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

== 3.4 Observed and Projected Impacts of Climate Change on Marine Systems ==

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<span id="introduction-2"></span>
=== 3.4.1 Introduction ===

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Ocean and coastal ecosystems and their resident species are under increasing pressure from a multitude of climate-induced drivers and non-climate drivers ( [[#3.1|Section 3.1]] ; Figure 3.12; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). This section builds from the assessment of biological responses to climate-impact drivers ( [[#3.3|Section 3.3]] ) to examine the new evidence about climate-change impacts at the level of marine ecosystems. It focuses on detection and attribution of observed changes to marine ecosystems and the projected changes under different future climate scenarios. This assessment considers emerging evidence on the effects of multiple non-climate drivers and physiological acclimation and/or evolutionary adaptation on these observations and projections.

The section focuses first on coastal ecosystems and seas ( [[#3.4.2|Section 3.4.2]] ), which have high spatial variability in physical and chemical characteristics, are affected by many non-climate drivers ( [[#3.1|Section 3.1]] ; Figure 3.12) and support rich fisheries, high biodiversity and high levels of species endemism. The assessment begins with warm-water coral reefs ( [[#3.4.2.1|Section 3.4.2.1]] ) because these highly threatened systems are at the vanguard of research on acclimation and evolutionary adaptation among coastal ecosystems. It follows with the other shallow, nearshore ecosystems dominated by habitat-forming species (e.g., rocky shores, kelp systems) and then nearshore sedimentary systems (estuaries, deltas, coastal wetlands and sandy beaches), before moving on to semi-enclosed seas, shelf seas, upwelling zones and polar seas.

The section continues on to oceanic and cross-cutting changes ( [[#3.4.3|Section 3.4.3]] ), which influence large areas of the epipelagic zone (&lt;200 m depth) while also affecting the mesopelagic (200–1000 m), the perpetually dark bathypelagic (depth &gt;1000 m) and the deep seafloor (benthic ecosystems at depths &gt;200 m) zones. Assessed in this section are species range shifts ( [[#3.4.3.1|Section 3.4.3.1]] ), phenological shifts and trophic mismatches ( [[#3.4.3.2|Section 3.4.3.2]] ), changes in communities and biodiversity ( [[#3.4.3.3.2|Section 3.4.3.3.2]] ), time of emergence of climate-impact signals in ecological systems from background natural variability ( [[#3.4.3.3.4|Section 3.4.3.3.4]] ) and changes in biomass, primary productivity and carbon export (Sections 3.4.3.4–3.4.3.6).

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=== 3.4.2 Coastal Ecosystems and Seas ===

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==== 3.4.2.1 Warm-Water Coral Reefs ====

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Warm-water coral reef ecosystems house one-quarter of the marine biodiversity and provide services in the form of food, income and shoreline protection to coastal communities around the world. These ecosystems are threatened by climate-induced and non-climate drivers, especially ocean warming, MHWs, ocean acidification, SLR, tropical cyclones, fisheries/overharvesting, land-based pollution, disease spread and destructive shoreline practices ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Hughes--2020|Hughes et al., 2020]] ). Warm-water coral reefs face near-term threats to their survival (Table 3.3), but research on observed and projected impacts is very advanced.

'''Table 3.3 |''' Summary of previous IPCC assessments of coral reefs

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| Coral reefs are one of the most vulnerable marine ecosystems ( ''high confidence'' ), and more than half of the world’s reefs are under medium or high risk of degradation.

Mass coral bleaching and mortality, triggered by positive temperature anomalies ( ''high confidence'' ), is the most widespread and conspicuous impact of climate change. Ocean acidification reduces biodiversity and the calcification rate of corals ( ''high confidence'' ) while at the same time increasing the rate of dissolution of the reef framework ( ''medium confidence'' ).

‘In summary, ocean warming is the primary cause of mass coral bleaching and mortality ( ''very high confidence'' ), which, together with ocean acidification, deteriorates the balance between coral reef construction and erosion ( ''high confidence'' ).’

| ‘Coral bleaching and mortality will increase in frequency and magnitude over the next decades ( ''very high confidence'' ).’ Analysis of the Coupled Model Intercomparison Project 5 ensemble projects the loss of coral reefs from most sites globally by 2050 under mid to high rates of warming ( ''very likely'' ).

‘Under the A1B CO 2 emission scenario, 99% of the reef locations will experience at least one severe bleaching event between 2090 and 2099, with ''limited evidence'' and ''low agreement'' that coral acclimation and/or adaptation will limit this trend.’

‘The onset of global dissolution [of coral reefs] is at an atmospheric CO 2 [concentration] of 560 ppm ( ''medium confidence'' ) and dissolution will be widespread in 2100’ (Representative Concentration Pathway, RCP8.5, ''medium confidence'' ).

‘A number of coral reefs could therefore keep up with the maximum rate of sea level rise (SLR) of 15.1 mm yr –1 projected for the end of the century [...], but lower net accretion [...] and increased turbidity will weaken this capability ( ''very high confidence'' ).’

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] ; [[#IPCC--2019c|IPCC, 2019c]] )''

|
|-
| ‘Climate change [...] has emerged as the greatest threat to coral reefs, with temperatures of just 1°C above the long-term summer maximum for an area (reference period 1985–1993) over 4–6 weeks being enough to cause mass coral bleaching [...] and mortality ( ''very high confidence'' ).’

Predictions of back-to-back bleaching events have become reality over 2015–2017 as have projections of declining coral abundance ( ''high confidence'' ).

| ‘Multiple lines of evidence indicate that the majority (70–90%) of warm water (tropical) coral reefs that exist today will disappear even if global warming is constrained to 1.5°C ( ''very high confidence'' ).’

Coral reefs, for example, are projected to decline by a further 70–90% at 1.5°C ( ''high confidence'' ) with larger losses (&gt;99%) at 2°C ( ''very high confidence'' ).

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘New evidence since AR5 and SR15 confirms the impacts of ocean warming and acidification on coral reefs ( ''high confidence'' ), enhancing reef dissolution and bioerosion ( ''high confidence'' ), affecting coral species distribution and leading to community changes ( ''high confidence'' ). The rate of SLR (primarily noticed in small reef islands) may outpace the growth of reefs to keep up, although there is ''low agreement'' in the literature ( ''low confidence'' ).’

‘Reefs are further exposed to other increased impacts, such as enhanced storm intensity, turbidity and increased runoff from the land ( ''high confidence'' ). Recovery of coral reefs resulting from repeated disturbance events is slow ( ''high confidence'' ) ''.'' Only few coral reef areas show some resilience to global change drivers ( ''low confidence'' ).’

| ‘Coral reefs will face very high risk at temperatures 1.5°C of global sea surface warming ( ''very high confidence'' ).’

‘Almost all coral reefs will degrade from their current state, even if global warming remains below 2°C ( ''very high confidence'' ), and the remaining shallow coral reef communities will differ in species composition and diversity from present reefs ( ''very high confidence'' ). This will greatly diminish the services they provide to society, such as food provision ( ''high confidence'' ), coastal protection ( ''high confidence'' ) and tourism ( ''medium confidence'' ).’

‘The very high vulnerability of coral reefs to warming, ocean acidification, increasing storm intensity and SLR under climate change, including enhanced bioerosion ( ''high confidence'' ), points to the importance of considering both mitigation and adaptation.’

|}

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[[File:5ffcc230559c2477d3fa6efd4f03d35a IPCC_AR6_WGII_Figure_3_012.png]]

'''Figure 3.12 |''' '''Summary assessment of observed hazards to coastal ecosystems and seas as assessed in Sectio''' '''n 3.''' '''4.2.'''

Global analyses published since AR5 show that mass coral bleaching events and disease outbreaks have increased due to more frequent and severe heat stress associated with ocean warming ( ''very high confidence, virtually certain'' ) ( [[#Donner--2017|Donner et al., 2017]] ; [[#Hughes--2018a|Hughes et al., 2018a]] ; [[#DeCarlo--2019|DeCarlo et al., 2019]] ; [[#Sully--2019|Sully et al., 2019]] ; [[#Tracy--2019|Tracy et al., 2019]] ). The mass coral bleaching, which occurred continuously across different parts of the tropics from 2014 to 2016, is considered the longest and most severe global coral bleaching event on record ( [[IPCC:Wg2:Chapter:Chapter-10#10.4.3|Section 10.4.3]] ; see Box 15.2; [[#Eakin--2019|Eakin et al., 2019]] ). The Great Barrier Reef underwent mass bleaching three times between 2016 and 2020 (see Box 11.2; [[#Pratchett--2021|Pratchett et al., 2021]] ), validating past model projections that some warm-water coral reefs would encounter bleaching-level heat stress multiple times per decade by the 2020s ( [[#Hoegh-Guldberg--1999|Hoegh-Guldberg, 1999]] ; [[#Donner--2009|Donner, 2009]] ).

Heat stress and mass bleaching events caused decreases in live coral cover ( ''virtually certain'' ) ( [[#Graham--2014|Graham et al., 2014]] ; [[#Hughes--2018b|Hughes et al., 2018b]] ), loss of sensitive species ( ''extremely likely'' ) ( [[#Donner--2019|Donner and Carilli, 2019]] ; [[#Lange--2019|Lange and Perry, 2019]] ; [[#Toth--2019|Toth et al., 2019]] ; [[#Courtney--2020|Courtney et al., 2020]] ), vulnerability to disease ( ''extremely likely'' ) ( [[#van%20Woesik--2017|van Woesik and Randall, 2017]] ; [[#Hadaidi--2018|Hadaidi et al., 2018]] ; [[#Brodnicke--2019|Brodnicke et al., 2019]] ; [[#Howells--2020|Howells et al., 2020]] ) and declines in coral recruitment in the tropics ( ''medium confidence'' ) ( [[#Hughes--2019|Hughes et al., 2019]] ; [[#Price--2019|Price et al., 2019]] ). Recent observations also suggest that excess nutrients can increase the susceptibility of corals to heat stress ( [[#DeCarlo--2020|DeCarlo et al., 2020]] ). Changes in coral community structure due to bleaching have caused declines in reef carbonate production ( ''high confidence'' ) ( [[#Perry--2017|Perry and Morgan, 2017]] ; [[#Lange--2019|Lange and Perry, 2019]] ; [[#Perry--2019|Perry and Alvarez-Filip, 2019]] ; [[#Courtney--2020|Courtney et al., 2020]] ; [[#van%20Woesik--2021|van Woesik and Cacciapaglia, 2021]] ) and in reef structural complexity ( ''high confidence, very likely'' ) ( [[#Couch--2017|Couch et al., 2017]] ; [[#Leggat--2019|Leggat et al., 2019]] ; [[#Magel--2019|Magel et al., 2019]] ), which increases water depth, reduces wave attenuation and increases coastal flood risk ( [[#Yates--2017|Yates et al., 2017]] ; [[#Beck--2018|Beck et al., 2018]] ). Corals may also lose reproductive synchrony through climate change ( [[#Shlesinger--2019|Shlesinger and Loya, 2019]] ), adding to their vulnerability. Bleaching and other drivers promote phase shifts to ecosystems dominated by macroalgae or other stress-tolerant species ( ''very high confidence'' ) ( [[#Graham--2015|Graham et al., 2015]] ; Stuart- [[#Smith--2018|Smith et al., 2018]] ), leading to changes in reef-fish species assemblages ( ''high confidence'' ) ( [[#Richardson--2018|Richardson et al., 2018]] ; [[#Robinson--2019a|Robinson et al., 2019a]] ; Stuart- [[#Smith--2021|Smith et al., 2021]] ).

Ocean acidification and associated declines in aragonite saturation state ( Ω aragonite ) decrease rates of calcification by corals and other calcifying reef organisms ( ''very high confidence'' ), reduce coral settlement ( ''medium confidence'' ) and increase bioerosion and dissolution of reef substrates ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Kline--2019|Kline et al., 2019]] ; [[#Pitts--2020|Pitts et al., 2020]] ). Warming can exacerbate the coral response to ocean acidification ( [[#Kornder--2018|Kornder et al., 2018]] ) and accelerate the decrease in coral skeletal density ( [[#Guo--2020|Guo et al., 2020]] ). In addition, reefs with lower coral cover and a higher proportion of slow-growing species, because of bleaching, are more sensitive to acidification (net dissolution occurs Ω aragonite = 2.3 for 100% coral cover, and Ω aragonite &gt;3.5 for 30% coral cover; [[#Kline--2019|Kline et al., 2019]] ). However, experimental evidence suggests that coral responses to ocean acidification are species specific ( ''medium confidence'' ) ( [[#Fabricius--2011|Fabricius et al., 2011]] ; [[#DeCarlo--2018|DeCarlo et al., 2018]] ; [[#Comeau--2019|Comeau et al., 2019]] ). Evidence from experiments suggests that crustose coralline algae, which contribute to reef structure and integrity and may be resistant to warming at the RCP8.5 level by 2100 ( [[#Cornwall--2019|Cornwall et al., 2019]] ), are also sensitive to declines in Ω aragonite ( ''high confidence'' ) ( [[#3.4.2.3|Section 3.4.2.3]] ; [[#Fabricius--2015|Fabricius et al., 2015]] ; [[#Smith--2020|Smith et al., 2020]] ). The integrated effect of acidification, bleaching, storms and other non-climate drivers on corals, coralline algae and other calcifiers can further compromise reef integrity and ecosystem services ( [[#Rivest--2017|Rivest et al., 2017]] ; [[#Cornwall--2018|Cornwall et al., 2018]] ; [[#Perry--2019|Perry and Alvarez-Filip, 2019]] ).

Since SROCC, there have been advances in experimental, field and modelling research on the projected response of coral cover and reef growth to bleaching and ocean acidification ( [[#Cziesielski--2019|Cziesielski et al., 2019]] ; [[#Morikawa--2019|Morikawa and Palumbi, 2019]] ; [[#Cornwall--2021|Cornwall et al., 2021]] ; [[#Klein--2021|Klein et al., 2021]] ; [[#Logan--2021|Logan et al., 2021]] ; [[#McManus--2021|McManus et al., 2021]] ), and on the effect of possible human interventions like assisted evolution on coral resilience ( [[#3.6.3.2.2|Section 3.6.3.2.2]] ; [[#Condie--2021|Condie et al., 2021]] ; [[#Hafezi--2021|Hafezi et al., 2021]] ; [[#Kleypas--2021|Kleypas et al., 2021]] ). New model projections incorporating physiological acclimation, larval dispersal and evolutionary processes find limited ability to adapt this century at rates of warming at or exceeding that in RCP4.5 ( ''high confidence, very likely'' ) ( [[#Bay--2017|Bay et al., 2017]] ; [[#Kubicek--2019|Kubicek et al., 2019]] ; [[#Matz--2020|Matz et al., 2020]] ; [[#McManus--2020|McManus et al., 2020]] ; [[#Logan--2021|Logan et al., 2021]] ; [[#McManus--2021|McManus et al., 2021]] ). For example, a global analysis ( [[#Logan--2021|Logan et al., 2021]] ) finds that increased thermal tolerance via evolution or switching to more stress-tolerant algal symbionts enable most (73–81%) coral to survive through 2100 under RCP2.6, but coral-dominated communities with a historical mix of coral taxa still disappear (0–8% coral survival) under RCP6.0 in simulations with adaptive mechanisms (Figure 3.13). Due to the impacts of warming, and to a lesser extent ocean acidification, global reef carbonate production is estimated to decline 71% by 2050 in SSP1-2.6, and the rate of SLR is estimated to exceed that of reef growth for 97% of reefs assessed, without adaptation by corals and their symbionts (WGI AR6 Table 9.9; [[#Cornwall--2021|Cornwall et al., 2021]] ; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ). The increased water depth due to coral loss and reef erosion, as well as reduced structural complexity, will limit wave attenuation and exacerbate the risk of flooding from SLR on reef-fringed shorelines and reef islands ( [[#Yates--2017|Yates et al., 2017]] ; [[#Beck--2018|Beck et al., 2018]] ; [[#Harris--2018|Harris et al., 2018]] ). Local coral reef fish species richness is projected to decline due to the impacts of warming on coral cover and diversity ( ''high confidence'' ), with declines up to 40% by 2060 in SSP5-8.5 ( [[#Strona--2021|Strona et al., 2021]] ).

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[[File:1b1407f3efeeed297db173219f1951da IPCC_AR6_WGII_Figure_3_013.png]]

'''Figure 3.13 |''' '''Coral reef futures, with and without adaptation.''' Graphs are based on a model of coral-symbiont evolutionary dynamics from [[#Logan--2021|Logan et al. (2021)]] , which simulates two coral types and symbiont populations for 1925 reef cells worldwide, from 1950 to 2100 drawn from simulations with National Oceanic and Atmospheric Administration–Geophysical Fluid Dynamics Laboratory Earth System Model (ESM2M) under four RCPs. Top panels show the simulated fraction of cells with healthy reefs, when both coral types are not in a state of severe bleaching or mortality, (i) without adaptive responses and (ii) with adaptive responses (symbiont evolution). Colours indicate maximum monthly sea surface temperature increase across all reef cells, versus a 1861–2010 baseline. Panels (a,b,c) depict snapshots of coral reef conditions at time points in the future, each with different levels of warming, drawn from the model-projected cover of the two coral types and from a literature assessment ( [[#3.4.2.1|Section 3.4.2.1]] ; [[#Hughes--2018b|Hughes et al., 2018b]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Darling--2019|Darling et al., 2019]] ; [[#Leggat--2019|Leggat et al., 2019]] ; [[#Cornwall--2021|Cornwall et al., 2021]] ).

These observed and projected impacts are supported by geological and paleo-ecological evidence showing a decline in coral reef extent and species richness under previous episodes of climate change and ocean acidification ( [[#Kiessling--2011|Kiessling and Simpson, 2011]] ; [[#Pandolfi--2011|Pandolfi et al., 2011]] ; [[#Kiessling--2012|Kiessling et al., 2012]] ; [[#Pandolfi--2014|Pandolfi and Kiessling, 2014]] ; [[#Kiessling--2015|Kiessling and Kocsis, 2015]] ). Major reef crises in the past 300 million years were governed by hyperthermal events ( ''medium confidence'' ) ( [[#3.2.4|Section 3.2.4.4]] ; Cross-Chapter Box PALEO in Chapter 1) longer in time scale than anthropogenic climate change, during which net coral reef accretion was more strongly affected than biodiversity ( ''medium confidence'' ).

In response to the global-scale decline in coral reefs and high future risk, recent literature focuses on finding thermal refuges and identifying uniquely resilient species, populations or reefs for targeted restoration and management ( [[#Hoegh-Guldberg--2018b|Hoegh-Guldberg et al., 2018b]] ). Reefs exposed to internal waves ( [[#Storlazzi--2020|Storlazzi et al., 2020]] ), turbidity ( [[#Sully--2020|Sully and van Woesik, 2020]] ) or warm-season cloudiness ( [[#Gonzalez-Espinosa--2021|Gonzalez-Espinosa and Donner, 2021]] ) are expected to be less sensitive to thermal stress. Mesophotic reefs (30–150 m) have also been proposed as thermal refugia ( [[#Bongaerts--2010|Bongaerts et al., 2010]] ), although evidence from recent bleaching events, subsurface temperature records and species overlap is mixed ( [[#Frade--2018|Frade et al., 2018]] ; [[#Rocha--2018b|Rocha et al., 2018b]] ; [[#Eakin--2019|Eakin et al., 2019]] ; [[#Venegas--2019|Venegas et al., 2019]] ; [[#Wyatt--2020|Wyatt et al., 2020]] ). A study of 2584 reef sites across the Indian and Pacific oceans estimated that 17% had sufficient cover of framework-building corals to warrant protection, 54% required recovery efforts and 28% were on a path to net erosion ( [[#Darling--2019|Darling et al., 2019]] ). There is ''medium evidence'' for greater bleaching resistance among reefs subject to temperature variability or frequent heat stress ( [[#Barkley--2018|Barkley et al., 2018]] ; [[#Gintert--2018|Gintert et al., 2018]] ; [[#Hughes--2018a|Hughes et al., 2018a]] ; [[#Morikawa--2019|Morikawa and Palumbi, 2019]] ), but with trade-offs in terms of diversity and structural complexity ( [[#Donner--2019|Donner and Carilli, 2019]] ; [[#Magel--2019|Magel et al., 2019]] ). There is ''limited agreement'' about the persistence of thermal tolerance in response to severe heat stress ( [[#Le%20Nohaïc--2017|Le Nohaïc et al., 2017]] ; [[#DeCarlo--2019|DeCarlo et al., 2019]] ; [[#Fordyce--2019|Fordyce et al., 2019]] ; [[#Leggat--2019|Leggat et al., 2019]] ; [[#Schoepf--2020|Schoepf et al., 2020]] ). Recovery and restoration efforts that target heat-resistant coral populations and culture heat-tolerant algal symbionts have the greatest potential of effectiveness under future warming ( ''high confidence'' ) (see Box 5.5 in SROCC Chapter 5; [[#Bay--2017|Bay et al., 2017]] ; [[#Darling--2018|Darling and Côté, 2018]] ; [[#Baums--2019|Baums et al., 2019]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Howells--2021|Howells et al., 2021]] ); however, there is ''low confidence'' that enhanced thermal tolerance can be sustained over time ( [[#3.6.3.3.2|Section 3.6.3.3.2]] ; [[#Buerger--2020|Buerger et al., 2020]] ). The effectiveness of active restoration and other specific interventions (e.g., reef shading) are further assessed in [[#3.6.3.3.2|Section 3.6.3.3.2]] .

In summary, additional evidence since SROCC and SR15 (Table 3.3) finds that living coral and reef growth are declining due to warming and MHWs ( ''very high confidence'' ). Coral reefs are under threat of transitioning to net erosion with &gt;1.5°C of global warming ( ''high confidence'' ), with impacts expected to occur fastest in the Atlantic Ocean. The effectiveness of conservation efforts to sustain living coral area, coral diversity and reef growth is limited for the majority of the world’s reefs with &gt;1.5°C of global warming ( ''high confidence'' ) ( [[#3.6.3.3.2|Section 3.6.3.3.2]] ; [[#Hoegh-Guldberg--2018b|Hoegh-Guldberg et al., 2018b]] ; [[#Bruno--2019|Bruno et al., 2019]] ; [[#Darling--2019|Darling et al., 2019]] ).

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==== 3.4.2.2 Rocky Shores ====

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Rocky shore ecosystems refer to a range of temperate intertidal and shallow coastal ecosystems that are dominated by different foundational organisms, including mussels, oysters, fleshy macroalgae, hard and soft corals, coralline algae, bryozoans and sponges, which create habitat for species-rich assemblages of invertebrates, fish, marine mammals and other organisms. Rocky shores provide services including wave attenuation, habitat provision and food resources, and these support commercial, recreational and Indigenous fisheries and shellfish aquaculture.

'''Table 3.4 |''' Summary of previous IPCC assessments of rocky shores

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| ‘Rocky shores are among the better-understood coastal ecosystems in terms of potential impacts of climate variability and change. The most prominent effects are range shifts of species in response to ocean warming ( ''high confidence'' ) and changes in species distribution and abundance ( ''high confidence'' ) mostly in relation to ocean warming and acidification.’

‘The dramatic decline of biodiversity in mussel beds of the Californian coast has been attributed to large-scale processes associated with climate-related drivers [...] ( ''high confidence'' ).’

| ‘The abundance and distribution of rocky shore species will continue to change in a warming world ( ''high confidence'' ). For example, the long-term consequences of ocean warming on mussel beds of the northeast Pacific are both positive (increased growth) and negative (increased susceptibility to stress and of exposure to predation) ( ''medium confidence'' ).’

‘Observations performed near natural CO 2 vents in the Mediterranean Sea show that diversity, biomass and trophic complexity of rocky shore communities will decrease at future pH levels ( ''high confidence'' ).’

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )''

|
|-
| ‘Changes in ocean circulation can have profound impacts on [temperate] marine ecosystems by connecting regions and facilitating the entry and establishment of species in areas where they were unknown before (‘tropicalization’ ...) as well as the arrival of novel disease agents ( ''medium agreement, limited evidence'' ).’

| ‘In the transition to 1.5°C, changes to water temperatures are expected to drive some species (e.g., plankton, fish) to relocate to higher latitudes and cause novel ecosystems to assemble ( ''high confidence'' ). Other ecosystems (e.g., kelp forests, coral reefs) are relatively less able to move, however, and are projected to experience high rates of mortality and loss ( ''very high confidence'' ).’

‘In the case of ‘less mobile’ ecosystems (e.g., coral reefs, kelp forests, intertidal communities), shifts in biogeographic ranges may be limited, with mass mortalities and disease outbreaks increasing in frequency as the exposure to extreme temperatures increases’ ( ''high agreement, robust evidence'' ).

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Intertidal rocky shores ecosystems are highly sensitive to ocean warming, acidification and extreme heat exposure during low tide emersion ( ''high confidence'' ).

‘Sessile calcified organisms (e.g., barnacles and mussels) in intertidal rocky shores are highly sensitive to extreme temperature events and acidification ( ''high confidence'' ), a reduction in their biodiversity and abundance have been observed in naturally acidified rocky reef ecosystems ( ''medium confidence'' ).’

| ‘Intertidal rocky shores are also expected to be at very high risk (transition above 3°C) under the RCP8.5 scenario ( ''medium confidence'' ). These ecosystems have low to moderate adaptive capacity, as they are highly sensitive to ocean temperatures and acidification.’

‘Benthic species will continue to relocate in the intertidal zones and experience mass mortality events due to warming ( ''high confidence'' ). Interactive effects between acidification and warming will exacerbate the negative impacts on rocky shore communities, causing a shift towards a less diverse ecosystem in terms of species richness and complexity, increasingly dominated by macroalgae ( ''high confidence'' ).’

|}

Observations since AR5 and SROCC (Table 3.4) find increased impacts of ocean warming on rocky shores. This includes extirpation of species at the warm edge of their ranges ( [[#Yeruham--2015|Yeruham et al., 2015]] ; [[#Martínez--2018|Martínez et al., 2018]] ), extension of poleward range boundaries ( [[#Sanford--2019|Sanford et al., 2019]] ), mortality from climate extremes ( [[#Seuront--2019|Seuront et al., 2019]] ), reduction in survival at shallower depths ( [[#Sorte--2019|Sorte et al., 2019]] ; [[#Wallingford--2019|Wallingford and Sorte, 2019]] ) and reorganisation of communities ( [[#Wilson--2019|Wilson et al., 2019]] ; [[#Mulders--2020|Mulders and Wernberg, 2020]] ; [[#Albano--2021|Albano et al., 2021]] ). Data collected after MHWs find ecological phase shifts ( ''moderate evidence, high agreement'' ) (e.g., California; [[#Rogers-Bennett--2019|Rogers-Bennett and Catton, 2019]] ; [[#McPherson--2021|McPherson et al., 2021]] ) and homogenisation of communities ( ''limited evidence'' ) (e.g., Alaska; [[#Weitzman--2021|Weitzman et al., 2021]] ). For example, the collapse of sea star populations in the Northeast Pacific due to a MHW-related disease outbreak ( [[#Hewson--2014|Hewson et al., 2014]] ; [[#Menge--2016|Menge et al., 2016]] ; [[#Miner--2018|Miner et al., 2018]] ; [[#Schiebelhut--2018|Schiebelhut et al., 2018]] ), including 80–100% loss of the common predatory sunflower star, ''Pycnopodia helianthoides'' ( ''very high confidence'' ) ( [[#Harvell--2019|Harvell et al., 2019]] ), triggered shifts from kelp- to urchin-dominated ecosystems ( [[#Schultz--2016|Schultz et al., 2016]] ; [[#Gravem--2017|Gravem and Morgan, 2017]] ; [[#McPherson--2021|McPherson et al., 2021]] ).

Multiple lines of evidence find that foundational calcifying organisms such as mussels are at high risk of decline due to both the individual and synergistic effects of warming, acidification and hypoxia ( ''high confidence'' ) ( [[#Sunday--2016|Sunday et al., 2016]] ; [[#Sorte--2017|Sorte et al., 2017]] ; [[#Sorte--2019|Sorte et al., 2019]] ; [[#Newcomb--2020|Newcomb et al., 2020]] ). Warmer temperatures reduce mussel and barnacle recruitment (e.g., northwest Atlantic; [[#Petraitis--2020|Petraitis and Dudgeon, 2020]] ) and the upper vertical limit of mussels (e.g., northeast Pacific, [[#Harley--2011|Harley, 2011]] ; and southwest Pacific, [[#Sorte--2019|Sorte et al., 2019]] ). Experiments show that ocean acidification negatively impacts mussel physiology ( ''very high confidence'' ), with evidence of reduced growth ( [[#Gazeau--2010|Gazeau et al., 2010]] ), attachment ( [[#Newcomb--2020|Newcomb et al., 2020]] ), biomineralisation ( [[#Fitzer--2014|Fitzer et al., 2014]] ) and shell thickness ( [[#Pfister--2016|Pfister et al., 2016]] ; [[#McCoy--2018|McCoy et al., 2018]] ). Net calcification and abundance of mussels and other foundational species, including oysters, are expected to decline due to ocean acidification ( ''very high confidence'' ) ( [[#Kwiatkowski--2016|Kwiatkowski et al., 2016]] ; [[#Sunday--2016|Sunday et al., 2016]] ; [[#McCoy--2018|McCoy et al., 2018]] ; [[#Meng--2018|Meng et al., 2018]] ), causing the reorganisation of communities ( ''high confidence'' ) ( [[#Kroeker--2013b|Kroeker et al., 2013b]] ; [[#Linares--2015|Linares et al., 2015]] ; [[#Brown--2016|Brown et al., 2016]] ; [[#Sunday--2016|Sunday et al., 2016]] ; [[#Agostini--2018|Agostini et al., 2018]] ; [[#Teixidó--2018|Teixidó et al., 2018]] ). Experiments indicate that acidification can interact with warming and hypoxia to increase the detrimental effects on mussels ( [[#Gu--2019|Gu et al., 2019]] ; [[#Newcomb--2020|Newcomb et al., 2020]] ). In regions where food is readily available to mussels, detrimental effects of ocean acidification may be dampened ( [[#Kroeker--2016|Kroeker et al., 2016]] ); however, recent findings are inconclusive ( [[#Brown--2018a|Brown et al., 2018a]] ).

Coralline algae, foundational taxa that create habitat for sea urchins and abalone, form rhodolith beds in temperate to Arctic habitats and bind together substrates, are expected to be highly susceptible to ocean acidification because they precipitate soluble magnesium calcite ( [[#Kuffner--2008|Kuffner et al., 2008]] ; [[#Williams--2021|Williams et al., 2021]] ). Damage from acidification varies among species and regions, and can be due to direct physiological stress ( [[#Marchini--2019|Marchini et al., 2019]] ) or interactions with non-calcifying competitors such as fleshy macroalgae ( [[#Smith--2020|Smith et al., 2020]] ). Experiments indicate that warming reduces calcification by coralline algae ( ''high confidence'' ) ( [[#Cornwall--2019|Cornwall et al., 2019]] ) and exacerbates the effect of acidification ( [[#Kim--2020|Kim et al., 2020]] ; [[#Williams--2021|Williams et al., 2021]] ).

In contrast to warm-water coral reefs, there are no regional or global numerical models of rocky shore ecosystem response to projected climate change and acidification. Experiments suggest that existing genetic variation could be sufficient for some mussels ( [[#Bitter--2019|Bitter et al., 2019]] ) and coralline algae ( [[#Cornwall--2020|Cornwall et al., 2020]] ) to adapt over generations to ocean acidification. Populations exposed to variable environments often have a greater capacity for phenotypic plasticity and resilience to environmental change [e.g., urchins (Gaitan-Espitia et al., 2017b) and coralline algae ( [[#3.3.2|Section 3.3.2]] ; [[#Rivest--2017|Rivest et al., 2017]] ; [[#Cornwall--2018|Cornwall et al., 2018]] )]. Although parental conditioning within and across generations is an acclimatisation mechanism to global change, there is ''limited evidence'' from experimental studies that this is applicable for marine invertebrates on rocky shores ( [[#Byrne--2020|Byrne et al., 2020]] ).

This assessment concludes that MHWs attributable to climate change ( [[#3.2.2.1|Section 3.2.2.1]] ) can cause fatal disease outbreaks or mass mortality among some key foundational species ( ''high confidence'' ) and contribute to ecological phase shifts ( ''medium confidence'' ) ''.'' The upper vertical limits of some species will also be constrained by climate change ( ''high confidence'' ). Experimental evidence since previous assessments further indicates that acidification decreases abundance and richness of calcifying species ( ''high confidence'' ), although there is ''limited evidence'' for acclimation in some species. Synergistic effects of warming and acidification will promote shifts towards macroalgal dominance in some ecosystems ( ''medium confidence'' ) and lead to reorganisation of communities ( ''medium confidence'' ).

<div id="3.4.2.3" class="h3-container"></div>

<span id="kelp-ecosystems"></span>
==== 3.4.2.3 Kelp Ecosystems ====

<div id="h3-15-siblings" class="h3-siblings"></div>

Kelp are temperate, habitat-forming marine macroalgae or seaweeds, mostly of the order ''Laminariales'' , which extend across one-quarter of the world’s coastlines ( [[#Assis--2020|Assis et al., 2020]] ; [[#Jayathilake--2020|Jayathilake and Costello, 2020]] ). The perennial species form dense underwater forest canopies and three-dimensional habitat that provides refuge for fish, crustaceans, invertebrates and marine mammals ( [[#Filbee-Dexter--2016|Filbee-Dexter et al., 2016]] ; [[#Wernberg--2019|Wernberg et al., 2019]] ). Kelp ecosystems support fisheries, aquaculture, fertiliser and food provision, including for local and Indigenous Peoples, along with regulating services in the form of wave attenuation and habitat provision. Kelp aquaculture can also buffer against local acidification ( [[#Xiao--2021|Xiao et al., 2021]] ) and contribute to carbon storage ( [[#Froehlich--2019|Froehlich et al., 2019]] ).

