USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit have released AMMonitor 2, an R package designed for remote wildlife monitoring. An R package is a collection of documentation, data, and functions that allow users to reuse the code and tools
Terri Donovan, PhD
Assistant Unit Leader - Vermont Cooperative Fish and Wildlife Research Unit
Research Interests
Terri's research emphases include population dynamics, population modeling and structured decision making, landscape ecology, and conservation biology. Current research efforts focus on adaptive management for both game and non-game species.
Teaching Interests
With a background in education, Terri is an avid teacher and enjoys working with all age groups. Current teaching efforts include an on-line Principles of Modeling course geared for graduate students and professionals, and studies abroad course in Costa Rica, where the focus is on how to re-establish and monitor a wildlife corridor for the three-wattled bellbird (Pajaro campana). Terri also directs the Spreadsheet Project, a suite of tutorials on quantitative data analysis and modeling in ecology.
Professional Experience
Assistant Unit Leader, Vermont Cooperative Fish and Wildlife Research Unit, 2000-
Education and Certifications
Ph D University of Missouri-Columbia 1994
MS Eastern Illinois University 1986
BS Eastern Illinois University 1986
Science and Products
Vermont Cooperative Fish and Wildlife Research Unit
USGS Cuban Treefrog Invasion Front Volume 1 (2014 - 2022) USGS Cuban Treefrog Invasion Front Volume 1 (2014 - 2022)
National Ecological Observatory Network Volume 1 (2024) National Ecological Observatory Network Volume 1 (2024)
Observations of tear-drinking by lepidopterans on moose (Alces americanus americanus) in northeastern North America Observations of tear-drinking by lepidopterans on moose (Alces americanus americanus) in northeastern North America
Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse
DeepFaune New England - Data DeepFaune New England - Data
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques Predicting wildlife distribution patterns in New England USA with expert elicitation techniques
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit have released AMMonitor 2, an R package designed for remote wildlife monitoring. An R package is a collection of documentation, data, and functions that allow users to reuse the code and tools
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit released AMMonitor 2, a fully open-source wildlife monitoring R package useful for students and users with some coding experience who desire a standardized yet flexible data management framework.
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit released AMMonitor 2, a fully open-source wildlife monitoring R package useful for students and users with some coding experience who desire a standardized yet flexible data management framework.
Observations of tear-drinking by lepidopterans on moose (Alces alces americana) in northeastern North America Observations of tear-drinking by lepidopterans on moose (Alces alces americana) in northeastern North America
DeepFaune New England: A species classification model for trail camera images in northeastern North America DeepFaune New England: A species classification model for trail camera images in northeastern North America
Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse
occupancyTuts: Occupancy modelling tutorials with RPresence occupancyTuts: Occupancy modelling tutorials with RPresence
Net carbon sequestration implications of intensified timber harvest in Northeastern U.S. forests Net carbon sequestration implications of intensified timber harvest in Northeastern U.S. forests
Evaluating a tandem human-machine approach to labelling of wildlife in remote camera monitoring Evaluating a tandem human-machine approach to labelling of wildlife in remote camera monitoring
Code for Two-stage approach to automatic detection with machine learning for improved surveillance of the invasive Cuban treefrog Code for Two-stage approach to automatic detection with machine learning for improved surveillance of the invasive Cuban treefrog
DeepFaune New England DeepFaune New England
AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1 AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1
AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.0.0 AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.0.0
occupancyTuts: A package for learning occupancy modeling with RPresence occupancyTuts: A package for learning occupancy modeling with RPresence
AMMonitor AMMonitor
Science and Products
Vermont Cooperative Fish and Wildlife Research Unit
USGS Cuban Treefrog Invasion Front Volume 1 (2014 - 2022) USGS Cuban Treefrog Invasion Front Volume 1 (2014 - 2022)
National Ecological Observatory Network Volume 1 (2024) National Ecological Observatory Network Volume 1 (2024)
Observations of tear-drinking by lepidopterans on moose (Alces americanus americanus) in northeastern North America Observations of tear-drinking by lepidopterans on moose (Alces americanus americanus) in northeastern North America
Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse Two-stage models improve machine learning classifiers in wildlife research: A case study in identifying false positive detections of Ruffed Grouse
DeepFaune New England - Data DeepFaune New England - Data
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques Predicting wildlife distribution patterns in New England USA with expert elicitation techniques
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit have released AMMonitor 2, an R package designed for remote wildlife monitoring. An R package is a collection of documentation, data, and functions that allow users to reuse the code and tools
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit have released AMMonitor 2, an R package designed for remote wildlife monitoring. An R package is a collection of documentation, data, and functions that allow users to reuse the code and tools
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit released AMMonitor 2, a fully open-source wildlife monitoring R package useful for students and users with some coding experience who desire a standardized yet flexible data management framework.
USGS researchers at the Vermont Cooperative Fish and Wildlife Research Unit released AMMonitor 2, a fully open-source wildlife monitoring R package useful for students and users with some coding experience who desire a standardized yet flexible data management framework.