data.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$Publication <- "10.1126/science.aac7287"
data.site$Credit <- "Ruan Veldtman and Jonathan Colville"
data.site$Email_contact <- "R.Veldtman@sanbi.org.za"
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
data_raw_aux <- data_raw[,c(14,59)]
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
###############################
# YIELD
###############################
data.yield <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "seed_weights")
data.yield_adapt <- data.yield %>%
rename(site_id=Site,yield=`Weight_of_10_sunflower_heads(=avergae*10)`) %>%
select(site_id,yield) %>% mutate(yield=yield/1000) %>%
group_by(site_id) %>% summarise_all(mean)
data.site <- data.site %>% left_join(data.yield_adapt,by="site_id")
data.site$yield_units <- "Seed weight of 10 sunflower heads (kg)"
data.site$yield2 <- NA
data.site$yield2_units <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators2 <- NA
data.site$yield_treatments_pollen_supplement2 <- NA
data_raw_obs_ini <- data_raw[,c(14,27,33,36:58)] %>%
rename(site_id=Site)
data_raw_obs_ini %>% group_by(site_id) %>% count()
data_raw_obs <- data_raw_obs_ini %>% gather(Organism_ID,abundance,c(4:26)) %>%
filter(abundance>0) %>% select(-`time(secs)`,-`crop density(flowerss/ha)`)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms <- select(data_raw_obs,Organism_ID) %>% unique() %>% filter(!is.na(Organism_ID))
list_organisms_guild <- list_organisms %>% left_join(gild_list,by=c("Organism_ID"))
#Check NA's in guild
x <- list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild$Guild[grepl("Lasioglossum",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Lycaenidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hesperiidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hypolimnas",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("large_hover",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Apis_millifera",list_organisms_guild$Organism_ID,ignore.case = T)] <- "honeybees"
list_organisms_guild$Guild[grepl("Acraea_horta",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Astylus_atromaculatus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Colotis",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("African Monarch butterfly",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Lygus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild$Guild[grepl("Macroglossum_trochilus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Muscid",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild$Guild[grepl("Noctuidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Precis_oenone",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Asarkina",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Sphecidae_wasp",list_organisms_guild$Organism_ID,ignore.case = T)] <- "non_bee_hymenoptera"
list_organisms_guild$Guild[grepl("Tenebrionidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Tetraloniella_braunsiana",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Xylocopa",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Danus_chrysippus_aegyptius",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
#Sanity Checks
list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
#Add guild to observations
data_obs_guild <- data_raw_obs %>% left_join(list_organisms_guild, by = "Organism_ID")
data_obs_guild %>% filter(is.na(Guild))
View(data_obs_guild)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
library(parzer)
dir_ini <- getwd()
science_raw <- read.delim("Database_Science.txt",sep = " ")
# Load data
data_raw <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "Scan sampling")
data_raw$month_of_study <- as.numeric(format(as.Date(data_raw$date, format="%Y/%m/%d"),"%m"))
# Select data
data.site <- data_raw[,c(1,2,3,11,14,15,16,19,32,33)] %>%
rename(site_id=Site,sampling_year=year,latitude=DDS,longitude=DDE,
variety=crop_variety,
field_size="Size(ha)",plant_density="crop density(plants/ha)",
flowerss_per_ha="crop density(flowerss/ha)") %>% unique()
# Fix crop and latitude
data.site$crop <- "Helianthus annuus"
data.site$latitude <- -1*data.site$latitude
data.site$study_id <- "Ruan_Veldtman_Helianthus_annuus_South_Africa_2011"
data.site$management <- "conventional"
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- NA
data.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$Publication <- "10.1126/science.aac7287"
data.site$Credit <- "Ruan Veldtman and Jonathan Colville"
data.site$Email_contact <- "R.Veldtman@sanbi.org.za"
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
data_raw_aux <- data_raw[,c(14,59)]
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
###############################
# YIELD
###############################
data.yield <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "seed_weights")
data.yield_adapt <- data.yield %>%
rename(site_id=Site,yield=`Weight_of_10_sunflower_heads(=avergae*10)`) %>%
select(site_id,yield) %>% mutate(yield=yield/1000) %>%
group_by(site_id) %>% summarise_all(mean)
