The National Park Service (NPS) Arctic Network (ARCN) Inventory and Monitoring (I&M) program monitors physical and natural resources in the National Park lands of Alaska including Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park and Noatak National Preserve. Terrestrial Vegetation and Soils is one of the systems chosen by ARCN for long term scientific monitoring in the Parks. I&M has committed to the highest ideals of data quality by monitoring natural systems in the same way, year after year according to published protocols with the goal of providing reliable scientific information to Park managers . The heart of the data management system for the Terrestrial Vegetation and Soils monitoring program is a Microsoft SQL Server relational database which allows Arctic Network to meet its paramount duty: assuring the security, accessibility and longevity of the monitoring data into the future. In May, 2025 Arctic Network anticipates reductions in the federal work force that threaten the continued support and maintenance of this database. Consequently, Arctic Network is immediately publishing a snapshot of the Terrestrial Vegetation and Soils monitoring database as an emergency step in assuring the data remain available to the public despite the uncertainty of I&M’s future. This report documents the Terrestrial Vegetation and Soils database export files and their contents. Methods Methods are not described in this report but are fully documented and publicly available in the Terrestrial Vegetation and Soils monitoring protocol and standard operating procedures (Table 1). Table 1. Links to background resources. Website https://www.nps.gov/im/arcn/vegsoils.htm ProjectReference https://irma.nps.gov/DataStore/Reference/Profile/2220078 Data Quality The data records in this release are provided ‘as-is’. Inventory and Monitoring data typically goes through a value-adding life cycle where data are collected, processed for quality, validated and then certified for analytical use. Under ideal circumstances I&M policy is to only publish fully certified and documented datasets. Due to the urgency with which these data are being published the user should recognize that some or all of the records in this data release may not have been shepherded through all quality control steps, and may or may not contain accurate indicators of quality. Arctic Network is publishing data of unconstrained quality in the belief that it will serve the public interest more than withholding the data entirely. Authority U.S. Government Works. Data and content created by government employees within the scope of their employment are not subject to domestic copyright protection under 17 U.S.C. 105. Government works are by default in the U.S. Public Domain. Database Metadata See the MetadataTables and MetadataColumns database tables for descriptions.

Brief Description: soils landscape geodatabase for Wrangell St. Elias Full Description: The Soil Resources Inventory (SRI) includes maps of the locations and extent of soils in a park; data about the physical, chemical, and biological properties of those soils; and information regarding the potential use and management of each soil. SRI data are intended to serve as the as the official database for all agency applications regarding soil resources.

Tabular data set summarizing detection and location of invasive plants on islands in Alaska Maritime National Wildlife Refuge between July 14, 2024 and July 31, 2024. Data has been reformatted from its original format to align with the Alaska Exotic Plants Information Clearinghouse (AKEPIC; https://accs.uaa.alaska.edu/invasive-species/non-native-plants/) submission template.

30 meter pixel grid data set with 1302 grid values and associated land cover attributes representing the land cover classes mapped during the KATM Land Cover Mapping Project (2000-2002)

Soil landscape inventory product for Aniakchak National Monument and Preserve. Full Description: The Soil Resources Inventory (SRI) includes maps of the locations and extent of soils in a park; data about the physical, chemical, and biological properties of those soils; and information regarding the potential use and management of each soil. SRI data are intended to serve as the as the official database for all agency applications regarding soil resources.

Soil landscape inventory product for Aniakchak National Monument and Preserve. Full Description: The Soil Resources Inventory (SRI) includes maps of the locations and extent of soils in a park; data about the physical, chemical, and biological properties of those soils; and information regarding the potential use and management of each soil. SRI data are intended to serve as the as the official database for all agency applications regarding soil resources.

Tabular datasets relating to invasive species detections in the northern Alaskan area. Data pertain to invasive species surveys conducted on the Arctic, Tetlin, and Kanuti National Wildlife Refuges by the Alaskan Invasive Species Program teams. Data were collected using a Survey123 form. Data were subsequently downloaded from the ArcGIS feature layer and manual quality control was performed at the end of each season by the project lead. Data were then reformatted to align with the AKEPIC data submission template (https://accs.uaa.alaska.edu/invasive-species/submit-data-to-akepic/) for submitting detection of invasive species information into the Alaska Exotic Plants Information Clearinghouse (AKEPIC) designed and run by the University of Alaska Anchorage (UAA) Alaska Center for Conservation Science (ACCS).

