data_raw$visit_wildbees <- (3)*abundance_visits$`native visitation rate`
data_raw$total_sampled_time <- 10*abundance_visits$SAMPLES
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(data_raw, "field_level_data_Taylor_Ricketts_Coffea_arabica_Costa_Rica_2001.csv")
setwd(dir_ini)
library(tidyverse)
library(sp) #Transforming latitude and longitude
library("iNEXT")
library(openxlsx)
library(readxl)
library(parzer) #parse coordinates
dir_ini <- getwd()
data_raw <- read_excel("66_AlexKleinAlmond_2009/Final_almond_flower visits_all bee database_observ_2009_species ID.xls",
sheet = "data")
data_raw <- as_tibble(data_raw)
data_raw$month_of_study <- as.numeric(format(as.Date(data_raw$Date, format="%Y/%m/%d"),"%m"))
# There should be 15 sites
data_raw %>% group_by(Site) %>% count() # OK!
data_raw$`Bloom Variety`[data_raw$Site=="Bramlett"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Full Belly"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Taber"] <- "Monterey + Nonpareil + Peerless"
View(data_raw)
data.site <- data_raw  %>%
select(Site,Lat,Long,`Bloom Variety`) %>%
group_by(Site,Lat,Long,`Bloom Variety`) %>% count() %>% select(-n) %>%
rename(site_id=Site,latitude=Lat,longitude=Long,variety=`Bloom Variety`)
data.site$study_id <- "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009"
data.site$crop <- "Prunus dulcis"
data.site$management <- NA
data.site$country <- "USA"
data.site$sampling_year <- 2009
data.site$field_size <- NA
data.site$yield <- NA
data.site$yield_units <- NA
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.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$plant_density <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
View(data.site)
library(tidyverse)
library(sp) #Transforming latitude and longitude
library("iNEXT")
library(openxlsx)
library(readxl)
library(parzer) #parse coordinates
dir_ini <- getwd()
data_raw <- read_excel("66_AlexKleinAlmond_2009/Final_almond_flower visits_all bee database_observ_2009_species ID.xls",
sheet = "data")
data_raw <- as_tibble(data_raw)
data_raw$month_of_study <- as.numeric(format(as.Date(data_raw$Date, format="%Y/%m/%d"),"%m"))
# There should be 15 sites
data_raw %>% group_by(Site) %>% count() # OK!
data_raw$`Bloom Variety`[data_raw$Site=="Bramlett"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Full Belly"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Taber"] <- "Monterey + Nonpareil + Peerless"
data.site <- data_raw  %>%
select(Site,Lat,Long,`Bloom Variety`) %>%
group_by(Site,Lat,Long,`Bloom Variety`) %>% count() %>% select(-n) %>%
rename(site_id=Site,latitude=Lat,longitude=Long,variety=`Bloom Variety`)
data.site$study_id <- "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009"
data.site$crop <- "Prunus dulcis"
data.site$management <- NA
data.site$country <- "USA"
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- 10
data.site$sampling_year <- 2009
data.site$field_size <- NA
data.site$yield <- NA
data.site$yield_units <- NA
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.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$plant_density <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$Publication <- "10.1111/j.1365-2664.2012.02144.x"
data.site$Credit <- "Claire Kremen and Alexandra-Maria Klein"
data.site$Email_contact <- "alexandra.klein@nature.uni-freiburg.de"
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
data_raw_obs <- data_raw %>%
select(Site,Visitor,Abundance,`Frequency (total # flowers visited)`) %>% rename(site_id=Site,Organism_ID=Visitor,
abundance=Abundance,
flowers_visited=`Frequency (total # flowers visited)`)
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
list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild$Guild[list_organisms_guild$Organism_ID=="Fruit fly"] <- "other_flies"
list_organisms_guild$Guild[is.na(list_organisms_guild$Guild)] <- "other_wild_bees"
#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")
# Remove entries with zero abundance
data_obs_guild  <- data_obs_guild  %>% filter(abundance>0)
insect_sampling <- tibble(
study_id = "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009",
site_id = data_obs_guild$site_id,
pollinator = data_obs_guild$Organism_ID,
guild = data_obs_guild$Guild,
sampling_method = "observation",
abundance = data_obs_guild$abundance,
total_sampled_area = NA,
total_sampled_time = 5*8*20/60, #netting+observations
total_sampled_flowers = NA,
Description = "On each orchard, 5 trees were observed. At each tree, eight groups of flowers were observed for 20 seconds each (total of around 13 min per orchard)."
