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Remote camera data on snow presence, snow depth, and wildlife detections on Moscow Mountain in Latah County, ID, USA. Reconyx Hyperfire I and Hyperfire II cameras were used and set to take hourly timelapse images and motion-triggered images. The cameras were deployed from October 2020 - May 2021. Snow presence was assessed up to 15 m from the camera. Snow depth was measured using virtual snow stakes created with the edger R package created by the author. Wildlife were marked as present in all photos in which they appear, and new individuals were counted. Snow density was collected using a federal or prairie snow sampler. Snow hardness was collected using a ram penetrometer. Solar radiation was calculated using hemispherical...
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We collected snow density measurements at camera sites from December 2020 - April 2021, at the same time as snow hardness measurements. We took measurements every few weeks as logistics allowed. We took samples near the camera site in snow visually similar to the snow in the camera viewshed (the geographical area that is visible from a location) to prevent snow conditions from being disturbed beyond normal camera deployment. We took snow density samples using a homemade prairie sampler in snow depths < 100 cm and using a federal snow sampler in snow depths > 100 cm. The sampler was inserted into the snow to remove a snow core. We retained the core if the depth of snow in the sampler was at least 90% of the actual...
This project will focus on integrating existing riverine/riparian landscape analyses to support decision making by the Arid Lands Initiative and associated partners in the Columbia Basin Partner Forum. This synthesis will produce a map of priority areas for the riparian and riverine landscape, and will include a stressors and threats analysis, with an assessment of resiliency to climate change. We will also complete the first phase of a multi-year project to develop an ecological systems classification for riverine1 systems in the Columbia Basin.
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Cheatgrass began invading the Great Basin about 100 years ago, changing large parts of the landscape from a rich, diverse ecosystem to one where a single invasive species dominates. Cheatgrass dominated areas experience more fires that burn more land than in native ecosystems, resulting in economic and resource losses. Therefore, the reduced production, or absence, of cheatgrass in previously invaded areas during years of adequate precipitation could be seen as a windfall. However, this cheatgrass dieoff phenomenon creates other problems for land managers like accelerated soil erosion, loss of early spring food supply for livestock and wildlife, and unknown recovery pathways. We used satellite data and scientific...
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Mean modeled snow-water-equivalent (meters) on February 20, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
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UW_Olallie_photo_metadata & image files: These are the raw timelapse photographs. The date/time stamp is inaccurate for the camera deployed in the open (at the SNOTEL) due to a programming error. This timestamp is one day early (i.e., subtract 1 day from the timestamp when using these data). Also available is metadata for two timelapse cameras and their associated snow depth poles (two visible in each camera's field of view) deployed at Olallie Meadows SNOTEL during water year 2015. One camera was deployed in the open area that is the Olallie Meadows SNOTEL station (the snow pillow is in the field of view). The other camera was deployed in the adjacent forest, approximately 60 m to the southeast of the SNOTEL....
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The percentage difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
Abstract (from http://www.nature.com/articles/srep24441): The 170 National Forests and Grasslands (NFs) in the conterminous United States are public lands that provide important ecosystem services such as clean water and timber supply to the American people. This study investigates the potential impacts of climate change on two key ecosystem functions (i.e., water yield and ecosystem productivity) using the most recent climate projections derived from 20 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 5 (CMIP5). We find that future climate change may result in a significant reduction in water yield but an increase in ecosystem productivity in NFs. On average, gross ecosystem productivity...
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Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of prediction from the statistical model averaged 3.7%, but for individual biomes, ranged from 0% to 21.5%. In validating the ability of the model to identify climates without analogs, 78% of 1528 locations outside North America and 81% of land area of the Caribbean Islands were predicted to have no analogs among the 46 biomes. Biome climates were projected...
map background search result map search result map Modeling Effects of Climate Change on Cheatgrass Die-Off Areas in the Northern Great Basin Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 North American vegetation model data for land-use planning in a changing climate: Snow Density Measurements at Remote Camera Stations on Moscow Mountain in Latah County, ID (12/1/20-4/30/21) Environmental Data at Remote Camera Stations on Moscow Mountain in Latah County, ID, USA (10/20/20-5/30/21) FY 2023 Projects Timelapse photos at SNOTEL station, locations, and associated metadata, Ollalie Meadows, Wash., 2015 Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeling Effects of Climate Change on Cheatgrass Die-Off Areas in the Northern Great Basin North American vegetation model data for land-use planning in a changing climate: