Get a list of species by country from IUCN

How many species are in each country according to IUCN Red List?

Florencia Grattarola

Last updated on 21 February 2024 4 min read

Today, my goal is to get a list of species per country according to the ICUN Red List. I could use the rredlist R package. There is a function that sounds helpful: rl_sp_country(). But just to test my API query techniques, I will use the IUCN API to find it out. Note: the rredlist package, does exactly the same, an API query.

You can check my other posts playing around with the iNaturalist API: First steps with the iNaturalist API and Using the iNaturalist API to detect novel records.

Let’s go!

The use of the IUCN API is strictly under the Terms of Use of the IUCN Red List of Threatened Species.

library(knitr)
library(countrycode)
library(rredlist)
library(httr)
library(jsonlite)
library(tidyverse)

We will use data from Latin America and the package countrycode to get the ISO2 code for each country.

LatinAmerica <- tibble(country= c('Mexico', 'Brazil', 'Costa Rica', 'Colombia', 'Peru', 'Argentina', 'Ecuador', 'Panama', 'Chile', 'Venezuela', 'Belize', 'Honduras', 'Bolivia', 'Guatemala', 'Cuba', 'Nicaragua', 'Paraguay', 'Bahamas', 'Jamaica', 'Trinidad and Tobago', 'Guyana', 'Dominican Republic', 'El Salvador', 'Suriname', 'Uruguay', 'Haiti')) %>%
  mutate(iso=countrycode(country, 'country.name', 'iso2c'))

LatinAmerica %>% kable()

country	iso
Mexico	MX
Brazil	BR
Costa Rica	CR
Colombia	CO
Peru	PE
Argentina	AR
Ecuador	EC
Panama	PA
Chile	CL
Venezuela	VE
Belize	BZ
Honduras	HN
Bolivia	BO
Guatemala	GT
Cuba	CU
Nicaragua	NI
Paraguay	PY
Bahamas	BS
Jamaica	JM
Trinidad and Tobago	TT
Guyana	GY
Dominican Republic	DO
El Salvador	SV
Suriname	SR
Uruguay	UY
Haiti	HT

Now, let’s build a function to get the list of species per country.

The function gets a list of countries iso codes and a IUCN token, and returns a tibble with the scientific name and taxon id of the species, the IUCN category and the country iso. We will use the packages httr and jsonlite to process the JSON call. To check that is doing what we want, the function will print on screen the process, with the result number and the queried country.

getSpeciesByCountriesIUCN <- function(country_iso, token) {

  speciesByCountries <- tibble(scientific_name = character(),
                               taxon_id = numeric(),
                               category = character(),
                               country = character())

  num_results = 0 # used to put the API to sleep and print on the console the num

  for(country_iso_i in country_iso) {  

    if ((num_results %% 10) + 10 == 10) {
      Sys.sleep(0) # every 10 calls, the code can stop for x seconds
    }

    call_url <- str_glue('https://apiv3.iucnredlist.org/api/v3/country/getspecies/',
                         '{country_iso_i}?token={token}')

    get_json_call <- GET(url = call_url) %>%
      content(as = "text") %>% fromJSON(flatten = TRUE)

    results <- as_tibble(get_json_call$result)

    speciesByCountries_i <- tibble(scientific_name = results$scientific_name,
                                   taxon_id = results$taxonid,
                                   category = results$category,
                                   country = country_iso_i)

    speciesByCountries <- rbind(speciesByCountries, speciesByCountries_i)
    num_results <- num_results + 1
    cat(num_results, ': ', country_iso_i, '\n')
  }
  return(speciesByCountries)
}

So, let’s try it out!

To use it you WILL need a token from IUCN. Here you can find more information on how to get it. https://apiv3.iucnredlist.org/api/v3/token.

token <- '' # paste here the token you get from IUCN

speciesByLatamCountriesIUCN <- getSpeciesByCountriesIUCN(LatinAmerica$iso, token)

head(speciesByLatamCountriesIUCN, n=5) %>%
  kable()

scientific_name	taxon_id	category	country
Abaeis nicippe	173005000	LC	MX
Abarema idiopoda	146784206	LC	MX
Abarema zolleriana	198888990	VU	MX
Abatia mexicana	126620170	VU	MX
Abeillia abeillei	22687170	LC	MX

Finally, let’s do some summaries to find out how many species we have per country, and, for instance, how many are not threatened according to the IUCN categories (LC), (VU), and (NT), and the percentage over the total.

speciesByLatamCountriesIUCN %>%
  mutate(countryName=countrycode(country, 'iso2c', 'country.name')) %>%
  group_by(countryName) %>%
  summarise(species_richness=n_distinct(scientific_name),
            non_threatened=n_distinct(scientific_name[category == 'LC' |
                                                         category == 'VU'|
                                                         category ==  'NT'])) %>%
  ungroup() %>%
  mutate(`%` = scales::label_percent()(round(non_threatened / species_richness, 2))) %>%
  rename(`Country name`=countryName,
         `Number of species`=species_richness,
         `Number of non-threatened species`=non_threatened) %>%
  kable(format.args= list(big.mark = ','))

Country name	Number of species	Number of non-threatened species	%
Argentina	4,587	4,146	90%
Bahamas	2,516	2,299	91%
Belize	3,750	3,522	94%
Bolivia	6,536	6,057	93%
Brazil	18,079	14,910	82%
Chile	2,382	1,976	83%
Colombia	14,570	12,628	87%
Costa Rica	7,455	6,734	90%
Cuba	3,459	3,014	87%
Dominican Republic	2,870	2,562	89%
Ecuador	11,343	9,087	80%
El Salvador	3,061	2,872	94%
Guatemala	5,880	5,194	88%
Guyana	5,211	4,935	95%
Haiti	2,870	2,410	84%
Honduras	5,667	5,154	91%
Jamaica	2,702	2,324	86%
Mexico	12,564	10,002	80%
Nicaragua	5,492	5,150	94%
Panama	7,645	6,822	89%
Paraguay	2,475	2,363	95%
Peru	10,169	8,981	88%
Suriname	4,412	4,220	96%
Trinidad & Tobago	3,075	2,868	93%
Uruguay	1,901	1,742	92%
Venezuela	10,117	8,953	88%

That’s all!

R IUCN API

Get a list of species by country from IUCN

Let’s go!

So, let’s try it out!

That’s all!

Florencia Grattarola

Postdoc Researcher