essay on climate change adaptation

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What is climate change adaptation and why is it crucial?

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• Adaptation refers to a wide range of measures to reduce vulnerability to climate change impacts, from planting crop varieties that are more resistant to drought to enhancing climate information and early warning systems to building stronger defences against floods.
• As the impacts of climate change accelerate — including more extreme weather and sea level rise — it is increasingly urgent that countries and communities adapt.
• Adaptation faces challenges including inadequate finance, knowledge gaps, and institutional constraints, particularly in developing countries.
• International agreements such as the Global Goal on Adaptation and the Global Stocktake are key to driving progress. So too are comprehensive National Adaptation Plans.
• Despite constraints, developing countries are among those leading the way on adaptation.

What is climate change adaptation?

Climate change adaptation refers to actions that help reduce vulnerability to the current or expected impacts of climate change like weather extremes and hazards, sea-level rise, biodiversity loss, or food and water insecurity.

Many adaptation measures need to happen at the local level, so rural communities and cities have a big role to play. Such measures include planting crop varieties that are more resistant to drought and practicing regenerative agriculture, improving water storage and use, managing land to reduce wildfire risks, and building stronger defences against extreme weather like floods and heat waves.   However, adaptation also needs to be driven at the national and international levels. In addition to developing the policies needed to guide adaptation, governments need to look at large-scale measures such as strengthening or relocating infrastructure from coastal areas affected by sea-level rise, building infrastructure able to withstand more extreme weather conditions, enhancing early warning systems and access to disaster information, developing insurance mechanisms specific to climate-related threats, and creating new protections for wildlife and natural ecosystems.

Why do we need to adapt? And why is it so urgent?

Scientific studies show that the Earth is now about 1.1°C warmer than it was in the 1800s. This warming is causing widespread and rapid changes in our planet’s atmosphere, ocean and ecosystems. As a result, weather and climate extremes are becoming more frequent in every region of the world. 

According to climate models, without significant climate action, the world is headed for 2.5 to 2.9°C temperature rise above pre-industrial levels this century, which is well above the safety limits established by scientists. 

With every fraction of a degree of warming, the impacts of climate change will become more frequent and more intense – and adaptation will become that much harder and more expensive for people and ecosystems. 

The urgency is especially great for developing countries, which are already feeling the impacts of climate change and are particularly vulnerable due to a combination of factors, including their geographical and climatic conditions, their high dependence on natural resources, and their limited capacity to adapt to a changing climate. Adaptation is also particularly important for women and young children, older populations, ethnic minorities, Indigenous Peoples, refugees and displaced persons, who are shown to be disproportionately affected by climate change.

Even in very positive scenarios in which we manage to significantly and swiftly cut greenhouse gas emissions, climate change will continue to impact our world for decades to come because of the energy already trapped in the system. This means cutting down emissions is only one part of our response to the climate crisis: adaptation is needed to limit the impacts and safeguard people and nature.

Climate change threatens the viability of agricultural livelihoods worldwide. Photo: Anesu Freddy/UNDP Zimbabwe

Nature-based solutions, such as planting mangroves, are key to adaptation. Photo: David Estrada/Grupo Creativo Naturaleza Secreta

What are the challenges related to climate change adaptation? 

Efforts to adapt to the impacts of climate change face a number of significant challenges.

The first major bottleneck for adaptation action is the availability of and access to finance. In fact, the adaptation finance needs of developing countries are estimated to be 10 to 18 times larger than what is currently available from public sources. 

Finance is needed to drive investment in a range of adaptation solutions, so countries can learn what works and scale up what is most effective. But it is also needed to empower communities – those on the frontlines of climate change – in locally-led, locally-appropriate action. 

Another major challenge is information and knowledge gaps. Accurate climate data is not easily available in many developing countries – localized risk assessments often do not exist – and systems for monitoring, learning and evaluation of adaptation are still fragmented. Without these pieces of the puzzle, it is difficult for governments, communities and the private sector to plan effectively and make sound decisions on where to invest. 

Finally, institutional and governance constraints are a major issue. Challenges of coordination among sectors and levels of government, and lack of specialized knowledge and experience – for example in realizing climate-risk informed planning and investments – are hindering effective adaptation in many countries.  

Climate information is crucial for communities, authorities and policymakers to make sound decisions. Photo: UNDP Malawi

What is the Global Goal on Adaptation?

The Global Goal on Adaptation, often referred to as "GGA”, is a key component of the Paris Agreement. It commits all 196 Parties of the Paris Agreement to enhancing resilience, reducing vulnerability, and supporting adaptation actions.

Its inclusion in the Paris Agreement was significant because it underscores the equal importance of adapting to climate change alongside efforts to reduce emissions. It also recognizes the vulnerability of developing countries to climate impacts and encourages support for their adaptation efforts.

At COP28 in Dubai , as part of the Global Stocktake , world leaders took decisions on the GGA, now named the “UAE Framework for Global Climate Resilience.” Countries agreed to global time-bound targets around specific themes and sectors – for example in areas such as water and sanitation, food and agriculture, and poverty eradication and livelihoods – as well as under what’s called the “ adaptation cycle ,” a global framework guiding countries on the steps necessary to plan for and implement adaptation.

These were important steps forward, however there is still a lot of work to be done to accelerate adaptation globally. The targets set need to be more detailed and a clear roadmap for increasing finance towards adaptation needs to be drawn. This includes realizing the goal of doubling adaptation finance by 2025. Developed countries must deliver pledged contributions to the Green Climate Fund, Adaptation Fund, the Least Developed Countries Fund and Special Climate Change Fund to support the world’s most vulnerable countries. At the same time, all governments must find new innovative sources of finance, including mobilizing the private sector, which has historically favoured mitigation initiatives.

What are National Adaptation Plans and why do they matter?

National Adaptation Plans (NAPs) are comprehensive medium and long-term strategies that outline how a nation will adapt to the changing climate and reduce its vulnerability to climate-related risks. Often, countries will focus their NAPs on key sectors that contribute to their economy, food security and natural resources. 

NAPs are a way for countries to prioritize their adaptation efforts, integrating climate considerations into their national policies and development plans, and mobilizing the required finance by supporting the development of effective financing strategies and directing investments.

NAPs are also crucial because they enable countries to systematically assess their vulnerability to climate change, identify adaptation needs and design effective strategies to build resilience. 

Notably, these plans link closely to Nationally Determined Contributions (NDCs) and other national and sectoral policies and programmes.  

Land reclamation is underway in Tuvalu’s capital, Funafuti, to protect communities from sea level rise. Photo: TCAP/UNDP

Automated weather stations provide data crucial for forecasting and early warning. Photo: Jamil Akhtar/UNDP Pakistan

What are some examples of climate adaptation around the world?

There are a great number of countries leading the way in climate change adaptation, many of them showing outsized ambition and innovation, despite limited resources.

In the Pacific, the small island state of Tuvalu has drawn on the best available science – and around 270,000 cubic meters of sand – to reclaim a 780m-long, 100m-wide strip of land to protect against sea level rise and storm waves beyond 2100. This is an important initiative for a low-lying atoll country comprised of only around 26 square kilometres of land. 

Other countries such as Malawi and Pakistan are modernizing the capture and use of climate data and early warning systems, equipping communities, farmers and policy makers with the information they need to protect lives and livelihoods. 

Cuba and Colombia are leading the way on nature-based approaches, restoring crucial ecosystems – mangroves, wetlands and more – to protect against floods and drought. In this process, Colombia is capitalising on the knowledge of its Indigenous Peoples , who have invaluable expertise in adapting to extreme environmental changes.

Bhutan , the world’s first carbon-negative country, and Chad are among the world’s Least Developed Countries (LDCs) to finalize National Adaptation Plans. The result of years of meticulous planning and rigorous consultation, the plans are crucial roadmaps for adaptation in the years ahead. In Bhutan’s case, the plan is deeply rooted in the country’s unique ethos of Gross National Happiness.

How does UNDP support countries on climate change adaptation?

For UNDP, adapting to climate change is inseparable from sustainable development and each one of the 17 Sustainable Development Goals . Adaptation is therefore a key pillar of UNDP’s support to developing countries worldwide.

Today, UNDP is the largest service provider in the UN system on climate change adaptation with active projects targeting more than 164 million people across more than 90 countries, including 13 Small Island Developing States and 44 Least Developed Countries.

Since 2002, with finance via global funds such as the Green Climate Fund, Global Environment Facility and Adaptation Fund, and hand-in-hand with governments, UNDP has completed more than 173 adaptation projects across 79 countries. This work has contributed to building the resilience of millions of people worldwide. For example, more than 3 million people are now covered by enhanced climate information and early warning systems, more than 645,000 people are benefitting from climate-smart agricultural practices, and 473,000 people have improved access to water.

To learn more about UNDP’s adaptation work, click here .

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Responding to Climate Change

NASA is a world leader in climate studies and Earth science. While its role is not to set climate policy or prescribe particular responses or solutions to climate change, its purview does include providing the robust scientific data needed to understand climate change. NASA then makes this information available to the global community – the public, policy- and decision-makers and scientific and planning agencies around the world.

Climate change is one of the most complex issues facing us today. It involves many dimensions – science, economics, society, politics, and moral and ethical questions – and is a global problem, felt on local scales, that will be around for thousands of years. Carbon dioxide, the heat-trapping greenhouse gas that is the primary driver of recent global warming, lingers in the atmosphere for many thousands of years, and the planet (especially the ocean) takes a while to respond to warming. So even if we stopped emitting all greenhouse gases today, global warming and climate change will continue to affect future generations. In this way, humanity is “committed” to some level of climate change.

How much climate change? That will be determined by how our emissions continue and exactly how our climate responds to those emissions. Despite increasing awareness of climate change, our emissions of greenhouse gases continue on a relentless rise . In 2013, the daily level of carbon dioxide in the atmosphere surpassed 400 parts per million for the first time in human history . The last time levels were that high was about three to five million years ago, during the Pliocene Epoch.

Because we are already committed to some level of climate change, responding to climate change involves a two-pronged approach:

• Reducing emissions of and stabilizing the levels of heat-trapping greenhouse gases in the atmosphere (“mitigation”) ;
• Adapting to the climate change already in the pipeline (“adaptation”) .

Mitigation and Adaptation

Mitigation – reducing climate change – involves reducing the flow of heat-trapping greenhouse gases into the atmosphere , either by reducing sources of these gases (for example, the burning of fossil fuels for electricity, heat, or transport) or enhancing the “sinks” that accumulate and store these gases (such as the oceans, forests, and soil). The goal of mitigation is to avoid significant human interference with Earth's climate , “stabilize greenhouse gas levels in a timeframe sufficient to allow ecosystems to adapt naturally to climate change, ensure that food production is not threatened, and to enable economic development to proceed in a sustainable manner” (from the 2014 report on Mitigation of Climate Change from the United Nations Intergovernmental Panel on Climate Change, page 4).

Adaptation – adapting to life in a changing climate – involves adjusting to actual or expected future climate. The goal is to reduce our risks from the harmful effects of climate change (like sea-level rise, more intense extreme weather events, or food insecurity). It also includes making the most of any potential beneficial opportunities associated with climate change (for example, longer growing seasons or increased yields in some regions).

Throughout history, people and societies have adjusted to and coped with changes in climate and extremes with varying degrees of success. Climate change (drought in particular) has been at least partly responsible for the rise and fall of civilizations . Earth’s climate has been relatively stable for the past 10,000 years, and this stability has allowed for the development of our modern civilization and agriculture. Our modern life is tailored to that stable climate and not the much warmer climate of the next thousand-plus years. As our climate changes, we will need to adapt. The faster the climate changes, the more difficult it will be.

While climate change is a global issue, it is felt on a local scale. Local governments are therefore at the frontline of adaptation. Cities and local communities around the world have been focusing on solving their own climate problems . They are working to build flood defenses, plan for heat waves and higher temperatures, install better-draining pavements to deal with floods and stormwater, and improve water storage and use.

According to the 2014 report on Climate Change Impacts, Adaptation and Vulnerability (page 8) from the United Nations Intergovernmental Panel on Climate Change, governments at various levels are also getting better at adaptation. Climate change is being included into development plans: how to manage the increasingly extreme disasters we are seeing, how to protect coastlines and deal with sea-level rise, how to best manage land and forests, how to deal with and plan for drought, how to develop new crop varieties, and how to protect energy and public infrastructure.

How NASA Is Involved

NASA, with its Eyes on the Earth and wealth of knowledge on Earth’s climate, is one of the world’s experts in climate science . NASA’s role is to provide the robust scientific data needed to understand climate change. For example, data from the agency’s Gravity Recovery and Climate Experiment (GRACE) , its follow-on mission ( GRACE-FO ), the Ice, Cloud and land Elevation Satellite (ICESat), and the ICESat-2 missions have shown rapid changes in the Earth's great ice sheets. The Sentinel-6 Michael Freilich and the Jason series of missions have documented rising global sea level since 1992.

NASA makes detailed climate data available to the global community – the public, policy-, and decision-makers and scientific and planning agencies around the world. It is not NASA’s role to set climate policy or recommend solutions to climate change. NASA is one of 13 U.S. government agencies that form part of the U.S. Global Change Research Program, which has a legal mandate to help the nation and the world understand, assess, predict, and respond to global change. These U.S. partner agencies include the Department of Agriculture , the Environmental Protection Agency , and the Department of Energy , each of which has a different role depending on their area of expertise.

Although NASA’s main focus is not on energy-technology research and development, work is being done around the agency and by/with various partners and collaborators to find other sources of energy to power our needs.

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For further reading on NASA’s work on mitigation and adaptation, take a look at these pages:

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• NASA Spinoff (Technology Transfer Program)

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The Adaptation Principles: 6 Ways to Build Resilience to Climate Change

STORY HIGHLIGHTS

• Climate risk cannot be reduced to zero, which means governments must take decisive action to help households and businesses manage them.
• A new World Bank report, “The Adaptation Principles: A Guide for Designing Strategies for Climate Change Adaptation and Resilience”, lays out 6 universal principles to help policymakers plan for adaptation…
• … Along with 26 actions, 12 tool boxes and 111 indicators.

Over the past decades, Uganda made remarkable progress in reducing poverty and boosting socio-economic development. In 1992, some 56 percent of the population was living in poverty. By 2016, that figure had fallen to 21 percent . Yet, the global economic ramifications of the COVID-19 pandemic and the effects of climate change are forcing the country to confront new challenges: shocks not only threaten further progress but can reverse hard won successes of the past.

Around 72 percent of Uganda’s labor force works in agriculture – a sector that is highly climate sensitive. Take coffee: Uganda is Africa’s second largest exporter of coffee. Over 17 percent of Uganda’s exports coming from just this high-value crop. Recent droughts, however, are estimated to have destroyed half of all coffee yields. In the coming decades, changing climatic conditions are expected to pose profound challenges to Uganda’s coffee sector : without adaptive measures, only 1 percent of Uganda’s current coffee producing land is expected to be able to continue production. And coffee is just one sector that could face mounting impacts from climate change: around 2.3 million poor people in Uganda also face high levels of flood risk.

In countries around the world, climate change poses a significant risk threatening the lives and livelihoods of people. These risks cannot be reduced to zero, which means governments must take decisive action to help firms and people manage them. Doing so requires planning ahead and putting in place proactive measures that not only reduce climate risk but also accelerate development, and cut poverty, according to a new report, The Adaptation Principles: A Guide for Designing Strategies for Climate Change Adaptation and Resilience .

“Adaptation cannot be an afterthought to development. Instead, by integrating it into policy thinking up front, governments can catalyze robust economic development while also reducing vulnerability to climate change,” says Lead Economist, Stéphane Hallegatte , who co-authored the report with Jun Rentschler and Julie Rozenberg, all of the World Bank.

The report lays out six universal “Principles of Adaptation and Resilience” and 26 concrete actions that governments can use to develop effective strategies. To support the development and design of these actions, it also includes 12 toolboxes with methodologies and data sources that can ensure that strategies are evidence-based.  

1. Build resilient foundations with rapid and inclusive development

Poverty and the lack of access to basic services—including infrastructure, financial services, health care, and social protection—are strong predictors of vulnerability to climate change . To put it another way: the poorer communities are, the more climate change will affect them. No adaptation strategy can be successful without ensuring high-vulnerability populations have the financial, technical, and institutional resources they need to adapt.

2. Help people and firms do their part.

It’s critical to boost the adaptive capacity of households and firms: many already have incentives to adapt, but they need help overcoming obstacles, ranging from a lack of information and financing, to behavioral biases and imperfect markets. Governments can make information on climate risks available, clarify responsibilities and liabilities, support innovation and access to the best technologies , and ensure financing is available to all especially for solutions that come with high upfront costs. And they will also need to provide direct support to the poorest people, who cannot afford to invest in adaptation but are the most vulnerable to experiencing devastating effects of climate change .

3. Revise land use plans and protect critical infrastructure.

In addition to direct support to households and businesses, governments must also play a role in protecting public investments, assets, and services. Power and water outages and transport disruptions are estimated to cost more than $390 billion per year already in developing countries. But if countries have the right data, risk models, and decision-making methods available, the incremental cost of building the resilience of new infrastructure assets is small—only around 3 percent of total investments. Urban and land use plans are also important responsibilities of the public sector, and they influence massive private investments in housing and productive assets, so it is vital these adapt to evolving long-term climate risks to avoid locking people into high-risk areas.

4. Help people and firms recover faster and better.

Risks and impacts cannot be reduced to zero. Governments must develop strategies to ensure that when disasters do occur, people and firms can cope without devastating long-term consequences, and can recover quickly. Preparation such as better hydromet data , early warning and emergency management systems reduces physical damage and economic losses—for example, shuttering windows ahead of a hurricane can reduce damage by up to 50 percent. The benefits of providing universal access to early warning systems globally have been repeatedly found to largely exceed costs, by factors of at least 4 to 10 . And then, financial inclusion, such as access to emergency borrowing, and social protection are essential ways to help firms and people get back on their feet. Adaptive social protection systems , which can be rapidly scaled up to cover more people and provide bigger support after a disaster, are particularly efficient, but they rely on delivery and finance mechanisms that have to be created before a crisis occurs.

5. Manage impacts at the macro level.

Coping with climate change impacts in one economic sector is already complicated. Coping with climate change impacts in all sectors at once requires strategic planning at the highest levels. Through many impacts in many sectors ---  from floods affecting housing prices to changes in ecosystems affecting agriculture productivity --- climate change will affect the macroeconomic situation and tax revenues. Some impacts on major sectors (especially exporting ones) can affect a country’s trade balance and capital flows. And spending needs for adaptation and resilience need to be added on top of existing contingent liabilities and current debt levels to create further pressure on public finances. The combination of these factors may result in new risks for macroeconomic stability, public finances and debt sustainability, and the broader financial sector. Governments will need to manage these risks . Because of the massive uncertainty that surrounds macroeconomic estimates of future climate change impacts, strategies to build the resilience of the economy, especially through appropriate diversification of the economic structure, export composition and tax base, are particularly attractive over the short term.

6. Prioritize according to needs, implement across sectors and monitor progress.

Governments must not only prioritize actions to make them compatible with available resources and capacity; they must also establish a robust institutional and legal framework , and a consistent system for monitoring progress. The main objective of an adaptation and resilience strategy is not to implement stand-alone projects: it is to ensure that all government departments and public agencies adopt and mainstream the strategy in all their decisions, and that governments continuously monitor and evaluate the impact of their decisions and actions, so they can address any challenges and adjust their actions accordingly.

The report provides a range of practical tools that can help governments implement adaptation strategies. For instance, economic analysis methodologies can help to select the most important interventions, and budget tagging methods can ensure spending is consistent with expectations. A set of 111 indicators is also provided to enable governments to track progress toward greater resilience, to identify areas that are lagging behind, and to prioritize effective measures. It also sheds light on how the COVID-19 pandemic and subsequent economic crisis can affect the design of an adaptation and resilience strategy, recognizing how it has changed the development landscape in all countries.

