sampling <- insect_sampling %>% group_by(study_id,site_id) %>% summarise(flowers=mean(total_sampled_flowers,na.rm = T),
area=mean(total_sampled_area),
time=mean(total_sampled_time))
visit_aux <- abundance_aux %>% left_join(sampling,by=c("study_id","site_id")) %>%
mutate(
vist_beetles = 60*100*beetles/time/flowers,
vist_bumblebees = 60*100*bumblebees/time/flowers,
vist_honeybees = 60*100*honeybees/time/flowers,
vist_humbleflies = 60*100*humbleflies/time/flowers,
vist_lepidoptera = 60*100*lepidoptera/time/flowers,
vist_non_bee_hymenoptera = 60*100*non_bee_hymenoptera/time/flowers,
vist_other_flies = 60*100*other_flies/time/flowers,
vist_other_wild_bees = 60*100*other_wild_bees/time/flowers,
vist_others = 60*100*other/time/flowers,
vist_syrphids =  60*100*syrphids/time/flowers,
vist_total = vist_beetles + vist_bumblebees +
vist_honeybees + vist_humbleflies +
vist_lepidoptera + vist_non_bee_hymenoptera +
vist_other_flies + vist_other_wild_bees + vist_others + vist_syrphids
) %>%
select(study_id,site_id,vist_beetles,vist_bumblebees,vist_honeybees, vist_humbleflies,
vist_lepidoptera,vist_non_bee_hymenoptera,vist_other_flies,
vist_other_wild_bees,vist_others,vist_syrphids,vist_total
)
View(visit_aux)
data.site <- data.site %>% left_join(visit_aux,by=c("study_id","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=NA,
Y_UTM=NA,
zone_UTM=NA,
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_pollen_supplement,
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$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$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$other,
total_sampled_area = data.site$area,
total_sampled_time = data.site$time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$vist_total,
visit_honeybee = data.site$vist_honeybees,
visit_bombus = data.site$vist_bumblebees,
visit_wildbees = data.site$vist_other_wild_bees,
visit_syrphids = data.site$vist_syrphids,
visit_humbleflies = data.site$vist_humbleflies,
visit_other_flies = data.site$vist_other_flies,
visit_beetles = data.site$vist_beetles,
visit_lepidoptera = data.site$vist_lepidoptera,
visit_nonbee_hymenoptera = data.site$vist_non_bee_hymenoptera,
visit_others = data.site$vist_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
)
View(field_level_data)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_2018, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(field_level_data_2019, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
field_level_data_2018 <- field_level_data %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
field_level_data_2019 <- field_level_data %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_2018, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(field_level_data_2019, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
setwd(dir_ini)
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("globalcrop.BEANS.BurnsStanley.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id[data.site$sampling_year==2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
data.site$study_id[data.site$sampling_year==2019] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
data.site$Credit <- "Katherine LW Burns & Dara A Stanley"
data.site$email <- "katherine.burns@ucdconnect.ie"
data.site$Publication <- NA
insect_sampling <- read_excel("globalcrop.BEANS.BurnsStanley.xlsx", sheet = "insect_sampling")
sites_2018 <- data.site$site_id[data.site$sampling_year==2018]
insect_sampling$study_id[insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
insect_sampling$study_id[!insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="other flies"] <-"other_flies"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling_2018 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
insect_sampling_2019 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2018, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(insect_sampling_2019, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
setwd(dir_ini)
abundance_aux <- insect_sampling %>% select(study_id,site_id,guild,abundance) %>%
group_by(study_id,site_id,guild) %>% count(wt=abundance) %>%
spread(key=guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(other_wild_bees=0,
syrphids=0,
humbleflies=0,
beetles=0,
non_bee_hymenoptera=0,
lepidoptera=0,
other=0,
total=0)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux$total <- rowSums(abundance_aux[,c(3:ncol(abundance_aux))])
data.site <- data.site %>% left_join(abundance_aux, by = c("study_id","site_id"))
abundace_field <- insect_sampling %>%
select(study_id, site_id,pollinator,abundance)%>%
