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National Park Service Northeast Region Deer Spotlight Monitoring, 2024-2025 Cumulative Data Package
Overabundant deer have harmful effects on forests by preventing regeneration of a number of important canopy tree species, and by preferentially browsing certain native species while avoiding invasive plants. Left unchecked, the combination of deer and invasive species can eliminate forests entirely, transforming them into invasive shrub thickets. Overabundant deer are also a human health risk, through the increased risk of deer-vehicle collisions and because of increased prevalence of tick-borne illnesses. The Northeast Region of the National Park Service is working to encourage resilient forests by managing overabundant deer, removing invasive species, and taking other actions such as planting climate-resilient tree species in key areas. An important part of this Resilient Forests Initiative is monitoring deer. Monitoring is used to determine where the populations are in need of intervention and to track the impacts of management actions. Multiple monitoring methods are possible depending on the park, including aerial forward-looking infrared surveys, camera traps, and spotlighting (with visible or infrared light). This data set represents the spotlight data collected at multiple parks in the Northeastern United States, including Gateway National Recreation Area (GATE), Marsh-Billings-Rockefeller National Historical Park (MABI), Morristown National Historical Park (MORR), Richmond National Battlefield Park (RICH), and Saratoga National Historical Park (SARA). The methods used are based on a protocol developed by the Heartland Inventory & Monitoring Network, and they produce two types of data: 1) bearings and distances to deer seen from a vehicle driving a route through the park, and 2) visibility information denoting how far observers feel they could see deer, taken every 0.05 mile (0.13 km) along the route. Visibility in some years is collected in two separate surveys with 0.10 mi intervals, with the second survey start point offset by 0.05 mi. Monitoring Objective: Estimate deer abundance (an index that approximates the number of deer per square mile) in the surveyed area with sufficient accuracy to support management decision-making. This data package contains a cumulative record of all monitoring data collected at the participating parks through the most recent field season and is organized into three (3) datasets: Deer_Locations_Cumulative_YYYY-MM-DD.csv - processed deer survey event data, including the raw data plus calculated locations of deer. Incidental observations are not included in this data set. Deer_VisibleArea_Cumulative_YYYY-MM-DD.csv - processed visibility survey event data, including the raw data plus calculated coordinates for the limit of visibility on either side of the vehicle. The limits of visibility are used to create a polygon in a Geographic Information System to estimate the area surveyed for each monitoring season and park. Incidental_Sightings_Cumulative_YYYY-MM-DD.csv - Incidental sightings of species other than deer that are recorded during the survey, including count, species, and observer location. Note that the date at the end of each data file represents the date that the dataset was last updated.
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Adirondack Inventory & Monitoring (AIM) Network Data Release Volume 1 (2021 - 2023)
공공데이터포털
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 files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans or by machine learning models, identifying wildlife targets within the media. If so, this information is stored in "annotations.csv" and "modeloutputs.csv", respectively. To protect privacy, all personally identifiable information (PII) have been removed, locations have been "blurred" by bounding boxes, and media featuring sensitive taxa or humans have been omitted. To enhance data reuse, the sbRehydrate() function in the AMMonitor R package will download files and re-create the original AMMonitor project (database + media files). See source code at https://code.usgs.gov/vtcfwru/ammonitor.
Adirondack Inventory & Monitoring (AIM) Network Data Release Volume 1 (2021 - 2023)
공공데이터포털
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 files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans or by machine learning models, identifying wildlife targets within the media. If so, this information is stored in "annotations.csv" and "modeloutputs.csv", respectively. To protect privacy, all personally identifiable information (PII) have been removed, locations have been "blurred" by bounding boxes, and media featuring sensitive taxa or humans have been omitted. To enhance data reuse, the sbRehydrate() function in the AMMonitor R package will download files and re-create the original AMMonitor project (database + media files). See source code at https://code.usgs.gov/vtcfwru/ammonitor.
Maine Department of Inland Fisheries and Wildlife Volume 1 (2022 - 2023)
공공데이터포털
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 files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans or by machine learning models, identifying wildlife targets within the media. If so, this information is stored in "annotations.csv" and "modeloutputs.csv", respectively. To protect privacy, all personally identifiable information (PII) have been removed, locations have been "blurred" by bounding boxes, and media featuring sensitive taxa or humans have been omitted. To enhance data reuse, the sbRehydrate() function in the AMMonitor R package will download files and re-create the original AMMonitor project (database + media files). See source code at https://code.usgs.gov/vtcfwru/ammonitor.
Maine Department of Inland Fisheries and Wildlife Volume 1 (2022 - 2023)
공공데이터포털
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 files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans or by machine learning models, identifying wildlife targets within the media. If so, this information is stored in "annotations.csv" and "modeloutputs.csv", respectively. To protect privacy, all personally identifiable information (PII) have been removed, locations have been "blurred" by bounding boxes, and media featuring sensitive taxa or humans have been omitted. To enhance data reuse, the sbRehydrate() function in the AMMonitor R package will download files and re-create the original AMMonitor project (database + media files). See source code at https://code.usgs.gov/vtcfwru/ammonitor.
USDA Green Mountain National Forest Volume 1 (2016 - 2022)
공공데이터포털
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 housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields in other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans or by machine learning models, identifying wildlife targets within the media. If so, this information is stored in "annotations.csv" and "modeloutputs.csv", respectively. To protect privacy, all personally identifiable information (PII) have been removed, locations have been "blurred" by bounding boxes, and media featuring sensitive taxa or humans have been omitted. To enhance data reuse, the sbRehydrate() function in the AMMonitor R package will download files and re-create the original AMMonitor project (database + media files). See source code at https://code.usgs.gov/vtcfwru/ammonitor.
