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Highlighted Publications

Last Update: 2018-05-08
Strain partitioning in southeastern Alaska: Is the Chatham Strait Fault active? [Details] [Full Publication]
Assessment of undiscovered oil and gas resources of the Susitna Basin, southern Alaska, 2017 [Details] [Full Publication]
Biological responses of Crested and Least auklets to volcanic destruction of nesting habitat in the Aleutian Islands, Alaska [Details] [Full Publication]
Development and characterization of 12 polymorphic microsatellite loci in the sea sandwort, Honckenya peploides [Details] [Full Publication]

Latest Data

Last Update: 2018-05-11
Data Used to Compare Photo-Interpreted and IfSAR-Derived Maps of Polar Bear Denning Habitat for the 1002 Area of the Arctic National Wildlife Refuge, Alaska, 2006-2016

These are data that characterize the distribution of polar bear denning habitat in 1002 Area of the Arctic National Wildlife Refuge, Alaska. They were generated to compare the efficacy of two different techniques: 1) from a previously published study (Durner et al., 2006) that used manual interpretation of aerial photos and 2) from computer interrogation of interferometric synthetic aperture radar (IfSAR) digital terrain models. Data include vector shapefiles of putative denning habitat derived using both methods, as well as a description of the IfSAR-derived digital terrain model (DTM) tiles used to generate the raster shapefiles. The IfSAR DTM are available for purchase through Intermap Technologies, Inc., and are not provided in the data release.

Influenza A Virus Data from Migratory Birds, Izembek National Wildlife Refuge, Alaska, 2011-2015

Data set containing avian influenza sampling information for late summer and early autumn waterfowl and gulls within and around the Izembek National Wildlife Refuge (NWR), Alaska, 2011-2015. Data contains species, age, sex, collection data and location of sampled migratory birds. Laboratory specific data used to identify presence and absence of influenza A viruses from collected samples are included.

Gulf Watch Alaska Nearshore Component: Sea Otter Aerial Survey Data Katmai National Park and Preserve, 2008, 2012, 2015

These data are part of the Gulf Watch Alaska (GWA) long term monitoring program, nearshore monitoring component. Specifically, these data describe sea otter (Enhydra lutris) aerial survey observations from the waters around Katmai National Park and Preserve from surveys conducted in 2008, 2012, and 2015. Sea otters are a keystone predator, well known for structuring the nearshore marine ecosystem through their consumption of invertebrate prey. The dataset consists of 3 comma-delimited files (CSV) exported from Microsoft Excel. The data consists of (1) Strip transect counts, (2) Intensive Search Unit (ISU) counts, and (3) Transect coordinates. For each aerial survey, a pilot flew an airplane at an altitude of 91 meters over pre-determined transects while an observer searched on one side of the plane and recorded sea otter group counts and locations. Sea otters observed within 400 meters of each transect were later used to estimate abundance. Sea otters sighted beyond the confines of designated transect swaths were also counted and mapped, time permitting. To estimate the number of sea otters in small groups (<20) not detected along transect swaths (e.g., due to diving behavior or the presence of kelp canopy), 400 meter diameter circles (i.e. ISUs) were searched intensively by periodically flying 5 concentric circles around an initiating group. These ISUs were distributed throughout the survey area in an attempt to accurately represent the full range of observation conditions encountered during the survey. When large groups of sea otters (≥20) were sighted on transect, they were circled until a complete count was made. Data are presented as three CSV files: KATM sea otter strip transect counts in dd.csv KATM sea otter ISU counts.csv KATM sea otter survey transect coordinates in dd.csv


Software

Last Update: 2018-05-11
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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