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

== Box 3.5: Small Island Developing States (SIDS) ==

<div id="section-3-4-5-7-block-1"></div>

Global warming of 1.5°C is expected to prove challenging for small island developing states (SIDS) that are already experiencing impacts associated with climate change ( ''high confidence'' ). At 1.5°C, compounding impacts from interactions between climate drivers may contribute to the loss of, or change in, critical natural and human systems ( ''medium to high confidence'' ). There are a number of reduced risks at 1.5°C versus 2°C, particularly when coupled with adaptation efforts ( ''medium to high confidence'' ).

'''Changing climate hazards for SIDS at 1.5°C'''

Mean surface temperature is projected to increase in SIDS at 1.5°C of global warming ( ''high confidence'' ). The Caribbean region will experience 0.5°C–1.5°C of warming compared to a 1971–2000 baseline, with the strongest warming occurring over larger land masses (Taylor et al., 2018) <sup>[[#fn:r823|823]]</sup> . Under the Representative Concentration Pathway (RCP)2.6 scenario, the western tropical Pacific is projected to experience warming of 0.5°C–1.7°C relative to 1961–1990. Extreme temperatures will also increase, with potential for elevated impacts as a result of comparably small natural variability (Reyer et al., 2017a) <sup>[[#fn:r824|824]]</sup> . Compared to the 1971–2000 baseline, up to 50% of the year is projected to be under warm spell conditions in the Caribbean at 1.5°C, with a further increase of up to 70 days at 2°C (Taylor et al., 2018) <sup>[[#fn:r825|825]]</sup> .

Changes in precipitation patterns, freshwater availability and drought sensitivity differ among small island regions ( ''medium to high confidence'' ). Some western Pacific islands and those in the northern Indian Ocean may see increased freshwater availability, while islands in most other regions are projected to see a substantial decline (Holding et al., 2016; Karnauskas et al., 2016) <sup>[[#fn:r826|826]]</sup> . For several SIDS, approximately 25% of the overall freshwater stress projected under 2°C at 2030 could be avoided by limiting global warming to 1.5°C (Karnauskas et al., 2018) <sup>[[#fn:r827|827]]</sup> . In accordance with an overall drying trend, an increasing drought risk is projected for Caribbean SIDS (Lehner et al., 2017) <sup>[[#fn:r828|828]]</sup> , and moderate to extreme drought conditions are projected to be about 9% longer on average at 2°C versus 1.5°C for islands in this region (Taylor et al., 2018) <sup>[[#fn:r829|829]]</sup> .

Projected changes in the ocean system at higher warming targets (Section 3.4.4), including potential changes in circulation (Section 3.3.7) and increases in both surface temperatures (Section 3.3.7) and ocean acidification (Section 3.3.10), suggest increasing risks for SIDS associated with warming levels close to and exceeding 1.5°C.

Differences in global sea level between 1.5°C and 2°C depend on the time scale considered and are projected to fully materialize only after 2100 (Section 3.3.9). Projected changes in regional sea level are similarly time dependent, but generally found to be above the global average for tropical regions including small islands (Kopp et al., 2014; Jevrejeva et al., 2016) <sup>[[#fn:r830|830]]</sup> . Threats related to sea level rise (SLR) for SIDS, for example from salinization, flooding, permanent inundation, erosion and pressure on ecosystems, will therefore persist well beyond the 21st century even under 1.5°C of warming (Section 3.4.5.3; Nicholls et al., 2018) <sup>[[#fn:r831|831]]</sup> . Prolonged interannual sea level inundations may increase throughout the tropical Pacific with ongoing warming and in the advent of an increased frequency of extreme La Niña events, exacerbating coastal impacts of projected global mean SLR (Widlansky et al., 2015) <sup>[[#fn:r832|832]]</sup> . Changes to the frequency of extreme El Niño and La Niña events may also increase the frequency of droughts and floods in South Pacific islands (Box 4.2, Section 3.5.2; Cai et al., 2012) <sup>[[#fn:r833|833]]</sup> .

