Editing IPCC:AR6/SROCC/Chapter-3 (section)

== Box 3.3 Polynyas ==

<div id="section-3-2-2-1-block-1"></div>

'''''Arctic Coastal Polynyas'''''

Arctic polynyas (areas of open water surrounded by sea ice) are important because they ventilate the Arctic Ocean. The polynyas induce bottom reaching convection on shallow shelves (Damm et al., 2018 <sup>[[#fn:r430|430]]</sup> ) because the warm and exposed ocean surface creates very high heat fluxes and new sea ice formation during winter, releasing brine and creating dense water (Barber et al., 2012 <sup>[[#fn:r431|431]]</sup> ). On the shallow Siberian shelves, the ocean surface waters are dominated by river runoff which is rich with sediments (Damm et al., 2018 <sup>[[#fn:r432|432]]</sup> ), which end up both in the dense bottom water and in new sea ice (Bauch et al., 2012 <sup>[[#fn:r433|433]]</sup> ; Janout et al., 2015 <sup>[[#fn:r434|434]]</sup> ). This process maintains the Arctic Ocean halocline (Bauch et al., 2011 <sup>[[#fn:r435|435]]</sup> ), which insulates the sea ice cover from the heat of the underlying Atlantic-derived waters.

Polynyas are projected to change in different ways depending on regional ice conditions and ice formation processes. Further reductions in sea ice are projected for Arctic shelf seas which have already lost ice in recent decades (Barnhart et al., 2015 <sup>[[#fn:r436|436]]</sup> ; Onarheim et al., 2018 <sup>[[#fn:r437|437]]</sup> ) so polynyas will cease to exist where seasonal sea ice disappears or evolve to become part of the marginal sea ice zone due to changes in ice dynamics (i.e., the North Water polynya and the Circumpolar Flaw Lead); new or enlarged polynyas could result in regions where thinner ice becomes more effectively advected offshore, or where marine terminating glaciers increase land ice fluxes to the marine system ( ''medium confidence'' ). The reduced survival rate of sea ice in the Transpolar Drift interrupts the transport of sediment-laden ice produced from Siberian shelf polynyas (Krumpen et al., 2019 <sup>[[#fn:r438|438]]</sup> ), with consequences for the associated biogeochemical matter and gas fluxes (Damm et al., 2018 <sup>[[#fn:r439|439]]</sup> ) ( ''medium confidence'' ).

Projected changes to polynyas are important because the spring phytoplankton bloom starts early as the ocean is often well-ventilated and nutrient rich, so the entire biological range from phytoplankton to seabirds to marine mammals thrive in polynya waters ( ''high confidence'' ) (Stirling, 1997 <sup>[[#fn:r440|440]]</sup> ; Arrigo and van Dijken, 2004 <sup>[[#fn:r441|441]]</sup> ; Karnovsky et al., 2009 <sup>[[#fn:r442|442]]</sup> ). Secondary production and upper food web processes are typically adapted to the early availability of energy to the system with arrival of higher trophic species (Asselin et al., 2011 <sup>[[#fn:r443|443]]</sup> ). Because of the abundance of marine food resources including seals, whales and fish in and around polynyas, Arctic peoples have hunted regularly in these areas for thousands of years (Barber and Massom, 2007 <sup>[[#fn:r444|444]]</sup> ). Recent implementation of Inuit-led marine management areas acknowledge the Inuit knowledge of polynyas, and recognise the potential for development of fisheries and other resources in polynya systems, provided these activities minimise harm on the environment and wildlife. The Inuit Circumpolar Council’s Pikialasorsuaq Commission is an example of a proposal to develop an Inuit management area in the North Water Polynya (Cross-Chapter Box 3 in Chapter 1).

'''''Antarctic Coastal Polynyas'''''

The Antarctic continent is surrounded by coastal polynyas, which form from the combined effects of winds and landfast ice in the lee of coastal features that protrude into the westward coastal current (Nihashi and Ohshima, 2015 <sup>[[#fn:r445|445]]</sup> ; Tamura et al., 2016 <sup>[[#fn:r446|446]]</sup> ). Intense ice growth within these polynyas contributes to the production of Antarctic Bottom Water, the densest and most voluminous water mass in the global ocean (Jacobs, 2004 <sup>[[#fn:r447|447]]</sup> ; Nicholls et al., 2008 <sup>[[#fn:r448|448]]</sup> ; Orsi and Wiederwohl, 2009 <sup>[[#fn:r449|449]]</sup> ; Ohshima et al., 2013 <sup>[[#fn:r450|450]]</sup> ). Sea ice production is greatest in Ross and Weddell sea polynyas and around East Antarctica (Drucker et al., 2011 <sup>[[#fn:r451|451]]</sup> ; Nihashi and Ohshima, 2015 <sup>[[#fn:r452|452]]</sup> ; Tamura et al., 2016 <sup>[[#fn:r453|453]]</sup> ) ( ''high confidence'' ).

Antarctic coastal polynyas are biological hot-spots that support high rates of primary production (Ainley et al., 2015 <sup>[[#fn:r454|454]]</sup> ; Arrigo et al., 2015 <sup>[[#fn:r455|455]]</sup> ) due to a combination of both high light (Park et al., 2017 <sup>[[#fn:r456|456]]</sup> ) and high nutrient levels, especially iron (Gerringa et al., 2015 <sup>[[#fn:r457|457]]</sup> ). Basal ice shelf melt is the primary supplier of iron to coastal polynyas (Arrigo and van Dijken, 2015 <sup>[[#fn:r458|458]]</sup> ) although sea ice melt and intrusions of Circumpolar Deep Water are significant in the Ross Sea (McGillicuddy et al., 2015 <sup>[[#fn:r459|459]]</sup> ; Hatta et al., 2017 <sup>[[#fn:r460|460]]</sup> ). As ice shelves retreat, the polynyas created in their wake also increase local primary production: the new polynyas created after the collapse of the Larsen A and B ice shelves are as productive as other Antarctic shelf regions, ''likely'' increasing organic matter export and altering marine ecosystem evolution (Cape et al., 2013 <sup>[[#fn:r461|461]]</sup> ). The recent calving of Mertz Glacier Tongue in East Antarctica has altered sea ice and ocean stratification (Fogwill et al., 2016 <sup>[[#fn:r462|462]]</sup> ) such that polynyas there are now twice as productive (Shadwick et al., 2017 <sup>[[#fn:r463|463]]</sup> ).

The productivity associated with these polynyas is a critical food source for some of the most abundant top predators in Antarctic waters, including penguins, albatross and seals (Raymond et al., 2014 <sup>[[#fn:r464|464]]</sup> ; Malpress et al., 2017 <sup>[[#fn:r465|465]]</sup> ) (Section 3.2.3.2.4). However, only a fraction of the carbon fixed by phytoplankton in coastal polynyas is consumed by upper trophic levels. The rest sinks to the seafloor where it is re-mineralised or sequestered (Shadwick et al., 2017 <sup>[[#fn:r466|466]]</sup> ), or is advected off the shelf (Lee et al., 2017b <sup>[[#fn:r467|467]]</sup> ). Given the high amount of residual macronutrients in polynya surface waters, there is evidence that future changes in ice shelf melt rates could increase water column productivity (Gerringa et al., 2015 <sup>[[#fn:r468|468]]</sup> ; Rickard and Behrens, 2016 <sup>[[#fn:r469|469]]</sup> ; Kaufman et al., 2017 <sup>[[#fn:r470|470]]</sup> ), influencing Antarctic coastal ecosystems and increasing the ability of continental shelf waters to sequester atmospheric carbon dioxide (Arrigo and van Dijken, 2015 <sup>[[#fn:r471|471]]</sup> ).

'''''The Weddell Polynya'''''

The Weddell Polynya is a large area of open water within the winter ice pack of the Weddell Sea close to the Maud Rise seamount (at approximately 65ºS, 3ºE), and has importance on a global scale for deep water ventilation. The polynya opens intermittently, and remained open from 1974 to 1976, with an area of 0.2–0.3 million km 2 (Carsey, 1980 <sup>[[#fn:r472|472]]</sup> ). A similar polynya appeared in spring 2017, with a smaller area in 2016, but did not occur in 2018 (Campbell et al., 2019 <sup>[[#fn:r473|473]]</sup> ; Jena et al., 2019 <sup>[[#fn:r474|474]]</sup> ). Based on these recent events, there is ''medium confidence'' in the drivers of Weddell Polynya formation; it forms over deep water and appears connected to sea ice divergence created by ocean eddies (Holland, 2001 <sup>[[#fn:r475|475]]</sup> ) or strong winds (Campbell et al., 2019 <sup>[[#fn:r476|476]]</sup> ; Francis et al., 2019 <sup>[[#fn:r477|477]]</sup> ; Wilson et al., 2019 <sup>[[#fn:r478|478]]</sup> ). Around Maud Rise, the ocean is weakly stratified, and winter sea ice formation causes brine release and the related deepening mixed layer brings warmer deep waters towards the surface. This causes heat loss to the atmosphere above 200 W m – ² (Campbell et al., 2019 <sup>[[#fn:r479|479]]</sup> ). These polynya formation processes cause deep ocean convection that releases heat from the deep ocean to the atmosphere (Smedsrud, 2005 <sup>[[#fn:r480|480]]</sup> ), and may contribute to the uptake of anthropogenic carbon (Bernardello et al., 2014 <sup>[[#fn:r481|481]]</sup> ).<br />

In some CMIP5 models, phases of Weddell polynya activity appear for decades or centuries at a time, and then cease for a similar period (Reintges et al., 2017 <sup>[[#fn:r482|482]]</sup> ). The observational era is not sufficiently long to rule out this behaviour. Models indicate that under anthropogenic climate change, surface freshening caused by increased precipitation reduces the occurrence of the Weddell polynya (de Lavergne et al., 2014). There are systematic biases in modelled ocean stratification resulting in ''low confidence'' in future Weddell Polynya projections (Reintges et al., 2017 <sup>[[#fn:r483|483]]</sup> ).

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<span id="physical-oceanography"></span>
==== 3.2.2.2 Physical Oceanography ====

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Consistent with the projected sea ice decline, there is ''high confidence'' that the Arctic Ocean will warm significantly towards the end of this century at the surface and in the deeper layers. Most CMIP5 models capture the seasonal changes in surface heat and freshwater fluxes for the present day climate, and show that the excess summer solar heating is used to melt sea ice, in a positive ice albedo feedback (Ding et al., 2016 <sup>[[#fn:r484|484]]</sup> ). Using RCP8.5, Vavrus et al. (2012) found that the Atlantic layer is projected to warm by 2.5°C at around 400 m depth at the end of the century, but only by 0.5°C in the surface mixed layer. Consistent results for lower Atlantic Water layer warming were found by Koenigk and Brodeau (2014) <sup>[[#fn:r485|485]]</sup> for RCP2.5 (0.5°C), RCP4.5 (1.0°C) and RCP8.5 (2.0°C).

Poleward ocean heat transport contributes to Arctic Ocean warming ( ''medium confidence'' ). Comparing 20 CMIP5 simulations for RCP8.5, Nummelin et al. (2017) found a 2°C–6°C range in Arctic amplification of surface air temperature north of 70°N, consistent with increased ocean heat transport. Comparing 26 different CMIP5 simulations for RCP4.5, Burgard and Notz (2017) found that ocean heat transport changes explain the Arctic Ocean multi-model mean warming, but that differences between models are compensated by changes in surface fluxes. Increased ocean heat transport into the Barents Sea beyond 2020 appears as a probable mechanism with continued warming (Koenigk and Brodeau, 2014 <sup>[[#fn:r486|486]]</sup> ; Årthun et al., 2019 <sup>[[#fn:r487|487]]</sup> ). Based on four CMIP5 models, the Barents Sea is projected to become ice-free during winter beyond 2050 under RCP8.5 (Onarheim and Årthun, 2017 <sup>[[#fn:r488|488]]</sup> ), to which the main response is an increased ocean-to-atmosphere heat flux and related surface warming (Smedsrud et al., 2013 <sup>[[#fn:r489|489]]</sup> ). The ocean heat transport increases in all Arctic gateways, but is dominated by the Barents Sea, and when winter sea ice disappears here the heat loss cannot increase further and the excess ocean heat continues into the Arctic Basin (Koenigk and Brodeau, 2014 <sup>[[#fn:r490|490]]</sup> ).

The surface mixed layer of the Arctic Ocean is expected to freshen in future because an intensified hydrological cycle will increase river runoff (Haine et al., 2015 <sup>[[#fn:r491|491]]</sup> ) ( ''medium confidence'' ). The related increase in stratification has the potential to contribute to the warming of the deep Atlantic Water layer, as upward vertical mixing will be reduced (Nummelin et al., 2016 <sup>[[#fn:r492|492]]</sup> ). There are, however, biases in salinity of ~1 across the Arctic Basin for the present day climate (Ilicak et al., 2016 <sup>[[#fn:r493|493]]</sup> ) in forced global ice-ocean models with configurations comparable to CMIP5, suggesting limited predictive skill for the Arctic freshwater cycle.

CMIP5 projections (Figure 3.3) indicate that observed Southern Ocean warming trends will continue under RCP4.5 and RCP8.5 scenarios, leading to 1°C–3°C warming by 2100 mostly in the upper ocean (Sallée et al., 2013a <sup>[[#fn:r494|494]]</sup> ). Projections demonstrate a similar distribution of heat storage to historical observations, notably focused in deep pools north of the Subantarctic Front (e.g., Armour et al., 2016 <sup>[[#fn:r495|495]]</sup> ). Antarctic Bottom Water becomes coherently warmer by up to 0.3°C by 2100 across the model ensemble under RCP8.5 (Heuzé et al., 2015 <sup>[[#fn:r496|496]]</sup> ). The upper ocean also becomes considerably fresher (salinity decrease of approximately 0.1) (Sallée et al., 2013b <sup>[[#fn:r497|497]]</sup> ) with an overall increase in stratification and a shallowing of mixed layers (Sallée et al., 2013a <sup>[[#fn:r498|498]]</sup> ). Although the sign of model changes appear mostly robust, there is ''low confidence'' in magnitude due to the large inter-model spread in projections and significant warm biases in historical water mass properties (Sallée et al., 2013a <sup>[[#fn:r499|499]]</sup> ) and sea surface temperature, which may be up to 3°C too high in the historical runs (Wang et al., 2014 <sup>[[#fn:r500|500]]</sup> ). Projections of changes in Southern Ocean circulation are discussed in Cross-Chapter Box 7 in Chapter 3.

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==== 3.2.2.3 Carbon and Ocean Acidification ====

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The Arctic and Southern Ocean have a systemic vulnerability to aragonite undersaturation (Orr et al., 2005 <sup>[[#fn:r501|501]]</sup> ). For the RCP8.5 scenario, the entire Arctic and Southern Ocean surface waters will ''very likely'' be typified by year-around conditions corrosive for aragonite minerals for 2090–2100 (Figure 3.4) (Hauri et al., 2015 <sup>[[#fn:r502|502]]</sup> ; Sasse et al., 2015 <sup>[[#fn:r503|503]]</sup> ), whilst under RCP2.6 the extent of undersaturated waters are reduced markedly. At a basin/circumpolar scale, there is ''high confidence'' in these projections due to our robust understanding of the driving mechanisms. However, there is ''medium confidence'' for the response of specific locations, due to the need for improved resolution of the local circulation, interactions with sea ice, and other processes that modulate the rate of acidification.

Under RCP8.5, melting ice causes the greatest declining rate of pH and CaCO 3 saturation state in the Central Arctic, Canadian Arctic Archipelago and Baffin Bay (Popova et al., 2014 <sup>[[#fn:r504|504]]</sup> ). In the Canada Basin, projections using RCP8.5 show reductions in mean surface pH from approximately 8.1 in 1986–2005 to 7.7 by 2066–2085, and aragonite saturation from 1.52–0.74 during the same period (Steiner et al., 2014 <sup>[[#fn:r505|505]]</sup> ). A shoaling of the aragonite saturation horizon of approximately 1200 m, a large increase in area extent of undersaturated surface waters, and a pH change in the surface water of –0.19 are projected using the SRES A1B scenario (broadly comparable to RCP6.0) in the Nordic Sea from 2000 to 2065 (Skogen et al., 2014 <sup>[[#fn:r506|506]]</sup> ). Under the same scenario, aragonite undersaturation is projected to occur in the bottom waters over the entire Kara Sea shelf by 2040 and over most of the Barents and East Greenland shelves by 2070 due to the accumulation of anthropogenic CO 2 (Wallhead et al., 2017 <sup>[[#fn:r507|507]]</sup> ).

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<span id="figure-3.4"></span>
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'''Figure 3.4'''

<span id="the-upper-ocean-010-m-at-end-of-this-century-20812100-characterised-by-undersaturated-conditions-for-aragonite-across-90-confidence-intervals-dark-red-to-light-red-for-the-representative-concentration-pathway-rcp8.5-a-and-rcp2.6-b-scenarios-in-the-coupled-model-intercomparison-project-phase-5-cmip5.-saturation-states-are-averaged-and-confidence-intervals-calculated-at"></span>
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'''The upper ocean (0–10 m) at end of this century (2081–2100), characterised by undersaturated conditions for aragonite across 90% confidence intervals (dark red to light red) for the Representative Concentration Pathway (RCP)8.5 (a) and RCP2.6 (b) scenarios in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Saturation states are averaged and confidence intervals calculated at […]'''
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[[File:c8a10b7483d8fc1fc700af74963ecd68 IPCC-SROCC-CH_3_4.jpg]]

The upper ocean (0–10 m) at end of this century (2081–2100), characterised by undersaturated conditions for aragonite across 90% confidence intervals (dark red to light red) for the Representative Concentration Pathway (RCP)8.5 (a) and RCP2.6 (b) scenarios in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Saturation states are averaged and confidence intervals calculated at each geographic location across the CNRM-CM5, HadGEM2-ES, GFDL-ESM2G, GFDL-ESM2G, IPSL-CM5-LR, IPSL-CM5-MR, MPI-LR, MPI-MR and NCAR-CESM1 models.

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<div id="section-3-2-2-3carbon-and-ocean-acidification-block-3"></div>

Under RCP8.5, the rate of CO 2 uptake by the Southern Ocean is projected to increase from the contemporary 0.91 Pg C yr ''–'' 1 to 2.38(1.65–2.55) Pg C yr ''–'' 1 by 2100, but the growth in uptake rate will slow and likely stop around 2070 ± 10 corresponding to cumulative CO 2 emissions of 1600 Gt C (Kessler and Tjiputra, 2016 <sup>[[#fn:r508|508]]</sup> ; Wang et al., 2016b <sup>[[#fn:r509|509]]</sup> ). This halt in the increase in the uptake rate of CO 2 is linked to the combined feedbacks from well-understood reductions in buffering capacity and warming, as well as the increased upwelling rate of carbon-rich Circumpolar Deep Water (Hauck and Volker, 2015 <sup>[[#fn:r509|509]]</sup> ) (Cross-Chapter Box 7 in Chapter 3). Although there is ''high agreement'' amongst models, contemporary biases in the fluxes of CO 2 in CMIP5 models in the Southern Ocean (Mongwe et al., 2018 <sup>[[#fn:r510|510]]</sup> ) suggest ''medium confidence'' levels for these projections.

Alongside the mean state changes, Southern Ocean aragonite saturation is also affected by the seasonal cycle of carbonate as well as by the impact of reduced buffering capacity (SM3.2.4) on the seasonal cycle of CO 2 (Sasse et al., 201511v; McNeil and Sasse, 2016 <sup>[[#fn:r512|512]]</sup> ). This leads to an amplification of the seasonal variability of pCO 2 (Hauck and Volker, 2015 <sup>[[#fn:r513|513]]</sup> ; McNeil and Sasse, 2016 <sup>[[#fn:r514|514]]</sup> ; Landschützer et al., 2018 <sup>[[#fn:r515|515]]</sup> ) and the hydrogen ion concentration that accelerates the onset of hypercapnia (i.e., high pCO 2 levels; pCO2 &gt; 1000 μ atm) to nearly 2 decades (~2085) ahead of anthropogenic CO 2 forcing (McNeil and Sasse, 2016 <sup>[[#fn:r516|516]]</sup> ). The seasonal cycles of pH and aragonite saturation will be attenuated (Kwiatkowski and Orr, 2018 <sup>[[#fn:r517|517]]</sup> ) (Section 5.2.2.3), however when the mean state changes are combined with the changes in seasonality, the onset of undersaturation is brought forward by 10–20 years (Table SM3.5). Model projections remain uncertain and affected by the resolution of local ocean physics, which leads to overall ''medium confidence'' in the timing of undersaturation and hypercapnia.

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=== 3.2.3 Impacts on Marine Ecosystems ===

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==== 3.2.3.1 Arctic ====

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Climate change has, and is projected to continue to have, significant implications for Arctic marine ecosystems, with consequences at different trophic levels both in the pelagic, benthic, and sympagic (sea ice related) realms (Figure 3.5). Specifically, climate change is projected to alter the distribution and properties of Arctic marine habitats with associated implications for species composition, production and ecosystem structure and function (Frainer et al., 2017 <sup>[[#fn:r518|518]]</sup> ; Kaartvedt and Titelman, 2018 <sup>[[#fn:r519|519]]</sup> ; Moore et al., 2018 <sup>[[#fn:r520|520]]</sup> ). The rate and severity of ecosystem impacts will be spatially heterogeneous and dependent on future emission scenarios.

In the few Arctic regions where data is sufficient to assess trends in biodiversity, the ecosystem level responses appear to be products of multiple interacting physical, chemical and biological processes (Frederiksen, 2017 <sup>[[#fn:r521|521]]</sup> ) ( ''medium confidence'' ). Climate change impacts on vertical fluxes and stratification (Sections 3.2.1.2.3, 3.2.2.2) will contribute to changes in bentho-pelagic-sympagic coupling. For instance, projected climate driven changes in ocean properties and hydrography (Section 3.2.2.2) and the abundance of pelagic grazers (Box 3.4) could alter the export of organic matter to the sea floor with associated impacts on the benthos in some Arctic shelf ecosystems (Moore and Stabeno, 2015 <sup>[[#fn:r522|522]]</sup> ; Stasko et al., 2018 <sup>[[#fn:r523|523]]</sup> ) ( ''low confidence'' ). Projected future reductions in summer sea ice (Section 3.2.1.1), increased stratification in summer, shifting currents and fronts and increased ocean temperatures (Section 3.2.2.2) and ocean acidification (Section 3.2.2.3) are all expected to impact the future production and distribution of several marine fish and invertebrates ( ''high confidence'' ).

Ocean acidification (Section 3.2.2.3) will affect several key Arctic species ( ''medium confidence'' ). The effects of current and projected levels of acidification have been examined for a broad suite of species groups (bivalves, cephalopods, echinoderms, crustaceans, corals and fishes) and these studies reveal species-specific differences in sensitivity, as well as differences in the scope for, and energetic cost of, adaptation (Luckman et al., 2014 <sup>[[#fn:r524|524]]</sup> ; Howes et al., 2015 <sup>[[#fn:r525|525]]</sup> ; Falkenberg et al., 2018 <sup>[[#fn:r526|526]]</sup> ).

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<span id="plankton-and-primary-production"></span>
===== 3.2.3.1.1 Plankton and primary production =====

There is evidence that the combination of loss of sea ice, freshening, and regional stratification (Sections 3.2.1.1 and 3.2.1.2) has affected the timing, distribution and production of primary producers (Moore et al., 2018 <sup>[[#fn:r527|527]]</sup> ) ( ''high confidence'' ). Satellite data show that the decline in ice cover has resulted in a &gt;30% increase in annual net primary production (NPP) in ice-free Arctic waters since 1998 (Arrigo and van Dijken, 2011 <sup>[[#fn:r528|528]]</sup> ; Bélanger et al., 2013 <sup>[[#fn:r529|529]]</sup> ; Arrigo and van Dijken, 2015 <sup>[[#fn:r530|530]]</sup> ; Kahru et al., 2016 <sup>[[#fn:r531|531]]</sup> ), a phenomenon corroborated by both ''in situ'' data (Stanley et al., 2015 <sup>[[#fn:r532|532]]</sup> ) and modelling studies (Vancoppenolle et al., 2013 <sup>[[#fn:r533|533]]</sup> ; Jin et al., 2016 <sup>[[#fn:r534|534]]</sup> ). Ice loss has also resulted in earlier phytoplankton blooms (Kahru et al., 2011 <sup>[[#fn:r535|535]]</sup> ) with blooms being dominated by larger-celled phytoplankton (Fujiwara et al., 2016 <sup>[[#fn:r536|536]]</sup> ). The longer open water season in the Arctic has also increased the incidence of autumn blooms, a phenomenon previously rarely observed in Arctic waters (Ardyna et al., 2017 <sup>[[#fn:r537|537]]</sup> ).

