#####################
#INSECT SAMPLING
#####################
insect_sampling_visits_i <- tibble(
study_id = new_study_name,
site_id = data.insect_i$site_id,
pollinator = data.insect_i$Pollinator,
guild = data.insect_i$Guild,
sampling_method = data.insect_i$Sampling.method,
abundance = data.insect_i$Abundance,
total_sampled_area = data.insect_i$Total_sampled_area,
total_sampled_time = data.insect_i$Total_sampled_time,
total_sampled_flowers = data.insect_i$Total_sampled_flowers,
Description = data.insect_i$`Description.(Fee.text)`
)
if (i==1){
insect_sampling_visits <- insect_sampling_visits_i
}else{
insect_sampling_visits <- bind_rows(insect_sampling_visits,insect_sampling_visits_i)
}
###############################################################
# FIELD LEVEL DATA
###############################################################
field_level_data_i <- tibble(
study_id=new_study_name,
site_id=data.site_i_mod$site_id,
crop=data.site_i_mod$crop,
variety=data.site_i_mod$variety,
management=data.site_i_mod$management,
country=data.site_i_mod$country,
latitude=data.site_i_mod$latitude,
longitude=data.site_i_mod$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month=data.site_i_mod$sampling_start_month,
sampling_end_month=data.site_i_mod$sampling_end_month,
sampling_year=data.site_i_mod$sampling_year,
field_size=data.site_i_mod$field.size,
yield=data.site_i_mod$total_yield,
yield_units="kg/ha",
yield2=NA,
yield2_units=NA,
yield_treatments_no_pollinators=NA,
yield_treatments_pollen_supplement=NA,
yield_treatments_no_pollinators2=NA,
yield_treatments_pollen_supplement2=NA,
fruits_per_plant=data.site_i_mod$mean_fruits_per_plant,
fruit_weight=data.site_i_mod$fruit_weight,
plant_density=NA,
seeds_per_fruit=data.site_i_mod$seeds_per_fruit,
seeds_per_plant=data.site_i_mod$seeds_per_plant,
seed_weight=data.site_i_mod$seed_weight,
observed_pollinator_richness=data.site_i_mod$observed_pollinator_richness,
other_pollinator_richness=data.site_i_mod$other_pollinator_richness,
other_richness_estimator_method=data.site_i_mod$other_richness_estimator_method,
richness_restriction="Only bees",
#pollinator_richness=data.site_i_mod$pollinator_richness,
#richness_estimator_method=data.site_i_mod$richness_estimator_method,
abundance=data.site_i_mod$abundance,
ab_honeybee=data.site_i_mod$ab_honeybee,
ab_bombus=data.site_i_mod$ab_bombus,
ab_wildbees=data.site_i_mod$ab_wildbees,
ab_syrphids=data.site_i_mod$ab_syrphids,
ab_humbleflies=NA,
ab_other_flies=NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others=data.site_i_mod$ab_others,
total_sampled_area=data.site_i_mod$total_sampled_area,
total_sampled_time=data.site_i_mod$total_sampled_time,
visitation_rate_units=NA,
visitation_rate=data.site_i_mod$visitation_rate,
visit_honeybee=data.site_i_mod$visit_honeybee,
visit_bombus=data.site_i_mod$visit_bombus,
visit_wildbees=data.site_i_mod$visit_wildbees,
visit_syrphids=data.site_i_mod$visit_syrphids,
visit_humbleflies=NA,
visit_other_flies=NA,
visit_beetles=NA,
visit_lepidoptera=NA,
visit_nonbee_hymenoptera=NA,
visit_others=data.site_i_mod$visit_others,
Publication=data.site_i_mod$Publication,
Credit=data.site_i_mod$Credit,
Email_contact=data.site_i_mod$email
)
if (i==1){
field_level_data <- field_level_data_i
}else{
field_level_data <- bind_rows(field_level_data,field_level_data_i)
}
}
############
# Sanity check
field_level_data$site_id %>% unique()
insect_sampling_visits$site_id %>% unique()
field_level_data$site_id[!field_level_data$site_id %in% insect_sampling_visits$site_id]
insect_sampling_visits$site_id[!insect_sampling_visits$site_id %in% field_level_data$site_id]
View(field_level_data)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_visits,"insect_sampling_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data,"field_level_data_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
View(insect_sampling_visits)
library(tidyverse)
library(openxlsx)
library("iNEXT")
dir_ini <- getwd()
#Load datasets: field_data
data.site <- read.xlsx("Observ_TW_NEW2.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
