Editing IPCC:AR6/WGII/Chapter-15 (section)

== 15.3 Observed Impacts and Projected Risks of Climate Change ==

<div id="h1-4-siblings" class="h1-siblings"></div>

Compared to larger landmasses, many climate change-driven impacts and risks are amplified for small islands. This is due largely to their boundedness (surrounded by ocean), their comparatively small land areas, and often their remoteness from more populated parts of the world, which restricts the global connectivity of islands. This is true on all types of islands (Figure 15.2).

<div id="_idContainer006" class="Figure"></div>

[[File:a6357627955d6cb059b3dd5e81ee97c5 IPCC_AR6_WGII_Figure_15_002.png]]

'''Figure 15.2 |''' '''Classification of small island types showing island characteristics and elements of human exposure (based on Nunn et a''' '''l.''' ''', 2016; [[#Kumar--2018|Kumar et al., 2018]] ).'''

<div id="15.3.1" class="h2-container"></div>

<span id="synthesis-of-observed-and-projected-changes-in-the-physical-basis"></span>
=== 15.3.1 Synthesis of Observed and Projected Changes in the Physical Basis ===

<div id="h2-3-siblings" class="h2-siblings"></div>

There is increased evidence of warming in the small islands, particularly in the latter half of the 20th century ( ''high confidence'' ). The diversity of metrics and timescales used across studies makes it impossible to provide explicit comparisons; however, Table 15.1 provides a summary of observed changes.

'''Table 15.1 |''' Observed changes in basic climate metrics.

{| class="wikitable"
|-
! Phenomenon

! Location

! Basic trends

! Specific metric

! Time period

! Reference literature

|-
| Air temp

| West Pacific

| Warmer

| Increase in daily mean minimum temp by 0.14°C per decade

| 1951–2015

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

|-
| Air temp

| Caribbean

| Warmer

| Increase in daily minimum temp by 0.28°C per decade

| 1961–2010

| [[#Stephenson--2014|Stephenson et al. (2014)]]

|-
| Air temp

| Mediterranean

| Warmer

| Increase in annual mean surface temp 0.19–0.25°C per decade

| 1960–2005

| [[#Mariotti--2015|Mariotti et al. (2015)]]

|-
| Land and sea temp

| Mediterranean

| Warmer

| Annual mean temperatures are now 1.54°C above the 1860–1890 level for land and sea

|
| (MedECC, 2020)

|-
| Rainfall

| Mediterranean

| Drier

| Decrease in annual mean precipitation by −0.6 mm d –1 and decade

| 1960–2005

| [[#Mariotti--2015|Mariotti et al. (2015)]] ; [[#Ducrocq--2016|Ducrocq et al. (2016)]]

|-
| Rainfall

| Pacific Ocean

| No clear pattern

| No significant long-term trends in rainfall

| 1951–2015

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

|-
| Rainfall

| Indian Ocean

| No clear pattern

|
| 1983–2015

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

|-
| Rainfall

| Caribbean

| No clear pattern

| No significant long-term trends in rainfall in the Caribbean over the 20th century

| 1901–2012

| [[#Jones--2015|Jones et al. (2015)]]

|-
| Drought

| Caribbean

| Low confidence in the direction of change

| Inconsistent between sub-regions and not statistically significant

| 1950–2016

| [[#Herrera--2017|Herrera and Ault (2017)]]

|-
| Drought

| Pacific Ocean

| Low confidence in the direction of change

| Inconsistent between sub-regions and not statistically significant in the tropical Pacific. Significant decrease in Hawaii and sub-tropical South Pacific

| 1951–2015

| McGree et al. (2016); [[#McGree--2019|McGree et al. (2019)]]

|-
| Tropical Cyclones

| North Atlantic

| Increase in intensity and decrease in frequency

|
| 1975–2009

| [[#Walsh--2016|Walsh et al. (2016)]]

|-
| Tropical Cyclones

| Western North Pacific

| Decreasing frequency

| Decrease in frequency except over central North Pacific

| 1977–2010

| [[#Walsh--2016|Walsh et al. (2016)]]

|-
| Tropical Cyclones

| South Pacific

| Increase in intensity and decrease in frequency

|
| 1989–2009

| [[#Walsh--2016|Walsh et al. (2016)]]

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

|-
| Tropical Cyclones

| Indian Ocean

| No clear pattern

| Poor data coverage

| 1961–2008

| [[#Tauvale--2019|Tauvale and Tsuboki (2019)]] ; [[#Kuleshov--2020|Kuleshov et al. (2020)]]

|-
| RSLR

| East Caribbean

| Greater than average

| 3–5 mm yr –1

| 1993–2014

| Becker et al. (2019)

|-
| RSLR

| West/North Caribbean

| Greater than average

| 2.5–3 mm yr –1

| 1993–2014

| Becker et al. (2019)

|-
| RSLR

| Western Tropical Pacific

| Greater than average

| 5–11 mm yr –1

| 1993–2014

| Becker et al. (2019)

|-
| RSLR

| Mauritius/Indian Ocean

| Greater than average

| 4 mm yr –1

| 1993–2014

| Becker et al. (2019)

|-
| RSLR

| Rodrigues/Indian Ocean

| Greater than average

| 6 mm yr –1

| 1993–2014

| Becker et al. (2019)

|}

Notes:

RSLR: relative sea-level rise

Some phenomena have no demonstrable trends in a region because of limited observed data, these include TC frequency in the northeastern Pacific and Indian oceans ( [[#Walsh--2016|Walsh et al., 2016]] ); other phenomena are too variable to detect an overarching trend, including rainfall in regions where inter-annual and decadal variabilities such as the El Niño-Southern Oscillation, North Atlantic Oscillation, Pacific Decadal Variability, Atlantic Multidecadal Variability are dominant ( [[#Jones--2015|Jones et al., 2015]] ; [[#McGree--2019|McGree et al., 2019]] ).

There are also marked regional variations in the rates of SLR ( [[#Merrifield--2011|Merrifield and Maltrud, 2011]] ; [[#Palanisamy--2012|Palanisamy et al., 2012]] ; [[#Esteban--2019|Esteban et al., 2019]] ) and relative SLR (RSLR; that is, incorporating land movement). Various factors, including interannual and decadal sea level variations associated with low-frequency modulation of ENSO and the Pacific Decadal Oscillation (PDO) and vertical land motion contribute to both relative sea level variations and related uncertainties. Increased distant-source swell height from extra-tropical cyclones (ETCs) also contributes to ESLs ( [[#Mentaschi--2017|Mentaschi et al., 2017]] ; [[#Vitousek--2017|Vitousek et al., 2017]] ). Together, these stressors increase ESLs and their impacts, including coastal erosion and marine flooding and their impacts on both ecosystems and ecosystem services and human activities ( [[#15.3.3.1|Section 15.3.3.1]] and Table 15.3).

'''Table 15.2 |''' A small subset of projected changes in basic climate metric. Med: Mediterranean; n.c.: no change.

{| class="wikitable"
|-
! rowspan="2"| Phenomenon

! rowspan="2"| Location

! rowspan="2"| General trend

! rowspan="2"| Metric

! colspan="2"| Specific projections 2040–2060

! colspan="2"| Specific projections 2080–2100

! rowspan="2"| Comments

! rowspan="2"| Reference

|-
! RCP 4.5

! RCP 8.5

! RCP 4.5

! RCP 8.5

|-
| rowspan="5"| Air temperature

| Caribbean

| Hotter, especially in the East

| Monthly mean temperature compared to 1971–2000

| n.a.

| 1.2°C rise

| 1.6C rise

| 3.0°C rise

| Specific to Lesser Antilles

| [[#Bowden--2020|Bowden et al. (2020)]] ; [[#Cantet--2014|Cantet et al. (2014)]]

|-
| East Atlantic

| Hotter

| Average annual temperature compared to 1971–2000

| 1.5–2°C rise

| 2.5°C rise

| n.a.

| n.a.

| ''Low-confidence'' , specific to Sao Tome and Principe

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

|-
| Med

| Hotter, especially in summer

| Average maximum daily temperature during summer compared to 1970–2000

| 1.6–1.9°C rise

| 2–2.5°C rise

| n.a.

| n.a.

| Specific to Sicily, Crete and Cyprus

| [[#Varotsos--2021|Varotsos et al. (2021)]]

|-
| Pacific

| Hotter

| Average temperature compared to 1986–2005

| 0.5–1.5°C rise

| 1.0–2.0°C rise

| 1.0–2.0°C rise

| 2.0–4.0°C rise

| Consistent in tropical latitudes

| [[#Lough--2016|Lough et al. (2016)]]

|-
| Global small islands

| Hotter

| Heat index compared to 1986–2005

| 1°C rise

| 1.5°C rise

| 1.3°C rise

| 2.8°C rise

| Equatorial, coastal and continental islands hotter than oceanic

| [[#Harter--2015|Harter et al. (2015)]]

|-
| rowspan="2"| ENSO

| rowspan="2"| Pacific

| More frequent extreme events

| Frequency compared to ~1900–1999

| n.a.

| n.a.

| n.a.

| 100% more El Niños, 73–100% more La Niñas

| High natural variability limits statistical significance in related patterns

| Cai et al., (2014); [[#Cai--2015b|Cai et al. (2015b)]]

|-
| Inconclusive change in variability

| Amplitude change compared to 1979–2005

| 0.02°C drop

| 0.01°C rise

| 0.04°C drop

| 0.04°C rise

| Specific projections are not statistically significant

| Cai et al., (2018); [[#Beobide-Arsuaga--2021|Beobide-Arsuaga et al. (2021)]]

|-
| rowspan="8"| Precipitation

| East Caribbean

| Slightly wetter, more extreme seasonality

| Total rainfall compared to wet/dry season compared to 1971–2001

| n.a.

| n.a.

| 5% rise/10% drop

| 8% rise/15% drop

| Significant local variability

| [[#Cantet--2014|Cantet et al. (2014)]]

|-
| West/North Caribbean

| Drier

| Annual rainfall compared to 1986–2005; consecutive dry days compared to 1961–1990

| n.a.

| 9% less rain

| n.a.

| Up to 327% more dry days

| Specific to Puerto Rico and US Virgin Islands

| Stennett- [[#Brown--2017|Brown et al. (2017)]] ; [[#Bowden--2020|Bowden et al. (2020)]]

|-
| East Atlantic

| Inconclusive change

| Monthly rainfall compared to 1971–2000

| 10–25-mm rise

| 10–25-mm drop

| n.a.

| n.a.

| ''Low-confidence'' , specific to Sao Tome and Principe

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

|-
| West Pacific

| Wetter, especially after mid-century

| Annual average rainfall compared to 1971-–2005

| 2% rise

| 6% rise

| 3% rise

| 8% rise

| ''Low-confidence'' , specific to Borneo

| [[#Sa’adi--2017|Sa’adi et al. (2017)]]

|-
| Central Pacific

| Drier, more extreme seasonality

| Total rainfall compared to 1975–2005

| 15% drop

| 20% drop

| 17% drop

| 30% drop

| ''Low-confidence'' , specific to Hawaii

| Timm et al. (2015)

|-
| Southwest Indian Ocean

| Drier during the wet season, especially south of 10S

| Average change in daily rainfall compared to 1971–2000

| n.a.

| n.a.

| n.a.

| 0.2 mm d –1 drop

| ''Low confidence''

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

|-
| Med

| Drier, but highly varied

| Annual mean precipitation compared to 1960–1990

| 70–100-mm drop

| 60–150- mm drop

| n.a.

| n.a.

| Specific to Malta; no significant change in Sicily, Crete and Cyprus

| [[#Varotsos--2021|Varotsos et al. (2021)]]

|-
| Global small islands

| Slightly wetter, highly variable

| Mean annual precipitation compared to 1986–2005

| &lt;1% rise

| &lt;1% rise

| 1.8% rise

| 3.2% rise

| Confidence limited by high standard deviation

| [[#Harter--2015|Harter et al. (2015)]]

|-
| rowspan="8"| Tropical Cyclones

| North Indian Ocean

| More storms in the west, fewer in the east

| Frequency compared to 1990–2013

| n.a.

| n.a.

| n.a.

| 30–60% rise/20–40% drop

| Specific to Arabian sea/Bay of Bengal

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

|-
| South Indian Ocean

| Fewer storms, fewer strong storms in east

| Storm/Category 4–5 frequency compared to 1979–2010

| n.a.

| n.a.

| n.a.

| 20–40% drop/0–20% drop

|
| [[#Bell--2019a|Bell et al. (2019a)]]

|-
| Northwest Pacific

| Slightly more and stronger storms at increasingly high latitudes

| Storm density compared to 1970–2000; poleward shift in annual mean of location of maximum intensity compared to 1980–2005

| n.a.

| n.a.

| n.a.

| 15–40% rise; 0.2°

| 10–40N, 140–170E

| Kossin et al. (2016); [[#Chand--2019|Chand et al. (2019)]]

|-
| Southwest and low-latitude Pacific

| Less frequent storms

| Storm density compared to 1970–2000

| n.a.

| n.a.

| n.a.

| 0–20% drop/20–30% drop

| South/North Pacific up to 20N, 100–140E

| [[#Bell--2019a|Bell et al. (2019a)]] [[#Chand--2019|Chand et al. (2019)]]

|-
| Northeast Pacific

| Less frequent storms

| Storm frequency compared to 1970–2016

| n.a.

| n.a.

| n.a.

| 2–13% drop

| No data for Southern Hemisphere

| [[#Bell--2019b|Bell et al. (2019b)]]

|-
| Central North Pacific

| More and stronger storms

| Mean annual TC/Category 4–5 composition compared to 1979–2010

| n.a.

| n.a.

| n.a.

| 31–88% rise

| Specific to Hawaii

| [[#Yoshida--2017|Yoshida et al. (2017)]]

|-
| Caribbean

| Slightly fewer storms

| Minor/major cyclones compared to 1984–2013

| n.a.

| 12% drop/n.c.

| n.a.

| n.a.

| Specific to lesser Antilles

| [[#Cantet--2021|Cantet et al. (2021)]]

|-
| East Atlantic

| More storms and slightly more frequent intense storms

| Storms per decade compared to 1979–2010

| n.a.

| n.a.

| n.a.

| 0–3 rise

| Specific to latitude &gt;15N

| [[#Yoshida--2017|Yoshida et al. (2017)]]

|-
| Extratropical cyclone

| Med

| Decreased frequency but increased intensity

| Frequency of storms compared to 1986–2005

| n.c.

| n.a.

| 12% drop

| n.a.

|
| [[#González-Alemán--2019|González-Alemán et al. (2019)]]

|}

Like observed impacts, projected impacts include some high confidence assessments, which are distributed across a diversity of models, timescales and metrics. Generalised trends, and specific projections when available, are provided in Table 15.2. However, actual values and spatial distribution of precipitation changes remain uncertain as they are strongly model dependent ( [[#Paeth--2017|Paeth et al., 2017]] ). Furthermore, the current capabilities of climate models, to adequately represent variability in climate drivers including ENSO, and the topography of small islands limit confidence in these future changes ( [[#Cai--2015a|Cai et al., 2015a]] ; [[#Harter--2015|Harter et al., 2015]] ; [[#Guilyardi--2016|Guilyardi et al., 2016]] ).

'''Table 15.3 |''' Percentage of selected islands classified as refugia for biodiversity at increasing levels of warming. While protected land is still ‘protected’ this table demonstrates the difficulty of protecting lands which might be ‘more resilient’ to climate change under increasing levels of warming and current land use practices. Derived from current and future projected distributions of ~130,000 terrestrial fungi, plants, invertebrates and vertebrates ( [[#Warren--2018a|Warren et al., 2018a]] ). Refugia=areas remaining climatically suitable for &gt;75% of the species modelled ( [[#Warren--2018b|Warren et al., 2018b]] ). '''Projections:''' based on mean impacts from 21 CMIP5 climate model patterns (no dispersal) and elevationally downscaled to 1 km under interpolated warming levels derived from RCP2.6, 4.5, 6.0 and 8.0 ( [[#Warren--2018a|Warren et al., 2018a]] ). First column-set: % island/island chain classified as a refugia based on '''''climate alone''''' ; second column-set: % natural land projected to be climate refugia—illustrating potential refugia ‘space’ already lost to habitat conversion. '''Colour key''' : white: &gt; 50%; yellow: 30–50%; red: 17–30%; dark red: &lt;17% of land classified as refugia.

{| class="wikitable"
|-
! Island(s)

! colspan="8"| Climate °C

! colspan="8"| Climate + land use °C

|-
|
| ''0.5''

| ''1''

| ''1.5''

| ''2''

| ''2.5''

| ''3''

| ''3.5''

| ''4''

| ''0.5''

| ''1''

| ''1.5''

| ''2''

| ''2.5''

| ''3''

| ''3.5''

| '''''4'''''

|-
| Aegean Islands

| 98

| 89

| 85

| 68

| 39

| 19

| 12

| 6

| 66

| 62

| 60

| 50

| 32

| 16

| 11

| 6

|-
| American Samoa

| 100

| 100

| 100

| 100

| 83

| 52

| 39

| 25

| 39

| 39

| 39

| 39

| 34

| 24

| 18

| 11

|-
| Andaman Nicobar

| 100

| 95

| 90

| 46

| 7

| 2

| 1

| 0

| 92

| 88

| 84

| 45

| 7

| 2

| 1

| 0

|-
| Balearic Islands

| 99

| 97

| 95

| 82

| 26

| 6

| 4

| 2

| 29

| 28

| 28

| 25

| 13

| 6

| 3

| 2

|-
| Bangka

| 100

| 100

| 97

| 3

| 1

| 0

| 0

| 0

| 20

| 20

| 19

| 1

| 0

| 0

| 0

| 0

|-
| Barbados

| 94

| 67

| 53

| 25

| 5

| 0

| 0

| 0

| 10

| 7

| 6

| 3

| 1

| 0

| 0

| 0

|-
| Borneo

| 98

| 92

| 89

| 60

| 25

| 14

| 10

| 6

| 67

| 62

| 60

| 43

| 24

| 13

| 10

| 6

|-
| Bougainville

| 92

| 81

| 77

| 62

| 39

| 28

| 24

| 19

| 87

| 77

| 74

| 58

| 37

| 27

| 23

| 18

|-
| British Indian Ocean Territory

| 100

| 100

| 94

| 0

| 0

| 0

| 0

| 0

| 47

| 47

| 47

| 0

| 0

| 0

| 0

| 0

|-
| Corsica

| 72

| 61

| 57

| 43

| 29

| 18

| 15

| 10

| 64

| 53

| 50

| 38

| 26

| 16

| 13

| 8

|-
| Crete

| 91

| 83

| 80

| 68

| 52

| 35

| 27

| 20

| 51

| 47

| 46

| 42

| 35

| 26

| 22

| 17

|-
| Cuba

| 97

| 94

| 92

| 69

| 14

| 4

| 3

| 1

| 48

| 46

| 45

| 36

| 10

| 4

| 3

| 1

|-
| Cyprus

| 53

| 51

| 49

| 44

| 32

| 20

| 14

| 8

| 48

| 46

| 44

| 37

| 24

| 14

| 9

| 6

|-
| Dominica

| 79

| 66

| 63

| 51

| 41

| 28

| 20

| 14

| 79

| 66

| 63

| 51

| 41

| 28

| 20

| 14

|-
| French Polynesia

| 100

| 100

| 100

| 100

| 100

| 81

| 68

| 54

| 38

| 38

| 38

| 38

| 38

| 32

| 28

| 23

|-
| Galapagos

| 91

| 82

| 79

| 67

| 50

| 27

| 18

| 13

| 93

| 88

| 86

| 74

| 54

| 33

| 21

| 14

|-
| Grenada

| 73

| 49

| 43

| 29

| 18

| 10

| 6

| 3

| 71

| 48

| 43

| 29

| 18

| 10

| 6

| 3

|-
| Guadeloupe

| 91

| 71

| 64

| 27

| 19

| 13

| 9

| 6

| 57

| 46

| 42

| 26

| 19

| 13

| 9

| 6

|-
| Guernsey

| 100

| 52

| 41

| 0

| 0

| 0

| 0

| 0

| 13

| 7

| 5

| 0

| 0

| 0

| 0

| 0

|-
| Hispaniola

| 77

| 60

| 54

| 35

| 22

| 15

| 12

| 9

| 55

| 43

| 40

| 28

| 19

| 13

| 11

| 8

|-
| Indonesia

| 95

| 87

| 81

| 54

| 28

| 17

| 14

| 11

| 60

| 55

| 51

| 36

| 23

| 15

| 12

| 10

|-
| Jamaica

| 77

| 65

| 61

| 47

| 31

| 17

| 10

| 5

| 64

| 54

| 51

| 40

| 27

| 15

| 9

| 4

|-
| Java

| 91

| 74

| 65

| 37

| 24

| 17

| 13

| 10

| 27

| 24

| 22

| 18

| 14

| 11

| 9

| 7

|-
| Kiribati

| 100

| 55

| 38

| 14

| 0

| 0

| 0

| 0

| 15

| 12

| 12

| 5

| 0

| 0

| 0

| 0

|-
| Madagascar

| 98

| 90

| 87

| 70

| 47

| 28

| 22

| 13

| 84

| 77

| 73

| 58

| 37

| 21

| 16

| 10

|-
| Maldives

| 100

| 38

| 1

| 0

| 0

| 0

| 0

| 0

| 16

| 0

| 0

| 0

| 0

| 0

| 0

| 0

|-
| Marajo

| 100

| 58

| 33

| 0

| 0

| 0

| 0

| 0

| 91

| 55

| 33

| 0

| 0

| 0

| 0

| 0

|-
| Marshall Islands

| 100

| 99

| 99

| 55

| 22

| 0

| 0

| 0

| 46

| 46

| 46

| 15

| 10

| 0

| 0

| 0

|-
| Mauritius

| 100

| 100

| 100

| 100

| 100

| 100

| 92

| 74

| 27

| 27

| 27

| 27

| 27

| 27

| 25

| 23

|-
| Micronesia

| 100

| 100

| 100

| 78

| 59

| 31

| 16

| 6

| 86

| 86

| 86

| 72

| 56

| 29

| 15

| 6

|-
| Montserrat

| 61

| 43

| 39

| 27

| 20

| 9

| 9

| 4

| 56

| 38

| 35

| 23

| 17

| 9

| 7

| 4

|-
| Nauru

| 100

| 100

| 97

| 0

| 0

| 0

| 0

| 0

| 11

| 11

| 11

| 0

| 0

| 0

| 0

| 0

|-
| New Caledonia

| 100

| 100

| 99

| 97

| 89

| 62

| 45

| 31

| 76

| 75

| 75

| 74

| 69

| 53

| 41

| 28

|-
| New Guinea

| 95

| 84

| 73

| 47

| 32

| 25

| 22

| 19

| 86

| 76

| 67

| 43

| 30

| 23

| 21

| 18

|-
| Northern Mariana Islands

| 100

| 100

| 99

| 95

| 58

| 29

| 19

| 11

| 49

| 49

| 49

| 46

| 35

| 22

| 16

| 9

|-
| Orinoco Delta

| 100

| 31

| 9

| 0

| 0

| 0

| 0

| 0

| 93

| 29

| 9

| 0

| 0

| 0

| 0

| 0

|-
| Palau

| 100

| 79

| 73

| 21

| 0

| 0

| 0

| 0

| 74

| 59

| 55

| 17

| 0

| 0

| 0

| 0

|-
| Palawan

| 86

| 70

| 64

| 36

| 21

| 12

| 9

| 6

| 55

| 47

| 44

| 31

| 20

| 12

| 9

| 6

|-
| Philippines

| 90

| 74

| 66

| 41

| 27

| 16

| 12

| 8

| 34

| 30

| 28

| 21

| 15

| 10

| 8

| 6

|-
| Prince Edward

| 100

| 100

| 100

| 100

| 100

| 97

| 9

| 0

| 35

| 35

| 35

| 35

| 35

| 33

| 2

| 0

|-
| Puerto Rico

| 84

| 66

| 59

| 41

| 25

| 15

| 11

| 7

| 63

| 52

| 49

| 36

| 24

| 14

| 11

| 7

|-
| Saint Lucia

| 77

| 50

| 45

| 29

| 14

| 6

| 3

| 1

| 72

| 50

| 45

| 29

| 14

| 6

| 3

| 1

|-
| Saint Vincent and the Grenadines

| 73

| 57

| 50

| 37

| 27

| 18

| 13

| 8

| 63

| 50

| 44

| 34

| 23

| 15

| 10

| 5

|-
| Samoa

| 100

| 100

| 100

| 99

| 89

| 67

| 56

| 46

| 34

| 34

| 34

| 34

| 31

| 24

| 22

| 20

|-
| Sardinia

| 95

| 87

| 83

| 65

| 34

| 16

| 10

| 5

| 41

| 38

| 37

| 31

| 22

| 12

| 8

| 4

|-
| Seychelles

| 100

| 100

| 98

| 83

| 57

| 25

| 16

| 9

| 25

| 25

| 25

| 22

| 18

| 8

| 6

| 5

|-
| Sicily

| 93

| 84

| 80

| 60

| 35

| 18

| 11

| 7

| 16

| 15

| 15

| 13

| 10

| 7

| 6

| 4

|-
| Singapore

| 100

| 100

| 100

| 98

| 9

| 0

| 0

| 0

| 14

| 14

| 14

| 13

| 3

| 0

| 0

| 0

|-
| Solomon Islands

| 93

| 79

| 74

| 48

| 28

| 15

| 10

| 6

| 92

| 78

| 73

| 48

| 28

| 15

| 10

| 6

|-
| Sri Lanka

| 98

| 94

| 89

| 64

| 23

| 11

| 7

| 5

| 47

| 46

| 44

| 36

| 16

| 7

| 5

| 4

|-
| Sulawesi

| 86

| 75

| 71

| 58

| 44

| 33

| 28

| 23

| 60

| 54

| 52

| 46

| 38

| 30

| 26

| 21

|-
| Sumatra

| 96

| 90

| 87

| 65

| 24

| 16

| 13

| 11

| 40

| 37

| 36

| 30

| 18

| 13

| 11

| 9

|-
| Sumba

| 98

| 90

| 86

| 70

| 49

| 23

| 11

| 4

| 36

| 33

| 31

| 26

| 18

| 9

| 4

| 2

|-
| Timor

| 92

| 84

| 80

| 66

| 48

| 30

| 22

| 15

| 11

| 10

| 9

| 8

| 7

| 5

| 4

| 3

|-
| Trinidad and Tobago

| 88

| 24

| 16

| 6

| 3

| 1

| 0

| 0

| 64

| 20

| 14

| 6

| 3

| 1

| 0

| 0

|-
| Tuvalu

| 100

| 100

| 100

| 34

| 0

| 0

| 0

| 0

| 3

| 3

| 3

| 0

| 0

| 0

| 0

| 0

|-
| Wallis and Futuna

| 100

| 100

| 100

| 65

| 32

| 11

| 3

| 0

| 35

| 35

| 35

| 33

| 21

| 7

| 1

| 0

|}

<div id="15.3.2" class="h2-container"></div>

<span id="trends-in-exposure-and-vulnerability"></span>
=== 15.3.2 Trends in Exposure and Vulnerability ===

<div id="h2-4-siblings" class="h2-siblings"></div>

Most of the research that has been conducted on exposure and vulnerability from climate change demonstrates that factors including those that are geopolitical and political, environmental, socioeconomic and cultural together conspire to increase exposure and vulnerability of small islands (Box 15.1; [[#Betzold--2015|Betzold, 2015]] ; [[#McCubbin--2015|McCubbin et al., 2015]] ; [[#Duvat--2017b|Duvat et al., 2017b]] ; [[#Otto--2017|Otto et al., 2017]] ; [[#Weir--2017|Weir et al., 2017]] ; [[#Taupo--2018|Taupo et al., 2018]] ; [[#Barclay--2019|Barclay et al., 2019]] ; [[#Hay--2019a|Hay et al., 2019a]] ; [[#Ratter--2019|Ratter et al., 2019]] ; [[#Salmon--2019|Salmon et al., 2019]] ; [[#Bordner--2020|Bordner et al., 2020]] ; [[#Douglass--2020|Douglass and Cooper, 2020]] ; [[#Duvat--2020a|Duvat et al., 2020a]] ). Additional pressures on coastal and marine environments, including overexploitation of natural resources, may further exacerbate possible impacts in the future ( [[#Bell--2013|Bell et al., 2013]] ; [[#Pinnegar--2019|Pinnegar et al., 2019]] ; [[#Siegel--2019|Siegel et al., 2019]] ).

Furthermore, these factors exacerbate climate change-induced problems such as coastal flooding and erosion faced by small islands. These impacts continue to worsen, putting small islands at increasingly higher risk to the impacts of climate change (Box 15.1). There are multiple stressors that affect the vulnerability of small islands to climate change ( [[#McNamara--2019|McNamara et al., 2019]] ).

The problems of increasing exposure and vulnerability are most clearly seen in atoll islands. For example, in the capital of Tuvalu, economic stressors, food-related stressors and overcrowding make the islands much more vulnerable to climate impacts including changing precipitation patterns, ESLs, intense strong winds, warming sea surface temperature (SST) and ocean acidification ( [[#McCubbin--2015|McCubbin et al., 2015]] ). Small islands, in trying to address the problem of limited land availability, put in place practices that lead to increasing exposure for island people. In Majuro, Marshall Islands ( [[#Ford--2012|Ford, 2012]] ), Tarawa, Kiribati ( [[#Biribo--2013|Biribo and Woodroffe, 2013]] ; [[#Duvat--2013|Duvat, 2013]] ), and the Maldives Islands ( [[#Kench--2012|Kench, 2012]] ; [[#Naylor--2015|Naylor, 2015]] ; [[#Duvat--2019b|Duvat and Magnan, 2019b]] ), population growth has led to land reclamation and the building of coastal protection structures, such as seawalls. Land reclamation and coastal protection structures negatively impact coastal and marine ecosystems, including reefs and mangroves, which compromise the protection services that they deliver to island communities through wave energy attenuation and sediment supply ( [[#Gracia--2018|Gracia et al., 2018]] ; [[#Curnick--2019|Curnick et al., 2019]] ; [[#Duvat--2019a|Duvat and Magnan, 2019a]] ) and may impact the long-term sustainable adaptive planning of islands ( [[#Giardino--2018|Giardino et al., 2018]] ). In addition, these construction activities disrupt natural coastal processes, thereby causing coastal erosion, which in turn increases the risk of flooding ( [[#Yamano--2007|Yamano et al., 2007]] ; [[#Duvat--2017b|Duvat et al., 2017b]] ) (Figure 15.3). This becomes a vicious cycle, with more land reclamation necessary to accommodate growing populations. Land reclamation requires stabilisation by protection structures, which then contributes to environmental degradation that increases the exposure and vulnerability of the communities living in these atolls ( [[#Duvat--2017b|Duvat et al., 2017b]] ).

<div id="_idContainer009" class="Figure"></div>

[[File:7d3aefa6ab28385d7a66ad38dcc02ce9 IPCC_AR6_WGII_Figure_15_003.png]]

'''Figure 15.3 |''' '''Percentage of current population in selected small islands occupying vulnerable land (the number of people on land that may be exposed to coastal inundation—either by permanently falling below MHHW, or temporarily falling below the local annual flood height) in 2100 under an RCP''' '''4.''' '''5 scenario (adapted from [[#Kulp--2019|Kulp and Strauss, 2019]] , using the CoastalDEM_Perm_p50 model).''' Positions on the map are based on the capital city or largest town.

<div id="15.3.3" class="h2-container"></div>

<span id="observed-impacts-and-projected-risks-on-natural-systems"></span>
=== 15.3.3 Observed Impacts and Projected Risks on Natural Systems ===

<div id="h2-5-siblings" class="h2-siblings"></div>

<div id="15.3.3.1" class="h3-container"></div>

<span id="impacts-on-marine-and-coastal-systems"></span>
==== 15.3.3.1 Impacts on Marine and Coastal Systems ====

<div id="h3-1-siblings" class="h3-siblings"></div>

<div id="15.3.3.1.1" class="h4-container"></div>

<span id="submergence-and-flooding-of-islands-and-coastal-areas"></span>
===== 15.3.3.1.1 Submergence and flooding of islands and coastal areas =====

<div id="h4-5-siblings" class="h4-siblings"></div>

Recent studies confirmed that observed ESL events causing extensive flooding generally resulted from compound effects, including the combination of SLR ( [[IPCC:Wg2:Chapter:Chapter-3#3.2.2.2|Section 3.2.2.2]] and Cross-Chapter Box SLR in Chapter 3) with ETCs, TCs and tropical depressions (WGI AR6 Sections 11.7.1 and 11.7.2, Seneviratne, 2021), ENSO-related high-water levels associated with high or spring tide and/or local human disturbances amplifying impacts ( ''high confidence'' ). For example, the major floods that occurred in 1987 and 2007 in the Maldives involved the combination of distant-source swells and high spring tides and the settlement of reclaimed low-lying areas (Box 15.1; [[#Wadey--2017|Wadey et al., 2017]] ). In the Tuamotu atolls, French Polynesia, the 1996 and 2011 floods were due to the combination of distant-source swells causing lagoon filling and the obstruction of inter-islet channels by human-built structures ( [[#Canavesio--2019|Canavesio, 2019]] ). In 2011, the flooding of the lagoon-facing coast of Majuro Atoll, Marshall Islands, resulted from the combination of high sea levels occurring during La Niña conditions and seasonally high tides ( [[#Ford--2018|Ford et al., 2018]] ). Another example is the widespread flooding caused by distant TC Pam (2015) in Kiribati and Tuvalu, which was attributed to the strong swell generated, the long duration of the event and exceptionally high regional sea levels ( [[#Hoeke--2021|Hoeke et al., 2021]] ). On high tropical islands, major floods often occurred during TC events, due to the cumulative effects of storm surge and river flooding, the impacts of which were exacerbated by human-induced changes to natural processes in urban areas. This, for example, occurred in 2014 (TC Bejisa) in Reunion Island, France, in a harbour area favourable to water accumulation ( [[#Duvat--2016|Duvat et al., 2016]] ); in 2015 (TC Pam) in Port Vila, Vanuatu, where urbanisation and human-induced changes to the river exacerbated flooding (Rey et al., 2017); and in 2017 (TC Irma) in Saint-Martin, Caribbean, where urbanisation had the same effect ( [[#Rey--2019|Rey et al., 2019]] ). Successive tropical depressions generating heavy rains were also involved in extensive flooding, for example, in 2012 in Fiji ( [[#Kuleshov--2014|Kuleshov et al., 2014]] ) and in 2014 in the Solomon Islands ( [[#Ha’apio--2019|Ha’apio et al., 2019]] ).

Reconstructions of past storm surges and modelling studies assessing storm surge risk similarly highlighted high variations of risk along island coasts, due to variations in exposure, topography and bathymetry ( ''high confidence'' ). For example, the storm surge caused by TC Oli (2010) on the high volcanic island of Tubuai, French Polynesia, ranged from a few centimetres to 2.5 m, depending on coast exposure ( [[#Barriot--2016|Barriot et al., 2016]] ). Investigating the contribution of reef characteristics to variations in wave-driven flooding on Roi-Namur Island, Kwajalein Atoll, Marshall Islands, [[#Quataert--2015|Quataert et al. (2015)]] found that the coasts fronted by narrow reefs with steep fore reef slopes and smoother reef flats are the most flood-prone. Modelling studies assessing storm surge risk in Fiji ( [[#McInnes--2014|McInnes et al., 2014]] ) and Samoa ( [[#McInnes--2016|McInnes et al., 2016]] ) confirmed the influence of coast exposure and water depth on risk distribution. In Apia, Samoa, Hoeke et al. (2015, p. 1117) found ‘differences in extreme sea levels in the order of 1 m at spatial scales of less than 1 km’ and estimated (p. 1131) that a ‘1 m SLR relative to constant topography increases wave energy reaching the shore by up to 200% during storm surges.’ These studies reaffirmed the main control exerted by SLR on ESL events and associated storm surges compared to ENSO ( ''high confidence'' ). In Hawaii and the Caribbean, SLR is projected to exponentially increase flooding, with nearly every centimetre of SLR causing a doubling of the probability of flooding ( [[#Taherkhani--2020|Taherkhani et al., 2020]] ). Simulations of SLR-induced flooding resulting from the combination of (a) direct marine flooding, (b) flow reversal in drainage networks caused by extreme tide levels and (c) the elevation of groundwater levels, at Honolulu, Hawaii, highlighted the major influence of this latter component (which is the most difficult to manage), as well as the increase of the proportion of triple-mechanism flooding as sea level rises ( [[#Habel--2020|Habel et al., 2020]] ). Where coral reefs buffer flooding through wave attenuation, flooding will be further aggravated by reef decline over time ( [[#15.3.3.1.3|Section 15.3.3.1.3]] ).

Larger-scale studies confirmed that projected changes in the wave climate superimposed on SLR will rapidly increase flooding in small islands, despite highly contrasting exposure profiles between ocean sub-regions ( ''high confidence'' ) ( [[#Shope--2016|Shope et al., 2016]] ; [[#Mentaschi--2017|Mentaschi et al., 2017]] ; [[#Shope--2017|Shope et al., 2017]] ; [[#Vitousek--2017|Vitousek et al., 2017]] ; [[#Morim--2019|Morim et al., 2019]] ). In particular, [[#Vitousek--2017|Vitousek et al. (2017)]] showed that even a 5–10-cm additional SLR (expected for ~2030–2050) will double flooding frequency in much of the Indian Ocean and Tropical Pacific, while TCs will remain the main driver of (rarer) flooding in the Caribbean Sea and Southern Tropical Pacific (Figure 15.3). Some Pacific atoll islands, which already experience major floods, will ''likely'' undergo annual wave-driven flooding over their entire surface from the 2060s–2070s ( [[#Storlazzi--2018|Storlazzi et al., 2018]] ) to 2090s ( [[#Beetham--2017|Beetham et al., 2017]] ) under RCP8.5, although future reef growth may delay the onset of flooding ( ''limited evidence, low agreement'' ) (key risk KR2 in Figure 15.5).

<div id="15.3.3.1.2" class="h4-container"></div>

<span id="reef-island-destabilisation-and-coastal-erosion"></span>
===== 15.3.3.1.2 Reef island destabilisation and coastal erosion =====

<div id="h4-6-siblings" class="h4-siblings"></div>

Over the past three to five decades, shoreline changes were dominated by stability on reef islands and erosion on high islands; attribution of observed erosion to SLR and other climate change-related drivers is challenged by the complex interplay of multiple climatic, ecological and human drivers ( ''high confidence'' ). Since the 1950s–1970s, and even in regions exhibiting higher than global-averaged SLR rates, atoll islands maintained their land area ( ''high confidence).'' A literature review including 709 Indian Ocean and Pacific Ocean atoll islands showed that 73.1% of these islands were stable in area, while, respectively, 15.5% and 11.4% increased and decreased in area ( [[#Duvat--2018|Duvat, 2018]] ). The rates of change did not correlate with SLR rates, suggesting that the impact of SLR on island land area was obscured by other climate drivers and human disturbances on some islands ( ''high confidence'' ) ( [[#Kench--2015|Kench et al., 2015]] ; [[#McLean--2015|McLean and Kench, 2015]] ; [[#Duvat--2018|Duvat, 2018]] ). However, reef island disappearance and reduction in land area was clearly observed in New Caledonia and the Solomon Islands, and was attributed to the synergistic interactions of gradual SLR with stronger trade winds causing higher sea levels and local tectonics in the Solomon Islands ( [[#Albert--2016|Albert et al., 2016]] ; [[#Garcin--2016|Garcin et al., 2016]] ). Despite important knowledge gaps on coastal erosion in high tropical islands, recent studies confirmed increasing shoreline retreat and beach loss over the past decades, mainly due to TC and ETC waves and human disturbances ( ''high confidence'' ) (e.g., in the Caribbean region: Anguilla, Saint-Kitts, Nevis, Montserrat, Dominica and Grenada ( [[#Cambers--2009|Cambers, 2009]] ; [[#Reguero--2018|Reguero et al., 2018]] )), and Pacific (Hawaii ( [[#Romine--2013|Romine and Fletcher, 2013]] ); Tubuai, French Polynesia ( [[#Salmon--2019|Salmon et al., 2019]] )) and Indian Oceans (Anjouan, Comoros ( [[#Ratter--2016|Ratter et al., 2016]] ).

Despite storm-induced erosion prevailing along some shoreline sections, recent studies reaffirmed the contribution of TC and ETC waves to coastal and reef island vertical building through massive reef-to-island sediment transfer ''(high confidence'' ). For example, TC Ophelia (1958) and Category 5 TC Fantala (2016), which eroded the islands of Jaluit Atoll, Marshall Islands ( [[#Ford--2016|Ford and Kench, 2016]] ), and Farquhar Atoll, Seychelles ( [[#Duvat--2017c|Duvat et al., 2017c]] ), respectively, also contributed to island and beach expansion. Likewise, tropical depressions can have constructional effects, as reported on Fakarava Atoll, French Polynesia ( [[#Duvat--2020b|Duvat et al., 2020b]] ). On Saint-Martin/Sint Maarten and Saint-Barthélemy, the 2017 hurricanes, which caused marked shoreline retreat at most beach sites, also enabled beach formation and beach ridge development along some natural coasts ( [[#Duvat--2019a|Duvat et al., 2019a]] ; [[#Pillet--2019|Pillet et al., 2019]] ). Similarly, El Niño and La Niña were involved in rapid and highly contrasting shoreline changes ( ''high confidence'' ), including reef island accretion in the Ryukyu Islands, Japan ( [[#Kayanne--2016|Kayanne et al., 2016]] ), beach shifts on Maiana and Aranuka atolls, Kiribati (Rankey, 2011), and beach erosion on Hawaii, USA ( [[#Barnard--2015|Barnard et al., 2015]] ). These contrasting shoreline responses were, respectively, due to coral reef degradation from past bleaching events providing material to islands, wave directional shifts, and increased wave energy. The role of bleaching events in increasing short-term sediment generation in atoll contexts was confirmed by a study conducted on Gaafu Dhaalu Atoll, Maldives, which reported an increase of sediment production from ~0.5 kg CaCO 3 m –2 yr -1 to ~3.7 kg CaCO 3 m –2 yr -1 between 2016 (pre-bleaching) and 2019 (bleaching + 3 years) ( [[#Perry--2020|Perry et al., 2020]] ).