Thinner Arctic sea ice cover has led to the appearance of intense phytoplankton blooms that develop beneath first-year sea ice ( ''medium confidence'' ). Blooms of this size (1000s of km 2 ) and intensity (peaks of approximately 30 mg Chla-m –3 ) were previously thought to be restricted to the marginal ice zone and the open ocean where ample light reaches the surface ocean for rapid phytoplankton growth (Arrigo et al., 2012 <sup>[[#fn:r538|538]]</sup> ). Evidence shows that these blooms can thrive beneath sea ice in areas of reduced thickness, increased coverage of melt ponds (Arrigo et al., 2014 <sup>[[#fn:r539|539]]</sup> ; Zhang et al., 2015 <sup>[[#fn:r540|540]]</sup> ; Jin et al., 2016 <sup>[[#fn:r541|541]]</sup> ; Horvat et al., 2017 <sup>[[#fn:r542|542]]</sup> ), first-year ridges at the snow-ice interface (Fernández-Méndez et al., 2018 <sup>[[#fn:r543|543]]</sup> ), and a large number of cracks (high lead fractions) in the ice (Assmy et al., 2017 <sup>[[#fn:r544|544]]</sup> ), although the latter has not changed significantly in the last three decades (Wang et al., 2016a <sup>[[#fn:r545|545]]</sup> ). Local features including snow-free or thin snow, hummocks and ridges commonly found on multi-year ice also provide habitat for ice algae (Lange et al., 2017 <sup>[[#fn:r546|546]]</sup> ).

The reduction in sea ice area and thickness in the Arctic Ocean appears to be indirectly impacting rates of NPP through increased exposure of the surface ocean to atmospheric forcing ( ''medium confidence'' ) and these indirect impacts will possibly increase in the future ( ''low confidence'' ). Greater wind stress has been shown to increase upwelling of nutrients at the shelf break both over ice-free waters (Williams and Carmack, 2015 <sup>[[#fn:r547|547]]</sup> ) and a partial ice cover (Schulze and Pickart, 2012 <sup>[[#fn:r548|548]]</sup> ), leading to more new production (Williams and Carmack, 2015 <sup>[[#fn:r549|549]]</sup> ). At the same time, enhanced vertical stratification (Section 3.2.1.2.2, SM3.2.2) and decreased upwelling of nutrients into surface waters (Capotondi et al., 2012 <sup>[[#fn:r550|550]]</sup> ; Nummelin et al., 2016 <sup>[[#fn:r551|551]]</sup> ) may reduce Arctic NPP in the future, especially in the central basin (Ardyna et al., 2017 <sup>[[#fn:r552|552]]</sup> ). It could also impact phytoplankton community composition and size structure, with small-celled phytoplankton, which require less nutrients, becoming more dominant as nutrient concentrations in surface waters decline (Yun et al., 2015 <sup>[[#fn:r553|553]]</sup> ).

In addition to its impact on phytoplankton bloom dynamics, the decline in the proportion of multi-year sea ice and proliferation of a thinner first year sea ice cover may favour growth of microalgae within the ice due to increased light availability ( ''medium confidence'' ). Recent studies suggest that the contribution of sea ice algae to total Arctic NPP is higher now than values measured previously (Song et al., 2016 <sup>[[#fn:r554|554]]</sup> ), accounting for nearly 10% of total NPP (ice plus water) and as much as 60% in places like the central Arctic (Fernández-Méndez et al., 2015 <sup>[[#fn:r555|555]]</sup> ).

Ongoing changes in NPP will impact the biogeochemistry and ecology of large parts of the Arctic Ocean ( ''high confidence'' ). In areas of enhanced nutrient availability and greater NPP, dominance by larger-celled microalgae increases vertical export efficiency from the surface downwards in both ice covered (Boetius et al., 2013 <sup>[[#fn:r556|556]]</sup> ; Lalande et al., 2014 <sup>[[#fn:r557|557]]</sup> ; Mäkelä et al., 2017 <sup>[[#fn:r558|558]]</sup> ) and open ocean (Le Moigne et al., 2015) areas. However, because exported biomass production may be increasing in some areas but declining in others, the net impact may be small (Randelhoff and Guthrie, 2016 <sup>[[#fn:r559|559]]</sup> ) (Sections 3.2.3.1.2, 5.3.6, SM3.2.6). Phytoplankton may have the capacity to compensate for ocean acidification under a range of temperatures and pH values (Hoppe et al., 2018 <sup>[[#fn:r560|560]]</sup> ).

Increased water temperatures (Section 3.2.1) and shifts in the spatial pattern and timing of the ice algal and phytoplankton blooms, have impacted the phenology, magnitude and duration of zooplankton production with associated changes in the zooplankton community composition ( ''medium confidence'' ). Negative effects of reductions in ice algae on zooplankton may be partially offset by predicted increases in water column phytoplankton production in the Bering Sea (Wang et al., 2015 <sup>[[#fn:r561|561]]</sup> ). Changes in sea ice coverage and thickness may alter the phenology, abundance and distribution of zooplankton in the future. Projected changes will initially have the most pronounced impact on sympagic amphipods, but will subsequently affect food web functioning and carbon dynamics of the pelagic system (Kohlbach et al., 2016 <sup>[[#fn:r562|562]]</sup> ).

At the more southern boundaries of the Arctic such as the southeastern Bering Sea, warm conditions have led to reduced production of large copepods and euphausiids ( ''medium confidence'' ) (Sigler et al., 2017 <sup>[[#fn:r563|563]]</sup> ; Kimmel et al., 2018 <sup>[[#fn:r564|564]]</sup> ). On more northern shelves, the increased open water period has led to increases in large copepods over a 60 year period within the Chukchi Sea (Ershova et al., 2015 <sup>[[#fn:r565|565]]</sup> ) and in recent years also the Beaufort Sea (Smoot and Hopcroft, 2017 <sup>[[#fn:r566|566]]</sup> ), while in the Central Basins zooplankton biomass in general has increased (Hunt et al., 2014 <sup>[[#fn:r567|567]]</sup> ; Rutzen and Hopcroft, 2018 <sup>[[#fn:r568|568]]</sup> ) ( ''medium confidence'' ).

There are inconsistent findings concerning the future development of copepods in the Arctic. Coupled biophysical model results suggest that sea ice loss will increase primary production and that will primarily be consumed pelagically by zooplankton grazers such as ''Calanus hyperboreus'' ; increasing their abundances in the central Arctic (Kvile et al., 2018 <sup>[[#fn:r569|569]]</sup> ). Feng et al. (2018) concluded that ''C. glacialis'' should continue to benefit from a warmer Arctic Ocean. On the other hand, in the transition zone between Arctic and Atlantic water masses, ''C. glacialis'' may face increasing competition from the more boreal ''C. finmarchicus'' (Dalpadado et al., 2016 <sup>[[#fn:r571|571]]</sup> ). Renaud et al. (2018) <sup>[[#fn:r572|572]]</sup> found the lipid content of ''Calanus'' spp. was related to size and not species. This suggests that climate driven shifts in dominant ''Calanus'' species may, because of overlap in size spectrum and contrary to earlier assumptions, not negatively impact their consumers in the Barents Sea.

The effects of ocean acidification on Arctic zooplankton and pteropods (small pelagic molluscs) have been examined for only a few species and these studies reveal that the severity of effects is dependent on emission scenarios and the species sensitivity and adaptive capacity. The copepod ''C. glacialis'' exhibits stage-specific sensitivities to ocean acidification with some stages being relatively insensitive to decreases in pH and other stages exhibiting substantial reductions in scope for growth (Bailey et al., 2017 <sup>[[#fn:r573|573]]</sup> ; Thor et al., 2018 <sup>[[#fn:r574|574]]</sup> ). Although there is strong evidence that pteropods are sensitive to the effects of ocean acidification (Manno et al., 2017 <sup>[[#fn:r575|575]]</sup> ) recent studies indicate they may exhibit some ability to adapt (Peck et al., 2016 <sup>[[#fn:r576|576]]</sup> ; Peck et al., 2018 <sup>[[#fn:r577|577]]</sup> ). However, the metabolic costs of adaptation may be constraining, especially during periods of low food availability (Lischka and Riebesell, 2016 <sup>[[#fn:r578|578]]</sup> ).

<div id="section-3-2-3-1-arctic-block-3"></div>

<span id="benthic-communities"></span>
===== 3.2.3.1.2 Benthic communities =====

There is evidence that earlier spring sea ice retreat and later autumn sea ice formation (Section 3.2.1.1) are changing the phenology of primary production with cascading effects on Arctic benthic community biodiversity and production (Link et al., 2013 <sup>[[#fn:r579|579]]</sup> ) ( ''medium confidence'' ). In the Barents Sea, evidence suggests that factors directly related to climate change (sea ice dynamics, ocean mixing, bottom-water temperature change, ocean acidification, river/glacier freshwater discharge; Sections 3.2.1.1, 3.2.1.2) are impacting the benthic species composition (Birchenough et al., 2015 <sup>[[#fn:r580|580]]</sup> ). Other human influenced activities, such as commercial bottom trawling and the introduction of non-native species are also regarded as major drivers of observed and expected changes in benthic community structure (Johannesen et al., 2017 <sup>[[#fn:r581|581]]</sup> ), and may interact with climate impacts.

Rapid and extensive structural changes in the rocky-bottom communities of two Arctic fjords in the Svalbard Archipelago during 1980–2010 have been documented and linked to gradually increasing seawater temperature and decreasing sea ice cover (Kortsch et al., 2012 <sup>[[#fn:r582|582]]</sup> ; Kortsch et al., 2015) <sup>[[#fn:r583|583]]</sup> . Also, there are indications of declining benthic biomass in the northern Bering Sea (Grebmeier and Cooper, 2016 <sup>[[#fn:r584|584]]</sup> ) and southern Chukchi Sea (Grebmeier et al., 2015 <sup>[[#fn:r585|585]]</sup> ). It is unclear whether these rapid ecosystem changes will be tipping points for local ecosystems (Chapter 6, Table 6.1; Wassmann and Lenton, 2012 <sup>[[#fn:r586|586]]</sup> ). However, biomass of kelps have increased considerably in the intertidal to shallow subtidal in Arctic regions over the last two decades, connected to reduced physical impact by ice scouring and increased light availability as a consequence of warming and concomitant fast-ice retreat (Kortsch et al., 2012 <sup>[[#fn:r587|587]]</sup> ; Paar et al., 2016 <sup>[[#fn:r588|588]]</sup> ) ( ''medium confidence'' ) (see Section 5.3.3 and SM3.2.6 for further information on kelp).

The growth, early survival and production of commercially important crab stocks in the Bering Sea are influenced by time-varying exposure to multiple interacting drivers including bottom temperature, larval advection, predation, competition and fishing (Burgos et al., 2013 <sup>[[#fn:r589|589]]</sup> ; Long et al., 2015 <sup>[[#fn:r590|590]]</sup> ; Ryer et al., 2016 <sup>[[#fn:r591|591]]</sup> ). In Newfoundland and Labrador waters and on the western Scotian Shelf, snow crab ( ''Chionoecetes opilio'' ) productivity has declined (Mullowney et al., 2014 <sup>[[#fn:r592|592]]</sup> ; Zisserson and Cook, 2017 <sup>[[#fn:r593|593]]</sup> ). Contrary to this, snow crabs have expanded their distribution in the Barents Sea and commercial harvesting increased (Hansen, 2016 <sup>[[#fn:r594|594]]</sup> ; Lorentzen et al., 2018 <sup>[[#fn:r595|595]]</sup> ) ( ''high confidence'' ).

Bering sea crabs exhibit species-specific sensitivities to reduced pH (Long et al., 2017 <sup>[[#fn:r596|596]]</sup> ; Swiney et al., 2017 <sup>[[#fn:r597|597]]</sup> ; Long et al., 2019 <sup>[[#fn:r598|598]]</sup> ). However, current pH levels do not appear to have negatively impacted crab production in the Bering or Barents Seas (Mathis et al., 2015 <sup>[[#fn:r599|599]]</sup> ; Punt et al., 2016 <sup>[[#fn:r600|600]]</sup> ).

<div id="section-3-2-3-1-arctic-block-4"></div>

<span id="fish"></span>
===== 3.2.3.1.3 Fish =====

Since AR5, additional evidence shows climate-induced physical and biogeochemical changes are impacting, and will continue to impact, the distribution and production of marine fish ( ''medium confidence'' ). Changes in the spatial distribution and production of Arctic fish are best documented for ecologically and commercially important stocks in the Bering and Barents Seas (Box 3.4; Figure 3.5), while data is severely limited in other Arctic shelf regions and the Central Arctic Ocean (CAO).

Higher temperature and changes in the quality and distribution of prey is already affecting marine fish (Wassmann et al., 2015 <sup>[[#fn:r601|601]]</sup> ; Dalpadado et al., 2016 <sup>[[#fn:r602|602]]</sup> ; Hunt et al., 2016 <sup>[[#fn:r603|603]]</sup> ; Section 3.2.3.1) ( ''high confidence'' for detection '', medium confidence'' for attribution). In the northern Barents Sea, Atlantic Sector, higher temperatures (Section 3.2.1.2) have expanded suitable feeding areas for boreal/subarctic species (Box 3.4) and has contributed to increased Atlantic cod ( ''Gadus morhua'' ) production (Kjesbu et al., 2014 <sup>[[#fn:r604|604]]</sup> ). In contrast, Arctic species like polar cod ( ''Boreogadus saida'' ) are expected to be affected negatively by a shortened ice covered season and reduced sea ice extent through loss of spawning habitat and shelter, increased predatory pressure, reduced prey availability (Christiansen, 2017 <sup>[[#fn:r605|605]]</sup> ), and impaired growth and reproductive success (Nahrgang et al., 2014 <sup>[[#fn:r606|606]]</sup> ). These changes may cause structural changes in food webs, with large piscivorous and semipelagic boreal fish species replacing small bodied Arctic benthivores (Box 3.4; Fossheim et al., 2015 <sup>[[#fn:r607|607]]</sup> ; Frainer et al., 2017 <sup>[[#fn:r608|608]]</sup> ).

