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Highlighted Publications

Last Update: 2016-09-21
Biogeography of boreal passerine range dynamics in western North America: past, present, and future [Details] [Full Publication]
Helminth community structure in two species of arctic-breeding waterfowl [Details] [Full Publication]
A strategy for recovering continuous behavioral telemetry data from Pacific walruses [Details] [Full Publication]
Space use of a dominant Arctic vertebrate: Effects of prey, sea ice, and land on Pacific walrus resource selection [Details] [Full Publication]

Highlighted Data

Last Update: 2016-09-12
Walrus used and available resource units for northeast Chukchi Sea, 2008-2012

Sea ice loss represents a stressor to the Pacific walrus (Odobenus rosmarus divergens), which feeds on benthic macroinvertebrates in the Bering and Chukchi seas. However, no studies have examined the effects of sea ice on foraging walrus space use patterns. Thus, we examined walrus foraging resource selection as a function of proximity to resting substrates and prey biomass with a matched use-availability design. We quantified biomass of 17 benthic taxa, which included amphipods, bivalves, polychaete, sand dollars, tunicates, and sipunculids. We included covariates for distance to sea ice and distance to land, and systematically developed a series of candidate models to examine interactions among benthic prey biomass and resting substrates. We ranked candidate models with Bayesian Information Criterion and made inferences on walrus resource selection based on the top-ranked model. Biomass of the bivalve family Tellinidae, distance to ice, distance to land, and the interaction of distances to ice and land were in the top-ranked model. Standardized model coefficients indicated that distance to ice explained the most variation in walrus foraging resource selection patterns followed by Tellinidae biomass. Distance to land and the interaction of distances to ice and land accounted for similar levels of variation in foraging walrus resource selection. These data represent the used and available resource units with the covariates of distance to land and distance to ice.

Gulf Watch Alaska Nearshore Component: Intertidal Mussel Site Data from Prince William Sound, Katmai National Park and Preserve, and Kenai Fjords National Park, 2008-2015

This data is part of the Gulf Watch Alaska (GWA) long term monitoring program, nearshore monitoring component. Specifically, these data describe mussel sampling and observations conducted in the northern Gulf of Alaska within the GWA program. The dataset consists of five comma separated files exported from a microsoft excel workbook. The data consists of 1. mussel sampling site layout information, 2. mussel count and 3. size measurements for mussels greater than 20 millimeters, 4. mussel count and 5. size measurements for all mussels collected from core samples. Samplers used transect tapes, quadrat frames, rulers, and core tools to sample mussels from mussel sites. Mussels greater than 20 millimeters were collected from a quadrat and measured with dial calipers to the nearest millimeter. Associated with the quadrat, but not within it, a small core sample was collected and all mussels greater than 1mm were counted and measured (measurements began in 2014). Sampling year, region, block, site, quadrat number, quardrat size (overall area sampled), and number of mussels in the core were recorded. Sites are in Alaska and include locations in Katmai National Park and Preserve, Kenai Fjords National Park and Prince William Sound. There are five mussel sites in each of those three regions. The time interval includes 2008-2015. Pacific blue mussels (Mytilus trossulus) are a conspicuous and abundant filter feeding marine invertebrate in the intertidal zone. Mussels are widely distributed, but also form relatively monotypic stands of larger individuals that are termed mussel beds. Although a number of factors such as environment, disturbance, predation and competition influence the abundance and distribution of mussels, they can be a competitively dominant intertidal species. Within the nearshore foodweb, mussels area a source of energy to a wide array of invertebrate, avian, and mammalian predators and are critically important prey for sea otters, black oystercatchers, harlequin ducks, Barrows goldeneye, and several species of sea stars.

USGS Alaska Benchmark Glacier Mass Balance Data - Phase 1; Gulkana and Wolverine Glaciers

Since the late 1950s, USGS has maintained a long-term glacier mass-balance program at three North American glaciers. Similar measurements began at Sperry Glacier, MT in 2005. Direct field measurements are combined with weather data and imagery analyses to estimate the seasonal and annual mass balance at each glacier in both a conventional and reference surface format (Cogley and others, 2011). The analysis framework (van Beusekom and others, 2010; O'Neel and others, 2014) is identical at each glacier to enable cross-comparison between output time series. Vocabulary used follows Cogley and others (2011) Glossary of glacier mass balance. Phase one of this data release will include input and output files from the USGS Alaska Benchmark Glacier Program. Three types of input are provided for Wolverine and Gulkana glaciers: 1) time-variable Accumulation Area Distribution; 2) time series of point water balance at three index sites on each glacier (with secondary sites given in recent years); 3) weather data from stations installed along the glacier margins. Two solution sets are output for each glacier: 1) Conventional glacier-wide mass balance from direct observations; 2) Geodetically calibrated, conventional glacier-wide mass balance, which represents our preferred solution. The USGS runs an analysis code to transform the three input data to the output data that will be included in Phase three of this data release. Output data represent surface mass balance estimates. We do not account for basal or englacial accumulation or ablation. Mass balances are reported in water equivalent (w.e.) units, and often represent integration of multiple field measurements. Whenever possible, we average multiple field measurements to account for surface roughness and measurement errors. These 'unprocessed observables' will form the basis of Phase two of this data release.


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

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