J
Jennifer K. Roach
Researcher at University of Alaska Fairbanks
Publications - 6
Citations - 242
Jennifer K. Roach is an academic researcher from University of Alaska Fairbanks. The author has contributed to research in topics: Climate change & Permafrost. The author has an hindex of 5, co-authored 6 publications receiving 201 citations.
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Mechanisms influencing changes in lake area in Alaskan boreal forest
TL;DR: In this article, the authors identify the primary mechanisms underlying heterogeneous trends in closed-basin lake area, and identify the most likely of nine mechanistic scenarios that combined three potential mechanisms for decreasing lake area (talik drainage, surface water evaporation, and terrestrialization).
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Landscape influences on climate-related lake shrinkage at high latitudes
TL;DR: Results indicate that postfire processes such as permafrost degradation, which also results from a warming climate, may promote lake drainage, particularly in coarse-textured soils and farther from rivers where overland flooding is less likely and downslope flow paths and negative hydraulic gradients between surface water and groundwater systems are more common.
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Assessment of Alaska Rain-on-Snow Events Using Dynamical Downscaling
Peter A. Bieniek,Uma S. Bhatt,John Walsh,Rick Lader,Brad Griffith,Jennifer K. Roach,Richard Thoman +6 more
TL;DR: In this paper, an understanding of the atmospheric drivers of rain on snow (ROS) events is required, and an analysis of the ice formed by cold-season rainfall or rain-on-snow is presented.
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Climate-induced lake drying causes heterogeneous reductions in waterfowl species richness
Jennifer K. Roach,Brad Griffith +1 more
TL;DR: In this article, the relationship between waterfowl species richness and lake size was modeled and trends in lake size were used to project historical, contemporary, and future richness at 2500+ lakes.
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Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery
TL;DR: In this paper, the authors compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction) and found that the simplest of the three methods, density slicing, performed best overall.