} else if(between(ex$plot[i], 1.3, 3.75)) {
ex$plotc[i] <- "1.3-3.75"
} else if(ex$plot[i] == 4) {
ex$plotc[i] <- "4"
} else if(between(ex$plot[i], 6, 9)) {
ex$plotc[i] <- "6-9"
} else if(ex$plot[i] == 12) {
ex$plotc[i] <- "12"
} else if(between(ex$plot[i], 12.5, 16)) {
ex$plotc[i] <- "12.5-16"
} else if(ex$plot[i] == 25) {
ex$plotc[i] <- "25"
} else if(between(ex$plot[i], 28, 50)) {
ex$plotc[i] <- "28-50"
} else if(ex$plot[i] == 75) {
ex$plotc[i] <- "75"
} else {
ex$plotc[i] <- ">100"
}
}
ex$plotc <- factor(ex$plotc,
levels = c("<1", "1", "1.3-3.75", "4", "6-9", "12", "12.5-16",
"25", "28-50", "75", ">100"))
ex <- ex %>%
mutate(seedn = rep(NA, nrow(ex)))
for(i in 1:nrow(ex)) {
if(is.na(ex$seeding_native[i])) {
ex$seedn[i] <- "native seeded"
} else if(ex$seeding_native[i] == 0) {
ex$seedn[i] <- "native not seeded"
} else {
ex$seedn[i] <- "native seeded"
}
}write.csv(ex,
file = "data/cleaned/exotic-cleaned.csv",
row.names = FALSE)nt <- all.1res.nt %>%
filter(str_detect(plant_category, "native"))
nt <- escalc(measure = "SMD",
n1i = n_trt,
n2i = n_cntrl,
m1i = mean_trt,
m2i = mean_cntrl,
sd1i = SD_trt,
sd2i = SD_cntrl,
data = nt)
nt <- nt %>%
filter(!is.na(yi)) # 1125 to 655 obsnt$dfc <- NA
for(i in 1:nrow(nt)) {
if(nt$duration_first[i] == 3) {
nt$dfc[i] <- "3"
} else if(between(nt$duration_first[i], 5, 6)) {
nt$dfc[i] <- "5-6"
} else if(between(nt$duration_first[i], 7, 12)) {
nt$dfc[i] <- "7-12"
} else if(between(nt$duration_first[i], 12, 18)) {
nt$dfc[i] <- "12-18"
} else if(between(nt$duration_first[i], 19, 24)) {
nt$dfc[i] <- "19-24"
} else if(between(nt$duration_first[i], 25, 36)) {
nt$dfc[i] <- "25-36"
} else if(between(nt$duration_first[i], 37, 50)) {
nt$dfc[i] <- "37-50"
} else if(between(nt$duration_first[i], 100, 200)) {
nt$dfc[i] <- "100-200"
} else {
nt$dfc[i] <- ">200"
}
}
nt$dfc <- factor(nt$df, levels = c("3", "5-6", "7-12", "12-18", "19-24", "25-36", "37-50", "100-200", ">200"))
nt$dlc <- NA
for(i in 1:nrow(nt)) {
if(between(nt$duration_last[i], 0, 1.5)) {
nt$dlc[i] <- "0-1.5"
} else if(nt$duration_last[i] == 2) {
nt$dlc[i] <- "2"
} else if(between(nt$duration_last[i], 3, 3.5)) {
nt$dlc[i] <- "3-3.5"
} else if(between(nt$duration_last[i], 4, 6)) {
nt$dlc[i] <- "4-6"
} else if(between(nt$duration_last[i], 7, 12)) {
nt$dlc[i] <- "7-12"
} else if(between(nt$duration_last[i], 13, 18)) {
nt$dlc[i] <- "13-18"
} else if(between(nt$duration_last[i], 19, 24)) {
nt$dlc[i] <- "19-24"
} else if(between(nt$duration_last[i], 36, 49)) {
nt$dlc[i] <- "36-49"
} else {
nt$dlc[i] <- ">100"
}
}
nt$dlc <- factor(nt$dl, levels = c("0-1.5", "2", "3-3.5", "4-6", "7-12", "13-18", "19-24",
"36-49", ">100"))
nt$cratc <- NA
for(i in 1:nrow(nt)) {
if(is.na(nt$C_rate[i])) {
nt$cratc[i] <- "idk"
} else if(between(nt$C_rate[i], 0, 100)) {
nt$cratc[i] <- "30-100"
} else if(between(nt$C_rate[i], 101, 160)) {
nt$cratc[i] <- "133-160"
} else if(between(nt$C_rate[i], 161, 200)) {
nt$cratc[i] <- "174-200"
} else if(between(nt$C_rate[i], 201, 300)) {
nt$cratc[i] <- "210-300"
} else if(between(nt$C_rate[i], 301, 400)) {
nt$cratc[i] <- "330-400"
} else if(between(nt$C_rate[i], 401, 500)) {
nt$cratc[i] <- "420-500"
} else if(between(nt$C_rate[i], 501, 600)) {
nt$cratc[i] <- "506-600"
} else if(between(nt$C_rate[i], 630, 700)) {
nt$cratc[i] <- "620-700"
} else if(between(nt$C_rate[i], 714, 999)) {
nt$cratc[i] <- "714-999"
} else if(between(nt$C_rate[i], 1000, 1330)) {
nt$cratc[i] <- "1000-1330"
} else if(between(nt$C_rate[i], 1600, 2000)) {
nt$cratc[i] <- "1600-2000"
} else if(between(nt$C_rate[i], 2001, 3000)) {
nt$cratc[i] <- "2110-3000"
} else if(between(nt$C_rate[i], 3001, 5000)) {
nt$cratc[i] <- "3346-5000"
} else {
nt$cratc[i] <- ">5000"
}
}
nt$cratc <- factor(nt$cratc, levels = c("30-100", "133-160", "174-200", "210-300", "330-400", "420-500",
"506-600", "620-700", "714-999", "1000-1330", "1600-2000",
"2110-3000", "3346-5000", ">5000"))
nt$capc <- NA
for(i in 1:nrow(nt)) {
if(nt$C_app[i] == 1) {
nt$capc[i] <- "1"
} else if(nt$C_app[i] == 2) {
nt$capc[i] <- "2"
} else if(between(nt$C_app[i], 3, 6)) {
nt$capc[i] <- "3-6"
} else if(between(nt$C_app[i], 7, 10)) {
nt$capc[i] <- "7-10"
} else if(between(nt$C_app[i], 15, 22)) {
nt$capc[i] <- "15-22"
} else if(between(nt$C_app[i], 32, 40)) {
nt$capc[i] <- "32-40"
} else {
nt$capc[i] <- ">40"
}
}
nt$capc <- factor(nt$capc, levels = c("1", "2", "3-6", "7-10", "15-22", "32-40", ">40"))
nt$capt <- NA
for(i in 1:nrow(nt)) {
if(nt$C_app_tm[i] == 0) {
nt$capt[i] <- "1 application total"
} else if(between(nt$C_app_tm[i], 0.001, 6)) {
nt$capt[i] <- "1-6"
} else if(between(nt$C_app_tm[i], 7, 12)) {
nt$capt[i] <- "7-12"
} else if(between(nt$C_app_tm[i], 13, 24)) {
nt$capt[i] <- "13-24"
} else if(between(nt$C_app_tm[i], 25, 36)) {
nt$capt[i] <- "25-36"
} else if(between(nt$C_app_tm[i], 37, 48)) {
nt$capt[i] <- "37-48"
} else {
nt$capt[i] <- ">48"
}
}
nt$capt <- factor(nt$capt, levels = c("1 application total", "1-6", "7-12", "13-24",
"25-36", "37-48", ">48"))
nt$plotc <- NA
for(i in 1:nrow(nt)) {
if(is.na(nt$plot[i])) {
nt$plotc[i] <- "idk"
} else if(nt$plot[i] < 1) {
nt$plotc[i] <- "<1"
} else if(nt$plot[i] == 1) {
nt$plotc[i] <- "1"
} else if(between(nt$plot[i], 1.3, 3.75)) {
nt$plotc[i] <- "1.3-3.75"
} else if(nt$plot[i] == 4) {
nt$plotc[i] <- "4"
} else if(between(nt$plot[i], 6, 9)) {
nt$plotc[i] <- "6-9"
} else if(nt$plot[i] == 12) {
nt$plotc[i] <- "12"
} else if(between(nt$plot[i], 12.5, 16)) {
nt$plotc[i] <- "12.5-16"
} else if(nt$plot[i] == 25) {
nt$plotc[i] <- "25"
} else if(between(nt$plot[i], 28, 50)) {
nt$plotc[i] <- "28-50"
} else if(nt$plot[i] == 75) {
nt$plotc[i] <- "75"
} else {
nt$plotc[i] <- ">100"
}
}
nt$plotc <- factor(nt$plotc,
levels = c("<1", "1", "1.3-3.75", "4", "6-9", "12", "12.5-16",
"25", "28-50", "75", ">100"))
nt <- nt %>%
mutate(seedn = rep(NA, nrow(nt)))
for(i in 1:nrow(nt)) {
if(is.na(nt$seeding_native[i])) {
nt$seedn[i] <- "native seeded"
} else if(nt$seeding_native[i] == 0) {
nt$seedn[i] <- "native not seeded"
} else {
nt$seedn[i] <- "native seeded"
}
}write.csv(nt,
file = "data/cleaned/native-cleaned.csv",
row.names = FALSE)