Deforestation Archives - Zero Carbon Analytics

Congo Basin deforestation threatens regional rainfall and global cocoa supply

November 18, 2025 by Joanne Bentley-McKune

Key points:

The tropical rainforests of the Congo Basin regulate rainfall both locally in Central Africa and across West Africa, but deforestation risks jeopardising this vital water source.
New ZCA analysis finds that deforestation in the Congo Basin could disrupt rainfall and significantly reduce cacao yields, resulting in substantial losses for producers and rising costs for importers.
The West African countries of Ivory Coast, Ghana and Nigeria, along with several Central African nations, account for more than 70% of global cacao production. Ivory Coast, the biggest producer, could see cumulative losses of almost 1.6 million tonnes by 2050.
Falling yields will be increasingly costly for importers as the impacts of deforestation accelerate over time. Deforestation is projected to contribute 11% of the total cocoa price in 2030, rising to 40% by 2050.
In 2050, Europe could end up paying USD 33.8 billion more for the equivalent of its current annual imports due to Congo Basin deforestation. With normal market growth and the price impacts of extreme weather factored in, Europe’s 2050 cocoa imports could total USD 84 billion, nine times the 2025 cost.
EU importers could face cumulative costs of USD 256 billion by 2050, almost double the global chocolate industry’s 2024 market value of USD 130 billion.
The Netherlands, Belgium and Germany – the biggest EU importers of Ivory Coast cocoa – could pay USD 13.1 billion, USD 6 billion and USD 4.4 billion more in 2050 for current shipment volumes, respectively, due to deforestation price impacts.
Our analysis found a critical window for intervention, as impacts remain manageable through the 2030s but accelerate dramatically after 2040.
Funding forest conservation in the Basin will be cheaper for the EU than the cost of inaction. EU importers could benefit from USD 1.8 to USD 6 in avoided costs for every dollar invested, depending on the conservation approach.
All conservation scenarios analysed showed promising returns, even at a 50% success rate, with community-led restoration showing the biggest benefits.

The Congo Basin’s rainforests drive regional rainfall

Rainforests are crucial for sustaining life on Earth, playing a vital role in carbon sequestration and hosting exceptional biodiversity. But, forests have an even more profound importance for our climate than carbon storage – they regulate the Earth’s temperature and freshwater flows.

Plants recycle 80–90% of rainfall back into the air in a vital feedback loop that sustains the global water cycle and cools the planet. Forests generate water in a process called evapotranspiration: Trees draw up groundwater through their roots and release it from their leaves, returning water to the atmosphere where it turns into clouds and falls as rain, creating a natural cooling system. In tropical areas, this recycling is so effective that air moving over forests produces at least twice as much rainfall as air moving over non-forested land.

The moisture forests release creates rainfall both locally and further away. A well-known example is the Amazon’s ‘flying rivers’, massive flows of water vapour generated by trees and carried by atmospheric currents, which deliver rainfall across Latin America up to thousands of kilometres away.

This type of long-distance climate link is called a teleconnection. In some parts of the world, losing a forest-rainfall teleconnection may present a “more imminent threat even than global warming”.

A less-studied but equally vital teleconnection exists between the Congo Basin in Central Africa, which contains the world’s second-largest tropical rainforest after the Amazon, and West Africa. The Congo Basin’s tropical rainforests generate up to 83% of local rainfall – more than the Amazon – keeping the climate humid and fuelling ongoing rainfall. This moisture does not just sustain the Congo Basin, as seasonal winds carry it hundreds of kilometres westward to deliver almost one-fifth of rainfall in West Africa.¹

Deforestation disrupts this natural system

Deforestation disrupts the natural process of water recycling, as cleared forest can no longer pump moisture into the atmosphere. In the Congo Basin, this could result in rainfall reductions of up to 40%. The high proportion of local rainfall controlled by the rainforest means that the Basin could be the region in the world where deforestation will have the biggest impact on rainfall.

Forest loss also disrupts the natural cooling system. Without the cooling effect of evaporation, the solar radiation that would normally drive evapotranspiration creates hot, low-pressure zones which alter regional wind patterns. These interact with West Africa’s monsoon winds, which bring the region’s crucial rainy seasons, in a climate teleconnection, causing the monsoon rain band to shift inland during the Northern Hemisphere summer and reducing rainfall along the West African Guinea coast.² Climate models show the disruption of this teleconnection could decrease rainfall by up to 20% along the Guinea coast during the rainy season.³

Deforestation in the Congo Basin, driven by small-scale agriculture and settlements, is a growing concern. If current rates of forest loss and degradation continue, 27% of the forest could be destroyed by 2050,⁴ directly threatening local rainfall and the moisture transport systems that millions across Africa rely on for water and agriculture. The destruction places farmers’ livelihoods and commodity supply chains at risk, making forest conservation in the Congo Basin a critical environmental security issue.

Congo basin deforestation puts African cocoa production at risk

One commodity at risk from the reduced rainfall is cocoa, produced from the seeds (cocoa beans) of the cacao plant, Theobroma cacao. Three out of four cocoa beans come from Africa, with the West African countries of Ivory Coast, Ghana and Nigeria, along with several Central African nations in the Congo Basin, accounting for more than 70% of global cocoa production.

Cacao can only thrive in a narrow band around the equator, called the ‘cocoa belt’, as it requires specific temperature and moisture conditions to grow. It is particularly sensitive to drought because it evolved in the humid Amazon Basin and has not adapted to the water stress from West Africa’s prolonged dry seasons. As a result, global cocoa supplies are particularly vulnerable to climate and land-use changes in the region.

Cacao cultivation in Africa is mostly low-tech, performed by smallholder farmers and relies almost entirely on rainfall, rather than irrigation. This rain-fed system makes crops highly dependent on reliable rainfall – a critical vulnerability given the crop’s low drought tolerance. Seasonal dry spells can severely reduce yields, and prolonged droughts can devastate entire harvests.⁵

Scientists believe that once forest loss exceeds a critical threshold, an irreversible ecological shift or ‘tipping point’ could be reached and the forest’s rain pump mechanism lost. Once gone, the mechanism cannot be fully restored, leading to persistently drier conditions locally and across West Africa, with cascading effects for supply chains. The threshold could be as low as 30% forest loss, or even lower, and Central Africa is estimated to have already lost 9% of its forests since 2000.

Impacts will be felt throughout the cocoa supply chain

Cocoa is not an easy raw material to replace in the confectionery industry, given its distinctive flavour and properties. As a result, prices tend to rise sharply when global cocoa supplies are low and buyers compete for limited stocks. The supply is highly inelastic, meaning production cannot be easily ramped up in response to a crisis, and even modest supply shocks trigger dramatic price swings.

For example, prices rose more than 400% in 2024 following crop failures in West Africa due to unseasonal wet weather followed by drought during the rainy season, driven by climate change.⁶ Swiss chocolate maker Barry Callebaut dropped its annual sales forecasts for 2025 due to “unprecedented volatility” in cocoa prices, resulting in a 20% drop in share prices.

Despite Africa’s dominance in cocoa production, the continent only reaps a small fraction of the value of the global cocoa industry. Farmers earn less than 7% of the final price when cocoa is sold as a chocolate, one of the smallest shares in the supply chain.⁷ Europe, the world’s largest importer of cocoa beans, captures the most profits in the higher-value stages of processing and manufacturing. The Netherlands and Belgium, for example, import cocoa beans, process them, then export cocoa products at a premium.

New ZCA analysis shows how deforestation could reduce production and destabilise global cocoa markets

New analysis by Zero Carbon Analytics shows how deforestation in the Congo Basin could disrupt cocoa production in the nine countries that make up three-quarters of global supply: Cameroon, the Central African Republic, Equatorial Guinea, the Democratic Republic of the Congo, and the Republic of Congo in Central Africa, and the West African countries of Ivory Coast, Ghana, Gabon and Nigeria.

Using deforestation trajectories and regional climate dynamics,⁸ research on how cocoa plants respond to drought,⁹ and the behaviour of cocoa in commodity markets,¹⁰ we projected how declining rainfall could reduce production and destabilise global cocoa trade.

African cocoa producers could face substantial yield losses due to rainfall decline caused by deforestation

Our analysis showed that deforestation-induced rainfall decline is projected to reduce cacao yields in all nine assessed countries, with cumulative losses totalling 256,000 tonnes across the nine countries by 2030, and 3.06 million tonnes by 2050 (Figure 1).

Figure 1

Major cocoa producers could face substantial losses, which could destabilise local economies. Ivory Coast, the biggest producer, could see cumulative losses of almost 1.6 million tonnes by 2050, around 80% of its current annual production volume. Cocoa is the biggest export commodity in Ivory Coast, making up roughly one-third of exports.

Losses could total 866,000 tonnes in Ghana, 377,000 tonnes in Nigeria and 205,000 tonnes in Cameroon by 2050. Cocoa accounts for more than half of agricultural exports in all three countries.

Deforestation will have an increasingly big impact on cocoa prices

Our model projected how the price of cocoa would change until 2050, and how much deforestation would impact future prices. We looked at three components that drive cocoa price and compared their impacts over time. The components were:

Our projections showed that deforestation will have an increasingly big impact on cocoa prices (Figure 2). Until 2030, normal market growth is expected to account for the majority of cocoa price (>80%), with climate risk and deforestation having a relatively small impact. In 2030, we project a cocoa price of USD 11.6 per kilogram, lower than the peak price of almost USD 13 per kilogram seen during the 2024 supply crisis.

Figure 2

By 2050, Congo Basin deforestation will persistently reduce rainfall and cocoa production, resulting in shortages and triggering exponential price increases.¹⁵ Our projections show a cocoa price of USD 68.1 per kilogram in 2050 – almost six times the 2030 price.¹⁶ By this time, normal market growth will account for just 37.3% of the price, the climate premium will contribute a modest 22.5%, and deforestation will have the biggest impact, driving 40.2% of the price.

Without deforestation, normal market growth plus the climate risk premium would result in a 2050 price of USD 41 per kilogram, just over three times the peak price during the 2024 supply crisis. Deforestation risk escalates this price by nearly two-thirds.

Production losses would cost major EU cocoa importers

The rising price of cocoa could have significant cost implications for importers, particularly in Europe. Using Trase Earth’s data on cocoa exported from the Ivory Coast,¹⁷ the region’s biggest cocoa exporter, we estimated what increased cocoa prices could mean for the 15 European countries that account for the majority of imports: The Netherlands, Germany, Belgium, France, the United Kingdom, Italy, Spain, Estonia, Bulgaria, Poland, Croatia, Russia, Portugal, Greece and Switzerland.¹⁸ ¹⁹

Assuming shipment volumes remain stable at 2022 levels, deforestation could result in these countries together paying USD 33.8 billion more for cocoa imports in 2050 than in 2025 (Figure 3). Including baseline market growth and the climate premium, the total costs exceed USD 84 billion – nine times the 2025 cost. Without the impacts of deforestation, the 2050 costs drop to USD 50 billion, or 5.5 times the 2025 value.

These importers could face cumulative additional costs of USD 256 billion by 2050, if no conservation action is taken to protect or restore forests – almost double the entire global chocolate industry’s 2024 market value of USD 130 billion.

Figure 3

For the Netherlands, the biggest importer of Ivory Coast cocoa, rainfall decline due to deforestation could mean shipments cost an additional USD 1.8 billion in 2035, USD 4 billion in 2040 and USD 13.1 billion in 2050, compared to 2025. Combined with normal market growth and climate disruption, this results in a 2050 cost for the same volumes of almost USD 33 billion (Figure 4).

Belgium and Germany, the next biggest importers, could see deforestation raise the cost of shipments by USD 6 billion and USD 4.4 billion in 2050, respectively, bringing overall costs to between USD 15 billion and USD 11 billion.

Figure 4

There is a critical window for intervention

While impacts remain manageable through the early 2030s, they accelerate dramatically after 2040, transforming from millions to billions in annual costs. This trajectory suggests that without immediate action to halt deforestation, annual import costs could exceed what major buyers can absorb, undermining the viability of the Ivory Coast’s cocoa sector and passing costs on to consumers.

New EU regulations, expected by 2026, will require cocoa imports to be deforestation-free. In response, the European Investment Bank (EIB) issued a EUR 100 million loan to the Ivorian national investment bank (Banque Nationale d’Investissement, or BNI) to support sustainable cocoa production, youth and female employment, and traceable, certified supply chains in Ivory Coast.

In addition to promoting sustainable cocoa production, Ivory Coast and the EU are collaborating on large-scale reforestation and forest protection initiatives aimed at reversing decades of environmental degradation. These efforts are supported by an additional EUR 150 million investment from the EIB, which is helping to finance the country’s national forest preservation, rehabilitation, and expansion strategy.

Analysis shows that Congo Basin conservation is cheaper for the EU than the cost of inaction

Comparing Ivory Coast cocoa trade data with the future cost of deforestation reveals a clear economic case for importers to invest in forest conservation in the Congo Basin. The projected cost impacts of deforestation for all EU countries up to 2050 are enough to fund comprehensive conservation for multiple decades, preventing damage and supporting sustainable development across Central Africa. The EU is the largest importer of Ivory Coast cocoa, importing 1.16 million tons across 12 EU countries in 2022.

We compared the cumulative costs the EU could face by 2050,²⁰ against recent investments made in conservation interventions in the region²¹ and found that funding actions to prevent deforestation in the Congo Basin²² could be economically beneficial, offering viable economic returns for sustainable finance.

We compared six conservation scenarios, each involving different shares of three intervention types:

Farmer-Managed Natural Regeneration (FMNR), a low-cost land restoration technique focused on growing trees and shrubs, including for food and timber
Subsistence agroforestry, where trees are integrated into agricultural land to bolster food security
Cocoa-banana agroforestry, or the co-growing of cocoa and banana trees.

Our conservation scenarios ranged from a low-cost community approach weighted towards FMNR, to a food security-focused scenario that is predominantly subsistence-based, and scenarios implementing different levels of agroforestry (Figures 5a and 5b).

All of the intervention scenarios provide clear benefit-cost ratios by 2050,²³ when they are anywhere between 50% to 100% successful at preventing deforestation-induced price increases.²⁴ Investments in conservation in the Congo Basin are robust, meaning they maintain positive returns even when projects are only 50% successful.²⁵

Figures 5a and 5b

The scenario that emphasises community-led restoration, which focuses on FMNR, showed the highest benefits. Returns range from 3:1 at 50% success to 6:1 at 100% success, meaning the EU could benefit from USD 3 to USD 6 in avoided costs by 2050 for every dollar it invests in community-led restoration.

Agroforestry-focused strategies showed slightly lower cost-benefit ratios, but still promise returns and may prove more sustainable in the long term, as they generate direct income streams that provide farmers with ongoing economic incentives to maintain projects, and give access to food and fodder.

The choice between strategies should ultimately depend on project-specific objectives, whether that be immediate cost-effectiveness, long-term sustainability, community ownership, or economic resilience.

