Carol Ladd

Timing of ice retreat alters seabird abundances and distributions in the southeast Bering Sea.

Timing of spring sea-ice retreat shapes the southeast Bering Sea food web. We compared summer seabird densities and average bathymetry depth distributions between years with early (typically warm) and late (typically cold) ice retreat. Averaged over all seabird species, densities in early-ice-retreat-years were 10.1% (95% CI: 1.1–47.9%) of that in late-ice-retreat-years. In early-ice-retreat-years, surface-foraging species had increased numbers over the middle shelf (50–150 m) and reduced numbers over the shelf slope (200–500 m). Pursuit-diving seabirds showed a less clear trend. Euphausiids and the copepod Calanus marshallae/glacialis were 2.4 and 18.1 times less abundant in early-ice-retreat-years, respectively, whereas age-0 walleye pollock Gadus chalcogrammus near-surface densities were 51× higher in early-ice-retreat-years. Our results suggest a mechanistic understanding of how present and future changes in sea-ice-retreat timing may affect top predators like seabirds in the southeastern Bering Sea.

Diagnostic sea ice predictability in the pan-Arctic and US Arctic regional seas

This study assesses sea ice predictability in the pan-Arctic and US Arctic regional (Bering, Chukchi, and Beaufort) seas with a purpose of understanding regional differences from the pan-Arctic perspective, and how predictability might change under changing climate. Lagged correlation is derived using existing output from the CESM Large Ensemble (CESM-LE), Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS), and NOAA Coupled Forecast System Reanalysis (CFSR) models. While qualitatively similar, quantitative differences exist in Arctic ice area lagged correlation in models with or without data assimilation. On regional scales, modeled ice area lagged correlations are strongly location- and season-dependent. A robust feature in the CESM-LE is that the pan-Arctic melt-to-freeze season ice area memory intensifies whereas the freeze-to-melt season memory weakens as climate warms, but there are across-region variations in the sea ice predictability changes with changing climate.

Results of the First Arctic Heat Open Science Experiment

AbstractSeasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–...

Nutrient and phytoplankton dynamics on the inner shelf of the eastern Bering Sea

The nitrogen cycle on the inner shelf of the southeastern Bering Sea is complicated due to limited nutrient replenishment across this broad shelf, and substantial nitrogen loss through sedimentary processes. While diffusion at the inner front may periodically support new production, the shelf is generally hypothesized to be a regenerative system. This study uses a combination of hydrographic surveys, and measurements of nitrogen assimilation and benthic fluxes to examine nitrogen cycling on the inner shelf, and connectivity between the middle and inner shelves of the southern and central Bering Sea. Results establish the inner shelf as primarily a regenerative system even in spring, although new production can occur at the inner front. Results also identify key processes that influence nutrient supply to the inner shelf, and reveal coupling between the middle shelf nutrient pool and production on the inner shelf. This article is protected by copyright. All rights reserved.