Time series on responses of anadromous fish (including salmon) in the high Arctic are limited, although these stocks will also be exposed to a wide range of future stressors (Reist et al., 2016 <sup>[[#fn:r609|609]]</sup> ). There is some evidence that environmental variability influences the production of anadromous species such as Arctic char ( ''Salvelinus alpinus'' ), brown trout ( ''Salmo trutta'' ), and Atlantic salmon ( ''Salmo salar'' ) through its influence on growth and winter survival (Jensen et al., 2018 <sup>[[#fn:r610|610]]</sup> ).

<span id="figure-3.5"></span>
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'''Figure 3.5'''

<span id="schematic-summary-of-key-drivers-that-are-causing-or-are-projected-to-cause-direct-effects-on-arctic-marine-ecosystems-section-3.2.1.2.-effects-presented-here-are-described-in-the-main-text-sections-3.2.3.1-3.2.4.1.1-3.2.4.2-3.2.4.3-with-associated-confidence-levels-and-citations.-for-mixed-effects-no-confidence-level-is-given-see-main-text-for-details-on"></span>
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'''Schematic summary of key drivers that are causing, or are projected to cause, direct effects on Arctic marine ecosystems (Section 3.2.1.2). Effects presented here are described in the main text (Sections 3.2.3.1; 3.2.4.1.1; 3.2.4.2; 3.2.4.3) with associated confidence levels and citations. For mixed effects, no confidence level is given (see main text for details on […]'''
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[[File:b9febfe6dc3285f5ce48ec8097e23c96 IPCC-SROCC-CH_3_5.jpg]]

Schematic summary of key drivers that are causing, or are projected to cause, direct effects on Arctic marine ecosystems (Section 3.2.1.2). Effects presented here are described in the main text (Sections 3.2.3.1; 3.2.4.1.1; 3.2.4.2; 3.2.4.3) with associated confidence levels and citations. For mixed effects, no confidence level is given (see main text for details on how multiple drivers cause interacting positive and negative effects). Projected effects are conceptual representations based on high emission scenarios (Section 3.2.1.2). The cross-sectional view of the Arctic ecosystem shows the association of key functional groups (marine mammals, birds, fish, zooplankton, phytoplankton and benthic assemblages) with Arctic marine habitats. Species depicted in the fishing net are not a comprehensive depiction of all target species.

The scope for adaptation of marine fish to a changing ocean conditions is uncertain, but knowledge is informed by previous biogeographic studies (Chernova, 2011 <sup>[[#fn:r611|611]]</sup> ; Lynghammar et al., 2013 <sup>[[#fn:r612|612]]</sup> ). The present niche partitioning between subarctic and Arctic pelagic fish species is expected to become more diffuse with potential negative impacts on cold adapted species such as polar cod (Laurel et al., 2017 <sup>[[#fn:r613|613]]</sup> ; Alabia et al., 2018 <sup>[[#fn:r614|614]]</sup> ; Logerwell et al., 2018 <sup>[[#fn:r615|615]]</sup> ) ( ''low confidence'' ). Winter ocean conditions in the high Arctic are projected to remain cold in most regions (Section 3.2.3.1), limiting the immigration of subarctic species that spawn in positive temperatures onto the high Arctic shelves (Landa et al., 2014 <sup>[[#fn:r616|616]]</sup> ). Projected increases in summer temperature may open gateways to subarctic pelagic foragers in summer, particularly in the inflow regions of the Kara and Chukchi Seas, and the shelf regions of east and west Greenland (Mueter et al., 2017 <sup>[[#fn:r617|617]]</sup> ; Joli et al., 2018 <sup>[[#fn:r618|618]]</sup> ). For example, t he pelagic capelin ( ''Mallotus villosus'' ) are capable of entering the CAO, but may be restricted in winter by availability of suitable spawning areas and lack of antifreeze proteins (Hop and Gjøsæter, 2013 <sup>[[#fn:r619|619]]</sup> ; Christiansen, 2017 <sup>[[#fn:r620|620]]</sup> ).

Regional climate scenarios, derived from down-scaled global climate scenarios, have been used to drive environmentally linked fish population models (Hermann et al., 2016 <sup>[[#fn:r621|621]]</sup> ; Holsman et al., 2016 <sup>[[#fn:r622|622]]</sup> ; Ianelli et al., 2016 <sup>[[#fn:r623|623]]</sup> ; Hermann et al., 2019 <sup>[[#fn:r624|624]]</sup> ). Hermann et al. (2019) <sup>[[#fn:r625|625]]</sup> contrasted future production of copepods and euphausiids in the eastern Bering Sea under scenarios derived from projected downscaled high spatial and temporal resolution ocean habitats under RCP4.5 and RCP8.5. Consistent with AR5, these updated scenarios project future declines in the abundance of large copepods under RCP8.5, a result that has been shown to negatively impact production of walleye pollock, Pacific cod ( ''Gadus microcephalus'' ) and arrowtooth flounder ( ''Atheresthes stomias'' ) (Sigler et al., 2017 <sup>[[#fn:r626|626]]</sup> ; Kimmel et al., 2018 <sup>[[#fn:r627|627]]</sup> ) ( ''medium confidence'' ). Hedger et al. (2013) predicts increases in Atlantic salmon abundance in northern Norway (river Alta around 70°N) with future warming ( ''low confidence'' ). Under end of century RCP8.5 projections, ocean acidification and higher ocean temperatures are expected to reduce production of Barents Sea cod (Stiasny et al., 2016 <sup>[[#fn:r629|629]]</sup> ; Koenigstein et al., 2018 <sup>[[#fn:r630|630]]</sup> ) ( ''low confidence'' ).

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<div id="section-3-2-3-1-arctic-block-5"></div>

<span id="seabirds-and-marine-mammals"></span>
===== 3.2.3.1.4 Seabirds and marine mammals =====

Environmental alterations caused by global warming are resulting in phenological, behavioural, physiological, and distributional changes in Arctic marine mammal and seabird populations (Gilg et al., 2012 <sup>[[#fn:r631|631]]</sup> ; Laidre et al., 2015 <sup>[[#fn:r632|632]]</sup> ; Gall et al., 2017 <sup>[[#fn:r633|633]]</sup> ) ( ''high confidence'' ). These changes include altered ecological interactions as well as direct responses to habitat degradation induced especially via loss of sea ice. Population responses to warming have not all been linear, some have been particularly strong and abrupt due to environmental regime shifts, as seen in black-legged kittiwakes ( ''Rissa tridactyla'' ). A steep population decline in kittiwake colonies distributed throughout their breeding range coincided with an abrupt warming of sea surface temperature in the 1990s, while their population dynamics did not seem to be affected during periods of more gradual warming (Descamps et al., 2017 <sup>[[#fn:r634|634]]</sup> ).

Seabirds and marine mammals are mobile animals that respond to changes in the distribution of their preferred habitats and prey, by shifting their range, altering the timing or pathways for migration or prey shifting when this is feasible (Post et al., 2013 <sup>[[#fn:r635|635]]</sup> ; Hamilton et al., 2019 <sup>[[#fn:r636|636]]</sup> ) ( ''very high confidence'' ). However, some species display strong site fidelity that can be maladaptive in a changing climate and Arctic endemic marine mammals (all of which are ice-affiliated for breeding) in general have little scope to move northward in response to warming (Kovacs et al., 2012 <sup>[[#fn:r637|637]]</sup> ; Hamilton et al., 2015 <sup>[[#fn:r638|638]]</sup> ). Changes in the location or availability of polar fronts, polynyas, tidal glacier fronts or ice edges have impacted where Arctic sea birds and marine mammals concentrate because of the influence these physical features have on productivity; traditionally these areas have been key foraging sites for top predators in the Arctic (deHart and Picco, 2015 <sup>[[#fn:r639|639]]</sup> ; Hamilton et al., 2017 <sup>[[#fn:r640|640]]</sup> ; Hunt et al., 2018 <sup>[[#fn:r641|641]]</sup> ).

In some species, shifts in distribution in response to changes in suitable habitat have been associated with increased mortality. Increased mortality rates of walrus ( ''Odobenus rosmarus)'' calves have been observed during on-shore stampedes of unusually large herds, because Pacific walrus females are no longer able to haul out on ice over the shelf in summer due to the retraction of the southern ice edge into the deep Arctic Ocean (Kovacs et al., 2016 <sup>[[#fn:r642|642]]</sup> ). Shifts in the temporal and spatial distribution and availability of suitable areas of sea ice for ice-breeding seals have occurred (Bajzak et al., 2011 <sup>[[#fn:r643|643]]</sup> ; Øigård et al., 2013 <sup>[[#fn:r6|6]]</sup> 44) with increases in strandings and pup mortality in years with little ice (Johnston et al., 2012c <sup>[[#fn:r645|645]]</sup> ; Soulen et al., 2013 <sup>[[#fn:r646|646]]</sup> ; Stenson and Hammill, 2014 <sup>[[#fn:r647|647]]</sup> ).

Climate impacts that reduce the availability of prey resources can negatively impact marine mammals (Asselin et al., 2011; Øigård et al., 2014; Choy et al., 2017) ( ''very high confidence'' ). Sea ice changes have increased the foraging effort of ringed seals ( ''Pusa hispida'' ) in the marginal ice zone north of Svalbard (Hamilton et al., 2015 <sup>[[#fn:r651|651]]</sup> ), also causing diet shifts (Lowther et al., 2017 <sup>[[#fn:r652|652]]</sup> ). Ringed seals in Svalbard are using terrestrial haul out sites during summer for the first time in observed history, following major declines in sea ice (Lydersen et al., 2017 <sup>[[#fn:r653|653]]</sup> ), an example of an adaptive behavioural response to extreme habitat changes. Sea ice related changes in the export of production to the benthos (Section 3.3.3.1) and associated changes in the benthic community (Section 3.4.1.1.2) may impact marine mammals dependent on benthic prey (e.g., walruses and gray whales, ''Eschrichtius robustus'' ) (Brower et al., 2017 <sup>[[#fn:r654|654]]</sup> ; Udevitz et al., 2017 <sup>[[#fn:r655|655]]</sup> ; Szpak et al., 2018 <sup>[[#fn:r656|656]]</sup> ).

Changes in the timing, distribution and thickness of sea ice and snow (Sections 3.2.1.1, 3.4.1.1) have been linked to phenological shifts, and changes in distribution, denning, foraging behaviour and survival rates of polar bears ( ''Ursus maritimus'' ) (Andersen et al., 2012 <sup>[[#fn:r657|657]]</sup> ; Hamilton et al., 2017 <sup>[[#fn:r658|658]]</sup> ; Escajeda et al., 2018 <sup>[[#fn:r659|659]]</sup> ) ( ''high confidence'' ). Less ice is also driving polar bears to travel over greater distances and swim more than previously both in offshore and in coastal areas, which can be particularly dangerous for young cubs (Durner et al., 2017 <sup>[[#fn:r660|660]]</sup> ; Pilfold et al., 2017 <sup>[[#fn:r661|661]]</sup> ; Lone et al., 2018 <sup>[[#fn:r662|662]]</sup> ). Cumulatively, changes in sea ice patterns are driving demographic changes in polar bears, including declines in some populations (Lunn et al., 2016 <sup>[[#fn:r663|663]]</sup> ; McCall et al., 2016 <sup>[[#fn:r664|664]]</sup> ), while others are stable or increasing (Voorhees et al., 2014 <sup>[[#fn:r665|665]]</sup> ; Aars et al., 2017 <sup>[[#fn:r666|666]]</sup> ). This is because protective management measures have been successful in allowing severely depleted populations to recover or because new food sources, such as carrion, are becoming available to polar bears in some regions (Galicia et al., 2016 <sup>[[#fn:r667|667]]</sup> ; Stapleton et al., 2016 <sup>[[#fn:r668|668]]</sup> ). Changes in the spatial distribution of polar bears and killer whales can have top-down effects on other marine mammal prey populations (Øigård et al., 2014 <sup>[[#fn:r669|669]]</sup> ; Breed et al., 2017 <sup>[[#fn:r670|670]]</sup> ; Smith et al., 2017a <sup>[[#fn:r671|671]]</sup> ).

