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Coastal communities SIDS and LDCs are unique in their position of vulnerability towards ocean-derived risks. They have high levels of exposure and sensitivity to these risks, in part owing to the heavy dependency on the sea for fisheries and tourism – core sectors that support their GDP, livelihoods as well as food security. The situation in these countries is changing rapidly, as is their exposure to different types of risks, and their ability to adapt and respond. The high dependence of many developing countries on tourism and imports and concomitant effects of the current pandemic and tropical cyclone Harold, for instance, are examples of how fragile some of the existing means of livelihood and food security are to external forces. Through a synthesis of peer-reviewed and grey literature, empirical data, and case studies from SIDS and LDCs, this report describes the prominent biophysical and anthropogenic stressors and their impacts on SIDS and LDCs, highlights the key social-ecological features of SIDS and LDCs that shape their vulnerabilities to these stressors, and suggests potential ways that can support SIDS and LDCs to mitigate ocean risks and build resilience.
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Kanae Tokunaga1, Abigayil Blandon2,3,
Robert Blasiak2,4, Jean-Baptiste Jouray2,
Colette C.C. Wabnitz5,6, Albert V. Norström2,7
1 Coastal and Marine Economics Lab, Gulf of Maine Research Institute, USA
2 Stockholm Resilience Centre, Stockholm University, Sweden
4 Graduate School of Agricultural and Life Sciences, The University of Tokyo, Japan
5 Stanford Center for Ocean Solutions, Stanford University, USA
6 Institute for the Oceans and Fisheries, University of British Columbia, Canada
7 Global Resilience Partnership, Stockholm University, Sweden
October 2021
This report is a contribution to the Ocean Risk and Resilience Action Alliance (ORRAA). It
has been led by the Stockholm Resilience Centre at Stockholm University and the Global
Resilience Partnership, and supported by the Government of Canada.
This publication has benetted from the generous and collaborative eorts of the many people
listed below with deep knowledge and diverse expertise, relevant to this work, who reviewed
this report and/or contributed to it with their time, and by recommending resourcesand
sharing experiences and valuable insights.
David Reidmiller, Climate Center, Gulf of Maine Research Institute
Piera Tortora, Organisation for Economic Co-operation and Development (OECD)
Kazumi Wakita, School of Marine Science and Technology, Tokai University
Layout and graphics: Jerker Lokrantz/Azote
Cover photos: Satellite image of hurricane Irma as it approaches the Leeward Islands at peak intensity, September 5, 2017. In the foreground, damaged
palm trees in the hurricane aermath. Photo: NASA and Alejandro Photography.
Cite this report as: Tokunaga K, Blandon A, Blasiak R, Jouray J-B, Wabnitz CCC, Norström AV (2021) Ocean risks in SIDS and LDCs. Ocean Risk and
Resilience Action Alliance (ORRAA) Report
Key messages
Small Island Developing States (SIDS) and
Least Developed Countries (LDCs) share certain
features that make their development paths
susceptible to ocean risks. Their economies are
heavily reliant on the natural environment; and they
are vitally dependent on public sector employment
and foreign nancing. These make SIDS and LDCs
particularly vulnerable to certain environmental and
socioeconomic stressors such as extreme weather
and geological events, coastal urbanization, as well as
global health and nancial crises.
However, SIDS and LDCs are not homogeneous
groups, but represent a set of countries and
territories that dier across many dimensions.
Countries and territories classied as SIDS and
LDCs are diverse in terms of population size, levels
of economic development, land masses, sizes
of territorial sea and exclusive economic zones
(EEZs), types and availabilities of natural resources,
cultures, histories, and governance systems. Thus,
vulnerabilities, adaptive and transformative capacities,
and pathways in which ocean risks manifest will vary
across coastal communities in SIDS and LDCs.
Ocean risks are coupled complex risks. Ocean
risks to coastal communities in SIDS and LDCs
are experienced across multiple dimensions. They
include environmental stressors linked to climate
change, such as oods, tropical storms, as well as
shis in species distributions and abundance. These
interact with socioeconomic stressors including
sheries overexploitation, pollution, dredging, and
poor land use. The unprecedented levels of hyper-
connectivity in our world exacerbate this ocean
risk landscape. Events such as pandemics, nancial
crises and synchronized food shocks propagate more
rapidly than in the past and with greater geographic
spread, and intersect with broader existing socio-
cultural, economic, and political vulnerabilities.
Eorts to quantify risk and vulnerability must pay
more explicit attention to the coupled complex
nature of ocean risks. For example, impacts from
sea level rise tend to be assessed in isolation from
the eects of ocean warming. Likewise, shing
communities located in areas that will be inundated
due to sea level rise likely will also be aected by
changes in sheries’ productivity. In such cases, coastal
infrastructure planning to adapt to climate change,
for instance, needs to consider possible shis in use
patterns, such as changes in sh processing facilities
and market functionalities. Such planning should also
consider changes in seafood demand by the global
market, demand for environmental conservation, and
development of the carbon market, among others,
while keeping social equity concerns in mind.
The complexity of ocean risk is mirrored
in the complexity of resilience, which is
multidimensional and dynamic. The global
community will need to gain experience in
understanding and addressing more complicated
risks in the coming years. This report highlights
examples of the socio-economic impacts of
displacements and migration, which disrupt local
social structures and can reduce or destroy social
capital critical for economic growth and resilience. At
the same time, an inability to relocate also negatively
impacts community resilience and may trap
communities in patterns of continually facing future
risks. It is important to keep in mind the context-
specicity of how ocean risks manifest and impact
SIDS and LDCs, meaning a diverse set of approaches
will be needed to adequately understand and
respond to risk and vulnerability. Context-dependent
solutions are essential; for instance, projects tailored
to local ecological systems may work better than
global-scale approaches under certain conditions.
Projects that are designed with local communities
can benet from local knowledge to ensure that
project address local demands and reect socio-
cultural contexts to achieve long-term success.
Strengthening of scientic and technical capacities
as well as integration of local indigeneous and
ecological knowledge can promote resilience,
sustainabiilty, and equity. SIDS and LDCs oen lack
domestic technical capacities and data to conduct
their own vulnerability and risk assessments. Thus,
investments in building domestic scientic and
technical capacities, baseline monitoring, data
collection, and deployment of blue techs are critical
for mitigating risks to build resilience. At the same
time, many communities in SIDS and LDCs hold
valuable local indigenous and ecological knowledge
that are oen neglected in the scientic or decision-
making process. Integration of these knowledge
systems can benet disaster response, resource
management, and climate adaptation.
Key messages 3
Denitions 5
Introduction 6
Key Features of SIDS and LDCs 8
Ocean risk landscape 14
Natural disasters, sea level rise, and oods 14
Ocean warming and ecosystem changes 16
Human migrations and displacements 17
Dependence on tourism, and the case of COVID-19 19
Climate change mitigation 20
Macroeconomic shocks and impacts 21
Interdependent risks 22
Achieving a sustainable, equitable, and resilient ocean economy 24
Novel nancial tools and insurance products 24
Expanding the knowledge base 26
References 27
Adaptive capacity - the social factors that enable
resilience to current, perceived, or expected
social-ecological change 1.
Blue economy - sustainable development
framework for developing countries addressing
equity in access to, development of, and the
sharing of benefits from marine resources;
offering scope for re-investment in human
development and the alleviation of crippling
national debt burdens 2.
Displacement - Involuntary and unforeseen
movement of people from their place of
residence due to weather-related impacts on
property and infrastructure 3.
Exclusive economic zones - areas of the sea in
which a coastal state has sovereign rights
(as prescribed by the 1982 United Nations
Convention on the Law of the Sea) regarding the
exploring, exploiting, conserving, and managing
living and non-living resources of the water
column, seabed and subsoil, including energy
production from water and wind, in its adjacent
section of the continental shelf extending 200
miles from the coastline.
Exposure - nature and degree to which a component
is in contact with or subject to a stressor.
Food and nutrition security - food and nutrition
security is achieved when adequate food
(quantity, quality, safety, socio-cultural
acceptability) is available and accessible for and
satisfactorily used and utilized by all individuals
at all times to live a healthy and active life 4.
Least Developed Countries (LDCs) - a group
of countries with low income and/or with
socioeconomic vulnerabilities.
Ocean economy - the sum of the economic
activities of ocean-based industries, and
the assets, goods, and services of marine
Ocean observing system - a collection of sensors
that collect data, the platforms that host these
sensors, and technology that sends the data to a
data collection center, often with satellite or cell
phone telemetry.Observing systems also include
computer models that produce forecasts of ocean
conditions 6.
Ocean risks - existing or potential impacts and
experiences of socioeconomic and environmental
stressors derived from the ocean or associated
with the ocean economy that derail SIDS
and LDCs from sustainable and equitable
development paths.
Resilience - the capacity of a system to cope,
adapt or transform in the changing social or
environmental conditions 7.
Sensitivity - degree to which a system is directly or
indirectly affected or modified by a stressor.
Small Island Developing States (SIDS) - a group
of countries and territories that share common
social, economic, and environmental challenges
in their development paths as small island states.
Social capital - features of social organization
such as networks, norms, and social trust that
facilitate coordination and cooperation for
mutual benefit 8.
Stressors - threats to a social-ecological system.
Stressors can be socioeconomic (e.g., market
shocks, coup d’état, population growth) or
environmental (e.g., tropical cyclone, sea level
rise, changing water quality).
Vulnerability - degree to which a system (or its
attributes) is susceptible to, or unable to cope
with, adverse effects of one or more stressors.
Vulnerability has three dimensions: exposure,
sensitivity, and adaptive capacity 9.
Climate change has been impacting marine
and coastal ecosystems globally. Carbon
emissions from human activities are causing
ocean warming, acidication and oxygen
loss with some evidence of changes in nutrient
cycling and primary production 10. Increasingly,
ocean warming and extreme temperature events
(i.e., marine heatwaves) are aecting marine and
coastal ecosystems through changes in population
productivity and spatial distribution 11–14, impacting
sheries with implications for food production and
dependent human communities 15–19. Distributions of
seagrass meadows and mangroves are contracting,
while the frequency of large-scale coral bleaching
events has increased, causing worldwide reef
degradation 20–22. Small island developing states
(SIDS), a group of countries and territories that
share common social, economic, and environmental
challenges in their development paths, and least
developed countries (LDCs), a group of countries
with low income and/or with socioeconomic
vulnerabilities, are disproportionately vulnerable to
these impacts 19,23,24. Many of these countries have
an outsized dependence on marine and coastal
resources and healthy ecosystems for income,
livelihoods and nutrition security 25–28. Coastal
ecosystems are also critical to their culture and
linked to many traditions 29.
We are simultaneously seeing increasing hopes and
expectations that the ocean will serve as an engine
to sustain future economic development 30. There
is an accelerating scramble for current, and future,
ocean benets that is unfolding with unprecedented
intensity and diversity (e.g., sheries, aquaculture,
mining, bioprospecting, shipping, conservation,
Morning aer Hurricane Maria, September 2017, between Castle Comfort and Roseau on the Island of Dominica.
communication, tourism, and geopolitics). This
scramble for the seas – or “blue acceleration” –
presents both risks and opportunities with a range of
ecological, economic, equity and policy ramications.
The future of the ocean economy in SIDS and LDCs
depends on their ability to navigate this new ocean
The international community has emphasized
the need to prioritize SIDS and LDCs in building
resilience against climate change and other risks
to achieve sustainable development goals; for
example, the SIDS Accelerated Modalities of Action
(SAMOA) Pathway was adopted in 2014 at the Third
International Conference on SIDS (Apia, Samoa),
and called for urgent actions and support for SIDS’
eorts to achieve their sustainable development.
Despite such calls and progress made since, gaps and
challenges remain 31, including access to nance to
support the sustainable development of key sectors,
such as sheries 32.
This report synthesizes peer-reviewed and grey
literature, empirical data, and case-studies to:
1. Highlight prominent environmental and
socioeconomic stressors and their impacts on
SIDS and LDCs;
2. Describe social-ecological features of SIDS and
LDCs that shape their vulnerabilities;
3. Describe potential ways that can support SIDS
and LDCs in mitigating ocean risks and building
Key Features of SIDS
and LDCs
Formally, SIDS were recognized at the 1992
United Nations Rio Conference on Environment
and Development as having shared unique
sustainable development challenges, such as
geographical remoteness, low economic diversity,
and a heavy reliance on marine and coastal
resources33. LDCs are determined based on per
capita incomes following World Bank’s low-income
countries (LICs) classication. Designation as LDCs
is also associated with the level of human assets
and economic vulnerability 34. LDCs therefore
include LICs as well as those lower-middle income
countries with low human assets and high economic
These classications and labels play a critical role in
determining access to certain types of nancing35.
For example, there are 24 countries who can receive
the World Bank’s International Development
Association’s concessional nancing (i.e., no interest,
40-year amortization with 10-year grace period) and
their eligibility is determined based on criteria such
as per capita income and their status as Small Island
States 36. Ocial development assistance (ODA) is
not available for non-LDC high income countries as
well as those that are members of G8 and current
and prospective members of the European Union
(EU) 37. Furthermore, LDCs can receive preferential
trade deals under the World Trade Organization
mechanism 38.
Many SIDS and coastal LDCs have economies
that are heavily reliant on coastal and marine
ecosystems, and oen have vast EEZs with rich
sheries resources. Consequently, communities and
households in SIDS and coastal LDCs largely depend
on sheries and aquaculture for nutrients and
livelihoods. Developmental nances, but also other
types of external resources through international
tourism, and sales of sheries access rights, play an
important role in these countries and territories39.
For example, coastal tourism brings in a large
amount of foreign income for many SIDS. In fact,
the tourism sector accounts for over 20% of GDP
for almost two-thirds of SIDS 40–42 (see also ORRAA
Report on Gender)*. Similarly, the sales of shing
licenses to distant water shing nations comprise a
* Wabnitz et al (2021) ORRAA Report.
signicant portion of public revenue and contribute
to essential public services such as education and
healthcare 43. Combined with the general lack of
economic diversity, their heavy reliance on external
resources makes them vulnerable not only to
environmental hazards such as extreme weather
and ecosystem changes but also to socioeconomic
stressors such as global nancial crises, pandemics,
and geopolitics.
