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
Filter Total Items: 24
National Ecological Observatory Network Volume 1 (2024) National Ecological Observatory Network Volume 1 (2024)
This volume's release consists of 31524 media files captured by autonomous wildlife monitoring devices under the project, National Ecological Observatory 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...
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
This volume's release consists of 80 media files captured by autonomous wildlife monitoring devices under the project, USDA Green Mountain National Forest. 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...
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
Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However, false positive detections from ML classifiers can result in erroneous ecological models that can lead to misguided management and conservation actions. We used a two-stage general approach to...
DeepFaune New England - Data DeepFaune New England - Data
DeepFaune New England (DFNE) is a model for species classification in trail camera imagery. This model is a re-trained version of the DeepFaune model for classifying European species in trial cameras, fine-tuned to classify taxa from northeastern North America. The DFNE model takes as input cropped images of each animal, which can be generated by an object detection model. DFNE...
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques 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...
Bureau of Land Management Riverside East Solar Energy Zone Volume 1 Bureau of Land Management Riverside East Solar Energy Zone Volume 1
This volume's release consists of 15184 media files captured by autonomous wildlife monitoring devices under the project, Bureau of Land Management Riverside East Solar Energy Zone. 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...
New Hampshire Fish and Game Department Volume 1 New Hampshire Fish and Game Department Volume 1
This volume's release consists of 463615 media files captured by autonomous wildlife monitoring devices under the project, New Hampshire Fish and Game Department. 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...
Mapping landscape connectivity for moose across the northeastern United States Mapping landscape connectivity for moose across the northeastern United States
Connectivity describes how well a landscape facilitates or impedes the movement of animals. Maximizing connectivity is a common management goal, especially for large mammals like moose (Alces americanus americanus) that occupy large home ranges and have the capacity to move long distances. Moose in the northeastern US (encompassing the states of Vermont, New Hampshire, Massachusetts...
USDA White Mountain National Forest Volume 1 (2014 - 2024) USDA White Mountain National Forest Volume 1 (2014 - 2024)
This volume's release consists of 325099 media files captured by autonomous wildlife monitoring devices under the project, USDA White Mountain National Forest. 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...
Maine Department of Inland Fisheries and Wildlife Moose Project - Volume 2 (2021 - 2024) Maine Department of Inland Fisheries and Wildlife Moose Project - Volume 2 (2021 - 2024)
This volume's release consists of 320104 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...
Massachusetts Wildlife Monitoring Project (2022 - 2024) Massachusetts Wildlife Monitoring Project (2022 - 2024)
This volume's release consists of 143321 media files captured by autonomous wildlife monitoring devices under the project, Massachusetts 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...
USDA Green Mountain National Forest Volume 1 (2016 - 2022) USDA Green Mountain National Forest Volume 1 (2016 - 2022)
This volume's release consists of 84049 media files captured by autonomous wildlife monitoring devices under the project, USDA Green Mountain National Forest. 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...
AMMonitor 2
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
Moose sighting on a trail camera
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.
Filter Total Items: 52
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
The DeepFaune New England model classifies wildlife species in trail camera images, identifying 24 taxa from northeastern North America with high (97%) accuracy. The model was adapted from the DeepFaune model for identifying European wildlife, demonstrating the practicality of transfer learning across continents. The majority of training data is openly licensed, and the model itself is...
Authors
Laurence Clarfeld, Katherine Gieder, Angela Fuller, Zhongqi Miao, Alexej Sirén, Shevenell Webb, Toni Morelli, Jillian Kilborn, Catherine Callahan, Leighlan Prout, Rachel Cliché, Riley Patry, Christopher Bernier, Susan Staats, Therese Donovan
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
Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However, false positive detections from ML classifiers can result in erroneous ecological models that can lead to misguided management and conservation actions. We used a two-stage general approach to...
Authors
Laurence Clarfeld, Katherina Gieder, Robert Abrams, Christopher Bernier, Joseph Cahill, Susan Staats, Scott Wixsom, Therese Donovan
occupancyTuts: Occupancy modelling tutorials with RPresence occupancyTuts: Occupancy modelling tutorials with RPresence
1. The occupancy modelling framework offers tremendous flexibility in estimating species abundance and distribution patterns while accounting for imperfect detection, and has seen rapid growth and adoption since its introduction at the beginning of the century. 2. At the same time, in an era of big data, there are increasing demands on developing quantitative skills and proficiency in...
