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ADVANCED REVIEW
Risks to future atoll habitability from climate-driven
environmental changes
Virginie K. E. Duvat
1
| Alexandre K. Magnan
1,2
| Chris T. Perry
3
|
Tom Spencer
4
| Johann D. Bell
5,6
| Colette C. C. Wabnitz
7,8,9
|
Arthur P. Webb
5,10
| Ian White
11
| Kathleen L. McInnes
12
|
Jean-Pierre Gattuso
2,13
| Nicholas A. J. Graham
14
| Patrick D. Nunn
15
|
Gonéri Le Cozannet
16
1
UMR LIENSs 7266, La Rochelle University-CNRS, Bâtiment ILE, La Rochelle, France
2
Institute for Sustainable Development and International Relations, Sciences-Po, Paris, France
3
Department of Geography, College of Life & Environmental Sciences, University of Exeter, UK
4
Cambridge Coastal Research Unit, Department of Geography, University of Cambridge, Cambridge, UK
5
Australian National Centre for Ocean Resources and Security (ANCORS), Innovation Campus, University of Wollongong, New South Wales,
Australia
6
Center for Oceans, Conservation International, Arlington, VA, USA
7
Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, Canada
8
Stockholm Resilience Center, Stockholm University, Sweden
9
Center for Ocean Solutions, Stanford University, Stanford, California
10
Tuvalu Coastal Adaptation Project (TCAP), Resilience & Sustainable Development Unit, United Nations Development Programme, Suva, Fiji
11
Australian National University, Fenner School of Environment and Society, Canberra, Australia
12
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
13
Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefranche, Villefranche-sur-mer, France
14
Lancaster Environment Centre, Lancaster University, UK
15
School of Social Sciences, University of the Sunshine Coast, Maroochydore, Queensland, Australia
16
BRGM, French Geological Survey, Risk and Prevention Department, Coastal Risks and Climate Change Unit, Orléans, France
Correspondence
Virginie K. E. Duvat, UMR LIENSs 7266,
La Rochelle University-CNRS, Bâtiment
ILE, 2 rue Olympe de Gouges, 17000 La
Rochelle, France.
Email: virginie.duvat@univ-lr.fr
Funding information
Agence de l'Environnement et de la
Maîtrise de l'Energie, Grant/Award
Number: 20ESC0016; Agence Nationale de
la Recherche, Grant/Award Numbers:
ANR-15-CE03-0003, ANR-10-LABX-14-01;
Commonwealth Scientific and Industrial
Research Organisation; David and Lucile
Packard Foundation, Grant/Award
Number: 2019-68336; DFAT-funded
Australia-Pacific Climate Partnership;
Gordon and Betty Moore Foundation,
Abstract
Recent assessments of future risk to atoll habitability have focused on island
erosion and submergence, and have overlooked the effects of other climate-
related drivers, as well as differences between ocean basins and island types.
Here we investigate the cumulative risk arising from multiple drivers (sea-level
rise; changes in rainfall, ocean–atmosphere oscillations and tropical cyclone
intensity; ocean warming and acidification) to five Habitability Pillars: Land,
Freshwater supply, Food supply, Settlements and infrastructure, and Economic
activities. Risk is assessed for urban and rural islands of the Pacific and Indian
Oceans, under RCP2.6 and RCP8.5, in 2050 and 2090, and considering a mod-
erate adaptation scenario. Risks will be highest in the Western Pacific which
will experience increased island destabilization together with a high threat to
freshwater, and decreased land-based and marine food supply from reef-
Received: 29 May 2020 Revised: 21 December 2020 Accepted: 23 December 2020
DOI: 10.1002/wcc.700
WIREs Clim Change. 2021;e700. wires.wiley.com/climatechange © 2021 Wiley Periodicals LLC. 1of28
https://doi.org/10.1002/wcc.700
Grant/Award Number: GBMF5668.02;
The Ocean Solutions Initiative supported
by the Prince Albert II of Monaco
Foundation, the Ocean Acidification
International Coordination Centre of the
International Atomic Energy Agency, the
Veolia Foundation, and the French
Facility for Global Environment; The
Royal Society; Walton Family Foundation,
Grant/Award Number: 2018-1371
Edited by Mike Hulme, Domain Editor
and Editor-in-Chief.
[Correction added on 28 January 2021
after first online publication: New
affiliation for Johann D. Bell has been
added and subsequent affiliation labels
has been fixed.]
dependent fish and tuna and tuna-like resources. Risk accumulation will occur
at a lower rate in the Central Pacific (lower pressure on land, with more lim-
ited cascading effects on other Habitability Pillars; increase in pelagic fish
stocks) and the Central Indian Ocean (mostly experiencing increased land
destabilization and reef degradation). Risk levels will vary significantly
between urban islands, depending on geomorphology and local shoreline dis-
turbances. Rural islands will experience less contrasting risk levels, but higher
risks than urban islands in the second half of the century.
This article is categorized under:
Trans-Disciplinary Perspectives > Regional Reviews
KEYWORDS
atolls, climate change impacts, habitability, Indian Ocean, Pacific Ocean, reef island
1|INTRODUCTION
Climate change impacts will increasingly compromise the essential dimensions of human life on low-lying tropical
islands (Magnan, Garschagen, et al., 2019). These dimensions include land, freshwater and food availability and the
maintenance of settlements and infrastructure, as well as economic activities. The future of populations living on atoll
islands in the Indian (Maldives) and Pacific Oceans (especially in Cook Islands, Tuvalu, Federated States of Micronesia
[FSM], Kiribati, Marshall Islands, Tokelau, French Polynesia; Supplementary Material SM1) will in part be determined
by how the reef-island systems on which they depend will respond to changes in climate and ocean dynamics. Several
recent assessments have focused on the risks of atoll island erosion and their temporary or permanent submergence
under increased wave heights and accelerated sea-level rise (SLR; Oppenheimer et al., 2019). Some authors have
suggested that these islands may become uninhabitable by 2060-90 under Representative Concentration Pathway (RCP)
8.5 due to annual flooding (e.g., Giardino et al., 2018; Storlazzi et al., 2018). Other studies have proposed that vertical
accretion of shoreline systems may limit future flooding and its consequences for settlements (e.g., Beetham &
Kench, 2018; Tuck et al., 2019).
These studies, however, generally overlook the effects of drivers other than SLR, especially changes in rainfall and
large-scale ocean–atmosphere oscillations, increasing tropical cyclone intensity, and ocean warming and acidification
(Gattuso et al., 2015; Mentaschi et al., 2017; Oppenheimer et al., 2019; Perry et al., 2018; Vitousek et al., 2017). It is the
combined effects of SLR and these drivers that control changes in island-scale reef growth, productivity and structure,
terrestrial and marine food resources, and the availability of freshwater on atoll islands. Moreover, contemporary
research also has neither adequately considered differences in climate and ocean changes between ocean basins or even
between islands (Nurse et al., 2014). Although we recognize that human factors, including socioeconomic dynamics,
human ingenuity, cultural change, population health crises, and geopolitics (e.g., Cinner et al., 2018), are also strong
drivers of risks to atoll habitability, here we focus on climate-related environmental drivers and assess the extent to
which their changes over the 21st century are likely to compromise atoll habitability.
“Atoll islands”(islands hereafter) refer to recently-formed (generally <4000 years BP), low-lying (mean elevation
generally <3 m) islands composed mostly of biologically derived carbonate sand, gravel and boulders, resting on reef
structures at or near contemporary sea level and often encircling a central lagoon (Gischler, 2016; McLean, 2011;
Woodroffe, 2008). Habitability of these islands is understood not only as “the ability of a place to support human life by
providing protection from hazards which challenge human survival, and by assuring adequate space, food and freshwa-
ter”(Weyer et al., 2019, p. 15) but also as the ability of that place to provide economic opportunities, which contribute
to health and well-being (Bennett et al., 2019; Costanza et al., 2016; Daw et al., 2015). Accordingly, the atoll island hab-
itability framework (Figure 1) presented here includes five major interrelated Habitability Pillars (HPs) that will all
experience first-order (that is, direct) climate change impacts: (1) availability of sufficient and safe land (“Land”);
(2) supply of safe freshwater, especially from local sources (“Freshwater supply”); (3) supply of nutritious food from local
2of28 DUVAT ET AL.