Recent research ( [[#Straub--2019|Straub et al., 2019]] ; [[#Butler--2020|Butler et al., 2020]] ; [[#Filbee-Dexter--2020b|Filbee-Dexter et al., 2020b]] ; [[#Tait--2021|Tait et al., 2021]] ) supports the findings of previous assessments (Table 3.5) that kelp and other seaweeds in most regions are undergoing mass mortalities from high temperature extremes and range shifts from warming ( ''very high confidence'' ). Kelp are highly sensitive to the direct effect of high temperature on survival ( [[#Nepper-Davidsen--2019|Nepper-Davidsen et al., 2019]] ) and indirect impact of temperature on herbivorous species ( [[#Ling--2008|Ling, 2008]] ; [[#Vergés--2016|Vergés et al., 2016]] ), upwelling and nutrient availability ( [[#Carr--2015|Carr and Reed, 2015]] ; [[#Schiel--2015|Schiel and Foster, 2015]] ). Synergies between warming, storms, pollution and intensified herbivory (due to removal or loss of predators including sea stars and otters that constrain herbivory by fish and urchin populations) can also cause physiological stress and physical damage in kelp, reducing productivity and reproduction ( [[#Rogers-Bennett--2019|Rogers-Bennett and Catton, 2019]] ; [[#Beas-Luna--2020|Beas-Luna et al., 2020]] ; [[#McPherson--2021|McPherson et al., 2021]] ).

'''Table 3.5 |''' Summary of previous IPCC assessments of kelp ecosystems

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| ‘Kelp forests have been reported to decline in temperate areas in both hemispheres, a loss involving climate change ( ''high confidence'' ). Decline in kelp populations attributed to ocean warming has been reported in southern Australia and the north coast of Spain.’

| ‘Kelp ecosystems will decline with the increased frequency of heatwaves and sea temperature extremes as well as through the impact of invasive subtropical species ( ''high confidence'' ).’

‘Climate change will contribute to the continued decline in the extent of [...] kelps in the temperate zone ( ''medium confidence'' ) and the range of [...] kelps in the Northern Hemisphere will expand poleward ( ''high confidence'' ) ''.'' ’

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )''

Observed movement of kelp ecosystems not assessed.

| ‘In the transition to 1.5°C of warming, changes to water temperatures will drive some species (e.g., plankton, fish) to relocate to higher latitudes and cause novel ecosystems to assemble ( ''high confidence'' ). Other ecosystems (e.g., kelp forests, coral reefs) are relatively less able to move, however, and are projected to experience high rates of mortality and loss ( ''very high confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘Kelp forests have experienced large-scale habitat loss and degradation of ecosystem structure and functioning over the past half century, implying a moderate to high level of risk at present conditions of global warming ( ''high confidence'' ).’

‘The abundance of kelp forests has decreased at a rate of ~2% per year over the past half century, mainly due to ocean warming and marine heat waves [...], as well as from other human stressors ( ''high confidence'' ).’

‘Changes in ocean currents have facilitated the entry of tropical herbivorous fish into temperate kelp forests decreasing their distribution and abundance ( ''medium confidence'' ).’

‘The loss of kelp forests is followed by the colonisation of turfs, which contributes to the reduction in habitat complexity, carbon storage and diversity ( ''high confidence'' ).’

| Kelp forests will face moderate to high risk at temperatures above 1.5°C global sea surface warming ( ''high confidence'' ).

‘Due to their low capacity to relocate and high sensitivity to warming, kelp forests are projected to experience higher frequency of mass mortality events as the exposure to extreme temperature rises ( ''very high confidence'' ).’

‘Changes in ocean currents have facilitated the entry of tropical herbivorous fish into temperate kelp forests decreasing their distribution and abundance ( ''medium confidence'' ).’

‘Kelp forests at low latitudes [...] will continue to retreat as a result of intensified extreme temperatures, and their low dispersal ability will elevate the risk of local extinction under RCP8.5 ( ''high confidence'' ).’

|}

Trends in kelp abundance since 1950 are uneven globally ( [[#Krumhansl--2016|Krumhansl et al., 2016]] ; [[#Wernberg--2019|Wernberg et al., 2019]] ), with population declines (e.g., giant kelp ''Macrocystis pyrifera'' in Tasmania, [[#Butler--2020|Butler et al., 2020]] ; and sugar kelp ''Saccharina latissima'' in the North Atlantic, [[#Filbee-Dexter--2020b|Filbee-Dexter et al., 2020b]] ) more common than increases or no change (e.g., giant kelp ''Macrocystis pyrifera'' in southern Chile; [[#Friedlander--2020|Friedlander et al., 2020]] ). Warming is driving range contraction and extirpation at the warm edge of species’ ranges and expansions at the cold range edge ( ''very high confidence'' ) ( [[#Smale--2019|Smale, 2019]] ; [[#Filbee-Dexter--2020b|Filbee-Dexter et al., 2020b]] ). Local declines in populations of kelp and other canopy-forming seaweeds driven by MHWs and other stressors have caused irreversible shifts to turf- or urchin-dominated ecosystems, with lower productivity and biodiversity ( ''high confidence'' ) ( [[#Filbee-Dexter--2014|Filbee-Dexter and Scheibling, 2014]] ; [[#Filbee-Dexter--2018|Filbee-Dexter and Wernberg, 2018]] ; [[#Rogers-Bennett--2019|Rogers-Bennett and Catton, 2019]] ; [[#Beas-Luna--2020|Beas-Luna et al., 2020]] ; Stuart- [[#Smith--2021|Smith et al., 2021]] ), ecosystems dominated by warm-affinity seaweeds or coral ( ''high confidence'' ) ( [[#Vergés--2019|Vergés et al., 2019]] ), and loss of genetic diversity ( [[#Coleman--2020a|Coleman et al., 2020a]] ; [[#Gurgel--2020|Gurgel et al., 2020]] ).

Species distribution models of kelp project range shifts and local extirpations with increasing levels of warming (Japan: [[#Takao--2015|Takao et al., 2015]] , [[#Sudo--2020|Sudo et al., 2020]] ; Australia: see Table 11.6, and [[#Assis--2018|Assis et al., 2018]] , [[#Martínez--2018|Martínez et al., 2018]] , [[#Castro--2020|Castro et al., 2020]] ; Europe: [[#de%20la%20Hoz--2019|de la Hoz et al., 2019]] ; North America: [[#Wilson--2019|Wilson et al., 2019]] ; South America: see Figure 12.3). There is ''high agreement'' on the direction but not the magnitude of change ( [[#Martínez--2018|Martínez et al., 2018]] ; [[#Castro--2020|Castro et al., 2020]] ), but effects of MHWs are not simulated. Where the length of higher-latitude coastlines is limited, range contractions are projected to occur, even with 2°C of global warming (i.e., SSP1-2.6) due to loss of habitat at the warm edge of species’ ranges ( [[#Martínez--2018|Martínez et al., 2018]] ). Poleward expansion of warm-affinity herbivores, including urchins, could further reduce warm-edge kelp populations ( [[#Castro--2020|Castro et al., 2020]] ; [[#Mulders--2020|Mulders and Wernberg, 2020]] ). Evidence from natural temperate CO 2 seeps suggests that ocean acidification at levels above those in RCP4.5 in 2100 could offset the increase in urchin abundance ( [[#Coni--2021|Coni et al., 2021]] ). Genetic analyses suggest that kelp populations at the midpoint of species’ ranges will have lower tolerance of warming than that implied by species distribution models, without assisted gene flow from warm-edge populations ( [[#King--2019|King et al., 2019]] ; [[#Wood--2021|Wood et al., 2021]] ).

While reducing non-climate drivers can help prevent kelp loss from warming and MHWs, there is limited potential for restoration of kelp ecosystems after transition to urchin-dominant ecosystems ( ''high confidence'' ). Current restoration efforts are generally small scale (&lt;0.1 km 2 ) and less advanced than those in ecosystems like coral reefs ( [[#Coleman--2020b|Coleman et al., 2020b]] ; [[#Eger--2020|Eger et al., 2020]] ; [[#Layton--2020|Layton et al., 2020]] ). Although abundance of herbivores limits kelp populations, there is ''limited evidence'' that restoring predators of herbivores by creating marine reserves, or directly removing grazing species, will increase kelp forest resilience to warming and extremes ( [[#Vergés--2019|Vergés et al., 2019]] ; [[#Wernberg--2019|Wernberg et al., 2019]] ). Active reseeding of wild kelp populations through transplantation and propagation of warm-tolerant genotypes ( [[#Coleman--2020b|Coleman et al., 2020b]] ; [[#Alsuwaiyan--2021|Alsuwaiyan et al., 2021]] ) can overcome low dispersal rates of many kelp species and facilitate effective restoration ( ''medium confidence'' ) ( [[#Morris--2020c|Morris et al., 2020c]] ).

Building on the conclusions of SROCC, this assessment finds that kelp ecosystems are expected to decline and undergo changes in community structure in the future due to warming and increasing frequency and intensity of MHWs ( ''high confidence'' ). Risk of loss of kelp ecosystems and shifts to turf- or urchin-dominated ecosystems are highest at the warm edge of species’ ranges ( ''high confidence'' ) and risks increase under RCP6.0 and RCP8.5 by the end of the century ( ''high confidence'' ).

<div id="3.4.2.4" class="h3-container"></div>

<span id="estuaries-deltas-and-coastal-lagoons"></span>
==== 3.4.2.4 Estuaries, Deltas and Coastal Lagoons ====

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Estuaries, deltas and lagoons encounter environmental gradients over small spatial scales, generating diverse habitats that support myriad ecosystem services, including food provision, regulation of erosion, nutrient recycling, carbon sequestration, recreation and tourism, and cultural significance ( [[#D’Alelio--2021|D’Alelio et al., 2021]] ; [[#Keyes--2021|Keyes et al., 2021]] ). Although these coastal ecosystems have historically been sensitive to erosion-accretion cycles driven by sea level, drought and storms ( ''high confidence'' ) ( [[#Peteet--2018|Peteet et al., 2018]] ; [[#Wang--2018c|Wang et al., 2018c]] ; [[#Jones--2019b|Jones et al., 2019b]] ; [[#Urrego--2019|Urrego et al., 2019]] ; [[#Hapsari--2020|Hapsari et al., 2020]] ; [[#Zhao--2020b|Zhao et al., 2020b]] ), they were impacted for much of the 20th century primarily by non-climate drivers ( ''very high confidence'' ) ( [[#Brown--2018b|Brown et al., 2018b]] ; [[#Ducrotoy--2019|Ducrotoy et al., 2019]] ; [[#Elliott--2019|Elliott et al., 2019]] ; [[#He--2019|He and Silliman, 2019]] ; [[#Andersen--2020|Andersen et al., 2020]] ; [[#Newton--2020|Newton et al., 2020]] ; [[#Stein--2020|Stein et al., 2020]] ). Nevertheless, the influence of climate-induced drivers has become more apparent over recent decades ( ''medium confidence'' ) (Table 3.6).

'''Table 3.6 |''' Summary of previous IPCC assessments of estuaries, deltas and coastal lagoons

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| Humans have impacted lagoons, estuaries and deltas ( ''high'' to ''very high confidence'' ), but non-climate drivers have been the primary agents of change ( ''very'' ''high confidence'' ).

In estuaries and lagoons, nutrient inputs have driven eutrophication, which has modified food-web structures ( ''high confidence'' ) and caused more-intense and longer-lasting hypoxia, more-frequent occurrence of harmful algal blooms and enhanced emissions of nitrous oxide ( ''high confidence'' ).

In deltas, land-use changes and associated disruption of sediment dynamics and land subsidence have driven changes that have been exacerbated by relative SLR and episodic events, including river floods and oceanic storm surges ( ''very high confidence'' ).

Increased coastal flooding, erosion and saltwater intrusions have led to degradation of ecosystems ( ''very high confidence'' ).

| Future changes in climate impact-drivers such as warming, acidification, waves, storms, sea level rise (SLR) and runoff will have consequences for ecosystem function and services in lagoons and estuaries ( ''high confidence'' ), but with regional differences in magnitude of change in impact drivers and ecosystem response.

Warming, changes in precipitation and changes in wind strength can interact to alter water-column salinity and stratification ( ''medium confidence'' ), which could impact water column oxygen content ( ''medium confidence'' ).

Land-use change, SLR and intensifying storms will alter deposition-erosion dynamics, impacting shoreline vegetation and altering turbidity ( ''medium confidence'' ). Together with warming, these drivers will alter the seasonal pattern of primary production and the distribution of biota throughout the ecosystems ( ''medium to high confidence'' ), impacting associated ecosystem services.

The projected impacts of climate change on deltas are associated mainly with pluvial floods and SLR, which will amplify observed impacts of interacting climate and non-climate drivers ( ''high confidence'' ).

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )''

|
|-
| Estuaries, deltas and lagoons were not assessed in this report.

| Under both a 1.5°C and 2°C of warming, relative to the pre-industrial era, deltas are expected to be highly threatened by SLR and localised subsidence ( ''high confidence'' ). The slower rate of SLR associated with 1.5°C of warming poses smaller risks of flooding and salinisation ( ''high confidence'' ), and facilitates greater opportunities for adaptation, including managing and restoring natural coastal ecosystems and infrastructure reinforcement ( ''medium confidence'' ).

[Intact coastal ecosystems] ‘may be effective in reducing the adverse impacts of rising sea levels and intensifying storms by protecting coastal and deltaic regions ( ''medium confidence'' ).’

‘Natural sedimentation rates are expected to be able to offset the effect of rising sea levels, given the slower rates of SLR associated with 1.5°C of warming ( ''medium confidence'' ). Other feedbacks, such as landward migration of wetlands and the adaptation of infrastructure, remain important ( ''medium confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Increased seawater intrusion caused by SLR has driven upstream redistribution of marine biotic communities in estuaries ( ''medium confidence'' ) where physical barriers, such as the availability of benthic substrates, do not limit availability of suitable habitats ( ''medium confidence'' ).

Warming has driven poleward range shifts in species’ distributions among estuaries ( ''medium confidence'' ).

Interactions between warming, eutrophication and hypoxia have increased the incidence of harmful algal blooms ( ''high confidence'' ), pathogenic bacteria, such as ''Vibrio'' species, ( ''low confidence'' ) and mortalities of invertebrates and fish communities ( ''medium confidence'' ).

| ‘Salinisation and expansion of hypoxic conditions will intensify in eutrophic estuaries, especially in mid and high latitudes with microtidal regimes ( ''high confidence'' ).’

‘The effects of warming will be more pronounced in high-latitude and temperate shallow estuaries with limited exchange with the open ocean [...] and seasonality that already leads to dead zone development [...] ( ''medium confidence'' ).’

Interaction between SLR and changes in precipitation will have greater impacts on shallow than deep estuaries ( ''medium confidence'' ).

Estuaries characterised by large tidal exchanges and associated well-developed sediments will be more resilient to projected SLR and changes in river flow ( ''medium confidence'' ). Human activities that inhibit sediment dynamics in coastal deltas increase their vulnerability to SLR ( ''medium confidence'' ).

|}

Estuarine biota are sensitive to warming ( ''high confidence'' ), with recent responses including changes in abundance of some fish stocks ( [[#Erickson--2021|Erickson et al., 2021]] ; [[#Woodland--2021|Woodland et al., 2021]] ), poleward shifts in distributions of fish species, communities and associated biogeographic transition zones (Table 12.3; [[#Franco--2020|Franco et al., 2020]] ; [[#Troast--2020|Troast et al., 2020]] ), recruits of warm-affinity species persisting into winter ( [[#Kimball--2020|Kimball et al., 2020]] ) and changes in seasonal timing of peaks in species abundance ( [[#Kimball--2020|Kimball et al., 2020]] ). MHWs can be more severe in estuaries than in adjacent coastal seas ( [[#Lonhart--2019|Lonhart et al., 2019]] ), causing conspicuous impacts ( ''very high confidence'' ), including mass mortality of intertidal vegetation ( [[#3.4.2.5|Section 3.4.2.5]] ), range shifts in algae and animals ( [[#Lonhart--2019|Lonhart et al., 2019]] ) and reduced spawning success among invertebrates ( [[#Shanks--2020|Shanks et al., 2020]] ).

Relative SLR extends the upstream limit of saline waters ( ''high confidence'' ) ( [[#Harvey--2020|Harvey et al., 2020]] ; [[#Jiang--2020|Jiang et al., 2020]] ) and alters tidal ranges ( ''high confidence'' ) ( [[#Idier--2019|Idier et al., 2019]] ; [[#Talke--2020|Talke et al., 2020]] ). Elevated water levels also alter submergence patterns for intertidal habitat ( ''high confidence'' ) ( [[#Andres--2019|Andres et al., 2019]] ), moving high-water levels inland ( ''high confidence'' ) ( [[#Peteet--2018|Peteet et al., 2018]] ; [[#Appeaning%20Addo--2020|Appeaning Addo et al., 2020]] ; [[#Liu--2020e|Liu et al., 2020e]] ) and increasing the salinity of coastal water tables and soils ( ''high confidence'' ) ( [[#Eswar--2021|Eswar et al., 2021]] ). These processes favour inland and/or upstream migration of intertidal habitat, where it is unconstrained by infrastructure, topography or other environmental features ( ''high confidence'' ) ( [[#Kirwan--2019|Kirwan and Gedan, 2019]] ; [[#Parker--2019|Parker and Boyer, 2019]] ; [[#Langston--2020|Langston et al., 2020]] ; [[#Magolan--2020|Magolan and Halls, 2020]] ; [[#Saintilan--2020|Saintilan et al., 2020]] ). The spread of ‘ghost forests’ along the North American east coast ( [[#Kirwan--2019|Kirwan and Gedan, 2019]] ) and elsewhere ( [[#Grieger--2020|Grieger et al., 2020]] ) illustrates this phenomenon. Along estuarine shorelines, changing submergence patterns and upstream penetration of saline waters interact synergistically to stress intertidal plants, changing species composition and reducing above-ground biomass, in some cases favouring invasive species ( [[#Xue--2018|Xue et al., 2018]] ; [[#Buffington--2020|Buffington et al., 2020]] ; [[#Gallego-Tévar--2020|Gallego-Tévar et al., 2020]] ). Overall, changing salinity and submergence patterns decrease the ability of shoreline vegetation to trap sediment ( [[#Xue--2018|Xue et al., 2018]] ), reducing accretion rates and increasing the vulnerability of estuarine shorelines to submergence by SLR and erosion by wave action ( ''medium confidence'' ) ( [[#Zhu--2020b|Zhu et al., 2020b]] ).

Drought and freshwater abstraction can reduce freshwater inflows to estuaries and lagoons, increasing salinity, reducing water quality ( [[#Brooker--2020|Brooker and Scharler, 2020]] ) and depleting resident macrophyte communities ( [[#Scanes--2020b|Scanes et al., 2020b]] ). Changes in freshwater input and SLR, combined with land-use change, can alter inputs of land-based sediments, causing expansion ( [[#Suyadi--2019|Suyadi et al., 2019]] ; [[#Magolan--2020|Magolan and Halls, 2020]] ) or contraction ( [[#Andres--2019|Andres et al., 2019]] ; [[#Appeaning%20Addo--2020|Appeaning Addo et al., 2020]] ; [[#Li--2020b|Li et al., 2020b]] ) of intertidal habitats. The same phenomena alter salinity gradients, which are the primary drivers of estuarine species distributions ( ''high confidence'' ) ( [[#Douglass--2020|Douglass et al., 2020]] ; [[#Lauchlan--2020|Lauchlan and Nagelkerken, 2020]] ). Extreme reduction of freshwater input can extend residence time of estuarine water, leading to persistent HABs ( [[#Lehman--2020|Lehman et al., 2020]] ) and converting estuaries to lagoons if the mouth clogs with sediment ( [[#Thom--2020|Thom et al., 2020]] ).

Acidification of estuarine water is a growing hazard ( ''medium confidence'' ) ( [[#Doney--2020|Doney et al., 2020]] ; [[#Scanes--2020a|Scanes et al., 2020a]] ; [[#Cai--2021|Cai et al., 2021]] ), and resident organisms display sensitivity to altered pH in laboratory settings ( ''medium confidence'' ) ( [[#Young--2019a|Young et al., 2019a]] ; [[#Morrell--2020|Morrell and Gobler, 2020]] ; [[#Pardo--2021|Pardo and Costa, 2021]] ). However, attribution of the biological effects of acidification is difficult because many biogeochemical processes affect estuarine carbon chemistry (Sections 3.2.3.1, 3.3.2). Warming can exacerbate the impacts of both acidification and hypoxia on estuarine organisms ( [[#Baumann--2018|Baumann and Smith, 2018]] ; [[#Collins--2019b|Collins et al., 2019b]] ; [[#Ni--2020|Ni et al., 2020]] ). These effects are further complicated by eutrophication, with high nitrogen loads associated with lower pH ( [[#Rheuban--2019|Rheuban et al., 2019]] ). Warming (including MHWs) and eutrophication interact to decrease estuarine oxygen content and pH, increasing the vulnerability of animals to MHWs ( [[#Brauko--2020|Brauko et al., 2020]] ) and exacerbating the incidence and impact of dead zones ( ''medium confidence'' ) ( [[#Altieri--2015|Altieri and Gedan, 2015]] ). The impacts of storms on estuaries are variable and are described in SM3.3.1.

All these impacts are projected to escalate under future climate change, but their magnitude depends on the amount of warming, the socioeconomic development pathway and implementation of adaptation strategies ( ''medium confidence'' ). Modelling studies ( [[#Lopes--2019|Lopes et al., 2019]] ; [[#Rodrigues--2019|Rodrigues et al., 2019]] ; [[#White--2019|White et al., 2019]] ; [[#Zhang--2019|Zhang and Li, 2019]] ; [[#Hong--2020|Hong et al., 2020]] ; [[#Krvavica--2020|Krvavica and Ružić, 2020]] ; [[#Liu--2020e|Liu et al., 2020e]] ; [[#Shalby--2020|Shalby et al., 2020]] ) suggest that responses of estuaries to SLR will be complex and context dependent ( [[#Khojasteh--2021|Khojasteh et al., 2021]] ), but project that salinity, tidal range, storm-surge amplitude, depth and stratification will increase with SLR ( ''medium confidence'' ), and that marine-dominated waters will penetrate farther upstream ( ''high confidence'' ). Without careful management of freshwater inputs, sediment augmentation and/or the restoration of shorelines to more natural states, transformation and loss of intertidal areas and wetland vegetation will increase with SLR ( ''high confidence'' ) ( [[#Doughty--2019|Doughty et al., 2019]] ; [[#Leuven--2019|Leuven et al., 2019]] ; [[#Yu--2019|Yu et al., 2019]] ; [[#Raw--2020|Raw et al., 2020]] ; [[#Shih--2020|Shih, 2020]] ; [[#Stein--2020|Stein et al., 2020]] ), with small, shallow microtidal estuaries being more vulnerable to impacts than deeper estuaries with well-developed sediments ( ''medium confidence'' ) ( [[#Leuven--2019|Leuven et al., 2019]] ; [[#Williamson--2021|Williamson and Guinder, 2021]] ). Warming and MHWs will enhance stratification and deoxygenation in shallow lagoons ( ''medium confidence'' ) ( [[#Derolez--2020|Derolez et al., 2020]] ) and will continue to drive range shifts among estuarine biota ( ''medium confidence'' ) ( [[#Veldkornet--2019|Veldkornet and Rajkaran, 2019]] ; [[#Zhang--2020c|Zhang et al., 2020c]] ), resulting in extirpations where thermal habitat is lost and potentially generating new habitat for warm-affinity species ( ''limited evidence, medium agreement'' ) ( [[#Veldkornet--2019|Veldkornet and Rajkaran, 2019]] ).

<div id="3.4.2.5" class="h3-container"></div>

<span id="vegetated-blue-carbon-ecosystems"></span>
==== 3.4.2.5 Vegetated Blue Carbon Ecosystems ====

<div id="h3-17-siblings" class="h3-siblings"></div>

Mangroves, salt marshes and seagrass beds (wetland ecosystems) are considered ‘blue carbon’ ecosystems due to their capacity to accumulate and store organic-carbon rich sediments (see Box 3.4; [[#Macreadie--2019|Macreadie et al., 2019]] ; [[#Rogers--2019|Rogers et al., 2019]] ) and provide an extensive range of other ecosystem services (see Box 3.4). Because these ecosystems are often found within estuaries and along sheltered coastlines, they share vulnerabilities, climate-induced drivers (Table 3.7) and non-climate drivers with estuaries and coastal lagoons ( [[#3.4.2.4|Section 3.4.2.4]] ).

'''Table 3.7 |''' Summary of previous IPCC assessments of mangroves, salt marshes and seagrass beds

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| Seagrasses occurring close to their upper thermal limits are already stressed by climate change ( ''high confidence'' ).

‘Increased CO 2 concentrations have increased seagrass photosynthetic rates by 20% ( ''limited evidence, high agreement'' ).’

| Climate change will drive ongoing declines in the extent of seagrasses in temperate waters ( ''medium confidence'' ) as well as poleward range expansions of seagrasses and mangroves, especially in the Northern Hemisphere ( ''high confidence'' ).

Beneficial effects of elevated CO 2 will increase seagrass productivity and carbon burial rates in salt marshes during the first half of the 21st century, but there is ''limited evidence'' that this will improve their survival or resistance to warming.

As a result, interactions between climate change and non-climate drivers will continue to cause declines in estuarine vegetated systems ( ''very high confidence'' ).

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )''

|
|-
| Vegetated blue carbon systems were not assessed in this report.

| Intact wetland ecosystems can reduce the adverse impacts of rising sea levels and intensifying storms by protecting shorelines ( ''medium confidence'' ), and their degradation could reduce remaining carbon budgets by up to 100 GtCO 2 .

Under 1.5°C of warming, natural sedimentation rates are projected to outpace SLR ( ''medium confidence'' ), but ‘other feedbacks, such as landward migration of wetlands and the adaptation of infrastructure, remain important ( ''medium confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] )''

|
|-
| Coastal ecosystems, including salt marshes, mangroves, vegetated dunes and sandy beaches, can build vertically and expand laterally in response to SLR, though this capacity varies across sites ( ''high confidence'' ). These ecosystems provide important services that include coastal protection and habitat for diverse biota. However, as a consequence of human actions that fragment wetland habitats and restrict landward migration, coastal ecosystems progressively lose their ability to adapt to climate-induced changes and provide ecosystem services, including acting as protective barriers ( ''high confidence'' ).’

Warming and SLR-driven salinisation of wetlands are causing shifts in the distribution of plant species inland and poleward. Examples include mangrove encroachment into subtropical salt marshes ( ''high confidence'' ) and contraction in extent of low-latitude seagrass meadows ( ''high confidence'' ).

Plants with low tolerance to flooding and extreme temperatures are particularly vulnerable, increasing the risk of extirpation ( ''medium confidence'' ).

Extreme-weather events, including heatwaves, droughts and storms, are causing mass mortalities and changes in community composition in coastal wetlands ( ''high confidence'' ).

Severe disturbance of wetlands or transitions among wetland community types can favour invasive species ( ''medium confidence'' ).

The degradation or loss of vegetated coastal ecosystems reduces carbon storage, with positive feedbacks to the climate system ( ''high confidence'' ).

| ‘Seagrass meadows ( ''high confidence'' ) [...] will face moderate to high risk at temperature above 1.5°C global sea surface warming.’

‘The transition from undetectable to moderate risk in salt marshes [...] takes place between 0.7°C–1.2°C of global sea surface warming ( ''medium/high confidence'' ), and between 0.9°C–1.8°C ( ''medium confidence'' ) in sandy beaches, estuaries and mangrove forests.’

‘The ecosystems at moderate to high risk under future emission scenarios are mangrove forests (transition from moderate to high risk at 2.5°C–2.7°C of global sea surface warming), estuaries and sandy beaches (2.3°C–3.0°C) and salt marshes (transition from moderate to high risk at 1.8°C–2.7°C and from high to very high risk at 3.0°C–3.4°C) ( ''medium confidence'' ).’

‘Global coastal wetlands will lose between 20–90% of their area depending on emissions scenario with impacts on their contributions to carbon sequestration and coastal protection ( ''high confidence'' ).’

Estuarine wetlands will remain resilient to modest rates of SLR where their sediment dynamics are unconstrained. But SLR and warming are projected to drive global loss of up to 90% of vegetated wetlands by the end of the century under the RCP8.5 ( ''medium confidence'' ), especially if landward migration and sediment supply are limited by human modification of shorelines and river flows ( ''medium confidence'' ).

‘Moreover, pervasive coastal squeeze and human-driven habitat deterioration will reduce the natural capacity of these ecosystems to adapt to climate impacts ( ''high confidence'' ).’

|}

Since AR5 and SROCC, syntheses have emphasised that the vulnerability of rooted wetland ecosystems to climate-induced drivers is exacerbated by non-climate drivers ( ''high confidence'' ) ( [[#Elliott--2019|Elliott et al., 2019]] ; [[#Ostrowski--2021|Ostrowski et al., 2021]] ; [[#Williamson--2021|Williamson and Guinder, 2021]] ) and climate variability ( ''high confidence'' ) ( [[#Day--2019|Day and Rybczyk, 2019]] ; [[#Kendrick--2019|Kendrick et al., 2019]] ; [[#Shields--2019|Shields et al., 2019]] ). Global rates of mangrove loss have been extensive but are slowing ( ''high confidence'' ) at least partially due to management interventions ( [[#Friess--2020b|Friess et al., 2020b]] ; [[#Goldberg--2020|Goldberg et al., 2020]] ). From 2000 to 2010 mangrove loss averaged 0.16% yr –1 , globally, but with greatest loss in Southeast Asia ( ''high confidence'' ) ( [[#Hamilton--2016|Hamilton and Casey, 2016]] ; [[#Friess--2019|Friess et al., 2019]] ; [[#Goldberg--2020|Goldberg et al., 2020]] ) and ubiquitous fragmentation leaving few mangroves intact (Bryan- [[#Brown--2020|Brown et al., 2020]] ). Salt-marsh ecosystems have also suffered extensive losses (up to 60% in places since the 1980s), especially in developed and rapidly developing countries ( ''medium confidence'' ) (Table 12.3; [[#Gu--2018|Gu et al., 2018]] ; [[#Stein--2020|Stein et al., 2020]] ). Similarly, 29% of seagrass meadows were lost from 1879–to 2006 due primarily to coastal development and degradation of water quality, with climate-change impacts escalating since 1990 ( ''medium confidence'' ) ( [[#Waycott--2009|Waycott et al., 2009]] ; [[#Sousa--2019|Sousa et al., 2019]] ; [[#Derolez--2020|Derolez et al., 2020]] ; [[#Green--2021a|Green et al., 2021a]] ). Local examples of habitat stability or growth (e.g., [[#de%20los%20Santos--2019|de los Santos et al., 2019]] ; [[#Laengner--2019|Laengner et al., 2019]] ; [[#Sousa--2019|Sousa et al., 2019]] ; [[#Suyadi--2019|Suyadi et al., 2019]] ; [[#Derolez--2020|Derolez et al., 2020]] ; [[#Goldberg--2020|Goldberg et al., 2020]] ; [[#McKenzie--2020|McKenzie and Yoshida, 2020]] ) indicate some resilience to climate change in the absence of non-climate drivers ( ''high confidence'' ). Nevertheless, previous declines have left wetland ecosystems more vulnerable to impacts from climate-induced drivers and non-climate drivers ( ''high confidence'' ) ( [[#Friess--2019|Friess et al., 2019]] ; [[#Williamson--2021|Williamson and Guinder, 2021]] ).

Warming and MHWs have affected the range, species composition and survival of some wetland ecosystems. Warming is allowing some, but not all ( [[#Rogers--2018|Rogers and Krauss, 2018]] ; [[#Saintilan--2018|Saintilan et al., 2018]] ), mangrove species to expand their ranges poleward ( ''high confidence'' ) ( [[#Friess--2019|Friess et al., 2019]] ; [[#Whitt--2020|Whitt et al., 2020]] ). This expansion can affect species interactions ( [[#Guo--2017|Guo et al., 2017]] ; [[#Friess--2019|Friess et al., 2019]] ), and enhance sediment accretion and carbon storage rates in some instances ( ''medium confidence'' ) ( [[#Guo--2017|Guo et al., 2017]] ; [[#Kelleway--2017|Kelleway et al., 2017]] ; [[#Chen--2018b|Chen et al., 2018b]] ; [[#Coldren--2019|Coldren et al., 2019]] ; [[#Raw--2019|Raw et al., 2019]] ). Drought, low sea levels and MHWs can cause significant die-offs among mangroves ( ''medium confidence'' ) ( [[#Lovelock--2017b|Lovelock et al., 2017b]] ; [[#Duke--2021|Duke et al., 2021]] ). Seagrasses are similarly vulnerable to warming ( ''high confidence'' ) ( [[#Repolho--2017|Repolho et al., 2017]] ; [[#Duarte--2018|Duarte et al., 2018]] ; [[#Jayathilake--2018|Jayathilake and Costello, 2018]] ; [[#Savva--2018|Savva et al., 2018]] ), which has been attributed as one cause of observed changes in distribution and community structure ( ''medium confidence'' ) ( [[#Hyndes--2016|Hyndes et al., 2016]] ; [[#Nowicki--2017|Nowicki et al., 2017]] ). MHWs, together with storm-driven turbidity and structural damage, can cause seagrass die-offs ( ''high confidence'' ) ( [[#Arias-Ortiz--2018|Arias-]] [[#Ortiz--2018|Ortiz et al., 2018]] ; [[#Kendrick--2019|Kendrick et al., 2019]] ; [[#Smale--2019|Smale et al., 2019]] ; [[#Strydom--2020|Strydom et al., 2020]] ), shifts to small, fast-growing species ( ''high confidence'' ) ( [[#Kendrick--2019|Kendrick et al., 2019]] ; [[#Shields--2019|Shields et al., 2019]] ; [[#Strydom--2020|Strydom et al., 2020]] ) and ecosystem collapse ( [[#Serrano--2021|Serrano et al., 2021]] ).

