detHist function

Compute Summary Statistics from Detection Histories

This function extracts various summary statistics from detection history data of various unmarkedFrame and unmarkedFit classes. 1.1

detHist(object, ...)

## S3 method for class 'unmarkedFitColExt'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccu'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccuFP'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccuRN'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccuMulti'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccuMS'
detHist(object, ...)

## S3 method for class 'unmarkedFrameOccu'
detHist(object, ...)

## S3 method for class 'unmarkedFrameOccuFP'
detHist(object, ...)

## S3 method for class 'unmarkedMultFrame'
detHist(object, ...)

## S3 method for class 'unmarkedFrameOccuMulti'
detHist(object, ...)

## S3 method for class 'unmarkedFrameOccuMS'
detHist(object, ...)

## S3 method for class 'unmarkedFitGOccu'
detHist(object, ...)

## S3 method for class 'unmarkedFrameOccuComm'
detHist(object, ...)

## S3 method for class 'unmarkedFitOccuComm'
detHist(object, ...)

Arguments

• object: an object of various unmarkedFrame or unmarkedFit

  classes containing detection history data.

• ...: additional arguments passed to the function.

Details

This function computes a number of summary statistics in data sets used for single-season occupancy models (MacKenzie et al. 2002), dynamic occupancy models (MacKenzie et al. 2003), Royle-Nichols models (Royle and Nichols 2003), false-positive occupancy models (Royle and Link 2006, Miller et al. 2011), multispecies occupancy models (Rota et al. 2016), and multistate occupancy models (Nichols et al. 2007, MacKenzie et al. 2009).

detHist can take data frames of the unmarkedFrameOccu, unmarkedFrameOccuFP, unmarkedMultFrame, unmarkedFrameOccuMulti, unmarkedFrameOccuMS classes as input. For convenience, the function can also extract the raw data from model objects of classes unmarkedFitColExt, unmarkedFitOccu, unmarkedFitOccuFP, unmarkedFitOccuRN, unmarkedFitOccuMulti, unmarkedFitOccuMS, unmarkedFitGOccu, and unmarkedFitOccuComm. Note that different model objects using the same data set will have identical values.

Returns

For objects of classes unmarkedFitOccu, unmarkedFitOccuRN, unmarkedFitOccuFP, unmarkedFitColExt, unmarkedFitOccuMS, unmarkedFitGOccu, unmarkedFitOccuComm, unmarkedFrameOccu, unmarkedFrameOccuFP, unmarkedMultFrame, unmarkedFrameOccuMS, unmarkedFrameOccuComm, detHist returns a list with the following components:

• hist.table.full: a table with the frequency of each observed detection history. For unmarkedFitGOccu objects, this element consists in a summary of the detections pooled across devices (secondary periods) within each primary period. This element is NULL for unmarkedFrameOccuComm and unmarkedFitOccuComm objects.

• hist.table.seasons: a list of tables with the frequency of each season-specific detection history.

• out.freqs: a matrix where the rows correspond to each sampling season and where columns consist of the number of sites sampled in season $t$ (sampled) and the number of sites with at least one detection in season $t$ (detected). For multiseason data, the matrix includes the number of sites sampled in season $t - 1$ with colonizations observed in season $t$

  (colonized), the number of sites sampled in season c("$t -\n$", "$1$") with extinctions observed in season $t$ (extinct), the number of sites sampled in season $t - 1$ without changes observed in season $t$ (static), and the number of sites sampled in season $t$ that were also sampled in season c("$t -\n$", "$1$") (common). For multispecies data, out.freqs

  presents, for each species, the number of sites sampled and the number of sites with at least one detection.

• out.props: a matrix where the rows correspond to each sampling season and where columns consist of the proportion of sites in season t with at least one detection (naive.occ). For multiseason data, the matrix includes the proportion of sites sampled in season $t - 1$ with colonizations observed in season $t$ (naive.colonization), the proportion of sites sampled in season $t - 1$ with extinctions observed in season $t$ (naive.extinction), and the proportion of sites sampled in season $t - 1$ with no changes observed in season $t$. For multispecies data, out.props presents the proportion of sites with a least one detection for each species.