SIDS and coastal LDCs are especially vulnerable
to climate change. For example, global indices of
climate change vulnerability highlight that SIDS and
LDCs are highly exposed to the impacts of climate
change, have a relatively low adaptive capacity,
and are among the world’s most sensitive states to
climate change (Figure 1). The economic damages
from climate change are also projected to be high
Figure 1. Exposure, Sensitivity, and Adaptive Capacity (Figure
shows the climate change sensitivity (horizontal axis) and
adaptivity capacity (vertical axis) scores calculated for each
Coastal State by Blasiak et al. (2017). The colors indicate LDC
SIDS (red), non-LDC SIDS (purple), Other LDC (blue), and other
(grey) countries. The size of the dot indicates climate change
exposure score calculated from using IPCC RCP scenario (near
term projection, as described by Blasiak et al. (2017). Data: Blasiak
et al. (2017) supporting information
Table 1. List of Coastal LDCs and SIDS (Regional classication follows UN region and sub-region classication).*
Region Subregion Country SIDS LDC
GNI per
capita, PPP
(current inter-
national $) Income group
stocks (%
of GNI)
category Other
Per capita
greenhouse gas
emissions (kt of
CO2 equivalent)
Africa Northern Africa Sudan SDN LDC 42,813,238 3,990 Lower middle income 77.06 IDA HIPC 0.013593
Sub-Saharan Africa Angola AGO LDC 31,825,295 6,380 Lower middle income 63.96 IBRD 0.001659
Benin BEN LDC 11,801,151 3,400 Low income 27.37 IDA HIPC 0.003447
Cape Verde CPV SIDS 549,935 7,330 Lower middle income 93.90 Blend 0.000773
Comoros COM SIDS LDC 850,886 3,210 Lower middle income 25.57 IDA HIPC 0.000779
Congo -
Kinshasa COD LDC 86,790,567 1,110 Low income 11.11 IDA HIPC 0.011624
Djibouti DJI LDC 973,560 5,620 Lower middle income 79.00 IDA 0.003186
Eritrea ERI LDC 3,213,972 1,610 Low income 51.48 IDA HIPC
Gambia GMB LDC 2,347,706 2,280 Low income 39.97 IDA HIPC 0.001853
Guinea GIN LDC 12,771,246 2,650 Low income 23.54 IDA HIPC 0.009515
Bissau GNB SIDS LDC 1,920,922 2,230 Low income 44.20 IDA HIPC 0.004738
Liberia LBR LDC 4,937,374 1,320 Low income 49.95 IDA HIPC 0.000685
Madagascar MDG LDC 26,969,307 1,660 Low income 29.90 IDA HIPC 0.005277
Mauritania MRT LDC 4,525,696 5,360 Lower middle income 71.55 IDA HIPC 0.003600
Mauritius MUS SIDS 1,265,711 26,840 Upper middle income IBRD 0.001634
Mozambique MOZ LDC 30,366,036 1,310 Low income 135.73 IDA HIPC 0.015296
São Tomé &
Príncipe STP SIDS LDC 215,056 4,130 Lower middle income 60.36 IDA HIPC 0.001038
Senegal SEN LDC 16,296,364 3,470 Lower middle income 58.83 IDA HIPC 0.004043
* LDC status were determined by referencing UN Committee for Development Policy Secretariat 174. SIDS status were determined by referencing UNCTAD 175. Population, GNI per capita, External debt
stocks, and per capita GHG emissions were obtained and calculated from World Bank and are for the most recent data as of April 2021. Red font used for population indicate microstate with countries less
than 200,000 people. Red font used for per capita GHG emissions indicate countries with per capita GHG emission higher than OECD countries. These were obtained via R package ‘wbstats’ (version1.0.4).
Income group, World Bank lending category and HIPC listings were obtained from World Bank 36. Abbreviations: IDA: International Development Association, IBRD: International Bank of Reconstruction and
Development, HIPC: Highly Indebted Poor Countries.
Region Subregion Country SIDS LDC
GNI per
capita, PPP
(current inter-
national $) Income group
stocks (%
of GNI)
category Other
Per capita
greenhouse gas
emissions (kt of
CO2 equivalent)
Africa Sub-Saharan Africa Seychelles SYC SIDS 97,625 29,470 High income IBRD 0.010309
Sierra Leone SLE LDC 7,813,215 1,770 Low income 44.42 IDA HIPC 0.001760
Somalia SOM LDC 15,442,905 Low income 268.83 IDA HIPC 0.001724
Tanzania TZA LDC 58,005,463 2,700 Low income 31.80 IDA HIPC 0.005002
Togo TGO LDC 8,082,366 1,670 Low income 40.01 IDA HIPC 0.003385
Americas Latin America and
the Caribbean Anguilla AIA SIDS
Antigua &
Barbuda ATG SIDS 97,118 21,780 High income IBRD 0.006114
Aruba ABW SIDS 106,314 36,300 High income 0.009977
Bahamas BHS SIDS 389,482 37,420 High income 0.013381
Barbados BRB SIDS 287,025 15,770 High income 0.005430
Belize BLZ SIDS 390,353 6,700 Upper middle income 80.03 IBRD 0.004645
British Virgin
Islands VGB SIDS 30,030 High income 0.004038
Islands CYM SIDS 64,948 41,790 High income 0.011579
Cuba CUB SIDS 11,333,483 Upper middle income 0.004656
Curaçao CUW SIDS 157,441 26,670 High income
Dominica DMA SIDS 71,808 12,250 Upper middle income 49.35 Blend 0.003140
Republic DOM SIDS 10,738,958 18,300 Upper middle income 42.42 IBRD 0.003363
Grenada GRD SIDS 112,003 16,080 Upper middle income 50.31 Blend 0.006759
Guyana GUY SIDS 782,766 13,540 Upper middle income 31.15 IDA HIPC 0.008129
Haiti HTI SIDS LDC 11,263,077 3,040 Low income 15.39 IDA HIPC 0.000862
Jamaica JAM SIDS 2,948,279 9,940 Upper middle income 98.83 IBRD 0.005445
Region Subregion Country SIDS LDC
GNI per
capita, PPP
(current inter-
national $) Income group
stocks (%
of GNI)
category Other
Per capita
greenhouse gas
emissions (kt of
CO2 equivalent)
Americas Latin America and
the Caribbean Montserrat MSR SIDS
Antilles ANT SIDS
Sint Maarten SXM SIDS 40,733 35,400 High income
St. Kitts &
Nevis KNA SIDS 52,834 26,360 High income IBRD 0.002551
St. Lucia LCA SIDS 182,790 15,180 Upper middle income 31.99 Blend 0.003390
St. Vincent &
Grenadines VCT SIDS 110,589 12,930 Upper middle income 43.59 Blend 0.002944
Suriname SUR SIDS 581,363 15,310 Upper middle income IBRD 0.004911
Trinidad &
Tobago TTO SIDS 1,394,973 27,140 High income IBRD 0.045589
Turks &
Caicos Islands TCA SIDS 38,191 28,020 High income 0.000508
Northern America Bermuda BMU SIDS 64,027 86,460 High income 0.009767
Asia South-eastern Asia Cambodia KHM LDC 16,486,542 4,320 Lower middle income 60.01 IDA 0.008619
(Burma) MMR LDC 54,045,420 5,170 Lower middle income 15.16 IDA 0.010278
Singapore SGP SIDS 5,703,569 92,270 High income 0.010524
Timor-Leste TLS SIDS LDC 1,293,119 4,970 Lower middle income 7.53 Blend 0.000847
Southern Asia Bangladesh BGD LDC 163,046,16 5,200 Lower middle income 18.01 IDA 0.001214
Maldives MDV SIDS 530,953 18,380 Upper middle income 52.70 IDA 0.001310
Western Asia Bahrain BHR SIDS 1,641,172 44,250 High income 0.025270
Yemen YEM LDC 29,161,922 3,520 Low income 31.26 IDA 0.001672
Oceania Melanesia Fiji FJI SIDS 889,953 13,120 Upper middle income 20.22 Blend 0.002610
Caledonia NCL SIDS 287,800 High income 0.008873
Region Subregion Country SIDS LDC
GNI per
capita, PPP
(current inter-
national $) Income group
stocks (%
of GNI)
category Other
Per capita
greenhouse gas
emissions (kt of
CO2 equivalent)
Oceania Melanesia Papua New
Guinea PNG SIDS 8,776,109 4,360 Lower middle income 78.81 Blend 0.001453
Islands SLB SIDS LDC 669,823 2,750 Lower middle income 22.27 IDA 0.008257
Vanuatu VUT SIDS LDC 299,882 3,320 Lower middle income 44.59 IDA 0.001788
Micronesia Guam GUM SIDS 167,294 High income 0.000537
Kiribati KIR SIDS LDC 117,606 4,650 Lower middle income IDA 0.000522
Islands MHL SIDS 58,791 5,090 Upper middle income IDA 0.000103
States of)
FSM SIDS 113,815 3,640 Lower middle income IDA 0.000536
Nauru NRU SIDS 12,581 17,820 Upper middle income IBRD
MNP SIDS 57,216 High income 0.000230
Palau PLW SIDS 18,008 19,580 High income IBRD
Polynesia American
Samoa ASM SIDS 55,312 Upper middle income 0.001056
Cook Islands COK SIDS
Polynesia PYF SIDS 279,287 High income 0.002535
Samoa WSM SIDS 197,097 6,500 Upper middle income 50.13 IDA 0.001883
Tonga TON SIDS 104,494 7,000 Upper middle income 34.68 IDA 0.001499
Tuvalu TUV SIDS LDC 11,646 6,180 Upper middle income IDA 0.000488
in SIDS and LDCs. For example, recent reviews
of existing economic assessments and models of
climate change impacts suggest that countries with
lower per capita income will see larger GDP losses in
the long run 44. This body of research also argues that
such regressive distribution of climate impacts across
countries is oen not accounted for in the estimation
of economic damages from climate change.
Despite having many of the shared features described
above, SIDS and LDCs should not be treated as
homogenous groups. They represent a diverse set
of countries and territories that dier across many
dimensions (Table 1). As of 2021, the list of LDCs
included 47 countries, 21 of which are Coastal States
with exclusive economic zones (EEZs), and the list
of SIDS included 58 countries and territories, with
9 countries appearing on both lists (LDC-SIDS)
(Table1). While the majority of the 58 recognized
SIDS are sovereign states, 20 of them are classied as
territories and/or are not the members of the United
Nations 45. Among SIDS, there is a great variability in
terms of land mass, territorial sea, natural resource
availabilities, as well as governance systems 42. For
example, Bahrain is an oil producing country, Papua
New Guinea is rich in forestry resources, and Tuvalu
is a coral atoll. Several SIDS are classied as high-
income countries (Table 1).
In summary, certain shared features make SIDS
and coastal LDCs particularly vulnerable to certain
environmental and socioeconomic stressors such
as extreme weather and geological events, coastal
urbanization, as well as global health and nancial
crises. However, dierences across dimensions such
as population size, levels of economic development,
land masses, sizes of territorial sea and EEZs, types
and availabilities of natural resources, cultures,
histories, and governance systems indicates
that vulnerabilities, adaptive and transformative
capacities, and pathways in which ocean risks
manifest will vary across coastal communities in SIDS
and LDCs.
Ocean risk landscape
Globally, 40% of the world’s population (i.e.,
2.4 billion people) live within 100 km of the
coast 46, and these numbers are higher for
SIDS and LDCs. Coping with environmental
stressors (sometimes referred to as natural hazards)
that are ocean-derived has dramatically shaped
resource use and human settlement in SIDS and
coastal communities across LDCs throughout their
histories. However, there is a growing scientic
recognition that we live in a time where humans are
the dominant force of planetary change – termed
the Anthropocene epoch47. Human activity is now
fundamentally modifying weather patterns, the
climate, the cryosphere (i.e., the frozen parts of
the Earth), and the ocean. The natural baseline
(e.g., frequency and intensity) of many of these
ocean-derived environmental stressors is changing.
Technological advancement in the past few decades
has led humanity to reach deeper and further into
the ocean, with rapidly increasing commercial
interests driving growth in existing industries and the
emergence of new ones 30,48. The Blue Acceleration,
a race among diverse and oen competing interests
for ocean food, material, and space, is driving an
unprecedented expansion in the intensity, and
diversity of socioeconomic stressors impacting SIDS
and LDC coastal communities (see also ORRAA
Report on the Blue Acceleration)*. Together, these
environmental (e.g., tropical cyclones, sea level rise)
and socioeconomic (e.g., urbanization, nancial crises)
stressors are creating ocean risks that can derail SIDS
and LDCs from sustainable development paths.
The next sections synthesize the impacts and
interactions of the key environmental and
socioeconomic stressors that are derived from the
ocean and/or associated with the ocean economy,
including extreme weather and geological events,
climate-induced sea level rise, coastal urbanization,
global pandemic, nancial crises, and the associated
ocean risks for SIDS and LDCs.
Natural disasters, sea level rise, and
The Working Group I contribution to the Sixth
Assessment Report of the Intergovernmental Panel
* Jouray et al (2021) ORRAA Report.
on Climate Change asserted that global mean sea
level will continue to rise through 2100, resulting
in more coastal areas experiencing increases in
relative sea level, coastal ooding, and coastal
erosion 49. Even if emissions were to stop today, it
is likely that sea-level rise (SLR) would increase
by an additional 0.7-1.1m by 2300. Considering the
“pledged emissions” through 2030, these numbers
increase to 0.8-1.4m of committed SLR. If emissions
continue beyond 2030, sea level will continue to rise
accordingly. SLR is therefore anticipated to be one of
the most expensive and irreversible consequences
of climate change worldwide. For example, a recent
study, using a spatially dynamic model of the world
economy, estimated that SLR would reduce global
real GDP by 0.19% in present value terms under an
intermediate scenario (RCP 4.5) of greenhouse gas
emissions 50. Corresponding country-level estimates
of SLR impacts on GDP, welfare, and population
project that the countries that will suer the most
GDP and population loss are LDCs,** predominantly
those found in sub-Saharan Africa. The study also
found varying degrees of impacts within and across
global regions (Figure 2). For instance, despite nearby
countries projected to experience large welfare and
population losses, Mauritania and Sierra Leone are
expected see an increase in GDP and population.
