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Calculate Biodiversity Indicators, including ES50 (Hurlbert index)

Source: R/analyze.R
calc_indicators.Rd

Calculate the expected number of marine species in a random sample of 50 individuals (records)

Usage

calc_indicators(df, esn = 50)

Arguments

df

data frame with unique species observations containing columns: cell, species, records

esn

expected number of marine species

Value

Data frame with the following extra columns: - n: number of records

  • sp: species richness - shannon: Shannon index - simpson: Simpson index - es: Hurlbert index (n = 50), i.e. expected species from 50 samples ES(50) - hill_1: Hill number exp(shannon) - hill_2: Hill number 1/simpson - hill_inf: Hill number 1/maxp

Details

The expected number of marine species in a random sample of 50 individuals (records) is an indicator on marine biodiversity richness. The ES50 is defined in OBIS as the sum(esi) over all species of the following per species calculation:

  • when `n - ni >= 50 (with n as the total number of records in the cell and ni the total number of records for the ith-species)

    • esi = 1 - exp(lngamma(n-ni+1) + lngamma(n-50+1) - lngamma(n-ni-50+1) - lngamma(n+1))

  • when n >= 50 - esi = 1

  • else - esi = NULL

Warning: ES50 assumes that individuals are randomly distributed, the sample size is sufficiently large, the samples are taxonomically similar, and that all of the samples have been taken in the same manner.