library(iNEXT)
dir_ini <- getwd()
options(digits=14)
data.site <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
# Check site_id
data.site %>% group_by(site_id,sampling_year) %>% count() %>% filter(n>1)
data.site$study_id[data.site$sampling_year==2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
data.site$study_id[data.site$sampling_year==2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
data.site$crop <- "Helianthus annuus"
data.site$management <- "conventional"
data.site$latitude <- parse_lat(data.site$latitude)
# when parsing longitude, some NAs appears
which(is.na(parse_lon(data.site$longitude)))
data.site$longitude[which(is.na(parse_lon(data.site$longitude)))]
data.site$longitude[2] <- "-3.56233ºW"
data.site$longitude[15] <- "-3.10787ºW"
data.site$longitude[20] <- "-3.61491ºW"
data.site$longitude[21] <- "-3.56197ºW"
data.site$longitude[26] <- "-4.24806ºW"
data.site$longitude[33] <- "-3.11277ºW"
data.site$longitude <- parse_lon(data.site$longitude)
data.site$yield_units <- "kg/ha"
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
View(insect_sampling)
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
insect_sampling_2018 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2018",
!is.na(abundance), abundance>0) %>% select(-Column1)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2017, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2017.csv")
write_csv(insect_sampling_2018, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2018.csv")
setwd(dir_ini)
library(tidyverse)
library(openxlsx)
library(parzer) #Transforming latitude and longitude
library(stringr)
library(iNEXT)
dir_ini <- getwd()
options(digits=14)
data.site <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
# Check site_id
data.site %>% group_by(site_id,sampling_year) %>% count() %>% filter(n>1)
data.site$study_id[data.site$sampling_year==2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
data.site$study_id[data.site$sampling_year==2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
data.site$crop <- "Helianthus annuus"
data.site$management <- "conventional"
data.site$latitude <- parse_lat(data.site$latitude)
# when parsing longitude, some NAs appears
which(is.na(parse_lon(data.site$longitude)))
data.site$longitude[which(is.na(parse_lon(data.site$longitude)))]
data.site$longitude[2] <- "-3.56233ºW"
data.site$longitude[15] <- "-3.10787ºW"
data.site$longitude[20] <- "-3.61491ºW"
data.site$longitude[21] <- "-3.56197ºW"
data.site$longitude[26] <- "-4.24806ºW"
data.site$longitude[33] <- "-3.11277ºW"
data.site$longitude <- parse_lon(data.site$longitude)
data.site$yield_units <- "kg/ha"
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
insect_sampling_2018 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2018",
!is.na(abundance), abundance>0) %>% select(-Column1)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2017, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2017.csv")
write_csv(insect_sampling_2018, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2018.csv")
setwd(dir_ini)
library(tidyverse)
library(openxlsx)
library(parzer) #Transforming latitude and longitude
library(stringr)
library(iNEXT)
dir_ini <- getwd()
options(digits=14)
data.site <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
# Check site_id
data.site %>% group_by(site_id,sampling_year) %>% count() %>% filter(n>1)
data.site$study_id[data.site$sampling_year==2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
data.site$study_id[data.site$sampling_year==2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
data.site$crop <- "Helianthus annuus"
data.site$management <- "conventional"
data.site$latitude <- parse_lat(data.site$latitude)
# when parsing longitude, some NAs appears
which(is.na(parse_lon(data.site$longitude)))
data.site$longitude[which(is.na(parse_lon(data.site$longitude)))]
data.site$longitude[2] <- "-3.56233ºW"
data.site$longitude[15] <- "-3.10787ºW"
