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Create spatial dataset of seamount peaks buffered to a specified radius for an area of interest or planning grid

get_seamounts_buffered.Rd

This function gets seamount peak locations within the area of interest or planning grid and adds a specified buffer around each peak.

Usage

get_seamounts_buffered(
  area_polygon = NULL,
  spatial_grid = NULL,
  buffer = NULL,
  name = "seamounts",
  antimeridian = NULL
)

Arguments

area_polygon

an `sf` polygon or multipolygon object of the area of interest (e.g., a country's EEZ)

spatial_grid

a `terra::rast()` or `sf` planning grid with the desired resolution and coordinate reference system generated by `get_grid()`. For a raster, values in the planning grid cells should be 1, while all other values are NA

buffer

numeric; the distance from the seamount peak to include in the output. Distance should be in the same units as the area_polygon or spatial_grid provided, use e.g. `sf::st_crs(spatial_grid, parameters = TRUE)$units_gdal` to check what units your planning grid or area polygon is in (works for raster as well as sf objects)

name

name to give to the raster or sf column

antimeridian

Does `area_polygon` or `spatial_grid` span the antimeridian? If so, this should be set to `TRUE`, otherwise set to `FALSE`. If set to `NULL` (default) the function will try to check if data spans the antimeridian and set this appropriately.

Value

If an `area_polygon` is supplied, an `sf` buffered seamounts object. If a `spatial_grid` is supplied, a raster or `sf` of gridded buffered seamount data, depending on `spatial_grid` format.

Details

Seamounts are classified as peaks at least 1000m higher than the surrounding seafloor [Morato et al. 2008](https://doi.org/10.3354/meps07268). The seamounts peak dataset is from [Yeson et al. 2021](https://doi.org/10.14324/111.444/ucloe.000030). [Morato et al. 2010](https://doi.org/10.1073/pnas.0910290107) find that seamounts have higher biodiversity within 30 - 40 km of the peak.

Examples

# Grab EEZ data first 
bermuda_eez <- get_area(area_name = "Bermuda", mregions_column = "territory1")
#> Cache is fresh. Reading: /tmp/RtmpI4RFAA/eez-2205f12f/eez.shp
#> (Last Modified: 2024-02-13 01:25:10.354267)
# Get buffered seamounts in Bermuda's EEZ - warns that buffering is not correct for long/lat (WGS 84) data. Buffer is in decimal degrees
seamounts_buffered <- get_seamounts_buffered(area_polygon = bermuda_eez, buffer = 0.5)
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersection assumes that they
#> are planar
#> Warning: attribute variables are assumed to be spatially constant throughout all geometries
#> Warning: st_buffer does not correctly buffer longitude/latitude data
#> dist is assumed to be in decimal degrees (arc_degrees).
#> although coordinates are longitude/latitude, st_union assumes that they are
#> planar
#> Spherical geometry (s2) switched on
# Get seamounts buffered to 30 km, in a planning grid
planning_grid <- get_grid(area_polygon = bermuda_eez, projection_crs = '+proj=laea +lon_0=-64.8108333 +lat_0=32.3571917 +datum=WGS84 +units=m +no_defs', resolution = 5000)
seamounts_buffered_gridded <- get_seamounts_buffered(spatial_grid = planning_grid, buffer = 30000)
#> Spherical geometry (s2) switched off
#> although coordinates are longitude/latitude, st_intersection assumes that they
#> are planar
#> Warning: attribute variables are assumed to be spatially constant throughout all geometries
#> Spherical geometry (s2) switched on