Authors
Therese Donovan, James Hines, Darryl MacKenzie
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
U.S. forests, particularly in the eastern states, provide an important offset to greenhouse gas (GHG) emissions. Some have proposed that forest-based natural climate solutions can be strengthened via a number of strategies, including increases in the production of forest biomass energy. We used output from a forest dynamics model (SORTIE-ND) in combination with a GHG accounting tool...
Authors
Michelle Brown, Charles D. Canham, Thomas Buchholz, John Gunn, Therese Donovan
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
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...
Authors
Laurence A. Clarfeld, Alexej P.K. Sirén, Brendan Mulhall, Tammy Wilson, Elena Bernier, John Farrell, Gus Lunde, Nicole Hardy, Katherine Gieder, Robert Abrams, Sue Staats, Scott McLellan, Therese Donovan
Advances in wildlife abundance estimation using pedigree reconstruction Advances in wildlife abundance estimation using pedigree reconstruction
The conservation and management of wildlife populations, particularly for threatened and endangered species are greatly aided with abundance, growth rate, and density measures. Traditional methods of estimating abundance and related metrics represent trade-offs in effort and precision of estimates. Pedigree reconstruction is an emerging, attractive alternate approach because its use of...
Authors
Elias Rosenblatt, Scott Creel, Katherina Gieder, James Murdoch, Therese Donovan
Birth rates and neonate survival in a parasite rich moose population in Vermont, USA Birth rates and neonate survival in a parasite rich moose population in Vermont, USA
Moose (Alces alces) populations are declining across much of their southern geographic range in North America. In Vermont and other northeastern states, measurable declines are attributed to low calf survival and reduced productivity associated with persistent winter tick (Dermacentor albipictus) parasitism. In 2017–2020, we studied 75 radio-collared female moose (38 calves and 37 adults...
Authors
Jacob DeBow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Nicholas Fortin, Katherina Gieder, James Murdoch, Therese Donovan
Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America
Genetic diversity is critical to a population’s ability to overcome gradual environment change. Large-bodied wildlife existing in regions with relatively high human population density are vulnerable to isolation-induced genetic drift, population bottlenecks, and loss of genetic diversity. Moose (Alces americanus americanus) in eastern North America have a complex history of drastic...
Authors
Elias Rosenblatt, Katherina Gieder, Therese Donovan, James Murdoch, Timothy P.L. Smith, Stephanie McKay, Michael P. Heaton, Theodore S. Kalbfleisch, Brenda M. Murdoch, Suraj Bhattarai, Emory Pacht, Emma Verbist, Veronica Basnayake, Stephanie McKay
Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data 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...
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese Donovan
Effects of winter ticks and internal parasites on moose survival in Vermont, USA 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...
Authors
Jacob Debow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Walter Cottrell, James Murdoch, Therese Donovan
Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival 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...
Authors
Elias Rosenblatt, Jacob Debow, Joshua Blouin, Therese 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 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...
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, James Hines, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese Donovan
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
This R code release is associated with the paper, Huber, K., H. Waddle, B. Glorioso, and T. Donovan. Two-stage approach to automatic detection with machine learning for improved surveillance of the invasive Cuban treefrog. Ecological Infomatics. In revision. The code begins by downloading the database released on ScienceBase, and accompanying scripts included in this repository to...
DeepFaune New England DeepFaune New England
This repository contains code for training and running the DeepFaune New England (DFNE) model for species classification in trail camera imagery. This model is a re-trained version of the DeepFaune model for classifying European species in trial cameras, fine-tuned to classify taxa from northeastern North America. The DFNE model takes as input cropped images of each animal, which can be...
AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1 AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1
Amid climate change and rapidly shifting land uses, effective methods for monitoring wildlife are critical to support scientifically-informed resource management decisions. As such, monitoring is motivated by ecological hypotheses or natural resource management objectives. The practice of using Autonomous Monitoring Units (AMUs) such as trail cameras or audio recorders to monitor...
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
Amid climate change and rapidly shifting land uses, effective methods for monitoring natural resources are critical to support scientifically-informed resource management decisions. The practice of using Autonomous Monitoring Units (AMUs) to monitor wildlife species has grown immensely in the past decade, with monitoring projects across species from birds, to bats, amphibians, insects...
occupancyTuts: A package for learning occupancy modeling with RPresence 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...
AMMonitor 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: 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...
Science and Products
Filter Total Items: 24
National Ecological Observatory Network Volume 1 (2024) National Ecological Observatory Network Volume 1 (2024)
This volume's release consists of 31524 media files captured by autonomous wildlife monitoring devices under the project, National Ecological Observatory 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...