The impacts of climate change are already here and fast increasing and there is no silver bullet to prevent them. Proactive and robust actions ahead of time, however, can go a long way to helping people and communities so that when a natural disaster strikes, not only are they better prepared to respond, but hard-won development gains are not lost.

Join us on Tuesday, December 1 2020, for a discussion on the main findings of this report .

“The Adaptation Principles: A Guide for Designing Strategies for Climate Change Adaptation and Resilience” was produced with financial support from the Global Facility for Disaster Reduction and Recovery .

• Report: The Adaptation Principles - A Guide for Designing Strategies for Climate Change Adaptation and Resilience
• Infographic: The Adaptation Principles at a Glance

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CLIMATE CHANGE:

Adapting to a new normal

Kevin C. Urama, Adamon N. Mukasa, and Anthony Simpasa

Bogolo J. Kenewendo

Turning political ambitions into concrete climate financing actions for Africa

Acting Chief Economist and Senior Director of the African Development Institute, African Development Bank

Principal Research Economist, Macroeconomic Policy, Forecasting and Debt Sustainability Division, African Development Bank

Lead Economist, Country Economics Department, and Acting Manager, Macroeconomic Policy, Forecasting and Debt Sustainability Division, African Development Bank

One of the main targets of the 27th Conference of the Parties to the United Nations Framework Convention on Climate Change ( COP27 ) in Sharm El-Sheik, Egypt, was “ to accelerate global climate action through emissions reduction, scaled-up adaptation efforts and enhanced flows of appropriate finance .” While the breakthrough agreement on a new “Loss and Damage” Fund for vulnerable countries is a welcome development, progress on climate finance leaves much to be desired. This is worrisome for African countries.

Recent reports on climate change such as the African Economic Outlook 2022 and the Sixth Assessment Report of the Intergovernmental Panel on Climate Change have reiterated that the climate crisis is likely to worsen, especially in Africa, and that the time for action to avert the impending catastrophe is now. World leaders have missed (again) the opportunity to move from mere political commitments and ambitions to concrete actions.

Africa’s climate paradox

As the late Kofi Annan perfectly put it, all continents are in the same boat when it comes to addressing climate change. However, individual regions and countries are not equally responsible for global environmental problems. This principle of common but differentiated responsibility and respective capabilities is at the core of climate justice and just energy transition.

Africa’s case is especially concerning. The continent is the least polluting region 1 of the world but faces a disproportionate burden from the impact of climate change. Between 1850 and 2020, Africa’s contribution to global emissions remained below 3 percent 2 and yet, it lost about 5 percent to 15 percent annually of GDP per capita growth between 1986 and 2015. About 70 percent of the used global carbon budget is accounted for by just the United States, European Union, United Kingdom, and China (Figure 35a). An average African had a carbon footprint of just 0.95 tons of carbon dioxide equivalent (tCO2eq) in 2020, well below the 2.0 tCO2eq required to achieve the net-zero transition target. On the other extreme, an average American had a carbon footprint of up to 14 tCO2eq, fifteen times higher than that of an average African (Figure 35b).

From climate finance commitments to reality and at scale

The $100-billion promise , 3 made by developed countries since 2009 at COP15 in Copenhagen, has still not been achieved. According to the OECD , [OECD.2022. “Climate Finance Provided and Mobilised by Developed Countries in 2016-2020.”] climate financing provided and mobilized by developed countries reached $83.3 billion in 2020, some $16.7 billion below the target. Indeed, a 2020 report commissioned by the United Nations concluded the only realistic scenario is that the $100-billion target will be out of reach in the short- to medium-term.

Africa’s share of global climate finance—provided and mobilized by developed countries for developing countries—increased by only 3 percentage points on average during 2010 to 2019, from 23 percent ($48 billion) in 2010–2015 to 26 percent ($73 billion) in 2016–2019 (Figure 36). This means that Africa benefited from $18.3 billion a year from 2016–2019, far behind Asia, which benefited $27.3 billion a year, over the same period. Yet, Africa accounted for about 40 percent of all countries eligible to benefit from this support, compared with only 20 percent for Asia. In addition, between 2010 and 2019, debt instruments (mostly loans) accounted for about two-thirds of all climate finance channeled to Africa, out of which two-fifths were on non-concessional terms.

Climate finance inflows to Africa are dwarfed by the enormity of resources needed for Nationally Developed Contributions (NDCs), estimated to range from about $1.3 trillion to $1.6 trillion between 2020 and 2030, or $118.2 billion to $145.5 billion per year over this period. Under the current climate finance trends, Africa’s annual financing gap could thus reach an estimated average of $108 billion per year until 2030. This climate injustice needs urgent attention.

Mobilizing more climate finance for Africa is within the reach of the global community. For instance, between January 2020 and September 2021, the global community mobilized about $17 trillion through various fiscal measures in response to the effects of the COVID-19 pandemic. Almost $15.3 trillion (or 90 percent of these fiscal measures) was mobilized by G-20 economies. This demonstration of political will and innovative use of fiscal policy rules to address the global threat posed by COVID-19 is commendable. Like COVID-19, climate change is a global commons problem but perhaps with even longer-term and systemic impacts.

Why Africa deserves more in climate financing

Mobilizing climate finance to avert the growing climate catastrophes in developing countries calls for similar political will and collective action. To this end, an important milestone is for the international community and developed countries to step up to the plate in mobilizing and providing the requisite climate resources to developing countries.

“Ultimately, climate change is a global commons problem. Climate solutions will not be sustainable unless all actors play their part. The climate challenge cannot be addressed if any country fails to meet its Nationally Determined Contributions.”

Achieving this will require significant reform of the current global climate finance architecture , 4 to ensure that the most vulnerable countries (especially in Africa), effectively harness climate resilience opportunities. The structure, flow, and scale of the global climate finance architecture, as currently designed, is misaligned with climate vulnerability. For example, as illustrated in Figure 36 above, more resilient and less vulnerable regions receive more climate finance, in per capita terms, than their less resilient but more vulnerable counterparts. Moreover, the climate finance architecture is modelled to mirror the current global financial architecture that is risk averse and discriminatory against fragile economies. The loose definition of climate finance has also led to proliferation of various climate finance instruments, including debt instruments. The latter exacerbates debt vulnerabilities in countries where climate impacts are already constraining fiscal health.

There is thus need for a clearer definition of climate finance, better coordination among existing global climate finance facilities, dedicated climate initiatives, as well as enhanced harmonization of funding requirements that can channel climate finance flows to the most climate-vulnerable countries. While African countries do have their part to play, the principle of common but differentiated responsibility and respective capabilities requires that the most polluting countries bear the greatest burden of climate financing.

Ultimately, climate change is a global commons problem. Climate solutions will not be sustainable unless all actors play their part. The climate challenge cannot be addressed if any country fails to meet its Nationally Determined Contributions (NDCs).

And the world cannot expect Africa to implement its NDCs if the expected climate finance flows to fund the conditional NDCs, are not made available. Should the current trends continue, it is certain that Africa will not achieve its NDCs by 2030. By implication, the global community will not be able to reach the Paris Climate Accord.

The charge due to custodians of the world’s lungs

United Nations Climate Change High-Level Champions’ Special Advisor Former Minister of Investment, Trade and Industry, Botswana

It is time to rebalance the scales in Africa’s favor when it comes to climate finance. The African continent is home to 16 percent of the world’s population and 25 percent of the world’s remaining rainforests 5 —yet Africa attracts only 3.19 percent of global climate finance ($30 billion of $940 billion global climate flows), and the pledges to accelerate adaptation and mitigation financing of $100 billion by 2020 in developing countries are yet to fully materialize. 6 Climate finance can be a catalytic tool for fiscal stability, especially for African countries that are struggling with economic recovery, amid multiple global shocks.

However, for African countries and non-state actors to attract increased climate finance and play a greater role in structuring the green financial architecture, Africa must position itself as a worthy investment destination for climate finance focused on long-term development issues. To achieve this, I propose a few key areas of focus for policymakers. First, countries must have green investment plans, and second, it is critical to bring the private sector to the table and to give it space to innovate. In addition, policymakers should use public finance to de-risk private investment and have a regulatory environment that enables doing business with variable financing tools. Lastly, developed countries must deliver on the pledges already made without any further and new conditionalities to spur green development for a common 1.5 degrees future.

“Of the great rainforests in the world, only the Congo rainforest has enough standing forest left to absorb more carbon from the atmosphere than it releases.”

African Nationally Determined Contributions (NDCs), that is countries’ action plans to cut emissions and adapt to climate impacts, should be accompanied by national investment strategies that prioritize green infrastructure and natural resource protection. These can create a green development pathway that promises economic growth opportunities, industrialization, and jobs, propelling Africa past a more traditional, less green infrastructure and development approach.

Country platforms should also encompass the private sector, so that there is a cohesive approach as to who will invest where, and who is best placed to tackle the varying aspects of mitigation and adaptation and protection. A good example of this approach on leveraging the private sector is the proposal by members of the “ Nairobi Declaration on Sustainable Insurance ” that identified the African insurance sector as a key climate mitigation and adaptation agent; and re-affirmed its triple role of risk manager, risk carrier, and investor through commitment to a Africa climate risk management fund. This fund will cover $14 billion worth of climate and nature-related risks such as floods, droughts, and tropical cyclones through innovative insurance products and solutions. These kind of innovations by the private sector are in line with what the Paris Agreement envisioned.

Second, debt-for-climate swaps and carbon markets should be rolled out more broadly as part of the solution to debt crises which plague a long and growing list of African nations. This effort starts with valuing Africa’s wealth in the totality of its nature assets. Nature has become the world’s most important commodity, and its protection is paramount for the world’s survival. According to the World Resources Institute, of the great rainforests in the world, only the Congo rainforest has enough standing forest left to absorb more carbon from the atmosphere than it releases . 7

Commercializing such nature assets, and making sure they attract fair value and benefit neighboring communities, is a key feature of the Africa Carbon Markets Initiative (ACMI) 8 —an initiative that has created a roadmap for developing African voluntary carbon markets, with the aim to accelerate and scale carbon credit production on the continent. The initiative proposes to leverage an advanced market commitment (AMC), which in essence is an upfront guarantee from buyers and multiple corporations, to purchase African carbon credits. This AMC will help send a strong demand signal and incentivize appetite for good quality and innovative credits. There is huge potential in making carbon markets work to attract more climate finance.

Third, there is need for gender-informed investing to enhance climate adaptation and resilience. At its core, this means acknowledging climate action as a development issue; recognizing that the climate crisis is not “gender-neutral,” and that women and girls are disproportionately affected; and finally, that the devastating impacts of extreme climate occurrences cause more economic scarring to the poorest and most vulnerable in our societies. 2xCollaborative has developed a gender-lens investing toolkit that can, and should be, widely used to promote gender-lens climate finance to businesses and adaptation projects, involved or led by women.

We cannot afford the current architecture of global green finance to perpetuate existing disparities in those it serves. It is time for African countries to unite, strategically position themselves, and demand that the world does more to deliver climate finance for the continent; it promises great return for all, and it is what is due to the custodians of the “lungs of the world.”

• 1. The Intergovernmental Panel on Climate Change (IPCC). 2021. “Climate Change 2021: The Physi-cal Science Basis.” Working Group I contribution to the Sixth Assessment Report. The Intergovernmental Panel on Climate Change.
• 2. AfDB.2022. “African Economic Outlook 2022”. African Development Bank.
• 3. Jocelyn Timperley. 2021. “The broken $100-billion promise of climate finance — and how to fix it.”
• 4. Charlene Watson, Liane Schalatek, and Aurélien Evéquoz. 2022. “The Global Climate Finance Architecture.”
• 5. World Bank Africa Region. 2017. “Forests in Sub-Saharan Africa: Challenges & Opportunities.” The Program on Forests (PROFOR).
• 6. Naran, Baysa. 2022. “Global Landscape of Climate Finance: A Decade of Data: 2011-2020.” Cli¬mate Policy Initiative.
• 7. Harris, Nancy and David Gibbs. 2021. “Forests Absorb Twice as Much Carbon as They Emit Each Year.” World Resources Institute.
• 8. ACMI is a joint initiative of GEAPP, SE4All, UNECA and supported by the UN Climate Change High Level Champions.

By Gracelin Baskaran

Gracelin Baskaran explains how climate vulnerability is deepening debt challenges in sub-Saharan Africa and how policymakers can manage it.

By Yacob Mulugetta

Yacob Mulugetta considers how African countries can insert themselves into green manufacturing value chains.

By U. Rashid Sumaila

U. Rashid Sumaila urges investment in a sustainable and inclusive African blue economy.

By Ede Ijjasz-Vasquez and Jamal Saghir

Ede Ijjasz-Vasquez and Jamal Saghir discuss sustainable climate adaptation investment strategies for Africa.

By Mahmoud Mohieldin

Mahmoud Mohieldin makes the case for increasing climate finance flows to Africa.

By John Mulligan

John Mulligan explains how the gold industry can help confront the challenges and opportunities of a changing climate in Africa.

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07 | Africa's Cities Realizing the new urban agenda

Foresight Africa: Top Priorities for the Continent in 2023

On January 30, AGI hosted a Foresight Africa launch featuring a high-level panel of leading Africa experts to offer insights on regional trends along with recommendations for national governments, regional organizations, multilateral institutions, the private sector, and civil society actors as they forge ahead in 2022.

Africa in Focus

What should be the top priority for Africa in 2023?

BY ALOYSIUS UCHE ORDU

Aloysius Uche Ordu introduces Foresight Africa 2023, which outlines top priorities for the year ahead and offers recommendations for supporting Africa at a time of heightened global turbulence.

Foresight Africa Podcast

The Foresight Africa podcast celebrates Africa’s dynamism and explores strategies for broadening the benefits of growth to all people of Africa.

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Climate adaption and resiliency.

NASA integrates climate adaptation and resilience considerations into the Agency’s policies, strategies, master plans, and partner engagements. This includes managing enterprise risk and supporting the mission through strategic planning and leveraging internal climate science expertise. ​​​​​​

What’s Up?

We are currently completing resilience assessment plans at each Center and working with DOE in developing the agency wide resilience framework under which Center resilience plans will reside.​​​​​​​

Priority 1: Ensure Access to Space

NASA designs, manufactures, tests, and launches rockets and payloads into space as part of its core mission. Maintaining access to space is critical to the continued execution of NASA’s mission. The National Oceanic and Atmospheric Administration (NOAA), international partners, and several commercial ventures rely on NASA to provide and support launch and control facilities and activities. NASA will maintain access to space by identifying and, as appropriate, managing climate-related risks to critical launch facilities, supporting infrastructure, and supply chain.

Priority 2: Integrate Climate Adaptation into Agency and Center Master Plans

NASA’s Agency Master Plan (AMP) aligns mission requirements with the Agency’s real property assets, while maintaining a long-term risk mitigation strategy (AMP Goal 4) and implementing sustainability best practices (AMP Goal 5). The 2011 AMP mentions risks due to climate change but does not emphasize or provide specific guidance on how this should be addressed. In 2019, NASA initiated a major revision and modernization of the AMP. The development of the AMP is an iterative process involving close consultation between Agency organizational, functional, and program leadership and its field installations, with a strong emphasis on mission- driven requirements and strategies. The AMP is a resource of information on NASA facility land use, constraints, and opportunities. It is a road map for future development and redevelopment of Agency real property. The AMP serves as a strategy in which future projects and proposals are examined to ensure alignment with the Agency Strategic Plan. Although proposed projects are subject to approval based on evolving NASA mission requirements and the availability of funds, the AMP provides an invaluable internal framework for conducting advanced facilities planning.

Priority 3: Integrate Climate Risks into Risk Analysis and Agency Resilience Planning

NASA is developing an Agency resilience framework (ARF) that will include adaptation to climate change. The framework will be integrated into the AMP and CMPs. The ARF will provide guidance for development of Center resilience plans (CRPs) that will include a process for identifying threats, vulnerabilities, and risks; developing adaptation strategies; and prioritizing adaptation actions. Centers will use mission essential functions, COOP plans, and key objectives as inputs in preparing baseline resilience assessments and strategies for real property, infrastructure, and public lands and waters.

Priority 4: Update Climate Modeling to Better Understand Agency Threats and Vulnerabilities

The Science Mission Directorate (SMD) influences the global climate science community by promoting principles of open data and science that foster more rapid progress in climate adaptation. NASA leads and contributes to the latest climate science, observations, models, and analyses to provide foundational and decisional knowledge in cooperation with many partners.

Global climate models do not provide projections at a resolution necessary to support local decision making. NASA, through the Goddard Institute for Space Studies (GISS) and others, is one of the few government agencies involved in the scientific community that generates downscaled, regional climate projections. NASA will use this climate change knowledge and Agency GIS capabilities to assess exposure, identify vulnerabilities, and develop adaptation strategies to address climate risk, some of which may also have climate change mitigation co- benefits.

Priority 5: Advance Aeronautics Research on Technologies and Processes that Reduce Contributors to Climate Change

NASA’s Aeronautics Research Mission Directorate (ARMD) explores aviation concepts and technologies, some of which support NASA climate resilience. ARMD’s aviation concepts, combined with ESD’s observational data, help NASA and other agencies reduce vulnerability to extreme events and long-term climate change. ARMD research and development of advanced technology and aircraft operations lead to climate change mitigation co-benefits for the global community, including GHG emission reductions through electric propulsion systems, as well as advanced composites and vehicle configurations.

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Perspective article, lessons from the pacific islands – adapting to climate change by supporting social and ecological resilience.

• 1 The Nature Conservancy (United States), Arlington, TX, United States
• 2 The Nature Conservancy (Micronesia), Kolonia, Micronesia
• 3 Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
• 4 The Nature Conservancy (Australia), Brisbane, QLD, Australia
• 5 Nature Conservancy Manus, Manus, Papua New Guinea

By necessity, Pacific Islands have become hubs of innovation, where climate strategies are piloted and refined to inform adaptation efforts globally. Pacific Island ecosystems are being degraded by pollution, overfishing, and unsustainable development. They also increasingly face severe climate impacts including sea-level rise, changing temperature and rainfall patterns. These impacts result inchanges in food and water security, loss of identity, climate-induced migration and threats to sovereignty. In response, communities in the region are leading climate adaptation strategies, often combining traditional practices and cutting-edge science, to build the resilience of their communities and ecosystems in the face of increasing climate risk. For example, communities are implementing resilient networks of marine protected areas using the best available science and strengthening tribal governance to manage these networks, experimenting with salt and drought tolerant crops, revegetating coastlines with native salt-tolerant plants, revitalizing traditional wells, and implementing climate-smart development plans. Often these efforts contribute to local development priorities and create co-benefits for multiple sustainable development goals (SDGs). These community efforts are being scaled up through provincial and national policies that reinforce the critical role that ecosystems play in climate adaptation and provide a model for the rest of the world. While adaptation efforts are critical to help communities cope with climate impacts, in some cases, they will be insufficient to address the magnitude of climate impacts and local development needs. Thus, there are inherent trade-offs and limitations to climate adaptation with migration being the last resort for some island communities.

Introduction

The Pacific Islands are facing devastating impacts of climate change including increasing droughts and water scarcity, coastal flooding and erosion, changes in rainfall that affect ecosystems and food production, and adverse impacts to human health ( IPCC, 2014 , 2018 ).

