Tammy L. Wilson, PhD
Assistant Unit Leader - Massachusetts Cooperative Fish and Wildlife Research Unit
Dr. Wilson received a BA from the University of Colorado, and graduate degrees from Utah State University. Prior to joining USGS, she was a Biometrician with the National Park Service Southwest Alaska Inventory and Monitoring Program. Dr. Wilson is an applied quantitative ecologist interested in the responses of wildlife to anthropogenic change. Her research focuses on the application of statistical models to determine species distribution, abundance, and habitat selection at multiple scales. She applies this work to support science-based decision-making in wildlife management and conservation. Although she mainly works on birds and mammals in upland habitats, she occasionally gets her feet wet to work on fish and marine invertebrates. Dr. Wilson teaches courses that improve students understanding of nature through quantitative ecology. This includes teaching advanced topics in landscape ecology, biometrics, and spatial modeling. She is committed to future that embraces and represents the full diversity of our nation so that all can feel inspiration and awe in nature.
Professional Experience
Assistant Unit Leader - Massachusetts Cooperative Fish and Wildlife Research Unit, 2020
Education and Certifications
PhD., Utah State University, 2010
M.S., Utah State University, 2005
B.A., University of Colorado, 1994
Science and Products
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 files are
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 files are ho
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 actual medi
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 media files
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 files are hou
Vermont Fish and Wildlife Department Volume 1 (2014 - 2022)
This volume's release consists of 41933 media files captured by autonomous wildlife monitoring devices under the project, Vermont Fish and Wildlife 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 files are ho
Winter tick counts and covariates in Massachusetts and New Hampshire from fall 2022
The dataset accompanies manuscript: "Monitoring off-host winter tick abundance on traditional moose hunting lands" . It is a single table that includes counts of winter tick (Dermacentor albipictus) obtained by a modified flagging technique developed by the Penobscot Nation. The table includes both detection and site covariates used for the data analyses presented in the paper. Data were collected
Monitoring questing winter tick abundance on traditional moose hunting lands
An important symbolic and subsistence animal for many Native American Tribes, the moose (Alces alces; mos in Algonquin, Penobscot language) has been under consistent threat in the northeastern United States because of winter tick (Dermacentor albipictus) parasitism over the past several decades, causing declines in moose populations throughout the region. This decline has raised concern for Tribes
Authors
Juliana Berube, Alexej P. K. Sirén, Benjamin Simpson, Kelly B. Klingler, Tammy L. Wilson
Accounting for missing ticks: Use (or lack thereof) of hierarchical models in tick ecology studies
Ixodid (hard) ticks play important ecosystem roles and have significant impacts on animal and human health via tick-borne diseases and physiological stress from parasitism. Tick occurrence, abundance, activity, and key life-history traits are highly influenced by host availability, weather, microclimate, and landscape features. As such, changes in the environment can have profound impacts on ticks
Authors
Alexej P.K. Sirén, Juliana Berube, Laurence A. Clarfeld, Cheryl F. Sullivan, Benjamin Simpson, Tammy L. Wilson
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
Authors
Laurence A. Clarfeld, Alexej P.K. Sirén, Brendan M. Mulhall, Tammy L. Wilson, Elena Bernier, John Farrell, Gus Lunde, Nicole Hardy, Katherine D. Gieder, Robert Abrams, Sue Staats, Scott McLellan, Therese M. Donovan
Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands
Mercury (Hg) is a widespread element and persistent pollutant, harmful to fish, wildlife, and humans in its organic, methylated form. The risk of Hg contamination is driven by factors that regulate Hg loading, methylation, bioaccumulation, and biomagnification. In remote locations, with infrequent access and limited data, understanding the relative importance of these factors can pose a challenge.