• n.seasons: the number of seasons (primary periods) in the data set.

• n.visits.season: the maximum number of visits per season in the data set.

• n.species: the number of species in the data set.

• missing.seasons: logical vector indicating whether data were collected or not during a given season (primary period), where TRUE indicates that no data were collected during the season.

For objects of classes unmarkedFitOccuMulti and unmarkedFrameOccuMulti, detHist returns a list with the following components:

• hist.table.full: a table with the frequency of each observed detection history. The species are coded with letters and follow the same order of presentation as in the other parts of the output.

• hist.table.species: a list of tables with the frequency of each species-specific detection history. The last element of hist.table.species features the number of sites with co-occurrence of the different species (coOcc).

• out.freqs: a matrix where the rows correspond to each species and where columns consist of the number of sites sampled during the season (sampled) and the number of sites with at least one detection (detected).

• out.props: a matrix where the rows correspond to each species and where columns consist of the proportion of sites with at least one detection during the season (naive.occ).

• n.seasons: the number of seasons (primary periods) in the data set.

• n.visits.season: the maximum number of visits per season in the data set.

• n.species: the number of species in the data set.

• missing.seasons: logical vector indicating whether data were collected or not during a given season (primary period), where TRUE indicates that no data were collected during the season.

References

MacKenzie, D. I., Nichols, J. D., Lachman, G. B., Droege, S., Royle, J. A., Langtimm, C. A. (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83 , 2248--2255.

MacKenzie, D. I., Nichols, J. D., Hines, J. E., Knutson, M. G., Franklin, A. B. (2003) Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology

84 , 2200--2207.

MacKenzie, D. I., Nichols, J. D., Seamans, M. E., Gutierrez, R. J. (2009) Modeling species occurrence dynamics with multiple states and imperfect detection. Ecology 90 , 823--835.

Mazerolle, M. J. (2015) Estimating detectability and biological parameters of interest with the use of the R environment. Journal of Herpetology 49 , 541--559.

Miller, D. A. W., Nichols, J. D., McClintock, B. T., Campbell Grant, E. H., Bailey, L. L. (2011) Improving occupancy estimation when two types of observational error occur: non-detection and species misidentification. Ecology 92 , 1422--1428.

Nichols, J. D., Hines, J. E., Mackenzie, D. I., Seamans, M. E., Gutierrez, R. J. (2007) Occupancy estimation and modeling with multiple states and state uncertainty. Ecology 88 , 1395--1400.

Rota, C. T., Ferreira, M. A. R., Kays, R. W., Forrester, T. D., Kalies, E. L., McShea, W. J., Parsons, A. W., Millspaugh, J. J. (2016) A multispecies occupancy model for two or more interacting species. Methods in Ecology and Evolution 7 , 1164--1173.

Royle, J. A., Link, W. A. (2006) Generalized site occupancy models allowing for false positive and false negative errors. Ecology

87 , 835--841.

Royle, J. A., Nichols, J. D. (2003) Estimating abundance from repeated presence-absence data or point counts. Ecology

84 , 777--790.

Author(s)

Marc J. Mazerolle

See Also

covDiag, countHist, countDist, detTime, mb.chisq, mb.gof.test

Examples

##data from Mazerolle (2015)
## Not run:

data(bullfrog)

##detection data
detections <- bullfrog[, 3:9]

##load unmarked package
if(require(unmarked)){

##assemble in unmarkedFrameOccu
bfrog <- unmarkedFrameOccu(y = detections)

##compute descriptive stats from data object
detHist(bfrog)

##run model
fm <- occu(~ 1 ~ 1, data = bfrog)
##compute descriptive stats from model object
detHist(fm)
}
## End(Not run)