The Trajectory Towards a Seasonally Ice-Free Arctic Ocean

Climate change in cold regions

Cold regions around the world include Arctic, Antarctic and High Mountain regions featuring low temperatures, ice-covered landscapes, permafrost, and unique ecologic interrelations. These environments are among the most sensitive to climate change and are changing rapidly as the global climate gets warmer. This editorial explores the complexity of the impacts of climate change on cold regions, highlighting recent changes across Earth system. The Special Issue here presented compiles studies that explore the climate change in different cold regions from various perspectives, including paleoclimatic reconstructions, isotherm shifts and climate projections. Despite progress, significant questions remain, demanding interdisciplinary approaches to better understand the interconnected factors shaping cold regions.

Phylogeography and molecular diversity of two highly abundant Themisto amphipod species in a rapidly changing Arctic Ocean

Rapid warming in the Arctic is drastically impacting marine ecosystems, affecting species communities and food-web structure. Pelagic Themisto amphipods are a major component of the Arctic zooplankton community and represent a key link between secondary producers and marine vertebrates at higher trophic levels. Two co-existing species dominate in the region: the larger Themisto libellula, considered a true polar species and the smaller Themisto abyssorum, a sub-Arctic, boreal-Atlantic species. Recent changes in abundance and distribution ranges have been detected in both species, likely due to the Atlantification of the Arctic. The ecology and genetic structure of these species are understudied, despite their high biomass and importance in the food web. For both species, we assessed genetic diversity, patterns of spatial genetic structure and demographic history using samples from the Greenland shelf, Fram Strait and Svalbard. This was achieved by analysing variation on the mitochondrial cytochrome c oxidase subunit 1 gene (mtCOI). The results revealed contrasting levels of mtCOI diversity: low levels in T. libellula and high levels in T. abyssorum. A lack of spatial genetic structure and a high degree of genetic connectivity were detected in both species in the study region. These patterns of diversity are potentially linked to the impacts of the Last Glacial Maximum. T. libellula populations may have been isolated in glacial refugia, undergoing gene flow restriction and vicariant effects, followed by a population expansion after deglaciation. Whereas T. abyssorum likely maintained a stable, widely distributed metapopulation further south, explaining the high diversity and connectivity. This study provides new data on the phylogeography of two ecologically important species, which can contribute to predicting how zooplankton communities and food-web structure will manifest in the rapidly changing Arctic.

Prediction of sea ice area based on the CEEMDAN-SO-BiLSTM model

This article proposes a combined prediction model based on a bidirectional long short-term memory (BiLSTM) neural network optimized by the snake optimizer (SO) under complete ensemble empirical mode decomposition with adaptive noise. First, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was used to decompose the sea ice area time series data into a series of eigenmodes and perform noise reduction to enhance the stationarity and smoothness of the time series. Second, this article used a bidirectional long short-term memory neural network optimized by the snake optimizer to fully exploit the characteristics of each eigenmode of the time series to achieve the prediction of each. Finally, the predicted values of each mode are superimposed and reconstructed as the final prediction values. Our model achieves a good score of RMSE: 1.047, MAE: 0.815, and SMAPE: 3.938 on the test set.

The Arctic Highlights Our Failure to Act in a Rapidly Changing World

In this perspective on the future of the Arctic, we explore actions taken to mitigate warming and adapt to change since the Paris agreement on the temperature threshold that should not be exceeded in order to avoid dangerous interference with the climate system. Although 5 years may seem too short a time for implementation of major interventions, it actually is a considerable time span given the urgency at which we must act if we want to avoid crossing the 1.5 to <2 °C global warming threshold. Actions required include co-production of research exploring possible futures; supporting Indigenous rights holders’ and stakeholders’ discourse on desired futures; monitoring Arctic change; funding strategic, regional adaptation; and, deep decarbonization through transformation of the energy system coupled with negative carbon emissions. We are now in the decisive decade concerning the future we leave behind for the next generations. The Arctic’s future depends on global action, and in turn, the Arctic plays a critical role in the global future.

Sea Ice Dynamics Drive Benthic Microbial Communities in McMurdo Sound, Antarctica