Overpopulation, pollution and overuse of natural resources (e.g., overfishing and intensive land and water use), and unsustainable development and mining are also degrading island ecosystems ( Burke et al., 2011 ; Hills et al., 2013 ; Balzan et al., 2018 ). While the Pacific Islands are often described as highly vulnerable to climate change and lacking adaptation options ( Pelling and Uitto, 2001 ), such descriptions disregard the ways in which Pacific Islanders are leading climate action and combining their own systems of knowledge with western science to implement locally relevant climate solutions ( Barnett and Campbell, 2010 ; Mcleod et al., 2018 ). The lack of appreciation for Pacific climate leadership is exacerbated by biases in climate research that prioritize western science and technological solutions over other systems of knowledge ( Jasanoff, 2007 ; Alston, 2014 ). It is critically important for global climate policy and national governments to recognize and support community efforts to build resilient communities and ecosystems through ecosystem-based adaptation strategies that are rooted in traditional knowledge and reinforced and supported by climate science, traditional leadership structures, and sustainable climate solutions.

Pacific Island leaders, along with leaders from other Small Island Developing States (SIDS), have been instrumental in shaping climate policies and the Paris Climate Agreement ( UNFCCC, 2015 ). They called for a loss and damages clause that allows islands to assess and quantify impacts of cyclones and weather-related events and were vocal advocates to limit warming of global mean temperature to 1.5°C. The recognition that warming of 1.5°C or higher increases the risk associated with irreversible damages such as the loss of entire ecosystems has just been articulated in the latest IPCC report ( IPCC, 2018 ). Despite their minimal contribution to global greenhouse gas emissions ( Hoad, 2015 ), many SIDS included ambitious mitigation targets in their national climate plans (i.e., Nationally Determined Contributions, NDC) to raise collective ambition to reduce GHG emissions globally ( Ourbak and Magnan, 2018 ).

Pacific Islanders are also leading climate action at the local level, implementing strategies to help communities and ecosystems to be more resilient to climate change. The region provides important opportunities for testing and refining adaptation responses at scale. The Pacific Islands are home to species found nowhere else on earth and are incredibly diverse, in terms of their ecosystems, geography, and demographics. Pacific Islanders have lived with natural environmental impacts for thousands of years and have adapted practices to accommodate periods of environmental fluctuations. Although the pace of environmental and climatic changes has increased, many communities are implementing climate-smart agriculture and are revitalizing traditional practices that utilize drought-tolerant species and the benefits of nature, such as using seaweed as compost to make soil more fertile, using palm fronds to shade plants during droughts, and planting vegetation to reduce flooding and erosion along coastlines. They are also combining these traditional practices with new scientific advancements such as the development of salt-tolerant and heat-tolerant crops and community-led GIS mapping of breadfruit trees vulnerable to climate impacts in the Marshall Islands. Communities are revitalizing traditional wells, establishing new protected areas and improving the management of existing protected areas, and developing climate-smart development plans that incorporate ecosystem-based adaptation.

However, ecosystem-based adaptation (EBA) efforts initiated by Pacific Island communities have largely been ignored in the peer-reviewed literature. Ecosystem-based adaptation is defined as combining biodiversity and ecosystem services into an adaptation and development strategy that increases the resilience of ecosystems and communities to climate change through the conservation, restoration, and sustainable management of ecosystems ( Colls et al., 2009 ). Researchers have highlighted the need for reflexive insights, including lessons and challenges implementing EBA projects, given the increased attention it has received in global and national climate discourse ( Doswald et al., 2014 ). Key benefits of EBA have been identified including: (1) securing water resources to help communities cope with drought (2) food and fisheries provision; and (3) buffering people form natural hazards, erosion, and flooding ( Munang et al., 2013 ).

Therefore, this paper presents local EBA examples that demonstrate how Pacific Island communities are leading the implementation of sustainable climate solutions and reinforcing the critical role of ecosystems in climate adaptation. We include examples that address the primary benefits of EBA including water security, food security, and coastal protection. We present examples of EBA projects that were implemented across Micronesia and Melanesia from 2015 to 2018. The EBA project s included a partnership among communities, local governments, and conservation NGOs (The Nature Conservancy, The Micronesia Conservation Trust, other local conservation partners across the Pacific). We discuss these EBA activities, identify barriers to implementation, and highlight the importance of supportive national policies and political will to reinforce and scale up these efforts.

Revitalizing Traditional Wells

Oneisomw (formerly Oneisom) is an island located in Chuuk State lagoon in the Federated States of Micronesia. It has a population of 638 inhabitants (2010 Census of Population and Housing) that is already experiencing the impacts of climate change. Villages are primarily located along the shoreline and are affected by coastal flooding during typhoons and high tide events. The communities rely on a combination of water tanks, aquifers, streams, and wells but freshwater security is threatened by drought and saltwater intrusion. Human impacts are also adversely affecting these freshwater sources and the coastal environment (e.g., pollution from dump sites, waste from pig pens, inadequate sanitation systems, erosion from unpaved pathways, solid waste dumping, and sediment runoff from inland clearing). To improve water security and reduce impacts in the coastal environment, Oneisomw residents have rehabilitated traditional water wells by cleaning them, planting vegetation buffer strips around wells and streams to stabilize degraded banks and reduce sedimentation and installing concrete covers over the wells to reduce trash and other pollutants from entering the wells. They also developed agreements with landowners who had wells to allow others to access water during drought. This approach was presented during a national mayor’s summit in 2018 and other communities have requested support to implement these actions to improve water security in their municipalities.

Such local actions need to be reinforced by the implementation of state and national water policies that promote watershed management and provide the foundation for the sustainable use and conservation of water resources (e.g., Pohnpei State Water Policy passed in 2018). This need was articulated at a stakeholder workshop in Pohnpei in 2017 that brought together local leaders, land-owners, and others who utilize the watershed area. While traditional leaders endorsed the process of managing the watershed sustainably, lack of cooperation and planning was noted along with the need to integrate State water management regulations into a national water policy framework to ensure a consistent flow of funds to manage the watershed and protect the full suite of ecosystem services.

Implementing Climate Smart Agriculture

Climate-smart agriculture (CSA) is defined as an integrated approach to managing cropland, livestock, forests and fisheries that aims to support food security under the new realities of climate change through sustainable and equitable transitions for agricultural systems and livelihoods across scales ( Lipper et al., 2014 ). It is designed to increase productivity (i.e., produce more food and boost local incomes), enhance the ability of communities to adapt to climate change and weather extremes, and decrease greenhouse gas (GHG) emissions from food production ( Steenwerth et al., 2014 ). When implemented in an island context, CSA can also support benefits to coastal ecosystem (e.g., by reducing sediment into the coastal zone through taro swamps, reducing pressure on wild-caught fisheries, reducing pollutants from fertilizers; Clarke and Thaman, 1993 ; International Fund for Agricultural Development [IFAD], 2017 ).

Communities across the Pacific are revitalizing traditional farming practices, based on agroforestry, to increase food security and reduce vulnerability to climate impacts, and they are also experimenting with salt and drought-tolerant crops ( FAO, 2010 ; Mcleod et al., 2018 ). Traditional farming practices include shading crops with palm leaves, maintaining trees around plants to provide shade, composting using seaweed. Some coastal fishing communities (e.g., Ahus, Papua New Guinea) have historically relied on fishing for food security and are now working with local NGOs, women’s groups and government agriculture officers to plant household gardens. Ahus is off the coast of Manus Island in Papua New Guinea and has a population of more than 700 residents. Observed climate impacts include sea-level rise, reduced marine protein sources, saltwater inundation of water wells, coastal erosion, storm surges, droughts, heavy rains, ocean acidification and coral bleaching. With support from the government and NGOs, Ahus has introduced new farming practices that are designed to improve food security, the health of the marine environment, and provide an important source of income for local households ( Tara, 2018 ). These include the introduction of growing food crops including greens, tomatoes and cabbages, composting in very sandy soils, raised gardens and local water collection in drums and small tanks. Women’s groups, in partnership with local conservation NGOs and agricultural extension officers have led trainings on farming methods such as the use of organic fertilizers and pesticides, raised beds to improve soil quality and eliminate saltwater intrusion, and the diversification of crops. These farming practices are being replicated and scaled through the provincial women’s network Pihi Environment and Development Forum (PEDF). Benefits have included changing and improving the diet of Ahus families, increased cash income for women selling produce at market and to local restaurants, food security especially when bad weather prevents fishing, better community cohesion as people shared ideas and produce.

Low cost aquaculture projects are also being implemented in Ahus, such as clam farming techniques from Palau that have been adapted to local conditions to provide food security and reseed local reefs with clam larvae to re-establish the local wild population. Community members in Tamil, Yap built a nursery utilizing traditional composting techniques and including food crops and plants to revegetate coastal areas vulnerable to erosion (e.g., Nipa Palm). The nursery reduces reliance on coastal fisheries that are being depleted, increases the diversity of food sources, improving community health, and reduces the impact of coastal erosion.

Implementation of Protected Areas

Tamil is a municipality on the island of Yap in the Federated States of Micronesia. It includes twelve villages with a total population of about 1200 people living in 848 households (Office of Statistics, Budget and Economic Management, Overseas Development Assistance, and Compact Management, 2011). The community has experienced flooding, erosion, and drought driven by climate change, in addition to saltwater intrusion into freshwater sources and taro patches. Water security is further impacted by poor water management, high dependence on the watershed, and lack of alternative water sources as many local wells are degraded or contaminated by waste and sedimentation from erosion. The community noted the following ecological impacts: declines in coral health, seagrass beds, and reduced fish populations due to increased sedimentation in the coastal environment and pollution run-off driving algal increases (LEAP 2017). To improve water security and coastal ecosystem health, the community declared their first Watershed Protected Area in 2017 (320 acres of watershed protected by traditional council members and recognized by state law). The Tamil watershed provides water to over half of the population of Yap, and its protection provides greater resiliency to and recovery from wildfires, and designates the area as a water conservation zone to increase water security in times of drought.

Similarly, in the island of Chuuk, the community of Oneisomw agreed to implement a locally managed marine area (LMMA) to reduce threats facing coral reefs (e.g., controlling dynamite fishing and overfishing, coral and sand removal, commercial harvesting). The LMMA supports seasonal or permanent closures and fishery management through the traditional management system ( mechen ). Based on the traditional mechen system, Oneisomw coral reef “owners” initiated an agreement to collectively enforce seasonal or longer closures of reef areas, based on scientific knowledge and community inputs, to ensure access to coral reef resources for future generations. The LMMA is the first marine protected area for the newly passed Protected Area Network (PAN) legislation. In 2018, the community initiated the process to develop their first land-based protected area by signing a memorandum of understanding with well owners to maintain healthy watersheds. The land-based protected area will reduce pollution and runoff around water sources and will include revegetation with green buffers to help maintain water quality. The next step is for the community to produce a management plan that will integrate a ridge-to-reef approach, which will help to design one of the first Ridge-to-reef protected areas in the country. These collective efforts support the FSM’s climate adaptation commitment to the UNFCCC and demonstrate that western and traditional natural resource management methods can be complimentary and mutually beneficial in meeting conservation and human wellbeing goals. They also show how local ideas addressing local needs in the FSM can help to support the ambitious targets of the Paris Agreement.

Climate-Smart Development Plans

Melekeok State is located along the east coast of the main island of Palau. The population includes about 300 residents (about 90 households) and the State is also host of the capitol building of the Palau national government. Most of the homes and infrastructure (e.g., elementary school, State office, retirement center) are located along the coast within 5 meters of the high-water mark, thus highly vulnerable to flooding and erosion due to storm impacts and sea-level rise ( ADB, 2012 ; Melekeok State Government, 2012 ). For example, Typhoon Bopha in 2012 caused significant damage to the community. In response to climate impacts and projections of future impacts, Palau developed a national climate change policy ( Government of Palau, 2015 ) which identifies the need for building ecosystem and community resilience. Additionally, the Melekeok community developed a climate-smart guidance document ( Polloi, 2018 ) due to their high dependence on their terrestrial and marine ecosystems ( Brander et al., 2018 ; Förster, 2018 ) in partnership with the Melekeok State government and conservation NGOs (e.g., the Nature Conservancy, Micronesia Conservation Trust).

The climate-smart development document provides guidance for updating current infrastructure, designated upland lease development for migrating vulnerable community members and infrastructure away from the coast, and recommendations to make future development less vulnerable to climate impacts. A key focus is to ensure that new development and refinement of existing structures are climate smart and do not cause environmental damages that threaten water quality and the marine ecosystem. For example, the state residential lease/housing program incorporates sustainable designs and approaches to support the resiliency and enhancement of ecosystem services. The residential lease agreement requires individuals to revegetate bare soils to reduce run-off and sedimentation into the coastal system, minimize stormwater flow to promote water infiltration and support water supply, install water catchment systems to reduce vulnerability to drought, and include renewable energy systems (e.g., solar panels) through existing national loan programs. In addition, new permits for land use, the development of residential areas, and commercial developments require measures that support water security and erosion control (e.g., hedge rows and filter strips to mitigate soil erosion). Melekeok State leadership is also considering legislation for climate proofing new residential houses that would require new houses to use hurricane clips in the construction.

These innovations in Palau provide a model for how to develop climate-smart development that also include benefits to the coastal and marine ecosystem. To upscale implementation and enforcement at national level, policies are needed that support sustainable financing mechanisms. Access to loans for building new homes should be provided under the condition of complying with guidance for climate-smart homeowners, similar to the Energy Efficiency Subsidy Program of the National Development Bank of Palau. Such policies could enhance the upscaling of adaptation strategies and their inclusion in local and national infrastructure development programs.

Challenges to Implementing Adaptation Strategies

A number of challenges threaten the success of local community-based adaptation projects including the remoteness of some islands, lack of capacity to implement and sustain projects, lack of governance and the way that impact is measured.

Remoteness of Islands

Logistical, technological, and weather-related obstacles are common in remote islands in the Pacific, causing delays to material-dependent projects. High costs of transportation and certain goods divert spending from on-the-ground implementation. Distance from markets can also limit economic growth. Such issues can lead to decreased interest in the region from international conservation supporters and investors. However, the logistical challenges and high costs related to often remote locations of islands is also a factor driving the development of local solutions for climate adaptation that build on local traditional knowledge. While some of the solutions are specific to the needs of islands, they inspire innovative approaches that can be applied in other areas.

Lack of Technical and Financial Capacity

Pacific Island countries face a number of capacity constraints (e.g., financial and project management, climate modeling and spatial analysis, and infrastructure maintenance; Dornan and Newton Cain, 2014 ). Sustained capacity in the local NGOs also is a challenge; as talented youth rise through the ranks of conservation programs, they are often recruited into higher-paying government or private sector jobs or seek opportunities abroad. Such staff turnover problems hinder long-term conservation projects by causing significant portions of funding sources to be repeatedly used toward capacity development. Local adaptation projects supported by external sources of funding (e.g., climate grants) often end when the grant is over, if there is not sufficient local capacity to continue the project. Finally, lack of technical capacity is also a challenge.

For example, enforcement of marine resource harvesting regulations requires expensive investments in equipment (e.g., boats and surveillance technologies) and advanced training. Enforcement funding is often gleaned from the end of project budgets, as expenditures such as staff time, materials, and planning commonly absorb substantial amounts of initial funding. Technical capacity for climate resilient agriculture is limited, and on-going support is often needed to address emerging threats (e.g., new garden pests in Ahus, Papua New Guinea).

Complex land tenure structures commonly follow traditional or tribal governance systems which can conflict with Western judicial laws and processes, making governance approaches ineffective. This can deter climate financing from large international organizations who require stringent contract-based agreements such as land transfers and easements for protected areas. Nevertheless, traditional tenure and knowledge systems can inform sustainable adaptation strategies and must be considered in the design of adaptation policies. Hence there is the challenge of ensuring compatibility between traditional and western governance systems. The recently established Local Communities and Indigenous Peoples Platform (LCIPP) under the UNFCCC can help to bridge these institutional challenges and ensure local traditional knowledge is considered in the provision of adaptation finance.

Measuring Impact

Many Pacific islands have small populations and small land masses. If donors prioritize their support based on the total number of hectares protected/restored or the total number of people who benefit from a given intervention, Pacific Island projects may not be selected for funding. However, the strong dependence on island communities on their ecosystems for food, livelihoods and traditional practices, provides opportunities for demonstrating how climate adaptation projects can result in direct benefits to both ecosystems and human wellbeing. Additionally, regional commitments to conservation and sustainability such as the Micronesia Challenge can be an important mechanism to scale conservation efforts by providing enabling conditions to better cope with climate change. Initiated by a coalition of regional governments and endorsed at an international level with sustainable funding and technical support for implementation, the Micronesia Challenge serves as a model for other regions. Indeed, it inspired the development of the Caribbean Challenge, Western Indian Ocean Challenge, and the Coral Triangle Initiative.

Scaling Ecosystem-Based Adaptation Through Supportive National Policies and Innovative Financing

Ecosystem-based adaptation actions that support human wellbeing and healthy ecosystems require financing and supportive policies to ensure their implementation, sustainability, and scaling across the region. Such policies must be continually evaluated and refined to ensure that they continue to address local needs in response to change social, ecological, and climatic conditions and must be developed in concert with traditional knowledge. For example, marine protected areas in Manus, Papua New Guinea work best when they reflect the latest science on fish movements and aggregation sites and also follow local tribal boundaries to enable clans to manage their customary land and seas as part of the protected area. This means that local tribes set the rules for their marine protected area that enable species sustainable and address local needs. Thus, in some communities (e.g., Ahus, Papua New Guinea), it is important to strengthen tribal governance and local institutions to mobilize resources and management of adaptation projects. Methods to do so include incorporating climate change into existing ward plans, aligning ward plans with existing provincial and government policies and plans and adapting these plans over time to address changing conditions.

Learning exchange between local, state and national governments are an important mechanism to discuss the challenges communities are encountering in adapting to climate change and to refine current policies with new scientific and local knowledge. They also can highlight gendered impacts of climate change and the differential capacities for adaptation. For example, women in some Pacific Islands are not entitled to land rights due to customary laws and practices which may limit their ability to grow food and resettle in areas less vulnerable to climate impacts. Therefore, policies are needed that consider these gendered impacts (e.g., addressing land ownership inequity as climate change is reducing the available land in some places such as Papua New Guinea; Mcleod et al., 2018 ).

Innovative financing for ecosystem-based adaptation includes the development of tools (e.g., green fees, payment for ecosystem services) and new partnerships with the private sector. For example, water utilities and other businesses that utilize nature for profit can be incentivized to protect the environment. Utilizing payment schemes, such as payments for ecosystem services, creates financial mechanisms to ensure that water is clean, sustainable, and generates new sources of revenue for watershed protection.

The examples above demonstrate positive steps taken by local communities and partners to implement EBA projects in small islands states, yet there is little systematic information on the large-scale effects of these measures for building climate resilience across the region. While some island communities can build resilience to climate change, others will face the limits of adaptation and use migration as a last resort for adapting to climate change impacts. Assessments that identify and predict where adaptation limits are likely to occur and who is most likely to be affected are essential to better plan for climate impacts ( Dow et al., 2013 ). Further, scientific assessments that provide evidence for the effectiveness of the EBA projects are lacking, especially those that include controls to assess the impacts of interventions and provide plausible counterfactual arguments regarding causal mechanisms ( Reid, 2011 ; Munroe et al., 2012 ). Research is also needed to highlight social, ecological, and economic opportunities for upscaling ecosystem-based adaptation and to assess the contribution of adaptation to enhancing island resilience to climate change. Current assessments tend to focus on quantifying biophysical and socio-economic benefits but fail to make the link to management and policy options that enable the implementation of local adaptation options ( Hills et al., 2013 ). In addition to research needs, there is the need for combining traditional with more recently introduced governance systems. Cross-regional exchanges and capacity building can foster the development of innovations that tackle the challenge of including local traditional knowledge and address the needs of island communities. Furthermore, platforms and partnerships that bring together leaders of traditional governance systems with representatives of Western governance systems can help to overcome barriers between different institutional systems and encourage the implementation of holistic community- and ecosystem-based adaptation approaches.

