Reference lists and using them

Overview

With reference lists we mean complete and authorative lists of all items or categories that constitute some collection. Their purpose is typically to promote standardization and thereby to ease collaborative work.

The n2khab package provides the following built-in reference lists, relevant to N2KHAB projects 1:

  • types: checklist of types (habitat (sub)types and regionally important biotopes) (documentation links: this website / installed package), represented by their current codes
  • env_pressures: checklist of environmental pressures, represented by codes (documentation links: this website / installed package)

Additionally, namelist provides names and (optionally) shortnames for IDs/codes used in the above lists (documentation links: this website / installed package).

More on list contents and package functionality

Beside enlisting all items, the reference lists provide additional information on them, sometimes in a generic way with variables like ‘attribute_1’, ‘attribute_2’, ‘tag_1’ and so on (explained in the documentation files). This information may be of a defining nature (and obligate), or may just provide useful categories and tags to filter by.

Reading functions of the n2khab package return the reference lists as tibbles, with appropriate text from namelist added. A tibble is a data frame that makes working in the tidyverse a little easier.

Multilanguage support

In the data source on disk, each item envisaged by a reference list is always represented by a code (sometimes a combination of two codes) – not a name. The same approach is often followed for other attributes (use of codes, not names or descriptions). However for some variables English has been used directly in the data source.

The splitting between code and explanatory names, shortnames and other language-dependent text made it possible to store the latter in multiple languages in namelist, in the variables name and shortname. Currently, this list systematically provides English and Dutch text for each code. This can be extended in future versions of the package (not necessarily in a systematic way).

Get the reference lists in R

Making the types reference list available in the R environment is as easy as:

read_types()
#> # A tibble: 110 × 25
#>    type    typelevel main_type type_name type_shortname typeclass typeclass_name
#>    <fct>   <fct>     <fct>     <fct>     <fct>          <fct>     <fct>         
#>  1 1130    main_type 1130      Estuaries Estuaries      CH        Coastal and h…
#>  2 1140    main_type 1140      Mudflats… Mud- and sand… CH        Coastal and h…
#>  3 1310    main_type 1310      Salicorn… Brackish pion… CH        Coastal and h…
#>  4 1310_p… subtype   1310      Salicorn… Salicornia ha… CH        Coastal and h…
#>  5 1310_zk subtype   1310      Low salt… Low saltmarsh… CH        Coastal and h…
#>  6 1310_zv subtype   1310      High sal… High saltmars… CH        Coastal and h…
#>  7 1320    main_type 1320      Spartina… Spartina swar… CH        Coastal and h…
#>  8 1330    main_type 1330      Atlantic… Atlantic salt… CH        Coastal and h…
#>  9 1330_da subtype   1330      Saltmars… Saltmarshes d… CH        Coastal and h…
#> 10 1330_h… subtype   1330      Halophyt… Halophytic gr… CH        Coastal and h…
#> # ℹ 100 more rows
#> # ℹ 18 more variables: hydr_class <fct>, hydr_class_name <fct>,
#> #   hydr_class_shortname <fct>, groundw_dep <fct>, groundw_dep_name <fct>,
#> #   groundw_dep_shortname <fct>, flood_dep <fct>, flood_dep_name <fct>,
#> #   flood_dep_shortname <fct>, tag_1 <chr>, tag_1_name <chr>,
#> #   tag_1_shortname <chr>, tag_2 <chr>, tag_2_name <chr>,
#> #   tag_2_shortname <chr>, tag_3 <chr>, tag_3_name <chr>, …

By default, English is used. But, you can also choose to get a tibble in another language:

read_types(lang = "nl")
#> # A tibble: 110 × 25
#>    type    typelevel main_type type_name type_shortname typeclass typeclass_name
#>    <fct>   <fct>     <fct>     <fct>     <fct>          <fct>     <fct>         
#>  1 1130    main_type 1130      Estuaria  estuaria       CH        Kust- en zilt…
#>  2 1140    main_type 1140      Bij eb d… bij eb droogv… CH        Kust- en zilt…
#>  3 1310    main_type 1310      Eenjarig… zilte pionier… CH        Kust- en zilt…
#>  4 1310_p… subtype   1310      Binnendi… binnendijkse … CH        Kust- en zilt…
#>  5 1310_zk subtype   1310      Buitendi… buitendijks l… CH        Kust- en zilt…
#>  6 1310_zv subtype   1310      Buitendi… buitendijks h… CH        Kust- en zilt…
#>  7 1320    main_type 1320      Schorren… schorren met … CH        Kust- en zilt…
#>  8 1330    main_type 1330      Atlantis… Atlantische s… CH        Kust- en zilt…
#>  9 1330_da subtype   1330      Buitendi… buitendijks s… CH        Kust- en zilt…
#> 10 1330_h… subtype   1330      Binnendi… zilte graslan… CH        Kust- en zilt…
#> # ℹ 100 more rows
#> # ℹ 18 more variables: hydr_class <fct>, hydr_class_name <fct>,
#> #   hydr_class_shortname <fct>, groundw_dep <fct>, groundw_dep_name <fct>,
#> #   groundw_dep_shortname <fct>, flood_dep <fct>, flood_dep_name <fct>,
#> #   flood_dep_shortname <fct>, tag_1 <chr>, tag_1_name <chr>,
#> #   tag_1_shortname <chr>, tag_2 <chr>, tag_2_name <chr>,
#> #   tag_2_shortname <chr>, tag_3 <chr>, tag_3_name <chr>, …

The lang argument is available in the below functions as well.

env_pressures is made available with:

read_env_pressures()
#> # A tibble: 35 × 7
#>    ep_code ep_abbrev        ep_name   ep_class ep_class_name explanation remarks
#>    <fct>   <fct>            <fct>     <fct>    <fct>         <chr>       <chr>  
#>  1 ep_011  011_struct       11 Chang… ep_clas… 1 Physical m… <NA>        <NA>   
#>  2 ep_012  012_soildyn_incr 12 Soil … ep_clas… 1 Physical m… <NA>        <NA>   
#>  3 ep_013  013_soildyn_decr 13 Soil … ep_clas… 1 Physical m… <NA>        <NA>   
#>  4 ep_014  014_aqconn       14 Aquat… ep_clas… 1 Physical m… <NA>        <NA>   
#>  5 ep_015  015_terrconn     15 Terre… ep_clas… 1 Physical m… <NA>        <NA>   
#>  6 ep_03.1 03.1_eutr_air    3.1 Eutr… ep_clas… 3 Eutrophica… <NA>        <NA>   
#>  7 ep_03.2 03.2_eutr_soil   3.2 Eutr… ep_clas… 3 Eutrophica… <NA>        <NA>   
#>  8 ep_03.3 03.3_eutr_gw     3.3 Eutr… ep_clas… 3 Eutrophica… <NA>        <NA>   
#>  9 ep_03.4 03.4_eutr_sw     3.4 Eutr… ep_clas… 3 Eutrophica… <NA>        <NA>   
#> 10 ep_04.1 04.1_acidif_air  4.1 Acid… ep_clas… 4 Acidificat… <NA>        <NA>   
#> # ℹ 25 more rows

When actually using these reading functions, you will – of course – assign its result to an object.


  1. With N2KHAB projects, we mean scientific monitoring programmes and research projects regarding Flemish Natura 2000 habitats and regionally important biotopes (RIBs).↩︎