Extreme precipitation in small island regions is often linked to tropical storms and contributes to the climate hazard (Khouakhi et al., 2017) <sup>[[#fn:r834|834]]</sup> . Similarly, extreme sea levels for small islands, particularly in the Caribbean, are linked to tropical cyclone occurrence (Khouakhi and Villarini, 2017) <sup>[[#fn:r835|835]]</sup> . Under a 1.5°C stabilization scenario, there is a projected decrease in the frequency of weaker tropical storms and an increase in the number of intense cyclones (Section 3.3.6; Wehner et al., 2018a) <sup>[[#fn:r836|836]]</sup> . There are not enough studies to assess differences in tropical cyclone statistics for 1.5°C versus 2°C (Section 3.3.6). There are considerable differences in the adaptation responses to tropical cyclones across SIDS (Cross-Chapter Box 11 in Chapter 4).

'''Impacts on key natural and human systems'''

Projected increases in aridity and decreases in freshwater availability at 1.5°C of warming, along with additional risks from SLR and increased wave-induced run-up, might leave several atoll islands uninhabitable (Storlazzi et al., 2015; Gosling and Arnell, 2016) <sup>[[#fn:r837|837]]</sup> . Changes in the availability and quality of freshwater, linked to a combination of changes to climate drivers, may adversely impact SIDS’ economies (White and Falkland, 2010; Terry and Chui, 2012; Holding and Allen, 2015; Donk et al., 2018) <sup>[[#fn:r838|838]]</sup> . Growth-rate projections based on temperature impacts alone indicate robust negative impacts on gross domestic product (GDP) per capita growth for SIDS (Sections 3.4.7.1, 3.4.9.1 and 3.5.4.9; Pretis et al., 2018) <sup>[[#fn:r839|839]]</sup> . These impacts would be reduced considerably under 1.5°C but may be increased by escalating risks from climate-related extreme weather events and SLR (Sections 3.4.5.3, 3.4.9.4 and 3.5.3)

Marine systems and associated livelihoods in SIDS face higher risks at 2°C compared to 1.5°C ( ''medium to high confidence'' ). Mass coral bleaching and mortality are projected to increase because of interactions between rising ocean temperatures, ocean acidification, and destructive waves from intensifying storms (Section 3.4.4 and 5.2.3, Box 3.4). At 1.5°C, approximately 70–90% of global coral reefs are projected to be at risk of long-term degradation due to coral bleaching, with these values increasing to 99% at 2°C (Frieler et al., 2013; Schleussner et al., 2016b) <sup>[[#fn:r840|840]]</sup> . Higher temperatures are also related to an increase in coral disease development, leading to coral degradation (Maynard et al., 2015) <sup>[[#fn:r841|841]]</sup> . For marine fisheries, limiting warming to 1.5°C decreases the risk of species extinction and declines in maximum catch potential, particularly for small islands in tropical oceans (Cheung et al., 2016a) <sup>[[#fn:r842|842]]</sup> .

Long-term risks of coastal flooding and impacts on populations, infrastructure and assets are projected to increase with higher levels of warming ( ''high confidence'' ). Tropical regions including small islands are expected to experience the largest increases in coastal flooding frequency, with the frequency of extreme water-level events in small islands projected to double by 2050 (Vitousek et al., 2017) <sup>[[#fn:r843|843]]</sup> . Wave-driven coastal flooding risks for reef-lined islands may increase as a result of coral reef degradation and SLR (Quataert et al., 2015) <sup>[[#fn:r844|844]]</sup> . Exposure to coastal hazards is particularly high for SIDS, with a significant share of population, infrastructure and assets at risk (Sections 3.4.5.3 and 3.4.9; Scott et al., 2012; Kumar and Taylor, 2015; Rhiney, 2015; Byers et al., 2018 <sup>[[#fn:r845|845]]</sup> ). Limiting warming to 1.5°C instead of 2°C would spare the inundation of lands currently home to 60,000 individuals in SIDS by 2150 (Rasmussen et al., 2018) <sup>[[#fn:r846|846]]</sup> . However, such estimates do not consider shoreline response (Section 3.4.5) or adaptation.

