Two data.frames must be provided to dsm. They are referred to as
observation.data and segment.data.
If multiple detection functions are to be used, then a column named ddfobj
must be included in observation.data and segment.data. This lets the
model know which detection function each observation is from. These are
numeric and ordered as the ddf.obj argument to dsm, e.g.,
ddf.obj=list(ship_ddf, aerial_ddf) means ship detections have ddfobj=1
and aerial detections have ddfobj=2 in the observation data.
When using mrds models that include mark-recapture components (currently
independent observer and trial modes are supported) then the format of the
observation data needs to be checked to ensure that observations are not
duplicated. The observer column is also required in the
observation.data.
Independent observer mode only unique observations (unique object IDs) are required.
Trial mode only observations made by observer 1 are required.
The segment.data table has the sample identifiers which define the
segments, the corresponding effort (line length) expended and the
environmental covariates that will be used to model abundance/density.
observation.data provides a link table between the observations used in
the detection function and the samples (segments), so that we can aggregate
the observations to the segments (i.e., observation.data is a "look-up
table" between the observations and the segments).
observation.data - the observation data.frame must have (at least) the
following columns:
object unique object identifier
Sample.Label the identifier for the segment where observation occurred
size the size of each observed group (e.g., 1 if all animals occurred
individually)
distance distance to observation
One can often also use observation.data to fit a detection function (so
additional columns for detection function covariates are allowed in this
table).
segment.data: the segment data.frame must have (at least) the following
columns:
Effort the effort (in terms of length of the segment)
Sample.Label identifier for the segment (unique!)
??? environmental covariates, for example location (projected latitude and longitude), and other relevant covariates (sea surface temperature, foliage type, altitude, bathymetry etc).