estimateN: Abundance point estimates

View source: R/estimateN.r

estimateNR Documentation

Abundance point estimates


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.


  area = NULL,
  control = RdistanceControls()



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 and showProgress=FALSE suppresses all intermediate output.


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)

See Also

dfuncEstim, abundEstim

Rdistance documentation built on July 9, 2023, 6:46 p.m.