View source: R/caribouHabitat.R
caribouHabitat | R Documentation |
Calculate the relative probability of caribou habitat use in spring, summer, fall and winter for caribou ranges in Northern Ontario, based on Hornseth and Rempel, 2016.
caribouHabitat(
landCover = NULL,
esker = NULL,
linFeat = NULL,
projectPoly = NULL,
caribouRange,
coefTable = coefTableHR,
...
)
landCover |
filename, SpatRaster or RasterLayer. Provincial landcover class |
esker |
filename, SpatRaster or RasterLayer or sf object. Eskers. If it is a raster then it should be esker density in m^2/ha. |
linFeat |
filename, SpatRaster, RasterLayer, or sf object or a list of these that will be combined. Linear features. If it is a raster then it should be linear feature density in m^2/ha. If a raster is provided as a list element then ptDensity will be used to assign a density of linear features in the pixel (default is 1). |
projectPoly |
filename or sf object. Polygon defining the project area. If caribouRange is a data.frame this must have a column called Range with the name of the caribou range represented by the polygon which corresponds to the Range column in the caribouRange data.frame |
caribouRange |
character or data.frame. If character the range where
caribou were located. See |
coefTable |
data.frame. table of coefficients to be used in the
model. Must match the format and naming of the default |
... |
optional arguments:
|
Caribou habitat use is calculated based on the availability of resources and
the presence of disturbances on the landscape. The primary source of resource
information is the landCover
but this is updated based on disturbance
information. All data sources can be provided either as filenames or as
spatial files. If filenames are provided then the landCover
is assumed
to be the Provincial Landcover for Ontario and is converted to resource types
using reclassPLC()
. The result is a CaribouHabitat object which has
methods defined for plotting and extracting the results. To update an existing
CaribouHabitat object with new data see updateCaribou()
.
A CaribouHabitat Object see CaribouHabitat
Rempel, R.S., Carlson, M., Rodgers, A.R., Shuter, J.L., Farrell, C.E., Cairns, D., Stelfox, B., Hunt, L.M., Mackereth, R.W. and Jackson, J.M., 2021. Modeling Cumulative Effects of Climate and Development on Moose, Wolf, and Caribou Populations. The Journal of Wildlife Management.
Hornseth, M.L. and Rempel, R.S., 2016. Seasonal resource selection of woodland caribou (Rangifer tarandus caribou) across a gradient of anthropogenic disturbance. Canadian Journal of Zoology, 94(2), pp.79-93. https://doi.org/10.1139/cjz-2015-0101
CaribouHabitat for information on the object
returned, updateCaribou()
for updating an existing
CaribouHabitat object, and plot()
for the plot method.
Caribou habitat functions:
CaribouHabitat-class
,
calcBinaryUse()
,
coefTableHR
,
coefTableStd
,
fnlcToResType
,
loadSpatialInputs()
,
plcToResType
,
rasterizeLineDensity()
,
reclassPLC()
,
resTypeCode
,
results()
,
rfuToResType
,
threshTable
,
updateCaribou()
# create example rasters
lc <- terra::rast(xmin = 0, xmax = 25000, ymin = 0, ymax = 25000,
resolution = 250, crs = "EPSG:5070")
lc[] <- 0
nd <- lc
nd[1:30, 1:30] <- 1
ad <- lc
ad[30:50, 3:50] <- 1
lc[] <- 1
lc[70:100, 70:100] <- 2
# create sf objects
lf <- sf::st_as_sf(sf::st_sfc(list(sf::st_linestring(matrix(c(0, 0, 10000, 10000),
ncol = 2, byrow = TRUE))),
crs = 5070))
esk <- sf::st_as_sf(sf::st_sfc(list(sf::st_linestring(matrix(c(0, 10000, 10000, 0),
ncol = 2, byrow = TRUE))),
crs = 5070))
projPol <- sf::st_sf(sf::st_as_sfc(sf::st_bbox(ad)))
# calculate relative probability of use
res <- caribouHabitat(landCover = lc,
linFeat = lf,
esker = esk,
natDist = nd,
anthroDist = ad,
projectPoly = projPol,
caribouRange = "Nipigon",
winArea = 1000 #leave as default NULL except for small examples
)
# plot the relative probability of use
plot(res)
# plot the predictor variables
plot(results(res, type ="processedData"))
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