Risks of impacts across sectors are projected to be higher at 1.5°C compared to the present, and will further increase at 2°C ( ''medium to high confidence'' ). Projections indicate that at 1.5°C there will be increased incidents of internal migration and displacement (Sections 3.5.5, 4.3.6 and 5.2.2; Albert et al., 2017) <sup>[[#fn:r847|847]]</sup> , limited capacity to assess loss and damage (Thomas and Benjamin, 2017) <sup>[[#fn:r848|848]]</sup> and substantial increases in the risk to critical transportation infrastructure from marine inundation (Monioudi et al., 2018) <sup>[[#fn:r849|849]]</sup> . The difference between 1.5°C and 2°C might exceed limits for normal thermoregulation of livestock animals and result in persistent heat stress for livestock animals in SIDS (Lallo et al., 2018) <sup>[[#fn:r850|850]]</sup> .

At 1.5°C, limits to adaptation will be reached for several key impacts in SIDS, resulting in residual impacts, as well as loss and damage (Section 1.1.1, Cross-Chapter Box 12 in Chapter 5). Limiting temperature increase to 1.5°C versus 2°C is expected to reduce a number of risks, particularly when coupled with adaptation efforts that take into account sustainable development (Section 3.4.2 and 5.6.3.1, Box 4.3 and 5.3, Mycoo, 2017; Thomas and Benjamin, 2017) <sup>[[#fn:r851|851]]</sup> . Region-specific pathways for SIDS exist to address climate change (Section 5.6.3.1, Boxes 4.6 and 5.3, Cross-Chapter Box 11 in Chapter 4).

<span id="food-nutrition-security-and-food-production-systems-including-fisheries-and-aquaculture"></span>
=== 3.4.6 Food, Nutrition Security and Food Production Systems (Including Fisheries and Aquaculture) ===

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<span id="crop-production"></span>
==== 3.4.6.1 Crop production ====

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Quantifying the observed impacts of climate change on food security and food production systems requires assumptions about the many non-climate variables that interact with climate change variables. Implementing specific strategies can partly or greatly alleviate the climate change impacts on these systems (Wei et al., 2017) <sup>[[#fn:r852|852]]</sup> , whilst the degree of compensation is mainly dependent on the geographical area and crop type (Rose et al., 2016) <sup>[[#fn:r853|853]]</sup> . Despite these uncertainties, recent studies confirm that observed climate change has already affected crop suitability in many areas, resulting in changes in the production levels of the main agricultural crops. These impacts are evident in many areas of the world, ranging from Asia (C. Chen et al., 2014; Sun et al., 2015; He and Zhou, 2016) <sup>[[#fn:r854|854]]</sup> to America (Cho and McCarl, 2017) <sup>[[#fn:r855|855]]</sup> and Europe (Ramirez-Cabral et al., 2016) <sup>[[#fn:r856|856]]</sup> , and they particularly affect the typical local crops cultivated in specific climate conditions (e.g., Mediterranean crops like olive and grapevine, Moriondo et al., 2013a, b) <sup>[[#fn:r857|857]]</sup> .

Temperature and precipitation trends have reduced crop production and yields, with the most negative impacts being on wheat and maize (Lobell et al., 2011) <sup>[[#fn:r858|858]]</sup> , whilst the effects on rice and soybean yields are less clear and may be positive or negative (Kim et al., 2013; van Oort and Zwart, 2018) <sup>[[#fn:r859|859]]</sup> . Warming has resulted in positive effects on crop yield in some high-latitude areas (Jaggard et al., 2007; Supit et al., 2010; Gregory and Marshall, 2012; C. Chen et al., 2014; Sun et al., 2015; He and Zhou, 2016; Daliakopoulos et al., 2017) <sup>[[#fn:r860|860]]</sup> , and may make it possible to have more than one harvest per year (B. Chen et al., 2014; Sun et al., 2015) <sup>[[#fn:r861|861]]</sup> . Climate variability has been found to explain more than 60% of the of maize, rice, wheat and soybean yield variations in the main global breadbaskets areas (Ray et al., 2015) <sup>[[#fn:r862|862]]</sup> , with the percentage varying according to crop type and scale (Moore and Lobell, 2015; Kent et al., 2017) <sup>[[#fn:r863|863]]</sup> . Climate trends also explain changes in the length of the growing season, with greater modifications found in the northern high-latitude areas (Qian et al., 2010; Mueller et al., 2015) <sup>[[#fn:r864|864]]</sup> .

The rise in tropospheric ozone has already reduced yields of wheat, rice, maize and soybean by 3–16% globally (Van Dingenen et al., 2009) <sup>[[#fn:r865|865]]</sup> . In some studies, increases in atmospheric CO <sub>2</sub> concentrations were found to increase yields by enhancing radiation and water use efficiencies (Elliott et al., 2014; Durand et al., 2018) <sup>[[#fn:r866|866]]</sup> . In open-top chamber experiments with a combination of elevated CO <sub>2</sub> and 1.5°C of warming, maize and potato yields were observed to increase by 45.7% and 11%, respectively (Singh et al., 2013; Abebe et al., 2016) <sup>[[#fn:r867|867]]</sup> . However, observations of trends in actual crop yields indicate that reductions as a result of climate change remain more common than crop yield increases, despite increased atmospheric CO <sub>2</sub> concentrations (Porter et al., 2014) <sup>[[#fn:r868|868]]</sup> . For instance, McGrath and Lobell (2013) <sup>[[#fn:r869|869]]</sup> indicated that production stimulation at increased atmospheric CO <sub>2</sub> concentrations was mostly driven by differences in climate and crop species, whilst yield variability due to elevated CO <sub>2</sub> was only about 50–70% of the variability due to climate. Importantly, the faster growth rates induced by elevated CO <sub>2</sub> have been found to coincide with lower protein content in several important C3 cereal grains (Myers et al., 2014) <sup>[[#fn:r870|870]]</sup> , although this may not always be the case for C4 grains, such as sorghum, under drought conditions (De Souza et al., 2015) <sup>[[#fn:r871|871]]</sup> . Elevated CO <sub>2</sub> concentrations of 568–590 ppm (a range that corresponds approximately to RCP6 in the 2080s and hence a warming of 2.3°C–3.3°C (van Vuuren et al., 2011a <sup>[[#fn:r872|872]]</sup> , AR5 WGI Table 12.2 ) alone reduced the protein, micronutrient and B vitamin content of the 18 rice cultivars grown most widely in Southeast Asia, where it is a staple food source, by an amount sufficient to create nutrition-related health risks for 600 million people (Zhu et al., 2018) <sup>[[#fn:r873|873]]</sup> . Overall, the effects of increased CO <sub>2</sub> concentrations alone during the 21st century are therefore expected to have a negative impact on global food security ( ''medium confidence'' ).

Crop yields in the future will also be affected by projected changes in temperature and precipitation. Studies of major cereals showed that maize and wheat yields begin to decline with 1°C–2°C of local warming and under nitrogen stress conditions at low latitudes ( ''high confidence'' ) (Porter et al., 2014; Rosenzweig et al., 2014) <sup>[[#fn:r874|874]]</sup> . A few studies since AR5 have focused on the impacts on cropping systems for scenarios where the global mean temperature increase is within 1.5°C. Schleussner et al. (2016b) <sup>[[#fn:r875|875]]</sup> projected that constraining warming to 1.5°C rather than 2°C would avoid significant risks of declining tropical crop yield in West Africa, Southeast Asia, and Central and South America. Ricke et al. (2016) <sup>[[#fn:r876|876]]</sup> highlighted that cropland stability declines rapidly between 1°C and 3°C of warming, whilst Bassu et al. (2014) <sup>[[#fn:r877|877]]</sup> found that an increase in air temperature negatively influences the modelled maize yield response by –0.5 t ha−1°C–1 and Challinor et al. (2014) <sup>[[#fn:r878|878]]</sup> reported similar effect for tropical regions. Niang et al. (2014) <sup>[[#fn:r879|879]]</sup> projected significantly lower risks to crop productivity in Africa at 1.5°C compared to 2°C of warming. Lana et al. (2017) <sup>[[#fn:r880|880]]</sup> indicated that the impact of temperature increases on crop failure of maize hybrids would be much greater as temperatures increase by 2°C compared to 1.5°C ( ''high confidence'' ). J. Huang et al. (2017) <sup>[[#fn:r881|881]]</sup> found that limiting warming to 1.5°C compared to 2°C would reduce maize yield losses over drylands. Although Rosenzweig et al. (2017, 2018) <sup>[[#fn:r882|882]]</sup> did not find a clear distinction between yield declines or increases in some breadbasket regions between the two temperature levels, they generally did find projections of decreasing yields in breadbasket regions when the effects of CO <sub>2</sub> fertilization were excluded. Iizumi et al. (2017) <sup>[[#fn:r883|883]]</sup> found smaller reductions in maize and soybean yields at 1.5°C than at 2°C of projected warming, higher rice production at 2°C than at 1.5°C, and no clear differences for wheat on a global mean basis. These results are largely consistent with those of other studies (Faye et al., 2018; Ruane et al., 2018) <sup>[[#fn:r884|884]]</sup> . In the western Sahel and southern Africa, moving from 1.5°C to 2°C of warming has been projected to result in a further reduction of the suitability of maize, sorghum and cocoa cropping areas and yield losses, especially for C3 crops, with rainfall change only partially compensating these impacts (Läderach et al., 2013; World Bank, 2013; Sultan and Gaetani, 2016) <sup>[[#fn:r885|885]]</sup> .