#Load datasets: insect_sampling
data.insect <- read.xlsx("Observ_TW_NEW2.xlsx",
sheet = "insect_sampling", startRow = 1)
data.insect <- as_tibble(data.insect)
data.insect %>% group_by(Guild) %>% count()
View(data.insect)
#Sanity checks sites:
data.insect %>% group_by(Guild) %>% count()
data.insect$Guild[data.insect$Guild=="honey bees"] <- "honeybees"
data.insect %>% group_by(Sampling.method) %>% count()
data.insect %>% group_by(Guild) %>% count()
#Sampling methods
data.insect %>% group_by(Sampling.method) %>% count()
#Sites
data.insect$site_id[!data.insect$site_id %in% data.site$site_id]
data.site$site_id[!data.site$site_id %in% data.insect$site_id]
data.insect$site_id %>% unique() %>% sort()
#Fixing months' format
months_id <- c("March" = "3", "April" = "4", "May" = "5", "June" = "6", "July" = "7",
"August" = "8")
data.site$sampling_end_month <- unname(months_id[data.site$sampling_end_month])
data.site$sampling_start_month <- unname(months_id[data.site$sampling_start_month])
#sanity check:
data.site$sampling_start_month %>% unique()
data.site$sampling_end_month %>% unique()
data.site$total_sampled_time <- 60*as.numeric(gsub("[^[:digit:]]", "", data.site$total_sampled_time))
data.insect$Total_sampled_time <- 60*as.numeric(gsub("[^[:digit:]]", "", data.insect$Total_sampled_time))
data.site$total_yield
# Add email and credit
data.site$email <- "Nicolas.Vereecken@ulb.be, Timothy.weekers@ulb.be"
data.site$Credit <- "Nicolas J. Vereecken, Timothy Weekers"
# Create a list of studies
studies.data <- data.site %>% group_by(study_id,crop,country,sampling_year) %>% count()
for (i in 1:nrow(studies.data)){
new_study_name <- paste(
"Nicolas_J_Vereecken",str_replace_all(studies.data$crop[i]," ","_"),
studies.data$country[i],studies.data$sampling_year[i],sep = "_")
data.site_i <- data.site %>% filter(study_id==studies.data$study_id[i],
crop==studies.data$crop[i],
country==studies.data$country[i],
sampling_year==studies.data$sampling_year[i])
data.insect_i <- data.insect %>% filter(study_id==studies.data$study_id[i],
site_id %in% data.site_i$site_id)
# Extract abundance
# Not every study contains bombus, honeybees or otherwildbees. We create those guilds
# by adding to data.insect_i three auxiliary rows with 0 abundances and the required guilds
data.insect_i_aux_honey <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="honeybees")
data.insect_i_aux_bombus <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="bumblebees")
data.insect_i_aux_wild <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="other wild bees")
data.insect_i_aux <- bind_rows(data.insect_i,data.insect_i_aux_honey,data.insect_i_aux_bombus,
data.insect_i_aux_wild)
abundance_aux <- data.insect_i_aux %>% group_by(site_id,Guild) %>%
summarise(total_guild=sum(Abundance)) %>% spread(Guild,total_guild)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux <- abundance_aux %>%
mutate(total=bumblebees+honeybees+`other wild bees`) %>%
rename(abundance = total, ab_bombus = bumblebees,
ab_honeybee = honeybees, ab_wildbees = `other wild bees`)
data.site_i_mod <- data.site_i %>% select(-ab_bombus,-ab_honeybee,-ab_wildbees,-abundance)%>%
left_join(abundance_aux, by = "site_id")
# Extract richness
richness_aux <- data.insect_i %>% group_by(site_id,Pollinator) %>%
summarise(total_pollinator=sum(Abundance)) %>% spread(Pollinator,total_pollinator)
richness_aux[is.na(richness_aux)] <- 0
richness_aux$r_obser <-  0
richness_aux$r_chao <-  0
for (j in 1:nrow(richness_aux)) {
x <- as.numeric(richness_aux[j,2:(ncol(richness_aux)-2)])
chao  <-  ChaoRichness(x, datatype = "abundance", conf = 0.95)
richness_aux$r_obser[j] <-  chao$Observed
richness_aux$r_chao[j] <-  chao$Estimator
}
#richness_aux <- richness_aux %>% select(site_id, pollinator_richness=r_chao) %>%
#  mutate(richness_estimator_method="Chao1")
richness_aux <- richness_aux %>% select(site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1")
data.site_i_mod <- data.site_i_mod %>%
select(-pollinator_richness,-richness_estimator_.Method)%>%
left_join(richness_aux, by = "site_id")
#####################
#INSECT SAMPLING