Authors
Krista K. Bartz, Michael P. Hannam, Tammy L. Wilson, Ryan F. Lepak, Jacob M. Ogorek, Daniel B. Young, Collin A. Eagles-Smith, David P. Krabbenhoft
The mysterious case of the missing razor clams
Oceans are changing and these changes are affecting animals that live there. Animals respond differently to changes in water temperature, food availability, or contaminants. Those responses can be seen in their genes. Gene transcription is a tool that allows scientists to see the response of an animal’s genes to its environment. We used gene transcription to compare two populations of Pacific razo
Authors
Heather Coletti, Lizabeth Bowen, Brenda Ballachey, Tammy L. Wilson, Shannon C. Waters, Michael Booz, Katrina Counihan, Tuula E. Hollmen, Benjamin Pister
Gene expression profiles in two razor clam populations: Discerning drivers of population status
With rapidly changing marine ecosystems, shifts in abundance and distribution are being documented for a variety of intertidal species. We examined two adjacent populations of Pacific razor clams (Siliqua patula) in lower Cook Inlet, Alaska. One population (east) supported a sport and personal use fishery, but this has been closed since 2015 due to declines in abundance, and the second population
Authors
Heather A. Coletti, Lizabeth Bowen, Brenda Ballachey, Tammy L. Wilson, Shannon C. Waters, Michael Booz, Katrina L Counihan, Tuula E. Hollmen, Benjamin Pister
Science and Products
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 files are
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 files are ho
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 actual medi
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 media files
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 files are hou
Vermont Fish and Wildlife Department Volume 1 (2014 - 2022)
This volume's release consists of 41933 media files captured by autonomous wildlife monitoring devices under the project, Vermont Fish and Wildlife 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 files are ho
Winter tick counts and covariates in Massachusetts and New Hampshire from fall 2022
The dataset accompanies manuscript: "Monitoring off-host winter tick abundance on traditional moose hunting lands" . It is a single table that includes counts of winter tick (Dermacentor albipictus) obtained by a modified flagging technique developed by the Penobscot Nation. The table includes both detection and site covariates used for the data analyses presented in the paper. Data were collected
Monitoring questing winter tick abundance on traditional moose hunting lands
An important symbolic and subsistence animal for many Native American Tribes, the moose (Alces alces; mos in Algonquin, Penobscot language) has been under consistent threat in the northeastern United States because of winter tick (Dermacentor albipictus) parasitism over the past several decades, causing declines in moose populations throughout the region. This decline has raised concern for Tribes
Authors
Juliana Berube, Alexej P. K. Sirén, Benjamin Simpson, Kelly B. Klingler, Tammy L. Wilson
Accounting for missing ticks: Use (or lack thereof) of hierarchical models in tick ecology studies
Ixodid (hard) ticks play important ecosystem roles and have significant impacts on animal and human health via tick-borne diseases and physiological stress from parasitism. Tick occurrence, abundance, activity, and key life-history traits are highly influenced by host availability, weather, microclimate, and landscape features. As such, changes in the environment can have profound impacts on ticks
Authors
Alexej P.K. Sirén, Juliana Berube, Laurence A. Clarfeld, Cheryl F. Sullivan, Benjamin Simpson, Tammy L. Wilson
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
Authors
Laurence A. Clarfeld, Alexej P.K. Sirén, Brendan M. Mulhall, Tammy L. Wilson, Elena Bernier, John Farrell, Gus Lunde, Nicole Hardy, Katherine D. Gieder, Robert Abrams, Sue Staats, Scott McLellan, Therese M. Donovan
Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands
Mercury (Hg) is a widespread element and persistent pollutant, harmful to fish, wildlife, and humans in its organic, methylated form. The risk of Hg contamination is driven by factors that regulate Hg loading, methylation, bioaccumulation, and biomagnification. In remote locations, with infrequent access and limited data, understanding the relative importance of these factors can pose a challenge.
Authors
Krista K. Bartz, Michael P. Hannam, Tammy L. Wilson, Ryan F. Lepak, Jacob M. Ogorek, Daniel B. Young, Collin A. Eagles-Smith, David P. Krabbenhoft
The mysterious case of the missing razor clams
Oceans are changing and these changes are affecting animals that live there. Animals respond differently to changes in water temperature, food availability, or contaminants. Those responses can be seen in their genes. Gene transcription is a tool that allows scientists to see the response of an animal’s genes to its environment. We used gene transcription to compare two populations of Pacific razo
Authors
Heather Coletti, Lizabeth Bowen, Brenda Ballachey, Tammy L. Wilson, Shannon C. Waters, Michael Booz, Katrina Counihan, Tuula E. Hollmen, Benjamin Pister
Gene expression profiles in two razor clam populations: Discerning drivers of population status
With rapidly changing marine ecosystems, shifts in abundance and distribution are being documented for a variety of intertidal species. We examined two adjacent populations of Pacific razor clams (Siliqua patula) in lower Cook Inlet, Alaska. One population (east) supported a sport and personal use fishery, but this has been closed since 2015 due to declines in abundance, and the second population
Authors
Heather A. Coletti, Lizabeth Bowen, Brenda Ballachey, Tammy L. Wilson, Shannon C. Waters, Michael Booz, Katrina L Counihan, Tuula E. Hollmen, Benjamin Pister