A significant reduction has been projected for the global production of wheat (by 6.0 ± 2.9%), rice (by 3.2 ± 3.7%), maize (by 7.4 ± 4.5%), and soybean, (by 3.1%) for each degree Celsius increase in global mean temperature (Asseng et al., 2015; C. Zhao et al., 2017) <sup>[[#fn:r886|886]]</sup> . Similarly, Li et al. (2017) <sup>[[#fn:r887|887]]</sup> indicated a significant reduction in rice yields for each degree Celsius increase, by about 10.3%, in the greater Mekong subregion ( ''medium confidence'' ; Cross-Chapter Box 6: Food Security in this chapter). Large rice and maize yield losses are to be expected in China, owing to climate extremes ( ''medium confidence'' ) (Wei et al., 2017; Zhang et al., 2017) <sup>[[#fn:r888|888]]</sup> .

While not often considered, crop production is also negatively affected by the increase in both direct and indirect climate extremes. Direct extremes include changes in rainfall extremes (Rosenzweig et al., 2014) <sup>[[#fn:r889|889]]</sup> , increases in hot nights (Welch et al., 2010; Okada et al., 2011) <sup>[[#fn:r890|890]]</sup> , extremely high daytime temperatures (Schlenker and Roberts, 2009; Jiao et al., 2016; Lesk et al., 2016) <sup>[[#fn:r891|891]]</sup> , drought (Jiao et al., 2016; Lesk et al., 2016) <sup>[[#fn:r892|892]]</sup> , heat stress (Deryng et al., 2014 <sup>[[#fn:r893|893]]</sup> , Betts et al., 2018) <sup>[[#fn:r894|894]]</sup> , flooding (Betts et al., 2018; Byers et al., 2018) <sup>[[#fn:r895|895]]</sup> , and chilling damage (Jiao et al., 2016) <sup>[[#fn:r896|896]]</sup> , while indirect effects include the spread of pests and diseases (Jiao et al., 2014; van Bruggen et al., 2015) <sup>[[#fn:r897|897]]</sup> , which can also have detrimental effects on cropping systems.

Taken together, the findings of studies on the effects of changes in temperature, precipitation, CO <sub>2</sub> concentration and extreme weather events indicate that a global warming of 2°C is projected to result in a greater reduction in global crop yields and global nutrition than global warming of 1.5°C ( ''high confidence'' ; Section 3.6).

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==== 3.4.6.2 Livestock production ====

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Studies of climate change impacts on livestock production are few in number. Climate change is expected to directly affect yield quantity and quality (Notenbaert et al., 2017) <sup>[[#fn:r898|898]]</sup> , as well as indirectly impacting the livestock sector through feed quality changes and spread of pests and diseases (Kipling et al., 2016) <sup>[[#fn:r899|899]]</sup> ( ''high confidence'' ). Increased warming and its extremes are expected to cause changes in physiological processes in livestock (i.e., thermal distress, sweating and high respiratory rates) (Mortola and Frappell, 2000) <sup>[[#fn:r900|900]]</sup> and to have detrimental effects on animal feeding, growth rates (André et al., 2011; Renaudeau et al., 2011; Collier and Gebremedhin, 2015) <sup>[[#fn:r901|901]]</sup> and reproduction (De Rensis et al., 2015) <sup>[[#fn:r902|902]]</sup> . Wall et al. (2010) <sup>[[#fn:r903|903]]</sup> observed reduced milk yields and increased cow mortality as the result of heat stress on dairy cow production over some UK regions.