There is ''high confidence'' that accelerating SLR and increased wave height will affect the geomorphology of reef islands ( [[#Baldock--2015|Baldock et al., 2015]] ; [[#Costa--2019|Costa et al., 2019]] ; [[#Tuck--2019|Tuck et al., 2019]] ) and coastal systems on high islands ( [[#Grady--2013|Grady et al., 2013]] ; [[#Barnard--2015|Barnard et al., 2015]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ), and that the responses of these systems will highly depend on changes in boundary conditions (wave regime and direction, exposure to extreme events, impacts of ocean warming and acidification on supporting ecosystems, bathymetry and reef flat roughness) and the degree of disturbance of their natural dynamics by human activities ( [[#Smithers--2014|Smithers and Hoeke, 2014]] ; [[#McLean--2015|McLean and Kench, 2015]] ; [[#Bheeroo--2016|Bheeroo et al., 2016]] ; [[#Ratter--2016|Ratter et al., 2016]] ; [[#Shope--2016|Shope et al., 2016]] ; [[#Duvat--2017a|Duvat et al., 2017a]] ; [[#Kench--2017|Kench and Mann, 2017]] ; [[#Kench--2018|Kench et al., 2018]] ; [[#Duvat--2019a|Duvat et al., 2019a]] ). Reef islands and beach and beach-dune systems that are not disturbed by human activities are, respectively, expected to migrate lagoonward ( [[#Webb--2010|Webb and Kench, 2010]] ; [[#Albert--2016|Albert et al., 2016]] ; [[#Beetham--2017|Beetham et al., 2017]] ; [[#Costa--2019|Costa et al., 2019]] ; [[#Tuck--2019|Tuck et al., 2019]] ) and landward ( [[#Bindoff--2019|Bindoff et al., 2019]] ), and to also experience increased erosion as well as changes in configuration, volume and elevation ( [[#Kench--2017|Kench and Mann, 2017]] ; [[#Tuck--2019|Tuck et al., 2019]] ) ( [[#Bramante--2020|Bramante et al., 2020]] ; [[#Kane--2020|Kane and Fletcher, 2020]] ). Small reef islands and narrow coastal systems affected by human disturbances will increasingly be at risk of disappearance due to SLR (KR2 in Figure 15.5), enhanced sediment loss caused by extreme events ( [[#Duvat--2019a|Duvat et al., 2019a]] ) and/or human activities ( ''high confidence'' ), as reported in Hawaii ( [[#Romine--2013|Romine and Fletcher, 2013]] ), Puerto Rico ( [[#Jackson--2012|Jackson et al., 2012]] ), Sicily ( [[#Anfuso--2012|Anfuso et al., 2012]] ), and Takuu, Papua New Guinea ( [[#Mann--2014|Mann and Westphal, 2014]] ). SLR will also increase coastal erosion in the Mediterranean Sea, (e.g., in the Aegean Archipelago, Greece ( [[#Monioudi--2017|Monioudi et al., 2017]] ), and Mallorca, Spain ( [[#Enríquez--2017|Enríquez et al., 2017]] ).

<div id="_idContainer021" class="Figure"></div>

[[File:a1cb2010756818ae2f65cc852f12fad6 IPCC_AR6_WGII_Figure_15_005.png]]

'''Figure 15.5 |''' '''Key risks in small islands'''. KR1 to KR8 are interconnected as shown by ''arrows'' , which causes risk accumulation leading to reduced island habitability. The main interconnections are shown in this figure: for example, loss of marine and coastal and terrestrial biodiversity and ecosystem services (KR1 and KR3, respectively) are projected to cause the submergence of reef islands (KR2), water insecurity (KR4), destruction of settlements and infrastructure (KR5), degradation of human health and well-being (KR6), economic decline and livelihood failure (KR7), and loss of cultural resources and heritage (KR8). Importantly, KRs result from both direct effects (e.g., decrease in rainfall will increase water insecurity) and indirect effects (e.g., loss of terrestrial biodiversity and ecosystem services will increase water insecurity, which will in turn cause the degradation of human health and well-being).

<div id="15.3.3.1.3" class="h4-container"></div>

<span id="impacts-on-marine-and-coastal-ecosystems"></span>
===== 15.3.3.1.3 Impacts on marine and coastal ecosystems =====

<div id="h4-7-siblings" class="h4-siblings"></div>

Loss of marine and coastal biodiversity and ecosystem services is a key risk in small islands (see KR1 in Figure 15.5). Coral bleaching caused by elevated water temperatures is the most visible and widespread manifestation of a climate change impact on coastal ecosystems in most small islands but is far from being the only one (Sections 3.4.2.1 and [[IPCC:Wg2:Chapter:Chapter-5#5.3|Section 5.3.4]] ; [[#Spalding--2015|Spalding and Brown, 2015]] ; [[#Hoegh-Guldberg--2017|Hoegh-Guldberg et al., 2017]] ; [[#IPCC--2018|IPCC, 2018]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ; [[#Sully--2019|Sully et al., 2019]] ). Severe coral bleaching, together with declines in coral abundance have been documented in many small islands, especially those in the Pacific Ocean and Indian Ocean (e.g., Guam, Fiji, Palau, Vanuatu, Chagos, Comoros, Mauritius, Seychelles, and the Maldives ( ''high confidence'' ) (Box 15.1; [[#Golbuu--2007|Golbuu et al., 2007]] ; [[#Woesik--2012|Woesik et al., 2012]] ; [[#Perry--2017|Perry and Morgan, 2017]] ; [[#Hughes--2018|Hughes et al., 2018]] ). During severe bleaching events, not only do reefs lose a significant amount of live coral cover, but they also experience a decrease in growth potential, and thus reef erosion surpasses reef accretion ( [[#Perry--2017|Perry and Morgan, 2017]] ). Median return time between two severe bleaching events has diminished steadily since 1980 and is now only 6 years (e.g., [[#Hughes--2017b|Hughes et al., 2017b]] ; [[#Hughes--2018|Hughes et al., 2018]] ) and is often associated with warm phase of ENSO events ( ''high confidence'' ) ( [[#Lix--2016|Lix et al., 2016]] ). Modelling of both bleaching and ocean acidification effects under future climate scenarios suggested that some Pacific small islands (e.g., Nauru, Guam, Northern Marianas Islands) will experience conditions that cause severe bleaching on an annual basis before 2040 and that 90% of the world reefs are projected to experience conditions that result in severe bleaching annually by 2055 ( ''medium confidence'' ) ( [[#van%20Hooidonk--2016|van Hooidonk et al., 2016]] ). Models are currently predicting the large-scale loss of coral reefs by mid-century under even low-emission scenarios. Even achieving emission 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 ( ''high confidence'' ) ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ).

Satellite data and local field studies at 3351 sites in 81 countries including small islands show that not all coral reefs are equally exposed to severe temperature stress events, and even similar coral reefs exposed to similar conditions show local and regional variation and species-specific responses ( [[#Sully--2019|Sully et al., 2019]] ). There is great variability in terms of sensitivity of corals to climate change, as also demonstrated in the Comoros Archipelago ( [[#Cowburn--2018|Cowburn et al., 2018]] ), in the Pacific ( [[#Fox--2019|Fox et al., 2019]] ; [[#Mollica--2019|Mollica et al., 2019]] ; [[#Romero-Torres--2020|Romero-Torres et al., 2020]] ) and globally ( [[#Sully--2019|Sully et al., 2019]] ; [[#McClanahan--2020|McClanahan et al., 2020]] ). It has been hypothesised that low-latitude tropical reefs bleached less than those in higher latitudes because: (a) of the geographical differences in species composition, (b) of the higher genotypic diversity at low latitudes, and (c) some corals were pre-adapted to thermal stress because of consistently warmer temperatures at low latitude prior to thermal stress events ( [[#Sully--2019|Sully et al., 2019]] ). However, latitudinal variation was not reported in other global surveys of coral bleaching occurrence ( [[#Donner--2017|Donner et al., 2017]] ; [[#Hughes--2017a|Hughes et al., 2017a]] ; [[#Hughes--2017b|Hughes et al., 2017b]] ; [[#McClanahan--2019|McClanahan et al., 2019]] ). [[#Ainsworth--2016|Ainsworth et al. (2016)]] and [[#Ateweberhan--2013|Ateweberhan et al. (2013)]] showed that coral bleaching can be mitigated by pre-exposure to elevated temperatures. Regionally, recovery is also highly variable. While some reefs in the Seychelles and Maldives were shown to recover to pre-disturbance levels of coral cover after previous bleaching events (Box 15.1; [[#Pisapia--2016|Pisapia et al., 2016]] ; [[#Koester--2020|Koester et al., 2020]] ), other reefs underwent seemingly permanent regime shifts toward domination by fleshy macro algae ( [[#Graham--2015|Graham et al., 2015]] ), or major declines in carbonate budgets, and thus the capacity of reefs to sustain vertical growth under rising sea levels ( [[#Perry--2017|Perry and Morgan, 2017]] ).

Despite their vital social and ecological value, substantial declines in seagrass communities have been documented in many small islands ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.5|Section 3.4.2.5]] ; [[#Arias-Ortiz--2018|Arias-Ortiz et al., 2018]] ; [[#Kendrick--2019|Kendrick et al., 2019]] ; [[#Brodie--2020|Brodie et al., 2020]] ), including Fiji ( [[#Joseph--2019|Joseph et al., 2019]] ), Reunion Island ( [[#Cuvillier--2017|Cuvillier et al., 2017]] ), Bermuda, Cayman Islands, US Virgin Islands ( [[#Waycott--2009|Waycott et al., 2009]] ), Kiribati ( [[#Brodie--2020|Brodie et al., 2020]] ), Federated States of Micronesia, and Palau ( [[#Short--2016|Short et al., 2016]] ), but attribution of such declines to climatic influences remains weak ( ''low confidence'' ). The impact of climate change on seagrasses goes beyond the loss of seagrass but includes acceleration of seagrass decomposition ( [[#Kelaher--2018|Kelaher et al., 2018]] ), palatability ( [[#Jimenez-Ramos--2017|Jimenez-Ramos et al., 2017]] ) and the cumulative effect of warming and eutrophication ( [[#Ontoria--2019|Ontoria et al., 2019]] ). Seagrasses face a multitude of threats including physical disturbance and direct damage caused by rapidly growing human populations, declines in water quality, and coastal erosion ( [[#Short--2016|Short et al., 2016]] ). Experimental studies have shown increased mortality, leaf necrosis, and respiration when seagrasses are exposed to higher-than-normal temperatures ( [[#Hernan--2017|Hernan et al., 2017]] ). As such, seagrass meadows growing near the edge of their thermal tolerance are at risk from rising temperatures ( [[#Pedersen--2016|Pedersen et al., 2016]] ). In the Mediterranean, seagrass meadows are already showing signs of regression, which may have been aggravated by climate change ( ''high confidence'' ). Some studies suggest seagrasses have potential for acclimation and adaptation ( [[#Duarte--2018|Duarte et al., 2018]] ; [[#Ruiz--2018|Ruiz et al., 2018]] ; [[#Beca-Carretero--2020|Beca-Carretero et al., 2020]] ). Chefaoui et al. (2018) attempted to forecast the distribution of two seagrasses in the future, including around the islands of Cyprus, Malta, Sicily and the Balearic Islands. Under the worst-case scenario, ''Posidonia oceanica'' was projected to lose 75% of suitable habitat by 2050. Conversely, it has been suggested that seagrasses could actually benefit from an increase in anthropogenic CO 2 because of increased growth and photosynthesis ( [[#Hopley--2007|Hopley et al., 2007]] ; [[#Waycott--2011|Waycott et al., 2011]] ; [[#Sunday--2016|Sunday et al., 2016]] ; [[#Repolho--2017|Repolho et al., 2017]] ). However, [[#Collier--2017|Collier et al. (2017)]] argued that when faced with increased heat waves, thermal stress will rarely be offset by the benefit of elevated CO 2 and therefore that the widespread belief that seagrasses will be a ‘winner’ under future climate change conditions seems unlikely ''(low confidence'' ).

Since 2011, the Caribbean region has been experiencing unprecedented influxes of the pelagic seaweed ''Sargassum'' . These extraordinary sargassum ‘blooms’ have resulted in mass strandings of sargassum throughout the Lesser Antilles, with significant damage to coastal habitats, mortality of seagrass beds and associated corals ( [[#van%20Tussenbroek--2017|van Tussenbroek et al., 2017]] ), as well as consequences for fisheries and tourism. Whether or not such events are related to long-term climate change remains unclear; however, it has been suggested that the influx may be related to strong Amazon discharge, enhanced West African upwelling, together with rising seawater temperatures in the Atlantic ( ''low confidence'' ) ( [[#Oviatt--2019|Oviatt et al., 2019]] ; [[#Wang--2019|Wang et al., 2019]] ). Since 2011, the Pacific atoll nation of Tuvalu has also been affected by algal blooms, the most recent being a large growth of ''Sargassum'' on the main atoll of Funafuti, and this phenomenon has been related to anthropogenic eutrophication and high seawater temperatures ( [[#De%20Ramon%20N’Yeurt--2014|De Ramon N’Yeurt and Iese, 2014]] ).

Mangroves face serious risks from deforestation and unsustainable coastal development ( [[IPCC:Wg2:Chapter:Chapter-3#3.4.2.5|Section 3.4.2.5]] ; [[#Gattuso--2015|Gattuso et al., 2015]] ). Large-scale die-offs around many small islands suggest that mangroves face increased risks from climate change ( [[#Sippo--2018|Sippo et al., 2018]] ). Mangrove seaward edge retreat has been demonstrated in American Samoa and at Tikina Wai in Fiji, in Bermuda, West Papua, Grand Cayman and attributed to long-term SLR or tectonic subsidence ( [[#Ellison--1993|Ellison, 1993]] ; [[#Ellison--2005|Ellison, 2005]] ; [[#Gilman--2007|Gilman et al., 2007]] ; [[#Ellison--2015|Ellison and Strickland, 2015]] ). Inundation-related mortality of mangroves could, in theory, be mitigated if mangrove substrates can ‘keep up’ with rising sea level by accretion. Pacific Island studies using radionuclides (e.g., 210Pb, 137Cs) have suggested that most mangroves are keeping up with current rates of SLR ( [[#Alongi--2008|Alongi, 2008]] ; [[#MacKenzie--2016|MacKenzie et al., 2016]] ), while surface elevation tables (SETs) suggest otherwise. [[#Lovelock--2015|Lovelock et al. (2015)]] reported that nearly 70% of the mangroves monitored with SETs are not keeping up with current SLR rates. If SLR exceeds 6 mm yr –1 , mangroves may be unable to maintain their elevation relative to sea level, a threshold likely to be surpassed in the next 30 years under high emission scenarios ( [[#Ellison--1993|Ellison, 1993]] ; [[#Saintilan--2020|Saintilan et al., 2020]] ). In these worst-case scenarios, flooding would result in tree, root and rhizome death and an abrupt change in elevation through peat collapse ( [[#Krauss--2010|Krauss et al., 2010]] ; [[#Lang’at--2014|Lang’at et al., 2014]] ), creating a positive feedback loop between SLR and elevation loss. Geomorphology, hydrology, tidal range and suspended sediments are important factors that will determine if mangroves will survive increased rates of SLR ( [[#Lovelock--2015|Lovelock et al., 2015]] ; [[#Sasmito--2015|Sasmito et al., 2015]] ; [[#Rogers--2019|Rogers et al., 2019]] ). TCs can cause extensive damage to mangroves ( [[#Short--2016|Short et al., 2016]] ). While immediate physical damage is often considerable, trees can sometimes recover by re-foliating, re-sprouting or regenerating ( [[#Kauffman--2010|Kauffman and Cole, 2010]] ). Examples of substantive mangrove recovery include the regrowth of trees in the Bay Islands of Honduras following Hurricane Mitch (October 1998) ( [[#Fickert--2018|Fickert, 2018]] ) and in the Nicobar Islands, India, following the December 2004 Indian Ocean Tsunami ( [[#Nehru--2018|Nehru and Balasubramanian, 2018]] ).

Sandy beaches are an important ecosystem in small islands, with high socioeconomic as well as ecosystem services value ( [[#Ellison--2018|Ellison, 2018]] ). Turtles and many seabirds nest just above the high-water mark on sandy beaches or among sand dunes, but TCs, rising seas, storm surges and heavy rainfall as well as inappropriate coastal development can erode beaches ( [[#15.3.1|Section 15.3.1.2]] ) resulting in damage to nests and eggs ( [[#Fuentes--2011|Fuentes et al., 2011]] ). Beach-nesting turtle populations are projected to become threatened around many small islands as a result of future climate change (e.g., Bonaire – Netherlands Antilles ( [[#Fish--2005|Fish et al., 2005]] ), Bioko Island – Equatorial Guinea ( [[#Veelenturf--2020|Veelenturf et al., 2020]] ), Cyprus ( [[#Varela--2019|Varela et al., 2019]] ), Raine Island – Australia ( [[#Pike--2015|Pike et al., 2015]] )), although other populations such as those around the Cape Verde Islands are projected to remain relatively robust ( [[#Abella%20Perez--2016|Abella Perez et al., 2016]] ). Turtles are also threatened by temperature rise around some small islands as warmer temperatures on nesting beaches can lead to an unbalanced sex ratio in the population (e.g., St. Eustatius island, ( [[#Laloë--2016|Laloë et al., 2016]] )).

<div id="15.3.3.1.4" class="h4-container"></div>

<span id="marine-and-coastal-ecosystem-services"></span>
===== 15.3.3.1.4 Marine and coastal ecosystem services =====

<div id="h4-8-siblings" class="h4-siblings"></div>

Intact coral reefs ( [[#Woodhead--2019|Woodhead et al., 2019]] ), seagrass meadows ( [[#Hejnowicz--2015|Hejnowicz et al., 2015]] ) and mangroves ( [[#UNEP--2014b|UNEP, 2014b]] ) ( [[#Friess--2016|Friess, 2016]] ) provide a variety of ecosystem services that are key to island communities, including provisioning services (e.g., timber, fisheries, aquaculture), regulating services (e.g., coastal protection, carbon storage, filtering of pollutants), cultural services ( [[#Pascua--2017|Pascua et al., 2017]] ) as well as supporting community resilience ( [[#Förster--2019|Förster et al., 2019]] ). If coastal ecosystems are degraded and lost, then the benefits they provide are also lost ( [[#Oleson--2018|Oleson et al., 2018]] ; [[#Förster--2019|Förster et al., 2019]] ; [[#Brodie--2020|Brodie et al., 2020]] ). In small islands where the risk of loss to ecosystem services is high (Cross-Chapter Box DEEP in Chapter 17), many of these ecosystem services cannot be easily replaced ( ''medium confidence'' ). The beneficial role that coral reefs play in coastal protection through wave attenuation, and therefore enhancing climate resilience in small islands, has been extensively studied (e.g., [[#Elliff--2017|Elliff and Silva, 2017]] ; [[#Harris--2018|Harris et al., 2018]] ; [[#Reguero--2018|Reguero et al., 2018]] ). Indeed, it has been demonstrated that in small islands (such as the Cayman Islands, Grenada, Bahamas) averted damages as a result of protecting intact coral reefs can be considerable when expressed as a percentage of GDP ( [[#Beck--2018|Beck et al., 2018]] ). [[#Ferrario--2014|Ferrario et al. (2014)]] conducted a global meta-analysis including many small islands across the Atlantic, Pacific and Indian oceans and found that coral reefs reduce wave height by an average of 84% (and wave energy by 97%) and that reef crests alone dissipate most of this energy. Based on another meta-analysis of 69 case studies worldwide (wave heights measured before and after the habitat), [[#Narayan--2016|Narayan et al. (2016)]] observed that coral reefs, mangroves and seagrass reduced wave height by 70%, 31% and 36%, respectively (Figure 15.4) and thus perform an essential role in protecting human lives and livelihoods ( ''high confidence'' ). Post-TC studies have provided additional evidence for the protection services offered by coastal ecosystems. On some Caribbean islands (e.g., Saint-Martin/Sint Maarten) where the dense indigenous vegetation belt was preserved, the vegetative structure buffered the waves of TCs Irma and José (2017), reducing the extent of marine inundation and shoreline retreat to a 30-m-wide coastal strip against values &gt;160 m in deforested areas ( [[#Duvat--2019a|Duvat et al., 2019a]] ; [[#Pillet--2019|Pillet et al., 2019]] ). By contrast, the destruction of mangrove ecosystems, even a few trees around the fringes, can accelerate coastal erosion, as exemplified by observations in Micronesia ( [[#Krauss--2010|Krauss et al., 2010]] ; [[#Nunn--2017a|Nunn et al., 2017a]] ).

