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detect: analyzing wildlife data with detection error

CRAN version CRAN download stats Build status License: GPL v2

The R package implements models to analyze site occupancy and count data models with detection error. The package development was supported by the Alberta Biodiversity Monitoring Institute and the Boreal Avian Modelling (BAM) Project.

Main functions:

  • svocc: single visit occupancy model (Lele et al. 2011, Moreno et al. 2010).
  • svabu: single visit Poisson and Negative Binomial abundance model based on conditional maximum likelihood (Solymos et al. 2012, Denes et al. 2016, Solymos & Lele 2016).
  • cmulti: conditional multinomial maximum likelihood estimation for removal and (point count) distance sampling, efficient and flexible setup for varying methodologies (Solymos et al. 2013, Solymos et al. 2018).


Install CRAN release version (recommended):


Development version:

install.packages("detect", repos = "")

User visible changes in the package are listed in the NEWS file.

Use the issue tracker to report a problem.


Denes, F., Solymos, P., Lele, S. R., Silveira, L. & Beissinger, S. 2017. Biome scale signatures of land use change on raptor abundance: insights from single-visit detection-based models. Journal of Applied Ecology, 54, 1268--1278. DOI: 10.1111/1365-2664.12818

Lele, S.R., Moreno, M. and Bayne, E. 2011. Dealing with detection error in site occupancy surveys: What can we do with a single survey? Journal of Plant Ecology, 5(1), 22--31. DOI: 10.1093/jpe/rtr042

Moreno, M. and Lele, S. R. 2010. Improved estimation of site occupancy using penalized likelihood. Ecology, 91, 341--346. DOI: 10.1890/09-1073.1

Solymos, P., Lele, S. R. and Bayne, E. 2012. Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error. Environmetrics, 23, 197--205. DOI: 10.1002/env.1149

Solymos, P., Matsuoka, S. M., Bayne, E. M., Lele, S. R., Fontaine, P., Cumming, S. G., Stralberg, D., Schmiegelow, F. K. A. & Song, S. J., 2013. Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation. Methods in Ecology and Evolution, 4, 1047--1058. DOI: 10.1111/2041-210X.12106

Solymos, P., Lele, S. R. 2016. Revisiting resource selection probability functions and single-visit methods: clarification and extensions. Methods in Ecology and Evolution, 7, 196--205. DOI: 10.1111/2041-210X.12432

Solymos, P., Matsuoka, S. M., Cumming, S. G., Stralberg, D., Fontaine, P., Schmiegelow, F. K. A., Song, S. J., and Bayne, E. M., 2018. Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity. Condor, 120, 765--786. DOI: 10.1650/CONDOR-18-32.1

Supporting info, including a tutorial for the QPAD method.


R package for analyzing wildlife data with detection error






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