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
This volume's release consists of 80 media files captured by autonomous wildlife monitoring devices under the project, USDA Green Mountain National Forest. 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...
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
Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However, false positive detections from ML classifiers can result in erroneous ecological models that can lead to misguided management and conservation actions. We used a two-stage general approach to...
DeepFaune New England - Data DeepFaune New England - Data
DeepFaune New England (DFNE) is a model for species classification in trail camera imagery. This model is a re-trained version of the DeepFaune model for classifying European species in trial cameras, fine-tuned to classify taxa from northeastern North America. The DFNE model takes as input cropped images of each animal, which can be generated by an object detection model. DFNE...
Predicting wildlife distribution patterns in New England USA with expert elicitation techniques 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...
Bureau of Land Management Riverside East Solar Energy Zone Volume 1 Bureau of Land Management Riverside East Solar Energy Zone Volume 1
This volume's release consists of 15184 media files captured by autonomous wildlife monitoring devices under the project, Bureau of Land Management Riverside East Solar Energy Zone. 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...
New Hampshire Fish and Game Department Volume 1 New Hampshire Fish and Game Department Volume 1
This volume's release consists of 463615 media files captured by autonomous wildlife monitoring devices under the project, New Hampshire Fish and Game Department. 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...
Mapping landscape connectivity for moose across the northeastern United States Mapping landscape connectivity for moose across the northeastern United States
Connectivity describes how well a landscape facilitates or impedes the movement of animals. Maximizing connectivity is a common management goal, especially for large mammals like moose (Alces americanus americanus) that occupy large home ranges and have the capacity to move long distances. Moose in the northeastern US (encompassing the states of Vermont, New Hampshire, Massachusetts...
USDA White Mountain National Forest Volume 1 (2014 - 2024) USDA White Mountain National Forest Volume 1 (2014 - 2024)
This volume's release consists of 325099 media files captured by autonomous wildlife monitoring devices under the project, USDA White Mountain National Forest. 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...
Maine Department of Inland Fisheries and Wildlife Moose Project - Volume 2 (2021 - 2024) Maine Department of Inland Fisheries and Wildlife Moose Project - Volume 2 (2021 - 2024)
This volume's release consists of 320104 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...
Massachusetts Wildlife Monitoring Project (2022 - 2024) Massachusetts Wildlife Monitoring Project (2022 - 2024)
This volume's release consists of 143321 media files captured by autonomous wildlife monitoring devices under the project, Massachusetts 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...
USDA Green Mountain National Forest Volume 1 (2016 - 2022) USDA Green Mountain National Forest Volume 1 (2016 - 2022)
This volume's release consists of 84049 media files captured by autonomous wildlife monitoring devices under the project, USDA Green Mountain National Forest. 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...
AMMonitor 2
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
Moose sighting on a trail camera
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.
Filter Total Items: 52
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
The DeepFaune New England model classifies wildlife species in trail camera images, identifying 24 taxa from northeastern North America with high (97%) accuracy. The model was adapted from the DeepFaune model for identifying European wildlife, demonstrating the practicality of transfer learning across continents. The majority of training data is openly licensed, and the model itself is...
Authors
Laurence Clarfeld, Katherine Gieder, Angela Fuller, Zhongqi Miao, Alexej Sirén, Shevenell Webb, Toni Morelli, Jillian Kilborn, Catherine Callahan, Leighlan Prout, Rachel Cliché, Riley Patry, Christopher Bernier, Susan Staats, Therese Donovan
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
Autonomous recording units are increasingly being used to monitor wildlife on large geographic and temporal scales, paired with machine learning (ML) to automate detection of wildlife. However, false positive detections from ML classifiers can result in erroneous ecological models that can lead to misguided management and conservation actions. We used a two-stage general approach to...
Authors
Laurence Clarfeld, Katherina Gieder, Robert Abrams, Christopher Bernier, Joseph Cahill, Susan Staats, Scott Wixsom, Therese Donovan
occupancyTuts: Occupancy modelling tutorials with RPresence occupancyTuts: Occupancy modelling tutorials with RPresence
1. The occupancy modelling framework offers tremendous flexibility in estimating species abundance and distribution patterns while accounting for imperfect detection, and has seen rapid growth and adoption since its introduction at the beginning of the century. 2. At the same time, in an era of big data, there are increasing demands on developing quantitative skills and proficiency in...