Author Contributions

EM conceived of and developed the manuscript with contributions from MB-A, JF, CF, BG, RJ, GP-K, MT, and ET. JF, CF, GG, BG, RJ, GP-K, MT, and ET collected the data that supported the analysis.

This study is an outcome of a project that is financially supported by the Nature Conservancy and the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU). This study is part of the International Climate Initiative (IKI) and the BMU supports this initiative on the basis of a decision adopted by the German Bundestag.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : small island developing states (SIDS), climate change, Pacific Islands, vulnerability, adaptation, ecosystem-based adaptation

Citation: Mcleod E, Bruton-Adams M, Förster J, Franco C, Gaines G, Gorong B, James R, Posing-Kulwaum G, Tara M and Terk E (2019) Lessons From the Pacific Islands – Adapting to Climate Change by Supporting Social and Ecological Resilience. Front. Mar. Sci. 6:289. doi: 10.3389/fmars.2019.00289

Received: 15 January 2019; Accepted: 17 May 2019; Published: 18 June 2019.

Reviewed by:

Copyright © 2019 Mcleod, Bruton-Adams, Förster, Franco, Gaines, Gorong, James, Posing-Kulwaum, Tara and Terk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Elizabeth Mcleod, [email protected]

This article is part of the Research Topic

Successes at the Interface of Ocean, Climate and Humans

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Research Article

Gender relations and decision-making on climate change adaptation in rural East African households: A qualitative systematic review

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark

Roles Conceptualization, Data curation, Formal analysis, Visualization, Writing – review & editing

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Department of Anthropology, University of Copenhagen, Copenhagen, Denmark

• Johanne Niemann, 
• Miriam El-Mahdi, 
• Helle Samuelsen, 
• Britt Pinkowski Tersbøl

• Published: January 10, 2024
• https://doi.org/10.1371/journal.pclm.0000279
• Peer Review
• Reader Comments

Background: Climatic changes are threatening rural livelihoods in East Africa. Evidence suggests that climate change adaptation in this context might reproduce inequitable intra-household gender relations and that adaptation may be more effective when women are involved in meaningful ways. Hence, a nuanced understanding of the gendered nature of intra-household adaptation decision-making is essential for gender-responsive research, policy-making and practice. This qualitative systematic review aimed to investigate how gender relations influence decision-making concerning climate change adaptation in rural East African households and how decisions about climate change adaptation influence intra-household gender dynamics, in turn. Applying qualitative meta-synthesis principles, systematic searches were conducted in 8 databases and supplemented with comprehensive hand searches. 3,662 unique hits were screened using predetermined inclusion criteria, leading to a final sample of 21 papers. Relevant findings of these studies were synthesised using inductive thematic coding, memoing and thematic analysis. While men tended to be the primary decision-makers, women exercised some decision-making power in traditionally female domains and in female-headed households. Women’s and men’s roles in intra-household adaptation decision-making appeared to be influenced by a plethora of interconnected factors, including gender norms, gendered divisions of labour and access, ownership and control over resources. Intra-household adaptation seemed to impact the dynamics between male and female household members. The pathways of this influence were complex, and the ultimate outcomes for men and women remained unclear. We discuss our findings with reference to theoretical literature on gender-transformative approaches in development and adaptation and previous research concerning the gendered nature of climate change adaptation in East Africa. We then discuss implications for gender-responsive adaptation interventions.

Citation: Niemann J, El-Mahdi M, Samuelsen H, Tersbøl BP (2024) Gender relations and decision-making on climate change adaptation in rural East African households: A qualitative systematic review. PLOS Clim 3(1): e0000279. https://doi.org/10.1371/journal.pclm.0000279

Editor: Girma Gezimu Gebre, Ritsumeikan University, JAPAN

Received: August 7, 2023; Accepted: December 1, 2023; Published: January 10, 2024

Copyright: © 2024 Niemann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This review is part of a larger research project funded by Danida, Danish Ministry of Foreign Affairs (grant awarded to authors BPT and HS). The work of the authors JN and ME was not remunerated. Publication fees are covered by the University of Copenhagen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Climatic changes, such as droughts, increased temperatures, unreliable rainfall and floods, are threatening rural livelihoods in East Africa. [ 1 ] To adapt to these challenges, farmers, fishers, and livestock holders are adopting a range of adaptation strategies, e.g., livelihood diversification including on-farm and off-farm activities, utilisation of new technologies and migration. [ 1 , 2 ] We refer to these strategies as autonomous climate change adaptation (CCA) practices. Moreover, governments, intergovernmental and non-governmental organisations (NGOs) are increasingly implementing interventions to enhance CCA in rural East Africa, [ 3 , 4 ] which we refer to as external CCA interventions or initiatives. However, studies indicate that neither climate change impacts nor CCA are gender-neutral [ 5 , 6 ]. Previous reviews indicate that CCA initiatives have the potential to reproduce or reinforce inequitable gender relations. [ 7 , 8 ] Furthermore, it has been argued that CCA initiatives may be more effective when women are involved in meaningful ways [ 9 ].

Acknowledging the importance of the gender-CCA nexus, leading UN agencies and NGOs now emphasise that equitable participation and benefits from CCA cannot be achieved without addressing fundamental social, economic and cultural structural barriers through intersectional gender-transformative approaches (GTAs) [ 10 , 11 ]. Simultaneously, adaptation research has paid increasing attention to the influence of gender norms and roles on individuals’, households’ and communities’ involvement in CCA practices and decision-making. A scoping review conducted in preparation for this systematic review suggested that, while scientific interest used to centre around comparing CCA in male- and female-headed households, the last five years have seen an increasing number of qualitative and mixed-methods studies investigating the gendered nature of CCA decision-making in rural East African households. These intra-household perspectives seem essential for policy-makers, practitioners and researchers striving to understand how gender norms and relations shape CCA practices and how these practices can, in turn, influence gender dynamics.

To our knowledge, no previous review has yet focused on this inter-dependency of intra-household gender relations and CCA practices, indicating a missed opportunity to synthesise research in order to make it more accessible to policy-making and practice. Moreover, most existing reviews concerning the gender-CCA nexus in sub-Saharan Africa have not been systematic or do not report on methodology in sufficient detail to appraise their quality [ 12 – 14 ].

Hence, the present review aims to investigate how gender and gender relations influence decision-making concerning CCA in rural East African households and how decisions about CCA influence intra-household gender dynamics, in turn. To this end, this review pursued three specific objectives: 1. to identify gender dynamics of intra-household CCA negotiations and decision-making, 2. to analyse underlying factors that shape the gendered nature of CCA decision-making, and 3. to explore how internal and external CCA processes affect intra-household gender dynamics. All specific objectives were achieved, but since the studies included in this review tended to focus on autonomous rather than external CCA initiatives, our findings for external CCA are less nuanced than findings regarding autonomous CCA.

This section situates the present review within the larger research project that it is a part of, justifies our choice to focus on qualitative evidence stemming from settings in East Africa, and clarifies key concepts employed throughout this article, including gender, CCA, GTAs and livelihoods.

The present review constitutes part of a larger research project developed in collaboration between the University of Dar es Salaam, the State University of Zanzibar and the University of Copenhagen. The project received funding from the Danish Ministry of Foreign Affairs (Danida) and investigates gendered encounters in CCA in four districts of Tanzania and Zanzibar. The present review served to inform our research protocol on gendered encounters at intra-household level.

The geographic focus of the present review is partly derived from the larger research project within which it is situated. Moreover, the aforementioned scoping review revealed that many reviews concerning the gender-CCA nexus have covered a wide range of locations, [e.g. 8 , 15 , 16 ] but gender roles and decision-making in CCA processes appear to be highly context-dependent. Thus, focusing on East Africa provided the necessary geographical focus to ensure that synthesis is feasible, while also ensuring that we could access sufficient primary data to allow for a nuanced analysis.

The motive for our choice to include only qualitative evidence in our analysis was that we deemed qualitative data to be most conducive for generating the nuanced, in-depth insights into intra-household CCA decision-making that was necessary to fulfill the review’s specific objectives. Nonetheless, we acknowledge the valuable contributions made by recent quantitative evidence in this field and the importance of integrating qualitative and quantitative evidence to advance gender-responsive research, policy and practice. To this end, we contextualize our findings with relevant quantitative evidence when presenting the results of our review.

Clarification of key concepts

In the present review, we adopt the United Nations Population Fund’s definition of gender as “the economic, social and cultural attributes and opportunities associated with being male or female.” [ 17 ] Thus, we contend that gender-responsive CCA research and practice must move past mere comparisons of women’s and men’s perceptions, experiences and activities. The present review stands in alignment with the work of an increasing number of scholars who emphasise that gender-responsive CCA ought to account for “social relations of production, cultural norms and broader political-economic institutions [that mediate] the nature of exchanges, opportunities and the distribution of resources [and] contribute to the specific constructions and experiences of vulnerability, as well as capacities to respond and cope with climate stresses” [ 18 ,p.28].

Further, the present review employs the Intergovernmental Panel on Climate Change’s definition of CCA as “the process of adjustment to actual or expected climate change and its effects in order to moderate harm or exploit beneficial opportunities.” [ 19 ,p.43] We distinguish between autonomous and external CCA practices. Following Malik, Qin and Smith, we understand autonomous CCA as CCA practices adopted “by individuals and communities without deliberative government planning or intervention,” [ 20 , p.14] which are nonetheless intertwined with “existing social, political, cultural and market institutions.” [ 20 ,p.15] On the other hand, we understand external CCA , also referred to as planned adaptation, as stemming from “a deliberative policy decision, based on an awareness that conditions have changed or are about to change and that action is required to return to, to maintain, or to achieve a desired state.” [ 20 ,p.4] We refer to such interventions as “external” rather than “planned” to underscore that autonomous CCA practices can also be planned.

Based on these conceptualisations of gender and CCA, we adopt Blythe et al.’s understanding of transformative CCA as an approach that addresses fundamental social, political and economic structures that together play a role in rendering populations more vulnerable and marginalised due to inequality. [ 21 ] Interventions employing GTAs embody this approach with specific focus on how gender ideology and norms embedded in these structures indirectly and directly shape women’s and men’s access to resources and to participation in decision-making fora. [ 22 , 23 ] GTAs are commonly conceptualised as spanning three primary dimensions: agency, relations, and institutional structures. [ 23 ] In this context, agency refers to “individual and collective capacities[…], attitudes, critical reflection, assets, actions, and access to services” [ 23 ,p.5]; relations entail “the expectations and cooperative or negotiation dynamics embedded within relationships between people in the home, market, community, and groups and organizations” [ 23 ,p.5]; and structures include “informal and formal institutional rules that govern collective, individual and institutional practices, such as environment, social norms, recognition and status” [ 23 ,p.5]. While GTAs are not explicitly addressed in the findings of this review, we return to the notions outlined here in the discussion.

The discussion also builds on the notion of livelihoods and livelihood transformations as conceptualised by Carr. [ 24 ] Carr notes that agrarian livelihoods are “project[s] of managing both social and natural processes to create and maintain particular socio-ecological states that further specific goals of those living in that system, particularly the goals of those whose authority provides them with privileges not enjoyed by others.” [ 24 ,p.71] According to Carr, gendered roles and identities tend to become more rigid when livelihoods are under environmental or social stress, and it is only when livelihood projects fail to ensure subsistence that spaces for re-negotiation and innovation tend to open up. [ 24 ] Such openings may present opportunities for re-arranging intra-household dynamics in a more equitable manner. However, the ensuing transitions are themselves characterised by power structures and pervasive norms and often pose new risks to different household members, especially those who are most vulnerable [ 24 ].

Materials and methods

The present review employed principles from the qualitative meta-synthesis approach. [ 25 , 26 ] This approach was chosen for its systematic and comprehensive manner of synthesising qualitative primary data in order to generate deeper insights into the phenomena under study. [ 25 ] Qualitative meta-syntheses commonly result in the formulation of frameworks, models or theories. [ 27 ] We chose not to formulate a framework based on our review findings given the scarcity of primary data for some of the themes under study and the questionable quality of some of the included articles (cf. Results). Nonetheless, we found that the application of qualitative meta-synthesis principles to our search, screening and analysis strategies to be useful in generating a comprehensive, in-depth overview of our field of interest.

Search strategy

As is common for qualitative meta-syntheses, [ 28 ] our goal was to retrieve all studies relevant to our review objectives. The search strategy consisted of systematic database searches and supplementary hand searches that were developed through iterative trial searches. Supplementary hand searches were deemed necessary because it has been shown that database searches often do not suffice to identify all qualitative research on a given topic. [ 25 ] Recognizing that systematic searches for qualitative studies tend to include trade-offs between recall (i.e., identifying all relevant studies) and precision (i.e., identifying few non-relevant studies), [ 29 ] we chose to prioritise recall and thus adopted several complementary search techniques.

Our systematic database search spanned 8 databases covering a wide range of disciplines related to the gender-CCA nexus: Anthropology Plus, [ 30 ] Anthrosource, [ 31 ] International Bibliography of the Social Sciences, [ 32 ] Scopus, [ 33 ] SocINDEX, [ 34 ] Sociological Abstracts, [ 35 ] Web of Science, [ 36 ] and Women’s Studies International.[ 37 ] The systematic database search was conducted on 04.05.2022. A detailed search log, including number of hits and search strings used for each database is available in S1 Text .

The supplementary hand searches were conducted between June and August 2022 and consisted of a range of techniques that are commonly included in the umbrella term berrypicking [ 28 , 38 ]: We conducted forward and backward searches of all studies included during the screening process, we searched all publications of the first authors of included studies, and we conducted comprehensive hand searches of selected journals (Nature Climate Change, [ 39 ] Climate Policy, [ 40 ] Climate and Development, [ 41 ] and Gender and Development [ 42 ]) and one database (African Journals OnLine [ 43 ]) that we had identified as highly relevant to this review during the aforementioned scoping review. African Journals OnLine could not be searched systematically due to the limited advanced search functions available in this database. Further information regarding the search terms used for journal and database hand searches are available in S1 Text .

Lastly, a second systematic database search was conducted in Scopus [ 33 ] and Web of Science [ 36 ] on 17.06.2023 to enhance recall of the newest relevant studies. Scopus [ 33 ] and Web of Science [ 36 ] were selected for this search because these databases had rendered the most absolute and relevant hits during the first systematic database search. Further information is available in S1 Text .

Screening of records

An overview of the screening process is given in Fig 1 . All hits were first saved in Zotero, [ 44 ] where duplicates were removed. All unique hits were then uploaded to Rayyan, [ 45 ] where titles and abstracts were screened independently by two researchers using predetermined inclusion criteria (except for hits resulting from the second database search, which were only screened by the first author due to time constraints). Incongruencies were resolved through discussion between the first and second authors. Next, full texts of all studies that had passed the title and abstract screening were screened using the same inclusion criteria. After this, Incongruencies were again resolved through discussion between the first and second authors.

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The inclusion criteria were as follows: 1. general study characteristics (studies had to be peer-reviewed and published in English), 2. population (studies had to include participants from rural regions of East Africa, as defined by the United Nations Statistics Division [ 46 ]), 3. methodology (studies had to report findings from qualitative primary data collection methods), and 4. content (studies had to report findings that explicitly describe how men and women negotiate CCA practices within households).

Quality appraisal of included studies

There seems to be no scientific consensus concerning the approach to designing and conducting quality appraisals when synthesising qualitative research. [ 27 ] We decided to appraise the quality of all included studies because the full-text screening had indicated great discrepancies of quality between studies, and we expected that our analysis would benefit from a more systematic overview over the quality of included studies.

We based the quality appraisal on Saini and Shlonsky’s Qualitative Research Quality Checklist. [ 27 ] This 25-item checklist covers studies’ theoretical frameworks, settings, research designs, sampling procedures, data collection, ethical issues, researcher reflexivity, data analysis, and reporting of the findings. This tool was chosen because it allows for an assessment of quality across a wide range of qualitative research designs, it is more comprehensive than other comparable tools, and it was developed and piloted in a rigorous and transparent manner. [ 27 ] We used the first 22 items of the Checklist and left out the last three items relating to fairness and the promotion of justice, since our main aim was to assess the quality of the findings. Each included article was assessed by one of the authors. As is common practice for qualitative reviews, [ 27 ] we chose to consider the quality appraisal results during our analysis rather than excluding any studies from the analysis.

Data extraction and analysis

The analysis followed a two-step process. First, primary findings relevant to the review’s specific objectives were extracted from all included studies through an iterative, thematic coding process. Authors of the included studies were not contacted during this process due to time constraints. Findings of each article were coded by one reviewer. We chose an inductive approach (i.e., rather than using predetermined themes and codes, we relied on themes and codes emerging from the included studies) because this allows for the preservation of the original interpretations of primary studies, which is essential for qualitative meta-syntheses [ 25 ].

Specifically, we coded 9 of the included studies openly, i.e., assigning codes that were as close as possible to the original meaning of the respective text passages. Based on these codes, we then developed a coding framework which grouped related codes under themes. Serving as a basis for the extraction of findings from the remaining included articles, this framework was then developed and expanded in an iterative manner. The authors compiled their extractions in a shared Google Sheets [ 47 ] table. During the coding process, the authors also collected information pertaining to studies’ settings and methodologies.

Once the coding had been completed, the authors shared their reflections on each theme, code, and interconnections between different themes and codes in an interactive analysis session using the ConceptBoard digital collaboration software. [ 48 ] The results from this session and the shared data extraction sheet were then used as a starting point for further thematic analysis.

This section provides an overview of the included studies, results of the quality appraisal, and a summary of the review findings based on three primary themes that emerged from the analysis (intra-household CCA decision-making, factors influencing gendered CCA decision-making and CCA impacts on intra-household gender dynamics). The section on intra-household CCA decision-making aligns most closely with the first specific objective, the section on factors influencing gendered CCA decision-making covers specific objective two, and the final section relates to specific objective three (cf. Introduction). Where relevant, we contextualize our qualitative findings with quantitative evidence stemming from mixed-methods studies included in our review as well as other articles identified through the systematic database searches.

Study characteristics

The screening process outlined above resulted in 21 included articles. [ 18 , 49 – 68 ] Of these, 18 resulted from the first database search and 3 were identified through supplementary hand searches. General characteristics of the articles are summarised in Table 1 , and detailed information for each article is available in S2 Table .

https://doi.org/10.1371/journal.pclm.0000279.t001

As evident from Table 1 , the final review sample included nearly equal amounts of qualitative and mixed-methods studies. Almost all of these studies employed focus group discussions, followed by key informant interviews and interviews with household members. Most studies appeared to have included both male and female participants, with some notable exceptions that only included women. [ 57 , 67 , 68 ] The included studies employed a wide range of theoretical frameworks and perspectives that commonly related to feminisms and intersectionality (see S2 Table for further details).

In terms of research settings, the included studies involved rural households pursuing a wide range of livelihood activities. While the most common livelihood profiles were dominated by agriculture, agropastoralism and pastoralism, several studies reported increasing diversification and non-farm activities, such as trade and wage labour. Such diversification was commonly described as a response to climatic stressors. Most settings experienced several stressors simultaneously, the most common one being increased frequency, duration or intensity of droughts. In many settings, climate-related livelihood diversification and other forms of intra-household CCA were clearly influenced by gender norms and relations. Moreover, CCA practises themselves also appeared to hold the potential to challenge and shift intra-household gender dynamics.

