View source: R/abapToSpOcc_single.R
abapToSpOcc_single | R Documentation |
This function transforms a raw ABAP data frame (returned by getAbapData
)
into an list which can be used to fit single-species occupancy models using
spPGOcc
(spatial) or PGOcc
(non-spatial). The spOccupancy
package fits single-species, multi-species,
and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC).
abapToSpOcc_single(abap_data, pentads = NULL, proj_coords = TRUE)
abap_data |
single-season ABAP data downloaded using |
pentads |
an |
proj_coords |
logical value indicating whether pentad coordinates are
projected ( |
The spPGOcc
function takes coords
as an
argument with X and Y coordinates included for each site. Within the context
of ABAP, these coords
are the centroid of each sampling pentad. In order to
provide these spatial data to this function, simply use getRegionPentads
and provide the same inputs for .region_type
and .region
that are specified
in corresponding getAbapData
call. If proj_coords is set to TRUE
then the coordinates will be transformed using the African Albers Equal Area
coordinate system (see here
for details). This projection is best suited for land masses extending in an
east-to-west orientation at mid-latitudes making it suitable for projecting
pentads in Southern Africa. The functions in the spOccupancy
package assume
that coordinates are projected so for best results it is recommended to always
project the data.
If pentads
are specified then the output can be automatically used in
spPGOcc
. If no spatial data are provided the output
can be used in PGOcc
.
In addition to reformatting the detection/non-detection ABAP data for use in
spOccupancy
occupancy models, this function also extracts two survey-level
covariates and adds them to the output list: hours
and jday
. The hours
variable is the total number of hours spent atlassing which is recorded on the
pentad card and jday
is the Julian day corresponding to the first day of
atlassing for that card.
A list containing data necessary for model fitting in spOccupancy
.
List elements are y
(detection/non-detection data), det.covs
(survey-level covariates),
and coords
(x and y centroids of pentads if spatial data are supplied).
The processing time of abapToSpOcc_single
can be considerably long if
the number of cards and pentads of the focal species is high, so patience may
be required.
Dominic Henry dominic.henry@gmail.com
Pachi Cervantes
spPGOcc
, PGOcc
abap_data <- getAbapData(.spp_code = 212,
.region_type = "province",
.region = "Eastern Cape",
.years = 2012)
abap_pentads <- getRegionPentads(.region_type = "province",
.region = "Eastern Cape")
## Return list for spatial occupancy model
spOcc <- abapToSpOcc_single(abap_data, abap_pentads)
str(spOcc)
## Return list for spatial occupancy model (without coordinate projection)
spOcc <- abapToSpOcc_single(abap_data, abap_pentads, proj_coords = FALSE)
str(spOcc)
## List for non-spatial occupancy model
spOcc <- abapToSpOcc_single(abap_data)
str(spOcc)
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