Several studies from different parts of the Arctic show evidence that changing temperatures impact seabird diets (Dorresteijn et al., 2012 <sup>[[#fn:r672|672]]</sup> ; Divoky et al., 2015 <sup>[[#fn:r673|673]]</sup> ; Vihtakari et al., 2018 <sup>[[#fn:r674|674]]</sup> ), reproductive success and body condition (Gaston et al., 2012 <sup>[[#fn:r675|675]]</sup> ; Provencher et al., 2012 <sup>[[#fn:r676|676]]</sup> ; Gaston and Elliott, 2014 <sup>[[#fn:r677|677]]</sup> ) ( ''high confidence'' ). Recent studies also show that changes in sea surface temperature and sea ice dynamics have impacts on the distribution and abundance of seabird prey with cascading impacts on seabird community composition (Gall et al., 2017 <sup>[[#fn:r678|678]]</sup> ), nutritional stress and decreased reproductive output (Dorresteijn et al., 2012 <sup>[[#fn:r679|679]]</sup> ; Divoky et al.; Kokubun et al., 2018 <sup>[[#fn:r680|680]]</sup> ) and survival (Renner et al., 2016 <sup>[[#fn:r681|681]]</sup> ; Hunt et al., 2018 <sup>[[#fn:r682|682]]</sup> ).

<div id="section-3-2-3-2-southern-ocean"></div>

<span id="southern-ocean"></span>
==== 3.2.3.2 3.2.3.2 Southern Ocean ====

<div id="section-3-2-3-2-southern-ocean-block-1"></div>

Marine ecosystem dynamics in the Antarctic region are dominated by the ACC and its frontal systems (Cross-Chapter Box 7 in Chapter 3), subpolar gyres, polar seasonality, the annual advance and retreat of sea ice (Section 3.2.1.1) and the supply of limiting micronutrients for productivity (most commonly iron) (Section 5.2.2.5). Antarctic krill ( ''Euphausia superba'' ) play a central role in Southern Ocean foodwebs as grazers and as prey items for fish, squid, marine mammals and seabirds (Schmidt and Atkinson, 2016 <sup>[[#fn:r683|683]]</sup> ; Trathan and Hill, 2016 <sup>[[#fn:r684|684]]</sup> ) (SM3.2.6). This is due in part to the high abundance and circumpolar distribution of Antarctic krill, although the abundance and importance of this species varies between different regions of the Southern Ocean (Larsen et al., 2014 <sup>[[#fn:r685|685]]</sup> ; Siegel, 2016 <sup>[[#fn:r686|686]]</sup> ; McCormack et al., 2017 <sup>[[#fn:r687|687]]</sup> ). Recent work has characterised the nature of habitat change for Southern Ocean biota at regional and circumpolar scales (Constable et al., 2014 <sup>[[#fn:r688|688]]</sup> ; Gutt et al., 2015 <sup>[[#fn:r689|689]]</sup> ; Constable et al., 2016 <sup>[[#fn:r690|690]]</sup> ; Hunt et al., 2016 <sup>[[#fn:r691|691]]</sup> ; Gutt et al., 2018 <sup>[[#fn:r692|692]]</sup> ), and the direct responses of biota to these changes (Constable et al., 2014 <sup>[[#fn:r693|693]]</sup> ) (summarised in Figure 3.6). These findings indicate that overlapping changes in key ocean and sea ice habitat characteristics (temperature, sea ice cover, iceberg scour, mixed layer depth, aragonite undersaturation; Sections 3.2.1, 3.2.2) will be important in determining future states of Southern Ocean ecosystems (Constable et al., 2014 <sup>[[#fn:r694|694]]</sup> ; Gutt et al., 2015 <sup>[[#fn:r695|695]]</sup> ) ( ''medium confidence'' ). However, there is a need to better characterise the nature and importance of indirect responses to physical change using models and observations. Important advances have also been made since AR5 in (i) identifying key variables to detect and attribute change in Southern Ocean ecosystems, as part of long-term circumpolar modelling designs (Constable et al., 2016 <sup>[[#fn:r696|696]]</sup> ), and (ii) refining methods for using sea ice projections from global climate models in ecological studies and ecosystem models for the Southern Ocean (Cavanagh et al., 2017 <sup>[[#fn:r697|697]]</sup> ).

<div id="section-3-2-3-2-southern-ocean-block-2"></div>

<span id="plankton-and-pelagic-primary-production"></span>
===== 3.2.3.2.1 Plankton and pelagic primary production =====

Changes in column-integrated phytoplankton biomass for the Southern Ocean are coupled with changes in the spatial extent of ice-free waters, suggesting little overall change in biomass per area at the circumpolar scale (Behrenfeld et al., 2016 <sup>[[#fn:r698|698]]</sup> ). Arrigo et al. (2008) <sup>[[#fn:r699|699]]</sup> also report no overall trend in remotely-sensed column-integrated primary production south of 50 ° S from 1998 to 2006. At a regional scale, local-scale forcings (e.g., retreating glaciers, topographically steered circulation and sea ice duration) and associated changes in stratification are key determinants of phytoplankton bloom dynamics at coastal stations on the West Antarctic Peninsula (Venables et al., 2013 <sup>[[#fn:r700|700]]</sup> ; Schofield et al., 2017 <sup>[[#fn:r701|701]]</sup> ; Kim et al., 2018 <sup>[[#fn:r702|702]]</sup> ; Schofield et al., 2018 <sup>[[#fn:r703|703]]</sup> ) ( ''medium confidence'' ). For example, a shallowing trend in mixed layer depth in the southern part of the Peninsula (as opposed to no trend in the north) associated with changes in sea ice duration over a 24-year period (from 1993 to 2017) has been linked to enhanced phytoplankton productivity (Schofield et al., 2018 <sup>[[#fn:r704|704]]</sup> ). The phenology of Southern Ocean phytoplankton blooms in this region may also be shifting to earlier in the growth season (Arrigo et al., 2017a <sup>[[#fn:r705|705]]</sup> ). However, the effect of climate change on Southern Ocean pelagic primary production is difficult to determine given that the length of time series data is insufficient (less than 30 years) to enable the climate change signature to be detected and attributed; and that, even when records are of sufficient length, data trends are often reported as being driven by climate change when they are due to a combination of climate change and variability.

Recent studies on the ecological effects of acidification in coastal waters near the Antarctic continent indicate a detrimental effect of acidification on primary production and changes to the structure and function of microbial communities (Hancock et al., 2017 <sup>[[#fn:r706|706]]</sup> ; Deppeler et al., 2018 <sup>[[#fn:r707|707]]</sup> ; Westwood et al., 2018 <sup>[[#fn:r708|708]]</sup> ) ( ''medium confidence'' ). Trimborn et al. (2017) report that Southern Ocean diatoms are more sensitive to ocean acidification and changes in irradiance than the prymnesiophyte ''Phaeocystis antarctica'' , which may have implications for biogeochemical cycling because diatoms and prymnesiophytes are generally considered key drivers of these cycles. Both laboratory manipulations and ''in situ'' experiments indicate that sea ice algae are tolerant to acidification (McMinn, 2017 <sup>[[#fn:r709|709]]</sup> ) ( ''medium confidence'' ). Model projections of trends in primary production in the Southern Ocean due to climate change from Leung et al. (2015) <sup>[[#fn:r710|710]]</sup> are summarised in Table 3.2.

<span id="section-2"></span>
<!-- START TABLE -->
'''Table 3.2:''' Model projections of trends due to climate change driven alteration of phytoplankton properties under RCP8.5 from 2006 to 2100 across three zones of the Southern Ocean, from Leung et al. (2015) <sup>[[#fn:r711|711]]</sup> . There is ''low confidence '' in predicted zonal changes in phytoplankton biomass due to  ''low confidence '' regarding future changes in iron supply in the Southern Ocean (Hutchins and Boyd, 2016 <sup>[[#fn:r712|712]]</sup> ). Acidification was not reported as an important driver in this modelling experiment.

<!-- TABLE -->
{| class="wikitable"
|-
| Zonal Band
| Predicted change in phytoplankton biomass
| Drivers
| Mechanisms
|-
| 40 ° S–50 ° S
| [[File:702f6140bb33c093f79f5159ebebed41 arrowup.png]]
| Higher mean underwater irradiance
More iron supply

| Shallowing of the summertime mixed layer depth
Change in iron supply mechanism

|-
| 50 ° S–65 ° S
| [[File:afb97dd099f055cf73abda49d9421cff arrowdown.png]]
| Lower mean underwater irradiance
| Deeper summertime mixed layer depth
Decreased summertime incident radiation (increased cloud fraction)

|-
| South of 65 ° S
| [[File:702f6140bb33c093f79f5159ebebed41 arrowup.png]]
| More iron supply
Higher mean underwater irradiance

Temperature

| Melting of sea ice
Warming ocean

|}
<!-- END TABLE -->

Previously reported declines in Antarctic krill abundance in the South Atlantic Sector (Atkinson et al., 2004 <sup>[[#fn:r725|725]]</sup> ) cited in WGII AR5 (Larsen et al., 2014 <sup>[[#fn:r726|726]]</sup> ) may not represent a long-term, climate driven, regional-scale decline (Fielding et al., 2014 <sup>[[#fn:r727|727]]</sup> ; Kinzey et al., 2015 <sup>[[#fn:r728|728]]</sup> ; Steinberg et al., 2015 <sup>[[#fn:r729|729]]</sup> ; Cox et al., 2018 <sup>[[#fn:r730|730]]</sup> ) ( ''medium confidence'' ) but could reflect a sudden, discontinuous change following an episodic period of anomalous peak abundance for this species (Loeb and Santora, 2015 <sup>[[#fn:r731|731]]</sup> ) ( ''low confidence'' ). Recent analyses have not detected trends in long-term krill abundance in the South Atlantic Sector in acoustic surveys (Fielding et al., 2014 <sup>[[#fn:r732|732]]</sup> ; Kinzey et al., 2015 <sup>[[#fn:r733|733]]</sup> ), net-based surveys (Steinberg et al., 2015 <sup>[[#fn:r734|734]]</sup> ) or reanalysis of historical data (Cox et al., 2018 <sup>[[#fn:r735|735]]</sup> ). Nevertheless, the spatial distribution and size composition of Antarctic krill may already have changed in association with change in the sea ice environment (Atkinson et al., 2019 <sup>[[#fn:r736|736]]</sup> ) ( ''medium confidence'' ) and may result in different regional trends in numerical krill abundance (Cox et al., 2018 <sup>[[#fn:r737|737]]</sup> ; Atkinson et al., 2019 <sup>[[#fn:r738|738]]</sup> ) ( ''medium confidence'' ).

The distribution of Antarctic krill is expected to change under future climate change because of changes in the location of the optimum conditions for growth and recruitment (Melbourne-Thomas et al., 2016 <sup>[[#fn:r739|739]]</sup> ; Piñones and Fedorov, 2016 <sup>[[#fn:r740|740]]</sup> ; Meyer et al., 2017 <sup>[[#fn:r741|741]]</sup> ; Murphy et al., 2017 <sup>[[#fn:r742|742]]</sup> ; Klein et al., 2018 <sup>[[#fn:r743|743]]</sup> ). The optimum conditions for krill are predicted to move southwards, with the decreases most apparent in the areas with the most rapid warming (Hill et al., 2013 <sup>[[#fn:r744|744]]</sup> ; Piñones and Fedorov, 2016 <sup>[[#fn:r745|745]]</sup> ) (Section 3.2.1.2.1) ( ''medium confidence'' ). The greatest projected reductions in krill due to the effects of warming and ocean acidification are predicted for the southwest Atlantic/Weddell Sea region (Kawaguchi et al., 2013 <sup>[[#fn:r746|746]]</sup> ; Piñones and Fedorov, 2016 <sup>[[#fn:r747|747]]</sup> ) ( ''low confidence'' ), which is the area of highest current krill concentrations, contains important foraging grounds for krill predators, and is also the main area of operation of the krill fishery. Modelled effects of warming on krill growth in the Scotia Sea and northern Antarctic Peninsula (AP) region resulted in reductions in total krill biomass under both RCP2.6 and RCP8.5 (Klein et al., 2018 <sup>[[#fn:r748|748]]</sup> ). Projections from a food web model for the West Antarctic Peninsula under simple scenarios for change in open water and sea ice-associated primary production from 2010 to 2050 (6, 15, and 41% increases in phytoplankton production with equivalent percentage decreases in ice algal production) indicate a decline in krill biomass with contemporaneous increases in the biomass of gelatinous salps (Suprenand and Ainsworth, 2017 <sup>[[#fn:r749|749]]</sup> ).

Current understanding of climate change effects on Southern Ocean zooplankton is largely based on observations and predictions from the South Atlantic and the West Antarctic Peninsula. Comparison of the mesozooplankton community in the southwestern Atlantic Sector between 1926–1938 and 1996–2013 showed no evidence of change despite surface ocean warming (Tarling et al., 2018 <sup>[[#fn:r713|713]]</sup> ). These results suggest that predictions of distributional shifts based on temperature niches may not reflect the actual levels of thermal resilience of key taxa. Sub-decadal cycles of macrozooplankton community composition adjacent to the West Antarctic Peninsula are strongly linked to climate indices, with evidence of increasing abundance for some species over the period from 1993 to 2013 (Steinberg et al., 2015 <sup>[[#fn:r714|714]]</sup> ). Pteropods are vulnerable to the effects of acidification, and new evidence indicates that eggs released at high CO 2 concentrations lack resilience to ocean acidification in the Scotia Sea region (Manno et al., 2016 <sup>[[#fn:r715|715]]</sup> ) ( ''medium confidence'' ).

<div id="section-3-2-3-2-southern-ocean-block-3"></div>

<span id="benthic-communities-1"></span>
===== 3.2.3.2.2 Benthic communities =====

Carbon uptake and storage by Antarctic benthic communities is predicted to increase with sea ice losses, because across-shelf growth gains from longer algal blooms outweigh ice scour mortality in the shallows (Barnes, 2017 <sup>[[#fn:r716|716]]</sup> ). Bentho-pelagic coupling and vertical energy flux will also influence Southern Ocean ecosystem responses to climate change (Jansen et al., 2017 <sup>[[#fn:r717|717]]</sup> ). Benthic communities in shallow water habitats mostly consist of dark-adapted invertebrates and rely on sea ice to create low-light marine environments. Increases in the amount of light reaching the shallow seabed under climate change may result in ecological regime shifts, in which invertebrate-dominated communities are replaced by macroalgal beds (Clark et al., 2015 <sup>[[#fn:r718|718]]</sup> ; Clark et al., 2017 <sup>[[#fn:r719|719]]</sup> ) ( ''low confidence'' ) (Table 6.1). Griffiths et al. (2017a) <sup>[[#fn:r720|720]]</sup> modelled distribution changes for 963 benthic invertebrate species in the Southern Ocean under RCP8.5 for 2099. Their results suggest that 79% of Antarctica’s endemic species will face a reduction in suitable temperature habitat (an average 12% reduction) over the current century. Predicted reductions in the number of species are most pronounced for the West Antarctic Peninsula and the Scotia Sea region (Griffiths et al., 2017a <sup>[[#fn:r720|720]]</sup> ).

<div id="section-3-2-3-2-southern-ocean-block-4"></div>

<span id="fish-1"></span>
===== 3.2.3.2.3 Fish =====

Many Antarctic fish have a narrow thermal tolerance as a result of physiological adaptations to cold water (Pörtner et al., 2014 <sup>[[#fn:r721|721]]</sup> ; Mintenbeck, 2017 <sup>[[#fn:r722|722]]</sup> ), which makes them vulnerable to the effects of increasing temperatures (Mueller et al., 2012 <sup>[[#fn:r723|723]]</sup> ; Beers and Jayasundara, 2015 <sup>[[#fn:r724|724]]</sup> ). Increasing water temperatures may displace icefish (family ''Channichthyidae'' ) in marginal habitats (e.g., shallow regions around subantarctic islands) as they lack haemoglobin and are unable to adjust blood parameters to an increasing oxygen demand (Mintenbeck et al., 201250‹) ( ''low confidence'' ). Future warming may also reduce the planktonic duration and increase egg and larval mortality for fish species, which is predicted to affect dispersal patterns, with implications for population connectivity and the ability of fish species to adapt to ongoing environmental change (Young et al., 2018 <sup>[[#fn:r751|751]]</sup> ). The Antarctic silverfish ( ''Pleuragramma antarctica'' ) is an important prey species in some regions of the Southern Ocean, and has an ice-dependent life cycle (Mintenbeck et al., 2012 <sup>[[#fn:r752|752]]</sup> ; Vacchi et al., 2012 <sup>[[#fn:r753|753]]</sup> ). Documented declines in the abundance of this species in some parts of the West Antarctic Peninsula may have consequences for associated food webs (Parker et al., 2015 <sup>[[#fn:r754|754]]</sup> ; Mintenbeck and Torres, 2017 <sup>[[#fn:r755|755]]</sup> ) ( ''low confidence'' ).

Myctophids and toothfish are important fish groups from both a food web (myctophids) and fishery (toothfish) perspective. Species distribution models for ''Electrona antarctica'' , a dominant myctophid species in the Southern Ocean, project habitat loss for this species under RCP4.5 (6.2 ± 6.0% loss) and RCP8.5 (13.1 ± 10.2% loss) by 2090, associated with increased sea surface temperature (Freer et al., 2018 <sup>[[#fn:r756|756]]</sup> ) ''.'' There have been no observed effects of climate change on the two species of toothfish that are found in the Southern Ocean: Patagonian and Antarctic toothfish ( ''Dissostichus eleginoides'' and ''D. mawsoni'' ), but recruitment is inversely correlated with sea surface temperature for Patagonian toothfish at South Georgia (Belchier and Collins, 2008 <sup>[[#fn:r757|757]]</sup> ). Given differences in temperature tolerances for Patagonian toothfish (with a wide temperature tolerance) and Antarctic toothfish (limited by a low tolerance for water temperatures above 2°C), the latter may be faced with reduced habitat and potential competition with southward-moving Patagonian toothfish under climate change (Mintenbeck, 2017 <sup>[[#fn:r758|758]]</sup> ) ( ''very low confidence'' ).

<div id="section-3-2-3-2-southern-ocean-block-5"></div>

<span id="seabirds-and-marine-mammals-1"></span>
===== 3.2.3.2.4 Seabirds and marine mammals =====

Since AR5, there has been an increasing body of evidence of climate-induced changes in populations of some Antarctic higher predators such as seabirds and marine mammals. These changes vary between different regions of the Southern Ocean and reflect differences in key drivers (Bost et al., 2009 <sup>[[#fn:r759|759]]</sup> ; Gutt et al., 2015 <sup>[[#fn:r760|760]]</sup> ; Constable et al., 2016 <sup>[[#fn:r761|761]]</sup> ; Hunt et al., 2016 <sup>[[#fn:r762|762]]</sup> ; Gutt et al., 2018 <sup>[[#fn:r763|763]]</sup> ), particularly sea ice extent and food availability ( ''high confidence)'' across regions (Sections 3.2.1.1.1, 5.2.3.1, 5.2.3.2, 5.2.4). The predictability of foraging grounds and ice cover are associated with variations in climate (Dugger et al., 2014 <sup>[[#fn:r764|764]]</sup> ; Youngflesh et al., 2017 <sup>[[#fn:r765|765]]</sup> ; Abrahms et al., 2018 <sup>[[#fn:r766|766]]</sup> ) (Section 3.2.1.1) and are the main drivers of observed population changes of Southern Ocean higher predators ( ''high confidence'' ) (Descamps et al., 2015 <sup>[[#fn:r767|767]]</sup> ; Jenouvrier et al., 2015 <sup>[[#fn:r768|768]]</sup> ; Sydeman et al., 2015 <sup>[[#fn:r769|769]]</sup> ; Abadi et al., 2017 <sup>[[#fn:r770|770]]</sup> ; Bjorndal et al., 2017 <sup>[[#fn:r771|771]]</sup> ; Fluhr et al., 2017 <sup>[[#fn:r772|772]]</sup> ; Hinke et al., 2017a <sup>[[#fn:r773|773]]</sup> ; Hinke et al., 2017b <sup>[[#fn:r774|774]]</sup> ; Pardo et al., 2017 <sup>[[#fn:r775|775]]</sup> ). The suitability of breeding habitats and the location of environmental features that facilitate the aggregation of prey are also influenced by climate change, and in turn influence the distribution in space and time of marine mammals and birds (Bost et al., 2015 <sup>[[#fn:r776|776]]</sup> ; Kavanaugh et al., 2015 <sup>[[#fn:r777|777]]</sup> ; Hindell et al., 2016 <sup>[[#fn:r778|778]]</sup> ; Santora et al., 2017 <sup>[[#fn:r779|779]]</sup> ) ( ''medium confidence'' ). Finally, biological parameters (reproductive success, mortality, fecundity and body condition), life history traits, morphological, physiological and behavioural characteristics of top predators in the Southern Ocean, as well as their patterns of activity (migration, distribution, foraging and reproduction) are also changing as a result of climate change (Braithwaite et al., 2015a <sup>[[#fn:r780|780]]</sup> ; Whitehead et al., 2015 <sup>[[#fn:r781|781]]</sup> ; Seyboth et al., 2016 <sup>[[#fn:r782|782]]</sup> ; Hinke et al., 2017b <sup>[[#fn:r783|783]]</sup> ) ( ''high confidence'' ).

Trends of populations of Antarctic penguins affected by climate change include both increases for gentoo penguins, ( ''Pygoscelis papua'' ) (Lynch et al., 2013 <sup>[[#fn:r784|784]]</sup> ; Dunn et al., 2016 <sup>[[#fn:r785|785]]</sup> ; Hinke et al., 2017a <sup>[[#fn:r786|786]]</sup> ), and decreases for Adélie ( ''P. adeliae),'' chinstrap ( ''P. antarctica),'' king ( ''Aptenodytes patagonicus'' ) and Emperor ( ''A. forsteri'' ) penguins (Trivelpiece et al., 2011 <sup>[[#fn:r787|787]]</sup> ; LaRue et al., 2013 <sup>[[#fn:r788|788]]</sup> ; Jenouvrier et al., 2014 <sup>[[#fn:r789|789]]</sup> ; Bost et al., 2015 <sup>[[#fn:r790|790]]</sup> ; Southwell et al., 2015 <sup>[[#fn:r791|791]]</sup> ; Younger et al., 2015 <sup>[[#fn:r792|792]]</sup> ; Cimino et al., 2016 <sup>[[#fn:r793|793]]</sup> ) ( ''high confidence'' ). Yet population shifts in Adélie penguins (Youngflesh et al., 2017 <sup>[[#fn:r794|794]]</sup> ) may have resulted from strong interannual environmental variability in good and bad years for prey and breeding habitat rather than climate change ( ''low confidence'' ). New evidence suggests that present Emperor penguin population estimates should be evaluated with caution based on the existence of breeding colonies yet to be discovered/confirmed (Ancel et al., 2017 <sup>[[#fn:r795|795]]</sup> ) as well as studies that draw conclusions based on trend estimates from single colonies (Kooyman and Ponganis, 2017 <sup>[[#fn:r796|796]]</sup> ).

Evidence for climate change impacts on Antarctic flying birds indicates that contraction of sea ice (seasonally and in specific regions), increases in sea surface temperatures, extreme events (snowstorms) and wind regime shifts can reduce breeding success and population growth rates in some species: southern fulmars ( ''Fulmarus glacialoides'' ), Antarctic petrels ( ''Thalassoica antarctica'' ) and black-browed albatrosses ( ''Thalassarche melanophris'' ) (Descamps et al., 2015 <sup>[[#fn:r797|797]]</sup> ; Jenouvrier et al., 2015 <sup>[[#fn:r798|798]]</sup> ; Pardo et al., 2017 <sup>[[#fn:r799|799]]</sup> ) ( ''low confidence)'' . Poleward population shifts with increased intensity and frequency of westerly winds affect functional traits, demographic rates, foraging range, rates of travel and flight speeds of flying birds (Weimerskirch et al., 2012 <sup>[[#fn:r800|800]]</sup> ; Jenouvrier et al., 2018 <sup>[[#fn:r801|801]]</sup> ) but also increase overlap with fisheries activities thus increasing the risk of bycatch and the need for mitigation measures (Krüger et al., 2018 <sup>[[#fn:r802|802]]</sup> ) ( ''medium confidence)'' .

