# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
View(data.site)
data.site <- data.site[1:35,]
View(data.site)
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site <- data.site[1:35,]
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id <- "Amparo_Lázaro_Prunus_dulcis_several_years"
# Fix unknow variety
data.site$variety[data.site$variety=="Unknown"] <- NA
# Rename management
data.site %>% select(management,ab_honeybee)
# Rename management
x <- data.site %>% select(management,ab_honeybee)
View(x)
data.site$management <- NA
data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
data.site$Publication
data.site$Credit
data.site$Publication <- "10.1016/j.agee.2018.05.004; 10.1016/j.agee.2019.02.009"
field_level_data <- tibble(
study_id = data.site$study_id,
site_id = data.site$site_id,
crop = data.site$crop,
variety = data.site$variety,
management = data.site$management,
country = data.site$country,
latitude = data.site$latitude,
longitude = data.site$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$sampling_start_month,
sampling_end_month = data.site$sampling_end_month,
sampling_year = data.site$sampling_year,
field_size = data.site$field_size,
yield=data.site$yield,
yield_units=data.site$yield_units,
yield2=data.site$yield2,
yield2_units=data.site$yield2_units,
yield_treatments_no_pollinators=data.site$yield_treatments_no_pollinators,
yield_treatments_pollen_supplement=data.site$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$seeds_per_fruit,
seeds_per_plant=data.site$seeds_per_plant,
seed_weight=data.site$seed_weight,
observed_pollinator_richness=data.site$observed_pollinator_richness,
other_pollinator_richness=data.site$other_pollinator_richness,
other_richness_estimator_method=data.site$other_richness_estimator_method,
richness_restriction = data.site$richness_restriction,
abundance = data.site$abundance,
ab_honeybee = data.site$ab_honeybee,
ab_bombus = data.site$ab_bombus,
ab_wildbees = data.site$ab_wildbees,
ab_syrphids = data.site$ab_syrphids,
ab_humbleflies= data.site$ab_humbleflies,
ab_other_flies= data.site$ab_other_flies,
ab_beetles=data.site$ab_beetles,
ab_lepidoptera=data.site$ab_lepidoptera,
ab_nonbee_hymenoptera=data.site$ab_nonbee_hymenoptera,
ab_others = data.site$ab_others,
total_sampled_area = data.site$total_sampled_area,
total_sampled_time = data.site$total_sampled_time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$visitation_rate,
visit_honeybee = data.site$visit_honeybee,
visit_bombus = data.site$visit_bombus,
visit_wildbees = data.site$visit_wildbees,
visit_syrphids = data.site$visit_syrphids,
visit_humbleflies = data.site$visit_humbleflies,
visit_other_flies = data.site$visit_other_flies,
visit_beetles = data.site$visit_beetles,
visit_lepidoptera = data.site$visit_lepidoptera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$Email_contact
)
field_level_data <- tibble(
study_id = data.site$study_id,
site_id = data.site$site_id,
crop = data.site$crop,
variety = data.site$variety,
management = data.site$management,
country = data.site$country,
latitude = data.site$latitude,
longitude = data.site$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$sampling_start_month,
sampling_end_month = data.site$sampling_end_month,
sampling_year = data.site$sampling_year,
field_size = data.site$field_size,
yield=data.site$yield,
yield_units=data.site$yield_units,
yield2=data.site$yield2,
yield2_units=data.site$yield2_units,
yield_treatments_no_pollinators=data.site$yield_treatments_no_pollinators,
yield_treatments_pollen_supplement=data.site$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$seeds_per_fruit,
seeds_per_plant=data.site$seeds_per_plant,
seed_weight=data.site$seed_weight,
observed_pollinator_richness=data.site$observed_pollinator_richness,
other_pollinator_richness=data.site$other_pollinator_richness,
other_richness_estimator_method=data.site$other_richness_estimator_method,
richness_restriction = data.site$richness_restriction,
abundance = data.site$abundance,
ab_honeybee = data.site$ab_honeybee,
ab_bombus = data.site$ab_bombus,
ab_wildbees = data.site$ab_wildbees,
ab_syrphids = data.site$ab_syrphids,
ab_humbleflies= data.site$ab_humbleflies,
ab_other_flies= data.site$ab_other_flies,
ab_beetles=data.site$ab_beetles,
ab_lepidoptera=data.site$ab_lepidoptera,
ab_nonbee_hymenoptera=data.site$ab_nonbee_hymenoptera,
ab_others = data.site$ab_others,
total_sampled_area = data.site$total_sampled_area,
total_sampled_time = data.site$total_sampled_time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$visitation_rate,
visit_honeybee = data.site$visit_honeybee,
visit_bombus = data.site$visit_bombus,
visit_wildbees = data.site$visit_wildbees,
visit_syrphids = data.site$visit_syrphids,
visit_humbleflies = data.site$visit_humbleflies,
visit_other_flies = data.site$visit_other_flies,
visit_beetles = data.site$visit_beetles,
visit_lepidoptera = data.site$visit_lepidoptera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
)
View(field_level_data)
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site <- data.site[1:35,]
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id <- "Amparo_Lázaro_Prunus_dulcis_several_years"
# Fix unknow variety
data.site$variety[data.site$variety=="Unknown"] <- NA
# Rename management
x <- data.site %>% select(site_id,management,ab_honeybee)
x
# Rename management
x <- data.site %>% select(site_id,sampling_year,management,ab_honeybee)
x
View(x)
View(field_level_data)
data.site$Credit
field_level_data_2015 <- field_level_data %>% filter(sampling_year==2015)
field_level_data_2016 <- field_level_data %>% filter(sampling_year==2016)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
View(field_level_data_2015)
View(field_level_data_2016)
write_csv(field_level_data_2015, "field_level_data_Amparo_Lázaro_Prunus_dulcis_2015.csv")
write_csv(field_level_data_2016, "field_level_data_Amparo_Lázaro_Prunus_dulcis_2016.csv")
setwd(dir_ini)
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site <- data.site[1:35,]
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id <- "Amparo_Lázaro_Prunus_dulcis_several_years"
# Fix unknow variety
data.site$variety[data.site$variety=="Unknown"] <- NA
# Rename management
x <- data.site %>% select(site_id,sampling_year,management,ab_honeybee,latitude,longitude) %>% filter(is.na(management))
x
# Rename management
x <- data.site %>%
select(site_id,sampling_year,management,ab_honeybee,latitude,longitude) %>%
filter(!is.na(management))
x
write.csv(x,"Amparo_Lázaro_Prunus_dulcis_Honeybee_hives.csv")
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca_EDITED.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
View(data.site)
data.site <- data.site[1:35,]
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id <- "Amparo_Lázaro_Prunus_dulcis_several_years"
# Fix unknow variety
data.site$variety[data.site$variety=="Unknown"] <- NA
# Rename management
x <- data.site %>%
select(site_id,sampling_year,management,ab_honeybee,latitude,longitude) %>%
filter(!is.na(management))
x
write.csv(x,"Amparo_Lázaro_Prunus_dulcis_Honeybee_hives.csv")
data.site$management <- NA
data.site$Publication <- "10.1016/j.agee.2018.05.004; 10.1016/j.agee.2019.02.009"
data.site$richness_restriction
field_level_data <- tibble(
study_id = data.site$study_id,
site_id = data.site$site_id,
crop = data.site$crop,
variety = data.site$variety,
management = data.site$management,
country = data.site$country,
latitude = data.site$latitude,
longitude = data.site$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$sampling_start_month,
sampling_end_month = data.site$sampling_end_month,
sampling_year = data.site$sampling_year,
field_size = data.site$field_size,
yield=data.site$yield,
yield_units=data.site$yield_units,
yield2=data.site$yield2,
yield2_units=data.site$yield2_units,
yield_treatments_no_pollinators=data.site$yield_treatments_no_pollinators,
yield_treatments_pollen_supplement=data.site$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$seeds_per_fruit,
seeds_per_plant=data.site$seeds_per_plant,
seed_weight=data.site$seed_weight,
observed_pollinator_richness=data.site$observed_pollinator_richness,
other_pollinator_richness=data.site$other_pollinator_richness,
other_richness_estimator_method=data.site$other_richness_estimator_method,
richness_restriction = data.site$richness_restriction,
abundance = data.site$abundance,
ab_honeybee = data.site$ab_honeybee,
ab_bombus = data.site$ab_bombus,
ab_wildbees = data.site$ab_wildbees,
ab_syrphids = data.site$ab_syrphids,
ab_humbleflies= data.site$ab_humbleflies,
ab_other_flies= data.site$ab_other_flies,
ab_beetles=data.site$ab_beetles,
ab_lepidoptera=data.site$ab_lepidoptera,
ab_nonbee_hymenoptera=data.site$ab_nonbee_hymenoptera,
ab_others = data.site$ab_others,
total_sampled_area = data.site$total_sampled_area,
total_sampled_time = data.site$total_sampled_time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$visitation_rate,
visit_honeybee = data.site$visit_honeybee,