Study quality

This section provides a general overview of the results of the quality appraisal. Detailed assessments for each article are available in S1 Table . The quality appraisal suggested that the included articles varied substantially in quality (in the present review, we define quality in terms of the factors included in Saini and Shlonsky’s Qualitative Research Quality Checklist [ 27 ]). Several studies appeared to be of high overall quality, characterised by strong internal cohesion between research questions, study design, and reporting of findings; detailed descriptions of qualitative methods; and evident reflexivity of the authors. [ 50 , 54 , 55 , 63 , 66 , 67 ] At the other end of the spectrum, two mixed-methods studies exhibited significant inconsistencies between their objectives, study design and implementation of qualitative methodologies. [ 58 , 59 ] Specifically, in the article by Tambulasi et al., there appeared to be a disconnect between the mixed-methods study design and the research objectives, which were phrased in a quantitative manner.[ 58 ] In the article by Ndlovu and Mjimba, participants for qualitative methodologies were recruited using stratified random sampling, pointing to a lack of internal cohesion [ 59 ].

For most studies, the appraisal was difficult because the articles contained incomplete information regarding data collection and analysis, ethical considerations or study limitations. In some cases, this lack of information was severe enough to undermine a thorough assessment of the studies’ overall quality. [ 52 , 53 , 57 , 60 – 62 , 64 ] This issue was present in mixed-methods and purely qualitative studies alike. Remarkably, even studies that were perceived as of high overall quality tended to lack information regarding ethical considerations, [ 50 , 66 , 67 ] risk of bias and other limitations [ 50 , 54 , 63 ].

Intra-household CCA decision-making

In this section, we describe how male and female household members negotiated the ways in which their households adapted to perceived climatic stressors. While most of the evidence under this theme related to autonomous CCA, the section also includes some observations regarding intra-household decision-making about external CCA interventions.

Generally, men tended to be the primary decision-makers about autonomous and external CCA within households. [ 18 , 58 ] As one male participant from Mphampha village, Malawi, put it: “The man is the head of the family; therefore he must control everything at home. He is the leader, the driver. It’s by culture.” [ 58 ,p.195] However, some studies identified women as the primary implementers of CCA decisions because they played key roles in sustaining households’ livelihoods, [ 62 , 65 , 66 ] with one participant from Gwembe district, Zambia, noting: "The men decide […] leaving women to cope with even the unfavorable decisions." [ 65 ,p.537] This finding of ours is supported by quantitative evidence from a rural household survey in Tanzania’s Morogoro region, which showed that men held significantly higher decision-making power than their wives [ 69 ].

It should be noted that one study found that perceptions about CCA decision-making varied considerably between male and female participants: In focus group discussions about livestock-rearing among Borana pastoralists in Kenya, women claimed that they were rarely involved in decisions concerning animal breeding, while male participants claimed that no decisions were made without women. [ 63 ] The authors of said study offered no potential explanation for this apparent discrepancy between men’s and women’s perceptions of decision-making processes. [ 63 ] However, this observation appears to underscore the complexity of CCA decision-making processes and the various forms of participation and influence exercised by different household members. At any rate, even in this study, male and female participants agreed that men held the primary responsibility for intra-household CCA decision-making [ 63 ].

Regarding decision-making about external CCA interventions, the pattern of male dominance in CCA decision-making was compounded in some settings by the fact that women’s work was centred around the private sphere of the home [ 58 , 61 ]. In these settings, men were primarily responsible for engaging with actors in the public sphere, including governmental actors and NGOs. For instance, Rao et al. observed that in Kenya, “men dominated the state-provided aid and relief facilities during floods or droughts; [with] women relying on their male relatives to fulfil their needs” [ 49 ,p.967].

As indicated by this observation, in many settings, the division of labour within households and communities was strongly gendered, i.e., women and men were responsible for different tasks and domains. [ 50 , 55 , 63 ] In some cases, women appeared to be the primary CCA decision-makers within the domains that fell under their responsibility, such as planting seeds, preserving produce and preparing food. For instance, Anbacha and Kjosavik noted that, in the Ethiopian Borana households that they studied, women had limited decision-making power in the context of livestock rearing but were able to adapt to climatic stressors to some extent by choosing which crops to plant. [ 63 ] This notion of gendered domains for decision-making aligns with quantitative evidence from rural households in Tanzania’s Morogoro region, which suggests that decisions about cover crops and vegetable cultivation fell under the female domain while men were often responsible for decisions about cash-based CCA strategies [ 69 ].

However, effective household-level CCA would often have required comprehensive, integrated solutions because the impacts of climatic stressors were complex and extensive. Where women’s decision-making power was limited to traditionally female domains, this could lead to less adaptive or even maladaptive responses. For instance, one female participant in Kakamega County, Kenya, explained that “since it is the role of women to feed the family, most women reduce their food consumption during food scarcity and some skip meals to spare food for the children" [ 55 ,p.6].

Besides these cases where women made CCA decisions within traditionally female domains, one study referenced a female participant who stated that, in her marriage, decision-making power was primarily dependent on personal knowledge and skills: "After he retired, my husband came here and [now he] helps in the shop. He is not good at networking, nor does he have business ideas, but I can trust him to look after the shop when I am selling miraa. I know how to invest cash and get profit, so have the final say financially." [ 18 ,p.31] This dynamic appeared to be an exception, though.

Some external CCA initiatives attempted to enhance women’s adaptive capacity by providing them with physical resources required for adaptation, e.g., livestock and seeds. However, in most studies, it appeared that the provision of resources did not suffice to enhance women’s CCA agency because these interventions did not challenge the intra-household gender dynamics vesting decision-making power with men. For instance, Tambulasi et al. noted that, when external CCA stakeholders provided women with chicken in Malawi’s Chikwawa District, it was male household members who decided how these chickens should be used to meet household needs [ 58 ].

While most CCA decisions appeared to be taken either by men for the entire household or by men and women for their respective domains, three articles also reported some degree of joint decision-making. [ 59 , 63 , 65 ] For instance, Khoza et al. stated that, among Zambian small-scale farmers choosing to adopt Climate-Smart Agriculture, some male household members decided that they wished to involve their spouses in the decision-making process. [ 65 ] Two other articles reported that female participants were increasingly demanding to be more involved in CCA decision-making processes on the basis of their growing contributions to household economies. [ 18 , 63 ] Quantitative evidence from rural households in Tanzania’s Morogoro region suggests that, in some settings, earning money outside of the household may, indeed, be associated with greater CCA decision-making power among women [ 69 ].

Moreover, Ndlovu and Mjimba found that, among agropastoralists in Zimbabwe’s Umzingwane District, an increase in joint decision-making processes was necessitated by increased frequency and severity of droughts. However, the authors “found that such consultations between spouses often drag [on] and the associated time lag has a bearing on the effectiveness of the proposed interventions to reduce drought related risks”, [ 59 ,p.6] indicating that an increase in joint decision-making might bring about novel challenges.

Lastly, one study suggested that the dynamics of intra-household CCA decision-making were significantly dependent on the gender of household heads. While studying how households decided about the adoption of Climate Smart Agriculture in Malawi and Zambia, Khoza et al. found that "[w]omen could only make decision (sic) in cases of de jure female household heads […] with the outright absence of an adult man to lead decision making. Where an adult male relative was present within household (sic) (such as brother, son or grandson), the woman consulted him and would [be] likely to adopt his opinion on [CSA] adoption." [ 65 ,p.536] The authors found that these differences in decision-making dynamics were rooted in norms of ownership and control over key productive assets, stating that “[w]omen could only own major productive assets if they were de jure female [household heads] and had inherited assets from the late husband.” [ 65 ,p.538] This observation implies that control over household assets might mediate how cultural gender norms and dynamics influence intra-household CCA decision-making. The following section explores this influence in greater depth.

Factors influencing gendered CCA decision-making

This section explores underlying factors that influence the roles played by male and female household members in intra-household CCA decision-making processes. As noted above, intra-household division of labour, CCA decision-making and control over resources are strongly influenced by sociocultural gender norms. Moreover, the foregoing section explored how the gender of household heads might shape intra-household CCA negotiations. This section focuses on access, ownership and control over resources—a third set of factors that appear to mediate the influence of gender on CCA decision-making.

Generally, studies included in this review found that men owned most productive household assets and thus controlled a large share of household resources. [ 58 , 63 ] In most studies, women were typically able to access key productive resources through male household members or relatives. [ 59 , 61 , 65 ] However, women’s access to resources was often less secure than men’s, since women could lose access due to divorce, bereavement and estrangement from male household members and relatives. [ 18 ] This observation aligns with quantitative evidence from rural households in Tanzania’s Morogoro region, which showed that being married was crucial for women’s but not for men’s adaptive capacity because married women were more likely to have access to productive land than their unmarried, widowed or divorced counterparts [ 70 ].

Two articles included in our review highlighted that, even when women’s access to resources and decision-making power were codified in formal institutions, discriminatory cultural norms could hinder women’s ability to exercise their formal rights. [ 49 , 61 ] For instance, Wangui and Smucker found that, regarding women’s ability to access irrigation in Tanzania, "[o]ne of the main constraints […] is access to land. […] Though in principle the [Tanzania Village Land] Act supports gender equity, it leaves a lot of leeway to village government to define the process by which village land is distributed. The process is a greater obstacle for women, who are expected to gain access primarily through their husbands. Women’s adaptation decisions are therefore constrained" [ 61 ,p.373].

Furthermore, while access to resources certainly appeared to influence women’s and men’s adaptive capacity, ownership and control over resources seemed to be much more strongly associated with CCA decision-making power. As Mnimbo et al. observed in Tanzania: “[The] capacity to adapt is shaped by access to and control over resources, as well as power to make decisions. In the study area, males own and have dominant power over household resources. For example, they can decide on trading even households’ assets during drought.” [ 52 ,p.103] This observation is supported by quantitative evidence from the same study, which indicated a significant, gendered divergence between access to and control over resources. For instance, though all female participants could access land, 75% of land was under male control [ 52 ].

Moreover, it appears as though climatic stressors might further decrease women’s control over resources and thus further constrain their CCA decision-making power. For instance, Rao et al. found that, in Kenya, the "customary practice of allocating some [live-]stock for the use of […] wives and daughters” [ 18 ,p.34] was increasingly threatened by persistent droughts. This limited female household members’ ability to engage in CCA through livelihood diversification because women were reliant on this livestock to stem initial investments needed to set up small businesses. In a similar vein, Rao et al. also found that male herders increasingly migrated due to drought, and that “when men moved away with livestock, women lost control over milk for consumption and sale” [ 49 ,p.967]. Though the authors did not assess how these dynamics impacted women’s intra-household CCA decision-making power, it appears plausible that decreased control over resources within their traditional domains might decrease women’s adaptive capacity. Similar patterns have also been observed in quantitative research. For instance, Tavenner et al. found that, within rural East African households, women’s control over resources tended to decrease with increasing commercialization of farming, [ 71 ] which is a common autonomous CCA strategy in this region.

The observation that climatic stressors and related CCA strategies might contribute to decreased adaptive capacity among women shows how intra-household CCA is not only influenced by gender norms, but can itself also impact the dynamics between male and female household members. The following section describes this reciprocal influence in more detail.

CCA impacts on intra-household gender dynamics

As described in the previous section, gendered divisions of labour appeared to influence intra-household CCA decision-making. Simultaneously, numerous studies suggest that CCA practices were influencing intra-household division of labour, in turn. [ 50 , 52 , 55 – 57 , 63 ] It should be noted, however, that intra-household gender dynamics appeared to be influenced by a range of interacting factors, including but not limited to climatic stressors. Other such factors included changes in cultural norms, [ 18 ] economic strain, [ 56 ] and increased governmental regulation of rural livelihoods. [ 63 ] Acknowledging these complex interconnections, we focus on the influence of climatic stressors as it was identified by the authors of the studies included in the present review.

One frequent observation was that, due to persistent drought, men were increasingly struggling to provide for their households in the manner that traditional gender norms demand. [ 50 , 56 ] As a consequence, women in several settings were entering traditionally male-dominated domains, and vice versa in order to secure households’ livelihoods. [ 49 , 50 , 55 , 63 , 65 ] For instance, Rosen et al. observed this tendency in Zambia: “Participant narratives suggested that drought blurred a historically gendered division of employment roles. A shrinking labour market forced men and women to prioritise potential earnings over workforce preferences, pushing women into jobs with heightened manual labor demands and men into labor sectors traditionally dominated by women” [ 56 ,p.6].

Specifically, several studies found that women increasingly engaged in income-generating activities like petty trade and wage labour. [ 49 , 50 , 55 – 57 , 63 ] Often, this trend was rooted not only in the necessity to diversify livelihood portfolios, but also in the fact that men were spending more time away from home due to temporary or permanent migration. [ 49 , 56 , 57 ] This tendency was particularly pronounced in settings where pastoralism continued to play significant roles for sustaining livelihoods. This shift in gendered division of labour reportedly led to increased workloads for women [e.g. 56 ] and a growing proportion of de-facto female-headed households. [ 18 , 49 , 52 , 56 ] Shifts like the ones that emerged in our analysis have also been quantified. For instance, Anbacha and Kjosavik noted that, in Ethiopian Borana households experiencing increased droughts, gendered divisions of labor were becoming increasingly blurred in many domains, including hut making, herding and crop farming [ 50 ].

While none of the articles included in our review addressed whether and how this trend influenced women’s and men’s roles in intra-household CCA decision-making, there is some evidence that climate-induced changes in gendered division of labour might contribute to conflicts between male and female household members. For instance, Anbacha and Kjosavik noted that, in Ethiopia, “participation of women in petty trade is […] creating gender conflicts within their households […]. Women stated that men were not happy when their wives participated in petty trade. Some women were even beaten up and warned by their husbands to stop trading"[ 63 ,p.8]. In some settings, intra-household CCA negotiations were also associated with gender conflict due to the resource constraints that climatic stressors placed on households, e.g., Rosen et al. noted that, in Zambia, “[m]arital relationships were challenged in times of drought, particularly when disagreements around household purchases could not be reconciled. Tightened household incomes required more joint decision-making in even small household purchases” [ 56 ,p.7].

Besides experiencing an increased workload and negative repercussions from gender conflict, women were sometimes negatively impacted by CCA practices that placed them in precarious situations. For instance, two studies reported that female participants engaged in prostitution as a means of escaping utter destitution, [ 56 , 68 ] and Rosen et al. found that, in Zambia, “the financial insecurity propagated by drought forced girls into early marriages. While participants indicated child marriage was prevalent prior to drought, they explained that heightened poverty from drought perpetuated girls being married off by their parents or guardians because they are no longer able to care for them or are getting a financial return from the dowry" [ 56 ,p.7].

The impacts of external CCA interventions on intra-household gender dynamics have not been covered in detail. However, one study found that, if external CCA actors did not consider gendered division of labour when planning and implementing their interventions, these interventions could contribute to the increasing workload for women during climate change: “[T]he NGOs do not synchronize their initiatives, but instead increase the strain on the women and their roles and responsibilities by spreading meetings over weeks, which clash with other community processes and chores pertinent to women. Eventually, the women are left with less time to complete household chores and other productive duties” [ 68 ,p.276].

Despite these instances of CCA practices having negative consequences for female household members, there also seems to be some evidence that CCA might increase women’s agency under certain circumstances. For instance, Anbacha and Kjosavik note that “[a]lthough the participation of women in petty trade has obviously increased their workload, this is gradually challenging the existing gender roles and women are negotiating for change in gender relations" [ 63 ,p.8]. In this study, while women’s increased involvement in income-generating activities led to gender conflict in the short term, it also enabled women to access and control cash, thus enhancing their dependence on male household members. [ 63 ] In a similar vein, Rosen et al. found that, in Zambia, women’s increased involvement in financial decision-making during droughts may have enhanced their influence on intra-household CCA negotiations but was also associated with increased quarrels between husbands and wives. [ 56 ] In sum, the foregoing observations seem to indicate that CCA strategies certainly seem to have the potential to influence intra-household gender dynamics, but the pathways appear to be complex and the ultimate outcomes for male and female household members remain unclear.

The present review aimed to investigate how gender influences decision-making concerning CCA in rural East African households and how decisions about CCA influence intra-household gender dynamics. To this end, systematic database searches were conducted in 8 databases and supplemented with comprehensive hand searches. 3,662 unique hits were screened using predetermined inclusion criteria, leading to a final sample of 21 included studies. Relevant findings of these studies were synthesised using inductive thematic coding, memoing and thematic analysis.

The findings suggested that, while men tended to be the primary decision-makers, women exercised some CCA decision-making power in domains that fell under their purview and in female-headed households. Moreover, women’s and men’s roles in intra-household CCA decision-making appeared to be influenced by a plethora of interconnected factors, including sociocultural gender norms, gendered divisions of labour and access, ownership and control over resources. Lastly, it became evident that intra-household CCA is not only influenced by gender norms but can itself also impact the dynamics between male and female household members. The pathways of this influence appear to be complex, and the ultimate outcomes for male and female household members remain unclear.

In the following sections, we outline several limitations of the present review before discussing our findings with reference to theoretical literature on GTAs in development and adaptation and previous research concerning the gendered nature of CCA in sub-Saharan Africa. In this discussion, we engage particularly with two literature reviews concerning the gendered nature of CCA practices within rural East African households that were published while we were conducting our review. [ 7 , 8 ] While neither of these articles focus primarily on CCA decision-making, their findings are adjacent to the issues studied in the present review. We then conclude by discussing implications for gender-responsive adaptation interventions.

Limitations

A number of limitations ought to be discussed. These relate to the quality and characteristics of the primary studies included in the analysis, the qualitative approach chosen for this review, and challenges inherent to studying intra-household CCA negotiations and decision-making. Firstly, two of the included mixed-methods studies did not distinguish clearly between findings resulting from quantitative and qualitative methodologies, [ 58 , 59 ] which made it hard to identify which findings to extract for our qualitative synthesis. Moreover, we identified some quality-related concerns in these two studies and other papers lacked clarity in reporting, rendering a quality assessment difficult. [ 53 , 57 , 60 – 62 , 64 ] As is common practice for qualitative reviews, [ 27 ] we chose not to exclude these studies from the analysis.

The findings of the present review were further limited by the relative scarcity of data in included primary studies regarding some of the issues we aimed to investigate. This limitation applies especially to intra-household negotiations about external CCA interventions and the impacts of such interventions on gender dynamics. Moreover, though many of the included studies explicitly or implicitly referenced intersectionality, the reporting of the findings in many cases lacked descriptions of multiple markers of difference, which made it difficult to consistently apply an intersectional approach in our analysis. Given that we excluded some otherwise relevant studies because they did not employ qualitative methods, [e.g. 72 ] it appears reasonable to assume that a mixed-methods review might have been able to draw on a richer base of primary data. We attempted to mitigate this limitation by contextualizing our findings with quantitative evidence from selected articles, which largely aligned with our qualitative results.

A mixed-methods or quantitative approach could also have mitigated some of the limitations inherent to all qualitative research, e.g., the limited generalizability of findings. [ 27 ] Since we synthesised qualitative primary data, the findings of the present review cannot necessarily be generalised to all rural households in East Africa. Rather, we hope that our findings may serve as a source of inspiration and a basis for reflection for researchers, policy-makers and practitioners engaging with CCA in East Africa and elsewhere.

Lastly, we encountered two challenges inherent in the field under study: First, as has been noted before, [ 8 ] the concept of CCA decision-making remains vague in many studies, and there appears to be no consensus about how decision-making should be assessed in qualitative and quantitative research. One study included in the present review found that perceptions of men’s and women’s involvement in intra-household CCA decisions differed greatly between male and female participants. [ 63 ] However, while many studies included in the present review did collect data from both male and female participants, [ 54 – 56 , 61 – 66 ] gendered differences or similarities in perceptions were rarely reported.

Second, as noted above (and applicable especially to our findings regarding the third specific objective), changes in gender dynamics in the settings under study appeared to be caused by a range of diverse, interconnected factors. Hence, it would be impudent to assume that all changes discussed above occurred purely in response to climatic stressors. In our analysis, we relied on the interpretations of the study authors, i.e., whenever a study identified climatic stressors as one reason for changes in gender dynamics, we assumed that to be true. Despite these limitations, we believe that the present review adds value to the discourses concerning the gendered nature of CCA in rural East Africa by virtue of its systematic and comprehensive approach to synthesising relevant qualitative evidence.

