neotoma2 (version 1.0.5)

get_sites: get_sites

Description

The get_sites() function is a wrapper for the Neotoma sites API endpoint. The function takes parameters defined by the user and returns a list of site information supplied by the Neotoma Paleoecological Database. The user may define all or none of the possible fields.

Usage

get_sites(x = NA, ...)

Value

The function returns either a single item of class "try-error"

describing the reason for failure (either misdefined parameters or an error from the Neotoma API), or a table of sites, with rows corresponding to the number of individual sites returned by the Neotoma API. Each "site" object contains 6 parameters that can be accessed as well: siteid, sitename, location, altitude, description, limited collection units information.

• loc An sf object that describes site's location.

• description

• collunits limited information on collunits

Arguments

x

Use a single integer or vector of integers representing unique Neotoma site identifiers (siteids) to extract site information.

...

accepted arguments, see details for more information.

Author

Socorro Dominguez

Details

A site object in Neotoma is a physical location at which one or more collection units are located. Each collection unit may have one or more datasets within it, defined by the dataset type. The get_sites() function searches for each site within Neotoma that matches the query parameters, and returns them as a sites object, a list of site objects. The get_sites() command wraps the Neotoma API (api.neotomadb.org) call for sites. The call itself uses a SQL query which accepts any one of the following parameters:

• siteid The unique site ID (integer) in Neotoma. Can be passed as a vector of site IDs.

• sitename The site name, or approximate match using the % wildcard.

• database The constituent database for the record. See get_table("constituentdatabases")

• altmin The minimum altitude range for site elevation (in meters).

• altmax The maximum altitude range for site elevation (in meters).

• datasetid The unique dataset ID (integer) in Neotoma. Can be passed as a vector of dataset IDs.

• datasettype Neotoma contains data for a number of datasettypes. This returns a subset of data types. For a complete list of available datasettypes, run neotoma2::get_table('datasettypes')

• doi The dataset DOI for a dataset contained within a site. Can be passed as a vector of DOIs.

• gpid The geopolitical name or identifier containing a site. Can be passed as a vector of names.

• keywords Keywords for samples within a set of sites. For example "modern" indicates a sample within the record uses the keyword "modern".

• contacts Contact names or IDs associated with a site.

• ageyoung A minimum spanning age for the record, in years before radiocarbon present (1950).

• ageold A maximum spanning age for the record, in years before radiocarbon present (1950).

• ageof An age which must be contained within the range of sample ages for a site.

• taxa The names of taxa which must be present within samples in a record.

• all_data The API only downloads the first 25 records of the query. For the complete records, use all_data=TRUE This call will then return a data object that contains site metadata for one or more sites, along with limited metadata describing the collection units and datasets located at that site.

Examples

# \donttest{
## Find all sites with a min altitude of 12m and a max altitude of 25m
## By default returns only 25 sites (default limit is 25):
sites_12to25 <- get_sites(altmin=12, altmax=25)
## Return all sites, using a minimum altitude of 2500m (returns >500 sites):
sites_2500 <- get_sites(altmin=2500, all_data = TRUE)
## To find all sites that contain the string "Alex%"
alex_sites <- get_sites(sitename="Alex%")
## To find sites in Brazil (again with default 25 records)
brazil <- '{"type": "Polygon",
"coordinates": [[
 [-73.125, -9.102096738726443],
 [-56.953125,-33.137551192346145],
 [-36.5625,-7.710991655433217],
 [-68.203125,13.923403897723347],
 [-73.125,-9.102096738726443]]]}'
brazil_sites <- get_sites(loc = brazil[1])

# Finding all sites with Liliaceae pollen in 1000 year bins:
lilysites <- c()
for (i in seq(0, 10000, by = 1000)) {
  lily <- get_sites(taxa=c("Liliaceae"),
                    ageyoung = i - 500,
                    ageold = i + 500,
                    all_data = TRUE)
  lilysites <- c(lilysites, length(lily))
}
plot(x = seq(0, 10000, by = 1000), y = lilysites, type = 'b')
# }