rfishbase 
Welcome to rfishbase 4. This is the fourth rewrite of the original
rfishbase package described in Boettiger et
al. (2012).
rfishbase 1.0relied on parsing of XML pages served directly from Fishbase.org.rfishbase 2.0relied on calls to a ruby-based API,fishbaseapi, that provided access to SQL snapshots of about 20 of the more popular tables in FishBase or SeaLifeBase.rfishbase 3.0side-stepped the API by making queries which directly downloaded compressed csv tables from a static web host. This substantially improved performance a reliability, particularly for large queries. The release largely remained backwards compatible with 2.0, and added more tables.rfishbase 4.0extends the static model and interface. Static tables are distributed in parquet and accessed through a provenance-based identifier. While old functions are retained, a new interface is introduced to provide easy access to all fishbase tables.
We welcome any feedback, issues or questions that users may encounter through our issues tracker on GitHub: https://github.com/ropensci/rfishbase/issues
Installation
remotes::install_github("ropensci/rfishbase")library("rfishbase")
library("dplyr") # convenient but not requiredGetting started
Generic table interface
All fishbase tables can be accessed by name using the fb_tbl()
function:
fb_tbl("ecosystem")# A tibble: 155,792 × 18
autoctr E_CODE EcosystemRefno Speccode Stockcode Status CurrentPresence
<int> <int> <int> <int> <int> <chr> <chr>
1 1 1 50628 549 565 native Present
2 2 1 189 552 568 native Present
3 3 1 189 554 570 native Present
4 4 1 79732 873 889 native Present
5 5 1 5217 948 964 native Present
6 7 1 39852 956 972 native Present
7 8 1 39852 957 973 native Present
8 9 1 39852 958 974 native Present
9 10 1 188 1526 1719 native Present
10 11 1 188 1626 1819 native Present
# … with 155,782 more rows, and 11 more variables: Abundance <chr>,
# LifeStage <chr>, Remarks <chr>, Entered <int>, Dateentered <dttm>,
# Modified <int>, Datemodified <dttm>, Expert <int>, Datechecked <dttm>,
# WebURL <chr>, TS <dttm>
You can see all the tables using fb_tables() to see a list of all the
table names (specify sealifebase if desired). Careful, there are a lot
of them! The fishbase databases have grown a lot in the decades, and
were not intended to be used directly by most end-users, so you may have
considerable work to determine what’s what. Keep in mind that many
variables can be estimated in different ways (e.g. trophic level), and
thus may report different values in different tables. Also note that
species is name (or SpecCode) is not always the primary key for a table
– many tables are specific to stocks or even individual samples, and
some tables are reference lists that are not species focused at all, but
meant to be joined to other tables (faoareas, etc). Compare tables
against what you see on fishbase.org, or ask on our issues forum for
advice!
fish <- c("Oreochromis niloticus", "Salmo trutta")
fb_tbl("species") %>%
mutate(sci_name = paste(Genus, Species)) %>%
filter(sci_name %in% fish) %>%
select(sci_name, FBname, Length)# A tibble: 2 × 3
sci_name FBname Length
<chr> <chr> <dbl>
1 Oreochromis niloticus Nile tilapia 60
2 Salmo trutta Sea trout 140
SeaLifeBase
SeaLifeBase.org 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
fb_tbl("species", "sealifebase")# A tibble: 97,220 × 109
SpecCode Genus Species Author SpeciesRefNo FBname FamCode Subfamily GenCode
<int> <chr> <chr> <chr> <int> <chr> <int> <chr> <int>
1 32307 Aapto… americ… (Pilsb… 19 <NA> 815 <NA> 27838
2 32306 Aapto… brinto… Newman… 81749 <NA> 815 <NA> 27838
3 32308 Aapto… callis… (Pilsb… 19 <NA> 815 <NA> 27838
4 32304 Aapto… leptod… Newman… 19 <NA> 815 <NA> 27838
5 32305 Aapto… trider… Newman… 19 <NA> 815 <NA> 27838
6 51720 Aaptos aaptos (Schmi… 19 <NA> 2630 <NA> 9253
7 165941 Aaptos bergma… de Lau… 108813 <NA> 2630 <NA> 9253
8 105687 Aaptos ciliata (Wilso… 3477 <NA> 2630 <NA> 9253
9 139407 Aaptos duchas… (Topse… 85482 <NA> 2630 <NA> 9253
10 130070 Aaptos laxosu… (Solla… 81108 <NA> 2630 <NA> 9253
# … with 97,210 more rows, and 100 more variables: TaxIssue <int>,
# Remark <chr>, PicPreferredName <chr>, PicPreferredNameM <chr>,
# PicPreferredNameF <chr>, PicPreferredNameJ <chr>, Source <chr>,
# AuthorRef <int>, SubGenCode <int>, Fresh <int>, Brack <int>,
# Saltwater <int>, Land <int>, BodyShapeI <chr>, DemersPelag <chr>,
# AnaCat <chr>, MigratRef <int>, DepthRangeShallow <int>,
# DepthRangeDeep <int>, DepthRangeRef <int>, DepthRangeComShallow <int>, …
Versions and importing all tables
By default, tables are downloaded the first time they are used.
