Welcome to rfishbase 3.0
. This package is the third rewrite of the original rfishbase
package described in Boettiger et al. (2012).
rfishbase
3.0 queries pre-compressed tables from a static server and employs local caching (through memoization) to provide much greater performance and stability, particularly for dealing with large queries involving 10s of thousands of species. The user is never expected to deal with pagination or curl headers and timeouts.
We welcome any feedback, issues or questions that users may encounter through our issues tracker on GitHub: https://github.com/ropensci/rfishbase/issues
FishBase makes it relatively easy to look up a lot of information on most known species of fish. However, looking up a single bit of data, such as the estimated trophic level, for many different species becomes tedious very soon. This is a common reason for using rfishbase
. As such, our first step is to assemble a good list of species we are interested in.
Almost all functions in rfishbase
take a list (character vector) of species scientific names, for example:
You can also read in a list of names from any existing data you are working with. When providing your own species list, you should always begin by validating the names. Taxonomy is a moving target, and this well help align the scientific names you are using with the names used by FishBase, and alert you to any potential issues:
Another typical use case is in wanting to collect information about all species in a particular taxonomic group, such as a Genus, Family or Order. The function species_list
recognizes six taxonomic levels, and can help you generate a list of names of all species in a given group:
[1] "Labroides dimidiatus" "Labroides bicolor"
[3] "Labroides pectoralis" "Labroides phthirophagus"
[5] "Labroides rubrolabiatus"
rfishbase
also recognizes common names. When a common name refers to multiple species, all matching species are returned:
# A tibble: 306 x 4
Species ComName Language SpecCode
<chr> <chr> <chr> <dbl>
1 Salmo obtusirostris Adriatic trout English 6210
2 Schizothorax richardsonii Alawan snowtrout English 8705
3 Schizopyge niger Alghad snowtrout English 24454
4 Salvelinus fontinalis American brook trout English 246
5 Salmo trutta Amu-Darya trout English 238
6 Salmo kottelati Antalya trout English 67602
7 Oncorhynchus apache Apache Trout English 2687
8 Oncorhynchus apache Apache trout English 2687
9 Plectropomus areolatus Apricot trout English 6082
10 Salmo trutta Aral Sea Trout English 238
# … with 296 more rows
Note that there is no need to validate names coming from common_to_sci
or species_list
, as these will always return valid names.
With a species list in place, we are ready to query fishbase for data. Note that if you have a very long list of species, it is always a good idea to try out your intended functions with a subset of that list first to make sure everything is working.
The species()
function returns a table containing much (but not all) of the information found on the summary or homepage for a species on fishbase.org. rfishbase
functions always return tidy data tables: rows are observations (e.g. a species, individual samples from a species) and columns are variables (fields).
# A tibble: 306 x 100
SpecCode Species SpeciesRefNo Author FBname PicPreferredName
<dbl> <chr> <dbl> <chr> <chr> <chr>
1 6210 Salmo … 59043 (Heck… Adria… Saobt_u0.jpg
2 8705 Schizo… 4832 (Gray… Snowt… Scric_u1.jpg
3 24454 Schizo… 4832 (Heck… Algha… <NA>
4 246 Salvel… 86798 (Mitc… Brook… Safon_u4.jpg
