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

18Citations
Citations of this article
129Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Summary: 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). 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. 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) flexible model specification through a user-friendly 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). To illustrate E-SURGE features, we provide implementation and analysis details for several occupancy models. We also provide simulated and real-world examples as well as further specifications and information in a companion wiki platform http://occupancyinesurge.wikidot.com/. © 2014 British Ecological Society.

Cite

CITATION STYLE

APA

Gimenez, O., Blanc, L., Besnard, A., Pradel, R., Doherty, P. F., Marboutin, E., & Choquet, R. (2014). Fitting occupancy models with E-SURGE: Hidden Markov modelling of presence-absence data. Methods in Ecology and Evolution, 5(6), 592–597. https://doi.org/10.1111/2041-210X.12191

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free