Which of the following best explains the success of the Central African rainfall prediction technique?

This section assesses changes in the ocean. It includes the physical and chemical properties (Section 5.2.2), their impacts on the pelagic ecosystem (Section 5.2.3) and deep seafloor system (Section 5.2.4). In this assessment, the open ocean and deep seafloor includes areas where the water column is deeper than 200 m; it is the main subject of Section 5.2. Coastal and shelf seas are primarily discussed in Section 5.3. 

The ocean is getting progressively warmer, with parallel changes in ocean chemistry such as acidification and oxygen loss, as documented in the AR5 (Rhein et al., 20135). The global scale warming and acidification trends are readily detectable in oceanic observations, well understood scientifically, and consistently projected by ESMs. Each of these has been directly attributed to anthropogenic forcing from changing concentrations of greenhouse gases and aerosols (Bindoff et al., 20136). These trends in the global average ocean temperature will continue for centuries after the anthropogenic forcing is stabilised (Collins et al., 20137). 

The impacts on ocean ecosystems and human societies are primarily driven by regional trends and by the local manifestation of the global-scale changes. At these smaller scales, the temperature, acidification, salinity, nutrient and oxygen concentrations in the ocean are also expected to exhibit basin and local-scale changes. However, the ocean also has significant natural variability at basin and local-scales with time scales from minutes to decades and longer (Rhein et al., 20138), which can mask the underlying observed and projected trends (see Box 5.1). The impact of multiple stressors on marine ecosystems is one of the main subjects of this chapter (Section 5.2.3, 5.2.4, 5.3), including new evidence and understanding since the last assessment report (e.g., Gunderson et al., 2016). The most severe impacts of a changing climate will typically be experienced when conditions are driven outside the range of previous experience at rates that are faster than human or ecological systems can adapt (Pörtner et al., 20149; Box 5.1).

This section summarises our emerging understanding of the primary changes to the ocean, along with an assessment of several key areas of scientific uncertainty about these changes. Because many of these long-term trends have already been extensively discussed in previous assessments (IPCC, 201310), much of this summary of the physical changes is brief except where there are significant new findings. 

Historically, scientific research expeditions starting in the 19th century have provided occasional sections measuring deep ocean properties (Roemmich et al., 201211). Greater spatial and temporal coverage of temperatures down to about 700 m was obtained using expendable bathythermographs along commercial shipping tracks starting in the 1970s (Abraham et al., 201312). Since the early 2000s, thousands of autonomous profiling floats (Argo floats) have provided high-quality temperature and salinity profiles of the upper 2000 m in ice-free regions of the ocean (Abraham et al., 201313; Riser et al., 201614). Further advances in autonomous floats have been developed that now allow these floats to operate in seasonally ice covered oceans (Wong and Riser, 201115; Wong and Riser, 201315), and more recently to profile the entire depth of the water column down to 4000 or 6000 m (Johnson et al., 201517; Zilberman, 201718) and to include biogeochemical properties (Johnson et al., 201719). Autonomous floats have revolutionised our sampling and accuracy of the global ocean temperature and salinity records and increased certainty and confidence in global estimates of the earth heat (temperature) budget, particularly since 2004 (Von Schuckmann et al., 2014; Roemmich et al., 201520; Riser et al., 201621), as demonstrated by the convergence of observational estimates of the changes in the heat budget of the upper 2000 m (Figure 5.1). New findings using data collected from such observing platforms mark significant progress since AR5.

To understand the recent and future climate, we use ensembles of coupled ocean-atmosphere-cryosphere-ecosystem models (ESMs) with the full-time history of atmospheric forcing (greenhouse gases, aerosols, solar radiation and volcanic eruptions) for the historical period and projections of the concentrations or emissions of these forcings to 2100. For these projections the RCPs of atmospheric emissions scenarios are used as specified by the Coupled Model Intercomparison Project, Phase 5 (CMIP5) (see Section 1.8.2.3, Cross-Chapter Box 1, and also IPCC AR5) . This chapter focuses on the low and high emissions scenarios RCP2.6 and RCP8.5, respectively. When these scenarios are used to drive ESMs, it is possible to simulate the recent and future patterns of changes in the ocean temperature, salinity and circulation (and other oceanic properties such as ocean oxygen concentration and acidification, Section 5.2.2.3 and 5.2.2.4). Finally, the projections of ocean changes also informs the detection, attribution and projection of risk and impacts on ecosystems (Sections 5.2.3, 5.2.4 and 5.3), ecosystem services (Section 5.4.1) and human well-being (Section 5.4.2) under climate change. 

The ocean will continue to take up heat in the coming decades for all plausible scenarios. As depicted in Figure 5.1, the ensemble of CMIP5 ESMs used by Cheng et al. (2019) project that under RCP2.6, the top 2000 m of the ocean will take up 935 ZJ of heat between 2015 and 2100 (with a very likely range of 650–1340 ZJ based on the 5th and 95th percentiles of the 25 ESMs used here that have available data from the historical, scenario and control runs for RCP2.6). Under RCP8.5 this ensemble projects heat uptake of 2180 ZJ (with a very likely range of 1710–2790 ZJ, based on 35 ESMs) between 2015 and 2100. By 2100 the ocean is very likely to warm by 2 to 4 times as much for low emissions (RCP2.6) and 5 to 7 times as much for the high emissions scenario (RCP8.5) compared with the observed changes since 1970. With the RCP8.5 scenario, the ocean is very likely to take up about twice as much heat as RCP2.6 (Figure. 5.1). Even under RCP2.6 the ocean will continue to warm for several centuries to come (Collins et al., 201352). It is virtually certain that the ocean will continue to take up heat throughout the 21st century, and the rate of uptake will depend upon on the emissions scenario we collectively choose to follow.

Since AR5, new global-scale data synthesis products, novel methods for their analyses, as well as progress in modeling have substantially increased our quantitative understanding of the role of the ocean in absorbing and storing CO2 from the atmosphere. The most important progress concerns the data-based quantification of the temporal variability of the ocean carbon sink. While AR5 assessed primarily the climatological mean processes governing the ocean carbon cycle, the most recent work now permits us to assess how these processes have changed in recent decades in response to climate variability and change. Here we focus specifically on the open ocean carbon cycle.

Ocean oxygen (O2) levels at the surface are controlled by the balance between oxygen production during photosynthesis, temperature-controlled solubility and air-sea exchange. Deeper in the water column, consumption of oxygen during respiration and redistribution by ocean circulation and mixing are dominant processes. In theory, a warmer more stratified ocean would have a reduced oxygen content, due to the combined influence of lowered gas solubility and a greater interior respiration of organic matter due to enhanced physical isolation of subsurface waters. In accord, global changes in ocean oxygen assessed from three different analyses of compiled global oxygen datasets going back to the 1960s agree that there is a net loss of oxygen from the ocean over all depths (see Table 5.2). For the 0–1000 m depth stratum that contains the most data and is common to all three analyses, oxygen is assessed to have declined by a very likely range of 0.5–3.3% between 1970 and 2010. For the surface ocean (0–100 m) and the thermocline later of 100–600 m the very likely range of oxygen declines are 0.2–2.1% and 0.7–3.5%, respectively (Table 5.2). Across two studies, global oxygen is assessed to have declined by a very likely range of 0.3–2.0%, with a similar range of decline for waters deeper than 600 m (Table 5.2). The regions of lowest oxygen, known as OMZs, with oxygen levels lower than 80 μmol L-1), are observed to be expanding by a very likely range of 3.0–8.3% across the three studies.

Regionally, all studies agree that the north Pacific and Southern Oceans have shown the largest overall oxygen declines (Figure 5.9), but there is some disagreement regarding the magnitude of the oxygen change in the tropical ocean, with some studies suggesting significant declines (Schmidtko et al., 2017) and other reporting more modest reductions (Helm et al., 2011; Ito et al., 2017) and data coverage is still limited for some regions and deeper than 1000 m. Based on the available data, the strongest declines in deep ocean oxygen have occurred in the Equatorial Pacific, North Pacific, Southern Ocean and South Atlantic, with intermediate declines in the Arctic, South Pacific and Equatorial Atlantic, while the north Atlantic has experienced a moderate oxygen increase below 1200 m (Figure 5.9). A particular difference between parallel oxygen analyses concerns the means of integrating and mapping sparse data across the ocean, both horizontally and vertically, with different studies making specific decisions about averaging grids and integration methods. Moreover, data remains sparse for some ocean regions, depths and periods. Taken together, the challenges of data sparsity, regional differences and the relatively large uncertainties on the oxygen changes across different studies, but also recognising that oxygen declines are significantly different to zero, leads to medium confidence in the observed oxygen decline. 

Syntheses of datasets from local time series tend to document stronger trends, with oxygen declines of over 20% at sites in the northeastern Pacific between 1956–2006 (Whitney et al., 2007), the Northwestern Pacific between 1954–2014 (Sasano et al., 2015) and the California Current between 1984–2011 (Bograd et al., 2015). Despite holding the highest inventory of oxygen in the ocean, oxygen levels in Southern Ocean contributed 25% to the global decline between 1970–1992 (Helm et al., 2011) and have fallen by over 150 Tmol per decade from the 1960s to present (Schmidtko et al., 2017). Observations along ocean cruises as part of the CLIVAR programme have also documented broad thermocline oxygen declines in the northern hemisphere oceans, accompanied by well understood oxygen increases in subtropical and southern hemispheres (Talley et al., 2016). 

Overall there is medium confidence that the oxygen content of the upper 1000 m has declined with a very likely loss of 0.5–3.3% between 1970-2010. OMZ are expanding in volume, by a very likely range of 3.0–8.3%. There is medium confidence that the largest regional changes have occurred in the Southern Ocean, equatorial regions, North Pacific and South Atlantic due to medium agreement among studies. 

The role of ocean warming alone in driving the oxygen changes can be appraised using solubility estimates, which vary between around 15–50% for the upper 1000 m oxygen trend between studies (Helm et al., 2011; Ito et al., 2017; Schmidtko et al., 2017). The role of other processes, linked to changing ocean ventilation and respiration are challenging to appraise directly, but tend to reinforce the impacts from warming and are probably predominant overall (Oschlies et al., 2018). Indeed, that the observed oxygen decline is negatively correlated with ocean heat content changes (Ito et al., 2017) reflects the overriding role of changing ocean ventilation and associated processes (see also Section 5.2.2). That the ratio of the associated oxygen to heat changes is larger than would be expected from thermal processes alone also highlights the role played by other processes (Oschlies et al., 2018). Local oxygen trends have emphasised the role of changes to ocean physics in western Northern Pacific (Whitney et al., 2013); Sasano et al. (2015), the southern California Current region (Goericke et al., 2015), and the Santa Barbara Basin (Goericke et al., 2015). In regions of high mesoscale activity, such as the tropical north Atlantic, low oxygen eddies can have a significant impact on oxygen dynamics (Karstensen et al., 2015; Grundle et al., 2017). Oxygen fluctuations in the deep ocean have been linked to changes in large scale ocean circulation (Watanabe et al., 2003; Stendardo and Gruber, 2012) and at the global scale, the observed oxygen decline is negatively correlated with ocean heat content changes (Ito et al., 2017). Changes to respiration rates, either due to temperature enhancement or in the amount/quality of organic material can also be important and the enhanced respiratory demand associated with an intensified monsoon has been invoked as a driver of the expansion of the Arabian Sea OMZ (Lachkar et al., 2018).

Ocean oxygen changes are also affected by climate variability on interannual and decadal timescales, especially for the tropical ocean OMZs (Deutsch et al., 2011). ENSO variability in particular affects the thermocline structure, which then alongside changes in circulation modulates oxygen solubility and respiratory demand in this region (Ito and Deutsch, 2013; Eddebbar et al., 2017). These drivers may then be combined with modifications to overturning and ventilation of OMZs by lateral jets and equatorial current intensity (Duteil et al., 2014). Centennial scale studies based on isotope proxies for low oxygen regions have demonstrated fluctuations in OMZ extent linked to decadal changes in tropical trade winds that affects interior ocean respiratory oxygen demand, which implies that it will be difficult to attribute recent changes in the Pacific OMZ to anthropogenic forcing alone (Deutsch et al., 2015). Parallel work based on oxygen observations (Llanillo et al., 2013), as well as modelling (Duteil et al., 2018) supports the importance of decadal scale variability in the eastern tropical Pacific OMZ. There is some evidence for the potential of a modulating impact on tropical Pacific oxygen at interannual timescales from atmospheric deposition of nitrogen and iron (Ito et al., 2016; Yang and Gruber, 2016).

Observed oxygen changes for the period 1970–2010 for 6 different layers within the ocean. The changes are shown as percentage change of global averages. The layers are depths 0–100, 100–600, 0–1000, and 600–bottom are in metres. The oxygen minimum zone (OMZ) is defined as the ocean volume change that is less than 80 μmol L-1. The estimates and confidence intervals are based published papers (Schmidtko et al. 2018, Ito et al. 2017 and Helm et al. 2011). The assessed change is the average of the available estimates and the 90% Confidence Interval (CI) combines the confidence as their standard deviation with two degrees of freedom.

Future changes in oxygen can be appraised from ESMs that account for the combined effects of ocean physics and biogeochemistry. Globally, these models project that it is very likely oxygen will decline by 3.2–3.7% or 1.6–2.0% (both across 90% confidence limits) for RCP8.5 or RCP2.6, respectively, relative to 2000 (Bopp et al., 2013). Focussing on the 100–600 m depth stratum, O2 changes by –4 to –3.1% for the RCP8.5 or by –0.5–0.1% for the RCP2.6 scenario (relative to 2006–2015, Figure 5.8d). It should be noted that ESMs appear to be underestimating the rate of oxygen change from available datasets from the historical period (Oschlies et al., 2018). Increased tropical ocean stratification reduces interior ocean oxygen by diminishing pathways of ventilation in the subtropical gyres and by inhibiting turbulent mixing with the oxygen-rich surface ocean (see Section 5.2.2.2.4). This relatively robust global modelled trend (Figure 5.8d) however masks important uncertainties in the projection of regional trends (Figure 5.8e), particularly in the tropical ocean OMZs (Bopp et al., 2013; Cocco et al., 2013; Cabré et al., 2015). The uncertainty in the trends in tropical ocean OMZs arises due to the fact that oxygen depletion due to warming induced reductions in oxygen saturation are opposed by oxygen enrichment due to reduced oxygen consumption during respiration in response to predicted declines in marine export production, as well as biases due to model resolution in the tropics and the length of the model spin up (Bopp et al., 2017). The 80 μmol L-1 threshold that may be used to define the volume of the oxygen minimum is projected to grow by a very likely range of 7.0 ± 5.6% by 2100 during the RCP8.5 scenario or show virtually no change during the RCP2.6 scenario, relative to a 1850–1900 reference period (Figure 5.10). At the seafloor, between 200–3000 m depth strata, the north Pacific, north Atlantic, Arctic and Southern Oceans may see oxygen declines by 0.3–3.7% by 2100 (relative to 2005), with abyssal ocean changes being lower and more localised around regions in the north Atlantic and Southern Ocean (Sweetman et al., 2017), but will be modulated by any future changes in overturning strength. There is high confidence that the largest changes in deep sea systems will occur after 2100 (Battaglia and Joos, 2018).

Simulations extended to 2300 suggest that by 2150 the trend of declining tropical ocean oxygen (both in terms of concentrations and volume of low oxygen waters) may reverse itself, mainly due to the effect of strong declines in primary production and organic matter fluxes to the ocean interior (Fu et al., 2018) or due to enhanced Antarctic ventilation (Yamamoto et al., 2015), but with low confidence due to limited evidence. At the global scale, 10,000 year intermediate complexity model simulations find that overall ocean oxygen loss shows near linear relationships to equilibrium temperature, itself linearly related to cumulative emissions, and any climate mitigation scenario will reduce peak oxygen loss by 4.4% per degree Celsius of avoided warming (Battaglia and Joos, 2018). 

In summary, the total oxygen content of the ocean is very likely to decline by 3.2–3.7% by 2100, relative to 2000, for RCP8.5 or by between 1.6–2.0% for RCP2.6 with medium confidence. There is medium confidence that sea floor changes will be more localised in the north Atlantic and Southern Oceans by 2100, but high confidence that the largest deep sea floor changes in oxygen will occur after 2100.

Changes to ocean nutrient cycling are driven by modifications to ocean mixing and transport (Section 5.2.2.2.2), internal biogeochemical cycling and fluctuations in external supply, particularly from rivers and the atmosphere. This assessment will focus on the main nutrients important for driving microbial growth (Section 5.2.2.6), namely nitrogen, phosphorus and iron. 

Diverse studies (including shipboard experiments and use of protein biomarkers) have highlighted nitrogen and phosphorus limitation in the stratified tropical ocean regions accompanied by widespread iron limitation at high latitudes and in upwelling regions that typically have elevated levels of productivity (Figure 5.11) (Moore et al., 2013288; Saito et al., 2014289; Browning et al., 2017290; Tagliabue et al., 2017291). Moreover, more extensive experimental work has demonstrated overlapping nitrogen-iron co-limitation at the boundaries between gyre and upwelling regimes (Browning et al., 2017292). There is high confidence arising from robust evidence and high agreement across different types of studies that the main limiting nutrient is either iron (in most major upwelling regions and the Southern, north Atlantic and sub-Arctic Pacific Oceans) or nitrogen and phosphorus (in the low productivity tropical ocean gyres).

There is limited evidence on contemporary trends in nutrient levels, either from time series sites or broader meta-analyses. Increasing inputs of anthropogenic nitrogen from the atmosphere are perturbing ocean nutrient levels (Jickells et al., 2017293). In the North Pacific in particular, additional atmospheric nitrogen input has raised the nitrogen to phosphorus ratio between 1988–2011 and induced a progressive shift towards phosphorus limitation in this region (Kim et al., 2011294; Kim et al., 2014295; Ren et al., 2017296). This tendency is supported by modelling experiments that find enhanced atmospheric nitrogen input only has a small influence on productivity due to expanded phosphorus limitation (Yang and Gruber, 2016) and other nitrogen cycle feedbacks (Somes et al., 2016298; Landolfi et al., 2017299).

In general, future increases in stratification (Dave and Lozier, 2013300; Talley et al., 2016301; Kwiatkowski et al., 2017302; and see also Section 5.2.2.2) will trap nutrients in the ocean interior and reduce upper ocean nutrient levels, alongside an additional local impact from changes to atmospheric delivery. However, no CMIP5 models accounted for changes in nutrient delivery from dust and anthropogenic aerosols during their experiments, which could be an important component of regional change (Wang et al., 2015b303; Somes et al., 2016304; Yang and Gruber, 2016305). ESMs project a decline in the nitrate content of the upper 100 m of 9–14% or 1.5–6% (across 90% confidence intervals) for the RCP8.5 or RCP2.6 scenario, respectively, by 2081–2100 relative to 2006–2015 (Figure 5.8g). The largest absolute declines in nitrate content is projected in the present day upwelling zones (Figure 5.8h). Projected changes to upper 100 m nitrate concentrations are significantly different to zero for both RCP8.5 and RCP2.6 at the 90% confidence level, but are overall lower for the RCP2.6. Scenario, internal variability and inter-model variability contribute roughly equally to the overall projection uncertainty in 2100 (Figure 5.8i) and there is no clear separation of nitrate trends between RCP8.5 and RCP2.6 outside the model uncertainty (Figure 5.8h).

Iron concentrations are projected to increase in the future from ESM simulations, due to enhanced lateral transport into high-latitude oceans and reduced biological consumption in regions of declining nitrate (Misumi et al., 2013314). Other modelling efforts also suggest greater levels of the more biologically available Fe(II) species in a warmer and more acidic ocean (Tagliabue and Völker, 2011315). These modelling studies tend to indicate greater ocean iron availability in the future overall, but the very limited skill of contemporary global ocean iron models in reproducing observations available from the new basin scale datasets from the international GEOTRACES program and neglect for parallel dust supply changes lower the confidence in the models’ projected changes (Tagliabue et al., 2016316). 

Overall, nitrate concentrations in the upper 100 m are very likely to decline by 9–14% by 2081–2100, relative to 2006–2015 for RCP8.5 or 1.5–6% for RCP2.6, in response to increased stratification, with medium confidence in these projections due to the limited evidence of past changes that can be robustly understood and reproduced by models. Surface ocean iron levels is projected to increase in the 21st century with low confidence due to systemic uncertainties in these models. 

Ocean primary productivity is a key process in the ocean carbon cycle (see Section 5.2.2.3), as well as for supporting pelagic ocean ecosystems (see Section 5.2.3). NPP is the product of phytoplankton growth rate and standing stock. Phytoplankton growth is controlled by the combination of temperature, light and nutrients, while the phytoplankton standing stock is modified by both gains from growth and losses due to grazing by zooplankton (Figure 5.12). Export production is here defined as the sinking flux of particulate organic carbon (produced by NPP) across a specified depth horizon. Otherwise known as the biological pump, export production is also a key component of the global carbon cycle (see Section 5.2.2.3) and an essential food supply to benthic organisms (see Section 5.2.3.2). Export production is regulated by the level of primary production and the transfer efficiency with depth, itself controlled by the type of sinking organic carbon, which is affected by the upper ocean food web structure (Boyd et al., 2019317). 

Satellite datasets that use mathematical algorithms to convert ocean colour, often alongside other remotely sensed information, into chlorophyll or other indexes of phytoplankton biomass and NPP provide the potential to deliver a global meta-analysis of changes in NPP. Since AR5, a variety of studies have reported relatively insignificant changes in overall open ocean chlorophyll levels of <±1% yr–1 for individual time periods (Boyce et al., 2014318; Gregg and Rousseaux, 2014319; Boyce and Worm, 2015320; Hammond et al., 2017321). Regionally, trends of ±4% between 2002–2015 for different regions are found when different satellite products are merged, with increases at high latitudes and moderate decreases at low latitudes (Mélin et al., 2017322. While some studies report good comparability of merged products (Mélin et al., 2017323), others highlight significant mismatches regarding absolute values and decadal trends in NPP between NPP algorithms (Gómez-Letona et al., 2017324). Satellite derived NPP shows significant mismatches when compared to in situ data and reducing uncertainties in derived NPP is a high priority for the community (Lee et al., 2015325), although there is a reasonable correlation in higher biomass coastal regions (Kahru et al., 2009326). Importantly, satellite records are not yet long enough to unambiguously isolate long term climate related trends from natural variability (Beaulieu et al., 2013327). Overall, there is low confidence in satellite-based trends in global ocean NPP due to the time series length and lack of corroborating in situ measurements or other validation time series. This is especially true at regional scales where distinct sets of poorly understood processes dominate. 

Future changes in NPP will result from the changing influence from temperature, light, nutrients and grazing (Figure 5.12). Across CMIP models, NPP is predicted to broadly decline or remain constant by 2081–2100, with mean changes by 2100 of –3.8 to –10.6% and –1.1–0.8% across 90% confidence intervals for the RCP85 and RCP26 scenario, respectively (all relative to 2006–2015), with a strong degree of regional symmetry (Figure 5.8k). As seen for nitrate, changes are most marked in low-latitude upwelling regions, which are projected to show the largest absolute declines. As for nitrate, projected NPP changes are lower for the RCP26 scenario (Figure 5.8j), but the overall uncertainty is dominated by internal and inter-model variability in 2100 (Figure 5.8l) which results in no clear separation of NPP trends between the RCP85 and RCP26 (Figure 5.8j). Tropical ocean NPP is projected to show a large decline, but is underpinned by substantial intermodal uncertainty, with mean changes of 11 ± 24% across the suite of CMIP5 models by 2100, relative to 2000 under RCP8.5 (Laufkötter et al., 2015328). However, if emergent constraints from the historical record that link the variability of tropical productivity to temperature anomalies then a four-fold decline in inter-model uncertainty results. This leads to a projected tropical ocean decline of 11 ± 6%, or from 6.8–16.2% across 90% confidence limits, depending on which historical constraint is used (Kwiatkowski et al., 2017329). NPP is projected to increases for higher latitude regions, such as the Arctic and Southern Oceans.

Detailed analyses of the interplay between different drivers of NPP, including temperature, light, nutrient levels and grazing from a subset of CMIP5 models, reveals a complex interplay with a strong latitudinal dependence (Laufkötter et al., 2015330) summarised in Figure 5.12. Warming acts to enhance growth, most notably at lower latitudes, while light conditions are also predicted to improve, mostly at the poles. Nutrient limitation shows a much more complex response across models, but tends to increase in the tropics and northern high latitudes, with little change in the Southern Ocean. Taken together there is a tendency for reduced growth rates across the entire ocean, but there is a large amount of inter-model variability. The changes in growth are allied to a consistent increase in the grazing loss of biomass to upper trophic levels. Since AR5, we have an increasing body of literature concerning role of biological feedbacks, especially due to interactions between organisms, specific physiological responses and from upper trophic levels on nutrient concentrations, linked to variable food quality (Kwiatkowski et al., 2018331), resource recycling (Boyd et al., 2015a332; Tagliabue et al., 2017333) and interactions between organisms (Lima-Mendez et al., 2015334), but their role in shaping the response of NPP to climate change remains a major unknown. Lastly, modelling work suggests that the increasing deposition of anthropogenic aerosols (supplying N and Fe) stimulates biological activity (Wang et al., 2015b335) and may compensate for warming driven reductions in primary productivity (Wang et al., 2015b336), but these effects do not form part of the CMIP5 projections assessed here.

CMIP5 models show a strong negative relationship between changes in stratification that reduces net nutrient supply and integrated export production (Fu et al., 2016337). Export production is projected to decline by 8.9–15.8% or 1.6–4.9% (across 90% confidence intervals) by 2100, relative to 2000 for the RCP8.5 or RCP2.6 scenario, respectively (Bopp et al., 2013338; Fu et al., 2016339; Laufkötter et al., 2016340). 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 (Guidi et al., 2016341; Tréguer et al., 2018342), which then affects the sinking speed and lability of exported particles through the ocean interior to the sea floor (Bopp et al., 2013343; Fu et al., 2016344; Laufkötter et al., 2016345). Declines in export production over much of the ocean mean that the flux arriving at the sea floor is also predicted to decline, while increases in export production are projected in the polar regions that see enhanced NPP (Sweetman et al., 2017346). 

The realism in model projections can be appraised via their ability to accurately simulate the limiting nutrient in specific ocean regions (Figure 5.11), with high model skill in reproducing surface distributions of nitrate and phosphate (Laufkötter et al., 2015347), raising confidence in projections in nitrogen and phosphorus limited systems, but poor skill in reproducing iron distributions (Tagliabue et al., 2016348) lowering confidence in iron limited regions (Figure 5.11). In addition to concentrations of specific nutrients, the response of NPP to environmental change is strongly controlled by accurate representation of the ratio of resources (Moreno et al., 2017349). Overall CMIP5 models skill in reproducing patterns of NPP and export production from limited satellite derived estimates range from poor to average (correlation coefficients of 0.1–0.6 across different models (Laufkötter et al., 2016; Moreno et al., 2017350)), but it should be noted that complete comprehensive observational datasets do not exist for these metrics with very few in situ observations. As export production is a much better understood net integral of changing net nutrient supply (Sarmiento and Gruber, 2002351) and can be constrained by interior ocean nutrient and oxygen levels, there is medium confidence in these projections for global changes. Improving the ability of models to reproduce historical NPP is crucial for more accurate projections as model biases in simulating contemporary ocean biogeochemistry play a key role in driving future projections (Fu et al., 2016352). 

