This document describes how to build indicators of Invasive Alien Species based on checklist data. In particular, this document takes into account the number of new introductions of alien species per year in Belgium.
Load libraries:
library(tidyverse) # To do datascience
library(magrittr) # To use extract2 function
library(tidylog) # To provide feedback on dplyr functions
library(rlang) # To use Standard Evaluation in dplyr (!!sym())
library(here) # To find files
library(trias) # To use functions developed for TrIAS
library(INBOtheme) # To use INBO theme for graphs
data_file <- here::here(
"data",
"interim",
"data_input_checklist_indicators.tsv"
)
data <- read_tsv(data_file,
na = "",
guess_max = 5000
)
We use function indicator_introduction_year
from
trias
library.
We select data at national level (no regional distributions):
data <-
data %>%
tidylog::filter(locationId == "ISO_3166:BE")
We group data by kingdom:
facet_column <- "kingdom"
We group data by habitat:
facet_column <- "habitat"
In this section we make little changes to the indicator graphs for publication on the Living Planet Index.
We group data by kingdom:
facet_column <- "kingdom"
We don’t take into account Fungi and Chromista due to a lack of comprehensive data on those kingdoms:
facet_column <- "habitat"
We don’t take into account combined habitats
freshwater|terrestrial
and marine|freshwater
due to a lack of comprehensive data on those habitats: