Editing IPCC:AR6/SR15/Chapter-3 (section)

== Box 3.4 Warm-Water (Tropical) Coral Reefs in a 1.5°C Warmer World ==

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Warm-water coral reefs face very high risks (Figure 3.18) from climate change. A world in which global warming is restricted to 1.5°C above pre-industrial levels would be a better place for coral reefs than that of a 2°C warmer world, in which coral reefs would mostly disappear (Donner et al., 2005; Hoegh-Guldberg et al., 2014; Schleussner et al., 2016b; van Hooidonk et al., 2016; Frieler et al., 2017; Hughes et al., 2017a) <sup>[[#fn:r704|704]]</sup> . Even with warming up until today (GMST for decade 2006–2015: 0.87°C; Chapter 1), a substantial proportion of coral reefs have experienced large-scale mortalities that have lead to much reduced coral populations (Hoegh-Guldberg et al., 2014) <sup>[[#fn:r705|705]]</sup> . In the last three years alone (2016–2018), large coral reef systems such as the Great Barrier Reef (Australia) have lost as much as 50% of their shallow water corals (Hughes et al., 2017b) <sup>[[#fn:r706|706]]</sup> .

Coral-dominated reefs are found along coastlines between latitudes 30°S and 30°N, where they provide habitat for over a million species (Reaka-Kudla, 1997) <sup>[[#fn:r707|707]]</sup> and food, income, coastal protection, cultural context and many other services for millions of people in tropical coastal areas (Burke et al., 2011; Cinner et al., 2012; Kennedy et al., 2013; Pendleton et al., 2016) <sup>[[#fn:r708|708]]</sup> . Ultimately, coral reefs are underpinned by a mutualistic symbiosis between reef-building corals and dinoflagellates from the genus ''Symbiodinium'' (Hoegh-Guldberg et al., 2017) <sup>[[#fn:r709|709]]</sup> . Warm-water coral reefs are found down to depths of 150 m and are dependent on light, making them distinct from the cold deep-water reef systems that extend down to depths of 2000 m or more. The difficulty in accessing deep-water reefs also means that the literature on the impacts of climate change on these systems is very limited by comparison to those on warm-water coral reefs (Hoegh-Guldberg et al., 2017) <sup>[[#fn:r710|710]]</sup> . Consequently, this Box focuses on the impacts of climate change on warm-water (tropical) coral reefs, particularly with respect to their prospects under average global surface temperatures of 1.5°C and 2°C above the pre-industrial period.

The distribution and abundance of coral reefs has decreased by approximately 50% over the past 30 years (Gardner et al., 2005; Bruno and Selig, 2007; De’ath et al., 2012) <sup>[[#fn:r711|711]]</sup> as a result of pollution, storms, overfishing and unsustainable coastal development (Burke et al., 2011; Halpern et al., 2015; Cheal et al., 2017) <sup>[[#fn:r712|712]]</sup> . More recently, climate change (i.e., heat stress; Hoegh-Guldberg, 1999; Baker et al., 2008; Spalding and Brown, 2015; Hughes et al., 2017b) <sup>[[#fn:r713|713]]</sup> has emerged as the greatest threat to coral reefs, with temperatures of just 1°C above the long-term summer maximum for an area (reference period 1985–1993) over 4–6 weeks being enough to cause mass coral bleaching (loss of the symbionts) and mortality ( ''very high confidence'' ) (WGII AR5, Box 18-2; Cramer et al., 2014) <sup>[[#fn:r714|714]]</sup> . Ocean warming and acidification can also slow growth and calcification, making corals less competitive compared to other benthic organisms such as macroalgae or seaweeds (Dove et al., 2013; Reyes-Nivia et al., 2013, 2014) <sup>[[#fn:r715|715]]</sup> . As corals disappear, so do fish and many other reef-dependent species, which directly impacts industries such as tourism and fisheries, as well as the livelihoods for many, often disadvantaged, coastal people (Wilson et al., 2006; Graham, 2014; Graham et al., 2015; Cinner et al., 2016; <sup>[[#fn:r716|716]]</sup> Pendleton et al., 2016) <sup>[[#fn:r717|717]]</sup> . These impacts are exacerbated by increasingly intense storms (Section 3.3.6), which physically destroy coral communities and hence reefs (Cheal et al., 2017) <sup>[[#fn:r718|718]]</sup> , and by ocean acidification (Sections 3.3.10 and 3.4.4.5), which can weaken coral skeletons, contribute to disease, and slow the recovery of coral communities after mortality events ( ''low to medium confidence'' ) (Gardner et al., 2005; Dove et al., 2013; Kennedy et al., 2013; Webster et al., 2013; Hoegh-Guldberg, 2014b; Anthony, 2016) <sup>[[#fn:r719|719]]</sup> . Ocean acidification also leads to enhanced activity by decalcifying organisms such as excavating sponges (Kline et al., 2012; Dove et al., 2013; Fang et al., 2013, 2014; Reyes-Nivia et al., 2013, 2014) <sup>[[#fn:r720|720]]</sup> .

The predictions of back-to-back bleaching events (Hoegh-Guldberg, 1999) <sup>[[#fn:r721|721]]</sup> have become the reality in the summers of 2016–2017 (e.g., Hughes et al., 2017b) <sup>[[#fn:r722|722]]</sup> , as have projections of declining coral abundance ( ''high confidence'' ). Models have also become increasingly capable and are currently predicting the large-scale loss of coral reefs by mid-century under even low-emissions scenarios (Hoegh-Guldberg, 1999; Donner et al., 2005; Donner, 2009; van Hooidonk and Huber, 2012; Frieler et al., 2013; Hoegh-Guldberg et al., 2014; van Hooidonk et al., 2016) <sup>[[#fn:r723|723]]</sup> . Even achieving emissions reduction targets consistent with the ambitious goal of 1.5°C of global warming under the Paris Agreement will result in the further loss of 70–90% of reef-building corals compared to today, with 99% of corals being lost under warming of 2°C or more above the pre-industrial period (Frieler et al., 2013; Hoegh-Guldberg, 2014b; Hoegh-Guldberg et al., 2014; Schleussner et al., 2016b; Hughes et al., 2017a) <sup>[[#fn:r724|724]]</sup> .

The assumptions underpinning these assessments are considered to be highly conservative. In some cases, ‘optimistic’ assumptions in models include rapid thermal adaptation by corals of 0.2°C–1°C per decade (Donner et al., 2005) <sup>[[#fn:r725|725]]</sup> or 0.4°C per decade (Schleussner et al., 2016b) <sup>[[#fn:r726|726]]</sup> , as well as very rapid recovery rates from impacts (e.g., five years in the case of Schleussner et al., 2016b) <sup>[[#fn:r727|727]]</sup> . Adaptation to climate change at these high rates, has not been documented, and recovery from mass mortality tends to take much longer (&gt;15 years; Baker et al., 2008) <sup>[[#fn:r728|728]]</sup> . Probability analysis also indicates that the underlying increases in sea temperatures that drive coral bleaching and mortality are 25% less ''likely'' under 1.5°C when compared to 2°C (King et al., 2017) <sup>[[#fn:r729|729]]</sup> . Spatial differences between the rates of heating suggest the possibility of temporary climate refugia (Caldeira, 2013; van Hooidonk et al., 2013; Cacciapaglia and van Woesik, 2015; Keppel and Kavousi, 2015) <sup>[[#fn:r730|730]]</sup> , which may play an important role in terms of the regeneration of coral reefs, especially if these refuges are protected from risks unrelated to climate change. Locations at higher latitudes are reporting the arrival of reef-building corals, which may be valuable in terms of the role of limited refugia and coral reef structures but will have low biodiversity ''(high'' ''confidence'' ) when compared to present-day tropical reefs (Kersting et al., 2017) <sup>[[#fn:r731|731]]</sup> . Similarly, deep-water (30–150 m) or mesophotic coral reefs (Bongaerts et al., 2010; Holstein et al., 2016) <sup>[[#fn:r732|732]]</sup> may play an important role because they avoid shallow water extremes (i.e., heat and storms) to some extent, although the ability of these ecosystems to assist in repopulating damaged shallow water areas may be limited (Bongaerts et al., 2017) <sup>[[#fn:r733|733]]</sup> .

Given the sensitivity of corals to heat stress, even short periods of overshoot (i.e., decades) are expected to be extremely damaging to coral reefs. Losing 70–90% of today’s coral reefs, however, will remove resources and increase poverty levels across the world’s tropical coastlines, highlighting the key issue of equity for the millions of people that depend on these valuable ecosystems (Cross-Chapter Box 6; Spalding et al., 2014; Halpern et al., 2015) <sup>[[#fn:r734|734]]</sup> . Anticipating these challenges to food and livelihoods for coastal communities will become increasingly important, as will adaptation options, such as the diversification of livelihoods and the development of new sustainable industries, to reduce the dependency of coastal communities on threatened ecosystems such as coral reefs (Cinner et al., 2012, 2016; Pendleton et al., 2016) <sup>[[#fn:r735|735]]</sup> . At the same time, coastal communities will need to pre-empt changes to other services provided by coral reefs such as coastal protection (Kennedy et al., 2013; Hoegh-Guldberg et al., 2014; Pörtner et al., 2014; Gattuso et al., 2015) <sup>[[#fn:r736|736]]</sup> . Other threats and challenges to coastal living, such as sea level rise, will amplify challenges from declining coral reefs, specially for SIDS and low-lying tropical nations. Given the scale and cost of these interventions, implementing them earlier rather than later would be expedient.

