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Arctic Tundra Vegetation Spectral Reflectances along Gradients of Latitude and Soil Type in Northwestern Siberia

Presenters Name: 
Kole Bowersox
Co Presenters Name: 
Primary Research Mentor: 
Howard Epstein
Secondary Research Mentor: 
Time: 
12:30 - 1:45
Time of Presentation: 
2019 - 12:30pm to 1:45pm
Session: 
3
Location: 
Newcomb Hall Ballroom
Presentation Type: 
Poster
Presentations Academic Category: 
Science
Grant Program Recipient: 
USOAR Program
Abstract: 

Arctic tundra vegetation has been dynamic over time, especially as the present-day climate change warms the Arctic regions at twice the rate of the global average. In general, the “greenness” of arctic tundra vegetation has been increasing throughout the Arctic (e.g. Alaska, Canada, and northern Russia) over at least the past 5 decades, suggesting broad environmental changes in these regions. Environmental scientists have been able to observe these changes from space, using satellite-based sensors; however, the resolutions of these sensors are typically coarse and do not necessarily allow us to understand the specifics of what might be happening on the ground. Field-based spectral data at much finer resolutions provide better connections between surface reflectances (what the sensors see) and the actual vegetation conditions on the ground. From 2007 to 2010, field-based hyperspectral data were collected within the Yamal Peninsula region of northwestern Siberia in Russia, across a range of locations that varied in soil type (texture) and latitude. We analyzed these data, looking at examining reflectances of different wavelengths along the latitudinal gradient and with different soil types; we also related reflectance variations to the biomass values of different plant types at the field sites. We have found that locations with low levels of moss and lichen biomass also tend to have low surface reflectances. This research improves our understanding of how spectral reflectances observed from satellites relate to specific tundra vegetation properties across latitudinal and soil texture gradients.