SLR, in conjunction with increases in extreme rainfall
events, will lead to more frequent and prominent
coastal ooding and erosion. Flood risks will be
further exacerbated by coastal development driven
by population growth and rapid urbanization. A recent
global analysis, using spatially detailed inundation
maps and night lights data suggested that cities
located in areas that are less than 10 meters above
sea level have a high annual probability of large-scale
oods that could displace >100,000 people 51.
With a 2°C increase in temperature, there will be
more intense tropical cyclones and the proportion
of Category 4 and 5 tropical cyclones will increase
by 13% 42,49. If major hard infrastructure (e.g., ports,
roads) and so infrastructure (e.g., nancial and
governance centers) are hit, these impacts will
ripple throughout the entire country. SIDS and
** This study also estimated the impacts of SLR for land-locked
coastal LDCs oen have critical infrastructure such
as transportation hubs, healthcare facilities, water
treatment plants, desalination plants, and power
stations in low-lying areas. This infrastructure is
exposed to stressors such as coastal ooding caused
by events such as large storms and tsunamis. For
instance, airports and ferry terminals that are critical
to the economies of Jamaica and St. Lucia will be
more frequently inundated over the course of the
coming century as a result of sea level rise and
stronger storms 52. Marine ooding can also impact
coastal aquifers, decreasing the availability of fresh
water supplies 53.
Local socio-economic factors and historical changes
to coastal areas can exacerbate the impacts of
SLR. Documented cases of coastal inundation and
erosion oen cite additional circumstances such as
vertical subsidence, engineering works, development
activities, or beach mining. For instance in the
Indian Ocean, on Anjouan Island, Comoros, coral
reef shing and beach mining worsened coastal
erosion to extend to the entire island’s coastline 54.
On the atoll island of Fongafale Islet, the capital of
Tuvalu, urbanization and construction activities in
swampland that have taken place since the 1970s
have worsened the impacts of SLR 55.
Figure 2. Economic impacts of coastal ooding (Figures show the ndings from Desmet et al. 2021 that estimated the impacts of sea level
rise on real GDP (top le), welfare (top right), and population (bottom le) in each country. Bars indicate the mean impact).
Some SIDS and LDCs are located in areas that
are seismically active and are impacted by
oshore earthquakes and tsunamis. Many coastal
communities in these countries have limited
access to advanced warning systems and scientic
information that would aid disaster planning56,57.
Lack of a routine monitoring and data can severely
limit their ability to benet from advanced
technologies that are employed by developed
countries to reduce their disaster risks from
geophysical and weather-related events. Increased
international support is critical for building and
strengthening local scientic infrastructure as well
as human and nancial resource capacities. Recent
developments in UN-led global observing systems
are aiding SIDS and LDCs in accessing, building, and
beneting from relevant scientic advances (Box1).
Further, in conjunction with building scientic
capacities, integration of local indigenous knowledge
and local ecological knowledge in the scientic
and decision-making process can lead to improved
understanding of the system. For instance, many
communities in Papua New Guinea have made use
of local indigenous and ecological knowledge to
manage disaster risks 58. Similarly, these knowledge
systems can improve resource management 59,60 and
climate change response and adaptation 61.
Ocean warming and ecosystem
The ocean has absorbed the bulk of human-induced
warming since the industrial era – about 90% of
the excess heat 10. This has caused unambiguous
increases in the global average sea surface
temperature (SST) over the 20th century. In addition
to gradual warming of the ocean, marine heatwaves
– dened as “a period of extreme warm near-SST
that persists for days to months and can extend up
to thousands of kilometers 62” – are also becoming
The UN Decade of Ocean Science for Sustainable
Development began in 2021. Decisions based on
indigenous knowledge or local ecological knowledge, in
conjunction with customary rules and practices, have
historically contributed to sustainable management
of coastal and marine natural resources 59,171 and to
planning for and recovery from natural disasters in
their coastal communities in SIDS and LDCs 58. As the
world shis into conditions unprecedented in human
history, however, relying solely on past experience
can limit these communities as they plan for the
future. Coastal communities in highly industrialized
countries are increasingly relying on scientic models
and projections for vulnerability assessments and
adaptation planning. SIDS and LDCs have limited
resources to establish and manage ocean observation
systems. Yet some regions, namely Caribbean SIDS
and Pacic SIDS, respectively, have establish regional
alliances for ocean observing systems to cooperate
in collecting and using ocean data (IOCARIBE-GOOS
in the Caribbean and PI-GOOS in Pacic Islands)27.
These eorts are both part of the Global Ocean
Observing Systems (GOOS) Regional Alliance, an eort
led by UNESCO’s Intergovernmental Oceanographic
Commission (IOC). These regional eorts have led,
among other things, to the establishment of a Tsunami
Warning System in the Caribbean and inundation
projections in Fiji 27.
There are thirteen GOOS Regional Alliances in the
world, including IOCARIBE-GOOS, PI-GOOS, and
Indian Ocean GOOS (IO-GOOS), and these regional
alliances are governed and funded in a variety of ways.
Ocean observing systems are costly, and SIDS and
LDCs rely heavily on external funds to establish and
maintain the systems. IOCARIBE-GOOS is governed
by the IOC sub-commission; PI-GOOS is governed by
the Pacic Islands Applied Geoscience Commission
and Secretariat of the Pacic Regional Environmental
Programme, and in the Indian Ocean, IO-GOOS is
governed by a memorandum of understanding among
marine institutes from 16 countries181. These Regional
GOOS alliances have been serving as international
collaboration platforms for ocean science, and in
SIDS, they have led to international collaborations
between SIDS and developed economies to attract
external funds to develop data and scientic products
to support local decisions. Although SIDS and LDCs
are limited by their lack of data 42,182,regional GOOS
have a tremendous potential to increase their scientic
capacity for monitoring, modeling and forecasting to
mitigate future risks.
The development of a Framework for Ocean Observing
in 2012, which established guidelines for the design
and implementation of ocean observing systems, led
to increased and strengthened collaboration among
ocean observing systems practitioners, institutions,
and scientists. Yet, there is a lack of budgetary
resources to coordinate and govern ocean observing
systems in a sustainable manner 183. GOOS can play a
pivotal role in providing baseline information not only
about oshore waters but also about coastal waters to
bring benet to coastal human populations. Continued
funding support and investments towards international
eort to strengthen GOOS can bring benets to coastal
communities SIDS and coastal LDCs and should be a
key component of the UN Decade of Ocean Science for
Sustainable Development and aligned eorts.
Ocean observing systems and scientic cooperation
Box 1
longer and more intense, with the frequency of the
most impactful marine heatwaves over the last few
decades having increased more than 20-fold because
of anthropogenic global warming 63–65. By the end of
the century, the IPCC projects that these extreme
events will become four times more frequent under
low emission scenarios (SSP1-2.6), or eight times
more frequent under high emission scenarios (SSP5-
Ocean warming will impact marine ecosystems by
changing the abundance and distributions of sh
species 66–68. Tropical regions, where many SIDS and
LDCs are located, are particularly vulnerable to
these shis in species as more sh make poleward
moves 69–72. The impacts of directional shis in sh
distribution can be gradual and felt over long periods
of time. Coastal shers who may be able to respond
and adapt to the changes at rst by traveling farther
from their home may not be able to continue to track
the changes as the range of shis become larger
over time. Gradual decline in stock abundance could
also result in chronic poverty and loss of shing as
livelihoods 73,74.
The sheries on which many SIDS and LDCs depend
for nutrition and livelihoods are oen transboundary
stocks, which are shared with neighboring countries.
Sustainable management of transboundary
stocks requires countries to collaborate to set up
management arrangements 75–77. Many SIDS have
vast EEZs with highly-migratory species such as
tunas, and they oen bear more conservation
burdens over such resources than distant water
shing nations that operate in their EEZs and nearby
international waters 78,79.
Countries have historically struggled to achieve
sustainable management of transboundary stocks,
and climate change is expected to further exacerbate
such challenges 77,80–82. In this context, eective
cooperation will grow increasingly relevant through
Regional Fisheries Management Organizations
and bilateral or multi-lateral joint management
agreements. To align with the sustainable
development agenda, these arrangements need to
mainstream issues of fairness and equity regarding
sharing of benets as well as burdens of management
and conservation 83 (Box 2).
Human migrations and displacements
When disasters hit coastal communities,
including those in SIDS and LDCs, people and
entire communities can be displaced. Gradual
environmental changes or slow-onset climate events
can cause displacement as well. In the year 2020
alone, 40.5 million people were displaced globally,
with three-quarters of this displacement caused by
natural disasters 84.
Between 2008 and 2019, there were nine natural
disaster events (seven storms, one ood, and one
earthquake) that caused more than one million
people to be displaced in just four countries
(Bangladesh, Myanmar, Haiti, and Cuba) (Figure 3). In
terms of per capita displacements, 17 natural disaster
events resulted in the displacement of more than 5%
of a country’s population. These included 15 storms,
one drought, and one earthquake. Nine of these
events occurred in Oceania (American Samoa, Fiji,
Federated States of Micronesia, Northern Mariana
Islands, Palau, Tonga, Tuvalu, and Vanuatu); seven in
the Americas (British Virgin Islands, Cuba, Dominica,
Haiti, and Sint Maarten (Dutch part)), and one in
Africa (Somalia). On average, over 2.9 million people
were displaced annually from 2008 to 2019.* These
numbers would certainly increase if they included
people displaced due to long-term gradual changes
or slow-onset climate events that disrupt their
physical and social infrastructure.
Countries and communities may also choose
to migrate as a precautionary measure and use
planned relocation as an adaptation strategy. A
survey of 86 case studies of community relocation in
Pacic Islands found that environmental variability
and natural hazards accounted for relocation of
communities in 37 of the cases 85. However, studies
of island migration commonly reveal the complexity
of a decision to migrate and rarely identify a single
cause. For example, research from the Pacic have
shown that culture, lifestyle, and a connection to
place are more signicant drivers of migration than
climate 86. However, nancial, legal, and political
barriers are expected to inhibit signicant levels
of environmentally-induced migration within and
across countries 87,88.
Migration and displacement can distort social
structure, weaken sociocultural fabric, and harm
social capital that is critical for economic growth and
resilience. The adverse impacts of displacement are
felt through multiple areas, including education and
health, and ultimately impact human capital and
labor productivity 3,84,89. Coastal communities oen
draw on social structures and capabilities that can
reduce risk and increase adaptive capacity in the
face of coastal hazards 90,91. Permanent relocation
of a community to a distant and foreign location
can erode culture, tradition, and identity of the
displaced people 84,92. Studies also show that failing
to assimilate in the destination communities can
result in environmental and resource degradation
* All of the numbers mentioned in this paragraph are
calculated based on Internal Displacement Data by International
Displacement Monitoring Center (https://www.internal-, as described by Figure 2. Per capita
displacement numbers use population data obtained from World
Bank and when population data was missing in
World Bank database.
SIDS in the Western and Central Pacic have vast
EEZs with rich sheries resources, including highly
migratory tropical tuna species. Parties to the Nauru
Agreement (PNA), a group which was formed in
1982 by the Federated States of Micronesia, Kiribati,
Marshall Islands, Nauru, Palau, Papua New Guinea,
Solomon Islands, and Tuvalu,* have been engaged in
cooperative and sustainable management of these
species. In their EEZs, skipjack tuna alone is valued
at over USD2 billion annually 184, and countries have
been gaining important revenue through the sale of
purse seine shing access rights to their waters to
distant water shing nations185,186. The purse seine
skipjack tuna shery has been managed through a
Vessel Day Scheme (VDS), which was introduced in
2007 and implemented in 2012, that allocates the
share of eort quotas among the Parties 187,188.** Under
this scheme vessel owners can purchase and trade
days shing at sea, within a total allowable eort
limit, in places subject to the PNA and Tokelau. The
primary motivation for the establishment of the PNA
was to form a united front against rich and powerful
distant water shing nations to ensure more equitable
negotiation outcomes in the sale of shing rights
while ensuring resource sustainability 43. In 2019, a
vessel day (the trading unit) in PNA waters cost on
average USD12,590, with the Parties collectively
generating over USD500 million in sheries-related
revenue annually 184. Revenue from the VDS provides
an average 37% of all government revenue across PNA
members and Tokelau (Bell et al. 2021), with monies
generated from licensing fees key to nancing public
infrastructure and providing basic services 25.
Recent stock assessments highlight the four key
tuna stocks in the western and central Pacic as in
a healthy state 189,190. Skipjack, yellown, and bigeye
tuna caught with purse seines benet from MSC
certication.*** Yet, as with many sheries around the
globe, tropical tuna are being impacted by climate
change 77. Existing studies project an eastward shi
of tuna across the region 191,192. Climate change is
therefore expected to create winners and losers
within the PNA as countries located in the western
Pacic (e.g., Papua New Guinea) will see their
proportion of the stock diminish, while countries
located in the central Pacic (e.g., Kiribati) will gain a
greater share 72,193,194. The PNA also face the challenge
of tuna moving out of their EEZs into international
waters, which is projected to result in revenue loss
from sheries access fees of USD 12 million per year
under the conservative Representative Conservation
Pathway (RCP) 4.5 scenario by 2050 – or USD 90
* Tokelau participates as an observer to PNA.
** VDS is currently implemented for tuna sheries that use
longline gear as well.
*** Currently, the MSC certication covers those that are
caught without sh aggregating device (FAD). As of March
2023, the certication will include those that use FAD as well.
million under a high greenhouse gas emissions
scenario (i.e., RCP 8.5) 193. Such change could reduce
incentives for cooperative management for countries
losing sh 193.
However, thus far, eorts to manage tuna stocks by
the PNA are paying o as they face climate challenges.
The VDS has several features that help the PNA adapt
to climate change. First, the scheme uses a rolling
historical reference of average shing eort input
(i.e., shing days) from recent years, as opposed to a
xed historical reference, to allocate shares 187,195,196.
The EU Common Fisheries Policy on the other hand,
for instance, has EU Member State’s quota shares
allocated based on catches in the 1970s. The PNA is
further responding by adapting their allocation policy
to climate change. In the early days of the VDS, the
Parties allocated the eort shares based on a the pre-
determined formulae that used a mix of the historical
shing eorts from the immediate seven years and
the relative stock abundance of each Party’s EEZ 197.
Currently, the eort allocation focuses on shing
eort as it has become more challenging to accurately
estimate the relative abundance of stocks in each
Party’s waters 195. The VDS has another advantage: it
allows Parties to trade shares.
