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Highlighted Publications

Last Update: 2018-02-20
Avian predator buffers against variability in marine habitats with flexible foraging behavior [Details] [Full Publication]
Patterns and controls of mercury accumulation in sediments from three thermokarst lakes on the Arctic Coastal Plain of Alaska [Details] [Full Publication]
Phylogeny and species traits predict bird detectability [Details] [Full Publication]
High-energy, high-fat lifestyle challenges an Arctic apex predator, the polar bear [Details] [Full Publication]

Latest Data

Last Update: 2018-02-15
Normalized Difference Vegetation Index, Biomass, and Nitrogen Content of Goose Forage, Northern Alaska, 2011-2015

This data set contains four tables of information regarding the sampling of plant biomass, nitrogen, cumulative thaw degree days, precipitation, and Normalized Difference Vegetation Index (NDVI) information for the Colville River Delta and Point Lonely area of northern Alaska from 2011-2015.

Marine ecology near Tufted Puffin colonies across the Aleutian Archipelago and Alaska Peninsula, 2012-2014

In the North Pacific Ocean and Bering Sea between August 2012-2014, data were collected on sea surface temperature and salinity data, marine bird and mammal surveys, hydroacoustic backscatter data, marine environment surrounding Tufted Puffin colonies, and body condition and diets of Tufted Puffin chicks.

Arctic Coastal Plain Seasonal Lake Drainage, Water Temperature, and Solute and Nutrient Concentrations, 2011 - 2014

This data release includes remotely sensed lake and lake chemistry and water temperature data collected from 2011 to 2014) from a series of lakes on the Arctic Coastal Plain of Alaska. Most of the data is from two sites within the Chipp River Basin.


Software

Last Update: 2018-02-15
USGS Sea Ice Email Script, 2017

Daily sea ice imagery and charting benefits logistics and navigational planning in the Alaskan Arctic waters, yet access to these data often requires high bandwidth data access and substantial GIS processing. This software script acquires, processes and delivers these data in a format that may be manipulated by openly available virtual globe software, be visualized by software commonly installed on all smart phones and computers, and that may be accessed through moderate band-width data communications available in remote Alaskan communities and offshore research vessels. The script sends daily or weekly e-mails with attached maps images and virtual globe data files of sea ice products, including the National Ice Center Marginal Ice Zone chart, and images of the 6.25 Km resolution passive microwave reflectance optimized to visualize sea ice. In the emailing the script provides links to the NASA MODIS imagery corrected to enhance visualization of sea ice; National Weather Service sea ice and surface forecast products, the NOAA NECP forecasted 24 h sea ice drift map, and the latest NOAA images from the POES AVHRR satellite.

qfasar: Quantitative Fatty Acid Signature Analysis in R

An implementation of Quantitative Fatty Acid Signature Analysis (QFASA) in R. QFASA is a method of estimating the diet composition of predators. The fundamental unit of information in QFASA is a fatty acid signature (signature), which is a vector of proportions describing the fatty acid composition of adipose tissue. Signature data from at least one predator and from samples of all potential prey types are required. Calibration coefficients, which adjust for the differential metabolism of individual fatty acids by predators, are also required. Given those data inputs, a predator signature is modeled as a mixture of potential prey signatures and its diet estimate is obtained as the mixture that minimizes a measure of distance between the observed and modeled signatures. A variety of estimation options, goodness-of-fit diagnostic procedures to assess the suitability of estimates, and simulation capabilities are implemented. Please refer to the package vignette and the documentation files for individual functions for details and references.

QFASA Robustness to Assumption Violations: Computer Code

Quantitative fatty acid signature analysis (QFASA; Iverson et al. 2004. Ecological Monographs 74:211-235) has become a common method of estimating diet composition, especially for marine mammals, but the performance of the method has received limited investigation. This software was developed to compare the bias of several QFASA estimators using computer simulation and develop recommendations regarding estimator selection (Bromaghin et al. 2015. Assessing the robustness of quantitative fatty acid signature analysis to assumption violations. Methods in Ecology and Evolution (publication expected in late 2015 or early 2016).

slope in the Susitna Basin - photo by Jamey Jones, USGS

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