The sensitivity of salt marshes and mangroves to RSLR depends on whether they accrete inorganic sediment and/or organic material at rates equivalent to rising water levels ( ''very high confidence'' ) ( [[#Peteet--2018|Peteet et al., 2018]] ; [[#FitzGerald--2019|FitzGerald and Hughes, 2019]] ; [[#Friess--2019|Friess et al., 2019]] ; [[#Gonneea--2019|Gonneea et al., 2019]] ; [[#Leo--2019|Leo et al., 2019]] ; [[#Marx--2020|Marx et al., 2020]] ; [[#Saintilan--2020|Saintilan et al., 2020]] ). Otherwise, wetland ecosystems must migrate either inland or upstream, or face gradual submergence in deeper, increasingly saline water ( ''very high confidence'' ) ( [[#3.4.2.4|Section 3.4.2.4]] ; [[#Andres--2019|Andres et al., 2019]] ; [[#Jones--2019b|Jones et al., 2019b]] ; [[#Cohen--2020|Cohen et al., 2020]] ; [[#Mafi-Gholami--2020|Mafi-Gholami et al., 2020]] ; [[#Magolan--2020|Magolan and Halls, 2020]] ; [[#Sklar--2021|Sklar et al., 2021]] ). Ability to migrate depends on local topography, the positioning of anthropogenic infrastructure and structures placed to defend such infrastructure ( [[#Schuerch--2018|Schuerch et al., 2018]] ; [[#Fagherazzi--2020|Fagherazzi et al., 2020]] ; [[#Cahoon--2021|Cahoon et al., 2021]] ). Submergence drives changes in community structure ( ''high confidence'' ) ( [[#Jones--2019b|Jones et al., 2019b]] ; [[#Yu--2019|Yu et al., 2019]] ; [[#Douglass--2020|Douglass et al., 2020]] ; [[#Langston--2020|Langston et al., 2020]] ) and functioning ( ''high confidence'' ) ( [[#Charles--2019|Charles et al., 2019]] ; [[#Buffington--2020|Buffington et al., 2020]] ; [[#Stein--2020|Stein et al., 2020]] ), and will eventually lead to extirpation of the most sensitive vegetation ( ''medium confidence'' ) ( [[#Schepers--2017|Schepers et al., 2017]] ; [[#Scalpone--2020|Scalpone et al., 2020]] ) and associated animals ( ''low confidence'' ) ( [[#Rosencranz--2018|Rosencranz et al., 2018]] ). The impacts of storms on wetlands are variable and described in SM3.3.1.

'''Table 3.8 |''' Estimates of vulnerability of coastal wetlands to sea level rise (SLR) on the basis of sediment cores

{| class="wikitable"
|-
! Region

! Habitat

! Reference

! colspan="2"| Rates of SLR at which habitat loss is

! colspan="2"| WGI AR6 Table 9.9 median estimate (and ''likely'' range) of SLR ( [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] )

|-
!
! ''Likely''

! ''Very likely''

! 2040–2060

! 2080–2100

|-
| Global

| Mangrove

| [[#Saintilan--2020|Saintilan et al. (2020)]]

| 4.2 a

| 6.1

| SSP1-1.9:

4.2 (2.9–6.1) mm yr –1

| 4.3 (2.5–6.6) mm yr –1

|-
| Southeastern USA

| Salt marsh

| [[#Törnqvist--2020|Törnqvist et al. (2020)]]

| 3.5 b

| 4.2 b

| SSP5-8.5:

7.3 (5.7–9.8) mm yr –1

| 12.2 (8.8–17.7) mm yr –1

|-
| UK

| Salt marsh

| [[#Horton--2018|Horton et al. (2018)]]

| 4.6 a

| 7.1 a

| colspan="2"|
|}

Notes:

(a) Estimate digitised from published figure

(b) Published figure digitised and remodelled as binomial generalised linear model (number drowned as compared with not drowned)

As noted in SROCC, given the diversity of coastal wetlands as well as the dependence of their future vulnerability to climate change on adaptation pathways ( [[#Krauss--2021|Krauss, 2021]] ; [[#Rogers--2021|Rogers, 2021]] ), projections of future impacts based on shoreline elevation estimated from satellite data and CMIP5 projections ( [[#Spencer--2016|Spencer et al., 2016]] ; [[#Schuerch--2018|Schuerch et al., 2018]] ) vary greatly. Although all approaches have individual strengths and weaknesses ( [[#Törnqvist--2021|Törnqvist et al., 2021]] ), paleorecords provide some clarity because they yield estimates of wetland responses to changes in climate in the absence of other anthropogenic drivers and are therefore inherently conservative. On the basis of paleorecords (Table 3.8), we assess that mangroves and salt marshes are ''likely'' at high risk from future SLR, even under SSP1-1.9, with impacts manifesting in the mid-term ( ''medium confidence'' ). Under SSP5-8.5, wetlands are ''very likely'' at high risk from SLR, with larger impacts manifesting before 2040 ( ''medium confidence'' ). By 2100, these ecosystems are at high risk of impacts under all scenarios except SSP1-1.9 ( ''high confidence'' ), with impacts most severe along coastlines with gently sloping shorelines, limited sediment inputs, small tidal ranges and limited space for inland migration ( ''very high confidence'' ) (Cross-Chapter Box SLR in Chapter 3; [[#Schuerch--2018|Schuerch et al., 2018]] ; [[#FitzGerald--2019|FitzGerald and Hughes, 2019]] ; [[#Leo--2019|Leo et al., 2019]] ; [[#Schuerch--2019|Schuerch et al., 2019]] ; [[#Raw--2020|Raw et al., 2020]] ; [[#Saintilan--2020|Saintilan et al., 2020]] ).

For seagrasses, recent projections for climate-change impacts vary by species and region. Warming is projected to increase the habitat available to ''Zostera marina'' on the east coast of the USA by 2100 but contract its southern range edge by 150–650 km under RCP2.6 and RCP8.5, respectively ( [[#Wilson--2019|]] [[#Wilson--2019|Wilson and Lotze, 2019]] ). Other species, such as ''Posidonia oceanica'' in the Mediterranean, might lose as much as 75% of their habitat by 2050 under RCP8.5 and become functionally extinct ( ''low confidence'' ) by 2100 ( [[#Chefaoui--2018|Chefaoui et al., 2018]] ). Observed impacts of MHWs ( [[#Kendrick--2019|Kendrick et al., 2019]] ; [[#Strydom--2020|Strydom et al., 2020]] ; [[#Serrano--2021|Serrano et al., 2021]] ) indicate that increasing intensity and frequency of MHWs ( [[#3.2.2.1|Section 3.2.2.1]] ) will have escalating impacts on seagrass ecosystems ( ''high confidence'' ). Habitat suitability can also be reduced by moderate RSLR, due to its impact on light attenuation ( ''medium confidence'' ) ( [[#Aoki--2020|Aoki et al., 2020]] ; [[#Ondiviela--2020|Ondiviela et al., 2020]] ; [[#Scalpone--2020|Scalpone et al., 2020]] ).

Overall, warming will drive range shifts in wetland species ( ''medium to high confidence'' ), but SLR poses the greatest risk for mangroves and salt marshes, with significant losses projected under all future scenarios by mid-century ( ''medium confidence'' ) and substantially greater losses by 2100 under all scenarios except SSP1-1.9 ( ''high confidence'' ). MHWs pose the greatest risk to seagrasses ( ''high confidence'' ). In all cases, losses will be greatest where accommodation space is constrained or where other non-climate drivers exacerbate risk from climate-induced drivers ( ''very high confidence'' ).

<div id="3.4.2.6" class="h3-container"></div>

<span id="sandy-beaches"></span>
==== 3.4.2.6 Sandy Beaches ====

<div id="h3-18-siblings" class="h3-siblings"></div>

'''Table 3.9 |''' Summary of previous IPCC assessments of sandy beaches.

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| ‘Globally, beaches and dunes have in general undergone net erosion over the past century or longer.’

‘Attributing shoreline changes to climate change is still difficult owing to the multiple natural and anthropogenic drivers contributing to coastal erosion.’

| ‘In the absence of adaptation, beaches, sand dunes and cliffs currently eroding will continue to do so under increasing sea level ( ''high confidence'' ).’

‘Coastal squeeze is expected to accelerate with a rising sea level. In many locations, finding sufficient sand to rebuild beaches and dunes artificially will become increasingly difficult and expensive as present supplies near project sites are depleted ( ''high confidence'' ).’

‘In the absence of adaptation measures, beaches and sand dunes currently affected by erosion will continue to be affected under increasing sea levels ( ''high confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Coastal ecosystems are already impacted by the combination of SLR, other climate-related ocean changes and adverse effects from human activities on ocean and land ( ''high confidence'' ). Attributing such impacts to SLR, however, remains challenging due to the influence of other climate-related and non-climate drivers such as infrastructure development and human-induced habitat degradation ( ''high confidence'' ). Coastal ecosystems, including salt marshes, mangroves, vegetated dunes and sandy beaches, can build vertically and expand laterally in response to SLR, though this capacity varies across sites ( ''high confidence'' ) as a consequence of human actions that fragment wetland habitats and restrict landward migration. Coastal ecosystems also progressively lose their ability to adapt to climate-induced changes and provide ecosystem services, including acting as protective barriers ( ''high confidence'' ).

‘Loss of breeding substrate, including mostly coastal habitats such as sandy beaches, can reduce the available nesting or pupping habitat for land-breeding marine turtles, lizards, seabirds and pinnipeds ( ''high confidence'' ).’

‘Overall, changes in sandy beach morphology have been observed from climate-related events, such as storm surges, intensified offshore winds and from coastal degradation caused by humans ( ''high confidence'' ), with impacts on beach habitats (e.g., benthic megafauna) ( ''medium confidence'' ).’

| ‘Sandy beach ecosystems will increasingly be at risk of eroding, reducing the habitable area for dependent organisms ( ''high confidence'' ).’

‘Sandy shorelines are expected to continue to reduce their area and change their topography due to SLR and increased extreme climatic erosive events. This will be especially important in low-lying coastal areas with high population and building densities ( ''medium confidence'' ).’

‘Assuming that the physiological underpinning of the relationship between body size and temperature can be applied to warming ( ''medium confidence'' ), the body size of sandy beach crustaceans is expected to decrease under warming ( ''low evidence, medium agreemen'' t).’

Sandy beaches transition from undetectable to moderate risk between 0.9°C and 1.8°C ( ''medium confidence'' ) of global sea surface warming and from moderate to high risk at 2.3°C–3.0°C of global sea surface warming ( ''medium confidence'' ).

‘Projected changes in mean and extreme sea levels and warming under RCP8.5 are expected to result in high risk of impacts on sandy beach ecosystems by the end of the 21st century ( ''medium confidence'' ), taking account of the slow recovery rate of sandy-beach vegetation, the direct loss of habitats and the high climatic sensitivity of some fauna.’

‘Under RCP2.6, the risk of impacts on sandy beaches is expected to be only slightly higher than the present-day level ( ''low confidence'' ). However, pervasive coastal urbanisation lowers the buffering capacity and recovery potential of sandy beach ecosystems to impacts from SLR and warming, and thus is expected to limit their resilience to climate change ( ''high confidence'' ).’

‘Coastal squeeze and human-driven habitat deterioration will reduce the natural capacity of these ecosystems to adapt to climate impacts ( ''high confidence'' ).’

|}

Sandy beaches comprise unvegetated, fine- to medium-grained sediments in the intertidal zones that line roughly one-third of the length of the world’s ice-free coastlines ( [[#Luijendijk--2018|Luijendijk et al., 2018]] ). The amenity value of beaches as cultural, recreational and residential destinations has driven extensive urbanisation of beach-associated coastlines ( [[#Todd--2019|Todd et al., 2019]] ). Beaches also provide habitat for many resident species, nesting habitat for marine vertebrates, filtration of coastal waters and protection of the coastline from erosion ( [[#McLachlan--2018|McLachlan and Defeo, 2018]] ). These soft-sediment coastal ecosystems are particularly vulnerable to habitat loss caused by erosion, especially where landward transgression is inhibited by infrastructure (Table 3.9).

Since SROCC, observed trends in coastal erosion continue to be obscured by beach nourishment that replaces eroded sediment or by coastal protection of areas at risk of erosion ( [[#3.6.3.1.1|Section 3.6.3.1.1]] ; Cross-Chapter Box SLR in Chapter 3). Nevertheless, RSLR, increases in wave energy and/or changes in wave direction, disruptions to sediment supplies (including sand mining) and other anthropogenic modifications of the coast have driven localised beach erosion ( ''very high confidence'' ) at rates up to 0.5–3 m yr –1 ( [[#Vitousek--2017a|Vitousek et al., 2017a]] ; [[#Vitousek--2017b|Vitousek et al., 2017b]] ; [[#Cambers--2019|Cambers and Wynne, 2019]] ; [[#Enríquez-de-Salamanca--2020|Enríquez-de-Salamanca, 2020]] ; [[#Sharples--2020|Sharples et al., 2020]] ). Corresponding analyses of coarse-scale (30-m resolution) global data estimate that 15% of tidal flats (including beaches) have been lost since 1984 ( ''medium confidence'' ) ( [[#Mentaschi--2018|Mentaschi et al., 2018]] ; [[#Murray--2019|Murray et al., 2019]] ) but with a corresponding number of the world’s beaches accreting (28%) as eroding (24%) ( ''medium confidence'' ) ( [[#Luijendijk--2018|Luijendijk et al., 2018]] ).

Progress is being made towards models that can project beach erosion under future scenarios despite inherent uncertainties and the presence of multiple confounding drivers in the coastal zone ( [[#Vitousek--2017b|Vitousek et al., 2017b]] ; [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ; [[#Cooper--2020a|Cooper et al., 2020a]] ; [[#Vousdoukas--2020b|Vousdoukas et al., 2020b]] ; [[#Vousdoukas--2020a|Vousdoukas et al., 2020a]] ). In the interim, models with varying levels of complexity estimate local loss of beach area to SLR by 2100 under RCP8.5-like scenarios, assuming minimal human intervention, ranging 30–70% ( ''low confidence'' ) ( [[#Vitousek--2017b|Vitousek et al., 2017b]] ; [[#Mori--2018|Mori et al., 2018]] ; [[#Ritphring--2018|Ritphring et al., 2018]] ; [[#Hallin--2019|Hallin et al., 2019]] ; [[#Kasmi--2020|Kasmi et al., 2020]] ). Within regions, projected impacts scale negatively with beach width and positively with the magnitude of projected SLR. None of these local studies, however, considered high-energy storm events, which are known to also impact sandy coasts ( ''high confidence'' ) (e.g., [[#Burvingt--2018|Burvingt et al., 2018]] ; [[#Garrote--2018|Garrote et al., 2018]] ; [[#Duvat--2019|Duvat et al., 2019]] ; [[#Sharples--2020|Sharples et al., 2020]] ), and model structure often had more influence on projected shoreline responses than did physical drivers ( [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ). Nevertheless, the most-advanced available models, which incorporate multiple coastal processes, including SLR, project that without anthropogenic barriers to erosion, 13.6–15.2% and 35.7–49.5% of the world’s beaches ''likely'' risk undergoing at least 100 m of shoreline retreat (relative to 2010) by 2050 and 2100, respectively ( ''low confidence'' ) ( [[#Vousdoukas--2020b|Vousdoukas et al., 2020b]] ). Aggregating these trends regionally suggests that relative rates of shoreline change under RCP4.5 and RCP8.5 diverge strongly after mid-century, with trends towards erosion escalating under RCP8.5 by 2100 ( ''medium confidence'' ) (Figure 3.14; [[#Vousdoukas--2020b|Vousdoukas et al., 2020b]] ). This trend supports the WGI AR6 assessment that projected SLR will contribute to erosion of sandy beaches, especially under high-emissions futures ( ''high confidence'' ) (WGI AR6 Technical Summary; [[#Arias--2021|Arias et al., 2021]] ).

<div id="_idContainer049" class="Figure"></div>

[[File:28ca7a67ead48d42a0650b0f9d1ad93b IPCC_AR6_WGII_Figure_3_014.png]]

'''Figure 3.14 |''' '''Relative trends in projected regional shoreline change (advance/retreat relative to 2010).''' Frequency distributions of median projected change by (a,c) 2050 and (b,d) 2100 under (a,b) RCP4.5 and (c,d) RCP8.5. Projections account for both long-term shoreline dynamics and sea level rise and assume no impediment to inland transgression of sandy beaches. Data for small island states are aggregated and plotted in the Caribbean. (Data are from [[#Vousdoukas--2020b|Vousdoukas et al., 2020b]] .) Values for reference regions established in the WGI AR6 Atlas ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ) were computed as area-weighted means from original country-level data. (For model assumptions and associated debate, see [[#Vousdoukas--2020a|Vousdoukas et al., 2020a]] and [[#Cooper--2020a|Cooper et al., 2020a]] .)

For beach fauna, ''emerging evidence'' links range shifts, increasing representation by warm-affinity species and mass mortalities to ocean warming ( ''limited evidence, high agreement'' ) ( [[#McLachlan--2018|McLachlan and Defeo, 2018]] ; [[#Martin--2019|Martin et al., 2019]] ). But even amongst the best-studied taxa, such as turtles, vulnerability to warming ( ''high confidence'' ) and SLR ( ''medium confidence'' ) anticipated on the basis of theory ( [[#Poloczanska--2009|Poloczanska et al., 2009]] ; [[#Saba--2012|Saba et al., 2012]] ; [[#Pike--2013|Pike, 2013]] ; [[#Laloë--2017|Laloë et al., 2017]] ; [[#Tilley--2019|Tilley et al., 2019]] ) yields only a few detected impacts in the field associated mainly with feminisation (female-skewed sex ratios driven by warmer nest temperatures) ( [[#Jensen--2018|Jensen et al., 2018]] ; [[#Colman--2019|Colman et al., 2019]] ; [[#Tilley--2019|Tilley et al., 2019]] ), phenology ( [[#Monsinjon--2019|Monsinjon et al., 2019]] ), reproductive success ( [[#Bladow--2019|Bladow and Milton, 2019]] ) and inter-nesting period ( [[#Valverde-Cantillo--2019|Valverde-Cantillo et al., 2019]] ). Moreover, although established vulnerabilities imply high projected future risk for turtles ( ''high confidence'' ) (e.g., [[#Almpanidou--2019|Almpanidou et al., 2019]] ; [[#Monsinjon--2019|Monsinjon et al., 2019]] ; [[#Patrício--2019|Patrício et al., 2019]] ; [[#Varela--2019|Varela et al., 2019]] ; [[#Santidrián%20Tomillo--2020|Santidrián Tomillo et al., 2020]] ), many populations remain resilient to change ( [[#Fuentes--2019|Fuentes et al., 2019]] ; [[#Valverde-Cantillo--2019|Valverde-Cantillo et al., 2019]] ; [[#Laloë--2020|Laloë et al., 2020]] ; [[#Lamont--2020|Lamont et al., 2020]] ), perhaps because variation in sand temperatures at nesting depth among beaches ''very likely'' exceeds the magnitude of warming anticipated by 2100, even under RCP8.5 ( ''medium confidence'' ) ( [[#Bentley--2020a|Bentley et al., 2020a]] ). As expected for a taxon with a long evolutionary history, turtles display natural adaptation, not only by virtue of broad geographic distributions that include natural climate-change refugia ( [[#Boissin--2019|Boissin et al., 2019]] ; [[#Jensen--2019|Jensen et al., 2019]] ), but also because some initial responses to warming might counteract anticipated impacts. For example, although feminisation poses a significant long-term risk to turtle populations ( ''high confidence'' ), it might contribute to population growth in the near to mid-term ( ''medium confidence'' ) ( [[#Patrício--2019|Patrício et al., 2019]] ). Resilience to climate change might be further enhanced by range extensions, alterations in nesting phenology and fine-scale nest-site selection ( ''medium confidence'' ) ( [[#Abella%20Perez--2016|Abella Perez et al., 2016]] ; [[#Santos--2017|Santos et al., 2017]] ; [[#Almpanidou--2018|Almpanidou et al., 2018]] ; [[#Rivas--2019|Rivas et al., 2019]] ; [[#Laloë--2020|Laloë et al., 2020]] ).

New literature since SROCC on climate impacts and risks has been scarce for most beach taxa besides turtles. (The impacts of storms on beach fauna are variable and are described in SM3.3.1.) Nevertheless, theoretical sensitivity to warming ( [[#3.3.2|Section 3.3.2]] ), together with the projected loss of habitat under future climate scenarios, suggest substantial impacts for populations and communities of beach fauna into the future ( ''high confidence'' ). These impacts will be exacerbated by coastal squeeze along urbanised coastlines ( ''high confidence'' ), albeit with magnitudes that cannot yet be accurately projected ( [[#McLachlan--2018|McLachlan and Defeo, 2018]] ; [[#Le%20Cozannet--2019|Le Cozannet et al., 2019]] ; [[#Leo--2019|Leo et al., 2019]] ).

<div id="3.4.2.7" class="h3-container"></div>

<span id="semi-enclosed-seas"></span>
==== 3.4.2.7 Semi-Enclosed Seas ====

<div id="h3-19-siblings" class="h3-siblings"></div>

This section assesses impacts on five SES, or seas larger than 200,000 km 2 with single entrances &lt;120 km wide, including the Persian Gulf, the Red Sea, the Black Sea, the Baltic Sea and the Mediterranean Sea. These SES are largely landlocked and are thus heavily influenced by surrounding landscapes, local and global climate-induced drivers, as well as non-climate drivers ( [[#3.1|Section 3.1]] ), making them highly vulnerable to cumulative threats. Key climate-induced drivers in SES are warming, increasing frequency and duration of MHWs, acidification and the increasing in size and number of OMZs (Figure 3.12; [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ). In AR5, SES were recognised as regionally significant for fisheries and tourism but highly exposed to both local and global stressors, offering limited options for organisms to migrate in response to climate change (Table 3.10).

'''Table 3.10 |''' Summary of past IPCC assessments of semi-enclosed seas (SES)

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] )''

|
|-
| ‘The surface waters of the SES exhibit significant warming from 1982, and most CBS [coastal boundary systems] show significant warming since 1950. Warming of the Mediterranean has led to the recent spread of tropical species invading from the Atlantic and Indian oceans.’

‘SES are highly vulnerable to changes in global temperature on account of their small [seawater] volume and landlocked nature. Consequently, SES will respond faster than most other parts of the ocean ( ''high confidence'' ).’

‘The impact of rising temperatures on SES is exacerbated by their vulnerability to other human influences such as over-exploitation, pollution and enhanced runoff from modified coastlines. Due to a mixture of global and local human stressors, key fisheries have undergone fundamental changes in their abundance and distribution over the past 50 years ( ''medium confidence'' ).’

| ‘Projected warming increases the risk of greater thermal stratification in some regions, which can lead to reduced O 2 ventilation [of underlying waters] and the formation of additional hypoxic zones, especially in the Baltic and Black seas ( ''medium confidence'' ).’

‘Changing rainfall intensity can exert a strong influence on the physical and chemical conditions within SES, and in some cases will combine with other climatic changes to transform these areas. These changes are ''likely'' to increase the risk of reduced bottom-water O 2 levels to Baltic and Black Sea ecosystems (due to reduced solubility, increased stratification, and microbial respiration), which is ''very likely'' to affect fisheries.’

Persian Gulf, Red Sea: ‘Extreme temperature events, such as heat waves, are projected to increase ( ''high confidence'' ) [... and] temperatures are ''very likely'' to increase above established thresholds for mass coral bleaching and mortality ( ''very high confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Semi-enclosed seas were not assessed in this report.

| ‘Projections from multiple fish species distribution models for multiple fish species show hotspots of decrease in species richness in the Indo-Pacific region, and semi-enclosed seas such as the Red Sea and Persian Gulf ( ''medium evidence, high agreement'' ).

In addition, geographic barriers, such as land boundaries [...] or lower oxygen water in deeper waters, are projected to limit species range shifts in SES, resulting in a larger relative decrease in species richness ( ''medium confidence'' ).’

|}

Since AR5, there is evidence for increasing frequency and duration of MHWs, extreme-weather events and a diversity of threats across depth strata causing mass-mortality events, local extirpations and coral reef decline ( ''high confidence'' ) ( [[#3.4.2.1|Section 3.4.2.1]] ; SM3.3.2; [[#Buchanan--2016a|Buchanan et al., 2016a]] ; [[#Shlesinger--2018|Shlesinger et al., 2018]] ; [[#Wabnitz--2018b|Wabnitz et al., 2018b]] ; [[#Garrabou--2019|Garrabou et al., 2019]] ). In most SES, non-climate drivers, including pollution, habitat destruction and especially overfishing, are decreasing the local adaptive capacity of organisms and the ability of ecosystems to cope with climate-change impacts ( ''high confidence'' ) ( [[#Cramer--2018|Cramer et al., 2018]] ; [[#Hidalgo--2018|Hidalgo et al., 2018]] ; [[#Ben-Hasan--2019|Ben-Hasan and Christensen, 2019]] ). The SLR is accelerating faster than expected ( ''high confidence'' ) ( [[#Kulp--2019|Kulp and Strauss, 2019]] ), posing a key risk to SES’ coastal ecosystems and the services they provide in urban areas, including drinking water provision, housing and recreational activities, among others ( [[#Hérivaux--2018|Hérivaux et al., 2018]] ; [[#Reimann--2018|Reimann et al., 2018]] ).

The size and number of OMZs are increasing worldwide and in most SES ( ''high confidence'' ) ( [[#Global%20Ocean%20Oxygen%20Network--2018|Global Ocean Oxygen Network, 2018]] ), with growing impacts on fish species diversity and ecosystem functioning. In the Persian Gulf and Red Sea, increasing nutrient loads associated with coastal activities and warming has increased the size of OMZs ( ''high confidence'' ) ( [[#Al-Said--2018|Al-Said et al., 2018]] ; [[#Lachkar--2019|Lachkar et al., 2019]] ). OMZs represent an even greater problem in the Black and Baltic seas, with broad implications for ecosystem function and services ( [[#Levin--2009|Levin et al., 2009]] ), especially where actions to reduce nutrient loading from land have been unable to reduce the OMZ coverage ( ''high confidence'' ) ( [[#Carstensen--2014|Carstensen et al., 2014]] ; [[#Miladinova--2017|Miladinova et al., 2017]] ; [[#Global%20Ocean%20Oxygen%20Network--2018|Global Ocean Oxygen Network, 2018]] ). In the Baltic Sea, OMZs are affecting the extent of suitable spawning areas of cod, ''Gadus morhua'' ( ''high confidence'' ) ( [[#Hinrichsen--2016|Hinrichsen et al., 2016]] ), while in the Black Sea, the combined effect of OMZs and warming is influencing the distribution and physiology of fish species, and their migration and schooling behaviour in their overwintering grounds ( ''medium confidence'' ) ( [[#Güraslan--2017|Güraslan et al., 2017]] ). Cascading effects on food webs have been reported in the Baltic, where detrimental effects of changing oxygen levels on zooplankton production, pelagic and piscivorous fish are influencing seasonal succession and species composition of phytoplankton ( ''high confidence'' ) ( [[#Viitasalo--2015|Viitasalo et al., 2015]] ).

In the Mediterranean Sea (Cross-Chapter Paper 4), the increase in climate extremes and mass-mortality events reported in AR5 has continued ( ''very high confidence'' ) ( [[#Gómez-Gras--2021|Gómez-Gras et al., 2021]] ). Extreme-weather events (including deep convection; [[#González-Alemán--2019|González-Alemán et al., 2019]] ) and MHWs have become more frequent ( [[#Darmaraki--2019|Darmaraki et al., 2019]] ) and are associated with mass mortality of benthic sessile species across the basin ( ''high confidence'' ) ( [[#Garrabou--2019|Garrabou et al., 2019]] ; [[#Gómez-Gras--2021|Gómez-Gras et al., 2021]] ). Since AR5, in the Persian Gulf and Red Sea, extreme temperatures, together with disease and predation, have continued to cause bleaching-induced mortality of corals, along with declines in the average coral-colony size ( ''high confidence'' ) ( [[#Burt--2019|Burt et al., 2019]] ). Poleward migration and tropicalisation of species ( [[#3.4.2.3|Section 3.4.2.3]] ) has also continued in the Mediterranean, and these phenomena have also become an issue in the Black Sea ( ''high confidence'' ) ( [[#Boltachev--2014|Boltachev and Karpova, 2014]] ; [[#Hidalgo--2018|Hidalgo et al., 2018]] ). Climate impacts on phytoplankton production and phenology show high spatial heterogeneity across the Mediterranean Sea ( ''medium evidence'' ) ( [[#Marbà--2015b|Marbà et al., 2015b]] ; [[#Salgado-Hernanz--2019|Salgado-Hernanz et al., 2019]] ), with consequent effects on the diversity and abundance of zooplankton and fish species ( ''medium confidence'' ) ( [[#Peristeraki--2019|Peristeraki et al., 2019]] ). Changes in primary production and a decrease in river runoff have also altered the optimum habitats for small pelagic fish in the Mediterranean, from the local to the basin scale ( [[#Piroddi--2017|Piroddi et al., 2017]] ). Evidence of impacts from ocean acidification is increasing, with the rates of coral calcification showing major decline in the Red Sea ( ''medium confidence'' ) ( [[#3.4.2.1|Section 3.4.2.1]] ; [[#Steiner--2018|Steiner et al., 2018]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). In the Mediterranean Sea, evidence of acidification events have been reported at the local scale ( [[#Hassoun--2015|Hassoun et al., 2015]] ), with impacts on bivalves and coralligenous species ( ''medium confidence'' ) ( [[#Lacoue-Labarthe--2016|Lacoue-Labarthe et al., 2016]] ).

Climate models project increasing frequency and intensity of MHWs ( ''high confidence'' ) ( [[#3.2.2.1|Section 3.2.2.1]] ), which will exacerbate warming-driven impacts in the Red Sea and Persian Gulf regions, and erode the resilience of Red Sea coral reefs ( ''high confidence'' ) ( [[#Osman--2018|Osman et al., 2018]] ; [[#Genevier--2019|Genevier et al., 2019]] ; [[#Kleinhaus--2020|Kleinhaus et al., 2020]] ). In the Persian Gulf region, extreme temperatures, &gt;35°C ( [[#Pal--2016|Pal and Eltahir, 2016]] ), have been linked with high rates of extirpation and a decrease in fisheries catch potential ( ''medium confidence'' ) ( [[#Wabnitz--2018b|Wabnitz et al., 2018b]] ). In the Mediterranean Sea, east–west gradients in rates of warming are projected to trigger spatially different changes in primary production, which combined with the increasing arrival of non-indigenous species, may trigger biogeographic changes in fish diversity, increasing in the eastern and decreasing in the western Mediterranean ( ''medium to high confidence'' ) ( [[#Albouy--2013|Albouy et al., 2013]] ; [[#Macias--2015|Macias et al., 2015]] ). Projections also show greater impacts from SLR than originally expected in the Mediterranean and Baltic (e.g., [[#Dieterich--2019|Dieterich et al., 2019]] ; [[#Thiéblemont--2019|Thiéblemont et al., 2019]] ). In the Baltic Sea, under high nutrient load and warming climate scenarios, eutrophication is projected to increase in the future (2069–2098) compared with historical (1976–2005) periods. In contrast, under continued nutrient load reductions following present management regulations, environmental conditions and ecological state will continue to improve independently of the climate-warming scenarios ( ''low to medium confidence'' ) ( [[#Saraiva--2019|Saraiva et al., 2019]] ).

<div id="3.4.2.8" class="h3-container"></div>

<span id="shelf-seas"></span>
==== 3.4.2.8 Shelf Seas ====

<div id="h3-20-siblings" class="h3-siblings"></div>

Shelf seas overlie the continental margin, often with maximum depths of &lt;200 m, and represent 7% of the global ocean by area ( [[#Simpson--2012|Simpson and Sharples, 2012]] ). These ecosystems are found offshore of every continent, generate 10–30% ( [[#Mackenzie--2000|Mackenzie et al., 2000]] ; [[#Andersson--2004|Andersson and Mackenzie, 2004]] ) of global marine net primary production and play a key role in global biogeochemical cycling, including the export of land-borne carbon and nutrients ( [[#Johnson--1999|Johnson et al., 1999]] ; [[#Nishioka--2011|Nishioka et al., 2011]] ; [[#Li--2019|Li et al., 2019]] ) to the deep ocean and recycling of fixed nitrogen back to the atmosphere via denitrification ( [[#Devol--2015|Devol, 2015]] ). The shelf seas are home to several of the world’s major industrial capture fisheries, such as those of the mid-Atlantic Bight, Scotian Shelf, Eastern Bering Sea Shelf and North Brazil Shelf ( [[#Barange--2018|Barange et al., 2018]] ), and support other marine industries, including aquaculture, extractive industries (oil, gas and mining), shipping and renewable energy installations.

'''Table 3.11 |''' Summary of past IPCC assessments of shelf seas

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] )''

|
|-
| ‘Primary productivity, biomass yields and fish capture rates have undergone large changes within the ECS [East China Sea] over the past decades ( ''limited evidence, medium agreement, low confidence'' ).’

‘Changing sea temperatures have influenced the abundance of phytoplankton, benthic biomass, cephalopod fisheries and the size of demersal trawl catches in the northern SCS [South China Sea] observed over the period 1976–2004 ( ''limited evidence, medium agreement'' ).’

‘Concurrent with the retreat of the ‘cold pool’ [...] on the northern Bering Sea shelf, [...] bottom trawl surveys of fish and invertebrates show a significant community-wide northward distributional shift and a colonisation of the former cold pool areas by sub-Arctic fauna ( ''high confidence'' ).’

‘Observed changes in the phenology of plankton groups in the North Sea over the past 50 years are driven by climate forcing, in particular regional warming ( ''high confidence'' ).’

| ‘Global warming will result in more frequent extreme events and greater associated risks to ocean ecosystems ( ''high confidence'' ). In some cases, [...] projected increases will eliminate ecosystems, and increase the risks and vulnerabilities to coastal livelihoods [and the vulnerabilities for food security including that of Southeast Asia] ( ''medium to high confidence'' ). Reducing stressors not related to climate change represents an opportunity to strengthen the ecological resilience within these regions, which may help them [biota] survive some projected changes in ocean temperature and chemistry.’

Changes in eutrophication and hypoxia are ''likely'' to influence shelf seas, but there is ''low confidence'' in the understanding of the magnitude of potential changes and impacts on ecosystem functioning, fisheries and other industries.

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘Species composition of fisheries catches since the 1970s in many shelf seas ecosystems of the world is increasingly dominated by warm-water species ( ''medium confidence'' ).’