FIGURE 1 Conceptual model of atoll island habitability. The atoll island system comprises five pillars supported by ecosystems and
societal conditions. Interactions between these pillars are illustrated by blue arrows: For example, habitable land is critical to settlements
and infrastructure, freshwater and food supply, economic activities, and natural vegetation development; in turn, the persistence of land is
dependent on supporting ecosystems; thus the reef ecosystem provides the island with sediment and reduces wave energy reaching the
coastline. Similarly, mangrove, seagrass, and the natural strandline vegetation stabilize shoreline systems and can limit erosion and marine
flooding
DUVAT ET AL.3of28
and/or imported sources (“Food supply”); (4) access to safe settlements and infrastructure that sustains freedoms and
opportunities, such as for trade, healthcare and education (“Settlements and infrastructure”); and (5) access to sustain-
able economic activities (“Economic activities”). In accordance with the definition of the Intergovernmental Panel on
Climate Change (IPCC, 2019), risk is referred to as the potential for adverse consequences to atoll social–ecological sys-
tems from climate change, recognizing the diversity of values and objectives associated with such systems. Risk can
arise from potential impacts of climate change as well as human responses to climate change.
We evaluate the extent to which each of these HPs will be affected by future climate and ocean changes over the
21st century, thereby increasing risks to life-supporting ecosystems and living conditions. We then assess the implica-
tions for future atoll habitability, from a biophysical and environmental perspective, as well as its variability across
Indian and Pacific Oceans and across islands representing contrasting socioeconomic situations (urban/rural). Section 2
presents the Materials and Methods used. More particularly, it sheds light on HP significance, regions and islands of
interest, climate threats considered, and the expert judgment-based risk assessment protocol. Sections 3 and 4 present
the Results, based on Coupled Model Intercomparison Project (CMIP) 5 climate projections generated for RCPs 2.6 and
8.5 at 2050 and 2090. Section 3 highlights current and future threats to each HP, while Section 4 assesses the risk posed
to habitability in four contrasting case study islands. Section 5 discusses the cumulative and cascading risks driven by
climate change in atoll settings, as well as the spatial variations of risk to habitability across ocean regions and islands.
2|MATERIALS AND METHODS
This assessment relies on three main methods: a comprehensive literature review (especially using the databases Scopus
and Web of Science); CMIP5 climate projections for the Indian and Pacific Oceans; and an expert judgment approach
to evaluate the risks caused to each HP under the two most documented climate scenarios (RCPs 2.6 and 8.5) at 2050
and 2090. The overall analysis has benefited from the 10-to-30-year experience of the authors in atoll environments, in
the research fields of geomorphology, ecology, hydrogeology, climate and impact modeling, subsistence and economic
activities, development and sustainability. Two 3-day workshops in September 2019 and February 2020 allowed for both
the framing elements (HPs, geographical scope, case studies, climate scenarios and timescales; Sections 2.1–2.3) and
assessment method (including test phase; Section 2.4) to be defined. Due to COVID-19 restrictions, the expert judgment
per se, and results analysis, were conducted remotely through video-conferences from February to April 2020.
2.1 |Habitability Pillars
The HPs were identified through the literature review, including peer-reviewed scientific papers and recent IPCC
reports. This process highlighted that (1) availability of sufficient and safe land (Land); (2) supply of safe freshwater,
especially from local sources (Freshwater supply); (3) supply of nutritious food from local and/or imported sources (Food
supply); (4) access to safe settlements and infrastructure that sustains freedoms and opportunities such as for trade,
healthcare and education (Settlements and infrastructure); and (5) access to sustainable economic activities (Economic
activities) are all key to atoll habitability. These five HPs are under threat from climate change on atolls (Nurse
et al., 2014, table 29-4, p. 1635), with detrimental impacts, especially to well-being and health. These latter two compo-
nents of habitability were not explicitly included in this study as HPs because they are mainly indirect outcomes of
climate-driven changes to HPs. Impacts on well-being essentially arise from impacts on livelihoods, services and land-
scapes. Although climate change can have a direct impact on health (e.g., loss of lives from extreme events), most con-
sequences for health are expected to be indirect, for example, through increased water and food insecurity
(Lovell, 2011).
2.1.1 |Availability of sufficient and safe land
A complex combination of physical and ecological factors determines whether an atoll island is habitable or not. These
factors include: island size and the extent of safe and utilizable land area (Spennemann, 1996; Weisler, 1999); island
positional stability (Aslam & Kench, 2017; Webb & Kench, 2010); elevation of shoreline and interior, determining sus-
ceptibility to wave-driven flooding (Owen et al., 2016; Woodroffe, 2008); island shape and geomorphic components,
4of28 DUVAT ET AL.
which influence resistance to storms (Ford & Kench, 2014; Kumar et al., 2018; Spennemann, 2009); sediment composi-
tion, which influences groundwater resources and agroforestry potential; and the nature and extent of vegetation cover
(Duvat, Pillet, et al., 2020; Duvat, Volto, & Salmon, 2017). Physical processes underpinning these attributes result from
the interplay of a number of factors that vary across and within ocean basins (McLean & Kench, 2015). They include
seasonal wave regimes (Kench et al., 2017; Morgan & Kench, 2014), exposure to high energy events such as storms and
tsunami (Duvat, Salvat, & Salmon, 2017; Duvat, Volto, & Salmon, 2017; Ford & Kench, 2014, 2016; Hoeke et al., 2013;
Kench et al., 2006; Scoffin, 1993), sea-level change (Kench et al., 2014; Perry et al., 2013), reef growth and related sedi-
ment supply and trapping by mangrove, seagrass and island vegetation (Krauss et al., 2014; Perry et al., 2011).
2.1.2 |Supply of safe freshwater, especially from local sources
The contemporary resilience of atoll populations partly lies in their ability to exploit diverse water sources: rainwater
harvesting, shallow fresh groundwater lenses (FGLs), desalinated water, imported water and, in extremis, coconuts
(Falkland & White, 2020; Foale, 2003). Access to freshwater remains highly climate-dependent, as shown for example
during the severe La Niña drought in 2011 across the southwestern Pacific (Kuleshov et al., 2014; Lorrey &
Renwick, 2011) that led to freshwater shortages and national emergencies. Among water sources, FGLs play a major
role in habitability, by providing adequate water to local communities and supporting agriculture and economic activi-
ties. FGLs result from a delicate balance between rapid rainwater recharge and continuing depletion due to evapotrans-
piration, discharge of groundwater to the surrounding ocean and lagoons, tidally-driven dispersive mixing with
underlying seawater and groundwater pumping. Salinity gradients through FGLs depend on island area; sediment com-
position; recharge, discharge and pumping rates; tidal mixing; and method(s) of groundwater extraction (White &
Falkland, 2010). Islands reliant on rainwater harvesting, either because their geomorphology and size do not support a
viable FGL or because pollution or overextraction has made their FGLs unusable (Falkland & White, 2020), are most at
risk of supply failure. For some households on these islands, as little as 10 days without rain can lead to water supply
failure (Quigley et al., 2016). At the other extreme, during high rainfalls, rainwater harvesting systems and ponded
water increase risks of water-borne diseases (WHO, 2015).
2.1.3 |Supply of nutritious food from local and/or imported sources
Achieving autonomous food security has always been a challenge on atolls because of limited land area and soil quality
and high dependency on marine resources, both of which are climate-sensitive. Ad hoc and unplanned terrestrial food
production (typically breadfruit, banana patches, coconut and others) remains common, including on many urban
islands (e.g., Funafuti, Tuvalu; Nukunonu, Tokelau; South Tarawa, Kiribati), and is key to people's diet. In addition,
governments and development agencies support integrated farming practices and invest in soil management. Yet
urbanization and human population growth have reduced land availability for locally-produced fruit and vegetables
(Campbell, 2015; Connell, 2014; Connell, 2020; Thaman, 1995). Food imports (especially rice, canned meat, sugary
drinks and snacks) have therefore become commonplace in both urban and rural islands (Campbell, 2020), inducing a
“nutrition transition”to cheaper, energy-dense, nutrient-poor foods (Hughes & Lawrence, 2005; Sievert et al., 2019;
Thow et al., 2010), with a concomitant increase in risk of diet-related noncommunicable diseases. Climate change is
poised to adversely affect food systems through disruptions in the ability of countries to import and distribute food, and
of households to purchase food, with the potential to magnify food and nutrition insecurity (Savage et al., 2020).