data.site <- data.site %>% left_join(data.yield_adapt,by="site_id")
data.site$yield_units <- "Seed weight of 10 sunflower heads (kg)"
data.site$yield2 <- NA
data.site$yield2_units <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators2 <- NA
data.site$yield_treatments_pollen_supplement2 <- NA
data_raw_obs_ini <- data_raw[,c(14,27,33,36:58)] %>%
rename(site_id=Site)
data_raw_obs_ini %>% group_by(site_id) %>% count()
data_raw_obs <- data_raw_obs_ini %>% gather(Organism_ID,abundance,c(4:26)) %>%
filter(abundance>0) %>% select(-`time(secs)`,-`crop density(flowerss/ha)`)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms <- select(data_raw_obs,Organism_ID) %>% unique() %>% filter(!is.na(Organism_ID))
list_organisms_guild <- list_organisms %>% left_join(gild_list,by=c("Organism_ID"))
#Check NA's in guild
x <- list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild$Guild[grepl("Lasioglossum",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Lycaenidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hesperiidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hypolimnas",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("large_hover",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Apis_millifera",list_organisms_guild$Organism_ID,ignore.case = T)] <- "honeybees"
list_organisms_guild$Guild[grepl("Acraea_horta",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Astylus_atromaculatus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Colotis",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("African Monarch butterfly",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Lygus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild$Guild[grepl("Macroglossum_trochilus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Muscid",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild$Guild[grepl("Noctuidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Precis_oenone",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Asarkina",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Sphecidae_wasp",list_organisms_guild$Organism_ID,ignore.case = T)] <- "non_bee_hymenoptera"
list_organisms_guild$Guild[grepl("Tenebrionidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Tetraloniella_braunsiana",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Xylocopa",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Danus_chrysippus_aegyptius",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
#Sanity Checks
list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
#Add guild to observations
data_obs_guild <- data_raw_obs %>% left_join(list_organisms_guild, by = "Organism_ID")
View(data_obs_guild)
View(list_organisms)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
library(parzer)
dir_ini <- getwd()
science_raw <- read.delim("Database_Science.txt",sep = " ")
# Load data
data_raw <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "Scan sampling")
data_raw$month_of_study <- as.numeric(format(as.Date(data_raw$date, format="%Y/%m/%d"),"%m"))
# Select data
data.site <- data_raw[,c(1,2,3,11,14,15,16,19,32,33)] %>%
rename(site_id=Site,sampling_year=year,latitude=DDS,longitude=DDE,
variety=crop_variety,
field_size="Size(ha)",plant_density="crop density(plants/ha)",
flowerss_per_ha="crop density(flowerss/ha)") %>% unique()
# Fix crop and latitude
data.site$crop <- "Helianthus annuus"
data.site$latitude <- -1*data.site$latitude
data.site$study_id <- "Ruan_Veldtman_Helianthus_annuus_South_Africa_2011"
data.site$management <- "conventional"
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- NA
data.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$Publication <- "10.1126/science.aac7287"
data.site$Credit <- "Ruan Veldtman and Jonathan Colville"
data.site$Email_contact <- "R.Veldtman@sanbi.org.za"
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
data_raw_aux <- data_raw[,c(14,59)]
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw_aux %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
###############################
# YIELD
###############################
data.yield <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "seed_weights")
data.yield_adapt <- data.yield %>%
rename(site_id=Site,yield=`Weight_of_10_sunflower_heads(=avergae*10)`) %>%
select(site_id,yield) %>% mutate(yield=yield/1000) %>%
group_by(site_id) %>% summarise_all(mean)
data.site <- data.site %>% left_join(data.yield_adapt,by="site_id")
data.site$yield_units <- "Seed weight of 10 sunflower heads (kg)"
data.site$yield2 <- NA
data.site$yield2_units <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_no_pollinators2 <- NA
data.site$yield_treatments_pollen_supplement2 <- NA
data_raw_obs_ini <- data_raw[,c(14,27,33,36:58)] %>%
rename(site_id=Site)
data_raw_obs_ini %>% group_by(site_id) %>% count()
data_raw_obs <- data_raw_obs_ini %>% gather(Organism_ID,abundance,c(4:26)) %>%
filter(abundance>0) %>% select(-`time(secs)`,-`crop density(flowerss/ha)`)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms <- select(data_raw_obs,Organism_ID) %>% unique() %>% filter(!is.na(Organism_ID))