‘Estuaries, shelf seas and a wide range of other intertidal and shallow-water habitats play an important role in the global carbon cycle through their primary production by rooted plants, seaweeds (macroalgae) and phytoplankton, and also by processing riverine organic carbon. However, the natural carbon dynamics of these systems have been greatly changed by human activities ( ''high confidence'' ).’

| ‘Direct anthropogenic impacts include coastal land-use change; indirect effects include increased nutrient delivery and other changes in river catchments, and marine resource exploitation in shelf seas. There is ''high confidence'' that these human-driven changes will continue, reflecting coastal settlement trends and global population growth.’

|}

Similar to other coastal ecosystems, evidence since SROCC (Table 3.11) suggests that shelf-sea ecosystems and the fisheries and aquaculture they support are sensitive to the interactive effects of climate-induced drivers, as well as non-climate drivers, including nutrient pollution, sedimentation, fishing pressure and resource extraction (Table 3.12; Figure 3.12). Changes in freshwater, nutrient and sediment inputs from rivers due to both climate-induced and non-climate drivers can influence productivity and nutrient limitation, ecosystem structure, carbon export and species diversity and abundance ( [[#Balch--2012|Balch et al., 2012]] ; [[#Picado--2014|Picado et al., 2014]] ), and can result in reduced water clarity and light penetration ( [[#Dupont--2013|Dupont and Aksnes, 2013]] ; [[#McGovern--2019|McGovern et al., 2019]] ). Seasonal bottom-water hypoxia occurs in some shelf seas (e.g., northern Gulf of Mexico, Bohai Sea, East China Sea) due to riverine inputs of freshwater and nutrients, promoting stratification, enhanced primary production and organic carbon export to bottom waters ( ''high confidence'' ) ( [[#Zhao--2017|Zhao et al., 2017]] ; [[#Wei--2019|Wei et al., 2019]] ; [[#Del%20Giudice--2020|Del Giudice et al., 2020]] ; [[#Große--2020|Große et al., 2020]] ; [[#Jarvis--2020|Jarvis et al., 2020]] ; [[#Rabalais--2020|Rabalais and Baustian, 2020]] ; [[#Song--2020a|Song et al., 2020a]] ; [[#Xiong--2020|Xiong et al., 2020]] ; [[#Zhang--2020a|Zhang et al., 2020a]] ).

'''Table 3.12 |''' Synthesis of interactive effects and their influence on shelf-sea ecosystems and the fisheries and aquaculture they support

{| class="wikitable"
|-
! Factor

! Example of effect

! Example references

|-
| Temperature

| Altered habitats for species, change in plankton, fish and macrofauna community structure, influence on species growth, thermal stress, altered diversity, altered productivity and altered phenology

| Liang et al. (2018); [[#Maharaj--2018|Maharaj et al. (2018)]] ; [[#Ma--2019|Ma et al. (2019)]] ; [[#Meyer--2019|Meyer and Kröncke (2019)]] ; [[#Yan--2019|Yan et al. (2019)]] ; [[#Bargahi--2020|Bargahi et al. (2020)]] ; [[#Bedford--2020|Bedford et al. (2020)]] ; [[#Denechaud--2020|Denechaud et al. (2020)]] ; [[#Friedland--2020b|Friedland et al. (2020b)]] ; [[#Mérillet--2020|Mérillet et al. (2020)]] ; [[#Nohe--2020|Nohe et al. (2020)]]

|-
| pH

| Acidification with hypoxia

| [[#Zhang--2019|Zhang and Wang (2019)]]

|-
| Salinity

| Change in species distribution due to altered salinity front distribution

| [[#Liu--2020c|Liu et al. (2020c)]]

|-
| Oxygen concentration

| Deoxygenation

| [[#Wei--2019|Wei et al. (2019)]] ; Del Giudice et al. (2020)

|-
| River discharge

| Change in plankton community structure

| [[#Shi--2020|Shi et al. (2020)]]

|-
| Nutrient pollution

| Enhanced primary production, change in plankton community structure

| Kong et al. (2019); [[#Nohe--2020|Nohe et al. (2020)]]

|-
| Sedimentation

| Modified ocean chemistry

| [[#Hallett--2018|Hallett et al. (2018)]]

|-
| Fishing pressure

| Increased vulnerability leading to changes in community structure

| [[#Maharaj--2018|Maharaj et al. (2018)]] ; [[#Wang--2019c|Wang et al. (2019c)]] ; [[#Hernvann--2020|Hernvann and Gascuel (2020)]]

|-
| Resource extraction

| Contamination, change in benthic community structure

| [[#Hall--2002|Hall (2002)]]

|}

Key risks to shelf seas include shifts or declines in marine micro- and macro-organism abundance and diversity driven by eutrophication, HABs and extreme events (storms and MHWs), and consequent effects on fisheries, resource extraction, transportation, tourism and marine renewable energy (Figure 3.12). The combined effects of deoxygenation and warming can affect the metabolism, growth, feeding behaviour and mobility of fish species ( [[#3.3.3|Section 3.3.3]] ). The increasing availability of observations mean that ecosystem changes in shelf seas can be increasingly attributed to climate change ( ''high confidence'' ) ( [[#Liang--2018|Liang et al., 2018]] ; [[#Maharaj--2018|Maharaj et al., 2018]] ; [[#Ma--2019|Ma et al., 2019]] ; [[#Meyer--2019|Meyer and Kröncke, 2019]] ; [[#Bargahi--2020|Bargahi et al., 2020]] ; [[#Bedford--2020|Bedford et al., 2020]] ; [[#Friedland--2020b|Friedland et al., 2020b]] ; [[#Mérillet--2020|Mérillet et al., 2020]] ). Eutrophication and seasonal bottom-water hypoxia in some shelf seas have been linked to warming ( ''high confidence'' ) ( [[#Wei--2019|Wei et al., 2019]] ; [[#Del%20Giudice--2020|Del Giudice et al., 2020]] ) and increased riverine nutrient loading ( ''high confidence'' ) ( [[#Wei--2019|Wei et al., 2019]] ; [[#Del%20Giudice--2020|Del Giudice et al., 2020]] ). Since SROCC, some severe HABs have been attributed to extreme events, such as MHWs ( [[IPCC:Wg2:Chapter:Chapter-14#14.4|Section 14.4.2]] ; [[#Roberts--2019|Roberts et al., 2019]] ; [[#Trainer--2019|Trainer et al., 2019]] ); however, a recent worldwide assessment of HABs attributed the increase in observed HABs to intensified monitoring associated with increased aquaculture production ( ''high confidence'' ) ( [[#Hallegraeff--2021|Hallegraeff et al., 2021]] ).

Since SROCC, changes in the community structure and diversity of plankton, macrofauna and infauna have been detected in some shelf seas, although attribution has been regionally specific (e.g ''.'' , bottom-water warming or hypoxia) ( [[#Meyer--2019|Meyer and Kröncke, 2019]] ; [[#Rabalais--2020|Rabalais and Baustian, 2020]] ). Detection of the picoplankton ''Synechococcus'' spp. in the North Sea is potentially linked to a summer decrease in copepod stocks and declining food-web efficiency ( ''low confidence'' ) ( [[#Schmidt--2020|Schmidt et al., 2020]] ). The seasonally distinct phytoplankton assemblages in the North Sea have begun to appear concurrently and homogenise ( [[#Nohe--2020|Nohe et al., 2020]] ). Changes in abundance, species composition and size of zooplankton have been detected in some shelf seas (Yellow Sea, North Sea, Celtic Sea and Tasman Sea), including a decline in stocks of larger copepods, increased abundances of gelatinous and meroplankton, and a shift to smaller species due to warming, increased river discharge, circulation change and/or extreme events ( ''high confidence'' ) ( [[#Wang--2018a|Wang et al., 2018a]] ; [[#Bedford--2020|Bedford et al., 2020]] ; [[#Evans--2020|Evans et al., 2020]] ; [[#Shi--2020|Shi et al., 2020]] ; [[#Edwards--2021|Edwards et al., 2021]] ).

Ocean warming has shifted distributions of fish ( [[#Free--2019|Free et al., 2019]] ; [[#Franco--2020|Franco et al., 2020]] ; [[#Pinsky--2020b|Pinsky et al., 2020b]] ; [[#Fredston--2021|Fredston et al., 2021]] ) and marine mammal species ( [[#Salvadeo--2010|Salvadeo et al., 2010]] ; [[#García-Aguilar--2018|García-Aguilar et al., 2018]] ; [[#Davis--2020|Davis et al., 2020]] ) poleward ( ''high confidence'' ) or deeper ( ''low to medium confidence'' ) ( [[#3.4.3.1|Section 3.4.3.1]] ; [[#Nye--2009|Nye et al., 2009]] ; [[#Pinsky--2013|Pinsky et al., 2013]] ; [[#Pinsky--2020b|Pinsky et al., 2020b]] ). Warming has also tropicalised the pelagic and demersal fish assemblages of mid- and high-latitude shelves ( ''high confidence'' ) ( [[#Montero-Serra--2015|Montero-Serra et al., 2015]] ; [[#Liang--2018|Liang et al., 2018]] ; [[#Maharaj--2018|Maharaj et al., 2018]] ; [[#Ma--2019|Ma et al., 2019]] ; [[#Friedland--2020a|Friedland et al., 2020a]] ; [[#Kakehi--2021|Kakehi et al., 2021]] ; [[#Punzón--2021|Punzón et al., 2021]] ). Fisheries catch composition in many shelf-sea ecosystems has become increasingly dominated by warm-water species since the 1970s ( ''high confidence'' ) ( [[#Cheung--2013|Cheung et al., 2013]] ; [[#Leitão--2018|Leitão et al., 2018]] ; [[#Maharaj--2018|Maharaj et al., 2018]] ; [[#McLean--2019|McLean et al., 2019]] ). Warming has taxonomically diversified fish communities along a latitudinal gradient in the North Sea but has homogenised functional diversity ( [[#McLean--2019|McLean et al., 2019]] ). However, in some regions, changing predator or prey distributions, temperature-dependent hypoxia, population changes, evolutionary adaptation and other biotic or abiotic processes, including species’ exploitation, confound responses to climate-induced drivers, which must therefore be interpreted with caution ( [[#Frank--2018|Frank et al., 2018]] ). For example, although, most species’ range edges are tracking temperature change on the northeast shelf of the USA ( ''medium confidence'' ) ( [[#Fredston-Hermann--2020|Fredston-Hermann et al., 2020]] ; [[#Fredston--2021|Fredston et al., 2021]] ), range edges of others are not.

A wide range of responses by fish and invertebrate populations to warming have been observed. The majority of responses have been detrimental, with the direction and magnitude of the response depending on ecoregion, taxonomy, life history and exploitation history ( [[#Free--2019|Free et al., 2019]] ; [[#Yati--2020|Yati et al., 2020]] ). For example, fisheries productivity has strongly decreased in the North Sea ( [[#Free--2019|Free et al., 2019]] ), and fisheries yields have also decreased in the Celtic Sea, attributed primarily to warming and secondarily to long-term exploitation ( [[#Hernvann--2020|Hernvann and Gascuel, 2020]] ; [[#Mérillet--2020|Mérillet et al., 2020]] ). Conversely, fish species diversity and overall productivity have increased in the Gulf of Maine, even with warming ( [[#Le%20Bris--2018|Le Bris et al., 2018]] ; [[#Friedland--2020a|Friedland et al., 2020a]] ; [[#Friedland--2020b|Friedland et al., 2020b]] ). Fisheries yields have decreased in the Yellow Sea, East China Sea and South China Sea partially due to overexploitation ( [[#Ma--2019|Ma et al., 2019]] ; [[#Wang--2019c|Wang et al., 2019c]] ), with warming exerting more influence on the yield of cold-water species than on temperate- and warm-water groups ( [[#Ma--2019|Ma et al., 2019]] ). The combined effects of exploitation and multi-decadal climate fluctuations make it difficult to assess global climate-change impacts on fisheries yields (Chapter 5; [[#Ma--2019|Ma et al., 2019]] ; [[#Bentley--2020b|Bentley et al., 2020b]] ; [[#Johnson--2020|Johnson et al., 2020]] ).

Since AR5, increasing spatio-temporal extent of hypoxia has been projected due to enhanced benthic respiration and reduced oxygen solubility from warming ( [[#Del%20Giudice--2020|Del Giudice et al., 2020]] ). Similar to the open ocean, large shifts in the phenology of phytoplankton blooms have been projected for shelf seas throughout subpolar and polar waters ( ''medium confidence'' ) ( [[#Henson--2018a|Henson et al., 2018a]] ; [[#Asch--2019|Asch et al., 2019]] ). Zooplankton, which are important prey for many fish species and sea birds, are expected to decrease in abundance on the northeast shelf of the USA ( [[#Grieve--2017|Grieve et al., 2017]] ); however, responses vary by shelf ecosystem ( [[#Chust--2014b|Chust et al., 2014b]] ). Trends towards tropicalisation will continue in the future ( ''high confidence'' ) ( [[#Cheung--2015|Cheung et al., 2015]] ; [[#Stortini--2015|Stortini et al., 2015]] ; [[#Allyn--2020|Allyn et al., 2020]] ; [[#Maltby--2020|Maltby et al., 2020]] ; [[#Costa--2021|Costa et al., 2021]] ), but uncertainty of future projections of fisheries production increases substantially beyond 2040 ( [[#Maltby--2020|Maltby et al., 2020]] ). Nevertheless, shelf-sea fisheries at lower latitudes are most vulnerable to climate change ( [[#Monnereau--2017|Monnereau et al., 2017]] ). Under future climate change marked by more frequent and intense extreme events and the influences of multiple drivers, more flexible and adaptive management approaches could reduce climate impacts on species while also supporting industry adaptation ( ''high confidence'' ) ( [[#3.6.3.1.2|Section 3.6.3.1.2]] ; [[#Shackell--2014|Shackell et al., 2014]] ; [[#Stortini--2015|Stortini et al., 2015]] ; [[#Hare--2016|Hare et al., 2016]] ; [[#Stortini--2017|Stortini et al., 2017]] ; [[#Greenan--2019|Greenan et al., 2019]] ; [[#Ocaña--2019|Ocaña et al., 2019]] ; [[#Maltby--2020|Maltby et al., 2020]] ).

<div id="3.4.2.9" class="h3-container"></div>

<span id="upwelling-zones"></span>
==== 3.4.2.9 Upwelling Zones ====

<div id="h3-21-siblings" class="h3-siblings"></div>

Eastern boundary upwelling systems (EBUS) comprise four important social–ecological systems in the Pacific (California and Peru-Humboldt) and Atlantic (Canary and Benguela) ocean basins. Each is characterised by high primary production, sustained by wind-driven upwelling that draws cold, nutrient-rich, generally low-pH and low-oxygen water to the surface ( [[#Bindoff--2019a|Bindoff et al., 2019a]] ). Despite their small relative size, the primary productivity in EBUS supports a vast biomass of marine consumers, including some of the world’s most productive fisheries ( [[#Pauly--2016|Pauly and Zeller, 2016]] ), along with many species of conservation significance ( [[#Bakun--2015|Bakun et al., 2015]] ).

Although upwelling is important in many other oceanic regions, we focus here on the most documented examples provided by the EBUS. Yet even here, observed changes in upwelling, temperature, acidification and loss of oxygen ( [[#Seabra--2019|Seabra et al., 2019]] ; [[#Abrahams--2021|Abrahams et al., 2021]] ; [[#Gallego--2021|Gallego et al., 2021]] ; [[#Varela--2021|Varela et al., 2021]] ) cannot be robustly attributed to anthropogenic climate change, and projected future changes in upwelling are expected to be relatively small and variable among and within EBUS ( [[#3.2.2.3|Section 3.2.2.3]] ; WGI AR6 Chapter 9; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ). We therefore have few updates to assessments provided by AR5 and SROCC (Table 3.13) and restrict our brief assessment to the limited amount of new evidence (Figure 3.12).

'''Table 3.13 |''' Summary of previous IPCC assessments of eastern boundary upwelling systems (EBUS)

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Lluch-Cota--2014|Lluch-Cota et al., 2014]] )''

|
|-
| ‘[EBUS] are vulnerable to changes that influence the intensity of currents, upwelling and mixing (and hence changes in sea surface temperature, wind strength and direction), as well as O 2 content, carbonate chemistry, nutrient content and the supply of organic carbon to deep offshore locations ( ''high confidence'' ).’

Climate-change-induced intensification of ocean upwelling in some EBUS, as observed in past decades, may lead to regional cooling, rather than warming, of surface waters and cause enhanced productivity ( ''medium confidence'' ), but also enhanced hypoxia, acidification and associated biomass reduction in fish and invertebrate stocks. Owing to contradictory observations, there is currently uncertainty about the future trends of major upwelling systems and how their drivers will shape ecosystem characteristics ( ''low confidence'' ).

‘Declining O 2 and shoaling of the aragonite saturation horizon through ocean acidification increase the risk of upwelling water being low in pH and O 2 , with impacts on coastal ecosystems and fisheries [...]. These risks and uncertainties are ''likely'' to involve significant challenges for fisheries and associated livelihoods along the west coasts of South America, Africa and North America ( ''low to medium confidence'' ).’

‘There is ''robust evidence'' and ''medium agreement'' that the California Current has experienced [...] an increase of the overall magnitude of upwelling events from 1967 to 2010 ( ''high confidence'' ). This is consistent with changes expected under climate change yet remains complicated by the influence of decadal-scale variability ( ''low confidence'' ).’ Declining oxygen concentrations and shoaling of the hypoxic boundary layer ''likely'' ‘reduced the available habitat for key benthic communities as well as fish and other mobile species. Together with the shoaling of the saturation horizon, these changes have increased the incidence of low O 2 and low pH water flowing onto the continental shelf ( ''high confidence'' ; 40 to 120 m), causing problems for industries such as the shellfish aquaculture industry.’

Despite its apparent sensitivity to environmental variability, there is ''limited evidence'' of ecological changes in the Benguela Current EBUS due to climate change.

| ‘Like other ocean sub-regions, [EBUS] are projected to warm under climate change, with increased stratification and intensified winds as westerly winds shift poleward ( ''likely'' ). However, cooling has also been predicted for some [EBUS], resulting from the intensification of wind-driven upwelling.’

‘There is ''medium agreement'' , despite ''limited evidence'' , that upwelling intensity and associated variables (e.g., temperature, nutrient and O 2 concentrations) from the Benguela system will change as a result of climate change.’

Any projected increase in upwelling intensity has potential disadvantages. ‘Elevated primary productivity may lead to decreasing trophic transfer efficiency, thus increasing the amount of organic carbon exported to the seabed, where it is ''virtually certain'' to increase microbial respiration and hence increase low O 2 stress.’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#IPCC--2019c|IPCC, 2019c]] ; [[#IPCC--2019d|IPCC, 2019d]] )''

|
|-
| ‘Increasing ocean acidification and oxygen loss are negatively impacting two of the four major upwelling systems: the California Current and Humboldt Current ( ''high confidence'' ). Ocean acidification and decrease in oxygen level in the California Current upwelling system have altered ecosystem structure, with direct negative impacts on biomass production and species composition ( ''medium confidence'' ).’

‘Three out of the four major Eastern Boundary Upwelling Systems (EBUS) have shown large-scale wind intensification in the past 60 years ( ''high confidence'' ). However, the interaction of coastal warming and local winds may have affected upwelling strength, with the direction of changes [varying] between and within EBUS ( ''low confidence'' ). Increasing trends in ocean acidification in the California Current EBUS and deoxygenation in California Current and Humboldt Current EBUS are observed in the last few decades ( ''high confidence'' ), although there is ''low confidence'' to distinguish anthropogenic forcing from internal climate variability. The expanding California EBUS OMZ [oxygen minimum zone] has altered ecosystem structure and fisheries catches ( ''medium confidence'' ).’

‘Overall, EBUS have been changing with intensification of winds that drives the upwelling, leading to changes in water temperature and other ocean biogeochemistry ( ''medium confidence'' ).’

‘The direction and magnitude of observed changes vary among and within EBUS, with uncertainties regarding the driving mechanisms behind this variability. Moreover, the high natural variability of EBUS and their insufficient representation by global ESMs [Earth system models] gives ''low confidence'' that these observed changes can be attributed to anthropogenic causes.’

| ‘Anthropogenic changes in EBUS will emerge primarily in the second half of the 21st century ( ''medium confidence'' ). EBUS will be impacted by climate change in different ways, with strong regional variability with consequences for fisheries, recreation and climate regulation ( ''medium confidence'' ). The Pacific EBUS are projected to have calcium carbonate undersaturation in surface waters within a few decades RCP8.5 ( ''high confidence'' ); combined with warming and decreasing oxygen levels, this will increase the impacts on shellfish larvae, benthic invertebrates, and demersal fishes ( ''high confidence'' ) and related fisheries and aquaculture ( ''medium confidence'' ).’

‘The inherent natural variability of EBUS, together with uncertainties in present and future trends in the intensity and seasonality of upwelling, coastal warming and stratification, primary production and biogeochemistry of source waters poses large challenges in projecting the response of EBUS to climate change and to the adaptation of governance of biodiversity conservation and living marine resources in EBUS ( ''high confidence'' ).’

‘Given the high sensitivity of the coupled human–natural EBUS to oceanographic changes, the future sustainable delivery of key ecosystem services from EBUS is at risk under climate change; those that are most at risk in the 21st century include fisheries ( ''high confidence'' ), aquaculture ( ''medium confidence'' ), coastal tourism ( ''low confidence'' ) and climate regulation ( ''low confidence'' ).’

‘For vulnerable human communities with a strong dependence on EBUS services and low adaptive capacity, such as those along the Canary Current system, unmitigated climate-change effects on EBUS (complicated by other non-climatic stresses such as social unrest) have a high risk of altering their development pathways ( ''high confidence'' ).’

|}

The California EBUS is arguably the best-studied of the four ecosystems in terms of robust projections of climate change, although even here, there is ''limited evidence'' and ''low agreement'' among projections. For example, trends in outputs from high-resolution, downscaled models in the California EBUS generally reflect those from underlying coarser-scale ESMs, but projections for physical variables are more convergent among modelling approaches than are those for biogeochemical variables ( ''high confidence'' ) ( [[#Howard--2020a|Howard et al., 2020a]] ; [[#Pozo%20Buil--2021|Pozo Buil et al., 2021]] ). Models agree on general warming in the California EBUS, with concomitant declines in oxygen content ( ''medium confidence'' ) ( [[#Howard--2020b|Howard et al., 2020b]] ; [[#Fiechter--2021|Fiechter et al., 2021]] ; [[#Pozo%20Buil--2021|Pozo Buil et al., 2021]] ). But implications for the future spatial distribution of species, including for some fisheries resources ( [[#Howard--2020b|Howard et al., 2020b]] ; [[#Fiechter--2021|Fiechter et al., 2021]] ), are confounded by local-scale oceanographic processes ( [[#Siedlecki--2021|Siedlecki et al., 2021]] ) and by lateral input of anthropogenic land-based nutrients ( [[#Kessouri--2021|Kessouri et al., 2021]] ), suggesting that such projections should be accorded ''low confidence'' .

More generally, changes in upwelling intensity are observed to affect organismal metabolism, population productivity and recruitment, and food-web structure ( ''medium confidence'' ) ( [[#van%20der%20Sleen--2018|van der Sleen et al., 2018]] ; [[#Brodeur--2019|Brodeur et al., 2019]] ; [[#Ramajo--2020|Ramajo et al., 2020]] ). But ''low confidence'' in projected trends in upwelling make it difficult to extrapolate these results to understand potential changes in the ecology of EBUS. Projected changes in fish biomass within EBUS ( [[#Carozza--2019|Carozza et al., 2019]] ) are therefore accorded ''low confidence'' . Finally, although MHWs are an important emerging hazard in the global ocean, with intensity, frequency and duration increasing strongly ( [[#3.2.2.1|Section 3.2.2.1]] ), the number of MHW days yr –1 within EBUS has been increasing more slowly (or decreasing faster, in the case of the Peru-Humboldt system) than in surrounding waters ( [[#Varela--2021|Varela et al., 2021]] ). Notwithstanding these trends, EBUS remain vulnerable both to MHWs ( ''high confidence'' ) (Sen [[#Gupta--2020|Gupta et al., 2020]] ) and to their long-lasting impacts ( ''high confidence'' ) ( [[#Arafeh-Dalmau--2019|Arafeh-Dalmau et al., 2019]] ; [[#Harvell--2019|Harvell et al., 2019]] ; [[#McPherson--2021|McPherson et al., 2021]] ). On this basis, the suggestion that EBUS may represent refugia from MHWs is accorded ''low confidence'' .

Despite ''low confidence'' in detailed projections for ecological changes in EBUS, the WGI assessment (WGI AR6 Chapter 9; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ) that upwelling-favourable winds will weaken (or be present for shorter durations) at low latitude but intensify at high latitude ( ''high confidence'' ), albeit by no more than 20% in either case ( ''medium confidence'' ), presents some key risks to associated EBUS ecosystems. These risks include potential decreases in provisioning services, including fisheries and marine aquaculture ( [[#Bertrand--2018|Bertrand et al., 2018]] ; [[#Kifani--2018|Kifani et al., 2018]] ; [[#Lluch-Cota--2018|Lluch-Cota et al., 2018]] ; [[#van%20der%20Lingen--2018|van der Lingen and Hampton, 2018]] ), and cultural services such as nature-based tourism ( [[#3.5|Section 3.5]] ).

<div id="3.4.2.10 " class="h3-container"></div>

<span id="polar-seas"></span>
==== 3.4.2.10 Polar Seas ====

<div id="h3-22-siblings" class="h3-siblings"></div>

The polar seas cover ~20% of the global ocean and include the deep Arctic Ocean and surrounding shelf seas as well as the Southern Ocean south of the polar front. They play a significant role in ocean circulation and absorption of anthropogenic CO 2 ( [[#Meredith--2019|Meredith et al., 2019]] ). The Arctic is characterised by polar seas surrounded by land, while the Antarctic comprises continental Antarctica surrounded by the Southern Ocean. These high-latitude ecosystems share key properties, including strong seasonality in solar radiation and sea ice coverage. Sea ice regulates water-column physics, chemistry and biology, air–sea exchange and is a critical habitat for many species. In spring, when solar radiation returns and sea ice melts, intense phytoplankton blooms fuel food webs that include rich communities of both resident and summer-migrant species, with typically high dependency on a few key species for trophic transfer ( [[#Meredith--2019|Meredith et al., 2019]] ; [[#Rogers--2020|Rogers et al., 2020]] ). Over the past two decades, Arctic Ocean surface temperature has increased in line with the global average, while there has been no uniform warming across the Antarctic ( ''high confidence'' ) (WGI AR6 Chapter 9; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ). Thus, the rate of change due to warming, and associated sea ice loss, is greater in the Arctic than in the Antarctic ( ''high confidence'' ) ( [[#3.2|Section 3.2]] ; Table 3.14; WGI AR6 Chapter 9; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ). Both Arctic and Antarctic regions have a long history of living resource extraction, including some of the largest fisheries on the globe in terms of catches. However, only the Arctic hosts human populations, holding a rich Indigenous knowledge and local knowledge (IKLK) on these social–ecological systems (Cross-Chapter Paper 6; [[#Meredith--2019|Meredith et al., 2019]] ).

Previous assessments of polar seas (Table 3.14) concluded that climate change has already profoundly influenced polar ecosystems, through changing species distributions and abundances from primary producers to top predators, including both ecologically and economically important species ( ''high confidence'' ), and that it will continue to do so (Table 3.14).

'''Table 3.14 |''' Summary of previous IPCC assessments for polar seas

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| Poleward species distributional shifts are due to climate warming ( ''medium to high confidence'' ).

Impacts of shifts in ocean conditions affect fish and shellfish abundances in the Arctic ( ''high confidence'' ).

Changes in sea ice and the physical environment to the west of the Antarctic Peninsula are altering phytoplankton stocks and productivity, and krill ( ''high confidence'' ).

| Some marine species will shift their ranges in response to changing ocean and sea ice conditions in the polar regions ( ''medium confidence'' ).

Loss of sea ice in summer and increased ocean temperatures are expected to impact secondary pelagic production in some regions of the Arctic Ocean, with associated changes in the energy pathways within the marine ecosystem ( ''medium confidence'' ).

Ocean acidification has the potential to inhibit embryo development and shell formation of some zooplankton and krill in the polar regions, with potentially far-reaching consequences to food webs in these regions ( ''medium confidence'' ).

Shifts in the timing and magnitude of seasonal biomass production could disrupt coupled phenologies in the food webs, leading to decreased survival of dependent species ( ''medium confidence'' ).

|-
|
|-
| ''SR15 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )''

|
|-
| ‘A fundamental transformation is occurring in polar organisms and ecosystems, driven by climate change ( ''high confidence'' ).’

| ‘The losses in sea ice at 1.5°C and 2°C of warming will result in habitat losses for organisms such as seals, polar bears, whales and seabirds. There is ''high agreement'' and ''robust evidence'' that phytoplankton species will change because of sea ice retreat and related changes in temperature and radiation, and this is ''very likely'' to benefit fisheries productivity [in the Arctic spring bloom system].’

‘‘Unique and threatened systems’ (RFC1), [including Arctic and coral reefs], display a transition from high to very high risk of transition at temperatures between 1.5°C and 2°C of global warming, as opposed to at 2.6°C of global warming in AR5 ( ''high confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Climate-induced changes in seasonal sea ice extent and thickness as well as ocean stratification are altering marine primary production ( ''high confidence'' ), with impacts on ecosystems ( ''medium confidence'' ).

Changes in the timing, duration and magnitude of primary production have occurred in both polar oceans, with marked regional or local variability ( ''high confidence'' ).

In both polar regions, climate-induced changes in ocean and sea ice conditions have expanded the range of temperate species and contracted the range of polar fish and ice-associated species ( ''high confidence'' ).

Ocean acidification will affect several key Arctic species ( ''medium confidence'' ).

| Future climate-induced changes in the polar oceans, sea ice, snow and permafrost will drive habitat and biome shifts, with associated changes in the ranges and abundance of ecologically important species ( ''medium confidence'' ).

Projected range expansion of sub-Arctic marine species will increase pressure for high-Arctic species ( ''medium confidence'' ), with regionally variable impacts.

Both polar oceans will be increasingly affected by CO 2 uptake, causing corrosive conditions for calcium carbonate shell-producing organisms ( ''high confidence'' ), with associated impacts on marine organisms and ecosystems ( ''medium confidence'' ).

The projected effects of climate-induced stressors on polar marine ecosystems present risks for commercial and subsistence fisheries, with implications for regional economies, cultures and the global supply of fish, shellfish, and Antarctic krill ( ''high confidence'' ).

|}

Since SROCC, evidence demonstrates that warmer oceans, less sea ice and increased advection results in increasing primary production in the Arctic, albeit with regional variation ( ''high confidence'' ), while trends remain spatially heterogeneous and less clear in the Antarctic ( ''medium confidence'' ) (Cross-Chapter Paper 6; [[#Del%20Castillo--2019|Del Castillo et al., 2019]] ; [[#Lewis--2020|Lewis et al., 2020]] ; [[#Pinkerton--2021|Pinkerton et al., 2021]] ; [[#Song--2021a|Song et al., 2021a]] ). Furthermore, climate warming influences key mechanisms determining energy transfer between trophic levels including (a) altered size spectra, (b) shifts in trophic pathways, (c) phenological mismatches and (d) increased top-down trophic regulation (Table 3.15); however, the scale of impacts from changes in these mechanisms on ecosystem productivity in warming polar oceans remains unresolved and is hence assigned ''low confidence'' .

'''Table 3.15 |''' Examples of mechanisms influencing the transfer of energy between lower trophic levels in warmer polar oceans

{| class="wikitable"
|-
! Mechanism

! Examples

! References

|-
| Altered size spectra

| Shifts towards smaller algal cells and zooplankton in warmer and more stratified oceans results in longer and less-efficient food chains, with lower lipid content.

| [[#Aarflot--2018|Aarflot et al. (2018)]] ; [[#Kimmel--2018|Kimmel et al. (2018)]] ; [[#Weydmann--2018|Weydmann et al. (2018)]] ; [[#Hop--2019|Hop et al. (2019)]] ; [[#Møller--2020|Møller and Nielsen (2020)]] ; [[#Spear--2020|Spear et al. (2020)]] ; but see [[#Dong--2021|Dong et al. (2021)]] and [[#Vernet--2017|Vernet et al. (2017)]] for opposite trends.

|-
| Shifts in trophic pathways

| Changes in microbial food-web interactions, including strengthening of the microbial loop, may reduce overall productivity. Transitions from sea ice algae to open-water phytoplankton production may reduce benthic–pelagic coupling and benthic production; transition from autotroph to heterotroph benthic production with increased water turbidity; shifts from krill-dominated to salp-dominated ecosystems in the Antarctic may have negative impacts on higher trophic levels.

| Cross-Chapter Paper 6; [[#Fujiwara--2016|Fujiwara et al. (2016)]] ; [[#Onda--2017|Onda et al. (2017)]] ; [[#Vernet--2017|Vernet et al. (2017)]] ; [[#Grebmeier--2018|Grebmeier et al. (2018)]] ; [[#Moore--2018b|Moore et al. (2018b)]] ; Cavan et al. (2019); [[#Vaqué--2019|Vaqué et al. (2019)]] ; [[#Yurkowski--2020|Yurkowski et al. (2020)]] ; Braekcman et al. (2021)

|-
| Phenological mismatches

| Mismatches in timing arise between spring phytoplankton blooms and zooplankton recruits.

| [[#Søreide--2010|Søreide et al. (2010)]] ; [[#Renaud--2018|Renaud et al. (2018)]] ; [[#Dezutter--2019|Dezutter et al. (2019)]]

|-
| Increased top-down trophic regulation

| Increased predation efficiency and top-down regulation of zooplankton by zooplanktivorous fish (due to more light with less sea ice) disconnects zooplankton and phytoplankton production.

| [[#Langbehn--2017|Langbehn and Varpe (2017)]] ; [[#Kaartvedt--2018|Kaartvedt and Titelman (2018)]] ; [[#Hobbs--2021|Hobbs et al. (2021)]]

|}

Major community shifts, both gradual and abrupt, are observed in polar oceans in response to warming trends and MHWs (Arctic only) ( ''high confidence'' ) (Figure 3.12; Cross-Chapter Paper 6; [[#Beaugrand--2019|Beaugrand et al., 2019]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Huntington--2020|Huntington et al., 2020]] ). In general, abundances and ranges of Arctic fish species are declining and contracting, while ranges of boreal fish species are expanding, both geographically and in terms of feeding interactions and ecological roles ( ''high confidence'' ) ( [[#Huserbråten--2019|Huserbråten et al., 2019]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Huntington--2020|Huntington et al., 2020]] ; [[#Pecuchet--2020a|Pecuchet et al., 2020a]] ), with variable outcomes for large commercial fish stocks (Cross-Chapter Paper 6; [[#Kjesbu--2014|Kjesbu et al., 2014]] ; [[#Holsman--2018|Holsman et al., 2018]] ; [[#Free--2019|Free et al., 2019]] ). The extreme seasonal solar radiation cycles of these high latitudes may both act as a barrier for species immigration and change predator–prey dynamics in previously ice-covered areas, factors not currently considered in projections ( ''limited evidence'' ) ( [[#Kaartvedt--2018|Kaartvedt and Titelman, 2018]] ; [[#Ljungström--2021|Ljungström et al., 2021]] ). Responses by marine mammals and birds to the ongoing changes in polar ecosystems are both positive and negative ( [[#Meredith--2019|Meredith et al., 2019]] ; [[#Bestley--2020|Bestley et al., 2020]] ). Phenological, behavioural, physiological and distributional changes are observed in marine mammals and birds in response to altered ecological interactions and habitat degradation, especially to loss of sea ice ( ''high confidence'' ) (see Box 3.2; Cross-Chapter Paper 6; [[#Beltran--2019|Beltran et al., 2019]] ; [[#Cusset--2019|Cusset et al., 2019]] ; [[#Descamps--2019|Descamps et al., 2019]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Huntington--2020|Huntington et al., 2020]] ). Reproductive failures and declining abundances attributed to warmer polar oceans and less sea ice cover are observed in populations of polar bears, ''Ursus maritimus'' , seals, whales and marine birds ( ''high confidence'' ) (see Box 3.2; Duffy- [[#Anderson--2019|Anderson et al., 2019]] ; [[#Ropert-Coudert--2019|Ropert-Coudert et al., 2019]] ; [[#Bestley--2020|Bestley et al., 2020]] ; [[#Chambault--2020|Chambault et al., 2020]] ; [[#Molnár--2020|Molnár et al., 2020]] ; [[#Stenson--2020|Stenson et al., 2020]] ). The ongoing changes in polar marine ecosystems can lead to temporary increases in biodiversity and functional diversity (e.g., due to immigration of boreal species in the Arctic, ''high confidence'' ), but reduced trophic-transfer efficiencies and functional redundancy, with uncertain consequences for ecosystem resilience and vulnerability ( ''limited evidence'' , ''low agreement'' ) ( [[#Griffith--2019b|Griffith et al., 2019b]] ; [[#Alabia--2020|Alabia et al., 2020]] ; [[#du%20Pontavice--2020|du Pontavice et al., 2020]] ; [[#Alabia--2021|Alabia et al., 2021]] ; [[#Frainer--2021|Frainer et al., 2021]] ).