Overall, these assessments balance the range of projections across models alongside the strength of different kinds of observational constraints available, as well as our theoretical or experimental understanding of the impact of a warmer, more stratified ocean on NPP and export production. As for AR5, net primary productivity is very likely to decline by 4–11% by 2081–2100, relative to 1850–1900, 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. It is very likely that tropical NPP will decline by 7–16% by 2100 for RCP8.5with medium confidence, as there are improved constraints from historical variability in this region. Globally, the increased stratification in the future is very likely to reduce export production by 9–16% in response to reduced nutrient supply, especially in tropical regions (medium confidence).

The concept of time of emergence (ToE) is defined as the time at which the signal of climate change in a given variable emerges from a measure of the background variability or noise (SROCC Glossary). In associating a calendar date with the detection, attribution and projection of climate trends, the concept of a ToE has proved useful for policy and planning particularly through informing important climatic thresholds and the uncertainties associated with past and future climate change (Hawkins and Sutton, 2012). However, there is not a single agreed metric and the ToE for a given variable thus depends on choices regarding the space and time scale, the threshold at which emergence is defined and the reference period (IPCC 5th Asseessment Report (AR5) Working Group I (WGI) Section 11.3.2.1). Recently, the ToE concept has been expanded to consider variables related to climatic hazards to marine organisms and ecosystems such as pH, carbonate ion concentrations, aragonite and calcite saturation states, nutrient levels and marine primary productivity (Box 5.1, Figure 1) (Ilyina et al., 2009; Friedrich et al., 2012; Keller et al., 2014b; Lovenduski et al., 2015; Rodgers et al., 2015). ToE assessments for the ocean typically quantify the internal variability using the standard deviation of the detrended data over a given time period (Keller et al., 2014b; Rodgers et al., 2015; Henson et al., 2016; Henson et al., 2017), the scenario and model uncertainty associated with different climate scenarios and across available ESMs (Frölicher et al., 2016), and in some cases the autocorrelation of noise (Weatherhead et al., 1998). As more components of ‘noise’ are accounted for, the ToE lengthens and the ToE is also affected by whether a control simulation or historical variability is used to determine the noise (Hameau et al., 2019). 

This assessment considers the ToE of hazards exposed to by marine organisms and ecosystems. These biological components of the ocean respond to climate hazards that emerge locally, rather than to the global and basin-scale averages reported in WGI AR5 (Stocker et al., 2013). Overall, ESMs show that there is an ordered emergence of the climate variables, with pH emerging rapidly across the entire open ocean, followed by sea surface temperature (SST), interior oxygen, upper ocean nutrient levels and finally NPP under both Representative Concentration Pathway (RCP)2.6 and RCP8.5 relative to the 1861–1900 reference period (Box 5.1, Figure 1). Anthropogenic signals remain detectable for over large parts of the ocean even for the RCP2.6 scenario for pH and SST, but are likely lowered for nutrients and NPP 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 discernable difference between scenarios. The climate signal of oxygen loss will very likely emerge from the historical climate 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 under RCP2.6 scenario in the 21st century and by 2090 the emerged area is declining (Henson et al., 2017) (Box 5.1 Figure 1). It has also been shown that changes to oxygen solubility or utilisation may emerge earlier than bulk oxygen levels (Hameau et al., 2019).

It must be noted that variability will be greater in the coastal ocean than for the open ocean, which will be important for both hazard exposure for coastal species and the detection of trends. For example, although signals of anthropogenic influences have already emerged from internal variability in the late 20th century for global and basin-scale averaged ocean surface and sub-surface temperature (very likely) (AR5 WGI Summary for Policymakers), their ToE and level of confidence vary greatly at local scales and in coastal seas (Frölicher et al., 2016). Pelagic organisms with small range size may thus be more (or less) at risk to warming with earlier (or later) ToE at the scale of the area that they inhabit. From an observational standpoint, analyses that account for autocorrelation of noise suggest time series of around a decade are sufficient to detect a trend in pH or SST, whereas datasets spanning 30 years or longer are typically needed for detection of emergence at local scales for oxygen, nitrate and primary productivity (Henson et al., 2016).

The rapidity of change and its geographic scope, encompassed in the ToE, can be linked to concepts of exposure to hazard and vulnerability of biota. As organisms have evolved to be adaptable to natural variations in the environmental conditions of their habitats, changes to their habitat conditions larger than that typically experienced or specific biological thresholds such as upper temperature or oxygen tolerance may become hazardous (Mora et al., 2013). This would then move from the statistical nature of the ‘detection and attribution’ nature of the ToE discussed above towards timescales of impacts on organisms useful for ecosystem projections. In doing so, it will be important to think about the differences in habitat suitability between different organisms, including their specific thresholds for specific drivers, for example, temperature, oxygen or calcium carbonate stability. Further, thresholds vary depending on habitat, for example, warming thresholds for coral bleaching (Pendleton et al., 2016) may differ from the temperature and oxygen thresholds for fishes such as Atlantic cod and tunas (Deutsch et al., 2015). Moreover, species with fast generation times relative to the ToE of key habitat conditions (e.g., phytoplankton) may evolve more quickly to environmental change and be less vulnerable to climate change than longer-lived, slower generation time species (e.g., large sharks) (Jones and Cheung, 2018). However, evidence on evolutionary adaptation to expected climate change is limited, thus while shorter generation time may facilitate adaptation to environmental change, it does not necessarily result in successful adaptation of organisms (Section 5.2.3.1).

Earlier ToE and their subsequent biological impacts on organisms and ecosystems increase the urgency of policy responses through both climate mitigation and adaptation (Sections 5.5). However, the rapid emergence of hazards at the local scale in the near-term (already past or in this decade) such as warming and ocean acidification and the resulting impacts on some of the more sensitivity or less adaptive biodiversity and ecosystem services may post challenges for international and regional policies as their often require multiple decades to designate and implement (Box 5.6). In contrast, scope for adaptation for national and local ocean governance can be more responsive to rapid changes (Sections 5.5.2, 5.5.3). This highlights the opportunities for multi-level adaptation that allows for reducing climate risks that are expected to emergence of stressors and impacts at different time frame (Mackenzie et al., 2014).

Marine pelagic ecosystems (the water column extending from the surface ocean down to the deep sea floor) face increasing climate related hazards from the changing environmental conditions (see Section 5.2.2). WGII AR5 (Pörtner et al., 2014) concluded, as also confirmed in Section 5.2.2, that long time series of more than three or four decades in length are necessary for determining biological trends in the ocean. However, long-term biological observations of pelagic ecosystems are rare and biased toward mid to high-latitude systems in the Northern Hemisphere (Edwards et al., 2013; Poloczanska et al., 2013; Poloczanska et al., 2016). This assessment, therefore, combines multiple lines of evidence ranging from experiments, field observations to model simulations to detect and attribute drivers of biological changes in the past, project future climate impacts and risks of pelagic ecosystems. In this section the pelagic ecosystem is subdivided into the surface, epipelagic ocean (<200 m, the uppermost part of the ocean that receives enough sunlight to allow photosynthesis) (Section 5.2.3.1) and the deep pelagic ocean, comprising the twilight, mesopelagic zone (200–1000 m) and the dark, bathypelagic zone (>1000 m deep) (Section 5.2.3.2). Although the WGII AR5 Chapter 30 defined the deep sea as below 1000 m (Hoegh-Guldberg et al., 2014), the absence of photosynthetically useful light and ensuing critical ecological, biogeochemical transformations, and altered human interactions that occur on much of the sea floor below 200 m have led both pelagic and benthic biologists to include the ocean waters and seafloor below 200 m within the definition of the deep sea (Herring and Dixon, 1998; Gage, 2003).

This section synthesises new evidence since AR5 to assess observed changes in relation to the effects of and the interactions between multiple climate and non-climate hazards, and to project future risks of impacts from these hazards on the epipelagic organisms, communities and food web interactions, and their scope and limitation to adapt.

The deep seafloor is assessed here as the vast area of the ocean bottom >200 m deep, beyond most continental shelves (Levin and Sibuet, 2012; Boyd et al., 2019) (Figure 5.15). Below 200 m changes in light, food supply and the physical environment lead to altered benthic (seafloor) animal taxonomic composition, morphologies, lifestyles and body sizes collectively understood to represent the deep sea (Tyler, 2003). 

Most deep seafloor ecosystems globally are experiencing rising temperatures, declining oxygen levels, and elevated CO2, leading to lower pH and carbonate undersaturation (WGII AR5 30.5.7; Section 5.2.2.3). Small changes in exposure to these hazards by deep seafloor ecosystem have been confirmed by observation over the past 50 years. However, analysis using direct seafloor observations of these hazards over the past 15-29 years suggest that the environmental conditions are highly variable over time because of the strong and variable influences by ocean conditions from the sea surface (Frigstad et al., 2015; Thomsen et al., 2017). Such high environmental variability makes it difficult to attribute observed trends to anthropogenic drivers using existing datasets (Smith et al., 2013; Hartman et al., 2015; Soltwedel et al., 2016; Thomsen et al., 2017) (high confidence). Projections from global ESMs suggest large changes for temperature by 2100 and beyond under RCP8.5 (relative to present day variation) (Mora et al., 2013; Sweetman et al., 2017; FAO, 2019). The magnitude of the projected changes is lower under RCP2.6, and in some cases the direction of projected change to 2100 varies regionally under either scenario (FAO, 2019) (high confidence).

Abyssal communities (3000–6000 m) cover over 50% of the ocean’s surface and are considered to be extremely food limited (Gage and Tyler, 1992; Smith et al., 2018684). There is a strong positive relationship between surface primary production, export flux, and organic matter supply to the abyssal seafloor (Smith et al., 2008685), with pulses of surface production reflected as carbon input on the deep seafloor in days to months (Thomsen et al., 2017686). Both vertical and horizontal transport contribute organic matter to the sea floor (Frischknecht et al., 2018687). Food supply to the seafloor regulates faunal biomass, explaining the strong positive relationships documented between surface production and seafloor faunal biomass in the Pacific Ocean (Smith et al., 2013688), Gulf of Mexico (Wei et al., 2011689) and north Atlantic Ocean (Hartman et al., 2015690). Extended time series and broad spatial coverage reveal strong positive relationship between annual POC flux and abyssal sediment community oxygen consumption (Rowe et al., 2008691; Smith et al., 2016a692). Observed reduction in in POC flux at the abyssal seafloor enhances the relative importance of the microbial loop and reduces the importance of benthic invertebrates in carbon transfer (Dunlop et al., 2016693) (single study, limited evidence). However, changes in the overlying mesopelagic and bathypelagic communities (see Section 5.2.3.2) will also affect food flux to the deep seafloor, as nekton and zooplankton transfer energy to depth through diel (daily day-night) vertical migrations, ontogenetic (life staged-based) migrations and falls of dead carcasses (Gage, 2003694). Therefore, climate change impacts on organic carbon export from the epipelagic (Section 5.2.3.1) and deeper pelagic systems (Section 5.2.3.2) can affect the energy available to support the abyssal seafloor ecosystems (medium confidence). However, because observations on historical changes in POC flux in abyssal seafloor ecosystems are limited to a few locations, long-term records show high variability, and mechanistic understanding of factors affecting the biological carbon pump is incomplete, there is limited evidence that the abyssal seafloor ecosystem has already been affected by changes in POC flux as a result of climate change. The metabolic rate of deep seafloor ectotherms, and consequently their demand for food, increases with temperature. Thus, observed warming in deep sea ecosystems (Hoegh-Guldberg et al., 2014695) (Section 5.2.2.2.1) is expected to increase the sensitivity of deep seafloor biota to decrease in food supplies associated with a change in POC flux (high confidence). However, there is limited evidence of observed changes in abyssal biota. Small deep sea biota demonstrate increased efficiency (effective use of food energy for growth and metabolism with minimal loss) at low food inputs (due to small size and dominance by prokaryotic taxa) (Gambi et al., 2017696). Adaptation to low food availability in abyssal ecosystems may confer higher capacity to adjust to reduced food availability than for shallow biota (limited evidence). Overall, the risk of impacts of climate change on abyssal ecosystems through reduction in food supplies from declining POC flux in the present day is low with low confidence. 

The globally integrated export flux of carbon is projected to decrease in the open ocean in the 21st century under RCP2.6 (by 1.6–4.9%) and RCP8.5 (by 8.9–15.8%) relative to 2000 (medium confidence) (Section 5.2.2.6). This change in export flux of carbon is projected to yield declines in POC flux at the abyssal seafloor (representing food supply to benthos) of up to –27% in the Atlantic and up to –31 to –40% in the Pacific and Indian Oceans, with some increases in polar regions (Sweetman et al. 2017697). In some models, additional dissolution of calcium carbonate due to ocean acidification further lowers POC flux, causing the projected export production declines to be up to 38% at the northeast Atlantic seafloor (Jones et al., 2014699). Lower POC fluxes to the abyss reduce food supply and have been projected to cause a size-shift towards smaller organisms (Jones et al., 2014), resulting in rising respiration rates, lower biomass production efficiency, and lesser energy transfer to higher trophic levels (Brown et al., 2004700) (medium confidence). Changes are projected to be largest for macrofauna and lesser and similar for megafauna and meiofauna (Jones et al., 2014) (limited evidence, low confidence). Projections using outputs from seven CMIP5 models suggest that 97.8 ± 0.6% (95% CI) of the abyssal seafloor area will experience a biomass decline by 2091–2100 relative to 2006–2015 under RCP8.5. The projected decreases in overall POC flux to the abyssal seafloor are projected to cause a 5.2–17.6% reduction in seafloor biomass in 2090–2100, relative to 2006–2015 under RCP8.5 (Jones et al., 2014701). The projected impacts on abyssal seafloor biomass are significantly larger under RCP8.5 than RCP4.5 (Jones et al., 2014703). However, existing estimates are based on total POC flux changes and do not account for changes in the type or quality of the sinking material, to which macrofaunal and meiofaunal invertebrates are highly sensitive (Smith et al., 2008704; Smith et al., 2009705; Tittensor et al., 2011706). The projections also do not account for direct faunal responses to changes in temperature, oxygen or the carbonate system, all of which will influence benthic responses to changing food availability (AR5 Chapter 30.5.7), reducing to medium confidence the risk assessment that is based on these projections (Figure 5.16). 