Authors
Therese Donovan, James Hines, Darryl MacKenzie
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
U.S. forests, particularly in the eastern states, provide an important offset to greenhouse gas (GHG) emissions. Some have proposed that forest-based natural climate solutions can be strengthened via a number of strategies, including increases in the production of forest biomass energy. We used output from a forest dynamics model (SORTIE-ND) in combination with a GHG accounting tool...
Authors
Michelle Brown, Charles D. Canham, Thomas Buchholz, John Gunn, Therese Donovan
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
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...
Authors
Laurence A. Clarfeld, Alexej P.K. Sirén, Brendan Mulhall, Tammy Wilson, Elena Bernier, John Farrell, Gus Lunde, Nicole Hardy, Katherine Gieder, Robert Abrams, Sue Staats, Scott McLellan, Therese Donovan
Advances in wildlife abundance estimation using pedigree reconstruction Advances in wildlife abundance estimation using pedigree reconstruction
The conservation and management of wildlife populations, particularly for threatened and endangered species are greatly aided with abundance, growth rate, and density measures. Traditional methods of estimating abundance and related metrics represent trade-offs in effort and precision of estimates. Pedigree reconstruction is an emerging, attractive alternate approach because its use of...
Authors
Elias Rosenblatt, Scott Creel, Katherina Gieder, James Murdoch, Therese Donovan
Birth rates and neonate survival in a parasite rich moose population in Vermont, USA Birth rates and neonate survival in a parasite rich moose population in Vermont, USA
Moose (Alces alces) populations are declining across much of their southern geographic range in North America. In Vermont and other northeastern states, measurable declines are attributed to low calf survival and reduced productivity associated with persistent winter tick (Dermacentor albipictus) parasitism. In 2017–2020, we studied 75 radio-collared female moose (38 calves and 37 adults...
Authors
Jacob DeBow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Nicholas Fortin, Katherina Gieder, James Murdoch, Therese Donovan
Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America
Genetic diversity is critical to a population’s ability to overcome gradual environment change. Large-bodied wildlife existing in regions with relatively high human population density are vulnerable to isolation-induced genetic drift, population bottlenecks, and loss of genetic diversity. Moose (Alces americanus americanus) in eastern North America have a complex history of drastic...
Authors
Elias Rosenblatt, Katherina Gieder, Therese Donovan, James Murdoch, Timothy P.L. Smith, Stephanie McKay, Michael P. Heaton, Theodore S. Kalbfleisch, Brenda M. Murdoch, Suraj Bhattarai, Emory Pacht, Emma Verbist, Veronica Basnayake, Stephanie McKay
Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data 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...
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese Donovan
Effects of winter ticks and internal parasites on moose survival in Vermont, USA 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...
Authors
Jacob Debow, Joshua Blouin, Elias Rosenblatt, Cedric Alexander, Katherina Gieder, Walter Cottrell, James Murdoch, Therese Donovan
Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival 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...
Authors
Elias Rosenblatt, Jacob Debow, Joshua Blouin, Therese 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 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...
Authors
Joshua Blouin, Jacob Debow, Elias Rosenblatt, James Hines, Cedric Alexander, Katherina Gieder, Nicholas Fortin, James Murdoch, Therese Donovan
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
This R code release is associated with the paper, Huber, K., H. Waddle, B. Glorioso, and T. Donovan. Two-stage approach to automatic detection with machine learning for improved surveillance of the invasive Cuban treefrog. Ecological Infomatics. In revision. The code begins by downloading the database released on ScienceBase, and accompanying scripts included in this repository to...
DeepFaune New England DeepFaune New England
This repository contains code for training and running the DeepFaune New England (DFNE) model for species classification in trail camera imagery. This model is a re-trained version of the DeepFaune model for classifying European species in trial cameras, fine-tuned to classify taxa from northeastern North America. The DFNE model takes as input cropped images of each animal, which can be...
AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1 AMMonitor: Remote monitoring of biodiversity in an adaptive framework. Version 2.1
Amid climate change and rapidly shifting land uses, effective methods for monitoring wildlife are critical to support scientifically-informed resource management decisions. As such, monitoring is motivated by ecological hypotheses or natural resource management objectives. The practice of using Autonomous Monitoring Units (AMUs) such as trail cameras or audio recorders to monitor...
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
Amid climate change and rapidly shifting land uses, effective methods for monitoring natural resources are critical to support scientifically-informed resource management decisions. The practice of using Autonomous Monitoring Units (AMUs) to monitor wildlife species has grown immensely in the past decade, with monitoring projects across species from birds, to bats, amphibians, insects...
occupancyTuts: A package for learning occupancy modeling with RPresence 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...
AMMonitor 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: 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...