group_by(study_id,site_id,pollinator) %>% count(wt=abundance)
abundace_field <- abundace_field %>% spread(key=pollinator,value=n)
abundace_field[is.na(abundace_field)] <- 0
abundace_field$r_obser <-  0
abundace_field$r_chao <-  0
for (i in 1:nrow(abundace_field)) {
x <- as.numeric(abundace_field[i,3:(ncol(abundace_field)-2)])
chao  <-  ChaoRichness(x, datatype = "abundance", conf = 0.95)
abundace_field$r_obser[i] <-  chao$Observed
abundace_field$r_chao[i] <-  chao$Estimator
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 1
richness_aux <- abundace_field %>% select(study_id,site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% dplyr::rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1",richness_restriction=NA)
if (percentage_species_morphos < 0.8){
richness_aux[,3:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux,by=c("study_id","site_id"))
##################
# VISITATION RATE AND SAMPLING
##################
insect_sampling$total_sampled_flowers <- as.numeric(insect_sampling$total_sampled_flowers)
sampling <- insect_sampling %>% group_by(study_id,site_id) %>% summarise(flowers=mean(total_sampled_flowers,na.rm = T),
area=mean(total_sampled_area),
time=mean(total_sampled_time))
View(abundace_field)
2/579/150
60*100*2/579/150
View(abundance_aux)
5*60*100*2/579/150
visit_aux <- abundance_aux %>% left_join(sampling,by=c("study_id","site_id")) %>%
mutate(
vist_beetles = 60*100*beetles/time/flowers,
vist_bumblebees = 60*100*bumblebees/time/flowers,
vist_honeybees = 60*100*honeybees/time/flowers,
vist_humbleflies = 60*100*humbleflies/time/flowers,
vist_lepidoptera = 60*100*lepidoptera/time/flowers,
vist_non_bee_hymenoptera = 60*100*non_bee_hymenoptera/time/flowers,
vist_other_flies = 60*100*other_flies/time/flowers,
vist_other_wild_bees = 60*100*other_wild_bees/time/flowers,
vist_others = 60*100*other/time/flowers,
vist_syrphids =  60*100*syrphids/time/flowers,
vist_total = vist_beetles + vist_bumblebees +
vist_honeybees + vist_humbleflies +
vist_lepidoptera + vist_non_bee_hymenoptera +
vist_other_flies + vist_other_wild_bees + vist_others + vist_syrphids
) %>%
select(study_id,site_id,vist_beetles,vist_bumblebees,vist_honeybees, vist_humbleflies,
vist_lepidoptera,vist_non_bee_hymenoptera,vist_other_flies,
vist_other_wild_bees,vist_others,vist_syrphids,vist_total
)
View(visit_aux)
View(abundace_field)
View(abundance_aux)
5*60*100*1/579/150
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("globalcrop.BEANS.BurnsStanley_REVISED.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id[data.site$sampling_year==2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
data.site$study_id[data.site$sampling_year==2019] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
data.site$Credit <- "Katherine LW Burns & Dara A Stanley"
data.site$email <- "katherine.burns@ucdconnect.ie"
data.site$Publication <- NA
insect_sampling <- read_excel("globalcrop.BEANS.BurnsStanley.xlsx", sheet = "insect_sampling")
insect_sampling <- read_excel("globalcrop.BEANS.BurnsStanley_REVISED.xlsx", sheet = "insect_sampling")
sites_2018 <- data.site$site_id[data.site$sampling_year==2018]
insect_sampling$study_id[insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
insect_sampling$study_id[!insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="other flies"] <-"other_flies"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling_2018 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
insect_sampling_2019 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2018, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(insect_sampling_2019, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
setwd(dir_ini)
abundance_aux <- insect_sampling %>% select(study_id,site_id,guild,abundance) %>%
group_by(study_id,site_id,guild) %>% count(wt=abundance) %>%
spread(key=guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(other_wild_bees=0,
syrphids=0,
humbleflies=0,
beetles=0,
non_bee_hymenoptera=0,
lepidoptera=0,
other=0,
total=0)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux$total <- rowSums(abundance_aux[,c(3:ncol(abundance_aux))])
data.site <- data.site %>% left_join(abundance_aux, by = c("study_id","site_id"))
abundace_field <- insect_sampling %>%
select(study_id, site_id,pollinator,abundance)%>%
group_by(study_id,site_id,pollinator) %>% count(wt=abundance)
abundace_field <- abundace_field %>% spread(key=pollinator,value=n)
abundace_field[is.na(abundace_field)] <- 0
abundace_field$r_obser <-  0
abundace_field$r_chao <-  0
for (i in 1:nrow(abundace_field)) {
x <- as.numeric(abundace_field[i,3:(ncol(abundace_field)-2)])
