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_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$fruits_per_plant,
fruit_weight= data.site$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$other_pollinator_richness,
richness_restriction = data.site$richness_restriction,
abundance = NA,
ab_honeybee = NA,
ab_bombus = NA,
ab_wildbees = NA,
ab_syrphids = NA,
ab_humbleflies= NA,
ab_other_flies= NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others = NA,
total_sampled_area = NA,
total_sampled_time = NA,
visitation_rate_units = "visits per unit of time",
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_Mark_Otieno_Cajanus_cajan_Kenya_2009.csv")
setwd(dir_ini)
View(field_level_data)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
dir_ini <- getwd()
field_level_data <- read_csv("Nacho-Lucas/datos/field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009_19 July 2020.csv")
View(field_level_data)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data, "field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009.csv")
setwd(dir_ini)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
dir_ini <- getwd()
field_level_data <- read_csv("Nacho-Lucas/datos/field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009_19 July 2020.csv")
View(field_level_data)
field_level_data <- field_level_data[1:12,]
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data, "field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009.csv")
setwd(dir_ini)
View(field_level_data)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_csv("Nacho-Lucas/datos/field_level_data_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
data.site <- as_tibble(data.site)
View(data.site)
field_level_data <- read_csv("Nacho-Lucas/datos/field_level_data_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
field_level_data <- as_tibble(field_level_data)
field_level_data$management <- "conventional"
View(data.site)
View(field_level_data)
mutate(field_level_data, abundance = ab_honeybee + ab_bombus + ab_wildbees)
field_level_data <- mutate(field_level_data, abundance = ab_honeybee + ab_bombus + ab_wildbees)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data, "field_level_data_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
setwd(dir_ini)
View(field_level_data)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read.xlsx("Nacho-Lucas/datos/Jessica_Pumpkin_fruit.xlsx")
data.site <- as_tibble(data.site)
data.site <- data.site %>% rename(site_id=site,yield=fruit.set)
data.site$yield <- data.site$yield
data.site$yield_units <- "Fruit weight per plant"
data.site$study_id <- "Jessica_D_Petersen_Cucurbita_pepo_USA_2011"
data.site$crop <- "Cucurbita pepo"
data.site$variety <- "Gladiator"
data.site$management <- NA
data.site$country <- "USA"
data.site$latitude <- NA
data.site$longitude <- NA
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- NA
data.site$sampling_start_month <- 7
data.site$sampling_end_month <- 8
data.site$sampling_year <- 2011
data.site$field_size <- NA
data.site$yield2 <- NA
data.site$yield2_units <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_pollen_supplement <- NA
data.site$yield_treatments_no_pollinators2 <- NA
data.site$yield_treatments_pollen_supplement2 <- NA
data.site$fruits_per_plant <- data.site$yield
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 <- "10.1111/1365-2664.12287"
data.site$Credit <- "Jessica D. Petersen and Brian A. Nault"
data.site$Email_contact <- "jessica.petersen@cornell.edu"
data_raw_obs <- read_excel("Nacho-Lucas/datos/Jessica_Pumpkin_abundance.xls",
sheet = "Hoja5") %>%
rename(abundance=visits,site_id=site,Organism_ID=species) %>% filter(abundance>0)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms <- 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()
#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 = "Jessica_D_Petersen_Cucurbita_pepo_USA_2011",
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 = 3*3*2*44,
total_sampled_time = 3*3*10,
total_sampled_flowers = NA,
Description = "Abundance information refers to average flower visits (frequency). The number of bees visiting pumpkin flowers in each field was counted three times. In each round, three 88 m-long transects. Each transect was surveyed for 10 min. The total number of visits was divided by the total number of flowers to achieve a visitation frequency for each bee species per sampling round. Visitation frequencies were averaged across the three sampling rounds")
View(insect_sampling)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling, "insect_sampling_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
setwd(dir_ini)
abundace_field <- data_obs_guild %>%
filter(!is.na(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$r_obser[i] <-  sum(x>0)
abundace_field$r_chao[i] <-  NA
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- 1
richness_aux <- abundace_field %>% select(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=NA,richness_restriction="Only 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 %>%
group_by(site_id,Guild) %>% count(wt=abundance) %>%
spread(key=Guild, value=n)
names(flowers_visited)
flowers_visited <- flowers_visited %>% mutate(beetles=0,humbleflies=0,lepidoptera=0,
non_bee_hymenoptera=0,other=0,
other_flies=0,syrphids=0,total=0)
flowers_visited[is.na(flowers_visited)] <- 0
