scholarly journals Quantifying effects of snow depth on caribou winter range selection and movement in Arctic Alaska

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Stine Højlund Pedersen ◽  
Torsten W. Bentzen ◽  
Adele K. Reinking ◽  
Glen E. Liston ◽  
Kelly Elder ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Snow Depth ◽  
The Arctic ◽  
Integrative Approach ◽  
Brooks Range ◽  
Winter Range ◽  
Depth Data ◽  
Arctic Alaska ◽  
Selection Of ◽  
Range Selection

Abstract Background Caribou and reindeer across the Arctic spend more than two thirds of their lives moving in snow. Yet snow-specific mechanisms driving their winter ecology and potentially influencing herd health and movement patterns are not well known. Integrative research coupling snow and wildlife sciences using observations, models, and wildlife tracking technologies can help fill this knowledge void. Methods Here, we quantified the effects of snow depth on caribou winter range selection and movement. We used location data of Central Arctic Herd (CAH) caribou in Arctic Alaska collected from 2014 to 2020 and spatially distributed and temporally evolving snow depth data produced by SnowModel. These landscape-scale (90 m), daily snow depth data reproduced the observed spatial snow-depth variability across typical areal extents occupied by a wintering caribou during a 24-h period. Results We found that fall snow depths encountered by the herd north of the Brooks Range exerted a strong influence on selection of two distinct winter range locations. In winters with relatively shallow fall snow depth (2016/17, 2018/19, and 2019/20), the majority of the CAH wintered on the tundra north of the Brooks Range mountains. In contrast, during the winters with relatively deep fall snow depth (2014/15, 2015/16, and 2017/18), the majority of the CAH caribou wintered in the mountainous boreal forest south of the Brooks Range. Long-term (19 winters; 2001–2020) monitoring of CAH caribou winter distributions confirmed this relationship. Additionally, snow depth affected movement and selection differently within these two habitats: in the mountainous boreal forest, caribou avoided areas with deeper snow, but when on the tundra, snow depth did not trigger significant deep-snow avoidance. In both wintering habitats, CAH caribou selected areas with higher lichen abundance, and they moved significantly slower when encountering deeper snow. Conclusions In general, our findings indicate that regional-scale selection of winter range is influenced by snow depth at or prior to fall migration. During winter, daily decision-making within the winter range is driven largely by snow depth. This integrative approach of coupling snow and wildlife observations with snow-evolution and caribou-movement modeling to quantify the multi-facetted effects of snow on wildlife ecology is applicable to caribou and reindeer herds throughout the Arctic.

A new species of Droharhynchia (Brachiopoda) from the lower Middle Devonian (Eifelian) of west-central Alaska

1994 ◽  
Vol 68 (6) ◽  
pp. 1235-1240 ◽  
Author(s):  
Mary E. Baxter ◽  
Robert B. Blodgett
Keyword(s):  
New Species ◽  
Middle Devonian ◽  
The Arctic ◽  
Geographic Proximity ◽  
Brooks Range ◽  
West Central ◽  
Arctic Alaska ◽  
Northern Alaska ◽  
A New Species

A new species of the genus Droharhynchia Sartenaer is established from lower Eifelian strata of west-central Alaska and the northwestern Brooks Range of Alaska. Droharhynchia rzhonsnitskayae n. sp. occurs in the Cheeneetnuk Limestone of the McGrath A-5 quadrangle, west-central Alaska, and the Baird Group of the Howard Pass B-5 quadrangle, northwestern Alaska. These occurrences extend the lower biostratigraphic range of both the genus and the subfamily Hadrorhynchiinae into the Eifelian. They also suggest close geographic proximity of the Farewell terrane of southwestern and west-central Alaska and the Arctic Alaska superterrane of northern Alaska during Devonian time.

scholarly journals Tectonochemistry of the Brooks Range Ophiolite, Alaska

Lithosphere ◽  
2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Joseph Biasi ◽  
Paul Asimow ◽  
Ronald Harris
Keyword(s):  
Continental Margin ◽  
Mineral Chemistry ◽  
The Arctic ◽  
Geochemical Data ◽  
New Mineral ◽  
Trace Element Geochemistry ◽  
Element Geochemistry ◽  
Brooks Range ◽  
Arctic Alaska ◽  
Intrusive Rocks

Abstract We present new whole-rock geochemical data from the Brooks Range ophiolite (BRO) together with new mineral chemistry data from the BRO, South Sandwich forearc, Izu-Bonin forearc, and Hess Deep. The analyses reveal that the Brooks Range ophiolite (BRO) was most likely created in a forearc setting. We show that this tectonic classification requires the Brookian orogeny to begin at ~163-169 Ma. The middle-Jurassic BRO contains abundant gabbros and other intrusive rocks that are geochemically similar to lithologies found in other forearc settings. Based on major, minor, and trace element geochemistry, we conclude that the BRO has clear signals of a subduction-related origin. High-precision olivine data from the BRO have a forearc signature, with possible geochemical input from a nearby arc. The Koyukuk terrane lies to the south of the Brooks Range; previous studies have concluded that the BRO is the forearc remnant of this arc-related terrane. These studies also conclude that collision between the Koyukuk Arc and the Arctic Alaska continental margin marks the beginning of the Brookian orogeny. Since the BRO is a forearc ophiolite, the collision between the Koyukuk Arc and the continental margin must have coincided with obduction of the BRO. Previously determined 40Ar/39Ar ages from the BRO’s metamorphic sole yield an obduction age of 163-169 Ma. Since the same collisional event that obducts the BRO also is responsible for the Brookian orogeny, we conclude that the BRO’s obduction age of ~163-169 Ma marks the beginning of this orogenic event.