1
West African forests themselves have an important teleconnection: they provide up to 30-40% of the total annual rainfall in the Ethiopian Highlands.
2
The coastal tropical region of West Africa that lies along the Gulf of Guinea.
3
This effect is also compounded by extensive local deforestation – for cocoa production as well as other commodities – within West Africa itself, which is believed to reduce local precipitation in adjacent forests by up to 50%. Local deforestation is also increasing the occurrence of extreme climate events in the region.
4
Compared to 2020.
5
Poor adaptation to local conditions also makes cacao trees susceptible to disease – a major contributor to reduced harvests in recent years.
6
Climate change is increasing the frequency of flooding and heatwaves in West Africa, and is anticipated to increase the severity of dry spells, reduce rainfall, and shift the timing of wet and dry seasons for parts of the West African cocoa belt.
7
Many farmers live in extreme poverty, often earning less than USD 1 a day, yet are reliant on this source of income.
8
Smith et al. (2023) projected that Congo Basin forest loss could reduce rainfall in the basin by 8-10% on average by 2100. We extracted country-specific forest loss percentages for Cameroon, the Central African Republic, the Republic of the Congo, the Democratic Republic of Congo, Equatorial Guinea and Gabon from Figure 4c. To capture how sensitive each region’s rainfall is to forest loss, we used Smith’s country-specific rainfall decreases for 2100 and translated forest loss percentages into rainfall reduction percentages for each country. For Ivory Coast, Ghana and Nigeria, we synthesise evidence from two climate modeling studies: Nogherotto et al. (2013) modeled complete removal of Congo Basin forest and found this reduced monsoon rainfall along the Guinea Coast by up to 20% (see figure 2 in source). Since our analysis uses the partial deforestation trajectory from Smith et al. (2023), we linearly scale Nogherotto’s estimates, acknowledging this assumes a linear relationship that may not hold across all deforestation levels. Duku & Hein (2021) simulated 50% tree cover loss in the Guineo-Congolian region and found rainfall reductions in West Africa of approximately 5-10% (Figure 5, panel a, in source), consistent with our linearly scaled estimate.
9
We drew from controlled field studies of cocoa in West Africa showing that 67% rainfall reduction causes 31% yield loss in cocoa trees, and scaled this to our rainfall reduction trajectory. We used an exponential decay function to capture the non-linear response of plants to water stress, where each additional percentage point of drought inflicts disproportionately more damage.
10
To model cocoa price responses to production scarcity, we implemented an exponential function reflecting commodity market dynamics. We calculated a ‘scarcity multiplier’ as exp(6.5 × production loss share), capped at 4.0× (400% increase), where production loss is derived from deforestation-driven yield declines. The coefficient of 6.5 captures cocoa’s extreme supply inelasticity, with relatively small supply reductions generating outsized price increases (a 10% production loss yields a 1.92× price multiplier, while a 20% loss approaches the 4.0× maximum). The multiplier is applied to baseline price projections of annual growth, a climate risk premium and adjusted for long-run demand elasticity (-0.57).
11
Based on the International Cocoa Organisation (ICCO) historical trends of a 5.1% compound annual growth rate (CAGR) 2000-2020, which excludes the dramatic price spike observed over 2024-2025.
12
Analysis indicates that by 2050, increased drought severity will impact 80% of cocoa production in Ivory Coast and virtually all production in Ghana. Most areas will experience modest increases, but substantial portions will face moderate drought intensification.
13
We included a 2% climate risk premium to capture forward-looking market expectations of climate impacts. Recent research shows that climate risk has significant predictive power for agricultural commodity prices, with investors willing to pay up to 295 basis points annually to access climate risk information. A 2024 study on EU cocoa markets found that extreme drought events alone could increase prices by 110-180% during crisis years by 2050 under climate change scenarios RCP2.6 and RCP8.5, respectively. Again, our climate premium, which compounds to a 209% increase by 2050, is broadly consistent with these estimates. Our climate premium is also consistent with estimates from sovereign bond markets, where countries highly exposed to climate risk face risk premiums of 1.13% to 2.75%, and with growing evidence that physical climate impacts are materially priced into commodity and capital markets. While bond risk premia aren’t directly transferable to commodity pricing, they indicate the scale of climate risk being priced into markets. The NGFS (2024) further notes that investors are now adjusting expected returns across asset classes to account for nature-related physical risks such as deforestation, biodiversity loss and food system disruption.
14
Our deforestation analysis focuses on systematic, gradual climate impacts, meaning it may underestimate costs from acute climate risks, including extreme weather events. The 2024 cocoa crisis, which triggered 400% price increases, shows how acute climate shocks can generate economic impacts far exceeding our model’s projections. Similarly, El Niño-Southern Oscillation (ENSO) events have caused yield losses of up to 89% in major cocoa-producing regions.
15
Our model includes a demand elasticity adjustment that provides some tempering effect as high prices reduce consumption. We use a long-run demand elasticity of –0.57 based on economic research on global cocoa markets. Cocoa’s limited substitutability keeps demand relatively inelastic, meaning price increases largely persist because there is no alternative for buyers to turn to. Our model assumes static production systems, with no adoption of drought-resistant cacao varieties or irrigation.
16
As a robustness check, we tested a Bayesian weighting approach that dynamically adjusts scenario probabilities based on system stress indicators (forest loss rates, rainfall reduction intensity). This approach results in a 2050 cocoa price of USD 81/kg versus USD 68.1/kg in our main model – a difference of 20% – suggesting our central estimates may be conservative. The Bayesian approach helps quantify uncertainty about the severity and timing of climate impacts while confirming our core finding that deforestation-driven climate impacts pose substantial economic risks to cocoa production.
17
We used 2022 export data and assumed static imports from 2022 levels for all years into the future.
18
From the Trase Earth dataset we extracted the trade volume (in tonnes) and multiplied this by our price estimates for different years, broken down into normal market growth, climate premium and deforestation components.
19
Listed in order of export volume from biggest to smallest.
20
All values used in the intervention analysis are present-value adjusted. Present value calculations employed a 3% discount rate over 25 years (2025-2050), with annual additional costs calculated as import volumes (tonnes) × 1000 × deforestation price impact (USD/kg), discounted to 2025 present value using standard financial formulas: PV = 1/(1+r)^n, where r is the discount rate and n is the number of years from the base year. USD 256 billion here, when present-value adjusted, results in a value of USD 146 billion.
21
The interventions include Regreening Africa, which focuses on FMNR in Ghana and Rwanda and has an average implementation cost of USD 115 per household every six years, as well as the Northern Congo Agroforestry Project, which includes cocoa-banana agroforestry at USD 1005 per hectare, and subsistence-type agroforestry at USD 861 per hectare, which are one-off costs.
22
We defined our target intervention area based on the Congo Basin area deforested over 2003-2017. We used the geographic bounds from Smith et al. (2023), which encompass the Congo Basin forests whose loss affects rainfall in cocoa-producing regions and for which we based our climate-economic model on. We extracted grid cells (Smith et al. Figure 1a) with non-negligible tree cover loss (>5%) over the period 2003-2017. This resulted in an intervention area of 427,477 km2 (or 21.7% of the Congo Basin broadleaf evergreen forests). We calculated population sizes by overlaying WorldPop spatial data and extracted the population density (people/km2). Based on this, we calculated an average population density for our intervention area. Surveys report that the average household size in the region is 5 people. Using this together with our people/km2, we were able to estimate how many households are in our intervention area for targeting.
23
Benefit-cost ratios (BCRs) were calculated as present value of avoided EU import costs divided by present value of intervention investments, with economic viability defined as BCR ≥ 1.0.
24
The analysis calculates the potential reduction in deforestation-driven cocoa price increases under varying intervention success rates (50%, 70%, 100%) to determine what portion of those projected price increases can be prevented, while maintaining full program costs regardless of outcomes. For example, a 50% success rate means that interventions successfully prevent 50% of projected deforestation (and therefore 50% of the associated modelled price impacts), but 100% of program costs are still incurred.
25
Our estimates are likely conservative because we have only included Ivory Coast, which accounts for approximately 50% of cocoa production in Africa, meaning the total economic impact of regional deforestation on EU importers could be larger when including other major producers such as Ghana, Nigeria and Cameroon.

Deforestation in Brazil’s Cerrado reduces soy production and threatens supply chains

November 17, 2025 by Joanne Bentley-McKune

Key points

Brazil’s tropical savanna – or Cerrado – has faced extensive clearing of native vegetation in recent decades, largely for soy production. Agricultural expansion leads to drying, which reduces productivity. This drives farmers to clear more land, further accelerating degradation.
Our new analysis found that when farmers clear native vegetation for soy, the climate impacts extend far beyond the cleared plots. These reduce yields at the regional scale and outweigh the gains from new farmland by 3:1. However, individual farmers who clear land still profit from their expansion, revealing a critical challenge for conservation policy.
Based on our calculations, if no land had been cleared for soy in the Cerrado since 2008, the region would have produced an additional USD 9.4 billion of soy – nearly 8% of the region’s soy output between 2013 and 2023.
Even more modest land conservation shows benefits. Avoiding just 10% of Cerrado clearing would have generated almost USD 1.0 billion in additional production. A 25% avoidance would have generated USD 2.35 billion, and a 35% avoidance would have generated USD 3.29 billion.
Importers’ supply chains are heavily exposed to regions damaged by clearing. China faces the biggest absolute threat, sourcing from areas where clearing has destroyed USD 5.0 billion of annual soy production capacity over 2013-2023, followed by Spain, the Netherlands and Germany.
However, Germany’s soy imports are concentrated in actively high-clearing municipalities. Each tonne Germany imports is linked to more local production loss than other buyers. Implementing deforestation-free supply chain measures could protect soy productivity – every million tonnes that Germany shifts toward zero-deforestation suppliers would preserve USD 43 million in regional productivity.
EU supply chains sourcing from recently cleared areas face non-compliance risks under EU regulations prohibiting imports from regions deforested since 2020. France, Romania and Portugal may be particularly exposed.
Brazil – and soy-importing countries – face a critical window for action. We find a threshold below which vegetation protection delivers maximum climate benefits. Nearly every actively-clearing municipality still retains this advantage.

Soy-driven deforestation is drying Brazil’s Cerrado

Brazil’s tropical savannas, locally known as the cerrado, are the country’s second-largest biome after tropical forests. The Cerrado includes grasslands, woodlands and Brazil’s upside-down forest, an extensive underground root system that stores more than five times the carbon found in its above-ground vegetation. This remarkable root network enables plants to survive droughts and fires by accessing deep water sources and nutrients stored below the surface.

In recent decades, the region has faced extensive clearing of native vegetation for agriculture. At least 46% of the Cerrado’s native vegetation has been cleared for pasture or crops. Brazil is the world’s largest producer and exporter of soy, which accounted for 14.5% of total exports between January and September 2025.¹Soy is also the second-largest direct driver of deforestation in Brazil, after cattle ranching.

The Matopiba region, an acronym for the Maranhão, Tocantins, Piauí and Bahia states, is considered the Cerrado’s newest ‘agricultural frontier’. Here, farming is expanding into previously uncultivated land. The soybean area increased by 253% between 2000 and 2014, at the expense of 50% of the region’s native vegetation.

In 2023, deforestation in the Cerrado reached 1.1 million hectares – more than twice that of the Amazon in the same year. Rates have eased more recently, though deforestation continues. Despite the extent of deforestation in the Cerrado, the region has been overlooked in environmental policies.²

Deforestation intensifies drought, which undermines soy production

Locally, clearing land interrupts evapotranspiration, undermining the Cerrado’s natural moisture recycling system and worsening heat stress. At a regional level, replacing native vegetation with cropland significantly alters the climate by disrupting the systems that carry moisture to Brazil and neighbouring countries, known as climate teleconnections (Box 1). As a result, land use change in the Cerrado impacts rainfall across South America.

Average annual evapotranspiration in the Cerrado decreased by approximately 44% from 2006 to 2019, while temperatures increased by around 3.5°C. Less evapotranspiration means the air holds less moisture, leading to fewer clouds and less rain. This, in turn, makes the land dry, causing a positive feedback loop.

The region experienced an unprecedented drought in 2024, which a scientific attribution study has confirmed would have been impossible without human-caused climate change, exacerbated by deforestation.

Box 1: How does deforestation impact rainfall?

As well as supporting biodiversity and sequestering carbon, forests regulate the Earth’s climate by maintaining its temperature and fresh water flows.

Forests move water in a process called evapotranspiration: trees draw up groundwater through their roots and release it through their leaves, returning the water to the atmosphere, where it turns into clouds and falls as rain. This creates a natural cooling system. Plants recycle 80–90% of rainfall back into the air in a feedback loop that sustains the global water cycle and cools the planet.

The water vapour generated by trees is carried by atmospheric currents and creates rainfall both locally and further away. This kind of long-distance climate link is called a teleconnection.

Deforestation disrupts this natural system, as evapotranspiration cannot take place when trees are cleared. Plus, without the cooling effect of evaporation, the solar energy that would normally drive evapotranspiration creates hot, low-pressure zones that alter regional wind patterns. In some parts of the world, losing a forest-rainfall teleconnection may present a “more imminent threat even than global warming”.

The Amazon’s ‘flying rivers’ are a well-known example of a forest-rainfall teleconnection. Less-studied but equally important teleconnections exist in the Congo Basin in Central Africa, which contains the world’s second-largest tropical rainforest, and in Brazil’s Cerrado.

In the Southern Brazilian Amazon – a soy cultivation region bordering the Cerrado – deforestation has been shown to reduce rainfall, shortening the growing season and undermining the region’s soy and beef production, which is largely rain-fed. A 2021 study estimated that if weak deforestation policies continue in the region, soy and beef revenues could fall by an estimated USD 186 billion by 2050. This dwarfs the profits that would be lost by conserving forests under stronger governance – around USD 19.5 billion.

A recent modelling study across five states in the Amazon and Cerrado showed that if deforestation‑induced disruptions to rainfall hadn’t occurred since the early 1980s, soybean yields would have been about 6.6% higher annually between 2011 and 2020.³ This is despite improved agricultural efficiency during that time, emphasising the overwhelming negative effect of altered rainfall on yields.

New analysis shows the impact of Cerrado deforestation on Brazilian agricultural productivity

New Zero Carbon Analytics analysis explored whether the drying caused by clearing land to plant more soy creates hidden productivity losses that counteract the benefits of expansion. We explored this using Trase Earth data on soy production, yield, exports and price from 840 municipalities in the Cerrado between 2013 and 2023, and combined this with rainfall and aridity data.⁴

Trase defines soy deforestation as “the soy area in the target year that overlaps with deforestation… in the five years prior to soy detection.” Given our study period of 2013-2023, this means our deforestation data captures forest loss from 2008 onwards (the five years before our earliest observation year) through 2022.

The Cerrado region would have produced 8% more soy from 2013-2023 without deforestation

Our analysis shows that soy-driven deforestation in the Cerrado is making the region drier.⁵ Greater soybean clearing was found to have dried out the local moisture balance in all municipalities since 2008. Areas with more vegetation loss experienced more arid conditions, confirming scientifically what farmers often observe anecdotally: clearing trees leads to less rainfall and moisture locally.

If no land had been cleared for soy in the Cerrado since 2008, our calculations show that the region would have produced an additional USD 9.4 billion of soy – equivalent to nearly 8% of the region’s soy output over the study period.⁶

We also calculated the amount of soy that would have been produced if 10%, 25%, 35% and 50% less land had been cleared for soy, giving an indication of the production benefits of conserving the Cerrado. Avoiding just 10% of clearing across our study region would have generated an additional USD 938.8 million of soy between 2013 and 2023, implying that nearly USD 1 billion of additional soy could have been produced if modest conservation actions were put in place (Figure 1).

Figure 1

More ambitious conservation scenarios could have resulted in proportionally larger benefits: avoiding 25% of clearing would have preserved USD 2.35 billion in additional agricultural value, while avoiding 35% would have approached USD 3.29 billion.⁷

These targets are realistic. Municipalities in our dataset that saw reduced clearing between 2008 and 2022 cut expansion by 56%, on average. Almost all (91%) of these municipalities maintained or increased production, demonstrating that reducing clearing does not limit output in the vast majority of cases.⁸

Intensifying existing cropland or adopting agroforestry may be better options economically than clearing more land. Better seed, improved management, double-cropping, and integrating trees (e.g. windbreaks, alley cropping) can improve yields and stabilise local moisture.

Losses were twelve times worse in wet years than in dry years

The impacts of clearing vary dramatically with weather conditions.⁹ During wet years with above-normal rainfall, we found that clearing 1,000 hectares for expansion caused regions to lose 14,627 tonnes of soy production. During dry years, the same clearing caused only 1,213 tonnes of lost production – a 12-fold difference.

This pattern is counterintuitive, but might be explained by a critical mechanism: during wet years, when farmers expect higher yields, cleared land cannot retain the extra rainfall that should boost productivity, while forested areas capture and store it.¹⁰ ¹¹

The extreme losses from a single wet year could wipe out multiple years of profits from expansion. These findings also suggest that traditional economic models that use average impacts may severely underestimate the actual financial risks of land clearing.

Models show that individual farmers may see profit from clearing land, but losses multiply at the municipal level

Our analysis revealed a paradox: land clearing for soy is profitable for individual farmers, but economically destructive at the regional level. At the municipal scale, clearing native vegetation created a 3:1 productivity loss between 2013 and 2023 – for every tonne of soy produced on new land, three tonnes were lost from existing fields due to climate spillovers.¹²

Yet, individual farmers still profited because they externalised most spillover costs. Farmers captured all the gains from their cleared land, while losses were distributed across all farms in the municipality, proportional to farm size (see Box 2).¹³ Individual farmers may view land clearing as profitable, yet unknowingly be participating in a system that reduces their long-term economic returns.

Box 2: An individual farmer scenario

Consider a soy farmer who expands their operation from 500 to 600 hectares by clearing 100 hectares of cerrado. From this new land, the farmer expects to produce about 300 additional tonnes of soy annually. If soy is priced at, say, USD 400 a tonne, they would expect to generate USD 120,000 in extra revenue each year.

