estimateN: estimateN - Abundance point estimates

In Rdistance: Density and Abundance from Distance-Sampling Surveys

estimateN - Abundance point estimates

Description

Estimate abundance from an Rdistance fitted model. This function is called internally by abundEstim. Most users will call abundEstim to estimate abundance unless they are running simulations or bootstrapping.

Usage

estimateN(object, area = NULL, propUnitSurveyed = 1)

Arguments

object	An Rdistance model frame or fitted distance function, normally produced by a call to dfuncEstim.
area	A scalar containing the total area of inference. Usually, this is study area size. If area is NULL (the default), area will be set to 1 square unit of the output units and density estimates will be produced. 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 several others are acceptable.
propUnitSurveyed	A scalar or vector of real numbers between 0 and 1. The proportion of the default sampling unit that was surveyed. If both sides of line transects were observed, propUnitSurveyed = 1. If only a single side of line transects were observed, set propUnitSurveyed = 0.5. For point transects, this should be set to the proportion of each circle that was observed. Length must either be 1 or the total number of transects in x.

Details

The abundance estimate for line-transect surveys (if no covariates are included in the detection function and both sides of the transect are observed) is

N =\frac{n(A)}{2(ESW)(L)}

where n is total number of sighted individuals (i.e., sum(groupSizes(dfunc))), L is the total length of surveyed transect (i.e., sum(effort(dfunc))), 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 (i.e., sum(groupSizes(dfunc))), P is the total number of surveyed points (i.e., sum(effort(dfunc))), 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.

Estimation of site-specific density (e.g., on every transect) is accomplished by predict(x, type = "density"), which returns a tibble containing density and abundance on the area surveyed by every transect.

Value

A list containing the following components:

density	Estimated density in the surveyed area.
abundance	Estimated abundance on the study area. Equals density if area is not specified.
n.groups	The number of detected groups (not individuals, unless all group sizes = 1).
n.seen	The number of individuals (sum of group sizes).
area	Total area of inference. Study area size
surveyedUnits	Number of surveyed sites. This is total transect length for line-transects or number of points for point-transects. This total transect length does not include transects with missing lengths.
propUnitSurveyed	Proportion of the standard survey unit that was observed
avg.group.size	Average group size on non-NA transects
w	Strip width.
pDetection	Probability of detection.

For line-transects that do not involve covariates, object$density is object$n.seen / (2 * propUnitSurveyed * object$w * object$pDetection * object$surveyedUnits)

See Also

dfuncEstim, abundEstim

Rdistance documentation built on April 12, 2025, 1:12 a.m.