Calcareous polar organisms are among the groups most sensitive to ocean acidification ( ''high confidence'' ) ( [[#3.3.2|Section 3.3.2]] ). [[#Niemi--2021|Niemi et al. (2021)]] reports that &gt;80% of sampled sea snail, ''Limacina helicina'' , a key species in pelagic food webs, displayed signs of shell dissolution in the Amundsen Gulf. However, bacteria, phytoplankton, zooplankton and benthic communities are found to be detrimentally impacted, resilient or even positively influenced by ocean acidification in observational and experimental studies ( [[#3.3|Section 3.3]] ; [[#Hildebrandt--2016|Hildebrandt et al., 2016]] ; [[#Thor--2018|Thor et al., 2018]] ; [[#Ericson--2019|Ericson et al., 2019]] ; [[#McLaskey--2019|McLaskey et al., 2019]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Petrou--2019|Petrou et al., 2019]] ; [[#Renaud--2019|Renaud et al., 2019]] ; [[#Brown--2020|Brown et al., 2020]] ; [[#Hancock--2020|Hancock et al., 2020]] ; [[#Henley--2020|Henley et al., 2020]] ; [[#Johnson--2020|Johnson and Hofmann, 2020]] ; [[#Torstensson--2021|Torstensson et al., 2021]] ). While fish larval stages may be sensitive, adult fish are expected to have low vulnerability to projected acidification levels ( [[#3.3.3|Section 3.3.3]] ; [[#Hancock--2020|Hancock et al., 2020]] ), although reduced swimming capacity in polar cod in an ocean acidification experiment has been observed ( [[#Kunz--2018|Kunz et al., 2018]] ). Polar organisms’ sensitivity to ocean acidification may increase with increasing light levels due to the loss of sea ice (algae; [[#Donahue--2019|Donahue et al., 2019]] ; [[#Kvernvik--2020|Kvernvik et al., 2020]] ), temperature stress (pteropods; [[#Johnson--2020|Johnson and Hofmann, 2020]] ) or indirectly via increased heterotrophic bacterial productivity ( ''limited evidence'' ) ( [[#Vaqué--2019|Vaqué et al., 2019]] ). Due to limited mechanistic understanding of observed effects, and mixed responses among Arctic species, future impacts of ocean acidification are assigned ''medium confidence'' for polar species and ''low confidence'' for outcomes for polar ecosystems ( [[#Meredith--2019|Meredith et al., 2019]] ; [[#Green--2021b|Green et al., 2021b]] ).

While levels of pollutants in biota (e.g., persistent organic pollutants, mercury) have generally declined over the past decades, recent increasing levels are associated with release from reservoirs in ice, snow and permafrost, and through changing food webs and pathways for trophic amplification ( ''medium confidence'' ) (see Box 3.2; [[#Ma--2016|Ma et al., 2016]] ; [[#Amélineau--2019|Amélineau et al., 2019]] ; [[#Foster--2019|Foster et al., 2019]] ; [[#Bourque--2020|Bourque et al., 2020]] ; [[#Kobusińska--2020|Kobusińska et al., 2020]] ). Also, a warmer climate, altered ocean currents and increased human activities elevate the risk of invasive species in the Arctic ( ''medium confidence'' ), potentially changing ecosystems in this region ( ''high confidence'' ) ( [[#Chan--2019|Chan et al., 2019]] ; [[#Goldsmit--2020|Goldsmit et al., 2020]] ). In the remote Antarctic, there is a lower risk of invasive species ( ''limited evidence'' ) ( [[#McCarthy--2019|McCarthy et al., 2019]] ; [[#Holland--2021|Holland et al., 2021]] ).

Fisheries are largely sustainably managed yet are expanding polewards following sea ice melt in the Arctic ( ''high confidence'' ) ( [[#Fauchald--2021|Fauchald et al., 2021]] ) and possibly in the Antarctic ( ''limited evidence'' ) ( [[#Santa%20Cruz--2018|Santa Cruz et al., 2018]] ). Tourism is increasing and expanding in both polar regions, while shipping and hydrocarbon exploration are growing in the Arctic, increasing the risks of compound effects on vulnerable and already stressed populations and ecosystems ( ''high confidence'' ) (Sections 3.6.3.1.3, 3.6.3.1.4; Cross-Chapter Paper 6; [[#Hauser--2018|Hauser et al., 2018]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Helle--2020|Helle et al., 2020]] ; [[#Rogers--2020|Rogers et al., 2020]] ; [[#Cavanagh--2021|Cavanagh et al., 2021]] ).

Ensemble global model projections indicate future increases in primary production and total animal biomass towards 2100 under RCP2.6 (~5 and 50%, respectively) and RCP8.5 (~10 and 70%, respectively), in the Arctic ( [[#Bryndum-Buchholz--2019|Bryndum-Buchholz et al., 2019]] ; [[#Lotze--2019|Lotze et al., 2019]] ; [[#Nakamura--2019|Nakamura and Oka, 2019]] ), highlighting opportunities for, and possibly conflicts over, new ecosystem services ( [[#3.5|Section 3.5]] ). For the Southern Ocean, no overall trends are apparent, but greater variability in both primary production and total animal biomass are projected under RCP2.6, with an ~5 and 15% increase in primary production and total animal biomass under RCP8.5, respectively ( [[#Bryndum-Buchholz--2019|Bryndum-Buchholz et al., 2019]] ; [[#Lotze--2019|Lotze et al., 2019]] ; [[#Nakamura--2019|Nakamura and Oka, 2019]] ). All projections presented exhibit high inter-model variability and hence uncertainty ( [[#Heneghan--2021|Heneghan et al., 2021]] ). Furthermore, regional models project significant distributional shifts and wide-ranging trends (i.e., relatively stable, increasing and declining) in productivity for key ecological and commercial species, and functional groups, with weak to strong dependence on emission scenarios, indicating ''low confidence'' in future outcomes for polar marine ecosystems and associated ecosystem services ( [[#3.5|Section 3.5]] ; [[#Piñones--2016|Piñones and Fedorov, 2016]] ; [[#Griffiths--2017|Griffiths et al., 2017]] ; [[#Klein--2018|Klein et al., 2018]] ; [[#Hansen--2019|Hansen et al., 2019]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Steiner--2019|Steiner et al., 2019]] ; [[#Tai--2019|Tai et al., 2019]] ; [[#Alabia--2020|Alabia et al., 2020]] ; [[#Holsman--2020|Holsman et al., 2020]] ; [[#Reum--2020|Reum et al., 2020]] ; [[#Veytia--2020|Veytia et al., 2020]] ; [[#Sandø--2021|Sandø et al., 2021]] ). Potentially highly influential tipping points associated with Arctic sea ice melt and Antarctic ocean circulation change adds to this uncertainty (Cross-Chapter Paper 6; [[#Heinze--2021|Heinze et al., 2021]] ). Nevertheless, increasing evidence supports that sustainable and adaptive ecosystem-based fisheries practices can reduce detrimental impacts of climate change on harvested populations ( ''medium confidence'' ) ( [[#3.6.3.1.2|Section 3.6.3.1.2]] ; [[#Klein--2018|Klein et al., 2018]] ; [[#Free--2019|Free et al., 2019]] ; [[#Hansen--2019|Hansen et al., 2019]] ; [[#Holsman--2020|Holsman et al., 2020]] ).

<div id="FAQ 3.2" class="h2-container"></div>

<span id="faq-3.2-how-are-marine-heatwaves-affecting-marine-life-and-human-communities"></span>
=== FAQ 3.2 | How are marine heatwaves affecting marine life and human communities? ===

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''Heatwaves happen in the ocean as well as in the atmosphere. Marine heatwaves (MHWs) are extended periods of unusually warm ocean temperatures relative to the typical temperatures for that location and time of year. Due to climate change, the number of days with MHWs has increased by 54% over the past century. These MHWs cause mortalities in a wide variety of marine species, from corals to kelp to seagrasses to fish to seabirds, and have consequent effects on ecosystems and industries like aquaculture and fisheries.''

Extreme events in the ocean can have damaging effects on marine ecosystems and the human communities that depend on them. The most common form of ocean extremes are MHWs, which are becoming more frequent and intense due to global warming. Because seawater absorbs and releases heat more slowly than air, temperature extremes in the ocean are not as pronounced as over land, but they can persist for much longer, often for weeks to months over areas covering hundreds of thousands of square kilometres. These MHWs can be more detrimental for marine species, in comparison with land species, because marine species are usually adapted to relatively stable temperatures.

A commonly used definition of MHWs is a period of at least 5 days whose temperatures are warmer than 90% of the historical records for that location and time of year. Marine heatwaves are described by their abruptness, magnitude, duration, intensity and other metrics. In addition, targeted methods are used to characterize MHWs that threaten particular ecosystems; for example, the accumulated heat stress above typical summer temperatures, described by ‘degree heating weeks’, is used to estimate the likelihood of coral bleaching.

Over the past century, MHWs have doubled in frequency, become more intense, lasted for longer and extended over larger areas. Marine heatwaves have occurred in every ocean region over the past few decades, most markedly in association with regional climate phenomena such as the El Niño/Southern Oscillation. During the 2015–2016 El Niño event, 70% of the world’s ocean surface encountered MHWs.

Such MHWs cause mortality of a wide variety of marine species, from corals to kelp to seagrasses to fish to seabirds, and they have consequent effects on ecosystems and industries such as mariculture and fisheries. Warm-water coral reefs, estuarine seagrass meadows and cold-temperate kelp forests are among the ecosystems most threatened by MHWs since they are attached to the seafloor (see FAQ 3.2). Unusually warm temperatures cause bleaching and associated death of warm-water corals, which can lead to shifts to low-diversity or algae-dominated reefs, changes in fish communities and deterioration of the physical reef structure, which causes habitat loss and increases the vulnerability of nearby shorelines to large-wave events and SLR. Since the early 1980s, the frequency and severity of mass coral bleaching events have increased sharply worldwide. For example, from 2016 through 2020, the Great Barrier Reef experienced mass coral bleaching three times in 5 years.

Mass loss of kelp from MHWs effects on the canopy-forming species has occurred across ocean basins, including the coasts of Japan, Canada, Mexico, Australia and New Zealand. In southern Norway and the northeast USA, mortality from MHWs contributed to the decline of sugar kelp over the past two decades and the spread of turf algal ecosystems that prevent recolonisation by the original canopy-forming species.

One of the largest and longest-duration MHWs, nicknamed the ‘Blob’, occurred in the Northeast Pacific Ocean, extending from California north towards the Bering Sea, from 2013 through 2015. Warming from the MHW persisted into 2016 off the West Coast of the USA and into 2018 in the deeper waters of a Canadian fjord. The consequent effects of this expansive MHW included widespread shifts in abundance, distribution and nutritional value of invertebrates and fish, a bloom of toxic algae off the West Coast of the USA that impacted fisheries, the decline of California kelp forests that contributed to the collapse of the abalone fishery, and mass mortality of seabirds.

The projected increase in the frequency, severity, duration and areal extent of MHWs threaten many marine species and ecosystems. These MHWs may exceed the thermal limits of species, and they may occur too frequently for the species to acclimate or for populations to recover. The majority of the world’s coral reefs are projected to decline and begin eroding due to more frequent bleaching-level MHWs if the world warms by more than 1.5°C. Recent research suggests possible shifts to more heat-tolerant coral communities but at the expense of species and habitat diversity. Other systems, including kelp forests, are most threatened near the edges of their ranges, although more research is needed into the effect of re-occurring MHWs on kelp forests and other vulnerable systems.

The projected ecological impacts of MHWs threaten local communities and Indigenous Peoples, incomes, fisheries, tourism and, in the case of coral reefs, shoreline protection from waves. High-resolution forecasts and early-warning systems, currently most advanced for coral reefs, can help people and industries prepare for MHWs and also collect data on their effects. Identifying and protecting locations and habitats with reduced exposure to MHWs is a key scientific endeavour. For example, corals may be protected from MHWs in tidally stirred waters or in reefs where cooler water upwells from subsurface. Marine protected areas and no-take zones, in addition to terrestrial protection surrounding vulnerable coastal ecosystems, cannot prevent MHWs from occurring. But, depending on the location and adherence by people to restrictions on certain activities, the cumulative effect of other stressors on vulnerable ecosystems can be reduced, potentially helping to enhance the rate of recovery of marine life.

[[File:49f3d65ce73740263fe5d885b8c8008e IPCC_AR6_WGII_Figure_3_FAQ_3_2.png]]

'''Figure FAQ3.2.1 |''' '''Impact pathway of a massive extreme marine heatwave, the northwest Pacific ‘Blob’, from causal mechanisms to initial effects, resulting nonlinear effects and the consequent impacts for humans.''' Lessons learnt from the Blob include the need to advance seasonal forecasts, real-time predictions, monitoring responses, education, possible fisheries impacts and adaptation.

<div id="3.4.3" class="h2-container"></div>

<span id="oceanic-systems-and-cross-cutting-changes"></span>
=== 3.4.3 Oceanic Systems and Cross-Cutting Changes ===

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The oceanic zone, comprising &gt;99% of the ocean’s volume, is highly exposed to climate-induced drivers because of its proximity to the atmosphere ( [[#3.2|Section 3.2]] ; [[#Pörtner--2014|Pörtner et al., 2014]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ), while its relative distance from human settlements and coastal ecosystems decreases variability and interactions, and permits many phenomena to be detected clearly and attributed to climate change. This section assesses how climate-driven changes influence oceanic biological systems over very large spatial scales and notes how impacts on the epipelagic zone affect the mesopelagic, bathypelagic and deep seafloor ecosystems.

<div id="3.4.3.1" class="h3-container"></div>

<span id="biogeography-and-species-range-shifts"></span>
==== 3.4.3.1 Biogeography and Species Range Shifts ====

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<div id="3.4.3.1.1" class="h4-container"></div>

<span id="observed-species-range-shifts"></span>
===== 3.4.3.1.1 Observed species range shifts =====

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Since previous assessments (Table 3.16), poleward range shifts have remained a ubiquitous response to climate change ( ''high confidence'' ), moving species from warmer regions into higher-latitude ecosystems ( [[#Fossheim--2015|Fossheim et al., 2015]] ; [[#Kumagai--2018|Kumagai et al., 2018]] ; [[#Burrows--2019|Burrows et al., 2019]] ; [[#Lenoir--2020|Lenoir et al., 2020]] ).

'''Table 3.16 |''' Summary of previous IPCC assessments of biogeography and species range shifts

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Pörtner--2014|Pörtner et al., 2014]] )''

|
|-
| The distribution and abundance of many fishes and invertebrates have shifted poleward and/or to deeper, cooler waters ( ''high confidence'' ).

On average, species’ distributions have shifted poleward by 72.0 ± 0.35 km per decade ( ''high confidence'' ).

| Spatial shifts of marine species due to projected warming will cause high-latitude invasions and high local-extinction rates in the tropics and semi-enclosed seas ( ''medium confidence'' ).

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘Ocean warming has contributed to observed changes in biogeography of organisms ranging from phytoplankton to marine mammals ( ''high confidence'' ).’

‘The direction of the majority of the shifts of epipelagic organisms are consistent with a response to warming ( ''high confidence'' )’ but are also shaped by oxygen concentrations and ocean currents across depth, latitudinal and longitudinal gradients ( ''high confidence'' ).

Geographic ranges have shifted since the 1950s by 51.5 ± 33.3 km per decade (mean and ''very likely'' range) and 29.0 ± 15.5 km per decade for organisms in the epipelagic and seafloor ecosystems, respectively.

| ‘Recent model projections since AR5 and SR15 continue to support global-scale range shifts of marine fishes at rates of tens to hundreds of km per decade in the 21st century, with rate of shifts being substantially higher under RCP8.5 than RCP2.6.’

|}

Thermal tolerances of epipelagic populations drive biogeographic change (Figures 3.10, 3.15), but the strength and direction of range shifts tend to be modulated by both climate-induced and non-climate drivers ( [[#Pinsky--2020b|Pinsky et al., 2020b]] ), including: (a) interactive effects of hypoxia and ocean acidification ( [[#Sampaio--2021|Sampaio et al., 2021]] ); (b) oceanic dispersal barriers ( [[#Choo--2021|Choo et al., 2021]] ), food and critical habitat availability ( [[#Alabia--2020|Alabia et al., 2020]] ; [[#Tanaka--2021|Tanaka et al., 2021]] ); (c) geographic position, including depth ( [[#Mardones--2021|Mardones et al., 2021]] ); and (d) ocean currents ( [[#Sunday--2015|Sunday et al., 2015]] ; [[#Chapman--2020|Chapman et al., 2020]] ; [[#Fuchs--2020|Fuchs et al., 2020]] ). The difference between physiological thermal tolerances ( [[#3.3.2|Section 3.3.2]] ) and local environmental conditions determines safety margins against future climate warming in ectotherms ( [[#Pinsky--2019|Pinsky et al., 2019]] ). Acclimation and evolution ( [[#3.3.4|Section 3.3.4]] ) and life-history stage ( [[#3.3.3|Section 3.3.3]] ) also alter species’ thermal tolerances. Biogeographic responses are further modulated by other interacting factors (Table 3.17).

'''Table 3.17 |''' Synthesis of selected processes conditioned by multiple environmental drivers that interact with warming to ultimately define range-shift responses

{| class="wikitable"
|-
! Factor

! Effect

! Example references

|-
| Evolution and acclimation

| Evolution of thermal tolerances and acclimation under local climatic conditions can increase resilience to future climate warming, slowing the loss of species at trailing (warm) range edges.

| [[#Palumbi--2014|Palumbi et al. (2014)]] ; [[#Miller--2020a|Miller et al. (2020a)]]

|-
| rowspan="4"| Marine heatwaves (MHWs)

| MHWs can influence the evolution of thermal tolerances by eliminating genotypes that are intolerant of elevated temperatures.

| [[#Buckley--2016|Buckley and Huey (2016)]] ; [[#Sunday--2019|Sunday et al. (2019)]]

|-
| MHWs can produce widespread die-offs of shallow-water benthic organisms triggering extensive contractions of their ranges.

| [[#Smale--2013|Smale and Wernberg (2013)]]

|-
| MHWs can facilitate range expansions by opening niches and/or enhancing recruitment of warm-affiliated species.

| [[#Leriorato--2019|Leriorato and Nakamura (2019)]] ; [[#Thomsen--2019|Thomsen et al. (2019)]] ; [[#Monaco--2021|Monaco et al. (2021)]]

|-
| Cold waves can halt or even reverse range expansions at leading edges.

| [[#Leriorato--2019|Leriorato and Nakamura (2019)]]

|-
| rowspan="3"| Ocean currents

| Ocean currents can influence range dynamics through their effect on dispersal, depending on their magnitude, direction and seasonal patterns.

| Hunt et al. (2016); [[#Kumagai--2018|Kumagai et al. (2018)]] ; [[#Fuchs--2020|Fuchs et al. (2020)]]

|-
| Where currents align with spatial gradients of warming, range expansions track thermal changes more closely. Conversely, directional mismatches result in consistently slower expansion rates and larger response lags, an effect more acute for benthic organisms relying on passive dispersion of larvae and propagules.

| García Molinos et al. (2017)

|-
| Rates of range contraction across taxa decreased (increased) under directional agreement (mismatch) with ocean currents, possibly associated with enhanced (reduced) flows of adaptive genes to warming in downstream (upstream) populations within the distributional range.

| García Molinos et al. (2017)

|-
| rowspan="2"| Climatic refugia

| Areas of locally stable climatic conditions, such as deeper waters or regions with internal tides or localised upwelling, can buffer the effects of regional warming, facilitating species persistence and conserving genetic diversity at rear-edge populations.

| [[#Smith--2014|Smith et al. (2014)]] ; [[#Assis--2016|Assis et al. (2016)]] ; [[#Lourenço--2016|Lourenço et al. (2016)]] ; [[#Wyatt--2020|Wyatt et al. (2020)]]

|-
| Distributional shifts into deeper, cooler habitats can offer an effective alternative response to latitudinal shifts, because sharper thermal gradients mean that vertical displacements, needed to compensate for the same amount of warming, are several orders of magnitude smaller than planar displacements.

| [[#Smith--2014|Smith et al. (2014)]] ; [[#Assis--2016|Assis et al. (2016)]] ; [[#Lourenço--2016|Lourenço et al. (2016)]]

|-
| rowspan="2"| Oxygen availability

| Oxygen supersaturation may extend ectotherm survival to extreme temperatures and increase thermal tolerances by compensating for the increasing metabolic demand at high temperatures.

| [[#Giomi--2019|Giomi et al. (2019)]]

|-
| Oxygen deprivation increases metabolic demand and respiration rates. Shallowing of oxygen-dead zones and subsequent hypoxic avoidance can render deep thermal refuges unsuitable for organisms.

| [[#Brown--2015|Brown and Thatje (2015)]] ; [[#Roman--2019|Roman et al. (2019)]] ; [[#Hughes--2020|Hughes et al. (2020)]]

|-
| Habitat availability and quality

| The availability and quality of habitat (underwater light conditions, adequate substrate, nutrient and food supply) set limits to the distribution of organisms and range-shift dynamics (e.g., resilience of populations to climate warming and the consolidation of range expansions).

| Krause- [[#Jensen--2019|Jensen et al. (2019)]] ; [[#Tamir--2019|Tamir et al. (2019)]]

|-
| rowspan="2"| Biotic interactions, including food availability

| Species interactions can confer resilience to warming by retarding habitat degradation and buffering the impacts of warming on organisms.

| [[#Falkenberg--2015|Falkenberg et al. (2015)]] ; [[#Giomi--2019|Giomi et al. (2019)]]

|-
| Changes in biotic interactions (e.g., altered predation rates, food availability, competition or trophic mismatches) induced by climate warming can modify range-shift dynamics.

| [[#Selden--2018|Selden et al. (2018)]] ; [[#Westerbom--2018|Westerbom et al. (2018)]] ; Figueira et al. (2019); Pinsky et al. (2020b); [[#Monaco--2021|Monaco et al. (2021)]]

|}

<div id="_idContainer057" class="Figure"></div>

[[File:4e2baa6bf62f0f7f0fb192daff36a272 IPCC_AR6_WGII_Figure_3_015.png]]

'''Figure 3.15 |''' '''Range-shift dynamics in marine ectotherms in response to climate warming.''' As the ocean warms, conditions at the edge of the species’ distribution may become warmer than the maximum thermal tolerance of the species (Figure 3.9), causing local populations to undergo a gradual decline in performance, a decreasing population size and ultimately their extirpation, resulting in a range contraction. Conversely, at the cool extreme of the distribution, habitats beyond the current range of the species will become thermally suitable in the future (i.e., within the species’ thermal tolerance range) and, providing the species can disperse to those locations, allow for the colonisation and consolidation of new populations and subsequent range expansion. These are processes conditioned by multiple drivers that interact with warming to ultimately define range-shift responses, some of which are described in Table 3.17. Note that physiological thermal tolerances relate to body temperatures of the organism rather than ambient temperatures.

A global meta-analysis of range shifts ( [[#Lenoir--2020|Lenoir et al., 2020]] ) that included data from 951 species (over half of which exhibited median range shifts consistent with climate change) estimates that marine species are moving poleward at a rate of 59.2 km per decade ( ''very likely'' range: 43.7–74.7 km per decade), closely matching the local climate velocity ( ''high confidence'' ). In some cases, warming-related distribution shifts were followed by density-dependent use of these areas, influencing associated fisheries ( [[#Baudron--2020|Baudron et al., 2020]] ), and in others, warming influenced competitive interactions: in the Arctic-Boreal Barents Sea, warming-induced increases in cod ( ''Gadus morhua'' ) abundance reduces haddock ( ''Melanogrammus aeglefinus'' ) abundance ( [[#Durant--2020|Durant et al., 2020]] ).

Biogeographic shifts lead to novel communities and biotic interactions ( ''high confidence'' ) ( [[#Zarco-Perello--2017|Zarco-Perello et al., 2017]] ; [[#Pecuchet--2020b|Pecuchet et al., 2020b]] ), with concomitant changes in ecosystem functioning and servicing ( ''high confidence'' ) ( [[#Vergés--2019|Vergés et al., 2019]] ; [[#Nagelkerken--2020|Nagelkerken et al., 2020]] ; [[#Peleg--2020|Peleg et al., 2020]] ). For instance, temperature-driven changes in distribution and abundance of copepods, the dominant zooplankton, were observed between 1960 and 2014 in the North Atlantic. These changes subsequently affect biogenic carbon cycling through alteration of microbial remineralisation and carbon sequestration in deep water ( ''medium confidence'' ) ( [[#3.4.3|Section 3.4.3.6]] ; [[#Pitois--2006|Pitois and Fox, 2006]] ; [[#Brun--2019|Brun et al., 2019]] ).

<div id="3.4.3.1.2" class="h4-container"></div>

<span id="observed-vertical-redistributions"></span>
===== 3.4.3.1.2 Observed vertical redistributions =====

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Epipelagic isotherms have recently (1980–2015) deepened at an average of 6.6 ± 18.8 m per decade ( [[#Pinsky--2019|Pinsky et al., 2019]] ), but there is ''low agreement'' on whether species move deeper in pursuit of thermal refuge. Prior studies suggested range shifts to depth ( [[#Dulvy--2008|Dulvy et al., 2008]] ; [[#Pinsky--2013|Pinsky et al., 2013]] ; [[#Yemane--2014|Yemane et al., 2014]] ), but increasing evidence suggests that fish and planktonic communities across large parts of the North Atlantic, sub-Arctic and northeast Pacific Ocean redistribute horizontally with horizontal climate velocity, except where vertical temperature gradients are particularly steep. There is ''low confidence'' for temperature-driven depth shifts in the epipelagic zone ( [[#Burrows--2019|Burrows et al., 2019]] ; [[#Campana--2020|Campana et al., 2020]] ; [[#Caves--2021|Caves and Johnsen, 2021]] ). At the same time, decreasing oxygen concentrations and the vertical expansion of OMZs have already decreased suitable habitat of pelagic fishes, including tuna and billfishes, by ~15% primarily due to vertical compression of environmental niches ( [[#Stramma--2012|Stramma et al., 2012]] ; [[#Deutsch--2015|Deutsch et al., 2015]] ).

<div id="3.4.3.1.3" class="h4-container"></div>

<span id="projected-changes-in-species-range-shifts"></span>
===== 3.4.3.1.3 Projected changes in species range shifts =====

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Continued changes in the biogeography of marine predators and prey are anticipated under future climate change, with climate velocity in the epipelagic zone during 2050–2100 under RCP8.5 projected to be sevenfold faster than that during 1955–2005 ( ''medium confidence'' ) (Figure 3.4; [[#Brito-Morales--2020|Brito-Morales et al., 2020]] ). This has substantial ecological implications, as projections suggest near elimination of overlaps between the distributions of certain predator–prey pairs in the northeast Atlantic Ocean when their current joint distributions (1989–2014) are compared with those projected (2037–2062) under RCP8.5 ( [[#Sadykova--2020|Sadykova et al., 2020]] ).

Deepening of epipelagic isotherms is projected to accelerate over 2006–2100 to rates of 8.5 m per decade under RCP4.5 and 32 m per decade under RCP8.5 ( [[#Jorda--2020|Jorda et al., 2020]] ). Although vertical redistribution of thermal niches is three to four orders of magnitude slower than horizontal displacement, maximum depth limits imposed by the seafloor and photic layer (both of which are projected to be reached in this century) will ''likely'' vertically compress suitable habitat for most marine organisms ( ''medium confidence'' ) ( [[#Dueri--2014|Dueri et al., 2014]] ; [[#Jorda--2020|Jorda et al., 2020]] ).

Projections from coupled biogeochemical and ecosystem models suggest a general decline in mesopelagic biomass ( [[#Lefort--2015|Lefort et al., 2015]] ), although this may vary among ocean basins. The volume of OMZs have been expanding at many locations ( ''high confidence'' ), and the oxygen content of the subsurface ocean is projected to decline to historically unprecedented conditions over the 21st century ( ''medium confidence'' ) ( [[#3.2.3|Section 3.2.3.2]] ; WGI AR6 [[IPCC:Wg2:Chapter:Chapter-5#5.3|Section 5.3.3.2]] ; [[#Canadell--2021|Canadell et al., 2021]] ) at a rate of 10–15 µM per decade in OMZs ( [[#3.2.3|Section 3.2.3.2]] ; [[#Breitburg--2018|Breitburg et al., 2018]] ). Oxygen availability and the effects of ocean acidification (Sections 3.3, 3.4.2) on zooplankton might become a dominant constraint in the upper ocean’s metabolic index, which is projected to decrease globally by 20% by 2100 ( [[#Deutsch--2015|Deutsch et al., 2015]] ; [[#Steinberg--2017|Steinberg and Landry, 2017]] ). In addition, extremely rapid acceleration of climate velocities projected in the mesopelagic under all emissions scenarios suggest that species in this ocean stratum will be even more exposed to future warming than species in the epipelagic (Figure 3.4; [[#Brito-Morales--2020|Brito-Morales et al., 2020]] ). But projections also suggest that warming-related increases in trophic efficiency lead to a 17% increase in the biomass of the deep-scattering layer (zooplankton and fish in the mesopelagic) by 2100 (low ''confidence'' ) ( [[#Bindoff--2019a|Bindoff et al., 2019a]] ). Observational studies appear to show that mesopelagic fishes adapted to warm water increased in abundance and distribution in the California Current associated with warming and the expansion of OMZ ( [[#Koslow--2019|Koslow et al., 2019]] ), suggesting that some mesopelagic fish stocks might be resilient to a changing climate ( ''medium confidence'' ).

<div id="3.4.3.2" class="h3-container"></div>

<span id="phenological-shifts-and-trophic-mismatches"></span>
==== 3.4.3.2 Phenological Shifts and Trophic Mismatches ====

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<div id="3.4.3.2.1 " class="h4-container"></div>

<span id="observed-changes"></span>
===== 3.4.3.2.1 Observed changes =====

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SROCC reported ''high confidence'' in phenological shifts towards earlier onset of biological events (Table 3.18), with phenological shifts among epipelagic species attributed to ocean warming ( ''high confidence'' ).

'''Table 3.18 |''' Summary of previous IPCC assessments of phenological shifts and trophic mismatches

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 WGII ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Larsen--2014|Larsen et al., 2014]] )''

|
|-
| ‘Changes to sea temperature have altered the phenology, or timing of key life-history events such as plankton blooms, and migratory patterns, and spawning in fish and invertebrates, over recent decades ( ''medium confidence'' ). There is ''medium to high agreement'' that these changes pose significant uncertainties and risks to fisheries, aquaculture and other coastal activities.’

The highly productive high-latitude spring bloom systems in the northeast Atlantic are responding to warming ( ''medium evidence, high agreement'' ), with the greatest changes being observed since the late 1970s in the phenology, distribution and abundance of plankton assemblages, and the reorganisation of fish assemblages, with a range of consequences for fisheries ( ''high confidence'' ).

‘Observed changes in the phenology of plankton groups in the North Sea over the past 50 years are driven by climate forcing, in particular regional warming ( ''high confidence'' ).’

‘On average, spring events in the ocean have advanced by 4.4 ± 0.7 days per decade (mean ± SE).’

‘Shifts in the timing and magnitude of seasonal biomass production could disrupt matched phenologies in the food webs, leading to decreased survival of dependent species ( ''medium confidence'' ). If the timing of primary and secondary production is no longer matched to the timing of spawning or egg release, survival could be impacted, with cascading implications to higher trophic levels. This impact would be exacerbated if shifts in timing occur rapidly ( ''medium confidence'' ).’

‘There is ''medium to high confidence'' that climate-induced disruptions in the synchrony between timing of spawning and hatching of some fish and shellfish and the seasonal increases in prey availability can result in increased larval or juvenile mortality or changes in the condition factor of fish and shellfish species in the Arctic marine ecosystems.’

| Projections of phenological shifts and trophic mismatches were not assessed in this report.

