Location
Postdoctoral Fellow

Personal Information

I am an ecologist broadly interested in methods that support landscape-scale monitoring and management of prioritized natural resources, particularly on public lands. I have developed methodology for acoustic monitoring of wildlife, including modeling approaches, hardware, and software tools. Currently, my research focuses on developing a national perspective for climate change refugia conservation within the U.S. Department of the Interior.

I received my PhD in Natural Resources from the University of Vermont’s Rubenstein School of Environment and Natural Resources. Then I worked as a postdoctoral associate with the Vermont Cooperative Fish and Wildlife Research Unit. As a doctoral student, I was a fellow in the National Science Foundation IGERT Smart Grid program, through which I obtained UVM’s Complex Systems Certificate. Professionally, I love solving problems, writing, teaching, coding, and getting to do science that studies and supports our network of public lands in the U.S. Outside of work, my main hobbies are creating and playing music on my guitar and piano, distance running, and birding by ear.

Primary Interests

Climate change adaptation planning, bioacoustics

Current Project

Developing a national perspective for climate change refugia conservation

Courses Taught

Current

ECO 691E Ecological Responses to Climate Change (Fall 2020)

Previous

Modeling Principles for Natural Resource Management (USFWS National Conservation Training Center)

Introduction to R for Natural Resources (University of Vermont)

Education

PhD., Natural Resources – University of Vermont

Master’s, Natural Resource Management – University of Pennsylvania

B.S., Biology – Cornell University

Publications

Balantic. C.M. & Donovan, T.M. 2020. AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R. Methods in Ecology and Evolution. DOI: 10.1111/2041‐210X.1339.

Balantic, C.M. & Donovan, T.M. 2019. Dynamic wildlife occupancy models using automated acoustic monitoring data. Ecological Applications. DOI: 10.1002/eap.1854. View Github repository to reproduce analysis.

Balantic, C.M. & Donovan, T.M. 2019. Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring. Bioacoustics. DOI: 10.1080/09524622.2019.1605309. View Github repository to reproduce analysis.

Balantic, C.M. & Donovan, T.M. 2019. Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species. Ecology and Evolution. DOI: 10.1002/ece3.5579. View Github repository to reproduce analysis.