#####################
insect_sampling_visits_i <- tibble(
study_id = new_study_name,
site_id = data.insect_i$site_id,
pollinator = data.insect_i$Pollinator,
guild = data.insect_i$Guild,
sampling_method = data.insect_i$Sampling.method,
abundance = data.insect_i$Abundance,
total_sampled_area = data.insect_i$Total_sampled_area,
total_sampled_time = data.insect_i$Total_sampled_time,
total_sampled_flowers = data.insect_i$Total_sampled_flowers,
Description = data.insect_i$`Description.(Fee.text)`
)
if (i==1){
insect_sampling_visits <- insect_sampling_visits_i
}else{
insect_sampling_visits <- bind_rows(insect_sampling_visits,insect_sampling_visits_i)
}
###############################################################
# FIELD LEVEL DATA
###############################################################
field_level_data_i <- tibble(
study_id=new_study_name,
site_id=data.site_i_mod$site_id,
crop=data.site_i_mod$crop,
variety=data.site_i_mod$variety,
management=data.site_i_mod$management,
country=data.site_i_mod$country,
latitude=data.site_i_mod$latitude,
longitude=data.site_i_mod$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month=data.site_i_mod$sampling_start_month,
sampling_end_month=data.site_i_mod$sampling_end_month,
sampling_year=data.site_i_mod$sampling_year,
field_size=data.site_i_mod$field.size,
yield=data.site_i_mod$total_yield,
yield_units="kg/ha",
yield2=NA,
yield2_units=NA,
yield_treatments_no_pollinators=NA,
yield_treatments_pollen_supplement=NA,
yield_treatments_no_pollinators2=NA,
yield_treatments_pollen_supplement2=NA,
fruits_per_plant=data.site_i_mod$mean_fruits_per_plant,
fruit_weight=data.site_i_mod$fruit_weight,
plant_density=NA,
seeds_per_fruit=data.site_i_mod$seeds_per_fruit,
seeds_per_plant=data.site_i_mod$seeds_per_plant,
seed_weight=data.site_i_mod$seed_weight,
observed_pollinator_richness=data.site_i_mod$observed_pollinator_richness,
other_pollinator_richness=data.site_i_mod$other_pollinator_richness,
other_richness_estimator_method=data.site_i_mod$other_richness_estimator_method,
richness_restriction="Only bees",
#pollinator_richness=data.site_i_mod$pollinator_richness,
#richness_estimator_method=data.site_i_mod$richness_estimator_method,
abundance=data.site_i_mod$abundance,
ab_honeybee=data.site_i_mod$ab_honeybee,
ab_bombus=data.site_i_mod$ab_bombus,
ab_wildbees=data.site_i_mod$ab_wildbees,
ab_syrphids=data.site_i_mod$ab_syrphids,
ab_humbleflies=NA,
ab_other_flies=NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others=data.site_i_mod$ab_others,
total_sampled_area=data.site_i_mod$total_sampled_area,
total_sampled_time=data.site_i_mod$total_sampled_time,
visitation_rate_units=NA,
visitation_rate=data.site_i_mod$visitation_rate,
visit_honeybee=data.site_i_mod$visit_honeybee,
visit_bombus=data.site_i_mod$visit_bombus,
visit_wildbees=data.site_i_mod$visit_wildbees,
visit_syrphids=data.site_i_mod$visit_syrphids,
visit_humbleflies=NA,
visit_other_flies=NA,
visit_beetles=NA,
visit_lepidoptera=NA,
visit_nonbee_hymenoptera=NA,
visit_others=data.site_i_mod$visit_others,
Publication=data.site_i_mod$Publication,
Credit=data.site_i_mod$Credit,
Email_contact=data.site_i_mod$email
)
if (i==1){
field_level_data <- field_level_data_i
}else{
field_level_data <- bind_rows(field_level_data,field_level_data_i)
}
}
View(field_level_data)
# Fix Management
field_level_data$management %>% unique()
############
# Sanity check
field_level_data$site_id %>% unique()
insect_sampling_visits$site_id %>% unique()
field_level_data$site_id[!field_level_data$site_id %in% insect_sampling_visits$site_id]
insect_sampling_visits$site_id[!insect_sampling_visits$site_id %in% field_level_data$site_id]
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_visits,"insect_sampling_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data,"field_level_data_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
View(insect_sampling_visits)
View(field_level_data)
library(tidyverse)
library(openxlsx)
library("iNEXT")
dir_ini <- getwd()
#Load datasets: field_data
data.site <- read.xlsx("Observ_TW_NEW2.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
