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Knowledge of snow cover distribution and disappearance dates over a wide range of scales is imperative for understanding hydrological dynamics and for habitat management of wildlife species that rely on snow cover. Identification of snow refugia, or places with relatively late snow disappearance dates (SDDs) compared to surrounding areas, is especially important as climate change alters snow cover timing and duration. The purpose of this study was to increase understanding of snow refugia in complex terrain spanning the rain-snow transition zone at fine spatial and temporal scales. To accomplish this objective, we used remote cameras to provide relatively high temporal and spatial resolution measurements on snowpack...
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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...
Categories: Data,
Publication;
Types: Citation;
Tags: Idaho,
Latah,
Moscow Mountain,
Odocoileus virginianus,
biota, All tags...
climatologyMeteorologyAtmosphere,
environment,
mule deer,
snow,
snow and ice cover,
snow depth,
snow disappearance date,
snow-dependent,
white-tailed deer, Fewer tags
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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...
Categories: Data,
Publication;
Types: Citation;
Tags: Idaho,
Latah,
Moscow Mountain,
Odocoileus hemionus,
Odocoileus virginianus, All tags...
camera trap,
location,
mule deer,
snow,
snow and ice cover,
snow density,
snow depth,
snow disappearance date,
snow presence,
snow-dependent,
white-tailed deer, Fewer tags
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UI_Mica_Location: Location metadata and meteorological and snow depth observations from met towers in the Mica Creek Experimental Forest. Data were collected at 7 different station sites at approximately half-hour intervals for water years 2003-2006, with discontinuous records due to equipment malfunction or damage. Stations were located within different forest harvest treatment sections, applied to the watershed in approximately 2001, including clear-cut harvest, partial harvest, and control sections (both second growth and old growth control forests). Site Data Citation for full description of the field campaign and sites. UI_Mica_met: Metadata and associated snow depth and SWE observations from 14 manual...
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Data Visualization & Tools,
Forests,
Idaho,
Landscapes,
Mica Creek, All tags...
Northwest CASC,
Other Water,
Science Tools For Managers,
Shoshone County,
Water, Coasts and Ice,
forest canopy density,
meteorological observations,
snow depth,
snow observations,
time-lapse photography, Fewer tags
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Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera‐based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used...
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