R Notebook

library(ggplot2); library(tidyverse)

Registered S3 method overwritten by 'dplyr':
  method           from
  print.rowwise_df     
-- Attaching packages --------------------------------------- tidyverse 1.2.1 --
v tibble  2.1.3     v purrr   0.3.2
v tidyr   0.8.3     v dplyr   0.8.1
v readr   1.3.1     v stringr 1.4.0
v tibble  2.1.3     v forcats 0.4.0
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

setwd("C:/Users/Admin/Google Drive/CIAT Fellowship/CIAT DATA/CIAT_Analysis")
# Load the dataset

Agro<-read.csv("Agro_Biodiversity.csv",header = T)
# Filter the data with eatable crops and plot area > 20m2. We only selected "Edible" crop and plot area>20 square meters 

Agro<-Agro %>% filter(Eating_Type=="Edible" & Plot_Area_m2>20) %>% select(Area,Family_Code,Plot_Code,Variety,Percent,Species,Plantation_Type,Eating_Type,Classification,Area_Ha,Latitude,Longitude,Altitude)

head(Agro)

NA

# Species Richness 
df<-Agro %>% dplyr::group_by(Family_Code, Species) %>% dplyr::summarise(N.Species=n()) %>% data.frame()

# The number of species in each family or farm

df1<-df %>% dplyr::group_by(Family_Code) %>% dplyr::summarise(N.Species=sum(N.Species)) 

# Calculating species richness

richness <- (df1$N.Species-1)/(log(sum(df1$N.Species)))

DF_Richness<- data.frame(df1,Richness=richness)

head(DF_Richness)

NA

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