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=== 3.4.5 Coastal and Low-Lying Areas, and Sea Level Rise ===

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Sea level rise (SLR) is accelerating in response to climate change (Section 3.3.9; Church et al., 2013) <sup>[[#fn:r737|737]]</sup> and will produce significant impacts ( ''high confidence'' ). In this section, impacts and projections of SLR are reported at global and city scales (Sections 3.4.5.1 and 3.4.5.2) and for coastal systems (Sections 3.4.5.3 to 3.4.5.6). For some sectors, there is a lack of precise evidence of change at 1.5°C and 2°C of global warming. Adaptation to SLR is discussed in Section 3.4.5.7.

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==== 3.4.5.1 Global / sub-global scale ====

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Sea level rise (SLR) and other oceanic climate changes are already resulting in salinization, flooding, and erosion and in the future are projected to affect human and ecological systems, including health, heritage, freshwater availability, biodiversity, agriculture, fisheries and other services, with different impacts seen worldwide ( ''high confidence'' ). Owing to the commitment to SLR, there is an overlapping uncertainty in projections at 1.5°C and 2°C (Schleussner et al., 2016b; Sanderson et al., 2017; Goodwin et al., 2018; Mengel et al., 2018; Nicholls et al., 2018; Rasmussen et al., 2018) <sup>[[#fn:r738|738]]</sup> and about 0.1 m difference in global mean sea level (GMSL) rise between 1.5°C and 2°C worlds in the year 2100 (Section 3.3.9, Table 3.3). Exposure and impacts at 1.5°C and 2°C differ at different time horizons (Schleussner et al., 2016b; Brown et al., 2018a, b; Nicholls et al., 2018; Rasmussen et al., 2018) <sup>[[#fn:r739|739]]</sup> . However, these are distinct from impacts associated with higher increases in temperature (e.g., 4ºC or more, as discussed in Brown et al., 2018a) <sup>[[#fn:r740|740]]</sup> over centennial scales. The benefits of climate change mitigation reinforce findings of earlier IPCC reports (e.g., Wong et al., 2014) <sup>[[#fn:r741|741]]</sup> .

Table 3.3 shows the land and people exposed to SLR (assuming there is no adaptation or protection at all) using the Dynamic Interactive Vulnerability Assessment (DIVA) model (extracted from Brown et al., 2018a <sup>[[#fn:r742|742]]</sup> and Goodwin et al., 2018 <sup>[[#fn:r743|743]]</sup> ; see also Supplementary Material 3.SM, Table 3.SM.4). Thus, exposure increases even with temperature stabilization. The exposed land area is projected to at least double by 2300 using a RCP8.5 scenario compared with a mitigation scenario (Brown et al., 2018a) <sup>[[#fn:r744|744]]</sup> . In the 21st century, land area exposed to sea level rise (assuming there is no adaptation or protection at all) is projected to be at least an order of magnitude larger than the cumulative land loss due to submergence (which takes into account defences) (Brown et al., 2016, 2018a) <sup>[[#fn:r745|745]]</sup> regardless of the SLR scenario applied. Slower rates of rise due to climate change mitigation may provide a greater opportunity for adaptation ( ''medium confidence'' ), which could substantially reduce impacts.

In agreement with the assessment in WGII AR5 Section 5.4.3.1 (Wong et al., 2014) <sup>[[#fn:r746|746]]</sup> , climate change mitigation may reduce or delay coastal exposure and impacts ( ''very high confidence'' ). Adaptation has the potential to substantially reduce risk through a portfolio of available options (Sections 5.4.3.1 and 5.5 of Wong et al., 2014; Sections 6.4.2.3 and 6.6 of Nicholls et al., 2007) <sup>[[#fn:r747|747]]</sup> . At 1.5°C in 2100, 31–69 million people (2010 population values) worldwide are projected to be exposed to flooding, assuming no adaptation or protection at all, compared with 32–79 million people (2010 population values) at 2°C in 2100 (Supplementary Material 3.SM, Table 3.SM.4; Rasmussen et al., 2018 <sup>[[#fn:r748|748]]</sup> ). As a result, up to 10.4 million more people would be exposed to sea level rise at 2°C compared with 1.5°C in 2100 ( ''medium confidence'' ). With a 1.5°C stabilization scenario in 2100, 62.7 million people per year are at risk from flooding, with this value increasing to 137.6 million people per year in 2300 (50th percentile average across SSP1–5, no socio-economic change after 2100). These projections assume that no upgrade to current protection levels occurs (Nicholls et al., 2018) <sup>[[#fn:r749|749]]</sup> . The number of people at risk increases by approximately 18% in 2030 if a 2°C scenario is used and by 266% in 2300 if an RCP8.5 scenario is considered (Nicholls et al., 2018) <sup>[[#fn:r750|750]]</sup> . Through prescribed IPCC Special Report on Emissions Scenarios (SRES) SLR scenarios, Arnell et al. (2016) <sup>[[#fn:r751|751]]</sup> also found that the number of people exposed to flooding increased substantially at warming levels higher than 2°C, assuming no adaptation beyond current protection levels. Additionally, impacts increased in the second half of the 21st century.

Coastal flooding is projected to cost thousands of billions of USD annually, with damage costs under constant protection estimated at 0.3–5.0% of global gross domestic product (GDP) in 2100 under an RCP2.6 scenario (Hinkel et al., 2014) <sup>[[#fn:r752|752]]</sup> . Risks are projected to be highest in South and Southeast Asia, assuming there is no upgrade to current protection levels, for all levels of climate warming (Arnell et al., 2016; Brown et al., 2016) <sup>[[#fn:r753|753]]</sup> . Countries with at least 50 million people exposed to SLR (assuming no adaptation or protection at all) based on a 1,280 Pg C emissions scenario (approximately a 1.5°C temperature rise above today’s level) include China, Bangladesh, Egypt, India, Indonesia, Japan, Philippines, United States and Vietnam (Clark et al., 2016) <sup>[[#fn:r754|754]]</sup> . Rasmussen et al. (2018) <sup>[[#fn:r755|755]]</sup> and Brown et al. (2018a) <sup>[[#fn:r756|756]]</sup> project that similar countries would have high exposure to SLR in the 21st century using 1.5°C and 2°C scenarios. Thus, there is ''high confidence'' that SLR will have significant impacts worldwide in this century and beyond.

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==== 3.4.5.2 Cities ====

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Observations of the impacts of SLR in cities are difficult to record because multiple drivers of change are involved. There are observations of ongoing and planned adaptation to SLR and extreme water levels in some cities (Araos et al., 2016; Nicholls et al., 2018) <sup>[[#fn:r757|757]]</sup> , whilst other cities have yet to prepare for these impacts ( ''high confidence'' ) (see Section 3.4.8 and Cross-Chapter Box 9 in Chapter 4). There are limited observations and analyses of how cities will cope with higher and/or multi-centennial SLR, with the exception of Amsterdam, New York and London (Nicholls et al., 2018) <sup>[[#fn:r758|758]]</sup> .

Coastal urban areas are projected to see more extreme water levels due to rising sea levels, which may lead to increased flooding and damage of infrastructure from extreme events (unless adaptation is undertaken), plus salinization of groundwater. These impacts may be enhanced through localized subsidence (Wong et al., 2014) <sup>[[#fn:r759|759]]</sup> , which causes greater relative SLR. At least 136 megacities (port cities with a population greater than 1 million in 2005) are at risk from flooding due to SLR (with magnitudes of rise possible under 1.5°C or 2°C in the 21st century, as indicated in Section 3.3.9) unless further adaptation is undertaken (Hanson et al., 2011; Hallegatte et al., 2013) <sup>[[#fn:r760|760]]</sup> . Many of these cities are located in South and Southeast Asia (Hallegatte et al., 2013; Cazenave and Cozannet, 2014; Clark et al., 2016; Jevrejeva et al., 2016) <sup>[[#fn:r761|761]]</sup> . Jevrejeva et al. (2016) <sup>[[#fn:r762|762]]</sup> projected that more than 90% of global coastlines could experience SLR greater than 0.2 m with 2°C of warming by 2040 (RCP8.5). However, for scenarios where 2°C is stabilized or occurs later in time, this figure is ''likely'' to differ because of the commitment to SLR. Raising existing dikes helps protect against SLR, substantially reducing risks, although other forms of adaptation exist. By 2300, dike heights under a non-mitigation scenario (RCP8.5) could be more than 2 m higher (on average for 136 megacities) than under climate change mitigation scenarios at 1.5°C or 2°C (Nicholls et al., 2018) <sup>[[#fn:r763|763]]</sup> . Thus, rising sea levels commit coastal cities to long-term adaptation ( ''high confidence'' ).