#Load datasets: insect_sampling
data.insect <- read.xlsx("Observ_TW_NEW2.xlsx",
sheet = "insect_sampling", startRow = 1)
data.insect <- as_tibble(data.insect)
#Sanity checks sites:
# Guilds
data.insect %>% group_by(Guild) %>% count()
data.insect$Guild[data.insect$Guild=="honey bees"] <- "honeybees"
data.insect %>% group_by(Guild) %>% count()
#Sampling methods
data.insect %>% group_by(Sampling.method) %>% count()
#Sites
data.insect$site_id[!data.insect$site_id %in% data.site$site_id]
data.site$site_id[!data.site$site_id %in% data.insect$site_id]
#Fixing months' format
months_id <- c("March" = "3", "April" = "4", "May" = "5", "June" = "6", "July" = "7",
"August" = "8")
data.site$sampling_end_month <- unname(months_id[data.site$sampling_end_month])
data.site$sampling_start_month <- unname(months_id[data.site$sampling_start_month])
#sanity check:
data.site$sampling_start_month %>% unique()
data.site$sampling_end_month %>% unique()
data.site$total_sampled_time <- 60*as.numeric(gsub("[^[:digit:]]", "", data.site$total_sampled_time))
data.insect$Total_sampled_time <- 60*as.numeric(gsub("[^[:digit:]]", "", data.insect$Total_sampled_time))
# Add email and credit
data.site$email <- "Nicolas.Vereecken@ulb.be, Timothy.weekers@ulb.be"
data.site$Credit <- "Nicolas J. Vereecken, Timothy Weekers"
# Create a list of studies
studies.data <- data.site %>% group_by(study_id,crop,country,sampling_year) %>% count()
for (i in 1:nrow(studies.data)){
new_study_name <- paste(
"Nicolas_J_Vereecken",str_replace_all(studies.data$crop[i]," ","_"),
studies.data$country[i],studies.data$sampling_year[i],sep = "_")
data.site_i <- data.site %>% filter(study_id==studies.data$study_id[i],
crop==studies.data$crop[i],
country==studies.data$country[i],
sampling_year==studies.data$sampling_year[i])
data.insect_i <- data.insect %>% filter(study_id==studies.data$study_id[i],
site_id %in% data.site_i$site_id)
# Extract abundance
# Not every study contains bombus, honeybees or otherwildbees. We create those guilds
# by adding to data.insect_i three auxiliary rows with 0 abundances and the required guilds
data.insect_i_aux_honey <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="honeybees")
data.insect_i_aux_bombus <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="bumblebees")
data.insect_i_aux_wild <- data.insect_i[nrow(data.insect_i),] %>%
mutate(Abundance=0,Guild="other wild bees")
data.insect_i_aux <- bind_rows(data.insect_i,data.insect_i_aux_honey,data.insect_i_aux_bombus,
data.insect_i_aux_wild)
abundance_aux <- data.insect_i_aux %>% group_by(site_id,Guild) %>%
summarise(total_guild=sum(Abundance)) %>% spread(Guild,total_guild)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux <- abundance_aux %>%
mutate(total=bumblebees+honeybees+`other wild bees`) %>%
rename(abundance = total, ab_bombus = bumblebees,
ab_honeybee = honeybees, ab_wildbees = `other wild bees`)
data.site_i_mod <- data.site_i %>% select(-ab_bombus,-ab_honeybee,-ab_wildbees,-abundance)%>%
left_join(abundance_aux, by = "site_id")
# Extract richness
richness_aux <- data.insect_i %>% group_by(site_id,Pollinator) %>%
summarise(total_pollinator=sum(Abundance)) %>% spread(Pollinator,total_pollinator)
richness_aux[is.na(richness_aux)] <- 0
richness_aux$r_obser <-  0
richness_aux$r_chao <-  0
for (j in 1:nrow(richness_aux)) {
x <- as.numeric(richness_aux[j,2:(ncol(richness_aux)-2)])
chao  <-  ChaoRichness(x, datatype = "abundance", conf = 0.95)
richness_aux$r_obser[j] <-  chao$Observed
richness_aux$r_chao[j] <-  chao$Estimator
}
#richness_aux <- richness_aux %>% select(site_id, pollinator_richness=r_chao) %>%
#  mutate(richness_estimator_method="Chao1")
richness_aux <- richness_aux %>% select(site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1")
data.site_i_mod <- data.site_i_mod %>%
select(-pollinator_richness,-richness_estimator_.Method)%>%
left_join(richness_aux, by = "site_id")
#####################
#INSECT SAMPLING
#####################
insect_sampling_visits_i <- tibble(
study_id = new_study_name,
site_id = data.insect_i$site_id,