<div id="_idContainer012" class="Figure"></div>

[[File:70b5381bbe7e40eceb637fbdf4241eba IPCC_AR6_WGII_Figure_15_004.png]]

'''Figure 15.4 |''' '''Ridge-to-reef interrelated protection services delivered by ecosystems on small islands.''' On small islands, terrestrial, coastal and marine ecosystems are interconnected and interdependent, with each ecosystem contributing towards maintaining the health of the others. Together, these ecosystems provide protection services against natural hazards (including flooding, erosion, landslides, mudflows, glacial melting and sedimentation) to human populations living on islands. As a consequence, the degradation of one or more of these ecosystems significantly reduces the protection services provided by this continuum of ecosystems. Conversely, the protection or restoration of one or more of these ecosystems also provides benefits to the other ecosystems and enhances the protection services provided to island inhabitants. See Box [https://www.ipcc.ch/chapter/15#CCP1.1 CCP1.1] for more details.

As corals, mangroves and seagrasses disappear, so do fish and other dependent organisms that directly benefit industries such as ecotourism and fisheries ( ''high confidence'' ) ( [[#Graham--2015|Graham et al., 2015]] ; [[#Cinner--2016|Cinner et al., 2016]] ). These impacts are sometimes exacerbated by catastrophic events such as tropical storms and marine heatwaves that destroy habitats and hence the resources upon which coastal fisheries depend ( [[#Sainsbury--2018|Sainsbury et al., 2018]] ). There is ''high confidence'' that climate change impacts, together with local human disturbances, will continue to denude coastal and marine ecosystem services in many small islands with serious consequences for vulnerable communities ( [[#Elliff--2017|Elliff and Silva, 2017]] ; [[#Bindoff--2019|Bindoff et al., 2019]] ).

<div id="15.3.3.2" class="h3-container"></div>

<span id="impacts-on-freshwater-systems"></span>
==== 15.3.3.2 Impacts on Freshwater Systems ====

<div id="h3-2-siblings" class="h3-siblings"></div>

Freshwater systems on small islands are exposed to dynamic climate impacts and are considered to be among the most threatened on the planet (key risk 3 in Box 15.1; [[#Settele--2014|Settele et al., 2014]] ; [[#IPCC--2018|IPCC, 2018]] ; [[#Butchart--2019|Butchart et al., 2019]] ). [[#Hoegh-Guldberg--2019|Hoegh-Guldberg et al. (2019)]] estimated that freshwater stress on small islands would be 25% less with a warming of 1.5°C or less as compared to 2.0°C. While some island regions are projected to experience substantial freshwater decline, an opposite trend is observed for some western Pacific and northern Indian Ocean islands ( [[#Holding--2016|Holding et al., 2016]] ; [[#Karnauskas--2016|Karnauskas et al., 2016]] ). Island topography and ecophysiology influence water storage capacity and rainfall response potential ( [[#Dunn--2018|Dunn et al., 2018]] ). On high volcanic and granitic islands, freshwater ecosystems are often closely connected with coastal spaces, and changes in freshwater supply from river systems have direct implications for salinity and sediment loads ( ''high confidence'' ) ( [[#Yang--2015|Yang et al., 2015]] ; [[#Zahid--2018|Zahid et al., 2018]] ). Climate impacts on streamflow patterns in tropical islands also create shifts in water supply for downstream users and habitat conditions for organisms supporting a wide range of ecosystem services ( ''high confidence'' ) ( [[#Strauch--2015|Strauch et al., 2015]] ; [[#Frazier--2019|Frazier and Brewington, 2019]] ; [[#Frauendorf--2020|Frauendorf et al., 2020]] ).

Projected changes in aridity are expected to impose freshwater stress on many small islands, especially SIDS ''(high confidence'' ).These changes are congruent with drought risk projections for Caribbean SIDS ( [[#Lehner--2017|Lehner et al., 2017]] ; [[#Taylor--2018|Taylor et al., 2018]] ) and aligned with observations from the Shared Socioeconomic Pathway (SSP) 2 scenario, where a 1°C increase in temperature (from 1.7°C to 2.7°C) could result in a 60% increase in the number of people projected to experience severe water resources stress from 2043 to 2071 ( [[#Schewe--2014|Schewe et al., 2014]] ; [[#Karnauskas--2018|Karnauskas et al., 2018]] ). In the Mediterranean region, freshwater resources will decline by 10–30% ''(medium confidence)'' ( [[#Koutroulis--2016|Koutroulis et al., 2016]] ; [[#Kumar--2020|Kumar et al., 2020]] ). For example, analysis of annual and seasonal streamflow data on the island of Mallorca shows a decreasing trend during spring and summer, with a reduction of up to 17% in some basins (Garcia, 2017).

The influence of climate change spans several variables for atoll islands with multiple, interacting forces that exacerbate impacts on freshwater ecosystems ( [[#Connell--2016|Connell, 2016]] ), including groundwater and freshwater resources ( [[#Warix--2017|Warix et al., 2017]] ). Analysis of groundwater resources on Roi-Namur, in the Marshall Islands, reveals that the extent of salinisation of fresh groundwater lenses varies with the scale of the overwash ( [[#Gingerich--2017|Gingerich et al., 2017]] ). [[#Alsumaiei--2018|Alsumaiei and Bailey (2018)]] estimated an 11–36% reduction in the fresh groundwater lens volume of the small atoll islands (area &lt; 0.6 km²) of the Maldives due to SLR. Small overwash events lead to saline conditions that last for up to 3 months ( [[#Oberle--2017|Oberle et al., 2017]] ).

SLR undermines the long-term persistence of freshwater-dependent ecosystems on islands ( [[#Goodman--2012|Goodman et al., 2012]] ) and is one of the greatest threats to the goods and services these environments provide (Box 16.1; [[#Mitsch--2013|Mitsch and Hernandez, 2013]] ). [[#Hoegh-Guldberg--2019|Hoegh-Guldberg et al. (2019)]] posit that as sea level rises, managing the risk of salinisation of freshwater resources will become increasingly important. On Roi-Namur, Marshall Islands, [[#Storlazzi--2018|Storlazzi et al. (2018)]] found that the availability of freshwater is impacted by the compounding effect of SLR and coastal flooding. In other Pacific atolls, [[#Terry--2012|Terry and Chui (2012)]] showed that freshwater resources could be significantly affected by a 0.40-m SLR. Similar impacts are anticipated for some Caribbean countries (Stennett- [[#Brown--2017|Brown et al., 2017]] ). Such changes in SLR could increase salinity in estuarine and aquifer water, affecting ground and surface water resources for drinking and irrigation water ( [[#Mycoo--2018a|Mycoo, 2018a]] ) across the region ( ''high confidence'' ). SLR also affects groundwater quality ( [[#Bailey--2016|Bailey et al., 2016]] ), salinity ( [[#Gingerich--2017|Gingerich et al., 2017]] ) and water-table height ( [[#Masterson--2014|Masterson et al., 2014]] ).

<div id="15.3.3.3" class="h3-container"></div>

<span id="impacts-on-terrestrial-biodiversity-systems"></span>
==== 15.3.3.3 Impacts on Terrestrial Biodiversity Systems ====

<div id="h3-3-siblings" class="h3-siblings"></div>

Despite encompassing approximately 2% of the Earth’s terrestrial surface, oceanic and other high-endemicity islands are estimated to harbour substantial proportions of existing species including ~25% extant global flora, ~12% birds and ~10% mammals ( [[#Alcover--1998|Alcover et al., 1998]] ; [[#Wetzel--2013|Wetzel et al., 2013]] ; [[#Kumar--2017|Kumar and Tehrany, 2017]] ). Islands also have higher densities of critically endangered species, hosting just under half of all species currently considered to be at risk of extinction ( [[#Spatz--2017a|Spatz et al., 2017a]] ; 2017b), hence making the loss of terrestrial biodiversity and related ecosystem services a KR (KR3) for small islands (Figure 15.5). Impacts from developing synergies between changing climate, natural and anthropogenic stressors on islands (Cross-Chapter Box DEEP in Chapter 17) could lead to disproportionate changes in global biodiversity. The most prominent drivers include: SLR, increasing intensities of extreme events (human activities—especially continuing/accelerating habitat destruction/degradation) and the introduction of invasive alien species (IAS) ( [[#Tershy--2015|Tershy et al., 2015]] ). When coupled with characteristic small island traits such as spatial and other resource limitations, these synergies play a critical role towards increasing the vulnerability of these insular ecosystems (Box [https://www.ipcc.ch/chapter/15#CCP1.1 CCP1.1] ). This is likely to hinder the adaptation response of terrestrial biota–increasing the risk of biodiversity loss and, in turn, impairing the resilience capacity of ecosystem functioning and services ( ''high confidence'' ) ( [[#Heller--2009|Heller and Zavaleta, 2009]] ; [[#Ferreira--2016|Ferreira et al., 2016]] ; [[#Vogiatzakis--2016|Vogiatzakis et al., 2016]] ).

Current observations of insular species response to climate change generally report geographic range shifts/reductions for species and vegetation associations in addition to resulting impacts on local ecology ( [[#Virah-Sawmy--2016|Virah-Sawmy et al., 2016]] ; [[#Koide--2017|Koide et al., 2017]] ; [[#Maharaj--2019|Maharaj et al., 2019]] ). These include changes in plant/animal phenology and resulting community alterations such as for the common Mediterranean island species ''Quercus ilex'' (holly oak) and ''Ficus carica'' (common fig). Species have been shifting greater distances to access not only suitable climate conditions but also, by association, suitable breeding conditions and seasonal food. Examples include: migratory birds such as ''Coturnix coturnix'' now having earlier spring arrival dates in the Mediterranean compared to six decades ago and the increased mortality of the iconic ''Argyroxiphium sandwicense'' (Hinahina) as result of warmer drier trends at Hawaiian high altitudes ( [[#Krushelnycky--2012|Krushelnycky et al., 2012]] ; [[#Taylor--2016a|Taylor and Kumar, 2016a]] ; [[#Vogiatzakis--2016|Vogiatzakis et al., 2016]] ). There have also been die-offs of some species from temperature extremes (e.g., flying fox species: ''Pteropus'' species) within the Pacific islands ( [[#Taylor--2016a|Taylor and Kumar, 2016a]] ).

Recorded alterations of ecological interactions include increased competition, changes to migratory routes ( [[#Harter--2015|Harter et al., 2015]] ) and mismatches between species, such as increased pathogen attacks on Mediterranean forest species ( [[#Vogiatzakis--2016|Vogiatzakis et al., 2016]] ). Also, in some areas of Madagascar there has been increased vulnerability to fire, due to the replacement of succulents by less fire-resilient species ( [[#Virah-Sawmy--2016|Virah-Sawmy et al., 2016]] ). Further, the low functional redundancy of island ecosystems implies a comparatively higher proportion of keystone species than continents, many of them being endemic ( [[#Harter--2015|Harter et al., 2015]] ), with potentially unpredictable system consequences due to climate-induced ecological changes. For example, Caribbean land crabs have been observed to alter their food intake as a response to drying conditions ( [[#McGaw--2019|McGaw et al., 2019]] ) and Aldabra giant land tortoises have reduced their activity in response to increasing temperature and decreasing precipitation ( [[#Falcon--2018|Falcon and Hansen, 2018]] ); such changes in both these ecosystem engineers are of potential consequence for seed dispersal, among other ecological functions.

The majority of studies modelling geographical range changes of small island species, to even the most optimistic 21st century climate change scenarios, imply a reduction in climate refugia (Table 15.3, Box [https://www.ipcc.ch/chapter/15#CCP1.1 CCP1.1] ). This is due to projected strong shifts, reductions or even complete losses of climatic niches resulting from inadequate geographic space for species to track suitable climate envelopes ( ''high confidence'' ) (e.g., [[#Maharaj--2013|Maharaj and New, 2013]] ; [[#Fortini--2015|Fortini et al., 2015]] ; [[#Struebig--2015b|Struebig et al., 2015b]] ). Because of the high proportion of global endemics hosted within small and especially isolated islands, the resulting increased extinction risk of such species (up to 100%) could lead to disproportionate losses in global biodiversity ( ''medium'' to ''high confidence'' ) ( [[#Harter--2015|Harter et al., 2015]] ; [[#Manes--2021|Manes et al., 2021]] ).

SLR has been projected to impact the terrestrial biodiversity of low-lying islands and coastal regions via large habitat losses both directly (e.g., submergence) and indirectly (e.g., salinity intrusion, salinisation of coastal wetlands and soil erosion) at even the 1-m scenario ( ''medium'' to ''high confidence'' ). However, these impacts vary depending on the islands’ topographical differences. In a study of SLR impacts on insular biodiversity hotspots, Bellard et al. (2013a) reported that the Caribbean islands, Sundaland and the Philippines were projected to suffer the most habitat loss while the East Melanesian islands were projected to be less (but not minimally) affected. The most threatened of these, the Caribbean, was projected to have between 8.7% and 49.2% of its islands entirely submerged, respectively, from 1-m to 6-m SLR ( [[#Bellard--2013a|Bellard et al., 2013a]] ). However, many current projection studies consider marine flooding directly and seldom incorporate other indirect impacts such as increased habitat losses from horizontal erosion loss, increased salinity levels, tidal ranges and extreme events. These projections are considered to be conservative, underestimating the extent of habitat loss to terrestrial biodiversity ( [[#Bellard--2013b|Bellard et al., 2013b]] ).

Marine flooding is expected to destroy habitats of coastal species, particularly range-restricted coastal and/or single-island endemics (many already listed as ''at least'' ‘threatened’ by the International Union for Conservation of Nature) within the limited terrain on atoll islands. These species have limited opportunities to accommodate such direct impacts of climate change apart from shifting further inland or to other neighbouring atolls which might have favourable habitat. However, fragmentation of habitat due to anthropogenic activity may hinder migration further inland, while shifting to neighbouring islands is not viable due to the water barrier between islands ( ''high confidence'' ) ( [[#Bellard--2013b|Bellard et al., 2013b]] ; [[#Wetzel--2013|Wetzel et al., 2013]] ; [[#Kumar--2017|Kumar and Tehrany, 2017]] ). Additionally, migratory birds, which use small islands (e.g., atolls) for stopovers or breeding/nesting sites, are projected to become impacted. Within the Mediterranean and Caribbean, significant losses to coastal wetlands—critical habitat for migratory birds—has already been observed, with further significant habitat losses, redistribution and changes in quality being projected across island systems such as the Bahamas (Caribbean) and Sardinia (Mediterranean) ( [[#Vogiatzakis--2016|Vogiatzakis et al., 2016]] ; [[#Wolcott--2018|Wolcott et al., 2018]] ).

Indirect impacts of SLR may potentially result in equal or more biodiversity loss than direct impacts ( ''medium confidence'' ). Relocation of displaced coastal human populations and associated intensive agriculture and urban areas inland to natural habitat may result in greater biodiversity loss than direct impacts—especially on islands with large coastal populations and urban centres ( [[#Wetzel--2012|Wetzel et al., 2012]] ; [[#Bellard--2013b|Bellard et al., 2013b]] ). Given the dense population of insular hotspots (~31.8% of existing humans within ~15.9% of inhabited global land area) and the fact that on many islands, large proportions of human populations live within coastal regions, it has been suggested that immense impacts from such relocations should be factored into projection and adaptation studies ( [[#Wetzel--2012|Wetzel et al., 2012]] ).

Tropical island natural habitats/systems are highly vulnerable to extreme weather events such as TCs, due to their small size, unique ecological systems and often low socioeconomic capacity ( ''high confidence'' ) (Box 15.2; [[#Goulding--2016|Goulding et al., 2016]] ; [[#Schütte--2018|Schütte et al., 2018]] ). Growing evidence suggests high resilience of forest habitats ( [[#Keppel--2014|Keppel et al., 2014]] ; [[#Luke--2017|Luke et al., 2017]] ), especially within intact forest ecosystems to hurricanes and cyclones ( [[#Goulding--2016|Goulding et al., 2016]] ). While initial damage can be high, relatively fast recovery rates have been reported for both floral and faunal components of these ecosystems ( [[#Cantrell--2014|Cantrell et al., 2014]] ; [[#Shiels--2014|Shiels et al., 2014]] ; [[#Monoy--2016|Monoy et al., 2016]] ; [[#Richardson--2018|Richardson et al., 2018]] ). Within the Caribbean in particular, high resilience of forest types has been associated with the ''current'' intensity and return rate of hurricanes over the past 150 years.

It should, however, be underscored that these relatively fast recovery rates are associated with the ''present'' intensity and return rate of TCs. They do not reflect the impacts of increasingly intense events such as Hurricane Dorian (2019), which resulted in almost complete inundation of several low-lying islands of the Bahamas from storm surges. Severe weather events also have indirect effects on the biodiversity of islands—interacting synergistically with other stressors, such as increased invasion by non-native species and land use change. For example, TCs within Papua New Guinea resulted in the destruction of subsistence gardens, which led inhabitants to clear forest areas for new farming areas and for harvesting of timber resources to rebuild ( [[#Goulding--2016|Goulding et al., 2016]] ).

The most recent projections suggest that TC intensity is predicted to increase as climate continues to change ( [[#Walsh--2016|Walsh et al., 2016]] ; [[#Kossin--2017|Kossin et al., 2017]] ). There are too few studies available to suggest potential future response trends of these ecosystems to this increased intensity; however, it seems plausible that present resilience capacities may be adversely impacted ( ''medium confidence'' ) ( [[#Marler--2014|Marler, 2014]] ). Further, the potential for stressors such as forest fragmentation/degradation or IAS combining with these increasingly intense events to cause precipitating ecosystem cascades is a real concern ( [[#Goulding--2016|Goulding et al., 2016]] ).

Continued high rates of habitat loss and degradation have been reported for many small islands as natural habitats continue to be cleared to meet increasing demands upon natural resources from rising human populations, agriculture, urbanisation, unsustainable tourism, overgrazing and fires. This increases the vulnerability of ecosystems within especially oceanic islands—where isolation has given rise to high levels of endemism but simple biotic communities, with low functional redundancy (Box [https://www.ipcc.ch/chapter/15#CCP1.1 CCP1.1] ). There is ''high confidence'' that climate change may exacerbate the effects of this habitat loss upon the biodiversity of these islands as the climate refugia (Table 15.3) and the upslope shifts of range-restricted, dispersal-limited and poorly competitive species, confined within narrow latitudinal (and decreasing altitudinal) gradients, are increasingly challenged by fragmented and degraded landscapes (e.g., [[#Struebig--2015a|Struebig et al., 2015a]] ; [[#IPBES--2019|IPBES, 2019]] ). Additionally, high-altitude ecosystems such as cloud forests which harbour high levels of endemism are projected to shrink due to increasing atmospheric temperature and competition from upward-shifting lowland species ( [[#Taylor--2016a|Taylor and Kumar, 2016a]] ). These may ultimately increase the risk of multiple extinctions, negatively impacting upon global biodiversity levels ( ''high confidence'' ) ( [[#Taylor--2016a|Taylor and Kumar, 2016a]] ; [[#Portner--2021|Portner et al., 2021]] ).

Analyses of historical and current threats indicate that IAS and disease have been the primary drivers of insular extinctions in modern history ( [[#Bellard--2016|Bellard et al., 2016]] ). Impacts of IAS on islands are projected to increase with time due to synergies between climate change and other traditional drivers such as increasing global trade, tourism, agricultural intensification, overexploitation and urbanisation ( [[#Bellard--2014|Bellard et al., 2014]] ; [[#Russell--2017|Russell et al., 2017]] ). Changing climate conditions may not necessarily increase the rate of IAS introductions but is expected to improve chances of IAS establishment via (a) altering IAS transport and introduction mechanisms, (b) increasing the impacts and distributions of existing IAS and (ci) altering the effectiveness of existing control strategies ( [[#Hellmann--2008|Hellmann et al., 2008]] ; [[#Russell--2017|Russell et al., 2017]] ). These are likely to enhance IAS impacts on islands including: restructuring of ecological communities leading to declines and extinctions/extirpations in flora and fauna, habitat degradation, declining ecosystem functioning, services and resilience and, in extreme cases, potential community homogenisation ( ''high confidence'' ) ( [[#Russell--2017|Russell and Blackburn, 2017]] ; [[#IPBES--2019|IPBES, 2019]] ). Given the high degree of endemicity within oceanic islands and their associated vulnerabilities, such exacerbation by changing climate poses a serious threat to decreasing global biodiversity ( ''medium'' to ''high confidence'' ) ( [[#van%20Kleunen--2015|van Kleunen et al., 2015]] ).

Compared to continents, terrestrial IAS are disproportionately prevalent on islands (almost three quarters of global species currently threatened by IAS and disease are found on islands) and also generate stronger impacts (e.g., within alpine ecosystems of high islands) than on continents ( ''high confidence)'' ( [[#Bellard--2014|Bellard et al., 2014]] ; [[#Bellard--2016|Bellard et al., 2016]] ; [[#Frazier--2019|Frazier and Brewington, 2019]] ). [[#Russell--2017|Russell and Blackburn (2017)]] suggested a correlation between small island size and increased numbers of IAS. SIDS within the Indian Ocean and in particular the Pacific SIDS region were reported to have significantly more IAS ( ''medium confidence'' ), while the Caribbean and Atlantic SIDS have fewer numbers but faster accumulation of IAS. Finally, while there have been developments in the eradication of IAS on islands ( [[#Jones--2016|Jones et al., 2016]] ), there is sparse evidence and hence assessment of the degree to which measures designed to prevent introduction and to manage invasion pathways and establishment have been successful.