Exotic plant inventory in Mount Rainier, North Cascades, and Olympic National Parks 2001-2002 tabular data. We focused our survey on habitats most susceptible to exotic plant invasion within the three parks. Susceptible habitats were defined as areas that provided both good substrates for exotic plant establishment and where there was a high probability of exotic seed dispersal. Using this definition, we identified four habitats for surveys: roads, trails, riparian areas (i.e., rivers), and developed zones. The objectives for these inventories were to: 1) document exotic plant species that occur in susceptible habitats in each park, 2) describe distribution and abundance patterns of exotic plant species across vulnerable habitats, 3) identify habitats with the greatest exotic species richness, 4) identify patterns of exotic species richness with respect to elevation and distance from trailhead, and 5) identify priority exotic species for control based on biologic and management considerations. We utilized a two stage sampling design. The first stage or strata was composed of the four sensitive habitats: roads, trails, riparian areas and developed zones. All four habitat types were identified in GIS. Within our four habitats, we included all developed zones on park owned land (i.e., no privately owned lands), all roads, all park maintained trails (i.e., no social or informal trails), and riparian areas with a slope ≤ 8% (safe access for field crews). Roads, trails, and riparian areas were considered to be linear features and were divided into segments along which subsamples (i.e., plots) were distributed. All segments were ≤ 5 miles in length and we generally utilized junctions with other trails, roads, or rivers to identify segments so that the segments could easily be identified in the field. Roads and trails had a minimum segment length of 0.5 miles and riparian areas had a minimum length of 1.0 miles. Segments were numbered within each strata and then randomly selected for sampling. After a random placement of the first plot within the first 0.5 miles of the randomly selected segment, plots were systematically distributed every mile within the road, trail, and riparian segments which had been randomly selected. All plots or subsamples covered an area of 100 m2 however, the dimensions and distribution of the plots varied depending on habitat type. Road and trail plots were 1m x 100 m and were established parallel to the road or trail. The first plot was located on the right or left side of the trail based on a coin toss and successive plots alternated sides. Riparian plots were also 100 m2, but plot dimensions varied based on the terrain in order to locate the entire plot within the riparian zone. Crew members determined the plot dimensions when they arrived at the plot location. Frequently, plots were square (i.e., 10m x 10m), but when rectangular plots were used, they were oriented perpendicular to the river to capture variation in plant distribution within the riparian area. Developed zone plots were 10m x 10 m and were located relative to a random location generated in the GIS. We surveyed 697 plots across the three parks and documented 112 exotic species in 348 (~50%) of the plots. We documented 42 species in MORA, 64 at NOCA, and 81 in OLYM. At all three parks, exotic species richness was generally highest in plots located in roadsides or developed zones. Our study documented 8 species that were not on the parks’ comprehensive online species lists (NPSpecies 2016): 2 at MORA and 6 at OLYM. Although we did not document any new species at NOCA, our study provided previously unavailable abundance information for that park.

Exotic plant inventory in Mount Rainier, North Cascades, and Olympic National Parks 2001-2002 tabular data. We focused our survey on habitats most susceptible to exotic plant invasion within the three parks. Susceptible habitats were defined as areas that provided both good substrates for exotic plant establishment and where there was a high probability of exotic seed dispersal. Using this definition, we identified four habitats for surveys: roads, trails, riparian areas (i.e., rivers), and developed zones. The objectives for these inventories were to: 1) document exotic plant species that occur in susceptible habitats in each park, 2) describe distribution and abundance patterns of exotic plant species across vulnerable habitats, 3) identify habitats with the greatest exotic species richness, 4) identify patterns of exotic species richness with respect to elevation and distance from trailhead, and 5) identify priority exotic species for control based on biologic and management considerations. We utilized a two stage sampling design. The first stage or strata was composed of the four sensitive habitats: roads, trails, riparian areas and developed zones. All four habitat types were identified in GIS. Within our four habitats, we included all developed zones on park owned land (i.e., no privately owned lands), all roads, all park maintained trails (i.e., no social or informal trails), and riparian areas with a slope ≤ 8% (safe access for field crews). Roads, trails, and riparian areas were considered to be linear features and were divided into segments along which subsamples (i.e., plots) were distributed. All segments were ≤ 5 miles in length and we generally utilized junctions with other trails, roads, or rivers to identify segments so that the segments could easily be identified in the field. Roads and trails had a minimum segment length of 0.5 miles and riparian areas had a minimum length of 1.0 miles. Segments were numbered within each strata and then randomly selected for sampling. After a random placement of the first plot within the first 0.5 miles of the randomly selected segment, plots were systematically distributed every mile within the road, trail, and riparian segments which had been randomly selected. All plots or subsamples covered an area of 100 m2 however, the dimensions and distribution of the plots varied depending on habitat type. Road and trail plots were 1m x 100 m and were established parallel to the road or trail. The first plot was located on the right or left side of the trail based on a coin toss and successive plots alternated sides. Riparian plots were also 100 m2, but plot dimensions varied based on the terrain in order to locate the entire plot within the riparian zone. Crew members determined the plot dimensions when they arrived at the plot location. Frequently, plots were square (i.e., 10m x 10m), but when rectangular plots were used, they were oriented perpendicular to the river to capture variation in plant distribution within the riparian area. Developed zone plots were 10m x 10 m and were located relative to a random location generated in the GIS. We surveyed 697 plots across the three parks and documented 112 exotic species in 348 (~50%) of the plots. We documented 42 species in MORA, 64 at NOCA, and 81 in OLYM. At all three parks, exotic species richness was generally highest in plots located in roadsides or developed zones. Our study documented 8 species that were not on the parks’ comprehensive online species lists (NPSpecies 2016): 2 at MORA and 6 at OLYM. Although we did not document any new species at NOCA, our study provided previously unavailable abundance information for that park.

Geodatabase used to collect exotic plan management data for upload to NISIMS