As highlighted above, the PNA is not immune to
climate change challenges. Yet, existing sustainable
sheries management eorts can help mitigate some
of the projected changes. Adaptive management
systems such as the VDS can help sheries
management reduce climate risks. Evidence also exists
that, where accurate spatial distribution of biomass
can be estimated, harvest control rules (i.e., harvest
control rules = rules based on stock status indicators
that determine how much shing can take place 198)
that takes changes in biomass into consideration
can help sheries become more resilient to climate
change 199. The PNA’s VDS example and this evidence
can help inform approaches to climate-proof sheries
management systems around the globe.
Parties to the Nauru Agreement and climate change
Box 2
Photo: Quentin Hanich
in the region to which they have been displaced
as the new entrants may not be familiar with the
informal rules or norms related to resource use 93. For
migration to be considered an adaptation measure,
the community needs to be exercising its agency in
making any such decisions 94,95.
Dependence on tourism, and the case
of COVID-19
Many SIDS and coastal LDCs are highly dependent
on income from tourism. For example, two thirds
of ODA eligible SIDS are securing more than 20%
of their GDP from tourism. Eight of countries have
tourism sharing more than 40% of their GDP 41,42.
This high dependence on coastal tourism can
result in multiple ocean risks in SIDS and LDC. For
example, meeting the food preferences of large
numbers of visitors also has serious impacts. On
the one hand, it results in demand for high levels of
food imports to meet tourists’ preferences, while on
the other hand, it has nutritional impacts for local
communities when tourism creates higher demand
Figure 3. Internal Displacement due to Natural Disasters in SIDS and Coastal LDCs (Figures show per capita (le) and total number of
(right) new internal displacement caused by natural disasters from 2008 – 2019 by dierent hazard types. Data: Internal Displacement
Monitoring Centre ( The denition of internally displaced persons follow the UN denition:
"Persons or groups of persons who have been forced or obliged to ee or to leave their homes or places of habitual residence, in
particular as a result of or in order to avoid the eects of armed conict, situations of generalized violence, violations of human rights
or natural or human-made disasters, and who have not crossed an internationally recognized State border” (Guiding Principles on
Internal Displacement, 1998). For more information, refer to Per capita
displacement numbers use population data obtained from World Bank and when population data was missing in
World Bank database.)
for local sh 96,97. In addition, tourism generates
demand for considerable imports of consumer
goods and construction materials used for tourism
Coastal tourism further adds stress to the chronic
waste problem in SIDS. Per capita waste production
by SIDS residents is 48% higher than the global
average, and recycling rate is low 98. Lack of
infrastructure, limited space, outdated waste
transportation vehicles and narrow roads challenge
these countries ability to manage waste and are
major culprit of marine litter 98,99. This chronic
waste problem is also closely linked to the fact that
tourists produce more waste; thus, development
of coastal tourism is poised to further worsen the
waste problem.
For tourism-dependent countries, the COVID-19
pandemic has been particularly damaging.
By March 2021, 38 countries had experienced
complete border closures for at least 40 weeks,
including 19 SIDS and 9 LDCs 100. Most severely hit
are Antigua and Barbuda, Belize, Fiji, Maldives and
Saint Lucia, who are expected to have their GDPs
decrease by more than 16% 41. The loss of income
from coastal tourism impacted communities
and household across these countries to cause
significant equity concerns (see also ORRAA
Report on Gender)*. Panelists at Island Finance
Forum 2021 predicted that international travelers
would focus on the extent to which healthcare
services are available in the destination country
in case they get sick when they arrive 101. This
suggests a slow and delayed economic recovery for
tourism-dependent SIDS and LDCs.
Using the pandemic as an example, however, we
also realize how complex interactions across key
economic sectors can either increase or reduce
vulnerabilities to ocean risks. For example, a
general downturn in coastal tourism also means
that beaches and other marine parks are receiving
fewer visitors, lowering associated impacts. As
such, the COVID-19 pandemic has had some
positive eects on environmental conservation
in the short-run 102. For example, a study of 29
urban tourist beaches in seven Latin-American
countries (Mexico, Panama, Colombia, Ecuador,
Brazil, Cuba, and Puerto Rico) found that lockdowns
contributed to decreased socioeconomic stressors
such as noise, odor, and litter on beaches, improved
dune vegetation, and increased burrow density
of crabs in some cases 103. However, if visitors do
not return aer the pandemic and the demand for
marine parks decreases, there is a concern that
countries and communities may not have sucient
nancial incentives and resources to continue
to protect these areas. Indeed, in a survey about
possible impacts of the pandemic on biodiversity
conservation, 60% of experienced conservation
experts expressed that the pandemic will have
negative impacts on biodiversity conservation 104.
Some of the concerns listed include government
prioritizing economic recovery over conservation,
reduced philanthropy, and increased illegal
activities due to reduced enforcement during the
pandemic. Fisheries were also aected by the
pandemic. The major positive impact was possible
recovery of some of the previously depleted
sh stocks as a result of prolonged slowdown
of commercial shing activities due to travel
restrictions and port closures 105. The pandemic has
also negatively impacted the shing sector in SIDS
and LDCs as demand has fallen for many seafood
product exports, and local demand to supply the
tourism sector has declined 102,106. The pandemic
also had signicant impacts on food systems,
including increased use of food sharing to maintain
food security within a community and a revival of
local food systems in many parts of the world 107,108.
* Wabnitz et al (2021) ORRAA Report.
Climate change mitigation
Many SIDS and LDCs have a large potential for
ocean and oshore energy (e.g., oshore wind,
ocean thermal energy conversion, wave and tidal
energy) and other renewable energy (e.g., solar
photovoltaic) development 109 (see also ORRAA
Report on the Blue Acceleration)**. However, these
countries have struggled to harness this potential
110. SIDS and LDCs are heavily reliant on imported
petroleum not only for transportation but also for
electricity generation110.*** As of 2015, at least 24 SIDS
relied more than 80% of their energy on imports 111.
Island States spend over USD 67 million on oil, and
oil price hikes such as the ones in 2008 contributed
to increase external debt for SIDS 112. This reliance,
coupled with the high volatility of petroleum prices
compared with renewables and other types of fossil
fuels, leads to strains on island economies.
Some of the major causes for limited adoption of
renewable energy technologies include lack of
policies that provide incentives for renewable energy
producers, limited technical capacity, barriers for
renewable energy producers to access the electric
grid, and isolated island grid systems that are
vulnerable to intermittent sources of energy 110,113.
Further, geographical remoteness of SIDS, many of
which are located in Indian Ocean and Pacic Ocean,
means higher transportation and logistical costs 114.
These factors make it costly to switch to renewable
energy sources such as oshore wind. Further,
because many of the ocean energy technologies
are at early stage of development, there is high
technological and nancial risks associated with
these technologies that limit access to nance 115.
There is also a great variability in terms of household
access to electricity in SIDS and LDCs 116. For these
countries, renewable energy development can
improve electricity access as well as energy security
to enhance their resilience 114. Out of seventy SIDS
and coastal LDCs with records, 19% reported that
less than 50% of the population has access to
electricity.**** The cost of electricity varies across these
countries, with SIDS facing signicantly higher costs
of electricity compared with continental LDCs 117.
Since tourism is an energy intensive sector, SIDS with
tourism-dependent economies emit higher levels
of greenhouse gases (GHGs), with some SIDS and
LDCs such as Trinidad & Tobago, Bahrain, Bahamas,
and Sudan having high GHG emissions per capita
(Table1). The development of a carbon market
could be benecial for climate change mitigation by
** Jouray et al (2021) ORRAA Report.
*** Also based on authors calculation using data published by
World Bank (
**** Authors calculation based on data published by World Bank
reducing global carbon emissions, but SIDS and LDCs
are disadvantaged in terms of their ability to benet
from the carbon market due to the barriers they face
in scaling up renewable energy usage.
Macroeconomic shocks and impacts
Many SIDS and LDCs are dependent on external
assets through ODA, remittance, and philanthropy.
This reliance on foreign nancing also makes SIDS
and LDCs sensitive to global economic cycles. For
example, the funds supplied as ocial development
assistance and other aid assistance by OECD
countries oen depend on prevailing economic
conditions. Since 1970, all OECD member companies
have pegged their target of 0.7% of their gross
national income to be made available as ODA,
although this target has seldom been hit by member
states 118. The amount of funding available therefore
uctuates with the global economic cycle, which is
also a key factor for the growth or contraction of the
tourism sector, as expenditure for tourism goes down
during recessions. Tourism-dependent SIDS and
LDCs are therefore doubly impacted during global
economic recessions. The 2007-08 nancial crisis
impacted SIDS more severely than other developing
countries for their reliance on tourism by reducing
GDP growth rate to 0.9% as compared to over 3% for
other developing countries 119.
Climate change can also impact nancial markets
and asset values, both globally and locally. The
literature on climate-related nancial risks identies
three types of potential risks to the nancial system:
(1) physical risks (i.e., environmental stressors
such as sea level rise, marine heatwaves, and
extreme weather events, and their direct impacts
on businesses and households); (2) transition risks
(i.e., those that stem from socioeconomic reactions
to climate change such as changes in carbon policy,
changes in consumer preferences, and changes in
production technologies); and (3) liability risks (i.e.,
those that stem from victims of climate damage
demanding compensation) 120,121. The impacts of
these three risk categories manifest themselves in
business operations and household activities and
are ultimately felt at the nancial market system
level. For example, decarbonization policies oen
impact energy sector to switch away from fossil fuels.
This energy transition makes fossil fuel resources
to lose their value and become stranded. This is an
example of transition risk that can pose a signicant
risk to oil- and gas-producing SIDS such as Trinidad
& Tobago, Bahrain, Angola, and Timor-Leste. Further,
some of these countries such as Trinidad & Tobago
and Bahrain also have high per-capita GHG emissions
and thus could also be impacted by global policies to
mitigate GHG emissions (Table 1).
Climate-related nancial risks, in turn, impact
businesses and household activities. Central banks
and nancial institutions have already been taking
actions to mitigate the impacts of these risks. As
of December 2020, 83 members and 13 observers,
including members from SIDS and LDCs, have joined
the Network for Greening the Financial System, a
network of central banks and supervisors focused
on these issues 122. While only 12% of central banks
currently incorporate sustainability goals into their
policy 123, as several countries set sustainability goals
as their primary policy objective, there may be hope
this will feed into central banks’ decisions. Climate
change can directly impact nancial systems, and
therefore, better understanding and incorporation
of climate risks and sustainability related goals
in central banks’ policies can help create overall
macroeconomic and nancial stability 121,123.
Interdependent risks
As technology develops and enables humans
to further expand the range of benets
derived from the ocean, understanding how
human activities impact coastal and marine
ecosystems grows increasingly complicated (see
also ORRAA Report on the Blue Acceleration)*.
While it is known that these multiple socioeconomic
stressors (e.g. shing, seabed mining, shipping, and
land reclamation) interact, and result in complex
impacts on the ocean, we have limited understanding
of what they are and how these interactions
occur124,125. Siloed academic disciplines limit scientic
approaches to fully understand the interactions
and cumulative impacts of multiple stressors 126.
Climate change will exacerbate this complexity,
altering the nature of interactions to create increased
uncertainty, and magnifying the impacts of such
interacting stressors 127,128. Ultimately, climate change
* Jouray et al (2021) ORRAA Report.
and its symptoms – ocean warming, acidication,
deoxygenation, etc. – will alter the structure and
functioning of the overall ecosystem and the
benets that it provides to humans 126,129. Since the
interactions among these multiple stressors pose
new ocean risks, these risks need to be considered
jointly, and seeking to address individual stressors in
isolation will be insucient to achieve sustainable
development goals 128,130 (Box 3).
In coastal ecosystems where local human impacts are
already prominent, added climate change stressors
will further amplify the interactions across multiple
stressors and their eects on local ecosystems 127,131,132.
For instance, anthropogenic climate change is now
attributed as a contributing cause for many natural
disasters 133. The increased frequency and magnitude
of storms also means there is an increased likelihood
that communities will be hit by multiple disasters
Ocean and coastal ecosystems provide essential
nutrients for many coastal communities in SIDS and
LDCs 28,200. Wild capture sheries and aquaculture
provide 17% of edible meat 201,202, and many coastal
communities depend on seafood as sources of healthy
nutrients. An analysis predicted that coastal sheries
in 16 of the 22 Pacic Island countries and territories
would not be able to provide sucient nutrition to a
rapidly growing population and that improved access to
tuna, more-ecient sheries governance, and expansion
of pond aquaculture can collectively improve food
security and public health 203,204. Further, a study found
a parallel transition in diet to consume more processed,
sweetened, and high caloric food as the changes in
natural environment that provide food take place.
Climate change threatens nutritional security of
communities in SIDS and LDCs in multiple ways. For
instance, climate change will reduce the availability
of sh for these communities 205. Tropical coastal
ecosystems are among the world’s most at-risk to
climate change especially when we take existing
threats such as land use changes and overshing
into consideration. In addition to ocean acidication
and gradual warming of the waters, more frequent
and intense marine heatwaves are expected 206. The
resulting coral bleaching, pole-ward shi of species,
and changes in species productivity will signicantly
reduce the availability of sh and therefore reduce the
variety and abundance of marine-derived nutrients
to these communities 207, with particularly severe
impacts on coastal communities 208. Explicit linkages
between human health and ocean health are evident
in many coastal communities in LDCs and SIDS, where
alternatives to nutritionally rich seafood are scarce –
declines in marine sh populations have been linked to
micronutrient deciencies and corresponding negative
health outcomes 207,28,209,210.
Ocean warming is also a factor in increasingly frequent
harmful algal blooms (HABs). Marine biotoxins
impact marine organisms that feed on toxic algae and
cause catastrophic damage to inshore sheries and
aquaculture operations by killing impacted sh and
shellsh. They could also cause severe food poisoning
for humans who consume impacted sh and shellsh.
A recent large-scale global study conducted by IOC
found 48% of the HAB events involved seafood toxins,
Nutrition, public health, and harmful algal blooms
Box 3
at the same time. On 12 January 2010, a magnitude
7.0 earthquake struck Haiti and displaced over 1.5
million people, or approximately 15% of the total
population (Figure 3). On 14 August 2021, another
major earthquake, magnitude 7.2, struck Haiti, amid
the global COVID-19 pandemic and immediately aer
the assassination of the president on 7 July 2021,
and was rapidly followed by a direct hit by a Tropical
Depression Grace on 16 August 2021. Following the
assassination, gang violence increased and displaced
over 19,000 people in Port-au-Prince, also impacting
food security 134,135. Tropical Depression Grace le
650,000 in need of humanitarian assistance 135.
These events contributed to deteriorating conditions
for stemming the COVID-19 pandemic as it became
more dicult to take preventative measures to avoid
contracting the disease 135.
The interdependencies of economic sectors in SIDS
and LDCs make these countries sensitive to system-
wide shocks such as natural disasters and global
pandemics and can prolong the recovery from such
shocks. Climate change, which produces long-term
gradual changes as well as acute shocks, adds to this
complexity. This new reality requires a corresponding
shi from single-shock or sector-specic risk mindset
to a coupled complex risk mindset 136.
and listed Central America and the Caribbean as one
of the regions seeing an increase in HAB events 211.
SIDS and LDCs lack infrastructure and capacity to
monitor the occurrences of harmful algal blooms, and
thus the consequences of these events can oen be
fatal or cause long term disabilities due to damage to
the nervous system resulting in paralytic, amnesic,
and neurologic symptoms 212. In 2021, an event killed
19 people in Madagascar who consumed a turtle that
had fed on toxic algae 213.
Increased and intensied aquaculture production
that cause nutrient pollution will increase the risks
of HABs211. Developed countries are investing in
early warning systems and forecasting to monitor
harmful algal blooms to reduce the impacts of marine
biotoxins on aquaculture 214. Aquaculture development
and coastal subsistence sheries in SIDS and LDCs
alike can benet from such systems to mitigate future
risks to food safety, nutritional security, and economic
Photo: Kanae Tokunaga
Achieving a sustainable, equitable,
and resilient ocean economy
This report has focused some of the key
environmental and socioeconomic stressors,
that are derived from the ocean and associated
with the ocean economy and highlighted
their associated risks to SIDS and LDCs. The report
has also described the complex web of interactions
created by multiple stressors and illustrated how
ocean risks are coupled complex risks. Resilience
has emerged as a popular approach or concept to
rethink and reshape development for dynamic and
turbulent contexts 137. Resilience refers to abilities
of a social-ecological system to anticipate, absorb,
accommodate, or recover from hazardous events7.
The complexity of ocean risks is mirrored in the
complexity of resilience, which is multidimensional
and dynamic. As such, context-dependent solutions
are essential. The future is expected to bring with it
a growing range of highly complex ocean risks. There
are a number of strategies for enhancing resilience
and several studies have made major progress in
synthesizing across disciplines, domains and systems
to identify more focused lists of these resilience-
enhancing strategies 138–140 .
Novel nancial tools and insurance
During the past decade, an increasing number of
SIDS have started referring themselves as Large
Ocean States or Great Ocean States, recognizing
the vast opportunities that ocean provides for their
economic development 141–143. Indeed, the ocean
oers unprecedented solutions and opportunities
for sustainable and equitable growth 21,144,145. For
instance, the development of oshore renewable
energy and the restoration and conservation of blue
carbon ecosystems such as mangroves and salt
marshes can contribute to reducing GHG emissions
and atmospheric levels of GHGs 144.
Foreign nancing can play a signicant role in
amplifying these countries’ eorts to diversify and
further develop their ocean economy sectors to build
resilience. Some of the key nancial instruments that
can be used to promote a sustainable ocean economy
include traditional loans and grants, carbon markets,
and insurance instruments 146. These instruments
can be designed to incentivize actions that promote
social-ecological system sustainability, conservation,
and equity and to reduce risks that could cause
SIDS and coastal LDCs to deviate from achieving
their development goals. Diversied sources of
nancial capital are a critical component to building
resilience. For example, private equity and venture
capital funds can also promote businesses whose
objectives are aligned with sustainable and socially
equitable economic development; however, less
than USD 50 billion is invested in emerging market
as opposed to USD 300 billion and USD 150 billion
invested in the United States and in Western Europe,
respectively147. Furthermore, a survey of 440 private
investors found that SDG 14 “Life Below Water” is the
least attractive SDG as a target for impact investing,
citing the diculty of turning ocean conservation into
investment products 148 (Box 4).
Public or philanthropic co-nancing or blended
nance, where public nance (e.g., ODA, development
banks) is used to attract private nancing, is critical
for a sustainable ocean economy as there are many
activities that cannot generate market returns 146.*
For example, coral reefs support over 25% of marine
species and 1 billion people worldwide150,151. But,
coral reefs are one of the most costly ecosystem
to restore,152–154, oen associated with large
nancial risk and low or uncertain market return.
There has a critical lack in nancing coral reef
conservation, protection, and restoration 150,151,155.
Thus, a blended nancing approach has been taken
with the establishment of Global Fund for Coral
Reefs in September 2020; the major goal for this is
to facilitate innovation and attract private market-
based investments to conserve and restore coral
reefs 151,156. Blended nance can also be useful for
attracting funds to foster ocean and oshore energy
developments in SIDS and LDCs.
Access to nance is also an essential attribute of
resilience because it can enable communities to
respond to shocks and adapt to changes 157. External
climate and development nancing continue to
represent key avenues to build and strengthen
adaptive capacities of LDCs and SIDS to mitigate
* For the discussion of who bears the risk and who gets paid out
rst, refer to the discussion of capital stack in the Ocean Finance
Handbook 149.
The Sustainable Development Goals (SDGs)
represent a shared vision for the future. Ocean-
related targets described under SDG14 “Life Below
Water” clearly articulate sustainable development
priorities for SIDS and LDCs that leverage ocean
sectors. There are other SDGs and associated
targets that directly address relevant challenges
for SIDS and LDCs, including SDG4 Education (e.g.,
target 4.a that calls for enhancing scholarship and
scientic capacities in SIDS and LDCs) and SDG7
Clean Energy (e.g., target 7.b that calls for increased
supply of modern and sustainable energy sources
in SIDS and LDCs) 130. At the same time, these
development goals reveal important tradeos
that need to be navigated as well as synergies that
can be cultivated to support multiple benets.
For instance, among the nine other targets under
achievement of two targets (target 14.1pollution
and 14.3 ocean acidication) could pose conicts
or tradeos with target 14.7,
three targets (target 14.4 restore sh stocks, 14.a
Scientic knowledge and technology transfer,
and 14.b Access to resources and market for
small shers) support the goal of target 14.7, and
the remaining four targets (target 14.2
Management of coastal and marine ecosystems,
14.5 Protect 10 percent of marine areas, 14.6
Reform sheries subsidies, and 14.c implement
international law) pose varied impacts on
achieving target 14.7 130.
Understanding linkages across dierent goals
nested within the SDGs can help countries evaluate
their progress towards SDGs 180, as well as providing
opportunities for creating co-benets.
Sustainable Development
Box 4
risks. However, it is also important to highlight
complementary measures to build domestic
capabilities (see also ORRAA Report on Gender)*.
For example, there is evidence that developing
internal nancing capabilities, as opposed to external
nancing, is more eective for building disaster
resilience 158. Stability and capabilities of governance
and nancial systems are critical for not attracting
but also improving the eectiveness of foreign
nancing 150,159. As such, investments in the domestic
nance sector as well as governance sector could
help amplify the benets gained through other funds.
* Wabnitz et al (2021) ORRAA Report.
At the country level, the National Adaptation
Plan process, established by the UNFCCC’s COP
16 Cancun Adaptation Framework, have resulted
in 22 developing countries announcing national
adaptation plans (NAPs) (as of March 2021, UNFCCC,
2021). Eorts to develop NAPs in other countries
are also underway with support from sources such
as the Green Climate Fund, a multi-sector funding
mechanism that supports climate mitigation and
adaptation 160,161. Upon approval of their NAPs,
countries can draw on support from Green Climate
Fund to operationalize them by implementing
projects 162. Regional eorts to coordinate adaptation
planning eorts have also started to take shape,
including, for instance, through the Caribbean
Community Climate Change Center and the
Secretariat for the Pacic Regional Environmental
Programme 42.
Greater future uncertainty also creates demands
for insurance. In the aermath of the 2010 Haiti
earthquake, the Caribbean Catastrophe Risk
Insurance Facility (CCRIF), the world’s rst multi-
country risk pool, established in 2007, provided
support to Haiti with over US$ 7.7 million payouts
under its parametric insurance scheme 163. Following
the 2021 earthquake, CCRIF was expected to make
payouts of approximately US$ 40 million 164. To hedge
against extreme weather events, sheries index
insurance was launched for sherfolks in Caribbean
countries by the Caribbean Oceans and Aquaculture
Sustainability Facility (COAST) in July 2019 with
funding support from the US State Department 165
(see also ORRAA Report on Gender)**. Under this
framework, governments can purchase COAST
policies, but to be eligible to participate in this
program, they must also implement the Caribbean
Community Common Fisheries Policy 166. COAST is
a parametric insurance scheme, and the rst of its
kind, in supporting sheries hedge against climate
risks. Meanwhile, mutual insurance schemes
have commonly been used in Asian countries to
insure shers and aquaculture operations due in
part to eorts to stabilize incomes against harvest
Recent studies have found that international
adaptation funding in LDC-SIDS has been ineective
at addressing the root causes of the problems168,169.
For instance, barriers to adaptation to reduce
climate-related disaster risks are oen rooted
in governance and technical capacities as well
as cognitive and cultural factors, yet, adaptation
projects funded by international adaptation funding
are sector specic (e.g., project targeting coastal
shery) 168. Further, existing public and private funds
cannot easily be mobilized to cope with the sudden
emergence of new risks such as COVID-19 41.
** Wabnitz et al (2021) ORRAA Report.
Expanding the knowledge base
Economic theory indicates that public nancing
towards pilot projects can contribute to expanding
investments in climate-related projects 170. Yet,
values of conducting pilot projects may not be
realized if the knowledge gained through the
pilot projects are not transferred to inform future
projects or to inform similar projects in other parts
of the world. Monitoring and evaluations backed by
environmental and socioeconomic data are crucial.
Context-dependent solutions are also essential; for
instance, projects tailored to local ecological systems
may work better than global-scale approaches
under certain ecological conditions 131. A critical
examination aimed at prioritizing and selecting cost-
ecient measures that can provide multiple benets
or co-benets is essential for mitigating climate
change and its impacts 144. All of these can benet
from ne-scale and long-term data.
There are many tools with varying scope
and objectives that can help assess risks and
vulnerabilities to articulate local challenges and
opportunities (Table 2). Yet, again, lack of data in SIDS
Table 2. Examples of dierent types of risk and vulnerability assessment tools and studies.
Reference Scope Key metrics and variables
Assessed countries/
Risk and vulnerability assessments
Heck et al., 2021 176 Assessment of storm risks
to sheries
storm hazard, exposure,
sensitivity, lack of adaptive
Thiault et al., 2018 177 Mapping of social-ecological
ecological exposure, ecological
sensitivity, ecological adaptive
capacity, social exposure, social
sensitivity, social adaptive
Small-scale shery
of Moorea, French
Blasiak et al., 2017 23 Assessment of climate
change vulnerabilities, focus
on coastal communities
climate change exposure,
sensitivity, adaptive capacity
Guillaumont, 2010 178 Assessment of
size and frequency of exogenous
shocks (natural shocks and
external/export shocks), exposure
to shocks, capacity to react to
Country-level/ SIDS
and LDCs
Comte et al., 2019 179 Comparison of eight global
vulnerability assessments
Study objectives, denition
of vulnerability, Formulae for
Monnereau et al., 2017 24 Assessment of climate
change vulnerabilities
in sheries sector, Cross
comparison of dierent
assessment methods
Metrics used to quantify
exposure, sensitivity, and adaptive
and LDCs as well as domestic technical capacities
oen limits their abilities to assess vulnerabilities
and risks at a ner temporal and geospatial
scale. This could limit these countries’ abilities to
benet from state-of-the-art scientic models and
tools. Investments in baseline monitoring, data
collection, and deployment of blue technologies
(e.g., underwater drone, AI for sheries electronic
monitoring) can certainly contribute to mitigating
ocean risks and to building resilience.
At the same time, many communities and cultures
in SIDS and LDCs hold rich local indigenous and
ecological knowledge. Yet, these knowledge
systems are oen neglected and not included in the
scientic and decision-making processes. Scientist
and decision-makers alike can benet from these
knowledge systems to contextualize their ndings
to cra context-specic solutions. Integration of
local indigenous and ecological knowledge as well
as collaborative or participatory approach can be
eective at designing solutions that meet the local
social-ecological context and at overcoming cognitive
or socio-cultural barriers to building resilience 58,171–173.
1. Janssen, M. A. & Ostrom, E. Resilience, vulnerability, and
adaptation: A cross-cutting theme of the International Human
Dimensions Programme on Global Environmental Change. Glob.
Environ. Change 16, 237–239 (2006).
2. UNEP. Blue Economy Concept Paper.
resources/report/blue-economy-concept-paper (2016).
3. Adger, W. N., de Campos, R. S. & Mortreux, C. Mobility,
displacement and migration, and their interactions with
vulnerability and adaptation to environmental risks. in Routledge
handbook of environmental displacement and migration (ed.
McLeman, R and Gemenne, F) 29–41 (2018).
4. Committee on world food security. Coming to terms with
terminology. http://ww (2012).
5. OECD. Ocean economy.
6. NERACOOS. About ocean observing systems. NERACOOS http://
7. IPCC. 2012: Managing the risks of extreme events and disasters to
advance climate change adaptation. A special report of Working
Groups I and II of the Intergovernmental Panel on Climate Change.
in Managing the risks of extreme events and disasters to advance
climate change adaptation: Special report of the intergovernmental
panel on climate change (eds. Barros, V. et al.) (Cambridge
University Press, 2012). doi:10.1017/CBO9781139177245.
8. Putnam, R. D. Bowling alone: America’s declining social capital:
originally published in Journal of Democracy 6 (1), 1995. J. Democr.
6, 65–78 (1995).
9. Thiault, L. et al. Harnessing the potential of vulnerability
assessments for managing social-ecological systems. Ecol. Soc. 26,
art1 (2021).
10. Bindo, N. L. et al. Changing ocean, marine ecosystems, and
dependent communities. in IPCC Special Report on the Ocean and
Cryosphere in a Changing Climate (2019).