<div id="15.3.4" class="h2-container"></div>

<span id="observed-impacts-and-projected-risks-on-human-systems"></span>
=== 15.3.4 Observed Impacts and Projected Risks on Human Systems ===

<div id="h2-6-siblings" class="h2-siblings"></div>

<div id="15.3.4.1" class="h3-container"></div>

<span id="island-settlements-and-infrastructure"></span>
==== 15.3.4.1 Island Settlements and Infrastructure ====

<div id="h3-4-siblings" class="h3-siblings"></div>

As a result of slow-onset ocean and climate changes and changes in extreme events, settlements and infrastructure of small islands are at growing risk due to climate change in the absence of adaptation measures ( ''high confidence'' ). Ocean acidification and deoxygenation, increased ocean temperatures and relative SLR are impacting marine, coastal and terrestrial biodiversity and ecosystem services, making settlements more exposed and vulnerable to climate-related hazards. Changes in rainfall patterns such as heavy precipitation result in annual flood events that damage major assets and result in a loss of human life. Examples of settlements where this has occurred are Port of Spain ( [[#Mycoo--2014b|Mycoo, 2014b]] ; 2018a), Haiti ( [[#Weissenberger--2018|Weissenberger, 2018]] ), Viti Levu ( [[#Brown--2017|Brown et al., 2017]] ; [[#Singh-Peterson--2018|Singh-Peterson and Iranacolaivalu, 2018]] ), urban areas of Fiji and Kiribati ( [[#McAneney--2017|McAneney et al., 2017]] ; [[#Cauchi--2021|Cauchi et al., 2021]] ), Male’, Maldives ( [[#Wadey--2017|Wadey et al., 2017]] ), and Mahé, in the Seychelles ( [[#Etongo--2019|Etongo, 2019]] ).

The main settlements of small islands are located along the coast and with decades of high-density coastal urban development, their population, buildings and infrastructure are currently exposed to multiple climate change-related hazards ( [[#Kumar--2015|Kumar and Taylor, 2015]] ; [[#Mycoo--2017|Mycoo, 2017]] ) and face key risks ( ''high confidence'' ) (KR5 in Figure 15.5). In many small islands, population is concentrated in the low-elevation coastal zone (LECZ), which is defined as coastal areas below 10-m elevation. Approximately 22 million in the Caribbean live below 6-m elevation ( [[#Cashman--2017|Cashman and Nagdee, 2017]] ) and an estimated 90% of Pacific Islanders live within 5 km of the coast, if Papua New Guinea is excluded ( [[#Andrew--2019|Andrew et al., 2019]] ). In the Solomon Islands and Vanuatu, over 60% of the population lives within 1 km of the coast ( [[#Andrew--2019|Andrew et al., 2019]] ). Most Pacific islands have ≥50% of their infrastructure within 500 m of the coast ( [[#Kumar--2015|Kumar and Taylor, 2015]] ), and in Kiribati, Marshall Islands and Tuvalu, &gt;95% of the infrastructure is located in the LECZ ( [[#Andrew--2019|Andrew et al., 2019]] ) (Figure 15.3). Sustainable development challenges including insufficient land use planning and land use competition contribute to increased vulnerability of human settlements to climate change in small islands ( [[#Kelman--2014|Kelman, 2014]] ; Mycoo, 2021).

Categories 4 and 5 TCs are severely impacting settlements and infrastructure in small islands. TC Maria in 2017 destroyed nearly all of Dominica’s infrastructure and losses per unit of GDP amounted to more than 225% of the annual GDP ( [[#Eckstein--2018|Eckstein et al., 2018]] ). Destruction from TC Winston in 2016 amounted to more than 20% of Fiji’s current GDP ( [[#Cox--2018|Cox et al., 2018]] ). Additionally, living conditions in human settlements are changing due to storm surge which is already penetrating further inland compared with a few decades ago ( [[#IPCC--2018|IPCC, 2018]] , [[IPCC:Wg2:Chapter:Chapter-3#3.4.4|Section 3.4.4.3]] ; [[#Brown--2018|Brown et al., 2018]] ).

A growing percentage of the population in small islands lives in informal settlements which occupy marginal lands leading to increased population exposure and vulnerability to climate-related hazards ( [[#Mycoo--2017|Mycoo and Donovan, 2017]] ). Unplanned settlements have compounded flooding brought on by slow-onset hazards such as coastal and riverine flooding and fast-onset events such as TCs and storm surges ( [[#Butcher-Gollach--2015|Butcher-Gollach, 2015]] ; [[#Chandra--2016|Chandra and Gaganis, 2016]] ; [[#Mycoo--2017|Mycoo, 2017]] ). Unsustainable land use practices and difficulties in enforcing land use zoning and building guidelines in informal settlements make them highly vulnerable to such events ( [[#Butcher-Gollach--2015|Butcher-Gollach, 2015]] ; [[#Mecartney--2017|Mecartney and Connell, 2017]] ; [[#Mycoo--2017|Mycoo, 2017]] ; 2018b; 2021; [[#Trundle--2018|Trundle et al., 2018]] ).

TC intensification in the future is ''likely'' to cause severe damage to human settlements and infrastructure in small islands. Additionally, SLR is expected to cause significant losses and damages ( [[#Martyr-Koller--2021|Martyr-Koller et al., 2021]] ). Based on SLR projections, almost all port and harbour facilities in the Caribbean will suffer inundation in the future ( [[#Cashman--2017|Cashman and Nagdee, 2017]] ). In Jamaica and St. Lucia, SLR and ESLs are projected to be key risks to transport infrastructure at 1.5°C unless further adaptation is undertaken ( [[#Monioudi--2018|Monioudi et al., 2018]] ). Similar findings were reported for Samoa ( [[#Fakhruddin--2015|Fakhruddin et al., 2015]] ). Even islands of higher elevation are expected to be threatened, given the high amount of infrastructure located near the coast, for example, Fiji ( [[#Kumar--2015|Kumar and Taylor, 2015]] ).

<div id="15.3.4.2" class="h3-container"></div>

<span id="human-health-and-well-being"></span>
==== 15.3.4.2 Human Health and Well-Being ====

<div id="h3-5-siblings" class="h3-siblings"></div>

Small islands face disproportionate health risks associated with changes in temperature and precipitation, climate variability, and extremes (Cross-Chapter Box INTERREG in Chapter 16; KR4 in [[#15.3|Section 15.3.9]] , Figure 15.5). Climate change is projected to increase the current burden of climate-related health risks ( [[#Weatherdon--2016|Weatherdon et al., 2016]] ; [[#Ebi--2018|Ebi et al., 2018]] ; [[#Schnitter--2019|Schnitter et al., 2019]] ). Health risks can arise from exposures to extreme weather and climate events, including heatwaves; changes in ecological systems associated with changing weather patterns that can result, for example, in more disease vectors, or in compromised safety and security of water and food; and exposures related to disruption of health systems, migration, and other factors (see Cross-Chapter Box ILLNESS in Chapter 2; [[#McIver--2016|McIver et al., 2016]] ; [[#Mycoo--2018a|Mycoo, 2018a]] ; [[#WHO--2018|WHO, 2018]] ).

Extreme weather and climate events, particularly TCs, floods, drought, and heatwaves can cause injuries, infectious diseases, and deaths (Box 15.1; [[#Schütte--2018|Schütte et al., 2018]] ). For example, Category 5 TC Winston hit Fiji on 20 February 2016. During the national state of emergency (7 March and 29 May 2016), the World Health Organization portable toolkit for an early warning alert and response system (EWARS in a Box) was deployed within 24 h; it recorded 34,113 cases of the nine syndromes among 326,861 consultations in a population of about 900,000; 48% of cases were influenza-like illnesses, 30% were acute watery diarrhoea, and 13% were suspected cases of dengue. There also were 583 cases of Zika-like illness (1.7% of all cases) and two large outbreaks of viral conjunctivitis (total of 880 cases). During TC Maria in Puerto Rico, there were more deaths per 100,000 among individuals living in municipalities with the lowest socioeconomic development and for men 65 years of age or older ( [[#Santos-Burgoa--2018|Santos-Burgoa et al., 2018]] ); this excess risk persisted for at least 1 year after the event. The first human cases of leptospirosis in the U.S. Virgin Islands occurred in 2017 after TC Irma and Maria. TCs also can affect treatment and care for people with non-communicable diseases, including exacerbation or complications of illness and premature death ( [[#Ryan--2015|Ryan et al., 2015]] ).

Heat-related mortality and risks of occupational heat stress in small island states are projected to increase with higher temperatures ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ; [[#Mendez-Lazaro--2018|Mendez-Lazaro et al., 2018]] ). Higher temperatures can also affect the productivity of outdoor workers ( [[#Taylor--2021|Taylor et al., 2021]] ). Climate change, urbanisation, and air pollution are risk factors for the rise of allergic diseases in Asia Pacific ( [[#Pawankar--2020|Pawankar et al., 2020]] ).

Tropical and subtropical islands face risks from vector-borne diseases, such as malaria, dengue fever, and the Zika virus. El Niño events can increase the risk of diseases such as Zika virus by increasing biting rates, decreasing mosquito mortality rates and shortening the time required for the virus to replicate within the mosquito ( [[#Caminade--2017|Caminade et al., 2017]] ). By combining disease prediction models with climate indicators that are routinely monitored, alongside evaluation tools, it is possible to generate probabilistic dengue outlooks in the Caribbean and early warning systems ( [[#Oritz--2015|Oritz et al., 2015]] ; [[#Lowe--2018|Lowe et al., 2018]] ). Projections suggest that more individuals will become at risk of dengue fever by the 2030s and beyond because of an increasing abundance of mosquitos and larger geographic range ( [[#Ebi--2018|Ebi et al., 2018]] ). Projected increases in mean temperature could double the dengue burden in New Caledonia by 2100 ( [[#Teurlai--2015|Teurlai et al., 2015]] ). In the Caribbean, Saharan dust transported across the Atlantic can interact with Caribbean seasonal climatic conditions to become respirable and contribute to asthma presentations at the emergency department (See Table 15.5; [[#Akpinar-Elci--2015|Akpinar-Elci et al., 2015]] ).

Ciguatera fish poisoning (CFP) is a foodborne illness caused by toxic dinoflagellate algae that proliferate on degraded coral reefs and that can contaminate reef fish; symptoms can remain for a few weeks to months. CFP occurs in tropical and subtropical regions, primarily in the South Pacific and Caribbean, but wherever reef fish are consumed ( [[#Traylor--2020|Traylor and Singhal, 2020]] ). In the Caribbean Sea, increasing ocean temperatures are expected to stabilise or slightly decrease the incidence of CFP because of shifts in species distribution of dinoflagellates associated with CFP ( [[#Kibler--2015|Kibler et al., 2015]] ). CFP is endemic in the Cook Islands and French Polynesia, where incidence is associated with SST anomalies ( [[#Zheng--2020|Zheng et al., 2020]] ). In the Canary Islands, tropicalisation trends due to climate change are expected to increase CFP occurrence in the future ( [[#Rodriguez--2017|Rodriguez et al., 2017]] ). In addition, in the Caribbean, increased density of ''Sargassum'' algae, possibly due to ocean temperature impacts on ocean currents compounded by agricultural pollution, may lead to increased respiratory illnesses ( [[#Resiere--2018|Resiere et al., 2018]] ; 2019; 2020).

Climate-driven changes in the ability to access locally grown or harvested food, either through environmental degradation or changes in extreme event magnitude and/or frequency, can increase dependence on imported food and increase rates of malnutrition and non-communicable diseases ( [[#Springmann--2016|Springmann et al., 2016]] ; [[#WHO--2018|WHO, 2018]] ; [[#Savage--2019|Savage et al., 2019]] ; [[#Lieber--2020|Lieber et al., 2020]] ). Projections suggest that local food accessibility could be reduced by 3.2% in the low- and middle-income countries of the Western Pacific (including the Philippines, Fiji, Papua New Guinea, Solomon Islands, and other Pacific islands) by 2050, with approximately 300,000 associated deaths possible ( [[#Springmann--2016|Springmann et al., 2016]] ). A climate change-related 20% decline in coral reef fish production in some Pacific Island countries by 2050 could exacerbate the population growth-driven gap between volume of fish needed for nutritional security and fish available through sustained harvest ( [[#Bell--2013|Bell et al., 2013]] ; [[#Cauchi--2019|Cauchi et al., 2019]] ; [[#Savage--2019|Savage et al., 2019]] )).

Heavy reliance on aquifers and rainwater harvesting in small islands, particularly atolls, coupled with overcrowding, population growth and contamination increase the risk of waterborne disease ( [[#McIver--2014|McIver et al., 2014]] ; 2016; [[#Strauch--2014|Strauch et al., 2014]] ). For example, seasonal rainfall in Kiribati is associated with waterborne disease (such as diarrhoea, cholera, and typhoid fever). Future projections indicate increases in the number of days of heavy rainfall by 2050, suggesting future increases in risk in heavily populated areas ( [[#McIver--2014|McIver et al., 2014]] ). Damage to water and sanitation services can cause infectious disease outbreaks, such as the cholera outbreak that occurred in Haiti following TC Matthew ( [[#Raila--2017|Raila and Anderson, 2017]] ; [[#Hulland--2019|Hulland et al., 2019]] ).

Evidence is emerging of the mental health impacts of climate change (limited evidence). Tuvaluans are experiencing distress because of the local environmental impacts caused or exacerbated by climate change, and by hearing about the potential future consequences of climate change ( [[#Gibson--2020|Gibson et al., 2020]] ).

<div id="15.3.4.3" class="h3-container"></div>

<span id="water-security"></span>
==== 15.3.4.3 Water Security ====

<div id="h3-6-siblings" class="h3-siblings"></div>

Climate change impacts on freshwater systems frequently exacerbate existing pressure, especially in locations already experiencing water scarcity ( [[#15.3.3.2|Section 15.3.3.2]] and Cross-Chapter Box INTERREG in Chapter 16; [[#Schewe--2014|Schewe et al., 2014]] ; [[#Holding--2016|Holding et al., 2016]] ; [[#Karnauskas--2016|Karnauskas et al., 2016]] ), making water security a key risk (KR4 in Figure 15.5) in small islands. Small islands are usually environments where demand for resources related to socioeconomic factors such as population growth, urbanisation and tourism already place increasing pressure on limited freshwater resources. In many small islands, water demand already exceeds supply. For example, in the Caribbean, Barbados is utilising close to 100% of its available water resources and St. Lucia has a water supply deficit of approximately 35% ( [[#Cashman--2014|Cashman, 2014]] ). On many Mediterranean islands, water demand regularly outstrips supply as a result of low average precipitation coupled with increasing water demand from economic activities such as irrigated agriculture and tourism ( [[#Hof--2014|Hof et al., 2014]] ; [[#Papadimitriou--2019|Papadimitriou et al., 2019]] ).

Population growth plays a major role in projected future water stress ( [[#Schewe--2014|Schewe et al., 2014]] ). Combining projected aridity change (fractional change compared to historical climatology) with population projections derived from SSP2 shows that the SIDS with high projected population growth rates are expected to experience the most severe freshwater stress by 2030 under a 2°C warming threshold scenario ( [[#Karnauskas--2018|Karnauskas et al., 2018]] ). For several SIDS (e.g., Belize and Jamaica), increasing aridity change is a prominent exacerbating factor, but for others (e.g., the Solomon Islands and Comoros) population growth is the main factor. An increase in temperature of 1°C (from 1.7°C to 2.7°C) could result in a 60% increase in the number of people projected to experience severe water resources stress in the period 2043–2071 ( [[#Schewe--2014|Schewe et al., 2014]] ; [[#Karnauskas--2018|Karnauskas et al., 2018]] ). Research on Jamaica concluded that the ability of rainwater harvesting to meet potable water needs between the 2030s and 2050s will be reduced based on predicted shorter intense showers and frequent dry spells ( [[#Aladenola--2016|Aladenola et al., 2016]] ).

The Caribbean and Pacific regions have historically been affected by severe droughts ( [[#Peters--2015|Peters, 2015]] ; [[#FAO--2016|FAO, 2016]] ; [[#Barkey--2017|Barkey and Bailey, 2017]] ; [[#Paeniu--2017|Paeniu et al., 2017]] ; [[#Trotman--2017|Trotman et al., 2017]] ; [[#Anshuka--2018|Anshuka et al., 2018]] ) with significant physical impacts and negative socioeconomic outcomes. Water quality is affected by drought as well as water availability. The El Niño related 2015–1016 drought in Vanuatu led to reliance on small amounts of contaminated water left at the bottom of household tanks ( [[#Iese--2021a|Iese et al., 2021a]] ). The highest land disturbance percentages have coincided with major droughts in Cuba ( [[#de%20Beurs--2019|de Beurs et al., 2019]] ). Drought has been shown to have an impact on rainwater harvesting in the Pacific ( [[#Quigley--2016|Quigley et al., 2016]] ) and Caribbean ( [[#Aladenola--2016|Aladenola et al., 2016]] ), especially in rural areas where connections to centralised public water supply have been difficult. Increasing trends in drought are apparent in the Caribbean ( [[#Herrera--2017|Herrera and Ault, 2017]] ) although trends in the western Pacific are not statistically significant ( [[#McGree--2016|McGree et al., 2016]] ).

Areas where a freshwater lens is thinner are most likely to be impacted by multiple climate stressors, and these areas tend to be in coastal zones where populations are likely to be most concentrated ( [[#Holding--2016|Holding et al., 2016]] ). In Barbados, where groundwater is relied upon for food production, urban use and environmental needs, higher food prices are expected in the future if informed land use management and integrated water resources policies are not implemented to manage groundwater in the short term, even with modest climate change threats ( [[#Gohar--2019|Gohar et al., 2019]] ).

<div id="15.3.4.4" class="h3-container"></div>

<span id="fisheries-and-agriculture"></span>
==== 15.3.4.4 Fisheries and Agriculture ====

<div id="h3-7-siblings" class="h3-siblings"></div>

Fisheries provide small islands with opportunities for economic development, revenues, food security and livelihoods ( [[#Bell--2018|Bell et al., 2018]] ). Ten Pacific Island countries and territories derive between 5% and &gt;90% of all government revenue (except grants) from access fees paid by industrial tuna-fishing fleets, mainly from distant-water fishing nations ( [[#Bell--2018|Bell et al., 2018]] ; [[#SPC--2019|SPC, 2019]] ). Under a high greenhouse gas emissions scenario (RCP8.5), the total biomass of three tuna species in the waters of 10 Pacific SIDS could decline by an average of 13% (range = −5–−20%) due to a greater proportion of fish occurring in the high seas ( [[#Bell--2021|Bell et al., 2021]] ), while projected increases have been anticipated for Ascension Island and Saint Helena in the South Atlantic ( [[#Townhill--2021|Townhill et al., 2021]] ). Additionally, seafood plays an important role in achieving food security in many islands. In the Pacific, fish protein is estimated to make up 50–90% of animal protein consumption in rural areas and 40–80% in urban areas ( [[#Bell--2009|Bell et al., 2009]] ; [[#Hanich--2018|Hanich et al., 2018]] ) with similar values reported for some Indian Ocean and Caribbean islands (e.g., Maldives, Antigua and Barbuda). It has been suggested that island nations may need to retain more of their tuna catch rather than to rely solely on coastal fisheries to achieve food security in the future (Cross-Chapter Box MOVING PLATE in Chapter 5; [[#Bell--2015|Bell et al., 2015]] ; [[#Bell--2018|Bell et al., 2018]] ). Furthermore, small island fisheries can be severely impacted by extreme events such as TCs, yet rapidly recovering pelagic fisheries can help to alleviate immediate food insecurity pressures in some circumstances, helping to build resilience ( [[#Pinnegar--2019|Pinnegar et al., 2019]] ).

Observed impacts of climate change on fish and fisheries in small islands include declines in reef-associated species due to coral bleaching or cyclone damage ( [[#Robinson--2019|Robinson et al., 2019]] ; [[#Magel--2020|Magel et al., 2020]] ), oceanic-scale shifts in the distribution of large pelagic fish and hence their fisheries ( [[#Erauskin-Extramiana--2019|Erauskin-Extramiana et al., 2019]] ), changes to the size structure or breeding behaviour of species (e.g., ( [[#Asch--2018|Asch et al., 2018]] ) (Sections 3.3.3.2 and 3.4.3.1)). Many studies of future fishery productivity in a changing climate suggest that yields will fall as a result of ocean productivity reductions, local species extinction and/or migration ( [[#Nurse--2011|Nurse, 2011]] ; [[#Asch--2018|Asch et al., 2018]] ; [[#Robinson--2019|Robinson et al., 2019]] ). Asch et al. (2018) provided future projections for biodiversity and the maximum catch potential of fisheries in Pacific Island countries and territories. These authors concluded that nine of 17 Pacific Island entities (Cook Islands, Federated States of Micronesia, Guam, Kiribati, Marshall Islands, Niue, Papua New Guinea, Solomon Islands, and Tuvalu) could experience ≥50% declines in maximum catch potential by 2100 relative to 1980–2000 under both an RCP2.6 and RCP8.5 scenario ( ''medium confidence'' ). In Wallis and Futuna, maximum catch potential was projected to increase slightly (around 10%) by 2050, later declining by the year 2100. Similar projections have now been provided for all countries worldwide, including Pacific, Caribbean, Atlantic, Mediterranean and Indian Ocean small islands ( [[#Cheung--2018|Cheung et al., 2018]] ). The small islands that show the largest anticipated decrease in the maximum catch potential of fisheries by the end of the century (according to an RCP4.5 and RCP8.5 scenario) include the Federated States of Micronesia, Kiribati, Nauru, Palau, Tokelau, Tuvalu, São Tomé and Príncipe, whereas some other small islands such as Bermuda, Easter Island (Chile), and Pitcairn Islands (UK), might actually witness increases in fish catch potential ( ''medium confidence'' ) ( [[#Cheung--2018|Cheung et al., 2018]] ). [[#Monnereau--2017|Monnereau et al. (2017)]] showed that for the fisheries sector, small island states are generally more vulnerable to climate change impacts compared to continental least-developed countries or coastal states because of their increased reliance on fisheries, the exposure of coastal communities to potential climatic threats and their limited adaptive capacity.

