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Software from the Alaska Science Center.

Filter Total Items: 20

Automated Walrus Haulout Cartography

This pyQGIS script and adjoining QGIS layout templates and style specification generate maps from satellite imagery and any derived geospatial outline data that are inventoried and cross-referenced in a tabular inventory file. The maps are intended for mangers, decision makers, and researchers to support real-time decision making and to provide a graphical record that may be publicly shared.

Sentinel Satellite Imagery Download Scripts

These Python scripts enable download of Sentinel 1 & 2 imagery for multiple study sites by accessing the Copernicus Data Base Ecosystem.

Tests of multistate CJS models to estimate survival conditioned on a partially-observed latent state

Polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) historically spent nearly the entire year on the sea ice but are increasingly using land habitat as sea ice becomes less available seasonally due to climate warming. The U.S. Geological Survey, Alaska Science Center maintains a research program on the SBS polar bear subpopulation and one important research question is whether habitat

Eelgrass Biomass Model

This code release contains R and JAGS code for estimating average eelgrass biomass at two lagoons (Izembek and Kinzarof) within the Izembek National Wildlife Refuge, Alaska, using data from point count surveys conducted by National Wildlife Refuge and U.S. Geological Survey (USGS) personnel. Biomass is estimated using a gamma hurdle model which models the probability of occurrence and eelgrass abu

Scripts to Analyze Altitude Selection in Migrating Pacific Flyway Geese

This code repo contains three scripts used in the associated manuscript to run the analyses (01_model_prob_flight.r; 02_model_altitude_selection.r) and the simulation used to make predictions (03_simulate_prob_fly_per_altitude.r). The analysis serves to evaluate conditions that affect 1) whether geese are in flight vs. resting on the water, 2) what altitude is selected by flying geese, and 3) what

Rayleigh Step-Selection Functions

This project aimed to find connections between step-selection functions (SSFs) and partial differential equation models of animal movement and, in doing so, improve the flexibility of SSFs. Please see the associated manuscript cited above for further details.

WiggleMatch: a spreadsheet for radiocarbon wiggle-matching

This spreadsheet enables statistical and visual wiggle-matching of sequential radiocarbon ages from a tree-ring chronology to the IntCal20 calibration curve. It will calculate and plot an optimal fit of the samples to the calibration curve and the user can then incrementally move the wiggle-match in time to see the effect in both goodness-of-fit statistics and visually on a graph. This is useful w


The goal of algaeClassify is to facilitate the analysis of taxonomic and functional trait data for phytoplankton.

Bayesian Hierarchical Model of Whimbrel Survival

This model combines resighting data from Whimbrels breeding at Kanuti National Wildlife Refuge with known-fate data and pseudo-resighting history from Whimbrels breeding at the Colville River Delta ('colv'). All Whimbrels in the study (n = 76) were marked with a USGS metal band and a uniquely coded engraved leg flag. In addition, 15 Whimbrels at Kanuti were equipped with surgically implanted satel

Reproductive Success from Movement Data

This software release includes code to conduct analyses presented in the manuscript titled: A hierarchical modeling framework for estimating individual- and population-level reproductive success from movement data


SeaLog is a robust data-logging application designed to collect at-sea data of marine birds and mammals. This software was developed collaboratively with the U.S. Geological Survey, the National Park Service, the U.S. Fish and Wildlife Service, and ABR, Inc. SeaLog is Windows 10 compatible, is highly customizable, and provides user designed maps to allow visual feedback of observations.

QFASA Robustness to Assumption Violations: Computer Code

Quantitative fatty acid signature analysis (QFASA; Iverson et al. 2004) has become a common method of estimating diet composition, especially for marine mammals, but the performance of the method has received limited investigation. Bromaghin et al. (In press) used computer simulation to compare the bias of several QFASA estimators and developed recommendations regarding estimator selection. Simula