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘Phenology of marine ectotherms in the epipelagic systems related to ocean warming ( ''high confidence'' ) and the timing of biological events has shifted earlier ( ''high confidence'' ).’

‘Timing of spring phenology of marine organisms is shifting to earlier in the year under warming, at an average rate of 4.4 ± 1.1 days per decade, although it is variable among taxonomic groups and among ocean regions.’

| Projections of phenological shifts and trophic mismatches were not assessed in this report.

|-
|
|-
| ''WGI AR6 [[IPCC:Wg2:Chapter:Chapter-2|Chapter 2]] ( [[#Gulev--2021|Gulev et al., 2021]] )''

|
|-
| ‘Phenological metrics for many species of marine organisms have changed in the last half century ( ''high confidence'' ), though many regions and many species of marine organisms remain under-sampled or even unsampled. The changes vary with location and with species ( ''high confidence'' ). There is a strong dependence of survival in higher trophic-level organisms (fish, exploited invertebrates, birds) on the availability of food at various stages in their life cycle, which in turn depends on the phenologies of both ( ''high confidence'' ). There is a gap in our understanding of how the varied responses of marine organisms to climate change, from a phenological perspective, might threaten the stability and integrity of entire ecosystems.’

| Projections of phenological shifts and trophic mismatches were not assessed in this report.

|}

'''Table 3.19 |''' Assessment of phenological shifts by taxon based on time series from field observations spanning at least 19 years published over the past 25 years

{| class="wikitable"
|-
! Taxon

! Rate of consistency of observations with climate change

! Estimated mean rate of change in seasonal timing

! Confidence

! Notes

|-
| Phytoplankton

| 78.41%

( ''n'' = 85)

| −7.5 d per decade

( ''n'' = 83)

| ''Very high confidence''

| ''Evidence most robust'' for changes in timing of blooms in the North Atlantic (e.g., [[#Chivers--2020|Chivers et al., 2020]] ) and Baltic (e.g., [[#Scharfe--2019|Scharfe and Wiltshire, 2019]] ; [[#Wasmund--2019|Wasmund et al., 2019]] ), with ''limited evidence'' from the Southern Hemisphere.

|-
| Holozooplankton

| 79.74%

( ''n'' = 77)

| −4.27 d per decade

( ''n'' = 58)

| ''Very high confidence''

| ''Evidence most robust'' in the northeast Atlantic (e.g., [[#Chevillot--2017|Chevillot et al., 2017]] ), but sparse elsewhere.

|-
| Meroplankton (taxa that are only temporarily in the plankton)

| 81.06%

( ''n'' = 72)

| −4.34 d per decade

( ''n'' = 64)

| ''Very high confidence''

| Includes earlier peak abundance of fish larvae in upwelling systems (e.g., [[#Asch--2015|Asch, 2015]] ).

|-
| Benthic invertebrates

| 72.34%

( ''n'' = 5)

| −8.5 d per decade

( ''n'' = 5)

| ''Low confidence'' ( ''limited evidence, medium agreement'' )

| ''Evidence is limited'' , uncertainty levels are high. Rate of consistency of responses with climate change is not significantly different from random chance.

|-
| Plants

| 100%

( ''n'' = 1)

| No estimate available

| ''Very low confidence''

| Just a single study for seagrasses, and only for consistency ( [[#Diaz-Almela--2007|Diaz-Almela et al., 2007]] ).

|-
| Fish

| 65.48%

( ''n'' = 109)

| −3.02 d per decade

( ''n'' = 43)

| ''Very high confidence''

| Includes earlier appearance of migratory fish in estuaries (e.g., [[#Chevillot--2017|Chevillot et al., 2017]] ), earlier spawning migrations for anadromous fish such as salmon (e.g., [[#Rubenstein--2019|Rubenstein et al., 2019]] ), earlier migrations for sole (e.g., [[#Fincham--2013|Fincham et al., 2013]] ) and tuna (e.g., [[#Dufour--2010|Dufour et al., 2010]] ), and earlier spawning of key commercial demersal (bottom-dwelling) species such as cod (e.g., [[#McQueen--2017|McQueen and Marshall, 2017]] ).

|-
| Marine reptiles

| 100.0%

( ''n'' = 4)

| −2.89 d per decade

( ''n'' = 4)

| ''Low confidence'' ( ''limited evidence, low agreement'' )

| ''Evidence is limited'' , uncertainty levels are high. Mean phenological shift is not significantly different from zero.

|-
| Seabirds

| 42.36%

( ''n'' = 56)

| +0.77 d per decade

( ''n'' = 51)

| ''Very low confidence'' ( ''limited evidence, low agreement'' )

| Neither the rate of consistency with climate change nor the phenological shift differ significantly from null expectations (50% consistency and no shift). Many seabirds are breeding earlier ( [[#Byrd--2008|Byrd et al., 2008]] ; [[#Sydeman--2009|Sydeman et al., 2009]] ), while breeding among others in temperate and polar regions has been delayed, which has been linked to later sea ice breakup or limited prey resources ( [[#Barbraud--2006|Barbraud and Weimerskirch, 2006]] ; [[#Wanless--2009|Wanless et al., 2009]] ; [[#Chambers--2014|Chambers et al., 2014]] ). Although the response of lifecycle events for many seabird species is variable in direction, there has usually been a more complex driver associated with climate that has been considered to be responsible ( [[#Sydeman--2015|Sydeman et al., 2015]] ). For many species, seasonal timing is moving earlier, especially in the Arctic (e.g., [[#Byrd--2008|Byrd et al., 2008]] ; [[#Descamps--2019|Descamps et al., 2019]] ), but for many species in the Southern Ocean, it is not ( [[#Barbraud--2006|Barbraud and Weimerskirch, 2006]] ; [[#Chambers--2014|Chambers et al., 2014]] ). This could be because of a much slower rate of warming in most of the Southern Ocean than in the Arctic.

|-
| Marine mammals

| 100.0%

( ''n'' = 4)

| −0.34 d per decade ( ''n'' = 4)

| ''Very low confidence'' ( ''limited evidence, low agreement'' )

| All studies of phenological changes for marine mammals have focused on whales (e.g., [[#Ramp--2015|Ramp et al., 2015]] ; [[#Hauser--2017|Hauser et al., 2017]] ; [[#Loseto--2018|Loseto et al., 2018]] ) or polar bears (e.g., [[#Cherry--2013|Cherry et al., 2013]] ; [[#Atwood--2016|Atwood et al., 2016]] ; [[#Escajeda--2018|Escajeda et al., 2018]] ) and have related timing to aspects of sea ice dynamics, highlighting the complexity of such processes. Mean phenological shift is not significantly different from zero at the global scale.

|}

Since SROCC, field data have continued to show that the phenology of biological events in the ocean is ''very likely'' ( ''high to very high confidence'' ) advancing in response to climate change, with 71.9% of published observations consistent with these anticipated effects (Figure 3.16a,b; Table 3.19), although most reports (95.6%) were from the Northern Hemisphere (Figure 3.16a). Biological events that are shifting earlier in response to climate change include phytoplankton blooms ( [[#Scharfe--2019|Scharfe and Wiltshire, 2019]] ; [[#Chivers--2020|Chivers et al., 2020]] ) such as: (a) those of HAB species ( [[#Forsblom--2019|Forsblom et al., 2019]] ; [[#Bucci--2020|Bucci et al., 2020]] ); (b) peaks in zooplankton abundance ( [[#Chevillot--2017|Chevillot et al., 2017]] ; [[#Forsblom--2019|Forsblom et al., 2019]] ); (c) the migration ( [[#Otero--2014|Otero et al., 2014]] ; [[#Kovach--2015|Kovach et al., 2015]] ; [[#Chust--2019|Chust et al., 2019]] ) and spawning of commercial fish ( [[#McQueen--2017|McQueen and Marshall, 2017]] ; [[#Kanamori--2019|Kanamori et al., 2019]] ), including crabs and squid ( [[#Henderson--2017|Henderson et al., 2017]] ); and (d) breeding of marine reptiles ( [[#Mazaris--2008|Mazaris et al., 2008]] ; [[#Cherkiss--2020|Cherkiss et al., 2020]] ). Moreover, different trophic levels within epipelagic food webs are responding at different rates ( ''very high confidence'' ) (Table 3.19; Figure 3.16b,c), with greater and more consistent responses by lower trophic levels (phytoplankton, holozooplankton and meroplankton) but less consistent, weaker and more varied responses by higher trophic levels. There were too few independent time series to make robust estimates for benthic invertebrates, plants, marine reptiles and mammals. This differential response across trophic levels could lead to trophic mismatches ( [[#Neuheimer--2018|Neuheimer et al., 2018]] ), where predators and their prey respond asynchronously to climate change ( [[#Edwards--2004|Edwards and Richardson, 2004]] ; [[#Rogers--2019|Rogers and Dougherty, 2019]] ; [[#Rubenstein--2019|Rubenstein et al., 2019]] ; [[#Émond--2020|Émond et al., 2020]] ), with potential population-level consequences, including declines in fish recruitment ( [[#Burthe--2012|Burthe et al., 2012]] ; [[#Chevillot--2017|Chevillot et al., 2017]] ; [[#McQueen--2017|McQueen and Marshall, 2017]] ; [[#Asch--2019|Asch et al., 2019]] ; [[#Durant--2019|Durant et al., 2019]] ; [[#Régnier--2019|Régnier et al., 2019]] ). Available evidence also suggests that feeding relationships could modulate species responses to climate change, as seen in breeding of surface-feeding and deeper-diving seabirds ( [[#Descamps--2019|Descamps et al., 2019]] ). These differential responses could determine ‘winners’ and ‘losers’ under future climate change ( [[#Lindén--2018|Lindén, 2018]] ).

<div id="_idContainer062" class="Figure"></div>

[[File:d1f25a14a1580fe6eb4b371e588bddc3 IPCC_AR6_WGII_Figure_3_016.png]]

'''Figure 3.16 |''' '''Observed responses to climate change based on a systematic Web of Science review of marine phenology studies exceeding 19 years in length to update the assessment in WGII AR5 Chapter 30 (Hoegh-Guldberg et al.''' ''', 2014).''' Error bars indicate 95% confidence limits (i.e., the ''extremely likely'' range).

'''(a)''' Global data shows changes in seasonal cycles of biota that are attributed (at least partly) to climate change (blue, ''n'' = 297 observations), and changes that are inconsistent with climate change (white, ''n'' = 116 observations). Each circle represents the centre of a study area.

'''(b)''' The proportion of phenological observations (showing means and ''extremely likely'' ranges) that are attributed to climate change (i.e., generally showing earlier timing) by taxonomic group.

'''(c)''' Observed shifts in timing (days per decade, showing means and ''extremely likely'' ranges), by taxonomic group, that are attributed to climate change. Negative shifts are earlier, positive shifts are later. (Details and additional plots are presented in 3.SM.3.3, Figure 3.SM.3 and Table 3.SM.1.)

<div id="3.4.3.2.2" class="h4-container"></div>

<span id="projected-changes"></span>
===== 3.4.3.2.2 Projected changes =====

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The CMIP6 ESM ensembles project that, by 2100, 18.8 ± 19.0% (mean ± ''very likely'' range) and 38.9 ± 9.4% of the ocean surface will ''very likely'' undergo a change of 20 d or more (advance or delay) in the start of the phytoplankton growth period under SSP1-2.6 and SSP5-8.5, respectively (Figure 3.17a,b) ( ''low confidence'' due to the dependence with the projected changes in phytoplankton biomass, the trends of which are reported with ''low confidence'' ) ( [[#3.4.3.4|Section 3.4.3.4]] ; SROCC [[IPCC:Wg2:Chapter:Chapter-5#5.2|Section 5.2.3]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). Phytoplankton growth is projected to begin later in the Northern Hemisphere subtropics, and earlier at high latitudes in some regions around the Antarctic Peninsula, and over large areas in the Northern Hemisphere ( ''low to medium confidence'' as there are improved constraints from historical variability in this region and consistency with CMIP5-based-studies results) ( [[#Henson--2018b|Henson et al., 2018b]] ; [[#Asch--2019|Asch et al., 2019]] ). There is ''high agreement'' in model projections that the start of the phytoplankton growth period will ''very likely'' advance in the Arctic Ocean under a high-emission scenario for CMIP5 and CMIP6 (Figure 3.17b; [[#Henson--2018b|Henson et al., 2018b]] ; [[#Asch--2019|Asch et al., 2019]] ; [[#Tedesco--2019|Tedesco et al., 2019]] ; [[#Lannuzel--2020|Lannuzel et al., 2020]] ). The CMIP6 ensemble projections further show limited changes in phenology across most of the Southern Ocean but large regional variations in the tropics (Figure 3.17). Overall, the regional patterns are qualitatively similar under SSP1-2.6 and SSP5-8.5 but with greater magnitude and larger areas under SSP5-8.5 ( ''low confidence'' ).

<div id="_idContainer065" class="Figure"></div>

[[File:aae03dd90e97291b745b7a026d4210dd IPCC_AR6_WGII_Figure_3_017.png]]

'''Figure 3.17 |''' '''Projected phytoplankton phenology.''' (a,c) Spatial patterns and (b,d) density distributions of projected change in phytoplankton phenology by 2100 under Shared Socioeconomic Pathway (SSP)1-2.6 and SSP5-8.5, respectively. Difference in the start of the phytoplankton growth period is calculated as 2090–2099 minus 1996–2013. Negative (positive) values indicate earlier (later) start of the phytoplankton growth period by 2100. The ensemble projections of global changes in phytoplankton phenology include, under SSP1-2.6 and SSP5-8.5, respectively, a total of five Coupled Model Intercomparison Project 6 Earth system models containing coupled ocean biogeochemical models that cover a wide range of complexity ( [[#Kwiatkowski--2019|Kwiatkowski et al., 2019]] ). (The phenology calculations are based on [[#Racault--2017|Racault et al., 2017]] , using updated data.)

At latitudes &gt;40°N, temperature-linked phenology of fish reproduction with high geographic fidelity to spawning grounds (geographic spawners) is projected to change at double the rate of that for phytoplankton, which will ''likely'' cause phenological mismatches resulting in increased risk of starvation for fish larvae ( ''medium to high confidence'' ) (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-2#2.3|Section 2.3.4.2.3]] ; [[#Asch--2019|Asch et al., 2019]] ; [[#Durant--2019|Durant et al., 2019]] ; [[#Régnier--2019|Régnier et al., 2019]] ; [[#Gulev--2021|Gulev et al., 2021]] ; [[#Laurel--2021|Laurel et al., 2021]] ). Furthermore, under RCP8.5, trophic mismatch events exceeding ±30 days ( [[#Asch--2019|Asch et al., 2019]] ) leading to fish-recruitment failure are expected to increase tenfold for geographic spawners across much of the North Atlantic, North Pacific and Arctic Ocean basins ( ''low confidence'' ) ( [[#Neuheimer--2018|Neuheimer et al., 2018]] ). In contrast, temporal mismatches between fish that relocate spawning grounds in response to environmental variations (environmental spawners) and phytoplankton blooms are projected to remain shorter and less varied, suggesting that across ocean basins, range shifts by environmental spawners may increase their resilience. Nevertheless, this compensation mechanism might fail at locations where phytoplankton bloom phenology is not controlled by temperature-driven water-column stratification, leading to a possible sixfold local increase in extreme mismatches under climate change ( [[#Asch--2019|Asch et al., 2019]] ).

<div id="3.4.3.3" class="h3-container"></div>

<span id="changes-in-community-composition-and-biodiversity"></span>
==== 3.4.3.3 Changes in Community Composition and Biodiversity ====

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<div id="3.4.3.3.1" class="h4-container"></div>

<span id="evidence-of-natural-adaptive-capacity-based-on-species-responses-to-past-climate-variability"></span>
===== 3.4.3.3.1 Evidence of natural adaptive capacity based on species’ responses to past climate variability =====

<div id="h4-9-siblings" class="h4-siblings"></div>

Responses to abrupt climate change in the geological past suggest that adaptive capacity is limited for marine animals (Cross-Chapter Box PALEO in Chapter 1). Temperatures during the last Interglacial (~125 ka), which were warmer than today, led to poleward range shifts of reef corals ( ''medium confidence'' ) ( [[#Kiessling--2012|Kiessling et al., 2012]] ; [[#Jones--2019a|Jones et al., 2019a]] ). Temperature has also driven marine range shifts over multi-million-year time scales ( ''medium confidence'' ) ( [[#Gibbs--2016|Gibbs et al., 2016]] ; [[#Reddin--2018|Reddin et al., 2018]] ). Warming climates, even with low ocean-warming rates, inevitably decreased tropical marine biodiversity compared with middle latitudes ( ''high confidence'' ) ( [[#Mannion--2014|Mannion et al., 2014]] ; [[#Crame--2020|Crame, 2020]] ; [[#Yasuhara--2020|Yasuhara et al., 2020]] ; [[#Raja--2021|Raja and Kiessling, 2021]] ).

The paleorecord confirms that marine biodiversity has been vulnerable to climate warming both globally and regionally ( ''very high confidence'' ) (Cross-Chapter Box PALEO in Chapter 1; [[#Stanley--2016|Stanley, 2016]] ). In extreme cases of warming (e.g., &gt;5.2°C), marine mass extinctions occurred in the geological past, and there may be a relationship between warming magnitude and extinction toll ( ''medium confidence'' ) ( [[#Song--2021b|Song et al., 2021b]] ). A combination of warming and spreading anoxia caused marine extinctions in ancient episodes of rapid climate warming ( ''high confidence'' ) ( [[#Bond--2017|Bond and Grasby, 2017]] ; [[#Benton--2018|Benton, 2018]] ; [[#Penn--2018|Penn et al., 2018]] ; [[#Them%20II--2018|Them II et al., 2018]] ; [[#Chen--2019|Chen and Xu, 2019]] ). The role of ocean acidification in ancient extinctions is yet to be resolved ( ''low confidence'' ) ( [[#Clapham--2011|Clapham and Payne, 2011]] ; [[#Clarkson--2015|Clarkson et al., 2015]] ; [[#Jurikova--2020|Jurikova et al., 2020]] ; [[#Müller--2020|Müller et al., 2020]] ).

<div id="3.4.3.3.2" class="h4-container"></div>

<span id="observed-and-projected-changes-in-contemporary-community-structure-and-biodiversity"></span>
===== 3.4.3.3.2 Observed and projected changes in contemporary community structure and biodiversity =====

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Ocean temperature is a major driver of species richness in the global ocean at evolutionary time scales ( [[#Tittensor--2010|Tittensor et al., 2010]] ; [[#Chaudhary--2021|Chaudhary et al., 2021]] ). This, together with temperature-driven range and phenology shifts evident across taxa and ocean ecosystems (Sections 3.4.3.1, 3.4.3.2), suggests that recent ocean warming ( [[#3.2.2.1|Section 3.2.2.1]] ) should alter biodiversity at regional to global scales. Since previous assessments (Table 3.20), the most common evidence supporting these expected changes is replacement of cold-adapted species by warm-adapted species within an ecosystem as waters warm ( [[#Worm--2021|Worm and Lotze, 2021]] ). Known as tropicalisation ( [[#3.4.2.3|Section 3.4.2.3]] ), this phenomenon has been attributed to ocean warming ( ''medium to high confidence'' ) in communities as diverse as kelp, invertebrates, plankton and fish ( [[#Burrows--2019|Burrows et al., 2019]] ; [[#Flanagan--2019|Flanagan et al., 2019]] ; [[#Ajani--2020|Ajani et al., 2020]] ; [[#Villarino--2020|Villarino et al., 2020]] ; [[#Punzón--2021|Punzón et al., 2021]] ; [[#Smith--2021|Smith et al., 2021]] ).

'''Table 3.20 |''' Summary of previous IPCC assessments of community composition and biodiversity

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Pörtner--2014|Pörtner et al., 2014]] )''

|
|-
| The paleoecological record shows that global climate changes comparable in magnitudes to those projected for the 21st century under all scenarios resulted in large-scale biome shifts and changes in community composition, and that for rates projected under RCP6 and 8.5 those changes were associated with species extinctions in some groups ( ''high confidence'' ).

Loss of corals due to bleaching has a potentially critical influence on the maintenance of marine biodiversity in the tropics ( ''high confidence'' ).

| Spatial shifts of marine species due to projected warming will cause high-latitude invasions and high local-extinction rates in the tropics and semi-enclosed seas ( ''medium confidence'' ).

Species richness and fisheries catch potential are projected to increase, on average, at mid and high latitudes ( ''high confidence'' ) and decrease at tropical latitudes ( ''medium confidence'' ).

‘Shifts in the geographical distributions of marine species [...] cause changes in community composition and interactions [...]. Thereby, climate change will reassemble communities and affect biodiversity, with differences over time and between biomes and latitudes ( ''high confidence'' ).’

‘Models are currently useful for developing scenarios of directional changes in net primary productivity, species distributions, community structure, and trophic dynamics of marine ecosystems, as well as their implications for ecosystem goods and services under climate change. However, specific quantitative projections by these models remain imprecise ( ''low confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| ‘Ocean warming has contributed to observed changes in biogeography of organisms ranging from phytoplankton to marine mammals ( ''high confidence'' ), consequently changing community composition ( ''high confidence'' ), and in some cases altering interactions between organisms and ecosystem function ( ''medium confidence'' ).’

| Poleward range shifts are projected to decrease species richness in tropical oceans, counterbalanced by increases in mid- to high-latitude regions, leading to global-scale species turnover ( ''medium confidence'' on trends, ''low confidence'' on magnitude because of model uncertainties and the limited number of published model simulations). ‘The projected intensity of species turnover is lower under low-emission scenarios ( ''high confidence'' ).’

‘Projections from multiple fish species distribution models show hotspots of decrease in species richness in the Indo-Pacific region, and semi-enclosed seas such as the Red Sea and Persian Gulf ( ''medium evidence, high agreement'' ). In addition, geographic barriers, such as land, [bounding the] poleward species range edge in semi-enclosed seas or low-oxygen water in deeper waters are projected to limit range shifts, resulting in a larger relative decrease in species richness ( ''medium confidence'' ).’

‘The large variation in sensitivity between different zooplankton taxa to future conditions of warming and ocean acidification suggests elevated risk on community structure and inter-specific interactions of zooplankton in the 21st century ( ''medium confidence'' ).’

|}

At local to regional scales, tropicalisation often increases species richness where warm-water species extend their ranges to overlap with existing communities and decreases species richness where warming waters extirpate species ( ''medium to high confidence'' ) ( [[#Friedland--2020a|Friedland et al., 2020a]] ; [[#Chaudhary--2021|Chaudhary et al., 2021]] ; [[#Worm--2021|Worm and Lotze, 2021]] ). Latitudinal estimates from catalogued observations show declining species richness in equatorial waters over the past 50 years, with concomitant increases in species richness at mid-latitudes; the pattern is especially prominent in free-swimming pelagic species (Figure 3.18; [[#Chaudhary--2021|Chaudhary et al., 2021]] ). Similar patterns among marine animals have been described previously for historical warming events ( [[#Song--2020b|Song et al., 2020b]] ). Tropicalisation is associated with increased representation of herbivorous species ( [[#Vergés--2016|Vergés et al., 2016]] ; [[#Zarco-Perello--2020|Zarco-Perello et al., 2020]] ; [[#Smith--2021|Smith et al., 2021]] ), although observations and theory suggest that dietary generalism can also favour range-shifting species ( [[#Monaco--2020|Monaco et al., 2020]] ; [[#Wallingford--2020|Wallingford et al., 2020]] ).

<div id="_idContainer068" class="Figure"></div>

[[File:775d59d4d5b1b9873ed3788209234bbd IPCC_AR6_WGII_Figure_3_018.png]]

'''Figure 3.18 |''' '''Changes in the latitudinal distribution of marine species richness.'''

'''(a)''' Observed species richness for three historical periods. The observed latitudinal patterns in species richness are for a suite of taxonomic groups based on 48,661 marine species ( [[#Chaudhary--2021|Chaudhary et al., 2021]] ).

'''(b)''' Projected changes in species richness under RCP4.5 and RCP8.5 are calculated as differences by grid cell by 2100 relative to 2006. Latitudinal global median (5° moving average). (Based on Figure 1b,c in [[#García%20Molinos--2016|García Molinos et al., 2016]] .) The projected latitudinal patterns in changes in species richness under climate change are based on a numerical model that includes species-specific information across a suite of taxonomic groups, based on 12,796 marine species ( [[#García%20Molinos--2016|García Molinos et al., 2016]] ).

At the community level, the magnitude and shape of projected future biodiversity changes differ depending on which groups are considered ( ''medium confidence'' ) ( [[#Chaudhary--2021|Chaudhary et al., 2021]] ). Molecular-based richness measures indicate that the most dramatic increases in diversity relative to current conditions are expected for photosynthetic eukaryotes and copepods in the Arctic Ocean ( [[#Ibarbalz--2019|Ibarbalz et al., 2019]] ). However, component eukaryotic taxa, for example diatoms ( [[#Busseni--2020|Busseni et al., 2020]] ), are projected to lose diversity by 2100 under RCP8.5. Ecosystem models project a decline in nutrient supply that drives the disappearance of less-competitive and larger phytoplankton types, leading to extinction of up to 30% of diatom types, particularly in the Northern Hemisphere, by 2100 under RCP8.5 ( [[#Henson--2021|Henson et al., 2021]] ). Models further suggest that high latitudes are ''likely'' to encounter entirely novel phytoplankton communities by 2100 under RCP8.5 (100% change in community composition; [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ; [[#Reygondeau--2020|Reygondeau et al., 2020]] ). At the polar edges, the increased richness is projected to coincide with high species turnover and increasing dominance of smaller phytoplankton types ( [[#Henson--2021|Henson et al., 2021]] ). These imply pronounced changes to both the oceans’ ecological and biogeochemical function, as regions dominated by small phytoplankton typically support less-productive food webs ( [[#3.4.3.4|Section 3.4.3.4]] ; [[#Stock--2017|Stock et al., 2017]] ; [[#Armengol--2019|Armengol et al., 2019]] ) and sequester less particulate organic carbon (POC) in the deep ocean ( [[#3.4.3.5|Section 3.4.3.5]] ; [[#Mouw--2016|Mouw et al., 2016]] ; [[#Cram--2018|Cram et al., 2018]] ) than areas dominated by larger size classes ( ''high confidence'' ).

The profound climatic and environmental changes projected for the Arctic region by 2100 (Cross-Chapter Paper 6) are also anticipated to alter the composition of apex assemblages like marine mammals (see Box 3.2; [[#Albouy--2020|Albouy et al., 2020]] ). Under both RCP2.6 and 8.5 scenarios the most vulnerable marine mammal species will be the North Pacific right whale ( ''Eubalaena japonica'' , listed as an endangered species; [[#IUCN--2020|IUCN, 2020]] ) and the grey whale ( ''Eschrichtius robustus'' , which has critically endangered subpopulations; [[#IUCN--2020|IUCN, 2020]] ). The extinction of the most-vulnerable species will disproportionately eliminate unique and important evolutionary lineages as well as functional diversity, with consequent impacts throughout the entire marine ecosystem ( [[#3.3.4|Section 3.3.4]] ). More generally, future warming and acidification simulated in mesocosm experiments support projections of a substantial increase in biomass and productivity of primary producers and secondary consumers, but a decrease by &gt;40% of primary consumers ( [[#Nagelkerken--2020|Nagelkerken et al., 2020]] ). On longer time scales, alteration of energy flow through marine food webs may lead to ecological tipping points ( [[#Wernberg--2016|Wernberg et al., 2016]] ; [[#Harley--2017|Harley et al., 2017]] ) after which the food web collapses into shorter, bottom-heavy trophic pyramids ( ''medium confidence'' ).

Global projections anticipate a ''likely'' future reorganisation of marine life of variable magnitude, contingent on emission scenario ( [[#Beaugrand--2015|Beaugrand et al., 2015]] ; [[#Jones--2015|Jones and Cheung, 2015]] ; [[#Barton--2016|Barton et al., 2016]] ; [[#García%20Molinos--2016|García Molinos et al., 2016]] ; [[#Nagelkerken--2020|Nagelkerken et al., 2020]] ; [[#Henson--2021|Henson et al., 2021]] ). Marine organism redistributions projected under RCP4.5 and RCP8.5 include extirpations and range contractions in the tropics, strongly decreasing tropical biodiversity, and range expansions at higher latitudes, associated with increased diversity and homogenisation of marine communities (Figure 3.18b). Under continuing climate change, the projected loss of biodiversity may ultimately threaten marine ecosystem stability ( ''medium confidence'' ) ( [[#Albouy--2020|Albouy et al., 2020]] ; [[#Nagelkerken--2020|Nagelkerken et al., 2020]] ; [[#Henson--2021|Henson et al., 2021]] ), altering both the functioning and structure of marine ecosystems and thus affecting service provisioning ( ''medium confidence'' ) ( [[#3.5|Section 3.5]] ; [[#Ibarbalz--2019|Ibarbalz et al., 2019]] ; [[#Righetti--2019|Righetti et al., 2019]] ).

However, biodiversity observations remain sparse, and statistical and modelling tools can provide conflicting diversity information (e.g., [[#Righetti--2019|Righetti et al., 2019]] ; [[#Dutkiewicz--2020|Dutkiewicz et al., 2020]] ) because correlative approaches assume that the modern-day relationship between marine species distribution and environmental conditions remains the same into the future, whereas mechanistic models permit marine species to respond dynamically to changing environmental forcing. Moreover, existing global projections of future biodiversity disproportionately focus on the effects sea surface temperature ( [[#Thomas--2012|Thomas et al., 2012]] ), typically overlooking other factors such as ocean acidification, deoxygenation and nutrient availability ( [[#3.2.3|Section 3.2.3]] ), and often failing to account for natural adaptation (e.g., [[#3.3.4|Section 3.3.4]] ; see Box 3.1; [[#Barton--2016|Barton et al., 2016]] ; [[#Henson--2021|Henson et al., 2021]] ).

<div id="3.4.3.3.3" class="h4-container"></div>

<span id="abrupt-ecosystem-shifts-and-extreme-events"></span>
===== 3.4.3.3.3 Abrupt ecosystem shifts and extreme events =====

<div id="h4-11-siblings" class="h4-siblings"></div>

Climate-change-driven changes in ocean characteristics and the frequency and intensity of extreme events ( [[#3.2|Section 3.2]] ) increase the risk of persistent, rapid and abrupt ecosystem change ( ''very high confidence'' ), often referred to as ecosystem collapses or regime shifts (AR6 WGI Chapter 9; [[#Collins--2019a|Collins et al., 2019a]] ; [[#Canadell--2021|Canadell and Jackson, 2021]] ; [[#Ma--2021|Ma et al., 2021]] ). Such abrupt changes include altering ecosystem structure, function and biodiversity outside the range of natural fluctuations ( [[#Collins--2019a|Collins et al., 2019a]] ; [[#Canadell--2021|Canadell and Jackson, 2021]] ). They can involve mass-mortality events and ‘tipping points’ or ‘critical transitions’, where strong positive feedbacks within an ecosystem lead to self-sustaining change (Figure 3.19a; [[#Scheffer--2012|Scheffer et al., 2012]] ; [[#Möllmann--2015|Möllmann et al., 2015]] ; [[#Biggs--2018|Biggs et al., 2018]] ). Abrupt ecosystem shifts have been observed in both large open-ocean ecosystems and coastal ecosystems ( [[#3.4.2|Section 3.4.2]] ), with dramatic social consequences through significant loss of diverse ecosystem services ( ''high confidence'' ) ( [[#3.5|Section 3.5]] ; [[#Biggs--2018|Biggs et al., 2018]] ; [[#Pinsky--2018|Pinsky et al., 2018]] ; [[#Beaugrand--2019|Beaugrand et al., 2019]] ; [[#Collins--2019a|Collins et al., 2019a]] ; [[#Filbee-Dexter--2020b|Filbee-Dexter et al., 2020b]] ; [[#Huntington--2020|Huntington et al., 2020]] ; [[#Trisos--2020|Trisos et al., 2020]] ; [[#Turner--2020b|Turner et al., 2020b]] ; [[#Canadell--2021|Canadell and Jackson, 2021]] ; [[#Ma--2021|Ma et al., 2021]] ; [[#Ruthrof--2021|Ruthrof et al., 2021]] ). A summary of previous assessments of abrupt ecosystem shifts and extreme events is provided in Table 3.21.

'''Table 3.21 |''' Summary of previous IPCC assessments of observed and projected abrupt ecosystem shifts and extreme events

{| class="wikitable"
|-
! Observations

! Projections

|-
| ''AR5 ( [[#Wong--2014|Wong et al., 2014]] )''

|
|-
| Observations of abrupt ecosystem shifts and extreme events were not assessed in this report.

| ‘Warming and acidification will lead to coral bleaching, mortality, and decreased constructional ability ( ''high confidence'' ), making coral reefs the most vulnerable marine ecosystem with little scope for adaptation. Temperate seagrass and kelp ecosystems will decline with the increased frequency of heatwaves and sea temperature extremes as well as through the impact of invasive subtropical species ( ''high confidence'' ).’

|-
|
|-
| ''SROCC ( [[#Collins--2019a|Collins et al., 2019a]] )''

|
|-
| ‘Marine heatwaves (MHWs), periods of extremely high ocean temperatures, have negatively impacted marine organisms and ecosystems in all ocean basins over the last two decades, including critical foundation species such as corals, seagrasses and kelps ( ''very high confidence'' ).’

| ‘Marine heatwaves are projected to further increase in frequency, duration, spatial extent and intensity (maximum temperature) ( ''very high confidence'' ). Climate models project increases in the frequency of marine heatwaves by 2081–2100, relative to 1850–1900, by approximately 50 times under RCP8.5 and 20 times under RCP2.6 ( ''medium confidence'' ).’

‘Extreme El Niño and La Niña events are projected to ''likely'' increase in frequency in the 21st century and to ''likely'' intensify existing hazards, with drier or wetter responses in several regions across the globe. Extreme El Niño events are projected to occur about twice as often under both RCP2.6 and RCP8.5 in the 21st century when compared to the 20th century ( ''medium confidence'' ).’

‘Limiting global warming would reduce the risk of impacts of MHWs, but critical thresholds for some ecosystems (e.g., kelp forests, coral reefs) will be reached at relatively low levels of future global warming ( ''high confidence'' ).’

|}

<div id="_idContainer077" class="Figure"></div>

[[File:8606e2823dc86adf18dafb7ba38045b4 IPCC_AR6_WGII_Figure_3_019.png]]

'''Figure 3.19 |''' '''Observed ecological regime shifts and their drivers in the oceans.'''