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==== 3.4.5.3 Small islands ====

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Qualitative physical observations of SLR (and other stresses) include inundation of parts of low-lying islands, land degradation due to saltwater intrusion in Kiribati and Tuvalu (Wairiu, 2017) <sup>[[#fn:r764|764]]</sup> , and shoreline change in French Polynesia (Yates et al., 2013) <sup>[[#fn:r765|765]]</sup> , Tuvalu (Kench et al., 2015, 2018) <sup>[[#fn:r766|766]]</sup> and Hawaii (Romine et al., 2013) <sup>[[#fn:r767|767]]</sup> . Observations, models and other evidence indicate that unconstrained Pacific atolls have kept pace with SLR, with little reduction in size or net gain in land (Kench et al., 2015, 2018; McLean and Kench, 2015; Beetham et al., 2017) <sup>[[#fn:r768|768]]</sup> . Whilst islands are highly vulnerable to SLR ( ''high confidence'' ), they are also reactive to change. Small islands are impacted by multiple climatic stressors, with SLR being a more important stressor to some islands than others (Sections 3.4.10, 4.3.5.6, 5.2.1, 5.5.3.3, Boxes 3.5, 4.3 and 5.3).

Observed adaptation to multiple drivers of coastal change, including SLR, includes retreat (migration), accommodation and defence. Migration (internal and international) has always been important on small islands (Farbotko and Lazrus, 2012; Weir et al., 2017) <sup>[[#fn:r769|769]]</sup> , with changing environmental and weather conditions being just one factor in the choice to migrate (Sections 3.4.10, 4.3.5.6 and 5.3.2; Campbell and Warrick, 2014) <sup>[[#fn:r770|770]]</sup> . Whilst flooding may result in migration or relocation, for example in Vunidogoloa, Fiji (McNamara and Des Combes, 2015; Gharbaoui and Blocher, 2016) <sup>[[#fn:r771|771]]</sup> and the Solomon Islands (Albert et al., 2017) <sup>[[#fn:r772|772]]</sup> , in situ adaptation may be tried or preferred, for example stilted housing or raised floors in Tubigon, Bohol, Philippines (Jamero et al., 2017) <sup>[[#fn:r773|773]]</sup> , raised roads and floors in Batasan and Ubay, Philippines (Jamero et al., 2018) <sup>[[#fn:r774|774]]</sup> , and raised platforms for faluw in Leang, Federated States of Micronesia (Nunn et al., 2017) <sup>[[#fn:r775|775]]</sup> . Protective features, such as seawalls or beach nourishment, are observed to locally reduce erosion and flood risk but can have other adverse implications (Sovacool, 2012; Mycoo, 2014, 2017; Nurse et al., 2014; AR5 Section 29.6.22) <sup>[[#fn:r776|776]]</sup> .

There is a lack of precise, quantitative studies of projected impacts of SLR at 1.5°C and 2°C. Small islands are projected to be at risk and very sensitive to coastal climate change and other stressors ''(high confidence'' ) (Nurse et al., 2014; Benjamin and Thomas, 2016; Ourbak and Magnan, 2017; Brown et al., 2018a; Nicholls et al., 2018; Rasmussen et al., 2018; <sup>[[#fn:r777|777]]</sup> AR5 Sections 29.3 and 29.4), such as oceanic warming, SLR (resulting in salinization, flooding and erosion), cyclones and mass coral bleaching and mortality (Section 3.4.4, Boxes 3.4 and 3.5). These impacts can have significant socio-economic and ecological implications, such as on health, agriculture and water resources, which in turn have impacts on livelihoods (Sovacool, 2012; Mycoo, 2014, 2017; Nurse et al., 2014) <sup>[[#fn:r778|778]]</sup> . Combinations of drivers causing adverse impacts are important. For example, Storlazzi et al. (2018) <sup>[[#fn:r779|779]]</sup> found that the impacts of SLR and wave-induced flooding (within a temperature horizon equivalent of 1.5°C), could affect freshwater availability on Roi-Namur, Marshall Islands, but is also dependent on other extreme weather events. Freshwater resources may also be affected by a 0.40 m rise in sea level (which may be experienced with a 1.5°C warming) in other Pacific atolls (Terry and Chui, 2012) <sup>[[#fn:r780|780]]</sup> . Whilst SLR is a major hazard for atolls, islands reaching higher elevations are also threatened given that there is often a lot of infrastructure located near the coast ( ''high confidence'' ) (Kumar and Taylor, 2015; Nicholls et al., 2018) <sup>[[#fn:r781|781]]</sup> . Tens of thousands of people on small islands are exposed to SLR (Rasmussen et al., 2018) <sup>[[#fn:r782|782]]</sup> . Giardino et al. (2018) <sup>[[#fn:r783|783]]</sup> found that hard defence structures on the island of Ebeye in the Marshall Islands were effective in reducing damage due to SLR at 1.5°C and 2°C. Additionally, damage was also reduced under mitigation scenarios compared with non-mitigation scenarios. In Jamaica and St Lucia, SLR and extreme sea levels are projected to threaten transport system infrastructure at 1.5°C unless further adaptation is undertaken (Monioudi et al., 2018) <sup>[[#fn:r784|784]]</sup> . Slower rates of SLR will provide a greater opportunity for adaptation to be successful ( ''medium confidence'' ), but this may not be substantial enough on islands with a very low mean elevation. Migration and/or relocation may be an adaptation option (Section 3.4.10). Thomas and Benjamin (2017) <sup>[[#fn:r785|785]]</sup> highlight three areas of concern in the context of loss and damage at 1.5°C: a lack of data, gaps in financial assessments, and a lack of targeted policies or mechanisms to address these issues (Cross-Chapter Box 12 in Chapter 5). Small islands are projected to remain vulnerable to SLR ( ''high confidence'' ).