However, our analysis shows that, on average, clearing 100 hectares reduces total municipal soy production by 837 tonnes annually through climate spillover effects. If the farmer’s 600-hectare operation is part of, say, 10,000 hectares of soy farmland in the municipality, the farmer bears roughly 6% of these regional losses – about 50 tonnes annually on their existing 500 hectares, or USD 20,000 in lost revenue each year.

The farmer gains 300 tonnes and loses 50 tonnes annually on average – a net gain of 250 tonnes.

The extreme risk of wet years

In a single particularly wet year, spillover losses could potentially wipe out multiple years of expected gains. Our analysis reveals that during wet years – when farmers may expect their best profits – the same 100 hectares of clearing costs the municipality 1,452 tonnes in lost production. The farmer’s 6% share of this loss equals 87 tonnes, worth USD 34,800 in a single year. During dry years, losses drop to just 7 tonnes, worth USD 2,700.

The financial reality

Over a decade with an equal amount of wet and dry years, losses would total USD 187,400. These losses would reduce the farmer’s expected returns over the decade by USD 1,012,60, or 16%.

Short-term gains vs. long-term losses are a challenge for conservation policy

Studies of farmer attitudes in the Cerrado state of Tocantins and the Matopiba agricultural frontier found that farmers were sceptical toward zero-deforestation policies, with producers expressing concerns about external interference and questioning the motivations behind conservation. Interviews with soy producers in Matopiba found that their decision-making tended to be economically motivated, clearing land when profitable opportunities arose and in anticipation of future restrictions. This resistance reflects tensions between local autonomy and external regulatory frameworks, as well as legitimate concerns about economic impacts on rural communities.

These studies reveal a challenge for sustainability initiatives, which often struggle to compete with the immediate profit seen from expansion. Farmers resist conservation measures because they view them as costly, yet deforestation ultimately reduces agricultural profitability for the region. Changing perspectives – from seeing conservation as limiting agricultural profit to recognising that it can enhance it – requires evidence that demonstrates the financial benefits of conservation-compatible development and for the evidence to be communicated in a way that speaks to individual farmers’ priorities and experiences.

Strategically intensifying existing farmland using improved technology and management practices offers the potential for better agricultural returns compared to continued expansion. The Amazon Soy Moratorium – an agreement whereby traders avoid purchasing soy from areas deforested after 2008 – demonstrated that soy can expand without driving deforestation and may, in fact, be more profitable in the long term.

Global soy supply chains are found to be heavily exposed to damage from clearing Brazil’s Cerrado

Soy production is heavily concentrated in three regions globally: 40% of soy is from Brazil, 28% is from the US and 12% is from Argentina. This means the global soy trade is tightly interconnected. There is limited flexibility for importers to switch suppliers without displacing other buyers.

Current patterns of soy expansion in the Cerrado are economically unsustainable and undermine the stability of the entire global supply. The world is facing finite agricultural frontiers and accelerating ecosystem damage. Supporting deforestation-free supply chains and investing in forest conservation could safeguard the productive capacity of existing suppliers and ensure long-term, stable soy supplies.

Sourcing from regions that suffered the most production losses shows supply chain vulnerability

China currently buys around three-quarters of Brazil’s soy, making it Brazil’s biggest trade partner for the commodity. The EU is the second-largest export destination, accounting for around 7%. Because most of Brazil’s recent soy expansion has been in the Cerrado, these buyers are highly exposed to clearing-linked risk, particularly for sourcing in the Cerrado’s Matopiba region.

Sourcing from regions where productivity is being undermined by deforestation means greater uncertainty in future soy availability and upward pressure on costs. To compare the risks in each country’s supply chain, we assessed which importing countries were most exposed to hidden productivity losses between 2013 and 2023. We identified the regions each country sources from and calculated the value of the soy that was never produced due to clearing-induced losses in each region (Figure 2).

Figure 2

China has, by far, the highest absolute exposure to clearing-linked production losses, partially because it is the largest importer, followed by Spain, the Netherlands, and Germany. China sources from Cerrado municipalities where land clearing destroyed almost USD 5 billion worth of soy production capacity from 2013 to 2023, equivalent to around half of the total value lost over the period.¹⁴

Without efforts to restore degraded land, this hidden productivity loss is permanent. This figure only reflects clearing during our study period; decades of prior deforestation mean total productivity losses are substantially larger.

Box 3: China’s food supply chain security depends on Brazil’s Cerrado conservation actions

As the top importer of Brazilian soy, China’s supply chain faces mounting risks from continued deforestation in its sourcing regions. China’s supplies are geographically concentrated, amplifying risk. Our analysis showed that 60% of China’s import volume from the Cerrado¹⁵comes from just three states: Mato Grosso (29.7%), Goias (20.1%) and Bahia (10.1%).¹⁶

Brazil’s deforestation protection policies, and how thoroughly they are enforced, will have a big impact on the future exposure of China’s supply chains. To give an idea of the scale of this impact, we modelled three future scenarios for the municipalities China sources from with different deforestation rates, and projected how much production capacity could be destroyed by 2033 (Figure 3):

Recent trend: If the average clearing rate from 2013 to 2022 continues (361.2 kilohectares per year), another USD 3.8 billion in productive capacity will be eliminated in China’s sourcing regions by 2033. This would bring the total productivity loss in the regions since 2013 to USD 8.7 billion.
Historical average: A return to the higher average clearing rates seen from 2008 to 2022 (435 kha/year) would mean additional productivity destruction reaches USD 4.5 billion, totalling USD 9.5 billion.
Policy failure: If conservation policies are weak and deforestation accelerates to rates projected by a recent analysis, at approximately 2.3 times historical rates (1,019 kha/year),¹⁷ China’s sourcing regions could face an additional USD 10.6 billion in productivity destruction, for a total exposure of USD 15.5 billion by 2033.

Figure 3

Changes to trade dynamics have amplified China’s soy supply chain exposure

China’s supply chain exposure has intensified with recent trade dynamics. US-China trade tensions drove Brazilian soy’s share of Chinese imports up to 71% in 2024, while US exports to China fell to zero from May 2025, down from 21% in 2024.¹⁸ ¹⁹Simultaneously, the EU’s new Deforestation Regulation (EUDR) may redirect deforestation-linked soy toward non-EU markets, such as China.

As EU buyers claim deforestation-free supplies, China risks inheriting a portfolio of suppliers from precisely the regions experiencing the highest productivity losses. These losses create supply chain fragility rather than immediate shortages. Degraded landscapes are less resilient to climate shocks, meaning droughts, floods or heatwaves that would be manageable in intact ecosystems can cause significant production disruptions. China’s concentrated dependence on these degraded regions amplifies vulnerability.²⁰

Brazil’s Soy China initiative is an opportunity to secure supply

Brazil and China’s new ‘Soy China’ initiative – a dedicated supply chain meeting Chinese sustainability standards – presents an opportunity to address productivity risks. The framework could allow China to demand deforestation-free sourcing, backed by economic self-interest. Our findings confirm that conservation and soy output are not only compatible but that reducing deforestation is essential for sustaining long-term productivity.²¹

Countries that source soy from high-clearing areas have the most to gain from investing in conservation

Countries sourcing soy from the Cerrado region can enhance their supply chain security by investing in conservation efforts – preventing the deforestation that puts their imports at risk – or by shifting their supply chains to forest-positive suppliers. Examining which countries source the most soy from heavily-cleared areas provides an indication of which countries could benefit the most from investing in Cerrado conservation to enhance their supply chain sustainability.²²

For each major importer, we estimated the soy output lost between 2013 and 2023 in the municipalities it buys from, then divided this by the amount of soy the country imported. This gives a per-tonne exposure intensity: higher values mean more sourcing from heavily-cleared areas and greater vulnerability to continued productivity losses.²³

Germany ranks highest. For every tonne of soy Germany imports, its sourcing regions lost USD 43 of productive capacity between 2013 and 2023 due to deforestation. Germany’s soy purchases are concentrated in municipalities that are actively clearing the Cerrado, which means each tonne imported is linked to more local production loss than other buyers.²⁴

However, countries that source heavily from regions affected by clearing are well-positioned to lead supply chain sustainability efforts. Every million tonnes that Germany shifts toward forest-positive suppliers would preserve USD 43 million in regional productivity (Figure 4).

Germany is followed by Saudi Arabia (USD 28/tonne), Spain and Romania (each USD 25/tonne), and Japan (USD 23/tonne). China has the largest total exposure (Figure 2) because of its high import volumes but a lower intensity (USD 11/tonne).²⁵

However, sourcing patterns are highly overlapped: Germany sources from municipalities where 98.7% of productivity benefits from conservation investment would be shared with other importers, primarily China. This creates a collective action challenge where conservation benefits are shared but costs may fall on individual investors, making coordinated funding more viable than unilateral action. Addressing deforestation-driven productivity losses therefore requires coordinated action, such as multilateral conservation mechanisms, supply chain consortia such as the Soy Moratorium or policy mechanisms such as the EU’s Deforestation Regulation (EUDR).

Figure 4

Box 4: For the EU, the economics favour Cerrado preservation as deforestation regulations ramp up

Our analysis reveals that EU importers have already absorbed at least USD 2.47 billion in hidden productivity losses from Cerrado deforestation over our study period. This cost will only grow without intervention to drastically reduce deforestation, our data, together with other studies, show.

Historical assessments estimate that the EU-soybean trade with Brazil and Argentina caused a cumulative loss of natural capital or ecosystem services of USD 1.7 trillion between 1961 and 2008, underscoring the long-term economic toll of land conversion.

Trade dynamics amplify this: EU–US tariffs announced this year have made US soy a costlier and less reliable option for European buyers. The European Commission imposed an additional 25% duty on US soybeans, which will take effect on 1 December 2025, as part of its retaliatory tariff package. This will raise import costs for EU buyers and reduce the competitiveness of US supply in the EU market.

At the same time, China dominates global soy demand, accounting for 60% of global imports, which intensifies competition for remaining export volumes and limits Europe’s leverage in securing a stable, low-risk supply.

EU exposure to deforestation regulations

The EU Deforestation Regulation (EUDR) prohibits EU countries from importing commodities from land that has been deforested since 31 December 2020. It was officially signed into law in June 2023 and is only anticipated to be fully implemented by December 2026.

Examining where EU countries sourced their soy from in 2022 and calculating their per-tonne exposure intensity gives an indication of how hard it will be for member states to comply with the EUDR. (2022 is the most recent trade data in our dataset reflecting 2017-2021 deforestation – just four years before and one year after the cutoff for deforestation-free imports.) .

Romania shows the highest exposure (USD 72/tonne), suggesting its supply chains were particularly linked to new clearing immediately before the EUDR cutoff. France has the highest absolute exposure of EU countries (USD 45.8 million), while large-volume importers like Spain and the Netherlands show lower intensities (USD 9/tonne and USD 7/tonne, respectively), indicating more diversified sourcing away from recently-cleared municipalities.

These patterns suggest that EU countries face differential EUDR compliance challenges. If those with high 2017-2021 exposure intensities have maintained similar sourcing patterns post-2020, they will require more substantial supply chain restructuring to meet EUDR requirements.²⁶

There is a critical window for intervention

We found that the relationship between land clearing and climate impacts changes as clearing occurs. The first hectares of clearing cause the most severe climate disruption. Then there is a turning point, after which additional clearing causes progressively less additional damage.²⁷

This threshold has implications for conservation strategy. Below the turning point, each hectare of vegetation loss creates large increases in local dryness, making conservation efforts highly effective at preventing climate damage.

Nearly all municipalities that experienced clearing during our study period remain below this critical threshold,²⁸meaning policies prioritising Cerrado protection could effectively prevent further damage. Once municipalities cross the turning point, additional conservation delivers much smaller climate benefits, as most of the damage has already occurred.

Brazil faces a present but shrinking policy window: its advantage of being below the threshold will be permanently lost as clearing intensifies and interventions give diminishing returns.

1
Comex Stat database, accessed 31 October 2025.
2
The study’s authors attribute the Cerrado being overlooked in the Soy Moratorium to “differences in public awareness, national politics and narratives, changes in trade relationships, leadership and sunk investments”.
3
The study is comparing yields on farms between (a) a scenario where deforestation did not reduce regional rainfall and (b) the present scenario where deforestation has reduced rainfall. The yield gap represents the lost productive potential of the current agricultural system due to the climate change that the system itself helped cause.
4
We used CHIRPS v3.0 rainfall maps to calculate the average annual rainfall at a spatial resolution of 0.05 degrees for each Brazilian municipality (2013–2023) by overlaying the rasters on official municipality boundaries and averaging the values inside each polygon. We then calculated anomalies relative to each municipality’s 1991–2020 baseline (we followed the World Meteorological Organisation (WMO) definition of climatological standard normals of 30-year averages, using the current 1991–2020 normal as baseline). Our aridity index, the standardised precipitation evapotranspiration index (SPEI), was based on monthly precipitation and potential evapotranspiration data from the Climatic Research Unit of the University of East Anglia at a spatial resolution of 0.5 degrees. Annual average values were calculated for each municipality for each year.
5
To assess land clearing’s impact on local aridity, we compiled panel data of municipalities in the Cerrado with yearly measurements of climate (SPEI, precipitation anomalies, see footnote 4) and land-use (land cleared for soy). Each municipality has repeated annual observations, which creates a hierarchical data structure (years nested within municipalities). We employed a linear mixed-effects model fit by restricted maximum likelihood (REML) to leverage this structure, as it appropriately accounts for the non-independence of observations from the same municipality. This approach allows each municipality to have its own baseline (random intercept) while estimating the overall effects of clearing and climate on aridity. We performed extensive diagnostic checks to ensure the reliability of the mixed-effects model. The model converged with REML criterion = 493.5. Together, our fixed predictors explain nearly half of the variation in SPEI (marginal R² = 0.488), and incorporating municipality‐level random effects raises explained variance to over two-thirds (conditional R² = 0.682), indicating that both clearing and local heterogeneity account for a substantial portion of SPEI variability. Greater soybean clearing systematically dries out the local moisture balance (SPEI) across all 840 municipalities.
6
Based on the 72% of municipality-years for which trade price data is available. The 8% figure represents the share of total production value. In volume terms, the foregone production of 34.2 million metric tonnes represents approximately 7% of total soy volume produced in the study region over 2013-2023. The difference between value and volume percentages reflects variation in soy prices across municipalities and years.
7
We looked at every municipality, year by year, and recorded how much cerrado was cleared for soy each year. For each location, we compared each year to the previous year and flagged it as a “reduction year” only when clearing went down (and the previous year had some clearing). For reduction years, we calculated the percent cut as “last year’s clearing minus this year’s, divided by last year’s”. The dollar figures we report are modeled gains calculated by estimating the tonnes of production “saved” by avoiding clearing (using our production-loss-per-kilohectare coefficient) and multiplying by the observed municipality-year prices, then summing across years. These are gross revenue numbers (they don’t subtract conservation costs) and assume behaviour doesn’t shift elsewhere. When we show an “all-wet” version, it’s the same calculation valued with the wet-year penalty.
8
To assess feasibility, we compared clearing rates and production levels between early (2013-2017) and recent (2018-2023) periods for each municipality in our sample. Among the 311 municipalities (51% of the sample) that reduced clearing between these periods, we calculated the percentage change in both clearing rates and production to determine whether output was maintained.
9
In our model, the interaction term (soy clearing × relative anomaly) allows the effect of land clearing on SPEI to depend on climate conditions. This tests whether clearing impacts are amplified during extreme wet or dry years. The negative clearing × anomaly interaction result in our model means that clearing has a stronger drying impact in anomalously wet years, when cleared landscapes lose moisture more rapidly, while in already dry conditions the marginal loss per hectare is smaller.
10
Our panel models are associational. The inference that clearing reduces local moisture availability is consistent with the negative SPEI association and robustness checks (municipality and year fixed effects, clustered standard errors, exclusion of top-decile municipalities), but we do not claim causal identification and cannot fully rule out time-varying confounders (such as technology or infrastructure upgrades).
11
Results are not driven by the very largest municipalities: excluding the top decile by soy area leaves the wet-year interaction negative and slightly larger in magnitude (−0.00612 to −0.00661). A stricter municipality fixed-effects model confirms the main drying effect but renders the interaction statistically weaker; we therefore emphasise the robust drying result and present wet-year amplification as a sensitivity consistent with the mixed-effects specification.
12
To do this, we built a municipality-by-year panel for 2013–2023 with (i) total soy production in each municipality and (ii) soy-driven clearing accumulated over the prior five years. We then compared years within the same municipality, controlling for municipality traits that don’t change over time and for shocks common to all municipalities in a given year. This tells us whether years with more recent clearing ended up with higher or lower total municipal production. Because the outcome is total production, the estimated effect automatically nets the output from new fields and any spillover losses (or gains) on existing fields – i.e., it’s a net effect per 1,000 hectares cleared. For dollar figures, we convert the implied tonnes using the observed municipality-year Free On Board (FOB) prices. We report standard errors that allow for correlation within municipalities (and years) and show robustness to outliers and to wet/dry conditions.
13
Illustrative area-to-tonnes conversions assume 3 t/ha for newly cleared soy area (close to the panel median yield). Substituting the observed median yield leaves conclusions unchanged and only rescales the illustrative totals. All tonne-to-USD conversions use municipality-year volume-weighted FOB prices.
14
This represents foregone production in China’s sourcing regions, not a direct cost to Chinese importers, but a measure of how much productive capacity has been lost in the areas where China sources its soy, and therefore the risk to China’s supply chain. China may not be the only importer sourcing from each region.
15
China sources Brazilian soy from 2,381 municipalities across 23 states nationwide, but our analysis focuses on 840 Cerrado municipalities.
16
24.7% of China’s imports came from the Matopiba region.
17
The paper estimates that the Cerrado loses 26.5 million hectares by 2050 under current Forest Code, which works out to 1,019 kha/year.
18
Bloomberg Intelligence report: Global Agriculture, Trade War Threatens US Chain as Opportunities Head South (2025). Accessed 13 October 2025.
19
China and the US are reported to have discussed expanding farm trade, including soy, in October 2025.
20
Brazil can still meet China’s volume demands in the near term. The risk is not immediate supply shortage, but rather systematic degradation of the productive base. As landscapes lose productivity, maintaining output requires either expanding clearing (worsening climate impacts) or accepting yield declines, meaning soy production in the region becomes increasingly vulnerable to disruption.
21
Brazil’s dependence on China as the single-largest buyer also places Brazil’s export programme at risk of shifts in Chinese demand or policy, trade disputes or economic slowdown.
22
In our calculations of the total value of lost production (above), countries that import the most will rank highly because they have a large import volume. Looking at which countries have sourced the most from highly-impacted regions results in a per-unit conservation benefit, showing which countries can most effectively work to protect their imports, regardless of volume.
23
We quantified municipality-level soy productivity losses from deforestation using fixed-effects panel regression models covering 840 Cerrado municipalities over 2013-2023. We converted losses to monetary values using municipality-specific FOB prices (USD/tonne) and matched these to country-level import flows using Trase supply chain data. To calculate country exposure, we allocated municipality losses to importing countries proportionally based on trade volumes. The exposure intensity was calculated as each country’s cumulative attributed losses divided by its total import volume. These values represent foregone production in source regions due to clearing, not direct costs to importers.
24
52% of Germany’s imports came from the Matopiba region – the active agricultural frontier.
25
While total exposure (USD millions) shows scale, USD/t shows how clearing-exposed each imported tonne is.
26
These results indicate supply chain risk profiles based on historical patterns rather than providing definitive EUDR compliance assessments. If EU countries shifted their supply chains between 2017 and post-2020, their EUDR exposure may differ from these estimates.
27
We estimated linear and quadratic coefficients for deforestation, which revealed an inflection point in the relationship between clearing and aridity. Below this inflection point, additional deforestation drives increasingly severe drying effects; beyond it, the marginal impact on SPEI decelerates, suggesting a plateau in sensitivity once forests are already heavily reduced.
28
Of the municipalities that experienced deforestation during our study period, only two exceeded the inflection point and entered the “plateau-response zone”. In these few municipalities, efforts might shift toward restoration strategies, such as reforestation or agroforestry, to rebuild moisture-regulating capacity.