Intra-household CCA dynamics and gender transformation

From a theoretical perspective, our findings appear to reflect Carr’s framing of agrarian livelihoods as projects that structure household members’ roles and activities in pursuit of a specific, though ever-changing set of social and material goals (cf. Clarification of concepts, for a more detailed description of Carr’s livelihood model). [ 24 ] As described above, Carr posits that re-negotiation of gender roles and identities is most likely to occur when agrarian livelihoods are failing or threatening to fail, and that these re-negotiations are shaped by power structures and often pose new risks to different household members, especially those who are most vulnerable [ 24 ].

The present review has revealed that rural livelihoods in settings across East Africa are faced with a wide array of social and environmental stressors, including changes in climate. Households’ responses are varied and can be seen as falling on a spectrum from reinforcing rigid gender roles and identities to opening up spaces for re-negotiation. For instance, women’s tendency to skip meals in order to fulfil their social duty of ensuring that all other household members are fed, seems to reflect a rigidification of gendered livelihood roles at the expense of vulnerable household members. At the other end of the spectrum, women’s increased engagement in income-generating activities and the increase in de-facto female-headed households might point towards more transformative shifts in gender relations, which may have both positive and negative consequences for women and households.

At first glance, this wide range of adaptive responses appears to deviate from the findings of a recent review concerning “gendered dimensions of Climate-Smart Agriculture in Kenya” [ 7 ,p.1], which found that decision-making about Climate Smart Agriculture consistently reinforced inequitable gender norms and roles. [ 7 ] While our findings do indicate that CCA might reinforce inequities in many instances, we have also found evidence of autonomous CCA processes that appeared to open up spaces for transformative re-negotiation. However, our review found no instances of external CCA interventions leading to such positive transformations. Hence, given that Climate-Smart Agriculture tends to be promoted by stakeholders that are external to households and communities, [ 7 ] our findings could in fact be considered as being in alignment as those of Brisebois et al. concerning CSA adoption in Kenya [ 7 ].

In general, our findings seem to align with Carr’s observation that re-negotiations of gender dynamics are more likely to occur when livelihood projects fail or are threatening to fail to provide basic material security. [ 24 ] However, the threshold for such changes appears to vary between settings and households, with some households adhering to rigid gender roles even when these threaten the subsistence of individual household members. These differences appear to be partly determined by local adaptation contexts and households’ options for re-considering their livelihood projects, e.g. by engaging in new income-generating activities or employing novel agricultural strategies.

Moreover, our findings align with Carr’s observation that, when stressors lead to a re-defining of livelihood projects, the ensuing changes in roles and activities tend to be associated with distinct risks for different household members. [ 24 ] This was evident, for instance, in the experiences of women who had become de-facto household heads due to male out-migration: While their changed position within the household might have increased their decision-making power and autonomy, many had to contend with challenges of access to resources and social standing within their communities, [ 65 ] as well as increased workloads [ 56 ].

Male household members, too, appeared to be threatened by changes in livelihood projects and associated shifts in gender dynamics, though the risks they faced generally were of a more social, less existential nature. For instance, some studies included in the present review found that gender-based domestic violence had surged when women increased their engagement in income-generating activities because male household members perceived these activities as threatening for their identities as primary providers. [e.g. 63 ] In a similar vein, some male participants expressed a fear of social repercussions from other community members who might view them as incapable of providing for their households. [ 63 ] This finding aligns with Carr’s observation that livelihood projects serve as a means to obtain social as well as material goals, and that powerful household members, especially male household heads, tend to determine these goals and may use means of coercion to sanction other household members’ non-compliance [ 24 ].

However, female participants in the studies included in the present review tended to continue to engage in income-generating activities despite the attempted coercion because of the great perceived threat of failure of more traditional livelihood projects. Male household members appeared to eventually accept these activities once they recognized the associated increase in household income. According to Carr, male household members may be more likely to tolerate or even support increased productivity among women if they are themselves secure in their gendered identities as primary providers. [ 24 ] Unfortunately, we cannot conclude with certainty whether this tendency was present in the households analysed in this review because only few of the included studies consistently provided information about household wealth and material security.

Implications for gender-responsive adaptation interventions

The previous section suggested that our findings may hold valuable insights regarding the potential for gender transformation through CCA in East African rural households. This section explores resulting implications for gender-responsive adaptation policies and initiatives, i.e., external CCA interventions. According to Carr, most development and adaptation interventions that aim to foster more equitable gender dynamics in agrarian households are unsuccessful—either because they fail to challenge the underlying power relations that lead to inequitable outcomes, or because they disrupt current livelihood projects but fail to support the creation of viable, contextually appropriate alternatives. [ 24 ] Evidence regarding external adaptation interventions was scarce in the present review, with some notable exceptions. [ 49 , 58 , 65 ] The few interventions that were discussed predominantly fell under the first category, i.e., they did not challenge the root causes of inequality. For instance, studies included in this review found that interventions which attempted to “empower” women by providing access to credit, land, other productive resources or information were often ineffective because the provided resources were co-opted by male household members or because rigid gender norms prevented women from exercising control over the use of their knowledge, skills and assets [ 58 , 65 ].

Rather than ensuring that male household members were secure in their identities as primary providers and could thus concede more agency to female household members, [ 24 ] these interventions appeared to attempt to “empower” women by enhancing their standing vis-a-vis men. When applied in isolation, these approaches appear to disregard the complexity of intra-household power relations and the importance of livelihood projects as means for achieving social goals, and might thus add to gender conflict rather than relieving tensions and opening up spaces for effective re-negotiation.

There certainly is a case to be made for targeted interventions that provide immediate relief from the acute risks faced by many women and girls in East African rural households. We agree with Galiè and Kantor’s notion that “[b]oth gender accommodative and transformative approaches can add value, […] with the mix of approaches at different points in the change process determined by contextual conditions.” [ 22 ,p.195] However, it appears crucial that stakeholders involved in designing, implementing and monitoring gender accommodative interventions are aware that their initiatives are likely to cause some disruption to current livelihood strategies, which may lead to novel risks and unexpected consequences for the communities, households and individuals they attempt to support [ 24 ].

Findings from the present review suggest that all external CCA interventions in this context ought to recognize not only that rural livelihoods are under stress, but also that communities, households and individuals are actively responding to these stressors and, in some settings, have begun to re-negotiate livelihood projects and associated gender roles and identities. For instance, our findings suggest that there may be an increase in joint decision-making processes in some settings, and that joint decision-making might involve novel challenges, such as greater time demands and sources of potential conflict. An external intervention aiming to foster equitable and effective joint decision-making might be most promising when it is built on a deep and comprehensive understanding of the underlying sociocultural dynamics and actively encourages participants to co-create alternative livelihood projects that can benefit all members of a household or community.

This underscores the importance of working with local conceptualizations of “empowerment” in the context of GTAs, rather than attempting to impose externally generated notions of who should be empowered to do what and in which manner. [ 22 ] Moreover, this approach might deviate slightly from previous operationalizations of GTAs, which emphasise the importance of fostering reflections about gender norms among participants [ 23 ]: If one views gender roles and identities as resulting from livelihood projects that are developed and maintained in pursuit of a specific, though dynamic set of material and social goals, [ 24 ] then discussions about gender transformation and equity become inextricably linked to the livelihood project and goals in question. Interventions that adopt this premise might initiate discussions and re-negotiations of gender dynamics not by prompting reflections on gender dynamics directly, but rather through reflections on women’s and men’s shared and individual livelihood aspirations.

The present review also contributes to the gender-transformative design and implementation discourse in another manner. As explained above (cf. Background), GTAs are commonly conceptualised as spanning three primary dimensions: agency, relations and institutional structures. [ 23 ] The gender dynamics of intra-household CCA negotiations and decision-making are most closely aligned with the relational dimension of GTAs. Regarding the relational dimension of GTAs, our findings further showed that women’s approaches to managing their relationships with their husbands depended not only on the quality of the dyadic relationship between husband and wife, but were influenced by a complex web of reciprocal relations spanning women’s support networks and kin beyond the confines of the household. This observation indicates that gender-responsive adaptation interventions might do well to consider not only marital relationships, but the complex web of relations that different household members navigate within and beyond the household.

Furthermore, the findings of the present review underscore the importance of gender-transformative interventions that address all three primary domains, as suggested by Hillebrand et al. [ 23 ] For instance, our findings suggest that agency, e.g., in the form of control over cash and productive assets, appears to have a critical influence on household members’ decision-making power. [ 51 , 52 , 58 , 61 , 63 , 65 ] Further, formal and informal institutions, e.g., policies governing land ownership and sociocultural norms regarding gendered divisions of labour, also appeared to shape the roles and identities that women and men embodied in intra-household CCA negotiations. [e.g. 61 ] However, analyses of external adaptation interventions revealed that addressing any of these factors did not appear to generate more equitable outcomes if intra-household relations remained unchanged [e.g. 58 ].

In sum, the present qualitative systematic review has shown that significant evidence gaps remain regarding the interplay of gender relations and CCA decision-making in rural East African households, especially concerning nuanced descriptions of intra-household CCA negotiations about external CCA interventions. Nonetheless, our analysis has revealed that the evidence base has grown substantially over the past five years. When synthesised, this knowledge significantly contributes to our understanding of the complex, context-dependent dynamics linking gender relations and intra-household CCA in rural East African households. We hope that the present review will provide guidance for policy-makers and practitioners who design, implement and evaluate gender-responsive CCA interventions in rural East Africa.

Supporting information

S1 checklist. prisma 2020 checklist..

https://doi.org/10.1371/journal.pclm.0000279.s001

S1 Text. Search strategy.

https://doi.org/10.1371/journal.pclm.0000279.s002

S1 Table. Quality appraisal of all included articles.

https://doi.org/10.1371/journal.pclm.0000279.s003

S2 Table. Study characteristics of all included articles.

https://doi.org/10.1371/journal.pclm.0000279.s004

Acknowledgments

The authors are thankful for the contributions of Isabelle Carson, Sophie Effing and Eileen Ziemann, who contributed to the supplementary hand searches as part of their MSc. Global Health programme at the University of Copenhagen; and for the support of Therese Møller, information specialist at the Social Science Library at the University of Copenhagen, who assisted in the development of the search strategy.

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Floods in southern Brazil kill at least 75 people in a week, force more than 80,000 to evacuate

RIO DE JANEIRO (AP) — Massive floods in Brazil’s southern Rio Grande do Sul state have killed at least 75 people over the last seven days, and another 103 were reported missing, local authorities said Sunday.

At least 155 people were injured, while damage from the rains forced more than 88,000 people from their homes. Approximately 16,000 took refuge in schools, gymnasiums and other temporary shelters.

The floods left a wake of devastation, including landslides, washed-out roads and collapsed bridges across the state. Operators reported electricity and communications cuts. More than 800,000 people are without a water supply, according to the civil defense agency, which cited figures from water company Corsan.

A rescue team pulled an elderly man in serious medical condition into a helicopter from a remote area in the Bento Gonçalves municipality, according to footage from military firefighters. Torrents of brown water poured over a nearby dam.

READ MORE: Heavy rains kill at least 7 in southeastern Brazil, 4-year-old rescued from collapsed house

On Saturday evening, residents in the town of Canoas stood up to their shoulders in muddy water and formed a human chain to pull boats carrying people to safety, according to video footage shared by local UOL news network.

The Guaiba river reached a record level of 5.33 meters (17.5 feet) on Sunday morning at 8 a.m. local time, surpassing levels seen during a historic 1941 deluge, when the river reached 4.76 meters.

“I repeat and insist: the devastation to which we are being subjected is unprecedented,” state Gov. Eduardo Leite said Sunday morning. He had previously said the state will need a “kind of ‘Marshall Plan’ to be rebuilt.”

Brazilian President Luiz Inácio Lula da Silva visited Rio Grande do Sul for a second time on Sunday, accompanied by Defense Minister José Múcio, Finance Minister Fernando Haddad and Environment Minister Marina Silva, among others. The leftist leader and his team surveyed the flooded streets of Porto Alegre from a helicopter.

“We need to stop running behind disasters. We need to see in advance what calamities might happen and we need to work,” Lula told journalists afterwards.

During Sunday mass at the Vatican, Pope Francis said he was praying for the state’s population. “May the Lord welcome the dead and comfort their families and those who had to abandon their homes,” he said.

The downpour started Monday and was expected to last through Sunday. In some areas, such as valleys, mountain slopes and cities, more than 300 millimeters (11.8 inches) of rain fell in less than a week, according to Brazil’s National Institute of Meteorology, known by the Portuguese acronym INMET, on Thursday.

The heavy rains were the fourth such environmental disaster in the state in a year, following floods in July, September and November 2023 that killed 75 people.

Weather across South America is affected by the climate phenomenon El Niño, a periodic, naturally occurring event that warms surface waters in the Equatorial Pacific region. In Brazil, El Niño has historically caused droughts in the north and intense rainfall in the south.

This year, the impacts of El Niño have been particularly dramatic, with  a historic drought in the Amazon . Scientists say extreme weather is happening more frequently due to human-caused climate change.

“These tragedies will continue to happen, increasingly worse and more frequent,” said Suely Araújo, a public policy coordinator at the Climate Observatory, a network of dozens of environmental and social groups.

Brazil needs to adjust to the effects of climate change, she said in a Friday statement, referring to a process known as adaptation.

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• Published: 17 April 2024

The economic commitment of climate change

• Maximilian Kotz   ORCID: orcid.org/0000-0003-2564-5043 1 , 2 ,
• Anders Levermann   ORCID: orcid.org/0000-0003-4432-4704 1 , 2 &
• Leonie Wenz   ORCID: orcid.org/0000-0002-8500-1568 1 , 3  

Nature volume  628 ,  pages 551–557 ( 2024 ) Cite this article

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• Environmental economics
• Environmental health
• Interdisciplinary studies
• Projection and prediction

Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons 1 , 2 , 3 , 4 , 5 , 6 . Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes 7 , 8 . Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

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Projections of the macroeconomic damage caused by future climate change are crucial to informing public and policy debates about adaptation, mitigation and climate justice. On the one hand, adaptation against climate impacts must be justified and planned on the basis of an understanding of their future magnitude and spatial distribution 9 . This is also of importance in the context of climate justice 10 , as well as to key societal actors, including governments, central banks and private businesses, which increasingly require the inclusion of climate risks in their macroeconomic forecasts to aid adaptive decision-making 11 , 12 . On the other hand, climate mitigation policy such as the Paris Climate Agreement is often evaluated by balancing the costs of its implementation against the benefits of avoiding projected physical damages. This evaluation occurs both formally through cost–benefit analyses 1 , 4 , 5 , 6 , as well as informally through public perception of mitigation and damage costs 13 .

Projections of future damages meet challenges when informing these debates, in particular the human biases relating to uncertainty and remoteness that are raised by long-term perspectives 14 . Here we aim to overcome such challenges by assessing the extent of economic damages from climate change to which the world is already committed by historical emissions and socio-economic inertia (the range of future emission scenarios that are considered socio-economically plausible 15 ). Such a focus on the near term limits the large uncertainties about diverging future emission trajectories, the resulting long-term climate response and the validity of applying historically observed climate–economic relations over long timescales during which socio-technical conditions may change considerably. As such, this focus aims to simplify the communication and maximize the credibility of projected economic damages from future climate change.

In projecting the future economic damages from climate change, we make use of recent advances in climate econometrics that provide evidence for impacts on sub-national economic growth from numerous components of the distribution of daily temperature and precipitation 3 , 7 , 8 . Using fixed-effects panel regression models to control for potential confounders, these studies exploit within-region variation in local temperature and precipitation in a panel of more than 1,600 regions worldwide, comprising climate and income data over the past 40 years, to identify the plausibly causal effects of changes in several climate variables on economic productivity 16 , 17 . Specifically, macroeconomic impacts have been identified from changing daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall that occur in addition to those already identified from changing average temperature 2 , 3 , 18 . Moreover, regional heterogeneity in these effects based on the prevailing local climatic conditions has been found using interactions terms. The selection of these climate variables follows micro-level evidence for mechanisms related to the impacts of average temperatures on labour and agricultural productivity 2 , of temperature variability on agricultural productivity and health 7 , as well as of precipitation on agricultural productivity, labour outcomes and flood damages 8 (see Extended Data Table 1 for an overview, including more detailed references). References  7 , 8 contain a more detailed motivation for the use of these particular climate variables and provide extensive empirical tests about the robustness and nature of their effects on economic output, which are summarized in Methods . By accounting for these extra climatic variables at the sub-national level, we aim for a more comprehensive description of climate impacts with greater detail across both time and space.

Constraining the persistence of impacts

A key determinant and source of discrepancy in estimates of the magnitude of future climate damages is the extent to which the impact of a climate variable on economic growth rates persists. The two extreme cases in which these impacts persist indefinitely or only instantaneously are commonly referred to as growth or level effects 19 , 20 (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for mathematical definitions). Recent work shows that future damages from climate change depend strongly on whether growth or level effects are assumed 20 . Following refs.  2 , 18 , we provide constraints on this persistence by using distributed lag models to test the significance of delayed effects separately for each climate variable. Notably, and in contrast to refs.  2 , 18 , we use climate variables in their first-differenced form following ref.  3 , implying a dependence of the growth rate on a change in climate variables. This choice means that a baseline specification without any lags constitutes a model prior of purely level effects, in which a permanent change in the climate has only an instantaneous effect on the growth rate 3 , 19 , 21 . By including lags, one can then test whether any effects may persist further. This is in contrast to the specification used by refs.  2 , 18 , in which climate variables are used without taking the first difference, implying a dependence of the growth rate on the level of climate variables. In this alternative case, the baseline specification without any lags constitutes a model prior of pure growth effects, in which a change in climate has an infinitely persistent effect on the growth rate. Consequently, including further lags in this alternative case tests whether the initial growth impact is recovered 18 , 19 , 21 . Both of these specifications suffer from the limiting possibility that, if too few lags are included, one might falsely accept the model prior. The limitations of including a very large number of lags, including loss of data and increasing statistical uncertainty with an increasing number of parameters, mean that such a possibility is likely. By choosing a specification in which the model prior is one of level effects, our approach is therefore conservative by design, avoiding assumptions of infinite persistence of climate impacts on growth and instead providing a lower bound on this persistence based on what is observable empirically (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for further exposition of this framework). The conservative nature of such a choice is probably the reason that ref.  19 finds much greater consistency between the impacts projected by models that use the first difference of climate variables, as opposed to their levels.

We begin our empirical analysis of the persistence of climate impacts on growth using ten lags of the first-differenced climate variables in fixed-effects distributed lag models. We detect substantial effects on economic growth at time lags of up to approximately 8–10 years for the temperature terms and up to approximately 4 years for the precipitation terms (Extended Data Fig. 1 and Extended Data Table 2 ). Furthermore, evaluation by means of information criteria indicates that the inclusion of all five climate variables and the use of these numbers of lags provide a preferable trade-off between best-fitting the data and including further terms that could cause overfitting, in comparison with model specifications excluding climate variables or including more or fewer lags (Extended Data Fig. 3 , Supplementary Methods Section  1 and Supplementary Table 1 ). We therefore remove statistically insignificant terms at later lags (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). Further tests using Monte Carlo simulations demonstrate that the empirical models are robust to autocorrelation in the lagged climate variables (Supplementary Methods Section  2 and Supplementary Figs. 4 and 5 ), that information criteria provide an effective indicator for lag selection (Supplementary Methods Section  2 and Supplementary Fig. 6 ), that the results are robust to concerns of imperfect multicollinearity between climate variables and that including several climate variables is actually necessary to isolate their separate effects (Supplementary Methods Section  3 and Supplementary Fig. 7 ). We provide a further robustness check using a restricted distributed lag model to limit oscillations in the lagged parameter estimates that may result from autocorrelation, finding that it provides similar estimates of cumulative marginal effects to the unrestricted model (Supplementary Methods Section 4 and Supplementary Figs. 8 and 9 ). Finally, to explicitly account for any outstanding uncertainty arising from the precise choice of the number of lags, we include empirical models with marginally different numbers of lags in the error-sampling procedure of our projection of future damages. On the basis of the lag-selection procedure (the significance of lagged terms in Extended Data Fig. 1 and Extended Data Table 2 , as well as information criteria in Extended Data Fig. 3 ), we sample from models with eight to ten lags for temperature and four for precipitation (models shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). In summary, this empirical approach to constrain the persistence of climate impacts on economic growth rates is conservative by design in avoiding assumptions of infinite persistence, but nevertheless provides a lower bound on the extent of impact persistence that is robust to the numerous tests outlined above.