Projected impacts of climate change on agriculture and fisheries pose serious threats to dependent human populations ( [[#Ren--2018|Ren et al., 2018]] ; [[#Hoegh-Guldberg--2019|Hoegh-Guldberg et al., 2019]] ), making the risk caused to livelihoods a key risk in small islands (KR7 in Figure 15.5). On small islands, despite biophysical commonalities (e.g., size and isolation), differences in economic status and level of dependence on agriculture and fisheries produce dynamic climate impacts ( [[#Balzan--2018|Balzan et al., 2018]] ). Climate change is impacting agricultural production in small islands through slow-onset stressors such as rising average temperatures, shifting rainfall patterns, SLR and extreme events like TCs. For example, TC Pam, a Category 5 cyclone, devastated Vanuatu in 2015 and caused losses and damages to the agriculture sector valued at USD 56.5 million (64.1% of GDP) ( [[#Nalau--2017|Nalau et al., 2017]] ), and TC Winston in 2016 resulted in losses and damages in the agriculture sector in Fiji valued at USD 254.7 million ( [[#Iese--2020|Iese et al., 2020]] ). In 2017, total losses and damages associated with hurricane Maria (Category 5) amounted to 224% of Dominica’s 2016 GDP ( [[#Barclay--2019|Barclay et al., 2019]] ). Losses and damages in agriculture often led to people eating imported processed foods affecting their diet and nutrition ( [[#Haynes--2020|Haynes et al., 2020]] ). Small islands communities are also witnessing the indirect effects of the COVID-19 pandemic on agricultural systems ( [[#Hickey--2020|Hickey and Unwin, 2020]] ). However, the limited diversity of agriculture production and reduced household incomes are contributing to low diet diversity (Iese et al., 2021b). [[#Bell--2015|Bell and Taylor (2015)]] assessed the effects of climate change on specific sectors of agriculture in the Pacific islands region and found that, by 2090, staple food crops of taro, sweet potato and rice are expected to suffer from moderate to high impact. Among export crops, coffee is expected to sustain the most significant impact due largely to increased temperatures in the highland areas of Papua New Guinea—a high production area ( [[#Bell--2016|Bell et al., 2016]] ). Livestock is an important protein source in some small islands and is particularly vulnerable to changes in temperature through heat stress ( [[#Bell--2015|Bell and Taylor, 2015]] ; [[#Lallo--2018|Lallo et al., 2018]] ). With the concentration of island people along (often reef-fringed) coasts, there is a comparatively large dependence on nearshore marine foods and coastal agricultural systems ( [[#Ticktin--2018|Ticktin et al., 2018]] ).

In the Caribbean, additional warming by 0.2°–1.0°C could lead to a predominantly drier region (5–15% less rain than present-day), a greater occurrence of droughts ( [[#Taylor--2018|Taylor et al., 2018]] ) along with associated impacts on agricultural production and yield in the region ( [[#Gamble--2017|Gamble et al., 2017]] ; [[#Hoegh-Guldberg--2019|Hoegh-Guldberg et al., 2019]] ; [[#Nicolas--2020|Nicolas et al., 2020]] ). Crop suitability modelling on several commercially important crops grown in Jamaica found that even an increase of less than 1.5°C could result in a reduction in the range of crops that farmers may grow ( [[#Rhiney--2018|Rhiney et al., 2018]] ).

Sugar yield in Fiji could decline by 2–14% under projected scenarios ( [[#McGree--2020|McGree et al., 2020]] ). Farmers in some small islands have utilised Indigenous knowledge systems built on local ontology to sharpen their sensitivity to environmental conditions ( [[#Shah--2018|Shah et al., 2018]] ). However, projected climate change across the Pacific could undermine climate-sensitive agricultural livelihoods and exacerbate food insecurity challenges ( [[#McCubbin--2017|McCubbin et al., 2017]] ; [[#Campbell--2021|Campbell et al., 2021]] ).

Projected climate impacts on island agroecosystem services could accentuate a myriad of social and ecological risks ( [[#Campbell--2021|Campbell, 2021]] ). Without proactive farm management practices, the projected impacts of climate change on drought patterns is a major threat to cocoa pollination services ( [[#Arnold--2018|Arnold et al., 2018]] ). Many tropical island agroforestry crops are completely dependent on insect pollination and it is therefore important to understand the climatic drivers of changing conditions related to pollinator abundance. Coastal agroforestry systems in small Pacific islands are vital to national food security but native biodiversity is rapidly declining ( [[#Ticktin--2018|Ticktin et al., 2018]] ). Biodiversity loss from traditional agroecosystems is a major threat to food and livelihoods security in SIDS ( [[#UNEP--2014a|UNEP, 2014a]] ). Additionally, while coastal-lowland salinisation and more frequent flooding attributable to SLR have impacted coastal agriculture on some islands ( [[#Cruz--2017|Cruz and Andrade, 2017]] ; [[#Wairiu--2017|Wairiu, 2017]] ), stronger TCs can sometimes shock island terrestrial food production warranting reconfiguration ( [[#Mertz--2010|Mertz et al., 2010]] ; [[#Duvat--2016|Duvat et al., 2016]] ; [[#Chakrabarti--2017|Chakrabarti et al., 2017]] ). Calls to conserve associated environments and to make terrestrial food production on islands more resilient to climate-driven shocks underscore concern about future food security ( [[#Connell--2013|Connell, 2013]] ; [[#de%20Scally--2014|de Scally, 2014]] ). Implicit in the latter is reversing the decades-long loss of Indigenous knowledge about food production in many island societies and incorporating it into future strategies ( [[#Mercer--2014b|Mercer et al., 2014b]] ; [[#Janif--2016|Janif et al., 2016]] ).

<div id="15.3.4.5" class="h3-container"></div>

<span id="economies"></span>
==== 15.3.4.5 Economies ====

<div id="h3-8-siblings" class="h3-siblings"></div>

Small island economies vary greatly in their nature, history/trends and viability under a changed climate. As elsewhere, few small island economies are overseen by governments that are adequately prepared for the economic impacts of climate change over the next few decades ( [[#Connell--2013|Connell, 2013]] ; [[#Hay--2013|Hay, 2013]] ). In particular, the lack of diversity that characterises most small island economies means they are especially vulnerable to global (climate-driven) shocks (Cross-Chapter Box DEEP in Chapter 17), be these the impacts of extreme events or more gradual longer-term change, which makes the maintenance of traditional mechanisms for coping with such shocks in many island societies all the more important ( [[#Granderson--2017|Granderson, 2017]] ; [[#Wilson--2018|Wilson and Forsyth, 2018]] ; [[#Nunn--2019b|Nunn and Kumar, 2019b]] ). As a result, the risk from climate change to economies constitutes a key risk (KR7 in Figure 15.5) in small islands.

Many island environments have been commercially exploited by external interests for much of their recent history. This is especially common for timber, the wholesale removal of forests, especially on tropical islands, exposing land to heavy rain that leads to denudation and increases lowland sedimentation ( [[#Wairiu--2017|Wairiu, 2017]] ; [[#Eppinga--2018|Eppinga and Pucko, 2018]] ). Negative aspects of both processes will be exacerbated by climate change, demonstrating the practical need for reforestation in many island contexts ( [[#Thomson--2016|Thomson et al., 2016]] ). Some small island economies are sustained by extractive industries such as mining, creating dependencies that lead to their environmental impacts being downplayed ( [[#Tserkezis--2016|Tserkezis and Tsakanikas, 2016]] ; [[#Shepherd--2018|Shepherd et al., 2018]] ). It is important to address these impacts as they will add to negative impacts of climate change ( [[#Clifford--2019|Clifford et al., 2019]] ).

Many small island economies are sustained by tourism and have invested heavily in associated infrastructure and capacity building ( [[#Cannonier--2018|Cannonier and Burke, 2018]] ). Some rural island communities have become dependent on tourism to the point that it would be difficult to revert to subsistence living ( [[#Lasso--2018|Lasso and Dahles, 2018]] ). Coast-focused (beach-sea) tourism in island contexts is already being impacted by beach erosion, elevated high SST causing coral bleaching, and associated marine-biodiversity loss, as well as more intense TCs ( [[#Tapsuwan--2015|Tapsuwan and Rongrongmuang, 2015]] ; [[#Parsons--2018|Parsons et al., 2018]] ; [[#Wabnitz--2018|Wabnitz et al., 2018]] ). The COVID-19 pandemic travel disruption significantly affected the tourism sector of Caribbean islands by reducing incomes that would have been used to enhance climate resilience ( [[#Sheller--2020|Sheller, 2020]] ). Many tourism interests downplay the impacts and future risks from climate change ( [[#Shakeela--2015|Shakeela and Becken, 2015]] ), a position that may be borne out by sustained/rising demand for small island vacationing in some locales ( [[#Katircioglu--2019|Katircioglu et al., 2019]] ). A way forward is for island tourism to emphasize its low-carbon and sustainable attributes, and to encourage smaller-scale eco-friendly holiday opportunities ( [[#Lee--2018|Lee et al., 2018]] ), in other words for island nations to embrace a ‘blue economy’ in line with SDG14 to conserve and utilise their oceans for sustainable futures ( [[#Hampton--2020|Hampton and Jeyacheya, 2020]] ; [[#Hassanali--2020|Hassanali, 2020]] ).

Given the high cost of imported goods, especially foodstuffs, larger island jurisdictions are striving to transform their economies to favour locally produced or locally constituted materials that employ local people and reduce their cost of living. The exposure of this component of island economies varies, yet manufacturing/commercial operations are usually found in the lowest-lying areas, often on reclaimed lands. This makes them especially vulnerable to rising sea level, part of a larger issue around the disproportionate exposure of infrastructure on small islands to climate change ( [[#Fakhruddin--2015|Fakhruddin et al., 2015]] ; [[#Kumar--2015|Kumar and Taylor, 2015]] ).

It is challenging to disentangle the role of climate change from that of globalisation and development in recent changes to human livelihoods on small islands, given that the latter have characterised many—especially SIDS—within the last few decades. However, recent climate change is clearly implicated in livelihood deterioration in many island contexts ( [[#Hernandez-Delgado--2015|Hernandez-Delgado, 2015]] ; [[#Nunn--2018|Nunn and Kumar, 2018]] ). For example, livelihood impacts of climate-driven stressors (including shoreline/riverbank erosion, flooding and erratic rainfall) in three Mahishkhocha island chars (river-mouth sand islands of Bangladesh) have been amplified by inadequate/misguided policy ( [[#Saha--2017|Saha, 2017]] ).The subordination of IKLK in favour of external adaptation strategies has accelerated livelihood decline in many island contexts ( [[#Wilson--2018|Wilson and Forsyth, 2018]] ). Although economic and financial development has the potential to reduce environmental (and livelihood) degradation in SIDS ( [[#Seetanah--2019|Seetanah et al., 2019]] ), it is also clear that uneven development can steepen core–periphery disparities, especially in archipelagic contexts, resulting in deteriorating rural/peripheral livelihoods at the expense of improving urban ones ( [[#Wilson--2013|Wilson, 2013]] ; [[#Sofer--2015|Sofer, 2015]] ) and increased rural–urban migration ( [[#Birk--2014|Birk and Rasmussen, 2014]] ; [[#Connell--2015|Connell, 2015]] ).

<div id="15.3.4.6" class="h3-container"></div>

<span id="migration"></span>
==== 15.3.4.6 Migration ====

<div id="h3-9-siblings" class="h3-siblings"></div>

Climate-related migration is considered to be a particular issue for small islands because changes in extreme events and slow-onset changes affect increasingly highly exposed and vulnerable low-lying coastal populations, therefore causing a threat to small island habitability (KR9 in Figure 15.5) ( [[#Storey--2010|Storey and Hunter, 2010]] ; [[#Kumar--2015|Kumar and Taylor, 2015]] ; [[#Duvat--2017b|Duvat et al., 2017b]] ; [[#Weir--2017|Weir and Pittock, 2017]] ; [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ; [[#Mycoo--2018a|Mycoo, 2018a]] ; [[#Rasmussen--2018|Rasmussen et al., 2018]] ). A typology of climate-related migration is provided in Cross-Chapter Box MIGRATE in Chapter 7. It is assumed that climate-related migration will increase in small islands; however, as is the case globally, the causes, form and outcomes are highly context specific. Types of climate-related migration occur across a continuum of agency from involuntary displacement at one end to voluntary movement to strategically reduce risks and planned resettlement at the other end ( [[#15.5.1|Section 15.5.1]] , also see Chapter 7; [[#Birk--2014|Birk and Rasmussen, 2014]] ; [[#Betzold--2015|Betzold, 2015]] ; McNamara and Des Combes, 2015; [[#Gharbaoui--2016|Gharbaoui and Blocher, 2016]] ; [[#Stojanov--2017|Stojanov et al., 2017]] ; [[#Weir--2020|Weir, 2020]] ).

Studies do not provide sufficiently robust evidence to attribute the various forms of migration to anthropogenic climate change directly on small islands or to accurately estimate the current number of climate-related migrants (see Chapter 7). Climate events and conditions strongly interact with other environmental stressors and economic, social, political and cultural reasons for migrating ( ''robust evidence, high agreement'' ) ( [[#Birk--2014|Birk and Rasmussen, 2014]] ; [[#Campbell--2014|Campbell and Warrick, 2014]] ; [[#Laczko--2014|Laczko and Piguet, 2014]] ; Marino and [[#Lazrus--2015|Lazrus, 2015]] ; [[#Connell--2016|Connell, 2016]] ; [[#Weber--2016b|Weber, 2016b]] ; [[#Stojanov--2017|Stojanov et al., 2017]] ; [[#Cashman--2019|Cashman and Yawson, 2019]] ).

Despite difficulties with attribution, the literature establishes that climate variability and extreme events and broad environmental pressures have contributed to some degree to human mobility on small islands over time ( ''medium evidence, high agreement'' ) ( [[#Birk--2014|Birk and Rasmussen, 2014]] ; [[#Campbell--2014a|Campbell, 2014a]] ; [[#Campbell--2014|Campbell and Warrick, 2014]] ; [[#Donner--2015|Donner, 2015]] ; [[#Kelman--2015a|Kelman, 2015a]] ; [[#Connell--2016|Connell, 2016]] ; [[#Stojanov--2017|Stojanov et al., 2017]] ; [[#Barnett--2018|Barnett and McMichael, 2018]] ; [[#Martin--2018|Martin et al., 2018]] ) and these studies can provide analogues from which to inform climate-migration responses ( [[#Birk--2014|Birk and Rasmussen, 2014]] ; [[#Kelman--2015a|Kelman, 2015a]] ; [[#Connell--2016|Connell, 2016]] ).

Similarly, studies do not provide robust evidence to project how the full range of climate drivers may influence migration patterns on small islands into the future, although studies are emerging that estimate populations affected as a consequence of projected SLR. [[#Rasmussen--2018|Rasmussen et al. (2018)]] estimated current populations of the world that are potentially subject to permanent inundation from projected local mean SLR associated with global mean surface temperature stabilisation targets of 1.5°C, 2.0°C and 2.5°C occurring in 2100. For the affected land area and population, this analysis included a subset of 58 SIDS, as defined by the United Nations, for which the results are shown in Table 15.4.

'''Table 15.4 |''' Global mean sea level rise (SLR) at 2100 projections and associated population of SIDS exposed to permanent inundation for global mean surface temperature stabilisation targets of 1.5°C, 2.0°C and 2.5°C. [[#Rasmussen--2018|Rasmussen et al. (2018)]] .

{| class="wikitable"
|-
! Stabilised Warming at 2100 a

! colspan="2"| 1.5°C

! colspan="2"| 2.0°C

! colspan="2"| 2.5°C

|-
! ''Percentile''

! ''50th''

! ''5th–95th''

! ''50th''

! ''5th–95th''

! ''50th''

! ''5th–95th''

|-
| Global mean SLR (cm) by percentile b

| 48

| 28–82

| 56

| 28–96

| 58

| 37–93

|-
| SIDS population exposure (thousands) by percentile c

| 400

| 300–560

| 420

| 300–640

| 430

| 320–630

|}

Notes:

(a) Above pre-industrial level.

(b) Values are centimetres above 2000 current-era baseline.

(c) Potentially affected population due to local mean SLR. Local mean SLR projections used for individual SIDS take account of variations from the global mean due to factors such as glacial isostatic adjustment, gravitational changes from ice melting, deltaic subsidence and tectonic movements.

The aggregate figures of population that could potentially be affected by permanent inundation shown in Table 15.4 and Figure 15.3 mask important differences in relative exposure between individual SIDS. Further, population affected by permanent inundation does not take into account the change in the frequency of ESL events and associated water-level attenuation (as per [[#Vafeidis--2019|Vafeidis et al., 2019]] ), nor does it account for adaptation measures that may alleviate impacts, future population growth or the extent to which populations could adaptively migrate ( [[#15.5.3|Section 15.5.3]] ). However, the analysis by [[#Rasmussen--2018|Rasmussen et al. (2018)]] shows that comparatively small changes in mean sea level can result in large increases in the frequencies of ESL events and, hence, the risk of coastal flooding of inhabited land, suggesting many areas of SIDS may become uninhabitable well before the time of permanent inundation (see also studies referenced in [[#15.3.3.1.1|Section 15.3.3.1.1]] ). A similar conclusion is drawn by [[#Kulp--2019|Kulp and Strauss (2019)]] , who show that land area home to 10% or more of the population of many SIDS is at risk of chronic coastal flooding or permanent inundation by 2100.

[[#Duvat--2021a|Duvat et al. (2021a)]] employed an integrated systems approach to analyse future risk to habitability in atoll islands, taking into account changes in various ocean and atmospheric climate drivers and a moderate adaptation scenario (i.e., adaptation responses that remain similar in nature and magnitude to currently observed responses). They found that, compared to present-day risk, additional risk to habitability in Male’, Maldives, and Fongafale, Tuvalu, is minimal under a low emissions scenario (RCP2.6) at 2050, although it may become moderate for Male and high for Fongafale by 2090. Under a worse-case emissions scenario (RCP8.5), future risk to habitability in these two urban islands may increase slightly in 2050, but may increase to moderate-to-high (for Male’) and high-to-very high (for Fongafale) by 2090.

Even where settlement locations and livelihoods remain secure, an increase in health diseases, decrease in the availability of potable water and increasing exposure to extreme events may reduce habitability ( [[#15.3.4.9.2|Section 15.3.4.9.2]] ; [[#Campbell--2014|Campbell and Warrick, 2014]] ; [[#Storlazzi--2018|Storlazzi et al., 2018]] ). For example, the Fijian coastal community of Vunidogoloa made the decision to relocate in response to regular inundation during high tides. Raising houses on stilts and constructing a seawall failed to prevent regular flood damage to buildings and the entire community eventually relocated as a ‘last resort’ adaptation measure to a site within customary land. The availability of customary land for the new site was a key factor of success in this relocation example although this will not guarantee success in every case as relocation may expose communities to new risks (McNamara and Des Combes, 2015; [[#Piggott-McKellar--2019a|Piggott-McKellar et al., 2019a]] ).

<div id="15.3.4.7" class="h3-container"></div>

<span id="culture"></span>
==== 15.3.4.7 Culture ====

<div id="h3-10-siblings" class="h3-siblings"></div>

Small island societies have developed IKLK-based responses to living in dynamic environments susceptible to climate variability and extremes, which are based in broader systems of culture and heritage ( ''high confidence'' ) ( [[#Barnett--2010|Barnett and Campbell, 2010]] ; [[#Lazrus--2015|Lazrus, 2015]] ; [[#Nunn--2017b|Nunn et al., 2017b]] ; [[#Bryant-Tokalau--2018b|Bryant-Tokalau, 2018b]] ; [[#Nalau--2018b|Nalau et al., 2018b]] ; [[#Perkins--2018|Perkins and Krause, 2018]] ). As expanded upon in [[#15.6.5|Section 15.6.5]] , cultural resources are thought to play an important role in climate change adaptation on small islands through contributing to adaptive capacity and resilience ( [[#McMillen--2014|McMillen et al., 2014]] ; [[#Petzold--2015|Petzold and Ratter, 2015]] ; [[#Nunn--2017b|Nunn et al., 2017b]] ; [[#Warrick--2017|Warrick et al., 2017]] ; [[#Falanruw--2018|Falanruw, 2018]] ; [[#Mondragón--2018|Mondragón, 2018]] ; [[#Neef--2018|Neef et al., 2018]] ; [[#Parsons--2018|Parsons et al., 2018]] ; [[#Perkins--2018|Perkins and Krause, 2018]] ; [[#Hagedoorn--2019|Hagedoorn et al., 2019]] ; 2020a) ( ''robust evidence, medium agreement)'' . Thus, loss of culture (KR8 in Figure 15.5) threatens adaptive capacity.