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==== 3.4.5.4 Deltas and estuaries ====

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Observations of SLR and human influence are felt through salinization, which leads to mixing in deltas and estuaries, aquifers, leading to flooding (also enhanced by precipitation and river discharge), land degradation and erosion. Salinization is projected to impact freshwater sources and pose risks to ecosystems and human systems (Section 5.4; Wong et al., 2014) <sup>[[#fn:r786|786]]</sup> . For instance, in the Delaware River estuary on the east coast of the USA, upward trends of salinity (measured since the 1900s), accounting for the effects of streamflow and seasonal variations, have been detected and SLR is a potential cause (Ross et al., 2015) <sup>[[#fn:r787|787]]</sup> .

Z. Yang et al. (2015) <sup>[[#fn:r788|788]]</sup> found that future climate scenarios for the USA (A1B 1.6°C and B1 2°C in the 2040s) had a greater effect on salinity intrusion than future land-use/land-cover change in the Snohomish River estuary in Washington state (USA). This resulted in a shift in the salinity both upstream and downstream in low flow conditions. Projecting impacts in deltas needs an understanding of both fluvial discharge and SLR, making projections complex because the drivers operate on different temporal and spatial scales (Zaman et al., 2017; Brown et al., 2018b) <sup>[[#fn:r789|789]]</sup> . The mean annual flood depth when 1.5°C is first projected to be reached in the Ganges-Brahmaputra delta may be less than the most extreme annual flood depth seen today, taking into account SLR, surges, tides, bathymetry and local river flows (Brown et al., 2018b) <sup>[[#fn:r790|790]]</sup> . Further, increased river salinity and saline intrusion in the Ganges-Brahmaputra-Meghna is ''likely'' with 2°C of warming (Zaman et al., 2017) <sup>[[#fn:r791|791]]</sup> . Salinization could impact agriculture and food security (Cross-Chapter Box 6 in this chapter). For 1.5°C or 2°C stabilization conditions in 2200 or 2300 plus surges, a minimum of 44% of the Bangladeshi Ganges-Brahmaputra, Indian Bengal, Indian Mahanadi and Ghanese Volta delta land area (without defences) would be exposed unless sedimentation occurs (Brown et al., 2018b) <sup>[[#fn:r792|792]]</sup> . Other deltas are similarly vulnerable. SLR is only one factor affecting deltas, and assessment of numerous geophysical and anthropogenic drivers of geomorphic change is important (Tessler et al., 2018) <sup>[[#fn:r793|793]]</sup> . For example, dike building to reduce flooding and dam building (Gupta et al., 2012) <sup>[[#fn:r794|794]]</sup> restricts sediment movement and deposition, leading to enhanced subsidence, which can occur at a greater rate than SLR (Auerbach et al., 2015; Takagi et al., 2016) <sup>[[#fn:r795|795]]</sup> . Although dikes remain essential for reducing flood risk today, promoting sedimentation is an advisable strategy (Brown et al., 2018b) <sup>[[#fn:r796|796]]</sup> which may involve nature-based solutions. Transformative decisions regarding the extent of sediment restrictive infrastructure may need to be considered over centennial scales (Brown et al., 2018b) <sup>[[#fn:r797|797]]</sup> . Thus, in a 1.5°C or 2°C warmer world, deltas, which are home to millions of people, are expected to be highly threatened from SLR and localized subsidence ( ''high confidence'' ).

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==== 3.4.5.5 Wetlands ====

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Observations indicate that wetlands, such as saltmarshes and mangrove forests, are disrupted by changing conditions (Sections 3.4.4.8; Wong et al., 2014; Lovelock et al., 2015) <sup>[[#fn:r798|798]]</sup> , such as total water levels and sediment availability. For example, saltmarshes in Connecticut and New York, USA, measured from 1900 to 2012, have accreted with SLR but have lost marsh surface relative to tidal datums, leading to increased marsh flooding and further accretion (Hill and Anisfeld, 2015) <sup>[[#fn:r799|799]]</sup> . This change stimulated marsh carbon storage and aided climate change mitigation.