Atoll communities have traditionally exhibited a significant dependence on fish for dietary protein and other essen-
tial micronutrients (Charlton et al., 2016). For example, average national fish consumption in Kiribati, Marshall Islands,
Tuvalu and Tokelau is five times greater than in the high islands of Melanesia (SM2.1a). Rapid population growth and
overfishing are already reducing levels of per capita fish consumption, with consequences for human health (Golden
et al., 2016; Hicks et al., 2019). There is an emerging gap in fish supply for urban atoll dwellers (Bell et al., 2011), exacer-
bated by the damage to proximal coral reef and seagrass habitats (SM2.2) and overexploitation of coastal fish stocks
(MacNeil et al., 2015; McClanahan et al., 2011; Sale et al., 2014). Climate-related declines in fish abundance and associ-
ated catches are likely to further amplify existing declines in the nutritional adequacy of diets (Golden et al., 2016).
Threats to fish supply are occurring despite availability of more than enough tuna and tuna-like species within the
Exclusive Economic Zones (EEZs) of atoll nations to satisfy domestic demand (Bell et al., 2015).
DUVAT ET AL.5of28
2.1.4 |Access to safe settlements and infrastructure that sustains freedoms and
opportunities
Owing to the comparatively small size and low elevation of atoll islands, settlements and infrastructure are all coastal
in character and therefore more exposed to climate-driven damage than many of their higher-island counterparts
(Kumar & Taylor, 2015). Risk to settlements is driven by context-specific combinations of climate-related hazards (SLR
and waves), the degree of degradation of surrounding ecosystems, and the distance to the shoreline and elevation of
buildings and infrastructure. Critical infrastructure for island habitability includes those that are key to the functioning
of the island internally (e.g., roads, fishing harbors, power and desalination plants, hydrocarbon reserves, administra-
tive buildings and services) and the ones used for connection with other islands, atolls and countries (e.g., commercial
and cruise ship harbors, regional and international airports, causeways and bridges connecting islands).
2.1.5 |Access to sustainable economic activities
Besides copra production (which is declining; Connell, 2014), atolls largely depend on fisheries, tourism, official devel-
opment assistance (ODA) and remittances for income generation. Most atoll states also have an extraordinary economic
dependence on industrial tuna fishing. The Western and Central Pacific Ocean and Indian Ocean are the world's first
and second largest tuna production areas, providing 55% and 15% of global tuna catch, respectively (Lecomte
et al., 2017; Pew, 2016). Consequently, the economies of atoll nations such as Kiribati, Tuvalu, Marshall Islands and
Tokelau have capitalized on their tuna resources and now have a particularly high dependence on tuna-fishing license
fees, deriving the majority of their government revenue in this way (Lam et al., 2020; SPC, 2019). In some atoll coun-
tries such as the Maldives, tourism represents a unique opportunity because small and dispersed land areas and remote-
ness from markets can be attractive in a niche tourism context (Cagua et al., 2014; Jiang & DeLacy, 2014;
Zimmerhackel et al., 2019). Many atoll nations also rely on ODA to bolster economic development (representing
ca. 15% of Gross National Income in Kiribati; Dornan & Pryke, 2017), and remittances from migrants working overseas
largely contribute to national incomes (14%, 11%, and 10% of GDP, respectively, in Marshall Islands, Tuvalu, and Kiri-
bati). Other activities include aquarium fisheries (e.g., Marshall Islands, French Polynesia, and Kiribati), pearl farming
(e.g., French Polynesia and Cook Islands), and subsidized copra production (e.g., Kiribati and French Polynesia). These
economic activities are highly sensitive to both climate shocks (e.g., changes in temperatures, flooding) and ecosystem
health, making the economy of atolls disproportionally vulnerable to climate change impacts.
2.2 |Regions and islands of interest
This study focuses on the two regions in which 96% of the world's atolls and the most populated atolls are located, namely
the Indian (56 atolls, according to Goldberg, 2016) and Pacific Oceans (367 atolls; Goldberg, 2016). Specifically, we assess the
exposure of atolls to climate stressors in three distinct subregions, the Central Indian Ocean, Western Pacific and Central
Pacific (Section 2.3). We also assess climate risk to habitability for four contrasting islands in the Central Indian Ocean and
Western Pacific (listed below; see SM5 for detailed description). These islands are representative of the diversity of atoll con-
texts and, with the exception of Nolhivaranfaru, Maldives, are documented and well-known by the authors. In addition, we
considered urban and rural islands to highlight variable exposure and vulnerability to climate stressors (Duvat, Magnan,
et al., 2017). Urban case studies are illustrated by Male', North Kaafu Atoll, Maldives, which is a “fortified”island, and
Fogafale (pronounced “Fongafale”), Funafuti Atoll, Tuvalu, which is flood-prone and has limited coastal protection. These
two urban islands are extreme situations thatarenotrepresentativeofatollurbanislands worldwide. They allow us however
to capture the wide spectrum of urban island situations. Rural casestudiesincludeTabiteuea, North Tarawa, Kiribati, bor-
dering the South Tarawa Urban District, and the remote island of Nolhivaranfaru, Haa Alifu-Noonu Atoll, Maldives.
2.3 |Climate stressors
The scientific literature, including recently released IPCC reports (IPCC, 2018, 2019) and peer-reviewed papers,
allowed identification of the major climate stressors affecting the HPs considered in this study. These include
6of28 DUVAT ET AL.
slow onset climate changes (in atmospheric temperatures and rainfall patterns), slow onset ocean changes
(in sea level, sea surface temperatures [SST] and ocean acidification), and changes in extreme events, especially
tropical cyclones, El Niño/La Niña events, marine heat waves and distance-source waves. Using these stressors,
we generated CMIP5 projections to estimate the exposure of each abovementioned subregion to climate change-
related risk (Section 3.1, SM3). These projections also served as starting points to assess climate risk to island
habitability (Section 4).
CMIP5 data (Taylor et al., 2012) show how the magnitudes of SLR, SST, rainfall, ocean pH and aragonite satura-
tion, ENSO and tropical cyclones will influence the five HPs. All vary (1) under two contrasting greenhouse gas
(GHG) emission scenarios, that is, RCP2.6 representing a strong mitigation scenario and RCP8.5 assuming continued
acceleration of GHGs emissions; and (2) at two time horizons, 2050 and 2090. The abovementioned stressors were
aggregated into a cumulative exposure index for each RCP scenario, timespan and subregion, following a three-step
approach: selection of the mean, minimum and maximum value for each parameter (SM3.1) from future projections,
and regional baseline values; development of a scoring system by subregion (SM_File 2_SM3); and establishment of
index scores (SM3.2).
2.4 |Risk assessment protocol
2.4.1 |Expert judgment and scoring system
The expert judgment-based assessment of the risk posed to habitability by climate change relied on an extensive litera-
ture review (including especially case study papers), available datasets, and the authors' own expertise. It followed a six-
step approach (Figure 2; SM4). Briefly, the protocol consisted of defining a set of prominent criteria contributing to risk
for each HP and in each of the four case studies considered (Step 1); as well as a scoring system to assess the additional
climate risks to each criterion under RCP2.6 and RCP8.5, and for 2050 and 2090 (Step 2, SM7). Six risk levels were con-
sidered: undetectable, very low, low, moderate, high, very high (Table SM4b). For each HP, between two and four of
the authors conducted a separate assessment for the criteria (first round of scoring), shared their respective scores, and
then convened (virtually) to discuss differences in assigned scores. Differences in scoring were discussed with special
attention paid to the rationale supporting scoring. Discussions allowed the collective refining of scores and arrival at a
final score (second round of scoring) and its consistency with the underlying rationale. Most first round scores were
convergent. Where differences in initial scores arose, these mainly resulted from differences in case study-oriented
knowledge and/or from differences in understanding of the underlying rationale. Discussing scores, and the related
rationale, therefore led to the strengthening of the description of case studies (SM5, SM7). Knowledge gaps are reflected
in the confidence levels which were attributed to each score (Step 3). The aggregation of scores for each HP (Step 4)
allowed identification of climate risk to island habitability as a whole (Step 5). The results were then translated into a
color scale to develop synthesis figures of climate risk to habitability across HPs and case studies (Step 6; Figures 5
and 6).