Some studies from the Pacific suggest that climate-migration linked to reduced habitability ( [[#15.3.4.6|Section 15.3.4.6]] ) can have particularly severe cultural implications in a small island context where community solidarity and cohesion linked to place-based identity are important aspects of adaptive capacity ( [[#Hofmann--2014|Hofmann, 2014]] ; [[#Lazrus--2015|Lazrus, 2015]] ; [[#Warrick--2017|Warrick et al., 2017]] ). In the Federated States of Micronesia, land is owned through the matrilineal system and hence puts women at the centre of decision-making. The deterioration and loss of land (through saltwater intrusion, flooding, drought, erosion) not only can lead to economic deprivation but it also compromises cultural identities: ‘Where land signifies political, social, and economic well-being, becoming bereft of land cuts off an important thread of people’s sense of belonging’ ( [[#Hofmann--2017|Hofmann, 2017]] , p. 82) particularly for Chuuk women. Land degradation and loss involves the ‘interruption to the matrilineal transmission of land’ ( [[#Hofmann--2017|Hofmann, 2017]] ; p. 82), the loss of identities, relationships and their customary authority.

The unquantifiable and highly localised cultural losses resulting from climate drivers are less researched and less acknowledged in policy than physical and economic losses ( [[#Karlsson--2015|Karlsson and Hovelsrud, 2015]] ; [[#Thomas--2018a|Thomas and Benjamin, 2018a]] ). In the Bahamas, prolonged displacement of the entire population of Ragged Island following Hurricane Irma (2017) highlighted the cultural losses that can result from climate-induced displacement from ancestral homelands. Threats to identity, sense of place and community cohesion resulted from displacement, although all were important foundational features of the Islanders’ self-initiated rehabilitation efforts and eventual return. Nonetheless, non-economic losses were not accounted for by policy addressing displacement ( [[#Thomas--2018a|Thomas and Benjamin, 2018a]] ). In the case of Monkey River Village in Belize, coastal erosion is threatening the community’s cemetery. Residents place significant spiritual and emotional value on the cemetery, which serves important community functions, and, thus, threats to it are perceived to be serious and necessary to be taken into account in any planned response ( [[#Karlsson--2015|Karlsson and Hovelsrud, 2015]] ). A similar situation exists on Carriacou in the West Indies where culturally and historically significant archaeological sites are being lost due to coastal erosion caused by a combination of sand mining and extreme climate-ocean events exacerbated by SLR ( [[#Fitzpatrick--2006|Fitzpatrick et al., 2006]] ).

Population and settlement concentration in coastal areas and high exposure to climate-driven coastal hazards on small islands mean that threats to tangible cultural heritage (archaeological sites, buildings, historic sites, UNESCO World Heritage Sites etc.) are high ( [[#Marzeion--2014|Marzeion and Levermann, 2014]] ; [[#Reimann--2018|Reimann et al., 2018]] ), although few studies examine this issue specifically in a small island context. On the island of Barbuda, archaeological sites containing important information on historical ecology and climatic shifts are at risk from coastal erosion and hurricanes. This loss of heritage represents identity loss, as “learning about the past is a crucial exploration of self that grounds and connects people to places” ( [[#Perdikaris--2017|Perdikaris et al., 2017]] ; p. 145). Losses and damages to heritage sites may also impact tourism and thus have significant economic impacts for narrow small island economies ( [[#15.3.4.5|Section 15.3.4.5]] ).

<div id="15.3.4.8" class="h3-container"></div>

<span id="transboundary-risksissues"></span>
==== 15.3.4.8 Transboundary Risks/Issues ====

<div id="h3-11-siblings" class="h3-siblings"></div>

Inter-regional transboundary impacts are those generated by processes originating in another region or continent well beyond the borders of an individual archipelagic nation or small island. Intra-regional transboundary impacts originate from a within-region source (e.g., the Caribbean). Some transboundary processes may have positive effects on the receiving small island or nation, although most that are reported have negative impacts (Table 15.5).

'''Table 15.5 |''' Summary of inter- and intra-regional transboundary risks and impacts on small islands.

{| class="wikitable"
|-
! '''Transboundary risks/issues'''

! '''Small island examples'''

! '''Reference'''

|-
| Large ocean waves from distant sources

| Unusually large deep ocean swells generated from sources in the mid- and high latitudes by extratropical cyclones (ETCs) cause considerable damage on the coasts of small islands thousands of kilometres away in the tropics. Impacts include inundation of settlements, infrastructure, and tourism facilities as well as coastal erosion. These waves can propagate to and influence reef islands in equatorial areas not usually exposed to high-energy waves.

Examples of extratropical swell waves causing flooding and inundation have been reported throughout the Pacific (French Polynesia, Fiji, Micronesia, the Marshall Islands, Kiribati, Papua New Guinea and the Solomon Islands). Modelling of future wave climates has been carried out for 25 tropical Pacific islands, and results suggests that December–February extreme wave heights will decrease for most islands by 2100 under both an RCP4.5 and RCP8.5 scenario, although the frequency of the large winter wave events may increase around the Hawaiian Islands. In the Caribbean, northerly swells affecting the islands have been recognised as a significant coastal hazard. They cause considerable seasonal damage to beaches, marine ecosystems and coastal infrastructure throughout the region.

| [[#Hoeke--2013|Hoeke et al. (2013)]] ; [[#Smithers--2014|Smithers and Hoeke (2014)]] ; [[#Shope--2016|Shope et al. (2016)]] ; [[#Canavesio--2019|Canavesio (2019)]] ; [[#Wandres--2020|Wandres et al. (2020)]]

[[#Jury--2018|Jury (2018)]]

|-
| Transcontinental dust clouds and their impacts

| The transport of airborne Saharan dust across the Atlantic into the Caribbean has been intensively studied. In the West African Sahel, where drought has been persistent since the mid-1960s, analysis has shown that there have been remarkable changes in dust emissions since the late 1940s. Variability in Sahel dust emissions may be related not only to droughts, but also to changes in the North Atlantic Oscillation (NAO), North Atlantic SST and the Atlantic Multidecadal Oscillation (AMO). The frequency of dust storms has been on the rise during the last decade. Forecasts suggest that their incidence will increase further. Transboundary movement of Saharan dust into the island regions of the Caribbean and the Mediterranean has been associated with human health problems including asthma cases in the Caribbean, cardiovascular morbidity in Cyprus and pulmonary disease in the Cape Verde islands.

| [[#Prospero--2003|Prospero and Lamb (2003)]] ; [[#Goudie--2014|Goudie (2014)]] ; [[#Schweitzer--2018|Schweitzer et al. (2018)]] ; [[#Goudie--2020|Goudie (2020)]] ; [[#Middleton--2008|Middleton et al. (2008)]] ; [[#Martins--2009|Martins et al. (2009)]] ; [[#Akpinar-Elci--2015|Akpinar-Elci et al. (2015)]] ; [[#Sakhamuri--2019|Sakhamuri and Cummings (2019)]]

|-
| Influx of Sargassum from distant sources

| Since 2011, the Caribbean region has witnessed unprecedented influxes of the pelagic seaweed Sargassum. These extraordinary sargassum ‘blooms’ have resulted in mass deposition of seaweed on beaches throughout the Lesser Antilles, with damage to coastal habitats, mortality of seagrass beds and associated corals, as well as consequences for fisheries and tourism. This recent phenomenon has been linked to climate change as well as the possible influence of nutrients from Amazon River floods and/or Sahara dust.

| [[#van%20Tussenbroek--2017|van Tussenbroek et al. (2017)]] ; [[#Oviatt--2019|Oviatt et al. (2019)]]

Franks et al. (2016); [[#Putman--2018|Putman et al. (2018)]]

|-
| Large-scale changes in the distribution of fisheries resources

| Ocean warming and other climatic phenomena (e.g., ENSO events and Indian Ocean Dipole) have been linked to observed oceanic shifts in tuna distribution with significant impacts on revenue for vulnerable small island states that depend on fisheries licences (e.g., 98% of national income in Tokelau, 66% of national income in Kiribati). The projected eastward redistribution of skipjack and yellowfin tuna due to climate change is expected to reduce the total tuna catch within the combined Exclusive Economic Zones of the 10 Pacific Island Countries and territories (PICTs) where most purse-seine activity occurs by approximately 10% by 2050. Projected increases in tuna biomass have been anticipated for Ascension Island and Saint Helena in the South Atlantic.

| [[#Bell--2018|Bell et al. (2018)]] ; [[#SPC--2019|SPC (2019)]] ; [[#Oremus--2020|Oremus et al. (2020)]] ; [[#Bell--2021|Bell et al. (2021)]] ; [[#Townhill--2021|Townhill et al. (2021)]]

|-
| Movement and impact of introduced and invasive species across boundaries

| The spread of IAS is regarded as a significant transboundary threat to the health of biodiversity and ecosystems worldwide.

The extent to which IAS (both animals and plants) successfully establish themselves at new locations in a changing climate will be dependent on many variables, but non-climate factors such as transmission pathways, suitability of the destination, ability to compete and adapt to new environments, and susceptibility to invasion of host ecosystems are deemed to be critical. Modelling studies have been used to project the future ‘invisibility’ of small island ecosystems subject to climate change and therefore to anticipate marine and terrestrial habitat degradation in the future.

Evidence suggests that hurricanes may have hastened the spread of highly invasive Indo-Pacific lionfish ( ''Pterois volitans'' ) throughout the Caribbean in recent years. Two IAS, the Common Green Iguana ( ''Iguana iguana'' ) and Cuban Treefrog ( ''Osteopilus septentrionalis'' ) were reported in the Caribbean island of Dominica, following the passage of TC Maria in 2017. Observations 7 months after the hurricane, within close proximity to ports, suggest that these animals were stowaways on ships or within relief containers.

| [[#Russell--2017|Russell et al. (2017)]]

[[#Vorsino--2014|Vorsino et al. (2014)]] ; [[#Taylor--2016b|Taylor and Kumar (2016b)]]

[[#Johnston--2015|Johnston and Purkis (2015)]] ; van den Burg et al. (2020)

|-
| Spread of pests and pathogens within and between island regions

| Increased climate instability has contributed to the emergence and spread of serious diseases carried by mosquitoes such as dengue, chikungunya and Zika. The incidence and severity of mosquito-borne diseases have increased significantly in Pacific, Indian Ocean and Caribbean islands during the past 10 years, which calls for a better understanding of how climate change is shaping disease prevalence and transmission.

Rising sea temperatures are thought to increase the frequency of disease outbreaks affecting reef buildings. Of the range of bacterial, fungal and protozoan diseases known to affect stony corals, many have explicit links to temperature. Global projections suggest that disease is as likely to cause coral mortality as bleaching in the coming decades at many localities, with effects occurring earlier at sites in the Caribbean compared to the Pacific and Indian oceans. Model hindcasts suggest that climate-driven changes in SST as well as extreme heatwave events have all played a significant role in the spread of white-band disease throughout the Caribbean.

Global food security is threatened by climate-related increases in crop pests and diseases. Black Sigatoka disease of bananas has recently completed its invasion of Latin American and Caribbean banana-growing areas. Infection risk has increased by a median of 44.2% across the Caribbean since the 1960s, due to increasing canopy wetness and improving temperature conditions for the pathogen.

| [[#Cao-Lormeau--2014|Cao-Lormeau and Musso (2014)]] ; [[#Caminade--2017|Caminade et al. (2017)]] ; [[#Pecl--2017|Pecl et al. (2017)]] ; [[#Filho--2019|Filho et al. (2019)]]

[[#Maynard--2015|Maynard et al. (2015)]] ; [[#Randall--2015|Randall and van Woesik (2015)]]

[[#Bebber--2019|Bebber (2019)]]

|-
| Human migration and displacement

| Currently there is limited empirical evidence that long-term climate change is driving transboundary human migration from islands; however, following Hurricane Maria, Puerto Rico witnessed ‘depopulation’ of 14% in only 2 years as a result of emigration to the US mainland.

| [[#Campbell--2014a|Campbell (2014a)]] ; [[#Melendez--2017|Melendez and Hinojosa (2017)]]

|-
| Transboundary risks to island food security. COVID-19 caused disruptions to food supply and disaster risk management operations

| While SIDS are a diverse group of nations, most share such characteristics as limited land availability, insularity and susceptibility to natural hazards that make them particularly vulnerable to global environmental and economic change processes leading to regional food insecurity. The Pacific Islands Forum Secretariat (PIFS) has established a transboundary Framework for Action on Food Security, that promotes cooperation, investments, research and development, capacity-building, and adaptation to mitigate climate change threats.

| [[#Connell--2013|Connell (2013)]] ; [[#Islam--2020|Islam and Kieu (2020)]] ; [[#Sheller--2020|Sheller (2020)]]

|}

<div id="15.3.4.9" class="h3-container"></div>

<span id="key-risks-in-small-islands"></span>
==== 15.3.4.9 Key Risks in Small Islands ====

<div id="h3-12-siblings" class="h3-siblings"></div>

<div id="15.3.4.9.1" class="h4-container"></div>

<span id="key-risk-approach"></span>
===== 15.3.4.9.1 Key risk approach =====

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

This section builds on cross-chapter work led by [[IPCC:Wg2:Chapter:Chapter-16|Chapter 16]] aimed at identifying and assessing KRs across sectors and regions ( [[IPCC:Wg2:Chapter:Chapter-16#16.5|Section 16.5]] and SM16). KRs are the risks of most pressing concern that are caused or exacerbated by climate change in a given region. A KR is defined as a ‘potentially’ severe risk, which can either be already severe or projected to become severe in the future, as a result of (a) changes in associated climate-related hazards and/or the exposure and/or vulnerability of natural and human systems to these hazards, and/or of (b) the adverse consequences of adaptation or mitigation responses to the risk. In line with the guidelines used in the WGII AR6, the identification of KRs in small islands is based on the chapter authors’ expert judgement, using scientific literature and five types of criteria: (1) importance of the affected system or dimension of the system, which is a value judgement left to readers to make; (2) magnitude of adverse consequences, based on their pervasiveness, degree and irreversibility, and on the potential for impact thresholds and cascading effects across the system; (3) likelihood of adverse consequences, although this probability is rarely quantifiable for small islands due to limited downscaled data at a small island level; (4) temporal characteristics of the risk, including its period of emergence, persistence over time and trend; and (5) ability to respond to the risk, with the severity of the risk being inversely proportional to this ability.

<div id="15.3.4.9.2" class="h4-container"></div>

<span id="key-risks-in-small-islands-1"></span>
===== 15.3.4.9.2 Key risks in small islands =====

<div id="h4-10-siblings" class="h4-siblings"></div>

Slow-onset climate and ocean changes, and changes in extreme events, are expected to cause and/or to amplify nine KRs in small islands, through both direct (e.g., decrease in rainfall will increase water insecurity) and indirect, that is, cascading effects: For example, loss of terrestrial biodiversity and ecosystem services will increase water insecurity, which will in turn cause the degradation of human health and well-being (Figure 15.5, Table 15.6 and SM16).

'''Table 15.6 |''' Adaptation options per key risk in small islands. This table summarises risk-oriented adaptation options, their level of implementation, enablers and effectiveness in reducing exposure and vulnerability, co-benefits and disbenefits in small islands. For KR2 (submergence of reef islands), not included, adaptation options are the same as for KR5.

{| class="wikitable"
|-
! Key risks

! colspan="2"| Risk-oriented adaptation options

! Evidence and agreement

! Implementation

! Key enablers

! Reduction of exposure and vulnerability

! Co-benefits

! Disbenefits

|-
| rowspan="5"| KR1. Loss of marine and coastal biodiversity and ecosystem services

| rowspan="2"| EbA measures (15.4.4)

| MPAs; paired terrestrial and MPAs

| ''Medium evidence, low agreement'' with regard to climate change adaptation and benefits

| Widespread across small islands, with climate resilience being a target of some MPAs

| Strong governance and sufficient financial resources

| Reduces the ecosystem exposure to human disturbances, increasing their resistance and resilience to climate events

| For biodiversity, food supply, economics, human health and well-being

|
|-
| Active restoration of coastal and marine ecosystems

| ''Limited evidence, low agreement'' with regard to long-term success

| Mostly small-scale: replanting of mangroves, seagrasses and beach vegetation; transplantation of corals; beach nourishment

| Funding: adaptation taxes and levies imposed on tourism; blue bonds; public–private partnerships

| Reduces the vulnerability of natural ecosystems by increasing their resilience

| Improved water quality; reduction in coastal erosion and flood risks; economic benefits

|
|-
| Hard protection (15.5.1)

| Hard structures designed to enhance marine biodiversity

| ''Medium evidence, medium agreement''

| Artificial reefs

| Funding: adaptation and environmental taxes and levies, with ''limited evidence'' of direct reinvestment in conservation and management

| Uncertainty on reduction of exposure and vulnerability of marine ecosystems; reduces the exposure of population and infrastructure to coastal risks

| For food supply, economies (tourism), human health and well-being

|
|-
| Diversifying livelihoods (15.5.6)

| Diversifying fisheries livelihoods (e.g., to aquaculture and tourism), changing fishing grounds and/or target species

| ''Limited'' to ''medium evidence'' , ''medium agreement''

| Examples in the Caribbean region and in the Pacific and Indian Oceans

| Improved governance and cooperation (e.g., through regional strategies); weather insurance to enhance resilience

| Reduces exposure and vulnerability of livelihoods through the diversification of income and spreading of risks; targeting less offshore pelagic species reduces exposure of coastal habitats to overfishing

| Sustainably managed fisheries, improved food and income security, greater economic and social resilience

|
|-
| Reef-to-ridge ecosystem management (Figure 15.4)

| Improved land use as a driver of marine ecosystem health, including better management of forests, nutrients and wastewater upland catchments

| ''Limited evidence, medium agreement''

| Mostly in the Caribbean region and Pacific

| Improved governance

| Reduces the exposure of coral reefs to human degradation, increasing their resilience

| Improved ecosystem protection services (e.g., against flooding, landslides and mudflows), biodiversity, human health and livelihoods

|
|-
| rowspan="5"| KR3. Loss of terrestrial biodiversity and ecosystem services

| Decreased deforestation (15.5.4)

|
| ''Limited'' to ''medium evidence, high agreement''

| Mostly in the Caribbean region and Pacific

| National determined contributions (NDCs), external and long-term funding, engagement of local landowners and resolution of land ownership issues, gender-sensitive participation

| For example, increase in forest extent, reduction in human exposure to natural disasters (hurricanes, landslides), improvement in vulnerability assessment scores

| Increased connectivity between forest fragments, reduced erosion, improved water supply and quality, improved human health and sanitation, improved livelihoods and soil health; decreased poverty; supports global mitigation

|
|-
| Increased reforestation (native species) (15.5.4)

| Towards habitat connectivity, heterogeneity and diversity

| ''Medium evidence, high agreement''

| Relatively widespread, with examples in the Caribbean region and Pacific

| NDC, funding, technical assistance, supply materials, provision of land, awareness raising, enforcement of policies, sense of shared responsibility, inclusion of IKLK, social capital

| Generally ''limited evidence'' , lack of long-term monitoring

| Increased DRR; fewer floods and landslides; reduced erosion; increased human health and well-being; increased quality of ecosystem services; increased adaptive capacity; supports global mitigation

|
|-
| EbA (15.5.4)

| Agroforestry and other silvicultural/agroecological practices (e.g., climate-smart agriculture)

| ''Medium evidence, high agreement''

| Widespread in the Caribbean region and Pacific Ocean

| NDC, shared access and benefit, local knowledge and training, farmers, private sector for developing technology, financing, data availability; political, institutional and socioeconomic conditions

| Limited examples, some increases in adaptive capacity

| Improved climate change awareness, increased well-being, improved gender equity, improved productivity and livelihoods

|
|-
| Watershed management/conservation (15.5.4)

| Reforestation, slope revegetation

| ''Medium evidence, high agreement''

| Widespread (e.g., in the Caribbean region and Pacific Ocean)

| Less socially and politically acceptable than engineering solutions; communication and trust between stakeholders; sustainable financing mechanisms; island remoteness barrier to logistical implementation

| Yes, through improved water security, reduced adaptation costs, reduced vulnerability to drought

| DRD, improved climate change awareness, increased water security and quality, reduced run-off and sedimentation, increased well-being and financial stability

|
|-
| Ridge-to-reef ecosystem management (Figure 15.4)

| Improved land use as a driver of terrestrial ecosystem health

| ''Medium evidence, high agreement''

| See above

| See above

| ''Limited but slowly increasing evidence'' to date

|
|-
| rowspan="2"| KR3. Loss of terrestrial biodiversity and ecosystem services

| Increasing the connectivity of protected areas (PAs) across elevation/climatic gradients to facilitate climate-driven redistribution of species (Figure 15.4)

| Establishment of new PAs, forested migration corridors across elevation/climatic gradients, improving landscape connectivity by permanent protection of stepping stones

| ''Very limited evidence, high agreement''

| Low degree of new implementations due to terrain limitations combined with competition from human land use needs; large variation in PA coverage among islands

| Conservation of larger areas of forest habitat surrounding PAs, reforestation of degraded areas, increasing and enforcement of forest cover within PAs, policies towards the coordination of conservation actions/partnerships, incorporation of ‘Other Effective area-based Conservation Measures’ (OECMs)

| Yes, especially if landscape connectivity is improved (migration corridors)

| Improved water security, improved coastal ecosystem health, greater resiliency and recovery from wildfires, reduced pollution, DRR

| May facilitate movement of IAS

|-
| Eradication of IAS (15.3.3.3)

|
| ''Robust evidence, high agreement''

| Widespread (&gt;700 islands)

| Integration of changing climate conditions within ongoing prevention, control and eradication strategies, prevention via ongoing vigilance and biosecurity via quarantine, control and monitoring of incoming cargo and goods into islands

| Yes, positive demographic and distributional responses of native species following eradication of IAS

| Food security, protection of ecosystem health and services, increased livelihood security

| A few native species harmed by eradication process

|-
| rowspan="4"| KR4. Water insecurity

| Rainwater harvesting (15.3.4.3)

|
| ''Robust evidence, high agreement''

| Widespread across small islands (e.g., Jamaica, Barbuda, Solomon Islands)

| Sociocultural and financial

| Yes

| Biodiversity (watershed protection); health; economic (reduced dependence on public supply); food security

| Dependent on mode of implementation. Nothing mentioned in the chapter.