Salinization may lead to shifts in wetland communities and their ecosystem functions (Herbert et al., 2015) <sup>[[#fn:r800|800]]</sup> . Some projections of wetland change, with magnitudes (but not necessarily rates or timing) of SLR analogous to 1.5°C and 2°C of global warming, indicate a net loss of wetlands in the 21st century (e.g., Blankespoor et al., 2014; Cui et al., 2015; Arnell et al., 2016; Crosby et al., 2016) <sup>[[#fn:r801|801]]</sup> , whilst others report a net gain with wetland transgression (e.g. Raabe and Stumpf, 2016 <sup>[[#fn:r802|802]]</sup> in the Gulf of Mexico). However, the feedback between wetlands and sea level is complex, with parameters such as a lack of accommodation space restricting inland migration, or sediment supply and feedbacks between plant growth and geomorphology (Kirwan and Megonigal, 2013; Ellison, 2014; Martínez et al., 2014; Spencer et al., 2016) <sup>[[#fn:r803|803]]</sup> still being explored. Reducing global warming from 2°C to 1.5°C will deliver long-term benefits, with natural sedimentation rates more ''likely'' keep up with SLR. It remains unclear how wetlands will respond and under what conditions (including other climate parameters) to a global temperature rise of 1.5°C and 2°C. However, they have great potential to aid and benefit climate change mitigation and adaptation ( ''medium confidence'' ) (Sections 4.3.2.2 and 4.3.2.3).

<div id="section-3-4-5-6"></div>

<span id="other-coastal-settings"></span>
==== 3.4.5.6 Other coastal settings ====

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Numerous impacts have not been quantified at 1.5°C or 2°C but remain important. This includes systems identified in WGII AR5 (AR5 – Section 5.4 of Wong et al., 2014) <sup>[[#fn:r804|804]]</sup> , such as beaches, barriers, sand dunes, rocky coasts, aquifers, lagoons and coastal ecosystems (for the last system, see Section 3.4.4.12). For example, SLR potentially affects erosion and accretion, and therefore sediment movement, instigating shoreline change (Section 5.4.2.1 of Wong et al., 2014) <sup>[[#fn:r805|805]]</sup> , which could affect land-based ecosystems. Global observations indicate no overall clear effect of SLR on shoreline change (Le Cozannet et al., 2014) <sup>[[#fn:r806|806]]</sup> , as it is highly site specific (e.g., Romine et al., 2013) <sup>[[#fn:r807|807]]</sup> . Infrastructure and geological constraints reduce shoreline movement, causing coastal squeeze. In Japan, for example, SLR is projected to cause beach losses under an RCP2.6 scenario, which will worsen under RCP8.5 (Udo and Takeda, 2017) <sup>[[#fn:r808|808]]</sup> . Further, compound flooding (the combined risk of flooding from multiple sources) has increased significantly over the past century in major coastal cities (Wahl et al., 2015) <sup>[[#fn:r809|809]]</sup> and is ''likely'' to increase with further development and SLR at 1.5°C and 2°C unless adaptation is undertaken. Thus, overall SLR will have a wide range of adverse effects on coastal zones (medium confidence).

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<span id="adapting-to-coastal-change"></span>
==== 3.4.5.7 Adapting to coastal change ====

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Adaptation to coastal change from SLR and other drivers is occurring today ( ''high confidence'' ) (see Cross-Chapter Box 9 in Chapter 4), including migration, ecosystem-based adaptation, raising infrastructure and defences, salt-tolerant food production, early warning systems, insurance and education (Section 5.4.2.1 of Wong et al., 2014) <sup>[[#fn:r810|810]]</sup> . Climate change mitigation will reduce the rate of SLR this century, decreasing the need for extensive and, in places, immediate adaptation. Adaptation will reduce impacts in human settings ( ''high confidence'' ) (Hinkel et al., 2014; Wong et al., 2014) <sup>[[#fn:r811|811]]</sup> , although there is less certainty for natural ecosystems (Sections 4.3.2 and 4.3.3.3). While some ecosystems (e.g., mangroves) may be able to move shoreward as sea levels increase, coastal development (e.g., coastal building, seawalls and agriculture) often interrupt these transitions (Saunders et al., 2014) <sup>[[#fn:r812|812]]</sup> . Options for responding to these challenges include reducing the impact of other stresses such as those arising from tourism, fishing, coastal development and unsustainable aquaculture/agriculture. In some cases, restoration of coastal habitats and ecosystems can be a cost-effective way of responding to changes arising from increasing levels of exposure from rising sea levels, changes in storm conditions, coastal inundation and salinization (Arkema et al., 2013; Temmerman et al., 2013; Ferrario et al., 2014; Hinkel et al., 2014; Spalding et al., 2014; Elliff and Silva, 2017) <sup>[[#fn:r813|813]]</sup> .

