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Activity Number: 577 - Statistical Models in Ecology
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #306636
Title: Uncovering Statistical Idiosyncrasies of Acoustic Bat Data
Author(s): Kathryn Irvine* and Wilson Wright and Katharine Banner and Thomas Rodhouse and Andrea Litt
Companies: US Geological Survey and Montana State Univsersity and Montana State University and National Park Service and Montana State University
Keywords: Bats; Monitoring; Survey Design; Occupancy Models; non-ignorable surveys

North American bats are facing increasingly serious conservation threats due to the rapid spread of the bat disease white-nose syndrome, an expanding footprint of the wind power industry, and accelerated global change. However, bats are under-studied relative to other taxonomic groups (amphibians, birds, carnivores, etc.) because of their cryptic and nocturnal behavior. To combat the dearth of data available to inform conservation and management of bats nationally, a collaborative monitoring effort was proposed in 2015 — the North American Bat monitoring program (NABat). The easiest way to collect data on bats is to use remotely deployed acoustic recording devices. On a given night zero to hundreds of echolocation calls can be recorded from multiple bat species. The spatial design for NABat was created to harness the occupancy modeling framework. However, based on empirical data and the realities of a collaborative monitoring effort, we were motivated to expand on the available model assessment techniques, understand ways to adjust model estimates for non-ignorable surveys, develop count detection models, and create R packages for conducting customized power analyses.

Authors who are presenting talks have a * after their name.

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