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
Silvio O Conte National Fish and Wildlife Refuge Wildlife Monitoring Project (2014 - 2024)
This volume's release consists of 90364 media files captured by autonomous wildlife monitoring devices under the project, Silvio O Conte National Fish and Wildlife Refuge Wildlife Monitoring Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time o
Dartmouth College Woodlands Wildlife Monitoring Project Volume 1 (2014 - 2024)
This volume's release consists of 46576 media files captured by autonomous wildlife monitoring devices under the project, Dartmouth College Woodlands Wildlife Monitoring Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual
Adirondack Inventory & Monitoring (AIM) Network Volume 1 (2021 - 2023)
This volume's release consists of 42105 media files captured by autonomous wildlife monitoring devices under the project, Adirondack Inventory & Monitoring (AIM) Network. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media f
SiMPL Wildlife Magnet Project Data Release Volume 1 (2019 - 2023)
This volume's release consists of 281258 media files captured by autonomous wildlife monitoring devices under the project, SiMPL Wildlife Magnet Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media files are housed w
Maine Department of Inland Fisheries and Wildlife Volume 1 (2022 - 2023)
This volume's release consists of 64642 media files captured by autonomous wildlife monitoring devices under the project, Maine Department of Inland Fisheries and Wildlife. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media
Evaluating a tandem human-machine approach to labelling of wildlife in remote camera monitoring
Remote cameras (“trail cameras”) are a popular tool for non-invasive, continuous wildlife monitoring, and as they become more prevalent in wildlife research, machine learning (ML) is increasingly used to automate or accelerate the labor-intensive process of labelling (i.e., tagging) photos. Human-machine hybrid tagging approaches have been shown to greatly increase tagging efficiency (i.e., time t
Population Structure and Genetic Diversity of Eastern North American Moose
Hair samples were collected in discrete areas during radio-collar studies in Vermont under the auspices of University of Vermont IACUC protocol #17-035 (n=106), New Hampshire (n=34), and Maine (n=57). Hair and tissue samples were opportunistically collected from animals that were harvested, died in vehicle collisions, or translocated throughout Vermont (n = 105), Quebec (n = 198), Massachusetts (n
Filter Total Items: 20
Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data
Moose (Alces alces) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese M. Donovan
Effects of winter ticks and internal parasites on moose survival in Vermont, USA
Moose (Alces alces) have experienced considerable declines along the periphery of their range in the northeastern United States. In Vermont, the population declined 45% from 2010 to 2017 despite minimal hunter harvest and adequate habitat. Similarly, nearby populations recently experienced epizootics characterized by >50% mortality. Declines have largely been associated with the effects of winter
Authors
Jacob Debow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Katherina D. Gieder, Walter Cottrell, James Murdoch, Therese M. Donovan
Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival
Moose populations in the northeastern United States have declined over the past 15 years, primarily due to the impacts of winter ticks. Research efforts have focused on the effects of winter tick infestation on moose survival and reproduction, but stress and nutritional responses to ticks and other stressors remain understudied. We examined the influence of several environmental factors on moose c
Authors
Elias Rosenblatt, Jacob Debow, Joshua Blouin, Therese M. Donovan, James Murdoch, Scott Creel, Will Rogers, Katherina Gieder, Nick Fortin, Cedric Alexander
Moose habitat selection and fitness consequences during two critical winter tick life stages in Vermont, United States
The moose (Alces alces) is a charismatic species in decline across much of their southern distribution in North America. In the northeastern United States, much of the reduction has been attributed to winter tick (Dermacentor albipictus) infestations. Winter ticks are fairly immobile throughout all life stages, and therefore their distribution patterns at any given time are shaped largely by the o
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, James E. Hines, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese M. Donovan
Remote ecological monitoring with smartphones and tasker
Researchers have increasingly used autonomous monitoring units to record animal sounds, track phenology with timed photographs, and snap images when triggered by motion. We piloted the use of smartphones to monitor wildlife in the Riverside East Solar Energy Zone (California) and at Indiana Dunes National Park (Indiana). For both efforts, we established remote autonomous monitoring stations in whi
Authors
Therese M. Donovan, Cathleen Balantic, Jonathan Katz, Mark Massar, Randy Knutson, Kara Duh, Peter Jones, Keith Epstein, Julien Lacasse-Roger, João Dias
Wildlife resistance and protection in a changing New England landscape
Rapid changes in climate and land use threaten the persistence of wildlife species. Understanding where species are likely to occur now and in the future can help identify areas that are resistant to change over time and guide conservation planning. We estimated changes in species distribution patterns and spatial resistance in five future scenarios for the New England region of the northeastern U
Authors
Schuyler B. Pearman-Gillman, Matthew J. Duveneck, James D. Murdoch, Therese M. Donovan
Drivers and consequences of alternative landscape futures on wildlife distributions in New England, United States
In an era of rapid climate and land transformation, it is increasingly important to understand how future changes impact natural systems. Scenario studies can offer the structure and perspective needed to understand the impacts of change and help inform management and conservation decisions. We implemented a scenario-based approach to assess how two high impact drivers of landscape change influenc
Authors
Schuyler B. Pearman-Gillman, Matthew J. Duveneck, James D. Murdoch, Therese M. Donovan
AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R
Ecological research and management programs are increasingly using autonomous monitoring units (AMUs) to collect large volumes of acoustic and/or photo data to address pressing management objectives or research goals. The data management requirements of an AMU-based monitoring effort are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses tha
Authors
Cathleen Balantic, Therese M. Donovan
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques
Understanding the impacts of landscape change on species distributions can help inform decision-making and conservation planning. Unfortunately, empirical data that span large spatial extents across multiple taxa are limited. In this study, we used expert elicitation techniques to develop species distribution models (SDMs) for harvested wildlife species (n = 10) in the New England region of the no
Authors
Schuyler B. Pearman-Gillman, Jonathan E. Katz, Ruth M. Mickey, James D. Murdoch, Therese M. Donovan
Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species
Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound-producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when
Authors
Cathleen Balantic, Therese M. Donovan
Bayesian statistics for beginners: A step-by-step approach
Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and
Authors
Therese M. Donovan, Ruth M. Mickey
Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring
Audio sampling of the environment can provide long-term, landscape-scale presence-absence data to model populations of sound-producing wildlife. Automated detection systems allow researchers to avoid manually searching through large volumes of recordings, but often produce unacceptable false positive rates. We developed methods that allow researchers to improve template-based automated detection u
Authors
Cathleen M. Balantic, Therese M. Donovan
occupancyTuts: A package for learning occupancy modeling with RPresence
Understanding how species are distributed in both space and time is a central question in ecology. Seemingly simple questions such as “How many individuals live in a particular patch?”, “Is a patch occupied by a target species?”, “How many species are there?”, and “what factors shape these pattern?” are questions routinely asked by ecologists. The tutorials in occupancyTuts will illustrate methods
AMMonitor
AMMonitor is an open source R package dedicated to collecting, storing, and analyzing AMU information in a way that 1) is cost-effective, 2) can efficiently process and store information, and 3) can take advantage of the vast and growing community of R analytics.
shinymgr: A framework for building, managing, and stitching Shiny modules into reproducible analyses and reports.
Shinymgr is an R package that provides a unifying framework for managing and deploying Shiny applications that consist of modules. Developers use the shinymgr framework to write modules and seamlessly combine them into Shiny apps, and users of these apps can execute reproducible analyses that can be incorporated into reports for rapid dissemination. The package includes 11 instructional tutorials
Science and Products
Silvio O Conte National Fish and Wildlife Refuge Wildlife Monitoring Project (2014 - 2024)
This volume's release consists of 90364 media files captured by autonomous wildlife monitoring devices under the project, Silvio O Conte National Fish and Wildlife Refuge Wildlife Monitoring Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time o
Dartmouth College Woodlands Wildlife Monitoring Project Volume 1 (2014 - 2024)
This volume's release consists of 46576 media files captured by autonomous wildlife monitoring devices under the project, Dartmouth College Woodlands Wildlife Monitoring Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual
Adirondack Inventory & Monitoring (AIM) Network Volume 1 (2021 - 2023)
This volume's release consists of 42105 media files captured by autonomous wildlife monitoring devices under the project, Adirondack Inventory & Monitoring (AIM) Network. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media f
SiMPL Wildlife Magnet Project Data Release Volume 1 (2019 - 2023)
This volume's release consists of 281258 media files captured by autonomous wildlife monitoring devices under the project, SiMPL Wildlife Magnet Project. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media files are housed w
Maine Department of Inland Fisheries and Wildlife Volume 1 (2022 - 2023)
This volume's release consists of 64642 media files captured by autonomous wildlife monitoring devices under the project, Maine Department of Inland Fisheries and Wildlife. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media
Evaluating a tandem human-machine approach to labelling of wildlife in remote camera monitoring
Remote cameras (“trail cameras”) are a popular tool for non-invasive, continuous wildlife monitoring, and as they become more prevalent in wildlife research, machine learning (ML) is increasingly used to automate or accelerate the labor-intensive process of labelling (i.e., tagging) photos. Human-machine hybrid tagging approaches have been shown to greatly increase tagging efficiency (i.e., time t
Population Structure and Genetic Diversity of Eastern North American Moose
Hair samples were collected in discrete areas during radio-collar studies in Vermont under the auspices of University of Vermont IACUC protocol #17-035 (n=106), New Hampshire (n=34), and Maine (n=57). Hair and tissue samples were opportunistically collected from animals that were harvested, died in vehicle collisions, or translocated throughout Vermont (n = 105), Quebec (n = 198), Massachusetts (n
Filter Total Items: 20
Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data
Moose (Alces alces) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese M. Donovan
Effects of winter ticks and internal parasites on moose survival in Vermont, USA
Moose (Alces alces) have experienced considerable declines along the periphery of their range in the northeastern United States. In Vermont, the population declined 45% from 2010 to 2017 despite minimal hunter harvest and adequate habitat. Similarly, nearby populations recently experienced epizootics characterized by >50% mortality. Declines have largely been associated with the effects of winter
Authors
