Summary statistics

0012_Summary_stats.qmd

General overview

In this manuscript we will provide the code needed to reproduce summary statistics reported in the Results section of the main text of the study “The hidden biodiversity knowledge split in biological collections”

Here you will find how we obtained the values of

  • Total fish binomial

  • Total fish binomials in countries of the Global South

  • Total fish binomials in countries of the Global North

  • Total name bearers in museums of Global South since 2000

  • Total name bearers in museum of Global North since 2000

  • Name bearers in Global North museums from Global South since 2000

  • Name bearers in Global South museums from Global North since 2000

All these descriptive statistics considered as Global North the countries in East Asia and Pacific, Europe and Central Asia and North America regions. We considered as Global South Latin America and Caribbean, Middle East and North Africa, South Asia and Sub-Saharan Africa.

Packages and data used

Packages

library(dplyr)   # data manipulation
library(tidyr)   # data tidying
library(glue)    # string interpolation
library(here)    # constructing file paths
library(readr)   # reading CSV files

# create period of 50 years
floor_period = function(value){ return(value - value %% 50) }

Data and data preparation

flow_period_region_country <- readr::read_csv(here::here("data", "raw", "flow_period_region_country.csv"))

We first classified, according to the regions defined above, the countries in which the specimen has been collected (region_type) and the country of the museum in which it is housed was classified as Global North and Global South

flow_period_region_country2 <- 
  flow_period_region_country |> 
  mutate(north.south.type = ifelse(region_type == "Latin America & Caribbean" | 
                                     region_type == "Sub-Saharan Africa" |
                                     region_type == "Middle East & North Africa" |
                                     region_type == "South Asia", "Global.South", "Global.North")) |> 
  mutate(north.south.museum = ifelse(region_museum == "Latin America & Caribbean" | 
                                       region_museum == "Sub-Saharan Africa" |
                                       region_museum == "Middle East & North Africa" |
                                       region_museum == "South Asia", "Global.South", "Global.North"))

Total fish binomial

total_fish_binomial <- 
  flow_period_region_country2 |> 
  pull(n) |> 
  sum()

The total fish binomial is 2.0246^{4}

Total fish binomials in museum countries of the Global South

total_fish_binomial_museum_south <- 
  flow_period_region_country2 |> 
  filter(north.south.museum == "Global.South") |> 
  pull(n) |> 
  sum()

Total fish binomials in museum countries of the Global North

total_fish_binomial_museum_north <- 
  flow_period_region_country2 |> 
  filter(north.south.museum == "Global.North") |> 
  pull(n) |> 
  sum()

Total name bearers in museums within Global North and South since 2000

# Total in Global North 
sum_post2000_total_north <- 
  flow_period_region_country2 |> 
  filter(period >= 2000) |> 
  filter(north.south.museum == "Global.North") |> 
  pull(n) |> 
  sum()

# Total in Global South
sum_post2000_total_south <- 
  flow_period_region_country2 |> 
  filter(period >= 2000) |> 
  filter(north.south.museum == "Global.South") |> 
  pull(n) |> 
  sum()

Name bearers in Global North museums from Global South since 2000

Calculating the number of name bearers collected in Global South and housed in Global North since 2000

sum_post2000_south_north <- 
  flow_period_region_country2 |> 
  filter(period >= 2000) |> 
  filter(north.south.type == "Global.South" & north.south.museum == "Global.North") |> 
  pull(n) |> 
  sum()

Name bearers in Global South museums from Global North since 2000

Calculating the number of name bearers collected in Global North countries and housed in Global South museums since 2000

sum_post2000_north_south <- 
  flow_period_region_country2 |> 
  filter(period >= 2000) |> 
  filter(north.south.type == "Global.North" & north.south.museum == "Global.South") |> 
  pull(n) |> 
  sum()

  • Proportion of name bearers from Global South housed in Global North museums since 2000 is of 37.2668289

  • Proportion of name bearers from Global North housed in Global South museums since 2000 is of 0.2196193