2.4.2 |Adaptation assumptions
We assume that, over the timeframe of analysis, future adaptation responses in urban and rural islands will
remain similar in nature and magnitude to currently observed responses. Two main reasons support this argu-
ment. First, because atoll communities have adapted to climate stress for centuries to millennia (Nunn, 2007),
and still implement climate risk reduction actions, we excluded the “no adaptation”scenario (Section 3.2). Sec-
ond, due to a lack of precise and empirically-based information on the extent and nature of adaptation limits in
atolls (Mechler et al., 2020; Roy et al., 2018), especially across the diversity of case study settings chosen, we did
not consider a “high adaptation”scenario involving more transformational changes. We therefore assume the con-
tinuation of the current level of adaptation measures, that is, moderate adaptation, which is considered feasible
and helps the understanding of risk under a nontransformational adaptation pathway. This adaptation scenario
considers mechanisms already implemented on the ground, including water desalination (to counter water stress),
remittances from islanders working abroad, food imports (which help compensate for the decline in locally-
DUVAT ET AL.7of28
FIGURE 2 Assessment protocol used in this study. See SM4 for further details
8of28 DUVAT ET AL.
produced food), hard protection to contain coastal erosion and flooding, and, in the Pacific Ocean, emerging tuna
fishing governance arrangements between countries. In the absence of local-scale modeling studies, our adapta-
tion assumptions do not consider exogenous parameters such as, in the tourism sector for example, the effect of
climate policy on international transportation or the ability for local operators to adapt to changing circum-
stances, including COVID-19 impacts.
3|CURRENT AND FUTURE CLIMATE THREATS TO HABITABILITY
PILLARS
3.1 |Climate projections
The mean rate of global SLR for 2006–2015 was 3.6 mm year
−1
(IPCC, 2019). Under RCP2.6, mean rates of 4.5 and
4.8 mm year
−1
are projected for 2050 for the Central Indian and Western Pacific Oceans respectively, and 4.6 and
5.1 mm year
−1
for 2090 (Figure 3, SM3). Under RCP 8.5, mean rates by region are 7.6 and 8.2 mm year
−1
for 2050,
and 15.0 and 15.4 mm year
−1
for 2090, respectively. SLR is projected to increase water depths above reefs surrounding
many islands (Perry et al., 2018), meaning that higher waves will reach shorelines, amplifying flooding frequency and
rates of shoreline erosion.
For SST, there is little projected change between 2050 and 2090 under RCP2.6 (Figure 3). Under RCP8.5, projected
SST increases from 2050 to 2090 by around 1.5C, likely increasing the frequency and magnitude of marine heat waves
(Dalton et al., 2020; Frölicher et al., 2018) and pushing mean SST levels above local coral bleaching thresholds more fre-
quently in all regions, except the Central Pacific (Figure 3). This is consistent with projections for the onset of annual
bleaching by ca. 2040 in Kiribati, Marshall Islands, Tokelau and Tuvalu in the Pacific Ocean, and in the Maldives (van
Hooidonk et al., 2016).
Rainfall projections indicate overall positive changes within ±10of the equatorial Pacific and northern Indian
Oceans (Figure 3). While under RCP2.6 small increases are projected for 2050 and 2090, larger (6% or more) positive
increases are projected under RCP8.5, especially for the Western Pacific. No decrease in annual rainfall is projected for
any of the emission scenarios considered. Mean rainfall change is therefore regarded as a minor driver in this assess-
ment. In contrast, projections suggest that the frequency of intense droughts may double over the course of the 21st
century (IPCC, 2019).
IPCC (2019) also finds that the frequency of extreme ENSO events will double under both RCP2.6 and RCP8.5 in
the 21st century, with the average frequency increasing from once every two decades to once per decade (Cai
et al., 2015; Cai et al., 2018; Cai, Borlace, et al., 2014). Extreme Indian Ocean Dipole (IOD) events are also projected to
increase in frequency (Cai, Santoso, et al., 2014). In nonequatorial atoll regions, the proportion of high-intensity tropical
cyclones is projected to increase whereas the total number of cyclones is expected to remain the same or decrease
slightly (Knutson et al., 2019; Murakami et al., 2020). Analysis of cyclones globally over the past 39 years has shown a
significant increase in intensity but in the northern Indian Ocean, equatorial and southern Pacific Ocean changes in
intensity have not been significant (p> 0.1). Increased wind speeds in the Southern Ocean and tropical Eastern Pacific
are projected to increase wave heights (Morim et al., 2018, 2019) and thus raise the potential for long period swell waves
to impact distant atoll islands.
Regarding ocean acidification, under RCP2.6 pH and aragonite saturation rate are projected to continue to fall until
2050 in the three subregions and revert to slightly higher values between 2050 and 2090 (Figure 3). Under RCP8.5, both
pH and the aragonite saturation rate (Ω
a
) continue to fall between 2050 and 2090, reaching Ω
a
values of <2.5 by 2090,
that is, below the typical values found in coral reef waters (Kleypas et al., 1999).
These projections provide a basis for assessing the cumulative exposure of each subregion (Figure 4; SM3.2).
Our assessment suggests low overall levels of increased exposure under RCP2.6 but increased SST stress in the
Central Indian Ocean, with a significantly increased cumulative exposure to climate stressors to at least 2090
under RCP8.5. Under RCP8.5, changing ocean chemistry conditions will be the most sustained drivers of this
increased exposure. The combination of risks generated by SLR and changes in SST will become significant
between 2050 and 2090 and will almost certainly be further exacerbated in most regions by increased cyclone
intensity, and in all regions by increased frequency of intense ENSO and IOD events (Figures 3 and 4
and SM3).
DUVAT ET AL.9of28
a
(a)
(b)
(c)
(d)
(e)
FIGURE 3 Projected changes in relevant climate change-driven ocean and atmospheric parameters within different atoll regions for
each emissions scenario in 2050 and 2090. Plots a–e show upper, mean and lower limit projected changes in each parameter under RCP2.6
and RCP8.5 in 2050 and 2090 for each atoll subregion (see also SM3.1). The threshold levels (gray bars) denote the following: for sea level
trend, the mean rate of global sea-level rise (3.6 mm year
−1
) between 2006 and 2015 (IPCC, 2019); for SST trends, regional bleaching
thresholds (from NOAA Coral Reef Watch, 2001–2020 time series data); for Aragonite Saturation State trends, the threshold below which
conditions for tropical reef-building corals are deemed to be “extremely marginal”(Guinotte et al., 2003); for surface pH, the mean surface
pH in tropical regions during the period 1980–2000 (IPCC, 2014, fig. 30.7)
10 of 28 DUVAT ET AL.
3.2 |Literature-based perspective on threats to Habitability Pillars
3.2.1 |Land (HP1)
A review of shoreline change of 709 Indo-Pacific atoll islands over the past 3–5 decades found no widespread trend in
land area change for larger (>10 ha) habitable islands (Duvat, 2019), indicating shoreline resilience in the face of recent
climate-driven changes. Nevertheless, the low elevation and permeable structure of all islands expose them to
overtopping-induced flooding, marginal breaching and/or saltwater intrusion (Canavesio, 2019; Hoeke et al., 2013;
Wadey et al., 2017). The likelihood of island flooding associated with extreme sea levels arises from a combination of
factors (regional sea-level, storm frequency variations, wave climate changes) and operates over multiple spatial–
temporal scales (Chand et al., 2013; Walsh et al., 2012). Major contributors are distant ocean waves that reach the
shorelines of atolls, resulting in enhanced wave setup and runup, overtopping of berms and protection structures, and
inundation of island interiors.
aaa
aaa
(a)
(b)
FIGURE 4 Cumulative climate change threats and related exposure of atoll regions, for two emission scenarios in 2050 and 2090, based
on mean projected rates of change. SM3.1 provides the full details. Panel a illustrates the cumulative climate and climate-related ocean
threats (high = 1.0, low = 0.0) to atoll habitability for each of the three delineated atoll regions. Panel b shows resultant cumulative exposure
index for each RCP scenario and atoll region. The index is described in SM3.2. The color graduation represents increasing exposure levels
from low (white to light blue) to high (deep blue)
DUVAT ET AL.11 of 28
Direct impacts of climate-ocean changes will result from extreme wave energy (from tropical cyclones and distant
storms) altering shorelines, while indirect effects will come from changes in the ecological make-up and structural com-
plexity of reefs (Harris et al., 2018; Perry et al., 2011; Quataert et al., 2015), and in the extent and health of mangroves
(Schuerch et al., 2018) and seagrasses, as well as terrestrial vegetation (Hernandez-Delgado, 2015). Changes affecting
reefs will limit their capacity to keep pace with SLR (Perry et al., 2018), attenuate wave energy, and contribute to sedi-
ment supply to islands. Increased frequency and intensity of coral bleaching events and increased ocean acidification
will be the most immediate drivers of such changes (Frölicher et al., 2018; Perry et al., 2018). Precisely how the former
will impact reef sediment generation is unclear, although short-term pulses of enhanced sediment generation have been
observed after bleaching events (Kayanne et al., 2016; Perry et al., 2020). Likewise, the implications of pH and aragonite
declines on sediment generation rates are poorly known. Despite these uncertainties, under RCP8.5 from 2050, the
accumulation of threats to reefs will severely exacerbate island flooding, as a result of SLR and reef erosion, leading to
island destabilization through increased wave impact on shorelines and a net reduction in sediment supply to islands
(Beetham et al., 2017; East et al., 2020; Shope et al., 2017; Shope & Storlazzi, 2019; Storlazzi et al., 2018). Decreased sed-
iment supply would in turn compromise the ability of mangrove substrates to keep pace with SLR (Lovelock
et al., 2015).
