openCR-package: Open Population Capture-Recapture Models

In openCR: Open Population Capture-Recapture

Open Population Capture–Recapture Models

Description

Functions for non-spatial open population analysis by Cormack-Jolly-Seber (CJS) and Jolly-Seber-Schwarz-Arnason (JSSA) methods, and by spatially explicit extensions of these methods. The methods build on Schwarz and Arnason (1996), Borchers and Efford (2008) and Pledger et al. (2010) (see vignette for more comprehensive references and likelihood). The parameterisation of JSSA recruitment is flexible (options include population growth rate λ, per capita recruitment f and seniority γ). Spatially explicit analyses may assume home-range centres are fixed or allow dispersal between primary sessions according to various probability kernels, including bivariate normal (BVN) and bivariate t (BVT) (Efford and Schofield 2022).

Details

Package:	openCR
Type:	Package
Version:	2.2.5
Date:	2022-09-25
License:	GNU General Public License Version 2 or later

Data are observations of marked individuals from a ‘robust’ sampling design (Pollock 1982). Primary sessions may include one or more secondary sessions. Detection histories are assumed to be stored in an object of class ‘capthist’ from the package secr. Grouping of occasions into primary and secondary sessions is coded by the ‘intervals’ attribute (zero for successive secondary sessions).

A few test datasets are provided (microtusCH, FebpossumCH, dipperCH, gonodontisCH, fieldvoleCH) and some from secr are also suitable e.g. ovenCH and OVpossumCH.

Models are defined using symbolic formula notation. Possible predictors include both pre-defined variables (b, session etc.), corresponding to ‘behaviour’ and other effects), and user-provided covariates.

Models are fitted by numerically maximizing the likelihood. The function openCR.fit creates an object of class openCR. Generic methods (print, AIC, etc.) are provided for each object class.

A link at the bottom of each help page takes you to the help index.

See openCR-vignette.pdf for more.

Author(s)

Murray Efford [e-mail]

References

Borchers, D. L. and Efford, M. G. (2008) Spatially explicit maximum likelihood methods for capture–recapture studies. Biometrics 64, 377–385.

Efford, M. G. and Schofield, M. R. (2020) A spatial open-population capture–recapture model. Biometrics 76, 392–402.

Efford, M. G. and Schofield, M. R. (2022) A review of movement models in open population capture–recapture. Methods in Ecology and Evolution. In press. https://doi.org/10.1111/2041-210X.13947

Glennie, R., Borchers, D. L., Murchie, M. Harmsen, B. J., and Foster, R. J. (2019) Open population maximum likelihood spatial capture–recapture. Biometrics 75, 1345–1355

Pledger, S., Pollock, K. H. and Norris, J. L. (2010) Open capture–recapture models with heterogeneity: II. Jolly-Seber model. Biometrics 66, 883–890.

Pollock, K. H. (1982) A capture–recapture design robust to unequal probability of capture. Journal of Wildlife Management 46, 752–757.

Schwarz, C. J. and Arnason, A. N. (1996) A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics 52, 860–873.

See Also

openCR.fit, capthist, ovenCH

Examples

## Not run: 

## a CJS model is fitted by default
openCR.fit(ovenCH)


## End(Not run)

openCR documentation built on Sept. 25, 2022, 5:06 p.m.