Alaska Science Center
These data are serum urea nitrogen and creatinine levels for polar bears captured in the southern Beaufort Sea 1983-2016 and the Chukchi Sea 1987-1993. The dataset includes relevant information about the bears that were captured including the latitude and longitude of their capture location, capture date, age class and sex, the age and number of cubs accompanying an adult female, and whether the bear denned during the previous winter or exhibited signs of being engaged in mating behavior at the time of or just prior to capture.
This data set contains allele sizes for 30 individuals of 9 previously published and 20 novel microsatellite loci and the molecular sex verification (n = 31) of Emperor Geese (Chen canagica) from various locations across Alaska. The allele sizes for the 20 microsatellite loci developed in this study are included for 10 White-fronted Geese (Anser albifrons) from Selawik, 11 Black Brant (Branta bernicla nigricans) from Kigigak Island, 10 Canada Geese (Branta canadensis) from Copper River Delta, and 9 Cackling Geese (Branta hutchinsii) from lower Kashunuk River (Hock Slough) and Tutakoke River.
This data is part of the Gulf Watch Alaska (GWA) long term monitoring program, nearshore monitoring component. The data consists of date, time, and temperature measurements from intertidal rocky sampling sites. The dataset is 5 comma separated files exported from a download from the HOBO temperature logger. Sites are in Alaska and include locations in Katmai National Park and Preserve, Kenai Fjords National Park and northern and western Prince William Sound. There are five sites in each of those areas. The time interval includes 2014-2016. Temperature loggers were set to record hourly. Each file is comprised of data from a single site from a given year. Loggers were re-used so the logger serial number is included in the data file in case any anomalies are found which might be due to the logger itself.
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.
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.
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).
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