Alaska Science Center
This data release contains a spreadsheet with migration and wintering locations of Red-throated Loons marked with satellite transmitters from four breeding populations in Alaska, 2000-2011. Implanted internal platform terminal transmitters (PTT) were programmed to elicit signals for 8 hours followed by a quiescent period of 48 - 120 hours, depending on season and year of study. Location data were collected by the CLS Argos system.
This data set includes information on collections of fecal or cloacal samples from wild birds at two locations in Alaska, USA. Samples were screened for Escherichia coli (E. coli) and tested for resistance to multiple antibiotics using a variety of methods.
This data release comprises 3 datasets used to develop forecasts of autumn body condition for adult female Pacific walruses in the Chukchi Sea during mid and late century time periods. The activity dataset contains daily telemetry records for 218 adult female walruses tracked for periods of 7 to 104 days during 2008-2014, in the Chukchi Sea. Records include the number of hours the walrus was in the water, number of hours the walrus was foraging, study area region where the walrus was located, depths of the foraging locations, and the proportion of the region covered by sea ice. The movement dataset contains telemetry records for 94 of these walruses, giving the dates they moved from one region to another, and the date of the beginning of minimum ice period for that year. The projected-ice dataset contains daily projections of ice conditions in the study area regions derived from 7 general circulation models of future ice availability for mid-century (2045-2054) and late-century (2090-2099) time periods. The movement and activity datasets were developed to model walrus activity and movement as functions of sea ice conditions. The projected-ice dataset was developed to provide input for those models to forecast future walrus activity and movement. Forecasting autumn body condition requires linkage to bioenergetics models.
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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