In densely settled areas, human constructions will increasingly compromise the natural ability of island shorelines
to vertically adjust to SLR by altering reef productivity, obstructing alongshore and cross-shore sediment transport path-
ways, and reducing the coastal accommodation space available for landform adjustment, including opportunities for
the landward migration of coastal habitats (Duvat & Magnan, 2019; McLean & Kench, 2015; Schuerch et al., 2018). If
pathways of in situ adaptation continue to be followed, this will make atolls increasingly dependent on protection struc-
tures, aimed at limiting shoreline erosion and flooding (Hinkel et al., 2018; Naylor, 2015; Wadey et al., 2017), and possi-
bly island raising (e.g., Hulhumale', Maldives; Brown et al., 2020).
3.2.2 |Freshwater supply (HP2)
Mean annual and wet-season rainfall are projected to increase across the equatorial Eastern and Central Pacific in the
20-year periods centered on 2050 and 2090 (relative to 1986–2005) but there is little change expected further from the
equator (ABoM and CSIRO, 2014) (Figures 3 and 4). The frequency and intensity of extreme rainfall events are projec-
ted to increase across the Western and Central Pacific, but their magnitude is uncertain (ABoM and CSIRO, 2014). Pro-
jected increases in frequency of the 1-in-20 year daily rainfall (baseline 1985–2005) for RCP2.6 and RCP8.5 are location-
specific, with doubling frequency for RCP2.6 (ABoM and CSIRO, 2014). The low confidence in the magnitudes of these
projected changes hinders the quantification of their impacts on freshwater supply, particularly as there are no compa-
rable projections for evapotranspiration (Falkland & White, 2020). Qualitatively, these intensifications suggest increased
local flooding as groundwater rises to the surface, increased pollution of FGLs (Falkland & White, 2020) and polluted
discharge onto surrounding reefs (Graham et al., 2018), with cascading negative impacts on shoreline protection, sedi-
ment supply, food production and health (UNICEF and WHO, 2019; White et al., 2007; WHO, 2015).
Increased frequency (and intensity under RCP8.5) of major ENSO and IOD events may challenge water security,
especially for rainwater harvesting on urban atolls. Modeling shows that, when there is no land area loss, the store of
freshwater increases slightly with SLR up to 0.4 m, as groundwater moves up from karst limestone basements into over-
lying unconsolidated Holocene sediments (Alam & Falkland, 1997; Galvis-Rodriguez et al., 2017). This magnitude of
SLR is comparable to sea-level differences experienced during major ENSO events (Widlansky et al., 2017) and to SLR
projected under RCP2.6 to 2090 (ABoM and CSIRO, 2014). With SLR rates of 15 mm year
−1
projected for RCP8.5 at
2090 (ABoM and CSIRO, 2014), land area loss could reduce groundwater availability by over 70% by 2090 (e.g., South
Tarawa; Alam & Falkland, 1997). Likewise, in the Maldives, islands narrower than 200 m are expected to experience
drastic reductions of their FGLs from the combined effects of variable rainfall patterns and SLR (Deng & Bailey, 2017).
More frequent island overtopping will cause salinization of FGLs (Burns, 2002; Hughes et al., 2020; Storlazzi
et al., 2018). Experiences in the Pacific and Indian Oceans and overwash modeling suggest that FGL recovery takes
between 1 and 5 years (Bailey, 2015; Bailey & Jenson, 2014; Chui & Terry, 2015). The implication is that alternative
sources of water will be needed during periods of FGL recovery.
Since projected increases in annual rainfall are relatively small, future freshwater security in atolls will depend sig-
nificantly on changes in the frequency and intensity of ENSO and IOD events, the intensity of cyclones and accompany-
ing storm surges (Chui & Terry, 2013), as well as the ability of habitable islands to build vertically to adjust to SLR.
12 of 28 DUVAT ET AL.
However, at least until 2030, nonclimate-change factors, including increasing freshwater demand, urbanization, water
pollution, governance and management failures, are expected to pose greater threats to freshwater security than climate
change (Falkland, 2011).
3.2.3 |Food supply (HP3)
Rapid population growth (3.2.4), urbanization and overfishing of coastal stocks will continue compounding food secu-
rity challenges by reducing land availability for agriculture and levels of per capita fish consumption, respectively
(SM2.3). These challenges will be exacerbated by projected declines in coastal fish abundance and catches in relevant
subregions (Asch et al., 2018; Bell, Allain, et al., 2018). For reef fisheries, recent coral bleaching and mortality
(e.g., Hughes et al., 2018), and resultant reef structural collapse, have led to declines in commonly targeted fish species
(Robinson, Wilson, Jennings, & Graham, 2019).
Minimizing the gap in fish supply is achievable through adequate protection (and restoration) of coral reef and
seagrass habitats (Brodie et al., 2020), improved management of coastal fish stocks (Bell, Allain, et al., 2018), increases
in the catch of tuna and tuna-like species from nearshore waters (e.g., Maldives; Yadav et al., 2019), as well as by pro-
viding greater access afforded to offshore tuna and tuna-like species for domestic consumption (Bell et al., 2015; FFA &
SPC, 2015). For Pacific atolls, expanding the use of nearshore fish aggregating devices (FADs) would increase supplies
of tuna for local food security (Bell, Allain, et al., 2018) (SM2.4). Filling the gap in fish supply is all the more crucial
given that climate-driven changes to soil moisture and salinization levels, rainfall and land area will increasingly con-
strain food production on atolls (Barkey & Bailey, 2017; Taylor et al., 2016).
Ocean warming and acidification are expected to significantly reduce live coral cover (Hoegh-Guldberg et al., 2011).
Although increased CO
2
concentrations should promote growth of seagrasses, on balance, climate change is likely to
continue to reduce this important fish habitat within atoll lagoons (Waycott et al., 2011) (SM2.5). Together, these effects
and the direct impact of ocean warming on coastal fish species are projected to reduce coastal fish stocks by 20%–50%
by 2050 (Asch et al., 2018; Pratchett et al., 2011, 2014). Degraded coral reefs may, however, support higher catches of
fast-growing herbivorous fish species (Pratchett et al., 2011), helping offset predicted declines in productivity of other
coastal fish species (Robinson, Wilson, Robinson, et al., 2019) (SM2.6). Climate change risks to coastal fish productivity,
exacerbated by inadequate management, are of particular concern for rural communities (Thow & Snowdon, 2010)
(SM2.1.b, SM2.3).
Climate change will also alter the distribution of tuna in both the Pacific and Indian Oceans (Bell et al., 2016; Bell,
Cisneros-Montemayor, et al., 2018). This is unlikely to affect plans to assist communities to catch more tuna around
FADs because, even under RCP8.5 in 2050, a large biomass of tuna is still expected to exist within atoll nations' EEZs
(Bell, Allain, et al., 2018). Projected decreases in tuna biomass in Marshall Islands, Tokelau and Tuvalu (SPC, 2019) will
necessitate allocation of a higher proportion of their (reduced) tuna resources to domestic consumption.