Changes in local- and regional-scale oceanographic features (Section 3.2.1.2) together with bathymetry control prey aggregation and distribution, and affect the ecological responses and biological traits of higher predators (particularly marine mammals) in the Southern Ocean (Lyver et al., 2014 <sup>[[#fn:r803|803]]</sup> ; Bost et al., 2015 <sup>[[#fn:r804|804]]</sup> ; Jenouvrier et al., 2015 <sup>[[#fn:r805|805]]</sup> ; Whitehead et al., 2015 <sup>[[#fn:r806|806]]</sup> ; Cimino et al., 2016 <sup>[[#fn:r807|807]]</sup> ; Hinke et al., 2017a <sup>[[#fn:r808|808]]</sup> ; Pardo et al., 2017 <sup>[[#fn:r809|809]]</sup> ) ( ''medium confidence'' ) and ''likely'' explain most of the observed population shifts (Kavanaugh et al., 2015 <sup>[[#fn:r810|810]]</sup> ; Hindell et al., 2016 <sup>[[#fn:r811|811]]</sup> ; Gurarie et al., 2017 <sup>[[#fn:r812|812]]</sup> ; Santora et al., 2017 <sup>[[#fn:r813|813]]</sup> ). Decadal climate cycles affect access to mesopelagic prey by southern elephant seals ( ''Mirounga leonina'' ) in the Indian Sector of the Southern Ocean and breeding females are excluded from highly productive continental shelf waters in years of increased sea ice extent and duration (Hindell et al., 2016 <sup>[[#fn:r814|814]]</sup> ) ( ''medium confidence)'' . To date there is no unified global estimate of the abundance of Antarctic pack ice seal species (Ross seals ( ''Ommatophoca rossi)'' , crabeater seals ( ''Lobodon carcinophaga)'' , leopard seals ( ''Hydrurga leptonyx)'' and Weddell seals ( ''Leptonychotes weddellii)'' ) as a reference point for understanding climate change impacts on these species (Southwell et al., 2012 <sup>[[#fn:r815|815]]</sup> ; Bester et al., 2017 <sup>[[#fn:r816|816]]</sup> ), although some regional population estimates for pack ice seals are available (Gurarie et al., 2017 <sup>[[#fn:r817|817]]</sup> and references therein). Analysis of long-term data suggests a genetic component to adaptation to climate change ( ''low confidence'' ) in Antarctic fur seals ( ''Arctocephalus gazella'' , Forcada and Hoffman (2014)) and pigmy blue whales ( ''Balaenoptera musculus brevicauda'' , Attard et al. (2015)).

Population trends of migratory baleen whales have been associated with krill abundance in the Atlantic and Pacific sectors of the Southern Ocean which is reflected in increased reproductive success, body condition and energy allocation (milk availability and transfer) to calves (Braithwaite et al., 2015a <sup>[[#fn:r818|818]]</sup> ; Braithwaite et al., 2015b <sup>[[#fn:r819|819]]</sup> ; Seyboth et al., 2016 <sup>[[#fn:r820|820]]</sup> ) ( ''high confidence'' ). There have been predictions of negative future impacts of climate change on krill and all whale species, although the magnitude of impacts differs among populations (Tulloch et al., 2019 <sup>[[#fn:r821|821]]</sup> ) as for other higher predators (Section 5. 2.3 ). Pacific blue (Tulloch et al., 2019 <sup>[[#fn:r822|822]]</sup> ) ( ''Balaenoptera musculus'' ), fin ( ''B. physalus'' ) and southern right whales ( ''Eubalaena australis'' ) are the most at risk but humpback whales ( ''Megaptera novaeangliae'' ) are also at risk, as consequence of reduced prey and increasing interspecific competition. Importantly, climate-related risks for whale populations are a product of environmental conditions and connectivity between whale foraging grounds (Southern Ocean) and breeding grounds (lower latitudes) (Section 5.2.3.1 ).

<div id="section-3-2-3-2-southern-ocean-block-6"></div>

<span id="pelagic-foodwebs-and-ecosystem-structure"></span>
===== 3.2.3.2.5 Pelagic foodwebs and ecosystem structure =====

This section assesses the impacts of ocean and sea ice changes on pelagic foodwebs and ecosystem structure. The ecological impacts of loss of ice shelves and retreat of coastal glaciers around Antarctica are assessed in Section 3.3.3.4. Recent syntheses of Southern Ocean ecosystem structure and function recognise the importance of at least two dominant energy pathways in pelagic foodwebs—a short trophic pathway transferring primary production to top predators via krill, and at least one other pathway that moves energy from smaller phytoplankton to top predators via copepods and small mesopelagic fishes—and indicate that the relative importance of these pathways will change under climate change (Murphy et al., 2013 <sup>[[#fn:r823|823]]</sup> ; Constable et al., 2016 <sup>[[#fn:r824|824]]</sup> ; Constable et al., 2017 <sup>[[#fn:r825|825]]</sup> ; McCormack et al., 2017 <sup>[[#fn:r826|826]]</sup> ) ( ''medium confidence'' ). Using an ecosystem model, Klein et al. (2018) <sup>[[#fn:r827|827]]</sup> found that the effects of warming on krill growth off the AP and in the Scotia Sea translated to increased risks of declines in krill predator populations, particularly penguins, under both RCP2.6 and RCP8.5. The relative importance of different energy pathways in Southern Ocean foodwebs has important implications for resource management, in particular the management of krill and toothfish fisheries by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) (Constable et al., 2016 <sup>[[#fn:r828|828]]</sup> ; Constable et al., 2017 <sup>[[#fn:r829|829]]</sup> ) (Sections 3.2.4.1.2, 3.5.3.2.2).

In summary, advances in knowledge regarding the impacts of climate change on Antarctic marine ecosystems since AR5 are consistent with the impacts described in Larsen et al. (2014) <sup>[[#fn:r830|830]]</sup> (also summarised in Figure 3.6). These advances include further descriptions of local-scale, climate-related influences (sea ice and stratification) on primary productivity, particularly in the West Antarctic Peninsula region (Section 3.2.3.2.1) ( ''medium confidence'' ). At the circumpolar scale, primary production is projected to increase in regions south of 65°S over the period from now to 2100 under RCP8.5 (Leung et al., 2015 <sup>[[#fn:r831|831]]</sup> ) ( ''low confidence'' ). However, ocean acidification may have a detrimental effect on coastal phytoplankton communities around the Antarctic continent (Section 3.2.3.2.1) ( ''medium confidence'' ). Increased information is also available regarding climate-driven changes in Antarctic krill populations in the south Atlantic, including the observed southward shift in the spatial distribution of krill in this region (Atkinson et al., 2019 <sup>[[#fn:r832|832]]</sup> ) ( ''medium confidence'' ) but evidence of a long-term trend in overall abundance in the region is equivocal (Section 3.2.3.2.1). Further habitat contraction for Antarctic krill is predicted in the future ( ''medium confidence'' ) (references detailed in Section 3.2.3.2.1). Under high emissions scenarios the majority of Antarctic seafloor species are projected to be negatively impacted by the end of the century (Griffiths et al., 2017a <sup>[[#fn:r833|833]]</sup> ) ( ''low confidence'' ). Observed changes in the geography of ice-associated habitats (sea ice, ice shelves and polynyas) have both positive and negative effects on seabirds and marine mammals, and will interact with ice dependent changes in Antarctic krill populations to compound the impacts on krill dependent predators (Klein et al., 2018 <sup>[[#fn:r834|834]]</sup> ) (Sections 3.2.3.2.1, 3.2.3.2.4) ( ''medium confidence'' ).

<span id="figure-3.6"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 3.6'''

<span id="schematic-summary-of-key-drivers-that-are-causing-or-are-projected-to-cause-direct-effects-on-southern-ocean-marine-ecosystems.-effects-presented-here-are-described-in-the-main-text-sections-3.2.3.2-3.3.3.4-with-associated-confidence-levels-and-citations.-projected-changes-indicated-by-an-asterisk-are-for-high-emissions-scenarios.-the-cross-sectional-view-of-the-southern"></span>
<!-- IMG CAPTION -->
'''Schematic summary of key drivers that are causing or are projected to cause direct effects on Southern Ocean marine ecosystems. Effects presented here are described in the main text (Sections 3.2.3.2, 3.3.3.4), with associated confidence levels and citations. Projected changes (indicated by an asterisk) are for high emissions scenarios. The cross-sectional view of the Southern […]'''
<!-- IMG FILE -->
[[File:49e88a41905cd8a2599ddce0e9957444 IPCC-SROCC-CH_3_6.jpg]]

Schematic summary of key drivers that are causing or are projected to cause direct effects on Southern Ocean marine ecosystems. Effects presented here are described in the main text (Sections 3.2.3.2, 3.3.3.4), with associated confidence levels and citations. Projected changes (indicated by an asterisk) are for high emissions scenarios. The cross-sectional view of the Southern Ocean ecosystem shows the association of key functional groups (marine mammals, birds, fish, zooplankton, phytoplankton and benthic assemblages) with Southern Ocean habitats. The configuration of the Southern Ocean foodweb is described in SM3.2.6.

<!-- END IMG -->
<span id="impacts-on-social-ecological-systems"></span>
=== 3.2.4 Impacts on Social-Ecological Systems ===

<div id="section-3-2-4-1-fisheries"></div>

<span id="fisheries"></span>
==== 3.2.4.1 Fisheries ====

<div id="section-3-2-4-1-fisheries-block-1"></div>

<span id="arctic-1"></span>
===== 3.2.4.1.1 Arctic =====

Arctic fisheries are important economically and societally. Large commercial fisheries exist off the coasts of Greenland and in the Barents and Bering Seas (Holsman et al., 2018 <sup>[[#fn:r835|835]]</sup> ; Peck and Pinnegar, 2018 <sup>[[#fn:r836|836]]</sup> ). First-wholesale value for commercial harvest of all species in 2017 in the Eastern Bering Sea was 2.68 billion USD, and for the Barents Sea around 1 billion USD to Norwegian fishers alone. The target species for these commercial fisheries include gadoids, flatfish, herring, red fish ( ''Sebastes'' sp.), salmonids, and capelin. Fisheries in other Arctic regions are relatively small-scale, locally operated, and target a limited number of species (Reist, 2018 <sup>[[#fn:r837|837]]</sup> ). Still, these fisheries are of considerable cultural, economic and subsistence importance to local communities (Section 3.5.2.1).

Climate change will affect the spatial distribution and productivity of some commercially important marine fish and shellfish under most RCPs (Section 3.2.3.1) with associated impacts on the distribution and economic viability of commercial fisheries ( ''high confidence'' ). Past performance suggests that high latitude fisheries have been resilient to changing environmental and market drivers. For example, the Norwegian cod fishery has exported dried cod over an unbroken period of more than a thousand years (Barrett et al., 2011 <sup>[[#fn:r838|838]]</sup> ), reflecting the resilience of the northern Norwegian cod fisheries to historic climate variability (Eide, 2017 <sup>[[#fn:r839|839]]</sup> ). Also, model projections indicate that expansions in suitable habitat for subarctic species and increased production of planktonic prey due to increasing temperatures and ice retreat, will continue to support commercially important fisheries (Lam et al., 2016 <sup>[[#fn:r840|840]]</sup> ; Eide, 2017 <sup>[[#fn:r841|841]]</sup> ; Haug et al., 2017 <sup>[[#fn:r842|842]]</sup> ; Peck and Pinnegar, 2018 <sup>[[#fn:r843|843]]</sup> ) (Section 3.2.3.1.3, Box 3.4) ( ''medium confidence'' ).

However, recent studies in the Bering Sea suggest that future fish production will also depend on how climate change and ocean acidification will alter the quality, quantity and availability of suitable prey; the thermal stress and metabolic demands of resident fish; and species interactions (Section 3.2.3.1.3), suggesting that the future of commercial fisheries in Arctic regions is uncertain (Holsman et al., 2018 <sup>[[#fn:r844|844]]</sup> ). It is also uncertain whether future autumn and winter ocean conditions will be conducive to the establishment of resident overwintering spawning populations that are large enough to support sustainable commercial fishing operations at higher latitude Arctic shelf regions (Section 3.2.3.1) ( ''medium confidence'' ).

Projecting the impacts of climate change on marine fisheries is inextricably intertwined with response scenarios regarding risk tolerance in future management of marine resources, advancements in fish capture technology, and markets drivers (e.g., local and global demand, emerging product lines, competition, processing efficiencies and energy costs) (Groeneveld et al., 2018 <sup>[[#fn:r845|845]]</sup> ). Seasonal and interannual variability in ocean conditions influences product quality and costs of fish capture (Haynie and Pfeiffer, 2012 <sup>[[#fn:r846|846]]</sup> ) (Table 3.4). Further, past experience suggests that barriers to diversification may limit the portfolio of viable target fisheries available to small-scale fisheries (Ward et al., 2017 <sup>[[#fn:r847|847]]</sup> ) ( ''low confidence'' ).