White-tailed Deer Monitoring for the Heartland Inventory and Monitoring Network: 2005-2023 - Data Package
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This dataset consists of occurrence observations for white-tailed deer in the National Park Service Heartland Inventory and Monitoring Network Parks. Because of their impacts on vegetation, disease transmission, visitor health, and vehicle-deer collisions, park managers at Arkansas Post National Memorial, Pea Ridge National Military Park, and Wilson’s Creek National Battlefield identified white-tailed deer as a vital sign for monitoring. Monitoring white-tailed deer populations better positions park management to take action to mitigate concerns involving deer. The overall goals of HTLN white-tailed deer monitoring are to 1) document annual changes in the number of white-tailed deer, as changes could signal presence of illegal deer harvest, disease, or other acute factors of concern for park management; 2) document long-term trends in the number of white-tailed deer to help park management determine if measures need to be taken to maintain herd health, minimize vegetation damage within a park, or alleviate visitor health concerns; and 3) annually map locations of white-tailed deer observed to assist park management in assessing the influences of management actions on deer usage of an area, habitat type, etc.
White-tailed Deer Monitoring for the Heartland Inventory and Monitoring Network: 2005-2023 - Data Package
공공데이터포털
This dataset consists of occurrence observations for white-tailed deer in the National Park Service Heartland Inventory and Monitoring Network Parks. Because of their impacts on vegetation, disease transmission, visitor health, and vehicle-deer collisions, park managers at Arkansas Post National Memorial, Pea Ridge National Military Park, and Wilson’s Creek National Battlefield identified white-tailed deer as a vital sign for monitoring. Monitoring white-tailed deer populations better positions park management to take action to mitigate concerns involving deer. The overall goals of HTLN white-tailed deer monitoring are to 1) document annual changes in the number of white-tailed deer, as changes could signal presence of illegal deer harvest, disease, or other acute factors of concern for park management; 2) document long-term trends in the number of white-tailed deer to help park management determine if measures need to be taken to maintain herd health, minimize vegetation damage within a park, or alleviate visitor health concerns; and 3) annually map locations of white-tailed deer observed to assist park management in assessing the influences of management actions on deer usage of an area, habitat type, etc.
Booderee National Park trends in mammal abundance
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A fox control program has been in place in Booderee National Park since 1999 with baiting occurring twice a year. From 2003 onwards baiting has been intensified, with baiting occurring once a month. Since 2003 monitoring has been undertaken to track trends in distribution and abundance of small-medium sized mammal species, in response to fox control. The dataset contains data on mammal species and numbers trapped in Booderee National Park, as well as a record of sex, weight, pes length, and presence of pouch young.
NCCN Elk LEWI Monitoring Data Package, 2008-2024
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This data package contains elk monitoring data collected under the auspices of the North Coast and Cascades Network (NCCN) Inventory and Monitoring Program during 2008-2024 at Lewis and Clark National Historical Park (LEWI). The monitoring protocol, publications, and all other associated links can be found in the project reference at: NCCN Monitoring Elk Ground (Lewis and Clark National Historical Park), https://irma.nps.gov/DataStore/Reference/Profile/2182083 Monitoring was initiated to track Roosevelt elk seasonal use and visitor viewing opportunities in and around the Fort Clatsop unit of Lewis and Clark National Historical Park (LEWI). The preservation of elk herds that frequent LEWI is central to the park’s purpose, “to preserve … the historic, cultural, scenic, and natural resources associated with the arrival of the Lewis and Clark Expedition in the lower Columbia River area, and … commemorating the culmination and the winter encampment of the Lewis and Clark Expedition in the winter of 1805-1806 …” (Public Law 108-387). Today, elk viewing opportunities in the park and surrounding Clatsop Plains region generate broad appeal with the visiting public. Elk range widely outside of park boundaries where habitat conditions are affected by urbanization, forest management, and agricultural practices, and where populations and behaviors of elk are influenced by hunting patterns, other human disturbance factors, and habitat change. Staff at LEWI have used data generated by elk monitoring to build community partnerships, to highlight regional habitat and land use planning effects on park resources, and to inform regional discussions of policies that may influence the park’s elk population. The primary monitoring objectives of the protocol are to measure the relative use and proportion of area used by elk during winter in the Fort Clatsop Unit of the park, and the rate at which elk are sighted from roads in and around the Fort Clatsop unit of . Relative use and the proportion of area used by elk are determined from annual elk fecal pellet surveys, wherein pairs of observers visit a systematic array of permanent plots in the fall to clear them of elk fecal pellets, and return to the plots in late winter to count elk fecal pellets that have accumulated during winter. Standardized road surveys are conducted in and near the Fort Clatsop park unit three or four times monthly during alternate months, where two observers drive four routes to record numbers of elk, location, and composition of each group observed. Data from road surveys are used to provide an index of elk viewing opportunities for park visitors along the selected set of routes.
White-tailed Deer Monitoring for the Heartland Inventory and Monitoring Network: 2005-2023 - Raw Data
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Raw data for the White-tailed Deer Monitoring for the Heartland Inventory and Monitoring Network: 2005-2023 datasets.
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