Jacob Debow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Katherina D. Gieder, Walter Cottrell, James Murdoch, Therese M. Donovan
Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival
Moose populations in the northeastern United States have declined over the past 15 years, primarily due to the impacts of winter ticks. Research efforts have focused on the effects of winter tick infestation on moose survival and reproduction, but stress and nutritional responses to ticks and other stressors remain understudied. We examined the influence of several environmental factors on moose c
Authors
Elias Rosenblatt, Jacob Debow, Joshua Blouin, Therese M. Donovan, James Murdoch, Scott Creel, Will Rogers, Katherina Gieder, Nick Fortin, Cedric Alexander
Moose habitat selection and fitness consequences during two critical winter tick life stages in Vermont, United States
The moose (Alces alces) is a charismatic species in decline across much of their southern distribution in North America. In the northeastern United States, much of the reduction has been attributed to winter tick (Dermacentor albipictus) infestations. Winter ticks are fairly immobile throughout all life stages, and therefore their distribution patterns at any given time are shaped largely by the o
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, James E. Hines, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese M. Donovan
Remote ecological monitoring with smartphones and tasker
Researchers have increasingly used autonomous monitoring units to record animal sounds, track phenology with timed photographs, and snap images when triggered by motion. We piloted the use of smartphones to monitor wildlife in the Riverside East Solar Energy Zone (California) and at Indiana Dunes National Park (Indiana). For both efforts, we established remote autonomous monitoring stations in whi
Authors
Therese M. Donovan, Cathleen Balantic, Jonathan Katz, Mark Massar, Randy Knutson, Kara Duh, Peter Jones, Keith Epstein, Julien Lacasse-Roger, João Dias
Wildlife resistance and protection in a changing New England landscape
Rapid changes in climate and land use threaten the persistence of wildlife species. Understanding where species are likely to occur now and in the future can help identify areas that are resistant to change over time and guide conservation planning. We estimated changes in species distribution patterns and spatial resistance in five future scenarios for the New England region of the northeastern U
Authors
Schuyler B. Pearman-Gillman, Matthew J. Duveneck, James D. Murdoch, Therese M. Donovan
Drivers and consequences of alternative landscape futures on wildlife distributions in New England, United States
In an era of rapid climate and land transformation, it is increasingly important to understand how future changes impact natural systems. Scenario studies can offer the structure and perspective needed to understand the impacts of change and help inform management and conservation decisions. We implemented a scenario-based approach to assess how two high impact drivers of landscape change influenc
Authors
Schuyler B. Pearman-Gillman, Matthew J. Duveneck, James D. Murdoch, Therese M. Donovan
AMMonitor: Remote monitoring of biodiversity in an adaptive framework with R
Ecological research and management programs are increasingly using autonomous monitoring units (AMUs) to collect large volumes of acoustic and/or photo data to address pressing management objectives or research goals. The data management requirements of an AMU-based monitoring effort are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses tha
Authors
Cathleen Balantic, Therese M. Donovan
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques
Understanding the impacts of landscape change on species distributions can help inform decision-making and conservation planning. Unfortunately, empirical data that span large spatial extents across multiple taxa are limited. In this study, we used expert elicitation techniques to develop species distribution models (SDMs) for harvested wildlife species (n = 10) in the New England region of the no
Authors
Schuyler B. Pearman-Gillman, Jonathan E. Katz, Ruth M. Mickey, James D. Murdoch, Therese M. Donovan
Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species
Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound-producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when
Authors
Cathleen Balantic, Therese M. Donovan
Bayesian statistics for beginners: A step-by-step approach
Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and
Authors
Therese M. Donovan, Ruth M. Mickey
Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring
Audio sampling of the environment can provide long-term, landscape-scale presence-absence data to model populations of sound-producing wildlife. Automated detection systems allow researchers to avoid manually searching through large volumes of recordings, but often produce unacceptable false positive rates. We developed methods that allow researchers to improve template-based automated detection u
Authors
Cathleen M. Balantic, Therese M. Donovan
occupancyTuts: A package for learning occupancy modeling with RPresence
Understanding how species are distributed in both space and time is a central question in ecology. Seemingly simple questions such as “How many individuals live in a particular patch?”, “Is a patch occupied by a target species?”, “How many species are there?”, and “what factors shape these pattern?” are questions routinely asked by ecologists. The tutorials in occupancyTuts will illustrate methods
AMMonitor
AMMonitor is an open source R package dedicated to collecting, storing, and analyzing AMU information in a way that 1) is cost-effective, 2) can efficiently process and store information, and 3) can take advantage of the vast and growing community of R analytics.
shinymgr: A framework for building, managing, and stitching Shiny modules into reproducible analyses and reports.
Shinymgr is an R package that provides a unifying framework for managing and deploying Shiny applications that consist of modules. Developers use the shinymgr framework to write modules and seamlessly combine them into Shiny apps, and users of these apps can execute reproducible analyses that can be incorporated into reports for rapid dissemination. The package includes 11 instructional tutorials