<div id="section-3-2-4-1-fisheries-block-2"></div>

<span id="southern-ocean-1"></span>
===== 3.2.4.1.2 Southern Ocean =====

This section examines climate change impacts on Southern Ocean fisheries for Antarctic krill and finfish. Management of these fisheries by CCAMLR and responses to climate change are discussed in Section 3.5.2.1. The main Antarctic fisheries are for Antarctic krill, and for Antarctic and Patagonian toothfish; in 2016 the reported catches for these species were approximately 260 thousand tons for krill (CCAMLR, 2017b <sup>[[#fn:r848|848]]</sup> ) and 11 thousand tons for Antarctic and Patagonian toothfish combined (CCAMLR, 2017a <sup>[[#fn:r850|850]]</sup> ). The mean annual wholesale value of the Antarctic krill fishery was 69.5 USD million yr -1 for the period from 2011 to 2015, and 206.7 million USD yr -1 for toothfish fisheries (combined) over the same period (CCAMLR, 2016b). The fishery for Antarctic krill in the southern Atlantic Sector and the northern West Antarctic Peninsula (together the current area of focus for the fishery) has become increasingly concentrated in space over recent decades, which has raised concern regarding localised impacts on krill predators (Hinke et al., 2017a <sup>[[#fn:r851|851]]</sup> ). The krill fishery has also changed its peak season of operation. In the early years of the fishery, most krill were taken in summer and autumn, with lowest catches being taken in spring. In recent years the lowest catches have occurred over summer, catches have peaked in late autumn, and very little fishing activity has occurred in spring (Nicol and Foster, 2016 <sup>[[#fn:r852|852]]</sup> ). Some of these temporal and spatial shifts in the fishery over time have been attributed to reductions in winter sea ice extent in the region (Kawaguchi et al., 2009 <sup>[[#fn:r853|853]]</sup> ) ( ''low confidence'' ). Recent increases in the use of krill catch to produce krill oil (as a human health supplement) has also led to vessels concentrating on fishing in autumn and winter when krill are richest in lipids (Nicol and Foster, 2016 <sup>[[#fn:r854|854]]</sup> ). Available evidence regarding future changes to Antarctic krill populations (Section 3.2.3.2.1) indicates that the impacts of climate change will be most pronounced in the areas that are currently most important for the Antarctic krill fishery: the Scotia Sea and the northern tip of the AP. Major future changes in the krill fishery itself are expected to be driven by global issues external to the Southern Ocean, including conservation decision making and socioeconomic drivers.

There is limited understanding of the consequences of climate change for Southern Ocean finfish fisheries. Lack of recovery of mackerel icefish ( ''Champsocephalus gunnari'' ) after cessation of fishing in 1995 has been related to anomalous water temperatures (~2 ° C increase related to a strong El Niño) in the subantarctic Indian Ocean and to availability of krill prey in the Atlantic region (Mintenbeck, 2017 <sup>[[#fn:r855|855]]</sup> ) ( ''low confidence'' ). Differences in temperature tolerance of Patagonian and Antarctic toothfish described in Section 3.2.3.2.3 may have implications for future fisheries of these two species.

<div id="section-3-2-4-2tourism"></div>

<span id="tourism"></span>
==== 3.2.4.2 Tourism ====

<div id="section-3-2-4-2tourism-block-1"></div>

Reductions in sea ice have facilitated an increase in marine and cruise tourism opportunities across the Arctic related to an increase in accessibility (Dawson et al., 2014 <sup>[[#fn:r856|856]]</sup> ; Johnston et al., 2017 <sup>[[#fn:r857|857]]</sup> ) ( ''high confidence'' ). While not exclusively ‘polar’, Alaska attracts the highest number of cruise passengers annually at just over one million; Svalbard attracts 40,000–50,000; Greenland 20,000–30,000; and Arctic Canada 3,500–5,000 (Johnston et al., 2017 <sup>[[#fn:r858|858]]</sup> ). Compared to a decade ago, there are more cruises on offer, ships travel further in a single season, larger vessels with more passenger berths are in operation, more purpose-built polar cruise vessels are being constructed, and private pleasure craft are appearing in the Arctic more frequently (Lasserre and Têtu, 2015 <sup>[[#fn:r859|859]]</sup> ; Johnston et al., 2017 <sup>[[#fn:r860|860]]</sup> ; Dawson et al., 2018 <sup>[[#fn:r861|861]]</sup> ). In Antarctica, almost 37,000 (predominantly shipborne) tourists visited in 2016–2017, with 51,707 during 2017–2018; there were 6700 tourists in 1992–1993 (the first year of record) (ATCM, 2018 <sup>[[#fn:r862|862]]</sup> ). Due to accessibility and convenience, these tourism operations are mostly based around the few ice-free areas of Antarctica, concentrated on the AP (Pertierra et al., 2017 <sup>[[#fn:r863|863]]</sup> ).

Canada’s Northwest Passage (southern route), which only saw occasional cruise ship transits in the early 2000s is now reliably accessible during the summer cruising season, and as a result has experienced a doubling and quadrupling of cruise and pleasure craft activity over the past decade (Johnston et al., 2017 <sup>[[#fn:r864|864]]</sup> ; Dawson et al., 2018 <sup>[[#fn:r865|865]]</sup> ). There is ''high confidence'' that demand for Arctic cruise tourism will continue to grow over the coming decade (Johnston et al., 2017 <sup>[[#fn:r866|866]]</sup> ). The anticipated implications of future climate change have become a driver for polar tourism. A niche market known as ‘last chance tourism’ has emerged whereby tourists explicitly seek to experience vanishing landscapes or seascapes, and natural and social heritage in the Arctic and Antarctic, before they disappear (Lemelin et al., 2010; Lamers et al., 2013 <sup>[[#fn:r867|867]]</sup> ).

Increases in polar cruise tourism pose risks and opportunities related to development, education, safety (including search and rescue), security within communities and environmental sustainability (Johnston et al., 2012a <sup>[[#fn:r868|868]]</sup> ; Johnston et al., 2012b <sup>[[#fn:r869|869]]</sup> ; Stewart et al., 2013 <sup>[[#fn:r870|870]]</sup> ; Dawson et al., 2014 <sup>[[#fn:r871|871]]</sup> ; Lasserre and Têtu, 2015 <sup>[[#fn:r872|872]]</sup> ; Stewart et al., 2015 <sup>[[#fn:r873|873]]</sup> ). In the Arctic, there are also risks and opportunities related to employment, health and well-being, and the commodification of culture (Stewart et al., 2013 <sup>[[#fn:r874|874]]</sup> ; Stewart et al., 2015 <sup>[[#fn:r875|875]]</sup> ). There is ''high confidence'' that biodiversity supported by ice-free areas, particularly those on the AP, are vulnerable to the introduction of terrestrial alien species via tourists and scientists (Chown et al., 2012 <sup>[[#fn:r876|876]]</sup> ; Huiskes et al., 2014 <sup>[[#fn:r877|877]]</sup> ; Hughes et al., 2015 <sup>[[#fn:r878|878]]</sup> ; Duffy et al., 2017 <sup>[[#fn:r879|879]]</sup> ; Lee et al., 2017a <sup>[[#fn:r880|880]]</sup> ) (Box 3.3) as well as to the direct impacts of humans (Pertierra et al., 2017 <sup>[[#fn:r881|881]]</sup> ). The tourism sector relies on a set of regulations that apply to all types of maritime shipping, yet cruise ships intentionally travel off regular shipping corridors and serve a very different purpose than other vessel types, so there is a need for region-specific governance regimes, specialised infrastructure, and focused policy attention (Dawson et al., 2014 <sup>[[#fn:r882|882]]</sup> ; Pashkevich et al., 2015 <sup>[[#fn:r883|883]]</sup> ; Pizzolato et al., 2016 <sup>[[#fn:r884|884]]</sup> ; Johnston et al., 2017 <sup>[[#fn:r885|885]]</sup> ). Private pleasure craft remain almost completely unregulated, and will pose unique risks in the future (Johnston et al., 2017 <sup>[[#fn:r886|886]]</sup> ).

<div id="section-3-2-4-3-transportation"></div>

<span id="transportation"></span>
==== 3.2.4.3 Transportation ====

<div id="section-3-2-4-3-transportation-block-1"></div>

The Arctic is reliant on marine transportation for the import of food, fuel and other goods. At the same time, the global appetite for maritime trade and commerce through the Arctic (including community re-supply, mining and resource development, tourism, fisheries, cargo, research, and military and icebreaking, etc.) is increasing as the region becomes more accessible because of reduced sea ice cover. There are four potential Arctic international trade routes: the Northwest Passage, the Northern Sea Route, the Arctic Bridge and the Transpolar Sea Route. All of these routes offer significant trade benefits because they provide substantial distance savings compared to traditional routes via the Suez or Panama Canals.

There is ''high confidence'' that shipping activity during the Arctic summer increased over the past two decades in regions for which there is information, concurrent with reductions in Arctic sea ice extent and the shift to predominantly seasonal ice cover (Pizzolato et al., 2014 <sup>[[#fn:r887|887]]</sup> ; Eguíluz et al., 2016 <sup>[[#fn:r888|888]]</sup> ; Pizzolato et al., 2016 <sup>[[#fn:r889|889]]</sup> ). Long term datasets over the pan-Arctic are incomplete, but the distance travelled by ships in Arctic Canada nearly tripled between 1990 and 2015 (from ~365,000 to ~920,000 km) (Dawson et al., 2018 <sup>[[#fn:r890|890]]</sup> ). Other non-environmental factors which influence Arctic shipping are natural resource development, regional trade, geopolitics, commodity prices, global economic and social trends, national priorities, tourism demand, ship building technologies and insurance costs (Lasserre and Pelletier, 2011 <sup>[[#fn:r891|891]]</sup> ; Têtu et al., 2015 <sup>[[#fn:r892|892]]</sup> ; Johnston et al., 2017 <sup>[[#fn:r893|893]]</sup> ). Current impacts associated with the observed increase in Arctic shipping include a higher rate of reported accidents per km travelled compared to southern waters (CCA, 2016), increases in vessel noise propagation (Halliday et al., 2017 <sup>[[#fn:r894|894]]</sup> ) and air pollution (Marelle et al., 2016 <sup>[[#fn:r895|895]]</sup> ). Disruptions to cultural and subsistence hunting activities from increased shipping (Huntington et al., 2015 <sup>[[#fn:r896|896]]</sup> ; Olsen et al., 2019 <sup>[[#fn:r897|897]]</sup> ) compound climate-related impacts to people (Sections 3.4.3.3.2, 3.4.3.3.3).

It is projected that shipping activity will continue to rise across the Arctic as northern routes become increasingly accessible (Stephenson et al., 2011 <sup>[[#fn:r898|898]]</sup> ; Stephenson et al., 2013 <sup>[[#fn:r899|899]]</sup> ; Barnhart et al., 2015 <sup>[[#fn:r900|900]]</sup> ; Melia et al., 2016 <sup>[[#fn:r901|901]]</sup> ), although mitigating economic and operational factors remain uncertain and could influence future traffic volume (Zhang et al., 2016 <sup>[[#fn:r902|902]]</sup> ). The Northern Sea Route is expected to be more viable than other routes because of infrastructure already in place (Milaković et al., 2018 <sup>[[#fn:r903|903]]</sup> ); favourable summer ice conditions in recent years have reduced transit times (Aksenov et al., 2017 <sup>[[#fn:r904|904]]</sup> ). In comparison, the Northwest Passage and Arctic Bridge presently have limited port and marine transportation infrastructure, incomplete soundings and hydrographic charting, challenging sea ice conditions and limited search and rescue capacity; these compound the risks from shipping activity (Stephenson et al., 2013 <sup>[[#fn:r905|905]]</sup> ; Johnston et al., 2017 <sup>[[#fn:r906|906]]</sup> ; Andrews et al., 2018 <sup>[[#fn:r907|907]]</sup> ).

Future shipping impacts will be regionally diverse considering the unique geographies, sea ice dynamics, infrastructure and service availability and regulatory regimes that exist across different Arctic nations. Considerations include socioeconomic and political implications related to safety (marine and local accidents), security (trafficking, terrorism and local issues), and environmental and cultural sustainability (invasive species, release of biocides, chemicals and other waste, marine mammal strikes, fuel spills, air and underwater noise pollution and impacts to subsistence hunting) (Arctic Council, 2015a <sup>[[#fn:r908|908]]</sup> ; Halliday et al., 2017 <sup>[[#fn:r909|909]]</sup> ; Hauser et al., 2018 <sup>[[#fn:r910|910]]</sup> ). Black carbon emissions from shipping activity within the Arctic are projected to increase (Arctic Council, 2017 <sup>[[#fn:r911|911]]</sup> ) and are more easily deposited at the surface in the region compared with emissions from lower latitudes (Sand et al., 2013 <sup>[[#fn:r912|912]]</sup> ). Commercial shipping mainly uses heavy fuel oil, with associated emissions of sulphur, nitrogen, metals, hydrocarbons, organic compounds, black carbon and fly ash to the atmosphere during combustion (Turner et al., 2017a <sup>[[#fn:r913|913]]</sup> ). Mitigation approaches include banning heavy fuel oil as already implemented in Antarctica and the waters around Svalbard, and the use of new technology like scrubbers.

The predominant shipborne activities in Antarctica are fishing, logistic support to land-based stations, and marine research vessels operating for both non-governmental and governmental sectors. Uncertainty in future Antarctic sea ice conditions (Section 3.2.2.1) pose challenges to considering potential impacts on these activities (Chown, 2017 <sup>[[#fn:r914|914]]</sup> ).

<span id="polar-ice-sheets-and-glaciers-changes-consequences-and-impacts"></span>