Filters: Contacts: Prakash, Anupma (X)
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At northern limits of a species? distribution, fish habitat requirements are often linked to thermal preferences, and the presence of overwintering habitat. However, logistical challenges and hydrologic processes typical of glacial systems could compromize the identification of these habitats, particularly in large river environments. Our goal was to identify and characterize spawning habitat for fall-run chum salmon Oncorhynchus keta and model habitat selection from spatial distributions of tagged individuals in the Tanana River, Alaska using an approach that combined ground surveys with remote sensing. Models included braiding, sinuosity, ice-free water surface area (indicating groundwater influence), and persistent...
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Tags: Baseline 5-Baseline data,
species of concern: Chinook salmo
We evaluate local differences in thermal regimes and turbulent heat fluxes across the heterogeneous canopy of a black spruce boreal forest on discontinuous permafrost in interior Alaska. The data were taken during an intensive observing period in the summer of 2013 from two micrometeorological towers 600 m apart in a central section of boreal forest, one in a denser canopy (DC) and the other in a sparser canopy, but under approximately similar atmospheric boundary layer (ABL) flow conditions. Results suggest that on average 34% of the half-hourly periods in a day are nonstationary, primarily during night and during ABL transitions. Also, thermal regimes differ between the two towers; specifically between midnight...
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Tags: Monitoring 1-Changes in Plant and Animal Distribution: Ecosystems
We employed an integrated approach that combined remote sensing techniques with field measurements to predict the presence/absence of near-surface permafrost in a section of the Alaska Highway corridor. We investigated the correlative relationships among vegetation type, topography, moss thickness, tussock condition and near-surface permafrost in the study area. Analysis of moss thickness and active-layer depth in low-lying plains (slope <8?) showed an inverse relationship in different vegetation classes. The maximum likelihood classification of remotely sensed data mapped 80% of the study area as covered with vegetation. We developed an empirical-statistical (Binary Logistic Regression) model to establish the statistical...
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Types: Citation,
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OGC WFS Layer,
OGC WMS Layer,
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Tags: Modeling,
Monitoring 3-Improve Permafrost Mapping,
and Monitoring
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Types: Citation,
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Tags: Adaptation planning 1-Best management practices,
landscape scale conservation: Fire
A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially continuous near-surface (< 1.6 m) permafrost map. The BLR model was used to establish the relationship between vegetation type, aspect-slope, and permafrost presence; it predicted permafrost presence with an accuracy of 88%. Near-surface permafrost occupies 45% of the total vegetated area and 37% of the total study area. As less than 50% of the study area is underlain by near-surface permafrost, this distribution is characterized as "sporadic" for the study area.; A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially...
Categories: Data,
Publication;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Modeling,
Monitoring 3-Improve Permafrost Mapping,
and Monitoring
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