3.2.4 |Settlements and infrastructure (HP4)
In 2017, 676,000 people were living in the Maldives, Kiribati, Marshall Islands, Tuamotu-Gambier, Tuvalu, FSM and
Tokelau (SM1). Together, these archipelagoes have experienced a 68% population increase since the mid-1980s, with
the main growth observed in the Maldives and Kiribati (SM1a). Urban/capital islands are home to most people, as a
consequence of better services and infrastructure, higher life expectancy and rural exodus (Duvat et al., 2013; Speelman
et al., 2017; Yamano et al., 2007). For example, in 2017, 49% of the 114,160 I-Kiribati were living in South Tarawa (<2%
of the country's land area), and in 2016, 32% of the 402,000 Maldivians were concentrated on Male' (<1% of the coun-
try's land area). This resulted in high population densities ranging from 1354 persons km
−2
on Rangiroa (Tuamotu) to
65,697 persons km
−2
on Male'.
On these islands, limited available land area forces the settlement of risk-prone areas, further increasing population
exposure to environmental hazards (Duvat, Magnan, et al., 2017). For atoll nations as a whole, Kumar and Taylor (2015)
estimated that 90% of built assets are located <100 m from the shoreline. On the capital islands of Rangiroa and Funa-
futi, land constraints have led to settlement in marginal low-lying areas, amplifying population exposure to flooding
(Duvat, Stahl, et al., 2020; Magnan, Ranché, et al., 2019; Yamano et al., 2007). The expansion of Male' through land
DUVAT ET AL.13 of 28
reclamation (+67% since the 1970s, mostly <1 m above Mean Sea Level) has also increased the exposure of people and
urban assets to sea-level extremes (Naylor, 2015).
About 59% and 61% of the populations of Tuvalu and the Marshall Islands, respectively, currently live on land below
annual flood levels. These proportions will increase by about 10% and 27%, respectively, in the case of a 1 m SLR by
2100 (Kulp & Strauss, 2019). On Ebeye, Kwajalein Atoll, Marshall Islands, the population annually affected by flooding
and erosion will increase from 5000 persons (>50% of its population) to 8800 (10,800) under RCP2.6 (RCP8.5) by 2100;
and Expected Annual Damages (EAD) to buildings and infrastructure are projected to increase 2.4–3.8 times by 2100
(Giardino et al., 2018).
Estimating future threats to settlements and infrastructure on atolls for the 21st century is challenging because of a
lack of knowledge of the influence of human drivers of exposure and vulnerability. In Tuvalu, migration flows have the
potential to slow population growth by the mid-century, from 3700 additional inhabitants if no out-migration occurs
against 320 inhabitants with substantial emigration (Milan et al., 2016). Future risk to settlements and infrastructure
will also depend on the effectiveness and sustainability of responses (Nunn & Kumar, 2018). On Ebeye, hard defenses
have the potential to reduce end-century flooding/erosion-induced EAD by 30%, and the annually affected population
by 40% (Giardino et al., 2018). Likewise, building seawalls 0.5, 1.0, and 1.5 m high could delay flooding for 0.2, 0.4, and
0.6 m of SLR respectively on the raised island of Hulhumale', Maldives, (Brown et al., 2020). Future threats to settle-
ments and infrastructure will also depend on efforts made to accommodate sea-level rise, including for example floor
raising (e.g., Tuamotu; Magnan, Ranché, et al., 2019).
3.2.5 |Economic activities (HP5)
In 2016, revenues derived from tuna-fishing license fees contributed 60%–98% of all (nonaid) government revenue to
Kiribati, Tuvalu, Marshall Islands and Tokelau (FFA, 2017). Overall, climate-driven redistribution of tuna is expected
to have greater effects on the economies of Pacific Ocean than Indian Ocean atolls (Bell et al., 2016; Bell, Allain,
et al., 2018). Under RCP8.5, by 2050, tuna biomass in national waters is projected to decrease by 15% in Marshall
Islands and 9% in Tuvalu and Tokelau, and to increase by 18% in Kiribati (SPC, 2019). Proportional decreases and
increases in tuna license revenue are expected to occur.
Together with other Pacific Island countries that are Parties to the Nauru Agreement (PNA), Kiribati, Marshall
Islands, Tokelau and Tuvalu have responded to climate variability and change through the “vessel day scheme”(VDS),
which enables the benefits of purse-seine fishing within their combined EEZs to be distributed equitably among them,
regardless of where the fish are caught (Aqorau et al., 2018; Johnson et al., 2020). Nevertheless, under RCP8.5 by 2050,
tuna biomass within the combined EEZs of PNA members is likely to decrease because conditions for tuna will become
more favorable further east in high-seas areas (SPC, 2019). This will necessitate new management arrangements and
could potentially set the stage for conflict between tuna-fishing nations (Pinsky et al., 2018).
Tourism grew in the Maldives between 1995 and 2017 from 315,000 international arrivals and US$211 million in
tourism receipts to 1.4 million and US$2742 million, respectively. In 2017, tourism accounted for 23% of GDP and 32%
of government revenue (Ministry of Tourism, 2018). While Pacific atoll nations are less likely to benefit from positive
visitor projections (World Bank, 2017) due to less developed tourism assets, FSM, Marshall Islands, Kiribati, and Tuvalu
are well placed to capitalize on nature-based experiences (e.g., diving, sport-fishing). Atoll tourism is assumed to be as
much at risk as in coastal areas elsewhere, where it relies on beach and marine activities (Bindoff et al., 2019;
Fauzel, 2019; Klint et al., 2015; Seetanah & Fauzel, 2019; van der Veeken et al., 2015). SLR, warmer SSTs and extreme
events are likely to affect tourism through damage to essential infrastructure (UNFCCC, 2005), loss of beaches and
coral bleaching (Koike et al., 2014; Weatherdon et al., 2016; Wielgus et al., 2002). Future COVID-like crises are likely to
affect tourism revenues through the reduction of world travel (Filho et al., 2020; Moosa et al., 2020). For example, due
to the COVID-19 crisis, the total revenue of the Maldivian government is “expected to fall by 49% in 2020, a drop of
approximately US$1 billion. With the increased spending to mitigate COVID-19 impact, the budget deficit for 2020 is
projected to reach $841 million”(UNDP & Ministry of Economic Development, 2020, p. 12).
ODA allocations to atoll nations have declined over the past decade (OECD, 2015). While commitments in climate
finance to Small Island Developing States have been made, current climate finance models may not be appropriate or large
enough to meet needs, and lack the required governance to effectively support resilience and promote sustainable develop-
ment (Williams & McDuie-Ra, 2018). The role of remittances for increased household resilience, and to finance adaptation,
could increase in importance if other income sources decline and externally-provided climate finance is insufficient
14 of 28 DUVAT ET AL.
(Bendandi & Pauw, 2016; Musah-Surugu et al., 2018; Nunn & Kumar, 2019). Remittances may also help limit rural exodus
and international migration attributable to climate change (Damette & Gittard, 2017). However, falling remittances as a
result of crises such as the current COVID-19 pandemic (IMF, 2020) may have profound and unforeseen economic impacts.
4|ASSESSMENT OF CLIMATE RISK TO FUTURE HABITABILITY IN FOUR
ATOLL ISLANDS
4.1 |Risk by Habitability Pillar
Risk to land (HP1, SM7.1) includes net coastal erosion, and permanent and temporary marine flooding. This risk is
estimated very low-to-low for all four islands in 2050 under RCP2.6, except for Fogafale which shows a low-to-moderate
risk due to its high susceptibility to flooding (Figure 5). By 2090 under RCP2.6, this risk increases to low-to-moderate
for Male', moderate for Nolhivaranfaru and Tabiteuea, and high for Fogafale. While there is a relatively small difference
in risk level between RCP2.6 and RCP8.5 in 2050, the risk to land increases substantially under RCP8.5 in 2090 com-
pared to RCP2.6, and is high for Nolhivaranfaru, high-to-very high for Male' and Tabiteuea, and very high for Fogafale.
This is due to sea-level projections diverging between low and high emission scenarios after 2050 only. Differences in
risk level are generally small between rural islands, but high between urban islands. Male' exhibits lower risk than
Fogafale, owing to its higher elevation and complete protection by engineered structures, while Fogafale is both
extremely low-lying and mostly unprotected.
