Antarctic Sea Ice—A Polar Opposite?

Maksym, Ted; Stammerjohn, Sharon; Ackley, Stephen F.; Massom, Robert A.

doi:10.5670/oceanog.2012.88

Cited by 102 publications

(95 citation statements)

References 45 publications

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“…As outlined above, the sea-ice field south of Macquarie Island has, over the past decades, trended towards increased duration (SID), extent (SIE) and concentration (SIC) and sea-ice affects female foraging behaviour and success. Most relevant to this study is that SID within the seals' feeding grounds (figure 3) has increased by up to 60 + 10 days between 1979 and 2010 [11,15,16,20]. Our analyses of the seals relationship with SID indicated inter-annual decreases (increases) in seal numbers at Macquarie Island tend to be associated with a longer (shorter) SID 3 years previous to the census.…”

Section: Discussionmentioning

confidence: 85%

Bottom-up regulation of a pole-ward migratory predator population

et al. 2014

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As the effects of regional climate change are most pronounced at polar latitudes, we might expect polar-ward migratory populations to respond as habitat suitability changes. The southern elephant seal (Mirounga leonina L.) is a pole-ward migratory species whose populations have mostly stabilized or increased in the past decade, the one exception being the Macquarie Island population which has decreased continuously over the past 50 years. To explore probable causes of this anomalous trend, we counted breeding female seals annually between 1988 and 2011 in order to relate annual rates of population change (r) to foraging habitat changes that have known connections with atmospheric variability. We found r (i) varied annually from 20.016 to 0.021 over the study period, (ii) was most effected by anomalous atmospheric variability after a 3 year time lag was introduced (R ¼ 0.51) and (iii) was associated with sea-ice duration (SID) within the seals' foraging range at the same temporal lag. Negative r years may be extrapolated to explain, at least partially, the overall trend in seal abundance at Macquarie Island; specifically, increasing SID within the seals foraging range has a negative influence on their abundance at the island. Evidence is accruing that suggests southern elephant seal populations may respond positively to a reduced sea-ice field.

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Section: Discussionmentioning

confidence: 85%

Bottom-up regulation of a pole-ward migratory predator population

et al. 2014

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“…Although we could not estimate trends in the bloom start date and bloom end date, we can expect a similar pattern to the ones detected for date of Dia-Chla maximum since these indices are highly correlated ( Figure S1 in the supplement). These observations combined with recent studies on the trends in sea surface temperature [64] and sea ice cover [65] over the last three decades, suggest a link between these two variables and the diatom phenology. For example, in the region south of 60 • S and from 60 • E to 120 • E (Figure 7, grey star) the earlier date of Dia-Chla maximum and the increased Dia-Chla maximum coincide with the observed increase trend in SST and decrease in sea ice cover (earlier sea ice melt).…”

Section: Trendsmentioning

confidence: 91%

Diatom Phenology in the Southern Ocean: Mean Patterns, Trends and the Role of Climate Oscillations

2016

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Diatoms are the major marine primary producers in the Southern Ocean and a key component of the carbon and silicate biogeochemical cycle. Using 15 years of satellite-derived diatom concentration from September to April (1997April ( -2012, we examine the mean patterns and the interannual variability of the diatom bloom phenology in the Southern Ocean. Mean spatial patterns of timing and duration of diatom blooms are generally associated with the position of the Southern Antarctic Circumpolar Current Front and of the maximum sea ice extent. In several areas the anomalies of phenological indices are found to be correlated with ENSO and SAM. Composite maps of the anomalies reveal distinct spatial patterns and opposite events of ENSO and SAM have similar effects on the diatom phenology. For example, in the Ross Sea region, a later start of the bloom and lower diatom biomass were observed associated with El Niño and negative SAM events; likely influenced by an increase in sea ice concentration during these events.

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“…Analysis of the Antarctica-wide sea ice cover, however, is of limited value given that the sea ice variability and trends are spatially heterogeneous (Maksym et al, 2012). For example, while the ice cover is increasing in the Ross Sea, it has at the same time decreased in the Bellingshausen-Amundsen (B-A) Sea region.…”

Section: Regional Analysismentioning

confidence: 99%

“…This follows previous record maxima in (Reid et al, 2015, resulting in an overall increase in Antarctic September sea ice extent of 1.1 % per decade since 1979. While the observed increase is statistically significant, Antarctica's SIE is also highly variable from year to year and region to region (e.g., Maksym et al, 2012;Parkinson and Cavalieri, 2012;. For example, around the West Antarctic Peninsula (WAP), there have been large decreases in sea ice extent and sea ice duration (e.g., Ducklow et al, 2012;Smith and Stammerjohn, 2001), coinciding with rapid warming since 1950 (Ducklow et al, 2012).…”

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confidence: 99%

Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels

et al. 2016

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Abstract. Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.

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Antarctic Sea Ice—A Polar Opposite?

Cited by 102 publications

References 45 publications

Bottom-up regulation of a pole-ward migratory predator population

Bottom-up regulation of a pole-ward migratory predator population

Diatom Phenology in the Southern Ocean: Mean Patterns, Trends and the Role of Climate Oscillations

Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels

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