5 238 Salmo … 4779 Linna… Sea t… Satru_u2.jpg
6 67602 Salmo … 99540 Turan… Antal… Sakot_m0.jpg
7 2687 Oncorh… 5723 (Mill… Apach… Onapa_u0.jpg
8 2687 Oncorh… 5723 (Mill… Apach… Onapa_u0.jpg
9 6082 Plectr… 5222 (R<fc… Squar… Plare_u4.jpg
10 238 Salmo … 4779 Linna… Sea t… Satru_u2.jpg
# … with 296 more rows, and 94 more variables: PicPreferredNameM <chr>,
# PicPreferredNameF <chr>, PicPreferredNameJ <chr>, FamCode <dbl>,
# Subfamily <chr>, GenCode <dbl>, SubGenCode <dbl>, BodyShapeI <chr>,
# Source <chr>, AuthorRef <lgl>, Remark <chr>, TaxIssue <dbl>,
# Fresh <dbl>, Brack <dbl>, Saltwater <dbl>, DemersPelag <chr>,
# Amphibious <lgl>, AmphibiousRef <lgl>, AnaCat <chr>, MigratRef <dbl>,
# DepthRangeShallow <dbl>, DepthRangeDeep <dbl>, DepthRangeRef <dbl>,
# DepthRangeComShallow <dbl>, DepthRangeComDeep <dbl>,
# DepthComRef <dbl>, LongevityWild <dbl>, LongevityWildRef <dbl>,
# LongevityCaptive <dbl>, LongevityCapRef <dbl>, Vulnerability <dbl>,
# Length <dbl>, LTypeMaxM <chr>, LengthFemale <dbl>, LTypeMaxF <chr>,
# MaxLengthRef <dbl>, CommonLength <dbl>, LTypeComM <chr>,
# CommonLengthF <dbl>, LTypeComF <chr>, CommonLengthRef <dbl>,
# Weight <dbl>, WeightFemale <dbl>, MaxWeightRef <dbl>, Pic <chr>,
# PictureFemale <chr>, LarvaPic <chr>, EggPic <chr>,
# ImportanceRef <dbl>, Importance <chr>, PriceCateg <chr>,
# PriceReliability <chr>, Remarks7 <chr>, LandingStatistics <chr>,
# Landings <chr>, MainCatchingMethod <chr>, II <chr>, MSeines <dbl>,
# MGillnets <dbl>, MCastnets <dbl>, MTraps <dbl>, MSpears <dbl>,
# MTrawls <dbl>, MDredges <dbl>, MLiftnets <dbl>, MHooksLines <dbl>,
# MOther <dbl>, UsedforAquaculture <chr>, LifeCycle <chr>,
# AquacultureRef <dbl>, UsedasBait <chr>, BaitRef <dbl>, Aquarium <chr>,
# AquariumFishII <chr>, AquariumRef <dbl>, GameFish <dbl>,
# GameRef <dbl>, Dangerous <chr>, DangerousRef <dbl>,
# Electrogenic <chr>, ElectroRef <dbl>, Complete <lgl>,
# GoogleImage <dbl>, Comments <chr>, Profile <chr>, PD50 <dbl>,
# Emblematic <dbl>, Entered <dbl>, DateEntered <dttm>, Modified <dbl>,
# DateModified <dttm>, Expert <dbl>, DateChecked <dttm>, TS <lgl>
Most tables contain many fields. To avoid overly cluttering the screen, rfishbase
displays tables as “tibbles” from the dplyr
package. These act just like the familiar data.frames
of base R except that they print to the screen in a more tidy fashion. Note that columns that cannot fit easily in the display are summarized below the table. This gives us an easy way to see what fields are available in a given table.
Most rfishbase
functions will let the user subset these fields by listing them in the fields
argument, for instance:
# A tibble: 306 x 3
Species PriceCateg Vulnerability
<chr> <chr> <dbl>
1 Salmo obtusirostris very high 47.0
2 Schizothorax richardsonii unknown 34.8
3 Schizopyge niger unknown 46.8
4 Salvelinus fontinalis very high 43.4
5 Salmo trutta very high 60.0
6 Salmo kottelati <NA> 33.7
7 Oncorhynchus apache very high 53.8
8 Oncorhynchus apache very high 53.8
9 Plectropomus areolatus very high 30.3
10 Salmo trutta very high 60.0
# … with 296 more rows
Alternatively, just subset the table using the standard column selection in base R ([[
) or dplyr::select
.
Unfortunately identifying what fields come from which tables is often a challenge. Each summary page on fishbase.org includes a list of additional tables with more information about species ecology, diet, occurrences, and many other things. rfishbase
provides functions that correspond to most of these tables.