)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling, "insect_sampling_Alexandra_Maria_Klein_Prunus_dulcis_USA_2009.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 %>%
group_by(site_id,Guild) %>% count(wt=abundance) %>%
spread(key=Guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(lepidoptera=0,beetles=0,
syrphids=0,other=0,humbleflies=0,
non_bee_hymenoptera=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$Estimator
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 0.9
richness_aux <- abundace_field %>% select(site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1",richness_restriction="mostly bees")
if (percentage_species_morphos < 0.8){
richness_aux[,2:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux, by = "site_id")
flowers_visited <- data_obs_guild_2 %>%
group_by(site_id,Guild) %>% count(wt=flowers_visited) %>%
spread(key=Guild, value=n)
names(flowers_visited)
flowers_visited <- flowers_visited %>% mutate(lepidoptera=0,beetles=0,
syrphids=0,other=0,humbleflies=0,
non_bee_hymenoptera=0,
total=0)
flowers_visited[is.na(flowers_visited)] <- 0
flowers_visited$total <- rowSums(flowers_visited[,c(2:ncol(flowers_visited))])
flowers_visited <- flowers_visited %>%
mutate(
visit_bumblebees=60*bumblebees/(40/3),
visit_honeybees=60*honeybees/(40/3),
visit_other_wild_bees=60*other_wild_bees/(40/3),
visit_lepidoptera=60*lepidoptera/(40/3),
visit_beetles=60*beetles/(40/3),
visit_other_flies=60*other_flies/(40/3),
visit_syrphids=60*syrphids/(40/3),
visit_other=60*other/(40/3),
visit_humbleflies=60*humbleflies/(40/3),
visit_non_bee_hymenoptera=60*non_bee_hymenoptera/(40/3),
visit_total=60*total/(40/3)
) %>%
select(site_id, visit_bumblebees,visit_honeybees,visit_other_wild_bees,visit_lepidoptera,
visit_beetles,visit_other_flies,visit_syrphids,visit_other,visit_humbleflies,
visit_non_bee_hymenoptera,visit_total)
data.site <- data.site %>% left_join(flowers_visited, 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,
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 = NA,
total_sampled_time = 40/3,
visitation_rate_units = "visited flowers per hour",
visitation_rate = data.site$visit_total,
visit_honeybee = data.site$visit_honeybees,
visit_bombus = data.site$visit_bumblebees,
visit_wildbees = data.site$visit_other_wild_bees,
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_non_bee_hymenoptera,
visit_others = data.site$visit_other,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$Email_contact
)
data.site$richness_restriction
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data, "field_level_data_Alexandra_Maria_Klein_Prunus_dulcis_USA_2009.csv")
setwd(dir_ini)
View(field_level_data)
library(tidyverse)
library(sp) #Transforming latitude and longitude
library("iNEXT")
library(openxlsx)
library(readxl)
library(parzer) #parse coordinates
dir_ini <- getwd()
data_raw <- read_excel("66_AlexKleinAlmond_2009/Final_almond_flower visits_all bee database_observ_2009_species ID.xls",
sheet = "data")
data_raw <- as_tibble(data_raw)
data_raw$month_of_study <- as.numeric(format(as.Date(data_raw$Date, format="%Y/%m/%d"),"%m"))
# There should be 15 sites
data_raw %>% group_by(Site) %>% count() # OK!
data_raw$`Bloom Variety`[data_raw$Site=="Bramlett"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Full Belly"] <- "Neplus + Nonpareil"
data_raw$`Bloom Variety`[data_raw$Site=="Taber"] <- "Monterey + Nonpareil + Peerless"
data.site <- data_raw  %>%
select(Site,Lat,Long,`Bloom Variety`) %>%
group_by(Site,Lat,Long,`Bloom Variety`) %>% count() %>% select(-n) %>%
rename(site_id=Site,latitude=Lat,longitude=Long,variety=`Bloom Variety`)
data.site$study_id <- "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009"
data.site$crop <- "Prunus dulcis"
data.site$management <- NA
data.site$country <- "USA"
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- 10
data.site$sampling_year <- 2009
data.site$field_size <- NA
data.site$yield <- NA
data.site$yield_units <- NA
data.site$yield2 <- NA
data.site$study_id <- "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009"
data.site$crop <- "Prunus dulcis"
data.site$management <- NA
data.site$country <- "USA"
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- 10
data.site$sampling_year <- 2009
data.site$field_size <- NA
data.site$yield <- NA
data.site$yield_units <- NA
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.site$fruits_per_plant <- NA
data.site$fruit_weight <- NA
data.site$plant_density <- NA