Regionally, while reductions in POC flux are projected at low and mid latitudes in the Pacific, Indian and Atlantic Oceans, increases are projected at high latitudes associated in part with reduction in sea ice cover (Yool et al., 2013707; Rogers, 2015708; Sweetman et al., 2017709; Yool et al. 2017710; FAO 2019711) (see Chapter 3) (medium confidence). Notably, Arctic and Southern Ocean POC fluxes at the abyssal seafloor are projected to increase by up to 38% and 21%, respectively by 2100 under RCP8.5 (Sweetman et al., 2017712). While an increase in food supply may yield higher benthic biomass at high latitudes, warmer temperatures and reduced pH projected for the polar regions (Chapter 3) would elevate faunal metabolic demands, likely diminishing the benefit of elevated food supply to an unknown extent (Sweetman et al., 2017713). Overall, given the limited food availability for fauna in the abyssal plains and the projected warming (Section 5.2.2.2.2) that increases the demand for food to support the elevated metabolic rates, the projected decrease in influx of organic matter and seafloor biomass will result in high risks of impacts to abyssal ecosystems by the end of the 21st century under RCP8.5 (medium confidence) (Figure 5.16). The risk of impacts is projected to be substantially lower under RCP4.5 or RCP2.6 (high confidence). The impacts on abyssal seafloor ecosystems affect functions that are important to support ecosystem services (see Section 5.4.1). For example, smaller-sized organisms exhibit reduced bioturbation intensity and depth of mixing causing reduced carbon sequestration (Smith et al., 2008714) (Figure 5.15). 

Bathyal ecosystems consist of numerous geomorphic features with steep topography (Figure 5.15). These include continental slopes covering 5.2% of the seafloor, over 9400 steep-sided canyons, and >9000 conical seamounts (submarine volcanos which are mainly inactive), as well as guyots and ridges which together cover ~6% of the seafloor (Harris et al., 2014). Seamounts and canyons support high animal densities and biomass including cold water coral, sponge and bryozoan reefs, exhibit high secondary production supported by locally enhanced primary production and intensified water flow, function as diversity hotspots and serve as stepping stones for larval dispersal (Rowden et al., 2010). Canyons transport particulate organic matter, migrating plankton and coarse material from the shelf, and are sites where intensified mixing and advection of water masses occurs (De Leo et al., 2010; Levin and Sibuet, 2012; Fernandez-Arcaya et al., 2017).  Slopes, canyons and seamounts exhibit strong vertical temperature, oxygen and pH gradients generating sharp ecological zonation (Levin and Sibuet, 2012), thus changes in exposures are expected to alter the distributions of their communities (Figure 5.15, 5.16) (medium confidence).  

In some regions, observational records document changing conditions in bathyal ecosystems (Levin, 2018; Section 5.2.2.4). In the Northeast Pacific continental slopes associated with the California Current ecosystem, observations over the past 25 years show high variability but an overall trend of decreasing ocean oxygen and pH levels with oxygen declines of up to 40% and pH declines of 0.08 units in California . (Goericke et al., 2015) (high agreement, robust evidence, high confidence). Large oxygen declines are linked to past warming events on continental margins, over multiple time scales from 1–100 ky (Dickson et al., 2012; Moffitt et al., 2015). Studies across modern oxygen gradients on slopes reveal that suboxic (5–10 µMol kg-1 O2) values lead to loss of biodiversity of fish (Gallo and Levin, 2016), invertebrates (Levin, 2003; Gallo and Levin, 2016; Sperling et al., 2016), and protozoans (Bernhard and Reimers, 1991; Gooday et al., 2000; Moffitt et al., 2014) (high confidence). Shoaling oxyclines on continental slopes have altered depth distributions of multiple co-occurring echinoid species over the past 25 years (Sato et al., 2017) and can reduce the growth rate, and change the skeletal structure and biochemical composition of a common sea urchin (Sato et al., 2018). In central Pacific oceanic canyons, fish abundance and diversity are reduced at 4 to 5 times higher oxygen concentrations than on continental slopes (<31 µMol kg-1 O2) (De Leo et al., 2012). Low oxygen on continental slopes causes reductions in faunal body size and bioturbation (Diaz and Rosenberg, 1995; Levin, 2003; Middelburg and Levin, 2009; Sturdivant et al., 2012), simplification of trophic structure reducing energy flow to upper trophic levels (Sperling et al., 2013), shifts in carbon processing pathways from metazoans to protozoans (Woulds et al., 2009), and reduced colonisation potential (Levin et al., 2013). These changes are expected to lead to altered ecosystem structure and function, with lower carbon burial (Smith et al., 2000; Levin and Dayton, 2009) (medium confidence). Both carbon sequestration and nitrogen recycling are highly sensitive to small changes in oxygenation within the suboxic zone (Deutsch et al., 2011).

Bathyal species adapted to OMZs where CO2 levels are characteristically high, appear less vulnerable to the negative impacts of ocean acidification (Taylor et al., 2014). Benthic foraminifera, which are often the numerically dominant deep sea taxon, show no significant effect of short-term exposure to ocean acidification on survival of multiple species (Dissard et al., 2010; Haynert et al., 2011; Keul et al., 2013; McIntyre-Wressnig et al., 2014; Wit et al., 2016) and in fact hypoxia in combination with elevated pCO2 favors survival of some foraminifera (Wit et al., 2016). However, lower pH exacerbates shallow foraminiferal sensitivity to warming (Webster et al., 2016). Limited evidence suggests that combined declines in pH and oxygen may lead to increase in some agglutinating taxa and a decrease in carbonate-producing foraminifera, including those using carbonate cement (van Dijk et al., 2017). Exposure to acidification (0.4 unit pH decrease) reduces fecundity and embryo development rate in a bathyal polychaete. Where both oxygen and CO2 stress occur together on bathyal slopes, oxygen can be the primary driver of change (Taylor et al. 2014; Sato et al. 2018). Nematodes are sensitive to changes in temperature (Danovaro et al., 2001; Danovaro et al., 2004; Yodnarasri et al., 2008) and elevated CO2 (Barry et al., 2004; Fleeger et al., 2006; Fleeger et al., 2010). There is low agreement about the direction of meiofaunal responses among studies, reflecting opposing responses in different regions. However, there is high agreement that meiofauna are sensitive to change in environment and food supply (medium confidence). Additional research is needed across all taxa on how hypoxia and pH interact (Gobler and Baumann, 2016). 

Continental slopes, seamounts and canyons (200–2500 m) are projected to experience significant warming, pH decline, oxygen loss and decline in POC flux by 2081–2100 (compared to 1951–2000) under RCP8.5 (Table 5.5). In contrast, the average changes are projected to be 30–50% less under RCP2.6 (Table 5.5) by 2081-2100. Most ocean regions at bathyal depths (200–2500 m) except the Southern and Arctic Oceans are predicted to experience on average declining export POC flux under RCP8.5 by 2081–2100 (Yool et al., 2017; FAO, 2019) with the largest declines of 0.7–8.1 mg C m-2 d-1 in the Northeast Atlantic (FAO, 2019). There is a strong macroecological relationship between depth, export POC flux, biomass and zonation of macrobenthos on continental slopes (Wei et al., 2011), such that lower POC fluxes will alter seafloor community biomass and structure (medium confidence) (See also Section 5.2.4.1). This is modified on the local scale by near-bottom currents, which alter sediment grain size, food availability, and larval dispersal (Wei et al., 2011). 

Declines in faunal biomass (6.1 ± 1.6% 95% C.I) are predicted for 96.6 ± 1.2% of seamounts under RCP8.5 by 2091–2100 relative to 2006–2015, driven by a projected 13.8 ± 3.3% drop in POC flux (Jones et al., 2014). The majority (85%) of mapped canyons are projected to experience comparable benthic biomass declines (Jones et al., 2014). By 2100 under RCP8.5, pH reductions exceeding -0.2 pH units are projected in ~ 23% of north Atlantic deep sea canyons and 8% of seamounts (Gehlen et al., 2014), with potential negative consequences for their cold water coral habitats (See Box 5.2).

Mean temperature (warming) signals are projected to emerge from background variability before 2040 in canyons of the Antarctic, northwest Atlantic, and South Pacific (FAO, 2019). Enhanced stratification and change in the intensity and frequency of downwelling processes under atmospheric forcing (including storms and density-driven cascading events would alter organic matter transported through canyons (Allen and Durrieu de Madron, 2009) (low confidence). Changes in the quantity and quality of transferred particulate organic matter, as well as physical disturbance during extreme events cause a complex combination of positive and negative impacts at different depths along the canyon floor (Canals et al., 2006; Pusceddu et al., 2010). Canyons and slopes are recognised as hosting many methane seeps and other chemosynthetic habitats (e.g., whale and wood falls) supported by massive transport of terrestrial organic matter (Pruski et al., 2017); their climate vulnerabilities are discussed below. 

Seamounts have been proposed to serve as refugia for cold water corals facing shoaling aragonite saturation horizons (Tittensor et al., 2011), but could become too warm for deep-water corals in some regions (e.g., projections off Australia) (Thresher et al., 2015) (one study, low confidence). Seamounts are major spawning grounds for fishes; reproduction on seamounts may be disrupted by warming (Henry et al., 2016) (one study, low confidence). In the north Atlantic, models suggest seamounts are an important source of cold water coral larvae that maintain resilience under shifting NAO conditions (Fox et al., 2016), thus loss of suitable seamount habitat may have far-reaching consequences (Gehlen et al., 2014) (low confidence) (also see Box 5.2).

Projected climate changes from the present to 2081–2100 given as mean (min, max) at the deep seafloor for continental slopes, canyons, seamounts and cold water corals mapped from 200–2500 m under RCP8.5 and RCP2.6 Projections are based on three 3D, fully coupled earth system models (ESMs) (as part of CMIP5): the Geophysical Fluid Dynamics Laboratory’s ESM 2G (GFDL-ESM-2G); the Institut Pierre Simon Laplace’s CM6-MR (IPSL-CM5A-MR); and (iii) the Max Planck Institute’s ESM-MR (MPI-ESM-MR). Export flux at 100 m was converted to export POC flux at the seafloor (epc) using the Martin curve following the equation: epc = epc100 (depth/ export depth)-0.858. Projections were made onto the (i) slope from a global ocean basin mask from World Ocean Atlas 2013 V2 (NOAA, 2013), (ii) global distribution of submarine canyons with canyon heads shallower than 1500 m (Harris and Whiteway, 2011); (iii) global distribution of seamounts with summits between 200–2500 m (Kim et al. 2011); and (iv) global occurrence of cold water corals between 200–2500 m (Freiwald et al. 2017).

Despite having nutrition derived largely from chemosynthetic sources fueled by fluids from the earth’s interior, hydrothermal vent and methane seep ecosystems are linked to surface ocean environments and water-column processes in many ways that can expose them to aspects of climate change (medium confidence). The reliance of vent and seep mussels on surface-derived photosynthetic production to supplement chemosynthetic food sources (Riou et al., 2010778; Riekenberg et al., 2016779; Demopoulos et al., 2019780), and in some cases as a cue for synchronised gametogenesis (sperm and egg production) (Dixon et al., 2006781; Tyler et al., 2007782) can make them vulnerable to changing amounts or timing of POC flux to the deep seabed in most areas except high latitudes, or to changes in timing of surface production (see Section 5.2.2.5) (limited evidence) Most of the large, habitat-forming (foundation) species at vents and seeps such as mussels, tubeworms, and clams require oxygen to serve as electron acceptor for aerobic hydrogen-, sulfide- and methane oxidation (Dubilier et al., 2008783) and appear unable to grow under dysoxic conditions (<5–10 µmol kg–1 O2) (Sweetman et al., 2017784) (medium confidence). The distributions of these taxa at seeps could be constrained by climate-driven expansion of midwater oxygen minima (Stramma et al., 2008785; Schmidtko et al., 2017786), which is occurring at water depths where seep ecosystems typically occur on continental margins (200–1000 m). Rising bottom temperatures or shifting of warm currents on continental margins could increase dissociation of buried gas hydrates on margins (Phrampus and Hornbach, 2012787) (low confidence) potentially intensifying anaerobic methane oxidation (which produces hydrogen sulfide) (Boetius and Wenzhoefer, 2013788) and expanding cover of methane seep communities (limited evidence). Larvae of vent species such as bathymodiolin mussels, alvinocarid shrimp, and some limpets that develop in or near surface waters (Herring and Dixon, 1998789; Arellano et al., 2014790), are likely to be exposed to warming waters, decreasing pH and carbonate saturation states, and in some places, reduced phytoplankton availability (Section 5.2.2), causing reduced calcification and growth rates (as in shallow water mussel larvae, Frieder et al. (2014)) (limited evidence, low confidence). Larvae originating at vents or seeps beneath upwelling regions may also be impaired by effects of hypoxia associated with expanding OMZ (Stramma et al., 2008791) during migration to the surface (limited evidence). Warming and its effects on climate cycles have the potential to alter patterns of larval transport and population connectivity through changes in circulation (Fox et al., 2016792) or surface generated mesoscale eddies (Adams et al., 2011793) (limited evidence; low confidence). Climate-induced changes in the distribution and cover of vent and seep foundation species may involve alteration of attachment substrate, food and refuge for the many habitat-endemic species that rely on them (Cordes et al., 2010794) and for the surrounding deep sea ecosystems which interact through transport of nutrients and microbes, movement of vagrant predators and scavengers, and plankton interactions (Levin et al., 2016795) (limited evidence; low confidence). There is, however, insufficient analysis of faunal symbiont and nutritional requirements, life histories, larval transport and cross-system interaction to quantify the extent of the consequences described above under future climate conditions. 

Cold water corals and sponges form large reefs at the deep seafloor mostly between 200–1500 m, creating complex 3D habitat that supports high biodiversity; they are found at the highest densities on hard substrates of continental slopes, canyons, and seamounts (Buhl-Mortensen et al., 2010). The meta-analysis reported in AR5 Chapter 6 Table 6-3 (Pörtner et al., 2014), identifies 10 studies involving 6 species of cold water corals that suggest low vulnerability to CO2 changes at RCP6.0 and medium vulnerability at RCP8.5, with negative effects starting at pCO2 of 445 µatm. 

Scleractinian corals have the capacity to acclimate to high CO2 conditions due to their capacity to upregulate the pH at the calcification site (Form and Riebesell, 2011; Rodolfo-Metalpa et al., 2015; Gori et al., 2016). The most widely distributed, habitat-forming species in deep water (e.g., Lophelia pertusa [renamed Desmophyllum pertusum) (Addamo et al., 2016)can continue to calcify at aragonite undersaturation and high CO2 levels projected for 2100 (750–1100 uatm) based on experiments (Georgian et al., 2016; Kurman et al., 2017) and observations along the natural gradient of carbon chemistry in their distributions (Fillinger and Richter, 2013; Movilla et al., 2014; Baco et al., 2017) (Appendix 1) (robust evidence, medium agreement, medium confidence) and thus appear to be able to acclimate to rising CO2 levels (Hennige et al., 2015). However, net calcification rates (difference between calcification and dissolution) of L. pertusa exposed to aragonite-undersaturated conditions (Ωarag < 1, where Ωarag =aragonite saturation state) often decreases to close to zero or even becomes negative (Lunden et al., 2014; Hennige et al., 2015; Büscher et al., 2017), with genetic variability underpinning ability to calcify at low aragonite saturation states (Kurman et al., 2017). Additionally, skeletons become longer, thinner and weaker (Hennige et al., 2015), and bioerosion is enhanced (e.g., by bacteria, fungi, annelids and sponges) (Schönberg et al., 2017), exacerbating effects of dissolution of the skeleton. L. pertusa can calcify when exposed to multiple environmental stresses in the laboratory (Hennige et al., 2015; Büscher et al., 2017), but cannot survive with warming above water temperatures of 14°C–15oC or oxygen concentrations below 1.6 ml l-1 in the Gulf of Mexico, 3.3 ml l-1 in the north Atlantic, 2 ml l-1 in the Mediterranean, and 0.5–1. 5 ml l-1 in the SE Atlantic (Brooke et al., 2013; Lunden et al., 2014; Hanz et al., 2019), highlighting the existence of critical thresholds for cold water coral populations living at the edge of their tolerance. The role of temporal dynamics, species-specific thermal tolerances, and food availability in mediating the response to combinations of stressors is recognised but is still poorly studied under in situ conditions (Lartaud et al., 2014; Naumann et al., 2014; Baco et al., 2017).

Sponges also form critical habitat in the deep ocean but are much less well studied than cold-water corals with respect to climate change. The geologic record, modern distributions and evolutionary and metabolic pathways suggest that sponges are more tolerant to warm temperatures, high CO2 and low oxygen than are cold-water corals (Schulz et al., 2013). One habitat forming, deep sea sponge along with its microbiome (microbial inhabitants) has been shown in laboratory experiments to tolerate a 5°C increase in temperature, albeit with evidence of stress (Strand et al., 2017), while ocean acidification (pH 7.5) reduces the feeding of two deep sea demosponge taxa (Robertson et al., 2017). 

Generally, the deep sea areas where cold water corals may be found are projected to be exposed to multiple climate hazards in the 21st century because of the projected ocean warming, oxygen loss, and decrease in POC flux (Table 5.5) under scenarios of greenhouse gas emissions. The average changes in these climate hazards for coral-water corals are projected to be almost halved under RCP2.6 relative to RCP8.5 (Table 5.5). Under RCP8.5, 95 ± 2% (95% CI) of cold-water coral habitats are projected to experience animal biomass decline (–8.6 ± 2.0%) globally by 2091–2100 relative to 2006–2015, driven by a projected 21 ± 9% drop in POC flux (medium confidence) (Jones et al., 2014). However, nutritional co-reliance of cold-water corals on zooplankton (Höfer et al., 2018) and carbon fixation by symbiotic microbes (Middelburg et al., 2015), is not incorporated into the models, adding uncertainty to these estimates. Regionally, suitable habitat for coral-water corals in the NE Atlantic is projected to decrease with multiple climatic hazards (warming, acidification, decreases in oxygen and POC flux) under RCP8.5 for 2081–2100 (FAO, 2019), with up to 98% loss of suitable habitat by 2099 due to shoaling aragonite saturation horizons. In the Southern hemisphere, a tolerance threshold of 7°C and decline of aragonite saturation below that required for survival (Ωarag <0.84) can cause large loss of cold water corals habitat (Solenosmilia variabilis) on seamounts off Australia and New Zealand under future projections of warming and acidification to 2099 at RCP4.5 and nearly complete loss under RCP8.5 (Thresher et al., 2015). 

Overall, cold water corals can survive conditions of aragonite-undersaturation associated with ocean acidification but sensitivity varies among species and skeletons will be weakened (medium confidence). The largest impacts on calcification and growth will occur when aragonite saturation is accompanied by warming and/or decrease in oxygen concentration beyond the tolerance limits of these corals (medium confidence). Given present day occurrence of 95% of cold water corals above the aragonite saturation horizon (Guinotte et al., 2006) and that no adaptation has been detected with regard to increased dissolution of exposed aragonite (Eyre et al., 2014), there is limited scope for the non-living components of cold water corals and for the large, non-living reef framework that comprises deep water reefs to avoid dissolution under RCP8.5 in the 21st century (high confidence). Multiple climatic hazards of warming, deoxygenation, aragonite under-saturation and decrease in POC flux are projected to negatively affect cold water corals worldwide from the present day by 2100 (high confidence). Uncertainty remains in the adaptive capacity of living cold water corals to cope with these changes and in the influence of altered regional current patterns on connectivity (Fox et al. 2016; Roberts et al., 2017). Sponges and the habitat they form may be less vulnerable than cold water corals to warming, acidification and deoxygenation that will occur under RCP8.5 in 2100 (low confidence). 

This section synthesises the assessment of climate impacts on open ocean and deep seafloor ecosystem structure and functioning and the levels of risk under future conditions of global warming (see SM5.2). The format for Figure 5.16 matches that of Figure 19.4 of AR5 (Pörtner et al., 2014) and Figure 3.20 of SR15 (Hoegh-Guldberg et al., 2018), indicating the levels of additional risk as colours (white, yellow, red and purple). Each column in Figure 5.16 indicates how risks increase with ocean warming, acidification (OA), deoxygenation, and POC flux with a focus on present day conditions (2000s) and future conditions by the year 2100 under low (RCP2.6) and high (RCP8.5) CO2 emission scenarios. The transition between the levels of risk to each type of ecosystem is estimated from key evidence assessed in earlier parts of this chapter (Sections 5.2.2, 5.2.3, 5.2.4). SST is chosen to provide an indication of the changes in all these variables because it is closely related to cumulative carbon emission (Gattuso et al., 2015) which is the main climatic driver of the hazards. SST scales with Global Mean Surface Temperature (GMST) by a factor of 1.44 according to changes in an ensemble of RCP8.5 simulations; with an uncertainty of about 4 % in this scaling factor based on differences between the RCP2.6 and RCP8.5 scenarios. The transition values may have an error of ±0.3°C depending on the consensus of expert judgment. The deep seafloor embers are generated based on earth system model projection of climate variables to the seafloor under RCP2.6 and RCP8.5 scenarios, and then translated to RCP associated change in SST. The assessed confidence in assigning the levels of risk at present day and future scenarios are low, medium, high and very high levels of confidence. A detailed account of the procedures involved in the ember for each type of ecosystem, such as their exposure to climate hazards, sensitivity of key biotic and abiotic components, natural adaptive capacity, observed impacts and projected risks, and regional hotspots of vulnerability is provided in the SM5.2 and Table 5.5. The risk assessment for cold water corals is in agreement with the conclusions in AR5 Chapter 6.3.1.4.1, although more recent literature is assessed in Box 5.2 and Table SM5.5. 

Overall, the upper ocean (0−700 m) and 700−2000 m layers have both warmed from 2004 to 2016 (virtually certain) and the abyssal ocean continues to warm in the Southern Hemisphere (high confidence). The ocean is stratifying; observed warming and high-latitude freshening are both surface intensified trends making the surface ocean lighter at a faster rate than deeper in the ocean (high confidence) (Section 5.2.2.2). It is very likely that stratification in the upper few hundred meters of the ocean will increase significantly in the 21st century. It is virtually certain that ocean pH is declining by ~0.02 pH units per decade where time series observations exist (Section 5.2.2.3). The anthropogenic pH signal has already emerged over the entire surface ocean (high confidence) and emission scenarios are the most important control of surface ocean pH relative to internal variability for most of the 21st century at both global and local scale (virtually certain). The oxygen content of the global ocean has declined by about 0.5−3.3% in 0−1000 m layer (Section 5.2.2.4). Over the next century oxygen declines of 3.5% by 2100 are predicted by CMIP5 models globally (medium confidence), with low confidence at regional scales, especially in the tropics. The largest changes in the deep sea will occur after 2100 (Section 5.2.2.3). CMIP5 models project a decrease in global NPP (medium confidence) with increases in high-latitude (low confidence) and decreases in low latitude (medium confidence) (Section 5.2.2.6) in response to changes in ocean nutrient supply (Section 5.2.2.5). These models also project reductions by 8.9−15.8% in the globally integrated POC flux for RCP8.5, with decreases in tropical regions and increases at higher latitudes (medium confidence), affecting the organic carbon supply to the deep sea floor ecosystems (high confidence) (Section 5.2.2.6). However, there is low confidence on the mechanistic understanding of how climatic drivers will affect the different components of the biological pump in the epipelagic ocean (Table 5.4). Therefore, the exposure to hazard for epipelagic ecosystems ranges from moderate (RCP2.6) to high (RCP8.5), with uncertain effects and tolerance of planktonic organisms, fishes and large vertebrates to interactive climate stressors. Major risks are predicted for declining productivity and fish biomass in tropical and subtropical waters (RCP8.5) (SM5.2). 

The climatic hazards for pelagic organisms from plankton to mammals are driving changes in eco-physiology, biogeography and ecology and biodiversity (high confidence) (Section 5.2.3.1). Observed and projected population declines in the equator-ward range boundary (medium confidence), expansion in the poleward boundary (high confidence), earlier timing of biological events (high confidence), overall shift species composition (high confidence) and decreases in animal biomass (medium confidence), are consistent with expected responses to climate change (Section 5.2.3; Figure 5.13). It is likely that increased OA has not yet caused sufficient reduction in fitness to decrease abundances of calcifying phytoplankton and zooplankton, but is very likely (high confidence) that calcifying planktonic organisms will experience great decreases in abundance and diversity under high emission scenarios by the end of the century. Therefore, impacts to the epipelagic ecosystems are already observed in the present day (Figure 5.16). Based on simulation modelling and experimental findings, the combined effects of warming, ocean deoxygenation, OA and changes in NPP in the 21st century are projected to exacerbate the impacts on the growth, reproduction and mortality of fishes, and consequently increase the risk of population decline (high confidence) (Section 5.2.3.1). There may be some capacity for adjustment and evolutionary adaptation that lowers their sensitivity to warming and decrease in oxygen (low confidence). However, historical responses in abundance and ranges of marine fishes to ocean warming and decrease in oxygen in the past suggest that adaptation is not always sufficient to mitigate the observed impacts (medium confidence) (Section 5.2.3) (SM5.2). 

Despite its remoteness, most of the deep seafloor ecosystems already have or are projected to experience rising temperatures and declining oxygen, pH and POC flux beyond natural variability within the next half century (See Section 5.2.4). On slopes, seamounts and canyons these changes are projected to be much larger under RCP8.5 than under RCP2.6 (high confidence), with greatest effects on seafloor community diversity and function from expansion of low oxygen zones and aragonite undersaturation (medium confidence). As critical thresholds of temperature, oxygen and CO2 are exceeded, coral species will alter their depth distributions, non-living carbonate will experience dissolution and bioerosion, and stress will be exacerbated by lower food supply. These changes are projected to cause loss of cold water coral habitat with highest climate hazard in the Arctic and north Atlantic Ocean (medium confidence), while sponges may be more tolerant (Box 5.2) (low confidence). Projected changes in food supply to the seafloor at abyssal depths combined with warmer temperatures are anticipated to cause reductions in biomass and body size (medium confidence) that could affect the carbon cycle in this century under RCP8.5 (low confidence). Even at hydrothermal vents and methane seeps, some dominant species such as mussels may be vulnerable to reduced photosynthetically-based food supply or have planktonic larvae or oxidising symbionts that are negatively affected by warming, acidification and oxygen loss (low confidence). 

Widespread attributes of deep seafloor fauna (e.g., great longevity, high levels of habitat specialisation including well-defined physiological tolerances and thresholds, dependence on environmental triggers for reproduction, and highly developed mutualistic interactions) can increase the vulnerability of selected taxa to changing conditions (FAO, 2019) (medium confidence). However, some deep sea taxa (e.g., foraminifera and nematodes) may be more resilient to environmental change than their shallow-water counterparts (low confidence). Observations, experiments and model projections indicate that impacts of climate change have or are expected to take place in this century, indicating a transition from undetectable risk to moderate risk at <1.5oC warming of sea surface temperature for continental slope, canyon and seamount habitats, and for cold water corals (Figure 5.16). 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) (Figure 5.16). 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 experiencing a transition from moderate to high risk below 3oC (SM5.2).

There is political and scientific agreement on the need for a wide range of mitigation actions to avoid dangerous climate change (UNEP, 20171616; IPCC, 20181617). Opportunities to reduce emissions by the greater use of ocean renewable energy are identified in Section 5.4.2.3.2. Here, in accordance with the approved scoping of this report, the assessment of mitigation options is limited to the management of natural ocean processes, that is, requiring policy intervention, with a focus on ‘blue carbon’. Natural processes per se, although important to the climate system and the global carbon cycle, are not a mitigation response. Two management approaches are possible: first, actions to maintain the integrity of natural carbon stores, thereby decreasing their potential release of greenhouse gases, whether caused by human or climate-drivers; and second, through actions that enhance the longterm (century-scale) removal of greenhouse gases from the atmosphere by marine systems, primarily by biological means. 