flowers_visited$total <- rowSums(flowers_visited[,c(2:ncol(flowers_visited))])
flowers_visited <- flowers_visited %>%
mutate(
visit_bumblebees=60*100*bumblebees/30,
visit_honeybees=60*100*honeybees/30,
visit_other_wild_bees=60*100*other_wild_bees/30,
visit_lepidoptera=60*100*lepidoptera/30,
visit_beetles=60*100*beetles/30,
visit_other_flies=60*100*other_flies/30,
visit_syrphids=60*100*syrphids/30,
visit_other=60*100*other/30,
visit_humbleflies=60*100*humbleflies/30,
visit_non_bee_hymenoptera=60*100*non_bee_hymenoptera/30,
visit_total=60*100*total/30
) %>%
select(site_id, visit_bumblebees,visit_honeybees,visit_other_wild_bees,visit_lepidoptera,
visit_beetles,visit_other_flies,visit_syrphids,visit_other,visit_humbleflies,
visit_non_bee_hymenoptera,visit_total)
data.site <- data.site %>% left_join(flowers_visited, by = "site_id")
scale(flowers_visited$visit_total) # Z-SCORE DATA IS OK
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$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$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_pollinator_richness,
richness_restriction = data.site$richness_restriction,
abundance = NA,
ab_honeybee = NA,
ab_bombus = NA,
ab_wildbees = NA,
ab_syrphids = NA,
ab_humbleflies= NA,
ab_other_flies= NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others = NA,
total_sampled_area = 3*3*2*44,
total_sampled_time = 3*3*10,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$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$Email_contact
)
field_level_data_rev <- read_csv("Nacho-Lucas/datos/field_level_data_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
field_level_data_rev <- as_tibble(field_level_data_rev)
field_level_data_rev$management <- "conventional"
field_level_data_rev <- mutate(field_level_data_rev, abundance = ab_honeybee + ab_bombus + ab_wildbees)
field_level_data_rev$visitation_rate_units = field_level_data_rev$visitation_rate_units
field_level_data_rev$visitation_rate = field_level_data_rev$visitation_rate
field_level_data_rev$visit_honeybee = field_level_data_rev$visit_honeybee
field_level_data_rev$visit_bombus = field_level_data_rev$visit_bombus
field_level_data_rev$visit_wildbees = field_level_data_rev$visit_wildbees
field_level_data_rev$visit_syrphids = field_level_data_rev$visit_syrphids
field_level_data_rev$visit_humbleflies = field_level_data_rev$visit_humbleflies
field_level_data_rev$visit_other_flies = field_level_data_rev$visit_other_flies
field_level_data_rev$visit_beetles = field_level_data_rev$visit_beetles
field_level_data_rev$visit_lepidoptera = field_level_data_rev$visit_lepidoptera
field_level_data_rev$visit_nonbee_hymenoptera = field_level_data_rev$visit_nonbee_hymenoptera
field_level_data_rev$visit_others = field_level_data_rev$visit_others
View(field_level_data_rev)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_rev, "field_level_data_Jessica_D_Petersen_Cucurbita_pepo_USA_2011.csv")
setwd(dir_ini)
# load libraries
library(tidyverse)
library("iNEXT")
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read.xlsx("Nacho-Lucas/datos/Mark_pigeonpea_fruit.xlsx")
data.site <- as_tibble(data.site)
data.site <- data.site %>% rename(site_id=site,yield=fruit.set)
data.site$yield <- data.site$yield
data.site$yield_units <- "Insect Pollination = Open pollination [control] - Self-pollination [Tulle bags]"
data.site$study_id <- "Mark_Otieno_Cajanus_cajan_Kenya_2009"
data.site$crop <- "Cajanus cajan"
data.site$variety <- NA
data.site$management <- NA
data.site$country <- "Kenya"
data.site$latitude <- NA
data.site$longitude <- NA
data.site$X_UTM <- NA
data.site$Y_UTM <- NA
data.site$zone_UTM <- NA
data.site$sampling_start_month <- 4
data.site$sampling_end_month <- 6
data.site$sampling_year <- 2009
data.site$field_size <- NA
data.site$yield2 <- NA
data.site$yield2_units <- NA
data.site$yield_treatments_no_pollinators <- NA
data.site$yield_treatments_pollen_supplement <- NA
data.site$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 <- "10.1007/s10841-015-9788-z"
data.site$Credit <- "Mark Otieno, C. Sheena Sidhu, Ben A. Woodcock, Andrew Wilby, Ioannis N. Vogiatzakis, Alice L. Mauchline, Mary W. Gikungu, and Simon G. Potts"
data.site$Email_contact <- "mmarkotieno@gmail.com"
data_raw_obs <- read_excel("Nacho-Lucas/datos/Mark_pigeonpea_abundance.xls",
sheet = "Hoja5") %>%
rename(abundance=visits,site_id=site,Organism_ID=species) %>% filter(abundance>0)
gild_list_raw <- read_csv("C:/Users/USUARIO/Desktop/OBservData/Thesaurus_Pollinators/Table_organism_guild_META.csv")
gild_list <- gild_list_raw %>% select(-Family) %>% unique()
list_organisms <- 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$Guild[grepl("Dactylurina",list_organisms_guild$Organism_ID,ignore.case = FALSE)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Euaspis abdominalis",list_organisms_guild$Organism_ID,ignore.case = FALSE)] <- "other_wild_bees"
list_organisms_guild$Guild[grepl("Pachymelus",list_organisms_guild$Organism_ID,ignore.case = FALSE)] <- "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 = "Mark_Otieno_Cajanus_cajan_Kenya_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 = NA,
total_sampled_flowers = NA,
Description = "Abundance information refers to the number of flower visits (frequency). Bees were observed along five 100 m-long 2 m-wide transects at field. Each transect was walked twice a day. Observation time was 10 min per transect."
