This passive acoustic recording device has been deployed in Montana (MT) as part of the North American Bat Monitoring Programs (NABat) summertime survey efforts. It has an ultrasonic microphone placed at the top of a 10ft pole that records echolocating bats fro
Kathi Irvine, Ph.D.
I am a Research Statistician with the U.S. Geological Survey at the Northern Rocky Mountain Science Center in Bozeman, Montana.
Research Interest
Prior to finding my home in the federal system in 2011, I was an assistant professor at Montana State University (2008-2010). Since receiving my PhD in Statistics from Oregon State University in 2007, I have collaborated with ecologists and biologists charged with monitoring natural resources on federal and state lands. My team provides statistical support for monitoring programs led by the National Park Service, Fish and Wildlife Service, and state agencies. Our work involves development of survey design and analysis strategies for a variety of plants, animals, and other indicators. We currently support monitoring of whitebark pine in the Greater Yellowstone Ecosystem, upland plant communities throughout the Western US, and bats across North America.
My applied statistical research involves developing analytical approaches for ordinal data and bat acoustic surveys that better link the ecological and observation process within a Bayesian framework, applications of causal analysis, investigating spatial sampling designs, and model-assisted methods for status and trend analyses. I mentor statistics students and support graduate research assistants at Montana State University (MSU). Several of my students have participated in writing peer-reviewed papers during their time at MSU. I encourage students interested in ecological statistics to contact me for possible graduate research assistantships, paid summer work, and other opportunities.
Related Projects:
https://www.whitenosesyndrome.org/
Education and Certifications
PhD. Statistics. Oregon State University
MS. Statistics. Oregon State University; MS. Ecology and Environmental Sciences. University of Maine
BS. Biology. University of North Carolina at Chapel Hill
Science and Products
North American Bat Monitoring Program (NABat)
Developing online integrated data visualization tools for WNS and NABat
Wetland State-and-Transition Model Project
Integrating Climate and Biological Data into Management Decisions for the Greater Sage-Grouse and their Habitats
Using a Collaborative Modeling Approach to Explore Climate and Landscape Change in the Northern Rockies and Inform Adaptive Management
Supplemental Results from: Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends
North American Bat Monitoring Program (NABat) Integrated Summer Species Distribution Model: Predicted Tricolored Bat Occupancy Probabilities (ver. 1.1, October 2024)
Attributed North American Grid-Based Offshore Sampling Frames
Status and Trends of North American Bats Summer Occupancy Analysis 2010-2019 Data Release
Rangewide summertime model predictions for three bat species (Myotis lucifigus, Myotis septentrionalis, and Perimyotis subflavus) from acoustic and mist net data 2010 to 2019
Bat Occupancy Model Predictions for Colorado, acoustic data from 2016-2017
Plant cover data sets for implementing beta distribution based models
Bat occupancy model predictions for Montana from acoustic and mist net data 2008-2010
This passive acoustic recording device has been deployed in Montana (MT) as part of the North American Bat Monitoring Programs (NABat) summertime survey efforts. It has an ultrasonic microphone placed at the top of a 10ft pole that records echolocating bats fro
Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends
Joint spatial modeling bridges the gap between disparate disease surveillance and population monitoring efforts informing conservation of at-risk bat species
NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations
Status and trends of North American bats: Summer occupancy analysis 2010-2019
• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends
Coupling validation effort with in situ bioacoustic data improves estimating relative activity and occupancy for multiple species with cross-species misclassifications
Resilience to fire and resistance to annual grass invasion in sagebrush ecosystems of US National Parks
Spatial Gaussian processes improve multi-species occupancy models when range boundaries are uncertain and nonoverlapping
Advancements in analytical approaches improve whitebark pine monitoring results
Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem
NABat: A top-down, bottom-up solution to collaborative continental-scale monitoring
Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance
The use of Bayesian priors in Ecology: The good, the bad and the not great
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Ecosystems-nabat-FPabund: software for fitting false-positive N-mixture models using NABat mobile acoustic data (version 1.0.0)
Vignette detailing application of multi-scale occupancy models to Hoary bat, Lasiurus cinereus, in Montana, 2020 - 2022
Vignette Bayesian Site Occupancy Model Bat Acoustic Data
Application of Spatially Misaligned Regression Model to Assess Impacts of White-Nose Syndrome
Online supporting information for "Improving geographically extensive acoustic survey designs for modeling species occurrence with imperfect detection and misidentification"
Software Supplement to accompany 'Estimating Species-Environment Relationships with Non-ignorable Sampling Designs'
R code for fitting and simulation study for zero-augmented beta model with errors
Science and Products
North American Bat Monitoring Program (NABat)
Developing online integrated data visualization tools for WNS and NABat
Wetland State-and-Transition Model Project
Integrating Climate and Biological Data into Management Decisions for the Greater Sage-Grouse and their Habitats
Using a Collaborative Modeling Approach to Explore Climate and Landscape Change in the Northern Rockies and Inform Adaptive Management
Supplemental Results from: Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends
North American Bat Monitoring Program (NABat) Integrated Summer Species Distribution Model: Predicted Tricolored Bat Occupancy Probabilities (ver. 1.1, October 2024)
Attributed North American Grid-Based Offshore Sampling Frames
Status and Trends of North American Bats Summer Occupancy Analysis 2010-2019 Data Release
Rangewide summertime model predictions for three bat species (Myotis lucifigus, Myotis septentrionalis, and Perimyotis subflavus) from acoustic and mist net data 2010 to 2019
Bat Occupancy Model Predictions for Colorado, acoustic data from 2016-2017
Plant cover data sets for implementing beta distribution based models
Bat occupancy model predictions for Montana from acoustic and mist net data 2008-2010
This passive acoustic recording device has been deployed in Montana (MT) as part of the North American Bat Monitoring Programs (NABat) summertime survey efforts. It has an ultrasonic microphone placed at the top of a 10ft pole that records echolocating bats fro
This passive acoustic recording device has been deployed in Montana (MT) as part of the North American Bat Monitoring Programs (NABat) summertime survey efforts. It has an ultrasonic microphone placed at the top of a 10ft pole that records echolocating bats fro
Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends
Joint spatial modeling bridges the gap between disparate disease surveillance and population monitoring efforts informing conservation of at-risk bat species
NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations
Status and trends of North American bats: Summer occupancy analysis 2010-2019
• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends
Coupling validation effort with in situ bioacoustic data improves estimating relative activity and occupancy for multiple species with cross-species misclassifications
Resilience to fire and resistance to annual grass invasion in sagebrush ecosystems of US National Parks
Spatial Gaussian processes improve multi-species occupancy models when range boundaries are uncertain and nonoverlapping
Advancements in analytical approaches improve whitebark pine monitoring results
Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem
NABat: A top-down, bottom-up solution to collaborative continental-scale monitoring
Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance
The use of Bayesian priors in Ecology: The good, the bad and the not great
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.