Efficient occupancy model-fitting for extensive citizen-science data.

ABSTRACT: Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved us

SUBMITTER: Dennis EB 

PROVIDER: S-EPMC5362231 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature