Relaxing the closure assumption in single-season occupancy models: staggered arrival and departure times

Ecology
By: , and 

Links

Abstract

Occupancy statistical models that account for imperfect detection have proved very useful in several areas of ecology, including species distribution and spatial dynamics, disease ecology, and ecological responses to climate change. These models are based on the collection of multiple samples at each of a number of sites within a given season, during which it is assumed the species is either absent or present and available for detection while each sample is taken. However, for some species, individuals are only present or available for detection seasonally. We present a statistical model that relaxes the closure assumption within a season by permitting staggered entry and exit times for the species of interest at each site. Based on simulation, our open model eliminates bias in occupancy estimators and in some cases increases precision. The power to detect the violation of closure is high if detection probability is reasonably high. In addition to providing more robust estimation of occupancy, this model permits comparison of phenology across sites, species, or years, by modeling variation in arrival or departure probabilities. In a comparison of four species of amphibians in Maryland we found that two toad species arrived at breeding sites later in the season than a salamander and frog species, and departed from sites earlier.
Publication type Article
Publication Subtype Journal Article
Title Relaxing the closure assumption in single-season occupancy models: staggered arrival and departure times
Series title Ecology
DOI 10.1890/12-1720.1
Volume 94
Issue 3
Year Published 2013
Language English
Publisher Ecological Society of America
Contributing office(s) Coop Res Unit Seattle
Description 8 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecology
First page 610
Last page 617
Google Analytic Metrics Metrics page
Additional publication details