'''(a)''' A conceptual representation of ecosystem resilience and regime shifts. Shift from Regime 1 to Regime 2 can be triggered by either a large shock (i.e., an abrupt environmental transition) or gradual internal or external change that erodes the dominant balancing feedbacks, reducing ecosystem resilience (indicated by the shallower dotted line, relative to the deeper ‘valley’ reflecting higher resilience). (Based on [[#Biggs--2018|Biggs et al., 2018]] ).

'''(b)''' The sum of the magnitude and extent of the abrupt community shifts that has been estimated at each geographic cell in the global ocean during 1960–2014, calculated as the ratio of the amplitude of the change in a particular year to the average magnitude of the change over the entire time series (thus, is dimensionless). (Based on [[#Beaugrand--2019|Beaugrand et al., 2019]] ).

Abrupt ecosystem shifts are associated with large-scale patterns of climate variability ( [[#Alheit--2019|Alheit et al., 2019]] ; [[#Beaugrand--2019|Beaugrand et al., 2019]] ; [[#Lehodey--2020|Lehodey et al., 2020]] ), some of which are projected to intensify with climate change ( ''medium confidence'' ) (WGI AR6 Chapter 1; [[#Wang--2017a|Wang et al., 2017a]] ; [[#Collins--2019a|Collins et al., 2019a]] ; [[#Chen--2021|Chen et al., 2021]] ). Over the past 60 years, abrupt ecosystem shifts have generally followed El Niño/Southern Oscillation events of any strength, but some periods had geographically limited ecological shifts (~0.25% of the global ocean in 1984–1987) and others more extensive shifts (14% of the global ocean in 2012–2015) ( ''medium confidence'' ) (Figure 3.19b; [[#Beaugrand--2019|Beaugrand et al., 2019]] ). Typically, interacting drivers, such as eutrophication and overharvest, reduce ecosystem resilience to climate extremes (e.g., MHWs, cyclones) or gradual warming, and hence promote ecosystem shifts ( ''high confidence'' ) (Figure 3.19a; [[#Rocha--2015|Rocha et al., 2015]] ; [[#Biggs--2018|Biggs et al., 2018]] ; [[#Babcock--2019|Babcock et al., 2019]] ; [[#Turner--2020b|Turner et al., 2020b]] ; [[#Bergstrom--2021|Bergstrom et al., 2021]] ; [[#Canadell--2021|Canadell and Jackson, 2021]] ; [[#Tait--2021|Tait et al., 2021]] ). Also, shifts in different ecosystems may be connected through common drivers or through cascading effects ( ''medium confidence'' ) ( [[#Rocha--2018a|Rocha et al., 2018a]] ).

Recent MHWs ( [[#3.2.2.1|Section 3.2.2.1]] ) have caused major ecosystem shifts and mass mortality in oceanic and coastal ecosystems, including corals, kelp forests and seagrass meadows (Sections 3.4.2.1, 3.4.2.3, 3.4.2.5, 3.4.2.6, 3.4.2.10; Cross-Chapter Box MOVING SPECIES in Chapter 5; Cross-Chapter Box EXTREMES in Chapter 2), with dramatic declines in species foundational for habitat formation or trophic flow, biodiversity declines, and biogeographic shifts in fish stocks ( ''very high confidence'' ) (Table 3.15; Cross-Chapter Box MOVING SPECIES in Chapter 5; [[#Canadell--2021|Canadell and Jackson, 2021]] ). Three major bleaching episodes on Australia’s Great Barrier Reef in 5 years corresponded with extreme temperatures in 2016, 2017 and 2020 ( [[#Pratchett--2021|Pratchett et al., 2021]] ). Between 1981 and 2017, MHWs have increased more than 20-fold due to anthropogenic climate change ( [[#3.2.2.1|Section 3.2.2.1]] ; WGI AR6 Chapter 9; [[#Laufkötter--2020|Laufkötter et al., 2020]] ; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ), increasing the risk of abrupt ecosystem shifts ( ''high confidence'' ) (Figure 3.19a; Cross-Chapter Box EXTREMES in Chapter 2; [[#van%20der%20Bolt--2018|van der Bolt et al., 2018]] ; [[#Garrabou--2021|Garrabou et al., 2021]] ; [[#Wernberg--2021|Wernberg, 2021]] ).

Ecosystems can recover from abrupt shifts (e.g., [[#Babcock--2019|Babcock et al., 2019]] ; [[#Christie--2019|Christie et al., 2019]] ; [[#Medrano--2020|Medrano et al., 2020]] ). However, where climate change is a dominant driver, ecosystem collapses increasingly cause permanent transitions ( ''high confidence'' ), although the extents of such transitions depend on the emission scenario ( [[#Trisos--2020|Trisos et al., 2020]] ; [[#Garrabou--2021|Garrabou et al., 2021]] ; [[#Klein--2021|Klein et al., 2021]] ; [[#Pratchett--2021|Pratchett et al., 2021]] ; [[#Wernberg--2021|Wernberg, 2021]] ). Over the coming decades, MHWs are projected to ''very likely'' become more frequent under all emission scenarios ( [[#3.2|Section 3.2]] ; WGI AR6 Chapter 9; [[#Fox-Kemper--2021|Fox-Kemper et al., 2021]] ), with intensities and rates too high for recovery of degraded foundational species, habitats or biodiversity ( ''medium confidence'' ) ( [[#Babcock--2019|Babcock et al., 2019]] ; [[#Garrabou--2021|Garrabou et al., 2021]] ; [[#Klein--2021|Klein et al., 2021]] ; [[#Serrano--2021|Serrano et al., 2021]] ; [[#Wernberg--2021|Wernberg, 2021]] ). Emission pathways that result in temperature overshoot above 1.5 o C will increase the risks of abrupt and irreversible shifts in coral reefs and other vulnerable ecosystems ( [[#3.4.4|Section 3.4.4]] ).

<div id="3.4.3.3.4" class="h4-container"></div>

<span id="time-of-emergence-species-exposure-to-altered-environments"></span>
===== 3.4.3.3.4 Time of emergence: species exposure to altered environments =====

<div id="h4-12-siblings" class="h4-siblings"></div>

Since SROCC, more studies have assessed the time of emergence for climate-induced drivers ( [[#3.2.3|Section 3.2.3]] ) and the ecosystem attributes through which the impacts manifest. However, as in previous assessments (Table 3.22), the time of emergence for a given driver or ecosystem attribute depends on the reference period, the definition of the signal emergence threshold and the spatio-temporal scales considered (see Box 5.1 in SROCC; [[#Kirtman--2013|Kirtman et al., 2013]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

'''Table 3.22 |''' Conclusions from previous IPCC assessments about projected time of emergence on coastal, ocean and deep-sea systems

{| class="wikitable"
|-
! Oceanic systems and chapter subsection

! Projections

|-
| Coastal ( [[#3.4.2|Section 3.4.2]] )

| ‘Multiple [climate-impact drivers] will emerge [...] in the 21st century under RCP8.5, while the time of emergence will be later and with less [climatic hazards] under RCP2.6. [Non-climate] impacts such as eutrophication add to, and in some cases, exacerbate these large-scale slow climate drivers beyond biological thresholds at local scale (e.g., deoxygenation)’ ( [[IPCC:Wg2:Chapter:Chapter-5#5.3|Section 5.3.7]] in SROCC; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

|-
| Epipelagic ( [[#3.4.3|Section 3.4.3]] )

| ‘Observed range shifts in response to climate change in some regions such as the north Atlantic are strongly influenced by warming due to both multi-decadal [climate change and] variability, suggesting that there is a longer time of emergence of range shifts from natural variability and a need for longer biological time series for robust attribution’ ( [[IPCC:Wg2:Chapter:Chapter-5#5.2|Section 5.2.3.1.1]] in SROCC; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

|-
| Open ocean ( [[#3.4.3|Section 3.4.3]] )

| ‘[The timing] for five primary drivers of marine ecosystem change (surface warming and acidification, oxygen loss, nitrate concentration and net primary production change) are all prior to 2100 for over 60% of the ocean area under RCP8.5 and over 30% under RCP2.6 ( ''very likely'' )’ (Figure 1 in Box 5.1 in SROCC, Box 5.1 in SROCC, Executive Summary in SROCC Chapter 5; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

‘Anthropogenic signals are expected to remain detectable over large parts of the ocean, even for the RCP2.6 scenario for pH and SST, but are ''likely'' [to be less conspicuous] for nutrients and NPP [net primary production] in the 21st century. For example, for the open ocean, the anthropogenic pH signal in Earth System Models’ (ESM) historical simulations is ''very likely'' to have emerged for three-quarters of the ocean prior to 1950, and it is ''very likely'' over 95% of the ocean has already been affected, with little discernible difference between scenarios’ (Executive Summary in SROCC Chapter 5, Box 5.1 in SROCC; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). ‘The climate signal of oxygen loss will ''very likely'' emerge by 2050 with a ''very likely'' range of 59–80% by 2031–2050 and rising with a ''very likely'' range of 79–91% of the ocean area by 2081–2100 (RCP8.5 emissions scenario). The emergence of oxygen loss is smaller in area for the RCP2.6 scenario in the 21st century and by 2090 the [area where emergence is evident is declining].’ It has also been shown that signatures of altered oxygen solubility or utilisation may emerge earlier than for oxygen levels (Executive Summary in SROCC Chapter 5, Box 5.1 in SROCC; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

|-
| Deep sea (Box 3.3)

| ‘Emergence of risk is expected to occur later at around the mid-21st century under RCP8.5 for abyssal plain and chemosynthetic ecosystems (vents and seeps)’ ( [[IPCC:Wg2:Chapter:Chapter-5#5.2|Section 5.2.5]] in SROCC; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). ‘All deep seafloor ecosystems are expected to be subject to at least moderate risk under RCP8.5 by the end of the 21st century, with cold water corals undergoing a transition from moderate to high risk below 3°C’ (SM5.2 in SROCC; [[#Bindoff--2019b|Bindoff et al., 2019b]] ).

|}

Anthropogenically driven changes in chlorophyll- ''a'' concentrations across an ensemble of 30 ESMs are expected to exceed natural variability under RCP8.5 by 2100 in ~65–80% of the global oceans, when the natural variability is calculated using the ensemble’s standard deviation ( [[#Schlunegger--2020|Schlunegger et al., 2020]] ); however, if two standard deviations are used, then significant trends in chlorophyll- ''a'' concentration are expected under RCP8.5 across ~31% of the global oceans by 2100 ( [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ). In contrast, the anthropogenic signal in phytoplankton community structure, which has a lower natural variability, will emerge under RCP8.5 across 63% of the ocean by 2100 when two standard deviations are used ( ''limited evidence'' ) ( [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ).

The time of emergence of climate impacts on ecosystems will be modulated jointly by species-specific adaptation potential ( [[#3.3.4|Section 3.3.4]] ; [[#Jones--2018|Jones and Cheung, 2018]] ; [[#Collins--2020|Collins et al., 2020]] ; [[#Gamliel--2020|Gamliel et al., 2020]] ; [[#Miller--2020a|Miller et al., 2020a]] ), speed of range shifts and spatial reorganisation ( ''high confidence'' ) (Sections 3.3, 3.4.2, 3.4.3). These ecosystem responses complicate projections of the time of emergence of environmental properties that impact biogeochemical cycling ( [[#Schlunegger--2019|Schlunegger et al., 2019]] ; [[#Schlunegger--2020|Schlunegger et al., 2020]] ; [[#Wrightson--2020|Wrightson and Tagliabue, 2020]] ), ecosystem structure and biodiversity (Figure 3.20a,c; [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ; [[#Trisos--2020|Trisos et al., 2020]] ), and higher trophic levels, including fisheries targets ( [[#Cheung--2020|Cheung and Frölicher, 2020]] ). Better accounting for multiple interacting factors in ESMs (see Box 3.1) will provide insight into how marine ecosystems will respond to future climate ( ''high confidence'' ).

The time of emergence of ecosystem responses supports planning for specific time-bound actions to reduce risks to ecosystems ( [[#3.6.3.2|Section 3.6.3.2.1]] ; [[#Bruno--2018|Bruno et al., 2018]] ; [[#Trisos--2020|Trisos et al., 2020]] ). Although under RCP8.5, climate refugia from SST after 2050 are primarily in the Southern Ocean in tropical waters, these refugia are mainly from deoxygenation ( [[#Bruno--2018|Bruno et al., 2018]] ). Marine assemblages in these places will be exposed to unprecedented temperatures after 2050, peaking in 2075 (Figure 3.20a,b; [[#Trisos--2020|Trisos et al., 2020]] ). In contrast, changes in phytoplankton community structure will emerge earlier, primarily in the Pacific Ocean subtropics and through much of the North Atlantic Ocean (Figure 3.20c,d; [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ). Under RCP8.5, changes in phytoplankton community structure and, to a lesser extent, exposure of marine species to unprecedented temperatures, will emerge earlier in marine protected areas (MPAs), covering ~7.7% of the global oceans ( [[#3.6.2.3|Section 3.6.2.3.2.1]] ; UNEP-WCMC and [[#IUCN--2020|IUCN, 2020]] ; [[#UNEP-WCMC%20and%20IUCN--2021|UNEP-WCMC and IUCN, 2021]] ) as compared with non-MPAs (Figure 3.20b,d). Such assessment can support planning for future MPA placement and extent. Because MPAs can serve as refugia from non-climate drivers (Sections 3.6.2.3, 3.6.3.2.1), they facilitate opportunities for adaptation among marine species and communities in coastal oceans ( [[#3.4.2|Section 3.4.2]] ).

<div id="_idContainer083" class="Figure"></div>

[[File:8f6c3fd05dd924e5d2f20a2442625694 IPCC_AR6_WGII_Figure_3_020.png]]

'''Figure 3.20 |''' '''Time of exposure to altered environments.'''

'''(a)''' Simulated spatial variation in the time of exposure of marine species to unprecedented temperatures under RCP8.5. Time of exposure is quantified as the median year after which local species are projected to encounter temperatures warmer than the historical maximum within their full geographic range for a period of at least 5 years. This estimate is based on 22 Coupled Model Intercomparison Project 5 (CMIP5) models, and is drawn from data presented by Trisos et al. (2020). Only regions that have times of emergence by 2100 are shown.

'''(b)''' The distribution in the time of exposure to unprecedented temperatures within marine assemblages ( [[#Trisos--2020|Trisos et al., 2020]] ) under RCP8.5 in marine protected areas (in turquoise) and in non-marine protected areas (in purple). Values were calculated after regridding to equal-area 0.5° hexagons.

'''(c)''' Time of emergence for phytoplankton community-structure changes (based on a proxy–ecosystem-model reflectance at 500 nm) under RCP8.5. Only regions with statistically significant ( ''p'' &lt; 0.05) trends that are presently largely ice free and have times of emergence by 2100 are shown. (Based on the results of one numerical model from [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ).

'''(d)''' The distribution in the time of emergence for changes in phytoplankton community structure (same proxy as in panel c) ( [[#Dutkiewicz--2019|Dutkiewicz et al., 2019]] ) under RCP8.5 in marine protected areas (in turquoise) and in non-marine protected areas (in purple). Values were calculated after regridding to equal-area 0.5° hexagons.

<div id="3.4.3.4" class="h3-container"></div>

<span id="biomass"></span>
==== 3.4.3.4 Biomass ====

<div id="h3-26-siblings" class="h3-siblings"></div>

<div id="3.4.3.4.1" class="h4-container"></div>

<span id="observed-changes-1"></span>
===== 3.4.3.4.1 Observed changes =====

<div id="h4-13-siblings" class="h4-siblings"></div>

Observed changes in biomass in the global ocean, beyond those for phytoplankton (Table 3.23), have not routinely been attributed to climate-induced drivers, but rather to the compound effects of multiple drivers, especially fishing ( [[#Christensen--2014|Christensen et al., 2014]] ; [[#Palomares--2020|Palomares et al., 2020]] ). We therefore do not assess observed changes in ocean biomass here.

'''Table 3.23 |''' Summary of previous IPCC assessments of changes in open ocean and deep-sea biomass

{| class="wikitable"
|-
! Measure

! Observations

! Projections

|-
| ''AR5 WGII ( [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Pörtner--2014|Pörtner et al., 2014]] )''

|
|-
| Chlorophyll- ''a'' /phytoplankton biomass

| ‘Phytoplankton biomass: the approximately 15-year archived time series of satellite-chlorophyll (as a proxy of phytoplankton biomass) is too short to reveal trends over time and their causes’ (WGII AR5 [[IPCC:Wg2:Chapter:Chapter-6#6.1.2|Section 6.1.2]] ; [[#Pörtner--2014|Pörtner et al., 2014]] ).

‘Chlorophyll concentrations measured by satellites have decreased in the subtropical gyres of the North Pacific, Indian and North Atlantic oceans by 9, 12 and 11%, respectively, over and above the inherent seasonal and interannual variability from 1998 to 2010 ( ''high confidence'' ; ''p'' ≤ 0.05). Significant warming over this period has resulted in increased water-column stratification, reduced mixed-layer depth and possibly decreases in nutrient availability and ecosystem productivity ( ''limited evidence, medium agreement'' ). The short time frame of these studies against well-established patterns of long-term variability leads to the conclusion that these changes are about as ''likely'' as not due to climate change’ (WGII AR5 Chapter 30; [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ).

| ‘Owing to contradictory observations there is currently uncertainty about the future trends of major upwelling systems and how their drivers (enhanced productivity, acidification and hypoxia) will shape ecosystem characteristics ( ''low confidence'' )’ (WGII AR5 [[IPCC:Wg2:Chapter:Chapter-6|Chapter 6]] Executive Summary; [[#Pörtner--2014|Pörtner et al., 2014]] ).

|-
| Animal biomass

| Observed changes in animal biomass were not assessed in this report.

| ‘The climate-change-induced intensification of ocean upwelling in some eastern boundary systems, as observed in the last decades, may lead to regional cooling, rather than warming, of surface waters and cause enhanced productivity ( ''medium confidence'' ), but also enhanced hypoxia, acidification and associated biomass reduction in fish and invertebrate stocks’ (WGII AR5 [[IPCC:Wg2:Chapter:Chapter-6|Chapter 6]] Executive Summary; [[#Pörtner--2014|Pörtner et al., 2014]] ).

|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Chlorophyll- ''a'' /phytoplankton biomass

| ‘[Changes reported] in overall open-ocean chlorophyll levels (a proxy of phytoplankton biomass) of less than ±1% yr –1 for individual time periods. Regionally, trends of ±4% between 2002 and 2015 for different regions are found when different satellite products are merged, with increases at high latitudes and moderate decreases at low latitudes’ (SROCC [[IPCC:Wg2:Chapter:Chapter-5#5.2.2|Section 5.2.2.6]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ).

| Projected changes in chlorophyll- ''a'' /phytoplankton biomass were not assessed in this report.

|-
| Animal biomass

| Observed changes in open-ocean and deep-sea biomass were not assessed in this report.

| ‘There is ''high agreement'' in model projections that global zooplankton biomass will ''very likely'' reduce in the 21st century, with projected decline under RCP8.5 almost doubled that of RCP2.6 ( ''very likely'' ). However, the strong dependence of the projected declines on phytoplankton production ( ''low confidence'' ) and simplification in representation of the zooplankton communities and food web render their projections having ''low confidence'' .’

The global biomass of marine animals, including those that contribute to fisheries, is projected to decrease by 4.3 ± 2.0% (95% confidence interval) and 15.0 ± 5.9% under RCP2.6 and RCP8.5, respectively, by 2080–2099 relative to 1986–2005, while the decrease is around 4.9% by 2031–2050 across all RCP2.6 and RCP8.5 ( ''very likely'' ). Regionally, total animal biomass decreases largely in tropical and mid-latitude oceans ( ''very likely'' ).

‘Projected decrease in upper-ocean export of organic carbon to the deep seafloor is expected to result in a loss of animal biomass on the deep seafloor by 5.2–17.6% by 2090–2100 compared to the present (2006–2015) under RCP8.5 with regional variations ( ''medium confidence'' ). Some increases are projected in the polar regions, due to enhanced stratification in the surface ocean, reduced primary production and shifts towards small phytoplankton ( ''medium confidence'' ). The projected impacts on biomass in the abyssal seafloor are larger under RCP8.5 than RCP4.5 ( ''very likely'' ).’

|-
| ''WGI AR6 [[IPCC:Wg2:Chapter:Chapter-2|Chapter 2]] ( [[#Gulev--2021|Gulev et al., 2021]] )''

|
|-
| Chlorophyll- ''a'' /phytoplankton biomass

| The multi-sensor time series of chlorophyll- ''a'' concentration has been updated to cover two decades (1998–2018).

‘Global trends in chlorophyll- ''a'' for the last two decades are insignificant over large areas of the global oceans, but some regions exhibit significant trends, with positive trends in parts of the Arctic and the Antarctic waters (&gt;3% yr –1 ), and both negative and positive trends (within ±3% yr –1 ) in parts of the tropics, subtropics and temperate waters.’

‘In the last two decades, the concentration of phytoplankton at the base of the marine food web, as indexed by chlorophyll concentration, has shown weak and variable trends in low and mid-latitudes and an increase in high latitudes ( ''medium confidence'' ).’

| Projected changes in open-ocean and deep-sea biomass were not assessed in this report.

|}

<div id="3.4.3.4.2" class="h4-container"></div>

<span id="projected-changes-1"></span>
===== 3.4.3.4.2 Projected changes =====

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Based on an ensemble of CMIP5 ESMs, SROCC projected declines in global zooplankton biomass by 2100 dependent on emission scenario ( ''low confidence'' ) (Table 3.23). The new CMIP6 ESM ensemble projects a decline in global zooplankton biomass by −3.9 ± 8.2% ( ''very likely range'' ) and −9.0 ± 8.9% in the period 2081–2100 relative to 1995–2014 under SSP1-2.6 and SSP5-8.5, respectively (Figure 3.21d; [[#Kwiatkowski--2020|Kwiatkowski et al., 2020]] ), thus reinforcing the SROCC assessment albeit with greater inter-model uncertainties.

<div id="_idContainer086" class="Figure"></div>

[[File:17b6a979e794ad7f282345cd4bdd0579 IPCC_AR6_WGII_Figure_3_021.png]]

'''Figure 3.21 |''' '''Projected change in marine biomass.''' Simulated global biomass changes of (a,b,c) surface phytoplankton, (d,e,f) zooplankton, (g,h,i) animals and (j,k,l) seafloor benthos. In (a,d,g,j), the multi-model mean (solid lines) and ''very likely range'' (envelope) over 2000–2100 relative to 1995–2014, for SSP1-2.6 and SSP5-8.5. Spatial patterns of simulated change by 2090–2099 are calculated relative to 1995–2014 for (b,e,h,k) SSP1-2.6 and (c,f,i,l) SSP5-8.5. Confidence intervals can be affected by the number of models available for the Coupled Model Intercomparison Project 6 (CMIP6) scenarios and for different variables. Only one model was available for panel (j), so no confidence interval is calculated. For panels (a–f), the ensemble projections of global changes in phytoplankton and zooplankton biomasses updated based on Kwiatkowski et al. (2019) include, under SSP1-2.6 and SSP5-8.5, respectively, a total of nine and ten CMIP6 Earth system models (ESMs). For panels (b,c,e,f), unhatched areas represent regions where at least 80% of models agree on the sign of biomass anomaly. For panels (g,h,i), the ensemble projections of global changes in total animal biomass updated based on [[#Tittensor--2021|Tittensor et al. (2021)]] include six to nine published global fisheries and marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project ( [[#Tittensor--2018|Tittensor et al., 2018]] ; [[#Tittensor--2021|Tittensor et al., 2021]] ), forced with standardised outputs from two CMIP6 ESMs. For panels (j,k,l), globally integrated changes in total seafloor biomass have been updated based on [[#Yool--2017|Yool et al. (2017)]] with one benthic model ( [[#Kelly-Gerreyn--2014|Kelly-Gerreyn et al., 2014]] ) forced with the CMIP6 ESM UKESM-1.

Using an ensemble of global-scale marine ecosystem and fisheries models (Fish-MIP) ( [[#Tittensor--2018|Tittensor et al., 2018]] ) with the CMIP5 ESM ensemble, SROCC concludes that projected ocean warming and decreased phytoplankton production and biomass will reduce global marine animal biomass during the 21st century ( ''medium confidence'' ). The simulated declines (with ''very likely range'' ) are −3.5 ± 4.8% and −14.0 ± 14.6% under RCP2.6 and RCP8.5, respectively, by 2080–2099 relative to 1995–2014 (SROCC [[IPCC:Wg2:Chapter:Chapter-5#5.2|Section 5.2.3]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Lotze--2019|Lotze et al., 2019]] ) [[#footnote-001|6]] . Updated Fish-MIP simulations with CMIP6 (Figure 3.21g,h,i) confirm the projected decline in total marine animal biomass in the 21st century ( [[#Tittensor--2021|Tittensor et al., 2021]] ). The simulated declines (with ''very likely range'' ) are −5.7 ± 4.1% and −15.5 ± 8.5% under SSP1-2.6 and SSP5-8.5, respectively, by 2080–2099 relative to 1995–2014 (Figure 3.21g), showing greater declines and lower inter-model uncertainties ( [[#Tittensor--2021|Tittensor et al., 2021]] ). These declines result from combined warming and decreased primary production (with ''low confidence'' in future changes in primary production; [[#3.4.3.5|Section 3.4.3.5]] ) and are amplified at each trophic level within all ESM and marine ecosystem model projections across all scenarios ( ''medium confidence'' ) ( [[#Kwiatkowski--2019|Kwiatkowski et al., 2019]] ; [[#Lotze--2019|Lotze et al., 2019]] ; [[#Tittensor--2021|Tittensor et al., 2021]] ). However, there is ''limited evidence'' about how underlying food-web mechanisms amplify the climate signal from primary producers to higher trophic levels, and several putative mechanisms have been proposed ( [[#3.4.4|Section 3.4.4.2.2]] ; [[#Chust--2014a|Chust et al., 2014a]] ; [[#Stock--2014|Stock et al., 2014]] ; [[#Kwiatkowski--2019|Kwiatkowski et al., 2019]] ; [[#Lotze--2019|Lotze et al., 2019]] ; [[#Heneghan--2021|Heneghan et al., 2021]] ). As assessed in SROCC, the biomass projections contain considerable regional variation with declines in tropical to temperate regions and strong increases in total animal biomass are projected in polar regions under high-emission scenarios, with climate-change effects that are spatially similar but less pronounced under lower-emission scenarios (Figure 3.21b,c,e,f,h,i; [[#Tai--2019|Tai et al., 2019]] ; [[#Tittensor--2021|Tittensor et al., 2021]] ).

SROCC assessed that reduced food supply to the deep sea will drive a reduction in abyssal seafloor biota by 2100 for RCP8.5 (Table 3.23). Simulations from one size-resolved benthic biomass model coupled to an ocean-biogeochemistry model forced with the CMIP5 ESM HadGEM2-ES ( [[#Yool--2017|Yool et al., 2017]] ) project a decline in the globally integrated total seafloor biomass of −1.1 and −17.6% by 2100 under RCP2.6 and RCP8.5, respectively ( ''limited evidence, high agreement'' ). In waters shallower than 100 m, total benthic biomass is projected to increase by 3.2% on average by 2100 under RCP8.5, primarily driven by warming-increased growth rates ( [[#Yool--2013|Yool et al., 2013]] ), while at depths &gt;2000 m (representing 83% of the ocean seafloor), declines of −32% arise from climate-driven decreases in surface primary production and POC flux to the seafloor ( [[#Yool--2013|Yool et al., 2013]] ; [[#Kelly-Gerreyn--2014|Kelly-Gerreyn et al., 2014]] ; [[#Yool--2015|Yool et al., 2015]] ; [[#Yool--2017|Yool et al., 2017]] ). These patterns are qualitatively similar under RCP2.6, except in the Pacific and Indian Ocean basins, where some increased total seafloor biomass is projected ( [[#Yool--2013|Yool et al., 2013]] ). Updated simulations with the same benthic biomass model ( [[#Kelly-Gerreyn--2014|Kelly-Gerreyn et al., 2014]] ) forced with the CMIP6 ESM UKESM-1 project declines in total seafloor biomass of −9.8 and −13.0% by 2081–2100 relative to 1995–2014 for SSP1-2.6 and SSP5-8.5, respectively (Figure 3.21j,k,l). These projected changes in benthic biomass are based on ''limited evidence'' . Development of ensemble projections forced with a range of ESMs and a benthic model that considers the ecological roles of temperature ( [[#Hunt--2006|Hunt and Roy, 2006]] ; [[#Reuman--2014|Reuman et al., 2014]] ), oxygen ( [[#Mosch--2012|Mosch et al., 2012]] ) and ocean acidification ( [[#Andersson--2011|Andersson et al., 2011]] ) will provide opportunities to better quantify uncertainty in projected declines in total seafloor biomass under climate change.

Overall, ocean warming and decreased phytoplankton production and biomass will drive a global decline in biomass for zooplankton ( ''low confidence'' ), marine animals ( ''medium confidence'' ) and seafloor benthos ( ''low confidence'' ), with regional differences in the direction and magnitude of changes ( ''high confidence'' ). There is increasing evidence that responses will amplify throughout the food web and at ocean depths, with relatively modest changes in surface primary producers translating into substantial changes at higher trophic levels and for deep-water benthic communities ( ''medium confidence'' ).

<div id="3.4.3.5" class="h3-container"></div>

<span id="changes-in-primary-production-and-biological-carbon-export-flux"></span>
==== 3.4.3.5 Changes in Primary Production and Biological Carbon Export Flux ====

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<div id="3.4.3.5.1" class="h4-container"></div>

<span id="observed-changes-in-primary-production"></span>
===== 3.4.3.5.1 Observed changes in primary production =====

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Analyses of satellite-derived primary production over the past two decades (1998–2018) showed generally weak and negative trends (up to −3.0%) at low and mid latitudes ( [[#Kulk--2020|Kulk et al., 2020]] ). In contrast, positive trends occurred in large areas of the South Atlantic and South Pacific Oceans, as well as in polar and coastal (upwelling) regions (up to +4.5%; Cross-Chapter Paper 6; [[#Kulk--2020|Kulk et al., 2020]] ). Data-assimilating ocean biogeochemical models estimate a global decline in primary production of 2.1% per decade in the period 1998–2015, driven by the shoaling mixed layer and decreasing nitrate concentrations ( [[#Gregg--2019|Gregg and Rousseaux, 2019]] ). This is consistent with previous assessments that identified ocean warming and increased stratification as the main drivers ( ''high confidence'' ) affecting the regional variability in primary production Bindoff et al. (2019). However, as noted in SROCC and WGI AR6 [[IPCC:Wg2:Chapter:Chapter-2|Chapter 2]] (Table 3.24; [[#Gulev--2021|Gulev et al., 2021]] ), observed interannual changes in primary production on global and regional scales are nonlinear and largely influenced by natural temporal variability, providing ''low confidence'' in the trends.

'''Table 3.24 |''' Summary of previous IPCC assessments of ocean primary production and carbon export flux

{| class="wikitable"
|-
! Process

! Observed impacts

! Projected impacts

|-
| ''SROCC ( [[#Bindoff--2019a|Bindoff et al., 2019a]] )''

|
|-
| Open-ocean

primary production

| ‘Past open-ocean productivity trends, including those determined by satellites, [are appraised with ''low confidence'' ] due to newly identified region-specific drivers of microbial growth and the lack of corroborating ''in situ'' time series datasets.’

| ‘Net primary productivity (NPP) is ''very likely'' to decline by 4–11% by 2081–2100, relative to 2006–2015, across CMIP5 models for RCP8.5, but there is ''low confidence'' for this estimate due to the ''medium agreement'' among models and the ''limited evidence'' from observations. The tropical ocean NPP will ''very likely'' to decline by 7–16% for RCP8.5, with ''medium confidence'' as there are improved constraints from historical variability in this region.’

|-
| Open-ocean carbon export

| ‘Analyses of long-term trends in primary production and particle export production, as well as model simulations, reveal that increasing temperatures, leading to enhanced stratification and nutrient limitation, will have the greatest influence on decreasing the flux of particulate organic carbon (POC) to the deep ocean. However, different lines of evidence (including observation, modelling and experimental studies) provide ''low confidence'' on the mechanistic understanding of how climate drivers affect different components of the biological pump in the epipelagic ocean, as well as changes in the efficiency and magnitude of carbon export in the deep ocean.’

| ‘The projected changes in export production can be larger than global primary production because they are affected by both, the NPP changes, but also how shifts in food-web structure modulates the ‘transfer efficiency’ of particulate organic material, which then affects the sinking speed and lability of exported particles through the ocean interior to the sea floor.’

