Tools for working with Marine Protected Areas to compute species diversity metrics using OBIS data.
remotes::install_github("BigelowLab/mpatools")
We use the wdpar R package
to fetch MPAs by country (or ‘global’ for the complete dataset.) By
default, we store the files you download in the path returned by
rappdirs::user_data_dir("wdpar") in
GeoPackage format. Once you have
downloaded a dataset you can simply read the file from disk using
read_mpa("name"). Below, we use the list_mpa() function to determine
if we already have the Cuba dataset.
library(rappdirs)
library(sf)
library(mpatools)
if ("Cuba" %in% list_mpa()){
mpa <- read_mpa(name = "Cuba")
} else {
mpa <- fetch_mpa(name = 'Cuba')
}
#
plot(sf::st_geometry(mpa))
Once you have MPA polygons in hand, it is easy to request OBIS records
that fall within the polygons. We use the
robis R
package to fetch occurrence data. By default we store files you downlaod
in the path returned by rappdirs::user_data_dir("robis") in
GeoPackage. Once you have downloaded
format you can simply read the file from disk using read_obis().
if ("Cuba" %in% list_obis()){
obis <- read_obis(name = "Cuba", form = "sf")
} else {
obis <- fetch_obis_country(name = 'Cuba')
}
head(obis)## Simple feature collection with 6 features and 164 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -77.45 ymin: 19.867 xmax: -75.37 ymax: 19.96056
## Geodetic CRS: WGS 84
## # A tibble: 6 × 165
## date_year scientificNameID scientificName superfamilyid individualCount
## <int> <chr> <chr> <int> <dbl>
## 1 1963 urn:lsid:marinespeci… Balaenoptera br… 148724 1
## 2 1957 urn:lsid:marinespeci… Parapagurion im… 155727 2
## 3 1930 urn:lsid:marinespeci… Tectarius anton… 14766 1
## 4 1930 urn:lsid:marinespeci… Nodilittorina 14766 2
## 5 1974 urn:lsid:marinespeci… Ziphius caviros… 148723 1
## 6 2018 urn:lsid:marinespeci… Reinhardorhynch… NA NA
## # … with 160 more variables: associatedReferences <chr>, dropped <lgl>,
## # aphiaID <int>, subclassid <int>, type <chr>, taxonRemarks <chr>,
## # phylumid <int>, familyid <int>, catalogNumber <chr>,
## # occurrenceStatus <chr>, basisOfRecord <chr>, terrestrial <lgl>,
## # superclass <chr>, modified <chr>, id <chr>, order <chr>,
## # recordNumber <chr>, georeferencedDate <chr>, superclassid <int>,
## # verbatimEventDate <chr>, infraorderid <int>, dataset_id <chr>, …
We actually find occurrences that fall within the convex hull of a set
of polygons, but you can enforce a stricter policy using the policy
argument for fetch_obis(). See ?fetch_obis.
plot(sf::st_geometry(mpa))
plot(sf::st_geometry(obis), col = 'orange', pch = 16, add = TRUE)
We use rappsdir R package
to manage the stirage location. We store data here
rappdirs::user_data_dir("wdpar") and here
rappdirs::user_data_dir("robis"). This is a very effective way to
store data per user. But if you want to store data at a system-wide
location you can do that using the ubiquitous path argument.