chao  <-  ChaoRichness(x, datatype = "abundance", conf = 0.95)
abundace_field$r_obser[i] <-  chao$Observed
abundace_field$r_chao[i] <-  chao$Estimator
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 1
richness_aux <- abundace_field %>% select(study_id,site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% dplyr::rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1",richness_restriction=NA)
if (percentage_species_morphos < 0.8){
richness_aux[,3:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux,by=c("study_id","site_id"))
##################
# VISITATION RATE AND SAMPLING
##################
insect_sampling$total_sampled_flowers <- as.numeric(insect_sampling$total_sampled_flowers)
sampling <- insect_sampling %>% group_by(study_id,site_id) %>% summarise(flowers=mean(total_sampled_flowers,na.rm = T),
area=mean(total_sampled_area),
time=mean(total_sampled_time))
View(sampling)
data.site <- data.site %>% left_join(sampling,by=c("study_id","site_id"))
field_level_data <- tibble(
study_id = data.site$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$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$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$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
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$area,
total_sampled_time = data.site$time,
visitation_rate_units = "visits per 100 flowers and hour",
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
)
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=NA,
Y_UTM=NA,
zone_UTM=NA,
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_pollen_supplement,
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$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$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$other,
total_sampled_area = data.site$area,
total_sampled_time = data.site$time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$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$email
)
View(data.site)
field_level_data <- tibble(
study_id = data.site$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$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$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$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
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$area,
total_sampled_time = data.site$time,
visitation_rate_units = "visits per 100 flowers and hour",
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$visit_lepidotera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
)
View(field_level_data)
field_level_data_2018 <- field_level_data %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
field_level_data_2019 <- field_level_data %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_2018, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(field_level_data_2019, "field_level_data_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
setwd(dir_ini)
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("globalcrop.BEANS.BurnsStanley_REVISED.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id[data.site$sampling_year==2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
data.site$study_id[data.site$sampling_year==2019] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
data.site$Credit <- "Katherine LW Burns & Dara A Stanley"
data.site$email <- "katherine.burns@ucdconnect.ie"
data.site$Publication <- NA
insect_sampling <- read_excel("globalcrop.BEANS.BurnsStanley_REVISED.xlsx", sheet = "insect_sampling")
sites_2018 <- data.site$site_id[data.site$sampling_year==2018]
insect_sampling$study_id[insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2018"
insect_sampling$study_id[!insect_sampling$site_id %in% sites_2018] <- "Katherine_LW_Burns_Vicia_faba_Ireland_2019"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="other flies"] <-"other_flies"
insect_sampling %>% group_by(guild) %>% count()
insect_sampling_2018 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
insect_sampling_2019 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
insect_sampling
insect_sampling <- insect_sampling %>%
rename(Description=`Description (Fee text)`)
insect_sampling_2018 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2018")
insect_sampling_2019 <- insect_sampling %>% filter(study_id=="Katherine_LW_Burns_Vicia_faba_Ireland_2019")
View(insect_sampling)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2018, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2018.csv")
write_csv(insect_sampling_2019, "insect_sampling_Katherine_LW_Burns_Vicia_faba_Ireland_2019.csv")
setwd(dir_ini)