|-
| Desalination (15.6.1)

|
| ''Limited evidence, high agreement''

| Relatively limited (e.g., Maldives)

| Financial

| Yes

| Health; economic (reduced dependence on public supply)

| Energy intensive (carbon footprint)

|-
| Reforestation (15.5.4)

|
| ''Medium evidence, high agreement''

| Examples reported in the Caribbean and Pacific (e.g., Fiji, Papua New Guinea)

| Governance–whole-of-island approaches foster integrated management practices in small islands

| Yes, through supporting wetland-oriented tourism

| Economic (agroforestry); biodiversity (watershed restoration); food security; DRR

| rowspan="2"| Dependent on mode of implementation. Nothing mentioned in the chapter.

|-
| PA management (terrestrial) (15.5.4)

|
| ''Medium evidence, high agreement''

| Widespread across small islands (e.g., Samoa, Jamaica, Haiti, Grenada)

| Financial/governance

| Yes, through soil stabilisation and sequestration of pollutants

| Biodiversity (forest conservation); DRR

|-
| rowspan="5"| KR5. Destruction of settlements and infrastructure

| Hard protection (15.5.1)

|
| ''Medium agreement, limited evidence'' with regard to climate change adaptation and success

| Widespread in both urban and rural areas of the Caribbean, Pacific and Indian Oceans

| External funding; sociocultural (meets the preference of the population); political–institutional (e.g., supported by business-as-usual approach of coastal risks); technical (requires materials and skills)

| Reduces exposure in some places but not in others; increases vulnerability

| ''Limited evidence'' of co-benefits

| Beach loss; erosion acceleration; ecosystem degradation through material extraction; increased SLR impacts

|-
| Accommodation (15.5.2)

|
| ''Limited evidence'' with regard to climate change adaptation and success

| Relatively limited

| Technological, financial, institutional, sociocultural

| ''Limited evidence'' to date

| Maintains the functionalities of coastal systems and allows their maintenance through landward migration, under SLR

|
|-
| Advance with land raising and/or through the creation of artificial islands (15.5.2)

|
| ''Limited evidence'' with regard to climate change adaptation (driven by population growth in the Maldives)

| Limited (e.g., Hulhumalé, Maldives)

| Technological, financial, institutional, sociocultural, high potential in urban (compared to rural) areas

| Reduces population exposure where high standard as in Hulhumalé, Maldives

| Offers new land for economic development, generates revenues through sale or lease of land in urban areas

| Widespread ecosystem destruction, increased negative impacts of SLR

|-
| Migration including planned resettlement (15.5.3)

|
| ''Limited evidence, low agreement'' with regard to climate change adaptation

| Village-scale planned resettlement supported by government policy/legislation in the Pacific

| Participatory inclusion of all social groups; financial (for small and remote communities); social–cultural connections; strong governance frameworks; enabling legislation; land availability or ownership; conditions in receiving locations; technical support

| Reduced exposure locally; has created new vulnerabilities at some locations by bearing significant economic cost, impacting social capital and reducing access to services

| New livelihood opportunities

| Loss of cultural heritage, impacts on receiving communities

|-
| EbA measures (15.4.4)

|
| ''Medium agreement, medium evidence''

| Increasingly experienced; includes artificial reefs, beach nourishment and vegetation (including mangrove) restoration

| Environmental/physical conditions; social acceptability; technical capacities (enhanced by external support); funding; inclusion in national adaptation policies

| ''Limited evidence'' to date

| Biodiversity strengthening; increased food supply; increased human health and well-being

|
|-
| KR6. Health degradation

| Increasing public awareness of health risks associated with climate change; providing training to health sector staff; improving reliability and safety of water storage practices (15.6.2)

|
| ''Limited evidence''

| Few examples

| Financial and human resources to implement options; early warning and response systems; integrating climate services into health decision-making systems; public uptake and buy in; improving health data collection systems

| Primarily reduces vulnerability

| Increased water security

|
|-
| rowspan="5"| KR7. Economic decline and livelihood failure

| Circular migration (15.5.3)

|
| ''Limited evidence'' with regard to climate change adaptation (mostly driven by economic or social factors)

| Examples in Tuvalu from outer to capital atoll and locations overseas

| Labour and education opportunities in Funafuti, Tuvalu, and overseas

| Yes, on Nanumea Atoll, Tuvalu

| Job and education for migrants

|
|-
| Diversifying livelihoods (15.5.6)

|
| ''Limited'' to ''medium evidence, low agreement''

| Observed in the Caribbean region and Pacific

| Use of IKLK and changing fishing areas; investment in technology and education

| Yes, in documented places (e.g., Antigua, Vanuatu, Madagascar, Dominican Republic)

| Reduction of pressure on previous fishing areas

| Greater catch putting increasing pressure on fish stock

|-
| Improved technology and equipment/training (15.5.6)

|
| ''Limited evidence, medium agreement''

| Examples in the Caribbean region and Pacific

| Investments in technologies and education (e.g., irrigation technologies, growing salt-tolerant crops and relocating crop cultivation in Jamaica)

| Yes, in documented places

| New technologies and education strengthening

|
|-
| Livestock husbandry (15.5.6)

|
| ''Limited evidence''

| Limited (e.g., small-scale livestock husbandry in Jamaica)

| Farm inputs and investments in technologies and education

| No evidence to date. Limited examples of successful livestock husbandry only in Jamaica

| Investments in farm inputs

|
|-
| Adaptive finance/education (15.5.6)

|
| ''Limited evidence, medium agreement''

| Limited (e.g., in Puerto Rico, women engage in new commercial enterprises that do not rely on traditional coffee supply chains or government assistance)

| Tourism income; investment in education and capacity building; working with nature and EbA

| Yes, reduces risk and avoids negative knock-on effects

| Generates opportunities (e.g., for wetland tourism)

|
|-
| rowspan="2"| KR7. Economic decline and livelihood failure

| Product/market diversification (15.5.6)

| Diversity of crops, gardening in different areas, storage and preservation of foodstuffs, engagement of women in new commercial enterprises

| ''Medium evidence, high agreement''

| Examples in the Caribbean region and Pacific

| Availability of crops and land, new markets

| Reduces vulnerability to tropical cyclones in Fiji and Vanuatu; new markets in Puerto Rico

| Increases food security and improves nutrition; increases income security

|
|-
| Adaptation in tourism policies (15.5.6)

|
| ''Limited evidence, high agreement''

| Limited (e.g., in the British Virgin Islands, policies like adaptation taxes and levies imposed on tourism can provide funding for adaptation measures)

| Tourism regulations and policies that mainstream climate change adaptations; taxes and levies imposed on tourism

| ''Limited evidence'' in reducing vulnerability

|
|-
| rowspan="2"| KR8. Loss of cultural resources and heritage

| Integrating IKLK with Western science to provide integrated approaches to climate change (15.6.5)

|
| ''Medium evidence, high agreement''

| Reported in the Pacific and Caribbean

| Use of IKLK for preparing for disasters and understanding environmental change; social networks in sharing information and helping others; eco-theology increasing people’s awareness of the environment

| Yes, can reduce vulnerability when IKLK supports robust adaptation; No, can increase vulnerability if IKLK no longer provides accurate information

| Can increase climate change information and its understanding in communities, and increase culturally appropriate climate adaptation

| Reports from Vanuatu indicate that IKLK are at times inaccurate (e.g., seasonal calendars, biophysical weather indicators) due to climate change

|-
| Hard protection (15.5.5.1)

|
| ''Medium agreement, limited evidence'' with regard to climate change adaptation and success

| Widespread in protecting cultural sites and villages in both urban and rural areas of the Caribbean, Pacific and Indian Oceans

| External funding; sociocultural (generally meets the preference of the population); political-institutional (e.g., supported by business-as-usual approach of coastal risks); technical (requires materials and skills)

| Reduces exposure in some places but not in others; increases vulnerability

| ''Limited evidence'' of co-benefits

| Beach loss; erosion acceleration; ecosystem degradation through material extraction; increased SLR impacts

|}

These KRs include loss of marine and coastal biodiversity and ecosystem services ( ''high confidence'' ) (KR1; for details on KR coverage, see [[#15.3.3.1|Section 15.3.3.1]] ); submergence of reef islands ( ''low confidence'' ) (KR2; [[#15.3.3.1.1|Section 15.3.3.1.1]] ); loss of terrestrial biodiversity and ecosystem services ( ''high confidence'' ) (KR3; [[#15.3.3.3|Section 15.3.3.3]] ); water insecurity ( ''medium-high confidence'' ) (KR4; [[#15.3.4.3|Section 15.3.4.3]] ); destruction of settlements and infrastructure ( ''high confidence'' ) (KR5; [[#15.3.4.1|Section 15.3.4.1]] ); degradation of human health and well-being ( ''low confidence'' ) (KR6; [[#15.3.4.2|Section 15.3.4.2]] ); economic decline and livelihood failure ( ''high confidence'' ) (KR7; Sections 15.3.4.4 and 15.3.4.5); and loss of cultural resources and heritage ( ''low confidence'' ) (KR8; [[#15.3.4.7|Section 15.3.4.7]] ).

Risk accumulation and amplification through cascading effects from ecosystems and ecosystem services to human systems will likely cause reduced habitability of some small islands ( ''high confidence'' ) identified as the overarching KR (KR9). Habitability is understood as the ability of these islands to support human life by providing protection from hazards which challenge human survival; by assuring adequate space, food and freshwater; and by providing economic opportunities, which contribute to health and well-being—recognising that both supportive ecosystems and sociocultural conditions (i.e., beliefs and values, institutions and governance arrangements, sense of community and attachment to place) play a critical role in habitability ( [[#Duvat--2021a|Duvat et al., 2021a]] ). The reduction of island habitability is expected to cause increased migration, along the afore-mentioned involuntary displacement to planned resettlement spectrum ( [[#15.3.4.6|Section 15.3.4.6]] ), which may eventually lead to population movements from exposed areas and depopulation of some islands. This risk is the highest for atoll nations, where some islands might become uninhabitable over this century ( [[#15.3.4.6|Section 15.3.4.6]] ; [[#Storlazzi--2018|Storlazzi et al., 2018]] ; [[#Duvat--2021a|Duvat et al., 2021a]] ). Despite a lack of literature assessing the risk of reduced habitability in non-atoll islands, the latter are also expected to experience decreased habitability, especially in their coastal areas.

<div id="box-15.1" class="h2-container box-container"></div>

'''Box 15.1 | Key Examples of Cumulative Impacts from Compound Events: Maldives Islands and Caribbean Region'''
<div id="h2-19-siblings" class="h2-siblings"></div>

'''Cumulative Impacts of the Compound Events of the 1998–2016 Period in the Maldives Islands'''
Between 1998 and 2016, the Maldives Islands were affected by three major climate events, including the 1997–1998 ENSO event, the 2007 flood event and the 2016 ENSO event, and by one tectonic event, the 2004 Indian Ocean tsunami ( [[#Morri--2015|Morri et al., 2015]] ). These events illustrate the cumulative and cascading risks that a series of events may cause in reef-dependent atoll contexts (Figure Box 15.1).

[[File:9e99beca64cbd208d342f2a881860f31 IPCC_AR6_WGII_Figure_15_Box_15_1_1.png]]

'''Figure Box 15.1.1 |''' '''Cascading and cumulative impacts of the compound events of the 1998–2016 period in the Maldives Islands.'''

The 1997–1998 ENSO event was severe in the Maldives and as a result the living coral cover dropped to &lt;10% ( [[#Bianchi--2003|Bianchi et al., 2003]] ). Recovery was still in progress in 2004 when the tsunami caused further (although not quantitatively assessed ( [[#Gischler--2006|Gischler and Kikinger, 2006]] )) damage to the reef ecosystem. Post-1998 recovery ultimately took 15 years, (i.e., longer than following the 1987 ENSO event, after which recovery had only taken a few years) and also longer than in the neighbouring undisturbed Chagos atolls, thereby suggesting the alteration of the recovery capacity of the reef ecosystem by human-induced reef degradation and climate change ( [[#Morri--2015|Morri et al., 2015]] ; [[#Pisapia--2017|Pisapia et al., 2017]] ). Mid-2016, a new ENSO event occurred, which reduced living coral cover by 75% ( [[#Perry--2017|Perry and Morgan, 2017]] ). Future recovery of the reef ecosystem, which is critical to both current livelihoods and economic activities (especially diving-oriented tourism and fishing) and to long-term island persistence, will mainly depend first on the frequency and magnitude of future bleaching events, which are expected to increase due to ocean warming, and second on the highly variable effects of anthropogenic disturbances locally ( [[#Perry--2017|Perry and Morgan, 2017]] ; [[#Pisapia--2017|Pisapia et al., 2017]] ; [[#Duvat--2019b|Duvat and Magnan, 2019b]] ).

Additionally, the 2004 Indian Ocean tsunami ( [[#Magnan--2006|Magnan, 2006]] ) and the 2007 flood ( [[#Wadey--2017|Wadey et al., 2017]] ) caused damage totalling 62% of the country’s GDP ( [[#Luetz--2017|Luetz, 2017]] ). The tsunami also downgraded the Maldives (now a middle-income country) to the Least Developed Countries category and caused within-country migration, with 30,000 people (9.6% of the country’s population) displaced ( [[#Republic%20of%20Maldives--2009|Republic of Maldives, 2009]] ). These successive events, which had cumulative devastating effects on the reef ecosystem and cascading effects on health and well-being, livelihoods and the economy, highlighted the risk posed by limited recovery time to the whole social–ecological system as well as the detrimental effect of local human disturbances on reef recovery.

'''Cumulative Impacts of the 2017 Hurricanes in the Caribbean Region'''
Among the 29 Caribbean SIDS, 22 were affected by at least one Category 4 or 5 TC in 2017. These events highlighted how the pre-cyclone high exposure and vulnerability of these islands and their populations has caused a ‘cumulative community vulnerability’ ( [[#Lichtveld--2018|Lichtveld, 2018]] , p. 28) that has amplified the impacts of these TCs, which will in turn increase the long-term vulnerability of affected islands. The exposure of these islands over their entire surface, combined with the concentration of people, infrastructure, utilities and public services in flood-prone coastal areas, inadequate housing, limited access to healthy food and transportation, and unpreparedness explains widespread-to-total devastation ( [[#Shultz--2018|Shultz et al., 2018]] ; [[#Briones--2019|Briones et al., 2019]] ). The destruction of transport systems ( [[#Lopez-Candales--2018|Lopez-Candales et al., 2018]] ) and island supply chains ( [[#Kim--2019|Kim and Bui, 2019]] ), which heavily depend on ports, roads, power and communications, made rescue logistically complex, explaining the lack of freshwater, food supplies, medications and fuel on some islands for several weeks after the event. This cumulative vulnerability caused ‘cascading public health consequences’ ( [[#Shultz--2018|Shultz et al., 2018]] , p. 9), including delayed (i.e., over the next year) mortality, physical injury during the clean-up and recovery phase and increased risk of chronic, vector-borne, contaminated water-related diseases as well as of mental sequelae ( [[#Kishore--2018|Kishore et al., 2018]] ; [[#Ferre--2019|Ferre et al., 2019]] ).

The loss of mangroves ( [[#Branoff--2018|Branoff, 2018]] ; [[#Walcker--2019|Walcker et al., 2019]] ; [[#Taillie--2020|Taillie et al., 2020]] ) and terrestrial forests ( [[#Eppinga--2018|Eppinga and Pucko, 2018]] ; [[#Feng--2018|Feng et al., 2018]] ; [[#Hu--2018|Hu and Smith, 2018]] ; [[#Van%20Beusekom--2018|Van Beusekom et al., 2018]] ) exacerbated the cyclone-induced economic crisis. In the most affected islands, the destruction of buildings and outmigration generated a significant loss of tangible (e.g., museums) and intangible (e.g., traditional artistry) cultural heritage ( [[#Boger--2019|Boger et al., 2019]] ). Prolonged displacement of entire island populations (e.g., Ragged Island, the Bahamas, Barbuda) caused ‘non-economic loss and damage’, including threats to health and well-being, and loss of culture, sense of place and agency ( [[#Thomas--2019|Thomas and Benjamin, 2019]] ), which may further exacerbate the long-term vulnerability of concerned communities.

In early 2020, while island communities were still recovering from the 2017 hurricanes, the COVID-19 pandemic caused the closure of global transportation, with devastating socioeconomic impacts on tourism-dependent Caribbean economies ( [[#Sheller--2020|Sheller, 2020]] ), illustrating how compounding crises increase island vulnerability to both climate- and non-climate-related events.

<div id="box-15.2" class="h2-container box-container"></div>

'''Box 15.2 | Loss and Damage and Small Islands'''
<div id="h2-20-siblings" class="h2-siblings"></div>

Loss and damage has a range of conceptualisations ( [[IPCC:Wg2:Chapter:Chapter-1#1.4.4.2|Section 1.4.4.2]] ; Cross-Chapter Box LOSS in Chapter 17) and is a critical issue for many small islands, closely related to issues of climate justice ( [[#15.7|Section 15.7]] ). Small islands are already experiencing an array of negative climate change impacts while climate risks are projected to increase as global average temperatures rise (Sections 15.3, 16.2; Cross-Chapter Paper 2). Barriers and limits to adaptation also contribute to greater levels of both economic and non-economic loss and damage for small islands (Sections 15.6, 16.4).

For SIDS in particular, loss and damage has negative implications for sustainable development ( [[#Benjamin--2018|Benjamin et al., 2018]] ). The costs of loss and damage, particularly from extreme events, can deplete national capital reserves ( [[#Noy--2019|Noy and Edmonds, 2019]] ). [[#Thomas--2017|Thomas and Benjamin (2017)]] show how loss and damage can lead to an ‘unvirtuous cycle of climate-induced erosion of development and resilience’. In this cycle, addressing loss and damage strains limited national resources, diverting public funding and other resources to address negative climate impacts. This in turn reduces resources and capacities which could be allocated to adaptation, building resilience and sustainable development, thereby increasing vulnerability to climate change and leading to further loss and damage where the cycle begins again. The cascading and cumulative impacts of extreme events experienced in Pacific and Caribbean SIDS exemplify that this cycle may already be in effect.

In addition to the strain on national resources that loss and damage currently presents, credit ratings of SIDS have recently begun to include vulnerability to climate change, which may have negative impacts on their abilities to borrow external funds, attract foreign investment or access concessional financing ( [[#Buhr--2018|Buhr et al., 2018]] ; [[#Volz--2020|Volz et al., 2020]] ). Costs of addressing loss and damage may also affect the ability of SIDS to repay external debt, thus endangering eligibility for future access to funding ( [[#Baarsch--2016|Baarsch and Kelman, 2016]] ; [[#Klomp--2017|Klomp, 2017]] ; [[#Shutter--2020|Shutter, 2020]] ). These factors may place SIDS in situations where they face mounting costs of climate change with eroding capacities and resources to address loss and damage.

In the international policy arena, small islands—as part of the AOSIS—have been strong advocates for including loss and damage in the United Nations Framework Convention on Climate Change (UNFCCC); highlighting the increasing and irreversible risks that climate change poses for islands in particular ( [[#Roberts--2015|Roberts and Huq, 2015]] ; [[#Adelman--2016|Adelman, 2016]] ; [[#Mace--2016|Mace and Verheyen, 2016]] ). AOSIS, along with other developing countries and groups, have advocated that there is a pressing need for finance and resources to address loss and damage as well as greater integration of loss and damage in the UNFCCC and the Paris Agreement, including in capacity building, technology and the global stocktake ( [[#Benjamin--2018|Benjamin et al., 2018]] ; [[#Nand--2020|Nand and Bardsley, 2020]] ).

<div id="15.4" class="h1-container"></div>

<span id="detection-and-attribution-of-observed-impacts-of-climate-change-on-small-islands"></span>