inlabru: mexdolphin – R documentation

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mexdolphin

Pan-tropical spotted dolphins in the Gulf of Mexico

Description

This a version of the mexdolphins dataset from the package dsm, reformatted as point process data for use with inlabru. The data are from a combination of several NOAA shipboard surveys conducted on pan-tropical spotted dolphins in the Gulf of Mexico. 47 observations of groups of dolphins wre detected. The group size was recorded, as well as the Beaufort sea state at the time of the observation. Transect width is 16 km, i.e. maximal detection distance 8 km (transect half-width 8 km).

Usage

data(mexdolphin)

Format

A list of objects:

points:: A SpatialPointsDataFrame object containing the locations of detected dolphin groups, with their size as an attribute.
samplers:: A SpatialLinesDataFrame object containing the transect lines that were surveyed.
mesh:: An inla.mesh object containing a Delaunay triangulation mesh (a type of discretization of continuous space) covering the survey region.
ppoly:: An SpatialPolygonsDataFrame object defining the boundary of the survey region.
simulated:: A SpatialPointsDataFrame object containing the locations of a simulated population of dolphin groups. The population was simulated from a 'codeinlabru model fitted to the actual survey data. Note that the simulated data do not have any associated size information.

Source

Library dsm.

References

Halpin, P.N., A.J. Read, E. Fujioka, B.D. Best, B. Donnelly, L.J. Hazen, C. Kot, K. Urian, E. LaBrecque, A. Dimatteo, J. Cleary, C. Good, L.B. Crowder, and K.D. Hyrenbach. 2009. OBIS-SEAMAP: The world data center for marine mammal, sea bird, and sea turtle distributions. Oceanography 22(2):104-115

NOAA Southeast Fisheries Science Center. 1996. Report of a Cetacean Survey of Oceanic and Selected Continental Shelf Waters of the Northern Gulf of Mexico aboard NOAA Ship Oregon II (Cruise 220)

Examples

data(mexdolphin, package = "inlabru")
ggplot() +
  gg(mexdolphin$mesh) +
  gg(mexdolphin$ppoly, color = "blue") +
  gg(mexdolphin$samplers) +
  gg(mexdolphin$points, aes(size = size), color = "red") +
  coord_equal()
  
ggplot() +
  gg(mexdolphin$mesh, col = mexdolphin$lambda, mask = mexdolphin$ppoly) +
  coord_equal()

## Not run: 
if (requireNamespace("ggmap", quietly = TRUE)) {
gmap(mexdolphin$depth) +
  gm(mexdolphin$ppoly, color = "blue") +
  gm(mexdolphin$samplers) +
  gm(mexdolphin$points, aes(size = size), color = "red")

gmap(mexdolphin$depth) +
  gm(mexdolphin$depth, aes(col = depth)) +
  gm(mexdolphin$ppoly)
}

## End(Not run)

inlabru

Bayesian Latent Gaussian Modelling using INLA and Extensions

v2.3.1

GPL (>= 2)

Authors

Finn Lindgren [aut, cre, cph] (<https://orcid.org/0000-0002-5833-2011>, Finn Lindgren continued development of the main code), Fabian E. Bachl [aut, cph] (Fabian Bachl wrote the main code), David L. Borchers [ctb, dtc, cph] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb, cph] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb, dtc, cph] (Lindesay Scott-Howard provided MRSea data import code), Seaton Andy [ctb] (Andy Seaton provided testing and bugfixes)

Initial release