Since AR5, planned and autonomous adaptation and forward planning have become more widespread (Araos et al., 2016; Nicholls et al., 2018) <sup>[[#fn:r814|814]]</sup> , but continued efforts are required as many localities are in the early stages of adapting or are not adapting at all (Cross-Chapter Box 9 in Chapter 4; Araos et al., 2016) <sup>[[#fn:r815|815]]</sup> . This is region and sub-sector specific, and also linked to non-climatic factors (Ford et al., 2015; Araos et al., 2016; Lesnikowski et al., 2016) <sup>[[#fn:r816|816]]</sup> . Adaptation pathways (e.g., Ranger et al., 2013; Barnett et al., 2014; Rosenzweig and Solecki, 2014; Buurman and Babovic, 2016) <sup>[[#fn:r817|817]]</sup> assist long-term planning but are not widespread practices despite knowledge of long-term risks (Section 4.2.2). Furthermore, human retreat and migration are increasingly being considered as an adaptation response (Hauer et al., 2016; Geisler and Currens, 2017) <sup>[[#fn:r818|818]]</sup> , with a growing emphasis on green adaptation. There are few studies on the adaptation limits to SLR where transformation change may be required (AR5 Section 5.5 of Wong et al., 2014 <sup>[[#fn:r819|819]]</sup> ; Nicholls et al., 2015 <sup>[[#fn:r820|820]]</sup> ). Sea level rise poses a long-term threat (Section 3.3.9), and adaptation will remain essential at the centennial scale under 1.5°C and 2°C of warming ( ''high confidence'' ).

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<span id="table-3.3"></span>
<!-- START TABLE -->
'''Table 3.3'''

<span id="land-and-people-exposed-to-sea-level-rise-slr-assuming-no-protection-at-all.-extracted-from-brown-et-al.-2018a-and-goodwin-et-al.-2018.-ssp-shared-socio--economic-pathway-wrt-with-respect-to-population-held-constant-at-2100-level."></span>
'''Land and people exposed to sea level rise (SLR), assuming no protection at all. Extracted from Brown et al. (2018a) and Goodwin et al. (2018). SSP: Shared Socio- Economic Pathway; wrt: with respect to; *: Population held constant at 2100 level.'''

<!-- TABLE -->
{| class="wikitable"
|-
! rowspan="2"| Climate scenario
! rowspan="2"| Impact factor, assuming there is no adaptation or protection at all (50th, [5th-95th percentiles])
! colspan="4"| Year
|-
! 2050
! 2100
! 2200
! 2300
|-
| 1.5°C
| Temperature rise wrt 1850–1900 (°C)
| 1.71
(1.44–2.16)

| 1.60
(1.26–2.33)

| 1.41
(1.15–2.10)

| 1.32
(1.12–1.81)

|-
|
| SLR (m) wrt 1986–2005
| 0.20
(0.14–0.29)

| 0.40
(0.26–0.62)

| 0.73
(0.47–1.25)

| 1.00
(0.59–1.55)

|-
|
| Land exposed (x10 <sup>3</sup> km <sup>2</sup> )
| 574
[558–597]

| 620
[575–669]

| 666
[595–772]

| 702
[666–853]

|-
|
| People exposed, SSP1–5 (millions)
| 127.9–139.0
[123.4–134.0,<br />
134.5–146.4]

| 102.7–153.5
[94.8–140.7,<br />
102.7–153.5]

| —
| 133.8–207.1
[112.3–169.6, 165.2–263.4]*

|-
| 2°C
| Temperature rise wrt 1850–1900 (° C)
| 1.76
(1.51–2.16)

| 2.03
(1.72–2.64)

| 1.90
(1.66–2.57)

| 1.80
(1.60–2.20)

|-
|
| SLR (m) wrt 1986-2005

| 0.20
(0.14–0.29)

| 0.46
(0.30–0.69)

| 0.90
(0.58–1.50)

| 1.26
(0.74–1.90)

|-
|
| Land exposed (x10 <sup>3</sup> km <sup>2</sup> )

| 575
[558–598]

| 637
[585–686]

| 705
[618–827]

| 767
[642–937]

|-
|
| People exposed, SSP1–5 (millions)

| 128.1–139.2
[123.6–134.2,<br />
134.7–146.6]

| 105.5–158.1
[97.0–144.1,<br />
118.1–179.0]

| —
| 148.3–233.0
[120.3–183.4, 186.4–301.8]*

|}
<!-- END TABLE -->

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