list_organisms_guild <- list_organisms %>% left_join(gild_list,by=c("Organism_ID"))
#Check NA's in guild
x <- list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild$Guild[grepl("Lasioglossum",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Lycaenidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hesperiidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Hypolimnas",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("large_hover",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Apis_millifera",list_organisms_guild$Organism_ID,ignore.case = T)] <- "honeybees"
list_organisms_guild$Guild[grepl("Acraea_horta",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Astylus_atromaculatus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Colotis",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("African Monarch butterfly",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Lygus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild$Guild[grepl("Macroglossum_trochilus",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Muscid",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild$Guild[grepl("Noctuidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Precis_oenone",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild$Guild[grepl("Asarkina",list_organisms_guild$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild$Guild[grepl("Sphecidae_wasp",list_organisms_guild$Organism_ID,ignore.case = T)] <- "non_bee_hymenoptera"
list_organisms_guild$Guild[grepl("Tenebrionidae",list_organisms_guild$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild$Guild[grepl("Tetraloniella_braunsiana",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Xylocopa",list_organisms_guild$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Danus_chrysippus_aegyptius",list_organisms_guild$Organism_ID,ignore.case = T)] <- "lepidoptera"
#Sanity Checks
list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
#Add guild to observations
data_obs_guild <- data_raw_obs %>% left_join(list_organisms_guild, by = "Organism_ID")
View(data_obs_guild)
data_obs_guild %>% group_by(guild) %>% count()
data_obs_guild %>% group_by(Guild) %>% count()
# Remove entries with zero abundance
data_obs_guild  <- data_obs_guild  %>% filter(abundance>0)
sampling_rounds <- data_raw_obs_ini %>% select(site_id,`time(secs)`) %>%
mutate(`time(secs)`=0.25*`time(secs)`/60) %>% #`time(secs)` refers to 4 transects apparently
group_by(site_id) %>% summarize_all(sum) %>% rename(time=`time(secs)`)
data_obs_guild <- data_obs_guild %>% left_join(sampling_rounds,by="site_id")
insect_sampling <- tibble(
study_id = "Ruan_Veldtman_Helianthus_annuus_South_Africa_2011",
site_id = data_obs_guild$site_id,
pollinator = data_obs_guild$Organism_ID,
guild = data_obs_guild$Guild,
sampling_method = "sweep net",
abundance = data_obs_guild$abundance,
total_sampled_area = NA,
total_sampled_time = data_obs_guild$time,
total_sampled_flowers = 400,
Description = "On each field study site, 100 flower heads in each of four parallel transects (total 400 flower heads) were surveyed in the morning and afternoon")
View(insect_sampling)
data_raw_obs_ini_ob <- read_excel("SouthAfrica Sunflower/Common_database_SA_Sunflower_2011_scan_collection_and_seed_weights.xlsx",
sheet = "collection_samples") %>%
rename(site_id = `CODE(A=away from natural; N=near natural; AM=morning; PM=afternoon; S=scan)`)
# Transform site labels
data_raw_obs_ini_ob$site_id <- substr(data_raw_obs_ini_ob$site_id, start = 1, stop = 2)
data_raw_obs_ini_ob %>% group_by(site_id) %>% count()
data_raw_obs_ob <- data_raw_obs_ini_ob %>% gather(Organism_ID,abundance,c(2:40)) %>%
filter(abundance>0)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms_ob <- select(data_raw_obs_ob,Organism_ID) %>% unique() %>% filter(!is.na(Organism_ID))
list_organisms_guild_ob <- list_organisms_ob %>% left_join(gild_list,by=c("Organism_ID"))
#Check NA's in guild
list_organisms_guild_ob %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild_ob$Guild[grepl("Lasioglossum",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Lycaenidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Hesperiidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Hypolimnas",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("large_hover",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild_ob$Guild[grepl("Apis_millifera",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "honeybees"
list_organisms_guild_ob$Guild[grepl("Acraea_horta",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Astylus_atromaculatus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Colotis",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("African Monarch butterfly",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Lygus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild_ob$Guild[grepl("Macroglossum_trochilus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Muscid",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild_ob$Guild[grepl("Noctuidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Precis_oenone",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Asarkina",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild_ob$Guild[grepl("Sphecidae_wasp",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "non_bee_hymenoptera"
list_organisms_guild_ob$Guild[grepl("Tenebrionidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Tetraloniella_braunsiana",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Xylocopa",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Danus_chrysippus_aegyptius",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("bee.red.abdomen.sp1",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- NA
list_organisms_guild_ob$Guild[grepl("Lasioglossum",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Lycaenidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Hesperiidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Hypolimnas",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("large_hover",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild_ob$Guild[grepl("Apis_millifera",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "honeybees"
list_organisms_guild_ob$Guild[grepl("Acraea_horta",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Astylus_atromaculatus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Colotis",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("African Monarch butterfly",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Lygus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild_ob$Guild[grepl("Macroglossum_trochilus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Muscid",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild_ob$Guild[grepl("Noctuidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Precis_oenone",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Asarkina",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "syrphids"
list_organisms_guild_ob$Guild[grepl("Sphecidae_wasp",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "non_bee_hymenoptera"
list_organisms_guild_ob$Guild[grepl("Tenebrionidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Tetraloniella_braunsiana",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Xylocopa",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Danus_chrysippus_aegyptius",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("bee.red.abdomen.sp1",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_wild_bees"
list_organisms_guild_ob$Guild[grepl("Bombyliidae_sp.1",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "humbleflies"
list_organisms_guild_ob$Guild[grepl("brown_skipper_sp1.",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Caliphoridae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild_ob$Guild[grepl("Cetoniidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Chamaesphecia_anthraciformis",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Chrysoperla",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild_ob$Guild[grepl("Cleridae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Coeliades_pisistratus",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Colias",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Fulgoridae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild_ob$Guild[grepl("Lace_bug",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other"
list_organisms_guild_ob$Guild[grepl("ladybird",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "beetles"
list_organisms_guild_ob$Guild[grepl("Mylothris",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
list_organisms_guild_ob$Guild[grepl("Sarcophagidae",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "other_flies"
list_organisms_guild_ob$Guild[grepl("Vanessa_cardui",list_organisms_guild_ob$Organism_ID,ignore.case = T)] <- "lepidoptera"
#Sanity Checks
list_organisms_guild_ob %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
#Add guild to observations
data_obs_guild_ob <- data_raw_obs_ob %>% left_join(list_organisms_guild_ob, by = "Organism_ID")
# Remove entries with zero abundance
data_obs_guild_ob  <- data_obs_guild_ob  %>% filter(abundance>0)
sampling_rounds_ob <- data_raw_obs_ini_ob %>% group_by(site_id) %>% count() %>%
mutate(n=n/6)
data_obs_guild_ob <- data_obs_guild_ob %>% left_join(sampling_rounds_ob,by="site_id")
insect_sampling_ob <- tibble(
study_id = "Ruan_Veldtman_Helianthus_annuus_South_Africa_2011",
site_id = data_obs_guild_ob$site_id,
pollinator = data_obs_guild_ob$Organism_ID,
guild = data_obs_guild_ob$Guild,
sampling_method = "observation",
abundance = data_obs_guild_ob$abundance,
total_sampled_area = NA,
total_sampled_time = NA,
total_sampled_flowers = NA,
Description = "Voucher specimens for all insect flower visitors that touched the reproductive structures of surveyed sunflower heads were collected. From this, all bee specimens were identified to the lowest possible taxonomic level.")