Risk to freshwater supply (HP2, SM7.2) includes groundwater salinization/loss and decrease in rainwater
harvesting and desalination. This risk is estimated as undetectable in 2050 under RCP2.6 for all islands, except for
Fogafale where the predominant source of freshwater, rainwater harvesting, will likely be disrupted by increased
cyclone-driven damage and drought frequency (Figure 5). While risk remains undetectable-to-very low in Male' under
both RCPs even in 2090 –because the island mainly relies on desalination –it increases slightly under RCP2.6 in 2090
in Nolhivaranfaru and Tabiteauea (to very low-to-low and very low, respectively) and, more in Fogafale (to low-to-mod-
erate). This increase is even more important under RCP8.5 in 2090 (moderate for Nolhivaranfaru; low-to-moderate for
Tabiteuea; moderate-to-high for Fogafale). Fogafale exhibits the highest risk level because of its main reliance on rain-
water harvesting which will be increasingly affected by droughts, cyclones, and flooding-induced damage over time. On
rural islands, risk becomes significant under RCP8.5 in 2090.
Risk to food supply (HP3, SM7.3) includes reduced reef fish production, redistribution of tuna and reduced
production of crops and livestock. This risk is assessed as very low for all islands under RCP2.6 in 2050 (Figure 5).
Differences between islands are pronounced in 2090 under both RCP2.6 (slightly above very low-to-low for Male', low-
to-moderate for Nolhivaranfaru, moderate for Fogafale and Tabiteuea) and RCP8.5 (from moderate to high, except for
Male' where it remains very low-to-low). The lower risk level for Male' is due to the relatively low dependence of house-
holds on local food compared to imports; these are assumed to increase over time to compensate for decreasing tuna
catches. The comparatively higher risk level for Fogafale results from the cumulative effects of decreased reef fish (60%
of total catches in Tuvalu) and tuna catches, and a reduction in agricultural and livestock productivity due to marine
flooding. In all cases, food imports are likely to increase to compensate for decreased local-to-national food production,
especially in the second half of this century.
Risk to settlements and infrastructure (HP4, SM7.4) includes loss of settlements, critical infrastructure and
transport connectivity. Since this risk is strongly influenced by risk to Land, risk levels partly reflect those of Land,
being very low-to-low under RCP2.6 in 2050, except for Fogafale (close to high); and low-to-moderate for
Nolhivaranfaru and Tabiteuea, moderate-to-high for Male' and very high for Fogafale under RCP2.6 in 2090 (Figure 5).
Mid-century and end-century risk levels are thus higher in Fogafale compared to other settings, as a result of both the
higher exposure of settlements and critical infrastructure to coastal risks (especially flooding) and the reduced extent
and effectiveness of protection structures. In contrast, because it is protected by its encircling engineered structures,
Male' exhibits very low-to-low risk under RCPs 2.6 and 8.5, respectively, in 2050. Since the effectiveness of coastal pro-
tection decreases over time under SLR and increased wave height (e.g., Brown et al., 2020; Giardino et al., 2018), risk to
settlements and infrastructure increases to moderate-to-high and high-to-very high respectively under both RCP2.6 and
RCP8.5 in 2090. Under RCP2.6 in 2090, risk levels are lower in rural islands compared to Male' because they exhibit
lower exposure of settlements and infrastructure compared to urban settings.
DUVAT ET AL.15 of 28
FIGURE 5 Additional climate risks to the five habitability pillars for four atoll islands in the central Indian and Western Pacific oceans.
“Additional”means additional risk to habitability compared to a present-day baseline. See Part II of the Supplementary Material for details
on the assessment method and results
16 of 28 DUVAT ET AL.
Risk to economic activities (HP5, SM7.5) includes declines in tuna fisheries and tourism revenues (especially in
the Maldives for the latter), and other revenue generating activities (e.g., aquaculture). This risk, which is highly
influenced by risks to Land and Food supply, is at most very low and at most low under RCP2.6 and RCP8.5 in 2050,
respectively, with higher levels on urban islands where these activities are more common (Figure 5). Consequently,
end-of-century risk to economic activities under RCP8.5 reaches much higher levels for urban islands (high for Fogafale
and high-to-very high for Male') compared to rural islands (moderate for Nolhivaranfaru and moderate-to-high for
Tabiteuea).
These findings firstly highlight that Freshwater supply (HP2), where use of desalination is always an option, is less
threatened by climate change than the other HPs. Conversely, Land (HP1) is at high risk from climate change impacts.
This risk cascades down to land-based Food supply (HP3), Settlements and infrastructure (HP4), and land-based Eco-
nomic activities (HP5). Second, risks are commonly very-low-to-low (in 2050) to moderate (in 2090) under RCP2.6 for
most HPs. Risks increase significantly between 2050 and 2090 under RCP8.5, from generally low classifications to mod-
erate or very high risk for most HPs and islands. Third, even the best protected urban island (Male'), with estimates of
undetectable to at most moderate risk under RCP 2.6 both in 2050 and 2090, faces high-to-very high risk under RCP8.5
in 2090 for Land (HP1), Settlements and infrastructure (HP4), as well as Economic activities (HP5).
4.2 |Cumulative risk
Aggregated risk levels (i.e., cross-HP; Figure 6) are relatively comparable for Male' and the two rural islands under both
RCP2.6 and RCP8.5 for both time horizons, with a slightly higher risk level for rural islands under RCP8.5 in 2090. In
comparison, Fogafale exhibits much higher risk levels under both RCPs and at both time markers, due to its exception-
ally flood-prone nature and exposure to other risks, especially related to Food supply (tuna fishing) and Land, with cas-
cading impacts to the three other HPs. Generally, the aggregated risk remains close to low-to-moderate under RCP2.6
in 2090 for rural islands having no or limited coastal protection structures, increasing to relatively high risk under
RCP8.5 in 2090. This is mainly because rural areas are more dependent on local resources and may be less able to offset
impacts through imports (for Food supply) or technology (for Freshwater supply) compared to urban islands. Finally,
this assessment shows that even a well-protected urban island like Male' will experience moderate-to-high additional
risk under RCP8.5 in 2090, suggesting limits to future reliance on the current heavily engineered adaptation strategy.
5|DISCUSSION
Our findings first highlight that climate change-related risk in atoll settings is driven by the cumulative and cascading
effects of a large set of climate stressors on HPs. Taken together, SLR, extreme ENSO events, storm wave height, and
coral reef degradation will cause major environmental changes on atolls from 2050 onwards under both RCP2.6 and
RCP 8.5. Expected changes include shoreline erosion and increased flooding of island interiors (threats to Land), poten-
tially leading to physical destabilization of islands, with multiple direct (e.g., through the deterioration of soil and FGL
quality, disruption of economic activities) and indirect (e.g., through the effects of decreased FGL quality on land-based
food production) cascading impacts on other HPs. Also, the declines in coastal fish stocks (and tuna and tuna-like spe-
cies' biomass within the EEZs of Western Pacific nations from 2050 onwards) will significantly reduce locally-sourced
fish supply. Therefore, climate risk to habitability is driven by multiple, interrelated climate stressors, where their addi-
tive effect will challenge the adaptation capacity of atolls.
Second, this study shows that climate risk to habitability will vary significantly between and within ocean basins,
irrespective of the climate scenario and timescale considered. Risk will be highest in the Western Pacific. For example,
Tuvalu is projected to experience (1) a high threat to Land, resulting from the cumulative effects of the highest SLR
rates in atoll regions (5.1 and 15.4 mm year
−1
in 2090 under RCP2.6 and RCP8.5, respectively), and increased tropical
cyclone and distant-source wave height; (2) a high threat to both Freshwater supply and land-based Food supply, as a
result of increased flooding and frequency of intense droughts; (3) the negative impacts of increased SST and ocean
acidification on nearshore habitats which will reduce reef-dependent fish stocks and contribute to Land destabilization,
through reef degradation and ensuing erosion; and (4) a decrease in tuna and tuna-like resources, which will further
impact Food supply from local sources. The Central Pacific (e.g., French Polynesia) is expected to be less subject to cli-
mate risk, as a result of (1) a lower increase in SST and extreme tropical cyclones having more limited impacts on the
DUVAT ET AL.17 of 28
reef ecosystem and therefore on Land and land-dependent HPs, as well as on reef-based Food supply, at least until
2050; and (2) an increase in tuna and tuna-like species in EEZs, which may offset the expected decrease in reef fish.
Risk accumulation will also occur, but at a lower rate, in the Central Indian Ocean compared to the Western Pacific.
However, the Maldives are projected to experience (1) increased Land destabilization (exacerbated by the small size of
most islands), as a result of the combination of relatively high rates of SLR (4.6 and 15.0 mm year
−1
in 2090 under
RCP2.6 and RCP8.5, respectively) and increased distant-source wave height (which will increase erosion and flooding)
with the highest SST values (under both RCP2.6 and RCP8.5 in 2050 and 2090) and increased frequency of extreme El
(e.g.,
(e.g.,
(e.g.,
(e.g.,
FIGURE 6 Aggregated additional climate risk to habitability for four atoll islands in the central Indian and Western Pacific oceans. See
especially SM8 for details on the method
18 of 28 DUVAT ET AL.