Further, a reduction in water supply might increase cattle water demand (Masike and Urich, 2008) <sup>[[#fn:r904|904]]</sup> . Generally, heat stress can be responsible for domestic animal mortality increase and economic losses (Vitali et al., 2009) <sup>[[#fn:r905|905]]</sup> , affecting a wide range of reproductive parameters (e.g., embryonic development and reproductive efficiency in pigs, Barati et al., 2008 <sup>[[#fn:r906|906]]</sup> ; ovarian follicle development and ovulation in horses, Mortensen et al., 2009) <sup>[[#fn:r907|907]]</sup> . Much attention has also been dedicated to ruminant diseases (e.g., liver fluke, Fox et al., 2011 <sup>[[#fn:r908|908]]</sup> ; blue-tongue virus, Guis et al., 2012 <sup>[[#fn:r909|909]]</sup> ; foot-and-mouth disease (FMD), Brito et al. (2017) <sup>[[#fn:r910|910]]</sup> ; and zoonotic diseases, Njeru et al., 2016; Simulundu et al., 2017) <sup>[[#fn:r911|911]]</sup> .

Climate change impacts on livestock are expected to increase. In temperate climates, warming is expected to lengthen the forage growing season but decrease forage quality, with important variations due to rainfall changes (Craine et al., 2010; Hatfield et al., 2011; Izaurralde et al., 2011) <sup>[[#fn:r912|912]]</sup> . Similarly, a decrease in forage quality is expected for both natural grassland in France (Graux et al., 2013) <sup>[[#fn:r913|913]]</sup> and sown pastures in Australia (Perring et al., 2010) <sup>[[#fn:r914|914]]</sup> . Water resource availability for livestock is expected to decrease owing to increased runoff and reduced groundwater resources. Increased temperature will ''likely'' induce changes in river discharge and the amount of water in basins, leading human and livestock populations to experience water stress, especially in the driest areas (i.e., sub-Saharan Africa and South Asia) ( ''medium confidence'' ) (Palmer et al., 2008) <sup>[[#fn:r915|915]]</sup> . Elevated temperatures are also expected to increase methane production (Knapp et al., 2014; M.A. Lee et al., 2017) <sup>[[#fn:r916|916]]</sup> . Globally, a decline in livestock of 7–10% is expected at about 2°C of warming, with associated economic losses between $9.7 and $12.6 billion (Boone et al., 2018) <sup>[[#fn:r917|917]]</sup> .

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<span id="fisheries-and-aquaculture-production"></span>
==== 3.4.6.3 Fisheries and aquaculture production ====

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Global fisheries and aquaculture contribute a total of 88.6 and 59.8 million tonnes of fish and other products annually (FAO, 2016) <sup>[[#fn:r918|918]]</sup> , and play important roles in the food security of a large number of countries (McClanahan et al., 2015; Pauly and Charles, 2015) <sup>[[#fn:r919|919]]</sup> as well as being essential for meeting the protein demand of a growing global population (Cinner et al., 2012, 2016; FAO, 2016; Pendleton et al., 2016) <sup>[[#fn:r920|920]]</sup> . A steady increase in the risks associated with bivalve fisheries and aquaculture at mid-latitudes is coincident with increases in temperature, ocean acidification, introduced species, disease and other drivers (Lacoue-Labarthe et al., 2016; Clements and Chopin, 2017; Clements et al., 2017; Parker et al., 2017) <sup>[[#fn:r921|921]]</sup> . Sea level rise and storm intensification pose a risk to hatcheries and other infrastructure (Callaway et al., 2012; Weatherdon et al., 2016) <sup>[[#fn:r922|922]]</sup> , whilst others risks are associated with the invasion of parasites and pathogens (Asplund et al., 2014; Castillo et al., 2017) <sup>[[#fn:r923|923]]</sup> . Specific human strategies have reduced these risks, which are expected to be moderate under RCP2.6 and very high under RCP8.5 (Gattuso et al., 2015) <sup>[[#fn:r924|924]]</sup> . The risks related to climate change for fin fish (Section 3.4.4) are producing a number of challenges for small-scale fisheries (e.g., Kittinger, 2013; Pauly and Charles, 2015; Bell et al., 2018) <sup>[[#fn:r925|925]]</sup> . Recent literature from 2015 to 2017 has described growing threats from rapid shifts in the biogeography of key species (Poloczanska et al., 2013, 2016; Burrows et al., 2014; García Molinos et al., 2015) <sup>[[#fn:r926|926]]</sup> and the ongoing rapid degradation of key ecosystems such as coral reefs, seagrass and mangroves (Section 3.4.4, Box 3.4). The acceleration of these changes, coupled with non-climate stresses (e.g., pollution, overfishing and unsustainable coastal development), are driving many small-scale fisheries well below the sustainable harvesting levels required to maintain these resources as a source of food (McClanahan et al., 2009, 2015; Cheung et al., 2010; Pendleton et al., 2016) <sup>[[#fn:r927|927]]</sup> . As a result, future scenarios surrounding climate change and global population growth increasingly project shortages of fish protein for many regions, such as the Pacific Ocean (Bell et al., 2013, 2018) <sup>[[#fn:r928|928]]</sup> and Indian Ocean (McClanahan et al., 2015) <sup>[[#fn:r929|929]]</sup> . Mitigation of these risks involves marine spatial planning, fisheries repair, sustainable aquaculture, and the development of alternative livelihoods (Kittinger, 2013; McClanahan et al., 2015; Song and Chuenpagdee, 2015; Weatherdon et al., 2016) <sup>[[#fn:r930|930]]</sup> . Other threats concern the increasing incidence of alien species and diseases (Kittinger et al., 2013; Weatherdon et al., 2016) <sup>[[#fn:r931|931]]</sup> .

