Fitting occupancy models with E-SURGE: Hidden Markov modelling of presence-absence data

Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175, CNRS, Montpellier, France
Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, USA
DOI
10.7287/peerj.preprints.84v1
Subject Areas
Biodiversity, Conservation Biology, Ecology, Statistics
Keywords
detectability, capture-recapture, detection-nondetection, hidden Markov models, E-SURGE, presence-absence, species occurrence
Copyright
© 2013 Gimenez et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Cite this article
Gimenez O, Blanc L, Besnard A, Pradel R, Doherty P, Choquet R. 2013. Fitting occupancy models with E-SURGE: Hidden Markov modelling of presence-absence data. PeerJ PrePrints 1:e84v1

Abstract

1. Occupancy – the proportion of area occupied by a species – is a key notion for addressing important questions in ecology, biogeography and conservation biology. Occupancy models allow estimating and inferring about species occurrence while accounting for false absences (or imperfect species detection). 2. Most occupancy models can be formulated as hidden Markov models (HMM) in which the state process captures the Markovian dynamic of the actual but latent states while the observation process consists of observations that are made from these underlying states. 3. We show how occupancy models can be implemented in program E-SURGE, which was initially developed to analyse capture-recapture data in the HMM framework. Replacing individuals by sites provides the user with access to several features of E-SURGE that are not available altogether or just not available in standard occupancy software: i) user-friendly model specification through a SAS/R-like syntax without having to write custom code, ii) decomposition of the observation and state processes in several steps to provide flexible parameterisation, iii) up-to-date diagnostics of model identifiability and iv) advanced numerical algorithms to produce fast and reliable results (including site random effects). 4. To illustrate E-SURGE features, we provide simulated data and the details of the implementation on the analysis of several occupancy models. These detailed examples are gathered in a companion wiki platform http://occupancyinesurge.wikidot.com/ .

Author Comment

The paper is currently submitted to Methods in Ecology and Evolution. Program E-SURGE v1.9.1 together with libraries can be downloaded from http://www.cefe.cnrs.fr/biostatistiques-et-biologie-des-populations/logiciels. Examples from the paper and more are available from the wiki platform http://occupancyinesurge.wikidot.com/.