Niño events (which will destabilize islands through reef degradation); (2) the negative impacts of decline in marine eco-
systems and Land destabilization on all HPs.
Third, this study highlights marked variations in climate risk to habitability across islands, depending on both their
geomorphology (especially size, elevation, and exposure to storms) and the effects of human activities on shoreline and
island stability. This is illustrated by the comparative analysis of future risk in Fogafale, emblematic of the cumulative
and destabilizing effects of climate change and human activities, and Male', where encircling engineered structures are
expected to reduce climate risk at least until 2050. Contrasts between rural islands are much lower due to limited
human intervention in shoreline and island dynamics. Furthermore, our assessment shows that aggregated risk levels
for rural islands are (1) lower in 2050 under both RCP2.6 and RCP8.5 compared to urban islands, especially Fogafale
(Figure 6); and (2) higher than in Male' in 2090 under both RCP2.6 and RCP8.5. This is due to the increased degrada-
tion of ecosystems and natural resources over time, which will challenge the capacities of rural islands to offset losses
through imports (for food supply) and technology (for freshwater supply and shoreline stabilization), under the moder-
ate adaptation scenario considered.
6|CONCLUSION
This study introduces a new perspective on climate risk to future atoll island habitability. Based on an interdisciplinary
assessment investigating the cumulative risk arising from multiple climate-ocean stressors (SLR; changes in rainfall,
ocean–atmosphere oscillations and tropical cyclone intensity; ocean warming and acidification), it assesses the risk cau-
sed to five major and interconnected Habitability Pillars (HPs; Land, Freshwater supply, Food supply, Settlements and
Infrastructure, and Economic activities). It does so at two spatial (ocean subregions and island) and temporal (2050 and
2090) scales, under the greenhouse gas concentration pathways RCP2.6 and RCP8.5 and a moderate adaptation sce-
nario. The findings reveal that climate risk to atoll habitability is not only driven by the impacts of SLR and increased
wave height on Land but rather, and importantly, by the cumulative and cascading effects of the abovementioned mul-
tiple climate stressors on these five HPs. The risk to Land, considered as the major HP (because it is the support to
human life) and expected to be severe from 2050 onwards under both RCP2.6 and RCP8.5, will impact Freshwater sup-
ply from local sources, land-based Food supply, Settlements and Infrastructure, and Economic activities. At the same
time, ocean warming and acidification will increasingly contribute to Land destabilization, and decrease Food supply
from local sources (including EEZs). Unless technology, human and finance capacity are significantly increased in a
timely manner to effectively offset climate change impacts, the cumulative effects of climate stressors under a moderate
adaptation scenario will generate impacts in the second half of the 21st century that will likely exceed the adaptive
capacity of atoll islands in the Western and Central Pacific and Indian Ocean.
Our findings indicate there will be significant spatial variations in risk across both ocean basins and islands. We pro-
ject that islands in the Western Pacific will experience disproportionate high risk from SLR, increased tropical cyclone
and distant-source wave height, increased frequency of intense droughts, ocean warming and acidification, and a mar-
ked decrease in fish, including tuna and tuna-like species. In this subregion, the five HPs will all be significantly and
simultaneously challenged, with limited compensation opportunities (e.g., through the replacement of nearshore fish
catches by pelagic catches) at the nation scale. In such locations, risk accumulation is thus expected to seriously chal-
lenge atoll habitability from 2050 onwards under RCP8.5. Conversely, in the Central Pacific and Indian Ocean, risk
accumulation is projected to increase at a lower rate. This is due, in the Central Pacific, to lower rates of SLR, lower
exposure to tropical cyclones, lower SST and increasing pelagic fish stocks and, in the Central Indian Ocean, to lower
exposure to tropical cyclones and droughts.
This study highlights an urgent need for future assessments of risk to atoll habitability to consider not only a wide
range of climate-driven factors and island cases, but also to highlight how these may differentially impact islands across
ocean basins. There is also a pressing need in future work to consider how these climate drivers of risk will impact upon
different adaptation scenarios and changes in nonclimatic drivers of risk, in ways that include other resultant habitabil-
ity dimensions, especially the health of communities.
ACKNOWLEDGMENTS
The authors acknowledge the assistance of Andrew Lenton, Michael Grose, Xuebin Zhang, Claire Trenham, and Mark
Hemer of the CSIRO Climate Science Centre for provision of climate projection data; and of Mary Taylor for support
on agriculture issues. They also thank reviewers for their insightful comments. The two workshops that allowed the
DUVAT ET AL.19 of 28
preparation of this article were funded by the Agence Nationale de la Recherche (France) under the STORISK research
project (No. ANR-15-CE03-0003) and by “The Ocean Solutions Initiative”supported by the Prince Albert II of Monaco
Foundation, the Ocean Acidification International Coordination Centre of the International Atomic Energy Agency,
the Veolia Foundation, and the French Facility for Global Environment. In addition, Alexandre K. Magnan gained sup-
port from the Agence Nationale de la Recherche (France) “Investissement d'avenir programme”(No. ANR-10-LABX-
14-01) and Ademe (Convention 20ESC0016). The contribution of Kathleen L. McInnes was supported by the DFAT-
funded Australia-Pacific Climate Partnership project entitled “NextGen Climate Projections for the Western Tropical
Pacific”and CSIRO. Colette Wabnitz gained support from the Walton Family Foundation (grant 2018-1371), the David
and Lucile Packard Foundation (grant 2019-68336), and the Gordon and Betty Moore Foundation (grant
GBMF5668.02). Nicholas A. J. Graham was funded by The Royal Society.
AUTHOR CONTRIBUTIONS
Virginie Duvat: Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology;
validation; visualization; writing-original draft; writing-review and editing. Alexandre Magnan: Conceptualization;
data curation; formal analysis; funding acquisition; investigation; methodology; validation; visualization; writing-
original draft; writing-review and editing. Chris Perry: Conceptualization; data curation; formal analysis; investiga-
tion; methodology; validation; visualization; writing-original draft; writing-review and editing. Thomas Spencer:
Formal analysis; investigation; methodology; validation; visualization; writing-original draft; writing-review and
editing. Johann Bell: Conceptualization; formal analysis; investigation; methodology; validation; visualization;
writing-original draft; writing-review and editing. Colette Wabnitz: Conceptualization; data curation; formal analysis;
investigation; methodology; validation; visualization; writing-original draft; writing-review and editing. Arthur Webb:
Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; visualization;
writing-original draft; writing-review and editing. Ian White: Conceptualization; data curation; formal analysis; inves-
tigation; methodology; validation; visualization; writing-original draft; writing-review and editing. Kathleen McInnes:
Conceptualization; data curation; formal analysis; investigation; methodology; visualization; writing-original draft;
writing-review and editing. Jean-Pierre Gattuso: Formal analysis; investigation; methodology; validation; visualiza-
tion; writing-review and editing. Nick Graham: Conceptualization; data curation; formal analysis; investigation; meth-
odology; validation; writing-original draft. Patrick Nunn: Formal analysis; validation; writing-review and editing.
Gonéri Le Cozannet: Formal analysis; validation; writing-review and editing.
CONFLICT OF INTEREST
The authors have declared no conflicts of interest for this article.
ORCID
Virginie K. E. Duvat https://orcid.org/0000-0002-9336-3833
Alexandre K. Magnan https://orcid.org/0000-0001-7421-5184
Chris T. Perry https://orcid.org/0000-0001-9398-2418
Tom Spencer https://orcid.org/0000-0003-2610-6201
Colette C. C. Wabnitz https://orcid.org/0000-0002-5076-9163
Ian White https://orcid.org/0000-0002-5455-4514
Kathleen L. McInnes https://orcid.org/0000-0002-1810-7215
Jean-Pierre Gattuso https://orcid.org/0000-0002-4533-4114
Nicholas A. J. Graham https://orcid.org/0000-0002-5332-0783
Patrick D. Nunn https://orcid.org/0000-0001-9295-5741
Gonéri Le Cozannet https://orcid.org/0000-0003-2421-3003
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How to cite this article: Duvat VKE, Magnan AK, Perry CT, et al. Risks to future atoll habitability from
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