Estimate abundance given a distance function,
a "merged" data frame containing detections and transect lengths, area,
and the number of sides surveyed (if line-transects).
This is called internally by abundEstim. Most users will call
abundEstim to estimate abundance.
estimateN(
dfunc,
data,
area = NULL,
surveyedSides,
lengthColumn,
control = RdistanceControls()
)A list containing the following components:
Estimated density in the surveyed area.
Estimated abundance on the study area.
The number of detections (not individuals, unless all group sizes = 1) used to estimate density and abundance.
The number of individuals (sum of group sizes) used to estimate density and abundance.
Total area of inference. Study area size
Number of surveyed sites. This is total transect length for line-transects and number of points for point-transects. This total transect length does not include NA transects.
Number of sides (1 or 2) of transects surveyed. Only relevant for line-transects.
Average group size on non-NA transects
Strip width.
Probability of detection.
For line-transects that do not involve covariates, x$density is x$n.seen / (x$surveyedSides * x$w * x$pDetection * x$surveyedUnits)
An estimate distance function (see dfuncEstim).
A data frame containing distance observations, transects,
and lengths. This data frame must have a column named 'siteID' that identifies
unique sites (transects or points). If observations were made on line-transects, this
data frame must also have a column named
by the lengthColumn parameter that contains transect lengths. NA
length transects are accepted and are dropped when computing total
transect length. Only observations on non-NA-length transects are toward density.
A scalar containing the total area of
inference. Commonly, this is study area size.
If area is NULL (the default),
area will be set to 1 square unit of the output units and this
produces abundance estimates equal density estimates.
If area is not NULL, it must have measurement units
assigned by the units package.
The units on area must be convertible
to squared output units. Units
on area must be two-dimensional.
For example, if output units are "foo",
units on area must be convertible to "foo^2" by the units
package.
Units of "km^2", "cm^2", "ha", "m^2", "acre", "mi^2", and many
others are acceptable.
The number of sides of the transect that were surveyed. Either 1 or 2. Only applies to line transects.
Character string specifying the (single) column in
siteData that contains transect lengths. This is ignored if
pointSurvey = TRUE. This column must have measurement units.
A list containing optimization control parameters such
as the maximum number of iterations, tolerance, the optimizer to use,
etc. See the
RdistanceControls function for explanation of each value,
the defaults, and the requirements for this list.
See examples below for how to change controls.
The abundance estimate for line-transect surveys (if no covariates
are included in the detection function and both sides of the transect
were observed) is
$$N =\frac{n(A)}{2(ESW)(L)}$$
where n is total number of sighted individuals
(i.e., sum(dfunc$detections$groupSizes)), L is the total length of
surveyed transect (i.e., sum(siteData[,lengthColumn])),
and ESW is effective strip width
computed from the estimated distance function (i.e., ESW(dfunc)).
If only one side of transects were observed, the "2" in the denominator
is not present (or, replaced with a "1").
The abundance estimate for point transect surveys (if no covariates are
included) is
$$N =\frac{n(A)}{\pi(ESR^2)(P)}$$
where n is total number of sighted individuals,
P is the total number of surveyed points,
and ESR is effective search radius
computed from the estimated distance function (i.e., ESR(dfunc)).
Setting plot.bs=FALSE and showProgress=FALSE
suppresses all intermediate output.
dfuncEstim, abundEstim