Because rfishbase
accesses the back end database, it does not always line up with the web display. Frequently rfishbase
functions will return more information than is available on the web versions of the these tables. Some information found on the summary homepage for a species is not available from the species
summary function, but must be extracted from a different table. For instance, the species Resilience
information is not one of the fields in the species
summary table, despite appearing on the species homepage of fishbase.org. To discover which table this information is in, we can use the special rfishbase
function list_fields
, which will list all tables with a field matching the query string:
# A tibble: 1 x 1
table
<chr>
1 stocks
This shows us that this information appears on the stocks
table. We can then request this data from the stocks table:
# A tibble: 408 x 3
Species Resilience StockDefs
<chr> <chr> <chr>
1 Salmo obtusirost… Medium Europe: Adriatic basin in Krka, Jardo, Vr…
2 Schizothorax ric… Medium Asia: Himalayan region of India, Sikkim a…
3 Schizopyge niger Medium Asia: Kashmir Valley in India and Azad Ka…
4 Salvelinus fonti… Medium North America: native to most of eastern …
5 Salmo trutta Medium Europe and Asia: Atlantic, North, White a…
6 Salmo trutta <NA> <i>Salmo trutta aralensis</i>: Asia: end…
7 Salmo trutta Medium <i>Salmo trutta fario</i>: Northeast Atl…
8 Salmo trutta Low "<i>Salmo trutta lacustris</i>\t: Europe:…
9 Salmo trutta <NA> "<i>Salmo trutta oxianus</i>\t: Asia: Am…
10 Salmo trutta <NA> <i>Salmo trutta aralensis</i>: Asia: Ara…
# … with 398 more rows
rfishbase
relies on periodic cache releases. By default rfishbase
will access the latest available release. Note that releases are roughly semi-annual and may not match the live version at Fishbase.org. You can view available releases with:
[1] "19.04" "18.1" "18.07" "17.07"
and you can set the version of FishBase you wish to access by setting the environmental variable:
Note that the same version number applies to both the fishbase
and sealifebase
data.
SeaLifeBase is maintained by the same organization and largely parallels the database structure of Fishbase. As such, almost all rfishbase
functions can instead be instructed to address the
We can begin by getting the taxa table for sealifebase:
(Note: running load_taxa()
at the beginning of any session, for either fishbase or sealifebase is a good way to “warm up” rfishbase by loading in taxonomic data it will need. This information is cached throughout your session and will make all subsequent commands run faster. But no worries if you skip this step, rfishbase
will peform it for you on the first time it is needed, and will cache these results thereafter.)
Let’s look at some Gastropods:
# A tibble: 19,479 x 9
SpecCode Species Genus Subfamily Family Order Class Phylum Kingdom
<dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 57 Salinator… Salin… <NA> Amphib… Pulmo… Gast… Mollu… Animal…
2 58 Tasmaphen… Tasma… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
3 59 Tasmaphen… Tasma… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
4 60 Torresiro… Torre… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
5 61 Victaphan… Victa… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
6 62 Victaphan… Victa… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
7 63 Victaphan… Victa… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
8 64 Victaphan… Victa… <NA> Rhytid… Pulmo… Gast… Mollu… Animal…
9 65 Anoglypta… Anogl… <NA> Caryod… Pulmo… Gast… Mollu… Animal…
10 66 Brazieres… Brazi… <NA> Caryod… Pulmo… Gast… Mollu… Animal…
# … with 19,469 more rows
All other tables can also take an argument to server
:
# A tibble: 121,348 x 108
SpecCode Species Author SpeciesRefNo FBname FamCode Subfamily GenCode
