L
Larissa L. Bailey
Researcher at Colorado State University
Publications - 131
Citations - 8375
Larissa L. Bailey is an academic researcher from Colorado State University. The author has contributed to research in topics: Population & Occupancy. The author has an hindex of 41, co-authored 123 publications receiving 7271 citations. Previous affiliations of Larissa L. Bailey include United States Geological Survey & North Carolina State University.
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Journal ArticleDOI
Assessing the fit of site-occupancy models
TL;DR: Evidence is found that the most global model considered provides a poor fit to the data, hence an overdispersion factor is estimated to adjust model selection procedures and inflate standard errors.
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Large scale wildlife monitoring studies: statistical methods for design and analysis
Kenneth H. Pollock,James D. Nichols,Theodore R. Simons,George L. Farnsworth,Larissa L. Bailey,John R. Sauer +5 more
TL;DR: Basic concepts based on actual avian, amphibian, and fish monitoring studies are presented in this article and it is believed that the estimation of detection probability should be built into the monitoring design through a double sampling approach.
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Improving inferences in population studies of rare species that are detected imperfectly
Darryl I. MacKenzie,James D. Nichols,Nicole Sutton,Kae Kawanishi,Larissa L. Bailey,Larissa L. Bailey +5 more
TL;DR: Two general approaches that researchers may wish to consider that incorporate the concept of imperfect detectability are suggested: borrowing information about detectability or the other quantities of interest from other times, places, or species; and using state variables other than abundance (e.g., species richness and occupancy).
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Investigating species co-occurrence patterns when species are detected imperfectly
TL;DR: A statistical method for modelling co-occurrence patterns between species while accounting for imperfect detection and site characteristics is presented and some evidence of a statistical interaction between species in terms of detectability is found that may be due to changes in relative abundances.
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Estimating site occupancy and species detection probability parameters for terrestrial salamanders
TL;DR: In this paper, the authors applied a new method to estimate proportion of area occupied using detection/nondetection data from a terrestrial salamander system in Great Smoky Mountains National Park.