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Model data from: Revisiting the status of the Arctic’s Last Ice Area as a refuge for marine predators

Schweiger, Axel1; Laidre, Kristin1; Zhang, Jinlun1; Cohen, Ben1; Steele, Mike1; Ferguson, Steve2; Moore, Kent3

Published May 05, 2026 on Dryad. https://doi.org/10.5061/dryad.b2rbnzsw6

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Abstract

The Last Ice Area (LIA), located north of the Canadian Arctic Archipelago and Greenland, has the Arctic’s oldest and thickest sea ice. The LIA is hypothesized to be a potential climate refuge for ice-dependent top predators as Arctic sea ice continues to decline. However, recent studies indicate the region may be less resilient than expected. We used a coupled biophysical model to examine the impact of changes in sea ice and nutrient availability on the LIA marine planktonic ecosystem and the ecological potential of this critical area. The model was used to generate two downscaled simulations, which were forced by two IPCC AR6 climate models (GFDL-ESM4 and CNRM-6-1-HR using the SSP5-8.5 shared socioeconomic pathway), to investigate potential changes in primary productivity (PP) with different rates of future warming. Both downscaled model runs, which captured observed sea-ice dynamics, predicted declines in LIA sea-ice concentration and thickness. Under CNRM-6-1-HR, summer sea ice was largely absent from the LIA by 2055–2070, shortly after it disappeared elsewhere in the Arctic. Under GFDL-ESM4, some summer sea ice persisted through 2070, although concentration and thickness were low. Concurrently with declining sea ice, both models predicted increases in PP through 2070, with annual values peaking in August. While increased PP would support higher trophic levels, ice-dependent top predators require an ice platform for foraging and resting. Our approach of integrating physical and biological forecasts is a step towards a more complete picture to date of anticipated ecological changes in the LIA. We identify future research needs, which include evaluating additional climate models and forcing scenarios, collecting in-situ ecological data, including top predators, and a mechanistic understanding of how lower-level ecological changes will affect the life history of top predators.