insect_sampling_total <- bind_rows(insect_sampling,insect_sampling_ob)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_total, "insect_sampling_Ruan_Veldtman_Helianthus_annuus_South_Africa_2011.csv")
setwd(dir_ini)
data_obs_guild_2 <- data_obs_guild %>%
group_by(site_id,Organism_ID,Guild) %>% summarise_all(sum,na.rm=TRUE)
abundance_aux <- data_obs_guild_2 %>% filter(!is.na(Guild)) %>%
group_by(site_id,Guild) %>% count(wt=abundance) %>%
spread(key=Guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(bumblebees=0,humbleflies=0,total=0)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux$total <- rowSums(abundance_aux[,c(2:ncol(abundance_aux))])
data.site <- data.site %>% left_join(abundance_aux, by = "site_id")
abundace_field <- data_obs_guild %>%
select(site_id,Organism_ID,abundance)%>%
group_by(site_id,Organism_ID) %>% count(wt=abundance)
abundace_field <- abundace_field %>% spread(key=Organism_ID,value=n)
abundace_field[is.na(abundace_field)] <- 0
abundace_field$r_obser <-  0
abundace_field$r_chao <-  0
for (i in 1:nrow(abundace_field)) {
x <- as.numeric(abundace_field[i,2:(ncol(abundace_field)-2)])
chao  <-  ChaoRichness(x, datatype = "abundance", conf = 0.95)
abundace_field$r_obser[i] <-  chao$Observed
abundace_field$r_chao[i] <-  chao$Estimator
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 0.9
richness_aux <- abundace_field %>% select(site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1",richness_restriction=NA)
if (percentage_species_morphos < 0.8){
richness_aux[,2:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux, by = "site_id")
visits_aux <- abundance_aux
visits_aux <- visits_aux %>% left_join(sampling_rounds, by = "site_id")
visitation_rate <- tibble(
site_id=visits_aux$site_id,
total_sampled_area = NA,
total_sampled_time = visits_aux$time,
visitation_rate_units = "visits per 100 sunflowers heads and hour",
visitation_rate = 60*100*visits_aux$total/visits_aux$time/400,
visit_honeybee = 60*100*visits_aux$honeybees/visits_aux$time/400,
visit_bombus = 60*100*visits_aux$bumblebees/visits_aux$time/400,
visit_wildbees = 60*100*visits_aux$other_wild_bees/visits_aux$time/400,
visit_syrphids = 60*100*visits_aux$syrphids/visits_aux$time/400,
visit_humbleflies = 60*100*visits_aux$humbleflies/visits_aux$time/400,
visit_other_flies = 60*100*visits_aux$other_flies/visits_aux$time/400,
visit_beetles = 60*100*visits_aux$beetles/visits_aux$time/400,
visit_lepidoptera = 60*100*visits_aux$lepidoptera/visits_aux$time/400,
visit_nonbee_hymenoptera = 60*100*visits_aux$non_bee_hymenoptera/visits_aux$time/400,
visit_others = 60*100*visits_aux$other/visits_aux$time/400,
)
data.site <- data.site %>% left_join(visitation_rate, by = "site_id")
field_level_data <- tibble(
study_id = data.site$study_id,
site_id = data.site$site_id,
crop = data.site$crop,
variety = data.site$variety,
management = data.site$management,
country = data.site$country,
latitude = data.site$latitude,
longitude = data.site$longitude,
X_UTM=data.site$X_UTM,
Y_UTM=data.site$Y_UTM,
zone_UTM=data.site$zone_UTM,
sampling_start_month = data.site$sampling_start_month,
sampling_end_month = data.site$sampling_end_month,
sampling_year = data.site$sampling_year,
field_size = data.site$field_size,
yield=data.site$yield,
yield_units=data.site$yield_units,
yield2=data.site$yield2,
yield2_units=data.site$yield2_units,
yield_treatments_no_pollinators=data.site$yield_treatments_no_pollinators,
yield_treatments_pollen_supplement=data.site$yield_treatments_no_pollinators,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density/10000,
seeds_per_fruit=data.site$seeds_per_fruit,
seeds_per_plant=data.site$seeds_per_plant,
seed_weight=data.site$seed_weight,
observed_pollinator_richness=data.site$observed_pollinator_richness,
other_pollinator_richness=data.site$other_pollinator_richness,
other_richness_estimator_method=data.site$other_richness_estimator_method,
richness_restriction = data.site$richness_restriction,
abundance = data.site$total,
ab_honeybee = data.site$honeybees,
ab_bombus = data.site$bumblebees,
ab_wildbees = data.site$other_wild_bees,
ab_syrphids = data.site$syrphids,
ab_humbleflies= data.site$humbleflies,
ab_other_flies= data.site$other_flies,
ab_beetles=data.site$beetles,
ab_lepidoptera=data.site$lepidoptera,
ab_nonbee_hymenoptera=data.site$non_bee_hymenoptera,
ab_others = data.site$other,
total_sampled_area = data.site$total_sampled_area,
total_sampled_time = data.site$total_sampled_time,
visitation_rate_units = data.site$visitation_rate_units,
visitation_rate = data.site$visitation_rate,
visit_honeybee = data.site$visit_honeybee,
visit_bombus = data.site$visit_bombus,
visit_wildbees = data.site$visit_wildbees,
visit_syrphids = data.site$visit_syrphids,
visit_humbleflies = data.site$visit_humbleflies,
visit_other_flies = data.site$visit_other_flies,
visit_beetles = data.site$visit_beetles,
visit_lepidoptera = data.site$visit_lepidoptera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$Email_contact
)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data, "field_level_data_Ruan_Veldtman_Helianthus_annuus_South_Africa_2011.csv")
setwd(dir_ini)