Regional Overview of Interior Alaska

2006 ◽  
Author(s):  
David Stone ◽  
David L. Verbyla
Keyword(s):  
Boreal Forest ◽  
Coastal Plain ◽  
The Arctic ◽  
Brooks Range ◽  
Alaska Range ◽  
Mountain Glaciers ◽  
Interior Alaska ◽  
Arctic Coastal Plain ◽  
Mountain System ◽  
Patterns And Processes

From continental macroclimate to microalluvial salt crusts, geology is a dominant factor that influences patterns and processes in the Alaskan boreal forest. In this chapter, we outline important geologic processes as a foundation for subsequent chapters that discuss the soil, hydrology, climate, and biota of the Alaskan boreal forest. We conclude the chapter with a discussion of interior Alaska from a regional perspective. Alaska can be divided into four major physiographic regions. The arctic coastal plain is part of the Interior Plains physiographic division of North America, analogous to the great plains east of the Rocky Mountains. The arctic coastal plain is predominantly alluvium underlaid by hundreds of meters of permafrost, resulting in many thaw lakes and ice wedges. South of the arctic coastal plain lies the Northern Cordillera, an extension of the Rocky Mountain system dominated by the Arctic Foothills, Brooks Range, Baird Mountains, and Delong Mountains. These mountains were glaciated during the Pleistocene. South of the Brooks Range lies interior Alaska, which is an intermontane plateau region analogous to the Great Basin/Colorado Plateau regions. This extensive region is characterized by wide alluvium-covered lowlands such as the Yukon Flats, Tanana Valley, and Yukon Delta, as well as moderate upland hills, domes, and mountains. Largely unglaciated, this region served as a refugium for biota during glacial periods. With the Northern and Southern Cordilleras acting as barriers, the major rivers of this region have long, meandering paths to the Bering Sea. The Southern Cordillera is composed of two mountain ranges: the Alaska Range to the north and the Kenai/Chugach/Wrangell-St. Elias Mountains to the south. The lowland belt between these mountains includes the Susitna and Copper River lowlands. The entire Southern Cordillera was glaciated during the Pleistocene and today has extensive mountain glaciers. Much of Alaska is made up of multiple geologic fragments that have been rafted together by the movements of the major plates called tectonic terranes (Thorson 1986, Connor and O’Haire 1988). Plate-tectonic theory explains such observations as the changing distribution of fossils with geologic time, the deep Aleutian Trench, high Alaskan mountain barriers, and mountain glaciers.

scholarly journals Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network

2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Snow Depth ◽  
Deep Neural Network ◽  
Arctic Basin ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Thickness ◽  
Arctic Sea

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.

scholarly journals Assimilation of D-InSAR snow depth data by an ensemble Kalman filter

2021 ◽  
Vol 14 (6) ◽  
Author(s):  
Jinming Yang ◽  
Chengzhi Li
Keyword(s):  
Remote Sensing ◽  
Kalman Filter ◽  
Water Resource ◽  
Ensemble Kalman Filter ◽  
Snow Depth ◽  
Resource Assessment ◽  
Measured Data ◽  
Hydrological Process ◽  
Depth Data ◽  
Water Resource Assessment

AbstractSnow depth mirrors regional climate change and is a vital parameter for medium- and long-term numerical climate prediction, numerical simulation of land-surface hydrological process, and water resource assessment. However, the quality of the available snow depth products retrieved from remote sensing is inevitably affected by cloud and mountain shadow, and the spatiotemporal resolution of the snow depth data cannot meet the need of hydrological research and decision-making assistance. Therefore, a method to enhance the accuracy of snow depth data is urgently required. In the present study, three kinds of snow depth data which included the D-InSAR data retrieved from the remote sensing images of Sentinel-1 synthetic aperture radar, the automatically measured data using ultrasonic snow depth detectors, and the manually measured data were assimilated based on ensemble Kalman filter. The assimilated snow depth data were spatiotemporally consecutive and integrated. Under the constraint of the measured data, the accuracy of the assimilated snow depth data was higher and met the need of subsequent research. The development of ultrasonic snow depth detector and the application of D-InSAR technology in snow depth inversion had greatly alleviated the insufficiency of snow depth data in types and quantity. At the same time, the assimilation of multi-source snow depth data by ensemble Kalman filter also provides high-precision data to support remote sensing hydrological research, water resource assessment, and snow disaster prevention and control program.

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