)
View(insect_sampling)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(insect_sampling, "insect_sampling_Mark_Otieno_Cajanus_cajan_Kenya_2009.csv")
setwd(dir_ini)
abundace_field <- data_obs_guild %>%
filter(!is.na(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$r_obser[i] <-  sum(x>0)
abundace_field$r_chao[i] <-  NA
}
# Load our estimation for taxonomic resolution
percentage_species_morphos <- (222-76)/222
richness_aux <- abundace_field %>% select(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=NA,richness_restriction=NA)
if (percentage_species_morphos < 0.8){
richness_aux[,2:ncol(richness_aux)] <- NA
}
data.site <- data.site %>% left_join(richness_aux,by="site_id")
flowers_visited <- data_obs_guild %>%
group_by(site_id,Guild) %>% count(wt=abundance) %>%
spread(key=Guild, value=n)
names(flowers_visited)
flowers_visited <- flowers_visited %>% mutate(beetles=0,bumblebees=0,
humbleflies=0,lepidoptera=0,non_bee_hymenoptera=0,other=0,
other_flies=0,syrphids=0,total=0)
flowers_visited[is.na(flowers_visited)] <- 0
flowers_visited$total <- rowSums(flowers_visited[,c(2:ncol(flowers_visited))])
flowers_visited <- flowers_visited %>%
mutate(
visit_bumblebees=bumblebees,
visit_honeybees=honeybees,
visit_other_wild_bees=other_wild_bees,
visit_lepidoptera=lepidoptera,
visit_beetles=beetles,
visit_other_flies=other_flies,
visit_syrphids=syrphids,
visit_other=other,
visit_humbleflies=humbleflies,
visit_non_bee_hymenoptera=non_bee_hymenoptera,
visit_total=total
) %>%
select(site_id, visit_bumblebees,visit_honeybees,visit_other_wild_bees,visit_lepidoptera,
visit_beetles,visit_other_flies,visit_syrphids,visit_other,visit_humbleflies,
visit_non_bee_hymenoptera,visit_total)
data.site <- data.site %>% left_join(flowers_visited, by = "site_id")
scale(flowers_visited$visit_total) # Z-SCORE DATA IS OK
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$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$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_pollinator_richness,
richness_restriction = data.site$richness_restriction,
abundance = NA,
ab_honeybee = NA,
ab_bombus = NA,
ab_wildbees = NA,
ab_syrphids = NA,
ab_humbleflies= NA,
ab_other_flies= NA,
ab_beetles=NA,
ab_lepidoptera=NA,
ab_nonbee_hymenoptera=NA,
ab_others = NA,
total_sampled_area = NA,
total_sampled_time = NA,
visitation_rate_units = "visits per unit of time",
visitation_rate = data.site$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$Email_contact
)
field_level_data_rev <- read_csv("Nacho-Lucas/datos/field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009_19 July 2020.csv")
field_level_data_rev[1:12,]
View(field_level_data_rev)
field_level_data_rev <- field_level_data_rev[1:12,]
field_level_data_rev$visitation_rate_units = field_level_data_rev$visitation_rate_units
field_level_data_rev$visitation_rate = field_level_data_rev$visitation_rate
field_level_data_rev$visit_honeybee = field_level_data_rev$visit_honeybee
field_level_data_rev$visit_bombus = field_level_data_rev$visit_bombus
field_level_data_rev$visit_wildbees = field_level_data_rev$visit_wildbees
field_level_data_rev$visit_syrphids = field_level_data_rev$visit_syrphids
field_level_data_rev$visit_humbleflies = field_level_data_rev$visit_humbleflies
field_level_data_rev$visit_other_flies = field_level_data_rev$visit_other_flies
field_level_data_rev$visit_beetles = field_level_data_rev$visit_beetles
field_level_data_rev$visit_lepidoptera = field_level_data_rev$visit_lepidoptera
field_level_data_rev$visit_nonbee_hymenoptera = field_level_data_rev$visit_nonbee_hymenoptera
field_level_data_rev$visit_others = field_level_data_rev$visit_others
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_rev, "field_level_data_Mark_Otieno_Cajanus_cajan_Kenya_2009.csv")
setwd(dir_ini)
