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This dataset contains water quality measurements and snow and ice data from Alaskan beaver ponds collected during the winter as part of the Arctic Beaver Observation Network and NSF ANS #1850578. The Arctic Beaver Observation Network is a 5-year project (2021-2026) funded by the National Science Foundation. The natural science part of the project uses remote sensing to observe the progress and impacts of beaver engineering in the Arctic, starting in Alaska and extending into Canada and Eurasia. The project also establishes field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost, as well as pond evolution documented using Unmanned Aerial Systems (UAS). Remote sensing work will map beaver ponds over time. Field measurements at tundra beaver ponds are made in August and late March. Data generated by field measurements include water level and temperature from pressure-transducers, subsurface imaging from ground-penetrating radar, sonar measurements for beaver pond bathymetry, tabular data associated with water quality measurements, and ice thickness and water depth (in winter). Data is also posted from UAS surveys: annual visible and multi-spectral surveys, as well as snow depth.
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Tapestry Beaver Pond Geochemistry
Major ion geochemistry and isotopes of nitrate for the Tapestry beaver pond in Atlanta, GA. Samples were collected from the surface from June 2019-March 2020 and from the hyporheic zone from June-August 2019. Logger data (DO and specific conductance at 10 minute intervals) were also collected from June-August 2019. Isotopes of nitrate (d15N and d18O) were measured for a subset of June-August 2019 surface and hyporheic samples. Data were used in the paper "Urban beaver dam shows hyporheic exchange helps mediate high nutrient groundwater and a high productivity pond"
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- Award ID(s):
- 2024411
- PAR ID:
- 10625736
- Publisher / Repository:
- HydroShare
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This dataset contains water quality measurements at Alaskan beaver ponds collected during the summer as part of the Arctic Beaver Observation Network and NSF ANS #1850578. The Arctic Beaver Observation Network is a 5-year project (2021-2026) funded by the National Science Foundation. The natural science part of the project uses remote sensing to observe the progress and impacts of beaver engineering in the Arctic, starting in Alaska and extending into Canada and Eurasia. The project also establishes field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost, as well as pond evolution documented using Unmanned Aerial Systems (UAS). Remote sensing work will map beaver ponds over time. Field measurements at tundra beaver ponds are made in August and late March. Data generated by field measurements include water level and temperature from pressure-transducers, subsurface imaging from ground-penetrating radar, sonar measurements for beaver pond bathymetry, tabular data associated with water quality measurements, and ice thickness and water depth (in winter). Data is also posted from UAS surveys: annual visible and multi-spectral surveys, as well as snow depth.more » « less
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This dataset contains water level, water temperature, and barometric pressure at Alaskan beaver ponds collected as part of the Arctic Beaver Observation Network and NSF ANS #1850578. The Arctic Beaver Observation Network is a 5-year project (2021-2026) funded by the National Science Foundation. The natural science part of the project uses remote sensing to observe the progress and impacts of beaver engineering in the Arctic, starting in Alaska and extending into Canada and Eurasia. The project also establishes field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost, as well as pond evolution documented using Unmanned Aerial Systems (UAS). Remote sensing work will map beaver ponds over time. Field measurements at tundra beaver ponds are made in August and late March. Data generated by field measurements include water level and temperature from pressure-transducers, subsurface imaging from ground-penetrating radar, sonar measurements for beaver pond bathymetry, tabular data associated with water quality measurements, and ice thickness and water depth (in winter). Data is also posted from UAS surveys: annual visible and multi-spectral surveys, as well as snow depth.more » « less
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Arctic landscapes are in a state of transition due to changes in climate occurring during both the summer and winter seasons. Scattered observations indicate that beavers (Castor canadensis) have moved from the forest into tundra areas during the last 20 years, likely in response to broader physical and ecosystem changes occurring in Arctic and Boreal regions. The implications of beaver inhabitation in the Arctic and Boreal are unique relative to other ecosystems due to the presence of permafrost and its vulnerability associated with beaver dams and inundation. Our study specifically examines the role of beavers in controlling surface water dynamics and related thermokarst development in low Arctic tundra regions. We mapped the number of beaver dams visible in sub-meter resolution satellite images acquired between 2002 and 2019 for a 100 square kilometer study area (12 years of imagery) near Kotzebue, Alaska and a 430 square kilometer study area (3 years of imagery) encompassing the entire northern Baldwin Peninsula, Alaska. We show that during the last two decades beaver-driven ecosystem engineering is responsible for the majority of surface water area changes and inferred thermokarst development in the study area. This has implications for interpreting surface water area changes and thermokarst dynamics in other Arctic and Boreal regions that may also result from beaver dam building activities. This geospatial dataset provides polygon vector files representing surface water area in a 100 square kilometer study area located near Kotzebue, Alaska. Surface water area maps were created using sub-meter resolution satellite imagery for the years 2002, 2007-2014, and 2017-2019. Image selection focused on cloud-free, ice-free, and calm surface water conditions with images being acquired between late-June and mid-August in a given year. All images were resampled to a spatial resolution of 70 centimeter to match the lowest resolution image in the time series prior to analysis. Within year image dates range from 25 June to 22 August with the average date of image acquisition being 17 July (table 1). Object-based image analysis was conducted in eCognition Essentials 1.3.more » « less
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