Net-zero progress overblown by inconsistencies in land carbon accounting

November 18, 2024 by ZCA Team Leave a Comment

Key points:

Nationally Determined Contributions (NDCs) – which outline national governments’ commitments to emissions reduction – account for land-based carbon removal using different methods to the IPCC.
When the methods are harmonised, NDCs reduce the budget for limiting warming within Paris Agreement goals by 15-18%, equivalent to bringing forward the deadline for net zero by five to seven years.
This means governments need to set far more ambitious mitigation targets to achieve net zero as defined by the IPCC, than covered by their current methods.
Differences in how emissions are reported from managed and unmanaged land in NDCs compared to the IPCC introduces opportunities for bias or misrepresentation, obscuring countries’ true climate impacts.
The amount of land designated for land-based removals in NDC pledges – about 1 billion hectares or the equivalent of around two-thirds of global arable land – is also impossible without complex trade-offs for food security, biodiversity and human livelihoods.
IPCC models give unrealistically optimistic estimates of land-based removal potential because they don’t consider land availability constraints, conflicts and human rights issues, or the erosion of land carbon sinks.
By comparison, a recent analysis modelling the social and ecological risks of land-based carbon removal potentially reduces the amount of land available for carbon removal by up to 79% compared to IPCC estimates.
This discrepancy suggests that status quo estimates of land-based carbon removal used to inform global and national climate ambition may be overblown and misleading.

Emissions reduction in NDCs

Under the Paris Agreement, adopted in 2015, countries around the world agreed to submit climate action plans called Nationally Determined Contributions (NDCs) every five years starting in 2020 to address greenhouse gas emissions.¹ NDCs translate global agreements into specific national targets and are the key mechanism for countries to show their commitment to reducing emissions – through, for example, phasing out fossil fuels, deploying renewable energy, decarbonising industries and electrifying transport.

Another approach to reducing emissions involves harnessing the ability of landscapes to capture and store carbon – a greenhouse gas inventory sector referred to as land use, land-use change, and forestry (LULUCF) by the Intergovernmental Panel on Climate Change (IPCC).² Natural landscapes around the world store significant amounts of carbon in plants and soil – global forests absorb an average of 7.6 billion metric tonnes of carbon dioxide per year, equivalent to around one and a half times the annual emissions of the US.

In the LULUCF component of their NDCs, countries pledge to plant new forests (afforestation), restore degraded forests (reforestation), protect existing forests and implement sustainable forest management and soil conservation techniques. To a much lesser degree, they also project the use of bioenergy with carbon capture and storage (BECCS), whereby trees, crops or algae will, in theory, be grown to capture carbon dioxide from the atmosphere and then converted into energy, such as biofuels, with the emissions stored below ground.

These forms of carbon dioxide removal are appealing to governments and industries because they don’t necessitate immediate, large-scale changes to a country’s industrial and energy sectors. However, although most IPCC pathways that aim to limit warming to Paris Agreement targets of 1.5°C or 2°C include carbon sequestration in land sinks, enhancing these sinks alone is insufficient to achieve the necessary carbon reductions. Ambitious and timely NDC commitments this decade could close the emissions gap needed to keep temperatures within targets but require a rapid shift away from traditional fossil fuels in addition to land-based removal.

Due to several scientific and political reasons outlined below, the potential contribution of land carbon sequestration to emissions reductions is significantly overestimated in NDCs and scientific models. This overestimation renders the commitments outlined in NDCs unrealistic and endangers the goals of the Paris Agreement. While several publications have explored this issue, no comprehensive, easy-to-read resource has been created to synthesise the findings. The goal of this briefing is to provide a concise summary of the various reasons NDCs disproportionately rely on land for carbon removal and to outline the potential implications for the Paris Agreement.

Land carbon fluxes are the most uncertain component of the global carbon budget

Countries annually report their progress on the emissions reductions pledged in their NDCs through National Greenhouse Gas Inventories (NGHGIs), following guidelines established by the United Nations Framework Convention on Climate Change (UNFCCC).

Collective progress towards the Paris Agreement goals is assessed every five years in the Global Stocktake, which provides benchmarks for countries for their NDC submissions. If NDCs are insufficient or lack ambition, there is a significant risk that the world will exceed the Global Carbon Budget – the total amount of carbon dioxide that can be emitted while keeping within global temperature targets, leading to temperature increases beyond the targets agreed upon in the Paris Agreement.

Because of the complex interactions of various human-driven effects on greenhouse gas fluxes from land – such as deforestation for agriculture – land carbon fluxes are the most uncertain component of the global carbon budget. At the national level, accurately tracking changes in forests and other land uses is also challenging due to variations in the quality and scope of land-use data , different reporting methods used, and difficulties in s eparating the influence of humans and climate on the environment as well as in reporting carbon movements in different ecosystems, with estimates relying significantly on simplified models. This means that estimates of emissions from LULUCF are less precise than those from fossil fuels, which are grounded in empirical data.

As a result, the Paris Agreement allows flexibility for countries to determine how they account for emissions and removals from the LULUCF sector, such as the use of different accounting and monitoring methods or different definitions of land-use types in their climate targets. In addition, developing countries are encouraged to gradually adopt economy-wide emission reduction targets depending on their economic and developmental needs. In comparison, developed countries are required to specify a specific, measurable and economy-wide reduction in overall emissions – for example, a 40% emissions reduction compared to 1990 levels.

NDC net-zero may not mean net-zero global emissions

The use of different carbon accounting methods for land-based removal between NDCs and model-based methods, such as those used by the IPCC, makes it hard to measure the emissions and temperature outcomes of current national commitments under the Paris Agreement.

While both NGHGIs and the models used by the IPCC to assess the pathways necessary to achieve specific climate targets aim to identify greenhouse gas fluxes from land, they differ in how they account for the role of human activity in these fluxes. This affects the extent to which each approach attributes these fluxes to a country’s mitigation efforts.³

This is especially problematic for countries that rely heavily on the land sector and forest management to achieve their NDCs, leading to over- or under-estimating true emissions and creating inconsistencies between national inventories and the global carbon budget.

A recent analysis illustrated how current NGHGIs for NDCs can make national emissions appear lower than the method applied by the IPCC in assessing alignment with the Paris Agreement. It concluded that once the methods are harmonised – such as by adjusting fluxes from land use – our overall carbon budget is reduced by 15-18%, which is equivalent to bringing forward the deadline for net zero up by five to seven years. What this means is that governments need to set far more ambitious mitigation targets to achieve net zero, as defined by the IPCC.

Unmanaged land is a blind spot in carbon accounting

Discrepancies in the LULUCF emissions estimates between IPCC models and NDCs arise partly because countries are not required to report emissions from unmanaged land – such as emissions from wildfires in remote forests where human intervention is minimal or absent – as these are considered natural rather than human-caused emissions. This has resulted in some highly forested countries designating large areas of forest as unmanaged. But as emissions are still released from these unmanaged areas, excluding them leads to an incomplete picture of the carbon cycle and a country’s total emissions.

This has introduced opportunities for bias or misrepresentation. For example, Canada does not include emissions from forest wildfires in its inventory, as around 34% of its forests are classified as ‘unmanaged’. This means that emissions from natural disturbances, such as wildfires, in these forests are not accounted for.⁴ Additionally, fires within its managed forests are also classified as natural disturbances rather than human-caused disturbances, and so are also excluded from the inventory.

This oversight leaves significant emissions unaccounted for, obscuring Canada’s true climate impact. Around 114 million metric tonnes of emissions was excluded per year from its inventory between 2005 and 2021 – equivalent to around half the total carbon dioxide emissions from gas in Canada in 2023.⁵ In 2023, a year of record-breaking wildfires, natural disturbances released an estimated 640 million metric tonnes of carbon from Canada’s forests, which is more than Canada’s carbon dioxide emissions from fossil fuels in 2022.

Managed land can lead to overestimates of climate progress

Flexible guidelines also mean that there is variation in what constitutes managed and unmanaged land. Under the Kyoto Protocol adopted in 1997, countries agreed to count greenhouse gas emissions and removals from land activities towards their climate targets only if they result from direct human actions. However, the IPCC later noted that as human activities and environmental changes are closely linked, they are not practical to separate in greenhouse gas inventories – for example, forest loss from both logging and climate-induced drought. Therefore, ‘managed land’ was introduced as a proxy for human effects in NDC guidelines, with all greenhouse gas fluxes occurring on managed land being counted regardless of whether they are driven by humans or the environment. This is not a feature of the IPCC’s models that are used for estimating carbon fluxes, which clearly distinguish between emissions from managed and unmanaged forests.

This means that countries can classify natural forests as managed land in their NGHGIs, enabling them to report natural carbon removal as emissions reductions. Including natural land as managed land can also give a misleading picture of a country’s actual climate efforts by overestimating carbon removals and making progress seem greater than it is. This is further aggravated by the fact that some countries – particularly those that are afforded flexibility in emissions accounting – also report implausibly high forest sinks, have incomplete assessments or have inconsistent estimates across reports. Some forest-dense countries are claiming credit for the carbon that their unmanaged forests are sequestering, using this as a means to justify fossil fuel extraction while also making net-zero claims.

Land-based removal plans are unrealistic

The lack of stringent accounting guidelines has led to a significant over-allocation of land for carbon removal in NDC pledges, beyond what is technically feasible or safe. The Land Gap Report calculated that there is about 1 billion hectares of land for land-based carbon removal included in NDC pledges to 2060 – equivalent to around two-thirds of the world’s arable land and a land area bigger than China. Such large-scale commitments would be impossible without catastrophic impacts, including the displacement of food production and threats to biodiversity.

Pledges for land-based removal in NDCs rely heavily on planting new forests or plantations, with about half of the land proposed for carbon removal in NDCs requiring changes in present land use. Land-use change is already the biggest driver of biodiversity loss, which is essential for ecosystem resilience and the provision of ecosystem services such as food and water security and carbon sequestration.⁶

In addition to the risks around increased competition for land use, estimates suggest that the ‘safe limit’ for expanding agriculture has already been passed, resulting in ecosystem degradation. Figure 1 shows that global cropland already exceeds the planetary boundary for sustainable land use, with land-use changes in pledges and current and projected BECCS projects adding nearly an extra two-thirds to the current land-use change area. There is very little land left that can be used for carbon dioxide removal without complex trade-offs. To be genuinely effective, carbon removals plans need to factor in ecological limits and support biodiversity.

Figure 1. Land for mitigation crosses planetary boundary thresholds

Even if the estimates of removal potential from land in NDCs were technically feasible, a 2023 analysis calculated that current NDCs are insufficient for meeting Paris Agreement targets – actions outlined in NDCs are due to result in warming of 2.5-2.9°C by 2100.

Limitations in IPCC models of future land carbon removal

While NDCs focus on near-term actions to reduce greenhouse gas emissions, Integrated Assessment Models (IAMs) used by the IPCC project long-term scenarios for achieving climate goals. IAMs assess the interactions between climate, energy, land use and economic systems to understand the long-term implications of different policy choices and emissions trajectories, offering different pathways that illustrate how various strategies can achieve climate targets. IPCC pathways offer a framework for countries to set their emissions reduction targets and to align their NDCs to demonstrate their commitment to international climate agreements.

However, recent research argues that the methodologies in IPCC models are over-relying on land-based removal by building in assumptions about land use that are unrealistic. The models do not reflect real-world conditions such as land availability, lack nuance by failing to capture the complexities of human systems and ecosystems, and expose vulnerable communities to avoidable risks. As IPCC reports are the primary mechanism informing the UNFCCC, inappropriate models have the potential to lead to misguided policies and ineffective climate action, ultimately hindering efforts to reduce greenhouse gas emissions and meet international climate goals.

Hidden assumptions mean models over-rely on land

A key challenge with the representation of land-based carbon removal in IAMs is the assumption that significant emissions generated in the near term will be offset in the distant future through decades of land-based removal.

Because of their emphasis on cost-effectiveness, least-cost pathways and supply-side technologies, IAMs often assume that large-scale BECCS and afforestation projects can be implemented easily, without considering competing demands for land. This leads to overestimations of the amount of land available for future carbon removal in the LULUCF sector. To demonstrate this, a 2018 study assessed the rate at which land uses change in IAMs and found that in scenarios limiting warming to 2°C by 2100, cropland for BECCS is projected to expand by 8.8 million hectares per year. This expansion rate is more than three times as fast as the historical expansion of soybean, which is currently the fastest-growing commodity crop and a significant driver of deforestation in the Amazon.

IAMs also have idealised assumptions that do not fully consider the technical, social and economic barriers to scaling up such efforts, such as land tenure issues, governance challenges, the potential for conflict over land use and human rights issues, including rights to food, water and a healthy environment.

IAMs are built on assumptions of ‘empty land’ that do not consider nomadic or Indigenous lifestyles or non-forest ecosystems, such as savannas, and also broadly assume that forests can be converted to cropland for bioenergy. BECCS only features in the NDCs of seven countries, totalling 80 million hectares of land, but it is much more prominent in modelled IPCC pathways, with a median land demand of 199 million hectares (ranging from 56 million to 482 million hectares) in 1.5°C-consistent pathways. However, given such a significant land demand for BECCS from a small number of countries in current NDCs, a land demand of 199 million hectares in future pathways is likely to be an underestimate if BECCS becomes as widespread as in modelled pathways.