Climate change is driving dramatic variability in sea ice dynamics, a key driver in polar marine ecosystems. Projected changes in Antarctica suggest that regional warming will force dramatic shifts in sea ice thickness and persistence, altering sea ice-associated primary production and deposition to the seafloor. To improve our understanding of the impacts of sea ice change on benthic ecosystems, we directly compared the benthic microbial communities underlying first-year sea ice (FYI) and multi-year sea ice (MYI). Using two tractable coastal habitats in McMurdo Sound, Antarctica, where FYI (Cape Evans) and MYI (New Harbour) prevail, we show that the structure and composition of the benthic microbial communities reflect the legacy of sea ice dynamics. At Cape Evans, an enrichment of known heterotrophic algal polysaccharide degrading taxa (e.g., Flavobacteriaceae, unclassified Gammaproteobacteria, and Rubritaleaceae) and sulfate-reducing bacteria (e.g., Desulfocapsaceae) correlated with comparatively higher chlorophyll a (14.2±0.8μgg^-1) and total organic carbon content (0.33%±0.04), reflecting increased productivity and seafloor deposition beneath FYI. Conversely, at New Harbour, an enrichment of known archaeal (e.g., Nitrosopumilaceae) and bacterial (e.g., Woeseiaceae and Nitrospiraceae) chemoautotrophs was common in sediments with considerably lower chlorophyll a (1.0±0.24μgg^-1) and total organic carbon content (0.17%±0.01), reflecting restricted productivity beneath MYI. We also report evidence of a submarine discharge of sub-permafrost brine from Taylor Valley into New Harbour. By comparing our two study sites, we show that under current climate-warming scenarios, changes to sea ice productivity and seafloor deposition are likely to initiate major shifts in benthic microbial communities, with heterotrophic organic matter degradation processes becoming increasingly important. This study provides the first assessment of how legacy sea ice conditions influence benthic microbial communities in Antarctica, contributing insight into sea ice-benthic coupling and ecosystem functioning in a polar environment.

Marginal ice zone fraction benchmarks sea ice and climate model skill

Global climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-ice models or from improvements in forcing driven by other GCM components. I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs from 1979-2014, showing modern GCMs do not plausibly estimate the response of SIA to warming in all months. I identify the marginal ice zone fraction (MIZF) as a metric that is less correlated to warming, has a response plausibly simulated from January-September (but not October-December), and has highly variable future projections across GCMs. These qualities make MIZF useful for evaluating the impact of sea-ice model changes on past, present, and projected sea-ice state.

Trade Volume Prediction Based on a Three-Stage Model When Arctic Sea Routes Open

With the advancement of global warming, the Arctic sea routes (ASRs) may open for the entire year. The ASRs will be far more competitive than they are now, and they will be the major international sea routes in the future. To date, most studies have researched the economic feasibility in the short term from a company’s perspective. To help to plan the shipping market in the future, we developed a three-stage model to simulate the trade demand of the ASRs for the long term. This model firstly considers the seasonal sea ice dynamics in the future and plans new paths for vessels shipping through the Arctic. Additionally, an improved trade prediction model was developed to adapt to the long-term forecasts. After verification, the accuracy of the model was found to be very high (R2 = 0.937). In comparison with another transportation cost model and a trade prediction model, our model was more reasonable. This study simulated the trade volumes of China, Europe (EU), and North America (NA) in 2100 with the ASRs open. The results show that the percentage of port trade can be up to 26% in representative concentration pathway (RCP)2.6, and the percentage of port trade can be up to 52% in RCP8.5.

Divergence of Arctic shrub growth associated with sea ice decline

Arctic sea ice extent (SIE) is declining at an accelerating rate with a wide range of ecological consequences. However, determining sea ice effects on tundra vegetation remains a challenge. In this study, we examined the universality or lack thereof in tundra shrub growth responses to changes in SIE and summer climate across the Pan-Arctic, taking advantage of 23 tundra shrub-ring chronologies from 19 widely distributed sites (56°N to 83°N). We show a clear divergence in shrub growth responses to SIE that began in the mid-1990s, with 39% of the chronologies showing declines and 57% showing increases in radial growth (decreasers and increasers, respectively). Structural equation models revealed that declining SIE was associated with rising air temperature and precipitation for increasers and with increasingly dry conditions for decreasers. Decreasers tended to be from areas of the Arctic with lower summer precipitation and their growth decline was related to decreases in the standardized precipitation evapotranspiration index. Our findings suggest that moisture limitation, associated with declining SIE, might inhibit the positive effects of warming on shrub growth over a considerable part of the terrestrial Arctic, thereby complicating predictions of vegetation change and future tundra productivity.

A novel method to test non-exclusive hypotheses applied to Arctic ice projections from dependent models

A major conundrum in climate science is how to account for dependence between climate models. This complicates interpretation of probabilistic projections derived from such models. Here we show that this problem can be addressed using a novel method to test multiple non-exclusive hypotheses, and to make predictions under such hypotheses. We apply the method to probabilistically estimate the level of global warming needed for a September ice-free Arctic, using an ensemble of historical and representative concentration pathway 8.5 emissions scenario climate model runs. We show that not accounting for model dependence can lead to biased projections. Incorporating more constraints on models may minimize the impact of neglecting model non-exclusivity. Most likely, September Arctic sea ice will effectively disappear at between approximately 2 and 2.5 K of global warming. Yet, limiting the warming to 1.5 K under the Paris agreement may not be sufficient to prevent the ice-free Arctic.