data.site$seeds_per_fruit <- NA
data.site$seeds_per_plant <- NA
data.site$seed_weight <- NA
data.site$Publication <- "10.1038/ncomms8414"
data.site$Credit <- "Alexandra-Maria Klein"
data.site$Email_contact <- "alexandra.klein@nature.uni-freiburg.de"
data.site$sampling_start_month <- NA
data.site$sampling_end_month <- NA
sites <- unique(data.site$site_id)
for (i in sites){
data.site$sampling_start_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% min()
data.site$sampling_end_month[data.site$site_id==i] <-
data_raw %>% filter(Site==i) %>%
select(month_of_study) %>% max()
}
data_raw_obs <- data_raw %>%
select(Site,Visitor,Abundance,`Frequency (total # flowers visited)`) %>% rename(site_id=Site,Organism_ID=Visitor,
abundance=Abundance,
flowers_visited=`Frequency (total # flowers visited)`)
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
list_organisms_guild %>% filter(is.na(Guild)) %>% group_by(Organism_ID) %>% count()
list_organisms_guild$Guild[list_organisms_guild$Organism_ID=="Fruit fly"] <- "other_flies"
list_organisms_guild$Guild[is.na(list_organisms_guild$Guild)] <- "other_wild_bees"
#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")
# Remove entries with zero abundance
data_obs_guild  <- data_obs_guild  %>% filter(abundance>0)
insect_sampling <- tibble(
study_id = "Alexandra_Maria_Klein_Prunus_dulcis_USA_2009",
site_id = data_obs_guild$site_id,
pollinator = data_obs_guild$Organism_ID,
guild = data_obs_guild$Guild,
sampling_method = "observation",
abundance = data_obs_guild$abundance,
total_sampled_area = NA,
total_sampled_time = 5*8*20/60, #netting+observations
total_sampled_flowers = NA,
Description = "On each orchard, 5 trees were observed. At each tree, eight groups of flowers were observed for 20 seconds each (total of around 13 min per orchard)."
)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling, "insect_sampling_Alexandra_Maria_Klein_Prunus_dulcis_USA_2009.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 %>%
group_by(site_id,Guild) %>% count(wt=abundance) %>%
spread(key=Guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(lepidoptera=0,beetles=0,
syrphids=0,other=0,humbleflies=0,
non_bee_hymenoptera=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$Estimator
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 0.9
richness_aux <- abundace_field %>% select(site_id,r_obser,r_chao)
richness_aux <- richness_aux %>% rename(observed_pollinator_richness=r_obser,
other_pollinator_richness=r_chao) %>%
mutate(other_richness_estimator_method="Chao1",richness_restriction="mostly bees")
if (percentage_species_morphos < 0.8){
richness_aux[,2:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux, by = "site_id")
flowers_visited <- data_obs_guild_2 %>%
group_by(site_id,Guild) %>% count(wt=flowers_visited) %>%
spread(key=Guild, value=n)
names(flowers_visited)
flowers_visited <- flowers_visited %>% mutate(lepidoptera=0,beetles=0,
syrphids=0,other=0,humbleflies=0,
non_bee_hymenoptera=0,
total=0)
flowers_visited[is.na(flowers_visited)] <- 0
flowers_visited$total <- rowSums(flowers_visited[,c(2:ncol(flowers_visited))])
flowers_visited <- flowers_visited %>%
mutate(
visit_bumblebees=60*bumblebees/(40/3),
visit_honeybees=60*honeybees/(40/3),
visit_other_wild_bees=60*other_wild_bees/(40/3),
visit_lepidoptera=60*lepidoptera/(40/3),
visit_beetles=60*beetles/(40/3),
visit_other_flies=60*other_flies/(40/3),
visit_syrphids=60*syrphids/(40/3),
visit_other=60*other/(40/3),
visit_humbleflies=60*humbleflies/(40/3),
visit_non_bee_hymenoptera=60*non_bee_hymenoptera/(40/3),
visit_total=60*total/(40/3)
) %>%
select(site_id, visit_bumblebees,visit_honeybees,visit_other_wild_bees,visit_lepidoptera,
visit_beetles,visit_other_flies,visit_syrphids,visit_other,visit_humbleflies,
visit_non_bee_hymenoptera,visit_total)
data.site <- data.site %>% left_join(flowers_visited, 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,
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 = NA,
total_sampled_time = 40/3,
visitation_rate_units = "visited flowers per hour",
visitation_rate = data.site$visit_total,
visit_honeybee = data.site$visit_honeybees,
visit_bombus = data.site$visit_bumblebees,
visit_wildbees = data.site$visit_other_wild_bees,
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_non_bee_hymenoptera,
visit_others = data.site$visit_other,
Publication = data.site$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_Alexandra_Maria_Klein_Prunus_dulcis_USA_2009.csv")
setwd(dir_ini)