The models have also been criticised by researchers for being opaque, with specific value judgments about the future buried in the mathematics of the model. By assuming that the financial costs of mitigation technologies will fall in the future – through applying a high discount rate in the model – solutions like BECCS, which has not yet been proven to work at scale, can appear more cost-effective than proven, readily implementable actions. As BECCS is considered ‘carbon neutral’ in the models, many IAMs also favour large-scale BECCS over renewable technologies to meet the requirements of one of the more ambitious climate pathways that assumes significant reductions in greenhouse gas emissions.⁷

A 2024 analysis found that a high discount rate in IAM models favours high overshoot scenarios – where global average temperatures temporarily exceed a warming target before dropping back down to, or below, the target in the future – rather than scenarios that would mitigate long-term warming effects. This is because of the short timescale over which economic adaptation is assessed in the models. These high overshoot scenarios result in a heavy reliance on land-based carbon dioxide removal in the future as emissions are not reduced fast enough to limit warming. Overshoot is estimated to be cheaper than longer-term solutions and is therefore favoured by the models. However, overshoot comes with various risks and uncertainties, such as species extinction and ecosystem collapse, and has potentially irreversible consequences. Overshoot also raises moral concerns, as climate-related impacts disproportionately affect vulnerable populations, especially in low-income countries.

Reliance on land carbon removal raises sustainability risks

A recent analysis proposed thresholds for land-based sequestration that account for social and ecological risks, thereby developing realistic and sustainable estimates for land-based CDR while accounting for environmental and resource limits (Table 1). The analysis estimates that the sustainable potential of LULUCF measures for carbon removal, including limited reforestation, forest restoration, reduced forest harvest, agroforestry and silvopasture, and BECCS is 3.3 billion-3.8 billion tonnes per year.⁸

The study finds that at high sustainability risk – the point at which multiple ecological and social sustainability limits are likely to be overstepped with potentially irreversible consequences – the value is 6.4 billion tonnes per year. These estimates of sustainable – and hence feasible – removal potential are more conservative than the average estimates in the IPCC’s Sixth Assessment Report – 15.6 billion metric tonnes of carbon dioxide per year between 2020 and 2050 for BECCS, forest and ecosystem protection, restoration and management, and agroforestry, as well as the Emissions Gap Report which included estimates of 5.9 billion tonnes per year by 2030 and 8.4 billion tonnes by 2035 for forestry-related land management,⁹ and the State of CDR Report at 7 billion-9 billion metric tonnes by 2050 from forestry-related removal, BECCS, ecosystem restoration and novel technologies such as direct air capture. Compared to IPCC estimates, a low sustainability risk scenario potentially reduces land available for carbon removal by around 79%.¹⁰

Overall, the greatest risks are linked to scenarios with slower emission reductions and higher reliance on future carbon removal technologies. This highlights the need to reduce emissions quickly and significantly and not rely on future carbon removals – including from land – in order to avoid the worst outcomes.

Table 1. Sustainability risks for land-based carbon dioxide removal for the five IPCC Illustrative Mitigation Pathways compatible with the Paris Agreement.

Data source: Sustainability limits needed for CO2 removal, 2024.
A/R refers to afforestation/reforestation. BECCS & A/R larger footprint assumes a low capture rate and conversion efficiency, while BECCS & A/R medium footprint assumes a medium capture rate and conversion efficiency.

Models do not account for land’s declining ability to store carbon

As IAMs are global in scale, their assumptions are simplified and generalised, and therefore they can miss key local dynamics, leading to ill-suited projections at the regional level.¹¹ IAMs often oversimplify ecosystems, which do not always behave linearly in response to human activities or climate change. For instance, land-use changes can trigger feedback loops that are difficult to capture accurately in simplified models. A 2024 analysis found that IAMs tend to underestimate the risks associated with the interaction between wildfire disturbances and climate change, particularly regarding their impact on the ability of forests to sequester carbon, risking an overly-optimistic estimate of how much carbon forests can remove and store, and inaccurate predictions of future emissions.

This is significant because land and ocean sinks are increasingly absorbing less carbon with rising temperatures. In higher emissions scenarios, the interaction between climate change and the carbon cycle becomes more uncertain due to the risk of positive feedback loops – such as forest fires and permafrost thaw – amplifying climate change impacts. These types of ecosystem responses are not fully integrated into models simply because of their sheer complexity. While models have tended to predict a slow erosion of natural carbon sinks over the next 100 years or so, other estimates suggest that the impact from feedback loops is happening much sooner than anticipated.

1
Each new NDC submitted needs to be more ambitious than the last.
2
LULUCF excludes non-carbon-dioxide agricultural emissions, such as methane from livestock.
3
One outcome is that estimates of land-use change due to afforestation or reforestation are in close agreement between NGHGIs and IPCC models, but differ for managed forests.
4
The Canadian government does not have a database for the net carbon flux in unmanaged lands in the country, making it difficult to track carbon emissions and evaluate whether Canada’s landmass is sequestering enough carbon to offset its emissions.
5
This is compounded by the fact that Canada classifies removals from mature forests as human-caused.
6
Agricultural land is already under significant pressure from rising global food demand, expanding populations and the need to balance land use with biodiversity conservation and climate mitigation efforts. A 2022 analysis estimated that afforestation and bioenergy production could place an additional 41.9 million people at risk of hunger by 2050 due to higher food prices and displacement of agricultural land
7
The RCP 2.6 emissions pathway in the IPCC’s Sixth Assessment Report.
8
Values obtained from Supplementary Table S1 in the report.
9
Values obtained from Table 6.2: Sectoral mitigation potentials in 2030 and 2035.
10
This is a rough calculation assuming a direct comparison between land-use footprint in the IPCC technical mitigation potential and the analysis in Deprez et al. (2024) and was calculated as the difference between the IPCC estimates of 15.6 billion metric tonnes and the lower sustainability risk estimate of 3.3 billion tonnes.
11
The IPCC recommends that these models are interpreted in the context of their assumptions.

Biodiversity offsetting and biocredits

November 22, 2023 by ZCA Team Leave a Comment

Key points:

Biodiversity offsets are a way of mitigating the impact of new infrastructure developments, compensating for biodiversity loss by protecting or restoring similar habitat elsewhere. Their use is often mandatory.
Biodiversity credits, or biocredits, are investments, typically voluntary, in projects that support biodiversity conservation, but which do not imply biodiversity loss elsewhere.
There is concern that companies could use biodiversity offsets to meet their environmental targets without making any meaningful changes to their unsustainable practices.
As biodiversity losses arising from development cannot be properly quantified, it is impossible to know what needs to be compensated for. So, offsets are unlikely to compensate properly for these losses.
Increased focus on trading biodiversity credits could draw attention away from more effective conservation actions and may provide further opportunity for greenwashing.
Biocredits may contribute meaningfully to conservation if strict accountability guidelines are followed.
The UK, France, Australia and the EU are actively promoting global biodiversity credit initiatives.

What is biodiversity offsetting?

The negative biodiversity impacts of some developments cannot be avoided, minimised or restored. Biodiversity offsetting is a form of impact mitigation that aims to compensate for these negative biodiversity impacts – at least in theory – by protecting, enhancing or restoring similar habitat elsewhere. These biodiversity offsets are based on a ‘no net loss’ policy – in other words, overall biodiversity is left no worse off than if the development had not happened.

For example, a developer clears land to build a mine and then compensates for the resulting loss of biodiversity by either purchasing degraded land and restoring the ecosystem on it, or by purchasing land that has a natural ecosystem on it and protecting it – under the assumption that it is likely to become degraded in the future.

Biodiversity offsetting is now widely used to compensate for biodiversity losses from developments and is part of planning and decision-making processes. For example, as a component of mandated Environmental Impact Assessments for developments.

But, as a conservation practice, biodiversity offsetting is highly controversial. Critics are concerned that offsets may be used by companies to meet their environmental targets without making any meaningful changes to their unsustainable practices. Parallels can be drawn with carbon offsets: For example, a fossil fuel company offsets its carbon emissions by planting a forest to remove CO2 from the atmosphere, rather than actually reducing its emissions, thereby “trading a known amount of emissions with an uncertain amount of emissions reductions”, the consequence of which could be a net increase in emissions.

Similarly, the consequences of biodiversity offsetting are, ultimately, increased biodiversity loss. This is in part because most offset projects compensate for a lost ecosystem by protecting land that might be lost in the future. Offset policies mostly define ‘no net loss’ against a baseline of what would have happened without the project and its offset. If the biodiversity loss from future degradation is overestimated, then the positive contribution of the offset will also be overestimated, giving the developer more scope to have a negative impact on biodiversity. While this may be defined as ‘no net loss’ within the current framework, the outcome would be less biodiversity than if the project had not happened.

What are biodiversity credits?

In response to these criticisms, biodiversity credits, or biocredits, which are typically purchased voluntarily, have emerged to direct money “towards meaningful and well-designed biodiversity conservation and management”. Biodiversity credits are investments in projects that support biodiversity conservation, but which do not imply biodiversity loss elsewhere. A 2022 report from the International Institute for Environment and Development (IIED) and the United Nations Development Programme (UNDP) endorses biocredits, arguing that because biocredits, unlike biodiversity offsetting, do not imply biodiversity loss elsewhere, they represent a “positive investment in biodiversity” that companies or other entities – such as philanthropists – can choose to make.

However, whether biocredits would realistically be used for non-offsetting purposes is a point of contention. There is also concern that policies may weaken over time under increasing pressure from developers, and that frameworks are being redefined to include financial and other non-environmental metrics, which could facilitate claims of success when the environmental contribution is, in fact, weak. Some also argue that without enforcement, there will not be sufficient investment in biocredit projects.

But the IIED and UNDP report is clear that, if used correctly, biocredits can contribute meaningfully to nature conservation and restoration. To ensure this, “buyers should be screened to ensure they are not using the credit to offset damage elsewhere” and “the investment in the purchase of the biocredits [should] maximise the social and biological impact compared to other potential investments”. The report also recommends that the metrics used to define a unit of biodiversity should include its cultural and social value.

Issues with trading units of biodiversity

The concept of ‘no net loss’ does not sit well with ecologists because it fails to recognise that biodiversity exists within complex ecosystems and cannot easily be isolated from its social, historical and evolutionary context. Because of this complexity, the losses arising from development cannot be properly quantified, and so it is impossible to know what needs to be compensated for. In fact, a 2021 study found “no evidence that biodiversity gains from offsets actually compensate for development-associated losses, because losses were never estimated”.

Moreover, as the ecological circumstances of two areas will never be identical, offsetting the impacts to one area by restoring or conserving another will always result in some degree of biodiversity loss.

Though a development may only be impacting a small area of land, the land required for compensating for this development may be much bigger – indeed, policy often requires that at least twice the area of biodiversity loss must be protected. Conservationists worry that there is simply not enough land available to compensate for expected biodiversity losses from future development.

There is also concern that increased focus on the trading of biodiversity credits will draw attention away from other, more robust, conservation actions. It could create even more scope for greenwashing – tricking consumers into thinking that their choice is sustainable through a false claim – if badly designed offsets or biocredits are marketed as supporting biodiversity or social equality.

As biocredit schemes are aimed at providing both economic and environmental benefits, this may also allow financial markets and short-term speculators to determine the price of conservation, thereby framing the value of conservation purely in terms of its profitability. But, assigning monetary value to nature does not always promote the conservation of biodiversity and may, in fact, result in the opposite. This also creates a “dangerous and misleading illusion of the substitutability” of critical ecosystem services that may actually be irreplaceable.

COP 15 and the Global Biodiversity Framework

In December 2022, the United Nations Biodiversity Conference (COP 15) concluded with the establishment of the Kunming-Montreal Global Biodiversity Framework (GBF). The core aim of this framework is to tackle the alarming decline in biodiversity, facilitate the restoration of ecosystems, and safeguard the rights of indigenous communities. It garnered widespread recognition for its progress in connecting human rights with biodiversity, encompassing concrete measures to stop and reverse the decline of natural ecosystems.

A pivotal target of the GBF is the commitment to safeguard 30% of the earth’s surface and 30% of degraded ecosystems by 2030. It also includes provisions for increased financial assistance to support developing nations in their conservation efforts.

However, a component of the GBF called Target 19 remained unchanged, despite reservations expressed prior to COP 15 by a group of 119 experts. The target underscores the importance of “increas[ing] the levels of financial resources made available from all sources… towards nature-positive economies” and “stimulating innovative schemes… such as biodiversity offsets [and] carbon credits”. Concerns revolved around the potential for the monetisation of nature, the creation of a global market for trading biodiversity credits, and the promotion of biodiversity offsetting without the requisite rigor to ensure a comprehensive reduction and reversal of biodiversity loss within the prescribed time frame.

Nations championing biodiversity credits

The GBF has rapidly propelled global initiatives forward. The UK, France, Australia and the EU are at the forefront of promoting “nature markets”.

UK and France

In March 2023, the UK government unveiled plans to launch three separate nature markets, one for biodiversity offsets, another for flood mitigation and one for clean water. These are to be integral to the UK’s Environmental Improvement Plan 2023, with the goal of increasing private financing for nature to a minimum of GBP 500 million annually by 2027 and GBP 1 billion cumulatively by 2030.

The UK and France are taking the lead in advocating for a global biodiversity credit market. They jointly introduced the Global Biodiversity Credits Roadmap in June 2023, which aligns with the GBF and outlines a strategy to expand worldwide efforts to support companies in procuring biodiversity credits. Working towards COP 16 in 2024, the two countries have committed to bringing together global expertise on biodiversity credits and establishing working groups to explore best practices, ranging from credit funding governance to monitoring frameworks. The Roadmap also intends to address the equitable distribution of income from biodiversity credits.

Australia

Australia has a well-established presence in biodiversity offsetting markets, with both existing and new initiatives in development. All six Australian states have implemented compliance-based biodiversity offsetting schemes, alongside a federal biodiversity offset scheme. Recently, the Northern Territory introduced a new policy framework for biodiversity offsets. The determination of offsets typically takes place on a case-by-case basis, with assessments considering the impact on critical species or habitats.

In addition to the existing offsetting schemes, Australia’s government is working on establishing a Nature Repair market, a controversial initiative aimed at addressing the funding gap for nature conservation and restoration in Australia. This initiative seeks to stimulate private investment in biodiversity efforts by rewarding landholders who actively engage in nature preservation. The Australia’s Minister of the Environment, Tanya Plibersek, stated that the initiative aims to turn Australia into the “Green Wall Street”.

The proposal faced significant backlash from members of the opposition bench, due to concerns about integrity and its potential for actual impact. Additionally, think tank The Australia Institute criticised the government’s insufficient environmental and economic justification for the scheme, stating that it cited unsubstantiated financial projections from a PwC report. As a result, the Committees have extended their deliberation period without a specified end date.

EU

In its most recent update to the EU Taxonomy for sustainable activities, the EU has chosen to include an element of biodiversity offsetting. This decision ignores the recommendation provided by the Platform on Sustainable Finance, a group of advisors to the EU’s executive branch, which had called for the removal of it from the list of economic activities related to biodiversity protection and nature restoration due to potential interpretational issues. Nonetheless, the EU decided to include it, albeit with slightly altered phrasing, leading to confusion over its precise meaning.

The decision has faced significant criticism from NGOs and civil society groups. In an open letter, they called for the removal of biodiversity offsetting, claiming that “offsetting is only compensating significant harm elsewhere and thus cannot represent a substantial contribution” to meeting the EU’s biodiversity objectives.

If not biodiversity offsetting and credits, then what?

The most straightforward solution is to avoid biodiversity losses as much as possible, with offsetting only used as a last resort.

Biocredits can encourage positive investment in biodiversity if strict accountability guidelines are followed and governance is transparent, and if a holistic approach that considers social, cultural and biological value is used.

Another potential solution is target-based ecological compensation, a new policy framework that offers an alternative to traditional biodiversity offsetting. It requires that compensation for biodiversity loss is linked to broader conservation goals to ensure that overarching targets for biodiversity are met, thereby enhancing compensation beyond an ad-hoc, reactive response.

An alternative proposal by the research center Enterprise for Society Centre (E4S) involves a centralised private sector biodiversity fund. According to E4S, this approach could enhance and simplify financing, allowing for direct allocation of funds to critical conservation areas, where they would contribute towards global restoration targets. The centrally-managed fund could also accommodate both current and historical compensation, particularly where local biodiversity offsetting is not mandated. However, transforming this into reality relies on the availability of comprehensive ecosystem data and transparent cost information.

