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

==== 3.4.2.6 Sandy Beaches ====

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

{| class="wikitable"
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! Observations

! Projections

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

|}

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

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

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

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[[File:28ca7a67ead48d42a0650b0f9d1ad93b IPCC_AR6_WGII_Figure_3_014.png]]

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

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

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

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