<dbl> <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl>
1 1 Phoron… Wrigh… 1 <NA> 4793 <NA> 12365
2 2 Phoron… Wrigh… 997 <NA> 4793 <NA> 12365
3 3 Phoron… Oka, … 1 horse… 4793 <NA> 12365
4 4 Phoron… Haswe… 1 Phoro… 4793 <NA> 12365
5 5 Phoron… Selys… 997 <NA> 4793 <NA> 12365
6 6 Phoron… Cori,… 1 phoro… 4793 <NA> 12365
7 7 Phoron… (Schn… 1 <NA> 4793 <NA> 12365
8 8 Phoron… Gilch… 1 <NA> 4793 <NA> 12366
9 9 Phoron… Pixel… 1 large… 4793 <NA> 12366
10 10 Phoron… Hilto… 1 Calif… 4793 <NA> 12366
# … with 121,338 more rows, and 100 more variables: TaxIssue <dbl>,
# Remark <chr>, PicPreferredName <chr>, PicPreferredNameM <chr>,
# PicPreferredNameF <chr>, PicPreferredNameJ <chr>, Source <chr>,
# AuthorRef <dbl>, SubGenCode <lgl>, Fresh <dbl>, Brack <dbl>,
# Saltwater <dbl>, Land <dbl>, BodyShapeI <lgl>, DemersPelag <chr>,
# AnaCat <chr>, MigratRef <dbl>, DepthRangeShallow <dbl>,
# DepthRangeDeep <dbl>, DepthRangeRef <dbl>, DepthRangeComShallow <dbl>,
# DepthRangeComDeep <dbl>, DepthComRef <dbl>, LongevityWild <dbl>,
# LongevityWildRef <dbl>, LongevityCaptive <dbl>, LongevityCapRef <dbl>,
# Vulnerability <dbl>, Length <dbl>, LTypeMaxM <chr>,
# LengthFemale <dbl>, LTypeMaxF <chr>, MaxLengthRef <dbl>,
# CommonLength <dbl>, LTypeComM <chr>, CommonLengthF <dbl>,
# LTypeComF <chr>, CommonLengthRef <dbl>, Weight <dbl>,
# WeightFemale <dbl>, MaxWeightRef <dbl>, Pic <lgl>,
# PictureFemale <lgl>, LarvaPic <lgl>, EggPic <lgl>,
# ImportanceRef <dbl>, Importance <chr>, Remarks7 <chr>,
# PriceCateg <chr>, PriceReliability <chr>, LandingStatistics <chr>,
# Landings <chr>, MainCatchingMethod <chr>, II <chr>, MSeines <dbl>,
# MGillnets <dbl>, MCastnets <dbl>, MTraps <dbl>, MSpears <dbl>,
# MTrawls <dbl>, MDredges <dbl>, MLiftnets <dbl>, MHooksLines <dbl>,
# MOther <dbl>, UsedforAquaculture <chr>, LifeCycle <chr>,
# AquacultureRef <dbl>, UsedasBait <chr>, BaitRef <dbl>, Aquarium <chr>,
# AquariumFishII <chr>, AquariumRef <dbl>, GameFish <dbl>,
# GameRef <lgl>, Dangerous <chr>, DangerousRef <dbl>,
# Electrogenic <chr>, ElectroRef <dbl>, Complete <lgl>, ASFA <lgl>,
# GoogleImage <dbl>, Emblematic <dbl>, Entered <dbl>,
# DateEntered <dttm>, Modified <dbl>, DateModified <dttm>, Expert <dbl>,
# DateChecked <dttm>, Synopsis <lgl>, DateSynopsis <lgl>, Flag <lgl>,
# Comments <chr>, VancouverAquarium <dbl>, Profile <lgl>,
# Sp2000_NameCode <chr>, Sp2000_HierarchyCode <chr>,
# Sp2000_AuthorRefNumber <chr>, E_Append <dbl>, E_DateAppend <date>,
# TS <dttm>
CAUTION: if switching between fishbase
and sealifebase
in a single R session, we strongly advise you always set server
explicitly in your function calls. Otherwise you may confuse the caching system.
rfishbase
3.0 tries to maintain as much backwards compatibility as possible with rfishbase 2.0. However, there are cases in which the rfishbase 2.0 behavior was not desirable – such as throwing errors when a introducing simple NA
s for missing data would be more appropriate, or returning vectors where data.frame
s were needed to include all the context.
Argument names have been retained where possible to maximize backwards compatibility. Using previous arguments that are no longer relevant (such as limit
for the maximum number of records) will not now introduce errors, but nor will they have any effect (they are simply consumed by the ...
). There are no longer any limits in return sizes.
You can still specify server using the rfishbase 2.x
format of providing a URL argument for server, e.g. "http://fishbase.ropensci.org/sealifebase"
or Sys.setenv(FISHBASE_API = "http://fishbase.ropensci.org/sealifebase")
, or simply Sys.setenv("FISHBASE_API" = "sealifebase")
if you prefer. Also recall that environmental variables can always be set in an .Renviron
file.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.