data.site$longitude[20] <- "-3.61491ºW"
data.site$longitude[21] <- "-3.56197ºW"
data.site$longitude[26] <- "-4.24806ºW"
data.site$longitude[33] <- "-3.11277ºW"
data.site$longitude <- parse_lon(data.site$longitude)
data.site$yield_units <- "kg/ha"
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
View(insect_sampling)
insect_sampling_2017 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
View(insect_sampling_2017)
library(tidyverse)
library(openxlsx)
library(parzer) #Transforming latitude and longitude
library(stringr)
library(iNEXT)
dir_ini <- getwd()
options(digits=14)
data.site <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
# Check site_id
data.site %>% group_by(site_id,sampling_year) %>% count() %>% filter(n>1)
data.site$study_id[data.site$sampling_year==2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
data.site$study_id[data.site$sampling_year==2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
data.site$crop <- "Helianthus annuus"
data.site$management <- "conventional"
data.site$latitude <- parse_lat(data.site$latitude)
# when parsing longitude, some NAs appears
which(is.na(parse_lon(data.site$longitude)))
data.site$longitude[which(is.na(parse_lon(data.site$longitude)))]
data.site$longitude[2] <- "-3.56233ºW"
data.site$longitude[15] <- "-3.10787ºW"
data.site$longitude[20] <- "-3.61491ºW"
data.site$longitude[21] <- "-3.56197ºW"
data.site$longitude[26] <- "-4.24806ºW"
data.site$longitude[33] <- "-3.11277ºW"
data.site$longitude <- parse_lon(data.site$longitude)
data.site$yield_units <- "kg/ha"
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
View(insect_sampling)
names(insect_sampling_2017)
new_row <- tibble(
site_id="PRE-NGI2_2017",
pollinator="Apis mellifera",
guild="honeybees",
sampling_method="census",
abundance=4,
total_sampled_area=711,
total_sampled_time=316,
total_sampled_flowers=2526,
Description="census of 1 min, within the field each in areas of aprox. 1.5x1.5m"
)
insect_sampling_2017_aux <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
View(new_row)
insect_sampling_2017 <- bind_rows(insect_sampling_2017_aux,new_row)
insect_sampling_2017_aux$total_sampled_area <- as.numeric(insect_sampling_2017_aux$total_sampled_area)
insect_sampling_2017_aux$total_sampled_flowers <- as.numeric(insect_sampling_2017_aux$total_sampled_flowers)
insect_sampling_2017 <- bind_rows(insect_sampling_2017_aux,new_row)
insect_sampling_2018 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2018",
!is.na(abundance), abundance>0) %>% select(-Column1)
insect_sampling_2018$total_sampled_area <- as.numeric(insect_sampling_2018$total_sampled_area)
insect_sampling_2018$total_sampled_flowers <- as.numeric(insect_sampling_2018$total_sampled_flowers)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2017, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2017.csv")
write_csv(insect_sampling_2018, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2018.csv")
setwd(dir_ini)
abundance_aux <- insect_sampling %>% filter(!is.na(abundance),sampling_method=="census") %>%
select(study_id,site_id,guild,abundance) %>%
group_by(study_id,site_id,guild) %>% count(wt=abundance) %>%
spread(key=guild, value=n)
View(insect_sampling)
insect_sampling <- bind_rows(insect_sampling,new_row)
View(insect_sampling)
insect_sampling$total_sampled_area <- as.numeric(insect_sampling$total_sampled_area)
insect_sampling$total_sampled_flowers <- as.numeric(insect_sampling$total_sampled_flowers)
insect_sampling <- bind_rows(insect_sampling,new_row)
abundance_aux <- insect_sampling %>% filter(!is.na(abundance),sampling_method=="census") %>%
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(humbleflies=0,total=0)
View(abundance_aux)
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017_aux <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
new_row <- tibble(
study_id="Silvia_Castro_Helianthus_annuus_Spain_2017",
site_id="PRE-NGI2_2017",
pollinator="Apis mellifera",
guild="honeybees",
sampling_method="census",
abundance=4,
total_sampled_area=711,
total_sampled_time=316,
total_sampled_flowers=2526,
Description="census of 1 min, within the field each in areas of aprox. 1.5x1.5m"
)
# Add the new column to the total insect sampling data and 2017 data
insect_sampling_2017_aux$total_sampled_area <- as.numeric(insect_sampling_2017_aux$total_sampled_area)
insect_sampling_2017_aux$total_sampled_flowers <- as.numeric(insect_sampling_2017_aux$total_sampled_flowers)
insect_sampling_2017 <- bind_rows(insect_sampling_2017_aux,new_row)
insect_sampling$total_sampled_area <- as.numeric(insect_sampling$total_sampled_area)
insect_sampling$total_sampled_flowers <- as.numeric(insect_sampling$total_sampled_flowers)
insect_sampling <- bind_rows(insect_sampling,new_row)
insect_sampling_2018 <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2018",
!is.na(abundance), abundance>0) %>% select(-Column1)
insect_sampling_2018$total_sampled_area <- as.numeric(insect_sampling_2018$total_sampled_area)
insect_sampling_2018$total_sampled_flowers <- as.numeric(insect_sampling_2018$total_sampled_flowers)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling_2017, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2017.csv")
write_csv(insect_sampling_2018, "insect_sampling_Silvia_Castro_Helianthus_annuus_Spain_2018.csv")
setwd(dir_ini)
abundance_aux <- insect_sampling %>% filter(!is.na(abundance),sampling_method=="census") %>%
select(study_id,site_id,guild,abundance) %>%
group_by(study_id,site_id,guild) %>% count(wt=abundance) %>%
spread(key=guild, value=n)
names(abundance_aux)
abundance_aux <- abundance_aux %>% mutate(humbleflies=0,total=0)
abundance_aux[is.na(abundance_aux)] <- 0
abundance_aux$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 %>% filter(!is.na(abundance),sampling_method=="census") %>%
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 <- 0.5
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"))
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$observed_pollinator_richness.y,
other_pollinator_richness=data.site$other_pollinator_richness.y,
other_richness_estimator_method=data.site$other_richness_estimator_method.y,
richness_restriction = data.site$richness_restriction.y,
abundance = data.site$total,#data.site$abundance,
ab_honeybee = data.site$honeybees,#data.site$ab_honeybee,
ab_bombus = data.site$bumblebees,#data.site$ab_bombus,
ab_wildbees = data.site$other_wild_bees,#data.site$ab_wildbees,
ab_syrphids = data.site$syrphids,#data.site$ab_syrphids,
ab_humbleflies= data.site$humbleflies,#data.site$ab_humbleflies,
ab_other_flies= data.site$other_flies,#data.site$ab_other_flies,
ab_beetles= data.site$beetles,#data.site$ab_beetles,
ab_lepidoptera= data.site$lepidoptera,#data.site$ab_lepidoptera,
ab_nonbee_hymenoptera= data.site$non_bee_hymenoptera,#data.site$ab_nonbee_hymenoptera,
ab_others = data.site$others,#data.site$ab_others,
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$email
)
field_level_data_2017 <- field_level_data %>% filter(sampling_year==2017)
field_level_data_2018 <- field_level_data %>% filter(sampling_year==2018)
View(field_level_data_2017)
View(insect_sampling)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_2017, "field_level_data_Silvia_Castro_Helianthus_annuus_Spain_2017.csv")
write_csv(field_level_data_2018, "field_level_data_Silvia_Castro_Helianthus_annuus_Spain_2018.csv")
setwd(dir_ini)
library(tidyverse)
library(openxlsx)
library(parzer) #Transforming latitude and longitude
library(stringr)
library(iNEXT)
dir_ini <- getwd()
options(digits=14)
data.site <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx",
sheet = "field_level_data", startRow = 1)
data.site <- as_tibble(data.site)
# Check site_id
data.site %>% group_by(site_id,sampling_year) %>% count() %>% filter(n>1)
data.site$study_id[data.site$sampling_year==2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
data.site$study_id[data.site$sampling_year==2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
data.site$crop <- "Helianthus annuus"
data.site$management <- "conventional"
data.site$latitude <- parse_lat(data.site$latitude)
# when parsing longitude, some NAs appears
which(is.na(parse_lon(data.site$longitude)))
data.site$longitude[which(is.na(parse_lon(data.site$longitude)))]
data.site$longitude[2] <- "-3.56233ºW"
data.site$longitude[15] <- "-3.10787ºW"
data.site$longitude[20] <- "-3.61491ºW"
data.site$longitude[21] <- "-3.56197ºW"
data.site$longitude[26] <- "-4.24806ºW"
data.site$longitude[33] <- "-3.11277ºW"
data.site$longitude <- parse_lon(data.site$longitude)
data.site$yield_units <- "kg/ha"
insect_sampling <- read.xlsx("Crop_pollination_database_SUNFLOWER_2020-07-29_corrected.xlsx", sheet = "insect_sampling")
data.site$site_id[!data.site$site_id %in% insect_sampling$site_id]
insect_sampling$site_id[!insect_sampling$site_id %in% data.site$site_id]
field_ID_2017 <- data.site %>% filter(sampling_year==2017) %>% select(site_id) %>% pull()
field_ID_2018 <- data.site %>% filter(sampling_year==2018) %>% select(site_id) %>% pull()
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2017] <- "Silvia_Castro_Helianthus_annuus_Spain_2017"
insect_sampling$study_id[insect_sampling$site_id %in% field_ID_2018] <- "Silvia_Castro_Helianthus_annuus_Spain_2018"
# Sanity check
which(insect_sampling$study_id=="POLLOLE project_Burgos")
insect_sampling %>% group_by(guild) %>% count()
insect_sampling$guild[insect_sampling$guild=="nonbee_hymenoptera"] <- "non_bee_hymenoptera"
insect_sampling$guild[insect_sampling$guild=="wildbees"] <- "other_wild_bees"
insect_sampling$guild[insect_sampling$guild=="bombus"] <- "bumblebees"
insect_sampling$guild[insect_sampling$guild=="honeybee"] <- "honeybees"
insect_sampling$guild[insect_sampling$guild=="Lepidoptera"] <- "lepidoptera"
insect_sampling$guild[insect_sampling$guild=="others "] <- "others"
insect_sampling %>% group_by(guild) %>% count()
# Modify Description
insect_sampling <- insect_sampling %>% rename(Description=`Description_(fee_text)`)
insect_sampling$Description[insect_sampling$sampling_method=="census"] <- insect_sampling$Column1[insect_sampling$sampling_method=="census"]
insect_sampling$total_sampled_area[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling$total_sampled_flowers[insect_sampling$sampling_method=="pan-traps"] <- NA
insect_sampling_2017_aux <- insect_sampling %>%
filter(study_id=="Silvia_Castro_Helianthus_annuus_Spain_2017",
!is.na(abundance), abundance>0) %>% select(-Column1)
new_row <- tibble(
study_id="Silvia_Castro_Helianthus_annuus_Spain_2017",
site_id="PRE-NGI2_2017",
pollinator="Apis mellifera",
guild="honeybees",
sampling_method="census",
abundance=4,
total_sampled_area=711,
total_sampled_time=316,
total_sampled_flowers=2526,
Description="census of 1 min, within the field each in areas of aprox. 1.5x1.5m"
)
# Add the new column to the total insect sampling data and 2017 data
insect_sampling_2017_aux$total_sampled_area <- as.numeric(insect_sampling_2017_aux$total_sampled_area)
insect_sampling_2017_aux$total_sampled_flowers <- as.numeric(insect_sampling_2017_aux$total_sampled_flowers)
insect_sampling_2017 <- bind_rows(insect_sampling_2017_aux,new_row)
insect_sampling$total_sampled_area <- as.numeric(insect_sampling$total_sampled_area)
insect_sampling$total_sampled_flowers <- as.numeric(insect_sampling$total_sampled_flowers)
insect_sampling <- bind_rows(insect_sampling,new_row)
insect_sampling %>% group_by(study_id,site_id,pollinator) %>% count()
insect_sampling %>% group_by(study_id,site_id,pollinator) %>% count() %>%
filter(n>1)
insect_sampling %>% group_by(study_id,site_id,pollinator,guild,sampling_method) %>% count() %>%
filter(n>1)
x <- insect_sampling %>% group_by(study_id,site_id,pollinator,guild,sampling_method) %>% count() %>%
filter(n>1)
View(x)