11. Britten, G. L., Dowd, M., Kanary, L. & Worm, B. Extended sheries
recovery timelines in a changing environment. Nat. Commun. 8,
15325 (2017).
12. Pecl, G. T. et al. Biodiversity redistribution under climate change:
Impacts on ecosystems and human well-being. Science 355,
eaai9214 (2017).
13. Pershing, A. J. et al. Challenges to natural and human communities
from surprising ocean temperatures. Proc. Natl. Acad. Sci. 116,
18378–18383 (2019).
14. Poloczanska, E. S. et al. Global imprint of climate change on
marine life. Nat. Clim. Change 3, 919–925 (2013).
15. Lam, V. W. Y. et al. Climate change, tropical sheries and prospects
for sustainable development. Nat. Rev. Earth Environ. 1, 440–454
16. Lam, V. W. Y., Cheung, W. W. L., Reygondeau, G. & Sumaila, U.
R. Projected change in global sheries revenues under climate
change. Sci. Rep. 6, 32607 (2016).
17. Lluch-Cota, S. E., Arreguín-Sánchez, F., Salvadeo, C. J. & Del Monte
Luna, P. Climate change impacts, vulnerabilities and adaptations:
Northeast Tropical Pacic marine sheries. in Impacts of climate
change on sheries and aquaculture Synthesis of current knowledge,
adaptation and mitigation options (eds. Barange, M. et al.) (FAO,
18. Oxenford, H. A. & Monnereau, I. Climate change impacts,
vulnerabilities and adaptations: Western Central Atlantic marine
sheries. in Impacts of climate change on sheries and aquaculture
Synthesis of current knowledge, adaptation and mitigation options
(eds. Barange, M. et al.) (FAO, 2018).
19. Thiault, L. et al. Escaping the perfect storm of simultaneous
climate change impacts on agriculture and marine sheries. Sci.
Adv. 5, eaaw9976 (2019).
20. Eddy, T. D. et al. Global decline in capacity of coral reefs to provide
ecosystem services. One Earth 4, 1278–1285 (2021).
21. Hoegh-Guldberg, O., Poloczanska, E. S., Skirving, W. & Dove,
S. Coral Reef Ecosystems under Climate Change and Ocean
Acidication. Front. Mar. Sci. 4, 158 (2017).
22. Hughes, T. P. et al. Global warming transforms coral reef
assemblages. Nature 556, 492–496 (2018).
23. Blasiak, R. et al. Climate change and marine sheries: Least
developed countries top global index of vulnerability. PLOS ONE
12, e0179632 (2017).
24. Monnereau, I. et al. The impact of methodological choices on
the outcome of national-level climate change vulnerability
assessments: An example from the global sheries sector. Fish
Fish. 18, 717–731 (2017).
25. Barclay, K. Impacts of tuna industries on coastal communities in
Pacic Island countries. Mar. Policy 34, 406–413 (2010).
26. Charlton, K. E. et al. Fish, food security and health in Pacic Island
countries and territories: a systematic literature review. BMC
Public Health 16, 285 (2016).
27. Grimes, S. Ocean science for development in SIDS: Facts and
gures. SciDev.Net
science-development-sids-facts-gures/ (2014).
28. Hicks, C. C. et al. Harnessing global sheries to tackle
micronutrient deciencies. Nature 574, 95–98 (2019).
29. Lau, J. D., Hicks, C. C., Gurney, G. G. & Cinner, J. E. What matters
to whom and why? Understanding the importance of coastal
ecosystem services in developing coastal communities. Ecosyst.
Serv. 35, 219–230 (2019).
30. Jouray, J.-B., Blasiak, R., Norström, A. V., Österblom, H. &
Nyström, M. The Blue acceleration: The trajectory of human
expansion into the ocean. One Earth 2, 43–54 (2020).
31. UN. Mid-Term Review of the SAMOA Pathway High level political
sites/53/2019/08/SAMOA-MTR-FINAL.pdf (2019).
32. Blasiak, R. & Wabnitz, C. C. C. Aligning sheries aid with
international development targets and goals. Mar. Policy 88, 86–92
33. UN-OHRLLS. Small Island Developing States: Small Island Big(ger)
SIDS-Small-Islands-Bigger-Stakes.pdf (2011).
34. UNCTAD. LDC - What is a least developed country? https://unctad.
org/press-material/ldc-what-least-developed-country (2017).
35. Robinson, S. & Dornan, M. International nancing for climate
change adaptation in small island developing states. Reg. Environ.
Change 17, 1103–1115 (2017).
36. World Bank. World Bank Country and Lending Groups. https://
world-bank-country-and-lending-groups (2021).
37. Global Environment Facility. Note on ODA eligiblity. https://w ww.les/council-meeting-documents/
38. WTO. WTO committee explores initiatives to increase developing
countries’ trading capacities.
news_e/news21_e/devel_29mar21_e.htm (2021).
39. United Nations. The Least Developed Countries report
2019. (United Nations Publications, 2019). doi:10.1163/
40. IMF. Small states resilience to natural disasters and climate
change - role for the IMF. Policy Pap. 16, (2016).
41. OECD. COVID-19 pandemic Towards a blue recovery in small
island developing states.
42. Thomas, A., Baptiste, A., Martyr-Koller, R., Pringle, P. & Rhiney,
K. Climate change and small island developing states. Annu. Rev.
Environ. Resour. 45, 1–27 (2020).
43. Pala, C. The mice that roared: how eight tiny countries took on
foreign shing eets. The Guardian (2021).
44. Piontek, F. et al. Integrated perspective on translating biophysical
to economic impacts of climate change. Nat. Clim. Change 11,
563–572 (2021).
45. UN Department of Economic and Social Aairs. List of SIDS:
Sustainable Development Knowledge Platform. https://
46. UN. Factsheet: People and Oceans. in (UN, 2017).
47. Folke, C. et al. Our future in the Anthropocene biosphere. Ambio
50, 834–869 (2021).
48. OECD. The Ocean Economy in 2030. (OECD Publishing, 2016).
49. IPCC. 2021: Summary for policymakers. in Climate change 2021:
The Physical science basis. Contribution of Working Group I to the
Sixth Assessment Report of the Intergovernmental Panel on Climate
Change (eds. Masson-Delmotte, V. et al.) (Cambridge University
Press, 2021).
50. Desmet, K. et al. Evaluating the economic cost of coastal ooding.
Am. Econ. J. Macroecon. 13, 444–486 (2021).
51. Kocornik-Mina, A., McDermott, T. K. J., Michaels, G. & Rauch, F.
Flooded Cities. Am. Econ. J. Appl. Econ. 12, 35–66 (2020).
52. Monioudi, I. Ν. et al. Climate change impacts on critical
international transportation assets of Caribbean Small Island
Developing States (SIDS): the case of Jamaica and Saint Lucia. Reg.
Environ. Change 18, 2211–2225 (2018).
53. Rotzoll, K. & Fletcher, C. H. Assessment of groundwater
inundation as a consequence of sea-level rise. Nat. Clim. Change 3,
477–481 (2013).
54. Ratter, B. M. W., Petzold, J. & Sinane, K. Considering the locals:
coastal construction and destruction in times of climate change
on Anjouan, Comoros. Nat. Resour. Forum 40, 112–126 (2016).
55. Yamano, H. et al. Atoll island vulnerability to ooding and
inundation revealed by historical reconstruction: Fongafale Islet,
Funafuti Atoll, Tuvalu. Glob. Planet. Change 57, 407–416 (2007).
56. Bird, D. K., Chagué-Go, C. & Gero, A. Human Response to
Extreme Events: a review of three post-tsunami disaster case
studies. Aust. Geogr. 42, 225–239 (2011).
57. Inazu, D., Ikeya, T., Waseda, T., Hibiya, T. & Shigihara, Y. Measuring
oshore tsunami currents using ship navigation records. Prog.
Earth Planet. Sci. 5, 38 (2018).
58. Sithole, W. W., Naser, M. M. & Guadagno, L. Indigenous knowledge
for disaster risk reduction: documenting community practices in
Papua New Guinea. (International Organization for Migration,
59. McClanahan, T. r. & Cinner, J. e. A framework for adaptive gear and
ecosystem-based management in the artisanal coral reef shery
of Papua New Guinea. Aquat. Conserv. Mar. Freshw. Ecosyst. 18,
493–507 (2008).
60. Silvano, R. A. M. & Valbo-Jørgensen, J. Beyond shermen’s tales:
contributions of shers’ local ecological knowledge to sh ecology
and sheries management. Environ. Dev. Sustain. 10, 657–675
61. Beckford, C. Climate change resiliency in Caribbean SIDS: building
greater synergies between science and local and traditional
knowledge. J. Environ. Stud. Sci. 8, 42–50 (2018).
62. IPCC. 2019: Annex I: Glossary. in IPCC special report on the ocean
and cryosphere in a changing climate (eds. Weyer, N. M. et al.)
63. Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under
global warming. Nature 560, 360–364 (2018).
64. Oliver, E. C. J. et al. Marine Heatwaves. Annu. Rev. Mar. Sci. 13,
313–342 (2021).
65. Oliver, E. C. J. et al. Longer and more frequent marine heatwaves
over the past century. Nat. Commun. 9, 1–12 (2018).
66. Cheung, W. W. L. et al. Large-scale redistribution of maximum
sheries catch potential in the global ocean under climate change.
Glob. Change Biol. 16, 24–35 (2010).
67. Hanich, Q. et al. Small-scale sheries under climate change in the
Pacic Islands region. Mar. Policy 88, 279–284 (2018).
68. Sumaila, U. R., Cheung, W. W. L., Lam, V. W. Y., Pauly, D. & Herrick,
S. Climate change impacts on the biophysics and economics of
world sheries. Nat. Clim. Change 1, 449–456 (2011).
69. Cheung, W. W. L. Signature of ocean warming in global sheries
catch. Nature 497, 365–368 (2013).
70. Golden, C. D. et al. Aquatic foods to nourish nations. Nature 1–6
(2021) doi:10.1038/s41586-021-03917-1.
71. Golden, C. D. et al. Nutrition: Fall in sh catch threatens human
health. Nature 534, 317–320 (2016).
72. Lehodey, P. et al. Vulnerability of oceanic sheries in the tropical
Pacic to climate change. in Vulnerability of tropical pacic sheries
and aquaculture to climate change (eds. Bell, J. D., Johnson, J. E. &
Hobday, A. J.) (Secretariat of the Pacic Community, 2011).
73. Cinner, J. E., Daw, T. & McClanahan, T. R. Socioeconomic Factors
that Aect Artisanal Fishers’ Readiness to Exit a Declining Fishery.
Conserv. Biol. 23, 124–130 (2009).
74. Free, C. M. et al. Impacts of historical warming on marine sheries
production. Science 363, 979–983 (2019).
75. Bailey, M., Rashid Sumaila, U. & Lindroos, M. Application of game
theory to sheries over three decades. Fish. Res. 102, 1–8 (2010).
76. Munro, G. R. The optimal management of transboundary
renewable resources. Can. J. Econ. 355–376 (1979).
77. Pinsky, M. L. et al. Preparing ocean governance for species on the
move. Science 360, 1189–1191 (2018).
78. Hanich, Q., Campbell, B., Bailey, M. & Molenaar, E. Research into
sheries equity and fairness—addressing conservation burden
concerns in transboundary sheries. Mar. Policy 51, 302–304
79. McCauley, D. J. et al. Wealthy countries dominate industrial shing.
Sci. Adv. 4, eaau2161 (2018).
80. Palacios-Abrantes, J. et al. Timing and magnitude of climate
driven range shis in transboundary sh stocks challenge
their management. 2021.08.26.456854 https://ww w. (2021)
81. Palacios-Abrantes, J., Reygondeau, G., Wabnitz, C. C. C. & Cheung,
W. W. L. The transboundary nature of the world’s exploited marine
species. Sci. Rep. 10, 17668 (2020).
82. Spijkers, J. et al. Exploring the future of shery conict through
narrative scenarios. One Earth 0, (2021).
83. Österblom, H. et al. Towards Ocean Equity. 65 (2020).
84. Internal Displacement Monitoring Center. Global Report on Internal
Displacement 2021.
default/les/publications/documents/grid2021_idmc.pdf (2021).
85. Campbell, J. R., Goldsmith, M. & Koshy, K. Community relocation as
an option for adaptation to the eects of climate change and climate
variability in Pacic Island Countries (PICs). (Asia-Pacic Network for
Global Change Research, 2005).
86. Webber, M. & Barnett, J. Accommodating migration to promote
adaptation to climate change. (The World Bank, 2010).
87. Barnett, J. & Chamberlain, N. Migration as climate change
adaptation: implications for the Pacic. Clim. Change Migr. S. Pac.
Perspect. Wellingt. N. Z. Inst. Policy Stud. (2010).
88. McLeman, R. Perception of climate migrants. Nat. Clim. Change 10,
600–601 (2020).
89. Suprenant, M. P. et al. Internal Displacement’s Impacts on Health
in Yemen.
pdf (2020).
90. Cinner, J. E. et al. Building adaptive capacity to climate change in
tropical coastal communities. Nat. Clim. Change 8, 117–123 (2018).
91. Petzold, J. & Magnan, A. K. Climate change: thinking small islands
beyond Small Island Developing States (SIDS). Clim. Change 152,
145–165 (2019).
92. Robinson, S. Climate change adaptation in SIDS: A systematic
review of the literature pre and post the IPCC Fih Assessment
Report. WIREs Clim. Change 11, e653 (2020).
93. Cassels, S., Curran, S. R. & Kramer, R. Do migrants degrade coastal
environments? Migration, natural resource extraction and poverty
in North Sulawesi, Indonesia. Hum. Ecol. 33, 329–363 (2005).
94. Betzold, C. Adapting to climate change in small island developing
states. Clim. Change 133, 481–489 (2015).
95. Remling, E. Migration as climate adaptation? Exploring discourses
amongst development actors in the Pacic Island region. Reg.
Environ. Change 20, 3 (2020).
96. Wabnitz, C. C., Cisneros-Montemayor, A. M., Hanich, Q. & Ota, Y.
Ecotourism, climate change and reef sh consumption in Palau:
Benets, trade-os and adaptation strategies. Mar. Policy 88,
323–332 (2018).