Risks of impacts related to climate change on low-latitude small-scale fin fisheries are moderate today but are expected to reach very high levels by 1.1°C of global warming. Projections for mid-to high-latitude fisheries include increases in fishery productivity in some cases (Cheung et al., 2013; Hollowed et al., 2013; Lam et al., 2014; FAO, 2016) <sup>[[#fn:r932|932]]</sup> . These projections are associated with the biogeographical shift of species towards higher latitudes (Fossheim et al., 2015) <sup>[[#fn:r933|933]]</sup> , which brings benefits as well as challenges (e.g., increased production yet a greater risk of disease and invasive species; ''low confidence'' ). Factors underpinning the expansion of fisheries production to high-latitude locations include warming, increased light levels and mixing due to retreating sea ice (Cheung et al., 2009) <sup>[[#fn:r934|934]]</sup> , which result in substantial increases in primary productivity and fish harvesting in the North Pacific and North Atlantic (Hollowed and Sundby, 2014) <sup>[[#fn:r935|935]]</sup> .

Present-day risks for mid-latitude bivalve fisheries and aquaculture become undetectible up to 1.1°C of global warming, moderate at 1.3°C, and moderate to high up to 1.9°C (Figure 3.18). For instance, Cheung et al. (2016a) <sup>[[#fn:r936|936]]</sup> , simulating the loss in fishery productivity at 1.5°C, 2°C and 3.5°C above the pre-industrial period, found that the potential global catch for marine fisheries will ''likely'' decrease by more than three million metric tonnes for each degree of warming. Low-latitude fin-fish fisheries have higher risks of impacts, with risks being moderate under present-day conditions and becoming high above 0.9°C and very high at 2°C of global warming. High-latitude fisheries are undergoing major transformations, and while production is increasing, present-day risk is moderate and is projected to remain moderate at 1.5°C and 2°C (Figure 3.18).

Adaptation measures can be applied to shellfish, large pelagic fish resources and biodiversity, and they include options such as protecting reproductive stages and brood stocks from periods of high ocean acidification (OA), stock selection for high tolerance to OA ( ''high confidence'' ) (Ekstrom et al., 2015; Rodrigues et al., 2015; Handisyde et al., 2016; Lee, 2016; Weatherdon et al., 2016; Clements and Chopin, 2017) <sup>[[#fn:r937|937]]</sup> , redistribution of highly migratory resources (e.g., Pacific tuna) ( ''high confidence'' ), governance instruments such as international fisheries agreements (Lehodey et al., 2015; Matear et al., 2015) <sup>[[#fn:r938|938]]</sup> , protection and regeneration of reef habitats, reduction of coral reef stresses, and development of alternative livelihoods (e.g., aquaculture; Bell et al., 2013, 2018) <sup>[[#fn:r939|939]]</sup> .

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