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Plot number of introduced taxa over time for pathways level 2

Source: R/visualize_pathways_year_level2.R
visualize_pathways_year_level2.Rd

Function to plot a line graph with number of taxa introduced over time through different CBD pathways level 2 for a specific CBD pathway level 1. Time expressed in years. Possible breakpoints: taxonomic (kingdoms + vertebrates/invertebrates).

Usage

visualize_pathways_year_level2(
  df,
  chosen_pathway_level1,
  bin = 10,
  from = 1950,
  category = NULL,
  facet_column = NULL,
  pathways = NULL,
  pathway_level1_names = "pathway_level1",
  pathway_level2_names = "pathway_level2",
  taxon_names = "key",
  kingdom_names = "kingdom",
  phylum_names = "phylum",
  first_observed = "first_observed",
  cbd_standard = TRUE,
  title = NULL,
  x_lab = "Time period",
  y_lab = "Number of introduced taxa"
)

Arguments

df

A data frame.

chosen_pathway_level1

character. Selected pathway level 1.

bin

numeric. Time span in years to use for agggregation. Default: 10.

from

numeric. Year trade-off: taxa introduced before this year are grouped all together. Default: 1950.

category

NULL (default) or character. One of the kingdoms as given in GBIF or Chordata (the phylum) or Not Chordata (all other phyla of Animalia):

  1. Plantae

  2. Animalia

  3. Fungi

  4. Chromista

  5. Archaea

  6. Bacteria

  7. Protozoa

  8. Viruses

  9. incertae sedis

  10. Chordata

  11. Not Chordata

facet_column

NULL (default) or character. The column to use to create additional facet wrap bar graphs underneath the main graph. When NULL, no facet graph are created. One of family, order, class, phylum, kingdom, locality, native_range, habitat. If column has another name, rename it before calling this function. Facet phylum is not allowed in combination with category equal to "Chordata" or "Not Chordata". Facet kingdom is allowed only with category equal to NULL.

pathways

character. Vector with pathways level 1 to visualize. The pathways are displayed following the order as in this vector.

pathway_level1_names

character. Name of the column of df containing information about pathways at level 1. Default: "pathway_level1".

pathway_level2_names

character. Name of the column of df containing information about pathways at level 2. Default: "pathway_level2".

taxon_names

character. Name of the column of df containing information about taxa. This parameter is used to uniquely identify taxa.

kingdom_names

character. Name of the column of df containing information about kingdom. Default: "kingdom".

phylum_names

character. Name of the column of df containing information about phylum. This parameter is used only if category is one of: "Chordata", "Not Chordata". Default: "phylum".

first_observed

character. Name of the column of df containing information about year of introduction. Default: "first_observed".

cbd_standard

logical. If TRUE the values of pathway level 1 are checked based on CBD standard as returned by pathways_cbd(). Error is returned if unmatched values are found. If FALSE, a warning is returned. Default: TRUE.

title

NULL or character. Title of the graph. Default: NULL.

x_lab

NULL or character. x-axis label. Default: "Number of introduced taxa".

y_lab

NULL or character. Title of the graph. Default: "Pathways".

Value

A list with three slots:

  • plot: ggplot2 object (or egg object if facets are used). NULL if there are no data to plot.

  • data_top_graph: data.frame (tibble) with data used for the main plot (top graph) in plot.

  • data_facet_graph: data.frame (tibble) with data used for the faceting plot in plot. NULL is returned if facet_column is NULL.

Examples

if (FALSE) { # \dontrun{
library(readr)
datafile <- paste0(
  "https://raw.githubusercontent.com/trias-project/indicators/master/data/",
  "interim/data_input_checklist_indicators.tsv"
)
data <- read_tsv(datafile,
  na = "",
  col_types = cols(
    .default = col_character(),
    key = col_double(),
    nubKey = col_double(),
    speciesKey = col_double(),
    first_observed = col_double(),
    last_observed = col_double()
  )
)
# All taxa
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape"
)

# Animalia
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  category = "Animalia"
)

# Chordata
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  category = "Chordata"
)

# Group by 20 years
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  bin = 20
)

# Group taxa introudced before 1970 alltogether
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  from = 1970
)

# facet locality
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  category = "Not Chordata",
  facet_column = "locality"
)

# facet habitat
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  facet_column = "habitat"
)

# Only taxa with pathways "horticulture" and "pet"
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  pathways = c("horticulture", "pet")
)

# Add a title
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  category = "Plantae",
  from = 1950,
  title = "Plantae - Pathway level 1"
)

# Personalize axis labels
visualize_pathways_year_level2(
  data,
  chosen_pathway_level1 = "escape",
  x_lab = "Jaar",
  y_lab = "Aantal geintroduceerde taxa"
)
} # }