These mitigation approaches match those proposed using terrestrial natural processes (Griscom et al., 20171618), with extensive afforestation and reforestation included in all climate models that limit future warming to 1.5⁰C (de Coninck et al., 2018). As on land, reliable carbon accounting is a critical consideration (Grassi et al., 20171619), together with confidence in the longterm security of carbon storage. The feasibility of climatically-significant (and societally acceptable) mitigation using marine natural processes therefore depends on a robust quantitative understanding of how human actions can affect the uptake and release of greenhouse gases from different marine environments, interacting with natural biological, physical and chemical processes. Whilst CO2 is the most important greenhouse gas, marine fluxes of methane and nitrous oxide can also be important, for both coastal regions and the open ocean (Arévalo-Martínez et al., 20151620; Borges et al., 20161621; Hamdan and Wickland, 20161622).

The term ‘blue carbon’ was originally used to cover biological carbon in all marine ecosystems (Nellemann et al., 20091623). Subsequent use of the term has focused on carbon-accumulating coastal habitats structured by rooted plants, such as mangroves, tidal salt marshes and seagrass meadows, that are relatively amenable to management (McLeod et al., 20111624; Pendleton et al., 20121625; Thomas, 20141626; Macreadie et al., 2017a1627; Alongi, 20181628; Windham-Myers et al., 20191629; Lovelock and Duarte, 20191630). Comparisons across the full range of freshwater and saline wetland types are assisted by standardised approaches (Nahlik and Fennessy, 20161631; Vázquez-González et al., 20171632). Seaweeds (macroalgae) can also be considered as coastal blue carbon (Krause-Jensen and Duarte, 20161633; Krause-Jensen et al., 20181634; Raven, 20181635), however, because of differences in their carbon processing, their climate mitigation potential is assessed separately within Section 5.5.1.2 below.

In the open ocean, the biological carbon pump is driven by the combination of photosynthesis by phytoplankton and downward transfer of particulate carbon by a variety of processes (Henson et al., 20101636; DeVries et al., 20171637); it results in large-scale transfer of around 10 GtC yr-1 carbon from near-surface waters to the ocean interior (Boyd et al., 20191638). Most of this carbon is respired in the mesopelagic and contributes to the 37,000 GtC inventory of DIC, with around ~0.1 GtC yr-1 eventually being permanently removed in deep sea sediments (Cartapanis et al., 20181639). In addition, the microbial carbon pump (Jiao et al., 20101640) produces refractory dissolved organic molecules throughout the water column at a rate of around 0.4 GtC yr-1 (Jiao et al., 2014b1641), which due to their residence time of hundreds to thousands of years maintain the 700 GtC inventory of dissolved organic carbon in the ocean (Jiao et al., 20101642; Jiao et al., 2014a1643; Legendre et al., 20151644; Jiao et al., 2018a1645). The natural removal of carbon by the various carbon pumps is closely balanced by upwelling and outgassing, with the ocean a moderate source of CO2 under pre-industrial conditions (Ciais et al., 20131646). The mitigation potential of managing natural processes in the open ocean is only briefly assessed here (Section 5.5.1.3).

Gattuso et al. (2018)1647 provide an overview assessment of the environmental, technical and societal feasibilities of using a range of ocean management actions to reduce climate change and its impacts. Their results for nine actions based on natural processes are summarised in Figure 5.23, also including marine renewable energy (wind, wave and tidal) for comparison. Eight semi-quantitative criteria were used to assess each action: maximum potential effectiveness by 2100 in reducing climatic drivers (ocean warming, ocean acidification and SLR), assuming full theoretical implementation; technological readiness and lead time to full potential effectiveness (subsequently combined as technical feasibility); duration of benefits; co-benefits; trade-offs (originally described as dis-benefits); cost-effectiveness; and governability (capability of implementation, and management of any associated conflicts). Here, governability is considered as a constraint (governability challenges) reversing the scoring scale used by Gattuso et al. (2018)1647

Global measures (circles in Figure 5.23) can be regarded as mitigation, reducing drivers; local measures (rectangles), are primarily EbA, reducing impacts (Section 5.5.2), although they may also contribute to mitigation; two actions were considered at both scales. Gattuso et al. (2018) did not consider the effects of actions on ocean oxygenation, notwithstanding the importance of deoxygenation as a component of climate change. Additional detail is given in SM5.4.

Recent reviews of the scope for using natural processes in the open ocean for climate mitigation are provided by Keller (2019a) and GESAMP (2019). The summary assessment given here is limited to direct and indirect biologically-based approaches, consistent with the scoping of this report and the major governance constraints on the large-scale application of open ocean interventions. 

Current NPP by marine phytoplankton is estimated to be 58 ± 7 GtC yr–1 (Legendre et al., 2015), similar to terrestrial primary production and around 6 times greater than anthropogenic emissions (Le Quere et al. (2016). However, over 99% of the biologically-fixed carbon returns to the atmosphere over a range of timescales (Cartapanis et al., 2018).

The direct method of increasing marine productivity involves adding land-derived nutrients that may currently limit primary production, particularly iron. This approach has been investigated experimentally, by modelling and by observations of natural system behaviour (Keller et al., 2014a; Bowie et al., 2015; Tagliabue et al., 2017). The 13 experimental studies to date (seven in the Southern Ocean, five in the Pacific, and one in the sub-tropical Atlantic) have shown that primary production can be, but is not always, enhanced by the addition of iron (Boyd et al., 2007; Yoon et al., 2016; GESAMP, 2019). 

The difficulties arise in demonstrating the time-scale of additional carbon removal, and in obtaining information on the consequences of the fertilisation for other marine ecosystem components, including ocean acidification and other potential side-effects (Williamson and Turley, 2012). Modelling studies (Aumont and Bopp, 2006) indicate that the climatic benefits could be relatively short-lived. Furthermore, public and political acceptability for ocean fertilisation is low (Williamson et al., 2012; Boyd and Bressac, 2016; Williamson and Bodle, 2016; Fuentes-George, 2017; McGee et al., 2018). Ocean iron fertilisation is regulated by the London Protocol, with amendments prohibiting such action unless constituting legitimate scientific research authorised under permit (see Section 5.5.4.1). There are additional governance constraints for the Southern Ocean where ocean iron fertilisation is theoretically considered to be most effective (Robinson et al., 2014).

Open ocean fertilisation by macro-nutrients (e.g., nitrate) has also been proposed, with modelled potential for gigaton-scale carbon removal (Harrison, 2017). Similar technical and governance considerations apply with regard to the quantification of mitigation benefits, the monitoring of potential adverse impacts, and the political acceptability of large-scale deployment. This approach would also involve higher costs, because of the much greater quantities of nutrients required (Williamson and Turley, 2012).

The indirect method of enhancing marine productivity uses physical devices to increase upwelling, thereby increasing the supply of a wide range of naturally-occurring nutrients from deeper water. This technique risks releasing additional CO2 to the atmosphere, reducing its potential for climate mitigation (Bauman et al., 2014). There may also be other undesirable climatic consequences, including disruption of regional weather patterns and long-term warming rather than cooling, if enhanced upwelling is deployed at large scale (Kwiatkowski et al., 2015).

Because of the many technical, environmental and governance issues relating to marine productivity enhancement, by either direct fertilisation or upwelling, there is low confidence that such open ocean manipulations provide a viable mitigation measure.

The AR5 concluded, with high agreement but limited evidence, that climate change impacts on coastal human settlements and communities could be reduced through coastal adaptation activities (Wong et al., 2014a). The limited evidence of the context-specific application of adaptation principles to support the assessment was highlighted as a knowledge gap for future research. This assessment reports progress made with developing such evidence and assesses human adaptation response to climate change in ecosystems, coastal communities and marine environments. 

Components of human adaptation responses include risk assessment, risk reduction, and pathways towards resilience (Cross-Chapter Box 2; Chapter 1.6). Residual risk remains where hazard, vulnerability and exposure intersect, subsequent to an adaptation pathway response. Here we focus on adaptation responses within ecosystems and in human systems, as framed in Chapter 1, and defined by: 

• Nature-based or ecosystem-based adaptation (5.5.2.1). The use of biodiversity and ecosystem services as part of an overall adaptation strategy to help people to adapt to the adverse effects of climate change. EbA uses the range of opportunities for the sustainable management, conservation, and restoration of ecosystems to provide services that enable people to adapt to the impacts of climate change (Narayan et al., 2016; Moosavi, 2017).
• Human systems – Built environment adaptation (5.5.2.3.1) Adaptation solutions pertaining to coastal built infrastructure and the systems that support such infrastructure (Mutombo and Ölçer, 2016; Forzieri et al., 2018).
• Human systems – Socioinstitutional adaptation (5.5.2.3) Adaptation responses within human social, governance and economic systems and sectors (Oswald Beiler et al., 2016; Thorne et al., 2017). This includes, but is not limited to community-based adaptation by coastal communities (5.5.2.3.2) based on empowering and promoting the adaptive capacity of communities, through appropriate use of context, culture, knowledge, agency, and community preferences (Archer et al., 2014; Shaffiril et al., 2017)

To avoid duplication, detailed consideration of adaptation responses to SLR and extreme events (including heat waves, and compound and cascading events) are avoided here, as they are covered by Chapter 4 and Chapter 6, respectively. Tables 5.7 and 5.8 provide a summary assessment of climate change impacts, human adaptation response and benefits in ecosystems and human systems respectively. Details of the assessed literature are in SM Table 5.7. Climate drivers and impacts reported in the adaptation literature are consistent with those reported in Sections 5.2 and 5.3. Physical impacts include the disruption of physical coastal processes, like sediment dynamics, leading to, for example, erosion, flooding and coastal infrastructure damage (see Tables 5.7 and 5.8). Ecological impacts include the loss of ecosystems and biodiversity (Sections 5.2.3, 5.2.4, 5.3), which affected provision of ecosystem services, like coastal protection or food provision. The most commonly reported non-climate human drivers are growing human coastal populations (Elliff and Silva, 2017; van Oppen et al., 2017a; Gattuso et al., 2018) with poorly planned or managed urban development (Barbier, 2015; Wigand et al., 2017), land use change (Robins et al., 2016), loss of ecosystems (Runting et al., 2017), socioeconomic vulnerability (Broto et al., 2015; Bennett et al., 2016) of many coastal communities, ineffective governance and knowledge gaps for implementation.

This section assesses adaptation response in coastal ecosystems, beginning with biological adaptation in species, and followed by a summary assessment of EbA as a response to climate change. 

Anthropogenic global change is impacting all warm water corals and the reef structures (Section 5.2.2.3.3; IPCC 5th Assessment Report (AR5)). These impacts are rapidly increasing in scale and intensity, exposing coral reefs to enhanced degradation rates and diminishing capacities to maintain ecological resilience, to absorb disturbances, and to adapt to the changes (Box 5.1) (Graham et al., 20141910; Rinkevich, 2015a1911; Harborne et al., 20171912). With the growing awareness that traditional reef conservation measures are insufficient to address climate change impacts on coral reefs (Section 5.2.2.1), adaptation interventions to enhance the resilience of coral reefs are being called for (Rinkevich, 19951913; Rinkevich, 20001914; Barton et al., 20171915). Intervention strategies that are still at the ‘proof-of-concept’ stage, include: ‘assisted colonisation’ – actively moving species that are confined to disappearing habitats (Hoegh-Guldberg et al., 20081916; Chauvenet et al., 20131917); ‘assisted evolution’ – developing corals resistant to climate change via accelerated natural evolution processes (van Oppen et al., 20151918); assisted coral chimerism (Rinkevich, 20191919); novel coral symbiont associations (McIlroy and Coffroth, 20171920); and coral microbiome manipulation (Bourne et al., 20161921; Sweet and Bulling, 20171922; van Oppen et al., 2017b1923). In contrast, the ‘coral gardening’ approachs⁠—coral farmed in nurseries and transplanted using a range of tactics to increase survivability, growth rates and reproduction (Rinkevich, 20061924; Rinkevich, 20141925)—is already in use. Other interventions that have already been implemented in some coral reefs, such as the use of artificial reefs (Ng et al., 2017) are limited in impacts, and all are also revealing considerable challenges (Riegl et al., 20111926; Coles and Riegl, 20131927; Ferrario et al., 20141928). 

Many of the alternative interventions that aim to increase the climate resilience of coral reefs involve culturing, selectively breeding and transplanting corals to enhance the adaptability of reef organisms to climate change, for example, by supporting the natural poleward range expansion of corals (West et al., 20171933; Vergés et al., 20191934). Advances in reef restoration techniques have been made in the last two decades (Rinkevich, 20141935; Lirman and Schopmeyer, 20161936), but assessments of the effectiveness of these techniques have mostly focused on the short-term feasibility of the technique (Frias-Torres and van de Geer, 20151937; Lirman and Schopmeyer, 20161938; Montoya Maya et al., 20161939; Jacob et al., 20171940; Rachmilovitz and Rinkevich, 20171941), while longer-term evaluation in the context of all the pillars of sustainable development (Section 5.4.2) is limited (Rinkevich, 2015b1942; Barton et al., 20171943; Flores et al., 20171944; Hein et al., 20171945). These alternative interventions, primarily the coral gardening approach, face two challenges. The first is scaling up; currently, these interventions have been tested at scales of hundreds of meters, while application at larger scale is lacking (Rinkevich, 20141946). The second challenge (Box 5.5, Figure 1) is the effectiveness of active reef restoration to mitigate or rehabilitate global change impacts (Shaish et al., 2010a1947; Schopmeyer et al., 20121948; Coles and Riegl, 20131949; Hernández-Delgado et al., 20141950; Rinkevich, 2015a1951; Wilson and Forsyth, 20181952) and whether it can keep up with rising sea levels (Perry et al., 20181953), especially in low-lying ocean states. 