97. Wabnitz, C. C. C. Adapting tourist seafood consumption practices
in Pacic Islands to climate change. in Predicting Future Oceans
215–225 (Elsevier, 2019). doi:10.1016/B978-0-12-817945-1.00020-
98. UN Environment Programme. SIDS Waste Management Outlook.
99. Verlis, K. M. & Wilson, S. P. Paradise Trashed: Sources and
solutions to marine litter in a small island developing state. Waste
Manag. 103, 128–136 (2020).
100. World Tourism Organization. COVID-19 Related Travel Restricitons:
A global review for tourism: Ninth Report as of 8 March 2021. https://
03/210309-Travel-Restrictions.pdf (2021).
101. Desai, K., Zutt, J., Maharaj, D., Phelps, J. & Adhikari, R. Debt and
Access to Finance for Small Island Developing States in the Era of
COVID-19 and Beyond. (2021).
102. Hudson, A. The ocean and COVID-19. United Nations Development
103. Soto, E. H. et al. How does the beach ecosystem change without
tourists during COVID-19 lockdown? Biol. Conserv. 255, 108972
104. Gibbons, D. W. et al. The relative importance of COVID-19
pandemic impacts on biodiversity conservation globally. Conserv.
Biol. (2021) doi:10.1111/cobi.13781.
105. UN ESCAP. Changing Sails: Accelerating Regional Actions
for Sustainable Oceans in Asia and the Pacic. (UN, 2020).
106. OHRLLS & FAO. COVID19 and Impacts on Food Security in LDCs,
LLDCs and SIDS. https://w
ohrlls/les/ohrlls-fao-report_nal.pdf (2020).
107. Bennett, N. J. et al. The COVID-19 Pandemic, small-scale sheries
and coastal shing communities. Coast. Manag. 48, 336–347
108. Stoll, J. S. et al. Alternative Seafood Networks During COVID-19:
Implications for resilience and sustainability. Front. Sustain. Food
Syst. 5, 614368 (2021).
109. ESMAP. Going Global: Expanding Oshore Wind to Emerging
Markets. (World Bank, 2019).
110. Tao, J. Y. & Finenko, A. Moving beyond LCOE: impact of various
nancing methods on PV protability for SIDS. Energy Policy 98,
749–758 (2016).
111. Genave, A., Blancard, S. & Garabedian, S. An assessment of energy
vulnerability in Small Island Developing States. Ecol. Econ. 171,
106595 (2020).
112. Feinstein, C. SIDS – Towards a sustainable energy future. (2014).
113. Tokunaga, K. & Konan, D. E. Home grown or imported? Biofuels life
cycle GHG emissions in electricity generation and transportation.
Appl. Energy 125, 123–131 (2014).
114. Chase, V. et al. Independent evaluation of the relevance and
eectiveness of the green climate fund’s investments in small island
developing states.
les/document/201123-sids-nal-report-top-web_2.pdf (2020).
115. IRENA. Fostering a blue economy: Oshore renewable energy. 48
116. Lucas, H., Fita, S., Talab, I., Marschel, C. & Cabeza, L. F. Critical
challenges and capacity building needs for renewable energy
deployment in Pacic Small Island Developing States (Pacic
SIDS). Renew. Energy 107, 42–52 (2017).
117. Low-carbon futures in Least Developed Countries. World Resources
carbon-futures-least-developed-countries (2019).
118. OECD. The 0.7% ODA/GNI target - a history. https://www.oecd.
nance-standards/the07odagnitarget-ahistory.htm (2016).
119. OECD. Making development co-operation work for small island
developing states. (OECD Publishing, 2018).
120. Carney, M. Breaking the tragedy of the horizon–climate change
and nancial stability. (2015).
121. Chenet, H., Ryan-Collins, J. & van Lerven, F. Finance, climate-
change and radical uncertainty: Towards a precautionary
approach to nancial policy. Ecol. Econ. 183, 106957 (2021).
122. Network for greening the nancial system. Annual Report 2020.les/medias/documents/
ngfs_annual_report_2020.pdf (2021).
123. Dikau, S. & Volz, U. Central bank mandates, sustainability
objectives and the promotion of green nance. Ecol. Econ. 184,
107022 (2021).
124. Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative
eects of multiple human stressors in marine systems. Ecol. Lett.
11, 1304–1315 (2008).
125. Crona, B. et al. Sharing the seas: a review and analysis of ocean
sector interactions. Environ. Res. Lett. 16, 063005 (2021).
126. Orr, J. A. et al. Towards a unied study of multiple stressors:
divisions and common goals across research disciplines. Proc. R.
Soc. B Biol. Sci. 287, 20200421 (2020).
127. Gissi, E. et al. A review of the combined eects of climate change
and other local human stressors on the marine environment. Sci.
Total Environ. 755, 142564 (2021).
128. Simpson, N. P. et al. A framework for complex climate change risk
assessment. One Earth 4, 489–501 (2021).
129. Doney, S. C. et al. Climate change impacts on marine ecosystems.
Annu. Rev. Mar. Sci. 4, 11–37 (2012).
130. Blanc, D. L., Freire, C. & Vierros, M. Mapping the linkages between
oceans and other Sustainable Development Goals: A preliminary
exploration. UNDESA Work. Pap. 34 (2017).
131. He, Q. & Silliman, B. R. Climate change, human impacts, and
coastal ecosystems in the anthropocene. Curr. Biol. 29, R1021–
R1035 (2019).
132. Schulte to Bühne, H., Tobias, J. A., Durant, S. M. & Pettorelli,
N. Improving predictions of climate change–land use change
interactions. Trends Ecol. Evol. 36, 29–38 (2021).
133. Pidcock, R. & McSweeney, R. Mapped: How climate change aects
extreme weather around the world. Carbon Brief https://www.ects-extreme-
weather-around-the-world (2021).
134. OCHA. Haiti: Flash Appeal - Earthquake (August 2021) - Haiti.
earthquake-august-2021 (2021).
135. OCHA Haiti. Haiti: Earthquake: Situation Report No. 3. https://les/resources/2021-08-31_
Haiti%20earthquake%20-%20SitRep%233.pdf (2021).
136. Zscheischler, J. et al. Future climate risk from compound events.
Nat. Clim. Change 8, 469–477 (2018).
137. Reyers, B., Folke, C., Moore, M.-L., Biggs, R. & Galaz, V. Social-
ecological systems insights for navigating the dynamics of the
anthropocene. Annu. Rev. Environ. Resour. 43, 267–289 (2018).
138. Berkes, F. & Ross, H. Community resilience: Toward an integrated
approach. Soc. Nat. Resour. 26, 17 (2013).
139. Biggs, R. et al. Toward principles for enhancing the resilience of
ecosystem services. Annu. Rev. Environ. Resour. 37, 421–448 (2012).
140. Carpenter, S. R. et al. General resilience to cope with extreme
events. Sustainability 4, 3248–3259 (2012).
141. Chan, N. “Large Ocean States”: Sovereignty, small islands, and
marine protected areas in global oceans governance. Glob. Gov.
Rev. Multilateralism Int. Organ. 24, 537–555 (2018).
142. Devex & The World Economic Forum. Catalyzing a new future:
From small islands to great ocean states. (2021).
143. Hume, A. et al. Towards an ocean-based large ocean states country
classication. Mar. Policy 134, 104766 (2021).
144. Gattuso, J.-P. et al. Ocean solutions to address climate change and
its eects on marine ecosystems. Front. Mar. Sci. 5, 337 (2018).
145. Morrison, T. H. et al. Advancing coral reef governance into the
anthropocene. One Earth 2, 64–74 (2020).
146. Sumaila, U. R. et al. Financing a sustainable ocean economy. Nat.
Commun. 12, 3259 (2021).
147. Ahmad, R. A., Reed, L. & Zhang, R. Private equity and venture
capital’s role in catalyzing sustainable investment. (International
Finance Corporation, Washington, DC, 2018). doi:10.1596/31056.
148. Libes, L. & Eldridge, M. Who, What, Where and How: 440 Investors.
Report-440-Investors-March-2019.pdf (2019).
149. Friends of Ocean Action. The ocean nance handbook: Increasing
nance for a healthy ocean.
150. Iyer, V., Mathias, K., Meyers, D., Victurine, R. & Walsh, M. Finance
tools for coral reef conservation: A guide. https://www.icriforum.
151. UNDP. Global Fund for Coral Reefs launches fundraising
campaign. United Nations Development Programme https://www.
fundraising-campaign (2021).
152. Bayraktarov, E. et al. The cost and feasibility of marine coastal
restoration. Ecol. Appl. 26, 1055–1074 (2016).
153. Secretariat of the convention on biological diversity. High-level
panel on global assessment of resources for implementing the
strategic plan for biodiversity 2011-2020.
154. Global biodiversity outlook 4: a mid-term assessment of progress
towards the implementation of the strategic plan for biodiversity
2011-2020. (Secretariat for the Convention on Biological Diversity,
155. Cooper, C. Today’s conservation challenges are bigger than
any one solution – or funder. Alliance magazine https://ww w.
bigger-than-any-one-solution-or-funder/ (2021).
156. Global Fund for Coral Reefs. How We Work. Global Funds for Coral
157. Green, K. M. et al. How adaptive capacity shapes the adapt, react,
cope response to climate impacts: insights from small-scale
sheries. Clim. Change 164, 15 (2021).
158. Zhang, D. & Managi, S. Financial development, natural disasters,
and economics of the Pacic small island states. Econ. Anal. Policy
66, 168–181 (2020).
159. Cisneros-Montemayor, A. M. et al. Enabling conditions for an
equitable and sustainable blue economy. Nature 591, 396–401
160. UNFCCC. National Adaptation Plans 2020.
default/les/resource/NAP-progress-publication-2020.pdf (2021).
161. Green Climate Fund. About GCF. Green Climate Fund https://w ww. (2021).
162. Green Climate Fund. Approved projects. Green Climate Fund
https://w (2021).
163. CCRIF SPC. About Us.
164. CCRIF. CCRIF to make US$40 million payout to Haiti following
devastating August 14 earthquake - Haiti. ReliefWeb https://
following-devastating-august-14-earthquake (2021).
165. Sainsbury, N. C., Turner, R. A., Townhill, B. L., Mangi, S. C. &
Pinnegar, J. K. The challenges of extending climate risk insurance
to sheries. Nat. Clim. Change 9, 896–897 (2019).
166. The Caribbean Catastrophe Risk Insurance Facility & World Bank
Group. The Caribbean Oceans and Aquaculture Sustainability
Facility. (2019).
167. Li, H. Experience and enlightenment of the shery mutual
insurance system in asian countries. Asian Agric. Res. 5, 127–130
168. Kuruppu, N. & Willie, R. Barriers to reducing climate enhanced
disaster risks in least developed country-small islands through
anticipatory adaptation. Weather Clim. Extrem. 7, 72–83 (2015).
169. Pelling, M. Urban governance and disaster risk reduction in the
Caribbean: the experiences of Oxfam GB. Environ. Urban. 23,
383–400 (2011).
170. Kotchen, M. J. & Costello, C. Maximizing the impact of climate
nance: Funding projects or pilot projects? J. Environ. Econ. Manag.
92, 270–281 (2018).
171. Aswani, S. & Hamilton, R. J. Integrating indigenous ecological
knowledge and customary sea tenure with marine and social
science for conservation of bumphead parrotsh ( Bolbometopon
muricatum ) in the Roviana Lagoon, Solomon Islands. Environ.
Conserv. 31, 69–83 (2004).
172. DeCaro, D. A., Arnold, C. A. (Tony), Frimpong Boamah, E. &
Garmestani, A. S. Understanding and applying principles of
social cognition and decision making in adaptive environmental
governance. Ecol. Soc. 22, (2017).
173. Kuruppu, N. & Liverman, D. Mental preparation for climate
adaptation: The role of cognition and culture in enhancing
adaptive capacity of water management in Kiribati. Glob. Environ.
Change 21, 657–669 (2011).
174. UN Committee for Development Policy Secretariat. Triennial
review dataset 2000-2018.
html/ (2018).
175. UNCTAD. Memo items of development status groups and
composition. UNCTADstat - Classications https://unctadstat.cations.html (2021).
176. Heck, N., Beck, M. W. & Reguero, B. Storm risk and marine
sheries: a global assessment. Mar. Policy 132, 104698 (2021).
177. Thiault, L. et al. Mapping social–ecological vulnerability to inform
local decision making. Conserv. Biol. 32, 447–456 (2018).
178. Guillaumont, P. Assessing the economic vulnerability of small
island developing states and the least developed countries. J. Dev.
Stud. 46, 828–854 (2010).
179. Comte, A., Pendleton, L. H., Bailly, D. & Quillérou, E. Conceptual
advances on global scale assessments of vulnerability: Informing
investments for coastal populations at risk of climate change. Mar.
Policy 99, 391–399 (2019).
180. OECD. Sustainable Development Goals and
181. Moltmann, T. et al. A Global Ocean Observing System (GOOS),
Delivered through enhanced collaboration across regions,
communities, and new technologies. Front. Mar. Sci. 6, 291 (2019).
182. Mycoo, M. A. Beyond 1.5°C: vulnerabilities and adaptation
strategies for Caribbean small island developing states. Reg.
Environ. Change 18, 2341–2353 (2018).
183. Tanhua, T. et al. What we have learned from the framework for
ocean observing: evolution of the global ocean observing system.
Front. Mar. Sci. 6, 471 (2019).
184. PNA Oce. PNA Oce Year Book 2019. (2019).
185. Havice, E. The structure of tuna access agreements in the
Western and Central Pacic Ocean: Lessons for vessel day scheme
planning. Mar. Policy 34, 979–987 (2010).
186. Miller, K. A. Climate variability and tropical tuna: management
challenges for highly migratory sh stocks. Mar. Policy 31, 56–70
187. Havice, E. Rights-based management in the Western and Central
Pacic Ocean tuna shery: Economic and environmental change
under the Vessel Day Scheme. Mar. Policy 42, 259–267 (2013).
188. Yeeting, A. D., Weikard, H. P., Bailey, M., Ram-Bidesi, V. & Bush, S.
R. Stabilising cooperation through pragmatic tolerance: the case
of the Parties to the Nauru Agreement (PNA) tuna shery. Reg.
Environ. Change 18, 885–897 (2018).