IPCC WGIII report: The land sector and climate mitigation

April 6, 2022 by ZCA Team Leave a Comment

This briefing summarises the Working Group III (WG3) of the IPCC’s main insights about the mitigation options with the Agriculture, Forestry and Other Land Uses (AFOLU) sector. The term “land sector” will be used throughout this briefing for clarity. The briefing also summarises the findings on the needs and limitations of land-based carbon dioxide removal (CDR).

Key points

Rapid deployment of mitigation in the land sector is essential in all 1.5°C pathways. It can provide up to 30% of the global mitigation needed for 1.5°C and 2°C pathways.
The sector offers significant near-term mitigation potential at relatively low cost. The global land-based mitigation potential is ~8–14 billion tonnes of CO₂ equivalent (GtCO₂-eq) each year between 2020-2050. About 30-50% of this potential could be achieved under USD20 per tCO2-eq. Options costing USD100 per tCO₂-eq or less could reduce global GHG emissions by at least half the 2019 level by 2030 (SPM C.12). But land-based mitigation cannot compensate for delayed emissions reductions in other sectors.
The IPCC recognises that carbon dioxide removal (CDR) is necessary to achieve net-zero GHG globally. Modelled scenarios rely heavily on forest planting and BECCs as main options to remove emissions from the atmosphere to achieve it.
But, the IPCC is not advocating for large-scale CDR. There are many uncertainties, risks and a lack of social licence for these options. It is still uncertain whether CDR through some land-based measures can be maintained in the very long term because sinks can saturate, for example. CDR cannot be deployed arbitrarily and given the time needed to ramp-up CDR, it can only make a limited contribution to reaching net zero in the timeframe required.
There is a substantial investment gap in the sector. The IPCC estimates that, to date, only USD 0.7 billion a year has been invested in land-based mitigation, well short of the more than USD 400 billion per year needed to deliver the up to 30% of global mitigation effort in deep mitigation scenarios.

The land sector is key to climate mitigation, but only within limits

The land sector is both a carbon source and a carbon sink. It accounted for ~13%-21% of global greenhouse gas (GHG) emissions between 2010-2019. ¹ But the land sector is also a carbon sink, as it draws CO₂ from the atmosphere when plants grow (through the process of photosynthesis). When the sector’s sources and sinks are added up, the land sector is considered a net sink of emissions – removing about 6.6 GtCO₂ a year for the period of 2010-2019. ²

The IPCC clearly states that the land sector has huge potential for mitigation. It can both reduce emissions – for example by changing farming and livestock practices – as well as remove them from the atmosphere, via measures like planting more forests and protecting existing ones. But the sector “cannot fully compensate for delayed action in other sectors”. (SPM C.9)

Overall, the IPCC estimates that the global land-based mitigation potential is ~8–14 billion tonnes of CO₂ equivalent (GtCO₂-eq) each year between 2020-2050, at costs below USD 100/tCO₂. ³ These estimates are slightly higher than those in AR5. Considering both integrated assessment models (IAMs) and sectoral economic potential estimates, WG3 states that “land-based mitigation could have the capacity to make the sector net-negative GHG emissions from 2036 although there are highly variable mitigation strategies for how [its] potential can be deployed for achieving climate targets”. ⁴ There are many options that can help reduce and remove emissions (Box 1). Most of the options to reduce emissions are available and ready to deploy, whereas CDR needs more investment. ⁵

The IPCC does not use the term ‘nature-based solutions’ (NbS), but ‘land-based mitigation measures’. When evaluating the mitigation potential within the sector, it discusses 20 measures, both supply and demand-side (Box 1). However, when it analyses mitigation pathways, it only includes a few options because of how climate models are currently built (see the role of CDR in mitigation pathways section for more detail).

Box 1. What are the main ways the land sector reduces and removes emissions between 2020-2050?

Forests and other ecosystems have the highest potential for carbon mitigation, according to global sectoral models. Protecting, managing and restoring these ecosystems is likely to reduce and/or sequester up to 7.4 billion tonnes of CO₂ equivalent each year between 2020 and 2050. ⁶ Crucially, the IPCC finds that protecting ecosystems has the highest potential. The report also stresses that halting deforestation and restoring peatlands is vital to keeping temperature rises below 2C.

Agriculture and demand-side measures provide the second and third highest potential for mitigation, potentially reducing and/or sequestering up to 4.1 and 3.6 billion tonnes of CO₂ equivalent a year respectively between 2020 and 2050. ⁷ For agriculture, the measures that have the greatest potential are soil carbon management in croplands and grasslands, agroforestry, biochar and rice cultivation, as well as livestock and nutrient management. On the demand-side, it’s shifting to healthy diets and reducing food waste and loss.

Land sector mitigation measures can have important co-benefits, but only if done properly. For example, “reforestation and forest conservation, avoided deforestation and restoration and conservation of natural ecosystems and biodiversity, improved sustainable forest management, agroforestry, soil carbon management and options that reduce CH₄ and N₂O emissions in agriculture from livestock and soil, can have multiple synergies with the sustainable development goals.” ⁸

But there are many risks and trade-offs. Large-scale or poorly planned deployment of bioenergy, biochar, and afforestation of naturally unforested land. (high confidence) for instance, can compete with scarce resources, such as agricultural land. ⁹ This can threaten food production and security and reduce adaptive capacity. The use of non-native species and monocultures (e.g. planting one type of tree) in forest projects can also lead to biodiversity loss, and negatively impact ecosystems. ¹⁰ There are also risks in relation to land’s ability to continue to act as a carbon sink in the future, which can reduce land sector measures’ capacity to mitigate emissions. ¹¹

Joint and rapid effort is key to achieving high levels of mitigation in the sector, the IPCC says. But there has been a lack of funds to support these efforts. The IPCC estimates that, to date, only USD 0.7 billion a year has been invested in the sector, well short of the more than USD 400 billion per year needed to deliver the up to 30% of global mitigation effort envisaged in deep mitigation scenarios.¹²

What does the IPCC say about the scale of land-based CDR?

Mitigation potential of different CDR options

CDR is defined by the IPCC as “human activities that remove emissions from the atmosphere and durably store it”. Thus, CDR excludes uptake of emissions not directly caused by humans. CDR can help in several phases of mitigation:

Reducing net CO₂ or GHG emission levels in the near-term
Counterbalancing residual emissions from hard-to-transition sectors like industry and agriculture to help reach net-zero CO₂ or GHG emissions targets in the mid-term
Achieving and sustaining net-negative CO₂ or GHG emissions in the long-term if deployed at levels exceeding annual residual emissions. ¹³ Therefore, offsets are discussed in the report as a way to counterbalance residual emissions, highlighting that hard-to-abate sectors could have more social licence to rely on CDR. ¹⁴

Currently, the only widely practised CDR methods include afforestation, reforestation, improved forest management, agroforestry and soil carbon sequestration. ¹⁵ Figure 1 presents the options that can be deployed on land as well as in the oceans. The IPCC discusses these options, presenting a summary of their mitigation potential, risks, co-benefits and costs. (Table 1 in the appendix) However, the IPCC does not go into detail on all options. For example, it mentions that the choice of feedstock for BECCS could lead to positive or negative impacts, but does not explore all feedstock options and their related consequences.

Figure 1. CDR methods across Land sector and Oceans (IPCC- WG3 Chapter 12, p.37)

The role of CDR in mitigation pathways

The WG3 report looks at what the science says about mitigating the climate crisis. As established in most scientific literature, achieving net zero by mid-century is the safest way to stay Paris aligned. There are, however, many different routes to net zero. Thus, the scope of this report is to chart the options, limits, benefits and trade-offs of pursuing a net-zero emissions society. To do this, the IPCC reviewed more than 3000 pathways, including over 1200 scenarios, to develop five “Illustrative Mitigation Pathways” (IMPs) and two high-emissions pathways for reference.

The report finds that “CDR is a necessary element to achieve net-zero CO₂ and GHG emissions, and counterbalance residual emissions from hard-to abate sectors”. ¹⁶ It is also a key element in scenarios that are likely to limit warming to 2°C or lower by 2100”. ¹⁷ All of its IMPs use land-based CDR, which is dominated by BECCS, afforestation and reforestation. ¹⁸

In most scenarios that limit temperatures to 2°C or lower, the IPCC predicts cumulative volumes of CO₂removed between 2020-2100 could reach (all median values): ¹⁹

BECCS – 328 GtCO₂
Net CO₂ removal on managed land (including afforestation and reforestation) – 252 GtCO₂
Direct Air Capture Capture and Storage (DACCS) – 29 GtCO₂

To put this into perspective, the remaining carbon budget assessed by WG1 from the beginning of 2020 onwards is 500 GtCO₂ for limiting warming to 1.5°C with a 50% chance of success. ²⁰ The IPCC also predicts that mitigation measures in 2°C or below pathways can significantly transform land all around the world. These pathways are “projected to reach net-zero CO₂ emissions in the land sector between the 2020s and 2070, with an increase in forest cover of about 322 million hectares (-67 to 890 million ha) [an area almost as big as the US and India combined] in 2050 in pathways limiting warming to 1.5°C with no or limited overshoot”. ²¹

Delaying action will result in larger and more rapid deployment of CDR later, especially if there is a temperature overshoot. Then, large-scale deployment of CDR will be needed to bring temperatures back. ²² Since IAM pathways rely on afforestation, reforestation and BECCS, delayed mitigation can lead to a lot of changes in land use, with negative impacts for sustainable development. ²³ The IPCC points out that “strong near-term mitigation to limit overshoot, and deployment of other CDR methods than afforestation / reforestation and BECCS may significantly reduce the contribution of these CDR methods in scenarios limiting warming to 1.5 or 2C”. ²⁴ “Stronger focus on demand-side mitigation implies less dependence on CDR and, consequently reduces pressure on land and biodiversity”. ²⁵ It adds that: “Within ambitious mitigation strategies…, CDR cannot serve as a substitute for deep emissions reductions”. ²⁶ To put this into perspective, the market for carbon offsets today, which include these CDR measures, reduce global emissions by about 0.1%, according to the Energy Transitions Commission.

But while most scenarios in WG3 still rely on CDR to achieve net-zero, the IPCC is not advocating for large amounts of it. Instead, the reliance on CDR reflects the state of climate modelling and research (see box 2 in appendix). The IPCC discusses the uncertainty, risks and lack of social licence for CDR, such as concerns that large-scale CDR could obstruct near-term emission reduction efforts or lead to an over-reliance on technologies that are still in their infancy. ²⁷ It stresses that there is uncertainty about how much CDR will be deployed in the future and the amount of CO₂ it can remove permanently from the atmosphere. ²⁸9 This is because some measures in the land sector cannot be maintained indefinitely as these sinks will ultimately saturate, while trees can also be cut down, burnt or die prematurely. ²⁹

Box 2. A word about climate models and the potential and limitations of land sector mitigation

Since the last IPCC reports, there have been more assessments of the total mitigation potential of the land sector. ³⁰ These can be split into:

Sectoral models: These estimate the potential of the sectors and/or individual measures. But they rarely capture cross-sector interactions, making it difficult for them to account for land competition and trade-offs. This could lead to double counting when aggregating sectoral estimates across different studies and methods. ³¹ They usually show higher mitigation potential as they include more land-based mitigation options than IAMs. ³²
IAMs and integrative land-use models (ILMs): IAMs assess multiple and interlinked practices across sectors, and thus account for interactions and trade-offs (i.e. land competition). IMLs combine different land-based mitigation options, which are only partially included in IAMs. Both have extended their coverage, but the modelling and analysis of land-based mitigation options is new compared to sectoral models. Consequently, “[Land sector] options are only partially included in these models, which mostly rely on afforestation, reforestation and BECCS”. ³³
Currently, most models do not consider, or have limited consideration of, the impact of future climate change on land. ³⁴.And there is still uncertainty about land’s ability to act as a sink in the future and how this will impact mitigation efforts. ³⁵ Bottom-up and non-IAM studies show significant potential for demand-side mitigation. ³⁶ (see Table 2 in the Appendix)

When evaluating the potential of different land-based mitigation measures, AR6 uses mainly sectoral models and compares to IAM’s, when available. But, AR6 still relies on IAMs/ILMs to devise mitigation pathways. This can be problematic in two main ways:

Climate change impacts on land and future mitigation potential: Given the IPCC WG1 finding that land sink efficiency is decreasing with climate change, relying too much on land to remove CO₂ from the atmosphere could be problematic. This could create a false sense of security and allow for land mitigation to be used as an excuse for not making deep emissions cuts. This is key as many corporations are relying on offsetting emissions in the land sector instead of reducing them.

Unrealistic CDR projections (over-reliance on BECCS and afforestation and reforestation): The volumes of future global CDR deployment assumed in IAM scenarios are large compared to current volumes of deployment. This is a challenge for scaling up. Similarly, the lack of representation of other options makes it difficult to compare different measures and envisage a different future that alters the contribution of land in terms of timing, potential and sustainability.

Appendix – Mitigation potential of different CDR measures

1
Chapter 7, p.4. This is different from emissions of the entire food system, which are estimated to account for 23-42% of global GHG emissions in 2018 – Ch.12, p.4. For sinks there is also a error of aprox +/- 5.2
2
Chapter 7, p.4. This is different from emissions of the entire food system, which are estimated to account for 23-42% of global GHG emissions in 2018 – Ch.12, p.4. For sinks there is also a error of aprox +/- 5.2. Chapter 3, p.42 : But there are still large uncertainties on net CO₂human emissions and its long-term trends. Currently, national GHG inventories (NGHGI) tend to overestimate the amount of CO₂ absorbed by sinks when compared to other global models. There is a gap of ~5.5 GtCO₂ a year between NGHGI and Bookkeeping models and dynamic global vegetation models. The difference largely results from different definitions of what “anthropogenic” means, which leads NGHGIs to estimate that more CO₂ is taken up by sinks.
3
Chapter 7, p.41. The bottom end represents the mean from IAMs and the upper end the mean estimate from global sectoral studies. The economic potential is about half of the technical potential from AFOLU, and about 30-50% could be achieved under USD20 tCO2-eq-1. Note that the IPCC uses a different methodology for individual AFOLU options than for the total sector potential.
4
Chapter 7, p.42. “Economic mitigation potential is the mitigation estimated to be possible at an annual cost of up to USD100 tCO2 -1 mitigated. This cost is the price at which society is willing to pay for mitigation and is used as a proxy to estimate the proportion of technical mitigation potential that could realistically be implemented.”
5
Chapter 7. 42
6
SPM, p.43
7
SPM, p.43
8
SPM, p. 53
9
SPM, p. 55
10
Chapter 7 of WGIII provides an overview of 20 mitigation measures, evaluating the co-benefits and risks from land-based mitigation measures, estimated global and regional mitigation potential and associated costs according to literature published over the last decade.
11
Chapter 7.4
12
Chapter 7, p.6. This is based on land-based carbon offsets (i.e. money from the Clean Development Mechanism, voluntary carbon standards, compliance markets and reduced deforestation).
13
SPM, p. 48
14
The IPCC evaluates previous offsets measures, such as REDD+, offsets within emissions trading systems, among others in chapter 7;Chapter 3, p. 14-15
15
SPM, p. 47
16
Chapter 12, p. 35
17
Chapter 12, p. 35
18
Chapter 12, p.4 and p. 55
19
Chapter 12, p. 5
20
Summary for policymakers, p. 6
21
Chapter 3, p. 6
22
Smith et al. 2019; Hasegawa et al. 2021
23
IPCC 2019, Hasegawa et al. 2021
24
Chapter 12, p. 56
25
Chapter 3, p. 7
26
Chapter 12, p. 38
27
Chapter 12, p. 39
28
Chapter 12, p. 3
29
Chapter 3, p.7
30
Chapter 7, p.40
31
Chapter 7, p.40-42
32
Chapter 3, p. 64
33
Annex III- p.29; Chapter 7, p.86
34
Chapter 7. 42
35
Chapter 7. 116
36
Chapter 3, p. 7

Indigenous people are essential to 1.5C

October 16, 2021 by ZCA Team Leave a Comment

Key points

Indigenous people and traditional local communities manage more than one third of the world’s intact forests and 80% of all terrestrial biodiversity lives on their lands.
Their territories have lower deforestation rates than other forest areas and their forestry management practices lead to better conservation.
Better forestry management and less deforestation means more carbon is stored and less is emitted.
Securing IP and TLC rights is a cheaper and more effective way to sequester carbon than offsets.