pollinator = data.insect_i$Pollinator,
guild = data.insect_i$Guild,
sampling_method = data.insect_i$Sampling.method,
abundance = data.insect_i$Abundance,
total_sampled_area = data.insect_i$Total_sampled_area,
total_sampled_time = data.insect_i$Total_sampled_time,
total_sampled_flowers = data.insect_i$Total_sampled_flowers,
Description = data.insect_i$`Description.(Fee.text)`
)
if (i==1){
insect_sampling_visits <- insect_sampling_visits_i
}else{
insect_sampling_visits <- bind_rows(insect_sampling_visits,insect_sampling_visits_i)
}
###############################################################
# FIELD LEVEL DATA
###############################################################
field_level_data_i <- tibble(
study_id=new_study_name,
site_id=data.site_i_mod$site_id,
crop=data.site_i_mod$crop,
variety=data.site_i_mod$variety,
management=data.site_i_mod$management,
country=data.site_i_mod$country,
latitude=data.site_i_mod$latitude,
longitude=data.site_i_mod$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month=data.site_i_mod$sampling_start_month,
sampling_end_month=data.site_i_mod$sampling_end_month,
sampling_year=data.site_i_mod$sampling_year,
field_size=data.site_i_mod$field.size,
yield=data.site_i_mod$total_yield,
yield_units="kg/ha",
yield2=NA,
yield2_units=NA,
yield_treatments_no_pollinators=NA,
yield_treatments_pollen_supplement=NA,
yield_treatments_no_pollinators2=NA,
yield_treatments_pollen_supplement2=NA,
fruits_per_plant=data.site_i_mod$mean_fruits_per_plant,
fruit_weight=data.site_i_mod$fruit_weight,
plant_density=NA,
seeds_per_fruit=data.site_i_mod$seeds_per_fruit,
seeds_per_plant=data.site_i_mod$seeds_per_plant,
seed_weight=data.site_i_mod$seed_weight,
observed_pollinator_richness=data.site_i_mod$observed_pollinator_richness,
other_pollinator_richness=data.site_i_mod$other_pollinator_richness,
other_richness_estimator_method=data.site_i_mod$other_richness_estimator_method,
richness_restriction="Only bees",
#pollinator_richness=data.site_i_mod$pollinator_richness,
#richness_estimator_method=data.site_i_mod$richness_estimator_method,
abundance=data.site_i_mod$abundance,
ab_honeybee=data.site_i_mod$ab_honeybee,
ab_bombus=data.site_i_mod$ab_bombus,
ab_wildbees=data.site_i_mod$ab_wildbees,
ab_syrphids=data.site_i_mod$ab_syrphids,
ab_humbleflies=NA,
ab_other_flies=NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others=data.site_i_mod$ab_others,
total_sampled_area=data.site_i_mod$total_sampled_area,
total_sampled_time=data.site_i_mod$total_sampled_time,
visitation_rate_units=NA,
visitation_rate=data.site_i_mod$visitation_rate,
visit_honeybee=data.site_i_mod$visit_honeybee,
visit_bombus=data.site_i_mod$visit_bombus,
visit_wildbees=data.site_i_mod$visit_wildbees,
visit_syrphids=data.site_i_mod$visit_syrphids,
visit_humbleflies=NA,
visit_other_flies=NA,
visit_beetles=NA,
visit_lepidoptera=NA,
visit_nonbee_hymenoptera=NA,
visit_others=data.site_i_mod$visit_others,
Publication=data.site_i_mod$Publication,
Credit=data.site_i_mod$Credit,
Email_contact=data.site_i_mod$email
)
if (i==1){
field_level_data <- field_level_data_i
}else{
field_level_data <- bind_rows(field_level_data,field_level_data_i)
}
}
# Fix Management
field_level_data$management %>% unique()
field_level_data$management[field_level_data$management=="Conventional"] <- "conventional"
field_level_data$management[field_level_data$management=="Organic"] <- "organic"
field_level_data$management[field_level_data$management=="Non-organic"] <- "IPM"
# Fix Management
field_level_data$management %>% unique()
############
# Sanity check
field_level_data$site_id %>% unique()
insect_sampling_visits$site_id %>% unique()
field_level_data$site_id[!field_level_data$site_id %in% insect_sampling_visits$site_id]
insect_sampling_visits$site_id[!insect_sampling_visits$site_id %in% field_level_data$site_id]
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_visits,"insect_sampling_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data,"field_level_data_Nicolas_J_Vereecken_several_crops_several_countries_several_years.csv")
setwd(dir_ini)