visit_bombus = data.site$visit_bombus,
visit_wildbees = data.site$visit_wildbees,
visit_syrphids = data.site$visit_syrphids,
visit_humbleflies = data.site$visit_humbleflies,
visit_other_flies = data.site$visit_other_flies,
visit_beetles = data.site$visit_beetles,
visit_lepidoptera = data.site$visit_lepidoptera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
)
# New study ID
data.site$study_id <- paste0("Amparo_Lázaro_Prunus_dulcis_several_",data.site$sampling_year)
# New study ID
data.site$study_id <- paste0("Amparo_Lázaro_Prunus_dulcis_Spain_",data.site$sampling_year)
# load libraries
library(tidyverse)
library("iNEXT")
library(parzer)
library(readxl)
library(openxlsx)
dir_ini <- getwd()
data.site <- read_excel("Crop_pollination_database_Almond_Mallorca_EDITED.xlsx", sheet = "field_level_data")
data.site <- as_tibble(data.site)
data.site <- data.site[1:35,]
data.site %>% group_by(site_id,sampling_year) %>% count()
# New study ID
data.site$study_id <- paste0("Amparo_Lázaro_Prunus_dulcis_Spain_",data.site$sampling_year)
# Fix unknow variety
data.site$variety[data.site$variety=="Unknown"] <- NA
# Rename management
x <- data.site %>%
select(site_id,sampling_year,management,ab_honeybee,latitude,longitude) %>%
filter(!is.na(management))
x
write.csv(x,"Amparo_Lázaro_Prunus_dulcis_Honeybee_hives.csv")
data.site$management <- NA
data.site$Publication <- "10.1016/j.agee.2018.05.004; 10.1016/j.agee.2019.02.009"
field_level_data <- tibble(
study_id = data.site$study_id,
site_id = data.site$site_id,
crop = data.site$crop,
variety = data.site$variety,
management = data.site$management,
country = data.site$country,
latitude = data.site$latitude,
longitude = data.site$longitude,
X_UTM=NA,
Y_UTM=NA,
zone_UTM=NA,
sampling_start_month = data.site$sampling_start_month,
sampling_end_month = data.site$sampling_end_month,
sampling_year = data.site$sampling_year,
field_size = data.site$field_size,
yield=data.site$yield,
yield_units=data.site$yield_units,
yield2=data.site$yield2,
yield2_units=data.site$yield2_units,
yield_treatments_no_pollinators=data.site$yield_treatments_no_pollinators,
yield_treatments_pollen_supplement=data.site$yield_treatments_pollen_supplement,
yield_treatments_no_pollinators2=data.site$yield_treatments_no_pollinators2,
yield_treatments_pollen_supplement2=data.site$yield_treatments_pollen_supplement2,
fruits_per_plant=data.site$mean_fruits_per_plant,
fruit_weight= data.site$fruit_weight,
plant_density=data.site$plant_density,
seeds_per_fruit=data.site$seeds_per_fruit,
seeds_per_plant=data.site$seeds_per_plant,
seed_weight=data.site$seed_weight,
observed_pollinator_richness=data.site$observed_pollinator_richness,
other_pollinator_richness=data.site$other_pollinator_richness,
other_richness_estimator_method=data.site$other_richness_estimator_method,
richness_restriction = data.site$richness_restriction,
abundance = data.site$abundance,
ab_honeybee = data.site$ab_honeybee,
ab_bombus = data.site$ab_bombus,
ab_wildbees = data.site$ab_wildbees,
ab_syrphids = data.site$ab_syrphids,
ab_humbleflies= data.site$ab_humbleflies,
ab_other_flies= data.site$ab_other_flies,
ab_beetles=data.site$ab_beetles,
ab_lepidoptera=data.site$ab_lepidoptera,
ab_nonbee_hymenoptera=data.site$ab_nonbee_hymenoptera,
ab_others = data.site$ab_others,
total_sampled_area = data.site$total_sampled_area,
total_sampled_time = data.site$total_sampled_time,
visitation_rate_units = "visits per 100 flowers and hour",
visitation_rate = data.site$visitation_rate,
visit_honeybee = data.site$visit_honeybee,
visit_bombus = data.site$visit_bombus,
visit_wildbees = data.site$visit_wildbees,
visit_syrphids = data.site$visit_syrphids,
visit_humbleflies = data.site$visit_humbleflies,
visit_other_flies = data.site$visit_other_flies,
visit_beetles = data.site$visit_beetles,
visit_lepidoptera = data.site$visit_lepidoptera,
visit_nonbee_hymenoptera = data.site$visit_nonbee_hymenoptera,
visit_others = data.site$visit_others,
Publication = data.site$Publication,
Credit = data.site$Credit,
Email_contact = data.site$email
)
field_level_data_2015 <- field_level_data %>% filter(sampling_year==2015)
field_level_data_2016 <- field_level_data %>% filter(sampling_year==2016)
setwd("C:/Users/USUARIO/Desktop/OBservData/Datasets_storage")
write_csv(field_level_data_2015, "field_level_data_Amparo_Lázaro_Prunus_dulcis_Spain_2015.csv")
write_csv(field_level_data_2016, "field_level_data_Amparo_Lázaro_Prunus_dulcis_Spain_2016.csv")
setwd(dir_ini)