Indigenous people (IP) and traditional local communities (TLC) have for centuries been custodians of the world’s forests, helping to protect biodiversity and fight climate change. The forests they manage are essential in regulating climate and helping to remove CO₂emissions from the atmosphere. Increasing evidence has shown that IP and TLC knowledge and practices are essential to conserving forests and biodiversity. IP and TLC, therefore, play a key role in limiting warming to 1.5^oC.

However, their role is often overlooked, especially in policymaking and climate-change negotiations. Not only this, but IP and TLC are usually portrayed by the media as victims of climate impacts. Thus, the false narrative goes, they need to adapt to climate impacts, when in fact they have a key role to play in mitigating them.
As the window for limiting warming to 1.5^oC closes, IP and TLC rights and knowledge need to be recognised as essential in fighting the climate crisis.

How forests help regulate temperature and mitigate climate change

By exchanging gases, energy and water, such as absorbing sunlight or evaporating water, forests play a key role in regulating climate (e.g promoting rainfall, and controlling local and regional temperatures). Forests also help to take carbon dioxide (CO₂) out of the atmosphere, helping to keep average global temperatures lower than they would otherwise be (see this briefing for more information). Therefore, forests are vital for climate mitigation, currently removing and storing 30% of all CO₂ emissions.

Deforestation is threatening the vital role that forests play

But forests are under increasing threat from deforestation. Since 1990, it is estimated that 178 million hectares of forest have been lost – an area roughly the size of Libya. Less forest means less carbon is removed from the atmosphere and stored. Not only this, but deforestation is actually increasing emissions from forests, especially in tropical regions. This is because forests can release carbon stored naturally when trees die or when the wood is burned or left to rot after being cut down. Between 2019-20, tropical forest loss emitted 2.6 billion metric tonnes of CO₂, equivalent to the annual emissions from 570 million cars. The problem is such that some forests risk becoming a carbon source rather than a carbon sink. Moreover, deforestation is changing the way that forests regulate climate, such as reducing evapotranspiration, which is already having major effects on local temperatures and both local and regional rainfall patterns. For example, it is estimated that deforested land in the Brazilian Amazon is up to 2°C warmer than adjacent or intact forests.
Therefore, keeping forests standing is essential to ensure they keep regulating climate and mitigating global climate change. In fact, all scenarios for limiting warming to 2°C this century rely upon reductions in deforestation and forest degradation. Timing is key here, as “rapid and far-reaching” emission reductions are required to limit the impact of climate change to 1.5°C, according to the IPCC. Forest and other nature-based solutions are readily available and can play a vital role in avoiding irreversible environmental tipping points.

IP and TLC are guardians of the forests that are vital to limiting warming

IP and TLC manage more than one third of the world’s intact forests and 80% of all terrestrial biodiversity lives on their lands. Their territories have lower deforestation rates (especially in Latin America) than other forest areas and their forestry management practices, such as selective harvesting, reforesting and controlling wildfires, lead to better conservation. In Brazil, their forests are considered the best-preserved areas (only 1.6% of deforestation occurred in their territories between 1985-2020). In fact, forests managed by indigenous people are as effective as government-protected areas – some even more so – at avoiding deforestation.

Better forestry management and less deforestation means more carbon is stored and less is emitted. According to the Food and Agriculture Organisation (FAO), “the forests in IP and TLC territories contain almost 30% of the carbon stored in Latin America’s forests and 14% of the carbon in the tropical forests worldwide.” In fact, IP-managed forests in Latin America “store more carbon than all the forests in Indonesia or the Democratic Republic of Congo, the two countries with the most tropical forest area after Brazil.” Many indigenous territories also produce less carbon when compared to non-indigenous protected areas and other non-indigenous territories. For instance, in Latin America between 2003 and 2016, IP and TLC forests lost less than “0.3% of their stored carbon, while areas that were neither indigenous territories nor protected areas lost 3.6%”.

Therefore, IP and TLC forests have a significant role in stabilising the climate. In fact, the IPCC recently acknowledged as much, stating in its AR6 report that IP and TLC can “accelerate wide-scale behaviour changes consistent with adapting to and limiting global warming to 1.5°C.” Indeed securing IP and TLC rights to their lands could avoid breaching climate tipping points. As we have seen, if their forests continue to be cut down, huge amounts of CO₂ would be released into the atmosphere, which could reduce rainfall and increase local temperatures and increase droughts and forest fires. In the Amazon Basin, loss of a major part of the IP and TLC forests – 45% of the intact forests in the region are in their territories – could lead to the region becoming a net source of emissions within the next 20 to 30 years.

Securing IP and TLC rights is a cheaper and more effective way to sequester carbon than offsets. According to FAO, the per-hectare cost of formally recognising and ensuring indigenous territorial rights is low – an area the size of Mexico would probably cost less than USD10 dollars per tonne of CO₂-eq to reduce carbon emissions.

The value of carbon stored and the many ecosystem services from IP and TLC lands far outweigh the costs to governments of securing land rights. For example, WRI estimated that the costs were just 1% of the total economic benefit from indigenous lands over a 20-year period, which it calculated at USD 523 billion – 1,165 billion for Brazil and USD 123 billion – 277 billion for Colombia.
Sequestering carbon by securing rights is also cheaper than other mitigation options. For example, the costs of carbon capture and storage for coal-fired power plants is five to 29 times higher than securing rights. According to the IPCC, curbing deforestation and forest degradation and permanently protecting large mature forests is also a faster, better and cheaper way to stabilise the global climate than relying on planting trees. The easiest and most effective way to do it is to give IP and TLC rights to their lands.

COP26 is a key opportunity for securing IP and TLC rights

The next UN Climate Change Conference (COP 26) in November 2021 offers a major opportunity for countries to review their NDC commitments and increase their ambitions. If they are serious about limiting warming to 1.5^oC, they need to recognise that IP and TLP are essential to reach this goal. To this end, IP and TLC must have a seat at the table. In particular, countries should:

Include the recognition and protection of IP and TLC land rights in NDCs, especially if forested countries are to achieve their targets.
Compensate and support IP and TLC for the range of ecosystem services they provide.
Protect their leaders and support indigenous and community grassroots organisations.

By giving IP greater rights to their lands, we can ensure that forests are able to help limit temperature rise to 1.5^oC.

The IPCC report on land use and climate change

August 10, 2019 by ZCA Team Leave a Comment

Key points

The wellbeing of the Earth’s land is key to the future of the planet. This brief draws from the latest scientific research to describe key land challenges and their relation to climate change.
Human activity affects 75% of the Earth’s land surface, causing widespread land degradation. Agriculture and timber/logging are key drivers of degradation, desertification and carbon emissions. A combination of climate change and human activity will increase pressure in the future.
Land use change already causes a quarter of man-made emissions, and climate change will have wide reaching impacts on land. At the moment, the land is a net carbon ‘sink’, but it’s possible climate change could damage land to the point where it becomes a net source of carbon emissions.
Sustainably managing land will be a key way to cut emissions and reduce the impacts of climate change. There are many options for ‘land based mitigation’ that cut emissions from land. We will need to pursue options that bring strong co-benefits, and strong synergies with each other.
Managing land well will be a key solution to climate change. Drawing on local and indigenous knowledge and gender-proofing mitigation and adaptation in this space will be vital for making good choices about how to proceed in this space.

Introduction

The land surface of the Earth provides critical resources to human society, helps regulate the climate and has the potential to play an important role in limiting climate change. Many governments have already made pledges about how they will use land to address climate change, and land-related initiatives make up 20% of current planned total emission reductions by 2030 under the Paris Climate Agreement.

But human demands¹ are driving unprecedented depletion of natural land resources. Degradation of land contributes to climate change, and could undermine the potential land has to help solve the climate crisis.

The SRCCL² is the latest special report produced by the Intergovernmental Panel on Climate Change (IPCC), the UN body responsible for assessing the latest climate change science. Released in August 2019³, it explores what climate change will mean for the future of land and human society, and explains how we can address climate change by using the Earth’s land more carefully.

The relationship between land and climate change is complicated. It’s hard to predict the future of land, and the people that rely on it. Generalisations are hard because the land system and the science that studies it is complex. Nevertheless, the SRCCL is the most comprehensive analysis of land and climate the IPCC has produced to date. It relies on the most recent scientific papers. The analysis of land and climate it contains will be a key input to the next IPCC Assessment Report (AR6), due to be published between 2021-22.

Land and climate change

Sinks and sources of emissions

Land, land use and land management are an important part of the climate system. The Earth’s soils, forests and other plants – its land system – emit greenhouse gases (GHGs), but also absorb them. Carbon cycles between the atmosphere and the land, and is stored in soil and biomass. When land is damaged or degraded – when soil becomes thinner, forests are cut down or replaced with plantations – the degraded land system releases the carbon it has stored, driving climate change through increased GHG emissions.

Land produces a lot of greenhouse gas emissions, accounting for about 23% (12 +/- 3 Gt carbon dioxide equivalent a year) of total net human emissions between 2007 and 2016. For carbon dioxide specifically, land produced the equivalent of 13% of total human carbon dioxide emissions over that period, mostly due to human activity, particularly deforestation.⁴

Land use change also emits methane (44% from human activities), and nitrous oxide (82% from human activities), both of which are powerful greenhouse gases.⁵ Agriculture is a major source for both. Agriculture emissions nearly doubled between 1961 and 2016, and make up just over half⁶ total greenhouse gas emissions in the land sector. Livestock (66%) and rice production (24%) are the major sources of methane, while about two-thirds of nitrous oxide emissions are associated with fertiliser use and manure management.⁷ Livestock emissions are split between Asia (37%), North America (26%), Latin America and the Caribbean (16%), Africa (14%) and Europe (8%).⁸

Land also absorbs greenhouse gases, acting as a ‘carbon sink’. So although the land sector produces emissions, overall it is a net sink of emissions, taking more carbon out of the atmosphere than it puts in. Between 2007 and 2016 these sinks removed 29%of total human carbon dioxide emissions from the atmosphere.⁹ There is no guarantee the land will continue to be a net carbon sink as climate change alters how natural systems work. More carbon dioxide in the atmosphere may boost plant growth leading to more uptake of carbon from the atmosphere¹⁰ but climate change will also degrade land’s capacity to store carbon, providing an opposing effect. Whether land will act as a net sink or a source in the future remains uncertain.

Climate change’s effect on land

Broadly, land use change often causes climate change, and climate change causes land change. Climate change affects land by changing weather patterns, including extreme events, which can lead to damage like vegetation loss, fire damage, or permafrost and coastal degradation.¹¹ For example:

Changes in rainfall patterns and more intense rainfall increase the risk of land degradation through landslides, extreme erosion events or flash floods.
In North America, thunderstorms could cause major landslides and flash flooding with severe economic losses (over US$20 billion annually).
Extreme events, such as heat and drought, increase the frequency and intensity of wildfires in forests.¹² In the Brazilian Amazon, during the drought of 2015, fire increased by 36% even with declining deforestation rates.

Attributing land degradation to climate change by making direct links between the two¹³can be hard, as impacts depend on local contexts and how land is managed. The effects are also often complex. For example, deforestation in the tropics will likely cause the climate to warm, but in temperate and boreal regions it will likely have a cooling effect. Climate change might even improve the state of the land in some parts of the world. Processes known as feedbacks – which amplify or dampen climate change and land degradation – further complicate the picture.

Despite the uncertainties, it is clear that climate change creates new and unprecedented risks for the land system and will likely lead to worse outcomes overall. Action is needed to protect land from climate change.

Land degradation

As well as being threatened by climate change, land is also under severe pressure from land use change. The resulting land degradation takes many forms,¹⁴ but overall reduces the land’s biological productivity, its ecological integrity and its role in providing services to humans and the planet.¹⁵ Estimates of how much of the Earth’s land is degraded vary – it could be between 7 and 40% of the land surface. When land becomes degraded, it is more likely to produce greenhouse gas emissions, and less likely to act as a carbon sink.

Degradation has many causes, from direct ones like changes to soil characteristics, deforestation or changes in plants’ composition, to changes in climate or environmental conditions, like changes in rainfall patterns, to changes in land use and management, like changing farming systems or urbanisation and infrastructure expansion.¹⁶ Overall, humans are the main cause of degradation, affecting 75% of the Earth’s land surface, with grazing, forest harvesting and forest plantations the main damaging activities.

Agriculture is a major cause of degradation. Agricultural land covers a large amount¹⁷ of the Earth’s land surface, and the amount of cropland is increasing, with most of the expansion driven by demand for livestock products. Irrigated areas have also expanded by about 50% over the last fifty years, contributing to freshwater withdrawals¹⁸ and local climate variability in many regions, and cropland expansion is also driving soil erosion, particularly in Sub-Saharan Africa, South America and Southeast Asia. An increase in mechanized agricultural systems is a major driver of deforestation in the Amazon,¹⁹ and also creates severe pressure on soils. Agriculture is also becoming more intense. The use of nitrogen fertilisers increased nine times over the same period,²⁰ driving further land degradation.

Deforestation is another important cause of degradation. Global forest area has declined by 3% since 1990 and continues to decline, although there are large uncertainties in this measurement.²¹ Between 60 and 85% of the total global forested area is used by humans at different levels of intensity. Only the tropics and northern boreal zones have large remaining areas of unused forest. Between 73 and 89% of other, non-forested natural ecosystems (natural grasslands, savannas, etc.) are used by humans.²²Around the world, pastures are replacing natural grasslands, and croplands are replacing forests.²³

Humans are having a huge effect on the planet, but it is hard to say how the overall balance of forest, savanna and grassland area is changing. For example, some research suggests forest area has actually increased globally. Taken together, human activity has had a huge and transformative effect on the Earth’s land surface and driven degradation of the land. Choices we make about future land management will be increasingly important as we address climate change; sustainable land management will be essential.²⁴

Desertification: degradation of drylands

When land degradation takes place in ‘drylands’²⁵ it is termed desertification,²⁶ a reduction in the land’s health, its productivity and its usefulness²⁷ Drylands cover nearly half the world’s land surface, are some of the most sensitive areas to climate change and human activity, and host a large and growing portion of the world’s population – nearly forty per cent – so desertification is a critical challenge.

Desertification reduces soil fertility and its capacity to sequester carbon, as warmer and drier soils release more soil carbon to the atmosphere. It can also decrease crop and livestock productivity, and contribute to food insecurity, poverty, migration and even conflict.²⁸ Countries in Africa and Asia, the Mediterranean region and Latin America and the Caribbean are particularly at risk. There are many causes. Across Africa desertification is mainly caused by drought, but in northern China it is mainly a result of human activity. Expanding croplands and unsustainable land management practices are the most important cause.

Climate change can drive desertification, but it depends on local context and interactions with other human activities.²⁹ For example, natural climate cycles were responsible for two-thirds of the expansion of the Sahara Desert between 1920 and 2003, while in China both human and climate factors have played a role in desertification. It isn’t always possible to demonstrate a clear climate link – different studies reach opposite conclusions on whether climate change has actually played a role in desertification in the Sahel region, for example. As a result, attribution of climate change to desertification is still challenging, in part because desertification is caused by multiple natural and human factors that vary between places and over time.³⁰

Land, climate and the food system

The way we produce and consume food contributes to many environmental and socio-economic problems, including climate change and land degradation. Since 1961, food supply per person has increased more than 30%. Over the same time period, use of nitrogen fertilisers has grown about eight times, and the water resources used for irrigation have more than doubled.³¹

This increase in food supply has not stopped many people globally suffering from hunger and diet-related diseases. An estimated 821 million people are undernourished worldwide – particularly in low-income countries, including parts of sub-Saharan Africa, South-Eastern Asia, Western Asia, and Latin America. At the same time, in many parts of the world an increase in the availability of food and diets higher in animal-based products have increased adult obesity rates. Globally 1.9 billion adults are overweight.

Food system³² emissions account for an estimated 25 to 30% of total human emissions,³³ with agriculture producing the largest portion of 10 to 12% from crop and livestock activities. Other emissions are produced along the food supply chain: 8 to 10% from land use and land use change including deforestation and peatland degradation, and 5 to 10% from supply chain activities.³⁴ High levels of food waste along the supply-chain and at consumer level also contribute.

Climate change already has huge impacts on the food system; future effects are likely to be very significant, but will vary widely across regions. For example, warming in India over the period 1981–2009 reduced crop yields by 5.2%, but in Australia reduction of crop yields have so far been countered by improvements in management and technology. Industrial livestock production will suffer, mostly from indirect climate change impacts, leading to rises in production costs and destruction of infrastructure. Farming systems will also suffer risks from variable grain availability and cost, and animals struggling to adapt to new climates.³⁵

Climate change will also have a negative effect on a host of issues which set the context for our food system, including poverty and vulnerability, cultural practices and gender issues. It can reduce incomes and impact farmers’ ability to endure price rises. It can affect food safety and human health in a range of ways, like lowering the nutrient content of food, or affecting contaminating organisms. It can threaten food security by increasing instability of supply due to increased frequency and severity of extreme events. It may cause widespread crop failure contributing to spikes in food prices, migration and conflict.