rfishbase defaults to download the latest available snapshot; be aware
that the most recent snapshot may be months behind the latest data on
fishbase.org. Check available releases:
available_releases()[1] "21.06" "19.04"
Users can trigger a one-time download of all fishbase tables (or a list
of desired tables) using fb_import(). This will ensure later use of
any function can operate smoothly even when no internet connection is
available. Any table already downloaded will not be re-downloaded.
(Note: fb_import() also returns a remote duckdb database connection to
the tables, for users who prefer to work with the remote data objects.)
conn <- fb_import()Low-memory environments
If you have very limited RAM (e.g. <= 2 GB available) it may be
helpful to use fishbase tables in remote form by setting
collect = FALSE. This allows the tables to remain on disk, while the
user is still able to use almost all dplyr functions (see the dbplyr
vignette). Once the table is appropriately subset, the user will need to
call dplyr::collect() to use generic non-dplyr functions, such as
plotting commmands.
fb_tbl("occurrence", collect = FALSE)# Source: table<occurrence> [?? x 106]
# Database: duckdb_connection
catnum2 OccurrenceRefNo SpecCode Syncode Stockcode GenusCol SpeciesCol
<int> <int> <int> <int> <int> <chr> <chr>
1 34424 36653 227 22902 241 "Megalops" "cyprinoid…
2 95154 45880 NA NA NA "" ""
3 97606 45880 NA NA NA "" ""
4 100025 45880 5520 25676 5809 "Johnius" "belangeri…
5 98993 45880 5676 16650 5969 "Chromis" "retrofasc…
6 99316 45880 454 23112 468 "Drepane" "punctata"
7 99676 45880 5388 145485 5647 "Gymnothorax" "boschi"
8 99843 45880 16813 119925 15264 "Hemiramphus" "balinensi…
9 100607 45880 8288 59635 8601 "Ostracion" "rhinorhyn…
10 101529 45880 NA NA NA "Scomberoides" "toloo-par…
# … with more rows, and 99 more variables: ColName <chr>, PicName <chr>,
# CatNum <chr>, URL <chr>, Station <chr>, Cruise <chr>, Gazetteer <chr>,
# LocalityType <chr>, WaterDepthMin <dbl>, WaterDepthMax <dbl>,
# AltitudeMin <int>, AltitudeMax <int>, LatitudeDeg <int>, LatitudeMin <dbl>,
# NorthSouth <chr>, LatitudeDec <dbl>, LongitudeDeg <int>,
# LongitudeMIn <dbl>, EastWest <chr>, LongitudeDec <dbl>, Accuracy <chr>,
# Salinity <chr>, LatitudeTo <dbl>, LongitudeTo <dbl>, LatitudeDegTo <int>, …
Interactive RStudio pane
RStudio users can also browse all fishbase tables interactively in the
RStudio connection browser by using the function fisbase_pane(). Note
that this function will first download a complete set of the fishbase
tables.
Backwards compatibility
rfishbase 4.0 tries to maintain as much backwards compatibility as
possible with rfishbase 3.0. Because parquet preserves native data
types, some encoded types may differ from earlier versions. As before,
these are not always the native type – e.g. fishbase encodes some
boolean (logical TRUE/FALSE) values as integer (-1, 0) or character
types. Use as.logical() to coerce into the appropriate type in that
case.
Toggling between fishbase and sealifebase servers using an environmental
variable, FISHBASE_API, is now deprecated.
Note that fishbase will store downloaded files by hash in the app
directory, given by db_dir(). The default location can be set by
configuring the desired path in the environmental variable,
FISHBASE_HOME.
Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