Committed damages until mid-century

We combine these empirical economic response functions (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) with an ensemble of 21 climate models (see Supplementary Table 5 ) from the Coupled Model Intercomparison Project Phase 6 (CMIP-6) 22 to project the macroeconomic damages from these components of physical climate change (see Methods for further details). Bias-adjusted climate models that provide a highly accurate reproduction of observed climatological patterns with limited uncertainty (Supplementary Table 6 ) are used to avoid introducing biases in the projections. Following a well-developed literature 2 , 3 , 19 , these projections do not aim to provide a prediction of future economic growth. Instead, they are a projection of the exogenous impact of future climate conditions on the economy relative to the baselines specified by socio-economic projections, based on the plausibly causal relationships inferred by the empirical models and assuming ceteris paribus. Other exogenous factors relevant for the prediction of economic output are purposefully assumed constant.

A Monte Carlo procedure that samples from climate model projections, empirical models with different numbers of lags and model parameter estimates (obtained by 1,000 block-bootstrap resamples of each of the regressions in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) is used to estimate the combined uncertainty from these sources. Given these uncertainty distributions, we find that projected global damages are statistically indistinguishable across the two most extreme emission scenarios until 2049 (at the 5% significance level; Fig. 1 ). As such, the climate damages occurring before this time constitute those to which the world is already committed owing to the combination of past emissions and the range of future emission scenarios that are considered socio-economically plausible 15 . These committed damages comprise a permanent income reduction of 19% on average globally (population-weighted average) in comparison with a baseline without climate-change impacts (with a likely range of 11–29%, following the likelihood classification adopted by the Intergovernmental Panel on Climate Change (IPCC); see caption of Fig. 1 ). Even though levels of income per capita generally still increase relative to those of today, this constitutes a permanent income reduction for most regions, including North America and Europe (each with median income reductions of approximately 11%) and with South Asia and Africa being the most strongly affected (each with median income reductions of approximately 22%; Fig. 1 ). Under a middle-of-the road scenario of future income development (SSP2, in which SSP stands for Shared Socio-economic Pathway), this corresponds to global annual damages in 2049 of 38 trillion in 2005 international dollars (likely range of 19–59 trillion 2005 international dollars). Compared with empirical specifications that assume pure growth or pure level effects, our preferred specification that provides a robust lower bound on the extent of climate impact persistence produces damages between these two extreme assumptions (Extended Data Fig. 3 ).

Estimates of the projected reduction in income per capita from changes in all climate variables based on empirical models of climate impacts on economic output with a robust lower bound on their persistence (Extended Data Fig. 1 ) under a low-emission scenario compatible with the 2 °C warming target and a high-emission scenario (SSP2-RCP2.6 and SSP5-RCP8.5, respectively) are shown in purple and orange, respectively. Shading represents the 34% and 10% confidence intervals reflecting the likely and very likely ranges, respectively (following the likelihood classification adopted by the IPCC), having estimated uncertainty from a Monte Carlo procedure, which samples the uncertainty from the choice of physical climate models, empirical models with different numbers of lags and bootstrapped estimates of the regression parameters shown in Supplementary Figs. 1 – 3 . Vertical dashed lines show the time at which the climate damages of the two emission scenarios diverge at the 5% and 1% significance levels based on the distribution of differences between emission scenarios arising from the uncertainty sampling discussed above. Note that uncertainty in the difference of the two scenarios is smaller than the combined uncertainty of the two respective scenarios because samples of the uncertainty (climate model and empirical model choice, as well as model parameter bootstrap) are consistent across the two emission scenarios, hence the divergence of damages occurs while the uncertainty bounds of the two separate damage scenarios still overlap. Estimates of global mitigation costs from the three IAMs that provide results for the SSP2 baseline and SSP2-RCP2.6 scenario are shown in light green in the top panel, with the median of these estimates shown in bold.

Damages already outweigh mitigation costs

We compare the damages to which the world is committed over the next 25 years to estimates of the mitigation costs required to achieve the Paris Climate Agreement. Taking estimates of mitigation costs from the three integrated assessment models (IAMs) in the IPCC AR6 database 23 that provide results under comparable scenarios (SSP2 baseline and SSP2-RCP2.6, in which RCP stands for Representative Concentration Pathway), we find that the median committed climate damages are larger than the median mitigation costs in 2050 (six trillion in 2005 international dollars) by a factor of approximately six (note that estimates of mitigation costs are only provided every 10 years by the IAMs and so a comparison in 2049 is not possible). This comparison simply aims to compare the magnitude of future damages against mitigation costs, rather than to conduct a formal cost–benefit analysis of transitioning from one emission path to another. Formal cost–benefit analyses typically find that the net benefits of mitigation only emerge after 2050 (ref.  5 ), which may lead some to conclude that physical damages from climate change are simply not large enough to outweigh mitigation costs until the second half of the century. Our simple comparison of their magnitudes makes clear that damages are actually already considerably larger than mitigation costs and the delayed emergence of net mitigation benefits results primarily from the fact that damages across different emission paths are indistinguishable until mid-century (Fig. 1 ).

Although these near-term damages constitute those to which the world is already committed, we note that damage estimates diverge strongly across emission scenarios after 2049, conveying the clear benefits of mitigation from a purely economic point of view that have been emphasized in previous studies 4 , 24 . As well as the uncertainties assessed in Fig. 1 , these conclusions are robust to structural choices, such as the timescale with which changes in the moderating variables of the empirical models are estimated (Supplementary Figs. 10 and 11 ), as well as the order in which one accounts for the intertemporal and international components of currency comparison (Supplementary Fig. 12 ; see Methods for further details).

Damages from variability and extremes

Committed damages primarily arise through changes in average temperature (Fig. 2 ). This reflects the fact that projected changes in average temperature are larger than those in other climate variables when expressed as a function of their historical interannual variability (Extended Data Fig. 4 ). Because the historical variability is that on which the empirical models are estimated, larger projected changes in comparison with this variability probably lead to larger future impacts in a purely statistical sense. From a mechanistic perspective, one may plausibly interpret this result as implying that future changes in average temperature are the most unprecedented from the perspective of the historical fluctuations to which the economy is accustomed and therefore will cause the most damage. This insight may prove useful in terms of guiding adaptation measures to the sources of greatest damage.

Estimates of the median projected reduction in sub-national income per capita across emission scenarios (SSP2-RCP2.6 and SSP2-RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ). a , Impacts arising from all climate variables. b – f , Impacts arising separately from changes in annual mean temperature ( b ), daily temperature variability ( c ), total annual precipitation ( d ), the annual number of wet days (>1 mm) ( e ) and extreme daily rainfall ( f ) (see Methods for further definitions). Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Nevertheless, future damages based on empirical models that consider changes in annual average temperature only and exclude the other climate variables constitute income reductions of only 13% in 2049 (Extended Data Fig. 5a , likely range 5–21%). This suggests that accounting for the other components of the distribution of temperature and precipitation raises net damages by nearly 50%. This increase arises through the further damages that these climatic components cause, but also because their inclusion reveals a stronger negative economic response to average temperatures (Extended Data Fig. 5b ). The latter finding is consistent with our Monte Carlo simulations, which suggest that the magnitude of the effect of average temperature on economic growth is underestimated unless accounting for the impacts of other correlated climate variables (Supplementary Fig. 7 ).

In terms of the relative contributions of the different climatic components to overall damages, we find that accounting for daily temperature variability causes the largest increase in overall damages relative to empirical frameworks that only consider changes in annual average temperature (4.9 percentage points, likely range 2.4–8.7 percentage points, equivalent to approximately 10 trillion international dollars). Accounting for precipitation causes smaller increases in overall damages, which are—nevertheless—equivalent to approximately 1.2 trillion international dollars: 0.01 percentage points (−0.37–0.33 percentage points), 0.34 percentage points (0.07–0.90 percentage points) and 0.36 percentage points (0.13–0.65 percentage points) from total annual precipitation, the number of wet days and extreme daily precipitation, respectively. Moreover, climate models seem to underestimate future changes in temperature variability 25 and extreme precipitation 26 , 27 in response to anthropogenic forcing as compared with that observed historically, suggesting that the true impacts from these variables may be larger.

The distribution of committed damages

The spatial distribution of committed damages (Fig. 2a ) reflects a complex interplay between the patterns of future change in several climatic components and those of historical economic vulnerability to changes in those variables. Damages resulting from increasing annual mean temperature (Fig. 2b ) are negative almost everywhere globally, and larger at lower latitudes in regions in which temperatures are already higher and economic vulnerability to temperature increases is greatest (see the response heterogeneity to mean temperature embodied in Extended Data Fig. 1a ). This occurs despite the amplified warming projected at higher latitudes 28 , suggesting that regional heterogeneity in economic vulnerability to temperature changes outweighs heterogeneity in the magnitude of future warming (Supplementary Fig. 13a ). Economic damages owing to daily temperature variability (Fig. 2c ) exhibit a strong latitudinal polarisation, primarily reflecting the physical response of daily variability to greenhouse forcing in which increases in variability across lower latitudes (and Europe) contrast decreases at high latitudes 25 (Supplementary Fig. 13b ). These two temperature terms are the dominant determinants of the pattern of overall damages (Fig. 2a ), which exhibits a strong polarity with damages across most of the globe except at the highest northern latitudes. Future changes in total annual precipitation mainly bring economic benefits except in regions of drying, such as the Mediterranean and central South America (Fig. 2d and Supplementary Fig. 13c ), but these benefits are opposed by changes in the number of wet days, which produce damages with a similar pattern of opposite sign (Fig. 2e and Supplementary Fig. 13d ). By contrast, changes in extreme daily rainfall produce damages in all regions, reflecting the intensification of daily rainfall extremes over global land areas 29 , 30 (Fig. 2f and Supplementary Fig. 13e ).

The spatial distribution of committed damages implies considerable injustice along two dimensions: culpability for the historical emissions that have caused climate change and pre-existing levels of socio-economic welfare. Spearman’s rank correlations indicate that committed damages are significantly larger in countries with smaller historical cumulative emissions, as well as in regions with lower current income per capita (Fig. 3 ). This implies that those countries that will suffer the most from the damages already committed are those that are least responsible for climate change and which also have the least resources to adapt to it.

Estimates of the median projected change in national income per capita across emission scenarios (RCP2.6 and RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ) are plotted against cumulative national emissions per capita in 2020 (from the Global Carbon Project) and coloured by national income per capita in 2020 (from the World Bank) in a and vice versa in b . In each panel, the size of each scatter point is weighted by the national population in 2020 (from the World Bank). Inset numbers indicate the Spearman’s rank correlation ρ and P -values for a hypothesis test whose null hypothesis is of no correlation, as well as the Spearman’s rank correlation weighted by national population.

To further quantify this heterogeneity, we assess the difference in committed damages between the upper and lower quartiles of regions when ranked by present income levels and historical cumulative emissions (using a population weighting to both define the quartiles and estimate the group averages). On average, the quartile of countries with lower income are committed to an income loss that is 8.9 percentage points (or 61%) greater than the upper quartile (Extended Data Fig. 6 ), with a likely range of 3.8–14.7 percentage points across the uncertainty sampling of our damage projections (following the likelihood classification adopted by the IPCC). Similarly, the quartile of countries with lower historical cumulative emissions are committed to an income loss that is 6.9 percentage points (or 40%) greater than the upper quartile, with a likely range of 0.27–12 percentage points. These patterns reemphasize the prevalence of injustice in climate impacts 31 , 32 , 33 in the context of the damages to which the world is already committed by historical emissions and socio-economic inertia.

Contextualizing the magnitude of damages

The magnitude of projected economic damages exceeds previous literature estimates 2 , 3 , arising from several developments made on previous approaches. Our estimates are larger than those of ref.  2 (see first row of Extended Data Table 3 ), primarily because of the facts that sub-national estimates typically show a steeper temperature response (see also refs.  3 , 34 ) and that accounting for other climatic components raises damage estimates (Extended Data Fig. 5 ). However, we note that our empirical approach using first-differenced climate variables is conservative compared with that of ref.  2 in regard to the persistence of climate impacts on growth (see introduction and Methods section ‘Empirical model specification: fixed-effects distributed lag models’), an important determinant of the magnitude of long-term damages 19 , 21 . Using a similar empirical specification to ref.  2 , which assumes infinite persistence while maintaining the rest of our approach (sub-national data and further climate variables), produces considerably larger damages (purple curve of Extended Data Fig. 3 ). Compared with studies that do take the first difference of climate variables 3 , 35 , our estimates are also larger (see second and third rows of Extended Data Table 3 ). The inclusion of further climate variables (Extended Data Fig. 5 ) and a sufficient number of lags to more adequately capture the extent of impact persistence (Extended Data Figs. 1 and 2 ) are the main sources of this difference, as is the use of specifications that capture nonlinearities in the temperature response when compared with ref.  35 . In summary, our estimates develop on previous studies by incorporating the latest data and empirical insights 7 , 8 , as well as in providing a robust empirical lower bound on the persistence of impacts on economic growth, which constitutes a middle ground between the extremes of the growth-versus-levels debate 19 , 21 (Extended Data Fig. 3 ).

Compared with the fraction of variance explained by the empirical models historically (<5%), the projection of reductions in income of 19% may seem large. This arises owing to the fact that projected changes in climatic conditions are much larger than those that were experienced historically, particularly for changes in average temperature (Extended Data Fig. 4 ). As such, any assessment of future climate-change impacts necessarily requires an extrapolation outside the range of the historical data on which the empirical impact models were evaluated. Nevertheless, these models constitute the most state-of-the-art methods for inference of plausibly causal climate impacts based on observed data. Moreover, we take explicit steps to limit out-of-sample extrapolation by capping the moderating variables of the interaction terms at the 95th percentile of the historical distribution (see Methods ). This avoids extrapolating the marginal effects outside what was observed historically. Given the nonlinear response of economic output to annual mean temperature (Extended Data Fig. 1 and Extended Data Table 2 ), this is a conservative choice that limits the magnitude of damages that we project. Furthermore, back-of-the-envelope calculations indicate that the projected damages are consistent with the magnitude and patterns of historical economic development (see Supplementary Discussion Section  5 ).

Missing impacts and spatial spillovers

Despite assessing several climatic components from which economic impacts have recently been identified 3 , 7 , 8 , this assessment of aggregate climate damages should not be considered comprehensive. Important channels such as impacts from heatwaves 31 , sea-level rise 36 , tropical cyclones 37 and tipping points 38 , 39 , as well as non-market damages such as those to ecosystems 40 and human health 41 , are not considered in these estimates. Sea-level rise is unlikely to be feasibly incorporated into empirical assessments such as this because historical sea-level variability is mostly small. Non-market damages are inherently intractable within our estimates of impacts on aggregate monetary output and estimates of these impacts could arguably be considered as extra to those identified here. Recent empirical work suggests that accounting for these channels would probably raise estimates of these committed damages, with larger damages continuing to arise in the global south 31 , 36 , 37 , 38 , 39 , 40 , 41 , 42 .

Moreover, our main empirical analysis does not explicitly evaluate the potential for impacts in local regions to produce effects that ‘spill over’ into other regions. Such effects may further mitigate or amplify the impacts we estimate, for example, if companies relocate production from one affected region to another or if impacts propagate along supply chains. The current literature indicates that trade plays a substantial role in propagating spillover effects 43 , 44 , making their assessment at the sub-national level challenging without available data on sub-national trade dependencies. Studies accounting for only spatially adjacent neighbours indicate that negative impacts in one region induce further negative impacts in neighbouring regions 45 , 46 , 47 , 48 , suggesting that our projected damages are probably conservative by excluding these effects. In Supplementary Fig. 14 , we assess spillovers from neighbouring regions using a spatial-lag model. For simplicity, this analysis excludes temporal lags, focusing only on contemporaneous effects. The results show that accounting for spatial spillovers can amplify the overall magnitude, and also the heterogeneity, of impacts. Consistent with previous literature, this indicates that the overall magnitude (Fig. 1 ) and heterogeneity (Fig. 3 ) of damages that we project in our main specification may be conservative without explicitly accounting for spillovers. We note that further analysis that addresses both spatially and trade-connected spillovers, while also accounting for delayed impacts using temporal lags, would be necessary to adequately address this question fully. These approaches offer fruitful avenues for further research but are beyond the scope of this manuscript, which primarily aims to explore the impacts of different climate conditions and their persistence.

Policy implications

We find that the economic damages resulting from climate change until 2049 are those to which the world economy is already committed and that these greatly outweigh the costs required to mitigate emissions in line with the 2 °C target of the Paris Climate Agreement (Fig. 1 ). This assessment is complementary to formal analyses of the net costs and benefits associated with moving from one emission path to another, which typically find that net benefits of mitigation only emerge in the second half of the century 5 . Our simple comparison of the magnitude of damages and mitigation costs makes clear that this is primarily because damages are indistinguishable across emissions scenarios—that is, committed—until mid-century (Fig. 1 ) and that they are actually already much larger than mitigation costs. For simplicity, and owing to the availability of data, we compare damages to mitigation costs at the global level. Regional estimates of mitigation costs may shed further light on the national incentives for mitigation to which our results already hint, of relevance for international climate policy. Although these damages are committed from a mitigation perspective, adaptation may provide an opportunity to reduce them. Moreover, the strong divergence of damages after mid-century reemphasizes the clear benefits of mitigation from a purely economic perspective, as highlighted in previous studies 1 , 4 , 6 , 24 .

Historical climate data

Historical daily 2-m temperature and precipitation totals (in mm) are obtained for the period 1979–2019 from the W5E5 database. The W5E5 dataset comes from ERA-5, a state-of-the-art reanalysis of historical observations, but has been bias-adjusted by applying version 2.0 of the WATCH Forcing Data to ERA-5 reanalysis data and precipitation data from version 2.3 of the Global Precipitation Climatology Project to better reflect ground-based measurements 49 , 50 , 51 . We obtain these data on a 0.5° × 0.5° grid from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database. Notably, these historical data have been used to bias-adjust future climate projections from CMIP-6 (see the following section), ensuring consistency between the distribution of historical daily weather on which our empirical models were estimated and the climate projections used to estimate future damages. These data are publicly available from the ISIMIP database. See refs.  7 , 8 for robustness tests of the empirical models to the choice of climate data reanalysis products.

Future climate data

Daily 2-m temperature and precipitation totals (in mm) are taken from 21 climate models participating in CMIP-6 under a high (RCP8.5) and a low (RCP2.6) greenhouse gas emission scenario from 2015 to 2100. The data have been bias-adjusted and statistically downscaled to a common half-degree grid to reflect the historical distribution of daily temperature and precipitation of the W5E5 dataset using the trend-preserving method developed by the ISIMIP 50 , 52 . As such, the climate model data reproduce observed climatological patterns exceptionally well (Supplementary Table 5 ). Gridded data are publicly available from the ISIMIP database.