How will climate change affect land in the future?

Scientists use climate models and different scenarios for temperature rise and socio-economic development to try and map out the future of land and climate.³⁶ But even so, predicting the future of land and climate change is complicated. Temperatures, land processes and human society will evolve differently across regions and biomes, with different implications for land use/cover. Mitigation policies can also impact land use as well as land-based mitigation impacts other land-related challenges. All this makes it harder to create universal predictions for the future. Instead, scientists describe many possible futures, or scenarios.

What is true in most future scenarios?

Most scenarios agree that land will play a key role in the future of our climate. The choices we make about how to manage land could act as a control knob for as much as 0.5°C of temperature rise in low-emissions scenarios. With the world looking to limit temperature rise to 1.5°C, this is hugely significant.

Land degradation alone is projected to reduce global food production.³⁷ Warming is likely to reduce crop yields, productivity and livestock production, with impacts varying across regions. Each 0.5 degree Celsius of temperature rise³⁸ will likely increase the risk of lower crop yields, but the effect will depend on how temperatures fall across the year and align with growing seasons. One degree of warming (relative to a 1981–2010 baseline)³⁹ will likely reduce average wheat, rice and soybean yield globally,⁴⁰ but some regions will see an increase; past three degrees of warming⁴¹ all crop yields will be impacted, unless adaptation measures are deployed. Lower yields could lead to instability in global grain trade and international grain prices, affecting those who are most vulnerable to food price spikes. Rising carbon dioxide levels in the atmosphere will also affect food production – more carbon dioxide could increase yield productivity, for example, but reduce the nutrient content of crops.⁴²

Drylands are expected to expand as a result of climate change. A temperature rise of 4°C – our current policy trajectory – would increase the area of drylands globally by 23% to cover 56% of the total land surface, with most of this expansion in developing countries. Most scenarios show climate change will likely increase the vulnerability of drylands to desertification. Climate change is also expected to decrease carbon sequestration from land, particularly in forests.

Risks from desertification are projected to increase. Depending on assumptions made about the future, the number of people in drylands impacted by threats to water, energy or land could reach over a billion, in worst-case scenarios with more than two degrees of temperature rise. In better managed futures with lower temperature rise the number could be much lower.⁴³

What affects which future we get?

What actually happens in the future will depend on how much temperatures rise, how much carbon dioxide is in the atmosphere, on the choices we make about how aggressively to mitigate climate change, where climate impacts occur, how we use land, and different scenarios of socio-economic development.⁴⁴ The exact effects of temperature rise on land degradation, desertification and food security will also vary depending on context and location.

Without any efforts to limit climate change, global mean temperatures are expected to rise between 2 °C and 7.8 °C by 2100,⁴⁵ with warming over land 1.2 to 1.4 times higher than global mean temperature rise. Even the lower end of this spectrum will be hugely damaging and disruptive; the upper end is likely to be disastrous for humans, the biosphere and land.

Future outcomes are highly dependent on what future socio-economic, development and political pathways human society chooses. For any level of temperature rise, vulnerability and exposure of people and land to climate damage will be higher in futures where there is higher population growth and lower incomes⁴⁶ or higher consumption.⁴⁷ Such futures will likely be more affected by land degradation, desertification, and food insecurity,⁴⁸ compared to more equitable scenarios. By contrast, futures with lower demand for agricultural commodities, and/or higher levels of agricultural productivity and globalized trade⁴⁹ will likely lead to better outcomes – the lowest emissions from land, lower food prices over time, and lower levels of forest loss.⁵⁰

Impacts on food will vary, with studies showing that by the end of the century, worlds characterised by nationalism and rising inequality⁵¹ could see some 400 or 600 million people respectively suffering from malnourishment. More optimistically, food insecurity could decline substantially in futures with higher incomes.⁵² Most future socio-economic worlds see higher water stress.

How can land help solve the climate crisis?

The land sector can be part of the solution to climate change. Indeed, all future pathways that limit temperature rise to 1.5 or well-below two degrees Celcius will require land-based mitigation and land-use change.⁵³

If done sensitively, there are mitigation options in the land space that can limit climate change and provide co-benefits for land. But land-based mitigation could also create adverse side effects for land and people by changing the land use system. To be effective, land-based mitigation will need to be regionally and context- dependent,⁵⁴ as countries suffer impacts differently and have different socio-economic characteristics.

Using land to help address climate change will be complex, and also increasingly likely to run into tradeoffs. For example, to limit temperature rise to 1.5 or two degrees⁵⁵ negative emissions technologies⁵⁶may need to be deployed over very large areas of land, which could contribute to desertification and land degradation.⁵⁷ Some 1.5ºC scenarios are achieved with limited or no NETs deployment, but are associated with large scale behavioural changes (including eating less meat and reducing food waste), agricultural intensification, and mitigation in other sectors. The longer we delay action, the more we will be into the realm of exceptionally hard choices, and delay will increase the need for adaptation, and potentially make land-based solutions less viable.⁵⁸

Reducing emissions from the land use space and preparing for the effects of climate change will require a sophisticated policy approach that recognises and incorporates local and indigenous knowledge. Indigenous peoples and local communities have extensive knowledge of the land and the characteristics of their specific region and this expertise can guide policy in these complex spaces. For example, indigenous knowledge can better predict future climate change and contribute insight where data is lacking, or facilitate climate adaptation. Mainstreaming gender in policy is also essential. Addressing gender issues ensures adaptation measures can benefit those who most need them, and can also unlock mitigation options by – for example – empowering women to participate in decision-making in agriculture.

1
Land use can be understood as the set of activities carried out by humans on land, for example, changing land cover via deforestation, afforestation, or agricultural production. https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter06_FINAL.pdf
2
The full title of the report is the “Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse gas fluxes in Terrestrial Ecosystems”.
3
The approval plenary runs from the 2nd – 6th August – see https://www.ipcc.ch/site/assets/uploads/2019/06/Info_Note_Participants_final.pdf
4
Global models estimate net CO2 emissions of 5.2 ± 2.6 GtCO2 yr-1 (likely range) from land use and land-use change during 2007-16. These net emissions are mostly due to deforestation, partly offset by afforestation/reforestation, and emissions and removals by other land use activities (very high confidence) from Table SPM.1; SPM, A.3.1.
5
Table SPM 1.
6
Estimate is in comparison of the 24% emissions from AFOLU sector. Calculated by IPCC through a combination of models.
7
https://www.nature.com/articles/nclimate3158
8
SRCCL, Chapter 2, 2.4.2.2, p. 39, line 47-53.
9
Represents a net sink of around 11.2 GtCO2 yr-1, see Table SPM 1.
10
This is a process known as CO₂ fertilisation, which stimulates plant growth and could lead to increases in vegetation, but this “greening” trend is contested in the literature/empirical evidence. https://onlinelibrary.wiley.com/doi/10.1111/j.1365-3040.1995.tb00630.x; https://www.pnas.org/content/113/36/10019
11
https://www.nature.com/articles/17789; https://www.nature.com/articles/nature01286; https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL032838; https://www.sciencedirect.com/science/article/pii/S0022169413004800/; https://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00324.1; https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2016GL069896; https://www.ncbi.nlm.nih.gov/pubmed/28360268
12
https://www.pnas.org/content/113/42/11770;https://www.nature.com/articles/srep26886; http://dx.doi.org/10.1038/s41558-017-0014-8
13
When degradation of land has been associated with climate change
14
Land degradation has many definitions across the scientific literature. In this report, the IPCC uses a broad definition derived from the IPCC AR 5 definition of desertification: “A negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity or value to humans. [Note: This definition applies to forest and non-forest land. Changes in land condition resulting solely from natural processes (such as volcanic eruptions) are not considered to be land degradation. Reduction of biological productivity or ecological integrity or value to humans can constitute degradation, but any one of these changes need not necessarily be considered degradation.]” SRCCL, Glossary, p.33.
15
https://arizona.pure.elsevier.com/en/publications/land-in-balance-the-scientific-conceptual-framework-for-land-degr; https://www.ipcc.ch/site/assets/uploads/2018/02/WGIIAR5-AnnexII_FINAL.pdf; https://www.unccd.int/sites/default/files/relevant-links/2017-01/UNCCD_Convention_ENG_0.pdf
16
SRCCL, Chapter 1, 1.2.2.3, p. 11, lines 11-14.
17
“Globally, cropland area changed by +15% and the area of permanent pastures by +8% since the early 1960s (FAOSTAT 2018), with strong regional differences” – SRCCL, Chapter 1, 1.2.2.3, p. 10, lines 17-18.
18
“Water withdrawals are defined as freshwater taken from ground or surface water sources, either permanently or temporarily, and conveyed to a place of use”. https://data.oecd.org/water/water-withdrawals.htm
19
https://www.ncbi.nlm.nih.gov/pubmed/16973742; https://www.sciencedirect.com/science/article/abs/pii/S0959378001000073; https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.13068
20
SRCCL, Chapter 1, 1.2.2.3, p. 11, line 7.
21
SRCCL, Chapter 1, 1.2.2.3, p. 11, lines 25-26.
22
SRCCL, Chapter 1, 1.2.2.2, p. 9, lines 9-16.
23
SRCCL, Chapter 1, 1.2.2.3, p. 11, lines 15-16.
24
https://www.unccd.int/sites/default/files/documents/2019-06/LDN_CF_report_web-english.pdf; https://pubs.acs.org/doi/abs/10.1021/es302545b; https://pdfs.semanticscholar.org/1dcd/dcb78cb7010fedb248f8c1f402ed5a0a731c.pdf
25
Drylands areas constitute of arid, semi-arid, and dry sub-humid areas
26
https://www.jstor.org/stable/25595197?seq=1#page_scan_tab_contents; https://www.millenniumassessment.org/documents/document.291.aspx.pdf; https://www.tandfonline.com/doi/abs/10.2989/AJRF.2009.26.3.2.947
27
.This definition was developed by the IPCC to explain the specific type of land degradation – desertification – that happens in a particular part of the world – the drylands. As such, it is defined in the report as “Land degradation in arid, semi-arid, and dry sub-humid areas resulting from many factors, including climatic variations and human activities (UNCCD, 1994)”. SRCCL, Glossary, p.16 https://treaties.un.org/Pages/ShowMTDSGDetails.aspx?src=UNTSONLINE&tabid=2&mtdsg_no=XXVII-10&chapter=27&lang=en
28
https://www.sciencedirect.com/science/article/pii/S1877343513000109?via%3Dihub; https://www.nature.com/articles/nclimate2837, https://www.nature.com/articles/nclimate3275; https://www.researchgate.net/publication/287507867_Effect_of_climate_change_on_the_vulnerability_of_a_socio-ecological_system_in_an_arid_area a; https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.12581; https://www.ecologyandsociety.org/vol23/iss1/art34/; https://www.sciencedirect.com/science/article/pii/S014098831400098X; https://www.nature.com/articles/nclimate3253
29
https://wad.jrc.ec.europa.eu/sites/default/files/atlas_pdf/1_WAD_Introduction.pdf
30
https://www.sciencedirect.com/science/article/abs/pii/S0034425716302280; https://www.ncbi.nlm.nih.gov/pubmed/26525278; https://onlinelibrary.wiley.com/doi/abs/10.1002/eco.1849;http://adsabs.harvard.edu/abs/2016AGUFM.A33G0330M;https://journals.ametsoc.org/doi/full/10.1175/2010JCLI3794.1;https://www.sciencedirect.com/science/article/abs/pii/S0140196316301641?via%3Dihub; https://journals.ametsoc.org/doi/10.1175/JCLI-D-17-0187.1
31
SRCCL, Chapter 5, Executive summary, p. 5, line 4-6.
32
The High Level Panel of Experts on Food Security and Nutrition defines food system as a system that “gathers all the elements (environment, people, inputs, processes, infrastructures, institutions, etc.) and activities that relate to the production, processing, distribution, preparation and consumption of food, and the output of these activities, including socio-economic and environmental outcomes.”
33
Percentage contribution to total human greenhouse gas emissions, averaged over 2007-2016. SRCCL, Chapter 5, p.61.
34
SRCCL, Chapter 5, Executive summary, p. 6, line 16-20.
35
SRCCL, Chapter 5, Section 5.2.2.2, p. 29, line 8-10.
36
For more information see Cross-Chapter box 9 in Chapter 6 of the SRCCL report. It includes explanations of the socioeconomic scenarios used by scientists as well as the policies that can be implemented in each future world, focused on land-related challenges.
37
https://onlinelibrary.wiley.com/doi/full/10.1111/1467-8489.12072; https://onlinelibrary.wiley.com/doi/full/10.1002/fes3.99; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0066428
38
The reference period for the modeling study is the “‘current decade’ from 2006–2015 forced by observations including observed CO2 concentrations that have increased from 380.9 parts per million (ppm) to 402.9 ppm over this decade. Mean warming over this period corresponds to about 0.9°C above the 1860–1880 period in the Berkeley Earth GMT dataset. The Future 1.5°C experiment is based on the RCP2.6 experiment and takes constant forcing for greenhouse gases and aerosols and sea-surface temperatures from the 2091–2100 decade. CO₂ concentrations in this experiment are constant at 423.4 ppm. The Future 2°C experiment uses scaled atmospheric and sea-surface temperature forcing from RCP2.6 and RCP4.5 with CO₂ concentrations set to 486.6 ppm”.
39
In comparison with 1981–2010 baseline. “The temperature impact was calculated as the yield change during the warming period relative to the yield during the baseline period normalized to +1 °C impact, assuming the impact showed a linear temperature response”.
40
A limitation of this study is the linear assumption between yield responses and temperature increase as yield response for each degree Celsius warming differs by growing season temperature level. Different CO₂concentration in the atmosphere can also affect yields.
41
“Some of the studies have associated temporal baselines, with center points typically between 1970 and 2005”, https://www.ipcc.ch/site/assets/uploads/2018/02/WGIIAR5-Chap7_FINAL.pdf, p.498.
42
https://ideas.repec.org/a/spr/climat/v124y2014i4p763-775.html; https://pubag.nal.usda.gov/catalog/237405; https://onlinelibrary.wiley.com/doi/10.1111/jac.12057; https://www.nature.com/articles/nature13179; https://advances.sciencemag.org/content/4/5/eaaq1012.abstract
43
See SRCCL, sections 2.3, 3.2.1, 3.3.2, 3.6.1, 3.6.2, 7.3.2.
44
These mitigation options can have positive or negative impacts on land and people.
45
Relative to the 1850-1900 reference period.
46
At similar temperatures, risks are higher in SSP3 than in SPP2 and SSP1. https://www.sciencedirect.com/science/article/pii/S0959378016300681
47
SSP3
48
https://www.sciencedirect.com/science/article/pii/S0959378016300681; https://www.pnas.org/content/111/9/3292/tab-article-info; https://www.sciencedirect.com/science/article/pii/S0959378016303399
49
SSP 1. https://www.sciencedirect.com/science/article/pii/S0959378016300681; https://www.sciencedirect.com/science/article/pii/S0959378016303399
50
SSP 1. https://www.sciencedirect.com/science/article/pii/S0959378016300681; https://www.sciencedirect.com/science/article/pii/S0959378016303399
51
SSP3 and SPP4, respectively.
52
SSP 1- Higher income (e.g., SSP1, SSP5), higher yields (e.g., SSP1, SSP5), and less meat intensive diets (e.g., SSP1) tend to result in reduced food insecurity SRCCL, CH.6, p.19.
53
Pathways assessed on the SRCCL.
54
SRCCL, Chapter 1, Section 1.4, p.29, line 4-10.
55
https://www.nature.com/articles/nclimate3096; https://www.sciencedirect.com/science/article/pii/S1876610217319410;https://www.nature.com/articles/nclimate2870
56
https://www.sciencedirect.com/science/article/pii/S0959378016303399; https://www.sciencedirect.com/science/article/pii/S0959378016300681; https://www.ipcc.ch/site/assets/uploads/sites/2/2019/02/SR15_Chapter2_Low_Res.pdf
57
https://www.sciencedirect.com/science/article/pii/S0959378016303399; https://iopscience.iop.org/article/10.1088/1748-9326/aabf9f
58
SRCCL, Chapter 6, Executive Summary , p.5.