Altogether, coral reefs of the future will not resemble those of today because of the projected decline and changes in the composition of corals and associated species in the remaining reefs (Section 5.3.4, Box 5.5 Figure 1) (Rinkevich, 20081954; Ban et al., 20141955) (high confidence). The very high vulnerability of coral reefs to warming, ocean acidification, increasing storm intensity and SLR under climate change (AR5 WG2), including enhanced bioerosion (Schönberg et al., 20171956) (high confidence) point to the importance of considering both mitigation (Section 5.5.1) and adaptation (Section 5.3.3.6) for coral reefs. Extensive research has explored adaptation measures involving the cultivation and transplantation of corals; however, the literature contains limited evidence on the comprehensive analysis of the relative costs and benefits of these interventions across the economic, ecological, social and cultural dimensions (Bayraktarov et al., 20161957; Flores et al., 20171958; Linden and Rinkevich, 20171959).

Many of the world’s great cities lie within the coastal region, and climate change impacts put these cities, their inhabitants and their economic activities at risk. Section 5.5.2.2 assesses the impacts of climate change, adaptation response and benefits upon human systems, including coastal communities, built infrastructure, fisheries and aquaculture, coastal tourism, government and health systems. Table 5.8 provides a summary of the assessment, with citations provided in the Supplementary Material Table 5.7.

Poorly planned (Ataur Rahman and Rahman, 2015), located (Abedin et al., 2014; Betzold and Mohamed, 2017; Linkon, 2018) and managed urban settlements or human systems, driven by growing human coastal populations (Perkins et al., 2015; Moosavi, 2017; Carter, 2018) and compounded by the disruption of coastal and catchment physical processes (Nagy et al., 2014; Broto et al., 2015; Marfai et al., 2015; Kabisch et al., 2017) and pollution (Zikra et al., 2015; Peng et al., 2017) are major human drivers of change compounding the impacts of climate change.

Coastal communities, built infrastructure and fisheries and aquaculture (Table 5.8) are likely to be significantly affected through the disruption of coastal physical processes (DasGupta and Shaw, 2015; Betzold and Mohamed, 2017; Hagedoorn et al., 2019) leading to coastal erosion, flooding, salt water intrusion and built infrastructure damage (Dhar and Khirfan, 2016; Hobday et al., 2016a; Jurjonas and Seekamp, 2018) (robust evidence, high agreement). Ecosystem degradation and biodiversity loss will further compound impacts in coastal communities and fisheries and aquaculture (Ataur Rahman and Rahman, 2015; Petzold and Ratter, 2015; Dhar and Khirfan, 2016), with sub-lethal species impacts like changes in the productivity and distribution of fisheries target species reported for the latter (Gourlie et al., 2018; Nursey-Bray et al., 2018; Pinsky et al., 2018) (high confidence). This is likely to result in decreased access to ecosystem services (Asch et al., 2018; Cheung et al., 2018b; Finkbeiner et al., 2018) (medium evidence, high agreement), local declines in agriculture and fisheries (Cvitanovic et al., 2016; Faraco et al., 2016) (high confidence) and livelihood impacts (Harkes et al., 2015; Busch et al., 2016; Valmonte-Santos et al., 2016) (high confidence) in coastal communities and fisheries and aquaculture, particularly increased food insecurity and health risk in the latter (high confidence). These livelihood impacts are likely to increase social vulnerability (high confidence). Businesses within coastal communities are likely to experience disruptions and losses (robust evidence, high agreement).

Adaptation action in pursuit of a climate resilient development pathway is likely to have a deeper transformative outcome than stepwise or ad hoc responses (Cross-Chapter Box 2 in Chapter 1). Recent literature highlighting the effectiveness of components of adaptation planning includes quantitative assessments of vulnerability in ecosystems (Kuhfuss et al., 2016), species (Cheung et al., 2015; Cushing et al., 2018), and communities (Islam et al., 2013; Himes-Cornell and Kasperski, 2015b), and integrated assessments of all of the above (Peirson et al., 2015; Kaplan-Hallam et al., 2017; McNeeley et al., 2017; Ramm et al., 2017; Mavromatidi et al., 2018). Seasonal and decadal forecasting tools have improved rapidly since AR5, especially in supporting management of living marine resources (Payne et al., 2017) and modelling to support decision making processes (Čerkasova et al., 2016; Chapman and Darby, 2016; Jiang et al., 2016; Justic et al., 2016; Joyce et al., 2017; Mitchell et al., 2017). Decision making processes are supported by economic evaluations (Bujosa et al., 2015; Jones et al., 2015), evaluations of ecosystem services (MacDonald et al., 2017; Micallef et al., 2018), participatory processes (Byrne et al., 2015) and social learning outcomes, the development of adaptation pathways, frameworks and decision making (Buurman and Babovic, 2016; Dittrich et al., 2016; Michailidou et al., 2016a; Osorio-Cano et al., 2017; Cumiskey et al., 2018), and indicators to support evaluation of adaptation actions (Carapuço et al., 2016; Nguyen et al., 2016) through monitoring frameworks (Huxham et al., 2015). Climate change adaptation responses are more effective when developed within institutional frameworks that include effective planning and cross-sector integration.

Evidence-based decision making for climate adaptation is strongly supported in the literature (Endo et al., 2017; Thorne et al., 2017) through better understanding of coastal ecosystems and human adaptation responses (Dutra et al., 2015; Cvitanovic et al., 2016), as well as consideration of non-climate change related factors. Relevant research includes the topics of: multiple-stakeholder participatory planning (Archer et al., 2014; Abedin and Shaw, 2015); trans-boundary ocean management (Gormley et al., 2015; Williams et al., 2016); ecosystem-based adaptation (Hobday et al., 2015; Dalyander et al., 2016; McNeeley et al., 2017; Osorio-Cano et al., 2017); and community-based adaptation with socioeconomic outcomes (Merkens et al., 2016). Research on applying ‘big data’ and high end computational capabilities could also help develop a comprehensive understanding of climate and non-climate variables in planning for coastal adaptation (Rumson et al., 2017). New knowledge from these research areas could substantially improve planning, implementation and monitoring of climate adaptation responses for marine systems, if research processes are participatory and inclusive (medium confidence).

Despite such interest, evaluations of the planning, implementation and monitoring of adaptation actions remain scarce (Miller et al., 2017). In a global analysis of 401 local governments, only 15% reported on adaptation actions (mostly large cities in high income countries), and 18% reported on planning towards adaptation policy (Araos et al., 2016). Thus, integrated adaptation planning with non-climate change related impacts remains an under-achieved ambition, especially in developing countries (Finkbeiner et al., 2018). Challenges reported for adaptation planning include uncoordinated, top-down approaches, a lack of political will, insufficient resources (Elias and Omojola, 2015; Porter et al., 2015), and access to information (Thorne et al., 2017).

Characteristics of successful adaptation frameworks include: a robust but flexible approach, accounting for deep uncertainty through well-coordinated participatory processes (Dutra et al., 2015; Jiao et al., 2015; Buurman and Babovic, 2016; Dittrich et al., 2016); well-developed monitoring systems (Barrett et al., 2015; Bell et al., 2018b); and taking a whole systems approach (Sheaves et al., 2016), with the identification of co-benefits for human development and the environment (Wise et al., 2016). The coastal adaptation framework literature is dominated by Australian, North American and European cities, with fewer studies from African and Caribbean sites, least developed countries and SIDS (Kuruppu and Willie, 2015; Torresan et al., 2016). 

In contrast with the many examples of proposed frameworks for climate resilient coastal adaptation, few studies have assessed their success, possibly due to the time-lag between implementation, monitoring, evaluation and reporting. Nevertheless, there is substantial support for ‘no regrets’ approaches addressing both proximate and systematic underlying drivers of vulnerability (Sánchez-Arcilla et al., 2016; Pentz and Klenk, 2017; Zandvoort et al., 2017) with leadership, adaptive management, capacity and the monitoring and evaluation of actions considered useful in governance responses (Dutra et al., 2015; Doherty et al., 2016). More extensive learning processes could help build decision makers’ capacity to tackle systemic drivers, guide pursuance climate change appropriate policies (Barange et al. 2018) and to scrutinise potentially maladaptive infrastructural investments (Wise et al., 2016). More effective coordination across a range of stakeholders, within and between organisations, especially in developing countries, would strengthen the global coastal adaptation response (medium confidence).

Education can help improve understanding of issues related to climate change and increase adaptive capacity (Fauville et al., 2011; Marshall et al., 2013; von Heland et al., 2014; Pescaroli and Magni, 2015; Tapsuwan and Rongrongmuang, 2015; Wynveen and Sutton, 2015). Participatory processes can facilitate the development of networks between coastal communities and environmental managers for the purposes of developing and implementing adaptation strategies (Wynveen and Sutton, 2015). Education, combined with other forms of institutional support empowers fisheries and aquaculture communities (Table 5.8) to make informed adaptation decisions and take action (medium evidence, medium agreement).

Local knowledge and Indigenous knowledge systems can complement scientific knowledge by, for example, improving community ability to understand their local environment (Andrachuk and Armitage, 2015), forecast extreme events (Audefroy and Sánchez, 2017) and help to increase community resilience (Leon et al., 2015; Sakakibara, 2017; Cinner et al., 2018; Panikkar et al., 2018). Committing resources could strengthen local level adaptation planning (Alam et al., 2016; Novak Colwell et al., 2017) through the inclusion of cultural practices (Audefroy and Sánchez, 2017; Fatorić and Seekamp, 2017) and Indigenous knowledge systems (Kuruppu and Willie, 2015; von Storch et al., 2015). Local knowledge can, however, act as a barrier to adaptation where there is a strong dependency upon such knowledge for immediate survival, to the detriment of long-term adaptation planning (Marshall et al., 2013; Metcalf et al., 2015). There is evidence, however, to suggest that vulnerability in fisheries communities and coastal tourism operators with high levels of local knowledge is reduced where they have a correspondingly high level of adaptive capacity (Marshall et al., 2013). Resource users with high levels of local knowledge may also be able to identify signals of change within their environment, and recognise the need to adapt. In these instances, fishers with higher local knowledge are expected to demonstrate a higher adaptive capacity than fishers with lower local knowledge, and can be expected to progress towards developing new strategies to combat the impacts of climate change (Kittinger et al., 2012). In these instances, local knowledge acts to promote adaptation (medium confidence). 

Localised, individual-scale behaviors can aggregate rapidly and contribute to the global adaptation response. This can be supported by clear messaging that clarifies the role of individuals, households and local businesses in addressing climate change. Coastal communities can improve the co-production of climate change knowledge (medium evidence, good agreement) through the integration of knowledge systems (Table 5.8). In fisheries and aquaculture, better-informed decision making tools (medium evidence, medium agreement) are supported by improved participatory processes (high confidence), integrating knowledge systems (medium evidence, good agreement) and improving decision support frameworks (medium evidence, medium agreement). 

Challenges persist in conducting economic assessments for built infrastructure adaptation due to complicated uncertainties such as the accuracy of climate projections and limited information regarding paths for future economic growth and adaptation technologies. Annual investment and maintenance costs of protecting coasts were projected to be 12–71 billion USD (Hinkel et al., 2014), which was considered significantly less than damage costs in the absence of such action. In an analysis of twelve Pacific island countries, 57% of assessed built infrastructure was located within 500 m of coastlines, requiring a replacement value of 21.9 billion USD. Substantial coastal adaptation costs (and international financing) are likely to be required in these countries (medium confidence).

In West African fisheries, loss of coastal ecosystems and productivity are estimated to require 5–10% of countries’ GDP in adaptation costs (Zougmoré et al., 2016). Similarly, for Pacific Islands and Coastal Territories, fisheries adaptation will require significant investment from local governments and the private sector (Rosegrant et al., 2016), with adaptation costs considered beyond the means of most of these countries (Campbell, 2017). In SIDS, tourism could provide the funding for climate change adaptation, but concerns with creating investment barriers, assumptions around cost-effectiveness and consumer driven demand remain barriers (Hess and Kelman, 2017). MPAs with multiple co-benefits, are considered a cost-effective strategy (Byrne et al., 2015). In 2004, the annual cost of managing 20–30% of global seas as MPAs was estimated at between 5–19 billion USD, with the creation of approximately one million jobs (Balmford et al., 2004).

Estimating adaptation costs is challenging because of wide ranging regional responses and uncertainty (Dittrich et al., 2016). Despite these challenges, the protection from flooding and frequent storms that coral reefs provide has been quantified by (Beck et al., 2018), who estimated that without reefs, damage from flooding and costs from frequent storms would double and triple respectively, while countries from Southeast Asia, East Asia and Central America could each save in excess of 400 million USD through good reef management. Although quantifying global adaptation costs remains challenging because of a wide range of regional responses and contexts, it is likely that managing ecosystems will contribute towards reducing costs associated with climate change associated coastal storms (medium confidence). Further research evaluating natural infrastructure is required (Roberts et al., 2017) to better understand costs and benefits of EBA.

There is a broad range of reported barriers and limits to climate change adaptation for both ecosystems and human systems. Coastal ecosystem-based adaptation can be physically constrained by space requirements and coastal squeeze (Sutton-Grier et al., 2015; Robins et al., 2016; Sánchez-Arcilla et al., 2016; Ahmed et al., 2017; Peña-Alonso et al., 2017; Salgado and Martinez, 2017; Triyanti et al., 2017; Schuerch et al., 2018), while the pace of climate change may exceed the adaptive capacity of ecosystems, for example, SLR may outpace the vertical reef accretion rate (Beetham et al., 2017; Elliff and Silva, 2017; Joyce et al., 2017). One technical limit for coral reef adaptation is that tools have not yet been developed for large-scale implementation (van Oppen et al., 2017a). Ecosystems may also have physiological and ecological constraints which are exceeded by climate change impacts (Miller et al., 2017; Wigand et al., 2017), and the recovery periods of natural systems (Gracia et al., 2018) and for ecological succession (Salgado and Martinez, 2017) may be outpaced by climate change impacts. The performance of ecosystems in EBA projects may be inhibited by the poor condition of the ecosystem (Nehren et al., 2017), highlighting the importance of effective implementation (Salgado and Martinez, 2017).

Social and cultural norms with conflicting and competing values (Miller et al., 2017), public lack of knowledge on climate change and distrust of information sources (Wynveen and Sutton, 2015), as well as populations increasingly distanced from, and unconcerned about nature (Romañach et al., 2018), may constrain ecosystem-based adaptation response. Examples of governance adaptation constraints include: inadequate policy, governance and institutional structures (Sánchez-Arcilla et al., 2016; Miller et al., 2017; Wigand et al., 2017), limited capacity (Sutton-Grier et al., 2015; Thorne et al., 2017), ineffective implementation (Nguyen et al., 2017; Comte and Pendleton, 2018), and poor enforcement (Nguyen et al., 2017). Governance constraints are compounded by lack of finances (Miller et al., 2017), financial costs of design and implementation (Gallagher et al., 2015) and the high cost of coastal land (Gracia et al., 2018), although ecosystem-based adaptation is considered cheaper than human-made structures (Nehren et al., 2017; Salgado and Martinez, 2017; Vikolainen et al., 2017; Gracia et al., 2018).

Knowledge limitations can include a lack of data (Sutton-Grier et al., 2015; Wigand et al., 2017; Romañach et al., 2018), for example, when an absence of baseline data may undermine coastline management (Perkins et al., 2015). Scale-relevant information may be required for local decision making (Robins et al., 2016; Thorne et al., 2017) and to comply with localised design requirements (Vikolainen et al., 2017). Other knowledge barriers include inherent uncertainties in models (Schaeffer-Novelli et al., 2016) and complexity of coastal systems (Wigand et al., 2017). A more nuanced knowledge barrier is the disconnect between scientific, community and decision making processes (Romañach et al., 2018). 

Substantial knowledge gaps are reported for ecosystem-based adaptation, including restoration of coral reef systems as an adaptation tool (Comte and Pendleton, 2018), managing mangrove and human response to climate change (Ward et al., 2016), advancing coastal EBA science by quantifying ecosystem services (Hernández-González et al.), and evaluating natural infrastructure (Roberts et al., 2017). Few syntheses of the context-specific application and cost-effectiveness of EBA approaches are to be found in the literature (Narayan et al., 2016).

Human systems have similar limitations. Improved understanding of limitations in built infrastructure, beach nourishment and nature-based adaptation responses, especially with respect to cost effectiveness and resilience, would substantially aid shoreline stabilisation attempts (Mackey and Ware, 2018). For artisanal fisheries, a range of physical and socioinstitutional limits and barriers to adaptation have been reported, including increasing occurrence and severity of storms limiting fishing time, technologically poor boats and fishing equipment and lack of access to credit and markets, among others (Islam et al., 2013). Conflicting interests and values of stakeholders (Evans et al., 2016), the path-dependent nature of organisations and resistance to change (Evans et al., 2016) and inadequate collaboration and public awareness (Oulahen et al., 2018) have been reported as socioinstitutional barriers. A knowledge gap persists in understanding how such limits and barriers interact to suppress adaptation response.

In some communities, climate change may not be prioritised in the face of chronic, daily challenges to secure livelihoods (Esteban et al., 2017; Fischer, 2018) or risk severity may be underestimated due to a high frequency of exposure in the recent past (Esteban et al., 2017). In a world with competing risks and urgent priorities, some local inhabitants appear to be unable to avoid, or are willing to carry, the risk associated with a climate impact in order to meet other, more pressing needs. This example reflects the reality of many poor, informal settlement dwellers in coastal areas around the world (medium confidence). Other human system barriers to effective adaptation action include insufficient climate change knowledge, inappropriate coping strategies, high dependency upon natural resources, level of exposure to hazards and weak community networks (Islam et al., 2013; Nanlohy et al., 2015; Lohmann, 2016; Koya et al., 2017; Senapati and Gupta, 2017; Cumiskey et al., 2018).

In summary, it is concluded that the broad range of reported barriers and limits to climate change adaptation for ecosystem and human system adaptation responses (high confidence). Limitations include the space that ecosystems require, non-climatic drivers and human impacts that need to be addressed as part of the adaptation response, the lowering of adaptive capacity of ecosystems because of climate change, and slower ecosystem recovery rates relative to the recurrence of climate impacts, availability of technology, knowledge and financial support and existing governance structures (medium confidence). (5.5.2.5)

There are many global, regional, national and local governance structures with interests in climate-driven ocean warming, acidification, deoxygenation and SLR, and their impacts on marine ecosystems and dependent communities (Galland et al., 20122428; Stephens, 20152429; Fennel and VanderZwaag, 20162430; Diamond, 20182431). The legal, policy and institutional response is therefore shared by many institutions developed for a number of distinct but inter-related fields, including governance regimes for ocean systems, climate change, marine environment, fisheries and the environment generally. A changing ocean poses several scale-related challenges for these governance institutions and processes, arising from:  

• The global and transboundary scales of the major changes to ocean properties (temperature, circulation, oxygen loss, acidification, etc.), with variability in their local expression;
• The regional scales of changes in ecosystem services following from the changes in ocean properties (including services provided to humans living far from the coasts); 
• The global scales of land-based drivers of those changes (both greenhouse gas emissions and changes in ecosystems services), which often motivate policy responses (primarily at the national level) and behavioural responses (primarily at the community level); 
• The scale dependent need for coordinated responses by the different governance structures, to ensure their overall effectiveness (see also Chapter 1)

For all of these challenges, the scales of the climate-related issues may be poorly matched to the scales of most governance institutions and processes, making effective responses or proactive initiatives difficult. Sections 5.2 to 5.4 provide evidence, through case histories and thematic overviews, that illustrates these four types of challenges. In some cases, more than one type of challenge is illustrated in a single example, such as when a change in an amount or availability of an ecosystem service is discussed in the context of factors influencing the vulnerability of socio-ecological systems to climate change (Sections 5.2., 5.3 and 5.4).  

Existing ocean governance structures for the ocean already face multi-dimensional challenges because of climate change, and this trend of increasing complexity will continue (Galaz et al., 20122432). Current international governance regimes and structures for fisheries and the ocean environment do not yet adequately address the issues of ocean warming, acidification and deoxygenation (Oral, 20182433); Box 5.6). At the time of the initial development and adoption of these legal and governance regimes, minimal attention was given to climate change and the effects of carbon dioxide emissions on the ocean, with associated impacts on the interacting physical, chemical, biological properties of the ecosystems, and the resulting risks and vulnerabilities of dependent communities and economic sectors. In particular, the governance of ocean ABNJ is a major challenge (Levin and Le Bris, 20152434); the collaborative structures and mechanisms for environmental assessment in ABNJ need further development (Warner, 20182435) (high confidence). Negotiations are currently ongoing regarding a new international agreement for marine biodiversity of ABNJ (UNEP, 20162436).  

Table 5.9: Ocean Governance and Climate Change: Major Issues 

Acronyms and organisations: CBD, Convention on Biological Diversity; CCAMLR, Convention on the Conservation of Antarctic Marine Living Resources; CITES, Convention on International Trade in Endangered Species of Wild Fauna and Flora; IMO: International Maritime Organization; London Convention: Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter; London Protocol: 1996 Protocol to the Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter; MARPOL Convention: International Convention for the Prevention of Pollution from Ships; NDCs: Nationally Determined Contributions; OSPAR Convention: Convention for the Protection of the Marine Environment of the North-East Atlantic; UN Fish Stocks Agreement: The Agreement for the Implementation of the Provisions of the United Nations Convention on the Law of the Sea of 10 December 1982 relating to the Conservation and Management of Straddling Fish Stocks and Highly Migratory Fish Stocks; UNCLOS: United Nations Convention on the Law of the Sea; UNFCCC: United Nations Framework Convention on Climate Change; WHC, World Heritage Convention: Convention Concerning the Protection of the World Cultural and Natural Heritage; FAO Compliance Agreement: The Agreement to Promote Compliance with International Conservation and Management Measures by Fishing Vessels on the High Seas; FAO PSMA: The Agreement on Port State Measures 

The following changes in governance may improve the ability of governance institutions and processes to address the challenges identified above:

• Cooperation on regional and global scales through various types of agreements of varying degrees of formality for States and other participants in governance 
• Increasing the voice and role in decision making for non-governmental participants such as Indigenous peoples, social and labour organisations 
• Increasing the horizontal integration of decision making across industry and societal sectors, under processes such as ‘integrated management’ and ‘marine spatial planning’ 
• Increasing resource mobilisation at the community scale to enable communities to experiment and innovate to address the challenges, and then to share their experiences with other communities and build cooperative approaches to promote strategies with successful outcomes 

These governance innovation strategies have the potential to increase the ability of the governance institutions and processes to successfully respond to all four types of scale-related challenges listed earlier. However, any of them also have the potential to fail to address their intended concerns effectively if implemented inappropriately, or to create new challenges as the initial priorities are addressed. In some countries, lack of capacity of the existing governance institutions, lack of access to basic facilities, insufficient income diversification and illiteracy are major hindrance for ocean governance in a changing climate (Bennett et al., 20142437; Salik et al., 20152438; Weng et al., 20152439; Karim and Uddin, 20192440; Sarkodie and Strezov, 20192441) (high confidence) 

Additional considerations identified by recent studies of ocean related mitigation and adaptation include the need for: early warning and precautionary management; multi-level and multi-sectoral governance responses; holistic, integrated and flexible management systems; integration of scientific and local knowledge as well as natural, social and economic investigation; identification and incorporation of a set of social indicators and checklists; adaptive governance; and incorporation of climate change effects in marine spatial planning (Hiwasaki et al., 20142470; Kettle et al., 20142471; Hernández-Delgado, 20152472; Himes-Cornell and Kasperski, 2015a2473; Pittman et al., 20152474; Colburn et al., 20162475; Creighton et al., 20162476; Hobday et al., 2016a2477; Audefroy and Sánchez, 20172478; Gissi et al., 20192479; Tuda et al., 20192480). Diverse adaptations of governance are being tried, and some are producing promising results (Sections 5.2, 5.3 and 5.4). However, rigorous further evaluation is needed regarding the effectiveness of these adaptations in achieving their goals in addressing specific governance challenges. Robust conclusions on the effectiveness of specific types of governance adaptations in various socioecological contexts would require a targeted assessment of ocean (and terrestrial) governance in a changing climate, possible as a key part of AR6. 

Ocean acidification is not specifically mentioned in the Paris Agreement on climate change (UNFCCC, 20152481) and has only been given limited attention to date in other UNFCCC discussions. Nevertheless, ocean acidification is widely considered to be part of the climate system: it is one of seven state-of-the-climate indicators used by the World Meteorological Organization (WMO, 2019); it featured strongly in AR5, being covered by both WGI and WGII; its impacts are assessed in many sections of this Chapter; and concerns regarding ocean acidification have been raised through many international governance structures, including the United Nations Convention on the Law of the Sea (UNCLOS), the Convention on Biological Diversity (CBD), the United Nations Environment Programme (UNEP), and the Intergovernmental Oceanographic Commission of the United Nations Educational, Scientific and Cultural Organization (IOC-UNESCO). 

Although many bodies have interests in ocean acidification, no unifying treaty or single instrument has been developed (Herr et al., 20142482; Harrould-Kolieb and Hoegh-Guldberg, 20192483) and there has been only limited governance action that is specific to the problem (Fennel and VanderZwaag, 20162484; Jagers et al., 20182485). Exceptions to this generalisation are the development of coordinated monitoring through the Global Ocean Acidification Observing Network (Newton et al., 20152486), with associated scientific support through the International Atomic Energy Agency (IAEA) (Osborn et al., 20172487; Watson-Wright and Valdés, 20182488); and SDG14.3, with its non-binding, and relatively general, commitment to ‘minimise and address the impacts of ocean acidification, including through enhanced scientific cooperation at all levels’.

One possible response to the fragmented responsibilities for ocean acidification governance would be the development of a new UN mechanism specifically to address ocean acidification (Kim, 2012). This option would take time and political will, and has not been widely supported (Harrould-Kolieb and Herr, 20122489). One pragmatic approach could be enhancing the involvement of UNFCCC with acidification governance (Herr et al., 20142490) together with increased use of multilateral environment agreements (Harrould-Kolieb and Herr, 20122491) (medium confidence). 

UNFCCC action to stabilise the climate by reducing CO2 emissions also necessarily addresses the problem of ocean acidification, which is primarily caused by anthropogenic CO2 dissolving in seawater and lowering pH. Nevertheless, there are also distinct ocean acidification mitigation and adaptation issues, including:

• Climate mitigation measures that might be focused on greenhouse gases other than CO2 
• pH-associated thresholds or tipping-points (Hughes et al., 20132492; Good et al., 20182493) that have implications for scenario-modelling of emission reductions (Steinacher et al., 20132494)
• The large-scale use of bioenergy with carbon capture and storage (BECCS) as a mitigation option, if this involved sub-seafloor CO2 storage, with risk of leakage and hence ocean acidification impacts (Blackford et al., 20142495)
• The use of other CO2 removal techniques (negative emissions) such as ocean fertilisation (Section 5.5.1.3), or solar radiation management, without CO2 emission reductions; both approaches would worsen ocean acidification (Williamson and Turley, 20122496; Keller et al., 2014a2497).

Adaptation to climate change could also include a more integrated approach to reduce ocean acidification impacts (Section 5.5.2). Proposed adaptation actions for ocean acidification (Kelly et al., 20112498; Billé et al., 20132499; Strong et al., 20142500; Albright et al., 2016a2501) include reduction of pollution and other stressors (thereby strengthening resilience); water treatment (e.g., for high value aquaculture); and the use of seaweed cultivation and seagrass restoration to slow longterm pH changes (although short-term variability may be increased) (Sabine, 20182502). These measures are generally applicable to relatively limited spatial scales; whilst they may succeed in ‘buying time’, their future effectiveness will decrease unless underlying global drivers are also addressed (high confidence).