The unmarked R package: Twelve years of advances in occurrence and abundance modelling in ecology

Abstract

AbstractSpecies distribution models (SDMs) are widely applied to understand the processes governing spatial and temporal variation in species abundance and distribution but often do not account for measurement errors such as false negatives and false positives.We describeunmarked, a package for the freely available and open‐source R software that provides a complete workflow for modelling species distribution and abundance while explicitly accounting for measurement errors. Here we focus on recent advances inunmarkedfunctionality to support multi‐species, multi‐state, and multi‐season data, as well as support for fitting models with random effects.For illustration, we present an analysis of Acadian FlycatcherEmpidonax virescensabundance on Roanoke River National Wildlife Refuge, North Carolina, USA, over 18 years. We found that Acadian Flycatcher abundance was initially greater in hardwood plantation habitat relative to bottomland hardwood forest along river levees but that abundance declined over time in both habitats.We plan forunmarkeddevelopment to keep pace with advances in hierarchical modelling in ecology, including better handling of continuous‐time data from camera trap and automated recording units and integrated models for multiple data streams.