inlabru: gorillas – R documentation

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gorillas

Gorilla nesting sites

Description

This is the gorillas dataset from the package spatstat.data, reformatted as point process data for use with inlabru.

Usage

data(gorillas)

Format

The data are a list that contains these elements:

nests:

A SpatialPointsDataFrame object containing the locations of the gorilla nests.

boundary:

An SpatialPolygonsDataFrame object defining the boundary of the region that was searched for the nests.

mesh:

An inla.mesh object containing a mesh that can be used with function lgcp to fit a LGCP to the nest data.

gcov:

A list of SpatialGridDataFrame objects, one for each of these spatial covariates:

aspect: Compass direction of the terrain slope. Categorical, with levels N, NE, E, SE, S, SW, W and NW, which are coded as integers 1 to 8.
elevation: Digital elevation of terrain, in metres.
heat: Heat Load Index at each point on the surface (Beer's aspect), discretised. Categorical with values Warmest (Beer's aspect between 0 and 0.999), Moderate (Beer's aspect between 1 and 1.999), Coolest (Beer's aspect equals 2). These are coded as integers 1, 2 and 3, in that order.
slopangle: Terrain slope, in degrees.
slopetype: Type of slope. Categorical, with values Valley, Toe (toe slope), Flat, Midslope, Upper and Ridge. These are coded as integers 1 to 6.
vegetation: Vegetation type: a categorical variable with 6 levels coded as integers 1 to 6 (in order of increasing expected habitat suitability)
waterdist: Euclidean distance from nearest water body, in metres.

plotsample

Plot sample of gorilla nests, sampling 9x9 over the region, with 60\

counts: A SpatialPointsDataFrame frame with elements x, y, count, exposure, being the x- and y-coordinates of the centre of each plot, the count in each plot and the area of each plot.
plots: A SpatialPolygonsDataFrame defining the individual plot boundaries.
nests: A SpatialPointsDataFrame giving the locations of each detected nest.

Source

Library spatstat.data.

References

Funwi-Gabga, N. (2008) A pastoralist survey and fire impact assessment in the Kagwene Gorilla Sanctuary, Cameroon. M.Sc. thesis, Geology and Environmental Science, University of Buea, Cameroon.

Funwi-Gabga, N. and Mateu, J. (2012) Understanding the nesting spatial behaviour of gorillas in the Kagwene Sanctuary, Cameroon. Stochastic Environmental Research and Risk Assessment 26 (6), 793-811.

Examples

data(gorillas, package = "inlabru") # get the data
# extract all the objects, for convenience:

# plot all the nests, mesh and boundary
ggplot() +
  gg(gorillas$mesh) +
  gg(gorillas$boundary) +
  gg(gorillas$nests)

# Plot the elevation covariate
plot(gorillas$gcov$elevation)

# Plot the plot sample
ggplot() +
  gg(gorillas$plotsample$plots) +
  gg(gorillas$plotsample$nests)

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