189. Adolf, S., Bush, S. R. & Vellema, S. Reinserting state agency in
global value chains: The case of MSC certied skipjack tuna. Fish.
Res. 182, 79–87 (2016).
190. Hare, S. R. et al. The western and central Pacic tuna shery: 2019
overview and status of stocks. 55 https://ocean
191. Lehodey, P., Senina, I., Calmettes, B., Hampton, J. & Nicol, S.
Modelling the impact of climate change on Pacic skipjack tuna
population and sheries. Clim. Change 119, 95–109 (2013).
192. Senina, I. et al. Impact of climate change on tropical tuna species
and tuna sheries in Pacic Island waters and high seas areas. http://leadmin/user_upload/common_oceans/docs/
Final-report-PacicTunaClimateChange.pdf (2018).
193. Bell, J. D. et al. Pathways to sustaining tuna-dependent Pacic
Island economies during climate change. Nat. Sustain. 1–11 (2021)
194. Bell, J. D. et al. Eects of climate change on oceanic sheries in the
tropical Pacic: implications for economic development and food
security. Clim. Change 1–14 (2012).
195. Clark, S. et al. Chapter 12. The Parties to the Nauru Agreement
(PNA) ‘Vessel Day Scheme’: A cooperative shery management
mechanism assisting member countries adapt to climate
variability and change. in Adaptive management of sheries in
response to climate change (FAO, 2021). doi:10.4060/cb3095en.
196. Priddle, E., Burden, M., Landman, J. & Kleisner, K. Climate-related
impacts on sheries management and governance in the North East
Atlantic. 37 (2017).
197. Dunn, S., Rodwell, L. & Joseph, G. The Palau Arrangement for
the management of the Western Pacic purse seine shery-
management scheme (Vessel Day Scheme). in Sharing the Fish
Conference, Perth (2006).
198. Pew Charitable Trust. Harvest control rules. Harvest control rules
approaches to eective long-term sheries management http://pew.
org/2adpw3p (2016).
199. Kritzer, J. P., Costello, C., Mangin, T. & Smith, S. L. Responsive
harvest control rules provide inherent resilience to adverse eects
of climate change and scientic uncertainty. ICES J. Mar. Sci. 76,
1424–1435 (2019).
200. Farmery, A. K. et al. Conceptualising value chain research to
integrate multiple food system elements. Glob. Food Secur. 28,
100500 (2021).
201. FAO. The State of World Fisheries and Aquaculture 2020. (FAO,
2020). doi:10.4060/ca9229en.
202. Lubchenco, J., Haugan, P. M. & Pangestu, M. E. Five priorities for a
sustainable ocean economy. Nature 588, 30–32 (2020).
203. Bell, J. D. et al. Diversifying the use of tuna to improve food security
and public health in Pacic Island countries and territories. Mar.
Policy 51, 584–591 (2015).
204. World Bank & United Nations Department of Economic and
Social Aairs. The Potential of the Blue Economy: Increasing
Long-term Benets of the Sustainable Use of Marin Resources
for Small Island Developing Staets and Coastal Least Developed
205. Gaines, S. et al. The Expected impacts of climate change on the
ocean economy. 56
impacts-climate-change-ocean-economy (2019).
206. IPCC. 2019: Summary for policymakers. in IPCC Special Report on
the Ocean and Cryosphere in a Changing Climate (eds. Pörtner, H.-O.
et al.) (2019).
207. Golden, C. D. et al. Nutrition: Fall in sh catch threatens human
health. Nat. News 534, 317 (2016).
208. World Health Organization. Guidance on mainstreaming
biodiversity for nutrition and health.
dd2b2924186a.pdf?sf vrsn=afd00782_1&download=true (2020).
209. Maire, E. et al. Micronutrient supply from global marine sheries
under climate change and overshing. Curr. Biol. 31, 4132-4138.e3
210. Golden, C. D. et al. Social-ecological traps link food systems to
nutritional outcomes. Glob. Food Secur. 30, 100561 (2021).
211. IOC. An unprecedented analysis on global harmful algal blooms
launched by IOC.
analysis-global-harmful-algal-blooms-launched-ioc (2021).
212. Visciano, P. et al. Marine biotoxins: Occurrence, toxicity, regulatory
limits and reference methods. Front. Microbiol. 7, 1051 (2016).
213. AFP. Nineteen die in Madagascar aer eating turtle. CGTN Africa
214. Fernandes-Salvador, J. A. et al. Current status of forecasting toxic
harmful algae for the north-east Atlantic shellsh aquaculture
industry. Front. Mar. Sci. 8, 656 (2021).
ResearchGate has not been able to resolve any citations for this publication.
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Technical Report
This evaluation assesses whether the GCF’s approach and investments have been relevant and effective in reducing the vulnerability of local communities in LDCs and of their livelihoods to the effects of climate change, and whether these impacts are likely to be sustained. It examines how and to what extent the GCF’s approach, mechanisms and financial modalities respond to the conditions facing LDCs. Moreover, the evaluation assesses the key enabling conditions for the GCF to support a paradigm shift towards low emission and climate resilient development pathways in LDCs. The evaluation team has structured the main findings and recommendations according to the core chapters of the report: responsiveness and relevance of the GCF to LDCs, coherence and complementarity of the GCF with other climate funds, country ownership and capacity development in LDCs, performance of the GCF’s business model and processes in LDCs, and results and impacts.
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Coral reefs worldwide are facing impacts from climate change, overfishing, habitat destruction, and pollution. The cumulative effect of these impacts on global capacity of coral reefs to provide ecosystem services is un- known. Here, we evaluate global changes in extent of coral reef habitat, coral reef fishery catches and effort, Indigenous consumption of coral reef fishes, and coral-reef-associated biodiversity. Global coverage of living coral has declined by half since the 1950s. Catches of coral-reef-associated fishes peaked in 2002 and are in decline despite increasing fishing effort, and catch-per-unit effort has decreased by 60% since 1950. At least 63% of coral-reef-associated biodiversity has declined with loss of coral extent. With projected continued degradation of coral reefs and associated loss of biodiversity and fisheries catches, the well-being and sustain- able coastal development of human communities that depend on coral reef ecosystem services are threatened.
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Despite contributing to healthy diets for billions of people, aquatic foods are often undervalued as a nutritional solution because their diversity is often reduced to the protein and energy value of a single food type (‘seafood’ or ‘fish’)1–4. Here we create a cohesive model that unites terrestrial foods with nearly 3,000 taxa of aquatic foods to understand the future impact of aquatic foods on human nutrition. We project two plausible futures to 2030: a baseline scenario with moderate growth in aquatic animal-source food (AASF) production, and a high-production scenario with a 15-million-tonne increased supply of AASFs over the business-as-usual scenario in 2030, driven largely by investment and innovation in aquaculture production. By comparing changes in AASF consumption between the scenarios, we elucidate geographic and demographic vulnerabilities and estimate health impacts from diet-related causes. Globally, we find that a high-production scenario will decrease AASF prices by 26% and increase their consumption, thereby reducing the consumption of red and processed meats that can lead to diet-related non-communicable diseases5,6 while also preventing approximately 166 million cases of inadequate micronutrient intake. This finding provides a broad evidentiary basis for policy makers and development stakeholders to capitalize on the potential of aquatic foods to reduce food and nutrition insecurity and tackle malnutrition in all its forms. Data on the nutrient content of almost 3,000 aquatic animal-source foods is combined with a food-systems model to show that an increase in aquatic-food production could reduce the inadequate intake of most nutrients.
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Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish.
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Fish are rich in bioavailable micronutrients, such as zinc and iron, deficiencies of which are a global food security concern.¹,² Global marine fisheries yields are threatened by climate change and overfishing,³,⁴ yet understanding of how these stressors affect the nutrients available from fisheries is lacking.⁵,⁶ Here, using global assessments of micronutrient content² and fisheries catch data,⁷ we investigate how the vulnerability status of marine fish species⁸,⁹ may translate into vulnerability of micronutrient availability at scales of both individual species and entire fishery assemblages for 157 countries. We further quantify the micronutrient evenness of catches to identify countries where interventions can optimize micronutrient supply. Our global analysis, including >800 marine fish species, reveals that, at a species level, micronutrient availability and vulnerability to both climate change and overfishing varies greatly, with tropical species displaying a positive co-tolerance, indicating greater persistence to both stressors at a community level.¹⁰ Global fisheries catches had relatively low nutritional vulnerability to fishing. Catches with higher species richness tend to be nutrient dense and evenly distributed but are more vulnerable to climate change, with 40% of countries displaying high vulnerability. Countries with high prevalence of inadequate micronutrient intake tend to have the most nutrient-dense catches, but these same fisheries are highly vulnerable to climate change, with relatively lower capacity to adapt.¹¹ Our analysis highlights the need to consolidate fisheries, climate, and food policies to secure the sustainable contribution of fish-derived micronutrients to food and nutrition security.
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Recognized as an emerging global crisis in the mid-1990s, the “nutrition transition” is marked by a shift to Western diets, dominated by highly processed, sugar-sweetened, and high caloric foods. Occurring in parallel to these health transitions are dramatic shifts in the natural systems that underlie food availability and access. Traditionally, environmental degradation and ecosystem change, and processes of nutritional transition, though often collinear and potentially causally linked, have been addressed in isolation. Food systems represent an emblematic social-ecological system, as both cultivated and wild foods are directly reliant on natural ecosystems and their processes. While healthy ecosystems are a necessary precondition of food production, they are not themselves sufficient to ensure continued benefits from local food systems. Mediating between food production and nutritional security are myriad governance and market institutions that shape differential access to food resources. Moreover, globalization and urbanization may shift communities from non-market to market-based economies, with profound implications for local environments and food systems. Specifically, we argue that it is this feedback between coupled socioeconomic and natural dynamics within food systems that reinforces specific nutritional outcomes, and may result in a social-ecological trap. Here, we use the case of reef-based food systems globally, paying particular attention to the Pacific to showcase social-ecological traps present in global food systems, and to illustrate how such traps lead to the acceleration of the nutrition transition. Improving both nutritional and environmental outcomes of food systems requires understanding the underlying drivers of each, and how they interact and reinforce each other. Only in recognizing these interactions and coupled dynamics will economic, governance, and environmental policies be positioned to address these food system challenges in an integrated fashion.
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Across the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal) the shellfish aquaculture industry is dominated by the production of mussels, followed by oysters and clams. A range of spatially and temporally variable harmful algal bloom species (HABs) impact the industry through their production of biotoxins that accumulate and concentrate in shellfish flesh, which negatively impact the health of consumers through consumption. Regulatory monitoring of harmful cells in the water column and toxin concentrations within shellfish flesh are currently the main means of warning of elevated toxin events in bivalves, with harvesting being suspended when toxicity is elevated above EU regulatory limits. However, while such an approach is generally successful in safeguarding human health, it does not provide the early warning that is needed to support business planning and harvesting by the aquaculture industry. To address this issue, a proliferation of web portals have been developed to make monitoring data widely accessible. These systems are now transitioning from “nowcasts” to operational Early Warning Systems (EWS) to better mitigate against HAB-generated harmful effects. To achieve this, EWS are incorporating a range of environmental data parameters and developing varied forecasting approaches. For example, EWS are increasingly utilizing satellite data and the results of oceanographic modeling to identify and predict the behavior of HABs. Modeling demonstrates that some HABs can be advected significant distances before impacting aquaculture sites. Traffic light indices are being developed to provide users with an easily interpreted assessment of HAB and biotoxin risk, and expert interpretation of these multiple data streams is being used to assess risk into the future. Proof-of-concept EWS are being developed to combine model information with in situ data, in some cases using machine learning-based approaches. This article: (1) reviews HAB and biotoxin issues relevant to shellfish aquaculture in the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal; (2) evaluates the current status of HAB events and EWS in the region; and (3) evaluates the potential of further improving these EWS though multi-disciplinary approaches combining heterogeneous sources of information.
International development country classifications are important for achieving development goals by directing differential support to a group of countries facing common development constraints. The small island developing States (SIDS) classification is a widely used country classification supporting developing island nations. Some nations are now self-identifying as “large ocean states” (LOS), citing the central role of the ocean for their development. Here we show the need for a new ocean-based LOS country classification by highlighting important limitations of current classifications. We analyze this further by enumerating 15 nations self-identifying as LOS since 2001 in official UN statements, most often citing ocean-based economy, size of ocean territory, and vulnerability to climate change as evidence. An ocean-based LOS classification, which requires further research to fully define, would complement existing classifications by targeting countries that disproportionately rely on the ocean to achieve sustainable development priorities, including the United Nations Sustainable Development Goals.
Coastal storms can affect marine fisheries in multiple ways and have the potential to negatively affect the socio-economic well-being of fishery dependent coastal nations. To date, storm risk to marine fisheries is poorly understood. This study provides a global assessment of coastal nations’ risk to storm impacts on their fisheries. We calculated a risk index of coastal nations to storms using the 5th IPCC risk framework. We find that tropical countries in the Caribbean, South- East Asia, and Oceania are most at risk, with multiple Small Island Developing States ranking the highest. Most coastal nations in Africa ranked low for overall risk, due to low exposure, but highest in terms of vulnerability. In addition, we detect a positive correlation between fishery specific adaptive capacity and the general adaptive capacity of coastal countries, suggesting that the capacities of fisheries to respond to climate change might be related to broader national adaptation capacities. The index provides can be used to guide the development of targeted strategies for increasing adaptive capacity of fishery dependent nations to storms, which are a significant threat to the well-being of coastal nations.
Estimates of climate change’s economic impacts vary widely, depending on the applied methodology. This uncertainty is a barrier for policymakers seeking to quantify the benefits of mitigation. In this Perspective, we provide a comprehensive overview and categorization of the pathways and methods translating biophysical impacts into economic damages. We highlight the open question of the persistence of impacts as well as key methodological gaps, in particular the effect of including inequality and adaptation in the assessments. We discuss the need for intensifying interdisciplinary research, focusing on the uncertainty of econometric estimates of damages as well as identification of the most socioeconomically relevant types of impact. A structured model intercomparison related to economic impacts is noted as a crucial next step. Uncertainty in estimates of the economic impacts of climate change makes it difficult to evaluate the benefits of mitigation. This Perspective reviews methods for determining economic damages from biophysical impacts, highlights critical gaps and suggests priorities moving forward.