‘As export production is a much better understood net integral of changing net nutrient supply and can be constrained by interior ocean nutrient and oxygen levels, there is ''medium confidence'' in projections for global [export production] changes [based on CMIP5 model runs].’

|-
| ''WGI AR6 Chapters 2, 5 ( [[#Canadell--2021|Canadell et al., 2021]] ; [[#Gulev--2021|Gulev et al., 2021]] )''

|
|-
| Open-ocean

primary production

| Global ocean marine primary production is estimated to be 47 ± 7.8 PgC yr –1 with ''low confidence'' because of the small number of recent studies and the insufficient length of the time series analysed. A small decrease in productivity is evident globally for the period 1998–2015, but regional changes are larger and of opposing signs ( ''low confidence'' ) (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-2#2.3|Section 2.3.4.2.2]] ; [[#Gulev--2021|Gulev et al., 2021]] ).

| ‘In CMIP5 models run under RCP8.5, [POC] export flux is projected to decline by 1–12% by 2100 ( [[#Taucher--2011|Taucher and Oschlies, 2011]] ; [[#Laufkötter--2015|Laufkötter et al., 2015]] ). Similar values are predicted in 18 CMIP6 models, with declines of 2.5–21.5% (median: −14%) [...] between 1900 and 2100 under the SSP5-8.5 scenario. The mechanisms driving these changes vary widely between models due to differences in parameterisation of particle formation, remineralisation and plankton community structure’ (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-5#5.4.4.2|Section 5.4.4.2]] ; [[#Canadell--2021|Canadell et al., 2021]] ).

|}

<div id="3.4.3.5.2" class="h4-container"></div>

<span id="projected-changes-in-primary-production"></span>
===== 3.4.3.5.2 Projected changes in primary production =====

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Across 10 CMIP5 and 13 CMIP6 ESM ensembles, global mean NPP is projected to decline by 2080–2099 relative to 2006–2015, under all RCPs and SSPs ( [[#Kwiatkowski--2020|Kwiatkowski et al., 2020]] ). However, under comparable radiative forcing, the CMIP6 multi-model mean projections of primary production declines (mean ± SD: −0.56 ± 4.12% under SSP1-2.6, and −3.00 ± 9.10% under SSP5-8.5) are less than those of previous CMIP5 models (3.42 ± 2.47% under RCP2.6, and 8.54 ± 5.88% under RCP8.5) (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-5#5.4.4.2|Section 5.4.4.2]] ; [[#Kwiatkowski--2020|Kwiatkowski et al., 2020]] ; [[#Canadell--2021|Canadell et al., 2021]] ). The inter-model uncertainty associated with CMIP6 NPP projections is larger than in CMIP5, and it is consistently larger than the scenario uncertainty. For each SSP across the CMIP6 ensemble, individual models project both increases and decreases in global primary production, reflecting a diverse suite of bottom-up and top-down ecological processes, which are variously parameterised across models ( [[#Laufkötter--2015|Laufkötter et al., 2015]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). Furthermore, accurate simulation of many of the biogeochemical tracers upon which NPP depends (e.g., the distribution of iron; [[#Tagliabue--2016|Tagliabue et al., 2016]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ) remains a significant and ongoing challenge to ESMs ( ''high confidence'' ) ( [[#Séférian--2020|Séférian et al., 2020]] ).

Regionally, multi-model mean changes in primary production show generally similar patterns of large declines in the North Atlantic and the western equatorial Pacific, while in the high latitudes, primary production consistently increases in CMIP5 and CMIP6 by 2100 (Cross-Chapter Paper 6; [[#Kwiatkowski--2020|Kwiatkowski et al., 2020]] ). In the Indian Ocean and subtropical North Pacific, which were regions of consistent NPP decline in CMIP5 projections ( [[#Bopp--2013|Bopp et al., 2013]] ), the regional declines are reduced in magnitude, less spatially extensive and are typically less robust in CMIP6. Further assessment of simultaneous changes in processes such as nutrient advection, nitrogen fixation, the microbial loop and top-down grazing pressure (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-5#5.4.4.2|Section 5.4.4.2]] ; [[#Laufkötter--2015|Laufkötter et al., 2015]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Canadell--2021|Canadell et al., 2021]] ) are required to fully understand the regional primary production response in CMIP6 ( [[#Kwiatkowski--2020|Kwiatkowski et al., 2020]] ). Given the regional variations in the estimates of primary production changes and the uncertainty in the representation of the dominant drivers, there remains ''low confidence'' in the projected global decline in NPP.

<div id="3.4.3.5.3" class="h4-container"></div>

<span id="observed-processes-driving-changes-in-global-export-flux"></span>
===== 3.4.3.5.3 Observed processes driving changes in global export flux =====

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The SROCC ''medium confidence'' assessment that warming, stratification, declines in productivity and changes in plankton community in the epipelagic zone result in reduced export of primary production to deeper layers (Table 3.24) is supported by subsequent literature ( [[#Bach--2019|Bach et al., 2019]] ; [[#Leung--2021|Leung et al., 2021]] ). Particulate organic carbon export efficiency is constrained by altered mixing and nutrient availability ( [[#Boyd--2019|Boyd et al., 2019]] ; [[#Lundgreen--2019|Lundgreen et al., 2019]] ), particle fragmentation ( [[#Briggs--2020|Briggs et al., 2020]] ) as well as viral, microbial and planktonic community structure ( [[#Fu--2016|Fu et al., 2016]] ; [[#Guidi--2016|Guidi et al., 2016]] ; [[#Flombaum--2020|Flombaum et al., 2020]] ; [[#Kaneko--2021|Kaneko et al., 2021]] ) and metabolic rates (Cavan et al., 2019). These processes are strongly interlinked, and their net effect on primary production export from the upper ocean remains difficult to quantify observationally ( [[#Boyd--2019|Boyd et al., 2019]] ). Since SROCC, there is increasing evidence that ocean deoxygenation can alter zooplankton community structure ( [[#Wishner--2018|Wishner et al., 2018]] ), zooplankton respiration rates ( [[#Cass--2014|Cass and Daly, 2014]] ; [[#Cavan--2017|Cavan et al., 2017]] ) and patterns of diel vertical migration ( [[#Aumont--2018|Aumont et al., 2018]] ), which may focus remineralisation of organic carbon at the upper margins of OMZs ( [[#3.4.3.4|Section 3.4.3.4]] on depth shifts due to OMZ; [[#Bianchi--2013|Bianchi et al., 2013]] ; [[#Archibald--2019|Archibald et al., 2019]] ).

Data on export flux from the upper ocean are limited either in coverage and consistency (ship-board sampling) or duration (sediment traps), and are subject to considerable spatial variability (as shown in satellite observations ( [[#Boyd--2019|Boyd et al., 2019]] ). As a result, trends are weak, inconsistent and often not statistically significant ( [[#Lomas--2010|Lomas et al., 2010]] ; [[#Cael--2017|Cael et al., 2017]] ; [[#Muller-Karger--2019|Muller-Karger et al., 2019]] ; [[#Xie--2019|Xie et al., 2019]] ). Deep-ocean fluxes are similarly equivocal ( [[#Smith--2018|Smith et al., 2018]] ; [[#Fischer--2019|Fischer et al., 2019]] ; [[#Fischer--2020|Fischer et al., 2020]] ). In coming years, an increasing number of Argo floats equipped with bio-optical sensors should help improve estimates of particle flux spatio-temporal variability (e.g., [[#Dall’Olmo--2016|Dall’Olmo et al., 2016]] ).

Projected changes

SROCC and WGI AR6 reported global declines in POC export flux, from −8.9 to −15.8% by 2100 relative to 2000 under RCP8.5 in CMIP5 models, and −2.5 to −21.5% (median value: −14%) between 1900 and 2100 under SSP5-8.5 in CMIP6 models (Table 3.24; WGI AR6 5.4.4.2; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Canadell--2021|Canadell et al., 2021]] ). In CMIP5 model runs, the decrease in the sinking flux of organic matter from the upper ocean into the ocean interior was strongly related to the changes in stratification that reduce net nutrient supply ( [[#Fu--2016|Fu et al., 2016]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ), especially in tropical regions, and the projections for global export production changes are reported with ''medium confidence'' . Increasing model complexity with more widespread representation of ocean biogeochemical processes between CMIP5 and CMIP6, and inclusion of more than one or two classes of phyto- and zooplankton, will provide opportunities to improve assessments of how climate-induced drivers affect different components of biological carbon pump in the epipelagic ocean, as well as changes in the efficiency and magnitude of carbon export in the deep ocean ( ''high confidence'' ) (see Box 3.3; [[#Le%20Quéré--2016|Le Quéré et al., 2016]] ; [[#Séférian--2020|Séférian et al., 2020]] ; [[#Wright--2021|Wright et al., 2021]] ).

<div id="box-3.2" class="h2-container box-container"></div>

'''Box 3.2 | Marine Birds and Mammals'''
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Marine birds (seabirds and shorebirds) and mammals include charismatic species and species that are economically, culturally and ecologically important ( [[#Sydeman--2015|Sydeman et al., 2015]] ; [[#Albouy--2020|Albouy et al., 2020]] ; [[#Pimiento--2020|Pimiento et al., 2020]] ). Their long generation times and slow population growth suggests limited evolutionary resilience to rapid climate change ( [[#3.3.4|Section 3.3.4]] ; [[#Sydeman--2015|Sydeman et al., 2015]] ; [[#Miller--2018|Miller et al., 2018]] ). According to the Red List Species Assessments of the International Union for Conservation of Nature ( [[#IUCN--2020|IUCN, 2020]] ), the greatest current hazards to these groups include human use of biological resources and areas, invasive species and pollution (see Figure Box 3.2.1; [[#Dias--2019|Dias et al., 2019]] ; [[#Lusseau--2021|Lusseau et al., 2021]] ). Impacts of climate change and severe weather are ranked among the five most-important hazards influencing 131 and 45 bird and mammal species, respectively (see Figure Box 3.2.1 for selection of species), including 24 bird and 7 mammal species that are currently listed as endangered, critically endangered or threatened. Furthermore, according to these IUCN assessments, climate change and severe weather are expected to impact an additional 122 and 18 marine bird and mammal species over the next 50–100 years, respectively (see Figure Box 3.2.1; [[#Dias--2019|Dias et al., 2019]] ).

[[File:abd6e7cedbae3d299905be104b2f8363 IPCC_AR6_WGII_Figure_3_Box_3_2_1.png]]

'''Figure Box 3.2.1 |''' '''Hazard assessment for marine birds and mammals.''' Number of (a) marine birds and (b) mammals currently impacted by different hazards (blue), and numbers of additional species expected to be exposed to these threats over the next 50–100 years (red), as assessed in the International Union for Conservation of Nature Red List ( [[#IUCN--2020|IUCN, 2020]] ). Seabird species include species in the key orders ''Sphenisciformes'' , ''Pelecaniformes, Suliformes, Anseriformes, Procellariiformes'' and ''Charadriiformes'' categorised as inhabitants of marine ecosystems ( ''n'' = 483 species, assessed in the period 2016–2019). Marine mammal species include the species reviewed by [[#Lusseau--2021|Lusseau et al. (2021)]] ( ''n'' = 136 species, assessed in the period 2008–2019).

Marine birds and mammals are vulnerable to climate-induced loss of breeding and foraging habitats such as sea ice ( [[#3.4.2.1|Section 3.4.2.1]] 2), sandy beaches ( [[#3.4.2.6|Section 3.4.2.6]] ), salt marshes ( [[#3.4.2.5|Section 3.4.2.5]] ) and seagrass beds ( ''high confidence'' ) ( [[#3.4.2.5|Section 3.4.2.5]] ; [[#Sydeman--2015|Sydeman et al., 2015]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ; [[#Ropert-Coudert--2019|Ropert-Coudert et al., 2019]] ; [[#Von%20Holle--2019|Von Holle et al., 2019]] ; [[#Albouy--2020|Albouy et al., 2020]] ; [[#Amano--2020|Amano et al., 2020]] ; [[#Bestley--2020|Bestley et al., 2020]] ; [[#Grose--2020|Grose et al., 2020]] ). With warming, shorebird population abundances decline in the tropics, ''likely'' due to heat stress and habitat loss, and increase at higher latitudes ( [[#Amano--2020|Amano et al., 2020]] ). Marine mammals dependent on sea ice habitat are particularly vulnerable to warming ( ''medium confidence'' ) ( [[#Albouy--2020|Albouy et al., 2020]] ; [[#Bestley--2020|Bestley et al., 2020]] ; [[#Lefort--2020|Lefort et al., 2020]] ), yet vulnerability can differ between populations. Ongoing sea ice loss is decreasing some polar bear populations while others remain stable, ''likely'' related to past harvesting history, regional differences in sea ice phenology and ecosystem productivity ( [[#Hamilton--2019|Hamilton and Derocher, 2019]] ; [[#Molnár--2020|Molnár et al., 2020]] ). Nevertheless, even under an intermediate emission scenario RCP4.5, increasing ice-free periods will ''likely'' reduce both recruitment and adult survival across most polar bear populations over the next four decades, threatening their existence ( ''medium confidence'' ) (see Figure Box 3.2.2; [[#Molnár--2020|Molnár et al., 2020]] ).

Climate change is affecting marine food-web dynamics ( ''high confidence'' ) (Sections 3.4.2, 3.4.3), and the vulnerability and adaptive capacity of marine birds and mammals to such changes is linked to the species’ breeding and feeding ecology. Higher-vulnerability species include central-place foragers (confined to, for example, breeding colonies fixed in space), diet and habitat specialists, and species with restricted distributions such as marine mammal populations in SES ( ''medium confidence'' ) ( [[#McMahon--2019|McMahon et al., 2019]] ; [[#Ropert-Coudert--2019|Ropert-Coudert et al., 2019]] ; [[#Albouy--2020|Albouy et al., 2020]] ; [[#Grose--2020|Grose et al., 2020]] ; [[#Sydeman--2021|Sydeman et al., 2021]] ). Surface-feeding and piscivorous marine birds appear to be more vulnerable to food-web changes than diving seabirds and planktivorous seabirds ( ''medium confidence'' ) ( [[#Sydeman--2021|Sydeman et al., 2021]] ). During the 2014–2015 Pacific heatwave, around 1 million piscivorous common murres died along a 1500 km coastal stretch in the Pacific USA due to reduced prey availability ( [[#Jones--2018b|Jones et al., 2018b]] ; [[#Piatt--2020|Piatt et al., 2020]] ). Marine birds are vulnerable to phenological shifts in food-web dynamics, as they have limited phenotypic plasticity of reproductive timing, with potentially little scope for evolutionary adaptation ( ''medium confidence'' ) ( [[#Keogan--2018|Keogan et al., 2018]] ), although changes in reproduction timing are observed in several species ( [[#3.4.4|Section 3.4.4.1]] ; [[#Sydeman--2015|Sydeman et al., 2015]] ; [[#Descamps--2019|Descamps et al., 2019]] ; [[#Sauve--2019|Sauve et al., 2019]] ). There is ''limited evidence'' of marine mammals’ capacity to adapt to shifting phenologies, but observed responses include changes in the onset of migrations, moulting and breeding ( [[#3.4.4|Section 3.4.4.1]] ; [[#Ramp--2015|Ramp et al., 2015]] ; [[#Hauser--2017|Hauser et al., 2017]] ; [[#Beltran--2019|Beltran et al., 2019]] ; [[#Bowen--2020|Bowen et al., 2020]] ; [[#Szesciorka--2020|Szesciorka et al., 2020]] ).

[[File:b63992502eb0157e86141d72a4d2831a IPCC_AR6_WGII_Figure_3_Box_3_2_2.png]]

'''Figure Box 3.2.2 |''' '''Modelled risk timelines for demographic impacts on circumpolar polar bear subpopulations, and associated confidence assessments, due to extended fasting periods with loss of sea ice.''' Years of first impact on cub recruitment (yellow), adult male survival (blue) and adult female survival (red) are shown for the (left) RCP4.5 and (right) RCP8.5. (Data from [[#Molnár--2020|Molnár et al., 2020]] ).

Increased emergence of infectious disease in mammals and birds is expected with ocean warming, due to new transmission pathways from changing species distributions, higher species densities caused by habitat loss and increased vulnerability due to environmental stress on individuals ( ''limited evidence'' ) ( [[#Sydeman--2015|Sydeman et al., 2015]] ; [[#VanWormer--2019|VanWormer et al., 2019]] ; [[#Sanderson--2020|Sanderson and Alexander, 2020]] ). Marine birds and mammals are ''likely'' to suffer from increased mortalities due to increasing frequencies of HABs, and of extreme weather, at sea, on sea ice, and in terrestrial breeding habitats ( [[#Broadwater--2018|Broadwater et al., 2018]] ; [[#Gibble--2018|Gibble and Hoover, 2018]] ; [[#Ropert-Coudert--2019|Ropert-Coudert et al., 2019]] ; [[#Grose--2020|Grose et al., 2020]] ). Also, climate-change driven distributional shifts have strengthened interactions with other anthropogenic impacts, through, for example, increasing risks of ship strikes and bycatch ( ''medium confidence'' ) (e.g., [[#Hauser--2018|Hauser et al., 2018]] ; [[#Krüger--2018|Krüger et al., 2018]] ; [[#Record--2019|Record et al., 2019]] ; [[#Santora--2020|Santora et al., 2020]] ).

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<span id="faq-3.3-are-we-approaching-so-called-tipping-points-in-the-ocean-and-what-can-we-do-about-it"></span>
=== FAQ 3.3 | Are we approaching so-called tipping points in the ocean and what can we do about it? ===

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''A tipping point is a threshold beyond which an abrupt or rapid change in a system occurs. Tipping points that have already been reached in ocean systems include the melting of sea ice in the Arctic, thermal bleaching of tropical coral reefs and the loss of kelp forests. Human-induced climate change will continue to force ecosystems into abrupt and often irreversible change, without strong mitigation and adaptation action.''

[[File:59158c48e099bf34294950c2e98d2958 IPCC_AR6_WGII_Figure_3_FAQ_3_3.png]]

'''Figure FAQ3.3.1 |''' '''Global map with examples of tipping points that have been passed in ocean systems around the world.''' Tipping points in ecological systems are linked to increasing impacts and vulnerability of dependent human communities. SES: semi-enclosed sea; EBUS: eastern boundary upwelling system; CBC; coastal boundary current.

A gradual change in water temperature or oxygen concentration can lead to a fundamental shift in the structure and/or composition of an ecosystem when a tipping point is exceeded. For example, all species have upper temperature limits below which they can thrive. In the tropics, prolonged warm temperatures can cause fatal ‘bleaching’ of tropical corals, leading reef ecosystems to degrade and become dominated by algae. In temperate regions, MHWs can kill or reduce the growth of kelp, threatening the other species that depend on the tall, canopy-forming marine plants for habitat. In the Arctic, rising temperatures are melting sea ice and reducing the available habitat for communities of ice-dependent species.

Once a tipping point is passed, the effects can be long-lasting and/or irreversible over time scales of decades or longer. An ecosystem or a population can remain in the new state, even if the driver of the change returns to previous levels. For example, once a coral reef has been affected by bleaching, it can take decades for corals to grow back, even if temperatures remain below the bleaching threshold. Crossing a tipping point can cause entire populations to collapse, causing local extinctions.

Tipping points are widespread across oceanic provinces and their ecosystems for climate variables like water temperature, oxygen concentration and acidification. Evidence suggests that ocean tipping points are being surpassed more frequently as the climate changes; scientists have estimated that abrupt shifts in communities of marine species occurred over 14% of the ocean in 2015, up from 0.25% of the ocean in the 1980s. Other human stressors to the ocean, including habitat destruction, overfishing, pollution and the spread of diseases, combine with climate change to push marine systems beyond tipping points. As an example, nutrient pollution from land together with climate change can lead to low-oxygen coastal areas referred to as ‘dead zones’.

<div id="_idContainer079" class="FAQ-Box_Header-continued"></div>

Box FAQ 3.3

Human communities can also experience tipping points that alter people’s relationships with marine ecosystem services. Indigenous Peoples and local communities may be forced to move from a particular location due to SLR, erosion or loss of marine resources. Current activities that help sustain Indigenous Peoples and their cultures may no longer be possible in the coming decades, and traditional diets or territories may have to be abandoned. These tipping points have implications for physical and mental health of marine-dependent human communities.

Adaptation solutions to the effects of ecological tipping points are rarely able to reverse their environmental impacts, and instead often require human communities to transform their livelihoods in different ways. Examples include diversifying income by shifting from fishing to tourism and relocating communities threatened by flooding to other areas to continue their livelihoods. Tipping points are being passed already in coral reefs and polar systems, and more will probably be reached in the near future given climate-change projections. Nevertheless, the chances of moving beyond additional tipping points in the future will be minimised if we reduce greenhouse gas emissions and we also act to limit other human impacts on the ocean, such as overfishing and nutrient pollution.

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<span id="reversibility-and-impacts-of-temporary-overshoot-of-1.5c-or-2c-warming"></span>
=== 3.4.4 Reversibility and Impacts of Temporary Overshoot of 1.5°C or 2°C Warming ===

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Scenarios limiting warming to the 1.5°C and 2°C limits in the Paris Agreement can involve temporarily exceeding those warming levels before declining again (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-4#4.6.2|Section 4.6.2.1]] ; [[#Lee--2021|Lee et al., 2021]] ). The effect of such ‘overshoot’ on marine and coastal ecosystems depends on the reversibility of both the response of climate-induced drivers and the response of organisms and ecosystems to the climate impact-drivers during the overshoot period. WGI AR6 assessed that temporary overshoot of a 2°C warming threshold has irreversible effects on global mean sea level and also effects on ocean heat content that persist beyond 2100 (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-4#4.6.2|Section 4.6.2.1]] ; [[#Lee--2021|Lee et al., 2021]] ). Model results indicate that sea surface temperatures ( ''high confidence'' ), Arctic sea ice ( ''high confidence'' ), surface ocean acidification ( ''very high confidence'' ) and surface ocean deoxygenation ( ''very high confidence'' ) are reversible within years to decades if net emissions reach zero or below (WGI AR6 Table 4.10; [[#Lee--2021|Lee et al., 2021]] ). Although changes in these surface ocean variables are reversible, habitat-forming ecosystems, including coral reefs and kelp forests, may undergo irreversible phase shifts with &gt;1.5°C warming (Sections 3.4.2.1, 3.4.2.3), and are thus at high risk this century in 1.5°C or 2°C scenarios involving overshoot ( [[#Tachiiri--2019|Tachiiri et al., 2019]] ). In an overshoot scenario in which CO 2 returns to 2040 levels by 2100 (SSP5-3.4-OS; [[#O’Neill--2016|O’Neill et al., 2016]] ), SST and Arctic sea ice do not fully return by 2100 to levels prior to the CO 2 peak ( ''medium confidence'' ) (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-4#4.6.2|Section 4.6.2.1]] ; [[#Lee--2021|Lee et al., 2021]] ), suggesting that reversal of marine ecological impacts from 21st century climate impacts would extend into the 22nd century or beyond ( [[#McManus--2021|McManus et al., 2021]] ). Models also indicate that global sea level rise, as well as warming, ocean acidification and deoxygenation at depth, are irreversible for centuries or longer ( ''very high confidence'' ) (WGI AR6 [[IPCC:Wg2:Chapter:Chapter-4#4.6.2|Section 4.6.2.1]] and Table 4.10; [[#Palter--2018|Palter et al., 2018]] ; [[#Li--2020c|Li et al., 2020c]] ; [[#Lee--2021|Lee et al., 2021]] ).

<div id="box-3.3" class="h2-container box-container"></div>

'''Box 3.3 | Deep-Sea Ecosystems'''
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Deep-sea ecosystems include all waters below the 200-m isobath as well as the underlying benthos, and they provide habitats for highly diversified and specialised biota, which play a key role in the cycling of carbon and other nutrients (see Figure Box 3.3.1; [[#Thurber--2014|Thurber et al., 2014]] ; [[#Middelburg--2018|Middelburg, 2018]] ; [[#Snelgrove--2018|Snelgrove et al., 2018]] ). The deep sea covers &gt;63% of Earth’s surface (Costello and Cheung, 2010) and is exposed to climate-driven changes in abyssal, intermediate and surface waters that influence sinking fluxes of particulate organic matter ( ''high confidence'' ) (see Figure Box 3.3.1; Sections 3.1, 3.2.1, 3.2.2, 3.4.3.4; WGII AR5 Section 30.5.7; SROCC Sections 5.2.3, 5.2.4; [[#Hoegh-Guldberg--2014|Hoegh-Guldberg et al., 2014]] ; [[#Bindoff--2019a|Bindoff et al., 2019a]] ). These ecosystems are also influenced by non-climate drivers, especially fisheries, oil and gas extraction ( [[#Thurber--2014|Thurber et al., 2014]] ; [[#Cordes--2016|Cordes et al., 2016]] ; [[#Zhang--2019a|Zhang et al., 2019a]] ); cable laying ( [[#United%20Nations--2021|United Nations, 2021]] ); and mineral resource exploration ( [[#Hein--2021|Hein et al., 2021]] ); with proposed large-scale deep-sea mining a potential future source of impacts ( [[#Danovaro--2018|Danovaro, 2018]] ; [[#Levin--2020|Levin et al., 2020]] ).

Ocean warming alters biological processes in deep-sea ecosystems in ways that affect deep-sea habitat, biodiversity and material processing. Enhancement of microbial respiration by warming attenuates sinking POC, which has been associated with the globally projected declines in total seafloor biomass of −9.8 and −13.0% by 2081–2100 relative to 1995–2014 under SSP1-2.6 and SSP5-8.5, respectively ( ''limited evidence'' ) ( [[#3.4.3.4|Section 3.4.3.4]] ). Additionally, climate-change-driven oxygen loss ( [[#3.2.3|Section 3.2.3.2]] ; [[#Luna--2012|Luna et al., 2012]] ; [[#Belley--2016|Belley et al., 2016]] ) and geographic shifts in predator distributions ( [[#3.4.3.1|Section 3.4.3.1]] ) are anticipated to affect deep-sea biodiversity ( ''limited evidence, high agreement'' ) ( [[#Smith--2012|Smith et al., 2012]] ; [[#Morato--2020|Morato et al., 2020]] ). Complex responses of some bathyal crustacean assemblages to environmental change suggest an increase in phylogenetic diversity but limited decreases in abundances with temperature ( [[#Ashford--2019|Ashford et al., 2019]] ). Acute mortality of some reef-forming cold-water corals to laboratory-simulated warming ( [[#Lunden--2014|Lunden et al., 2014]] ) suggests that both long-term warming and the increase of MHWs in intermediate and deep waters ( [[#Elzahaby--2019|Elzahaby and Schaeffer, 2019]] ) could pose significant risk to associated ecosystems ( ''high confidenc'' e). Thermal tolerance thresholds (lethal and sub-lethal) of scleractinians in laboratory settings depend on their geographic position and capacity for thermal adaptation, as well as other factors including food, oxygen and pH ( ''medium to high confidence'' ) ( [[#Naumann--2013|Naumann et al., 2013]] ; [[#Hennige--2014|Hennige et al., 2014]] ; [[#Lunden--2014|Lunden et al., 2014]] ; [[#Naumann--2014|Naumann et al., 2014]] ; [[#Georgian--2016|Georgian et al., 2016]] ; [[#Gori--2016|Gori et al., 2016]] ; [[#Maier--2016|Maier et al., 2016]] ; [[#Büscher--2017|Büscher et al., 2017]] ).

The extension and intensification of deep-water acidification ( [[#3.2.3|Section 3.2.3.1]] ) has been identified as a further key risk to deep-water coral ecosystems ( ''medium confidence'' ) ( [[#Bindoff--2019a|Bindoff et al., 2019a]] ). Literature since SROCC supports this assessment ( [[#Morato--2020|Morato et al., 2020]] ; [[#Puerta--2020|Puerta et al., 2020]] ), although scleractinians and gorgonians are found in regions undersaturated with respect to aragonite ( [[#Thresher--2011|Thresher et al., 2011]] ; [[#Fillinger--2013|Fillinger and Richter, 2013]] ; [[#Baco--2017|Baco et al., 2017]] ). Laboratory experiments on reef-forming scleractinians show variable results, with regional acclimation potential and population-genetic adaptations ( [[#Georgian--2016|Georgian et al., 2016]] ; [[#Kurman--2017|Kurman et al., 2017]] ). ''Desmophyllum pertusum'' 7 [[#footnote-000|1]] and ''Madrepora oculata'' maintain calcification in moderately low pH (7.75) and near-saturation of aragonite ( [[#Hennige--2014|Hennige et al., 2014]] ; [[#Maier--2016|Maier et al., 2016]] ; [[#Büscher--2017|Büscher et al., 2017]] ), but lower pH (7.6) and corrosive conditions lead to net dissolution of ''D. pertusum'' skeletons ( ''high confidence'' ) ( [[#Lunden--2014|Lunden et al., 2014]] ; [[#Kurman--2017|Kurman et al., 2017]] ; [[#Gómez--2018|Gómez et al., 2018]] ). Experiments suggest that ''D. dianthus'' is more sensitive to warming than acidification and when both are high, as projected under climate change. Warming appears to compensate for declines in calcification, with fitness also sensitive to food availability ( [[#Bramanti--2013|Bramanti et al., 2013]] ; [[#Movilla--2014|Movilla et al., 2014]] ; [[#Gori--2016|Gori et al., 2016]] ; [[#Baussant--2017|Baussant et al., 2017]] ; [[#Büscher--2017|Büscher et al., 2017]] ; [[#Schönberg--2017|Schönberg et al., 2017]] ; [[#Höfer--2018|Höfer et al., 2018]] ; [[#Maier--2019|Maier et al., 2019]] ).

In OMZ regions ( [[#3.2.3|Section 3.2.3.2]] ), benthic species distributions ( [[#Sperling--2016|Sperling et al., 2016]] ; [[#Levin--2018|Levin, 2018]] ; [[#Gallo--2020|Gallo et al., 2020]] ), abundance and composition of demersal fishes in canyons ( [[#De%20Leo--2012|De Leo et al., 2012]] ) and deep-pelagic zooplankton ( [[#Wishner--2018|Wishner et al., 2018]] ) follow oxygen gradients, indicating that deep-sea biodiversity and ecosystem structure will be impacted by extension of hypoxic areas ( ''medium confidence'' ). Fossil records show benthic population collapse and turnover when oxygen ranged from oxic to mildly or severely hypoxic (Cross-Chapter Box PALEO in Chapter 1; [[#Moffitt--2015|Moffitt et al., 2015]] ). Regional extirpations among cold-water corals in the paleorecord were associated with substantial declines in oxygen, coincident with abrupt warming and altered properties of intermediate water-masses ( [[#Wienberg--2018|Wienberg et al., 2018]] ; [[#Hebbeln--2019|Hebbeln et al., 2019]] ). Despite mortality and functional impacts from low oxygen concentrations observed in aquaria ( [[#Lunden--2014|Lunden et al., 2014]] ), recent observations of the deep-water coral ''D. pertusum'' suggest adaptive capacity to hypoxia among specimens from OMZ regions that are highly productive ( ''low confidence'' ) ( [[#Hanz--2019|Hanz et al., 2019]] ; [[#Hebbeln--2020|Hebbeln et al., 2020]] ).

Chemosynthetic ecosystems could be particularly prone to oxygen decline ( ''low to medium confidence'' ). Projected OMZ expansion in the vicinity of seep communities could favour sulphide-tolerant species, as suggested from fossil records ( [[#Moffitt--2015|Moffitt et al., 2015]] ), but this will exclude large symbiont-bearing foundation species of methane-seep ecosystems ( [[#Fischer--2012|Fischer et al., 2012]] ; [[#Sweetman--2017|Sweetman et al., 2017]] ). Projected warming, or shifts in warm-current circulation along continental margins, could enhance dissociation of buried methane hydrates ( [[#Phrampus--2012|Phrampus and Hornbach, 2012]] ; [[#Phrampus--2014|Phrampus et al., 2014]] ), either increasing anaerobic methane oxidation ( [[#Boetius--2013|Boetius and Wenzhöfer, 2013]] ), which benefits seep communities, or increasing gas fluxes, which would decrease anaerobic methane oxidation rates and exclude chemosynthetic fauna.

Environmental niche models ( [[#FAO--2019|FAO, 2019]] ; [[#Morato--2020|Morato et al., 2020]] ; [[#Puerta--2020|Puerta et al., 2020]] ) project that under RCP8.5, &gt;50% of present-day scleractinian habitats in the North Atlantic Ocean will become unsuitable by 2100, with greater impacts on ''D. pertusum'' than on ''D. dianthus'' or ''M. oculata'' . For gorgonians, corresponding habitat loss is ''likely'' &gt;80%. Much less is known about the environmental niches of deep-sea sponges, preventing a similar assessment ( [[#Kazanidis--2019|Kazanidis et al., 2019]] ; [[#Puerta--2020|Puerta et al., 2020]] ).

Climate-driven impacts further limit the resilience of deep-sea ecosystems to impacts from human activities ( ''high confidence'' ) ( [[#Levin--2015|Levin and Le Bris, 2015]] ; [[#Rogers--2015|Rogers, 2015]] ; [[#Sweetman--2017|Sweetman et al., 2017]] ). However, assessing cumulative climatic and non-climatic impacts is challenging for these data-poor environments ( [[#Ashford--2018|Ashford et al., 2018]] ; [[#Levin--2018|Levin, 2018]] ; [[#Armstrong--2019|Armstrong et al., 2019]] ; [[#Heffernan--2019|Heffernan, 2019]] ; [[#Kazanidis--2020|Kazanidis et al., 2020]] ; [[#Orejas--2020|Orejas et al., 2020]] ), where lack of knowledge increases the possibility of overlooking ecosystem vulnerabilities and risks ( [[#Levin--2021|Levin, 2021]] ). A paucity of information about the natural variability and historical trends of these habitats prevents robust assessment of adaptive capacities and potential vulnerabilities to extreme events ( [[#Aguzzi--2019|Aguzzi et al., 2019]] ; [[#Levin--2019|Levin et al., 2019]] ; [[#Chapron--2020|Chapron et al., 2020]] ; [[#Danovaro--2020|Danovaro et al., 2020]] ; [[#Le%20Bris--2020|Le Bris and Levin, 2020]] ; [[#Levin--2021|Levin, 2021]] ). The spatial resolution of CMIP5 models is too coarse to robustly project changes in mesoscale circulation at the seafloor ( [[#Sulpis--2019|Sulpis et al., 2019]] ), on which deep-sea ecosystems depend for organic material supplies and dispersal of planktonic and planktotrophic larvae ( ''high confidence'' ) ( [[#Fox--2016|Fox et al., 2016]] ; [[#Mitarai--2016|Mitarai et al., 2016]] ; [[#Dunn--2018|Dunn et al., 2018]] ). Higher-resolution modelling from CMIP6 ( [[#Orr--2017|Orr et al., 2017]] ), multi-annual and high-frequency records of ocean bottom-water properties ( [[#Meinen--2020|Meinen et al., 2020]] ), and better understanding and accounting of biogeochemical mechanisms of organic carbon transport to the ocean interior is expected to improve this capacity ( [[#Boyd--2019|Boyd et al., 2019]] ; [[#Séférian--2020|Séférian et al., 2020]] ).

[[File:0eef17c2358561813f4bb48823289f96 IPCC_AR6_WGII_Figure_3_Box_3_3_1.png]]

'''Figure Box 3.3.1 |''' '''The combination of climate-induced drivers in different deep-ocean ecosystems.''' (Key physical and biological drivers of change in the deep-sea and benthic habitats with specific vulnerabilities are discussed in [[#3.4.3.3|Section 3.4.3.3]] .)

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[[#footnote-000-backlink|1]] 7 Previously named ''Lophelia pertusa''

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<span id="vulnerability-resilience-and-adaptive-capacity-in-marine-socialecological-systems-including-impacts-on-ecosystem-services"></span>