Historical economic data

Historical economic data come from the DOSE database of sub-national economic output 53 . We use a recent revision to the DOSE dataset that provides data across 83 countries, 1,660 sub-national regions with varying temporal coverage from 1960 to 2019. Sub-national units constitute the first administrative division below national, for example, states for the USA and provinces for China. Data come from measures of gross regional product per capita (GRPpc) or income per capita in local currencies, reflecting the values reported in national statistical agencies, yearbooks and, in some cases, academic literature. We follow previous literature 3 , 7 , 8 , 54 and assess real sub-national output per capita by first converting values from local currencies to US dollars to account for diverging national inflationary tendencies and then account for US inflation using a US deflator. Alternatively, one might first account for national inflation and then convert between currencies. Supplementary Fig. 12 demonstrates that our conclusions are consistent when accounting for price changes in the reversed order, although the magnitude of estimated damages varies. See the documentation of the DOSE dataset for further discussion of these choices. Conversions between currencies are conducted using exchange rates from the FRED database of the Federal Reserve Bank of St. Louis 55 and the national deflators from the World Bank 56 .

Future socio-economic data

Baseline gridded gross domestic product (GDP) and population data for the period 2015–2100 are taken from the middle-of-the-road scenario SSP2 (ref.  15 ). Population data have been downscaled to a half-degree grid by the ISIMIP following the methodologies of refs.  57 , 58 , which we then aggregate to the sub-national level of our economic data using the spatial aggregation procedure described below. Because current methodologies for downscaling the GDP of the SSPs use downscaled population to do so, per-capita estimates of GDP with a realistic distribution at the sub-national level are not readily available for the SSPs. We therefore use national-level GDP per capita (GDPpc) projections for all sub-national regions of a given country, assuming homogeneity within countries in terms of baseline GDPpc. Here we use projections that have been updated to account for the impact of the COVID-19 pandemic on the trajectory of future income, while remaining consistent with the long-term development of the SSPs 59 . The choice of baseline SSP alters the magnitude of projected climate damages in monetary terms, but when assessed in terms of percentage change from the baseline, the choice of socio-economic scenario is inconsequential. Gridded SSP population data and national-level GDPpc data are publicly available from the ISIMIP database. Sub-national estimates as used in this study are available in the code and data replication files.

Climate variables

Following recent literature 3 , 7 , 8 , we calculate an array of climate variables for which substantial impacts on macroeconomic output have been identified empirically, supported by further evidence at the micro level for plausible underlying mechanisms. See refs.  7 , 8 for an extensive motivation for the use of these particular climate variables and for detailed empirical tests on the nature and robustness of their effects on economic output. To summarize, these studies have found evidence for independent impacts on economic growth rates from annual average temperature, daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall. Assessments of daily temperature variability were motivated by evidence of impacts on agricultural output and human health, as well as macroeconomic literature on the impacts of volatility on growth when manifest in different dimensions, such as government spending, exchange rates and even output itself 7 . Assessments of precipitation impacts were motivated by evidence of impacts on agricultural productivity, metropolitan labour outcomes and conflict, as well as damages caused by flash flooding 8 . See Extended Data Table 1 for detailed references to empirical studies of these physical mechanisms. Marked impacts of daily temperature variability, total annual precipitation, the number of wet days and extreme daily rainfall on macroeconomic output were identified robustly across different climate datasets, spatial aggregation schemes, specifications of regional time trends and error-clustering approaches. They were also found to be robust to the consideration of temperature extremes 7 , 8 . Furthermore, these climate variables were identified as having independent effects on economic output 7 , 8 , which we further explain here using Monte Carlo simulations to demonstrate the robustness of the results to concerns of imperfect multicollinearity between climate variables (Supplementary Methods Section  2 ), as well as by using information criteria (Supplementary Table 1 ) to demonstrate that including several lagged climate variables provides a preferable trade-off between optimally describing the data and limiting the possibility of overfitting.

We calculate these variables from the distribution of daily, d , temperature, T x , d , and precipitation, P x , d , at the grid-cell, x , level for both the historical and future climate data. As well as annual mean temperature, \({\bar{T}}_{x,y}\) , and annual total precipitation, P x , y , we calculate annual, y , measures of daily temperature variability, \({\widetilde{T}}_{x,y}\) :

the number of wet days, Pwd x , y :

and extreme daily rainfall:

in which T x , d , m , y is the grid-cell-specific daily temperature in month m and year y , \({\bar{T}}_{x,m,{y}}\) is the year and grid-cell-specific monthly, m , mean temperature, D m and D y the number of days in a given month m or year y , respectively, H the Heaviside step function, 1 mm the threshold used to define wet days and P 99.9 x is the 99.9th percentile of historical (1979–2019) daily precipitation at the grid-cell level. Units of the climate measures are degrees Celsius for annual mean temperature and daily temperature variability, millimetres for total annual precipitation and extreme daily precipitation, and simply the number of days for the annual number of wet days.

We also calculated weighted standard deviations of monthly rainfall totals as also used in ref.  8 but do not include them in our projections as we find that, when accounting for delayed effects, their effect becomes statistically indistinct and is better captured by changes in total annual rainfall.

Spatial aggregation

We aggregate grid-cell-level historical and future climate measures, as well as grid-cell-level future GDPpc and population, to the level of the first administrative unit below national level of the GADM database, using an area-weighting algorithm that estimates the portion of each grid cell falling within an administrative boundary. We use this as our baseline specification following previous findings that the effect of area or population weighting at the sub-national level is negligible 7 , 8 .

Empirical model specification: fixed-effects distributed lag models

Following a wide range of climate econometric literature 16 , 60 , we use panel regression models with a selection of fixed effects and time trends to isolate plausibly exogenous variation with which to maximize confidence in a causal interpretation of the effects of climate on economic growth rates. The use of region fixed effects, μ r , accounts for unobserved time-invariant differences between regions, such as prevailing climatic norms and growth rates owing to historical and geopolitical factors. The use of yearly fixed effects, η y , accounts for regionally invariant annual shocks to the global climate or economy such as the El Niño–Southern Oscillation or global recessions. In our baseline specification, we also include region-specific linear time trends, k r y , to exclude the possibility of spurious correlations resulting from common slow-moving trends in climate and growth.

The persistence of climate impacts on economic growth rates is a key determinant of the long-term magnitude of damages. Methods for inferring the extent of persistence in impacts on growth rates have typically used lagged climate variables to evaluate the presence of delayed effects or catch-up dynamics 2 , 18 . For example, consider starting from a model in which a climate condition, C r , y , (for example, annual mean temperature) affects the growth rate, Δlgrp r , y (the first difference of the logarithm of gross regional product) of region r in year y :

which we refer to as a ‘pure growth effects’ model in the main text. Typically, further lags are included,

and the cumulative effect of all lagged terms is evaluated to assess the extent to which climate impacts on growth rates persist. Following ref.  18 , in the case that,

the implication is that impacts on the growth rate persist up to NL years after the initial shock (possibly to a weaker or a stronger extent), whereas if

then the initial impact on the growth rate is recovered after NL years and the effect is only one on the level of output. However, we note that such approaches are limited by the fact that, when including an insufficient number of lags to detect a recovery of the growth rates, one may find equation ( 6 ) to be satisfied and incorrectly assume that a change in climatic conditions affects the growth rate indefinitely. In practice, given a limited record of historical data, including too few lags to confidently conclude in an infinitely persistent impact on the growth rate is likely, particularly over the long timescales over which future climate damages are often projected 2 , 24 . To avoid this issue, we instead begin our analysis with a model for which the level of output, lgrp r , y , depends on the level of a climate variable, C r , y :

Given the non-stationarity of the level of output, we follow the literature 19 and estimate such an equation in first-differenced form as,

which we refer to as a model of ‘pure level effects’ in the main text. This model constitutes a baseline specification in which a permanent change in the climate variable produces an instantaneous impact on the growth rate and a permanent effect only on the level of output. By including lagged variables in this specification,

we are able to test whether the impacts on the growth rate persist any further than instantaneously by evaluating whether α L  > 0 are statistically significantly different from zero. Even though this framework is also limited by the possibility of including too few lags, the choice of a baseline model specification in which impacts on the growth rate do not persist means that, in the case of including too few lags, the framework reverts to the baseline specification of level effects. As such, this framework is conservative with respect to the persistence of impacts and the magnitude of future damages. It naturally avoids assumptions of infinite persistence and we are able to interpret any persistence that we identify with equation ( 9 ) as a lower bound on the extent of climate impact persistence on growth rates. See the main text for further discussion of this specification choice, in particular about its conservative nature compared with previous literature estimates, such as refs.  2 , 18 .

We allow the response to climatic changes to vary across regions, using interactions of the climate variables with historical average (1979–2019) climatic conditions reflecting heterogenous effects identified in previous work 7 , 8 . Following this previous work, the moderating variables of these interaction terms constitute the historical average of either the variable itself or of the seasonal temperature difference, \({\hat{T}}_{r}\) , or annual mean temperature, \({\bar{T}}_{r}\) , in the case of daily temperature variability 7 and extreme daily rainfall, respectively 8 .

The resulting regression equation with N and M lagged variables, respectively, reads:

in which Δlgrp r , y is the annual, regional GRPpc growth rate, measured as the first difference of the logarithm of real GRPpc, following previous work 2 , 3 , 7 , 8 , 18 , 19 . Fixed-effects regressions were run using the fixest package in R (ref.  61 ).

Estimates of the coefficients of interest α i , L are shown in Extended Data Fig. 1 for N  =  M  = 10 lags and for our preferred choice of the number of lags in Supplementary Figs. 1 – 3 . In Extended Data Fig. 1 , errors are shown clustered at the regional level, but for the construction of damage projections, we block-bootstrap the regressions by region 1,000 times to provide a range of parameter estimates with which to sample the projection uncertainty (following refs.  2 , 31 ).

Spatial-lag model

In Supplementary Fig. 14 , we present the results from a spatial-lag model that explores the potential for climate impacts to ‘spill over’ into spatially neighbouring regions. We measure the distance between centroids of each pair of sub-national regions and construct spatial lags that take the average of the first-differenced climate variables and their interaction terms over neighbouring regions that are at distances of 0–500, 500–1,000, 1,000–1,500 and 1,500–2000 km (spatial lags, ‘SL’, 1 to 4). For simplicity, we then assess a spatial-lag model without temporal lags to assess spatial spillovers of contemporaneous climate impacts. This model takes the form:

in which SL indicates the spatial lag of each climate variable and interaction term. In Supplementary Fig. 14 , we plot the cumulative marginal effect of each climate variable at different baseline climate conditions by summing the coefficients for each climate variable and interaction term, for example, for average temperature impacts as:

These cumulative marginal effects can be regarded as the overall spatially dependent impact to an individual region given a one-unit shock to a climate variable in that region and all neighbouring regions at a given value of the moderating variable of the interaction term.

Constructing projections of economic damage from future climate change

We construct projections of future climate damages by applying the coefficients estimated in equation ( 10 ) and shown in Supplementary Tables 2 – 4 (when including only lags with statistically significant effects in specifications that limit overfitting; see Supplementary Methods Section  1 ) to projections of future climate change from the CMIP-6 models. Year-on-year changes in each primary climate variable of interest are calculated to reflect the year-to-year variations used in the empirical models. 30-year moving averages of the moderating variables of the interaction terms are calculated to reflect the long-term average of climatic conditions that were used for the moderating variables in the empirical models. By using moving averages in the projections, we account for the changing vulnerability to climate shocks based on the evolving long-term conditions (Supplementary Figs. 10 and 11 show that the results are robust to the precise choice of the window of this moving average). Although these climate variables are not differenced, the fact that the bias-adjusted climate models reproduce observed climatological patterns across regions for these moderating variables very accurately (Supplementary Table 6 ) with limited spread across models (<3%) precludes the possibility that any considerable bias or uncertainty is introduced by this methodological choice. However, we impose caps on these moderating variables at the 95th percentile at which they were observed in the historical data to prevent extrapolation of the marginal effects outside the range in which the regressions were estimated. This is a conservative choice that limits the magnitude of our damage projections.

Time series of primary climate variables and moderating climate variables are then combined with estimates of the empirical model parameters to evaluate the regression coefficients in equation ( 10 ), producing a time series of annual GRPpc growth-rate reductions for a given emission scenario, climate model and set of empirical model parameters. The resulting time series of growth-rate impacts reflects those occurring owing to future climate change. By contrast, a future scenario with no climate change would be one in which climate variables do not change (other than with random year-to-year fluctuations) and hence the time-averaged evaluation of equation ( 10 ) would be zero. Our approach therefore implicitly compares the future climate-change scenario to this no-climate-change baseline scenario.

The time series of growth-rate impacts owing to future climate change in region r and year y , δ r , y , are then added to the future baseline growth rates, π r , y (in log-diff form), obtained from the SSP2 scenario to yield trajectories of damaged GRPpc growth rates, ρ r , y . These trajectories are aggregated over time to estimate the future trajectory of GRPpc with future climate impacts:

in which GRPpc r , y =2020 is the initial log level of GRPpc. We begin damage estimates in 2020 to reflect the damages occurring since the end of the period for which we estimate the empirical models (1979–2019) and to match the timing of mitigation-cost estimates from most IAMs (see below).

For each emission scenario, this procedure is repeated 1,000 times while randomly sampling from the selection of climate models, the selection of empirical models with different numbers of lags (shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) and bootstrapped estimates of the regression parameters. The result is an ensemble of future GRPpc trajectories that reflect uncertainty from both physical climate change and the structural and sampling uncertainty of the empirical models.

Estimates of mitigation costs

We obtain IPCC estimates of the aggregate costs of emission mitigation from the AR6 Scenario Explorer and Database hosted by IIASA 23 . Specifically, we search the AR6 Scenarios Database World v1.1 for IAMs that provided estimates of global GDP and population under both a SSP2 baseline and a SSP2-RCP2.6 scenario to maintain consistency with the socio-economic and emission scenarios of the climate damage projections. We find five IAMs that provide data for these scenarios, namely, MESSAGE-GLOBIOM 1.0, REMIND-MAgPIE 1.5, AIM/GCE 2.0, GCAM 4.2 and WITCH-GLOBIOM 3.1. Of these five IAMs, we use the results only from the first three that passed the IPCC vetting procedure for reproducing historical emission and climate trajectories. We then estimate global mitigation costs as the percentage difference in global per capita GDP between the SSP2 baseline and the SSP2-RCP2.6 emission scenario. In the case of one of these IAMs, estimates of mitigation costs begin in 2020, whereas in the case of two others, mitigation costs begin in 2010. The mitigation cost estimates before 2020 in these two IAMs are mostly negligible, and our choice to begin comparison with damage estimates in 2020 is conservative with respect to the relative weight of climate damages compared with mitigation costs for these two IAMs.

Data availability

Data on economic production and ERA-5 climate data are publicly available at https://doi.org/10.5281/zenodo.4681306 (ref. 62 ) and https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , respectively. Data on mitigation costs are publicly available at https://data.ene.iiasa.ac.at/ar6/#/downloads . Processed climate and economic data, as well as all other necessary data for reproduction of the results, are available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

Code availability

All code necessary for reproduction of the results is available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

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Acknowledgements

We gratefully acknowledge financing from the Volkswagen Foundation and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the Government of the Federal Republic of Germany and Federal Ministry for Economic Cooperation and Development (BMZ).

Open access funding provided by Potsdam-Institut für Klimafolgenforschung (PIK) e.V.

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Maximilian Kotz, Anders Levermann & Leonie Wenz

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All authors contributed to the design of the analysis. M.K. conducted the analysis and produced the figures. All authors contributed to the interpretation and presentation of the results. M.K. and L.W. wrote the manuscript.

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Extended data figures and tables

Extended data fig. 1 constraining the persistence of historical climate impacts on economic growth rates..

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature ( a ), daily temperature variability ( b ), total annual precipitation ( c ), the number of wet days ( d ) and extreme daily precipitation ( e ) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a – e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R 2 , Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2 . The resulting models without later lags are shown in Supplementary Figs. 1 – 3 .

Extended Data Fig. 2 Incremental lag-selection procedure using information criteria and within-region R 2 .

Starting from a panel-based fixed-effects distributed lag model estimating the effects of climate on economic growth using the real historical data (as in equation ( 4 )) with ten lags for all climate variables (as shown in Extended Data Fig. 1 ), lags are incrementally removed for one climate variable at a time. The resulting Bayesian and Akaike information criteria are shown in a – e and f – j , respectively, and the within-region R 2 and number of observations in k – o and p – t , respectively. Different rows show the results when removing lags from different climate variables, ordered from top to bottom as annual mean temperature, daily temperature variability, total annual precipitation, the number of wet days and extreme annual precipitation. Information criteria show minima at approximately four lags for precipitation variables and ten to eight for temperature variables, indicating that including these numbers of lags does not lead to overfitting. See Supplementary Table 1 for an assessment using information criteria to determine whether including further climate variables causes overfitting.

Extended Data Fig. 3 Damages in our preferred specification that provides a robust lower bound on the persistence of climate impacts on economic growth versus damages in specifications of pure growth or pure level effects.

Estimates of future damages as shown in Fig. 1 but under the emission scenario RCP8.5 for three separate empirical specifications: in orange our preferred specification, which provides an empirical lower bound on the persistence of climate impacts on economic growth rates while avoiding assumptions of infinite persistence (see main text for further discussion); in purple a specification of ‘pure growth effects’ in which the first difference of climate variables is not taken and no lagged climate variables are included (the baseline specification of ref.  2 ); and in pink a specification of ‘pure level effects’ in which the first difference of climate variables is taken but no lagged terms are included.

Extended Data Fig. 4 Climate changes in different variables as a function of historical interannual variability.

Changes in each climate variable of interest from 1979–2019 to 2035–2065 under the high-emission scenario SSP5-RCP8.5, expressed as a percentage of the historical variability of each measure. Historical variability is estimated as the standard deviation of each detrended climate variable over the period 1979–2019 during which the empirical models were identified (detrending is appropriate because of the inclusion of region-specific linear time trends in the empirical models). See Supplementary Fig. 13 for changes expressed in standard units. Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Extended Data Fig. 5 Contribution of different climate variables to overall committed damages.

a , Climate damages in 2049 when using empirical models that account for all climate variables, changes in annual mean temperature only or changes in both annual mean temperature and one other climate variable (daily temperature variability, total annual precipitation, the number of wet days and extreme daily precipitation, respectively). b , The cumulative marginal effects of an increase in annual mean temperature of 1 °C, at different baseline temperatures, estimated from empirical models including all climate variables or annual mean temperature only. Estimates and uncertainty bars represent the median and 95% confidence intervals obtained from 1,000 block-bootstrap resamples from each of three different empirical models using eight, nine or ten lags of temperature terms.

Extended Data Fig. 6 The difference in committed damages between the upper and lower quartiles of countries when ranked by GDP and cumulative historical emissions.

Quartiles are defined using a population weighting, as are the average committed damages across each quartile group. The violin plots indicate the distribution of differences between quartiles across the two extreme emission scenarios (RCP2.6 and RCP8.5) and the uncertainty sampling procedure outlined in Methods , which accounts for uncertainty arising from the choice of lags in the empirical models, uncertainty in the empirical model parameter estimates, as well as the climate model projections. Bars indicate the median, as well as the 10th and 90th percentiles and upper and lower sixths of the distribution reflecting the very likely and likely ranges following the likelihood classification adopted by the IPCC.

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Kotz, M., Levermann, A. & Wenz, L. The economic commitment of climate change. Nature 628 , 551–557 (2024). https://doi.org/10.1038/s41586-024-07219-0

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Received : 25 January 2023

Accepted : 21 February 2024

Published : 17 April 2024

Issue Date : 18 April 2024

DOI : https://doi.org/10.1038/s41586-024-07219-0

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